From 7162ecf88624615c78a332de482f5defd297e415 Mon Sep 17 00:00:00 2001
From: Vinod K C <vinod.kc@huawei.com>
Date: Tue, 7 Apr 2015 10:42:08 -0700
Subject: [PATCH 01/95] [SPARK-6733][ Scheduler]Added
 scala.language.existentials

Author: Vinod K C <vinod.kc@huawei.com>

Closes #5384 from vinodkc/Suppression_Scala_existential_code and squashes the following commits:

82a3a1f [Vinod K C] Added scala.language.existentials
---
 .../src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala | 1 +
 .../test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala | 1 +
 2 files changed, 2 insertions(+)

diff --git a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
index 917cce1f9686c..c82ae4baa3630 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
@@ -24,6 +24,7 @@ import java.util.concurrent.atomic.AtomicInteger
 
 import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet, Map, Stack}
 import scala.concurrent.duration._
+import scala.language.existentials
 import scala.language.postfixOps
 import scala.util.control.NonFatal
 
diff --git a/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala
index 29d4ec5f85c1e..fc7349330cf86 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala
@@ -22,6 +22,7 @@ import java.util.Random
 
 import scala.collection.mutable
 import scala.collection.mutable.ArrayBuffer
+import scala.language.existentials
 
 import com.github.fommil.netlib.BLAS.{getInstance => blas}
 import org.scalatest.FunSuite

From 2c32bef1790dac6f77ef9674f6106c2e24ea0338 Mon Sep 17 00:00:00 2001
From: sksamuel <sam@sksamuel.com>
Date: Tue, 7 Apr 2015 10:43:22 -0700
Subject: [PATCH 02/95] Replace use of .size with .length for Arrays

Invoking .size on arrays is valid, but requires an implicit conversion to SeqLike. This incurs a compile time overhead and more importantly a runtime overhead, as the Array must be wrapped before the method can be invoked. For example, the difference in generated byte code is:

  public int withSize();
    Code:
       0: getstatic     #23                 // Field scala/Predef$.MODULE$:Lscala/Predef$;
       3: aload_0
       4: invokevirtual #25                 // Method array:()[I
       7: invokevirtual #29                 // Method scala/Predef$.intArrayOps:([I)Lscala/collection/mutable/ArrayOps;
      10: invokeinterface #34,  1           // InterfaceMethod scala/collection/mutable/ArrayOps.size:()I
      15: ireturn

  public int withLength();
    Code:
       0: aload_0
       1: invokevirtual #25                 // Method array:()[I
       4: arraylength
       5: ireturn

Author: sksamuel <sam@sksamuel.com>

Closes #5376 from sksamuel/master and squashes the following commits:

77ec261 [sksamuel] Replace use of .size with .length for Arrays.
---
 .../apache/spark/network/nio/Connection.scala |  2 +-
 .../apache/spark/rdd/AsyncRDDActions.scala    | 10 ++++-----
 .../scala/org/apache/spark/rdd/BlockRDD.scala |  2 +-
 .../org/apache/spark/rdd/CartesianRDD.scala   |  4 ++--
 .../org/apache/spark/rdd/CheckpointRDD.scala  |  2 +-
 .../org/apache/spark/rdd/CoGroupedRDD.scala   |  4 ++--
 .../org/apache/spark/rdd/CoalescedRDD.scala   |  2 +-
 .../apache/spark/rdd/DoubleRDDFunctions.scala |  4 ++--
 .../spark/rdd/OrderedRDDFunctions.scala       |  2 +-
 .../apache/spark/rdd/PairRDDFunctions.scala   |  2 +-
 .../main/scala/org/apache/spark/rdd/RDD.scala | 22 +++++++++----------
 .../apache/spark/rdd/RDDCheckpointData.scala  |  6 ++---
 .../org/apache/spark/rdd/SubtractedRDD.scala  |  2 +-
 .../scala/org/apache/spark/rdd/UnionRDD.scala |  6 ++---
 .../spark/rdd/ZippedPartitionsRDD.scala       |  4 ++--
 .../apache/spark/rdd/ZippedWithIndexRDD.scala |  2 +-
 .../org/apache/spark/storage/RDDInfo.scala    |  2 +-
 .../apache/spark/ui/ConsoleProgressBar.scala  |  4 ++--
 .../apache/spark/util/collection/BitSet.scala |  2 +-
 19 files changed, 42 insertions(+), 42 deletions(-)

diff --git a/core/src/main/scala/org/apache/spark/network/nio/Connection.scala b/core/src/main/scala/org/apache/spark/network/nio/Connection.scala
index 04eb2bf9ba4ab..6b898bd4bfc1b 100644
--- a/core/src/main/scala/org/apache/spark/network/nio/Connection.scala
+++ b/core/src/main/scala/org/apache/spark/network/nio/Connection.scala
@@ -181,7 +181,7 @@ abstract class Connection(val channel: SocketChannel, val selector: Selector,
     buffer.get(bytes)
     bytes.foreach(x => print(x + " "))
     buffer.position(curPosition)
-    print(" (" + bytes.size + ")")
+    print(" (" + bytes.length + ")")
   }
 
   def printBuffer(buffer: ByteBuffer, position: Int, length: Int) {
diff --git a/core/src/main/scala/org/apache/spark/rdd/AsyncRDDActions.scala b/core/src/main/scala/org/apache/spark/rdd/AsyncRDDActions.scala
index 646df283ac069..3406a7e97e368 100644
--- a/core/src/main/scala/org/apache/spark/rdd/AsyncRDDActions.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/AsyncRDDActions.scala
@@ -45,7 +45,7 @@ class AsyncRDDActions[T: ClassTag](self: RDD[T]) extends Serializable with Loggi
         }
         result
       },
-      Range(0, self.partitions.size),
+      Range(0, self.partitions.length),
       (index: Int, data: Long) => totalCount.addAndGet(data),
       totalCount.get())
   }
@@ -54,8 +54,8 @@ class AsyncRDDActions[T: ClassTag](self: RDD[T]) extends Serializable with Loggi
    * Returns a future for retrieving all elements of this RDD.
    */
   def collectAsync(): FutureAction[Seq[T]] = {
-    val results = new Array[Array[T]](self.partitions.size)
-    self.context.submitJob[T, Array[T], Seq[T]](self, _.toArray, Range(0, self.partitions.size),
+    val results = new Array[Array[T]](self.partitions.length)
+    self.context.submitJob[T, Array[T], Seq[T]](self, _.toArray, Range(0, self.partitions.length),
       (index, data) => results(index) = data, results.flatten.toSeq)
   }
 
@@ -111,7 +111,7 @@ class AsyncRDDActions[T: ClassTag](self: RDD[T]) extends Serializable with Loggi
    */
   def foreachAsync(f: T => Unit): FutureAction[Unit] = {
     val cleanF = self.context.clean(f)
-    self.context.submitJob[T, Unit, Unit](self, _.foreach(cleanF), Range(0, self.partitions.size),
+    self.context.submitJob[T, Unit, Unit](self, _.foreach(cleanF), Range(0, self.partitions.length),
       (index, data) => Unit, Unit)
   }
 
@@ -119,7 +119,7 @@ class AsyncRDDActions[T: ClassTag](self: RDD[T]) extends Serializable with Loggi
    * Applies a function f to each partition of this RDD.
    */
   def foreachPartitionAsync(f: Iterator[T] => Unit): FutureAction[Unit] = {
-    self.context.submitJob[T, Unit, Unit](self, f, Range(0, self.partitions.size),
+    self.context.submitJob[T, Unit, Unit](self, f, Range(0, self.partitions.length),
       (index, data) => Unit, Unit)
   }
 }
diff --git a/core/src/main/scala/org/apache/spark/rdd/BlockRDD.scala b/core/src/main/scala/org/apache/spark/rdd/BlockRDD.scala
index fffa1911f5bc2..71578d1210fde 100644
--- a/core/src/main/scala/org/apache/spark/rdd/BlockRDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/BlockRDD.scala
@@ -36,7 +36,7 @@ class BlockRDD[T: ClassTag](@transient sc: SparkContext, @transient val blockIds
 
   override def getPartitions: Array[Partition] = {
     assertValid()
-    (0 until blockIds.size).map(i => {
+    (0 until blockIds.length).map(i => {
       new BlockRDDPartition(blockIds(i), i).asInstanceOf[Partition]
     }).toArray
   }
diff --git a/core/src/main/scala/org/apache/spark/rdd/CartesianRDD.scala b/core/src/main/scala/org/apache/spark/rdd/CartesianRDD.scala
index 9059eb13bb5d8..c1d6971787572 100644
--- a/core/src/main/scala/org/apache/spark/rdd/CartesianRDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/CartesianRDD.scala
@@ -53,11 +53,11 @@ class CartesianRDD[T: ClassTag, U: ClassTag](
   extends RDD[Pair[T, U]](sc, Nil)
   with Serializable {
 
-  val numPartitionsInRdd2 = rdd2.partitions.size
+  val numPartitionsInRdd2 = rdd2.partitions.length
 
   override def getPartitions: Array[Partition] = {
     // create the cross product split
-    val array = new Array[Partition](rdd1.partitions.size * rdd2.partitions.size)
+    val array = new Array[Partition](rdd1.partitions.length * rdd2.partitions.length)
     for (s1 <- rdd1.partitions; s2 <- rdd2.partitions) {
       val idx = s1.index * numPartitionsInRdd2 + s2.index
       array(idx) = new CartesianPartition(idx, rdd1, rdd2, s1.index, s2.index)
diff --git a/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala b/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala
index 760c0fa3ac96a..0d130dd4c7a60 100644
--- a/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala
@@ -49,7 +49,7 @@ class CheckpointRDD[T: ClassTag](sc: SparkContext, val checkpointPath: String)
     if (fs.exists(cpath)) {
       val dirContents = fs.listStatus(cpath).map(_.getPath)
       val partitionFiles = dirContents.filter(_.getName.startsWith("part-")).map(_.toString).sorted
-      val numPart =  partitionFiles.size
+      val numPart =  partitionFiles.length
       if (numPart > 0 && (! partitionFiles(0).endsWith(CheckpointRDD.splitIdToFile(0)) ||
           ! partitionFiles(numPart-1).endsWith(CheckpointRDD.splitIdToFile(numPart-1)))) {
         throw new SparkException("Invalid checkpoint directory: " + checkpointPath)
diff --git a/core/src/main/scala/org/apache/spark/rdd/CoGroupedRDD.scala b/core/src/main/scala/org/apache/spark/rdd/CoGroupedRDD.scala
index 07398a6fa62f6..7021a339e879b 100644
--- a/core/src/main/scala/org/apache/spark/rdd/CoGroupedRDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/CoGroupedRDD.scala
@@ -99,7 +99,7 @@ class CoGroupedRDD[K](@transient var rdds: Seq[RDD[_ <: Product2[K, _]]], part:
 
   override def getPartitions: Array[Partition] = {
     val array = new Array[Partition](part.numPartitions)
-    for (i <- 0 until array.size) {
+    for (i <- 0 until array.length) {
       // Each CoGroupPartition will have a dependency per contributing RDD
       array(i) = new CoGroupPartition(i, rdds.zipWithIndex.map { case (rdd, j) =>
         // Assume each RDD contributed a single dependency, and get it
@@ -120,7 +120,7 @@ class CoGroupedRDD[K](@transient var rdds: Seq[RDD[_ <: Product2[K, _]]], part:
     val sparkConf = SparkEnv.get.conf
     val externalSorting = sparkConf.getBoolean("spark.shuffle.spill", true)
     val split = s.asInstanceOf[CoGroupPartition]
-    val numRdds = split.deps.size
+    val numRdds = split.deps.length
 
     // A list of (rdd iterator, dependency number) pairs
     val rddIterators = new ArrayBuffer[(Iterator[Product2[K, Any]], Int)]
diff --git a/core/src/main/scala/org/apache/spark/rdd/CoalescedRDD.scala b/core/src/main/scala/org/apache/spark/rdd/CoalescedRDD.scala
index 5117ccfabfcc2..0c1b02c07d09f 100644
--- a/core/src/main/scala/org/apache/spark/rdd/CoalescedRDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/CoalescedRDD.scala
@@ -166,7 +166,7 @@ private class PartitionCoalescer(maxPartitions: Int, prev: RDD[_], balanceSlack:
 
   // determines the tradeoff between load-balancing the partitions sizes and their locality
   // e.g. balanceSlack=0.10 means that it allows up to 10% imbalance in favor of locality
-  val slack = (balanceSlack * prev.partitions.size).toInt
+  val slack = (balanceSlack * prev.partitions.length).toInt
 
   var noLocality = true  // if true if no preferredLocations exists for parent RDD
 
diff --git a/core/src/main/scala/org/apache/spark/rdd/DoubleRDDFunctions.scala b/core/src/main/scala/org/apache/spark/rdd/DoubleRDDFunctions.scala
index 71e6e300fec5f..29ca3e9c4bd04 100644
--- a/core/src/main/scala/org/apache/spark/rdd/DoubleRDDFunctions.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/DoubleRDDFunctions.scala
@@ -70,7 +70,7 @@ class DoubleRDDFunctions(self: RDD[Double]) extends Logging with Serializable {
   @Experimental
   def meanApprox(timeout: Long, confidence: Double = 0.95): PartialResult[BoundedDouble] = {
     val processPartition = (ctx: TaskContext, ns: Iterator[Double]) => StatCounter(ns)
-    val evaluator = new MeanEvaluator(self.partitions.size, confidence)
+    val evaluator = new MeanEvaluator(self.partitions.length, confidence)
     self.context.runApproximateJob(self, processPartition, evaluator, timeout)
   }
 
@@ -81,7 +81,7 @@ class DoubleRDDFunctions(self: RDD[Double]) extends Logging with Serializable {
   @Experimental
   def sumApprox(timeout: Long, confidence: Double = 0.95): PartialResult[BoundedDouble] = {
     val processPartition = (ctx: TaskContext, ns: Iterator[Double]) => StatCounter(ns)
-    val evaluator = new SumEvaluator(self.partitions.size, confidence)
+    val evaluator = new SumEvaluator(self.partitions.length, confidence)
     self.context.runApproximateJob(self, processPartition, evaluator, timeout)
   }
 
diff --git a/core/src/main/scala/org/apache/spark/rdd/OrderedRDDFunctions.scala b/core/src/main/scala/org/apache/spark/rdd/OrderedRDDFunctions.scala
index 6fdfdb734d1b8..6afe50161dacd 100644
--- a/core/src/main/scala/org/apache/spark/rdd/OrderedRDDFunctions.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/OrderedRDDFunctions.scala
@@ -56,7 +56,7 @@ class OrderedRDDFunctions[K : Ordering : ClassTag,
    * order of the keys).
    */
   // TODO: this currently doesn't work on P other than Tuple2!
-  def sortByKey(ascending: Boolean = true, numPartitions: Int = self.partitions.size)
+  def sortByKey(ascending: Boolean = true, numPartitions: Int = self.partitions.length)
       : RDD[(K, V)] =
   {
     val part = new RangePartitioner(numPartitions, self, ascending)
diff --git a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala
index bf1303d39592d..05351ba4ff76b 100644
--- a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala
@@ -823,7 +823,7 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)])
    * RDD will be <= us.
    */
   def subtractByKey[W: ClassTag](other: RDD[(K, W)]): RDD[(K, V)] =
-    subtractByKey(other, self.partitioner.getOrElse(new HashPartitioner(self.partitions.size)))
+    subtractByKey(other, self.partitioner.getOrElse(new HashPartitioner(self.partitions.length)))
 
   /** Return an RDD with the pairs from `this` whose keys are not in `other`. */
   def subtractByKey[W: ClassTag](other: RDD[(K, W)], numPartitions: Int): RDD[(K, V)] =
diff --git a/core/src/main/scala/org/apache/spark/rdd/RDD.scala b/core/src/main/scala/org/apache/spark/rdd/RDD.scala
index ddbfd5624e741..d80d94a588346 100644
--- a/core/src/main/scala/org/apache/spark/rdd/RDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/RDD.scala
@@ -316,7 +316,7 @@ abstract class RDD[T: ClassTag](
   /**
    * Return a new RDD containing the distinct elements in this RDD.
    */
-  def distinct(): RDD[T] = distinct(partitions.size)
+  def distinct(): RDD[T] = distinct(partitions.length)
 
   /**
    * Return a new RDD that has exactly numPartitions partitions.
@@ -488,7 +488,7 @@ abstract class RDD[T: ClassTag](
   def sortBy[K](
       f: (T) => K,
       ascending: Boolean = true,
-      numPartitions: Int = this.partitions.size)
+      numPartitions: Int = this.partitions.length)
       (implicit ord: Ordering[K], ctag: ClassTag[K]): RDD[T] =
     this.keyBy[K](f)
         .sortByKey(ascending, numPartitions)
@@ -852,7 +852,7 @@ abstract class RDD[T: ClassTag](
    * RDD will be &lt;= us.
    */
   def subtract(other: RDD[T]): RDD[T] =
-    subtract(other, partitioner.getOrElse(new HashPartitioner(partitions.size)))
+    subtract(other, partitioner.getOrElse(new HashPartitioner(partitions.length)))
 
   /**
    * Return an RDD with the elements from `this` that are not in `other`.
@@ -986,14 +986,14 @@ abstract class RDD[T: ClassTag](
       combOp: (U, U) => U,
       depth: Int = 2): U = {
     require(depth >= 1, s"Depth must be greater than or equal to 1 but got $depth.")
-    if (partitions.size == 0) {
+    if (partitions.length == 0) {
       return Utils.clone(zeroValue, context.env.closureSerializer.newInstance())
     }
     val cleanSeqOp = context.clean(seqOp)
     val cleanCombOp = context.clean(combOp)
     val aggregatePartition = (it: Iterator[T]) => it.aggregate(zeroValue)(cleanSeqOp, cleanCombOp)
     var partiallyAggregated = mapPartitions(it => Iterator(aggregatePartition(it)))
-    var numPartitions = partiallyAggregated.partitions.size
+    var numPartitions = partiallyAggregated.partitions.length
     val scale = math.max(math.ceil(math.pow(numPartitions, 1.0 / depth)).toInt, 2)
     // If creating an extra level doesn't help reduce the wall-clock time, we stop tree aggregation.
     while (numPartitions > scale + numPartitions / scale) {
@@ -1026,7 +1026,7 @@ abstract class RDD[T: ClassTag](
       }
       result
     }
-    val evaluator = new CountEvaluator(partitions.size, confidence)
+    val evaluator = new CountEvaluator(partitions.length, confidence)
     sc.runApproximateJob(this, countElements, evaluator, timeout)
   }
 
@@ -1061,7 +1061,7 @@ abstract class RDD[T: ClassTag](
       }
       map
     }
-    val evaluator = new GroupedCountEvaluator[T](partitions.size, confidence)
+    val evaluator = new GroupedCountEvaluator[T](partitions.length, confidence)
     sc.runApproximateJob(this, countPartition, evaluator, timeout)
   }
 
@@ -1140,7 +1140,7 @@ abstract class RDD[T: ClassTag](
    * the same index assignments, you should sort the RDD with sortByKey() or save it to a file.
    */
   def zipWithUniqueId(): RDD[(T, Long)] = {
-    val n = this.partitions.size.toLong
+    val n = this.partitions.length.toLong
     this.mapPartitionsWithIndex { case (k, iter) =>
       iter.zipWithIndex.map { case (item, i) =>
         (item, i * n + k)
@@ -1243,7 +1243,7 @@ abstract class RDD[T: ClassTag](
         queue ++= util.collection.Utils.takeOrdered(items, num)(ord)
         Iterator.single(queue)
       }
-      if (mapRDDs.partitions.size == 0) {
+      if (mapRDDs.partitions.length == 0) {
         Array.empty
       } else {
         mapRDDs.reduce { (queue1, queue2) =>
@@ -1489,7 +1489,7 @@ abstract class RDD[T: ClassTag](
     }
     // The first RDD in the dependency stack has no parents, so no need for a +-
     def firstDebugString(rdd: RDD[_]): Seq[String] = {
-      val partitionStr = "(" + rdd.partitions.size + ")"
+      val partitionStr = "(" + rdd.partitions.length + ")"
       val leftOffset = (partitionStr.length - 1) / 2
       val nextPrefix = (" " * leftOffset) + "|" + (" " * (partitionStr.length - leftOffset))
 
@@ -1499,7 +1499,7 @@ abstract class RDD[T: ClassTag](
       } ++ debugChildren(rdd, nextPrefix)
     }
     def shuffleDebugString(rdd: RDD[_], prefix: String = "", isLastChild: Boolean): Seq[String] = {
-      val partitionStr = "(" + rdd.partitions.size + ")"
+      val partitionStr = "(" + rdd.partitions.length + ")"
       val leftOffset = (partitionStr.length - 1) / 2
       val thisPrefix = prefix.replaceAll("\\|\\s+$", "")
       val nextPrefix = (
diff --git a/core/src/main/scala/org/apache/spark/rdd/RDDCheckpointData.scala b/core/src/main/scala/org/apache/spark/rdd/RDDCheckpointData.scala
index f67e5f1857979..6afd63d537d75 100644
--- a/core/src/main/scala/org/apache/spark/rdd/RDDCheckpointData.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/RDDCheckpointData.scala
@@ -94,10 +94,10 @@ private[spark] class RDDCheckpointData[T: ClassTag](@transient rdd: RDD[T])
       new SerializableWritable(rdd.context.hadoopConfiguration))
     rdd.context.runJob(rdd, CheckpointRDD.writeToFile[T](path.toString, broadcastedConf) _)
     val newRDD = new CheckpointRDD[T](rdd.context, path.toString)
-    if (newRDD.partitions.size != rdd.partitions.size) {
+    if (newRDD.partitions.length != rdd.partitions.length) {
       throw new SparkException(
-        "Checkpoint RDD " + newRDD + "(" + newRDD.partitions.size + ") has different " +
-          "number of partitions than original RDD " + rdd + "(" + rdd.partitions.size + ")")
+        "Checkpoint RDD " + newRDD + "(" + newRDD.partitions.length + ") has different " +
+          "number of partitions than original RDD " + rdd + "(" + rdd.partitions.length + ")")
     }
 
     // Change the dependencies and partitions of the RDD
diff --git a/core/src/main/scala/org/apache/spark/rdd/SubtractedRDD.scala b/core/src/main/scala/org/apache/spark/rdd/SubtractedRDD.scala
index c27f435eb9c5a..e9d745588ee9a 100644
--- a/core/src/main/scala/org/apache/spark/rdd/SubtractedRDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/SubtractedRDD.scala
@@ -76,7 +76,7 @@ private[spark] class SubtractedRDD[K: ClassTag, V: ClassTag, W: ClassTag](
 
   override def getPartitions: Array[Partition] = {
     val array = new Array[Partition](part.numPartitions)
-    for (i <- 0 until array.size) {
+    for (i <- 0 until array.length) {
       // Each CoGroupPartition will depend on rdd1 and rdd2
       array(i) = new CoGroupPartition(i, Seq(rdd1, rdd2).zipWithIndex.map { case (rdd, j) =>
         dependencies(j) match {
diff --git a/core/src/main/scala/org/apache/spark/rdd/UnionRDD.scala b/core/src/main/scala/org/apache/spark/rdd/UnionRDD.scala
index 4239e7e22af89..3986645350a82 100644
--- a/core/src/main/scala/org/apache/spark/rdd/UnionRDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/UnionRDD.scala
@@ -63,7 +63,7 @@ class UnionRDD[T: ClassTag](
   extends RDD[T](sc, Nil) {  // Nil since we implement getDependencies
 
   override def getPartitions: Array[Partition] = {
-    val array = new Array[Partition](rdds.map(_.partitions.size).sum)
+    val array = new Array[Partition](rdds.map(_.partitions.length).sum)
     var pos = 0
     for ((rdd, rddIndex) <- rdds.zipWithIndex; split <- rdd.partitions) {
       array(pos) = new UnionPartition(pos, rdd, rddIndex, split.index)
@@ -76,8 +76,8 @@ class UnionRDD[T: ClassTag](
     val deps = new ArrayBuffer[Dependency[_]]
     var pos = 0
     for (rdd <- rdds) {
-      deps += new RangeDependency(rdd, 0, pos, rdd.partitions.size)
-      pos += rdd.partitions.size
+      deps += new RangeDependency(rdd, 0, pos, rdd.partitions.length)
+      pos += rdd.partitions.length
     }
     deps
   }
diff --git a/core/src/main/scala/org/apache/spark/rdd/ZippedPartitionsRDD.scala b/core/src/main/scala/org/apache/spark/rdd/ZippedPartitionsRDD.scala
index d0be304762e1f..a96b6c3d23454 100644
--- a/core/src/main/scala/org/apache/spark/rdd/ZippedPartitionsRDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/ZippedPartitionsRDD.scala
@@ -52,8 +52,8 @@ private[spark] abstract class ZippedPartitionsBaseRDD[V: ClassTag](
     if (preservesPartitioning) firstParent[Any].partitioner else None
 
   override def getPartitions: Array[Partition] = {
-    val numParts = rdds.head.partitions.size
-    if (!rdds.forall(rdd => rdd.partitions.size == numParts)) {
+    val numParts = rdds.head.partitions.length
+    if (!rdds.forall(rdd => rdd.partitions.length == numParts)) {
       throw new IllegalArgumentException("Can't zip RDDs with unequal numbers of partitions")
     }
     Array.tabulate[Partition](numParts) { i =>
diff --git a/core/src/main/scala/org/apache/spark/rdd/ZippedWithIndexRDD.scala b/core/src/main/scala/org/apache/spark/rdd/ZippedWithIndexRDD.scala
index 8c43a559409f2..523aaf2b860b5 100644
--- a/core/src/main/scala/org/apache/spark/rdd/ZippedWithIndexRDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/ZippedWithIndexRDD.scala
@@ -41,7 +41,7 @@ class ZippedWithIndexRDD[T: ClassTag](@transient prev: RDD[T]) extends RDD[(T, L
 
   /** The start index of each partition. */
   @transient private val startIndices: Array[Long] = {
-    val n = prev.partitions.size
+    val n = prev.partitions.length
     if (n == 0) {
       Array[Long]()
     } else if (n == 1) {
diff --git a/core/src/main/scala/org/apache/spark/storage/RDDInfo.scala b/core/src/main/scala/org/apache/spark/storage/RDDInfo.scala
index 0186eb30a1905..034525b56f59c 100644
--- a/core/src/main/scala/org/apache/spark/storage/RDDInfo.scala
+++ b/core/src/main/scala/org/apache/spark/storage/RDDInfo.scala
@@ -52,6 +52,6 @@ class RDDInfo(
 private[spark] object RDDInfo {
   def fromRdd(rdd: RDD[_]): RDDInfo = {
     val rddName = Option(rdd.name).getOrElse(rdd.id.toString)
-    new RDDInfo(rdd.id, rddName, rdd.partitions.size, rdd.getStorageLevel)
+    new RDDInfo(rdd.id, rddName, rdd.partitions.length, rdd.getStorageLevel)
   }
 }
diff --git a/core/src/main/scala/org/apache/spark/ui/ConsoleProgressBar.scala b/core/src/main/scala/org/apache/spark/ui/ConsoleProgressBar.scala
index 67f572e79314d..77c0bc8b5360a 100644
--- a/core/src/main/scala/org/apache/spark/ui/ConsoleProgressBar.scala
+++ b/core/src/main/scala/org/apache/spark/ui/ConsoleProgressBar.scala
@@ -65,7 +65,7 @@ private[spark] class ConsoleProgressBar(sc: SparkContext) extends Logging {
     val stageIds = sc.statusTracker.getActiveStageIds()
     val stages = stageIds.map(sc.statusTracker.getStageInfo).flatten.filter(_.numTasks() > 1)
       .filter(now - _.submissionTime() > FIRST_DELAY).sortBy(_.stageId())
-    if (stages.size > 0) {
+    if (stages.length > 0) {
       show(now, stages.take(3))  // display at most 3 stages in same time
     }
   }
@@ -81,7 +81,7 @@ private[spark] class ConsoleProgressBar(sc: SparkContext) extends Logging {
       val total = s.numTasks()
       val header = s"[Stage ${s.stageId()}:"
       val tailer = s"(${s.numCompletedTasks()} + ${s.numActiveTasks()}) / $total]"
-      val w = width - header.size - tailer.size
+      val w = width - header.length - tailer.length
       val bar = if (w > 0) {
         val percent = w * s.numCompletedTasks() / total
         (0 until w).map { i =>
diff --git a/core/src/main/scala/org/apache/spark/util/collection/BitSet.scala b/core/src/main/scala/org/apache/spark/util/collection/BitSet.scala
index f79e8e0491ea1..41cb8cfe2afa3 100644
--- a/core/src/main/scala/org/apache/spark/util/collection/BitSet.scala
+++ b/core/src/main/scala/org/apache/spark/util/collection/BitSet.scala
@@ -39,7 +39,7 @@ class BitSet(numBits: Int) extends Serializable {
     val wordIndex = bitIndex >> 6 // divide by 64
     var i = 0
     while(i < wordIndex) { words(i) = -1; i += 1 }
-    if(wordIndex < words.size) {
+    if(wordIndex < words.length) {
       // Set the remaining bits (note that the mask could still be zero)
       val mask = ~(-1L << (bitIndex & 0x3f))
       words(wordIndex) |= mask

From 12322159147581602978f7f5a6b33b887ef781a1 Mon Sep 17 00:00:00 2001
From: Reynold Xin <rxin@databricks.com>
Date: Tue, 7 Apr 2015 12:37:33 -0700
Subject: [PATCH 03/95] [SPARK-6750] Upgrade ScalaStyle to 0.7.

0.7 fixes a bug that's pretty useful, i.e. inline functions no longer return explicit type definition.

Author: Reynold Xin <rxin@databricks.com>

Closes #5399 from rxin/style0.7 and squashes the following commits:

54c41b2 [Reynold Xin] Actually update the version.
09c759c [Reynold Xin] [SPARK-6750] Upgrade ScalaStyle to 0.7.
---
 project/plugins.sbt                           |  2 +-
 project/project/SparkPluginBuild.scala        | 16 +-------
 .../scalastyle/NonASCIICharacterChecker.scala | 39 -------------------
 3 files changed, 2 insertions(+), 55 deletions(-)
 delete mode 100644 project/spark-style/src/main/scala/org/apache/spark/scalastyle/NonASCIICharacterChecker.scala

diff --git a/project/plugins.sbt b/project/plugins.sbt
index ee45b6a51905e..7096b0d3ee7de 100644
--- a/project/plugins.sbt
+++ b/project/plugins.sbt
@@ -19,7 +19,7 @@ addSbtPlugin("com.github.mpeltonen" % "sbt-idea" % "1.6.0")
 
 addSbtPlugin("net.virtual-void" % "sbt-dependency-graph" % "0.7.4")
 
-addSbtPlugin("org.scalastyle" %% "scalastyle-sbt-plugin" % "0.6.0")
+addSbtPlugin("org.scalastyle" %% "scalastyle-sbt-plugin" % "0.7.0")
 
 addSbtPlugin("com.typesafe" % "sbt-mima-plugin" % "0.1.6")
 
diff --git a/project/project/SparkPluginBuild.scala b/project/project/SparkPluginBuild.scala
index 8863f272da415..471d00bd8223f 100644
--- a/project/project/SparkPluginBuild.scala
+++ b/project/project/SparkPluginBuild.scala
@@ -24,20 +24,6 @@ import sbt.Keys._
  * becomes available for scalastyle sbt plugin.
  */
 object SparkPluginDef extends Build {
-  lazy val root = Project("plugins", file(".")) dependsOn(sparkStyle, sbtPomReader)
-  lazy val sparkStyle = Project("spark-style", file("spark-style"), settings = styleSettings)
+  lazy val root = Project("plugins", file(".")) dependsOn(sbtPomReader)
   lazy val sbtPomReader = uri("https://github.com/ScrapCodes/sbt-pom-reader.git#ignore_artifact_id")
-
-  // There is actually no need to publish this artifact.
-  def styleSettings = Defaults.defaultSettings ++ Seq (
-    name                 :=  "spark-style",
-    organization         :=  "org.apache.spark",
-    scalaVersion         :=  "2.10.4",
-    scalacOptions        :=  Seq("-unchecked", "-deprecation"),
-    libraryDependencies  ++= Dependencies.scalaStyle
-  )
-
-  object Dependencies {
-    val scalaStyle = Seq("org.scalastyle" %% "scalastyle" % "0.4.0")
-  }
 }
diff --git a/project/spark-style/src/main/scala/org/apache/spark/scalastyle/NonASCIICharacterChecker.scala b/project/spark-style/src/main/scala/org/apache/spark/scalastyle/NonASCIICharacterChecker.scala
deleted file mode 100644
index 3d43c35299555..0000000000000
--- a/project/spark-style/src/main/scala/org/apache/spark/scalastyle/NonASCIICharacterChecker.scala
+++ /dev/null
@@ -1,39 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License.  You may obtain a copy of the License at
- *
- *    http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-
-package org.apache.spark.scalastyle
-
-import java.util.regex.Pattern
-
-import org.scalastyle.{PositionError, ScalariformChecker, ScalastyleError}
-
-import scalariform.lexer.Token
-import scalariform.parser.CompilationUnit
-
-class NonASCIICharacterChecker extends ScalariformChecker {
-  val errorKey: String = "non.ascii.character.disallowed"
-
-  override def verify(ast: CompilationUnit): List[ScalastyleError] = {
-    ast.tokens.filter(hasNonAsciiChars).map(x => PositionError(x.offset)).toList
-  }
-
-  private def hasNonAsciiChars(x: Token) =
-    x.rawText.trim.nonEmpty && !Pattern.compile( """\p{ASCII}+""", Pattern.DOTALL)
-    .matcher(x.text.trim).matches()
-
-}

From 596ba77c5fdca79486396989e549632153055caf Mon Sep 17 00:00:00 2001
From: Masayoshi TSUZUKI <tsudukim@oss.nttdata.co.jp>
Date: Tue, 7 Apr 2015 14:29:53 -0700
Subject: [PATCH 04/95] [SPARK-6568] spark-shell.cmd --jars option does not
 accept the jar that has space in its path

escape spaces in the arguments.

Author: Masayoshi TSUZUKI <tsudukim@oss.nttdata.co.jp>

Closes #5347 from tsudukim/feature/SPARK-6568 and squashes the following commits:

9180aaf [Masayoshi TSUZUKI] [SPARK-6568] spark-shell.cmd --jars option does not accept the jar that has space in its path
---
 core/src/main/scala/org/apache/spark/util/Utils.scala      | 2 +-
 core/src/test/scala/org/apache/spark/util/UtilsSuite.scala | 6 ++++--
 2 files changed, 5 insertions(+), 3 deletions(-)

diff --git a/core/src/main/scala/org/apache/spark/util/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala
index 0fdfaf300e95d..25ae6ee579ab3 100644
--- a/core/src/main/scala/org/apache/spark/util/Utils.scala
+++ b/core/src/main/scala/org/apache/spark/util/Utils.scala
@@ -1661,7 +1661,7 @@ private[spark] object Utils extends Logging {
   /**
    * Format a Windows path such that it can be safely passed to a URI.
    */
-  def formatWindowsPath(path: String): String = path.replace("\\", "/")
+  def formatWindowsPath(path: String): String = path.replace("\\", "/").replace(" ", "%20")
 
   /**
    * Indicates whether Spark is currently running unit tests.
diff --git a/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
index 5d93086082189..b7cc84078983a 100644
--- a/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
@@ -241,6 +241,7 @@ class UtilsSuite extends FunSuite with ResetSystemProperties {
     assertResolves("C:/path/to/file.txt", "file:/C:/path/to/file.txt", testWindows = true)
     assertResolves("C:\\path\\to\\file.txt", "file:/C:/path/to/file.txt", testWindows = true)
     assertResolves("file:/C:/path/to/file.txt", "file:/C:/path/to/file.txt", testWindows = true)
+    assertResolves("file:/C:/path to/file.txt", "file:/C:/path%20to/file.txt", testWindows = true)
     assertResolves("file:///C:/path/to/file.txt", "file:/C:/path/to/file.txt", testWindows = true)
     assertResolves("file:/C:/file.txt#alias.txt", "file:/C:/file.txt#alias.txt", testWindows = true)
     intercept[IllegalArgumentException] { Utils.resolveURI("file:foo") }
@@ -264,8 +265,9 @@ class UtilsSuite extends FunSuite with ResetSystemProperties {
     assertResolves("hdfs:/jar1,file:/jar2,jar3", s"hdfs:/jar1,file:/jar2,file:$cwd/jar3")
     assertResolves("hdfs:/jar1,file:/jar2,jar3,jar4#jar5",
       s"hdfs:/jar1,file:/jar2,file:$cwd/jar3,file:$cwd/jar4#jar5")
-    assertResolves("hdfs:/jar1,file:/jar2,jar3,C:\\pi.py#py.pi",
-      s"hdfs:/jar1,file:/jar2,file:$cwd/jar3,file:/C:/pi.py#py.pi", testWindows = true)
+    assertResolves("""hdfs:/jar1,file:/jar2,jar3,C:\pi.py#py.pi,C:\path to\jar4.jar""",
+      s"hdfs:/jar1,file:/jar2,file:$cwd/jar3,file:/C:/pi.py#py.pi,file:/C:/path%20to/jar4.jar",
+      testWindows = true)
   }
 
   test("nonLocalPaths") {

From e6f08fb42fda35952ea8b005170750ae551dc7d9 Mon Sep 17 00:00:00 2001
From: Xiangrui Meng <meng@databricks.com>
Date: Tue, 7 Apr 2015 14:34:15 -0700
Subject: [PATCH 05/95] Revert "[SPARK-6568] spark-shell.cmd --jars option does
 not accept the jar that has space in its path"

This reverts commit 596ba77c5fdca79486396989e549632153055caf.
---
 core/src/main/scala/org/apache/spark/util/Utils.scala      | 2 +-
 core/src/test/scala/org/apache/spark/util/UtilsSuite.scala | 6 ++----
 2 files changed, 3 insertions(+), 5 deletions(-)

diff --git a/core/src/main/scala/org/apache/spark/util/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala
index 25ae6ee579ab3..0fdfaf300e95d 100644
--- a/core/src/main/scala/org/apache/spark/util/Utils.scala
+++ b/core/src/main/scala/org/apache/spark/util/Utils.scala
@@ -1661,7 +1661,7 @@ private[spark] object Utils extends Logging {
   /**
    * Format a Windows path such that it can be safely passed to a URI.
    */
-  def formatWindowsPath(path: String): String = path.replace("\\", "/").replace(" ", "%20")
+  def formatWindowsPath(path: String): String = path.replace("\\", "/")
 
   /**
    * Indicates whether Spark is currently running unit tests.
diff --git a/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
index b7cc84078983a..5d93086082189 100644
--- a/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
@@ -241,7 +241,6 @@ class UtilsSuite extends FunSuite with ResetSystemProperties {
     assertResolves("C:/path/to/file.txt", "file:/C:/path/to/file.txt", testWindows = true)
     assertResolves("C:\\path\\to\\file.txt", "file:/C:/path/to/file.txt", testWindows = true)
     assertResolves("file:/C:/path/to/file.txt", "file:/C:/path/to/file.txt", testWindows = true)
-    assertResolves("file:/C:/path to/file.txt", "file:/C:/path%20to/file.txt", testWindows = true)
     assertResolves("file:///C:/path/to/file.txt", "file:/C:/path/to/file.txt", testWindows = true)
     assertResolves("file:/C:/file.txt#alias.txt", "file:/C:/file.txt#alias.txt", testWindows = true)
     intercept[IllegalArgumentException] { Utils.resolveURI("file:foo") }
@@ -265,9 +264,8 @@ class UtilsSuite extends FunSuite with ResetSystemProperties {
     assertResolves("hdfs:/jar1,file:/jar2,jar3", s"hdfs:/jar1,file:/jar2,file:$cwd/jar3")
     assertResolves("hdfs:/jar1,file:/jar2,jar3,jar4#jar5",
       s"hdfs:/jar1,file:/jar2,file:$cwd/jar3,file:$cwd/jar4#jar5")
-    assertResolves("""hdfs:/jar1,file:/jar2,jar3,C:\pi.py#py.pi,C:\path to\jar4.jar""",
-      s"hdfs:/jar1,file:/jar2,file:$cwd/jar3,file:/C:/pi.py#py.pi,file:/C:/path%20to/jar4.jar",
-      testWindows = true)
+    assertResolves("hdfs:/jar1,file:/jar2,jar3,C:\\pi.py#py.pi",
+      s"hdfs:/jar1,file:/jar2,file:$cwd/jar3,file:/C:/pi.py#py.pi", testWindows = true)
   }
 
   test("nonLocalPaths") {

From fc957dc78138e72036dbbadc9a54f155d318c038 Mon Sep 17 00:00:00 2001
From: lewuathe <lewuathe@me.com>
Date: Tue, 7 Apr 2015 14:36:57 -0700
Subject: [PATCH 06/95] [SPARK-6720][MLLIB] PySpark
 MultivariateStatisticalSummary unit test for normL1...

... and normL2.
Add test cases to insufficient unit test for `normL1` and `normL2`.

Ref: https://github.com/apache/spark/pull/5359

Author: lewuathe <lewuathe@me.com>

Closes #5374 from Lewuathe/SPARK-6720 and squashes the following commits:

5541b24 [lewuathe] More accurate tests
dc5718c [lewuathe] [SPARK-6720] PySpark MultivariateStatisticalSummary unit test for normL1 and normL2
---
 python/pyspark/mllib/tests.py | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/python/pyspark/mllib/tests.py b/python/pyspark/mllib/tests.py
index 47dad7d12e4e4..61ef398487c0c 100644
--- a/python/pyspark/mllib/tests.py
+++ b/python/pyspark/mllib/tests.py
@@ -363,6 +363,13 @@ def test_col_norms(self):
         self.assertEqual(10, len(summary.normL1()))
         self.assertEqual(10, len(summary.normL2()))
 
+        data2 = self.sc.parallelize(xrange(10)).map(lambda x: Vectors.dense(x))
+        summary2 = Statistics.colStats(data2)
+        self.assertEqual(array([45.0]), summary2.normL1())
+        import math
+        expectedNormL2 = math.sqrt(sum(map(lambda x: x*x, xrange(10))))
+        self.assertTrue(math.fabs(summary2.normL2()[0] - expectedNormL2) < 1e-14)
+
 
 class VectorUDTTests(PySparkTestCase):
 

From 77bcceb9f01e97cb6f41791f2167b40c4311f701 Mon Sep 17 00:00:00 2001
From: Cheng Lian <lian@databricks.com>
Date: Wed, 8 Apr 2015 07:00:56 +0800
Subject: [PATCH 07/95] [SPARK-6748] [SQL] Makes QueryPlan.schema a lazy val

`DataFrame.collect()` calls `SparkPlan.executeCollect()`, which consists of a single line:

```scala
execute().map(ScalaReflection.convertRowToScala(_, schema)).collect()
```

The problem is that, `QueryPlan.schema` is a function. And since 1.3.0, `convertRowToScala` starts returning a `GenericRowWithSchema`. Thus, every `GenericRowWithSchema` instance holds a separate copy of the schema object. Also, YJP profiling result of the following simple micro benchmark (executed in Spark shell) shows that constructing the schema object takes up to ~35% CPU time.

```scala
sc.parallelize(1 to 10000000).
  map(i => (i, s"val_$i")).
  toDF("key", "value").
  saveAsParquetFile("file:///tmp/src.parquet")

// Profiling started from this line
sqlContext.parquetFile("file:///tmp/src.parquet").collect()
```

<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/5398)
<!-- Reviewable:end -->

Author: Cheng Lian <lian@databricks.com>

Closes #5398 from liancheng/spark-6748 and squashes the following commits:

3159469 [Cheng Lian] Makes QueryPlan.schema a lazy val
---
 .../scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala   | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala
index 02f7c26a8ab6e..7967189cacb24 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala
@@ -150,7 +150,7 @@ abstract class QueryPlan[PlanType <: TreeNode[PlanType]] extends TreeNode[PlanTy
     }.toSeq
   }
 
-  def schema: StructType = StructType.fromAttributes(output)
+  lazy val schema: StructType = StructType.fromAttributes(output)
 
   /** Returns the output schema in the tree format. */
   def schemaString: String = schema.treeString

From c83e03948b184ffb3a9418fecc4d2c26ae33b057 Mon Sep 17 00:00:00 2001
From: Josh Rosen <joshrosen@databricks.com>
Date: Tue, 7 Apr 2015 16:18:55 -0700
Subject: [PATCH 08/95] [SPARK-6737] Fix memory leak in OutputCommitCoordinator

This patch fixes a memory leak in the DAGScheduler, which caused us to leak a map entry per submitted stage.  The problem is that the OutputCommitCoordinator needs to be informed when stages end in order to remove entries from its `authorizedCommitters` map, but the DAGScheduler only called it in one of the four code paths that are used to mark stages as completed.

This patch fixes this issue by consolidating the processing of stage completion into a new `markStageAsFinished` method and updates DAGSchedulerSuite's `assertDataStructuresEmpty` assertion to also check the OutputCommitCoordinator data structures.  I've also added a comment at the top of DAGScheduler so that we remember to update this test when adding new data structures.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #5397 from JoshRosen/SPARK-6737 and squashes the following commits:

af3b02f [Josh Rosen] Consolidate stage completion handling code in a single method.
e96ce3a [Josh Rosen] Consolidate stage completion handling code in a single method.
3052aea [Josh Rosen] Comment update
7896899 [Josh Rosen] Fix SPARK-6737 by informing OutputCommitCoordinator of all stage end events.
4ead1dc [Josh Rosen] Add regression tests for SPARK-6737
---
 .../apache/spark/scheduler/DAGScheduler.scala | 63 ++++++++++---------
 .../scheduler/OutputCommitCoordinator.scala   |  7 +++
 .../spark/scheduler/DAGSchedulerSuite.scala   |  1 +
 3 files changed, 42 insertions(+), 29 deletions(-)

diff --git a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
index c82ae4baa3630..c912520fded3b 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
@@ -50,6 +50,10 @@ import org.apache.spark.storage.BlockManagerMessages.BlockManagerHeartbeat
  * not caused by shuffle file loss are handled by the TaskScheduler, which will retry each task
  * a small number of times before cancelling the whole stage.
  *
+ * Here's a checklist to use when making or reviewing changes to this class:
+ *
+ *  - When adding a new data structure, update `DAGSchedulerSuite.assertDataStructuresEmpty` to
+ *    include the new structure. This will help to catch memory leaks.
  */
 private[spark]
 class DAGScheduler(
@@ -111,6 +115,8 @@ class DAGScheduler(
   //       stray messages to detect.
   private val failedEpoch = new HashMap[String, Long]
 
+  private [scheduler] val outputCommitCoordinator = env.outputCommitCoordinator
+
   // A closure serializer that we reuse.
   // This is only safe because DAGScheduler runs in a single thread.
   private val closureSerializer = SparkEnv.get.closureSerializer.newInstance()
@@ -128,8 +134,6 @@ class DAGScheduler(
   private[scheduler] val eventProcessLoop = new DAGSchedulerEventProcessLoop(this)
   taskScheduler.setDAGScheduler(this)
 
-  private val outputCommitCoordinator = env.outputCommitCoordinator
-
   // Called by TaskScheduler to report task's starting.
   def taskStarted(task: Task[_], taskInfo: TaskInfo) {
     eventProcessLoop.post(BeginEvent(task, taskInfo))
@@ -710,9 +714,10 @@ class DAGScheduler(
       // cancelling the stages because if the DAG scheduler is stopped, the entire application
       // is in the process of getting stopped.
       val stageFailedMessage = "Stage cancelled because SparkContext was shut down"
-      runningStages.foreach { stage =>
-        stage.latestInfo.stageFailed(stageFailedMessage)
-        listenerBus.post(SparkListenerStageCompleted(stage.latestInfo))
+      // The `toArray` here is necessary so that we don't iterate over `runningStages` while
+      // mutating it.
+      runningStages.toArray.foreach { stage =>
+        markStageAsFinished(stage, Some(stageFailedMessage))
       }
       listenerBus.post(SparkListenerJobEnd(job.jobId, clock.getTimeMillis(), JobFailed(error)))
     }
@@ -887,10 +892,9 @@ class DAGScheduler(
         new TaskSet(tasks.toArray, stage.id, stage.newAttemptId(), stage.jobId, properties))
       stage.latestInfo.submissionTime = Some(clock.getTimeMillis())
     } else {
-      // Because we posted SparkListenerStageSubmitted earlier, we should post
-      // SparkListenerStageCompleted here in case there are no tasks to run.
-      outputCommitCoordinator.stageEnd(stage.id)
-      listenerBus.post(SparkListenerStageCompleted(stage.latestInfo))
+      // Because we posted SparkListenerStageSubmitted earlier, we should mark
+      // the stage as completed here in case there are no tasks to run
+      markStageAsFinished(stage, None)
 
       val debugString = stage match {
         case stage: ShuffleMapStage =>
@@ -902,7 +906,6 @@ class DAGScheduler(
           s"Stage ${stage} is actually done; (partitions: ${stage.numPartitions})"
       }
       logDebug(debugString)
-      runningStages -= stage
     }
   }
 
@@ -968,22 +971,6 @@ class DAGScheduler(
     }
 
     val stage = stageIdToStage(task.stageId)
-
-    def markStageAsFinished(stage: Stage, errorMessage: Option[String] = None): Unit = {
-      val serviceTime = stage.latestInfo.submissionTime match {
-        case Some(t) => "%.03f".format((clock.getTimeMillis() - t) / 1000.0)
-        case _ => "Unknown"
-      }
-      if (errorMessage.isEmpty) {
-        logInfo("%s (%s) finished in %s s".format(stage, stage.name, serviceTime))
-        stage.latestInfo.completionTime = Some(clock.getTimeMillis())
-      } else {
-        stage.latestInfo.stageFailed(errorMessage.get)
-        logInfo("%s (%s) failed in %s s".format(stage, stage.name, serviceTime))
-      }
-      listenerBus.post(SparkListenerStageCompleted(stage.latestInfo))
-      runningStages -= stage
-    }
     event.reason match {
       case Success =>
         listenerBus.post(SparkListenerTaskEnd(stageId, stage.latestInfo.attemptId, taskType,
@@ -1099,7 +1086,6 @@ class DAGScheduler(
           logInfo(s"Marking $failedStage (${failedStage.name}) as failed " +
             s"due to a fetch failure from $mapStage (${mapStage.name})")
           markStageAsFinished(failedStage, Some(failureMessage))
-          runningStages -= failedStage
         }
 
         if (disallowStageRetryForTest) {
@@ -1215,6 +1201,26 @@ class DAGScheduler(
     submitWaitingStages()
   }
 
+  /**
+   * Marks a stage as finished and removes it from the list of running stages.
+   */
+  private def markStageAsFinished(stage: Stage, errorMessage: Option[String] = None): Unit = {
+    val serviceTime = stage.latestInfo.submissionTime match {
+      case Some(t) => "%.03f".format((clock.getTimeMillis() - t) / 1000.0)
+      case _ => "Unknown"
+    }
+    if (errorMessage.isEmpty) {
+      logInfo("%s (%s) finished in %s s".format(stage, stage.name, serviceTime))
+      stage.latestInfo.completionTime = Some(clock.getTimeMillis())
+    } else {
+      stage.latestInfo.stageFailed(errorMessage.get)
+      logInfo("%s (%s) failed in %s s".format(stage, stage.name, serviceTime))
+    }
+    outputCommitCoordinator.stageEnd(stage.id)
+    listenerBus.post(SparkListenerStageCompleted(stage.latestInfo))
+    runningStages -= stage
+  }
+
   /**
    * Aborts all jobs depending on a particular Stage. This is called in response to a task set
    * being canceled by the TaskScheduler. Use taskSetFailed() to inject this event from outside.
@@ -1264,8 +1270,7 @@ class DAGScheduler(
           if (runningStages.contains(stage)) {
             try { // cancelTasks will fail if a SchedulerBackend does not implement killTask
               taskScheduler.cancelTasks(stageId, shouldInterruptThread)
-              stage.latestInfo.stageFailed(failureReason)
-              listenerBus.post(SparkListenerStageCompleted(stage.latestInfo))
+              markStageAsFinished(stage, Some(failureReason))
             } catch {
               case e: UnsupportedOperationException =>
                 logInfo(s"Could not cancel tasks for stage $stageId", e)
diff --git a/core/src/main/scala/org/apache/spark/scheduler/OutputCommitCoordinator.scala b/core/src/main/scala/org/apache/spark/scheduler/OutputCommitCoordinator.scala
index 9e29fd13821dc..7c184b1dcb308 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/OutputCommitCoordinator.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/OutputCommitCoordinator.scala
@@ -59,6 +59,13 @@ private[spark] class OutputCommitCoordinator(conf: SparkConf) extends Logging {
   private val authorizedCommittersByStage: CommittersByStageMap = mutable.Map()
   private type CommittersByStageMap = mutable.Map[StageId, mutable.Map[PartitionId, TaskAttemptId]]
 
+  /**
+   * Returns whether the OutputCommitCoordinator's internal data structures are all empty.
+   */
+  def isEmpty: Boolean = {
+    authorizedCommittersByStage.isEmpty
+  }
+
   /**
    * Called by tasks to ask whether they can commit their output to HDFS.
    *
diff --git a/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala
index 63360a0f189a3..eb759f0807a17 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala
@@ -783,6 +783,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     assert(scheduler.runningStages.isEmpty)
     assert(scheduler.shuffleToMapStage.isEmpty)
     assert(scheduler.waitingStages.isEmpty)
+    assert(scheduler.outputCommitCoordinator.isEmpty)
   }
 
   // Nothing in this test should break if the task info's fields are null, but

From d138aa8ee23f4450242da3ac70a493229a90c76b Mon Sep 17 00:00:00 2001
From: Omede Firouz <ofirouz@palantir.com>
Date: Tue, 7 Apr 2015 23:36:31 -0400
Subject: [PATCH 09/95] [SPARK-6705][MLLIB] Add fit intercept api to ml
 logisticregression

I have the fit intercept enabled by default for logistic regression, I
wonder what others think here. I understand that it enables allocation
by default which is undesirable, but one needs to have a very strong
reason for not having an intercept term enabled so it is the safer
default from a statistical sense.

Explicitly modeling the intercept by adding a column of all 1s does not
work. I believe the reason is that since the API for
LogisticRegressionWithLBFGS forces column normalization, and a column of all
1s has 0 variance so dividing by 0 kills it.

Author: Omede Firouz <ofirouz@palantir.com>

Closes #5301 from oefirouz/addIntercept and squashes the following commits:

9f1286b [Omede Firouz] [SPARK-6705][MLLIB] Add fitInterceptTerm to LogisticRegression
1d6bd6f [Omede Firouz] [SPARK-6705][MLLIB] Add a fit intercept term to ML LogisticRegression
9963509 [Omede Firouz] [MLLIB] Add fitIntercept to LogisticRegression
2257fca [Omede Firouz] [MLLIB] Add fitIntercept param to logistic regression
329c1e2 [Omede Firouz] [MLLIB] Add fit intercept term
bd9663c [Omede Firouz] [MLLIB] Add fit intercept api to ml logisticregression
---
 .../spark/ml/classification/LogisticRegression.scala |  8 ++++++--
 .../org/apache/spark/ml/param/sharedParams.scala     | 12 ++++++++++++
 .../ml/classification/LogisticRegressionSuite.scala  |  9 +++++++++
 3 files changed, 27 insertions(+), 2 deletions(-)

diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
index 49c00f77480e8..34625745dd0a8 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
@@ -31,7 +31,7 @@ import org.apache.spark.storage.StorageLevel
  * Params for logistic regression.
  */
 private[classification] trait LogisticRegressionParams extends ProbabilisticClassifierParams
-  with HasRegParam with HasMaxIter with HasThreshold
+  with HasRegParam with HasMaxIter with HasFitIntercept with HasThreshold
 
 
 /**
@@ -55,6 +55,9 @@ class LogisticRegression
   /** @group setParam */
   def setMaxIter(value: Int): this.type = set(maxIter, value)
 
+  /** @group setParam */
+  def setFitIntercept(value: Boolean): this.type = set(fitIntercept, value)
+
   /** @group setParam */
   def setThreshold(value: Double): this.type = set(threshold, value)
 
@@ -67,7 +70,8 @@ class LogisticRegression
     }
 
     // Train model
-    val lr = new LogisticRegressionWithLBFGS
+    val lr = new LogisticRegressionWithLBFGS()
+      .setIntercept(paramMap(fitIntercept))
     lr.optimizer
       .setRegParam(paramMap(regParam))
       .setNumIterations(paramMap(maxIter))
diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/sharedParams.scala b/mllib/src/main/scala/org/apache/spark/ml/param/sharedParams.scala
index 5d660d1e151a7..0739fdbfcbaae 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/param/sharedParams.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/param/sharedParams.scala
@@ -106,6 +106,18 @@ private[ml] trait HasProbabilityCol extends Params {
   def getProbabilityCol: String = get(probabilityCol)
 }
 
+private[ml] trait HasFitIntercept extends Params {
+  /**
+   * param for fitting the intercept term, defaults to true
+   * @group param
+   */
+  val fitIntercept: BooleanParam =
+    new BooleanParam(this, "fitIntercept", "indicates whether to fit an intercept term", Some(true))
+
+  /** @group getParam */
+  def getFitIntercept: Boolean = get(fitIntercept)
+}
+
 private[ml] trait HasThreshold extends Params {
   /**
    * param for threshold in (binary) prediction
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
index b3d1bfcfbee0f..35d8c2e16c6cd 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
@@ -46,6 +46,7 @@ class LogisticRegressionSuite extends FunSuite with MLlibTestSparkContext {
     assert(lr.getPredictionCol == "prediction")
     assert(lr.getRawPredictionCol == "rawPrediction")
     assert(lr.getProbabilityCol == "probability")
+    assert(lr.getFitIntercept == true)
     val model = lr.fit(dataset)
     model.transform(dataset)
       .select("label", "probability", "prediction", "rawPrediction")
@@ -55,6 +56,14 @@ class LogisticRegressionSuite extends FunSuite with MLlibTestSparkContext {
     assert(model.getPredictionCol == "prediction")
     assert(model.getRawPredictionCol == "rawPrediction")
     assert(model.getProbabilityCol == "probability")
+    assert(model.intercept !== 0.0)
+  }
+
+  test("logistic regression doesn't fit intercept when fitIntercept is off") {
+    val lr = new LogisticRegression
+    lr.setFitIntercept(false)
+    val model = lr.fit(dataset)
+    assert(model.intercept === 0.0)
   }
 
   test("logistic regression with setters") {

From 8d2a36c0fdfbea9f58271ef6aeb89bb79b22cf62 Mon Sep 17 00:00:00 2001
From: Kay Ousterhout <kayousterhout@gmail.com>
Date: Tue, 7 Apr 2015 22:40:42 -0700
Subject: [PATCH 10/95] [SPARK-6754] Remove unnecessary TaskContextHelper

The TaskContextHelper was originally necessary because TaskContext was written in Java, which does
not have a way to specify that classes are package-private, so TaskContextHelper existed to work
around this. Now that TaskContext has been re-written in Scala, this class is no longer necessary.

rxin can you look at this? It looks like you missed this bit of cleanup when you moved TaskContext from Java to Scala in #4324

cc ScrapCodes and pwendell who added this originally.

Author: Kay Ousterhout <kayousterhout@gmail.com>

Closes #5402 from kayousterhout/SPARK-6754 and squashes the following commits:

f089800 [Kay Ousterhout] [SPARK-6754] Remove unnecessary TaskContextHelper
---
 .../org/apache/spark/TaskContextHelper.scala  | 29 -------------------
 .../apache/spark/scheduler/DAGScheduler.scala |  4 +--
 .../org/apache/spark/scheduler/Task.scala     |  6 ++--
 3 files changed, 5 insertions(+), 34 deletions(-)
 delete mode 100644 core/src/main/scala/org/apache/spark/TaskContextHelper.scala

diff --git a/core/src/main/scala/org/apache/spark/TaskContextHelper.scala b/core/src/main/scala/org/apache/spark/TaskContextHelper.scala
deleted file mode 100644
index 4636c4600a01a..0000000000000
--- a/core/src/main/scala/org/apache/spark/TaskContextHelper.scala
+++ /dev/null
@@ -1,29 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License.  You may obtain a copy of the License at
- *
- *    http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package org.apache.spark
-
-/**
- * This class exists to restrict the visibility of TaskContext setters.
- */
-private [spark] object TaskContextHelper {
-
-  def setTaskContext(tc: TaskContext): Unit = TaskContext.setTaskContext(tc)
-
-  def unset(): Unit = TaskContext.unset()
-  
-}
diff --git a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
index c912520fded3b..508fe7b3303ca 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
@@ -645,13 +645,13 @@ class DAGScheduler(
       val split = rdd.partitions(job.partitions(0))
       val taskContext = new TaskContextImpl(job.finalStage.id, job.partitions(0), taskAttemptId = 0,
         attemptNumber = 0, runningLocally = true)
-      TaskContextHelper.setTaskContext(taskContext)
+      TaskContext.setTaskContext(taskContext)
       try {
         val result = job.func(taskContext, rdd.iterator(split, taskContext))
         job.listener.taskSucceeded(0, result)
       } finally {
         taskContext.markTaskCompleted()
-        TaskContextHelper.unset()
+        TaskContext.unset()
       }
     } catch {
       case e: Exception =>
diff --git a/core/src/main/scala/org/apache/spark/scheduler/Task.scala b/core/src/main/scala/org/apache/spark/scheduler/Task.scala
index 4d9f940813b8e..8b592867ee31d 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/Task.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/Task.scala
@@ -22,7 +22,7 @@ import java.nio.ByteBuffer
 
 import scala.collection.mutable.HashMap
 
-import org.apache.spark.{TaskContextHelper, TaskContextImpl, TaskContext}
+import org.apache.spark.{TaskContextImpl, TaskContext}
 import org.apache.spark.executor.TaskMetrics
 import org.apache.spark.serializer.SerializerInstance
 import org.apache.spark.util.ByteBufferInputStream
@@ -54,7 +54,7 @@ private[spark] abstract class Task[T](val stageId: Int, var partitionId: Int) ex
   final def run(taskAttemptId: Long, attemptNumber: Int): T = {
     context = new TaskContextImpl(stageId = stageId, partitionId = partitionId,
       taskAttemptId = taskAttemptId, attemptNumber = attemptNumber, runningLocally = false)
-    TaskContextHelper.setTaskContext(context)
+    TaskContext.setTaskContext(context)
     context.taskMetrics.setHostname(Utils.localHostName())
     taskThread = Thread.currentThread()
     if (_killed) {
@@ -64,7 +64,7 @@ private[spark] abstract class Task[T](val stageId: Int, var partitionId: Int) ex
       runTask(context)
     } finally {
       context.markTaskCompleted()
-      TaskContextHelper.unset()
+      TaskContext.unset()
     }
   }
 

From 15e0d2bd1304db62fad286c1bb687e87c361e16c Mon Sep 17 00:00:00 2001
From: Reynold Xin <rxin@databricks.com>
Date: Wed, 8 Apr 2015 00:24:59 -0700
Subject: [PATCH 11/95] [SPARK-6765] Fix test code style for streaming.

So we can turn style checker on for test code.

Author: Reynold Xin <rxin@databricks.com>

Closes #5409 from rxin/test-style-streaming and squashes the following commits:

7aea69b [Reynold Xin] [SPARK-6765] Fix test code style for streaming.
---
 .../flume/FlumePollingStreamSuite.scala       | 29 ++++++------
 .../streaming/flume/FlumeStreamSuite.scala    |  4 +-
 .../streaming/mqtt/MQTTStreamSuite.scala      |  3 +-
 .../streaming/BasicOperationsSuite.scala      |  6 ++-
 .../spark/streaming/CheckpointSuite.scala     | 45 ++++++++++++++-----
 .../apache/spark/streaming/FailureSuite.scala |  4 +-
 .../spark/streaming/InputStreamsSuite.scala   | 15 ++++---
 .../streaming/ReceivedBlockHandlerSuite.scala |  4 +-
 .../streaming/ReceivedBlockTrackerSuite.scala |  6 ++-
 .../spark/streaming/ReceiverSuite.scala       | 11 ++---
 .../streaming/StreamingContextSuite.scala     |  5 ++-
 .../streaming/StreamingListenerSuite.scala    |  4 +-
 .../spark/streaming/TestSuiteBase.scala       | 28 +++++++-----
 .../spark/streaming/UISeleniumSuite.scala     |  3 +-
 .../streaming/WindowOperationsSuite.scala     |  4 +-
 .../WriteAheadLogBackedBlockRDDSuite.scala    | 12 +++--
 .../scheduler/JobGeneratorSuite.scala         |  2 +-
 .../streaming/util/WriteAheadLogSuite.scala   |  2 +-
 .../spark/streamingtest/ImplicitSuite.scala   |  3 +-
 19 files changed, 115 insertions(+), 75 deletions(-)

diff --git a/external/flume/src/test/scala/org/apache/spark/streaming/flume/FlumePollingStreamSuite.scala b/external/flume/src/test/scala/org/apache/spark/streaming/flume/FlumePollingStreamSuite.scala
index e04d4088df7dc..2edea9b5b69ba 100644
--- a/external/flume/src/test/scala/org/apache/spark/streaming/flume/FlumePollingStreamSuite.scala
+++ b/external/flume/src/test/scala/org/apache/spark/streaming/flume/FlumePollingStreamSuite.scala
@@ -1,21 +1,20 @@
 /*
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements.  See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership.  The ASF licenses this file
- * to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance
- * with the License.  You may obtain a copy of the License at
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
  *
- * http://www.apache.org/licenses/LICENSE-2.0
+ *    http://www.apache.org/licenses/LICENSE-2.0
  *
- * Unless required by applicable law or agreed to in writing,
- * software distributed under the License is distributed on an
- * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
- * KIND, either express or implied.  See the License for the
- * specific language governing permissions and limitations
- * under the License.
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
  */
+
 package org.apache.spark.streaming.flume
 
 import java.net.InetSocketAddress
@@ -213,7 +212,7 @@ class FlumePollingStreamSuite extends FunSuite with BeforeAndAfter with Logging
     assert(counter === totalEventsPerChannel * channels.size)
   }
 
-  def assertChannelIsEmpty(channel: MemoryChannel) = {
+  def assertChannelIsEmpty(channel: MemoryChannel): Unit = {
     val queueRemaining = channel.getClass.getDeclaredField("queueRemaining")
     queueRemaining.setAccessible(true)
     val m = queueRemaining.get(channel).getClass.getDeclaredMethod("availablePermits")
diff --git a/external/flume/src/test/scala/org/apache/spark/streaming/flume/FlumeStreamSuite.scala b/external/flume/src/test/scala/org/apache/spark/streaming/flume/FlumeStreamSuite.scala
index 51d273af8da84..39e6754c81dbf 100644
--- a/external/flume/src/test/scala/org/apache/spark/streaming/flume/FlumeStreamSuite.scala
+++ b/external/flume/src/test/scala/org/apache/spark/streaming/flume/FlumeStreamSuite.scala
@@ -151,7 +151,9 @@ class FlumeStreamSuite extends FunSuite with BeforeAndAfter with Matchers with L
   }
 
   /** Class to create socket channel with compression */
-  private class CompressionChannelFactory(compressionLevel: Int) extends NioClientSocketChannelFactory {
+  private class CompressionChannelFactory(compressionLevel: Int)
+    extends NioClientSocketChannelFactory {
+
     override def newChannel(pipeline: ChannelPipeline): SocketChannel = {
       val encoder = new ZlibEncoder(compressionLevel)
       pipeline.addFirst("deflater", encoder)
diff --git a/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala b/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala
index 24d78ecb3a97d..a19a72c58a705 100644
--- a/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala
+++ b/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala
@@ -139,7 +139,8 @@ class MQTTStreamSuite extends FunSuite with Eventually with BeforeAndAfter {
             msgTopic.publish(message)
           } catch {
             case e: MqttException if e.getReasonCode == MqttException.REASON_CODE_MAX_INFLIGHT =>
-              Thread.sleep(50) // wait for Spark streaming to consume something from the message queue
+              // wait for Spark streaming to consume something from the message queue
+              Thread.sleep(50)
           }
         }
       }
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala
index cf191715d29d6..87bc20f79c3cd 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala
@@ -171,7 +171,9 @@ class BasicOperationsSuite extends TestSuiteBase {
   test("flatMapValues") {
     testOperation(
       Seq( Seq("a", "a", "b"), Seq("", ""), Seq() ),
-      (s: DStream[String]) => s.map(x => (x, 1)).reduceByKey(_ + _).flatMapValues(x => Seq(x, x + 10)),
+      (s: DStream[String]) => {
+        s.map(x => (x, 1)).reduceByKey(_ + _).flatMapValues(x => Seq(x, x + 10))
+      },
       Seq( Seq(("a", 2), ("a", 12), ("b", 1), ("b", 11)), Seq(("", 2), ("", 12)), Seq() ),
       true
     )
@@ -474,7 +476,7 @@ class BasicOperationsSuite extends TestSuiteBase {
       stream.foreachRDD(_ => {})  // Dummy output stream
       ssc.start()
       Thread.sleep(2000)
-      def getInputFromSlice(fromMillis: Long, toMillis: Long) = {
+      def getInputFromSlice(fromMillis: Long, toMillis: Long): Set[Int] = {
         stream.slice(new Time(fromMillis), new Time(toMillis)).flatMap(_.collect()).toSet
       }
 
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala
index 91a2b2bba461d..54c30440a6e8d 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala
@@ -43,7 +43,7 @@ class CheckpointSuite extends TestSuiteBase {
 
   var ssc: StreamingContext = null
 
-  override def batchDuration = Milliseconds(500)
+  override def batchDuration: Duration = Milliseconds(500)
 
   override def beforeFunction() {
     super.beforeFunction()
@@ -72,7 +72,7 @@ class CheckpointSuite extends TestSuiteBase {
     val input = (1 to 10).map(_ => Seq("a")).toSeq
     val operation = (st: DStream[String]) => {
       val updateFunc = (values: Seq[Int], state: Option[Int]) => {
-        Some((values.sum + state.getOrElse(0)))
+        Some(values.sum + state.getOrElse(0))
       }
       st.map(x => (x, 1))
       .updateStateByKey(updateFunc)
@@ -199,7 +199,12 @@ class CheckpointSuite extends TestSuiteBase {
     testCheckpointedOperation(
       Seq( Seq("a", "a", "b"), Seq("", ""), Seq(), Seq("a", "a", "b"), Seq("", ""), Seq() ),
       (s: DStream[String]) => s.map(x => (x, 1)).reduceByKey(_ + _),
-      Seq( Seq(("a", 2), ("b", 1)), Seq(("", 2)), Seq(), Seq(("a", 2), ("b", 1)), Seq(("", 2)), Seq() ),
+      Seq(
+        Seq(("a", 2), ("b", 1)),
+        Seq(("", 2)),
+        Seq(),
+        Seq(("a", 2), ("b", 1)),
+        Seq(("", 2)), Seq() ),
       3
     )
   }
@@ -212,7 +217,8 @@ class CheckpointSuite extends TestSuiteBase {
     val n = 10
     val w = 4
     val input = (1 to n).map(_ => Seq("a")).toSeq
-    val output = Seq(Seq(("a", 1)), Seq(("a", 2)), Seq(("a", 3))) ++ (1 to (n - w + 1)).map(x => Seq(("a", 4)))
+    val output = Seq(
+      Seq(("a", 1)), Seq(("a", 2)), Seq(("a", 3))) ++ (1 to (n - w + 1)).map(x => Seq(("a", 4)))
     val operation = (st: DStream[String]) => {
       st.map(x => (x, 1))
         .reduceByKeyAndWindow(_ + _, _ - _, batchDuration * w, batchDuration)
@@ -236,7 +242,13 @@ class CheckpointSuite extends TestSuiteBase {
             classOf[TextOutputFormat[Text, IntWritable]])
           output
         },
-        Seq(Seq(("a", 2), ("b", 1)), Seq(("", 2)), Seq(), Seq(("a", 2), ("b", 1)), Seq(("", 2)), Seq()),
+        Seq(
+          Seq(("a", 2), ("b", 1)),
+          Seq(("", 2)),
+          Seq(),
+          Seq(("a", 2), ("b", 1)),
+          Seq(("", 2)),
+          Seq()),
         3
       )
     } finally {
@@ -259,7 +271,13 @@ class CheckpointSuite extends TestSuiteBase {
             classOf[NewTextOutputFormat[Text, IntWritable]])
           output
         },
-        Seq(Seq(("a", 2), ("b", 1)), Seq(("", 2)), Seq(), Seq(("a", 2), ("b", 1)), Seq(("", 2)), Seq()),
+        Seq(
+          Seq(("a", 2), ("b", 1)),
+          Seq(("", 2)),
+          Seq(),
+          Seq(("a", 2), ("b", 1)),
+          Seq(("", 2)),
+          Seq()),
         3
       )
     } finally {
@@ -298,7 +316,13 @@ class CheckpointSuite extends TestSuiteBase {
             output
           }
         },
-        Seq(Seq(("a", 2), ("b", 1)), Seq(("", 2)), Seq(), Seq(("a", 2), ("b", 1)), Seq(("", 2)), Seq()),
+        Seq(
+          Seq(("a", 2), ("b", 1)),
+          Seq(("", 2)),
+          Seq(),
+          Seq(("a", 2), ("b", 1)),
+          Seq(("", 2)),
+          Seq()),
         3
       )
     } finally {
@@ -533,7 +557,8 @@ class CheckpointSuite extends TestSuiteBase {
    * Advances the manual clock on the streaming scheduler by given number of batches.
    * It also waits for the expected amount of time for each batch.
    */
-  def advanceTimeWithRealDelay[V: ClassTag](ssc: StreamingContext, numBatches: Long): Seq[Seq[V]] = {
+  def advanceTimeWithRealDelay[V: ClassTag](ssc: StreamingContext, numBatches: Long): Seq[Seq[V]] =
+  {
     val clock = ssc.scheduler.clock.asInstanceOf[ManualClock]
     logInfo("Manual clock before advancing = " + clock.getTimeMillis())
     for (i <- 1 to numBatches.toInt) {
@@ -543,7 +568,7 @@ class CheckpointSuite extends TestSuiteBase {
     logInfo("Manual clock after advancing = " + clock.getTimeMillis())
     Thread.sleep(batchDuration.milliseconds)
 
-    val outputStream = ssc.graph.getOutputStreams.filter { dstream =>
+    val outputStream = ssc.graph.getOutputStreams().filter { dstream =>
       dstream.isInstanceOf[TestOutputStreamWithPartitions[V]]
     }.head.asInstanceOf[TestOutputStreamWithPartitions[V]]
     outputStream.output.map(_.flatten)
@@ -552,4 +577,4 @@ class CheckpointSuite extends TestSuiteBase {
 
 private object CheckpointSuite extends Serializable {
   var batchThreeShouldBlockIndefinitely: Boolean = true
-}
\ No newline at end of file
+}
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/FailureSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/FailureSuite.scala
index 26435d8515815..0c4c06534a693 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/FailureSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/FailureSuite.scala
@@ -29,9 +29,9 @@ class FailureSuite extends TestSuiteBase with Logging {
   val directory = Utils.createTempDir()
   val numBatches = 30
 
-  override def batchDuration = Milliseconds(1000)
+  override def batchDuration: Duration = Milliseconds(1000)
 
-  override def useManualClock = false
+  override def useManualClock: Boolean = false
 
   override def afterFunction() {
     Utils.deleteRecursively(directory)
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala
index 7ed6320a3d0bc..e6ac4975c5e68 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala
@@ -52,7 +52,7 @@ class InputStreamsSuite extends TestSuiteBase with BeforeAndAfter {
       "localhost", testServer.port, StorageLevel.MEMORY_AND_DISK)
     val outputBuffer = new ArrayBuffer[Seq[String]] with SynchronizedBuffer[Seq[String]]
     val outputStream = new TestOutputStream(networkStream, outputBuffer)
-    def output = outputBuffer.flatMap(x => x)
+    def output: ArrayBuffer[String] = outputBuffer.flatMap(x => x)
     outputStream.register()
     ssc.start()
 
@@ -164,7 +164,7 @@ class InputStreamsSuite extends TestSuiteBase with BeforeAndAfter {
     val countStream = networkStream.count
     val outputBuffer = new ArrayBuffer[Seq[Long]] with SynchronizedBuffer[Seq[Long]]
     val outputStream = new TestOutputStream(countStream, outputBuffer)
-    def output = outputBuffer.flatMap(x => x)
+    def output: ArrayBuffer[Long] = outputBuffer.flatMap(x => x)
     outputStream.register()
     ssc.start()
 
@@ -196,7 +196,7 @@ class InputStreamsSuite extends TestSuiteBase with BeforeAndAfter {
     val queueStream = ssc.queueStream(queue, oneAtATime = true)
     val outputBuffer = new ArrayBuffer[Seq[String]] with SynchronizedBuffer[Seq[String]]
     val outputStream = new TestOutputStream(queueStream, outputBuffer)
-    def output = outputBuffer.filter(_.size > 0)
+    def output: ArrayBuffer[Seq[String]] = outputBuffer.filter(_.size > 0)
     outputStream.register()
     ssc.start()
 
@@ -204,7 +204,7 @@ class InputStreamsSuite extends TestSuiteBase with BeforeAndAfter {
     val clock = ssc.scheduler.clock.asInstanceOf[ManualClock]
     val input = Seq("1", "2", "3", "4", "5")
     val expectedOutput = input.map(Seq(_))
-    //Thread.sleep(1000)
+
     val inputIterator = input.toIterator
     for (i <- 0 until input.size) {
       // Enqueue more than 1 item per tick but they should dequeue one at a time
@@ -239,7 +239,7 @@ class InputStreamsSuite extends TestSuiteBase with BeforeAndAfter {
     val queueStream = ssc.queueStream(queue, oneAtATime = false)
     val outputBuffer = new ArrayBuffer[Seq[String]] with SynchronizedBuffer[Seq[String]]
     val outputStream = new TestOutputStream(queueStream, outputBuffer)
-    def output = outputBuffer.filter(_.size > 0)
+    def output: ArrayBuffer[Seq[String]] = outputBuffer.filter(_.size > 0)
     outputStream.register()
     ssc.start()
 
@@ -352,7 +352,8 @@ class TestServer(portToBind: Int = 0) extends Logging {
           logInfo("New connection")
           try {
             clientSocket.setTcpNoDelay(true)
-            val outputStream = new BufferedWriter(new OutputStreamWriter(clientSocket.getOutputStream))
+            val outputStream = new BufferedWriter(
+              new OutputStreamWriter(clientSocket.getOutputStream))
 
             while(clientSocket.isConnected) {
               val msg = queue.poll(100, TimeUnit.MILLISECONDS)
@@ -384,7 +385,7 @@ class TestServer(portToBind: Int = 0) extends Logging {
 
   def stop() { servingThread.interrupt() }
 
-  def port = serverSocket.getLocalPort
+  def port: Int = serverSocket.getLocalPort
 }
 
 /** This is a receiver to test multiple threads inserting data using block generator */
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala
index ef4873de2f5a9..c090eaec2928d 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala
@@ -96,7 +96,7 @@ class ReceivedBlockHandlerSuite extends FunSuite with BeforeAndAfter with Matche
       testBlockStoring(handler) { case (data, blockIds, storeResults) =>
         // Verify the data in block manager is correct
         val storedData = blockIds.flatMap { blockId =>
-          blockManager.getLocal(blockId).map { _.data.map {_.toString}.toList }.getOrElse(List.empty)
+          blockManager.getLocal(blockId).map(_.data.map(_.toString).toList).getOrElse(List.empty)
         }.toList
         storedData shouldEqual data
 
@@ -120,7 +120,7 @@ class ReceivedBlockHandlerSuite extends FunSuite with BeforeAndAfter with Matche
       testBlockStoring(handler) { case (data, blockIds, storeResults) =>
         // Verify the data in block manager is correct
         val storedData = blockIds.flatMap { blockId =>
-          blockManager.getLocal(blockId).map { _.data.map {_.toString}.toList }.getOrElse(List.empty)
+          blockManager.getLocal(blockId).map(_.data.map(_.toString).toList).getOrElse(List.empty)
         }.toList
         storedData shouldEqual data
 
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala
index 42fad769f0c1a..b63b37d9f9cef 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala
@@ -228,7 +228,8 @@ class ReceivedBlockTrackerSuite
    * Get all the data written in the given write ahead log files. By default, it will read all
    * files in the test log directory.
    */
-  def getWrittenLogData(logFiles: Seq[String] = getWriteAheadLogFiles): Seq[ReceivedBlockTrackerLogEvent] = {
+  def getWrittenLogData(logFiles: Seq[String] = getWriteAheadLogFiles)
+    : Seq[ReceivedBlockTrackerLogEvent] = {
     logFiles.flatMap {
       file => new WriteAheadLogReader(file, hadoopConf).toSeq
     }.map { byteBuffer =>
@@ -244,7 +245,8 @@ class ReceivedBlockTrackerSuite
   }
 
   /** Create batch allocation object from the given info */
-  def createBatchAllocation(time: Long, blockInfos: Seq[ReceivedBlockInfo]): BatchAllocationEvent = {
+  def createBatchAllocation(time: Long, blockInfos: Seq[ReceivedBlockInfo])
+    : BatchAllocationEvent = {
     BatchAllocationEvent(time, AllocatedBlocks(Map((streamId -> blockInfos))))
   }
 
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala
index aa20ad0b5374e..10c35cba8dc53 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala
@@ -308,7 +308,7 @@ class ReceiverSuite extends TestSuiteBase with Timeouts with Serializable {
     val errors = new ArrayBuffer[Throwable]
 
     /** Check if all data structures are clean */
-    def isAllEmpty = {
+    def isAllEmpty: Boolean = {
       singles.isEmpty && byteBuffers.isEmpty && iterators.isEmpty &&
         arrayBuffers.isEmpty && errors.isEmpty
     }
@@ -320,24 +320,21 @@ class ReceiverSuite extends TestSuiteBase with Timeouts with Serializable {
     def pushBytes(
         bytes: ByteBuffer,
         optionalMetadata: Option[Any],
-        optionalBlockId: Option[StreamBlockId]
-      ) {
+        optionalBlockId: Option[StreamBlockId]) {
       byteBuffers += bytes
     }
 
     def pushIterator(
         iterator: Iterator[_],
         optionalMetadata: Option[Any],
-        optionalBlockId: Option[StreamBlockId]
-      ) {
+        optionalBlockId: Option[StreamBlockId]) {
       iterators += iterator
     }
 
     def pushArrayBuffer(
         arrayBuffer: ArrayBuffer[_],
         optionalMetadata: Option[Any],
-        optionalBlockId: Option[StreamBlockId]
-      ) {
+        optionalBlockId: Option[StreamBlockId]) {
       arrayBuffers +=  arrayBuffer
     }
 
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala
index 2e5005ef6ff14..d1bbf39dc7897 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala
@@ -213,7 +213,7 @@ class StreamingContextSuite extends FunSuite with BeforeAndAfter with Timeouts w
     ssc = new StreamingContext(sc, Milliseconds(100))
     var runningCount = 0
     SlowTestReceiver.receivedAllRecords = false
-    //Create test receiver that sleeps in onStop()
+    // Create test receiver that sleeps in onStop()
     val totalNumRecords = 15
     val recordsPerSecond = 1
     val input = ssc.receiverStream(new SlowTestReceiver(totalNumRecords, recordsPerSecond))
@@ -370,7 +370,8 @@ object TestReceiver {
 }
 
 /** Custom receiver for testing whether a slow receiver can be shutdown gracefully or not */
-class SlowTestReceiver(totalRecords: Int, recordsPerSecond: Int) extends Receiver[Int](StorageLevel.MEMORY_ONLY) with Logging {
+class SlowTestReceiver(totalRecords: Int, recordsPerSecond: Int)
+  extends Receiver[Int](StorageLevel.MEMORY_ONLY) with Logging {
 
   var receivingThreadOption: Option[Thread] = None
 
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala
index f52562b0a0f73..852e8bb71d4f6 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala
@@ -38,8 +38,8 @@ class StreamingListenerSuite extends TestSuiteBase with Matchers {
 
   // To make sure that the processing start and end times in collected
   // information are different for successive batches
-  override def batchDuration = Milliseconds(100)
-  override def actuallyWait = true
+  override def batchDuration: Duration = Milliseconds(100)
+  override def actuallyWait: Boolean = true
 
   test("batch info reporting") {
     val ssc = setupStreams(input, operation)
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala b/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala
index 3565d621e8a6c..c3cae8aeb6d15 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala
@@ -53,8 +53,9 @@ class TestInputStream[T: ClassTag](ssc_ : StreamingContext, input: Seq[Seq[T]],
     val selectedInput = if (index < input.size) input(index) else Seq[T]()
 
     // lets us test cases where RDDs are not created
-    if (selectedInput == null)
+    if (selectedInput == null) {
       return None
+    }
 
     val rdd = ssc.sc.makeRDD(selectedInput, numPartitions)
     logInfo("Created RDD " + rdd.id + " with " + selectedInput)
@@ -104,7 +105,9 @@ class TestOutputStreamWithPartitions[T: ClassTag](parent: DStream[T],
     output.clear()
   }
 
-  def toTestOutputStream = new TestOutputStream[T](this.parent, this.output.map(_.flatten))
+  def toTestOutputStream: TestOutputStream[T] = {
+    new TestOutputStream[T](this.parent, this.output.map(_.flatten))
+  }
 }
 
 /**
@@ -148,34 +151,34 @@ class BatchCounter(ssc: StreamingContext) {
 trait TestSuiteBase extends FunSuite with BeforeAndAfter with Logging {
 
   // Name of the framework for Spark context
-  def framework = this.getClass.getSimpleName
+  def framework: String = this.getClass.getSimpleName
 
   // Master for Spark context
-  def master = "local[2]"
+  def master: String = "local[2]"
 
   // Batch duration
-  def batchDuration = Seconds(1)
+  def batchDuration: Duration = Seconds(1)
 
   // Directory where the checkpoint data will be saved
-  lazy val checkpointDir = {
+  lazy val checkpointDir: String = {
     val dir = Utils.createTempDir()
     logDebug(s"checkpointDir: $dir")
     dir.toString
   }
 
   // Number of partitions of the input parallel collections created for testing
-  def numInputPartitions = 2
+  def numInputPartitions: Int = 2
 
   // Maximum time to wait before the test times out
-  def maxWaitTimeMillis = 10000
+  def maxWaitTimeMillis: Int = 10000
 
   // Whether to use manual clock or not
-  def useManualClock = true
+  def useManualClock: Boolean = true
 
   // Whether to actually wait in real time before changing manual clock
-  def actuallyWait = false
+  def actuallyWait: Boolean = false
 
-  //// A SparkConf to use in tests. Can be modified before calling setupStreams to configure things.
+  // A SparkConf to use in tests. Can be modified before calling setupStreams to configure things.
   val conf = new SparkConf()
     .setMaster(master)
     .setAppName(framework)
@@ -346,7 +349,8 @@ trait TestSuiteBase extends FunSuite with BeforeAndAfter with Logging {
 
       // Wait until expected number of output items have been generated
       val startTime = System.currentTimeMillis()
-      while (output.size < numExpectedOutput && System.currentTimeMillis() - startTime < maxWaitTimeMillis) {
+      while (output.size < numExpectedOutput &&
+        System.currentTimeMillis() - startTime < maxWaitTimeMillis) {
         logInfo("output.size = " + output.size + ", numExpectedOutput = " + numExpectedOutput)
         ssc.awaitTerminationOrTimeout(50)
       }
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/UISeleniumSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/UISeleniumSuite.scala
index 87a0395efbf2a..998426ebb82e5 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/UISeleniumSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/UISeleniumSuite.scala
@@ -32,7 +32,8 @@ import org.apache.spark._
 /**
  * Selenium tests for the Spark Web UI.
  */
-class UISeleniumSuite extends FunSuite with WebBrowser with Matchers with BeforeAndAfterAll with TestSuiteBase {
+class UISeleniumSuite
+  extends FunSuite with WebBrowser with Matchers with BeforeAndAfterAll with TestSuiteBase {
 
   implicit var webDriver: WebDriver = _
 
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/WindowOperationsSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/WindowOperationsSuite.scala
index a5d2bb2fde16c..c39ad05f41520 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/WindowOperationsSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/WindowOperationsSuite.scala
@@ -22,9 +22,9 @@ import org.apache.spark.storage.StorageLevel
 
 class WindowOperationsSuite extends TestSuiteBase {
 
-  override def maxWaitTimeMillis = 20000  // large window tests can sometimes take longer
+  override def maxWaitTimeMillis: Int = 20000  // large window tests can sometimes take longer
 
-  override def batchDuration = Seconds(1)  // making sure its visible in this class
+  override def batchDuration: Duration = Seconds(1)  // making sure its visible in this class
 
   val largerSlideInput = Seq(
     Seq(("a", 1)),
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/rdd/WriteAheadLogBackedBlockRDDSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/rdd/WriteAheadLogBackedBlockRDDSuite.scala
index 7a6a2f3e577dd..c3602a5b73732 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/rdd/WriteAheadLogBackedBlockRDDSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/rdd/WriteAheadLogBackedBlockRDDSuite.scala
@@ -28,10 +28,13 @@ import org.apache.spark.storage.{BlockId, BlockManager, StorageLevel, StreamBloc
 import org.apache.spark.streaming.util.{WriteAheadLogFileSegment, WriteAheadLogWriter}
 import org.apache.spark.util.Utils
 
-class WriteAheadLogBackedBlockRDDSuite extends FunSuite with BeforeAndAfterAll with BeforeAndAfterEach {
+class WriteAheadLogBackedBlockRDDSuite
+  extends FunSuite with BeforeAndAfterAll with BeforeAndAfterEach {
+
   val conf = new SparkConf()
     .setMaster("local[2]")
     .setAppName(this.getClass.getSimpleName)
+
   val hadoopConf = new Configuration()
 
   var sparkContext: SparkContext = null
@@ -86,7 +89,8 @@ class WriteAheadLogBackedBlockRDDSuite extends FunSuite with BeforeAndAfterAll w
    * @param numPartitionsInWAL Number of partitions to write to the Write Ahead Log
    * @param testStoreInBM Test whether blocks read from log are stored back into block manager
    */
-  private def testRDD(numPartitionsInBM: Int, numPartitionsInWAL: Int, testStoreInBM: Boolean = false) {
+  private def testRDD(
+      numPartitionsInBM: Int, numPartitionsInWAL: Int, testStoreInBM: Boolean = false) {
     val numBlocks = numPartitionsInBM + numPartitionsInWAL
     val data = Seq.fill(numBlocks, 10)(scala.util.Random.nextString(50))
 
@@ -110,7 +114,7 @@ class WriteAheadLogBackedBlockRDDSuite extends FunSuite with BeforeAndAfterAll w
       "Unexpected blocks in BlockManager"
     )
 
-    // Make sure that the right `numPartitionsInWAL` blocks are in write ahead logs, and other are not
+    // Make sure that the right `numPartitionsInWAL` blocks are in WALs, and other are not
     require(
       segments.takeRight(numPartitionsInWAL).forall(s =>
         new File(s.path.stripPrefix("file://")).exists()),
@@ -152,6 +156,6 @@ class WriteAheadLogBackedBlockRDDSuite extends FunSuite with BeforeAndAfterAll w
   }
 
   private def generateFakeSegments(count: Int): Seq[WriteAheadLogFileSegment] = {
-    Array.fill(count)(new WriteAheadLogFileSegment("random", 0l, 0))
+    Array.fill(count)(new WriteAheadLogFileSegment("random", 0L, 0))
   }
 }
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/scheduler/JobGeneratorSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/scheduler/JobGeneratorSuite.scala
index 4150b60635ed6..7865b06c2e3c2 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/scheduler/JobGeneratorSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/scheduler/JobGeneratorSuite.scala
@@ -90,7 +90,7 @@ class JobGeneratorSuite extends TestSuiteBase {
       val receiverTracker = ssc.scheduler.receiverTracker
 
       // Get the blocks belonging to a batch
-      def getBlocksOfBatch(batchTime: Long) = {
+      def getBlocksOfBatch(batchTime: Long): Seq[ReceivedBlockInfo] = {
         receiverTracker.getBlocksOfBatchAndStream(Time(batchTime), inputStream.id)
       }
 
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/util/WriteAheadLogSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/util/WriteAheadLogSuite.scala
index 8335659667f22..a3919c43b95b4 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/util/WriteAheadLogSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/util/WriteAheadLogSuite.scala
@@ -291,7 +291,7 @@ object WriteAheadLogSuite {
     manager
   }
 
-  /** Read data from a segments of a log file directly and return the list of byte buffers.*/
+  /** Read data from a segments of a log file directly and return the list of byte buffers. */
   def readDataManually(segments: Seq[WriteAheadLogFileSegment]): Seq[String] = {
     segments.map { segment =>
       val reader = HdfsUtils.getInputStream(segment.path, hadoopConf)
diff --git a/streaming/src/test/scala/org/apache/spark/streamingtest/ImplicitSuite.scala b/streaming/src/test/scala/org/apache/spark/streamingtest/ImplicitSuite.scala
index d0bf328f2b74d..d66750463033a 100644
--- a/streaming/src/test/scala/org/apache/spark/streamingtest/ImplicitSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streamingtest/ImplicitSuite.scala
@@ -25,7 +25,8 @@ package org.apache.spark.streamingtest
  */
 class ImplicitSuite {
 
-  // We only want to test if `implict` works well with the compiler, so we don't need a real DStream.
+  // We only want to test if `implicit` works well with the compiler,
+  // so we don't need a real DStream.
   def mockDStream[T]: org.apache.spark.streaming.dstream.DStream[T] = null
 
   def testToPairDStreamFunctions(): Unit = {

From f7e21dd1ec4541be54eb01d8b15cfcc6714feed0 Mon Sep 17 00:00:00 2001
From: Marcelo Vanzin <vanzin@cloudera.com>
Date: Wed, 8 Apr 2015 10:14:52 -0700
Subject: [PATCH 12/95] [SPARK-6506] [pyspark] Do not try to retrieve
 SPARK_HOME when not needed...

....

In particular, this makes pyspark in yarn-cluster mode fail unless
SPARK_HOME is set, when it's not really needed.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #5405 from vanzin/SPARK-6506 and squashes the following commits:

e184507 [Marcelo Vanzin] [SPARK-6506] [pyspark] Do not try to retrieve SPARK_HOME when not needed.
---
 python/pyspark/java_gateway.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/python/pyspark/java_gateway.py b/python/pyspark/java_gateway.py
index 0a16cbd8bff62..2a5e84a7dfdb4 100644
--- a/python/pyspark/java_gateway.py
+++ b/python/pyspark/java_gateway.py
@@ -29,11 +29,10 @@
 
 
 def launch_gateway():
-    SPARK_HOME = os.environ["SPARK_HOME"]
-
     if "PYSPARK_GATEWAY_PORT" in os.environ:
         gateway_port = int(os.environ["PYSPARK_GATEWAY_PORT"])
     else:
+        SPARK_HOME = os.environ["SPARK_HOME"]
         # Launch the Py4j gateway using Spark's run command so that we pick up the
         # proper classpath and settings from spark-env.sh
         on_windows = platform.system() == "Windows"

From 9d44ddce1d1e19011026605549c37d0db6d6afa1 Mon Sep 17 00:00:00 2001
From: Kay Ousterhout <kayousterhout@gmail.com>
Date: Wed, 8 Apr 2015 10:26:45 -0700
Subject: [PATCH 13/95] [SPARK-6753] Clone SparkConf in ShuffleSuite tests

Prior to this change, the unit test for SPARK-3426 did not clone the
original SparkConf, which meant that that test did not use the options
set by suites that subclass ShuffleSuite.scala. This commit fixes that
problem.

JoshRosen would be great if you could take a look at this, since you wrote this
test originally.

Author: Kay Ousterhout <kayousterhout@gmail.com>

Closes #5401 from kayousterhout/SPARK-6753 and squashes the following commits:

368c540 [Kay Ousterhout] [SPARK-6753] Clone SparkConf in ShuffleSuite tests
---
 core/src/test/scala/org/apache/spark/ShuffleSuite.scala | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/core/src/test/scala/org/apache/spark/ShuffleSuite.scala b/core/src/test/scala/org/apache/spark/ShuffleSuite.scala
index f57921b768310..30b6184c77839 100644
--- a/core/src/test/scala/org/apache/spark/ShuffleSuite.scala
+++ b/core/src/test/scala/org/apache/spark/ShuffleSuite.scala
@@ -242,14 +242,14 @@ abstract class ShuffleSuite extends FunSuite with Matchers with LocalSparkContex
       shuffleSpillCompress <- Set(true, false);
       shuffleCompress <- Set(true, false)
     ) {
-      val conf = new SparkConf()
+      val myConf = conf.clone()
         .setAppName("test")
         .setMaster("local")
         .set("spark.shuffle.spill.compress", shuffleSpillCompress.toString)
         .set("spark.shuffle.compress", shuffleCompress.toString)
         .set("spark.shuffle.memoryFraction", "0.001")
       resetSparkContext()
-      sc = new SparkContext(conf)
+      sc = new SparkContext(myConf)
       try {
         sc.parallelize(0 until 100000).map(i => (i / 4, i)).groupByKey().collect()
       } catch {

From 8d812f9986f2edf420a18ca822711c9765f480e2 Mon Sep 17 00:00:00 2001
From: Reynold Xin <rxin@databricks.com>
Date: Wed, 8 Apr 2015 11:31:48 -0700
Subject: [PATCH 14/95] [SPARK-6765] Fix test code style for graphx.

So we can turn style checker on for test code.

Author: Reynold Xin <rxin@databricks.com>

Closes #5410 from rxin/test-style-graphx and squashes the following commits:

89e253a [Reynold Xin] [SPARK-6765] Fix test code style for graphx.
---
 .../org/apache/spark/graphx/GraphSuite.scala  | 71 ++++++++++---------
 .../spark/graphx/LocalSparkContext.scala      |  2 +-
 .../apache/spark/graphx/VertexRDDSuite.scala  | 26 +++----
 .../graphx/lib/ConnectedComponentsSuite.scala | 18 ++---
 .../spark/graphx/lib/PageRankSuite.scala      | 33 ++++-----
 .../StronglyConnectedComponentsSuite.scala    | 23 +++---
 6 files changed, 88 insertions(+), 85 deletions(-)

diff --git a/graphx/src/test/scala/org/apache/spark/graphx/GraphSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/GraphSuite.scala
index 8d15150458d26..a570e4ed75fc3 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/GraphSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/GraphSuite.scala
@@ -38,12 +38,12 @@ class GraphSuite extends FunSuite with LocalSparkContext {
       val doubleRing = ring ++ ring
       val graph = Graph.fromEdgeTuples(sc.parallelize(doubleRing), 1)
       assert(graph.edges.count() === doubleRing.size)
-      assert(graph.edges.collect.forall(e => e.attr == 1))
+      assert(graph.edges.collect().forall(e => e.attr == 1))
 
       // uniqueEdges option should uniquify edges and store duplicate count in edge attributes
       val uniqueGraph = Graph.fromEdgeTuples(sc.parallelize(doubleRing), 1, Some(RandomVertexCut))
       assert(uniqueGraph.edges.count() === ring.size)
-      assert(uniqueGraph.edges.collect.forall(e => e.attr == 2))
+      assert(uniqueGraph.edges.collect().forall(e => e.attr == 2))
     }
   }
 
@@ -64,7 +64,7 @@ class GraphSuite extends FunSuite with LocalSparkContext {
       assert( graph.edges.count() === rawEdges.size )
       // Vertices not explicitly provided but referenced by edges should be created automatically
       assert( graph.vertices.count() === 100)
-      graph.triplets.collect.map { et =>
+      graph.triplets.collect().map { et =>
         assert((et.srcId < 10 && et.srcAttr) || (et.srcId >= 10 && !et.srcAttr))
         assert((et.dstId < 10 && et.dstAttr) || (et.dstId >= 10 && !et.dstAttr))
       }
@@ -75,15 +75,17 @@ class GraphSuite extends FunSuite with LocalSparkContext {
     withSpark { sc =>
       val n = 5
       val star = starGraph(sc, n)
-      assert(star.triplets.map(et => (et.srcId, et.dstId, et.srcAttr, et.dstAttr)).collect.toSet ===
-        (1 to n).map(x => (0: VertexId, x: VertexId, "v", "v")).toSet)
+      assert(star.triplets.map(et => (et.srcId, et.dstId, et.srcAttr, et.dstAttr)).collect().toSet
+        === (1 to n).map(x => (0: VertexId, x: VertexId, "v", "v")).toSet)
     }
   }
 
   test("partitionBy") {
     withSpark { sc =>
-      def mkGraph(edges: List[(Long, Long)]) = Graph.fromEdgeTuples(sc.parallelize(edges, 2), 0)
-      def nonemptyParts(graph: Graph[Int, Int]) = {
+      def mkGraph(edges: List[(Long, Long)]): Graph[Int, Int] = {
+        Graph.fromEdgeTuples(sc.parallelize(edges, 2), 0)
+      }
+      def nonemptyParts(graph: Graph[Int, Int]): RDD[List[Edge[Int]]] = {
         graph.edges.partitionsRDD.mapPartitions { iter =>
           Iterator(iter.next()._2.iterator.toList)
         }.filter(_.nonEmpty)
@@ -102,7 +104,8 @@ class GraphSuite extends FunSuite with LocalSparkContext {
       assert(nonemptyParts(mkGraph(sameSrcEdges).partitionBy(EdgePartition1D)).count === 1)
       // partitionBy(CanonicalRandomVertexCut) puts edges that are identical modulo direction into
       // the same partition
-      assert(nonemptyParts(mkGraph(canonicalEdges).partitionBy(CanonicalRandomVertexCut)).count === 1)
+      assert(
+        nonemptyParts(mkGraph(canonicalEdges).partitionBy(CanonicalRandomVertexCut)).count === 1)
       // partitionBy(EdgePartition2D) puts identical edges in the same partition
       assert(nonemptyParts(mkGraph(identicalEdges).partitionBy(EdgePartition2D)).count === 1)
 
@@ -140,10 +143,10 @@ class GraphSuite extends FunSuite with LocalSparkContext {
       val g = Graph(
         sc.parallelize(List((0L, "a"), (1L, "b"), (2L, "c"))),
         sc.parallelize(List(Edge(0L, 1L, 1), Edge(0L, 2L, 1)), 2))
-      assert(g.triplets.collect.map(_.toTuple).toSet ===
+      assert(g.triplets.collect().map(_.toTuple).toSet ===
         Set(((0L, "a"), (1L, "b"), 1), ((0L, "a"), (2L, "c"), 1)))
       val gPart = g.partitionBy(EdgePartition2D)
-      assert(gPart.triplets.collect.map(_.toTuple).toSet ===
+      assert(gPart.triplets.collect().map(_.toTuple).toSet ===
         Set(((0L, "a"), (1L, "b"), 1), ((0L, "a"), (2L, "c"), 1)))
     }
   }
@@ -154,10 +157,10 @@ class GraphSuite extends FunSuite with LocalSparkContext {
       val star = starGraph(sc, n)
       // mapVertices preserving type
       val mappedVAttrs = star.mapVertices((vid, attr) => attr + "2")
-      assert(mappedVAttrs.vertices.collect.toSet === (0 to n).map(x => (x: VertexId, "v2")).toSet)
+      assert(mappedVAttrs.vertices.collect().toSet === (0 to n).map(x => (x: VertexId, "v2")).toSet)
       // mapVertices changing type
       val mappedVAttrs2 = star.mapVertices((vid, attr) => attr.length)
-      assert(mappedVAttrs2.vertices.collect.toSet === (0 to n).map(x => (x: VertexId, 1)).toSet)
+      assert(mappedVAttrs2.vertices.collect().toSet === (0 to n).map(x => (x: VertexId, 1)).toSet)
     }
   }
 
@@ -177,12 +180,12 @@ class GraphSuite extends FunSuite with LocalSparkContext {
       // Trigger initial vertex replication
       graph0.triplets.foreach(x => {})
       // Change type of replicated vertices, but preserve erased type
-      val graph1 = graph0.mapVertices {
-        case (vid, integerOpt) => integerOpt.map((x: java.lang.Integer) => (x.toDouble): java.lang.Double)
+      val graph1 = graph0.mapVertices { case (vid, integerOpt) =>
+        integerOpt.map((x: java.lang.Integer) => x.toDouble: java.lang.Double)
       }
       // Access replicated vertices, exposing the erased type
       val graph2 = graph1.mapTriplets(t => t.srcAttr.get)
-      assert(graph2.edges.map(_.attr).collect.toSet === Set[java.lang.Double](1.0, 2.0, 3.0))
+      assert(graph2.edges.map(_.attr).collect().toSet === Set[java.lang.Double](1.0, 2.0, 3.0))
     }
   }
 
@@ -202,7 +205,7 @@ class GraphSuite extends FunSuite with LocalSparkContext {
     withSpark { sc =>
       val n = 5
       val star = starGraph(sc, n)
-      assert(star.mapTriplets(et => et.srcAttr + et.dstAttr).edges.collect.toSet ===
+      assert(star.mapTriplets(et => et.srcAttr + et.dstAttr).edges.collect().toSet ===
         (1L to n).map(x => Edge(0, x, "vv")).toSet)
     }
   }
@@ -211,7 +214,7 @@ class GraphSuite extends FunSuite with LocalSparkContext {
     withSpark { sc =>
       val n = 5
       val star = starGraph(sc, n)
-      assert(star.reverse.outDegrees.collect.toSet === (1 to n).map(x => (x: VertexId, 1)).toSet)
+      assert(star.reverse.outDegrees.collect().toSet === (1 to n).map(x => (x: VertexId, 1)).toSet)
     }
   }
 
@@ -221,7 +224,7 @@ class GraphSuite extends FunSuite with LocalSparkContext {
       val edges: RDD[Edge[Int]] = sc.parallelize(Array(Edge(1L, 2L, 0)))
       val graph = Graph(vertices, edges).reverse
       val result = graph.mapReduceTriplets[Int](et => Iterator((et.dstId, et.srcAttr)), _ + _)
-      assert(result.collect.toSet === Set((1L, 2)))
+      assert(result.collect().toSet === Set((1L, 2)))
     }
   }
 
@@ -237,7 +240,8 @@ class GraphSuite extends FunSuite with LocalSparkContext {
       assert(subgraph.vertices.collect().toSet === (0 to n by 2).map(x => (x, "v")).toSet)
 
       // And 4 edges.
-      assert(subgraph.edges.map(_.copy()).collect().toSet === (2 to n by 2).map(x => Edge(0, x, 1)).toSet)
+      assert(subgraph.edges.map(_.copy()).collect().toSet ===
+        (2 to n by 2).map(x => Edge(0, x, 1)).toSet)
     }
   }
 
@@ -273,9 +277,9 @@ class GraphSuite extends FunSuite with LocalSparkContext {
         sc.parallelize((1 to n).flatMap(x =>
           List((0: VertexId, x: VertexId), (0: VertexId, x: VertexId))), 1), "v")
       val star2 = doubleStar.groupEdges { (a, b) => a}
-      assert(star2.edges.collect.toArray.sorted(Edge.lexicographicOrdering[Int]) ===
-        star.edges.collect.toArray.sorted(Edge.lexicographicOrdering[Int]))
-      assert(star2.vertices.collect.toSet === star.vertices.collect.toSet)
+      assert(star2.edges.collect().toArray.sorted(Edge.lexicographicOrdering[Int]) ===
+        star.edges.collect().toArray.sorted(Edge.lexicographicOrdering[Int]))
+      assert(star2.vertices.collect().toSet === star.vertices.collect().toSet)
     }
   }
 
@@ -300,21 +304,23 @@ class GraphSuite extends FunSuite with LocalSparkContext {
           throw new Exception("map ran on edge with dst vid %d, which is odd".format(et.dstId))
         }
         Iterator((et.srcId, 1))
-      }, (a: Int, b: Int) => a + b, Some((active, EdgeDirection.In))).collect.toSet
+      }, (a: Int, b: Int) => a + b, Some((active, EdgeDirection.In))).collect().toSet
       assert(numEvenNeighbors === (1 to n).map(x => (x: VertexId, n / 2)).toSet)
 
       // outerJoinVertices followed by mapReduceTriplets(activeSetOpt)
-      val ringEdges = sc.parallelize((0 until n).map(x => (x: VertexId, (x+1) % n: VertexId)), 3)
+      val ringEdges = sc.parallelize((0 until n).map(x => (x: VertexId, (x + 1) % n: VertexId)), 3)
       val ring = Graph.fromEdgeTuples(ringEdges, 0) .mapVertices((vid, attr) => vid).cache()
       val changed = ring.vertices.filter { case (vid, attr) => attr % 2 == 1 }.mapValues(-_).cache()
-      val changedGraph = ring.outerJoinVertices(changed) { (vid, old, newOpt) => newOpt.getOrElse(old) }
+      val changedGraph = ring.outerJoinVertices(changed) { (vid, old, newOpt) =>
+        newOpt.getOrElse(old)
+      }
       val numOddNeighbors = changedGraph.mapReduceTriplets(et => {
         // Map function should only run on edges with source in the active set
         if (et.srcId % 2 != 1) {
           throw new Exception("map ran on edge with src vid %d, which is even".format(et.dstId))
         }
         Iterator((et.dstId, 1))
-      }, (a: Int, b: Int) => a + b, Some(changed, EdgeDirection.Out)).collect.toSet
+      }, (a: Int, b: Int) => a + b, Some(changed, EdgeDirection.Out)).collect().toSet
       assert(numOddNeighbors === (2 to n by 2).map(x => (x: VertexId, 1)).toSet)
 
     }
@@ -340,17 +346,18 @@ class GraphSuite extends FunSuite with LocalSparkContext {
       val n = 5
       val reverseStar = starGraph(sc, n).reverse.cache()
       // outerJoinVertices changing type
-      val reverseStarDegrees =
-        reverseStar.outerJoinVertices(reverseStar.outDegrees) { (vid, a, bOpt) => bOpt.getOrElse(0) }
+      val reverseStarDegrees = reverseStar.outerJoinVertices(reverseStar.outDegrees) {
+        (vid, a, bOpt) => bOpt.getOrElse(0)
+      }
       val neighborDegreeSums = reverseStarDegrees.mapReduceTriplets(
         et => Iterator((et.srcId, et.dstAttr), (et.dstId, et.srcAttr)),
-        (a: Int, b: Int) => a + b).collect.toSet
+        (a: Int, b: Int) => a + b).collect().toSet
       assert(neighborDegreeSums === Set((0: VertexId, n)) ++ (1 to n).map(x => (x: VertexId, 0)))
       // outerJoinVertices preserving type
       val messages = reverseStar.vertices.mapValues { (vid, attr) => vid.toString }
       val newReverseStar =
         reverseStar.outerJoinVertices(messages) { (vid, a, bOpt) => a + bOpt.getOrElse("") }
-      assert(newReverseStar.vertices.map(_._2).collect.toSet ===
+      assert(newReverseStar.vertices.map(_._2).collect().toSet ===
         (0 to n).map(x => "v%d".format(x)).toSet)
     }
   }
@@ -361,7 +368,7 @@ class GraphSuite extends FunSuite with LocalSparkContext {
       val edges = sc.parallelize(List(Edge(1, 2, 0), Edge(2, 1, 0)), 2)
       val graph = Graph(verts, edges)
       val triplets = graph.triplets.map(et => (et.srcId, et.dstId, et.srcAttr, et.dstAttr))
-        .collect.toSet
+        .collect().toSet
       assert(triplets ===
         Set((1: VertexId, 2: VertexId, "a", "b"), (2: VertexId, 1: VertexId, "b", "a")))
     }
@@ -417,7 +424,7 @@ class GraphSuite extends FunSuite with LocalSparkContext {
       val graph = Graph.fromEdgeTuples(edges, 1)
       val neighborAttrSums = graph.mapReduceTriplets[Int](
         et => Iterator((et.dstId, et.srcAttr)), _ + _)
-      assert(neighborAttrSums.collect.toSet === Set((0: VertexId, n)))
+      assert(neighborAttrSums.collect().toSet === Set((0: VertexId, n)))
     } finally {
       sc.stop()
     }
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/LocalSparkContext.scala b/graphx/src/test/scala/org/apache/spark/graphx/LocalSparkContext.scala
index a3e28efc75a98..d2ad9be555770 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/LocalSparkContext.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/LocalSparkContext.scala
@@ -26,7 +26,7 @@ import org.apache.spark.SparkContext
 */
 trait LocalSparkContext {
   /** Runs `f` on a new SparkContext and ensures that it is stopped afterwards. */
-  def withSpark[T](f: SparkContext => T) = {
+  def withSpark[T](f: SparkContext => T): T = {
     val conf = new SparkConf()
     GraphXUtils.registerKryoClasses(conf)
     val sc = new SparkContext("local", "test", conf)
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/VertexRDDSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/VertexRDDSuite.scala
index c9443d11c76cf..d0a7198d691d7 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/VertexRDDSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/VertexRDDSuite.scala
@@ -25,7 +25,7 @@ import org.apache.spark.storage.StorageLevel
 
 class VertexRDDSuite extends FunSuite with LocalSparkContext {
 
-  def vertices(sc: SparkContext, n: Int) = {
+  private def vertices(sc: SparkContext, n: Int) = {
     VertexRDD(sc.parallelize((0 to n).map(x => (x.toLong, x)), 5))
   }
 
@@ -52,7 +52,7 @@ class VertexRDDSuite extends FunSuite with LocalSparkContext {
       val vertexA = VertexRDD(sc.parallelize(0 until 75, 2).map(i => (i.toLong, 0))).cache()
       val vertexB = VertexRDD(sc.parallelize(25 until 100, 2).map(i => (i.toLong, 1))).cache()
       val vertexC = vertexA.minus(vertexB)
-      assert(vertexC.map(_._1).collect.toSet === (0 until 25).toSet)
+      assert(vertexC.map(_._1).collect().toSet === (0 until 25).toSet)
     }
   }
 
@@ -62,7 +62,7 @@ class VertexRDDSuite extends FunSuite with LocalSparkContext {
       val vertexB: RDD[(VertexId, Int)] =
         sc.parallelize(25 until 100, 2).map(i => (i.toLong, 1)).cache()
       val vertexC = vertexA.minus(vertexB)
-      assert(vertexC.map(_._1).collect.toSet === (0 until 25).toSet)
+      assert(vertexC.map(_._1).collect().toSet === (0 until 25).toSet)
     }
   }
 
@@ -72,7 +72,7 @@ class VertexRDDSuite extends FunSuite with LocalSparkContext {
       val vertexB = VertexRDD(sc.parallelize(50 until 100, 2).map(i => (i.toLong, 1)))
       assert(vertexA.partitions.size != vertexB.partitions.size)
       val vertexC = vertexA.minus(vertexB)
-      assert(vertexC.map(_._1).collect.toSet === (0 until 50).toSet)
+      assert(vertexC.map(_._1).collect().toSet === (0 until 50).toSet)
     }
   }
 
@@ -106,7 +106,7 @@ class VertexRDDSuite extends FunSuite with LocalSparkContext {
       val vertexB = VertexRDD(sc.parallelize(8 until 16, 2).map(i => (i.toLong, 1)))
       assert(vertexA.partitions.size != vertexB.partitions.size)
       val vertexC = vertexA.diff(vertexB)
-      assert(vertexC.map(_._1).collect.toSet === (8 until 16).toSet)
+      assert(vertexC.map(_._1).collect().toSet === (8 until 16).toSet)
     }
   }
 
@@ -116,11 +116,11 @@ class VertexRDDSuite extends FunSuite with LocalSparkContext {
       val verts = vertices(sc, n).cache()
       val evens = verts.filter(q => ((q._2 % 2) == 0)).cache()
       // leftJoin with another VertexRDD
-      assert(verts.leftJoin(evens) { (id, a, bOpt) => a - bOpt.getOrElse(0) }.collect.toSet ===
+      assert(verts.leftJoin(evens) { (id, a, bOpt) => a - bOpt.getOrElse(0) }.collect().toSet ===
         (0 to n by 2).map(x => (x.toLong, 0)).toSet ++ (1 to n by 2).map(x => (x.toLong, x)).toSet)
       // leftJoin with an RDD
       val evensRDD = evens.map(identity)
-      assert(verts.leftJoin(evensRDD) { (id, a, bOpt) => a - bOpt.getOrElse(0) }.collect.toSet ===
+      assert(verts.leftJoin(evensRDD) { (id, a, bOpt) => a - bOpt.getOrElse(0) }.collect().toSet ===
         (0 to n by 2).map(x => (x.toLong, 0)).toSet ++ (1 to n by 2).map(x => (x.toLong, x)).toSet)
     }
   }
@@ -134,7 +134,7 @@ class VertexRDDSuite extends FunSuite with LocalSparkContext {
       val vertexC = vertexA.leftJoin(vertexB) { (vid, old, newOpt) =>
         old - newOpt.getOrElse(0)
       }
-      assert(vertexC.filter(v => v._2 != 0).map(_._1).collect.toSet == (1 to 99 by 2).toSet)
+      assert(vertexC.filter(v => v._2 != 0).map(_._1).collect().toSet == (1 to 99 by 2).toSet)
     }
   }
 
@@ -144,11 +144,11 @@ class VertexRDDSuite extends FunSuite with LocalSparkContext {
       val verts = vertices(sc, n).cache()
       val evens = verts.filter(q => ((q._2 % 2) == 0)).cache()
       // innerJoin with another VertexRDD
-      assert(verts.innerJoin(evens) { (id, a, b) => a - b }.collect.toSet ===
+      assert(verts.innerJoin(evens) { (id, a, b) => a - b }.collect().toSet ===
         (0 to n by 2).map(x => (x.toLong, 0)).toSet)
       // innerJoin with an RDD
       val evensRDD = evens.map(identity)
-      assert(verts.innerJoin(evensRDD) { (id, a, b) => a - b }.collect.toSet ===
+      assert(verts.innerJoin(evensRDD) { (id, a, b) => a - b }.collect().toSet ===
         (0 to n by 2).map(x => (x.toLong, 0)).toSet)    }
   }
 
@@ -161,7 +161,7 @@ class VertexRDDSuite extends FunSuite with LocalSparkContext {
       val vertexC = vertexA.innerJoin(vertexB) { (vid, old, newVal) =>
         old - newVal
       }
-      assert(vertexC.filter(v => v._2 == 0).map(_._1).collect.toSet == (0 to 98 by 2).toSet)
+      assert(vertexC.filter(v => v._2 == 0).map(_._1).collect().toSet == (0 to 98 by 2).toSet)
     }
   }
 
@@ -171,7 +171,7 @@ class VertexRDDSuite extends FunSuite with LocalSparkContext {
       val verts = vertices(sc, n)
       val messageTargets = (0 to n) ++ (0 to n by 2)
       val messages = sc.parallelize(messageTargets.map(x => (x.toLong, 1)))
-      assert(verts.aggregateUsingIndex[Int](messages, _ + _).collect.toSet ===
+      assert(verts.aggregateUsingIndex[Int](messages, _ + _).collect().toSet ===
         (0 to n).map(x => (x.toLong, if (x % 2 == 0) 2 else 1)).toSet)
     }
   }
@@ -183,7 +183,7 @@ class VertexRDDSuite extends FunSuite with LocalSparkContext {
       val edges = EdgeRDD.fromEdges(sc.parallelize(List.empty[Edge[Int]]))
       val rdd = VertexRDD(verts, edges, 0, (a: Int, b: Int) => a + b)
       // test merge function
-      assert(rdd.collect.toSet == Set((0L, 0), (1L, 3), (2L, 9)))
+      assert(rdd.collect().toSet == Set((0L, 0), (1L, 3), (2L, 9)))
     }
   }
 
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/lib/ConnectedComponentsSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/lib/ConnectedComponentsSuite.scala
index 3915be15b3434..4cc30a96408f8 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/lib/ConnectedComponentsSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/lib/ConnectedComponentsSuite.scala
@@ -32,7 +32,7 @@ class ConnectedComponentsSuite extends FunSuite with LocalSparkContext {
     withSpark { sc =>
       val gridGraph = GraphGenerators.gridGraph(sc, 10, 10)
       val ccGraph = gridGraph.connectedComponents()
-      val maxCCid = ccGraph.vertices.map { case (vid, ccId) => ccId }.sum
+      val maxCCid = ccGraph.vertices.map { case (vid, ccId) => ccId }.sum()
       assert(maxCCid === 0)
     }
   } // end of Grid connected components
@@ -42,7 +42,7 @@ class ConnectedComponentsSuite extends FunSuite with LocalSparkContext {
     withSpark { sc =>
       val gridGraph = GraphGenerators.gridGraph(sc, 10, 10).reverse
       val ccGraph = gridGraph.connectedComponents()
-      val maxCCid = ccGraph.vertices.map { case (vid, ccId) => ccId }.sum
+      val maxCCid = ccGraph.vertices.map { case (vid, ccId) => ccId }.sum()
       assert(maxCCid === 0)
     }
   } // end of Grid connected components
@@ -50,8 +50,8 @@ class ConnectedComponentsSuite extends FunSuite with LocalSparkContext {
 
   test("Chain Connected Components") {
     withSpark { sc =>
-      val chain1 = (0 until 9).map(x => (x, x+1) )
-      val chain2 = (10 until 20).map(x => (x, x+1) )
+      val chain1 = (0 until 9).map(x => (x, x + 1))
+      val chain2 = (10 until 20).map(x => (x, x + 1))
       val rawEdges = sc.parallelize(chain1 ++ chain2, 3).map { case (s,d) => (s.toLong, d.toLong) }
       val twoChains = Graph.fromEdgeTuples(rawEdges, 1.0)
       val ccGraph = twoChains.connectedComponents()
@@ -73,12 +73,12 @@ class ConnectedComponentsSuite extends FunSuite with LocalSparkContext {
 
   test("Reverse Chain Connected Components") {
     withSpark { sc =>
-      val chain1 = (0 until 9).map(x => (x, x+1) )
-      val chain2 = (10 until 20).map(x => (x, x+1) )
+      val chain1 = (0 until 9).map(x => (x, x + 1))
+      val chain2 = (10 until 20).map(x => (x, x + 1))
       val rawEdges = sc.parallelize(chain1 ++ chain2, 3).map { case (s,d) => (s.toLong, d.toLong) }
       val twoChains = Graph.fromEdgeTuples(rawEdges, true).reverse
       val ccGraph = twoChains.connectedComponents()
-      val vertices = ccGraph.vertices.collect
+      val vertices = ccGraph.vertices.collect()
       for ( (id, cc) <- vertices ) {
         if (id < 10) {
           assert(cc === 0)
@@ -120,9 +120,9 @@ class ConnectedComponentsSuite extends FunSuite with LocalSparkContext {
       // Build the initial Graph
       val graph = Graph(users, relationships, defaultUser)
       val ccGraph = graph.connectedComponents()
-      val vertices = ccGraph.vertices.collect
+      val vertices = ccGraph.vertices.collect()
       for ( (id, cc) <- vertices ) {
-        assert(cc == 0)
+        assert(cc === 0)
       }
     }
   } // end of toy connected components
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/lib/PageRankSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/lib/PageRankSuite.scala
index fc491ae327c2a..95804b07b1db0 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/lib/PageRankSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/lib/PageRankSuite.scala
@@ -19,15 +19,12 @@ package org.apache.spark.graphx.lib
 
 import org.scalatest.FunSuite
 
-import org.apache.spark.SparkContext
-import org.apache.spark.SparkContext._
 import org.apache.spark.graphx._
-import org.apache.spark.graphx.lib._
 import org.apache.spark.graphx.util.GraphGenerators
-import org.apache.spark.rdd._
+
 
 object GridPageRank {
-  def apply(nRows: Int, nCols: Int, nIter: Int, resetProb: Double) = {
+  def apply(nRows: Int, nCols: Int, nIter: Int, resetProb: Double): Seq[(VertexId, Double)] = {
     val inNbrs = Array.fill(nRows * nCols)(collection.mutable.MutableList.empty[Int])
     val outDegree = Array.fill(nRows * nCols)(0)
     // Convert row column address into vertex ids (row major order)
@@ -35,13 +32,13 @@ object GridPageRank {
     // Make the grid graph
     for (r <- 0 until nRows; c <- 0 until nCols) {
       val ind = sub2ind(r,c)
-      if (r+1 < nRows) {
+      if (r + 1 < nRows) {
         outDegree(ind) += 1
-        inNbrs(sub2ind(r+1,c)) += ind
+        inNbrs(sub2ind(r + 1,c)) += ind
       }
-      if (c+1 < nCols) {
+      if (c + 1 < nCols) {
         outDegree(ind) += 1
-        inNbrs(sub2ind(r,c+1)) += ind
+        inNbrs(sub2ind(r,c + 1)) += ind
       }
     }
     // compute the pagerank
@@ -64,7 +61,7 @@ class PageRankSuite extends FunSuite with LocalSparkContext {
 
   def compareRanks(a: VertexRDD[Double], b: VertexRDD[Double]): Double = {
     a.leftJoin(b) { case (id, a, bOpt) => (a - bOpt.getOrElse(0.0)) * (a - bOpt.getOrElse(0.0)) }
-      .map { case (id, error) => error }.sum
+      .map { case (id, error) => error }.sum()
   }
 
   test("Star PageRank") {
@@ -80,12 +77,12 @@ class PageRankSuite extends FunSuite with LocalSparkContext {
       // Static PageRank should only take 2 iterations to converge
       val notMatching = staticRanks1.innerZipJoin(staticRanks2) { (vid, pr1, pr2) =>
         if (pr1 != pr2) 1 else 0
-      }.map { case (vid, test) => test }.sum
+      }.map { case (vid, test) => test }.sum()
       assert(notMatching === 0)
 
       val staticErrors = staticRanks2.map { case (vid, pr) =>
-        val correct = (vid > 0 && pr == resetProb) ||
-          (vid == 0 && math.abs(pr - (resetProb + (1.0 - resetProb) * (resetProb * (nVertices - 1)) )) < 1.0E-5)
+        val p = math.abs(pr - (resetProb + (1.0 - resetProb) * (resetProb * (nVertices - 1)) ))
+        val correct = (vid > 0 && pr == resetProb) || (vid == 0L && p < 1.0E-5)
         if (!correct) 1 else 0
       }
       assert(staticErrors.sum === 0)
@@ -95,8 +92,6 @@ class PageRankSuite extends FunSuite with LocalSparkContext {
     }
   } // end of test Star PageRank
 
-
-
   test("Grid PageRank") {
     withSpark { sc =>
       val rows = 10
@@ -109,18 +104,18 @@ class PageRankSuite extends FunSuite with LocalSparkContext {
 
       val staticRanks = gridGraph.staticPageRank(numIter, resetProb).vertices.cache()
       val dynamicRanks = gridGraph.pageRank(tol, resetProb).vertices.cache()
-      val referenceRanks = VertexRDD(sc.parallelize(GridPageRank(rows, cols, numIter, resetProb))).cache()
+      val referenceRanks = VertexRDD(
+        sc.parallelize(GridPageRank(rows, cols, numIter, resetProb))).cache()
 
       assert(compareRanks(staticRanks, referenceRanks) < errorTol)
       assert(compareRanks(dynamicRanks, referenceRanks) < errorTol)
     }
   } // end of Grid PageRank
 
-
   test("Chain PageRank") {
     withSpark { sc =>
-      val chain1 = (0 until 9).map(x => (x, x+1) )
-      val rawEdges = sc.parallelize(chain1, 1).map { case (s,d) => (s.toLong, d.toLong) }
+      val chain1 = (0 until 9).map(x => (x, x + 1))
+      val rawEdges = sc.parallelize(chain1, 1).map { case (s, d) => (s.toLong, d.toLong) }
       val chain = Graph.fromEdgeTuples(rawEdges, 1.0).cache()
       val resetProb = 0.15
       val tol = 0.0001
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/lib/StronglyConnectedComponentsSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/lib/StronglyConnectedComponentsSuite.scala
index df54aa37cad68..1f658c371ffcf 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/lib/StronglyConnectedComponentsSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/lib/StronglyConnectedComponentsSuite.scala
@@ -34,8 +34,8 @@ class StronglyConnectedComponentsSuite extends FunSuite with LocalSparkContext {
       val edges = sc.parallelize(Seq.empty[Edge[Int]])
       val graph = Graph(vertices, edges)
       val sccGraph = graph.stronglyConnectedComponents(5)
-      for ((id, scc) <- sccGraph.vertices.collect) {
-        assert(id == scc)
+      for ((id, scc) <- sccGraph.vertices.collect()) {
+        assert(id === scc)
       }
     }
   }
@@ -45,8 +45,8 @@ class StronglyConnectedComponentsSuite extends FunSuite with LocalSparkContext {
       val rawEdges = sc.parallelize((0L to 6L).map(x => (x, (x + 1) % 7)))
       val graph = Graph.fromEdgeTuples(rawEdges, -1)
       val sccGraph = graph.stronglyConnectedComponents(20)
-      for ((id, scc) <- sccGraph.vertices.collect) {
-        assert(0L == scc)
+      for ((id, scc) <- sccGraph.vertices.collect()) {
+        assert(0L === scc)
       }
     }
   }
@@ -60,13 +60,14 @@ class StronglyConnectedComponentsSuite extends FunSuite with LocalSparkContext {
       val rawEdges = sc.parallelize(edges)
       val graph = Graph.fromEdgeTuples(rawEdges, -1)
       val sccGraph = graph.stronglyConnectedComponents(20)
-      for ((id, scc) <- sccGraph.vertices.collect) {
-        if (id < 3)
-          assert(0L == scc)
-        else if (id < 6)
-          assert(3L == scc)
-        else
-          assert(id == scc)
+      for ((id, scc) <- sccGraph.vertices.collect()) {
+        if (id < 3) {
+          assert(0L === scc)
+        } else if (id < 6) {
+          assert(3L === scc)
+        } else {
+          assert(id === scc)
+        }
       }
     }
   }

From 66159c35010af35098dd1ec75475bb5d4d0fd6ca Mon Sep 17 00:00:00 2001
From: Reynold Xin <rxin@databricks.com>
Date: Wed, 8 Apr 2015 11:32:44 -0700
Subject: [PATCH 15/95] [SPARK-6765] Fix test code style for mllib.

So we can turn style checker on for test code.

Author: Reynold Xin <rxin@databricks.com>

Closes #5411 from rxin/test-style-mllib and squashes the following commits:

d8a2569 [Reynold Xin] [SPARK-6765] Fix test code style for mllib.
---
 .../org/apache/spark/ml/param/TestParams.scala |  2 +-
 .../mllib/classification/NaiveBayesSuite.scala |  2 +-
 .../StreamingLogisticRegressionSuite.scala     |  2 +-
 .../spark/mllib/clustering/KMeansSuite.scala   | 10 +++++++---
 .../spark/mllib/clustering/LDASuite.scala      |  4 ++--
 .../clustering/StreamingKMeansSuite.scala      |  4 ++--
 .../spark/mllib/random/RandomRDDsSuite.scala   |  5 +++--
 .../spark/mllib/recommendation/ALSSuite.scala  |  3 +++
 .../regression/RidgeRegressionSuite.scala      |  2 +-
 .../StreamingLinearRegressionSuite.scala       |  2 +-
 .../apache/spark/mllib/util/TestingUtils.scala | 14 +++++++-------
 .../spark/mllib/util/TestingUtilsSuite.scala   | 18 +++++++++++-------
 12 files changed, 40 insertions(+), 28 deletions(-)

diff --git a/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala b/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala
index 1a65883d78a71..ce52f2f230085 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala
@@ -28,7 +28,7 @@ class TestParams extends Params {
   def setInputCol(value: String): this.type = { set(inputCol, value); this }
   def getInputCol: String = get(inputCol)
 
-  override def validate(paramMap: ParamMap) = {
+  override def validate(paramMap: ParamMap): Unit = {
     val m = this.paramMap ++ paramMap
     require(m(maxIter) >= 0)
     require(m.contains(inputCol))
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/classification/NaiveBayesSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/classification/NaiveBayesSuite.scala
index f9fe3e006ccb8..ea89b17b7c08f 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/classification/NaiveBayesSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/classification/NaiveBayesSuite.scala
@@ -102,7 +102,7 @@ class NaiveBayesSuite extends FunSuite with MLlibTestSparkContext {
   def validateModelFit(
       piData: Array[Double],
       thetaData: Array[Array[Double]],
-      model: NaiveBayesModel) = {
+      model: NaiveBayesModel): Unit = {
     def closeFit(d1: Double, d2: Double, precision: Double): Boolean = {
       (d1 - d2).abs <= precision
     }
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/classification/StreamingLogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/classification/StreamingLogisticRegressionSuite.scala
index d50c43d439187..5683b55e8500a 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/classification/StreamingLogisticRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/classification/StreamingLogisticRegressionSuite.scala
@@ -30,7 +30,7 @@ import org.apache.spark.streaming.TestSuiteBase
 class StreamingLogisticRegressionSuite extends FunSuite with TestSuiteBase {
 
   // use longer wait time to ensure job completion
-  override def maxWaitTimeMillis = 30000
+  override def maxWaitTimeMillis: Int = 30000
 
   // Test if we can accurately learn B for Y = logistic(BX) on streaming data
   test("parameter accuracy") {
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/clustering/KMeansSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/clustering/KMeansSuite.scala
index 7bf250eb5a383..0f2b26d462ad2 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/clustering/KMeansSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/clustering/KMeansSuite.scala
@@ -199,9 +199,13 @@ class KMeansSuite extends FunSuite with MLlibTestSparkContext {
   test("k-means|| initialization") {
 
     case class VectorWithCompare(x: Vector) extends Ordered[VectorWithCompare] {
-      @Override def compare(that: VectorWithCompare): Int = {
-        if(this.x.toArray.foldLeft[Double](0.0)((acc, x) => acc + x * x) >
-          that.x.toArray.foldLeft[Double](0.0)((acc, x) => acc + x * x)) -1 else 1
+      override def compare(that: VectorWithCompare): Int = {
+        if (this.x.toArray.foldLeft[Double](0.0)((acc, x) => acc + x * x) >
+          that.x.toArray.foldLeft[Double](0.0)((acc, x) => acc + x * x)) {
+          -1
+        } else {
+          1
+        }
       }
     }
 
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/clustering/LDASuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/clustering/LDASuite.scala
index 302d751eb8a94..15de10fd13a19 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/clustering/LDASuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/clustering/LDASuite.scala
@@ -19,7 +19,7 @@ package org.apache.spark.mllib.clustering
 
 import org.scalatest.FunSuite
 
-import org.apache.spark.mllib.linalg.{DenseMatrix, Matrix, Vectors}
+import org.apache.spark.mllib.linalg.{Vector, DenseMatrix, Matrix, Vectors}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.mllib.util.TestingUtils._
 
@@ -141,7 +141,7 @@ private[clustering] object LDASuite {
     (terms.toArray, termWeights.toArray)
   }
 
-  def tinyCorpus = Array(
+  def tinyCorpus: Array[(Long, Vector)] = Array(
     Vectors.dense(1, 3, 0, 2, 8),
     Vectors.dense(0, 2, 1, 0, 4),
     Vectors.dense(2, 3, 12, 3, 1),
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/clustering/StreamingKMeansSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/clustering/StreamingKMeansSuite.scala
index 850c9fce507cd..f90025d535e45 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/clustering/StreamingKMeansSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/clustering/StreamingKMeansSuite.scala
@@ -27,7 +27,7 @@ import org.apache.spark.util.random.XORShiftRandom
 
 class StreamingKMeansSuite extends FunSuite with TestSuiteBase {
 
-  override def maxWaitTimeMillis = 30000
+  override def maxWaitTimeMillis: Int = 30000
 
   test("accuracy for single center and equivalence to grand average") {
     // set parameters
@@ -59,7 +59,7 @@ class StreamingKMeansSuite extends FunSuite with TestSuiteBase {
     // estimated center from streaming should exactly match the arithmetic mean of all data points
     // because the decay factor is set to 1.0
     val grandMean =
-      input.flatten.map(x => x.toBreeze).reduce(_+_) / (numBatches * numPoints).toDouble
+      input.flatten.map(x => x.toBreeze).reduce(_ + _) / (numBatches * numPoints).toDouble
     assert(model.latestModel().clusterCenters(0) ~== Vectors.dense(grandMean.toArray) absTol 1E-5)
   }
 
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDsSuite.scala
index 6395188a0842a..63f2ea916d457 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDsSuite.scala
@@ -181,7 +181,8 @@ class RandomRDDsSuite extends FunSuite with MLlibTestSparkContext with Serializa
       val poisson = RandomRDDs.poissonVectorRDD(sc, poissonMean, rows, cols, parts, seed)
       testGeneratedVectorRDD(poisson, rows, cols, parts, poissonMean, math.sqrt(poissonMean), 0.1)
 
-      val exponential = RandomRDDs.exponentialVectorRDD(sc, exponentialMean, rows, cols, parts, seed)
+      val exponential =
+        RandomRDDs.exponentialVectorRDD(sc, exponentialMean, rows, cols, parts, seed)
       testGeneratedVectorRDD(exponential, rows, cols, parts, exponentialMean, exponentialMean, 0.1)
 
       val gamma = RandomRDDs.gammaVectorRDD(sc, gammaShape, gammaScale, rows, cols, parts, seed)
@@ -197,7 +198,7 @@ private[random] class MockDistro extends RandomDataGenerator[Double] {
   // This allows us to check that each partition has a different seed
   override def nextValue(): Double = seed.toDouble
 
-  override def setSeed(seed: Long) = this.seed = seed
+  override def setSeed(seed: Long): Unit = this.seed = seed
 
   override def copy(): MockDistro = new MockDistro
 }
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/recommendation/ALSSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/recommendation/ALSSuite.scala
index 8775c0ca9df84..b3798940ddc38 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/recommendation/ALSSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/recommendation/ALSSuite.scala
@@ -203,6 +203,7 @@ class ALSSuite extends FunSuite with MLlibTestSparkContext {
    * @param numProductBlocks number of product blocks to partition products into
    * @param negativeFactors whether the generated user/product factors can have negative entries
    */
+  // scalastyle:off
   def testALS(
       users: Int,
       products: Int,
@@ -216,6 +217,8 @@ class ALSSuite extends FunSuite with MLlibTestSparkContext {
       numUserBlocks: Int = -1,
       numProductBlocks: Int = -1,
       negativeFactors: Boolean = true) {
+    // scalastyle:on
+
     val (sampledRatings, trueRatings, truePrefs) = ALSSuite.generateRatings(users, products,
       features, samplingRate, implicitPrefs, negativeWeights, negativeFactors)
 
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/regression/RidgeRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/regression/RidgeRegressionSuite.scala
index 43d61151e2471..d6c93cc0e49cd 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/regression/RidgeRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/regression/RidgeRegressionSuite.scala
@@ -35,7 +35,7 @@ private object RidgeRegressionSuite {
 
 class RidgeRegressionSuite extends FunSuite with MLlibTestSparkContext {
 
-  def predictionError(predictions: Seq[Double], input: Seq[LabeledPoint]) = {
+  def predictionError(predictions: Seq[Double], input: Seq[LabeledPoint]): Double = {
     predictions.zip(input).map { case (prediction, expected) =>
       (prediction - expected.label) * (prediction - expected.label)
     }.reduceLeft(_ + _) / predictions.size
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/regression/StreamingLinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/regression/StreamingLinearRegressionSuite.scala
index 24fd8df691817..26604dbe6c1ef 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/regression/StreamingLinearRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/regression/StreamingLinearRegressionSuite.scala
@@ -29,7 +29,7 @@ import org.apache.spark.streaming.TestSuiteBase
 class StreamingLinearRegressionSuite extends FunSuite with TestSuiteBase {
 
   // use longer wait time to ensure job completion
-  override def maxWaitTimeMillis = 20000
+  override def maxWaitTimeMillis: Int = 20000
 
   // Assert that two values are equal within tolerance epsilon
   def assertEqual(v1: Double, v2: Double, epsilon: Double) {
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtils.scala b/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtils.scala
index e957fa5d25f4c..352193a67860c 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtils.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtils.scala
@@ -95,16 +95,16 @@ object TestingUtils {
     /**
      * Comparison using absolute tolerance.
      */
-    def absTol(eps: Double): CompareDoubleRightSide = CompareDoubleRightSide(AbsoluteErrorComparison,
-      x, eps, ABS_TOL_MSG)
+    def absTol(eps: Double): CompareDoubleRightSide =
+      CompareDoubleRightSide(AbsoluteErrorComparison, x, eps, ABS_TOL_MSG)
 
     /**
      * Comparison using relative tolerance.
      */
-    def relTol(eps: Double): CompareDoubleRightSide = CompareDoubleRightSide(RelativeErrorComparison,
-      x, eps, REL_TOL_MSG)
+    def relTol(eps: Double): CompareDoubleRightSide =
+      CompareDoubleRightSide(RelativeErrorComparison, x, eps, REL_TOL_MSG)
 
-    override def toString = x.toString
+    override def toString: String = x.toString
   }
 
   case class CompareVectorRightSide(
@@ -166,7 +166,7 @@ object TestingUtils {
         x.toArray.zip(y.toArray).forall(x => x._1 ~= x._2 relTol eps)
       }, x, eps, REL_TOL_MSG)
 
-    override def toString = x.toString
+    override def toString: String = x.toString
   }
 
   case class CompareMatrixRightSide(
@@ -229,7 +229,7 @@ object TestingUtils {
         x.toArray.zip(y.toArray).forall(x => x._1 ~= x._2 relTol eps)
       }, x, eps, REL_TOL_MSG)
 
-    override def toString = x.toString
+    override def toString: String = x.toString
   }
 
 }
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtilsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtilsSuite.scala
index b0ecb33c28483..59e6c778806f4 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtilsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtilsSuite.scala
@@ -88,16 +88,20 @@ class TestingUtilsSuite extends FunSuite {
     assert(!(17.8 ~= 17.59 absTol 0.2))
 
     // Comparisons of numbers very close to zero, and both side of zeros
-    assert(Double.MinPositiveValue ~== 4 * Double.MinPositiveValue absTol 5 * Double.MinPositiveValue)
-    assert(Double.MinPositiveValue !~== 6 * Double.MinPositiveValue absTol 5 * Double.MinPositiveValue)
-
-    assert(-Double.MinPositiveValue ~== 3 * Double.MinPositiveValue absTol 5 * Double.MinPositiveValue)
-    assert(Double.MinPositiveValue !~== -4 * Double.MinPositiveValue absTol 5 * Double.MinPositiveValue)
+    assert(
+      Double.MinPositiveValue ~== 4 * Double.MinPositiveValue absTol 5 * Double.MinPositiveValue)
+    assert(
+      Double.MinPositiveValue !~== 6 * Double.MinPositiveValue absTol 5 * Double.MinPositiveValue)
+
+    assert(
+      -Double.MinPositiveValue ~== 3 * Double.MinPositiveValue absTol 5 * Double.MinPositiveValue)
+    assert(
+      Double.MinPositiveValue !~== -4 * Double.MinPositiveValue absTol 5 * Double.MinPositiveValue)
   }
 
   test("Comparing vectors using relative error.") {
 
-    //Comparisons of two dense vectors
+    // Comparisons of two dense vectors
     assert(Vectors.dense(Array(3.1, 3.5)) ~== Vectors.dense(Array(3.130, 3.534)) relTol 0.01)
     assert(Vectors.dense(Array(3.1, 3.5)) !~== Vectors.dense(Array(3.135, 3.534)) relTol 0.01)
     assert(Vectors.dense(Array(3.1, 3.5)) ~= Vectors.dense(Array(3.130, 3.534)) relTol 0.01)
@@ -130,7 +134,7 @@ class TestingUtilsSuite extends FunSuite {
 
   test("Comparing vectors using absolute error.") {
 
-    //Comparisons of two dense vectors
+    // Comparisons of two dense vectors
     assert(Vectors.dense(Array(3.1, 3.5, 0.0)) ~==
       Vectors.dense(Array(3.1 + 1E-8, 3.5 + 2E-7, 1E-8)) absTol 1E-6)
 

From 6ada4f6f52cf1d992c7ab0c32318790cf08b0a0d Mon Sep 17 00:00:00 2001
From: Davies Liu <davies@databricks.com>
Date: Wed, 8 Apr 2015 13:31:45 -0700
Subject: [PATCH 16/95] [SPARK-6781] [SQL] use sqlContext in python shell

Use `sqlContext` in PySpark shell, make it consistent with SQL programming guide. `sqlCtx` is also kept for compatibility.

Author: Davies Liu <davies@databricks.com>

Closes #5425 from davies/sqlCtx and squashes the following commits:

af67340 [Davies Liu] sqlCtx -> sqlContext
15a278f [Davies Liu] use sqlContext in python shell
---
 docs/ml-guide.md                              |  2 +-
 docs/sql-programming-guide.md                 |  4 +-
 .../spark/examples/sql/JavaSparkSQL.java      | 20 ++---
 .../ml/simple_text_classification_pipeline.py |  2 +-
 .../src/main/python/mllib/dataset_example.py  |  6 +-
 python/pyspark/ml/classification.py           |  4 +-
 python/pyspark/ml/feature.py                  |  4 +-
 python/pyspark/shell.py                       |  6 +-
 python/pyspark/sql/context.py                 | 79 +++++++++----------
 python/pyspark/sql/dataframe.py               |  6 +-
 python/pyspark/sql/functions.py               |  2 +-
 python/pyspark/sql/types.py                   |  4 +-
 12 files changed, 69 insertions(+), 70 deletions(-)

diff --git a/docs/ml-guide.md b/docs/ml-guide.md
index c08c76d226713..771a07183e26f 100644
--- a/docs/ml-guide.md
+++ b/docs/ml-guide.md
@@ -493,7 +493,7 @@ from pyspark.ml.feature import HashingTF, Tokenizer
 from pyspark.sql import Row, SQLContext
 
 sc = SparkContext(appName="SimpleTextClassificationPipeline")
-sqlCtx = SQLContext(sc)
+sqlContext = SQLContext(sc)
 
 # Prepare training documents, which are labeled.
 LabeledDocument = Row("id", "text", "label")
diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md
index 4441d6a000a02..663f656883721 100644
--- a/docs/sql-programming-guide.md
+++ b/docs/sql-programming-guide.md
@@ -1642,7 +1642,7 @@ moved into the udf object in `SQLContext`.
 <div data-lang="scala"  markdown="1">
 {% highlight java %}
 
-sqlCtx.udf.register("strLen", (s: String) => s.length())
+sqlContext.udf.register("strLen", (s: String) => s.length())
 
 {% endhighlight %}
 </div>
@@ -1650,7 +1650,7 @@ sqlCtx.udf.register("strLen", (s: String) => s.length())
 <div data-lang="java"  markdown="1">
 {% highlight java %}
 
-sqlCtx.udf().register("strLen", (String s) -> { s.length(); });
+sqlContext.udf().register("strLen", (String s) -> { s.length(); });
 
 {% endhighlight %}
 </div>
diff --git a/examples/src/main/java/org/apache/spark/examples/sql/JavaSparkSQL.java b/examples/src/main/java/org/apache/spark/examples/sql/JavaSparkSQL.java
index dee794840a3e1..8159ffbe2d269 100644
--- a/examples/src/main/java/org/apache/spark/examples/sql/JavaSparkSQL.java
+++ b/examples/src/main/java/org/apache/spark/examples/sql/JavaSparkSQL.java
@@ -55,7 +55,7 @@ public void setAge(int age) {
   public static void main(String[] args) throws Exception {
     SparkConf sparkConf = new SparkConf().setAppName("JavaSparkSQL");
     JavaSparkContext ctx = new JavaSparkContext(sparkConf);
-    SQLContext sqlCtx = new SQLContext(ctx);
+    SQLContext sqlContext = new SQLContext(ctx);
 
     System.out.println("=== Data source: RDD ===");
     // Load a text file and convert each line to a Java Bean.
@@ -74,11 +74,11 @@ public Person call(String line) {
       });
 
     // Apply a schema to an RDD of Java Beans and register it as a table.
-    DataFrame schemaPeople = sqlCtx.createDataFrame(people, Person.class);
+    DataFrame schemaPeople = sqlContext.createDataFrame(people, Person.class);
     schemaPeople.registerTempTable("people");
 
     // SQL can be run over RDDs that have been registered as tables.
-    DataFrame teenagers = sqlCtx.sql("SELECT name FROM people WHERE age >= 13 AND age <= 19");
+    DataFrame teenagers = sqlContext.sql("SELECT name FROM people WHERE age >= 13 AND age <= 19");
 
     // The results of SQL queries are DataFrames and support all the normal RDD operations.
     // The columns of a row in the result can be accessed by ordinal.
@@ -99,12 +99,12 @@ public String call(Row row) {
     // Read in the parquet file created above.
     // Parquet files are self-describing so the schema is preserved.
     // The result of loading a parquet file is also a DataFrame.
-    DataFrame parquetFile = sqlCtx.parquetFile("people.parquet");
+    DataFrame parquetFile = sqlContext.parquetFile("people.parquet");
 
     //Parquet files can also be registered as tables and then used in SQL statements.
     parquetFile.registerTempTable("parquetFile");
     DataFrame teenagers2 =
-      sqlCtx.sql("SELECT name FROM parquetFile WHERE age >= 13 AND age <= 19");
+      sqlContext.sql("SELECT name FROM parquetFile WHERE age >= 13 AND age <= 19");
     teenagerNames = teenagers2.toJavaRDD().map(new Function<Row, String>() {
       @Override
       public String call(Row row) {
@@ -120,7 +120,7 @@ public String call(Row row) {
     // The path can be either a single text file or a directory storing text files.
     String path = "examples/src/main/resources/people.json";
     // Create a DataFrame from the file(s) pointed by path
-    DataFrame peopleFromJsonFile = sqlCtx.jsonFile(path);
+    DataFrame peopleFromJsonFile = sqlContext.jsonFile(path);
 
     // Because the schema of a JSON dataset is automatically inferred, to write queries,
     // it is better to take a look at what is the schema.
@@ -133,8 +133,8 @@ public String call(Row row) {
     // Register this DataFrame as a table.
     peopleFromJsonFile.registerTempTable("people");
 
-    // SQL statements can be run by using the sql methods provided by sqlCtx.
-    DataFrame teenagers3 = sqlCtx.sql("SELECT name FROM people WHERE age >= 13 AND age <= 19");
+    // SQL statements can be run by using the sql methods provided by sqlContext.
+    DataFrame teenagers3 = sqlContext.sql("SELECT name FROM people WHERE age >= 13 AND age <= 19");
 
     // The results of SQL queries are DataFrame and support all the normal RDD operations.
     // The columns of a row in the result can be accessed by ordinal.
@@ -151,7 +151,7 @@ public String call(Row row) {
     List<String> jsonData = Arrays.asList(
           "{\"name\":\"Yin\",\"address\":{\"city\":\"Columbus\",\"state\":\"Ohio\"}}");
     JavaRDD<String> anotherPeopleRDD = ctx.parallelize(jsonData);
-    DataFrame peopleFromJsonRDD = sqlCtx.jsonRDD(anotherPeopleRDD.rdd());
+    DataFrame peopleFromJsonRDD = sqlContext.jsonRDD(anotherPeopleRDD.rdd());
 
     // Take a look at the schema of this new DataFrame.
     peopleFromJsonRDD.printSchema();
@@ -164,7 +164,7 @@ public String call(Row row) {
 
     peopleFromJsonRDD.registerTempTable("people2");
 
-    DataFrame peopleWithCity = sqlCtx.sql("SELECT name, address.city FROM people2");
+    DataFrame peopleWithCity = sqlContext.sql("SELECT name, address.city FROM people2");
     List<String> nameAndCity = peopleWithCity.toJavaRDD().map(new Function<Row, String>() {
       @Override
       public String call(Row row) {
diff --git a/examples/src/main/python/ml/simple_text_classification_pipeline.py b/examples/src/main/python/ml/simple_text_classification_pipeline.py
index d281f4fa44282..c73edb7fd6b20 100644
--- a/examples/src/main/python/ml/simple_text_classification_pipeline.py
+++ b/examples/src/main/python/ml/simple_text_classification_pipeline.py
@@ -33,7 +33,7 @@
 
 if __name__ == "__main__":
     sc = SparkContext(appName="SimpleTextClassificationPipeline")
-    sqlCtx = SQLContext(sc)
+    sqlContext = SQLContext(sc)
 
     # Prepare training documents, which are labeled.
     LabeledDocument = Row("id", "text", "label")
diff --git a/examples/src/main/python/mllib/dataset_example.py b/examples/src/main/python/mllib/dataset_example.py
index b5a70db2b9a3c..fcbf56cbf0c52 100644
--- a/examples/src/main/python/mllib/dataset_example.py
+++ b/examples/src/main/python/mllib/dataset_example.py
@@ -44,19 +44,19 @@ def summarize(dataset):
         print >> sys.stderr, "Usage: dataset_example.py <libsvm file>"
         exit(-1)
     sc = SparkContext(appName="DatasetExample")
-    sqlCtx = SQLContext(sc)
+    sqlContext = SQLContext(sc)
     if len(sys.argv) == 2:
         input = sys.argv[1]
     else:
         input = "data/mllib/sample_libsvm_data.txt"
     points = MLUtils.loadLibSVMFile(sc, input)
-    dataset0 = sqlCtx.inferSchema(points).setName("dataset0").cache()
+    dataset0 = sqlContext.inferSchema(points).setName("dataset0").cache()
     summarize(dataset0)
     tempdir = tempfile.NamedTemporaryFile(delete=False).name
     os.unlink(tempdir)
     print "Save dataset as a Parquet file to %s." % tempdir
     dataset0.saveAsParquetFile(tempdir)
     print "Load it back and summarize it again."
-    dataset1 = sqlCtx.parquetFile(tempdir).setName("dataset1").cache()
+    dataset1 = sqlContext.parquetFile(tempdir).setName("dataset1").cache()
     summarize(dataset1)
     shutil.rmtree(tempdir)
diff --git a/python/pyspark/ml/classification.py b/python/pyspark/ml/classification.py
index 4ff7463498cce..7f42de531f3b4 100644
--- a/python/pyspark/ml/classification.py
+++ b/python/pyspark/ml/classification.py
@@ -91,9 +91,9 @@ class LogisticRegressionModel(JavaModel):
     # The small batch size here ensures that we see multiple batches,
     # even in these small test examples:
     sc = SparkContext("local[2]", "ml.feature tests")
-    sqlCtx = SQLContext(sc)
+    sqlContext = SQLContext(sc)
     globs['sc'] = sc
-    globs['sqlCtx'] = sqlCtx
+    globs['sqlContext'] = sqlContext
     (failure_count, test_count) = doctest.testmod(
         globs=globs, optionflags=doctest.ELLIPSIS)
     sc.stop()
diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py
index 433b4fb5d22bf..1cfcd019dfb18 100644
--- a/python/pyspark/ml/feature.py
+++ b/python/pyspark/ml/feature.py
@@ -117,9 +117,9 @@ def setParams(self, numFeatures=1 << 18, inputCol="input", outputCol="output"):
     # The small batch size here ensures that we see multiple batches,
     # even in these small test examples:
     sc = SparkContext("local[2]", "ml.feature tests")
-    sqlCtx = SQLContext(sc)
+    sqlContext = SQLContext(sc)
     globs['sc'] = sc
-    globs['sqlCtx'] = sqlCtx
+    globs['sqlContext'] = sqlContext
     (failure_count, test_count) = doctest.testmod(
         globs=globs, optionflags=doctest.ELLIPSIS)
     sc.stop()
diff --git a/python/pyspark/shell.py b/python/pyspark/shell.py
index 1a02fece9c5a5..81aa970a32f76 100644
--- a/python/pyspark/shell.py
+++ b/python/pyspark/shell.py
@@ -53,9 +53,9 @@
 try:
     # Try to access HiveConf, it will raise exception if Hive is not added
     sc._jvm.org.apache.hadoop.hive.conf.HiveConf()
-    sqlCtx = HiveContext(sc)
+    sqlCtx = sqlContext = HiveContext(sc)
 except py4j.protocol.Py4JError:
-    sqlCtx = SQLContext(sc)
+    sqlCtx = sqlContext = SQLContext(sc)
 
 print("""Welcome to
       ____              __
@@ -68,7 +68,7 @@
     platform.python_version(),
     platform.python_build()[0],
     platform.python_build()[1]))
-print("SparkContext available as sc, %s available as sqlCtx." % sqlCtx.__class__.__name__)
+print("SparkContext available as sc, %s available as sqlContext." % sqlContext.__class__.__name__)
 
 if add_files is not None:
     print("Warning: ADD_FILES environment variable is deprecated, use --py-files argument instead")
diff --git a/python/pyspark/sql/context.py b/python/pyspark/sql/context.py
index c2d81ba804110..93e2d176a5b6f 100644
--- a/python/pyspark/sql/context.py
+++ b/python/pyspark/sql/context.py
@@ -37,12 +37,12 @@
 __all__ = ["SQLContext", "HiveContext", "UDFRegistration"]
 
 
-def _monkey_patch_RDD(sqlCtx):
+def _monkey_patch_RDD(sqlContext):
     def toDF(self, schema=None, sampleRatio=None):
         """
         Converts current :class:`RDD` into a :class:`DataFrame`
 
-        This is a shorthand for ``sqlCtx.createDataFrame(rdd, schema, sampleRatio)``
+        This is a shorthand for ``sqlContext.createDataFrame(rdd, schema, sampleRatio)``
 
         :param schema: a StructType or list of names of columns
         :param samplingRatio: the sample ratio of rows used for inferring
@@ -51,7 +51,7 @@ def toDF(self, schema=None, sampleRatio=None):
         >>> rdd.toDF().collect()
         [Row(name=u'Alice', age=1)]
         """
-        return sqlCtx.createDataFrame(self, schema, sampleRatio)
+        return sqlContext.createDataFrame(self, schema, sampleRatio)
 
     RDD.toDF = toDF
 
@@ -75,13 +75,13 @@ def __init__(self, sparkContext, sqlContext=None):
         """Creates a new SQLContext.
 
         >>> from datetime import datetime
-        >>> sqlCtx = SQLContext(sc)
+        >>> sqlContext = SQLContext(sc)
         >>> allTypes = sc.parallelize([Row(i=1, s="string", d=1.0, l=1L,
         ...     b=True, list=[1, 2, 3], dict={"s": 0}, row=Row(a=1),
         ...     time=datetime(2014, 8, 1, 14, 1, 5))])
         >>> df = allTypes.toDF()
         >>> df.registerTempTable("allTypes")
-        >>> sqlCtx.sql('select i+1, d+1, not b, list[1], dict["s"], time, row.a '
+        >>> sqlContext.sql('select i+1, d+1, not b, list[1], dict["s"], time, row.a '
         ...            'from allTypes where b and i > 0').collect()
         [Row(c0=2, c1=2.0, c2=False, c3=2, c4=0...8, 1, 14, 1, 5), a=1)]
         >>> df.map(lambda x: (x.i, x.s, x.d, x.l, x.b, x.time,
@@ -133,18 +133,18 @@ def registerFunction(self, name, f, returnType=StringType()):
         :param samplingRatio: lambda function
         :param returnType: a :class:`DataType` object
 
-        >>> sqlCtx.registerFunction("stringLengthString", lambda x: len(x))
-        >>> sqlCtx.sql("SELECT stringLengthString('test')").collect()
+        >>> sqlContext.registerFunction("stringLengthString", lambda x: len(x))
+        >>> sqlContext.sql("SELECT stringLengthString('test')").collect()
         [Row(c0=u'4')]
 
         >>> from pyspark.sql.types import IntegerType
-        >>> sqlCtx.registerFunction("stringLengthInt", lambda x: len(x), IntegerType())
-        >>> sqlCtx.sql("SELECT stringLengthInt('test')").collect()
+        >>> sqlContext.registerFunction("stringLengthInt", lambda x: len(x), IntegerType())
+        >>> sqlContext.sql("SELECT stringLengthInt('test')").collect()
         [Row(c0=4)]
 
         >>> from pyspark.sql.types import IntegerType
-        >>> sqlCtx.udf.register("stringLengthInt", lambda x: len(x), IntegerType())
-        >>> sqlCtx.sql("SELECT stringLengthInt('test')").collect()
+        >>> sqlContext.udf.register("stringLengthInt", lambda x: len(x), IntegerType())
+        >>> sqlContext.sql("SELECT stringLengthInt('test')").collect()
         [Row(c0=4)]
         """
         func = lambda _, it: imap(lambda x: f(*x), it)
@@ -229,26 +229,26 @@ def createDataFrame(self, data, schema=None, samplingRatio=None):
         :param samplingRatio: the sample ratio of rows used for inferring
 
         >>> l = [('Alice', 1)]
-        >>> sqlCtx.createDataFrame(l).collect()
+        >>> sqlContext.createDataFrame(l).collect()
         [Row(_1=u'Alice', _2=1)]
-        >>> sqlCtx.createDataFrame(l, ['name', 'age']).collect()
+        >>> sqlContext.createDataFrame(l, ['name', 'age']).collect()
         [Row(name=u'Alice', age=1)]
 
         >>> d = [{'name': 'Alice', 'age': 1}]
-        >>> sqlCtx.createDataFrame(d).collect()
+        >>> sqlContext.createDataFrame(d).collect()
         [Row(age=1, name=u'Alice')]
 
         >>> rdd = sc.parallelize(l)
-        >>> sqlCtx.createDataFrame(rdd).collect()
+        >>> sqlContext.createDataFrame(rdd).collect()
         [Row(_1=u'Alice', _2=1)]
-        >>> df = sqlCtx.createDataFrame(rdd, ['name', 'age'])
+        >>> df = sqlContext.createDataFrame(rdd, ['name', 'age'])
         >>> df.collect()
         [Row(name=u'Alice', age=1)]
 
         >>> from pyspark.sql import Row
         >>> Person = Row('name', 'age')
         >>> person = rdd.map(lambda r: Person(*r))
-        >>> df2 = sqlCtx.createDataFrame(person)
+        >>> df2 = sqlContext.createDataFrame(person)
         >>> df2.collect()
         [Row(name=u'Alice', age=1)]
 
@@ -256,11 +256,11 @@ def createDataFrame(self, data, schema=None, samplingRatio=None):
         >>> schema = StructType([
         ...    StructField("name", StringType(), True),
         ...    StructField("age", IntegerType(), True)])
-        >>> df3 = sqlCtx.createDataFrame(rdd, schema)
+        >>> df3 = sqlContext.createDataFrame(rdd, schema)
         >>> df3.collect()
         [Row(name=u'Alice', age=1)]
 
-        >>> sqlCtx.createDataFrame(df.toPandas()).collect()  # doctest: +SKIP
+        >>> sqlContext.createDataFrame(df.toPandas()).collect()  # doctest: +SKIP
         [Row(name=u'Alice', age=1)]
         """
         if isinstance(data, DataFrame):
@@ -316,7 +316,7 @@ def registerDataFrameAsTable(self, df, tableName):
 
         Temporary tables exist only during the lifetime of this instance of :class:`SQLContext`.
 
-        >>> sqlCtx.registerDataFrameAsTable(df, "table1")
+        >>> sqlContext.registerDataFrameAsTable(df, "table1")
         """
         if (df.__class__ is DataFrame):
             self._ssql_ctx.registerDataFrameAsTable(df._jdf, tableName)
@@ -330,7 +330,7 @@ def parquetFile(self, *paths):
         >>> parquetFile = tempfile.mkdtemp()
         >>> shutil.rmtree(parquetFile)
         >>> df.saveAsParquetFile(parquetFile)
-        >>> df2 = sqlCtx.parquetFile(parquetFile)
+        >>> df2 = sqlContext.parquetFile(parquetFile)
         >>> sorted(df.collect()) == sorted(df2.collect())
         True
         """
@@ -352,7 +352,7 @@ def jsonFile(self, path, schema=None, samplingRatio=1.0):
         >>> shutil.rmtree(jsonFile)
         >>> with open(jsonFile, 'w') as f:
         ...     f.writelines(jsonStrings)
-        >>> df1 = sqlCtx.jsonFile(jsonFile)
+        >>> df1 = sqlContext.jsonFile(jsonFile)
         >>> df1.printSchema()
         root
          |-- field1: long (nullable = true)
@@ -365,7 +365,7 @@ def jsonFile(self, path, schema=None, samplingRatio=1.0):
         ...     StructField("field2", StringType()),
         ...     StructField("field3",
         ...         StructType([StructField("field5", ArrayType(IntegerType()))]))])
-        >>> df2 = sqlCtx.jsonFile(jsonFile, schema)
+        >>> df2 = sqlContext.jsonFile(jsonFile, schema)
         >>> df2.printSchema()
         root
          |-- field2: string (nullable = true)
@@ -386,11 +386,11 @@ def jsonRDD(self, rdd, schema=None, samplingRatio=1.0):
         If the schema is provided, applies the given schema to this JSON dataset.
         Otherwise, it samples the dataset with ratio ``samplingRatio`` to determine the schema.
 
-        >>> df1 = sqlCtx.jsonRDD(json)
+        >>> df1 = sqlContext.jsonRDD(json)
         >>> df1.first()
         Row(field1=1, field2=u'row1', field3=Row(field4=11, field5=None), field6=None)
 
-        >>> df2 = sqlCtx.jsonRDD(json, df1.schema)
+        >>> df2 = sqlContext.jsonRDD(json, df1.schema)
         >>> df2.first()
         Row(field1=1, field2=u'row1', field3=Row(field4=11, field5=None), field6=None)
 
@@ -400,7 +400,7 @@ def jsonRDD(self, rdd, schema=None, samplingRatio=1.0):
         ...     StructField("field3",
         ...                 StructType([StructField("field5", ArrayType(IntegerType()))]))
         ... ])
-        >>> df3 = sqlCtx.jsonRDD(json, schema)
+        >>> df3 = sqlContext.jsonRDD(json, schema)
         >>> df3.first()
         Row(field2=u'row1', field3=Row(field5=None))
         """
@@ -480,8 +480,8 @@ def createExternalTable(self, tableName, path=None, source=None,
     def sql(self, sqlQuery):
         """Returns a :class:`DataFrame` representing the result of the given query.
 
-        >>> sqlCtx.registerDataFrameAsTable(df, "table1")
-        >>> df2 = sqlCtx.sql("SELECT field1 AS f1, field2 as f2 from table1")
+        >>> sqlContext.registerDataFrameAsTable(df, "table1")
+        >>> df2 = sqlContext.sql("SELECT field1 AS f1, field2 as f2 from table1")
         >>> df2.collect()
         [Row(f1=1, f2=u'row1'), Row(f1=2, f2=u'row2'), Row(f1=3, f2=u'row3')]
         """
@@ -490,8 +490,8 @@ def sql(self, sqlQuery):
     def table(self, tableName):
         """Returns the specified table as a :class:`DataFrame`.
 
-        >>> sqlCtx.registerDataFrameAsTable(df, "table1")
-        >>> df2 = sqlCtx.table("table1")
+        >>> sqlContext.registerDataFrameAsTable(df, "table1")
+        >>> df2 = sqlContext.table("table1")
         >>> sorted(df.collect()) == sorted(df2.collect())
         True
         """
@@ -505,8 +505,8 @@ def tables(self, dbName=None):
         The returned DataFrame has two columns: ``tableName`` and ``isTemporary``
         (a column with :class:`BooleanType` indicating if a table is a temporary one or not).
 
-        >>> sqlCtx.registerDataFrameAsTable(df, "table1")
-        >>> df2 = sqlCtx.tables()
+        >>> sqlContext.registerDataFrameAsTable(df, "table1")
+        >>> df2 = sqlContext.tables()
         >>> df2.filter("tableName = 'table1'").first()
         Row(tableName=u'table1', isTemporary=True)
         """
@@ -520,10 +520,10 @@ def tableNames(self, dbName=None):
 
         If ``dbName`` is not specified, the current database will be used.
 
-        >>> sqlCtx.registerDataFrameAsTable(df, "table1")
-        >>> "table1" in sqlCtx.tableNames()
+        >>> sqlContext.registerDataFrameAsTable(df, "table1")
+        >>> "table1" in sqlContext.tableNames()
         True
-        >>> "table1" in sqlCtx.tableNames("db")
+        >>> "table1" in sqlContext.tableNames("db")
         True
         """
         if dbName is None:
@@ -578,11 +578,11 @@ def _get_hive_ctx(self):
 class UDFRegistration(object):
     """Wrapper for user-defined function registration."""
 
-    def __init__(self, sqlCtx):
-        self.sqlCtx = sqlCtx
+    def __init__(self, sqlContext):
+        self.sqlContext = sqlContext
 
     def register(self, name, f, returnType=StringType()):
-        return self.sqlCtx.registerFunction(name, f, returnType)
+        return self.sqlContext.registerFunction(name, f, returnType)
 
     register.__doc__ = SQLContext.registerFunction.__doc__
 
@@ -595,13 +595,12 @@ def _test():
     globs = pyspark.sql.context.__dict__.copy()
     sc = SparkContext('local[4]', 'PythonTest')
     globs['sc'] = sc
-    globs['sqlCtx'] = sqlCtx = SQLContext(sc)
+    globs['sqlContext'] = SQLContext(sc)
     globs['rdd'] = rdd = sc.parallelize(
         [Row(field1=1, field2="row1"),
          Row(field1=2, field2="row2"),
          Row(field1=3, field2="row3")]
     )
-    _monkey_patch_RDD(sqlCtx)
     globs['df'] = rdd.toDF()
     jsonStrings = [
         '{"field1": 1, "field2": "row1", "field3":{"field4":11}}',
diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py
index c30326ebd133e..ef91a9c4f522d 100644
--- a/python/pyspark/sql/dataframe.py
+++ b/python/pyspark/sql/dataframe.py
@@ -110,7 +110,7 @@ def saveAsParquetFile(self, path):
         >>> parquetFile = tempfile.mkdtemp()
         >>> shutil.rmtree(parquetFile)
         >>> df.saveAsParquetFile(parquetFile)
-        >>> df2 = sqlCtx.parquetFile(parquetFile)
+        >>> df2 = sqlContext.parquetFile(parquetFile)
         >>> sorted(df2.collect()) == sorted(df.collect())
         True
         """
@@ -123,7 +123,7 @@ def registerTempTable(self, name):
         that was used to create this :class:`DataFrame`.
 
         >>> df.registerTempTable("people")
-        >>> df2 = sqlCtx.sql("select * from people")
+        >>> df2 = sqlContext.sql("select * from people")
         >>> sorted(df.collect()) == sorted(df2.collect())
         True
         """
@@ -1180,7 +1180,7 @@ def _test():
     globs = pyspark.sql.dataframe.__dict__.copy()
     sc = SparkContext('local[4]', 'PythonTest')
     globs['sc'] = sc
-    globs['sqlCtx'] = SQLContext(sc)
+    globs['sqlContext'] = SQLContext(sc)
     globs['df'] = sc.parallelize([(2, 'Alice'), (5, 'Bob')])\
         .toDF(StructType([StructField('age', IntegerType()),
                           StructField('name', StringType())]))
diff --git a/python/pyspark/sql/functions.py b/python/pyspark/sql/functions.py
index 146ba6f3e0d98..daeb6916b58bc 100644
--- a/python/pyspark/sql/functions.py
+++ b/python/pyspark/sql/functions.py
@@ -161,7 +161,7 @@ def _test():
     globs = pyspark.sql.functions.__dict__.copy()
     sc = SparkContext('local[4]', 'PythonTest')
     globs['sc'] = sc
-    globs['sqlCtx'] = SQLContext(sc)
+    globs['sqlContext'] = SQLContext(sc)
     globs['df'] = sc.parallelize([Row(name='Alice', age=2), Row(name='Bob', age=5)]).toDF()
     (failure_count, test_count) = doctest.testmod(
         pyspark.sql.functions, globs=globs,
diff --git a/python/pyspark/sql/types.py b/python/pyspark/sql/types.py
index 45eb8b945dcb0..7e0124b13671b 100644
--- a/python/pyspark/sql/types.py
+++ b/python/pyspark/sql/types.py
@@ -434,7 +434,7 @@ def _parse_datatype_json_string(json_string):
     >>> def check_datatype(datatype):
     ...     pickled = pickle.loads(pickle.dumps(datatype))
     ...     assert datatype == pickled
-    ...     scala_datatype = sqlCtx._ssql_ctx.parseDataType(datatype.json())
+    ...     scala_datatype = sqlContext._ssql_ctx.parseDataType(datatype.json())
     ...     python_datatype = _parse_datatype_json_string(scala_datatype.json())
     ...     assert datatype == python_datatype
     >>> for cls in _all_primitive_types.values():
@@ -1237,7 +1237,7 @@ def _test():
     globs = pyspark.sql.types.__dict__.copy()
     sc = SparkContext('local[4]', 'PythonTest')
     globs['sc'] = sc
-    globs['sqlCtx'] = sqlCtx = SQLContext(sc)
+    globs['sqlContext'] = SQLContext(sc)
     globs['ExamplePoint'] = ExamplePoint
     globs['ExamplePointUDT'] = ExamplePointUDT
     (failure_count, test_count) = doctest.testmod(

From 2f482d706b9d38820472c3152dbd1612c98729bd Mon Sep 17 00:00:00 2001
From: Tijo Thomas <tijoparacka@gmail.com>
Date: Wed, 8 Apr 2015 13:42:29 -0700
Subject: [PATCH 17/95] [SPARK-6767][SQL] Fixed Query DSL error in spark sql
 Readme

Fixed the  following error
query.where('key > 30).select(avg('key)).collect()
<console>:43: error: value > is not a member of Symbol
              query.where('key > 30).select(avg('key)).collect()

Author: Tijo Thomas <tijoparacka@gmail.com>

Closes #5415 from tijoparacka/ERROR_SQL_DATAFRAME_EXAMPLE and squashes the following commits:

234751e [Tijo Thomas] Fixed Query DSL error in spark sql Readme
---
 sql/README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sql/README.md b/sql/README.md
index fbb3200a3a4b4..237620e3fa808 100644
--- a/sql/README.md
+++ b/sql/README.md
@@ -56,6 +56,6 @@ res2: Array[org.apache.spark.sql.Row] = Array([238,val_238], [86,val_86], [311,v
 
 You can also build further queries on top of these `DataFrames` using the query DSL.
 ```
-scala> query.where('key > 30).select(avg('key)).collect()
+scala> query.where(query("key") > 30).select(avg(query("key"))).collect()
 res3: Array[org.apache.spark.sql.Row] = Array([274.79025423728814])
 ```

From 86403f5525782bc9656ab11790f7020baa6b2c1f Mon Sep 17 00:00:00 2001
From: Michelangelo D'Agostino <mdagostino@civisanalytics.com>
Date: Wed, 8 Apr 2015 16:48:45 -0400
Subject: [PATCH 18/95] [SPARK-5242]: Add --private-ips flag to EC2 script

The `spark_ec2.py` script currently references the `ip_address` and `public_dns_name` attributes of an instance. On private networks, these fields aren't set, so we have problems.

This PR introduces a `--private-ips` flag that instead refers to the `private_ip_address` attribute in both cases.

Author: Michelangelo D'Agostino <mdagostino@civisanalytics.com>

Closes #5244 from mdagost/ec2_private_nets and squashes the following commits:

b684c67 [Michelangelo D'Agostino] STY: A few python lint changes.
a4a2eac [Michelangelo D'Agostino] ENH: Fix IP's typo and refactor conditional logic into functions.
c004604 [Michelangelo D'Agostino] ENH: Add --private-ips flag.
---
 ec2/spark_ec2.py | 64 +++++++++++++++++++++++++++++++++++-------------
 1 file changed, 47 insertions(+), 17 deletions(-)

diff --git a/ec2/spark_ec2.py b/ec2/spark_ec2.py
index 879a52cef8ff0..0c1f24761d0de 100755
--- a/ec2/spark_ec2.py
+++ b/ec2/spark_ec2.py
@@ -282,6 +282,10 @@ def parse_args():
     parser.add_option(
         "--vpc-id", default=None,
         help="VPC to launch instances in")
+    parser.add_option(
+        "--private-ips", action="store_true", default=False,
+        help="Use private IPs for instances rather than public if VPC/subnet " +
+             "requires that.")
 
     (opts, args) = parser.parse_args()
     if len(args) != 2:
@@ -707,7 +711,7 @@ def get_instances(group_names):
 # Deploy configuration files and run setup scripts on a newly launched
 # or started EC2 cluster.
 def setup_cluster(conn, master_nodes, slave_nodes, opts, deploy_ssh_key):
-    master = master_nodes[0].public_dns_name
+    master = get_dns_name(master_nodes[0], opts.private_ips)
     if deploy_ssh_key:
         print "Generating cluster's SSH key on master..."
         key_setup = """
@@ -719,8 +723,9 @@ def setup_cluster(conn, master_nodes, slave_nodes, opts, deploy_ssh_key):
         dot_ssh_tar = ssh_read(master, opts, ['tar', 'c', '.ssh'])
         print "Transferring cluster's SSH key to slaves..."
         for slave in slave_nodes:
-            print slave.public_dns_name
-            ssh_write(slave.public_dns_name, opts, ['tar', 'x'], dot_ssh_tar)
+            slave_address = get_dns_name(slave, opts.private_ips)
+            print slave_address
+            ssh_write(slave_address, opts, ['tar', 'x'], dot_ssh_tar)
 
     modules = ['spark', 'ephemeral-hdfs', 'persistent-hdfs',
                'mapreduce', 'spark-standalone', 'tachyon']
@@ -809,7 +814,8 @@ def is_cluster_ssh_available(cluster_instances, opts):
     Check if SSH is available on all the instances in a cluster.
     """
     for i in cluster_instances:
-        if not is_ssh_available(host=i.public_dns_name, opts=opts):
+        dns_name = get_dns_name(i, opts.private_ips)
+        if not is_ssh_available(host=dns_name, opts=opts):
             return False
     else:
         return True
@@ -923,7 +929,7 @@ def get_num_disks(instance_type):
 #
 # root_dir should be an absolute path to the directory with the files we want to deploy.
 def deploy_files(conn, root_dir, opts, master_nodes, slave_nodes, modules):
-    active_master = master_nodes[0].public_dns_name
+    active_master = get_dns_name(master_nodes[0], opts.private_ips)
 
     num_disks = get_num_disks(opts.instance_type)
     hdfs_data_dirs = "/mnt/ephemeral-hdfs/data"
@@ -948,10 +954,12 @@ def deploy_files(conn, root_dir, opts, master_nodes, slave_nodes, modules):
         print "Deploying Spark via git hash; Tachyon won't be set up"
         modules = filter(lambda x: x != "tachyon", modules)
 
+    master_addresses = [get_dns_name(i, opts.private_ips) for i in master_nodes]
+    slave_addresses = [get_dns_name(i, opts.private_ips) for i in slave_nodes]
     template_vars = {
-        "master_list": '\n'.join([i.public_dns_name for i in master_nodes]),
+        "master_list": '\n'.join(master_addresses),
         "active_master": active_master,
-        "slave_list": '\n'.join([i.public_dns_name for i in slave_nodes]),
+        "slave_list": '\n'.join(slave_addresses),
         "cluster_url": cluster_url,
         "hdfs_data_dirs": hdfs_data_dirs,
         "mapred_local_dirs": mapred_local_dirs,
@@ -1011,7 +1019,7 @@ def deploy_files(conn, root_dir, opts, master_nodes, slave_nodes, modules):
 #
 # root_dir should be an absolute path.
 def deploy_user_files(root_dir, opts, master_nodes):
-    active_master = master_nodes[0].public_dns_name
+    active_master = get_dns_name(master_nodes[0], opts.private_ips)
     command = [
         'rsync', '-rv',
         '-e', stringify_command(ssh_command(opts)),
@@ -1122,6 +1130,20 @@ def get_partition(total, num_partitions, current_partitions):
     return num_slaves_this_zone
 
 
+# Gets the IP address, taking into account the --private-ips flag
+def get_ip_address(instance, private_ips=False):
+    ip = instance.ip_address if not private_ips else \
+        instance.private_ip_address
+    return ip
+
+
+# Gets the DNS name, taking into account the --private-ips flag
+def get_dns_name(instance, private_ips=False):
+    dns = instance.public_dns_name if not private_ips else \
+        instance.private_ip_address
+    return dns
+
+
 def real_main():
     (opts, action, cluster_name) = parse_args()
 
@@ -1230,7 +1252,7 @@ def real_main():
         if any(master_nodes + slave_nodes):
             print "The following instances will be terminated:"
             for inst in master_nodes + slave_nodes:
-                print "> %s" % inst.public_dns_name
+                print "> %s" % get_dns_name(inst, opts.private_ips)
             print "ALL DATA ON ALL NODES WILL BE LOST!!"
 
         msg = "Are you sure you want to destroy the cluster {c}? (y/N) ".format(c=cluster_name)
@@ -1294,13 +1316,17 @@ def real_main():
 
     elif action == "login":
         (master_nodes, slave_nodes) = get_existing_cluster(conn, opts, cluster_name)
-        master = master_nodes[0].public_dns_name
-        print "Logging into master " + master + "..."
-        proxy_opt = []
-        if opts.proxy_port is not None:
-            proxy_opt = ['-D', opts.proxy_port]
-        subprocess.check_call(
-            ssh_command(opts) + proxy_opt + ['-t', '-t', "%s@%s" % (opts.user, master)])
+        if not master_nodes[0].public_dns_name and not opts.private_ips:
+            print "Master has no public DNS name.  Maybe you meant to specify " \
+                "--private-ips?"
+        else:
+            master = get_dns_name(master_nodes[0], opts.private_ips)
+            print "Logging into master " + master + "..."
+            proxy_opt = []
+            if opts.proxy_port is not None:
+                proxy_opt = ['-D', opts.proxy_port]
+            subprocess.check_call(
+                ssh_command(opts) + proxy_opt + ['-t', '-t', "%s@%s" % (opts.user, master)])
 
     elif action == "reboot-slaves":
         response = raw_input(
@@ -1318,7 +1344,11 @@ def real_main():
 
     elif action == "get-master":
         (master_nodes, slave_nodes) = get_existing_cluster(conn, opts, cluster_name)
-        print master_nodes[0].public_dns_name
+        if not master_nodes[0].public_dns_name and not opts.private_ips:
+            print "Master has no public DNS name.  Maybe you meant to specify " \
+                "--private-ips?"
+        else:
+            print get_dns_name(master_nodes[0], opts.private_ips)
 
     elif action == "stop":
         response = raw_input(

From 55a92ef34c0b57b6e379523d5d79baa05392de37 Mon Sep 17 00:00:00 2001
From: unknown <l00251599@HGHY1L002515991.china.huawei.com>
Date: Wed, 8 Apr 2015 13:56:42 -0700
Subject: [PATCH 19/95] [SPARK-4346][SPARK-3596][YARN] Commonize the monitor
 logic

1. YarnClientSchedulerBack.asyncMonitorApplication use Client.monitorApplication so that commonize the monitor logic
2. Support changing the yarn client monitor interval, see #5292
3. More details see discussion on https://github.com/apache/spark/pull/3143

Author: unknown <l00251599@HGHY1L002515991.china.huawei.com>
Author: Sephiroth-Lin <linwzhong@gmail.com>

Closes #5305 from Sephiroth-Lin/SPARK-4346_3596 and squashes the following commits:

47c0014 [unknown] Edit conflicts
52b29fe [unknown] Interrupt thread when we call stop()
d4298a1 [unknown] Unused, don't push
aaacb42 [Sephiroth-Lin] don't wrap the entire block in the try
ee2b2fd [Sephiroth-Lin] update
6483a2a [unknown] Catch exception
6b47ff7 [unknown] Update code
568f46f [unknown] YarnClientSchedulerBack.asyncMonitorApplication should be common with Client.monitorApplication
---
 .../org/apache/spark/deploy/yarn/Client.scala | 10 +++++-
 .../cluster/YarnClientSchedulerBackend.scala  | 32 ++++++-------------
 2 files changed, 18 insertions(+), 24 deletions(-)

diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
index 79d55a09eb671..7219852c0a752 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
@@ -40,6 +40,7 @@ import org.apache.hadoop.yarn.api.protocolrecords._
 import org.apache.hadoop.yarn.api.records._
 import org.apache.hadoop.yarn.client.api.{YarnClient, YarnClientApplication}
 import org.apache.hadoop.yarn.conf.YarnConfiguration
+import org.apache.hadoop.yarn.exceptions.ApplicationNotFoundException
 import org.apache.hadoop.yarn.util.Records
 
 import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkContext, SparkException}
@@ -561,7 +562,14 @@ private[spark] class Client(
     var lastState: YarnApplicationState = null
     while (true) {
       Thread.sleep(interval)
-      val report = getApplicationReport(appId)
+      val report: ApplicationReport =
+        try {
+          getApplicationReport(appId)
+        } catch {
+          case e: ApplicationNotFoundException =>
+            logError(s"Application $appId not found.")
+            return (YarnApplicationState.KILLED, FinalApplicationStatus.KILLED)
+        }
       val state = report.getYarnApplicationState
 
       if (logApplicationReport) {
diff --git a/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala b/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala
index 8abdc26b43806..407dc1ac4d37d 100644
--- a/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala
+++ b/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala
@@ -34,7 +34,7 @@ private[spark] class YarnClientSchedulerBackend(
 
   private var client: Client = null
   private var appId: ApplicationId = null
-  @volatile private var stopping: Boolean = false
+  private var monitorThread: Thread = null
 
   /**
    * Create a Yarn client to submit an application to the ResourceManager.
@@ -57,7 +57,8 @@ private[spark] class YarnClientSchedulerBackend(
     client = new Client(args, conf)
     appId = client.submitApplication()
     waitForApplication()
-    asyncMonitorApplication()
+    monitorThread = asyncMonitorApplication()
+    monitorThread.start()
   }
 
   /**
@@ -123,34 +124,19 @@ private[spark] class YarnClientSchedulerBackend(
    * If the application has exited for any reason, stop the SparkContext.
    * This assumes both `client` and `appId` have already been set.
    */
-  private def asyncMonitorApplication(): Unit = {
+  private def asyncMonitorApplication(): Thread = {
     assert(client != null && appId != null, "Application has not been submitted yet!")
     val t = new Thread {
       override def run() {
-        while (!stopping) {
-          var state: YarnApplicationState = null
-          try {
-            val report = client.getApplicationReport(appId)
-            state = report.getYarnApplicationState()
-          } catch {
-            case e: ApplicationNotFoundException =>
-              state = YarnApplicationState.KILLED
-          }
-          if (state == YarnApplicationState.FINISHED ||
-            state == YarnApplicationState.KILLED ||
-            state == YarnApplicationState.FAILED) {
-            logError(s"Yarn application has already exited with state $state!")
-            sc.stop()
-            stopping = true
-          }
-          Thread.sleep(1000L)
-        }
+        val (state, _) = client.monitorApplication(appId, logApplicationReport = false)
+        logError(s"Yarn application has already exited with state $state!")
+        sc.stop()
         Thread.currentThread().interrupt()
       }
     }
     t.setName("Yarn application state monitor")
     t.setDaemon(true)
-    t.start()
+    t
   }
 
   /**
@@ -158,7 +144,7 @@ private[spark] class YarnClientSchedulerBackend(
    */
   override def stop() {
     assert(client != null, "Attempted to stop this scheduler before starting it!")
-    stopping = true
+    monitorThread.interrupt()
     super.stop()
     client.stop()
     logInfo("Stopped")

From 9418280547f962eaf309bfff9986cdd848409643 Mon Sep 17 00:00:00 2001
From: Wenchen Fan <cloud0fan@outlook.com>
Date: Wed, 8 Apr 2015 13:57:01 -0700
Subject: [PATCH 20/95] [SQL][minor] remove duplicated resolveGetField and
 update comment

It's after https://github.com/apache/spark/pull/5189

Author: Wenchen Fan <cloud0fan@outlook.com>

Closes #5304 from cloud-fan/tmp and squashes the following commits:

c58c9b3 [Wenchen Fan] remove duplicated code and update comment
---
 .../sql/catalyst/analysis/Analyzer.scala      | 32 +------------------
 .../catalyst/plans/logical/LogicalPlan.scala  | 13 +++-----
 2 files changed, 6 insertions(+), 39 deletions(-)

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
index 119cb9c3a4400..b3aba4f68ddf9 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
@@ -293,7 +293,7 @@ class Analyzer(
             logDebug(s"Resolving $u to $result")
             result
           case UnresolvedGetField(child, fieldName) if child.resolved =>
-            resolveGetField(child, fieldName)
+            q.resolveGetField(child, fieldName, resolver)
         }
     }
 
@@ -313,36 +313,6 @@ class Analyzer(
      */
     protected def containsStar(exprs: Seq[Expression]): Boolean =
       exprs.exists(_.collect { case _: Star => true }.nonEmpty)
-
-    /**
-     * Returns the resolved `GetField`, and report error if no desired field or over one
-     * desired fields are found.
-     */
-    protected def resolveGetField(expr: Expression, fieldName: String): Expression = {
-      def findField(fields: Array[StructField]): Int = {
-        val checkField = (f: StructField) => resolver(f.name, fieldName)
-        val ordinal = fields.indexWhere(checkField)
-        if (ordinal == -1) {
-          throw new AnalysisException(
-            s"No such struct field $fieldName in ${fields.map(_.name).mkString(", ")}")
-        } else if (fields.indexWhere(checkField, ordinal + 1) != -1) {
-          throw new AnalysisException(
-            s"Ambiguous reference to fields ${fields.filter(checkField).mkString(", ")}")
-        } else {
-          ordinal
-        }
-      }
-      expr.dataType match {
-        case StructType(fields) =>
-          val ordinal = findField(fields)
-          StructGetField(expr, fields(ordinal), ordinal)
-        case ArrayType(StructType(fields), containsNull) =>
-          val ordinal = findField(fields)
-          ArrayGetField(expr, fields(ordinal), ordinal, containsNull)
-        case otherType =>
-          throw new AnalysisException(s"GetField is not valid on fields of type $otherType")
-      }
-    }
   }
 
   /**
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LogicalPlan.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LogicalPlan.scala
index 2e9f3aa4ec4ad..d8f5858f5033e 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LogicalPlan.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LogicalPlan.scala
@@ -205,11 +205,10 @@ abstract class LogicalPlan extends QueryPlan[LogicalPlan] with Logging {
       // One match, but we also need to extract the requested nested field.
       case Seq((a, nestedFields)) =>
         try {
-
-          // The foldLeft adds UnresolvedGetField for every remaining parts of the name,
-          // and aliased it with the last part of the name.
-          // For example, consider name "a.b.c", where "a" is resolved to an existing attribute.
-          // Then this will add UnresolvedGetField("b") and UnresolvedGetField("c"), and alias
+          // The foldLeft adds GetFields for every remaining parts of the identifier,
+          // and aliases it with the last part of the identifier.
+          // For example, consider "a.b.c", where "a" is resolved to an existing attribute.
+          // Then this will add GetField("c", GetField("b", a)), and alias
           // the final expression as "c".
           val fieldExprs = nestedFields.foldLeft(a: Expression)(resolveGetField(_, _, resolver))
           val aliasName = nestedFields.last
@@ -234,10 +233,8 @@ abstract class LogicalPlan extends QueryPlan[LogicalPlan] with Logging {
   /**
    * Returns the resolved `GetField`, and report error if no desired field or over one
    * desired fields are found.
-   *
-   * TODO: this code is duplicated from Analyzer and should be refactored to avoid this.
    */
-  protected def resolveGetField(
+  def resolveGetField(
       expr: Expression,
       fieldName: String,
       resolver: Resolver): Expression = {

From 7d7384c781ea72e1eabab3daca2e237e3b0fc666 Mon Sep 17 00:00:00 2001
From: Venkata Ramana Gollamudi <ramana.gollamudi@huawei.com>
Date: Wed, 8 Apr 2015 18:42:34 -0700
Subject: [PATCH 21/95] [SPARK-6451][SQL] supported code generation for
 CombineSum

Author: Venkata Ramana Gollamudi <ramana.gollamudi@huawei.com>

Closes #5138 from gvramana/sum_fix_codegen and squashes the following commits:

95f5fe4 [Venkata Ramana Gollamudi] rebase merge changes
12f45a5 [Venkata Ramana Gollamudi] Combined and added code generations tests as per comment
d6a76ac [Venkata Ramana Gollamudi] added support for codegeneration for CombineSum and tests
---
 .../sql/execution/GeneratedAggregate.scala    | 44 ++++++++-
 .../spark/sql/execution/SparkStrategies.scala |  2 +-
 .../org/apache/spark/sql/SQLQuerySuite.scala  | 92 ++++++++++++++++++-
 3 files changed, 133 insertions(+), 5 deletions(-)

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
index a8018b9213f2b..861a2c21ad9a0 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
@@ -99,7 +99,10 @@ case class GeneratedAggregate(
         // but really, common sub expression elimination would be better....
         val zero = Cast(Literal(0), calcType)
         val updateFunction = Coalesce(
-          Add(Coalesce(currentSum :: zero :: Nil), Cast(expr, calcType)) :: currentSum :: Nil)
+          Add(
+            Coalesce(currentSum :: zero :: Nil),
+            Cast(expr, calcType)
+          ) :: currentSum :: zero :: Nil)
         val result =
           expr.dataType match {
             case DecimalType.Fixed(_, _) =>
@@ -109,6 +112,45 @@ case class GeneratedAggregate(
 
         AggregateEvaluation(currentSum :: Nil, initialValue :: Nil, updateFunction :: Nil, result)
 
+      case cs @ CombineSum(expr) =>
+        val calcType = expr.dataType
+          expr.dataType match {
+            case DecimalType.Fixed(_, _) =>
+              DecimalType.Unlimited
+            case _ =>
+              expr.dataType
+          }
+
+        val currentSum = AttributeReference("currentSum", calcType, nullable = true)()
+        val initialValue = Literal.create(null, calcType)
+
+        // Coalasce avoids double calculation...
+        // but really, common sub expression elimination would be better....
+        val zero = Cast(Literal(0), calcType)
+        // If we're evaluating UnscaledValue(x), we can do Count on x directly, since its
+        // UnscaledValue will be null if and only if x is null; helps with Average on decimals
+        val actualExpr = expr match {
+          case UnscaledValue(e) => e
+          case _ => expr
+        }
+        // partial sum result can be null only when no input rows present 
+        val updateFunction = If(
+          IsNotNull(actualExpr),
+          Coalesce(
+            Add(
+              Coalesce(currentSum :: zero :: Nil), 
+              Cast(expr, calcType)) :: currentSum :: zero :: Nil),
+          currentSum)
+          
+        val result =
+          expr.dataType match {
+            case DecimalType.Fixed(_, _) =>
+              Cast(currentSum, cs.dataType)
+            case _ => currentSum
+          }
+
+        AggregateEvaluation(currentSum :: Nil, initialValue :: Nil, updateFunction :: Nil, result)
+        
       case a @ Average(expr) =>
         val calcType =
           expr.dataType match {
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
index f754fa770d1b5..23f7e5609414b 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
@@ -155,7 +155,7 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
     }
 
     def canBeCodeGened(aggs: Seq[AggregateExpression]): Boolean = !aggs.exists {
-      case _: Sum | _: Count | _: Max | _: CombineSetsAndCount => false
+      case _: CombineSum | _: Sum | _: Count | _: Max | _: CombineSetsAndCount => false
       // The generated set implementation is pretty limited ATM.
       case CollectHashSet(exprs) if exprs.size == 1  &&
            Seq(IntegerType, LongType).contains(exprs.head.dataType) => false
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
index 87e7cf8c8af9f..1ad92a3941187 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
@@ -20,6 +20,7 @@ package org.apache.spark.sql
 import org.apache.spark.sql.test.TestSQLContext
 import org.scalatest.BeforeAndAfterAll
 
+import org.apache.spark.sql.execution.GeneratedAggregate
 import org.apache.spark.sql.functions._
 import org.apache.spark.sql.catalyst.errors.TreeNodeException
 import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan
@@ -102,14 +103,99 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll {
       sql("SELECT ABS(2.5)"),
       Row(2.5))
   }
-
+  
   test("aggregation with codegen") {
     val originalValue = conf.codegenEnabled
     setConf(SQLConf.CODEGEN_ENABLED, "true")
-    sql("SELECT key FROM testData GROUP BY key").collect()
+    // Prepare a table that we can group some rows.
+    table("testData")
+      .unionAll(table("testData"))
+      .unionAll(table("testData"))
+      .registerTempTable("testData3x")
+
+    def testCodeGen(sqlText: String, expectedResults: Seq[Row]): Unit = {
+      val df = sql(sqlText)
+      // First, check if we have GeneratedAggregate.
+      var hasGeneratedAgg = false
+      df.queryExecution.executedPlan.foreach {
+        case generatedAgg: GeneratedAggregate => hasGeneratedAgg = true
+        case _ =>
+      }
+      if (!hasGeneratedAgg) {
+        fail(
+          s"""
+             |Codegen is enabled, but query $sqlText does not have GeneratedAggregate in the plan.
+             |${df.queryExecution.simpleString}
+           """.stripMargin)
+      }
+      // Then, check results.
+      checkAnswer(df, expectedResults)
+    }
+
+    // Just to group rows.
+    testCodeGen(
+      "SELECT key FROM testData3x GROUP BY key",
+      (1 to 100).map(Row(_)))
+    // COUNT
+    testCodeGen(
+      "SELECT key, count(value) FROM testData3x GROUP BY key",
+      (1 to 100).map(i => Row(i, 3)))
+    testCodeGen(
+      "SELECT count(key) FROM testData3x",
+      Row(300) :: Nil)
+    // COUNT DISTINCT ON int
+    testCodeGen(
+      "SELECT value, count(distinct key) FROM testData3x GROUP BY value",
+      (1 to 100).map(i => Row(i.toString, 1)))
+    testCodeGen(
+      "SELECT count(distinct key) FROM testData3x",
+      Row(100) :: Nil)
+    // SUM
+     testCodeGen(
+       "SELECT value, sum(key) FROM testData3x GROUP BY value",
+       (1 to 100).map(i => Row(i.toString, 3 * i)))
+     testCodeGen(
+      "SELECT sum(key), SUM(CAST(key as Double)) FROM testData3x",      
+      Row(5050 * 3, 5050 * 3.0) :: Nil)
+    // AVERAGE
+    testCodeGen(
+      "SELECT value, avg(key) FROM testData3x GROUP BY value",
+      (1 to 100).map(i => Row(i.toString, i)))
+    testCodeGen(
+      "SELECT avg(key) FROM testData3x",
+      Row(50.5) :: Nil)
+    // MAX
+    testCodeGen(
+      "SELECT value, max(key) FROM testData3x GROUP BY value",
+      (1 to 100).map(i => Row(i.toString, i)))
+    testCodeGen(
+      "SELECT max(key) FROM testData3x",
+      Row(100) :: Nil)
+    // Some combinations.
+    testCodeGen(
+      """
+        |SELECT
+        |  value,
+        |  sum(key),
+        |  max(key),
+        |  avg(key),
+        |  count(key),
+        |  count(distinct key)
+        |FROM testData3x
+        |GROUP BY value
+      """.stripMargin,
+      (1 to 100).map(i => Row(i.toString, i*3, i, i, 3, 1)))
+    testCodeGen(
+      "SELECT max(key), avg(key), count(key), count(distinct key) FROM testData3x",
+      Row(100, 50.5, 300, 100) :: Nil)
+    // Aggregate with Code generation handling all null values
+    testCodeGen(
+      "SELECT  sum('a'), avg('a'), count(null) FROM testData",
+      Row(0, null, 0) :: Nil)
+      
+    dropTempTable("testData3x")
     setConf(SQLConf.CODEGEN_ENABLED, originalValue.toString)
   }
-
   test("Add Parser of SQL COALESCE()") {
     checkAnswer(
       sql("""SELECT COALESCE(1, 2)"""),

From 891ada5be1e7fdd796380e2626d80843f2ef6017 Mon Sep 17 00:00:00 2001
From: Cheng Lian <lian@databricks.com>
Date: Wed, 8 Apr 2015 18:47:39 -0700
Subject: [PATCH 22/95] [SPARK-6696] [SQL] Adds HiveContext.refreshTable to
 PySpark

<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/5349)
<!-- Reviewable:end -->

Author: Cheng Lian <lian@databricks.com>

Closes #5349 from liancheng/py-refresh-table and squashes the following commits:

004bec0 [Cheng Lian] Adds HiveContext.refreshTable to PySpark
---
 python/pyspark/sql/context.py | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/python/pyspark/sql/context.py b/python/pyspark/sql/context.py
index 93e2d176a5b6f..e8529a8f8e3a4 100644
--- a/python/pyspark/sql/context.py
+++ b/python/pyspark/sql/context.py
@@ -574,6 +574,15 @@ def _ssql_ctx(self):
     def _get_hive_ctx(self):
         return self._jvm.HiveContext(self._jsc.sc())
 
+    def refreshTable(self, tableName):
+        """Invalidate and refresh all the cached the metadata of the given
+        table. For performance reasons, Spark SQL or the external data source
+        library it uses might cache certain metadata about a table, such as the
+        location of blocks. When those change outside of Spark SQL, users should
+        call this function to invalidate the cache.
+        """
+        self._ssql_ctx.refreshTable(tableName)
+
 
 class UDFRegistration(object):
     """Wrapper for user-defined function registration."""

From 1b2aab8d5b9cc2ff702506038bd71aa8debe7ca0 Mon Sep 17 00:00:00 2001
From: Reynold Xin <rxin@databricks.com>
Date: Wed, 8 Apr 2015 20:35:29 -0700
Subject: [PATCH 23/95] [SPARK-6765] Fix test code style for SQL

So we can turn style checker on for test code.

Author: Reynold Xin <rxin@databricks.com>

Closes #5412 from rxin/test-style-sql and squashes the following commits:

9098a31 [Reynold Xin] One more compilation error ...
8c7250a [Reynold Xin] Fix compilation.
82d0944 [Reynold Xin] Indentation.
0b03fbb [Reynold Xin] code review.
f2f4348 [Reynold Xin] oops.
ef4ec48 [Reynold Xin] Hive module.
7e0db5e [Reynold Xin] sql module
04ec7ac [Reynold Xin] catalyst module
---
 .../sql/catalyst/DistributionSuite.scala      |   3 +-
 .../sql/catalyst/analysis/AnalysisSuite.scala |  10 +-
 .../analysis/HiveTypeCoercionSuite.scala      |   8 +-
 .../ExpressionEvaluationSuite.scala           | 134 ++++++++++++------
 .../optimizer/ConstantFoldingSuite.scala      |  51 ++++---
 .../optimizer/FilterPushdownSuite.scala       |   3 +-
 .../catalyst/optimizer/OptimizeInSuite.scala  |   2 +-
 .../spark/sql/catalyst/plans/PlanTest.scala   |   5 +-
 .../sql/catalyst/plans/SameResultSuite.scala  |   2 +-
 .../sql/catalyst/trees/TreeNodeSuite.scala    |   8 +-
 .../apache/spark/sql/CachedTableSuite.scala   |   3 +-
 .../org/apache/spark/sql/DataFrameSuite.scala |   3 +-
 .../org/apache/spark/sql/QueryTest.scala      |   2 +-
 .../org/apache/spark/sql/SQLQuerySuite.scala  |  30 ++--
 .../sql/ScalaReflectionRelationSuite.scala    |   5 +-
 .../spark/sql/UserDefinedTypeSuite.scala      |   2 +-
 .../sql/columnar/ColumnarTestUtils.scala      |   4 +-
 .../NullableColumnAccessorSuite.scala         |   3 +-
 .../columnar/NullableColumnBuilderSuite.scala |   3 +-
 .../TestCompressibleColumnBuilder.scala       |   2 +-
 .../sql/execution/debug/DebuggingSuite.scala  |   2 +-
 .../org/apache/spark/sql/jdbc/JDBCSuite.scala |  98 ++++++-------
 .../org/apache/spark/sql/json/JsonSuite.scala |  17 ++-
 .../spark/sql/parquet/ParquetIOSuite.scala    |   2 +-
 .../sql/parquet/ParquetSchemaSuite.scala      |   2 +
 .../spark/sql/sources/DDLTestSuite.scala      |   8 +-
 .../spark/sql/sources/FilteredScanSuite.scala |   3 +-
 .../spark/sql/sources/PrunedScanSuite.scala   |   5 +-
 .../spark/sql/sources/SaveLoadSuite.scala     |   2 +-
 .../spark/sql/sources/TableScanSuite.scala    |   9 +-
 .../spark/sql/hive/ErrorPositionSuite.scala   |   2 +-
 .../spark/sql/hive/HiveInspectorSuite.scala   |  33 +++--
 .../sql/hive/InsertIntoHiveTableSuite.scala   |  57 ++++++--
 .../spark/sql/hive/StatisticsSuite.scala      |   2 +-
 .../execution/BigDataBenchmarkSuite.scala     |  12 +-
 .../hive/execution/HiveComparisonTest.scala   |  27 ++--
 .../hive/execution/HiveQueryFileTest.scala    |  11 +-
 .../sql/hive/execution/HiveQuerySuite.scala   |  13 +-
 .../hive/execution/HiveResolutionSuite.scala  |   3 +-
 .../sql/hive/execution/HiveSerDeSuite.scala   |   3 +-
 .../execution/HiveTypeCoercionSuite.scala     |   6 +-
 .../sql/hive/execution/HiveUdfSuite.scala     |  16 ++-
 .../sql/hive/execution/PruningSuite.scala     |   2 +-
 .../sql/hive/execution/SQLQuerySuite.scala    |   4 +-
 .../apache/spark/sql/hive/parquetSuites.scala |   7 +-
 45 files changed, 395 insertions(+), 234 deletions(-)

diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/DistributionSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/DistributionSuite.scala
index 46b2250aab231..ea82cd2622de9 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/DistributionSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/DistributionSuite.scala
@@ -30,7 +30,7 @@ class DistributionSuite extends FunSuite {
       inputPartitioning: Partitioning,
       requiredDistribution: Distribution,
       satisfied: Boolean) {
-    if (inputPartitioning.satisfies(requiredDistribution) != satisfied)
+    if (inputPartitioning.satisfies(requiredDistribution) != satisfied) {
       fail(
         s"""
         |== Input Partitioning ==
@@ -40,6 +40,7 @@ class DistributionSuite extends FunSuite {
         |== Does input partitioning satisfy required distribution? ==
         |Expected $satisfied got ${inputPartitioning.satisfies(requiredDistribution)}
         """.stripMargin)
+    }
   }
 
   test("HashPartitioning is the output partitioning") {
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala
index ee7b14c7a157c..6e3d6b9263e86 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala
@@ -27,6 +27,8 @@ import org.apache.spark.sql.types._
 import org.apache.spark.sql.catalyst.dsl.expressions._
 import org.apache.spark.sql.catalyst.dsl.plans._
 
+import scala.collection.immutable
+
 class AnalysisSuite extends FunSuite with BeforeAndAfter {
   val caseSensitiveCatalog = new SimpleCatalog(true)
   val caseInsensitiveCatalog = new SimpleCatalog(false)
@@ -41,10 +43,10 @@ class AnalysisSuite extends FunSuite with BeforeAndAfter {
     }
 
 
-  def caseSensitiveAnalyze(plan: LogicalPlan) =
+  def caseSensitiveAnalyze(plan: LogicalPlan): Unit =
     caseSensitiveAnalyzer.checkAnalysis(caseSensitiveAnalyzer(plan))
 
-  def caseInsensitiveAnalyze(plan: LogicalPlan) =
+  def caseInsensitiveAnalyze(plan: LogicalPlan): Unit =
     caseInsensitiveAnalyzer.checkAnalysis(caseInsensitiveAnalyzer(plan))
 
   val testRelation = LocalRelation(AttributeReference("a", IntegerType, nullable = true)())
@@ -147,7 +149,7 @@ class AnalysisSuite extends FunSuite with BeforeAndAfter {
       name: String,
       plan: LogicalPlan,
       errorMessages: Seq[String],
-      caseSensitive: Boolean = true) = {
+      caseSensitive: Boolean = true): Unit = {
     test(name) {
       val error = intercept[AnalysisException] {
         if(caseSensitive) {
@@ -202,7 +204,7 @@ class AnalysisSuite extends FunSuite with BeforeAndAfter {
 
   case class UnresolvedTestPlan() extends LeafNode {
     override lazy val resolved = false
-    override def output = Nil
+    override def output: Seq[Attribute] = Nil
   }
 
   errorTest(
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercionSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercionSuite.scala
index 70aef1cac421a..fcd745f43cfbf 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercionSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercionSuite.scala
@@ -96,7 +96,9 @@ class HiveTypeCoercionSuite extends PlanTest {
     widenTest(StringType, TimestampType, None)
 
     // ComplexType
-    widenTest(NullType, MapType(IntegerType, StringType, false), Some(MapType(IntegerType, StringType, false)))
+    widenTest(NullType,
+      MapType(IntegerType, StringType, false),
+      Some(MapType(IntegerType, StringType, false)))
     widenTest(NullType, StructType(Seq()), Some(StructType(Seq())))
     widenTest(StringType, MapType(IntegerType, StringType, true), None)
     widenTest(ArrayType(IntegerType), StructType(Seq()), None)
@@ -113,7 +115,9 @@ class HiveTypeCoercionSuite extends PlanTest {
     // Remove superflous boolean -> boolean casts.
     ruleTest(Cast(Literal(true), BooleanType), Literal(true))
     // Stringify boolean when casting to string.
-    ruleTest(Cast(Literal(false), StringType), If(Literal(false), Literal("true"), Literal("false")))
+    ruleTest(
+      Cast(Literal(false), StringType),
+      If(Literal(false), Literal("true"), Literal("false")))
   }
 
   test("coalesce casts") {
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala
index 3dbefa40d2808..d2b1090a0cdd5 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala
@@ -82,10 +82,13 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
     assert(BitwiseNot(1.toByte).eval(EmptyRow).isInstanceOf[Byte])
   }
 
+  // scalastyle:off
   /**
    * Checks for three-valued-logic.  Based on:
    * http://en.wikipedia.org/wiki/Null_(SQL)#Comparisons_with_NULL_and_the_three-valued_logic_.283VL.29
-   * I.e. in flat cpo "False -> Unknown -> True", OR is lowest upper bound, AND is greatest lower bound.
+   * I.e. in flat cpo "False -> Unknown -> True",
+   *   OR is lowest upper bound,
+   *   AND is greatest lower bound.
    * p       q       p OR q  p AND q  p = q
    * True    True    True    True     True
    * True    False   True    False    False
@@ -102,7 +105,7 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
    * False   True
    * Unknown Unknown
    */
-
+  // scalastyle:on
   val notTrueTable =
     (true, false) ::
     (false, true) ::
@@ -165,7 +168,9 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
     checkEvaluation(In(Literal(1), Seq(Literal(1), Literal(2))), true)
     checkEvaluation(In(Literal(2), Seq(Literal(1), Literal(2))), true)
     checkEvaluation(In(Literal(3), Seq(Literal(1), Literal(2))), false)
-    checkEvaluation(In(Literal(1), Seq(Literal(1), Literal(2))) && In(Literal(2), Seq(Literal(1), Literal(2))), true)
+    checkEvaluation(
+      In(Literal(1), Seq(Literal(1), Literal(2))) && In(Literal(2), Seq(Literal(1), Literal(2))),
+      true)
   }
 
   test("Divide") {
@@ -180,7 +185,8 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
     checkEvaluation(Divide(Literal.create(null, IntegerType), Literal(0)), null)
     checkEvaluation(Divide(Literal.create(null, DoubleType), Literal(0.0)), null)
     checkEvaluation(Divide(Literal.create(null, IntegerType), Literal(1)), null)
-    checkEvaluation(Divide(Literal.create(null, IntegerType), Literal.create(null, IntegerType)), null)
+    checkEvaluation(Divide(Literal.create(null, IntegerType), Literal.create(null, IntegerType)),
+      null)
   }
 
   test("Remainder") {
@@ -195,7 +201,8 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
     checkEvaluation(Remainder(Literal.create(null, IntegerType), Literal(0)), null)
     checkEvaluation(Remainder(Literal.create(null, DoubleType), Literal(0.0)), null)
     checkEvaluation(Remainder(Literal.create(null, IntegerType), Literal(1)), null)
-    checkEvaluation(Remainder(Literal.create(null, IntegerType), Literal.create(null, IntegerType)), null)
+    checkEvaluation(Remainder(Literal.create(null, IntegerType), Literal.create(null, IntegerType)),
+      null)
   }
 
   test("INSET") {
@@ -264,7 +271,8 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
     checkEvaluation("ab" like regEx, true, new GenericRow(Array[Any]("a%b")))
     checkEvaluation("a\nb" like regEx, true, new GenericRow(Array[Any]("a%b")))
 
-    checkEvaluation(Literal.create(null, StringType) like regEx, null, new GenericRow(Array[Any]("bc%")))
+    checkEvaluation(Literal.create(null, StringType) like regEx, null,
+      new GenericRow(Array[Any]("bc%")))
   }
 
   test("RLIKE literal Regular Expression") {
@@ -507,8 +515,10 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
   }
 
   test("array casting") {
-    val array = Literal.create(Seq("123", "abc", "", null), ArrayType(StringType, containsNull = true))
-    val array_notNull = Literal.create(Seq("123", "abc", ""), ArrayType(StringType, containsNull = false))
+    val array = Literal.create(Seq("123", "abc", "", null),
+      ArrayType(StringType, containsNull = true))
+    val array_notNull = Literal.create(Seq("123", "abc", ""),
+      ArrayType(StringType, containsNull = false))
 
     {
       val cast = Cast(array, ArrayType(IntegerType, containsNull = true))
@@ -765,7 +775,8 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
     checkEvaluation(Coalesce(Literal.create(null, StringType) :: Nil), null, row)
     checkEvaluation(Coalesce(Literal.create(null, StringType) :: c1 :: c2 :: Nil), "^Ba*n", row)
 
-    checkEvaluation(If(c3, Literal.create("a", StringType), Literal.create("b", StringType)), "a", row)
+    checkEvaluation(
+      If(c3, Literal.create("a", StringType), Literal.create("b", StringType)), "a", row)
     checkEvaluation(If(c3, c1, c2), "^Ba*n", row)
     checkEvaluation(If(c4, c2, c1), "^Ba*n", row)
     checkEvaluation(If(Literal.create(null, BooleanType), c2, c1), "^Ba*n", row)
@@ -842,18 +853,20 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
     checkEvaluation(GetItem(BoundReference(3, typeMap, true),
       Literal("aa")), "bb", row)
     checkEvaluation(GetItem(Literal.create(null, typeMap), Literal("aa")), null, row)
-    checkEvaluation(GetItem(Literal.create(null, typeMap), Literal.create(null, StringType)), null, row)
+    checkEvaluation(
+      GetItem(Literal.create(null, typeMap), Literal.create(null, StringType)), null, row)
     checkEvaluation(GetItem(BoundReference(3, typeMap, true),
       Literal.create(null, StringType)), null, row)
 
     checkEvaluation(GetItem(BoundReference(4, typeArray, true),
       Literal(1)), "bb", row)
     checkEvaluation(GetItem(Literal.create(null, typeArray), Literal(1)), null, row)
-    checkEvaluation(GetItem(Literal.create(null, typeArray), Literal.create(null, IntegerType)), null, row)
+    checkEvaluation(
+      GetItem(Literal.create(null, typeArray), Literal.create(null, IntegerType)), null, row)
     checkEvaluation(GetItem(BoundReference(4, typeArray, true),
       Literal.create(null, IntegerType)), null, row)
 
-    def quickBuildGetField(expr: Expression, fieldName: String) = {
+    def quickBuildGetField(expr: Expression, fieldName: String): StructGetField = {
       expr.dataType match {
         case StructType(fields) =>
           val field = fields.find(_.name == fieldName).get
@@ -861,7 +874,9 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
       }
     }
 
-    def quickResolve(u: UnresolvedGetField) = quickBuildGetField(u.child, u.fieldName)
+    def quickResolve(u: UnresolvedGetField): StructGetField = {
+      quickBuildGetField(u.child, u.fieldName)
+    }
 
     checkEvaluation(quickBuildGetField(BoundReference(2, typeS, nullable = true), "a"), "aa", row)
     checkEvaluation(quickBuildGetField(Literal.create(null, typeS), "a"), null, row)
@@ -872,7 +887,8 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
     )
 
     assert(quickBuildGetField(BoundReference(2,typeS, nullable = true), "a").nullable === true)
-    assert(quickBuildGetField(BoundReference(2, typeS_notNullable, nullable = false), "a").nullable === false)
+    assert(quickBuildGetField(BoundReference(2, typeS_notNullable, nullable = false), "a").nullable
+      === false)
 
     assert(quickBuildGetField(Literal.create(null, typeS), "a").nullable === true)
     assert(quickBuildGetField(Literal.create(null, typeS_notNullable), "a").nullable === true)
@@ -896,7 +912,8 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
     checkEvaluation(Add(c1, c2), 3, row)
     checkEvaluation(Add(c1, Literal.create(null, IntegerType)), null, row)
     checkEvaluation(Add(Literal.create(null, IntegerType), c2), null, row)
-    checkEvaluation(Add(Literal.create(null, IntegerType), Literal.create(null, IntegerType)), null, row)
+    checkEvaluation(
+      Add(Literal.create(null, IntegerType), Literal.create(null, IntegerType)), null, row)
 
     checkEvaluation(-c1, -1, row)
     checkEvaluation(c1 + c2, 3, row)
@@ -919,7 +936,8 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
     checkEvaluation(Add(c1, c2), 3.1, row)
     checkEvaluation(Add(c1, Literal.create(null, DoubleType)), null, row)
     checkEvaluation(Add(Literal.create(null, DoubleType), c2), null, row)
-    checkEvaluation(Add(Literal.create(null, DoubleType), Literal.create(null, DoubleType)), null, row)
+    checkEvaluation(
+      Add(Literal.create(null, DoubleType), Literal.create(null, DoubleType)), null, row)
 
     checkEvaluation(-c1, -1.1, row)
     checkEvaluation(c1 + c2, 3.1, row)
@@ -942,7 +960,8 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
     checkEvaluation(LessThan(c1, c2), true, row)
     checkEvaluation(LessThan(c1, Literal.create(null, IntegerType)), null, row)
     checkEvaluation(LessThan(Literal.create(null, IntegerType), c2), null, row)
-    checkEvaluation(LessThan(Literal.create(null, IntegerType), Literal.create(null, IntegerType)), null, row)
+    checkEvaluation(
+      LessThan(Literal.create(null, IntegerType), Literal.create(null, IntegerType)), null, row)
 
     checkEvaluation(c1 < c2, true, row)
     checkEvaluation(c1 <= c2, true, row)
@@ -985,54 +1004,84 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
     val s = 'a.string.at(0)
 
     // substring from zero position with less-than-full length
-    checkEvaluation(Substring(s, Literal.create(0, IntegerType), Literal.create(2, IntegerType)), "ex", row)
-    checkEvaluation(Substring(s, Literal.create(1, IntegerType), Literal.create(2, IntegerType)), "ex", row)
+    checkEvaluation(
+      Substring(s, Literal.create(0, IntegerType), Literal.create(2, IntegerType)), "ex", row)
+    checkEvaluation(
+      Substring(s, Literal.create(1, IntegerType), Literal.create(2, IntegerType)), "ex", row)
 
     // substring from zero position with full length
-    checkEvaluation(Substring(s, Literal.create(0, IntegerType), Literal.create(7, IntegerType)), "example", row)
-    checkEvaluation(Substring(s, Literal.create(1, IntegerType), Literal.create(7, IntegerType)), "example", row)
+    checkEvaluation(
+      Substring(s, Literal.create(0, IntegerType), Literal.create(7, IntegerType)), "example", row)
+    checkEvaluation(
+      Substring(s, Literal.create(1, IntegerType), Literal.create(7, IntegerType)), "example", row)
 
     // substring from zero position with greater-than-full length
-    checkEvaluation(Substring(s, Literal.create(0, IntegerType), Literal.create(100, IntegerType)), "example", row)
-    checkEvaluation(Substring(s, Literal.create(1, IntegerType), Literal.create(100, IntegerType)), "example", row)
+    checkEvaluation(Substring(s, Literal.create(0, IntegerType), Literal.create(100, IntegerType)),
+      "example", row)
+    checkEvaluation(Substring(s, Literal.create(1, IntegerType), Literal.create(100, IntegerType)),
+      "example", row)
 
     // substring from nonzero position with less-than-full length
-    checkEvaluation(Substring(s, Literal.create(2, IntegerType), Literal.create(2, IntegerType)), "xa", row)
+    checkEvaluation(Substring(s, Literal.create(2, IntegerType), Literal.create(2, IntegerType)),
+      "xa", row)
 
     // substring from nonzero position with full length
-    checkEvaluation(Substring(s, Literal.create(2, IntegerType), Literal.create(6, IntegerType)), "xample", row)
+    checkEvaluation(Substring(s, Literal.create(2, IntegerType), Literal.create(6, IntegerType)),
+      "xample", row)
 
     // substring from nonzero position with greater-than-full length
-    checkEvaluation(Substring(s, Literal.create(2, IntegerType), Literal.create(100, IntegerType)), "xample", row)
+    checkEvaluation(Substring(s, Literal.create(2, IntegerType), Literal.create(100, IntegerType)),
+      "xample", row)
 
     // zero-length substring (within string bounds)
-    checkEvaluation(Substring(s, Literal.create(0, IntegerType), Literal.create(0, IntegerType)), "", row)
+    checkEvaluation(Substring(s, Literal.create(0, IntegerType), Literal.create(0, IntegerType)),
+      "", row)
 
     // zero-length substring (beyond string bounds)
-    checkEvaluation(Substring(s, Literal.create(100, IntegerType), Literal.create(4, IntegerType)), "", row)
+    checkEvaluation(Substring(s, Literal.create(100, IntegerType), Literal.create(4, IntegerType)),
+      "", row)
 
     // substring(null, _, _) -> null
-    checkEvaluation(Substring(s, Literal.create(100, IntegerType), Literal.create(4, IntegerType)), null, new GenericRow(Array[Any](null)))
+    checkEvaluation(Substring(s, Literal.create(100, IntegerType), Literal.create(4, IntegerType)),
+      null, new GenericRow(Array[Any](null)))
 
     // substring(_, null, _) -> null
-    checkEvaluation(Substring(s, Literal.create(null, IntegerType), Literal.create(4, IntegerType)), null, row)
+    checkEvaluation(Substring(s, Literal.create(null, IntegerType), Literal.create(4, IntegerType)),
+      null, row)
 
     // substring(_, _, null) -> null
-    checkEvaluation(Substring(s, Literal.create(100, IntegerType), Literal.create(null, IntegerType)), null, row)
+    checkEvaluation(
+      Substring(s, Literal.create(100, IntegerType), Literal.create(null, IntegerType)),
+      null,
+      row)
 
     // 2-arg substring from zero position
-    checkEvaluation(Substring(s, Literal.create(0, IntegerType), Literal.create(Integer.MAX_VALUE, IntegerType)), "example", row)
-    checkEvaluation(Substring(s, Literal.create(1, IntegerType), Literal.create(Integer.MAX_VALUE, IntegerType)), "example", row)
+    checkEvaluation(
+      Substring(s, Literal.create(0, IntegerType), Literal.create(Integer.MAX_VALUE, IntegerType)),
+      "example",
+      row)
+    checkEvaluation(
+      Substring(s, Literal.create(1, IntegerType), Literal.create(Integer.MAX_VALUE, IntegerType)),
+      "example",
+      row)
 
     // 2-arg substring from nonzero position
-    checkEvaluation(Substring(s, Literal.create(2, IntegerType), Literal.create(Integer.MAX_VALUE, IntegerType)), "xample", row)
+    checkEvaluation(
+      Substring(s, Literal.create(2, IntegerType), Literal.create(Integer.MAX_VALUE, IntegerType)),
+      "xample",
+      row)
 
     val s_notNull = 'a.string.notNull.at(0)
 
-    assert(Substring(s, Literal.create(0, IntegerType), Literal.create(2, IntegerType)).nullable === true)
-    assert(Substring(s_notNull, Literal.create(0, IntegerType), Literal.create(2, IntegerType)).nullable === false)
-    assert(Substring(s_notNull, Literal.create(null, IntegerType), Literal.create(2, IntegerType)).nullable === true)
-    assert(Substring(s_notNull, Literal.create(0, IntegerType), Literal.create(null, IntegerType)).nullable === true)
+    assert(Substring(s, Literal.create(0, IntegerType), Literal.create(2, IntegerType)).nullable
+      === true)
+    assert(
+      Substring(s_notNull, Literal.create(0, IntegerType), Literal.create(2, IntegerType)).nullable
+        === false)
+    assert(Substring(s_notNull,
+      Literal.create(null, IntegerType), Literal.create(2, IntegerType)).nullable === true)
+    assert(Substring(s_notNull,
+      Literal.create(0, IntegerType), Literal.create(null, IntegerType)).nullable === true)
 
     checkEvaluation(s.substr(0, 2), "ex", row)
     checkEvaluation(s.substr(0), "example", row)
@@ -1065,17 +1114,20 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
     checkEvaluation(BitwiseAnd(c1, c4), null, row)
     checkEvaluation(BitwiseAnd(c1, c2), 0, row)
     checkEvaluation(BitwiseAnd(c1, Literal.create(null, IntegerType)), null, row)
-    checkEvaluation(BitwiseAnd(Literal.create(null, IntegerType), Literal.create(null, IntegerType)), null, row)
+    checkEvaluation(
+      BitwiseAnd(Literal.create(null, IntegerType), Literal.create(null, IntegerType)), null, row)
 
     checkEvaluation(BitwiseOr(c1, c4), null, row)
     checkEvaluation(BitwiseOr(c1, c2), 3, row)
     checkEvaluation(BitwiseOr(c1, Literal.create(null, IntegerType)), null, row)
-    checkEvaluation(BitwiseOr(Literal.create(null, IntegerType), Literal.create(null, IntegerType)), null, row)
+    checkEvaluation(
+      BitwiseOr(Literal.create(null, IntegerType), Literal.create(null, IntegerType)), null, row)
 
     checkEvaluation(BitwiseXor(c1, c4), null, row)
     checkEvaluation(BitwiseXor(c1, c2), 3, row)
     checkEvaluation(BitwiseXor(c1, Literal.create(null, IntegerType)), null, row)
-    checkEvaluation(BitwiseXor(Literal.create(null, IntegerType), Literal.create(null, IntegerType)), null, row)
+    checkEvaluation(
+      BitwiseXor(Literal.create(null, IntegerType), Literal.create(null, IntegerType)), null, row)
 
     checkEvaluation(BitwiseNot(c4), null, row)
     checkEvaluation(BitwiseNot(c1), -2, row)
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConstantFoldingSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConstantFoldingSuite.scala
index a0efe9e2e7f6b..4396bd0dda9a9 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConstantFoldingSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConstantFoldingSuite.scala
@@ -176,40 +176,39 @@ class ConstantFoldingSuite extends PlanTest {
   }
 
   test("Constant folding test: expressions have null literals") {
-    val originalQuery =
-      testRelation
-        .select(
-          IsNull(Literal(null)) as 'c1,
-          IsNotNull(Literal(null)) as 'c2,
+    val originalQuery = testRelation.select(
+      IsNull(Literal(null)) as 'c1,
+      IsNotNull(Literal(null)) as 'c2,
 
-          GetItem(Literal.create(null, ArrayType(IntegerType)), 1) as 'c3,
-          GetItem(Literal.create(Seq(1), ArrayType(IntegerType)), Literal.create(null, IntegerType)) as 'c4,
-          UnresolvedGetField(
-            Literal.create(null, StructType(Seq(StructField("a", IntegerType, true)))),
-            "a") as 'c5,
+      GetItem(Literal.create(null, ArrayType(IntegerType)), 1) as 'c3,
+      GetItem(
+        Literal.create(Seq(1), ArrayType(IntegerType)), Literal.create(null, IntegerType)) as 'c4,
+      UnresolvedGetField(
+        Literal.create(null, StructType(Seq(StructField("a", IntegerType, true)))),
+        "a") as 'c5,
 
-          UnaryMinus(Literal.create(null, IntegerType)) as 'c6,
-          Cast(Literal(null), IntegerType) as 'c7,
-          Not(Literal.create(null, BooleanType)) as 'c8,
+      UnaryMinus(Literal.create(null, IntegerType)) as 'c6,
+      Cast(Literal(null), IntegerType) as 'c7,
+      Not(Literal.create(null, BooleanType)) as 'c8,
 
-          Add(Literal.create(null, IntegerType), 1) as 'c9,
-          Add(1, Literal.create(null, IntegerType)) as 'c10,
+      Add(Literal.create(null, IntegerType), 1) as 'c9,
+      Add(1, Literal.create(null, IntegerType)) as 'c10,
 
-          EqualTo(Literal.create(null, IntegerType), 1) as 'c11,
-          EqualTo(1, Literal.create(null, IntegerType)) as 'c12,
+      EqualTo(Literal.create(null, IntegerType), 1) as 'c11,
+      EqualTo(1, Literal.create(null, IntegerType)) as 'c12,
 
-          Like(Literal.create(null, StringType), "abc") as 'c13,
-          Like("abc", Literal.create(null, StringType)) as 'c14,
+      Like(Literal.create(null, StringType), "abc") as 'c13,
+      Like("abc", Literal.create(null, StringType)) as 'c14,
 
-          Upper(Literal.create(null, StringType)) as 'c15,
+      Upper(Literal.create(null, StringType)) as 'c15,
 
-          Substring(Literal.create(null, StringType), 0, 1) as 'c16,
-          Substring("abc", Literal.create(null, IntegerType), 1) as 'c17,
-          Substring("abc", 0, Literal.create(null, IntegerType)) as 'c18,
+      Substring(Literal.create(null, StringType), 0, 1) as 'c16,
+      Substring("abc", Literal.create(null, IntegerType), 1) as 'c17,
+      Substring("abc", 0, Literal.create(null, IntegerType)) as 'c18,
 
-          Contains(Literal.create(null, StringType), "abc") as 'c19,
-          Contains("abc", Literal.create(null, StringType)) as 'c20
-        )
+      Contains(Literal.create(null, StringType), "abc") as 'c19,
+      Contains("abc", Literal.create(null, StringType)) as 'c20
+    )
 
     val optimized = Optimize(originalQuery.analyze)
 
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/FilterPushdownSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/FilterPushdownSuite.scala
index 55c6766520a1e..1448098c770aa 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/FilterPushdownSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/FilterPushdownSuite.scala
@@ -432,7 +432,8 @@ class FilterPushdownSuite extends PlanTest {
 
     val originalQuery = {
       z.join(x.join(y))
-        .where(("x.b".attr === "y.b".attr) && ("x.a".attr === 1) && ("z.a".attr >= 3) && ("z.a".attr === "x.b".attr))
+        .where(("x.b".attr === "y.b".attr) && ("x.a".attr === 1) &&
+          ("z.a".attr >= 3) && ("z.a".attr === "x.b".attr))
     }
 
     val optimized = Optimize(originalQuery.analyze)
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/OptimizeInSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/OptimizeInSuite.scala
index 233e329cb2038..966bc9ada1e6e 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/OptimizeInSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/OptimizeInSuite.scala
@@ -52,7 +52,7 @@ class OptimizeInSuite extends PlanTest {
     val optimized = Optimize(originalQuery.analyze)
     val correctAnswer =
       testRelation
-        .where(InSet(UnresolvedAttribute("a"), HashSet[Any]()+1+2))
+        .where(InSet(UnresolvedAttribute("a"), HashSet[Any]() + 1 + 2))
         .analyze
 
     comparePlans(optimized, correctAnswer)
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/plans/PlanTest.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/plans/PlanTest.scala
index 129d091ca03e3..e7cafcc96de87 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/plans/PlanTest.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/plans/PlanTest.scala
@@ -45,12 +45,13 @@ class PlanTest extends FunSuite {
   protected def comparePlans(plan1: LogicalPlan, plan2: LogicalPlan) {
     val normalized1 = normalizeExprIds(plan1)
     val normalized2 = normalizeExprIds(plan2)
-    if (normalized1 != normalized2)
+    if (normalized1 != normalized2) {
       fail(
         s"""
           |== FAIL: Plans do not match ===
           |${sideBySide(normalized1.treeString, normalized2.treeString).mkString("\n")}
-        """.stripMargin)
+         """.stripMargin)
+    }
   }
 
   /** Fails the test if the two expressions do not match */
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/plans/SameResultSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/plans/SameResultSuite.scala
index 11e6831b24768..1273921f6394c 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/plans/SameResultSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/plans/SameResultSuite.scala
@@ -32,7 +32,7 @@ class SameResultSuite extends FunSuite {
   val testRelation = LocalRelation('a.int, 'b.int, 'c.int)
   val testRelation2 = LocalRelation('a.int, 'b.int, 'c.int)
 
-  def assertSameResult(a: LogicalPlan, b: LogicalPlan, result: Boolean = true) = {
+  def assertSameResult(a: LogicalPlan, b: LogicalPlan, result: Boolean = true): Unit = {
     val aAnalyzed = a.analyze
     val bAnalyzed = b.analyze
 
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala
index 274f3ede0045c..4eb8708335dcf 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala
@@ -25,12 +25,12 @@ import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.types.{StringType, NullType}
 
 case class Dummy(optKey: Option[Expression]) extends Expression {
-  def children = optKey.toSeq
-  def nullable = true
-  def dataType = NullType
+  def children: Seq[Expression] = optKey.toSeq
+  def nullable: Boolean = true
+  def dataType: NullType = NullType
   override lazy val resolved = true
   type EvaluatedType = Any
-  def eval(input: Row) = null.asInstanceOf[Any]
+  def eval(input: Row): Any = null.asInstanceOf[Any]
 }
 
 class TreeNodeSuite extends FunSuite {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala
index c240f2be955ca..f7b5f08beb92f 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala
@@ -92,7 +92,8 @@ class CachedTableSuite extends QueryTest {
 
   test("too big for memory") {
     val data = "*" * 10000
-    sparkContext.parallelize(1 to 200000, 1).map(_ => BigData(data)).toDF().registerTempTable("bigData")
+    sparkContext.parallelize(1 to 200000, 1).map(_ => BigData(data)).toDF()
+      .registerTempTable("bigData")
     table("bigData").persist(StorageLevel.MEMORY_AND_DISK)
     assert(table("bigData").count() === 200000L)
     table("bigData").unpersist(blocking = true)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
index 1db0cf7daac03..f5df8c6a59f10 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
@@ -329,8 +329,9 @@ class DataFrameSuite extends QueryTest {
     checkAnswer(
       decimalData.agg(avg('a cast DecimalType(10, 2))),
       Row(new java.math.BigDecimal(2.0)))
+    // non-partial
     checkAnswer(
-      decimalData.agg(avg('a cast DecimalType(10, 2)), sumDistinct('a cast DecimalType(10, 2))), // non-partial
+      decimalData.agg(avg('a cast DecimalType(10, 2)), sumDistinct('a cast DecimalType(10, 2))),
       Row(new java.math.BigDecimal(2.0), new java.math.BigDecimal(6)) :: Nil)
   }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala b/sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala
index 9b4dd6c620fec..9a81fc5d72819 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala
@@ -67,7 +67,7 @@ class QueryTest extends PlanTest {
     checkAnswer(df, Seq(expectedAnswer))
   }
 
-  def sqlTest(sqlString: String, expectedAnswer: Seq[Row])(implicit sqlContext: SQLContext): Unit = {
+  def sqlTest(sqlString: String, expectedAnswer: Seq[Row])(implicit sqlContext: SQLContext) {
     test(sqlString) {
       checkAnswer(sqlContext.sql(sqlString), expectedAnswer)
     }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
index 1ad92a3941187..1392b4819131b 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
@@ -268,7 +268,10 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll {
       Row(java.sql.Timestamp.valueOf("1969-12-31 16:00:00.002")))
 
     checkAnswer(sql(
-      "SELECT time FROM timestamps WHERE time IN ('1969-12-31 16:00:00.001','1969-12-31 16:00:00.002')"),
+      """
+        |SELECT time FROM timestamps
+        |WHERE time IN ('1969-12-31 16:00:00.001','1969-12-31 16:00:00.002')
+      """.stripMargin),
       Seq(Row(java.sql.Timestamp.valueOf("1969-12-31 16:00:00.001")),
         Row(java.sql.Timestamp.valueOf("1969-12-31 16:00:00.002"))))
 
@@ -334,7 +337,7 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll {
       Row("1"))
   }
 
-  def sortTest() = {
+  def sortTest(): Unit = {
     checkAnswer(
       sql("SELECT * FROM testData2 ORDER BY a ASC, b ASC"),
       Seq(Row(1,1), Row(1,2), Row(2,1), Row(2,2), Row(3,1), Row(3,2)))
@@ -413,7 +416,10 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll {
 
   test("from follow multiple brackets") {
     checkAnswer(sql(
-      "select key from ((select * from testData limit 1) union all (select * from testData limit 1)) x limit 1"),
+      """
+        |select key from ((select * from testData limit 1)
+        |  union all (select * from testData limit 1)) x limit 1
+      """.stripMargin),
       Row(1)
     )
 
@@ -423,7 +429,11 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll {
     )
 
     checkAnswer(sql(
-      "select key from (select * from testData limit 1 union all select * from testData limit 1) x limit 1"),
+      """
+        |select key from
+        |  (select * from testData limit 1 union all select * from testData limit 1) x
+        |  limit 1
+      """.stripMargin),
       Row(1)
     )
   }
@@ -470,7 +480,10 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll {
       Seq(Row(1, 0), Row(2, 1)))
 
     checkAnswer(
-      sql("SELECT COUNT(a), COUNT(b), COUNT(1), COUNT(DISTINCT a), COUNT(DISTINCT b) FROM testData3"),
+      sql(
+        """
+          |SELECT COUNT(a), COUNT(b), COUNT(1), COUNT(DISTINCT a), COUNT(DISTINCT b) FROM testData3
+        """.stripMargin),
       Row(2, 1, 2, 2, 1))
   }
 
@@ -1083,7 +1096,8 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll {
   }
 
   test("SPARK-3483 Special chars in column names") {
-    val data = sparkContext.parallelize(Seq("""{"key?number1": "value1", "key.number2": "value2"}"""))
+    val data = sparkContext.parallelize(
+      Seq("""{"key?number1": "value1", "key.number2": "value2"}"""))
     jsonRDD(data).registerTempTable("records")
     sql("SELECT `key?number1` FROM records")
   }
@@ -1168,8 +1182,8 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll {
   }
 
   test("SPARK-6145: ORDER BY test for nested fields") {
-    jsonRDD(sparkContext.makeRDD(
-      """{"a": {"b": 1, "a": {"a": 1}}, "c": [{"d": 1}]}""" :: Nil)).registerTempTable("nestedOrder")
+    jsonRDD(sparkContext.makeRDD("""{"a": {"b": 1, "a": {"a": 1}}, "c": [{"d": 1}]}""" :: Nil))
+      .registerTempTable("nestedOrder")
 
     checkAnswer(sql("SELECT 1 FROM nestedOrder ORDER BY a.b"), Row(1))
     checkAnswer(sql("SELECT a.b FROM nestedOrder ORDER BY a.b"), Row(1))
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/ScalaReflectionRelationSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/ScalaReflectionRelationSuite.scala
index 17e923ca48502..3fa00fd9d0ccb 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/ScalaReflectionRelationSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/ScalaReflectionRelationSuite.scala
@@ -80,7 +80,7 @@ class ScalaReflectionRelationSuite extends FunSuite {
 
   test("query case class RDD") {
     val data = ReflectData("a", 1, 1L, 1.toFloat, 1.toDouble, 1.toShort, 1.toByte, true,
-                           new java.math.BigDecimal(1), new Date(12345), new Timestamp(12345), Seq(1,2,3))
+      new java.math.BigDecimal(1), new Date(12345), new Timestamp(12345), Seq(1,2,3))
     val rdd = sparkContext.parallelize(data :: Nil)
     rdd.toDF().registerTempTable("reflectData")
 
@@ -103,7 +103,8 @@ class ScalaReflectionRelationSuite extends FunSuite {
     val rdd = sparkContext.parallelize(data :: Nil)
     rdd.toDF().registerTempTable("reflectOptionalData")
 
-    assert(sql("SELECT * FROM reflectOptionalData").collect().head === Row.fromSeq(Seq.fill(7)(null)))
+    assert(sql("SELECT * FROM reflectOptionalData").collect().head ===
+      Row.fromSeq(Seq.fill(7)(null)))
   }
 
   // Equality is broken for Arrays, so we test that separately.
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala
index fe618e0e8e767..902da5c3ba6d6 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala
@@ -63,7 +63,7 @@ private[sql] class MyDenseVectorUDT extends UserDefinedType[MyDenseVector] {
     }
   }
 
-  override def userClass = classOf[MyDenseVector]
+  override def userClass: Class[MyDenseVector] = classOf[MyDenseVector]
 
   private[spark] override def asNullable: MyDenseVectorUDT = this
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnarTestUtils.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnarTestUtils.scala
index c7a40845db16c..b301818a008e7 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnarTestUtils.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnarTestUtils.scala
@@ -27,7 +27,7 @@ import org.apache.spark.sql.catalyst.expressions.GenericMutableRow
 import org.apache.spark.sql.types.{Decimal, DataType, NativeType}
 
 object ColumnarTestUtils {
-  def makeNullRow(length: Int) = {
+  def makeNullRow(length: Int): GenericMutableRow = {
     val row = new GenericMutableRow(length)
     (0 until length).foreach(row.setNullAt)
     row
@@ -93,7 +93,7 @@ object ColumnarTestUtils {
 
   def makeUniqueValuesAndSingleValueRows[T <: NativeType](
       columnType: NativeColumnType[T],
-      count: Int) = {
+      count: Int): (Seq[T#JvmType], Seq[GenericMutableRow]) = {
 
     val values = makeUniqueRandomValues(columnType, count)
     val rows = values.map { value =>
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnAccessorSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnAccessorSuite.scala
index bb305355276bf..a0702144f942c 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnAccessorSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnAccessorSuite.scala
@@ -31,7 +31,8 @@ class TestNullableColumnAccessor[T <: DataType, JvmType](
   with NullableColumnAccessor
 
 object TestNullableColumnAccessor {
-  def apply[T <: DataType, JvmType](buffer: ByteBuffer, columnType: ColumnType[T, JvmType]) = {
+  def apply[T <: DataType, JvmType](buffer: ByteBuffer, columnType: ColumnType[T, JvmType])
+    : TestNullableColumnAccessor[T, JvmType] = {
     // Skips the column type ID
     buffer.getInt()
     new TestNullableColumnAccessor(buffer, columnType)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnBuilderSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnBuilderSuite.scala
index 75a47498683f4..3a5605d2335d7 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnBuilderSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnBuilderSuite.scala
@@ -27,7 +27,8 @@ class TestNullableColumnBuilder[T <: DataType, JvmType](columnType: ColumnType[T
   with NullableColumnBuilder
 
 object TestNullableColumnBuilder {
-  def apply[T <: DataType, JvmType](columnType: ColumnType[T, JvmType], initialSize: Int = 0) = {
+  def apply[T <: DataType, JvmType](columnType: ColumnType[T, JvmType], initialSize: Int = 0)
+    : TestNullableColumnBuilder[T, JvmType] = {
     val builder = new TestNullableColumnBuilder(columnType)
     builder.initialize(initialSize)
     builder
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/TestCompressibleColumnBuilder.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/TestCompressibleColumnBuilder.scala
index 0b18b4119268f..fc8ff3b41d0e6 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/TestCompressibleColumnBuilder.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/TestCompressibleColumnBuilder.scala
@@ -35,7 +35,7 @@ object TestCompressibleColumnBuilder {
   def apply[T <: NativeType](
       columnStats: ColumnStats,
       columnType: NativeColumnType[T],
-      scheme: CompressionScheme) = {
+      scheme: CompressionScheme): TestCompressibleColumnBuilder[T] = {
 
     val builder = new TestCompressibleColumnBuilder(columnStats, columnType, Seq(scheme))
     builder.initialize(0, "", useCompression = true)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/debug/DebuggingSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/debug/DebuggingSuite.scala
index 4e9472c60249e..358d8cf06e463 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/debug/DebuggingSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/debug/DebuggingSuite.scala
@@ -30,4 +30,4 @@ class DebuggingSuite extends FunSuite {
   test("DataFrame.typeCheck()") {
     testData.typeCheck()
   }
-}
\ No newline at end of file
+}
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala
index 592ed4b23b7d3..3596b183d4328 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala
@@ -45,10 +45,12 @@ class JDBCSuite extends FunSuite with BeforeAndAfter {
 
     conn = DriverManager.getConnection(url, properties)
     conn.prepareStatement("create schema test").executeUpdate()
-    conn.prepareStatement("create table test.people (name TEXT(32) NOT NULL, theid INTEGER NOT NULL)").executeUpdate()
+    conn.prepareStatement(
+      "create table test.people (name TEXT(32) NOT NULL, theid INTEGER NOT NULL)").executeUpdate()
     conn.prepareStatement("insert into test.people values ('fred', 1)").executeUpdate()
     conn.prepareStatement("insert into test.people values ('mary', 2)").executeUpdate()
-    conn.prepareStatement("insert into test.people values ('joe ''foo'' \"bar\"', 3)").executeUpdate()
+    conn.prepareStatement(
+      "insert into test.people values ('joe ''foo'' \"bar\"', 3)").executeUpdate()
     conn.commit()
 
     sql(
@@ -132,25 +134,25 @@ class JDBCSuite extends FunSuite with BeforeAndAfter {
   }
 
   test("SELECT *") {
-    assert(sql("SELECT * FROM foobar").collect().size == 3)
+    assert(sql("SELECT * FROM foobar").collect().size === 3)
   }
 
   test("SELECT * WHERE (simple predicates)") {
-    assert(sql("SELECT * FROM foobar WHERE THEID < 1").collect().size == 0)
-    assert(sql("SELECT * FROM foobar WHERE THEID != 2").collect().size == 2)
-    assert(sql("SELECT * FROM foobar WHERE THEID = 1").collect().size == 1)
-    assert(sql("SELECT * FROM foobar WHERE NAME = 'fred'").collect().size == 1)
-    assert(sql("SELECT * FROM foobar WHERE NAME > 'fred'").collect().size == 2)
-    assert(sql("SELECT * FROM foobar WHERE NAME != 'fred'").collect().size == 2)
+    assert(sql("SELECT * FROM foobar WHERE THEID < 1").collect().size === 0)
+    assert(sql("SELECT * FROM foobar WHERE THEID != 2").collect().size === 2)
+    assert(sql("SELECT * FROM foobar WHERE THEID = 1").collect().size === 1)
+    assert(sql("SELECT * FROM foobar WHERE NAME = 'fred'").collect().size === 1)
+    assert(sql("SELECT * FROM foobar WHERE NAME > 'fred'").collect().size === 2)
+    assert(sql("SELECT * FROM foobar WHERE NAME != 'fred'").collect().size === 2)
   }
 
   test("SELECT * WHERE (quoted strings)") {
-    assert(sql("select * from foobar").where('NAME === "joe 'foo' \"bar\"").collect().size == 1)
+    assert(sql("select * from foobar").where('NAME === "joe 'foo' \"bar\"").collect().size === 1)
   }
 
   test("SELECT first field") {
     val names = sql("SELECT NAME FROM foobar").collect().map(x => x.getString(0)).sortWith(_ < _)
-    assert(names.size == 3)
+    assert(names.size === 3)
     assert(names(0).equals("fred"))
     assert(names(1).equals("joe 'foo' \"bar\""))
     assert(names(2).equals("mary"))
@@ -158,10 +160,10 @@ class JDBCSuite extends FunSuite with BeforeAndAfter {
 
   test("SELECT second field") {
     val ids = sql("SELECT THEID FROM foobar").collect().map(x => x.getInt(0)).sortWith(_ < _)
-    assert(ids.size == 3)
-    assert(ids(0) == 1)
-    assert(ids(1) == 2)
-    assert(ids(2) == 3)
+    assert(ids.size === 3)
+    assert(ids(0) === 1)
+    assert(ids(1) === 2)
+    assert(ids(2) === 3)
   }
 
   test("SELECT * partitioned") {
@@ -169,46 +171,46 @@ class JDBCSuite extends FunSuite with BeforeAndAfter {
   }
 
   test("SELECT WHERE (simple predicates) partitioned") {
-    assert(sql("SELECT * FROM parts WHERE THEID < 1").collect().size == 0)
-    assert(sql("SELECT * FROM parts WHERE THEID != 2").collect().size == 2)
-    assert(sql("SELECT THEID FROM parts WHERE THEID = 1").collect().size == 1)
+    assert(sql("SELECT * FROM parts WHERE THEID < 1").collect().size === 0)
+    assert(sql("SELECT * FROM parts WHERE THEID != 2").collect().size === 2)
+    assert(sql("SELECT THEID FROM parts WHERE THEID = 1").collect().size === 1)
   }
 
   test("SELECT second field partitioned") {
     val ids = sql("SELECT THEID FROM parts").collect().map(x => x.getInt(0)).sortWith(_ < _)
-    assert(ids.size == 3)
-    assert(ids(0) == 1)
-    assert(ids(1) == 2)
-    assert(ids(2) == 3)
+    assert(ids.size === 3)
+    assert(ids(0) === 1)
+    assert(ids(1) === 2)
+    assert(ids(2) === 3)
   }
 
   test("Basic API") {
-    assert(TestSQLContext.jdbc(urlWithUserAndPass, "TEST.PEOPLE").collect.size == 3)
+    assert(TestSQLContext.jdbc(urlWithUserAndPass, "TEST.PEOPLE").collect().size === 3)
   }
 
   test("Partitioning via JDBCPartitioningInfo API") {
     assert(TestSQLContext.jdbc(urlWithUserAndPass, "TEST.PEOPLE", "THEID", 0, 4, 3)
-      .collect.size == 3)
+      .collect.size === 3)
   }
 
   test("Partitioning via list-of-where-clauses API") {
     val parts = Array[String]("THEID < 2", "THEID >= 2")
-    assert(TestSQLContext.jdbc(urlWithUserAndPass, "TEST.PEOPLE", parts).collect.size == 3)
+    assert(TestSQLContext.jdbc(urlWithUserAndPass, "TEST.PEOPLE", parts).collect().size === 3)
   }
 
   test("H2 integral types") {
     val rows = sql("SELECT * FROM inttypes WHERE A IS NOT NULL").collect()
-    assert(rows.size == 1)
-    assert(rows(0).getInt(0) == 1)
-    assert(rows(0).getBoolean(1) == false)
-    assert(rows(0).getInt(2) == 3)
-    assert(rows(0).getInt(3) == 4)
-    assert(rows(0).getLong(4) == 1234567890123L)
+    assert(rows.size === 1)
+    assert(rows(0).getInt(0) === 1)
+    assert(rows(0).getBoolean(1) === false)
+    assert(rows(0).getInt(2) === 3)
+    assert(rows(0).getInt(3) === 4)
+    assert(rows(0).getLong(4) === 1234567890123L)
   }
 
   test("H2 null entries") {
     val rows = sql("SELECT * FROM inttypes WHERE A IS NULL").collect()
-    assert(rows.size == 1)
+    assert(rows.size === 1)
     assert(rows(0).isNullAt(0))
     assert(rows(0).isNullAt(1))
     assert(rows(0).isNullAt(2))
@@ -230,27 +232,27 @@ class JDBCSuite extends FunSuite with BeforeAndAfter {
     val rows = sql("SELECT * FROM timetypes").collect()
     val cal = new GregorianCalendar(java.util.Locale.ROOT)
     cal.setTime(rows(0).getAs[java.sql.Timestamp](0))
-    assert(cal.get(Calendar.HOUR_OF_DAY) == 12)
-    assert(cal.get(Calendar.MINUTE) == 34)
-    assert(cal.get(Calendar.SECOND) == 56)
+    assert(cal.get(Calendar.HOUR_OF_DAY) === 12)
+    assert(cal.get(Calendar.MINUTE) === 34)
+    assert(cal.get(Calendar.SECOND) === 56)
     cal.setTime(rows(0).getAs[java.sql.Timestamp](1))
-    assert(cal.get(Calendar.YEAR) == 1996)
-    assert(cal.get(Calendar.MONTH) == 0)
-    assert(cal.get(Calendar.DAY_OF_MONTH) == 1)
+    assert(cal.get(Calendar.YEAR) === 1996)
+    assert(cal.get(Calendar.MONTH) === 0)
+    assert(cal.get(Calendar.DAY_OF_MONTH) === 1)
     cal.setTime(rows(0).getAs[java.sql.Timestamp](2))
-    assert(cal.get(Calendar.YEAR) == 2002)
-    assert(cal.get(Calendar.MONTH) == 1)
-    assert(cal.get(Calendar.DAY_OF_MONTH) == 20)
-    assert(cal.get(Calendar.HOUR) == 11)
-    assert(cal.get(Calendar.MINUTE) == 22)
-    assert(cal.get(Calendar.SECOND) == 33)
-    assert(rows(0).getAs[java.sql.Timestamp](2).getNanos == 543543543)
+    assert(cal.get(Calendar.YEAR) === 2002)
+    assert(cal.get(Calendar.MONTH) === 1)
+    assert(cal.get(Calendar.DAY_OF_MONTH) === 20)
+    assert(cal.get(Calendar.HOUR) === 11)
+    assert(cal.get(Calendar.MINUTE) === 22)
+    assert(cal.get(Calendar.SECOND) === 33)
+    assert(rows(0).getAs[java.sql.Timestamp](2).getNanos === 543543543)
   }
 
   test("H2 floating-point types") {
     val rows = sql("SELECT * FROM flttypes").collect()
-    assert(rows(0).getDouble(0) == 1.00000000000000022) // Yes, I meant ==.
-    assert(rows(0).getDouble(1) == 1.00000011920928955) // Yes, I meant ==.
+    assert(rows(0).getDouble(0) === 1.00000000000000022) // Yes, I meant ==.
+    assert(rows(0).getDouble(1) === 1.00000011920928955) // Yes, I meant ==.
     assert(rows(0).getAs[BigDecimal](2)
         .equals(new BigDecimal("123456789012345.54321543215432100000")))
   }
@@ -264,7 +266,7 @@ class JDBCSuite extends FunSuite with BeforeAndAfter {
         |         user 'testUser', password 'testPass')
       """.stripMargin.replaceAll("\n", " "))
     val rows = sql("SELECT * FROM hack").collect()
-    assert(rows(0).getDouble(0) == 1.00000011920928955) // Yes, I meant ==.
+    assert(rows(0).getDouble(0) === 1.00000011920928955) // Yes, I meant ==.
     // For some reason, H2 computes this square incorrectly...
     assert(math.abs(rows(0).getDouble(1) - 1.00000023841859331) < 1e-12)
   }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala
index 706c966ee05f5..1fe0b76c00be3 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala
@@ -380,8 +380,10 @@ class JsonSuite extends QueryTest {
       sql("select * from jsonTable"),
       Row("true", 11L, null, 1.1, "13.1", "str1") ::
         Row("12", null, new java.math.BigDecimal("21474836470.9"), null, null, "true") ::
-        Row("false", 21474836470L, new java.math.BigDecimal("92233720368547758070"), 100, "str1", "false") ::
-        Row(null, 21474836570L, new java.math.BigDecimal("1.1"), 21474836470L, "92233720368547758070", null) :: Nil
+        Row("false", 21474836470L,
+          new java.math.BigDecimal("92233720368547758070"), 100, "str1", "false") ::
+        Row(null, 21474836570L,
+          new java.math.BigDecimal("1.1"), 21474836470L, "92233720368547758070", null) :: Nil
     )
 
     // Number and Boolean conflict: resolve the type as number in this query.
@@ -404,7 +406,8 @@ class JsonSuite extends QueryTest {
     // Widening to DecimalType
     checkAnswer(
       sql("select num_num_2 + 1.2 from jsonTable where num_num_2 > 1.1"),
-      Row(new java.math.BigDecimal("21474836472.1")) :: Row(new java.math.BigDecimal("92233720368547758071.2")) :: Nil
+      Row(new java.math.BigDecimal("21474836472.1")) ::
+        Row(new java.math.BigDecimal("92233720368547758071.2")) :: Nil
     )
 
     // Widening to DoubleType
@@ -913,8 +916,10 @@ class JsonSuite extends QueryTest {
     df1.registerTempTable("applySchema1")
     val df2 = df1.toDF
     val result = df2.toJSON.collect()
+    // scalastyle:off
     assert(result(0) === "{\"f1\":1,\"f2\":\"A1\",\"f3\":true,\"f4\":[\"1\",\" A1\",\" true\",\" null\"]}")
     assert(result(3) === "{\"f1\":4,\"f2\":\"D4\",\"f3\":true,\"f4\":[\"4\",\" D4\",\" true\",\" 2147483644\"],\"f5\":2147483644}")
+    // scalastyle:on
 
     val schema2 = StructType(
       StructField("f1", StructType(
@@ -968,7 +973,8 @@ class JsonSuite extends QueryTest {
 
     // Access elements of a BigInteger array (we use DecimalType internally).
     checkAnswer(
-      sql("select arrayOfBigInteger[0], arrayOfBigInteger[1], arrayOfBigInteger[2] from complexTable"),
+      sql("select arrayOfBigInteger[0], arrayOfBigInteger[1], arrayOfBigInteger[2] " +
+        " from complexTable"),
       Row(new java.math.BigDecimal("922337203685477580700"),
         new java.math.BigDecimal("-922337203685477580800"), null)
     )
@@ -1008,7 +1014,8 @@ class JsonSuite extends QueryTest {
 
     // Access elements of an array field of a struct.
     checkAnswer(
-      sql("select structWithArrayFields.field1[1], structWithArrayFields.field2[3] from complexTable"),
+      sql("select structWithArrayFields.field1[1], structWithArrayFields.field2[3] " +
+        "from complexTable"),
       Row(5, null)
     )
   }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala
index 203bc79f153dd..97c0f439acf13 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala
@@ -218,7 +218,7 @@ class ParquetIOSuiteBase extends QueryTest with ParquetTest {
   }
 
   test("compression codec") {
-    def compressionCodecFor(path: String) = {
+    def compressionCodecFor(path: String): String = {
       val codecs = ParquetTypesConverter
         .readMetaData(new Path(path), Some(configuration))
         .getBlocks
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetSchemaSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetSchemaSuite.scala
index 61f1cf347ab0f..c964b6d984557 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetSchemaSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetSchemaSuite.scala
@@ -180,10 +180,12 @@ class ParquetSchemaSuite extends FunSuite with ParquetTest {
     val caseClassString =
       "StructType(List(StructField(c1,IntegerType,false), StructField(c2,BinaryType,true)))"
 
+    // scalastyle:off
     val jsonString =
       """
         |{"type":"struct","fields":[{"name":"c1","type":"integer","nullable":false,"metadata":{}},{"name":"c2","type":"binary","nullable":true,"metadata":{}}]}
       """.stripMargin
+    // scalastyle:on
 
     val fromCaseClassString = ParquetTypesConverter.convertFromString(caseClassString)
     val fromJson = ParquetTypesConverter.convertFromString(jsonString)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/DDLTestSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/DDLTestSuite.scala
index 54af50c6e10ad..3f24a497390c1 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/sources/DDLTestSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/DDLTestSuite.scala
@@ -17,6 +17,7 @@
 
 package org.apache.spark.sql.sources
 
+import org.apache.spark.rdd.RDD
 import org.apache.spark.sql._
 import org.apache.spark.sql.types._
 
@@ -31,7 +32,7 @@ class DDLScanSource extends RelationProvider {
 case class SimpleDDLScan(from: Int, to: Int)(@transient val sqlContext: SQLContext)
   extends BaseRelation with TableScan {
 
-  override def schema =
+  override def schema: StructType =
     StructType(Seq(
       StructField("intType", IntegerType, nullable = false,
         new MetadataBuilder().putString("comment", "test comment").build()),
@@ -57,8 +58,9 @@ case class SimpleDDLScan(from: Int, to: Int)(@transient val sqlContext: SQLConte
     ))
 
 
-  override def buildScan() = sqlContext.sparkContext.parallelize(from to to).
-    map(e => Row(s"people$e", e * 2))
+  override def buildScan(): RDD[Row] = {
+    sqlContext.sparkContext.parallelize(from to to).map(e => Row(s"people$e", e * 2))
+  }
 }
 
 class DDLTestSuite extends DataSourceTest {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/FilteredScanSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/FilteredScanSuite.scala
index 773bd1602d5e5..cb5e5147ff189 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/sources/FilteredScanSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/FilteredScanSuite.scala
@@ -19,6 +19,7 @@ package org.apache.spark.sql.sources
 
 import scala.language.existentials
 
+import org.apache.spark.rdd.RDD
 import org.apache.spark.sql._
 import org.apache.spark.sql.types._
 
@@ -41,7 +42,7 @@ case class SimpleFilteredScan(from: Int, to: Int)(@transient val sqlContext: SQL
       StructField("b", IntegerType, nullable = false) ::
       StructField("c", StringType, nullable = false) :: Nil)
 
-  override def buildScan(requiredColumns: Array[String], filters: Array[Filter]) = {
+  override def buildScan(requiredColumns: Array[String], filters: Array[Filter]): RDD[Row] = {
     val rowBuilders = requiredColumns.map {
       case "a" => (i: Int) => Seq(i)
       case "b" => (i: Int) => Seq(i * 2)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/PrunedScanSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/PrunedScanSuite.scala
index 08fb5380dc026..6a1ddf2f8e98b 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/sources/PrunedScanSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/PrunedScanSuite.scala
@@ -19,6 +19,7 @@ package org.apache.spark.sql.sources
 
 import scala.language.existentials
 
+import org.apache.spark.rdd.RDD
 import org.apache.spark.sql._
 import org.apache.spark.sql.types._
 
@@ -34,12 +35,12 @@ case class SimplePrunedScan(from: Int, to: Int)(@transient val sqlContext: SQLCo
   extends BaseRelation
   with PrunedScan {
 
-  override def schema =
+  override def schema: StructType =
     StructType(
       StructField("a", IntegerType, nullable = false) ::
       StructField("b", IntegerType, nullable = false) :: Nil)
 
-  override def buildScan(requiredColumns: Array[String]) = {
+  override def buildScan(requiredColumns: Array[String]): RDD[Row] = {
     val rowBuilders = requiredColumns.map {
       case "a" => (i: Int) => Seq(i)
       case "b" => (i: Int) => Seq(i * 2)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/SaveLoadSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/SaveLoadSuite.scala
index 43bc8eb2d11a7..cb287ba85c1f8 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/sources/SaveLoadSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/SaveLoadSuite.scala
@@ -114,4 +114,4 @@ class SaveLoadSuite extends DataSourceTest with BeforeAndAfterAll {
       message.contains("Append mode is not supported"),
       "We should complain that 'Append mode is not supported' for JSON source.")
   }
-}
\ No newline at end of file
+}
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala
index 7928600ac2fb5..60c8c00bda4d5 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala
@@ -19,6 +19,7 @@ package org.apache.spark.sql.sources
 
 import java.sql.{Timestamp, Date}
 
+import org.apache.spark.rdd.RDD
 import org.apache.spark.sql._
 import org.apache.spark.sql.types._
 
@@ -35,10 +36,10 @@ class SimpleScanSource extends RelationProvider {
 case class SimpleScan(from: Int, to: Int)(@transient val sqlContext: SQLContext)
   extends BaseRelation with TableScan {
 
-  override def schema =
+  override def schema: StructType =
     StructType(StructField("i", IntegerType, nullable = false) :: Nil)
 
-  override def buildScan() = sqlContext.sparkContext.parallelize(from to to).map(Row(_))
+  override def buildScan(): RDD[Row] = sqlContext.sparkContext.parallelize(from to to).map(Row(_))
 }
 
 class AllDataTypesScanSource extends SchemaRelationProvider {
@@ -57,9 +58,9 @@ case class AllDataTypesScan(
   extends BaseRelation
   with TableScan {
 
-  override def schema = userSpecifiedSchema
+  override def schema: StructType = userSpecifiedSchema
 
-  override def buildScan() = {
+  override def buildScan(): RDD[Row] = {
     sqlContext.sparkContext.parallelize(from to to).map { i =>
       Row(
         s"str_$i",
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/ErrorPositionSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/ErrorPositionSuite.scala
index 968557c9c4686..d960a30e00738 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/ErrorPositionSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/ErrorPositionSuite.scala
@@ -136,7 +136,7 @@ class ErrorPositionSuite extends QueryTest with BeforeAndAfter {
    * @param query the query to analyze
    * @param token a unique token in the string that should be indicated by the exception
    */
-  def positionTest(name: String, query: String, token: String) = {
+  def positionTest(name: String, query: String, token: String): Unit = {
     def parseTree =
       Try(quietly(HiveQl.dumpTree(HiveQl.getAst(query)))).getOrElse("<failed to parse>")
 
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala
index c482c6de8a736..2a7374cc172b7 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala
@@ -116,21 +116,20 @@ class HiveInspectorSuite extends FunSuite with HiveInspectors {
   }
 
   def checkDataType(dt1: Seq[DataType], dt2: Seq[DataType]): Unit = {
-    dt1.zip(dt2).map {
-      case (dd1, dd2) =>
-        assert(dd1.getClass === dd2.getClass)  // DecimalType doesn't has the default precision info
+    dt1.zip(dt2).foreach { case (dd1, dd2) =>
+      assert(dd1.getClass === dd2.getClass)  // DecimalType doesn't has the default precision info
     }
   }
 
   def checkValues(row1: Seq[Any], row2: Seq[Any]): Unit = {
-    row1.zip(row2).map {
-      case (r1, r2) => checkValue(r1, r2)
+    row1.zip(row2).foreach { case (r1, r2) =>
+      checkValue(r1, r2)
     }
   }
 
   def checkValues(row1: Seq[Any], row2: Row): Unit = {
-    row1.zip(row2.toSeq).map {
-      case (r1, r2) => checkValue(r1, r2)
+    row1.zip(row2.toSeq).foreach { case (r1, r2) =>
+      checkValue(r1, r2)
     }
   }
 
@@ -141,7 +140,7 @@ class HiveInspectorSuite extends FunSuite with HiveInspectors {
         assert(r1.compare(r2) === 0)
       case (r1: Array[Byte], r2: Array[Byte])
         if r1 != null && r2 != null && r1.length == r2.length =>
-        r1.zip(r2).map { case (b1, b2) => assert(b1 === b2) }
+        r1.zip(r2).foreach { case (b1, b2) => assert(b1 === b2) }
       case (r1, r2) => assert(r1 === r2)
     }
   }
@@ -166,7 +165,8 @@ class HiveInspectorSuite extends FunSuite with HiveInspectors {
     val constantData = constantExprs.map(_.eval())
     val constantNullData = constantData.map(_ => null)
     val constantWritableOIs = constantExprs.map(e => toWritableInspector(e.dataType))
-    val constantNullWritableOIs = constantExprs.map(e => toInspector(Literal.create(null, e.dataType)))
+    val constantNullWritableOIs =
+      constantExprs.map(e => toInspector(Literal.create(null, e.dataType)))
 
     checkValues(constantData, constantData.zip(constantWritableOIs).map {
       case (d, oi) => unwrap(wrap(d, oi), oi)
@@ -202,7 +202,8 @@ class HiveInspectorSuite extends FunSuite with HiveInspectors {
       case (t, idx) => StructField(s"c_$idx", t)
     })
 
-    checkValues(row, unwrap(wrap(Row.fromSeq(row), toInspector(dt)), toInspector(dt)).asInstanceOf[Row])
+    checkValues(row,
+      unwrap(wrap(Row.fromSeq(row), toInspector(dt)), toInspector(dt)).asInstanceOf[Row])
     checkValue(null, unwrap(wrap(null, toInspector(dt)), toInspector(dt)))
   }
 
@@ -212,8 +213,10 @@ class HiveInspectorSuite extends FunSuite with HiveInspectors {
     val d = row(0) :: row(0) :: Nil
     checkValue(d, unwrap(wrap(d, toInspector(dt)), toInspector(dt)))
     checkValue(null, unwrap(wrap(null, toInspector(dt)), toInspector(dt)))
-    checkValue(d, unwrap(wrap(d, toInspector(Literal.create(d, dt))), toInspector(Literal.create(d, dt))))
-    checkValue(d, unwrap(wrap(null, toInspector(Literal.create(d, dt))), toInspector(Literal.create(d, dt))))
+    checkValue(d,
+      unwrap(wrap(d, toInspector(Literal.create(d, dt))), toInspector(Literal.create(d, dt))))
+    checkValue(d,
+      unwrap(wrap(null, toInspector(Literal.create(d, dt))), toInspector(Literal.create(d, dt))))
   }
 
   test("wrap / unwrap Map Type") {
@@ -222,7 +225,9 @@ class HiveInspectorSuite extends FunSuite with HiveInspectors {
     val d = Map(row(0) -> row(1))
     checkValue(d, unwrap(wrap(d, toInspector(dt)), toInspector(dt)))
     checkValue(null, unwrap(wrap(null, toInspector(dt)), toInspector(dt)))
-    checkValue(d, unwrap(wrap(d, toInspector(Literal.create(d, dt))), toInspector(Literal.create(d, dt))))
-    checkValue(d, unwrap(wrap(null, toInspector(Literal.create(d, dt))), toInspector(Literal.create(d, dt))))
+    checkValue(d,
+      unwrap(wrap(d, toInspector(Literal.create(d, dt))), toInspector(Literal.create(d, dt))))
+    checkValue(d,
+      unwrap(wrap(null, toInspector(Literal.create(d, dt))), toInspector(Literal.create(d, dt))))
   }
 }
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/InsertIntoHiveTableSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/InsertIntoHiveTableSuite.scala
index 8011952e0d535..ecb990e8aac91 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/InsertIntoHiveTableSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/InsertIntoHiveTableSuite.scala
@@ -115,11 +115,36 @@ class InsertIntoHiveTableSuite extends QueryTest with BeforeAndAfter {
   test("SPARK-4203:random partition directory order") {
     sql("CREATE TABLE tmp_table (key int, value string)")
     val tmpDir = Utils.createTempDir()
-    sql(s"CREATE TABLE table_with_partition(c1 string) PARTITIONED by (p1 string,p2 string,p3 string,p4 string,p5 string) location '${tmpDir.toURI.toString}'  ")
-    sql("INSERT OVERWRITE TABLE table_with_partition  partition (p1='a',p2='b',p3='c',p4='c',p5='1') SELECT 'blarr' FROM tmp_table")
-    sql("INSERT OVERWRITE TABLE table_with_partition  partition (p1='a',p2='b',p3='c',p4='c',p5='2') SELECT 'blarr' FROM tmp_table")
-    sql("INSERT OVERWRITE TABLE table_with_partition  partition (p1='a',p2='b',p3='c',p4='c',p5='3') SELECT 'blarr' FROM tmp_table")
-    sql("INSERT OVERWRITE TABLE table_with_partition  partition (p1='a',p2='b',p3='c',p4='c',p5='4') SELECT 'blarr' FROM tmp_table")
+    sql(
+      s"""
+         |CREATE TABLE table_with_partition(c1 string)
+         |PARTITIONED by (p1 string,p2 string,p3 string,p4 string,p5 string)
+         |location '${tmpDir.toURI.toString}'
+        """.stripMargin)
+    sql(
+      """
+        |INSERT OVERWRITE TABLE table_with_partition
+        |partition (p1='a',p2='b',p3='c',p4='c',p5='1')
+        |SELECT 'blarr' FROM tmp_table
+      """.stripMargin)
+    sql(
+      """
+        |INSERT OVERWRITE TABLE table_with_partition
+        |partition (p1='a',p2='b',p3='c',p4='c',p5='2')
+        |SELECT 'blarr' FROM tmp_table
+      """.stripMargin)
+    sql(
+      """
+        |INSERT OVERWRITE TABLE table_with_partition
+        |partition (p1='a',p2='b',p3='c',p4='c',p5='3')
+        |SELECT 'blarr' FROM tmp_table
+      """.stripMargin)
+    sql(
+      """
+        |INSERT OVERWRITE TABLE table_with_partition
+        |partition (p1='a',p2='b',p3='c',p4='c',p5='4')
+        |SELECT 'blarr' FROM tmp_table
+      """.stripMargin)
     def listFolders(path: File, acc: List[String]): List[List[String]] = {
       val dir = path.listFiles()
       val folders = dir.filter(_.isDirectory).toList
@@ -196,34 +221,42 @@ class InsertIntoHiveTableSuite extends QueryTest with BeforeAndAfter {
     testData.registerTempTable("testData")
 
     val testDatawithNull = TestHive.sparkContext.parallelize(
-      (1 to 10).map(i => ThreeCloumntable(i, i.toString,null))).toDF()
+      (1 to 10).map(i => ThreeCloumntable(i, i.toString, null))).toDF()
 
     val tmpDir = Utils.createTempDir()
-    sql(s"CREATE TABLE table_with_partition(key int,value string) PARTITIONED by (ds string) location '${tmpDir.toURI.toString}' ")
-    sql("INSERT OVERWRITE TABLE table_with_partition  partition (ds='1') SELECT key,value FROM testData")
+    sql(
+      s"""
+         |CREATE TABLE table_with_partition(key int,value string)
+         |PARTITIONED by (ds string) location '${tmpDir.toURI.toString}'
+       """.stripMargin)
+    sql(
+      """
+        |INSERT OVERWRITE TABLE table_with_partition
+        |partition (ds='1') SELECT key,value FROM testData
+      """.stripMargin)
 
     // test schema the same between partition and table
     sql("ALTER TABLE table_with_partition CHANGE COLUMN key key BIGINT")
     checkAnswer(sql("select key,value from table_with_partition where ds='1' "),
-      testData.collect.toSeq
+      testData.collect().toSeq
     )
     
     // test difference type of field
     sql("ALTER TABLE table_with_partition CHANGE COLUMN key key BIGINT")
     checkAnswer(sql("select key,value from table_with_partition where ds='1' "),
-      testData.collect.toSeq
+      testData.collect().toSeq
     )
 
     // add column to table
     sql("ALTER TABLE table_with_partition ADD COLUMNS(key1 string)")
     checkAnswer(sql("select key,value,key1 from table_with_partition where ds='1' "),
-      testDatawithNull.collect.toSeq
+      testDatawithNull.collect().toSeq
     )
 
     // change column name to table
     sql("ALTER TABLE table_with_partition CHANGE COLUMN key keynew BIGINT")
     checkAnswer(sql("select keynew,value from table_with_partition where ds='1' "),
-      testData.collect.toSeq
+      testData.collect().toSeq
     )
 
     sql("DROP TABLE table_with_partition")
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala
index ccd0e5aa51f95..00a69de9e4262 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala
@@ -142,7 +142,7 @@ class StatisticsSuite extends QueryTest with BeforeAndAfterAll {
         after: () => Unit,
         query: String,
         expectedAnswer: Seq[Row],
-        ct: ClassTag[_]) = {
+        ct: ClassTag[_]): Unit = {
       before()
 
       var df = sql(query)
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/BigDataBenchmarkSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/BigDataBenchmarkSuite.scala
index 42a82c1fbf5c7..a3f5921a0cb23 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/BigDataBenchmarkSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/BigDataBenchmarkSuite.scala
@@ -28,6 +28,7 @@ import org.apache.spark.sql.hive.test.TestHive._
 class BigDataBenchmarkSuite extends HiveComparisonTest {
   val testDataDirectory = new File("target" + File.separator + "big-data-benchmark-testdata")
 
+  val userVisitPath = new File(testDataDirectory, "uservisits").getCanonicalPath
   val testTables = Seq(
     TestTable(
       "rankings",
@@ -63,7 +64,7 @@ class BigDataBenchmarkSuite extends HiveComparisonTest {
         |  searchWord STRING,
         |  duration INT)
         |  ROW FORMAT DELIMITED FIELDS TERMINATED BY ","
-        |  STORED AS TEXTFILE LOCATION "${new File(testDataDirectory, "uservisits").getCanonicalPath}"
+        |  STORED AS TEXTFILE LOCATION "$userVisitPath"
       """.stripMargin.cmd),
     TestTable(
       "documents",
@@ -83,7 +84,10 @@ class BigDataBenchmarkSuite extends HiveComparisonTest {
       "SELECT pageURL, pageRank FROM rankings WHERE pageRank > 1")
 
     createQueryTest("query2",
-      "SELECT SUBSTR(sourceIP, 1, 10), SUM(adRevenue) FROM uservisits GROUP BY SUBSTR(sourceIP, 1, 10)")
+      """
+        |SELECT SUBSTR(sourceIP, 1, 10), SUM(adRevenue) FROM uservisits
+        |GROUP BY SUBSTR(sourceIP, 1, 10)
+      """.stripMargin)
 
     createQueryTest("query3",
       """
@@ -113,8 +117,8 @@ class BigDataBenchmarkSuite extends HiveComparisonTest {
         |CREATE TABLE url_counts_total AS
         |  SELECT SUM(count) AS totalCount, destpage
         |  FROM url_counts_partial GROUP BY destpage
-        |-- The following queries run, but generate different results in HIVE likely because the UDF is not deterministic
-        |-- given different input splits.
+        |-- The following queries run, but generate different results in HIVE
+        |-- likely because the UDF is not deterministic given different input splits.
         |-- SELECT CAST(SUM(count) AS INT) FROM url_counts_partial
         |-- SELECT COUNT(*) FROM url_counts_partial
         |-- SELECT * FROM url_counts_partial
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala
index a5ec312ee430c..027056d4b865f 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala
@@ -255,8 +255,9 @@ abstract class HiveComparisonTest
           .filterNot(_ contains "hive.outerjoin.supports.filters")
           .filterNot(_ contains "hive.exec.post.hooks")
 
-      if (allQueries != queryList)
+      if (allQueries != queryList) {
         logWarning(s"Simplifications made on unsupported operations for test $testCaseName")
+      }
 
       lazy val consoleTestCase = {
         val quotes = "\"\"\""
@@ -305,13 +306,16 @@ abstract class HiveComparisonTest
                 try {
                   // Hooks often break the harness and don't really affect our test anyway, don't
                   // even try running them.
-                  if (installHooksCommand.findAllMatchIn(queryString).nonEmpty)
+                  if (installHooksCommand.findAllMatchIn(queryString).nonEmpty) {
                     sys.error("hive exec hooks not supported for tests.")
+                  }
 
-                  logWarning(s"Running query ${i+1}/${queryList.size} with hive.")
+                  logWarning(s"Running query ${i + 1}/${queryList.size} with hive.")
                   // Analyze the query with catalyst to ensure test tables are loaded.
                   val answer = hiveQuery.analyzed match {
-                    case _: ExplainCommand => Nil // No need to execute EXPLAIN queries as we don't check the output.
+                    case _: ExplainCommand =>
+                      // No need to execute EXPLAIN queries as we don't check the output.
+                      Nil
                     case _ => TestHive.runSqlHive(queryString)
                   }
 
@@ -394,21 +398,24 @@ abstract class HiveComparisonTest
         case tf: org.scalatest.exceptions.TestFailedException => throw tf
         case originalException: Exception =>
           if (System.getProperty("spark.hive.canarytest") != null) {
-            // When we encounter an error we check to see if the environment is still okay by running a simple query.
-            // If this fails then we halt testing since something must have gone seriously wrong.
+            // When we encounter an error we check to see if the environment is still
+            // okay by running a simple query. If this fails then we halt testing since
+            // something must have gone seriously wrong.
             try {
               new TestHive.HiveQLQueryExecution("SELECT key FROM src").stringResult()
               TestHive.runSqlHive("SELECT key FROM src")
             } catch {
               case e: Exception =>
-                logError(s"FATAL ERROR: Canary query threw $e This implies that the testing environment has likely been corrupted.")
-                // The testing setup traps exits so wait here for a long time so the developer can see when things started
-                // to go wrong.
+                logError(s"FATAL ERROR: Canary query threw $e This implies that the " +
+                  "testing environment has likely been corrupted.")
+                // The testing setup traps exits so wait here for a long time so the developer
+                // can see when things started to go wrong.
                 Thread.sleep(1000000)
             }
           }
 
-          // If the canary query didn't fail then the environment is still okay, so just throw the original exception.
+          // If the canary query didn't fail then the environment is still okay,
+          // so just throw the original exception.
           throw originalException
       }
     }
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQueryFileTest.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQueryFileTest.scala
index 02518d516261b..f7b37dae0a5f3 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQueryFileTest.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQueryFileTest.scala
@@ -24,8 +24,9 @@ import org.apache.spark.sql.catalyst.util._
 /**
  * A framework for running the query tests that are listed as a set of text files.
  *
- * TestSuites that derive from this class must provide a map of testCaseName -> testCaseFiles that should be included.
- * Additionally, there is support for whitelisting and blacklisting tests as development progresses.
+ * TestSuites that derive from this class must provide a map of testCaseName -> testCaseFiles
+ * that should be included. Additionally, there is support for whitelisting and blacklisting
+ * tests as development progresses.
  */
 abstract class HiveQueryFileTest extends HiveComparisonTest {
   /** A list of tests deemed out of scope and thus completely disregarded */
@@ -54,15 +55,17 @@ abstract class HiveQueryFileTest extends HiveComparisonTest {
     case (testCaseName, testCaseFile) =>
       if (blackList.map(_.r.pattern.matcher(testCaseName).matches()).reduceLeft(_||_)) {
         logDebug(s"Blacklisted test skipped $testCaseName")
-      } else if (realWhiteList.map(_.r.pattern.matcher(testCaseName).matches()).reduceLeft(_||_) || runAll) {
+      } else if (realWhiteList.map(_.r.pattern.matcher(testCaseName).matches()).reduceLeft(_||_) ||
+        runAll) {
         // Build a test case and submit it to scala test framework...
         val queriesString = fileToString(testCaseFile)
         createQueryTest(testCaseName, queriesString)
       } else {
         // Only output warnings for the built in whitelist as this clutters the output when the user
         // trying to execute a single test from the commandline.
-        if(System.getProperty(whiteListProperty) == null && !runAll)
+        if (System.getProperty(whiteListProperty) == null && !runAll) {
           ignore(testCaseName) {}
+        }
       }
   }
 }
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
index de140fc72a2c3..af781a502e9f3 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
@@ -37,7 +37,8 @@ import org.apache.spark.sql.hive.test.TestHive._
 case class TestData(a: Int, b: String)
 
 /**
- * A set of test cases expressed in Hive QL that are not covered by the tests included in the hive distribution.
+ * A set of test cases expressed in Hive QL that are not covered by the tests
+ * included in the hive distribution.
  */
 class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter {
   private val originalTimeZone = TimeZone.getDefault
@@ -237,7 +238,8 @@ class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter {
   }
 
   createQueryTest("modulus",
-    "SELECT 11 % 10, IF((101.1 % 100.0) BETWEEN 1.01 AND 1.11, \"true\", \"false\"), (101 / 2) % 10 FROM src LIMIT 1")
+    "SELECT 11 % 10, IF((101.1 % 100.0) BETWEEN 1.01 AND 1.11, \"true\", \"false\"), " +
+      "(101 / 2) % 10 FROM src LIMIT 1")
 
   test("Query expressed in SQL") {
     setConf("spark.sql.dialect", "sql")
@@ -309,7 +311,8 @@ class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter {
     "SELECT * FROM src a JOIN src b ON a.key = b.key")
 
   createQueryTest("small.cartesian",
-    "SELECT a.key, b.key FROM (SELECT key FROM src WHERE key < 1) a JOIN (SELECT key FROM src WHERE key = 2) b")
+    "SELECT a.key, b.key FROM (SELECT key FROM src WHERE key < 1) a JOIN " +
+      "(SELECT key FROM src WHERE key = 2) b")
 
   createQueryTest("length.udf",
     "SELECT length(\"test\") FROM src LIMIT 1")
@@ -457,6 +460,7 @@ class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter {
   createQueryTest("lateral view3",
     "FROM src SELECT key, D.* lateral view explode(array(key+3, key+4)) D as CX")
 
+  // scalastyle:off
   createQueryTest("lateral view4",
     """
       |create table src_lv1 (key string, value string);
@@ -466,6 +470,7 @@ class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter {
       |insert overwrite table src_lv1 SELECT key, D.* lateral view explode(array(key+3, key+4)) D as CX
       |insert overwrite table src_lv2 SELECT key, D.* lateral view explode(array(key+3, key+4)) D as CX
     """.stripMargin)
+  // scalastyle:on
 
   createQueryTest("lateral view5",
     "FROM src SELECT explode(array(key+3, key+4))")
@@ -584,7 +589,7 @@ class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter {
     }
   }
 
-  def isExplanation(result: DataFrame) = {
+  def isExplanation(result: DataFrame): Boolean = {
     val explanation = result.select('plan).collect().map { case Row(plan: String) => plan }
     explanation.contains("== Physical Plan ==")
   }
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveResolutionSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveResolutionSuite.scala
index f4440e5b7846a..8ad3627504229 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveResolutionSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveResolutionSuite.scala
@@ -25,7 +25,8 @@ case class Nested(a: Int, B: Int)
 case class Data(a: Int, B: Int, n: Nested, nestedArray: Seq[Nested])
 
 /**
- * A set of test cases expressed in Hive QL that are not covered by the tests included in the hive distribution.
+ * A set of test cases expressed in Hive QL that are not covered by the tests
+ * included in the hive distribution.
  */
 class HiveResolutionSuite extends HiveComparisonTest {
 
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveSerDeSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveSerDeSuite.scala
index 7486bfa82b00b..d05e11fcf281b 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveSerDeSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveSerDeSuite.scala
@@ -26,8 +26,9 @@ import org.apache.spark.sql.hive.test.TestHive
  */
 class HiveSerDeSuite extends HiveComparisonTest with BeforeAndAfterAll {
 
-  override def beforeAll() = {
+  override def beforeAll(): Unit = {
     TestHive.cacheTables = false
+    super.beforeAll()
   }
 
   createQueryTest(
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveTypeCoercionSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveTypeCoercionSuite.scala
index ab0e0443c7faa..f0f04f8c73fb4 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveTypeCoercionSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveTypeCoercionSuite.scala
@@ -35,8 +35,10 @@ class HiveTypeCoercionSuite extends HiveComparisonTest {
 
   val nullVal = "null"
   baseTypes.init.foreach { i =>
-    createQueryTest(s"case when then $i else $nullVal end ", s"SELECT case when true then $i else $nullVal end FROM src limit 1")
-    createQueryTest(s"case when then $nullVal else $i end ", s"SELECT case when true then $nullVal else $i end FROM src limit 1")
+    createQueryTest(s"case when then $i else $nullVal end ",
+      s"SELECT case when true then $i else $nullVal end FROM src limit 1")
+    createQueryTest(s"case when then $nullVal else $i end ",
+      s"SELECT case when true then $nullVal else $i end FROM src limit 1")
   }
 
   test("[SPARK-2210] boolean cast on boolean value should be removed") {
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala
index d7c5d1a25a82b..7f49eac490572 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala
@@ -123,9 +123,10 @@ class HiveUdfSuite extends QueryTest {
       IntegerCaseClass(1) :: IntegerCaseClass(2) :: Nil).toDF()
     testData.registerTempTable("integerTable")
 
-    sql(s"CREATE TEMPORARY FUNCTION testUDFIntegerToString AS '${classOf[UDFIntegerToString].getName}'")
+    val udfName = classOf[UDFIntegerToString].getName
+    sql(s"CREATE TEMPORARY FUNCTION testUDFIntegerToString AS '$udfName'")
     checkAnswer(
-      sql("SELECT testUDFIntegerToString(i) FROM integerTable"), //.collect(),
+      sql("SELECT testUDFIntegerToString(i) FROM integerTable"),
       Seq(Row("1"), Row("2")))
     sql("DROP TEMPORARY FUNCTION IF EXISTS testUDFIntegerToString")
 
@@ -141,7 +142,7 @@ class HiveUdfSuite extends QueryTest {
 
     sql(s"CREATE TEMPORARY FUNCTION testUDFListListInt AS '${classOf[UDFListListInt].getName}'")
     checkAnswer(
-      sql("SELECT testUDFListListInt(lli) FROM listListIntTable"), //.collect(),
+      sql("SELECT testUDFListListInt(lli) FROM listListIntTable"),
       Seq(Row(0), Row(2), Row(13)))
     sql("DROP TEMPORARY FUNCTION IF EXISTS testUDFListListInt")
 
@@ -156,7 +157,7 @@ class HiveUdfSuite extends QueryTest {
 
     sql(s"CREATE TEMPORARY FUNCTION testUDFListString AS '${classOf[UDFListString].getName}'")
     checkAnswer(
-      sql("SELECT testUDFListString(l) FROM listStringTable"), //.collect(),
+      sql("SELECT testUDFListString(l) FROM listStringTable"),
       Seq(Row("a,b,c"), Row("d,e")))
     sql("DROP TEMPORARY FUNCTION IF EXISTS testUDFListString")
 
@@ -170,7 +171,7 @@ class HiveUdfSuite extends QueryTest {
 
     sql(s"CREATE TEMPORARY FUNCTION testStringStringUdf AS '${classOf[UDFStringString].getName}'")
     checkAnswer(
-      sql("SELECT testStringStringUdf(\"hello\", s) FROM stringTable"), //.collect(),
+      sql("SELECT testStringStringUdf(\"hello\", s) FROM stringTable"),
       Seq(Row("hello world"), Row("hello goodbye")))
     sql("DROP TEMPORARY FUNCTION IF EXISTS testStringStringUdf")
 
@@ -187,7 +188,7 @@ class HiveUdfSuite extends QueryTest {
 
     sql(s"CREATE TEMPORARY FUNCTION testUDFTwoListList AS '${classOf[UDFTwoListList].getName}'")
     checkAnswer(
-      sql("SELECT testUDFTwoListList(lli, lli) FROM TwoListTable"), //.collect(),
+      sql("SELECT testUDFTwoListList(lli, lli) FROM TwoListTable"),
       Seq(Row("0, 0"), Row("2, 2"), Row("13, 13")))
     sql("DROP TEMPORARY FUNCTION IF EXISTS testUDFTwoListList")
 
@@ -247,7 +248,8 @@ class PairUdf extends GenericUDF {
   override def initialize(p1: Array[ObjectInspector]): ObjectInspector =
     ObjectInspectorFactory.getStandardStructObjectInspector(
       Seq("id", "value"),
-      Seq(PrimitiveObjectInspectorFactory.javaIntObjectInspector, PrimitiveObjectInspectorFactory.javaIntObjectInspector)
+      Seq(PrimitiveObjectInspectorFactory.javaIntObjectInspector,
+        PrimitiveObjectInspectorFactory.javaIntObjectInspector)
   )
 
   override def evaluate(args: Array[DeferredObject]): AnyRef = {
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/PruningSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/PruningSuite.scala
index 8474d850c9c6c..067b577f1560e 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/PruningSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/PruningSuite.scala
@@ -143,7 +143,7 @@ class PruningSuite extends HiveComparisonTest with BeforeAndAfter {
       sql: String,
       expectedOutputColumns: Seq[String],
       expectedScannedColumns: Seq[String],
-      expectedPartValues: Seq[Seq[String]]) = {
+      expectedPartValues: Seq[Seq[String]]): Unit = {
     test(s"$testCaseName - pruning test") {
       val plan = new TestHive.HiveQLQueryExecution(sql).executedPlan
       val actualOutputColumns = plan.output.map(_.name)
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
index 817b9dcb8f505..7811bd2e9effb 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
@@ -422,7 +422,7 @@ class SQLQuerySuite extends QueryTest {
   }
 
   test("resolve udtf with single alias") {
-    val rdd = sparkContext.makeRDD((1 to 5).map(i => s"""{"a":[$i, ${i+1}]}"""))
+    val rdd = sparkContext.makeRDD((1 to 5).map(i => s"""{"a":[$i, ${i + 1}]}"""))
     jsonRDD(rdd).registerTempTable("data")
     val df = sql("SELECT explode(a) AS val FROM data")
     val col = df("val")
@@ -435,7 +435,7 @@ class SQLQuerySuite extends QueryTest {
     // is not in a valid state (cannot be executed). Because of this bug, the analysis rule of
     // PreInsertionCasts will actually start to work before ImplicitGenerate and then
     // generates an invalid query plan.
-    val rdd = sparkContext.makeRDD((1 to 5).map(i => s"""{"a":[$i, ${i+1}]}"""))
+    val rdd = sparkContext.makeRDD((1 to 5).map(i => s"""{"a":[$i, ${i + 1}]}"""))
     jsonRDD(rdd).registerTempTable("data")
     val originalConf = getConf("spark.sql.hive.convertCTAS", "false")
     setConf("spark.sql.hive.convertCTAS", "false")
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/parquetSuites.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/parquetSuites.scala
index 5f71e1bbc2d2e..d5dd0bf58e702 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/parquetSuites.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/parquetSuites.scala
@@ -1,4 +1,3 @@
-
 /*
  * Licensed to the Apache Software Foundation (ASF) under one or more
  * contributor license agreements.  See the NOTICE file distributed with
@@ -887,7 +886,11 @@ abstract class ParquetPartitioningTest extends QueryTest with BeforeAndAfterAll
 
     test(s"SPARK-5775 read struct from $table") {
       checkAnswer(
-        sql(s"SELECT p, structField.intStructField, structField.stringStructField FROM $table WHERE p = 1"),
+        sql(
+          s"""
+             |SELECT p, structField.intStructField, structField.stringStructField
+             |FROM $table WHERE p = 1
+           """.stripMargin),
         (1 to 10).map(i => Row(1, i, f"${i}_string")))
     }
 

From 2fe0a1aaeebbf7f60bd4130847d738c29f1e3d53 Mon Sep 17 00:00:00 2001
From: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Date: Wed, 8 Apr 2015 22:45:40 -0700
Subject: [PATCH 24/95] [SPARK-5654] Integrate SparkR

This pull requests integrates SparkR, an R frontend for Spark. The SparkR package contains both RDD and DataFrame APIs in R and is integrated with Spark's submission scripts to work on different cluster managers.

Some integration points that would be great to get feedback on:

1. Build procedure: SparkR requires R to be installed on the machine to be built. Right now we have a new Maven profile `-PsparkR` that can be used to enable SparkR builds

2. YARN cluster mode: The R package that is built needs to be present on the driver and all the worker nodes during execution. The R package location is currently set using SPARK_HOME, but this might not work on YARN cluster mode.

The SparkR package represents the work of many contributors and attached below is a list of people along with areas they worked on

edwardt (edwart) - Documentation improvements
Felix Cheung (felixcheung) - Documentation improvements
Hossein Falaki (falaki)  - Documentation improvements
Chris Freeman (cafreeman) - DataFrame API, Programming Guide
Todd Gao (7c00) - R worker Internals
Ryan Hafen (hafen) - SparkR Internals
Qian Huang (hqzizania) - RDD API
Hao Lin (hlin09) - RDD API, Closure cleaner
Evert Lammerts (evertlammerts) - DataFrame API
Davies Liu (davies) - DataFrame API, R worker internals, Merging with Spark
Yi Lu (lythesia) - RDD API, Worker internals
Matt Massie (massie) - Jenkins build
Harihar Nahak (hnahak87) - SparkR examples
Oscar Olmedo (oscaroboto) - Spark configuration
Antonio Piccolboni (piccolbo) - SparkR examples, Namespace bug fixes
Dan Putler (dputler) - Dataframe API, SparkR Install Guide
Ashutosh Raina (ashutoshraina) - Build improvements
Josh Rosen (joshrosen) - Travis CI build
Sun Rui (sun-rui)- RDD API, JVM Backend, Shuffle improvements
Shivaram Venkataraman (shivaram) - RDD API, JVM Backend, Worker Internals
Zongheng Yang (concretevitamin) - RDD API, Pipelined RDDs, Examples and EC2 guide

Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Author: Shivaram Venkataraman <shivaram.venkataraman@gmail.com>
Author: Zongheng Yang <zongheng.y@gmail.com>
Author: cafreeman <cfreeman@alteryx.com>
Author: Shivaram Venkataraman <shivaram@eecs.berkeley.edu>
Author: Davies Liu <davies@databricks.com>
Author: Davies Liu <davies.liu@gmail.com>
Author: hlin09 <hlin09pu@gmail.com>
Author: Sun Rui <rui.sun@intel.com>
Author: lythesia <iranaikimi@gmail.com>
Author: oscaroboto <oscarjr@gmail.com>
Author: Antonio Piccolboni <antonio@piccolboni.info>
Author: root <edward>
Author: edwardt <edwardt.tril@gmail.com>
Author: hqzizania <qian.huang@intel.com>
Author: dputler <dan.putler@gmail.com>
Author: Todd Gao <todd.gao.2013@gmail.com>
Author: Chris Freeman <cfreeman@alteryx.com>
Author: Felix Cheung <fcheung@AVVOMAC-119.local>
Author: Hossein <hossein@databricks.com>
Author: Evert Lammerts <evert@apache.org>
Author: Felix Cheung <fcheung@avvomac-119.t-mobile.com>
Author: felixcheung <felixcheung_m@hotmail.com>
Author: Ryan Hafen <rhafen@gmail.com>
Author: Ashutosh Raina <ashutoshraina@users.noreply.github.com>
Author: Oscar Olmedo <oscarjr@gmail.com>
Author: Josh Rosen <rosenville@gmail.com>
Author: Yi Lu <iranaikimi@gmail.com>
Author: Harihar Nahak <hnahak87@users.noreply.github.com>

Closes #5096 from shivaram/R and squashes the following commits:

da64742 [Davies Liu] fix Date serialization
59266d1 [Davies Liu] check exclusive of primary-py-file and primary-r-file
55808e4 [Davies Liu] fix tests
5581c75 [Davies Liu] update author of SparkR
f731b48 [Shivaram Venkataraman] Only run SparkR tests if R is installed
64eda24 [Shivaram Venkataraman] Merge branch 'R' of https://github.com/amplab-extras/spark into R
d7c3f22 [Shivaram Venkataraman] Address code review comments Changes include 1. Adding SparkR docs to API docs generated 2. Style fixes in SparkR scala files 3. Clean up of shell scripts and explanation of install-dev.sh
377151f [Shivaram Venkataraman] Merge remote-tracking branch 'apache/master' into R
eb5da53 [Shivaram Venkataraman] Merge pull request #3 from davies/R2
a18ff5c [Davies Liu] Update sparkR.R
5133f3a [Shivaram Venkataraman] Merge pull request #7 from hqzizania/R3
940b631 [hqzizania] [SPARKR-92] Phase 2: implement sum(rdd)
0e788c0 [Shivaram Venkataraman] Merge pull request #5 from hlin09/doc-fix
3487461 [hlin09] Add tests log in .gitignore.
1d1802e [Shivaram Venkataraman] Merge pull request #4 from felixcheung/r-require
11981b7 [felixcheung] Update R to fail early if SparkR package is missing
c300e08 [Davies Liu] remove duplicated file
b045701 [Davies Liu] Merge branch 'remote_r' into R
19c9368 [Davies Liu] Merge branch 'sparkr-sql' of github.com:amplab-extras/SparkR-pkg into remote_r
f8fa8af [Davies Liu] mute logging when start/stop context
e7104b6 [Davies Liu] remove ::: in SparkR
a1777eb [Davies Liu] move rules into R/.gitignore
e88b649 [Davies Liu] Merge branch 'R' of github.com:amplab-extras/spark into R
6e20e71 [Davies Liu] address comments
b433817 [Davies Liu] Merge branch 'master' of github.com:apache/spark into R
a1cedad [Shivaram Venkataraman] Merge pull request #228 from felixcheung/doc
e089151 [Davies Liu] Merge pull request #225 from sun-rui/SPARKR-154_2
463e28c [Davies Liu] Merge pull request #2 from shivaram/doc-fixes
bc2d6d8 [Shivaram Venkataraman] Remove arg from sparkR.stop and update docs
d425363 [Shivaram Venkataraman] Some doc fixes for column, generics, group
1f1a7e0 [Shivaram Venkataraman] Some fixes to DataFrame, RDD, SQLContext docs
104ad4e [Shivaram Venkataraman] Check the right env in exists
cf5cd99 [Shivaram Venkataraman] Remove unused numCols argument
85a50ec [Shivaram Venkataraman] Merge pull request #226 from RevolutionAnalytics/master
3eacfc0 [Davies Liu] fix flaky test
733380d [Davies Liu] update R examples (remove master from args)
b21a0da [Davies Liu] Merge pull request #1 from shivaram/log4j-tests
a1493d7 [Shivaram Venkataraman] Address comments
e1f83ab [Shivaram Venkataraman] Send Spark INFO logs to a file in SparkR tests
58276f5 [Shivaram Venkataraman] Merge branch 'R' of https://github.com/amplab-extras/spark into R
52cc92d [Shivaram Venkataraman] Add license to create-docs.sh
6ff5ea2 [Shivaram Venkataraman] Add instructions to generate docs
1f478c5 [Shivaram Venkataraman] Merge branch 'R' of https://github.com/amplab-extras/spark into R
02b4833 [Shivaram Venkataraman] Add a script to generate R docs (Rd, html) Also fix some issues with our documentation
d6d3729 [Davies Liu] enable spark and pyspark tests
0e5a83f [Davies Liu] fix code style
afd8a77 [Davies Liu] Merge branch 'R' of github.com:amplab-extras/spark into R
d87a181 [Davies Liu] fix flaky tests
7100fb9 [Shivaram Venkataraman] Fix libPaths in README
bdf3a14 [Davies Liu] Merge branch 'R' of github.com:amplab-extras/spark into R
05e7375 [Davies Liu] sort generics
b44e371 [Shivaram Venkataraman] Include RStudio instructions in README
855537f [Davies Liu] Merge branch 'R' of github.com:amplab-extras/spark into R
9fb6af3 [Davies Liu] mark R classes/objects are private
423ea3c [Shivaram Venkataraman] Ignore unknown jobj in cleanup
974e4ea [Davies Liu] fix flaky test
410ec18 [Davies Liu] fix zipRDD() tests
d8b24fc [Davies Liu] disable spark and python tests temporary
ce3ca62 [Davies Liu] fix license check
7da0049 [Davies Liu] fix build
2892e29 [Davies Liu] support R in YARN cluster
ebd4d07 [Davies Liu] Merge branch 'R' of github.com:amplab-extras/spark into R
38cbf59 [Davies Liu] fix test of zipRDD()
756ece0 [Shivaram Venkataraman] Update README remove outdated TODO
d436f26 [Davies Liu] add missing files
40d193a [Shivaram Venkataraman] Merge pull request #224 from sun-rui/SPARKR-224-new
1a16cd6 [Davies Liu] rm PROJECT_HOME
56670ef [Davies Liu] rm man page
ba4b80b [Davies Liu] Merge branch 'remote_r' into R
f04080c [Davies Liu] Merge branch 'sparkr-sql' of github.com:amplab-extras/SparkR-pkg into remote_r
028cbfb [Davies Liu] fix exit code of sparkr unit test
42d8b4c [Davies Liu] Merge branch 'R' of github.com:amplab-extras/spark into R
ef26015 [Davies Liu] Merge branch 'R' of github.com:amplab-extras/spark into R
a1870e8 [Shivaram Venkataraman] Merge pull request #214 from sun-rui/SPARKR-156_3
cb6e5e3 [Shivaram Venkataraman] Add scripts to start SparkR on windows
8030847 [Shivaram Venkataraman] Set windows file separators, install dirs
05afef0 [Shivaram Venkataraman] Only stop backend JVM if R launched it
95d2de3 [Davies Liu] fix spark-submit with R scripot
baefd9e [Shivaram Venkataraman] Make bin/sparkR use spark-submit As a part of this move the R initialization functions into first.R and first-submit.R
d6f2bdd [Shivaram Venkataraman] Fix run-tests path
ea90fab [Davies Liu] fix spark-submit with R path and sparkR -h
0e2412c [Davies Liu] fix bin/sparkR
9f6aa1f [Davies Liu] Merge branch 'R' of github.com:amplab-extras/spark into R
479e3fe [Davies Liu] change println() to logging
52ca6e5 [Shivaram Venkataraman] Add missing comma
716b16f [Shivaram Venkataraman] Merge branch 'R' of https://github.com/amplab-extras/spark into R
2d235d4 [Shivaram Venkataraman] Build SparkR with Maven profile
aae881b [Davies Liu] fix rat
ff776aa [Shivaram Venkataraman] Fix style
e4f1937 [Shivaram Venkataraman] Remove DFC example
f7b6936 [Davies Liu] remove Spark prefix for class
043959e [Davies Liu] cleanup
ba53b09 [Davies Liu] support R in spark-submit
f403b4a [Davies Liu] rm .travis.yml
c4a5bdf [Davies Liu] run sparkr tests in Spark
e8fc7ca [Davies Liu] fix .gitignore
35e5755 [Davies Liu] reduce size of example data
50bff63 [Davies Liu] add LICENSE header for R sources
facb6e0 [Davies Liu] add .gitignore for .o, .so, .Rd
18e5eed [Davies Liu] update docs
0a0e632 [Davies Liu] move sparkR into bin/
a76472f [Davies Liu] fix path of assembly jar
df3eeea [Davies Liu] move R/examples into examples/src/main/r
3415cc7 [Davies Liu] move Scala source into core/ and sql/
180fc9c [Davies Liu] move scala
014d253 [Davies Liu] delete man pages
49a8133 [Davies Liu] Merge branch 'remote_r' into R
44994c2 [Davies Liu] Moved files to R/
2fc553f [Shivaram Venkataraman] Merge pull request #222 from davies/column2
b043876 [Davies Liu] fix test
5e610cb [Davies Liu] add more API for Column
6f95d49 [Shivaram Venkataraman] Merge pull request #221 from shivaram/sparkr-stop-start
3214c6d [Shivaram Venkataraman] Merge pull request #217 from hlin09/cleanClosureFix
f5d3355 [Shivaram Venkataraman] Merge pull request #218 from davies/merge
70f620c [Davies Liu] address comments
4b1628d [Davies Liu] Merge branch 'sparkr-sql' of github.com:amplab-extras/SparkR-pkg into merge
3139325 [Shivaram Venkataraman] Merge pull request #212 from davies/toDF
6122e0e [Davies Liu] handle NULL
bc2ff38 [Davies Liu] handle NULL
7f5e70c [Davies Liu] Update SerDe.scala
46454e4 [Davies Liu] address comments
dd52cbc [Shivaram Venkataraman] Merge pull request #220 from shivaram/sparkr-utils-include
662938a [Shivaram Venkataraman] Include utils before SparkR for `head` to work Before this change calling `head` on a DataFrame would not work from the sparkR script as utils would be loaded after SparkR and placed ahead in the search list. This change requires utils to be loaded before SparkR
1bc2998 [Shivaram Venkataraman] Merge pull request #179 from evertlammerts/sparkr-sql
7695d36 [Evert Lammerts] added tests
8190127 [Evert Lammerts] fixed parquetFile signature
d8c8fcc [Shivaram Venkataraman] Merge pull request #219 from shivaram/sparkr-build-final
963c7ee [Davies Liu] Merge branch 'master' into merge
8bff523 [Shivaram Venkataraman] Remove staging repo now that 1.3 is released
e52258f [Davies Liu] Merge branch 'sparkr-sql' of github.com:amplab-extras/SparkR-pkg into toDF
05b9126 [Shivaram Venkataraman] Merge pull request #215 from davies/agg
8e1497d [Davies Liu] Update DataFrame.R
72adb14 [Davies Liu] Update SQLContext.R
66cc92a [Davies Liu] address commets
55c38bc [Shivaram Venkataraman] Merge pull request #216 from davies/select2
3e0555d [Shivaram Venkataraman] Merge pull request #193 from davies/daemon
0467474 [Davies Liu] add more selecter for DataFrame
9a6be74 [Davies Liu] include grouping columns in agg()
e87bb98 [Davies Liu] improve comment and logging
a6dc435 [Davies Liu] remove dependency of jsonlite
26a3621 [Davies Liu] support date.frame and Date/Time
4e4908a [Davies Liu] createDataFrame from rdd
5757b95 [Shivaram Venkataraman] Merge pull request #196 from davies/die
90f2692 [Shivaram Venkataraman] Merge pull request #211 from hlin09/generics
8583968 [Davies Liu] readFully()
46cea3d [Davies Liu] retry
01aa5ee [Davies Liu] add config for using daemon, refactor
ff948db [hlin09] Remove missingOrInteger.
ecdfda1 [hlin09] Remove duplication.
411b751 [Davies Liu] make RStudio happy
8f8813f [Davies Liu] switch back to use parallel
6bccbbf [hlin09] Move roxygen doc back to implementation.
ffd6e8e [Shivaram Venkataraman] Merge pull request #210 from hlin09/hlin09
471c794 [hlin09] Move getJRDD and broadcast's value to 00-generic.R.
89b886d [hlin09] Move setGeneric() to 00-generics.R.
97dde1a [hlin09] Add a test for access operators.
09ff163 [Shivaram Venkataraman] Merge pull request #204 from cafreeman/sparkr-sql
15a713f [cafreeman] Fix example for `dropTempTable`
dc1291b [hlin09] Add checks for namespace access operators in cleanClosure.
b4c0b2e [Davies Liu] use fork package
3db5649 [cafreeman] Merge branch 'sparkr-sql' of https://github.com/amplab-extras/SparkR-pkg into sparkr-sql
789be97 [Shivaram Venkataraman] Merge pull request #207 from shivaram/err-remove
e60578a [cafreeman] update tests to guarantee row order
5eec6fc [Shivaram Venkataraman] Merge pull request #206 from sun-rui/SPARKR-156_2
3f7aed6 [Sun Rui] Fix minor typos in the function description.
a8cebf0 [Shivaram Venkataraman] Remove print statement in SparkRBackendHandler This print statement is noisy for SQL methods which have multiple APIs (like loadDF). We already have a better error message when no valid methods are found
5e3a576 [Sun Rui] Fix indentation.
f3d99a6 [Sun Rui] [SPARKR-156] phase 2: implement zipWithIndex() of the RDD class.
a582810 [cafreeman] Merge branch 'dfMethods' into sparkr-sql
7a5d6fd [cafreeman] `withColumn` and `withColumnRenamed`
c5fa3b9 [cafreeman] New `select` method
bcb0bf5 [Shivaram Venkataraman] Merge pull request #180 from davies/group
9dd6a5a [Davies Liu] Update SparkRBackendHandler.scala
e6fb8d8 [Davies Liu] improve logging
428a99a [Davies Liu] remove test, catch exception
fef99de [cafreeman] `intersect`, `subtract`, `unionAll`
befbd32 [cafreeman] `insertInto`
9d01bcd [cafreeman] `dropTempTable`
d8c1c09 [Davies Liu] add test to start and stop context multiple times
18c6004 [Shivaram Venkataraman] Merge pull request #201 from sun-rui/SPARKR-156_1
dfb399a [Davies Liu] address comments
f06ccec [Sun Rui] Use mapply() instead of for statement.
3c7674f [Davies Liu] Merge branch 'die' of github.com:davies/SparkR-pkg into die
ac8a852 [Davies Liu] close monitor connection in sparkR.stop()
4d0fb56 [Shivaram Venkataraman] Merge pull request #203 from shivaram/sparkr-hive-fix
62b0760 [Shivaram Venkataraman] Fix test hive context package name
47a613f [Shivaram Venkataraman] Fix HiveContext package name
fb3b139 [Davies Liu] fix tests
d0d4626 [Shivaram Venkataraman] Merge pull request #199 from davies/load
8b7fb67 [Davies Liu] fix HiveContext
bb46832 [Davies Liu] Merge branch 'sparkr-sql' of github.com:amplab-extras/SparkR-pkg into load
e9e2a03 [Davies Liu] Merge branch 'sparkr-sql' of github.com:amplab-extras/SparkR-pkg into group
b875b4f [Davies Liu] fix style
de2abfa [Shivaram Venkataraman] Merge pull request #202 from cafreeman/sparkr-sql
3675fcf [cafreeman] Update `explain` and fixed doc for `toJSON`
5fd9575 [Davies Liu] Merge branch 'sparkr-sql' of github.com:amplab-extras/SparkR-pkg into load
6fac596 [Davies Liu] support Column expression in agg()
f10a24e [Davies Liu] address comments
ff8b005 [cafreeman] 'saveAsParquetFile`
a5c2887 [cafreeman] fix test
3fab0f8 [cafreeman] `showDF`
779c102 [cafreeman] `isLocal`
68b11cf [cafreeman] `toJSON`
0ac4abc [cafreeman] 'explain`
20242c4 [cafreeman] clean up docs
6a1fe64 [Shivaram Venkataraman] Merge pull request #198 from cafreeman/sparkr-sql
198c130 [Shivaram Venkataraman] Merge pull request #200 from shivaram/sparkr-sql-build
870acd4 [Shivaram Venkataraman] Use rc2 explicitly
8b9a963 [cafreeman] Merge branch 'sparkr-sql' of https://github.com/amplab-extras/SparkR-pkg into sparkr-sql
bc90115 [cafreeman] Fixed docs
3865f39 [Sun Rui] [SPARKR-156] phase 1: implement zipWithUniqueId() of the RDD class.
a37fd80 [Davies Liu] Update sparkR.R
d18f9d3 [Shivaram Venkataraman] Remove SparkR snapshot build We now have 1.3.0 RC2 on Apache Staging
8de958d [Davies Liu] Update SparkRBackend.scala
4e0becc [Shivaram Venkataraman] Merge pull request #194 from davies/api
197a79b [Davies Liu] add HiveContext (commented)
32aa01d [Shivaram Venkataraman] Merge pull request #191 from felixcheung/doc
5073e07 [Davies Liu] Merge branch 'sparkr-sql' of github.com:amplab-extras/SparkR-pkg into load
7918634 [cafreeman] Fix test
acea146 [cafreeman] remove extra line
74269f3 [cafreeman] Merge branch 'dfMethods' into sparkr-sql
cd7ac8a [Shivaram Venkataraman] Merge pull request #197 from cafreeman/sparkr-sql
494a4dd [cafreeman] update export
e14c328 [cafreeman] `selectExpr`
32b37d1 [cafreeman] Fixed indent in `join` test.
2e7b190 [Felix Cheung] small update on yarn deploy mode.
8ff29d6 [Davies Liu] fix tests
12a6db2 [Davies Liu] Merge branch 'sparkr-sql' of github.com:amplab-extras/SparkR-pkg into api
294ca4a [cafreeman] `join`, `sort`, and `filter`
4fa6343 [cafreeman] Refactor `join` generic for use with `DataFrame`
3f22c8d [Shivaram Venkataraman] Merge pull request #195 from cafreeman/sparkr-sql
2b6f980 [Davies Liu] shutdown the JVM after R process die
e8639c3 [cafreeman] New 1.3 repo and updates to `column.R`
ed9a89f [Davies Liu] address comments
03bcf20 [Davies Liu] Merge branch 'group' of github.com:davies/SparkR-pkg into group
39c253d [Davies Liu] Merge branch 'sparkr-sql' of github.com:amplab-extras/SparkR-pkg into group
98cc97a [Davies Liu] fix test and docs
e2d144a [Felix Cheung] Fixed small typos
3beadcf [Davies Liu] Merge branch 'sparkr-sql' of github.com:amplab-extras/SparkR-pkg into api
06cbc2d [Davies Liu] launch R worker by a daemon
8a676b1 [Shivaram Venkataraman] Merge pull request #188 from davies/column
524c122 [Davies Liu] Merge branch 'sparkr-sql' of github.com:amplab-extras/SparkR-pkg into column
f798402 [Davies Liu] Update column.R
1d0f2ae [Davies Liu] Update DataFrame.R
03402eb [Felix Cheung] Updates as per feedback on sparkR-submit
76cf2e0 [Shivaram Venkataraman] Merge pull request #192 from cafreeman/sparkr-sql
1955a09 [cafreeman] return object instead of a list of one object
f585929 [cafreeman] Fix brackets
e998356 [cafreeman] define generic for 'first' in RDD API
71d66a1 [Davies Liu] fix first(0
8ec21af [Davies Liu] fix signature
acae527 [Davies Liu] refactor
d7b17a4 [Davies Liu] fix approxCountDistinct
7dfe27d [Davies Liu] fix cyclic namespace dependency
8caf5bb [Davies Liu] use S4 methods
5c0bb24 [Felix Cheung] Doc updates: build and running on YARN
773baf0 [Zongheng Yang] Merge pull request #178 from davies/random
862f07c [Shivaram Venkataraman] Merge pull request #190 from shivaram/SPARKR-79
b457833 [Shivaram Venkataraman] Merge pull request #189 from shivaram/stdErrFix
f7caeb8 [Davies Liu] Update SparkRBackend.scala
8c4deae [Shivaram Venkataraman] Remove unused function
6e51c7f [Shivaram Venkataraman] Fix stderr redirection on executors
7afa4c9 [Shivaram Venkataraman] Merge pull request #186 from hlin09/funcDep3
4d36ab1 [hlin09] Add tests for broadcast variables.
3f57e56 [hlin09] Fix comments.
7b72487 [hlin09] Fix comments.
ae05bf1 [Davies Liu] Merge branch 'sparkr-sql' of github.com:amplab-extras/SparkR-pkg into column
abb4bb9 [Davies Liu] add Column and expression
eb8ac11 [Shivaram Venkataraman] Set Spark version 1.3.0 in Windows build
5c72e73 [Davies Liu] wait atmost 100 seconds
e425437 [Shivaram Venkataraman] Merge pull request #177 from lythesia/master
a00f502 [lythesia] fix indents
0346e5f [Davies Liu] address comment
6134649 [Shivaram Venkataraman] Merge pull request #187 from cafreeman/sparkr-sql
ad0935e [lythesia] minor fixes
b0e7f73 [cafreeman] Update `sampleDF` test
7b0d070 [lythesia] keep partitions check
889c265 [cafreeman] numToInt utility function
27dd3a0 [lythesia] modify tests for repartition
cad0f0c [cafreeman] Fix docs and indents
2808dcf [cafreeman] Three more DataFrame methods
5ef66fb [Davies Liu] send back the port via temporary file
3b46429 [Davies Liu] Merge branch 'master' of github.com:amplab-extras/SparkR-pkg into random
798f453 [cafreeman] Merge branch 'sparkr-sql' into dev
9aa4acf [Shivaram Venkataraman] Merge pull request #184 from davies/socket
020bce8 [Shivaram Venkataraman] Merge pull request #183 from cafreeman/sparkr-sql
222e06b [cafreeman] Lazy evaluation and formatting changes
e776324 [Davies Liu] fix import
211cc15 [cafreeman] Merge branch 'sparkr-sql' into dev
3351afd [hlin09] Replaces getDependencies with cleanClosure, to serialize UDFs to workers.
e7c56d6 [lythesia] fix random partition key
50c74b1 [Davies Liu] address comments
083c89f [cafreeman] Remove commented lines an unused import
dfa119b [hlin09] Improve the coverage of processClosure.
a41c9b9 [cafreeman] Merge branch 'wrapper' into sparkr-sql
1cd714f [cafreeman] Wrapper function docs.
db0cd9e [cafreeman] Clean up for wrapper functions
818c19f [cafreeman] Update schema-related functions
a57884e [cafreeman] Remove unused import
d72e830 [cafreeman] Add wrapper for `StructField` and `StructType`
2ea2ecf [lythesia] use generic arg
09b9512 [hlin09] add docs
f4f077c [hlin09] Add recursive cleanClosure for function access.
f84ad27 [hlin09] Merge remote-tracking branch 'upstream/master' into funcDep2
5300766 [Shivaram Venkataraman] Merge pull request #185 from hlin09/hlin09
07aa7c0 [hlin09] Unifies the implementation of lapply with lapplyParitionsWithIndex.
f4dbb0b [Davies Liu] use socket in worker
8282c59 [Davies Liu] Update DataFrame.R
ba495a8 [Davies Liu] Update NAMESPACE
36dffb3 [cafreeman] Add 'head` and `first`
534a95f [cafreeman] Schema-related methods
64f488d [cafreeman] Cache and Persist Methods
30d71fd [cafreeman] Standardize method arguments for DataFrame methods
785898b [Shivaram Venkataraman] Merge pull request #182 from cafreeman/sparkr-sql
2619003 [Shivaram Venkataraman] Merge pull request #181 from cafreeman/master
a9bbe0b [cafreeman] Update existing SparkSQL functions
8c241a3 [cafreeman] Merge with master, include changes to method args
68d6de4 [cafreeman] Fix typos
8d2ec6e [Davies Liu] add sum/max/min/avg/mean
774e687 [Davies Liu] add missing API in SQLContext
1e72b4b [Davies Liu] missing API in SQLContext
3294949 [Chris Freeman] Restore `rdd` argument to `getJRDD`
3a58ebc [Davies Liu] rm unrelated file
8bd93b5 [Davies Liu] fix signature
c652b4c [cafreeman] Update method signatures to use generic arg
48c8827 [Davies Liu] update NAMESPACE
84e2d8c [Davies Liu] groupBy and agg()
7c3ddbd [Davies Liu] create jmode in JVM
9465426 [Davies Liu] load and save
982f342 [lythesia] fix numeric issue
7651d84 [lythesia] fix coalesce
4e712e1 [Davies Liu] use random port in backend
041d22b [Shivaram Venkataraman] Merge pull request #172 from cafreeman/sparkr-sql
0d07770 [cafreeman] Added `limit` and updated `take`
301d8e5 [cafreeman] Remove extraneous map functions
0387db2 [cafreeman] Remove colNames
04c4b65 [lythesia] add repartition/coalesce
231deab [cafreeman] Change reserialize to serializeToBytes
acf7e1a [cafreeman] Rework the Scala to R DataFrame Conversion
481ae37 [cafreeman] Updated stale comments and standardized arg names
21d4a97 [hlin09] Adds cleanClosure to capture the function closures.
d24ffb4 [hlin09] Merge remote-tracking branch 'upstream/master' into funcDep2
8be02de [hlin09] Revert "loop 1-12 test pass."
fddb9cc [hlin09] Revert "add docs"
f8ef0ab [hlin09] Revert "More docs"
8e4b3da [hlin09] Revert "More docs"
57e005b [hlin09] Revert "fix tests."
c10148e [Shivaram Venkataraman] Merge pull request #174 from shivaram/sparkr-runner
910e3be [Shivaram Venkataraman] Add a timeout for initialization Also move sparkRBackend.stop into a finally block
bf52b17 [Shivaram Venkataraman] Merge remote-tracking branch 'amplab-sparkr/master' into sparkr-runner
08102b0 [Shivaram Venkataraman] Merge pull request #176 from lythesia/master
9c77b20 [Chris Freeman] Merge pull request #2 from shivaram/sparkr-sql
179ab38 [lythesia] add try counts and increase time interval
71a73b2 [Shivaram Venkataraman] Use a getter for serialization mode This change encapsulates the semantics of serialization mode for RDDs inside a getter function. For PipelinedRDDs if a backing JavaRDD is available we use that else we fall back to a default serialization mode
06bf250 [Shivaram Venkataraman] Merge pull request #173 from shivaram/windows-space-fix
88bf97f [Shivaram Venkataraman] Create SparkContext for R shell launch
f9268d9 [Shivaram Venkataraman] Fix code review comments
e6ad12d [Shivaram Venkataraman] Update comment describing sparkR-submit
17eda4c [Shivaram Venkataraman] Merge pull request #175 from falaki/docfix
ba2b72b [Hossein] Spark 1.1.0 is default
4cd7d3f [lythesia] retry backend connection
749e2d0 [Hossein] Updated README
bc04cf4 [Shivaram Venkataraman] Use SPARKR_BACKEND_PORT in sparkR.R as default Change SparkRRunner to use EXISTING_SPARKR_BACKEND_PORT to differentiate between the two
22a19ac [Shivaram Venkataraman] Use a semaphore to wait for backend to initalize Also pick a random port to avoid collisions
7f1f0f8 [cafreeman] Move comments to fit 100 char line length
8b84e4e [cafreeman] Make if statements more explicit
ce5d5ab [cafreeman] New tests for Union and Object File
b063320 [cafreeman] Changed 'serialized' to 'serializedMode'
0981dff [Zongheng Yang] Merge pull request #168 from sun-rui/SPARKR-153_2
86fc639 [Shivaram Venkataraman] Move sparkR-submit into pkg/inst
fd8f8a9 [Shivaram Venkataraman] Merge branch 'hqzizania-master'
a33dbea [Shivaram Venkataraman] Merge branch 'master' of https://github.com/hqzizania/SparkR-pkg into hqzizania-master
384e6e2 [Shivaram Venkataraman] Merge pull request #171 from hlin09/hlin09
1f5a6ac [hlin09] fixed comments
7f7596a [cafreeman] Additional handling for "row" serialization
8c3b8c5 [cafreeman] Add test for UnionRDD on "row" serialization
b1141f8 [cafreeman] Fixed formatting issues.
5db30bf [cafreeman] Changed serialized from bool to string
2f0c0b8 [cafreeman] Add check for serialized type
d243dfb [cafreeman] Clean up code
5ff63a2 [cafreeman] Change test from boolean to string
77fec1a [cafreeman] Updated .Rd files
9224989 [cafreeman] Various updates for DataFrame to RRDD
26af62b [cafreeman] DataFrame to RRDD
e004481 [cafreeman] Update UnionRDD test
5292be7 [hlin09] Adds support of pipeRDD().
e2a7560 [Shivaram Venkataraman] Merge pull request #170 from cafreeman/sparkr-sql
5d537f4 [cafreeman] Add pairRDD to Description
b6fa88e [cafreeman] Updating to current master
0cda231 [Sun Rui] [SPARKR-153] phase 2: implement aggregateByKey() and foldByKey().
95ee6b4 [Shivaram Venkataraman] Merge remote-tracking branch 'amplab-sparkr/master' into sparkr-runner
67fbc60 [Shivaram Venkataraman] Add support for SparkR shell to use spark-submit This ensures that SparkConf options are read in both in batch and interactive modes
2271030 [Shivaram Venkataraman] Merge pull request #167 from sun-rui/removePartionByInRDD
7fcb46a [Sun Rui] Remove partitionBy() in RDD.
52f94c4 [Shivaram Venkataraman] Merge pull request #160 from lythesia/master
59e2d54 [lythesia] merge with upstream
5836650 [Zongheng Yang] Merge pull request #163 from sun-rui/SPARKR-153_1
141723e [Sun Rui] fix comments.
f73a07e [Shivaram Venkataraman] Merge pull request #165 from shivaram/sparkr-sql-build
10ffc6d [Shivaram Venkataraman] Set Spark version to 1.3 using staging dependency Also fix the maven build
c91ede2 [Shivaram Venkataraman] Merge pull request #164 from hlin09/hlin09
9d335a9 [hlin09] Makes git to ignore Eclipse meta files.
94066bf [Sun Rui] [SPARKR-153] phase 1: implement fold() and aggregate().
9c391c7 [hqzizania] Merge remote-tracking branch 'upstream/master'
5f29551 [hqzizania] 	modified:   pkg/R/RDD.R 	modified:   pkg/R/context.R
d968664 [lythesia] fix comment
7972858 [Shivaram Venkataraman] Merge pull request #159 from sun-rui/SPARKR-150_2
7690878 [lythesia] separate out pair RDD functions
f4573c1 [Sun Rui] Use reduce() instead of sortBy().take() to get the ordered elements.
63e62ed [Sun Rui] [SPARKR-150] phase 2: implement takeOrdered() and top().
050390b [Shivaram Venkataraman] Fix bugs in inferring R file
8398f2e [Shivaram Venkataraman] Add sparkR-submit helper script Also adjust R file path for YARN cluster mode
bd6705b [Zongheng Yang] Merge pull request #154 from sun-rui/SPARKR-150
c7964c9 [Sun Rui] Merge with upstream master.
7feac38 [Sun Rui] Use default arguments for sortBy() and sortKeyBy().
de2bfb3 [Sun Rui] Fix minor comments and add more test cases.
0c6e071 [Zongheng Yang] Merge pull request #157 from lythesia/master
f5038c0 [lythesia] pull out anonymous functions in groupByKey
ba6f044 [lythesia] fixes for reduceByKeyLocally
343b6ab [Oscar Olmedo] Export sparkR.stop Closes #156 from oscaroboto/master
25639cf [Shivaram Venkataraman] Replace tabs with spaces
bb25920 [Shivaram Venkataraman] Merge branch 'dputler-master'
fd836db [hlin09] fix tests.
24a7f13 [hlin09] More docs
a465165 [hlin09] More docs
6ad4fc3 [hlin09] add docs
b082a35 [lythesia] add reduceByKeyLocally
7ca6512 [Shivaram Venkataraman] First cut of SparkRRunner
193f5fe [hlin09] loop 1-12 test pass.
345f1b8 [dputler] [SPARKR-195] Implemented project style guidelines for if-else statements
8043559 [Sun Rui] Add a TODO to use binary search in the range partitioner.
91b2fd6 [Sun Rui] Add more test cases.
e8ebbe4 [Shivaram Venkataraman] Merge pull request #152 from cafreeman/sparkr-sql
0c53d6c [dputler] Data frames now coerced to lists, and messages issued for a data frame or matrix on how they are parallelized
6d57ec0 [cafreeman] Remove json test file since we're using a temp
ac1ef09 [cafreeman] Update registerTempTable test
d9da451 [Sun Rui] [SPARKR-150] phase 1: implement sortBy() and sortByKey().
08ff30b [Shivaram Venkataraman] Merge pull request #153 from hqzizania/master
9767e8e [hqzizania] 	modified:   pkg/man/collect-methods.Rd
5d69f0a [hqzizania] 	modified:   pkg/R/RDD.R
4914091 [hqzizania] 	modified:   pkg/inst/tests/test_rdd.R
742a68b [cafreeman] Update test_sparkRSQL.R
a95823e [hqzizania] 	modified:   pkg/R/RDD.R
2d04526 [cafreeman] Formatting
fae9bdd [cafreeman] Renamed to SQLUtils.scala
39888ea [Chris Freeman] Update test_sparkSQL.R
fce2453 [cafreeman] Updated documentation for SQLContext
13fbf12 [cafreeman] Regenerated .Rd files
51ecf41 [cafreeman] Updated Scala object
30d7337 [cafreeman] Added SparkSQL test
74b3ed6 [cafreeman] Incorporate code feedback
554bda0 [Zongheng Yang] Merge pull request #147 from shivaram/sparkr-ec2-fixes
a5f4f8f [cafreeman] Squashed commit of the following:
f34bb88 [Shivaram Venkataraman] Remove profiling information from this PR
c662f29 [Zongheng Yang] Merge pull request #146 from shivaram/spark-1.2-build
21e9b74 [Zongheng Yang] Merge pull request #145 from lythesia/master
76f6b9e [Shivaram Venkataraman] Merge pull request #149 from hqzizania/master
1c2dbec [lythesia] minor fix for refactoring join code
5b380d3 [hqzizania] 	modified:   pkg/man/combineByKey.Rd 	modified:   pkg/man/groupByKey.Rd 	modified:   pkg/man/partitionBy.Rd 	modified:   pkg/man/reduceByKey.Rd
98794fe [hqzizania] 	modified:   pkg/R/RDD.R
b66534d [Zongheng Yang] Merge pull request #144 from shivaram/fix-rd-files
60da1df [Shivaram Venkataraman] Initialize timing variables
179aa75 [Shivaram Venkataraman] Bunch of fixes for longer running jobs 1. Increase the timeout for socket connection to wait for long jobs 2. Add some profiling information in worker.R 3. Put temp file writes before stdin writes in RRDD.scala
06d99f0 [Shivaram Venkataraman] Fix URI to have right number of slashes
add97f5 [Shivaram Venkataraman] Use URL encode to create valid URIs for jars
4eec962 [lythesia] refactor join functions
73430c6 [Shivaram Venkataraman] Make SparkR work on paths with spaces on Windows
aaf8f47 [Shivaram Venkataraman] Exclude hadoop client from Spark dependency
227ee42 [Zongheng Yang] Merge pull request #141 from shivaram/SPARKR-140
ac5ceb1 [Shivaram Venkataraman] Fix code review comments
32394de [Shivaram Venkataraman] Regenerate Rd files for SparkR This fixes a number of issues in SparkR man pages. The main changes are 1. Don't export or generate docs for PipelineRDD 2. Fix variable names for Filter, count to match base methods 3. Document missing arguments for sparkR.init, print.jobj etc.
e157bf6 [Shivaram Venkataraman] Use prev_serialized to track if JRDD is serialized This changes introduces a new variable in PipelineRDD environment to track if the prev_jrdd is serialized or not.
7428a7e [Zongheng Yang] Merge pull request #143 from shivaram/SPARKR-181
7dd1797 [Shivaram Venkataraman] Address code review comments
8f81c45 [Shivaram Venkataraman] Remove roxygen export for PipelinedRDD
0cb90f1 [Zongheng Yang] Merge pull request #142 from shivaram/SPARKR-169
d1c6e6c [Shivaram Venkataraman] Buffer stderr from R and return it on Exception This change buffers the last 100 lines from R process and passes these lines back to the driver if we have an exception. This will help users debug why their tasks failed on the cluster
d6c1393 [Shivaram Venkataraman] Suppress warnings from normalizePath
a382835 [Shivaram Venkataraman] Fix serialization tracking in pipelined RDDs When creating a pipeline RDD, we need to check if the JavaRDD belonging to the parent is serialized.
da39529 [Zongheng Yang] Merge pull request #140 from sun-rui/SPARKR-183
2814caa [Sun Rui] Merge with upstream master.
cd2a5b3 [Sun Rui] Add reference to Nagle's algorithm and clean code.
52356b6 [Shivaram Venkataraman] Merge pull request #139 from shivaram/fix-backend-exit
97e5a1f [Sun Rui] [SPARKR-183] Fix the issue that parallelize collect tests are slow.
a9f8e8e [Shivaram Venkataraman] Merge pull request #138 from concretevitamin/fix-collect-test
125ae43 [Shivaram Venkataraman] Fix SparkR backend to exit in more cases This change has two fixes 1. When the workspace is saved (from R or RStudio) the backend connection seems to be closed before the finalizer is run. In such cases we reopen the connection and stop the backend 2. With RStudio when R is restarted, there are port-conflicts which appear due to a race condition between the JVM and rsession restart. This change adds a 1 sec sleep to avoid this race.
12c102a [Zongheng Yang] Simplify a unit test.
9c0637a [Zongheng Yang] Merge pull request #137 from shivaram/fix-docs
0df0e18 [Shivaram Venkataraman] Fix documentation for includePackage
7549f88 [Zongheng Yang] Merge pull request #136 from shivaram/man-updates
7edbe46 [Shivaram Venkataraman] Add missing man pages
9cb9567 [Shivaram Venkataraman] Merge pull request #131 from shivaram/rJavaExpt
1fa722e [Shivaram Venkataraman] Rename to SerDe now
2fcb051 [Shivaram Venkataraman] Rename to SerDeJVMR
d112cf0 [Shivaram Venkataraman] Style fixes
9fd01cc [Shivaram Venkataraman] Remove unnecessary braces
0881931 [Shivaram Venkataraman] Some more style fixes
f00b531 [Shivaram Venkataraman] Address code review comments. Big changes include style fixes throughout for named arguments
c09ba05 [Shivaram Venkataraman] Change jobj id to be just an integer Add a new print.jobj that gets the class name and prints it Also add a utility function isInstanceOf
be05b16 [Shivaram Venkataraman] Check if context, connection exist before stopping
d596a23 [Shivaram Venkataraman] Address code review comments
396e7ac [Shivaram Venkataraman] Changes to make new backend work on Windows This change uses file.path to construct the Java binary path in a OS agnostic way and uses system2 to handle quoting binary paths correctly. Tests pass on Mac OSX and a Windows EC2 instance.
e7a4e03 [Shivaram Venkataraman] Remove unused file BACKEND.md
62f380b [Shivaram Venkataraman] Update worker.R to use new deserialization call
8b9c4e6 [Shivaram Venkataraman] Change RDD name, setName to use new backend
6dcd5c5 [Shivaram Venkataraman] Merge branch 'master' of https://github.com/amplab-extras/SparkR-pkg into rJavaExpt
0873397 [Shivaram Venkataraman] Refactor java object tracking into a new singleton. Also add comments describing each class
95db964 [Shivaram Venkataraman] Add comments, cleanup new R code
bcd4258 [Zongheng Yang] Merge pull request #130 from lythesia/master
74dbc5e [Sun Rui] Match method using parameter types.
7ad4a4d [Sun Rui] Use 1 char to represent types on the backend->client direction.
bace887 [Sun Rui] Use an integer count for the backend java object ID because Uniqueness isn't guaranteed by System.identityHashCode().
b38d04f [Sun Rui] Use 1 char to represent types on the client -> backend direction.
f88bc68 [lythesia] Merge branch 'master' of github.com:lythesia/SparkR-pkg
71d41f5 [lythesia] add test case for fullOuterJoin
eb4f423 [lythesia] --amend
cffecc5 [lythesia] add test case for fullOuterJoin
a547dd2 [Shivaram Venkataraman] Move classTag, rddRef into newJObject call This avoids them getting eagerly garbage collected
1255391 [Shivaram Venkataraman] Add a finalizer for jobj objects This enables Java objects to be garbage collected on the backend when they are no longer referenced in R. Also rename newJava to newJObject to be more consistent with callJMethod
70fa409 [Sun Rui] Add YARN Conf Dir to the class path when launching the backend.
a1108ca [lythesia] add fullOuterJoin in RDD.R
2152727 [Shivaram Venkataraman] Remove empty file
cd08bee [Shivaram Venkataraman] Update all functions to use new backend All unit tests pass.
9de49b7 [Shivaram Venkataraman] Add high level calls for methods, constructors Also update BACKEND.md
5a97ea4 [Shivaram Venkataraman] Add jobj S3 class that holds backend refs
e071d3e [Shivaram Venkataraman] Change SparkRBackend to use general method calls This change uses a custom protocl + JNI to invoke any method on a given object type. Also update serializers, deserializers to make code more concise
49f0404 [Shivaram Venkataraman] Merge pull request #129 from lythesia/master
7f8cd82 [lythesia] update man
4715ed2 [Yi Lu] Update RDD.R
5a53801 [lythesia] fix name,setName
4f3870b [lythesia] add name,setName in RDD.R
1c25700 [Shivaram Venkataraman] Merge pull request #128 from sun-rui/SPARKR-165
c8507d8 [Sun Rui] [SPARKR-165] IS_SCALAR is not present in R before 3.1
2cff2bd [Sun Rui] Add function to invoke Java method.
7a31da1 [Shivaram Venkataraman] Merge branch 'dputler-master'. Closes #119
0ceba82 [Shivaram Venkataraman] Merge branch 'master' of https://github.com/dputler/SparkR-pkg into dputler-master
735f70c [Shivaram Venkataraman] Merge pull request #125 from 7c00/rawcon
fccfe6c [Shivaram Venkataraman] Merge pull request #127 from sun-rui/SPARKR-164
387bd57 [Sun Rui] [SPARKR-164] Temporary files used by SparkR accumulat as time goes on.
5f2268f [Shivaram Venkataraman] Add support to stop backend
5f745c0 [Shivaram Venkataraman] Update notes in backend
22015c1 [Shivaram Venkataraman] Add first cut of SparkR Backend
52821da [Todd Gao] switch the order of packages and function deps
d7b0007 [Todd Gao] remove memCompress
cb6873e [Shivaram Venkataraman] Merge pull request #126 from sun-rui/SPARKR-147
c5962eb [Todd Gao] further optimize using rawConnection
f04c6e0 [Sun Rui] [SPARKR-147] Support multiple directories as input to textFile.
b7de604 [Todd Gao] optimize execFunctionDeps loading in worker.R
4d4fc30 [Shivaram Venkataraman] Merge pull request #122 from cafreeman/master
b508877 [cafreeman] Update SparkR_IDE_Setup.sh
21ed9d7 [cafreeman] Update build.sbt
f73ec16 [cafreeman] Delete SparkR_IDE_Setup_Guide.md
d63b026 [cafreeman] Delete SparkR_Quick_Start_Guide.md
6e6cb62 [cafreeman] Update SparkR_IDE_Setup.sh
bc6042b [cafreeman] Update build.sbt
a8197d5 [cafreeman] Merge remote-tracking branch 'upstream/master'
d671564 [Zongheng Yang] Merge pull request #123 from shivaram/jcheck-void
76b8d00 [Zongheng Yang] Merge pull request #124 from shivaram/master
b690d58 [Shivaram Venkataraman] Specify how to change Spark versions in README
0fb003d [Shivaram Venkataraman] Merge branch 'master' of https://github.com/amplab-extras/SparkR-pkg into jcheck-void
1c227b4 [Shivaram Venkataraman] Also add a check in context.R
96812b6 [Shivaram Venkataraman] Check for exceptions after void method calls
f5c216d [cafreeman] Merge remote-tracking branch 'upstream/master'
90c8933 [Zongheng Yang] Merge pull request #121 from shivaram/fix-sort-order
bd0e3b4 [Shivaram Venkataraman] Fix saveAsTextFile test case
2e55f67 [Shivaram Venkataraman] Merge branch 'master' of https://github.com/amplab-extras/SparkR-pkg into fix-sort-order
f10c607 [Shivaram Venkataraman] Merge pull request #118 from sun-rui/saveAsTextFile
6c9bfc0 [Sun Rui] Merge remote-tracking branch 'SparkR_upstream/master' into saveAsTextFile
6faedbe [cafreeman] Update SparkR_IDE_Setup_Guide.md
57008bc [cafreeman] Update SparkR_IDE_Setup.sh
bb1c17d [cafreeman] Update SparkR_IDE_Setup.sh
538bfdb [cafreeman] Update SparkR_Quick_Start_Guide.md
31322c6 [cafreeman] Update SparkR_IDE_Setup.sh
ca3f593 [Sun Rui] Refactor RRDD code.
df58d95 [cafreeman] Update SparkR_Quick_Start_Guide.md
b488c88 [cafreeman] Rename Spark_IDE_Setup.sh to SparkR_IDE_Setup.sh
b2545a4 [cafreeman] Added IDE Setup Guide
0ffb5de [cafreeman] Merge branch 'master' of https://github.com/cafreeman/SparkR-pkg
bd8fbfb [cafreeman] Merge remote-tracking branch 'upstream/master'
98efa5b [cafreeman] Added Quick Start Guide
3cf88f2 [Shivaram Venkataraman] Sort lists before comparing in unit tests Since Spark doesn't guarantee that shuffle results will always be in the same order, we need to sort the results before comparing for deterministic behavior
d621dbc [Shivaram Venkataraman] Merge pull request #120 from sun-rui/objectFile
c4a44d7 [Sun Rui] Add @seealso in comments and extract some common code into a function.
724e3a4 [cafreeman] Update Spark_IDE_Setup.sh
8153e5a [Sun Rui] [SPARKR-146] Support read/save object files in SparkR.
17f9909 [cafreeman] Update Spark_IDE_Setup.sh
a9eb080 [cafreeman] IDE Shell Script
64d800c [dputler] Merge remote branch 'upstream/master'
1fbdb2e [dputler] Added the ability for the user to specify a text file location throught the use of tilde expansion or just the file name if it is in the working directory.
d83c017 [Shivaram Venkataraman] Merge pull request #113 from sun-rui/stringHashCodeInC
a7d9cdb [Sun Rui] Fix build on Windows.
7d81b05 [Shivaram Venkataraman] Merge pull request #114 from hlin09/hlin09
47c4bb7 [hlin09] fix reviews
a457f7f [Shivaram Venkataraman] Merge pull request #116 from dputler/master
0fa48d1 [Shivaram Venkataraman] Merge pull request #117 from sun-rui/keyBy
85cfeb4 [Sun Rui] [SPARKR-144] Implement saveAsTextFile() in the RDD class.
09083d9 [Sun Rui] Add keyBy() to the RDD class.
caad5d7 [dputler] Adding the script to install software on the Cloudera Quick Start VM.
dca3d05 [hlin09] Minor fix.
ece5f7d [hlin09] Merge remote-tracking branch 'upstream/master' into hlin09
a40874b [hlin09] Use extendible accumulators aggregate the cogroup values.
d0347ce [Zongheng Yang] Merge pull request #112 from sun-rui/outer_join
492f76e [Sun Rui] Refine code and add description.
ba01358 [Shivaram Venkataraman] Merge pull request #115 from sun-rui/SPARKR-130
5c8e46e [Sun Rui] Fix per the review comments.
7190a2c [Sun Rui] Update comment to add a reference to storage levels.
1da705e [hlin09] Fix the review comments.
c4b77be [Sun Rui] [SPARKR-130] Add persist(storageLevel) API to RDD.
b424a1a [hlin09] Add function cogroup().
9770312 [Shivaram Venkataraman] Merge pull request #111 from hlin09/hlin09
cead7df [hlin09] fix review comments.
54f712e [Sun Rui] Implement string hash code in C.
425f0c6 [Sun Rui] Add leftOuterJoin() and rightOuterJoin() to the RDD class.
39509c7 [hlin09] add Rd file for foreach and foreachPartition.
63d6ac7 [hlin09] Adds function foreach() and foreachPartition().
9c954df [Zongheng Yang] Merge pull request #105 from sun-rui/join
c71228d [Sun Rui] Pre-allocate list with fixed length. Add test case for join() using string key.
bc3e9f6 [Shivaram Venkataraman] Merge pull request #108 from concretevitamin/take-optimize
c06fc90 [Zongheng Yang] Fix: only optimize for unserialized dataset case.
d399aeb [Zongheng Yang] Apply size-capping on logical representation instead of physical.
e4217dd [Zongheng Yang] Merge pull request #107 from shivaram/master
7952180 [Shivaram Venkataraman] Copy, use getLocalDirs from Spark Utils.scala
08e24c3 [Zongheng Yang] Merge pull request #109 from hlin09/hlin09
97d4e02 [Zongheng Yang] Min() upper-bound size with actual size.
bb779bf [hlin09] Rename the filter function to filterRDD to follow the API consistency. Filter() is also kept.
ce1661f [Zongheng Yang] Fix slow take(): deserialize only up to necessary # of elements.
4dca9b1 [Shivaram Venkataraman] Merge pull request #106 from hlin09/hlin09
1220d92 [hlin09] Adds function numPartitions().
2326a65 [Shivaram Venkataraman] Use SPARK_LOCAL_DIRS to create tmp files
e119757 [hlin09] Minor fix.
9c24c8b [hlin09] Adds function countByKey().
48fce67 [hlin09] Adds countByValue().
6679eef [Sun Rui] Update documentation for join().
70586b4 [Sun Rui] Add join() to the RDD class.
e6fb999 [Zongheng Yang] Merge pull request #103 from shivaram/rlibdir-fix
a21f146 [Shivaram Venkataraman] Merge pull request #102 from hlin09/hlin09
32eb619 [Shivaram Venkataraman] Merge pull request #104 from sun-rui/add_keys_values
d8692e9 [Sun Rui] Add keys() and values() for the RDD class.
18b9be1 [Shivaram Venkataraman] Allow users to set where SparkR is installed This also adds a warning if somebody tries to call sparkR.init multiple times.
a17f135 [hlin09] Adds tests for flatMap and flatMapValues.
4bcf59b [hlin09] Adds function flatMapValues.
4a193ef [Zongheng Yang] Merge pull request #101 from ashutoshraina/master
60d22f2 [Ashutosh Raina] changed sbt version
5400793 [Zongheng Yang] Merge pull request #98 from shivaram/windows-fixes-build
36d61a7 [Shivaram Venkataraman] Merge pull request #97 from hlin09/hlin09
f7d7d89 [hlin09] Remove redundant code in test.
6bbe823 [hlin09] minor style fix.
9b47f3a [Shivaram Venkataraman] Merge pull request #100 from hnahak87/patch-1
7f6e4ea [Harihar Nahak] Update logistic_regression.R
a605047 [Shivaram Venkataraman] Merge pull request #99 from hlin09/makefile
323151d [hlin09] Fix yar flag in Makefile to remove build error in Maven.
8911897 [hlin09] Make reserialize() private function in package.
79aee73 [Shivaram Venkataraman] Add notes on how to build SparkR on windows
49a99e7 [Shivaram Venkataraman] Clean up some commented code
ddc271b [Shivaram Venkataraman] Only append file:/// to non empty jar paths
a53952e [Shivaram Venkataraman] Add windows build scripts
325b179 [hlin09] Merge remote-tracking branch 'upstream/master' into hlin09
daf5040 [hlin09] Add reserialize() before union if two RDDs are not both serialized.
536afb1 [hlin09] Add new function of union().
7044677 [Shivaram Venkataraman] Merge branch 'master' of https://github.com/amplab-extras/SparkR-pkg into windows-fixes
d22a02d [Zongheng Yang] Merge pull request #94 from shivaram/windows-fixes-stdin
51924f7 [Shivaram Venkataraman] Merge pull request #90 from oscaroboto/master
eb97d85 [Shivaram Venkataraman] Merge pull request #96 from sun-rui/add_clarification_readme
5a128f4 [Sun Rui] Add clarification on setting Spark master when launching the SparkR shell.
187526a [oscaroboto] Update sparkR.R
32c567b [Shivaram Venkataraman] Merge pull request #95 from concretevitamin/master
4cd2d5e [Zongheng Yang] Notes about spark-ec2.
1c28e3b [Shivaram Venkataraman] Merge branch 'master' of https://github.com/amplab-extras/SparkR-pkg into windows-fixes
8e8a029 [Zongheng Yang] Merge pull request #92 from shivaram/sparkr-yarn
721043b [Zongheng Yang] Update README.md with YARN instructions.
1681f58 [Shivaram Venkataraman] Use temporary files for input instead of stdin This fixes a bug for Windows where stdin would get truncated
b084314 [oscaroboto] removed ... from example
44c93d4 [oscaroboto] Added example to SparkR.R
be82dcc [Shivaram Venkataraman] Merge pull request #93 from hlin09/hlin09
868554d [oscaroboto] Update sparkR.R
488ac47 [hlin09] Add generated Rd file of previous added functions, distinct() and mapValues().
b2740ad [hlin09] Add test for filter all elements. Add filter() as alias.
08d3631 [hlin09] Minor style fixes.
2c0e34f [hlin09] Adds function Filter(), which extracts the elements that satisfy a predicate.
5951d3b [Shivaram Venkataraman] Remove SBT plugin
4e70ced [oscaroboto] changed ExecutorEnv to sparkExecutorEnvMap, to make it consistent with sparkEnvirMap
903d18a [oscaroboto] changed executorEnv to sparkExecutorEnvMap,  will do the same in R
f97346e [oscaroboto] executorEnv to lower-case e
88a524e [oscaroboto] Added LD_LIBRARY_PATH to the ExecutorEnv. This is need so that the nodes can find libjvm.so, or if the master has a different LD_LIBRARY_PATH then the nodes. Make sure to export LD_LIBRARY_PATH  that includes the path to libjvm.so in the nodes.
1d208ae [oscaroboto] added the YARN_CONF_DIR to the classpath
8a9b75c [oscaroboto] forgot to change hm and ee inside the for loops
579db58 [Shivaram Venkataraman] Merge pull request #91 from sun-rui/add_max_min
4381efa [Sun Rui] use reduce() to implemement max() and min().
a5459c5 [Shivaram Venkataraman] Consolidate yarn flags
86b04eb [Shivaram Venkataraman] Don't use quotes around yarn
bf0797f [Shivaram Venkataraman] Add dependency on spark yarn module
af5fe77 [Shivaram Venkataraman] Fix SBT build, add dependency tree plugin
4917607 [Sun Rui] Add maximum() and minimum() API to RDD.
51bbbe4 [Shivaram Venkataraman] Changes to make SparkR work with YARN
9d5e3ab [oscaroboto] a few stylistic changes. Also change vars to sparkEnvirMap and eevars to ExecutorEnv, to match sparkR.R
578f545 [oscaroboto] a few stylistic changes
39eea2f [oscaroboto] Modification to dynamically create a sparkContext with YARN. Added .setExecutorEnv to the sparkConf in createSparkContext within the RRDD object. This modification was made together with sparkR.R
17ec42e [oscaroboto] A modification to dynamically create a sparkContext with YARN. sparkR.R modified to pass custom Jar file names and EnvironmentEnv to the sparkConf. RRDD.scala was also modified to accept the new inputs to creatSparkContext.
624ac9d [Shivaram Venkataraman] Merge pull request #87 from sun-rui/SPARKR-125
4f213db [Shivaram Venkataraman] Merge pull request #89 from sun-rui/SPARKR-108
eb833c5 [Shivaram Venkataraman] Merge pull request #88 from hlin09/hlin09
07bf971 [Sun Rui] [SPARKR-108] Implement map-side reduction for reduceByKey().
4accba1 [hlin09] Fixes style and adds an optional param 'numPartition' in distinct().
80d303a [hlin09] typo fixed.
e37a9b5 [hlin09] Adds function distinct() and mapValues().
08dac06 [Sun Rui] [SPARKR-125] Get the iterator of the parent RDD before launching a R worker process in compute() of RRDD/PairwiseRRDD
c4ba53c [Shivaram Venkataraman] Merge pull request #85 from edwardt/master
72a9d27 [root] reorder to keep relative ordering the same
f3fcb10 [root] fix up build.sbt also to match pom.xml
5ecbe3e [root] Make spark verison configurable in build script per ISSUE122
a44e63d [Shivaram Venkataraman] Merge pull request #84 from sun-rui/SPARKR-94
fbb5663 [Sun Rui] Add {} to one-line functions and add a test case for lookup where no match is found.
95beb4e [Shivaram Venkataraman] Merge pull request #82 from edwardt/master
36776c5 [edwardt] missed one 0.9.0 revert
b26deec [Sun Rui] [SPARKR-94] Add a  method to get an element of a pair RDD object by key.
1ba256e [edwardt] Keep 0.9.0 and says uses 1.1.0 by default
5380c43 [root] missed one version
21f74da [root] upgrade to spark version 1.1.0 to match lastest merge list
ddfcde9 [root] merge
67d067a [Shivaram Venkataraman] Merge pull request #81 from sun-rui/SparkR-117
993868f [Sun Rui] [SPARKR-117] Update Spark dependency to 1.1.0
d20661a [Zongheng Yang] Merge pull request #80 from sun-rui/master
0b2da9f [Sun Rui] Update Rd file and add a test case for mapPartitions.
5879648 [Sun Rui] Add mapPartitions() method to RDD for API consistency.
c033461 [Shivaram Venkataraman] Merge pull request #79 from sun-rui/fix-kmeans
f62b77e [Sun Rui] Adjust coding style.
b40911d [Sun Rui] Fix syntax error in examples/kmeans.R.
5304451 [Shivaram Venkataraman] Merge pull request #78 from sun-rui/master
70ffbfb [Sun Rui] Fix a bug that modifications to build.sbt won't trigger rebuilding.
a25696c [Shivaram Venkataraman] Merge pull request #76 from edwardt/addjira
b8bbd93 [edwardt] Update README.md
615d930 [edwardt] Update README.md
e522e69 [edwardt] Update README.md
03e6ced [edwardt] Update README.md
3007015 [root] don't check in gedit buffer file'
c35c9a6 [root] Add where to enter bugs ad feeback
469eae3 [edwardt] Update README.md
61b4a43 [edwardt] Update Makefile (style uniformity)
ce3337d [edwardt] Update README.md
7ff68fc [root] Merge branch 'master' of https://github.com/edwardt/SparkR-pkg
16353f5 [root] add links to devtools and install_github
513b9e5 [Shivaram Venkataraman] Merge pull request #72 from edwardt/master
31608a4 [edwardt] Update Makefile (style uniformity)
4ffe146 [root] Makefile: factor out SPARKR_VERSION to reduce potential copy&paste error; cp & rm called with -f in build/clean phase; .gitignore includes checkpoints and unit test log generated by run-tests.sh
715275f [Zongheng Yang] Merge pull request #68 from shivaram/master
90e2083 [Shivaram Venkataraman] Add return type to hasNext
8eb983d [Shivaram Venkataraman] Fix up comment
2206164 [Shivaram Venkataraman] Delete temporary files after they are read This change deletes temporary files used for communication between Rscript and the JVM once they have been completely read.
5881da7 [Zongheng Yang] Merge pull request #67 from shivaram/improve-shuffle
81251e2 [Shivaram Venkataraman] Address code review comments
a5f573f [Shivaram Venkataraman] Use a better list append in shuffles This is helpful in scenarios where we have a large number of values in a bucket
388e64d [Shivaram Venkataraman] Merge pull request #55 from RevolutionAnalytics/master
e1f95b6 [Zongheng Yang] Merge pull request #65 from concretevitamin/parallelize-fix
fc1a71a [Zongheng Yang] Fix that collect(parallelize(sc,1:72,15)) drops elements.
b8204c5 [Zongheng Yang] Minor: update a URL in README.
86f30c3 [Antonio Piccolboni] better fix for amplab-extras/SparkR-pkg#53
b3c318d [Antonio Piccolboni] delayed loading to have all namespaces available.
f323e97 [Antonio Piccolboni] tentative fix for amplab-extras/SparkR-pkg#53
6f82269 [Zongheng Yang] Merge pull request #48 from shivaram/master
8f433e5 [Shivaram Venkataraman] Move up Hadoop in pom.xml and add back protobufs As Hadoop 1.0.4 doesn't use protobufs, we can't exclude protobufs from Spark always. This change tries to order the dependencies so that the shader first picks up Hadoop's protobufs over Mesos.
bfe7e26 [Shivaram Venkataraman] Merge pull request #36 from RevolutionAnalytics/vectorize-examples
059ae41 [Antonio Piccolboni] and more formatting
9dbd531 [Antonio Piccolboni] more formatting per committer request
948738a [Antonio Piccolboni] converted tabs to spaces per project request
49f5f5a [Shivaram Venkataraman] Merge pull request #35 from shivaram/master
3eb5ad3 [Shivaram Venkataraman] on_failure -> after_failure in travis.yml
139bdee [Shivaram Venkataraman] Cache sbt, maven, ivy dependencies
4ebced2 [Shivaram Venkataraman] Merge pull request #34 from shivaram/master
8437061 [Shivaram Venkataraman] Exclude protobuf from Spark dependency in Maven This avoids pulling in multiple versions of protobuf from Mesos and Hadoop.
91aa527 [Antonio Piccolboni] vectorized version, 36s 10 slices 10^6 per slice. The older version takes 30 sec on 1/10th of data.
f137a57 [Antonio Piccolboni] for rstudio users
1f7ffb0 [Antonio Piccolboni] implemented using matrices and vectorized calls wherever possible
46b23df [Antonio Piccolboni] replace require with library
b15d7db [Antonio Piccolboni] faster parsing
8b7aeb3 [Antonio Piccolboni] 22x speed improvement, 3X mem impovement
c5bce07 [Zongheng Yang] Merge pull request #30 from shivaram/string-tests
21fa2d8 [Shivaram Venkataraman] Fix bug where serialized was not changed for RRRD Reason: When an RRDD is created in getJRDD we have converted any possibly unserialized RDD to a serialized RDD.
9d1ea20 [Shivaram Venkataraman] Merge branch 'master' of github.com:amplab/SparkR-pkg into string-tests
7b9348c [Shivaram Venkataraman] Add tests for partition with string keys Add two tests one with a string array and one from a textFile to test both codepaths
aacd726 [Shivaram Venkataraman] Update README with maven proxy instructions
803e62c [Shivaram Venkataraman] Merge pull request #28 from concretevitamin/master
7c093e6 [Zongheng Yang] Use inherits() to test an object's class.
061c591 [Shivaram Venkataraman] Merge pull request #26 from hafen/master
90f9fda [Ryan Hafen] Fix isRdd() to properly check for class
5b10cc7 [Zongheng Yang] Merge pull request #24 from shivaram/master
7014f83 [Shivaram Venkataraman] Remove unused transformers in maven's pom.xml
b00cea5 [Shivaram Venkataraman] Add support for a Maven build
11ec9b2 [Shivaram Venkataraman] Merge pull request #12 from concretevitamin/pipelined
6b18a90 [Zongheng Yang] Merge branch 'master' into pipelined
57127b8 [Zongheng Yang] Merge pull request #23 from shivaram/master
1ac3940 [Zongheng Yang] Review feedback.
a06fb34 [Zongheng Yang] Remove outdated comment.
0a1fc13 [Shivaram Venkataraman] Fixes for using SparkR with Hadoop2. 1. Exclude ASM, Netty from Hadoop similar to Spark. 2. Concat services files to ensure HDFS filesystems work. 3. Update README with an example
9a1db44 [Zongheng Yang] Merge pull request #22 from shivaram/master
e462448 [Shivaram Venkataraman] Use `$` for calling `put` instead of .jrcall
ed4559a [Shivaram Venkataraman] Add support for passing Spark environment vars This change creates a new `createSparkContext` method in RRDD as we can't pass Map<String, String> through rJava. Also use SPARK_MEM in local mode to increase heap size and update the README with some examples.
10228fb [Shivaram Venkataraman] Merge pull request #20 from concretevitamin/digit-ex
1398d9f [Zongheng Yang] Add linear_solver_mnist to examples/.
d484c2a [Zongheng Yang] Add tests for actions on PipelinedRDD.
d9cb95c [Zongheng Yang] Add setCheckpointDir() to context.R; comment fix.
f8bc8a9 [Zongheng Yang] Minor edits per Shivaram's comments.
8cd67f7 [Shivaram Venkataraman] Merge pull request #15 from shivaram/master
d4468a9 [Shivaram Venkataraman] Remove trailing comma
e2714b8 [Shivaram Venkataraman] Remove Apache Staging repo and update README
334eace [Zongheng Yang] Add a multi-transformation test to benchmark on pipelining.
5650ad7 [Zongheng Yang] Put serialized field inside env for both RDD and PipelinedRDD.
0b9e8bb [Zongheng Yang] First cut at PipelinedRDD.
a4c431e [Zongheng Yang] Add `isCheckpointed` field and checkpoint().
dac0795 [Zongheng Yang] Minor inline comment style fix.
bfb8e26 [Zongheng Yang] Add isCached field (inside an env) and unpersist().
295bff6 [Zongheng Yang] Merge pull request #11 from shivaram/master
4cb209c [Shivaram Venkataraman] Search rLibDir in worker before libPaths This ensures we pick up the SparkR intended and not an older version installed on the same machine
ef198ff [Zongheng Yang] Merge pull request #10 from shivaram/unit-tests
e0557a8 [Shivaram Venkataraman] Update travis to install plyr
8b18bc1 [Shivaram Venkataraman] Merge branch 'master' of github.com:amplab/SparkR-pkg into unit-tests
4a9ca31 [Shivaram Venkataraman] Use smaller broadcast and plyr instead of Matrix Matrix package takes around 2s to load and slows down unit tests.
21c6a61 [Zongheng Yang] Merge pull request #8 from shivaram/master
08c2947 [Shivaram Venkataraman] Move dev install directory to front of libPaths
bda42ee [Shivaram Venkataraman] Merge pull request #7 from JoshRosen/travis
cc5f5c0 [Josh Rosen] Add Travis CI integration (using craigcitro/r-travis)
b6c864b [Shivaram Venkataraman] Merge pull request #6 from concretevitamin/env-style-fix
4fcef22 [Zongheng Yang] Use one style ($) for accessing names in environments.
8a948c6 [Shivaram Venkataraman] Merge pull request #4 from shivaram/master
24978eb [Shivaram Venkataraman] Update README to use install_github
8899db4 [Shivaram Venkataraman] Update TODO.md
91792de [Shivaram Venkataraman] Update Spark requirements
f34f4bf [Shivaram Venkataraman] Check tests for failures and output error msg
cd750d3 [Shivaram Venkataraman] Update run-tests to use new path
1877b7c [Shivaram Venkataraman] Unset R_TESTS to make tests work with R CMD check Also silence Akka remoting logs and update Makefile to build on log4j changes
e60e18a [Shivaram Venkataraman] Update README to remove Spark installation notes
4450189 [Shivaram Venkataraman] Add Spark 0.9 dependency from Apache Staging Also clean up assembly jar from inst on make clean
5eb2131 [Shivaram Venkataraman] Update repo path in README
ec8210e [Shivaram Venkataraman] Remove broadcastId hack as it is public in Spark
9f0e080 [Shivaram Venkataraman] Merge branch 'install-github'
5c88fbd [Shivaram Venkataraman] Add helper script to run tests
77450a1 [Shivaram Venkataraman] Remove dependency on Spark Logging
6cb00d1 [Shivaram Venkataraman] Update README and add helper script install-dev.sh
28346ca [Shivaram Venkataraman] Only normalize if SPARK_HOME is not empty
0fd6571 [Shivaram Venkataraman] Normalize SPARK_HOME before passing it
ff96d5c [Shivaram Venkataraman] Pass in SPARK_HOME and jar file path
34c4dce [Shivaram Venkataraman] Move src into pkg and update Makefile This enables the package to be installed using install_github using devtools and automates the build procedure.
b25afed [Shivaram Venkataraman] Change package name to edu.berkeley.cs.amplab
c691464 [Shivaram Venkataraman] Add Apache 2.0 License file
27a4a4b [Shivaram Venkataraman] Add notes on how to compile roxygen2 docs
ca63844 [Shivaram Venkataraman] Add broadcast documentation Also generate documentation for sample, takeSample etc.
e4dd976 [Shivaram Venkataraman] Update TODO.md
e42d435 [Shivaram Venkataraman] Add support for broadcast variables
6b638e7 [Shivaram Venkataraman] Add the assembly jar to SparkContext
bf24e32 [Shivaram Venkataraman] Merge branch 'master' of github.com:amplab/SparkR-pkg
43c05ce [Zongheng Yang] Fix a flaky/incorrect test for sampleRDD().
c6a9dfc [Zongheng Yang] Initial port of the kmeans example.
6885581 [Zongheng Yang] Implement element-level sampleRDD() and takeSample() with tests.
d3a4987 [Zongheng Yang] Add a test for lapplyPartitionsWithIndex on pairwise RDD.
c7899c1 [Zongheng Yang] Add lapplyPartitionsWithIndex, with a test and an alias function.
a9a7436 [Shivaram Venkataraman] Add DFC example from Tselil, Benjamin and Jonah
fbc5a95 [Zongheng Yang] Implement take() and takeSample().
c4a3409 [Shivaram Venkataraman] Use RDD instead of RRDD
dfad3f5 [Zongheng Yang] Add test_utils.R: a unit test for convertJListToRList().
a45227d [Zongheng Yang] Update .gitignore.
238fe6e [Zongheng Yang] Add a unit test for textFile().
a88898b [Zongheng Yang] Rename test_rrd to test_rrdd
10c8baa [Shivaram Venkataraman] Make SparkR work as a standalone package. Changes include: 1. Adding a new `sbt` project that builds RRDD.scala 2. Change the onLoad functions to load the assembly jar for SparkR 3. Set rLibDir in RRDD.scala and worker.R to load things correctly
78adcd8 [Shivaram Venkataraman] Add a gitignore
ca6108f [Shivaram Venkataraman] Merge branch 'SparkR-scalacode' of ../SparkR
999bd61 [Shivaram Venkataraman] Update collectPartition in R and use ClassTag
c58f63e [Shivaram Venkataraman] Update collectPartition in R and use ClassTag
48265fd [Shivaram Venkataraman] Use new version of collectPartitions in take
d4fe086 [Shivaram Venkataraman] Move collectPartitions to JavaRDDLike Also remove numPartitions in JavaRDD and update R code
bfecd7b [Shivaram Venkataraman] Scala 2.10 changes 1. Update sparkR script 2. Use classTag instead of classManifest
092a4b3 [Shivaram Venkataraman] Add combineByKey, update TODO
ac0d81d [Shivaram Venkataraman] Add more documentation
d1dc3fa [Shivaram Venkataraman] Add more documentation
c515e3a [Shivaram Venkataraman] Update TODO
db56a34 [Shivaram Venkataraman] Add a test case for include package
41cea51 [Shivaram Venkataraman] Ensure all parent environments are serialized. Also add a test case with an inline function
a978e84 [Shivaram Venkataraman] Add support to include packages in the worker
12bf8ce [Shivaram Venkataraman] Add support to include packages in the worker
fb7e72c [Shivaram Venkataraman] Cleanup TODO
16ac314 [Shivaram Venkataraman] Add documentation for functions in context, sparkR
85b1d25 [Shivaram Venkataraman] Set license to Apache
88f1101 [Shivaram Venkataraman] Add unit test running instructions
c40768e [Shivaram Venkataraman] Update TODO
0c7efbf [Shivaram Venkataraman] Refactor RRDD.scala and add comments to functions
5880d42 [Shivaram Venkataraman] Refactor RRDD.scala and add comments to functions
2dee36c [Shivaram Venkataraman] Remove empty test file
a82219b [Shivaram Venkataraman] Update TODOs
5db00dc [Shivaram Venkataraman] Add reduceByKey, groupByKey and refactor shuffle Other changes include 1. Adding unit tests for basic RDD functions and shuffle 2. Add a word count example 3. Change the dependency serialization to handle double loading of SparkR    package 4. Allow partitionBy to operate on any RDDs to create pair-wise RDD.
f196479 [Shivaram Venkataraman] Add reduceByKey, groupByKey and refactor shuffle Other changes include 1. Adding unit tests for basic RDD functions and shuffle 2. Add a word count example 3. Change the dependency serialization to handle double loading of SparkR    package 4. Allow partitionBy to operate on any RDDs to create pair-wise RDD.
987e36f [Shivaram Venkataraman] Add perf todo
0b03265 [Shivaram Venkataraman] Update TODO with testing, docs todo
685aaad [Zongheng Yang] First cut at refactoring worker.R. Remove pairwiseWorker.R.
95b9ddc [Zongheng Yang] First cut at refactoring worker.R. Remove pairwiseWorker.R.
4f00895 [Zongheng Yang] Remove the unnecessary `pairwise' flag in RRDD class. Reasons:
75d36d9 [Zongheng Yang] Working versions: partitionBy() and collectPartition() for RRDD.
e3fbd9d [Zongheng Yang] Working versions: partitionBy() and collectPartition() for RRDD.
67a4335 [Zongheng Yang] Add unit test for parallelize() and collect() pairwise data.
100ae65 [Zongheng Yang] Properly parallelize() and collect() pairwise data.
cd0a5e2 [Zongheng Yang] Properly parallelize() and collect() pairwise data.
aea16c3 [Zongheng Yang] WIP: second cut at partitionBy. Running into R/Scala communication issues.
45eb943 [Zongheng Yang] WIP: second cut at partitionBy. Running into R/Scala communication issues.
11c893b [Zongheng Yang] WIP: need to figure out the logic of (whether or not) shipping a hash func
82c201a [Zongheng Yang] WIP: need to figure out the logic of (whether or not) shipping a hash func
b3bfad2 [Zongheng Yang] Update TODO: take() done.
0e45293 [Zongheng Yang] Add ability to parallelize key-val collections in R.
f60406a [Zongheng Yang] Add ability to parallelize key-val collections in R.
7d7fe3b [Zongheng Yang] Re-implement take(): take a partition at a time and append.
a054e55 [Zongheng Yang] Fix take() tests(): mode difference.
9de0935 [Zongheng Yang] Implement take() for RRDD.
1e4427e [Zongheng Yang] Implement take() for RRDD.
ec3cd67 [Shivaram Venkataraman] Use temp file in Spark to pipe output
417aaed [Shivaram Venkataraman] Use temp file in Spark to pipe output
bb0a3c3 [Shivaram Venkataraman] Add conf directory to classpath
9594d8a [Shivaram Venkataraman] Clean up LR example
3b26b58 [Shivaram Venkataraman] Add a list of things to do.
cabce68 [Shivaram Venkataraman] Fix warnings from package check
fde3f9c [Shivaram Venkataraman] Flatten by default and disable recursive unlist
ab2e061 [Shivaram Venkataraman] Create LIB_DIR before installing SparkR package
555220a [Shivaram Venkataraman] Add readme and update Makefile
1319cda [Shivaram Venkataraman] Make standalone programs run with sparkR
ae19fa8 [Shivaram Venkataraman] Add support for cache and use `tempfile`
4e89ca4 [Shivaram Venkataraman] Add support for apply, reduce, count Also serialize closures using `save` and add two examples
25a0bea [Shivaram Venkataraman] Add support for apply, reduce, count Also serialize closures using `save` and add two examples
f50223f [Zongheng Yang] Make parallelize() and collect() use lists. Add a few more tests for them.
fc7693f [Zongheng Yang] Refactor and enhance the previously added unit test a little bit.
6de9b81 [Zongheng Yang] Add a simple unit test for parallelize().
8b95155 [Zongheng Yang] Add testthat skeleton infrastructure
ef305bf [Zongheng Yang] parallelize() followed by collect() now work for vectors/lists of strings and numerics (should work for other primitives as well).
dc16af4 [Zongheng Yang] Comment: toArray() allocates memory for a copy
f50121e [Zongheng Yang] Make parallelize() return JavaRDD[Array[Byte]]. Add RRDD.scala with a helper function in the singleton object.
46eb063 [Zongheng Yang] Make parallelize() return JavaRDD[Array[Byte]]. Add RRDD.scala with a helper function in the singleton object.
6b4938a [Zongheng Yang] parallelize(): a raw can be parallelized by JavaSparkContext and get back JavaRDD
978aa0f [Zongheng Yang] Add parallelize() skeleton: only return serialized slices now
84c1fd2 [Zongheng Yang] Use .jsimplify() to get around generic List's get() type erasure problem
f16b891 [Zongheng Yang] Convert a few reflectionc alls to .jcall
1284c13 [Zongheng Yang] WIP on collect(): JavaListToRList() failed with errors.
4c2e516 [Zongheng Yang] Add simple prototype of S4 class RRDD. Make TextFile() returns an RRDD.
82aa17a [Zongheng Yang] Add textFile()
83ce63f [Zongheng Yang] Create a JavaSparkContext and save it in .sparkEnv using sparkR.init()
01cdf0e [Zongheng Yang] Add Makefile for SparkR
fc9cae2 [Shivaram Venkataraman] Add skeleton R package
---
 .gitignore                                    |    2 +
 .rat-excludes                                 |    2 +
 R/.gitignore                                  |    6 +
 R/DOCUMENTATION.md                            |   12 +
 R/README.md                                   |   67 +
 R/WINDOWS.md                                  |   13 +
 R/create-docs.sh                              |   46 +
 R/install-dev.bat                             |   27 +
 R/install-dev.sh                              |   36 +
 R/log4j.properties                            |   28 +
 R/pkg/DESCRIPTION                             |   35 +
 R/pkg/NAMESPACE                               |  182 ++
 R/pkg/R/DataFrame.R                           | 1270 ++++++++++++++
 R/pkg/R/RDD.R                                 | 1539 +++++++++++++++++
 R/pkg/R/SQLContext.R                          |  520 ++++++
 R/pkg/R/SQLTypes.R                            |   64 +
 R/pkg/R/backend.R                             |  115 ++
 R/pkg/R/broadcast.R                           |   86 +
 R/pkg/R/client.R                              |   57 +
 R/pkg/R/column.R                              |  199 +++
 R/pkg/R/context.R                             |  225 +++
 R/pkg/R/deserialize.R                         |  184 ++
 R/pkg/R/generics.R                            |  543 ++++++
 R/pkg/R/group.R                               |  132 ++
 R/pkg/R/jobj.R                                |  101 ++
 R/pkg/R/pairRDD.R                             |  789 +++++++++
 R/pkg/R/serialize.R                           |  195 +++
 R/pkg/R/sparkR.R                              |  266 +++
 R/pkg/R/utils.R                               |  467 +++++
 R/pkg/R/zzz.R                                 |   21 +
 R/pkg/inst/profile/general.R                  |   22 +
 R/pkg/inst/profile/shell.R                    |   31 +
 R/pkg/inst/tests/test_binaryFile.R            |   90 +
 R/pkg/inst/tests/test_binary_function.R       |   68 +
 R/pkg/inst/tests/test_broadcast.R             |   48 +
 R/pkg/inst/tests/test_context.R               |   50 +
 R/pkg/inst/tests/test_includePackage.R        |   57 +
 R/pkg/inst/tests/test_parallelize_collect.R   |  109 ++
 R/pkg/inst/tests/test_rdd.R                   |  644 +++++++
 R/pkg/inst/tests/test_shuffle.R               |  209 +++
 R/pkg/inst/tests/test_sparkSQL.R              |  695 ++++++++
 R/pkg/inst/tests/test_take.R                  |   67 +
 R/pkg/inst/tests/test_textFile.R              |  162 ++
 R/pkg/inst/tests/test_utils.R                 |  137 ++
 R/pkg/inst/worker/daemon.R                    |   52 +
 R/pkg/inst/worker/worker.R                    |  128 ++
 R/pkg/src/Makefile                            |   27 +
 R/pkg/src/Makefile.win                        |   27 +
 R/pkg/src/string_hash_code.c                  |   49 +
 R/pkg/tests/run-all.R                         |   21 +
 R/run-tests.sh                                |   39 +
 bin/sparkR                                    |   39 +
 bin/sparkR.cmd                                |   23 +
 bin/sparkR2.cmd                               |   26 +
 core/pom.xml                                  |   51 +
 .../org/apache/spark/api/r/RBackend.scala     |  145 ++
 .../apache/spark/api/r/RBackendHandler.scala  |  223 +++
 .../scala/org/apache/spark/api/r/RRDD.scala   |  450 +++++
 .../scala/org/apache/spark/api/r/SerDe.scala  |  340 ++++
 .../org/apache/spark/deploy/RRunner.scala     |   92 +
 .../org/apache/spark/deploy/SparkSubmit.scala |   73 +-
 .../spark/deploy/SparkSubmitArguments.scala   |    8 +-
 dev/run-tests                                 |   15 +
 dev/run-tests-codes.sh                        |    1 +
 dev/run-tests-jenkins                         |    2 +
 docs/README.md                                |   12 +-
 docs/_layouts/global.html                     |    1 +
 docs/_plugins/copy_api_dirs.rb                |   15 +-
 examples/src/main/r/kmeans.R                  |   93 +
 examples/src/main/r/linear_solver_mnist.R     |  107 ++
 examples/src/main/r/logistic_regression.R     |   62 +
 examples/src/main/r/pi.R                      |   46 +
 examples/src/main/r/wordcount.R               |   42 +
 .../spark/launcher/CommandBuilderUtils.java   |    8 +-
 .../launcher/SparkSubmitCommandBuilder.java   |   87 +-
 .../launcher/CommandBuilderUtilsSuite.java    |    6 +-
 pom.xml                                       |    3 +
 .../org/apache/spark/sql/GroupedData.scala    |    2 +-
 .../org/apache/spark/sql/api/r/SQLUtils.scala |  127 ++
 .../spark/deploy/yarn/ApplicationMaster.scala |    3 +
 .../yarn/ApplicationMasterArguments.scala     |   11 +
 .../org/apache/spark/deploy/yarn/Client.scala |   13 +-
 .../spark/deploy/yarn/ClientArguments.scala   |   11 +
 83 files changed, 12043 insertions(+), 55 deletions(-)
 create mode 100644 R/.gitignore
 create mode 100644 R/DOCUMENTATION.md
 create mode 100644 R/README.md
 create mode 100644 R/WINDOWS.md
 create mode 100755 R/create-docs.sh
 create mode 100644 R/install-dev.bat
 create mode 100755 R/install-dev.sh
 create mode 100644 R/log4j.properties
 create mode 100644 R/pkg/DESCRIPTION
 create mode 100644 R/pkg/NAMESPACE
 create mode 100644 R/pkg/R/DataFrame.R
 create mode 100644 R/pkg/R/RDD.R
 create mode 100644 R/pkg/R/SQLContext.R
 create mode 100644 R/pkg/R/SQLTypes.R
 create mode 100644 R/pkg/R/backend.R
 create mode 100644 R/pkg/R/broadcast.R
 create mode 100644 R/pkg/R/client.R
 create mode 100644 R/pkg/R/column.R
 create mode 100644 R/pkg/R/context.R
 create mode 100644 R/pkg/R/deserialize.R
 create mode 100644 R/pkg/R/generics.R
 create mode 100644 R/pkg/R/group.R
 create mode 100644 R/pkg/R/jobj.R
 create mode 100644 R/pkg/R/pairRDD.R
 create mode 100644 R/pkg/R/serialize.R
 create mode 100644 R/pkg/R/sparkR.R
 create mode 100644 R/pkg/R/utils.R
 create mode 100644 R/pkg/R/zzz.R
 create mode 100644 R/pkg/inst/profile/general.R
 create mode 100644 R/pkg/inst/profile/shell.R
 create mode 100644 R/pkg/inst/tests/test_binaryFile.R
 create mode 100644 R/pkg/inst/tests/test_binary_function.R
 create mode 100644 R/pkg/inst/tests/test_broadcast.R
 create mode 100644 R/pkg/inst/tests/test_context.R
 create mode 100644 R/pkg/inst/tests/test_includePackage.R
 create mode 100644 R/pkg/inst/tests/test_parallelize_collect.R
 create mode 100644 R/pkg/inst/tests/test_rdd.R
 create mode 100644 R/pkg/inst/tests/test_shuffle.R
 create mode 100644 R/pkg/inst/tests/test_sparkSQL.R
 create mode 100644 R/pkg/inst/tests/test_take.R
 create mode 100644 R/pkg/inst/tests/test_textFile.R
 create mode 100644 R/pkg/inst/tests/test_utils.R
 create mode 100644 R/pkg/inst/worker/daemon.R
 create mode 100644 R/pkg/inst/worker/worker.R
 create mode 100644 R/pkg/src/Makefile
 create mode 100644 R/pkg/src/Makefile.win
 create mode 100644 R/pkg/src/string_hash_code.c
 create mode 100644 R/pkg/tests/run-all.R
 create mode 100755 R/run-tests.sh
 create mode 100755 bin/sparkR
 create mode 100644 bin/sparkR.cmd
 create mode 100644 bin/sparkR2.cmd
 create mode 100644 core/src/main/scala/org/apache/spark/api/r/RBackend.scala
 create mode 100644 core/src/main/scala/org/apache/spark/api/r/RBackendHandler.scala
 create mode 100644 core/src/main/scala/org/apache/spark/api/r/RRDD.scala
 create mode 100644 core/src/main/scala/org/apache/spark/api/r/SerDe.scala
 create mode 100644 core/src/main/scala/org/apache/spark/deploy/RRunner.scala
 create mode 100644 examples/src/main/r/kmeans.R
 create mode 100644 examples/src/main/r/linear_solver_mnist.R
 create mode 100644 examples/src/main/r/logistic_regression.R
 create mode 100644 examples/src/main/r/pi.R
 create mode 100644 examples/src/main/r/wordcount.R
 create mode 100644 sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala

diff --git a/.gitignore b/.gitignore
index d162fa9cca994..d54d21b802be8 100644
--- a/.gitignore
+++ b/.gitignore
@@ -63,6 +63,8 @@ ec2/lib/
 rat-results.txt
 scalastyle.txt
 scalastyle-output.xml
+R-unit-tests.log
+R/unit-tests.out
 
 # For Hive
 metastore_db/
diff --git a/.rat-excludes b/.rat-excludes
index 8c61e67a0c7d1..8aca5a7f7a967 100644
--- a/.rat-excludes
+++ b/.rat-excludes
@@ -67,3 +67,5 @@ logs
 .*scalastyle-output.xml
 .*dependency-reduced-pom.xml
 known_translations
+DESCRIPTION
+NAMESPACE
diff --git a/R/.gitignore b/R/.gitignore
new file mode 100644
index 0000000000000..9a5889ba28b2a
--- /dev/null
+++ b/R/.gitignore
@@ -0,0 +1,6 @@
+*.o
+*.so
+*.Rd
+lib
+pkg/man
+pkg/html
diff --git a/R/DOCUMENTATION.md b/R/DOCUMENTATION.md
new file mode 100644
index 0000000000000..931d01549b265
--- /dev/null
+++ b/R/DOCUMENTATION.md
@@ -0,0 +1,12 @@
+# SparkR Documentation
+
+SparkR documentation is generated using in-source comments annotated using using
+`roxygen2`. After making changes to the documentation, to generate man pages,
+you can run the following from an R console in the SparkR home directory
+
+    library(devtools)
+    devtools::document(pkg="./pkg", roclets=c("rd"))
+
+You can verify if your changes are good by running
+
+    R CMD check pkg/
diff --git a/R/README.md b/R/README.md
new file mode 100644
index 0000000000000..a6970e39b55f3
--- /dev/null
+++ b/R/README.md
@@ -0,0 +1,67 @@
+# R on Spark
+
+SparkR is an R package that provides a light-weight frontend to use Spark from R.
+
+### SparkR development
+
+#### Build Spark
+
+Build Spark with [Maven](http://spark.apache.org/docs/latest/building-spark.html#building-with-buildmvn) and include the `-PsparkR` profile to build the R package. For example to use the default Hadoop versions you can run
+```
+  build/mvn -DskipTests -Psparkr package
+```
+
+#### Running sparkR
+
+You can start using SparkR by launching the SparkR shell with
+
+    ./bin/sparkR
+
+The `sparkR` script automatically creates a SparkContext with Spark by default in
+local mode. To specify the Spark master of a cluster for the automatically created
+SparkContext, you can run
+
+    ./bin/sparkR --master "local[2]"
+
+To set other options like driver memory, executor memory etc. you can pass in the [spark-submit](http://spark.apache.org/docs/latest/submitting-applications.html) arguments to `./bin/sparkR`
+
+#### Using SparkR from RStudio
+
+If you wish to use SparkR from RStudio or other R frontends you will need to set some environment variables which point SparkR to your Spark installation. For example 
+```
+# Set this to where Spark is installed
+Sys.setenv(SPARK_HOME="/Users/shivaram/spark")
+# This line loads SparkR from the installed directory
+.libPaths(c(file.path(Sys.getenv("SPARK_HOME"), "R", "lib"), .libPaths()))
+library(SparkR)
+sc <- sparkR.init(master="local")
+```
+
+#### Making changes to SparkR
+
+The [instructions](https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark) for making contributions to Spark also apply to SparkR.
+If you only make R file changes (i.e. no Scala changes) then you can just re-install the R package using `R/install-dev.sh` and test your changes.
+Once you have made your changes, please include unit tests for them and run existing unit tests using the `run-tests.sh` script as described below. 
+    
+#### Generating documentation
+
+The SparkR documentation (Rd files and HTML files) are not a part of the source repository. To generate them you can run the script `R/create-docs.sh`. This script uses `devtools` and `knitr` to generate the docs and these packages need to be installed on the machine before using the script.
+    
+### Examples, Unit tests
+
+SparkR comes with several sample programs in the `examples/src/main/r` directory.
+To run one of them, use `./bin/sparkR <filename> <args>`. For example:
+
+    ./bin/sparkR examples/src/main/r/pi.R local[2]
+
+You can also run the unit-tests for SparkR by running (you need to install the [testthat](http://cran.r-project.org/web/packages/testthat/index.html) package first):
+
+    R -e 'install.packages("testthat", repos="http://cran.us.r-project.org")'
+    ./R/run-tests.sh
+
+### Running on YARN
+The `./bin/spark-submit` and `./bin/sparkR` can also be used to submit jobs to YARN clusters. You will need to set YARN conf dir before doing so. For example on CDH you can run
+```
+export YARN_CONF_DIR=/etc/hadoop/conf
+./bin/spark-submit --master yarn examples/src/main/r/pi.R 4
+```
diff --git a/R/WINDOWS.md b/R/WINDOWS.md
new file mode 100644
index 0000000000000..3f889c0ca3d1e
--- /dev/null
+++ b/R/WINDOWS.md
@@ -0,0 +1,13 @@
+## Building SparkR on Windows
+
+To build SparkR on Windows, the following steps are required
+
+1. Install R (>= 3.1) and [Rtools](http://cran.r-project.org/bin/windows/Rtools/). Make sure to
+include Rtools and R in `PATH`.
+2. Install
+[JDK7](http://www.oracle.com/technetwork/java/javase/downloads/jdk7-downloads-1880260.html) and set
+`JAVA_HOME` in the system environment variables.
+3. Download and install [Maven](http://maven.apache.org/download.html). Also include the `bin`
+directory in Maven in `PATH`.
+4. Set `MAVEN_OPTS` as described in [Building Spark](http://spark.apache.org/docs/latest/building-spark.html).
+5. Open a command shell (`cmd`) in the Spark directory and run `mvn -DskipTests -Psparkr package`
diff --git a/R/create-docs.sh b/R/create-docs.sh
new file mode 100755
index 0000000000000..4194172a2e115
--- /dev/null
+++ b/R/create-docs.sh
@@ -0,0 +1,46 @@
+#!/bin/bash
+
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Script to create API docs for SparkR
+# This requires `devtools` and `knitr` to be installed on the machine.
+
+# After running this script the html docs can be found in 
+# $SPARK_HOME/R/pkg/html
+
+# Figure out where the script is
+export FWDIR="$(cd "`dirname "$0"`"; pwd)"
+pushd $FWDIR
+
+# Generate Rd file
+Rscript -e 'library(devtools); devtools::document(pkg="./pkg", roclets=c("rd"))'
+
+# Install the package
+./install-dev.sh
+
+# Now create HTML files
+
+# knit_rd puts html in current working directory
+mkdir -p pkg/html
+pushd pkg/html
+
+Rscript -e 'library(SparkR, lib.loc="../../lib"); library(knitr); knit_rd("SparkR")'
+
+popd
+
+popd
diff --git a/R/install-dev.bat b/R/install-dev.bat
new file mode 100644
index 0000000000000..008a5c668bc45
--- /dev/null
+++ b/R/install-dev.bat
@@ -0,0 +1,27 @@
+@echo off
+
+rem
+rem Licensed to the Apache Software Foundation (ASF) under one or more
+rem contributor license agreements.  See the NOTICE file distributed with
+rem this work for additional information regarding copyright ownership.
+rem The ASF licenses this file to You under the Apache License, Version 2.0
+rem (the "License"); you may not use this file except in compliance with
+rem the License.  You may obtain a copy of the License at
+rem
+rem    http://www.apache.org/licenses/LICENSE-2.0
+rem
+rem Unless required by applicable law or agreed to in writing, software
+rem distributed under the License is distributed on an "AS IS" BASIS,
+rem WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+rem See the License for the specific language governing permissions and
+rem limitations under the License.
+rem
+
+rem Install development version of SparkR
+rem
+
+set SPARK_HOME=%~dp0..
+
+MKDIR %SPARK_HOME%\R\lib
+
+R.exe CMD INSTALL --library="%SPARK_HOME%\R\lib"  %SPARK_HOME%\R\pkg\
diff --git a/R/install-dev.sh b/R/install-dev.sh
new file mode 100755
index 0000000000000..55ed6f4be1a4a
--- /dev/null
+++ b/R/install-dev.sh
@@ -0,0 +1,36 @@
+#!/bin/bash
+
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# This scripts packages the SparkR source files (R and C files) and
+# creates a package that can be loaded in R. The package is by default installed to
+# $FWDIR/lib and the package can be loaded by using the following command in R:
+#
+#   library(SparkR, lib.loc="$FWDIR/lib")
+#
+# NOTE(shivaram): Right now we use $SPARK_HOME/R/lib to be the installation directory
+# to load the SparkR package on the worker nodes.
+
+
+FWDIR="$(cd `dirname $0`; pwd)"
+LIB_DIR="$FWDIR/lib"
+
+mkdir -p $LIB_DIR
+
+# Install R
+R CMD INSTALL --library=$LIB_DIR $FWDIR/pkg/
diff --git a/R/log4j.properties b/R/log4j.properties
new file mode 100644
index 0000000000000..701adb2a3da1d
--- /dev/null
+++ b/R/log4j.properties
@@ -0,0 +1,28 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Set everything to be logged to the file target/unit-tests.log
+log4j.rootCategory=INFO, file
+log4j.appender.file=org.apache.log4j.FileAppender
+log4j.appender.file.append=true
+log4j.appender.file.file=R-unit-tests.log
+log4j.appender.file.layout=org.apache.log4j.PatternLayout
+log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
+
+# Ignore messages below warning level from Jetty, because it's a bit verbose
+log4j.logger.org.eclipse.jetty=WARN
+org.eclipse.jetty.LEVEL=WARN
diff --git a/R/pkg/DESCRIPTION b/R/pkg/DESCRIPTION
new file mode 100644
index 0000000000000..1842b97d43651
--- /dev/null
+++ b/R/pkg/DESCRIPTION
@@ -0,0 +1,35 @@
+Package: SparkR
+Type: Package
+Title: R frontend for Spark
+Version: 1.4.0
+Date: 2013-09-09
+Author: The Apache Software Foundation
+Maintainer: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
+Imports:
+    methods
+Depends:
+    R (>= 3.0),
+    methods,
+Suggests:
+    testthat
+Description: R frontend for Spark
+License: Apache License (== 2.0)
+Collate:
+    'generics.R'
+    'jobj.R'
+    'SQLTypes.R'
+    'RDD.R'
+    'pairRDD.R'
+    'column.R'
+    'group.R'
+    'DataFrame.R'
+    'SQLContext.R'
+    'broadcast.R'
+    'context.R'
+    'deserialize.R'
+    'serialize.R'
+    'sparkR.R'
+    'backend.R'
+    'client.R'
+    'utils.R'
+    'zzz.R'
diff --git a/R/pkg/NAMESPACE b/R/pkg/NAMESPACE
new file mode 100644
index 0000000000000..a354cdce74afa
--- /dev/null
+++ b/R/pkg/NAMESPACE
@@ -0,0 +1,182 @@
+#exportPattern("^[[:alpha:]]+")
+exportClasses("RDD")
+exportClasses("Broadcast")
+exportMethods(
+              "aggregateByKey",
+              "aggregateRDD",
+              "cache",
+              "checkpoint",
+              "coalesce",
+              "cogroup",
+              "collect",
+              "collectAsMap",
+              "collectPartition",
+              "combineByKey",
+              "count",
+              "countByKey",
+              "countByValue",
+              "distinct",
+              "Filter",
+              "filterRDD",
+              "first",
+              "flatMap",
+              "flatMapValues",
+              "fold",
+              "foldByKey",
+              "foreach",
+              "foreachPartition",
+              "fullOuterJoin",
+              "glom",
+              "groupByKey",
+              "join",
+              "keyBy",
+              "keys",
+              "length",
+              "lapply",
+              "lapplyPartition",
+              "lapplyPartitionsWithIndex",
+              "leftOuterJoin",
+              "lookup",
+              "map",
+              "mapPartitions",
+              "mapPartitionsWithIndex",
+              "mapValues",
+              "maximum",
+              "minimum",
+              "numPartitions",
+              "partitionBy",
+              "persist",
+              "pipeRDD",
+              "reduce",
+              "reduceByKey",
+              "reduceByKeyLocally",
+              "repartition",
+              "rightOuterJoin",
+              "sampleRDD",
+              "saveAsTextFile",
+              "saveAsObjectFile",
+              "sortBy",
+              "sortByKey",
+              "sumRDD",
+              "take",
+              "takeOrdered",
+              "takeSample",
+              "top",
+              "unionRDD",
+              "unpersist",
+              "value",
+              "values",
+              "zipRDD",
+              "zipWithIndex",
+              "zipWithUniqueId"
+             )
+
+# S3 methods exported
+export(
+       "textFile",
+       "objectFile",
+       "parallelize",
+       "hashCode",
+       "includePackage",
+       "broadcast",
+       "setBroadcastValue",
+       "setCheckpointDir"
+      )
+export("sparkR.init")
+export("sparkR.stop")
+export("print.jobj")
+useDynLib(SparkR, stringHashCode)
+importFrom(methods, setGeneric, setMethod, setOldClass)
+
+# SparkRSQL
+
+exportClasses("DataFrame")
+
+exportMethods("columns",
+              "distinct",
+              "dtypes",
+              "explain",
+              "filter",
+              "groupBy",
+              "head",
+              "insertInto",
+              "intersect",
+              "isLocal",
+              "limit",
+              "orderBy",
+              "names",
+              "printSchema",
+              "registerTempTable",
+              "repartition",
+              "sampleDF",
+              "saveAsParquetFile",
+              "saveAsTable",
+              "saveDF",
+              "schema",
+              "select",
+              "selectExpr",
+              "show",
+              "showDF",
+              "sortDF",
+              "subtract",
+              "toJSON",
+              "toRDD",
+              "unionAll",
+              "where",
+              "withColumn",
+              "withColumnRenamed")
+
+exportClasses("Column")
+
+exportMethods("abs",
+              "alias",
+              "approxCountDistinct",
+              "asc",
+              "avg",
+              "cast",
+              "contains",
+              "countDistinct",
+              "desc",
+              "endsWith",
+              "getField",
+              "getItem",
+              "isNotNull",
+              "isNull",
+              "last",
+              "like",
+              "lower",
+              "max",
+              "mean",
+              "min",
+              "rlike",
+              "sqrt",
+              "startsWith",
+              "substr",
+              "sum",
+              "sumDistinct",
+              "upper")
+
+exportClasses("GroupedData")
+exportMethods("agg")
+
+export("sparkRSQL.init",
+       "sparkRHive.init")
+
+export("cacheTable",
+       "clearCache",
+       "createDataFrame",
+       "createExternalTable",
+       "dropTempTable",
+       "jsonFile",
+       "jsonRDD",
+       "loadDF",
+       "parquetFile",
+       "sql",
+       "table",
+       "tableNames",
+       "tables",
+       "toDF",
+       "uncacheTable")
+
+export("print.structType",
+       "print.structField")
diff --git a/R/pkg/R/DataFrame.R b/R/pkg/R/DataFrame.R
new file mode 100644
index 0000000000000..feafd56909a67
--- /dev/null
+++ b/R/pkg/R/DataFrame.R
@@ -0,0 +1,1270 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# DataFrame.R - DataFrame class and methods implemented in S4 OO classes
+
+#' @include jobj.R SQLTypes.R RDD.R pairRDD.R column.R group.R
+NULL
+
+setOldClass("jobj")
+
+#' @title S4 class that represents a DataFrame
+#' @description DataFrames can be created using functions like
+#'              \code{jsonFile}, \code{table} etc.
+#' @rdname DataFrame
+#' @seealso jsonFile, table
+#'
+#' @param env An R environment that stores bookkeeping states of the DataFrame
+#' @param sdf A Java object reference to the backing Scala DataFrame
+#' @export
+setClass("DataFrame",
+         slots = list(env = "environment",
+                      sdf = "jobj"))
+
+setMethod("initialize", "DataFrame", function(.Object, sdf, isCached) {
+  .Object@env <- new.env()
+  .Object@env$isCached <- isCached
+  
+  .Object@sdf <- sdf
+  .Object
+})
+
+#' @rdname DataFrame
+#' @export
+dataFrame <- function(sdf, isCached = FALSE) {
+  new("DataFrame", sdf, isCached)
+}
+
+############################ DataFrame Methods ##############################################
+
+#' Print Schema of a DataFrame
+#' 
+#' Prints out the schema in tree format
+#' 
+#' @param x A SparkSQL DataFrame
+#' 
+#' @rdname printSchema
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' printSchema(df)
+#'}
+setMethod("printSchema",
+          signature(x = "DataFrame"),
+          function(x) {
+            schemaString <- callJMethod(schema(x)$jobj, "treeString")
+            cat(schemaString)
+          })
+
+#' Get schema object
+#' 
+#' Returns the schema of this DataFrame as a structType object.
+#' 
+#' @param x A SparkSQL DataFrame
+#' 
+#' @rdname schema
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' dfSchema <- schema(df)
+#'}
+setMethod("schema",
+          signature(x = "DataFrame"),
+          function(x) {
+            structType(callJMethod(x@sdf, "schema"))
+          })
+
+#' Explain
+#' 
+#' Print the logical and physical Catalyst plans to the console for debugging.
+#' 
+#' @param x A SparkSQL DataFrame
+#' @param extended Logical. If extended is False, explain() only prints the physical plan.
+#' @rdname explain
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' explain(df, TRUE)
+#'}
+setMethod("explain",
+          signature(x = "DataFrame"),
+          function(x, extended = FALSE) {
+            queryExec <- callJMethod(x@sdf, "queryExecution")
+            if (extended) {
+              cat(callJMethod(queryExec, "toString"))
+            } else {
+              execPlan <- callJMethod(queryExec, "executedPlan")
+              cat(callJMethod(execPlan, "toString"))
+            }
+          })
+
+#' isLocal
+#'
+#' Returns True if the `collect` and `take` methods can be run locally
+#' (without any Spark executors).
+#'
+#' @param x A SparkSQL DataFrame
+#'
+#' @rdname isLocal
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' isLocal(df)
+#'}
+setMethod("isLocal",
+          signature(x = "DataFrame"),
+          function(x) {
+            callJMethod(x@sdf, "isLocal")
+          })
+
+#' ShowDF
+#'
+#' Print the first numRows rows of a DataFrame
+#'
+#' @param x A SparkSQL DataFrame
+#' @param numRows The number of rows to print. Defaults to 20.
+#'
+#' @rdname showDF
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' showDF(df)
+#'}
+setMethod("showDF",
+          signature(x = "DataFrame"),
+          function(x, numRows = 20) {
+            cat(callJMethod(x@sdf, "showString", numToInt(numRows)), "\n")
+          })
+
+#' show
+#'
+#' Print the DataFrame column names and types
+#'
+#' @param x A SparkSQL DataFrame
+#'
+#' @rdname show
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' show(df)
+#'}
+setMethod("show", "DataFrame",
+          function(object) {
+            cols <- lapply(dtypes(object), function(l) {
+              paste(l, collapse = ":")
+            })
+            s <- paste(cols, collapse = ", ")
+            cat(paste("DataFrame[", s, "]\n", sep = ""))
+          })
+
+#' DataTypes
+#' 
+#' Return all column names and their data types as a list
+#' 
+#' @param x A SparkSQL DataFrame
+#' 
+#' @rdname dtypes
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' dtypes(df)
+#'}
+setMethod("dtypes",
+          signature(x = "DataFrame"),
+          function(x) {
+            lapply(schema(x)$fields(), function(f) {
+              c(f$name(), f$dataType.simpleString())
+            })
+          })
+
+#' Column names
+#' 
+#' Return all column names as a list
+#' 
+#' @param x A SparkSQL DataFrame
+#' 
+#' @rdname columns
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' columns(df)
+#'}
+setMethod("columns",
+          signature(x = "DataFrame"),
+          function(x) {
+            sapply(schema(x)$fields(), function(f) {
+              f$name()
+            })
+          })
+
+#' @rdname columns
+#' @export
+setMethod("names",
+          signature(x = "DataFrame"),
+          function(x) {
+            columns(x)
+          })
+
+#' Register Temporary Table
+#' 
+#' Registers a DataFrame as a Temporary Table in the SQLContext
+#' 
+#' @param x A SparkSQL DataFrame
+#' @param tableName A character vector containing the name of the table
+#' 
+#' @rdname registerTempTable
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' registerTempTable(df, "json_df")
+#' new_df <- sql(sqlCtx, "SELECT * FROM json_df")
+#'}
+setMethod("registerTempTable",
+          signature(x = "DataFrame", tableName = "character"),
+          function(x, tableName) {
+              callJMethod(x@sdf, "registerTempTable", tableName)
+          })
+
+#' insertInto
+#'
+#' Insert the contents of a DataFrame into a table registered in the current SQL Context.
+#'
+#' @param x A SparkSQL DataFrame
+#' @param tableName A character vector containing the name of the table
+#' @param overwrite A logical argument indicating whether or not to overwrite
+#' the existing rows in the table.
+#'
+#' @rdname insertInto
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' df <- loadDF(sqlCtx, path, "parquet")
+#' df2 <- loadDF(sqlCtx, path2, "parquet")
+#' registerTempTable(df, "table1")
+#' insertInto(df2, "table1", overwrite = TRUE)
+#'}
+setMethod("insertInto",
+          signature(x = "DataFrame", tableName = "character"),
+          function(x, tableName, overwrite = FALSE) {
+            callJMethod(x@sdf, "insertInto", tableName, overwrite)
+          })
+
+#' Cache
+#' 
+#' Persist with the default storage level (MEMORY_ONLY).
+#' 
+#' @param x A SparkSQL DataFrame
+#' 
+#' @rdname cache-methods
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' cache(df)
+#'}
+setMethod("cache",
+          signature(x = "DataFrame"),
+          function(x) {
+            cached <- callJMethod(x@sdf, "cache")
+            x@env$isCached <- TRUE
+            x
+          })
+
+#' Persist
+#'
+#' Persist this DataFrame with the specified storage level. For details of the
+#' supported storage levels, refer to
+#' http://spark.apache.org/docs/latest/programming-guide.html#rdd-persistence.
+#'
+#' @param x The DataFrame to persist
+#' @rdname persist
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' persist(df, "MEMORY_AND_DISK")
+#'}
+setMethod("persist",
+          signature(x = "DataFrame", newLevel = "character"),
+          function(x, newLevel) {
+            callJMethod(x@sdf, "persist", getStorageLevel(newLevel))
+            x@env$isCached <- TRUE
+            x
+          })
+
+#' Unpersist
+#'
+#' Mark this DataFrame as non-persistent, and remove all blocks for it from memory and
+#' disk.
+#'
+#' @param x The DataFrame to unpersist
+#' @param blocking Whether to block until all blocks are deleted
+#' @rdname unpersist-methods
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' persist(df, "MEMORY_AND_DISK")
+#' unpersist(df)
+#'}
+setMethod("unpersist",
+          signature(x = "DataFrame"),
+          function(x, blocking = TRUE) {
+            callJMethod(x@sdf, "unpersist", blocking)
+            x@env$isCached <- FALSE
+            x
+          })
+
+#' Repartition
+#'
+#' Return a new DataFrame that has exactly numPartitions partitions.
+#'
+#' @param x A SparkSQL DataFrame
+#' @param numPartitions The number of partitions to use.
+#' @rdname repartition
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' newDF <- repartition(df, 2L)
+#'}
+setMethod("repartition",
+          signature(x = "DataFrame", numPartitions = "numeric"),
+          function(x, numPartitions) {
+            sdf <- callJMethod(x@sdf, "repartition", numToInt(numPartitions))
+            dataFrame(sdf)     
+          })
+
+#' toJSON
+#'
+#' Convert the rows of a DataFrame into JSON objects and return an RDD where
+#' each element contains a JSON string.
+#'
+#' @param x A SparkSQL DataFrame
+#' @return A StringRRDD of JSON objects
+#' @rdname tojson
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' newRDD <- toJSON(df)
+#'}
+setMethod("toJSON",
+          signature(x = "DataFrame"),
+          function(x) {
+            rdd <- callJMethod(x@sdf, "toJSON")
+            jrdd <- callJMethod(rdd, "toJavaRDD")
+            RDD(jrdd, serializedMode = "string")
+          })
+
+#' saveAsParquetFile
+#'
+#' Save the contents of a DataFrame as a Parquet file, preserving the schema. Files written out
+#' with this method can be read back in as a DataFrame using parquetFile().
+#'
+#' @param x A SparkSQL DataFrame
+#' @param path The directory where the file is saved
+#' @rdname saveAsParquetFile
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' saveAsParquetFile(df, "/tmp/sparkr-tmp/")
+#'}
+setMethod("saveAsParquetFile",
+          signature(x = "DataFrame", path = "character"),
+          function(x, path) {
+            invisible(callJMethod(x@sdf, "saveAsParquetFile", path))
+          })
+
+#' Distinct
+#'
+#' Return a new DataFrame containing the distinct rows in this DataFrame.
+#'
+#' @param x A SparkSQL DataFrame
+#' @rdname distinct
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' distinctDF <- distinct(df)
+#'}
+setMethod("distinct",
+          signature(x = "DataFrame"),
+          function(x) {
+            sdf <- callJMethod(x@sdf, "distinct")
+            dataFrame(sdf)
+          })
+
+#' SampleDF
+#'
+#' Return a sampled subset of this DataFrame using a random seed.
+#'
+#' @param x A SparkSQL DataFrame
+#' @param withReplacement Sampling with replacement or not
+#' @param fraction The (rough) sample target fraction
+#' @rdname sampleDF
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' collect(sampleDF(df, FALSE, 0.5)) 
+#' collect(sampleDF(df, TRUE, 0.5))
+#'}
+setMethod("sampleDF",
+          # TODO : Figure out how to send integer as java.lang.Long to JVM so
+          # we can send seed as an argument through callJMethod
+          signature(x = "DataFrame", withReplacement = "logical",
+                    fraction = "numeric"),
+          function(x, withReplacement, fraction) {
+            if (fraction < 0.0) stop(cat("Negative fraction value:", fraction))
+            sdf <- callJMethod(x@sdf, "sample", withReplacement, fraction)
+            dataFrame(sdf)
+          })
+
+#' Count
+#' 
+#' Returns the number of rows in a DataFrame
+#' 
+#' @param x A SparkSQL DataFrame
+#' 
+#' @rdname count
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' count(df)
+#' }
+setMethod("count",
+          signature(x = "DataFrame"),
+          function(x) {
+            callJMethod(x@sdf, "count")
+          })
+
+#' Collects all the elements of a Spark DataFrame and coerces them into an R data.frame.
+#'
+#' @param x A SparkSQL DataFrame
+#' @param stringsAsFactors (Optional) A logical indicating whether or not string columns
+#' should be converted to factors. FALSE by default.
+
+#' @rdname collect-methods
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' collected <- collect(df)
+#' firstName <- collected[[1]]$name
+#' }
+setMethod("collect",
+          signature(x = "DataFrame"),
+          function(x, stringsAsFactors = FALSE) {
+            # listCols is a list of raw vectors, one per column
+            listCols <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "dfToCols", x@sdf)
+            cols <- lapply(listCols, function(col) {
+              objRaw <- rawConnection(col)
+              numRows <- readInt(objRaw)
+              col <- readCol(objRaw, numRows)
+              close(objRaw)
+              col
+            })
+            names(cols) <- columns(x)
+            do.call(cbind.data.frame, list(cols, stringsAsFactors = stringsAsFactors))
+          })
+
+#' Limit
+#' 
+#' Limit the resulting DataFrame to the number of rows specified.
+#' 
+#' @param x A SparkSQL DataFrame
+#' @param num The number of rows to return
+#' @return A new DataFrame containing the number of rows specified.
+#' 
+#' @rdname limit
+#' @export
+#' @examples
+#' \dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' limitedDF <- limit(df, 10)
+#' }
+setMethod("limit",
+          signature(x = "DataFrame", num = "numeric"),
+          function(x, num) {
+            res <- callJMethod(x@sdf, "limit", as.integer(num))
+            dataFrame(res)
+          })
+
+# Take the first NUM rows of a DataFrame and return a the results as a data.frame
+
+#' @rdname take
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' take(df, 2)
+#' }
+setMethod("take",
+          signature(x = "DataFrame", num = "numeric"),
+          function(x, num) {
+            limited <- limit(x, num)
+            collect(limited)
+          })
+
+#' Head
+#'
+#' Return the first NUM rows of a DataFrame as a data.frame. If NUM is NULL, 
+#' then head() returns the first 6 rows in keeping with the current data.frame 
+#' convention in R.
+#'
+#' @param x A SparkSQL DataFrame
+#' @param num The number of rows to return. Default is 6.
+#' @return A data.frame
+#'
+#' @rdname head
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' head(df)
+#' }
+setMethod("head",
+          signature(x = "DataFrame"),
+          function(x, num = 6L) {
+          # Default num is 6L in keeping with R's data.frame convention
+            take(x, num)
+          })
+
+#' Return the first row of a DataFrame
+#'
+#' @param x A SparkSQL DataFrame
+#'
+#' @rdname first
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' first(df)
+#' }
+setMethod("first",
+          signature(x = "DataFrame"),
+          function(x) {
+            take(x, 1)
+          })
+
+#' toRDD()
+#' 
+#' Converts a Spark DataFrame to an RDD while preserving column names.
+#' 
+#' @param x A Spark DataFrame
+#' 
+#' @rdname DataFrame
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' rdd <- toRDD(df)
+#' }
+setMethod("toRDD",
+          signature(x = "DataFrame"),
+          function(x) {
+            jrdd <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "dfToRowRDD", x@sdf)
+            colNames <- callJMethod(x@sdf, "columns")
+            rdd <- RDD(jrdd, serializedMode = "row")
+            lapply(rdd, function(row) {
+              names(row) <- colNames
+              row
+            })
+          })
+
+#' GroupBy
+#'
+#' Groups the DataFrame using the specified columns, so we can run aggregation on them.
+#'
+#' @param x a DataFrame
+#' @return a GroupedData
+#' @seealso GroupedData
+#' @rdname DataFrame
+#' @export
+#' @examples
+#' \dontrun{
+#'   # Compute the average for all numeric columns grouped by department.
+#'   avg(groupBy(df, "department"))
+#'
+#'   # Compute the max age and average salary, grouped by department and gender.
+#'   agg(groupBy(df, "department", "gender"), salary="avg", "age" -> "max")
+#' }
+setMethod("groupBy",
+           signature(x = "DataFrame"),
+           function(x, ...) {
+             cols <- list(...)
+             if (length(cols) >= 1 && class(cols[[1]]) == "character") {
+               sgd <- callJMethod(x@sdf, "groupBy", cols[[1]], listToSeq(cols[-1]))
+             } else {
+               jcol <- lapply(cols, function(c) { c@jc })
+               sgd <- callJMethod(x@sdf, "groupBy", listToSeq(jcol))
+             }
+             groupedData(sgd)
+           })
+
+#' Agg
+#'
+#' Compute aggregates by specifying a list of columns
+#'
+#' @rdname DataFrame
+#' @export
+setMethod("agg",
+          signature(x = "DataFrame"),
+          function(x, ...) {
+            agg(groupBy(x), ...)
+          })
+
+
+############################## RDD Map Functions ##################################
+# All of the following functions mirror the existing RDD map functions,           #
+# but allow for use with DataFrames by first converting to an RRDD before calling #
+# the requested map function.                                                     #
+###################################################################################
+
+#' @rdname lapply
+setMethod("lapply",
+          signature(X = "DataFrame", FUN = "function"),
+          function(X, FUN) {
+            rdd <- toRDD(X)
+            lapply(rdd, FUN)
+          })
+
+#' @rdname lapply
+setMethod("map",
+          signature(X = "DataFrame", FUN = "function"),
+          function(X, FUN) {
+            lapply(X, FUN)
+          })
+
+#' @rdname flatMap
+setMethod("flatMap",
+          signature(X = "DataFrame", FUN = "function"),
+          function(X, FUN) {
+            rdd <- toRDD(X)
+            flatMap(rdd, FUN)
+          })
+
+#' @rdname lapplyPartition
+setMethod("lapplyPartition",
+          signature(X = "DataFrame", FUN = "function"),
+          function(X, FUN) {
+            rdd <- toRDD(X)
+            lapplyPartition(rdd, FUN)
+          })
+
+#' @rdname lapplyPartition
+setMethod("mapPartitions",
+          signature(X = "DataFrame", FUN = "function"),
+          function(X, FUN) {
+            lapplyPartition(X, FUN)
+          })
+
+#' @rdname foreach
+setMethod("foreach",
+          signature(x = "DataFrame", func = "function"),
+          function(x, func) {
+            rdd <- toRDD(x)
+            foreach(rdd, func)
+          })
+
+#' @rdname foreach
+setMethod("foreachPartition",
+          signature(x = "DataFrame", func = "function"),
+          function(x, func) {
+            rdd <- toRDD(x)
+            foreachPartition(rdd, func)
+          })
+
+
+############################## SELECT ##################################
+
+getColumn <- function(x, c) {
+  column(callJMethod(x@sdf, "col", c))
+}
+
+#' @rdname select
+setMethod("$", signature(x = "DataFrame"),
+          function(x, name) {
+            getColumn(x, name)
+          })
+
+setMethod("$<-", signature(x = "DataFrame"),
+          function(x, name, value) {
+            stopifnot(class(value) == "Column")
+            cols <- columns(x)
+            if (name %in% cols) {
+              cols <- lapply(cols, function(c) {
+                if (c == name) {
+                  alias(value, name)
+                } else {
+                  col(c)
+                }
+              })
+              nx <- select(x, cols)
+            } else {
+              nx <- withColumn(x, name, value)
+            }
+            x@sdf <- nx@sdf
+            x
+          })
+
+#' @rdname select
+setMethod("[[", signature(x = "DataFrame"),
+          function(x, i) {
+            if (is.numeric(i)) {
+              cols <- columns(x)
+              i <- cols[[i]]
+            }
+            getColumn(x, i)
+          })
+
+#' @rdname select
+setMethod("[", signature(x = "DataFrame", i = "missing"),
+          function(x, i, j, ...) {
+            if (is.numeric(j)) {
+              cols <- columns(x)
+              j <- cols[j]
+            }
+            if (length(j) > 1) {
+              j <- as.list(j)
+            }
+            select(x, j)
+          })
+
+#' Select
+#'
+#' Selects a set of columns with names or Column expressions.
+#' @param x A DataFrame
+#' @param col A list of columns or single Column or name
+#' @return A new DataFrame with selected columns
+#' @export
+#' @rdname select
+#' @examples
+#' \dontrun{
+#'   select(df, "*")
+#'   select(df, "col1", "col2")
+#'   select(df, df$name, df$age + 1)
+#'   select(df, c("col1", "col2"))
+#'   select(df, list(df$name, df$age + 1))
+#'   # Columns can also be selected using `[[` and `[`
+#'   df[[2]] == df[["age"]]
+#'   df[,2] == df[,"age"]
+#'   # Similar to R data frames columns can also be selected using `$`
+#'   df$age
+#' }
+setMethod("select", signature(x = "DataFrame", col = "character"),
+          function(x, col, ...) {
+            sdf <- callJMethod(x@sdf, "select", col, toSeq(...))
+            dataFrame(sdf)
+          })
+
+#' @rdname select
+#' @export
+setMethod("select", signature(x = "DataFrame", col = "Column"),
+          function(x, col, ...) {
+            jcols <- lapply(list(col, ...), function(c) {
+              c@jc
+            })
+            sdf <- callJMethod(x@sdf, "select", listToSeq(jcols))
+            dataFrame(sdf)
+          })
+
+#' @rdname select
+#' @export
+setMethod("select",
+          signature(x = "DataFrame", col = "list"),
+          function(x, col) {
+            cols <- lapply(col, function(c) {
+              if (class(c)== "Column") {
+                c@jc
+              } else {
+                col(c)@jc
+              }
+            })
+            sdf <- callJMethod(x@sdf, "select", listToSeq(cols))
+            dataFrame(sdf)
+          })
+
+#' SelectExpr
+#'
+#' Select from a DataFrame using a set of SQL expressions.
+#'
+#' @param x A DataFrame to be selected from.
+#' @param expr A string containing a SQL expression
+#' @param ... Additional expressions
+#' @return A DataFrame
+#' @rdname selectExpr
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' selectExpr(df, "col1", "(col2 * 5) as newCol")
+#' }
+setMethod("selectExpr",
+          signature(x = "DataFrame", expr = "character"),
+          function(x, expr, ...) {
+            exprList <- list(expr, ...)
+            sdf <- callJMethod(x@sdf, "selectExpr", listToSeq(exprList))
+            dataFrame(sdf)
+          })
+
+#' WithColumn
+#'
+#' Return a new DataFrame with the specified column added.
+#'
+#' @param x A DataFrame
+#' @param colName A string containing the name of the new column.
+#' @param col A Column expression.
+#' @return A DataFrame with the new column added.
+#' @rdname withColumn
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' newDF <- withColumn(df, "newCol", df$col1 * 5)
+#' }
+setMethod("withColumn",
+          signature(x = "DataFrame", colName = "character", col = "Column"),
+          function(x, colName, col) {
+            select(x, x$"*", alias(col, colName))
+          })
+
+#' WithColumnRenamed
+#'
+#' Rename an existing column in a DataFrame.
+#'
+#' @param x A DataFrame
+#' @param existingCol The name of the column you want to change.
+#' @param newCol The new column name.
+#' @return A DataFrame with the column name changed.
+#' @rdname withColumnRenamed
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' newDF <- withColumnRenamed(df, "col1", "newCol1")
+#' }
+setMethod("withColumnRenamed",
+          signature(x = "DataFrame", existingCol = "character", newCol = "character"),
+          function(x, existingCol, newCol) {
+            cols <- lapply(columns(x), function(c) {
+              if (c == existingCol) {
+                alias(col(c), newCol)
+              } else {
+                col(c)
+              }
+            })
+            select(x, cols)
+          })
+
+setClassUnion("characterOrColumn", c("character", "Column"))
+
+#' SortDF 
+#'
+#' Sort a DataFrame by the specified column(s).
+#'
+#' @param x A DataFrame to be sorted.
+#' @param col Either a Column object or character vector indicating the field to sort on
+#' @param ... Additional sorting fields
+#' @return A DataFrame where all elements are sorted.
+#' @rdname sortDF
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' sortDF(df, df$col1)
+#' sortDF(df, "col1")
+#' sortDF(df, asc(df$col1), desc(abs(df$col2)))
+#' }
+setMethod("sortDF",
+          signature(x = "DataFrame", col = "characterOrColumn"),
+          function(x, col, ...) {
+            if (class(col) == "character") {
+              sdf <- callJMethod(x@sdf, "sort", col, toSeq(...))
+            } else if (class(col) == "Column") {
+              jcols <- lapply(list(col, ...), function(c) {
+                c@jc
+              })
+              sdf <- callJMethod(x@sdf, "sort", listToSeq(jcols))
+            }
+            dataFrame(sdf)
+          })
+
+#' @rdname sortDF
+#' @export
+setMethod("orderBy",
+          signature(x = "DataFrame", col = "characterOrColumn"),
+          function(x, col) {
+            sortDF(x, col)
+          })
+
+#' Filter
+#'
+#' Filter the rows of a DataFrame according to a given condition.
+#'
+#' @param x A DataFrame to be sorted.
+#' @param condition The condition to sort on. This may either be a Column expression
+#' or a string containing a SQL statement
+#' @return A DataFrame containing only the rows that meet the condition.
+#' @rdname filter
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' filter(df, "col1 > 0")
+#' filter(df, df$col2 != "abcdefg")
+#' }
+setMethod("filter",
+          signature(x = "DataFrame", condition = "characterOrColumn"),
+          function(x, condition) {
+            if (class(condition) == "Column") {
+              condition <- condition@jc
+            }
+            sdf <- callJMethod(x@sdf, "filter", condition)
+            dataFrame(sdf)
+          })
+
+#' @rdname filter
+#' @export
+setMethod("where",
+          signature(x = "DataFrame", condition = "characterOrColumn"),
+          function(x, condition) {
+            filter(x, condition)
+          })
+
+#' Join
+#'
+#' Join two DataFrames based on the given join expression.
+#'
+#' @param x A Spark DataFrame
+#' @param y A Spark DataFrame
+#' @param joinExpr (Optional) The expression used to perform the join. joinExpr must be a 
+#' Column expression. If joinExpr is omitted, join() wil perform a Cartesian join
+#' @param joinType The type of join to perform. The following join types are available:
+#' 'inner', 'outer', 'left_outer', 'right_outer', 'semijoin'. The default joinType is "inner".
+#' @return A DataFrame containing the result of the join operation.
+#' @rdname join
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' df1 <- jsonFile(sqlCtx, path)
+#' df2 <- jsonFile(sqlCtx, path2)
+#' join(df1, df2) # Performs a Cartesian
+#' join(df1, df2, df1$col1 == df2$col2) # Performs an inner join based on expression
+#' join(df1, df2, df1$col1 == df2$col2, "right_outer")
+#' }
+setMethod("join",
+          signature(x = "DataFrame", y = "DataFrame"),
+          function(x, y, joinExpr = NULL, joinType = NULL) {
+            if (is.null(joinExpr)) {
+              sdf <- callJMethod(x@sdf, "join", y@sdf)
+            } else {
+              if (class(joinExpr) != "Column") stop("joinExpr must be a Column")
+              if (is.null(joinType)) {
+                sdf <- callJMethod(x@sdf, "join", y@sdf, joinExpr@jc)
+              } else {
+                if (joinType %in% c("inner", "outer", "left_outer", "right_outer", "semijoin")) {
+                  sdf <- callJMethod(x@sdf, "join", y@sdf, joinExpr@jc, joinType)
+                } else {
+                  stop("joinType must be one of the following types: ",
+                       "'inner', 'outer', 'left_outer', 'right_outer', 'semijoin'")
+                }
+              }
+            }
+            dataFrame(sdf)
+          })
+
+#' UnionAll
+#'
+#' Return a new DataFrame containing the union of rows in this DataFrame
+#' and another DataFrame. This is equivalent to `UNION ALL` in SQL.
+#'
+#' @param x A Spark DataFrame
+#' @param y A Spark DataFrame
+#' @return A DataFrame containing the result of the union.
+#' @rdname unionAll
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' df1 <- jsonFile(sqlCtx, path)
+#' df2 <- jsonFile(sqlCtx, path2)
+#' unioned <- unionAll(df, df2)
+#' }
+setMethod("unionAll",
+          signature(x = "DataFrame", y = "DataFrame"),
+          function(x, y) {
+            unioned <- callJMethod(x@sdf, "unionAll", y@sdf)
+            dataFrame(unioned)
+          })
+
+#' Intersect
+#'
+#' Return a new DataFrame containing rows only in both this DataFrame
+#' and another DataFrame. This is equivalent to `INTERSECT` in SQL.
+#'
+#' @param x A Spark DataFrame
+#' @param y A Spark DataFrame
+#' @return A DataFrame containing the result of the intersect.
+#' @rdname intersect
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' df1 <- jsonFile(sqlCtx, path)
+#' df2 <- jsonFile(sqlCtx, path2)
+#' intersectDF <- intersect(df, df2)
+#' }
+setMethod("intersect",
+          signature(x = "DataFrame", y = "DataFrame"),
+          function(x, y) {
+            intersected <- callJMethod(x@sdf, "intersect", y@sdf)
+            dataFrame(intersected)
+          })
+
+#' Subtract
+#'
+#' Return a new DataFrame containing rows in this DataFrame
+#' but not in another DataFrame. This is equivalent to `EXCEPT` in SQL.
+#'
+#' @param x A Spark DataFrame
+#' @param y A Spark DataFrame
+#' @return A DataFrame containing the result of the subtract operation.
+#' @rdname subtract
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' df1 <- jsonFile(sqlCtx, path)
+#' df2 <- jsonFile(sqlCtx, path2)
+#' subtractDF <- subtract(df, df2)
+#' }
+setMethod("subtract",
+          signature(x = "DataFrame", y = "DataFrame"),
+          function(x, y) {
+            subtracted <- callJMethod(x@sdf, "except", y@sdf)
+            dataFrame(subtracted)
+          })
+
+#' Save the contents of the DataFrame to a data source
+#'
+#' The data source is specified by the `source` and a set of options (...).
+#' If `source` is not specified, the default data source configured by
+#' spark.sql.sources.default will be used.
+#'
+#' Additionally, mode is used to specify the behavior of the save operation when
+#' data already exists in the data source. There are four modes:
+#'  append: Contents of this DataFrame are expected to be appended to existing data.
+#'  overwrite: Existing data is expected to be overwritten by the contents of
+#     this DataFrame.
+#'  error: An exception is expected to be thrown.
+#'  ignore: The save operation is expected to not save the contents of the DataFrame
+#     and to not change the existing data.
+#'
+#' @param df A SparkSQL DataFrame
+#' @param path A name for the table
+#' @param source A name for external data source
+#' @param mode One of 'append', 'overwrite', 'error', 'ignore'
+#'
+#' @rdname saveAsTable
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' saveAsTable(df, "myfile")
+#' }
+setMethod("saveDF",
+          signature(df = "DataFrame", path = 'character', source = 'character',
+                    mode = 'character'),
+          function(df, path = NULL, source = NULL, mode = "append", ...){
+            if (is.null(source)) {
+              sqlCtx <- get(".sparkRSQLsc", envir = .sparkREnv)
+              source <- callJMethod(sqlCtx, "getConf", "spark.sql.sources.default",
+                                    "org.apache.spark.sql.parquet")
+            }
+            allModes <- c("append", "overwrite", "error", "ignore")
+            if (!(mode %in% allModes)) {
+              stop('mode should be one of "append", "overwrite", "error", "ignore"')
+            }
+            jmode <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "saveMode", mode)
+            options <- varargsToEnv(...)
+            if (!is.null(path)) {
+                options[['path']] = path
+            }
+            callJMethod(df@sdf, "save", source, jmode, options)
+          })
+
+
+#' saveAsTable
+#'
+#' Save the contents of the DataFrame to a data source as a table
+#'
+#' The data source is specified by the `source` and a set of options (...).
+#' If `source` is not specified, the default data source configured by
+#' spark.sql.sources.default will be used.
+#'
+#' Additionally, mode is used to specify the behavior of the save operation when
+#' data already exists in the data source. There are four modes:
+#'  append: Contents of this DataFrame are expected to be appended to existing data.
+#'  overwrite: Existing data is expected to be overwritten by the contents of
+#     this DataFrame.
+#'  error: An exception is expected to be thrown.
+#'  ignore: The save operation is expected to not save the contents of the DataFrame
+#     and to not change the existing data.
+#'
+#' @param df A SparkSQL DataFrame
+#' @param tableName A name for the table
+#' @param source A name for external data source
+#' @param mode One of 'append', 'overwrite', 'error', 'ignore'
+#'
+#' @rdname saveAsTable
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' saveAsTable(df, "myfile")
+#' }
+setMethod("saveAsTable",
+          signature(df = "DataFrame", tableName = 'character', source = 'character',
+                    mode = 'character'),
+          function(df, tableName, source = NULL, mode="append", ...){
+            if (is.null(source)) {
+              sqlCtx <- get(".sparkRSQLsc", envir = .sparkREnv)
+              source <- callJMethod(sqlCtx, "getConf", "spark.sql.sources.default",
+                                    "org.apache.spark.sql.parquet")
+            }
+            allModes <- c("append", "overwrite", "error", "ignore")
+            if (!(mode %in% allModes)) {
+              stop('mode should be one of "append", "overwrite", "error", "ignore"')
+            }
+            jmode <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "saveMode", mode)
+            options <- varargsToEnv(...)
+            callJMethod(df@sdf, "saveAsTable", tableName, source, jmode, options)
+          })
+
diff --git a/R/pkg/R/RDD.R b/R/pkg/R/RDD.R
new file mode 100644
index 0000000000000..604ad03c407b9
--- /dev/null
+++ b/R/pkg/R/RDD.R
@@ -0,0 +1,1539 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# RDD in R implemented in S4 OO system.
+
+setOldClass("jobj")
+
+#' @title S4 class that represents an RDD
+#' @description RDD can be created using functions like
+#'              \code{parallelize}, \code{textFile} etc.
+#' @rdname RDD
+#' @seealso parallelize, textFile
+#'
+#' @slot env An R environment that stores bookkeeping states of the RDD
+#' @slot jrdd Java object reference to the backing JavaRDD
+#' to an RDD
+#' @export
+setClass("RDD",
+         slots = list(env = "environment",
+                      jrdd = "jobj"))
+
+setClass("PipelinedRDD",
+         slots = list(prev = "RDD",
+                      func = "function",
+                      prev_jrdd = "jobj"),
+         contains = "RDD")
+
+setMethod("initialize", "RDD", function(.Object, jrdd, serializedMode,
+                                        isCached, isCheckpointed) {
+  # Check that RDD constructor is using the correct version of serializedMode
+  stopifnot(class(serializedMode) == "character")
+  stopifnot(serializedMode %in% c("byte", "string", "row"))
+  # RDD has three serialization types:
+  # byte: The RDD stores data serialized in R.
+  # string: The RDD stores data as strings.
+  # row: The RDD stores the serialized rows of a DataFrame.
+  
+  # We use an environment to store mutable states inside an RDD object.
+  # Note that R's call-by-value semantics makes modifying slots inside an
+  # object (passed as an argument into a function, such as cache()) difficult:
+  # i.e. one needs to make a copy of the RDD object and sets the new slot value
+  # there.
+
+  # The slots are inheritable from superclass. Here, both `env' and `jrdd' are
+  # inherited from RDD, but only the former is used.
+  .Object@env <- new.env()
+  .Object@env$isCached <- isCached
+  .Object@env$isCheckpointed <- isCheckpointed
+  .Object@env$serializedMode <- serializedMode
+
+  .Object@jrdd <- jrdd
+  .Object
+})
+
+setMethod("initialize", "PipelinedRDD", function(.Object, prev, func, jrdd_val) {
+  .Object@env <- new.env()
+  .Object@env$isCached <- FALSE
+  .Object@env$isCheckpointed <- FALSE
+  .Object@env$jrdd_val <- jrdd_val
+  if (!is.null(jrdd_val)) {
+    # This tracks the serialization mode for jrdd_val
+    .Object@env$serializedMode <- prev@env$serializedMode
+  }
+
+  .Object@prev <- prev
+
+  isPipelinable <- function(rdd) {
+    e <- rdd@env
+    !(e$isCached || e$isCheckpointed)
+  }
+
+  if (!inherits(prev, "PipelinedRDD") || !isPipelinable(prev)) {
+    # This transformation is the first in its stage:
+    .Object@func <- func
+    .Object@prev_jrdd <- getJRDD(prev)
+    .Object@env$prev_serializedMode <- prev@env$serializedMode
+    # NOTE: We use prev_serializedMode to track the serialization mode of prev_JRDD
+    # prev_serializedMode is used during the delayed computation of JRDD in getJRDD
+  } else {
+    pipelinedFunc <- function(split, iterator) {
+      func(split, prev@func(split, iterator))
+    }
+    .Object@func <- pipelinedFunc
+    .Object@prev_jrdd <- prev@prev_jrdd # maintain the pipeline
+    # Get the serialization mode of the parent RDD
+    .Object@env$prev_serializedMode <- prev@env$prev_serializedMode
+  }
+
+  .Object
+})
+
+#' @rdname RDD
+#' @export
+#'
+#' @param jrdd Java object reference to the backing JavaRDD
+#' @param serializedMode Use "byte" if the RDD stores data serialized in R, "string" if the RDD
+#' stores strings, and "row" if the RDD stores the rows of a DataFrame
+#' @param isCached TRUE if the RDD is cached
+#' @param isCheckpointed TRUE if the RDD has been checkpointed
+RDD <- function(jrdd, serializedMode = "byte", isCached = FALSE,
+                isCheckpointed = FALSE) {
+  new("RDD", jrdd, serializedMode, isCached, isCheckpointed)
+}
+
+PipelinedRDD <- function(prev, func) {
+  new("PipelinedRDD", prev, func, NULL)
+}
+
+# Return the serialization mode for an RDD.
+setGeneric("getSerializedMode", function(rdd, ...) { standardGeneric("getSerializedMode") })
+# For normal RDDs we can directly read the serializedMode
+setMethod("getSerializedMode", signature(rdd = "RDD"), function(rdd) rdd@env$serializedMode )
+# For pipelined RDDs if jrdd_val is set then serializedMode should exist
+# if not we return the defaultSerialization mode of "byte" as we don't know the serialization
+# mode at this point in time.
+setMethod("getSerializedMode", signature(rdd = "PipelinedRDD"),
+          function(rdd) {
+            if (!is.null(rdd@env$jrdd_val)) {
+              return(rdd@env$serializedMode)
+            } else {
+              return("byte")
+            }
+          })
+
+# The jrdd accessor function.
+setMethod("getJRDD", signature(rdd = "RDD"), function(rdd) rdd@jrdd )
+setMethod("getJRDD", signature(rdd = "PipelinedRDD"),
+          function(rdd, serializedMode = "byte") {
+            if (!is.null(rdd@env$jrdd_val)) {
+              return(rdd@env$jrdd_val)
+            }
+
+            computeFunc <- function(split, part) {
+              rdd@func(split, part)
+            }
+
+            packageNamesArr <- serialize(.sparkREnv[[".packages"]],
+                                         connection = NULL)
+
+            broadcastArr <- lapply(ls(.broadcastNames),
+                                   function(name) { get(name, .broadcastNames) })
+
+            serializedFuncArr <- serialize(computeFunc, connection = NULL)
+
+            prev_jrdd <- rdd@prev_jrdd
+
+            if (serializedMode == "string") {
+              rddRef <- newJObject("org.apache.spark.api.r.StringRRDD",
+                                   callJMethod(prev_jrdd, "rdd"),
+                                   serializedFuncArr,
+                                   rdd@env$prev_serializedMode,
+                                   packageNamesArr,
+                                   as.character(.sparkREnv[["libname"]]),
+                                   broadcastArr,
+                                   callJMethod(prev_jrdd, "classTag"))
+            } else {
+              rddRef <- newJObject("org.apache.spark.api.r.RRDD",
+                                   callJMethod(prev_jrdd, "rdd"),
+                                   serializedFuncArr,
+                                   rdd@env$prev_serializedMode,
+                                   serializedMode,
+                                   packageNamesArr,
+                                   as.character(.sparkREnv[["libname"]]),
+                                   broadcastArr,
+                                   callJMethod(prev_jrdd, "classTag"))
+            }
+            # Save the serialization flag after we create a RRDD
+            rdd@env$serializedMode <- serializedMode
+            rdd@env$jrdd_val <- callJMethod(rddRef, "asJavaRDD") # rddRef$asJavaRDD()
+            rdd@env$jrdd_val
+          })
+
+setValidity("RDD",
+            function(object) {
+              jrdd <- getJRDD(object)
+              cls <- callJMethod(jrdd, "getClass")
+              className <- callJMethod(cls, "getName")
+              if (grep("spark.api.java.*RDD*", className) == 1) {
+                TRUE
+              } else {
+                paste("Invalid RDD class ", className)
+              }
+            })
+
+
+############ Actions and Transformations ############
+
+#' Persist an RDD
+#'
+#' Persist this RDD with the default storage level (MEMORY_ONLY).
+#'
+#' @param x The RDD to cache
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10, 2L)
+#' cache(rdd)
+#'}
+#' @rdname cache-methods
+#' @aliases cache,RDD-method
+setMethod("cache",
+          signature(x = "RDD"),
+          function(x) {
+            callJMethod(getJRDD(x), "cache")
+            x@env$isCached <- TRUE
+            x
+          })
+
+#' Persist an RDD
+#'
+#' Persist this RDD with the specified storage level. For details of the
+#' supported storage levels, refer to
+#' http://spark.apache.org/docs/latest/programming-guide.html#rdd-persistence.
+#'
+#' @param x The RDD to persist
+#' @param newLevel The new storage level to be assigned
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10, 2L)
+#' persist(rdd, "MEMORY_AND_DISK")
+#'}
+#' @rdname persist
+#' @aliases persist,RDD-method
+setMethod("persist",
+          signature(x = "RDD", newLevel = "character"),
+          function(x, newLevel) {
+            callJMethod(getJRDD(x), "persist", getStorageLevel(newLevel))
+            x@env$isCached <- TRUE
+            x
+          })
+
+#' Unpersist an RDD
+#'
+#' Mark the RDD as non-persistent, and remove all blocks for it from memory and
+#' disk.
+#'
+#' @param x The RDD to unpersist
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10, 2L)
+#' cache(rdd) # rdd@@env$isCached == TRUE
+#' unpersist(rdd) # rdd@@env$isCached == FALSE
+#'}
+#' @rdname unpersist-methods
+#' @aliases unpersist,RDD-method
+setMethod("unpersist",
+          signature(x = "RDD"),
+          function(x) {
+            callJMethod(getJRDD(x), "unpersist")
+            x@env$isCached <- FALSE
+            x
+          })
+
+#' Checkpoint an RDD
+#'
+#' Mark this RDD for checkpointing. It will be saved to a file inside the
+#' checkpoint directory set with setCheckpointDir() and all references to its
+#' parent RDDs will be removed. This function must be called before any job has
+#' been executed on this RDD. It is strongly recommended that this RDD is
+#' persisted in memory, otherwise saving it on a file will require recomputation.
+#'
+#' @param x The RDD to checkpoint
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' setCheckpointDir(sc, "checkpoints")
+#' rdd <- parallelize(sc, 1:10, 2L)
+#' checkpoint(rdd)
+#'}
+#' @rdname checkpoint-methods
+#' @aliases checkpoint,RDD-method
+setMethod("checkpoint",
+          signature(x = "RDD"),
+          function(x) {
+            jrdd <- getJRDD(x)
+            callJMethod(jrdd, "checkpoint")
+            x@env$isCheckpointed <- TRUE
+            x
+          })
+
+#' Gets the number of partitions of an RDD
+#'
+#' @param x A RDD.
+#' @return the number of partitions of rdd as an integer.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10, 2L)
+#' numPartitions(rdd)  # 2L
+#'}
+#' @rdname numPartitions
+#' @aliases numPartitions,RDD-method
+setMethod("numPartitions",
+          signature(x = "RDD"),
+          function(x) {
+            jrdd <- getJRDD(x)
+            partitions <- callJMethod(jrdd, "splits")
+            callJMethod(partitions, "size")
+          })
+
+#' Collect elements of an RDD
+#'
+#' @description
+#' \code{collect} returns a list that contains all of the elements in this RDD.
+#'
+#' @param x The RDD to collect
+#' @param ... Other optional arguments to collect
+#' @param flatten FALSE if the list should not flattened
+#' @return a list containing elements in the RDD
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10, 2L)
+#' collect(rdd) # list from 1 to 10
+#' collectPartition(rdd, 0L) # list from 1 to 5
+#'}
+#' @rdname collect-methods
+#' @aliases collect,RDD-method
+setMethod("collect",
+          signature(x = "RDD"),
+          function(x, flatten = TRUE) {
+            # Assumes a pairwise RDD is backed by a JavaPairRDD.
+            collected <- callJMethod(getJRDD(x), "collect")
+            convertJListToRList(collected, flatten,
+              serializedMode = getSerializedMode(x))
+          })
+
+
+#' @description
+#' \code{collectPartition} returns a list that contains all of the elements
+#' in the specified partition of the RDD.
+#' @param partitionId the partition to collect (starts from 0)
+#' @rdname collect-methods
+#' @aliases collectPartition,integer,RDD-method
+setMethod("collectPartition",
+          signature(x = "RDD", partitionId = "integer"),
+          function(x, partitionId) {
+            jPartitionsList <- callJMethod(getJRDD(x),
+                                           "collectPartitions",
+                                           as.list(as.integer(partitionId)))
+
+            jList <- jPartitionsList[[1]]
+            convertJListToRList(jList, flatten = TRUE,
+              serializedMode = getSerializedMode(x))
+          })
+
+#' @description
+#' \code{collectAsMap} returns a named list as a map that contains all of the elements
+#' in a key-value pair RDD. 
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(list(1, 2), list(3, 4)), 2L)
+#' collectAsMap(rdd) # list(`1` = 2, `3` = 4)
+#'}
+#' @rdname collect-methods
+#' @aliases collectAsMap,RDD-method
+setMethod("collectAsMap",
+          signature(x = "RDD"),
+          function(x) {
+            pairList <- collect(x)
+            map <- new.env()
+            lapply(pairList, function(i) { assign(as.character(i[[1]]), i[[2]], envir = map) })
+            as.list(map)
+          })
+
+#' Return the number of elements in the RDD.
+#'
+#' @param x The RDD to count
+#' @return number of elements in the RDD.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' count(rdd) # 10
+#' length(rdd) # Same as count
+#'}
+#' @rdname count
+#' @aliases count,RDD-method
+setMethod("count",
+          signature(x = "RDD"),
+          function(x) {
+            countPartition <- function(part) {
+              as.integer(length(part))
+            }
+            valsRDD <- lapplyPartition(x, countPartition)
+            vals <- collect(valsRDD)
+            sum(as.integer(vals))
+          })
+
+#' Return the number of elements in the RDD
+#' @export
+#' @rdname count
+setMethod("length",
+          signature(x = "RDD"),
+          function(x) {
+            count(x)
+          })
+
+#' Return the count of each unique value in this RDD as a list of
+#' (value, count) pairs.
+#'
+#' Same as countByValue in Spark.
+#'
+#' @param x The RDD to count
+#' @return list of (value, count) pairs, where count is number of each unique
+#' value in rdd.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, c(1,2,3,2,1))
+#' countByValue(rdd) # (1,2L), (2,2L), (3,1L)
+#'}
+#' @rdname countByValue
+#' @aliases countByValue,RDD-method
+setMethod("countByValue",
+          signature(x = "RDD"),
+          function(x) {
+            ones <- lapply(x, function(item) { list(item, 1L) })
+            collect(reduceByKey(ones, `+`, numPartitions(x)))
+          })
+
+#' Apply a function to all elements
+#'
+#' This function creates a new RDD by applying the given transformation to all
+#' elements of the given RDD
+#'
+#' @param X The RDD to apply the transformation.
+#' @param FUN the transformation to apply on each element
+#' @return a new RDD created by the transformation.
+#' @rdname lapply
+#' @aliases lapply
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' multiplyByTwo <- lapply(rdd, function(x) { x * 2 })
+#' collect(multiplyByTwo) # 2,4,6...
+#'}
+setMethod("lapply",
+          signature(X = "RDD", FUN = "function"),
+          function(X, FUN) {
+            func <- function(split, iterator) {
+              lapply(iterator, FUN)
+            }
+            lapplyPartitionsWithIndex(X, func)
+          })
+
+#' @rdname lapply
+#' @aliases map,RDD,function-method
+setMethod("map",
+          signature(X = "RDD", FUN = "function"),
+          function(X, FUN) {
+            lapply(X, FUN)
+          })
+
+#' Flatten results after apply a function to all elements
+#'
+#' This function return a new RDD by first applying a function to all
+#' elements of this RDD, and then flattening the results.
+#'
+#' @param X The RDD to apply the transformation.
+#' @param FUN the transformation to apply on each element
+#' @return a new RDD created by the transformation.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' multiplyByTwo <- flatMap(rdd, function(x) { list(x*2, x*10) })
+#' collect(multiplyByTwo) # 2,20,4,40,6,60...
+#'}
+#' @rdname flatMap
+#' @aliases flatMap,RDD,function-method
+setMethod("flatMap",
+          signature(X = "RDD", FUN = "function"),
+          function(X, FUN) {
+            partitionFunc <- function(part) {
+              unlist(
+                lapply(part, FUN),
+                recursive = F
+              )
+            }
+            lapplyPartition(X, partitionFunc)
+          })
+
+#' Apply a function to each partition of an RDD
+#'
+#' Return a new RDD by applying a function to each partition of this RDD.
+#'
+#' @param X The RDD to apply the transformation.
+#' @param FUN the transformation to apply on each partition.
+#' @return a new RDD created by the transformation.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' partitionSum <- lapplyPartition(rdd, function(part) { Reduce("+", part) })
+#' collect(partitionSum) # 15, 40
+#'}
+#' @rdname lapplyPartition
+#' @aliases lapplyPartition,RDD,function-method
+setMethod("lapplyPartition",
+          signature(X = "RDD", FUN = "function"),
+          function(X, FUN) {
+            lapplyPartitionsWithIndex(X, function(s, part) { FUN(part) })
+          })
+
+#' mapPartitions is the same as lapplyPartition.
+#'
+#' @rdname lapplyPartition
+#' @aliases mapPartitions,RDD,function-method
+setMethod("mapPartitions",
+          signature(X = "RDD", FUN = "function"),
+          function(X, FUN) {
+            lapplyPartition(X, FUN)
+          })
+
+#' Return a new RDD by applying a function to each partition of this RDD, while
+#' tracking the index of the original partition.
+#'
+#' @param X The RDD to apply the transformation.
+#' @param FUN the transformation to apply on each partition; takes the partition
+#'        index and a list of elements in the particular partition.
+#' @return a new RDD created by the transformation.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10, 5L)
+#' prod <- lapplyPartitionsWithIndex(rdd, function(split, part) {
+#'                                          split * Reduce("+", part) })
+#' collect(prod, flatten = FALSE) # 0, 7, 22, 45, 76
+#'}
+#' @rdname lapplyPartitionsWithIndex
+#' @aliases lapplyPartitionsWithIndex,RDD,function-method
+setMethod("lapplyPartitionsWithIndex",
+          signature(X = "RDD", FUN = "function"),
+          function(X, FUN) {
+            FUN <- cleanClosure(FUN)
+            closureCapturingFunc <- function(split, part) {
+              FUN(split, part)
+            }
+            PipelinedRDD(X, closureCapturingFunc)
+          })
+
+#' @rdname lapplyPartitionsWithIndex
+#' @aliases mapPartitionsWithIndex,RDD,function-method
+setMethod("mapPartitionsWithIndex",
+          signature(X = "RDD", FUN = "function"),
+          function(X, FUN) {
+            lapplyPartitionsWithIndex(X, FUN)
+          })
+
+#' This function returns a new RDD containing only the elements that satisfy
+#' a predicate (i.e. returning TRUE in a given logical function).
+#' The same as `filter()' in Spark.
+#'
+#' @param x The RDD to be filtered.
+#' @param f A unary predicate function.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' unlist(collect(filterRDD(rdd, function (x) { x < 3 }))) # c(1, 2)
+#'}
+#' @rdname filterRDD
+#' @aliases filterRDD,RDD,function-method
+setMethod("filterRDD",
+          signature(x = "RDD", f = "function"),
+          function(x, f) {
+            filter.func <- function(part) {
+              Filter(f, part)
+            }
+            lapplyPartition(x, filter.func)
+          })
+
+#' @rdname filterRDD
+#' @aliases Filter
+setMethod("Filter",
+          signature(f = "function", x = "RDD"),
+          function(f, x) {
+            filterRDD(x, f)
+          })
+
+#' Reduce across elements of an RDD.
+#'
+#' This function reduces the elements of this RDD using the
+#' specified commutative and associative binary operator.
+#'
+#' @param x The RDD to reduce
+#' @param func Commutative and associative function to apply on elements
+#'             of the RDD.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' reduce(rdd, "+") # 55
+#'}
+#' @rdname reduce
+#' @aliases reduce,RDD,ANY-method
+setMethod("reduce",
+          signature(x = "RDD", func = "ANY"),
+          function(x, func) {
+
+            reducePartition <- function(part) {
+              Reduce(func, part)
+            }
+
+            partitionList <- collect(lapplyPartition(x, reducePartition),
+                                     flatten = FALSE)
+            Reduce(func, partitionList)
+          })
+
+#' Get the maximum element of an RDD.
+#'
+#' @param x The RDD to get the maximum element from
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' maximum(rdd) # 10
+#'}
+#' @rdname maximum
+#' @aliases maximum,RDD
+setMethod("maximum",
+          signature(x = "RDD"),
+          function(x) {
+            reduce(x, max)
+          })
+
+#' Get the minimum element of an RDD.
+#'
+#' @param x The RDD to get the minimum element from
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' minimum(rdd) # 1
+#'}
+#' @rdname minimum
+#' @aliases minimum,RDD
+setMethod("minimum",
+          signature(x = "RDD"),
+          function(x) {
+            reduce(x, min)
+          })
+
+#' Add up the elements in an RDD.
+#'
+#' @param x The RDD to add up the elements in
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' sumRDD(rdd) # 55
+#'}
+#' @rdname sumRDD 
+#' @aliases sumRDD,RDD
+setMethod("sumRDD",
+          signature(x = "RDD"),
+          function(x) {
+            reduce(x, "+")
+          })
+
+#' Applies a function to all elements in an RDD, and force evaluation.
+#'
+#' @param x The RDD to apply the function
+#' @param func The function to be applied.
+#' @return invisible NULL.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' foreach(rdd, function(x) { save(x, file=...) })
+#'}
+#' @rdname foreach
+#' @aliases foreach,RDD,function-method
+setMethod("foreach",
+          signature(x = "RDD", func = "function"),
+          function(x, func) {
+            partition.func <- function(x) {
+              lapply(x, func)
+              NULL
+            }
+            invisible(collect(mapPartitions(x, partition.func)))
+          })
+
+#' Applies a function to each partition in an RDD, and force evaluation.
+#'
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' foreachPartition(rdd, function(part) { save(part, file=...); NULL })
+#'}
+#' @rdname foreach
+#' @aliases foreachPartition,RDD,function-method
+setMethod("foreachPartition",
+          signature(x = "RDD", func = "function"),
+          function(x, func) {
+            invisible(collect(mapPartitions(x, func)))
+          })
+
+#' Take elements from an RDD.
+#'
+#' This function takes the first NUM elements in the RDD and
+#' returns them in a list.
+#'
+#' @param x The RDD to take elements from
+#' @param num Number of elements to take
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' take(rdd, 2L) # list(1, 2)
+#'}
+#' @rdname take
+#' @aliases take,RDD,numeric-method
+setMethod("take",
+          signature(x = "RDD", num = "numeric"),
+          function(x, num) {
+            resList <- list()
+            index <- -1
+            jrdd <- getJRDD(x)
+            numPartitions <- numPartitions(x)
+
+            # TODO(shivaram): Collect more than one partition based on size
+            # estimates similar to the scala version of `take`.
+            while (TRUE) {
+              index <- index + 1
+
+              if (length(resList) >= num || index >= numPartitions)
+                break
+
+              # a JList of byte arrays
+              partitionArr <- callJMethod(jrdd, "collectPartitions", as.list(as.integer(index)))
+              partition <- partitionArr[[1]]
+
+              size <- num - length(resList)
+              # elems is capped to have at most `size` elements
+              elems <- convertJListToRList(partition,
+                                           flatten = TRUE,
+                                           logicalUpperBound = size,
+                                           serializedMode = getSerializedMode(x))
+              # TODO: Check if this append is O(n^2)?
+              resList <- append(resList, elems)
+            }
+            resList
+          })
+
+#' First
+#'
+#' Return the first element of an RDD
+#'
+#' @rdname first
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' first(rdd)
+#' }
+setMethod("first",
+          signature(x = "RDD"),
+          function(x) {
+            take(x, 1)[[1]]
+          })
+
+#' Removes the duplicates from RDD.
+#'
+#' This function returns a new RDD containing the distinct elements in the
+#' given RDD. The same as `distinct()' in Spark.
+#'
+#' @param x The RDD to remove duplicates from.
+#' @param numPartitions Number of partitions to create.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, c(1,2,2,3,3,3))
+#' sort(unlist(collect(distinct(rdd)))) # c(1, 2, 3)
+#'}
+#' @rdname distinct
+#' @aliases distinct,RDD-method
+setMethod("distinct",
+          signature(x = "RDD"),
+          function(x, numPartitions = SparkR::numPartitions(x)) {
+            identical.mapped <- lapply(x, function(x) { list(x, NULL) })
+            reduced <- reduceByKey(identical.mapped,
+                                   function(x, y) { x },
+                                   numPartitions)
+            resRDD <- lapply(reduced, function(x) { x[[1]] })
+            resRDD
+          })
+
+#' Return an RDD that is a sampled subset of the given RDD.
+#'
+#' The same as `sample()' in Spark. (We rename it due to signature
+#' inconsistencies with the `sample()' function in R's base package.)
+#'
+#' @param x The RDD to sample elements from
+#' @param withReplacement Sampling with replacement or not
+#' @param fraction The (rough) sample target fraction
+#' @param seed Randomness seed value
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10) # ensure each num is in its own split
+#' collect(sampleRDD(rdd, FALSE, 0.5, 1618L)) # ~5 distinct elements
+#' collect(sampleRDD(rdd, TRUE, 0.5, 9L)) # ~5 elements possibly with duplicates
+#'}
+#' @rdname sampleRDD
+#' @aliases sampleRDD,RDD
+setMethod("sampleRDD",
+          signature(x = "RDD", withReplacement = "logical",
+                    fraction = "numeric", seed = "integer"),
+          function(x, withReplacement, fraction, seed) {
+
+            # The sampler: takes a partition and returns its sampled version.
+            samplingFunc <- function(split, part) {
+              set.seed(seed)
+              res <- vector("list", length(part))
+              len <- 0
+
+              # Discards some random values to ensure each partition has a
+              # different random seed.
+              runif(split)
+
+              for (elem in part) {
+                if (withReplacement) {
+                  count <- rpois(1, fraction)
+                  if (count > 0) {
+                    res[(len + 1):(len + count)] <- rep(list(elem), count)
+                    len <- len + count
+                  }
+                } else {
+                  if (runif(1) < fraction) {
+                    len <- len + 1
+                    res[[len]] <- elem
+                  }
+                }
+              }
+
+              # TODO(zongheng): look into the performance of the current
+              # implementation. Look into some iterator package? Note that
+              # Scala avoids many calls to creating an empty list and PySpark
+              # similarly achieves this using `yield'.
+              if (len > 0)
+                res[1:len]
+              else
+                list()
+            }
+
+            lapplyPartitionsWithIndex(x, samplingFunc)
+          })
+
+#' Return a list of the elements that are a sampled subset of the given RDD.
+#'
+#' @param x The RDD to sample elements from
+#' @param withReplacement Sampling with replacement or not
+#' @param num Number of elements to return
+#' @param seed Randomness seed value
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:100)
+#' # exactly 5 elements sampled, which may not be distinct
+#' takeSample(rdd, TRUE, 5L, 1618L)
+#' # exactly 5 distinct elements sampled
+#' takeSample(rdd, FALSE, 5L, 16181618L)
+#'}
+#' @rdname takeSample
+#' @aliases takeSample,RDD
+setMethod("takeSample", signature(x = "RDD", withReplacement = "logical",
+                                  num = "integer", seed = "integer"),
+          function(x, withReplacement, num, seed) {
+            # This function is ported from RDD.scala.
+            fraction <- 0.0
+            total <- 0
+            multiplier <- 3.0
+            initialCount <- count(x)
+            maxSelected <- 0
+            MAXINT <- .Machine$integer.max
+
+            if (num < 0)
+              stop(paste("Negative number of elements requested"))
+
+            if (initialCount > MAXINT - 1) {
+              maxSelected <- MAXINT - 1
+            } else {
+              maxSelected <- initialCount
+            }
+
+            if (num > initialCount && !withReplacement) {
+              total <- maxSelected
+              fraction <- multiplier * (maxSelected + 1) / initialCount
+            } else {
+              total <- num
+              fraction <- multiplier * (num + 1) / initialCount
+            }
+
+            set.seed(seed)
+            samples <- collect(sampleRDD(x, withReplacement, fraction,
+                                         as.integer(ceiling(runif(1,
+                                                                  -MAXINT,
+                                                                  MAXINT)))))
+            # If the first sample didn't turn out large enough, keep trying to
+            # take samples; this shouldn't happen often because we use a big
+            # multiplier for thei initial size
+            while (length(samples) < total)
+              samples <- collect(sampleRDD(x, withReplacement, fraction,
+                                           as.integer(ceiling(runif(1,
+                                                                    -MAXINT,
+                                                                    MAXINT)))))
+
+            # TODO(zongheng): investigate if this call is an in-place shuffle?
+            sample(samples)[1:total]
+          })
+
+#' Creates tuples of the elements in this RDD by applying a function.
+#'
+#' @param x The RDD.
+#' @param func The function to be applied.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(1, 2, 3))
+#' collect(keyBy(rdd, function(x) { x*x })) # list(list(1, 1), list(4, 2), list(9, 3))
+#'}
+#' @rdname keyBy
+#' @aliases keyBy,RDD
+setMethod("keyBy",
+          signature(x = "RDD", func = "function"),
+          function(x, func) {
+            apply.func <- function(x) {
+              list(func(x), x)
+            }
+            lapply(x, apply.func)
+          })
+
+#' Return a new RDD that has exactly numPartitions partitions.
+#' Can increase or decrease the level of parallelism in this RDD. Internally,
+#' this uses a shuffle to redistribute data.
+#' If you are decreasing the number of partitions in this RDD, consider using
+#' coalesce, which can avoid performing a shuffle.
+#'
+#' @param x The RDD.
+#' @param numPartitions Number of partitions to create.
+#' @seealso coalesce
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(1, 2, 3, 4, 5, 6, 7), 4L)
+#' numPartitions(rdd)                   # 4
+#' numPartitions(repartition(rdd, 2L))  # 2
+#'}
+#' @rdname repartition
+#' @aliases repartition,RDD
+setMethod("repartition",
+          signature(x = "RDD", numPartitions = "numeric"),
+          function(x, numPartitions) {
+            coalesce(x, numToInt(numPartitions), TRUE)
+          })
+
+#' Return a new RDD that is reduced into numPartitions partitions.
+#'
+#' @param x The RDD.
+#' @param numPartitions Number of partitions to create.
+#' @seealso repartition
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(1, 2, 3, 4, 5), 3L)
+#' numPartitions(rdd)               # 3
+#' numPartitions(coalesce(rdd, 1L)) # 1
+#'}
+#' @rdname coalesce
+#' @aliases coalesce,RDD
+setMethod("coalesce",
+           signature(x = "RDD", numPartitions = "numeric"),
+           function(x, numPartitions, shuffle = FALSE) {
+             numPartitions <- numToInt(numPartitions)
+             if (shuffle || numPartitions > SparkR::numPartitions(x)) {
+               func <- function(s, part) {
+                 set.seed(s)  # split as seed
+                 start <- as.integer(sample(numPartitions, 1) - 1)
+                 lapply(seq_along(part),
+                        function(i) {
+                          pos <- (start + i) %% numPartitions
+                          list(pos, part[[i]])
+                        })
+               }
+               shuffled <- lapplyPartitionsWithIndex(x, func)
+               repartitioned <- partitionBy(shuffled, numPartitions)
+               values(repartitioned)
+             } else {
+               jrdd <- callJMethod(getJRDD(x), "coalesce", numPartitions, shuffle)
+               RDD(jrdd)
+             }
+           })
+
+#' Save this RDD as a SequenceFile of serialized objects.
+#'
+#' @param x The RDD to save
+#' @param path The directory where the file is saved
+#' @seealso objectFile
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:3)
+#' saveAsObjectFile(rdd, "/tmp/sparkR-tmp")
+#'}
+#' @rdname saveAsObjectFile
+#' @aliases saveAsObjectFile,RDD
+setMethod("saveAsObjectFile",
+          signature(x = "RDD", path = "character"),
+          function(x, path) {
+            # If serializedMode == "string" we need to serialize the data before saving it since
+            # objectFile() assumes serializedMode == "byte".
+            if (getSerializedMode(x) != "byte") {
+              x <- serializeToBytes(x)
+            }
+            # Return nothing
+            invisible(callJMethod(getJRDD(x), "saveAsObjectFile", path))
+          })
+
+#' Save this RDD as a text file, using string representations of elements.
+#'
+#' @param x The RDD to save
+#' @param path The directory where the splits of the text file are saved
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:3)
+#' saveAsTextFile(rdd, "/tmp/sparkR-tmp")
+#'}
+#' @rdname saveAsTextFile
+#' @aliases saveAsTextFile,RDD
+setMethod("saveAsTextFile",
+          signature(x = "RDD", path = "character"),
+          function(x, path) {
+            func <- function(str) {
+              toString(str)
+            }
+            stringRdd <- lapply(x, func)
+            # Return nothing
+            invisible(
+              callJMethod(getJRDD(stringRdd, serializedMode = "string"), "saveAsTextFile", path))
+          })
+
+#' Sort an RDD by the given key function.
+#'
+#' @param x An RDD to be sorted.
+#' @param func A function used to compute the sort key for each element.
+#' @param ascending A flag to indicate whether the sorting is ascending or descending.
+#' @param numPartitions Number of partitions to create.
+#' @return An RDD where all elements are sorted.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(3, 2, 1))
+#' collect(sortBy(rdd, function(x) { x })) # list (1, 2, 3)
+#'}
+#' @rdname sortBy
+#' @aliases sortBy,RDD,RDD-method
+setMethod("sortBy",
+          signature(x = "RDD", func = "function"),
+          function(x, func, ascending = TRUE, numPartitions = SparkR::numPartitions(x)) {          
+            values(sortByKey(keyBy(x, func), ascending, numPartitions))
+          })
+
+# Helper function to get first N elements from an RDD in the specified order.
+# Param:
+#   x An RDD.
+#   num Number of elements to return.
+#   ascending A flag to indicate whether the sorting is ascending or descending.
+# Return:
+#   A list of the first N elements from the RDD in the specified order.
+#
+takeOrderedElem <- function(x, num, ascending = TRUE) {          
+  if (num <= 0L) {
+    return(list())
+  }
+  
+  partitionFunc <- function(part) {
+    if (num < length(part)) {
+      # R limitation: order works only on primitive types!
+      ord <- order(unlist(part, recursive = FALSE), decreasing = !ascending)
+      list(part[ord[1:num]])
+    } else {
+      list(part)
+    }
+  }
+
+  reduceFunc <- function(elems, part) {
+    newElems <- append(elems, part)
+    # R limitation: order works only on primitive types!
+    ord <- order(unlist(newElems, recursive = FALSE), decreasing = !ascending)
+    newElems[ord[1:num]]
+  }
+  
+  newRdd <- mapPartitions(x, partitionFunc)
+  reduce(newRdd, reduceFunc)
+}
+
+#' Returns the first N elements from an RDD in ascending order.
+#'
+#' @param x An RDD.
+#' @param num Number of elements to return.
+#' @return The first N elements from the RDD in ascending order.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(10, 1, 2, 9, 3, 4, 5, 6, 7))
+#' takeOrdered(rdd, 6L) # list(1, 2, 3, 4, 5, 6)
+#'}
+#' @rdname takeOrdered
+#' @aliases takeOrdered,RDD,RDD-method
+setMethod("takeOrdered",
+          signature(x = "RDD", num = "integer"),
+          function(x, num) {          
+            takeOrderedElem(x, num)
+          })
+
+#' Returns the top N elements from an RDD.
+#'
+#' @param x An RDD.
+#' @param num Number of elements to return.
+#' @return The top N elements from the RDD.
+#' @rdname top
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(10, 1, 2, 9, 3, 4, 5, 6, 7))
+#' top(rdd, 6L) # list(10, 9, 7, 6, 5, 4)
+#'}
+#' @rdname top
+#' @aliases top,RDD,RDD-method
+setMethod("top",
+          signature(x = "RDD", num = "integer"),
+          function(x, num) {          
+            takeOrderedElem(x, num, FALSE)
+          })
+
+#' Fold an RDD using a given associative function and a neutral "zero value".
+#'
+#' Aggregate the elements of each partition, and then the results for all the
+#' partitions, using a given associative function and a neutral "zero value".
+#' 
+#' @param x An RDD.
+#' @param zeroValue A neutral "zero value".
+#' @param op An associative function for the folding operation.
+#' @return The folding result.
+#' @rdname fold
+#' @seealso reduce
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(1, 2, 3, 4, 5))
+#' fold(rdd, 0, "+") # 15
+#'}
+#' @rdname fold
+#' @aliases fold,RDD,RDD-method
+setMethod("fold",
+          signature(x = "RDD", zeroValue = "ANY", op = "ANY"),
+          function(x, zeroValue, op) {
+            aggregateRDD(x, zeroValue, op, op)
+          })
+
+#' Aggregate an RDD using the given combine functions and a neutral "zero value".
+#'
+#' Aggregate the elements of each partition, and then the results for all the
+#' partitions, using given combine functions and a neutral "zero value".
+#' 
+#' @param x An RDD.
+#' @param zeroValue A neutral "zero value".
+#' @param seqOp A function to aggregate the RDD elements. It may return a different
+#'              result type from the type of the RDD elements.
+#' @param combOp A function to aggregate results of seqOp.
+#' @return The aggregation result.
+#' @rdname aggregateRDD
+#' @seealso reduce
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(1, 2, 3, 4))
+#' zeroValue <- list(0, 0)
+#' seqOp <- function(x, y) { list(x[[1]] + y, x[[2]] + 1) }
+#' combOp <- function(x, y) { list(x[[1]] + y[[1]], x[[2]] + y[[2]]) }
+#' aggregateRDD(rdd, zeroValue, seqOp, combOp) # list(10, 4)
+#'}
+#' @rdname aggregateRDD
+#' @aliases aggregateRDD,RDD,RDD-method
+setMethod("aggregateRDD",
+          signature(x = "RDD", zeroValue = "ANY", seqOp = "ANY", combOp = "ANY"),
+          function(x, zeroValue, seqOp, combOp) {        
+            partitionFunc <- function(part) {
+              Reduce(seqOp, part, zeroValue)
+            }
+            
+            partitionList <- collect(lapplyPartition(x, partitionFunc),
+                                     flatten = FALSE)
+            Reduce(combOp, partitionList, zeroValue)
+          })
+
+#' Pipes elements to a forked external process.
+#'
+#' The same as 'pipe()' in Spark.
+#'
+#' @param x The RDD whose elements are piped to the forked external process.
+#' @param command The command to fork an external process.
+#' @param env A named list to set environment variables of the external process.
+#' @return A new RDD created by piping all elements to a forked external process.
+#' @rdname pipeRDD
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' collect(pipeRDD(rdd, "more")
+#' Output: c("1", "2", ..., "10")
+#'}
+#' @rdname pipeRDD
+#' @aliases pipeRDD,RDD,character-method
+setMethod("pipeRDD",
+          signature(x = "RDD", command = "character"),
+          function(x, command, env = list()) {
+            func <- function(part) {
+              trim.trailing.func <- function(x) {
+                sub("[\r\n]*$", "", toString(x))
+              }
+              input <- unlist(lapply(part, trim.trailing.func))
+              res <- system2(command, stdout = TRUE, input = input, env = env)
+              lapply(res, trim.trailing.func)
+            }
+            lapplyPartition(x, func)
+          })
+
+# TODO: Consider caching the name in the RDD's environment
+#' Return an RDD's name.
+#'
+#' @param x The RDD whose name is returned.
+#' @rdname name
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(1,2,3))
+#' name(rdd) # NULL (if not set before)
+#'}
+#' @rdname name
+#' @aliases name,RDD
+setMethod("name",
+          signature(x = "RDD"),
+          function(x) {
+            callJMethod(getJRDD(x), "name")
+          })
+
+#' Set an RDD's name.
+#'
+#' @param x The RDD whose name is to be set.
+#' @param name The RDD name to be set.
+#' @return a new RDD renamed.
+#' @rdname setName
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(1,2,3))
+#' setName(rdd, "myRDD")
+#' name(rdd) # "myRDD"
+#'}
+#' @rdname setName
+#' @aliases setName,RDD
+setMethod("setName",
+          signature(x = "RDD", name = "character"),
+          function(x, name) {
+            callJMethod(getJRDD(x), "setName", name)
+            x
+          })
+
+#' Zip an RDD with generated unique Long IDs.
+#'
+#' Items in the kth partition will get ids k, n+k, 2*n+k, ..., where
+#' n is the number of partitions. So there may exist gaps, but this
+#' method won't trigger a spark job, which is different from
+#' zipWithIndex.
+#'
+#' @param x An RDD to be zipped.
+#' @return An RDD with zipped items.
+#' @seealso zipWithIndex
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list("a", "b", "c", "d", "e"), 3L)
+#' collect(zipWithUniqueId(rdd)) 
+#' # list(list("a", 0), list("b", 3), list("c", 1), list("d", 4), list("e", 2))
+#'}
+#' @rdname zipWithUniqueId
+#' @aliases zipWithUniqueId,RDD
+setMethod("zipWithUniqueId",
+          signature(x = "RDD"),
+          function(x) {
+            n <- numPartitions(x)
+
+            partitionFunc <- function(split, part) {
+              mapply(
+                function(item, index) {
+                  list(item, (index - 1) * n + split)
+                },
+                part,
+                seq_along(part),
+                SIMPLIFY = FALSE)
+            }
+
+            lapplyPartitionsWithIndex(x, partitionFunc)
+          })
+
+#' Zip an RDD with its element indices.
+#'
+#' The ordering is first based on the partition index and then the
+#' ordering of items within each partition. So the first item in
+#' the first partition gets index 0, and the last item in the last
+#' partition receives the largest index.
+#'
+#' This method needs to trigger a Spark job when this RDD contains
+#' more than one partition.
+#'
+#' @param x An RDD to be zipped.
+#' @return An RDD with zipped items.
+#' @seealso zipWithUniqueId
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list("a", "b", "c", "d", "e"), 3L)
+#' collect(zipWithIndex(rdd))
+#' # list(list("a", 0), list("b", 1), list("c", 2), list("d", 3), list("e", 4))
+#'}
+#' @rdname zipWithIndex
+#' @aliases zipWithIndex,RDD
+setMethod("zipWithIndex",
+          signature(x = "RDD"),
+          function(x) {
+            n <- numPartitions(x)
+            if (n > 1) {
+              nums <- collect(lapplyPartition(x,
+                                              function(part) {
+                                                list(length(part))
+                                              }))
+              startIndices <- Reduce("+", nums, accumulate = TRUE)
+            }
+
+            partitionFunc <- function(split, part) {
+              if (split == 0) {
+                startIndex <- 0
+              } else {
+                startIndex <- startIndices[[split]]
+              }
+
+              mapply(
+                function(item, index) {
+                  list(item, index - 1 + startIndex)
+                },
+                part,
+                seq_along(part),
+                SIMPLIFY = FALSE)
+           }
+
+           lapplyPartitionsWithIndex(x, partitionFunc)
+         })
+
+#' Coalesce all elements within each partition of an RDD into a list.
+#'
+#' @param x An RDD.
+#' @return An RDD created by coalescing all elements within
+#'         each partition into a list.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, as.list(1:4), 2L)
+#' collect(glom(rdd))
+#' # list(list(1, 2), list(3, 4))
+#'}
+#' @rdname glom
+#' @aliases glom,RDD
+setMethod("glom",
+          signature(x = "RDD"),
+          function(x) {
+            partitionFunc <- function(part) {
+              list(part)
+            }
+            
+            lapplyPartition(x, partitionFunc)
+          })
+
+############ Binary Functions #############
+
+#' Return the union RDD of two RDDs.
+#' The same as union() in Spark.
+#'
+#' @param x An RDD.
+#' @param y An RDD.
+#' @return a new RDD created by performing the simple union (witout removing
+#' duplicates) of two input RDDs.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:3)
+#' unionRDD(rdd, rdd) # 1, 2, 3, 1, 2, 3
+#'}
+#' @rdname unionRDD
+#' @aliases unionRDD,RDD,RDD-method
+setMethod("unionRDD",
+          signature(x = "RDD", y = "RDD"),
+          function(x, y) {
+            if (getSerializedMode(x) == getSerializedMode(y)) {
+              jrdd <- callJMethod(getJRDD(x), "union", getJRDD(y))
+              union.rdd <- RDD(jrdd, getSerializedMode(x))
+            } else {
+              # One of the RDDs is not serialized, we need to serialize it first.
+              if (getSerializedMode(x) != "byte") x <- serializeToBytes(x)
+              if (getSerializedMode(y) != "byte") y <- serializeToBytes(y)
+              jrdd <- callJMethod(getJRDD(x), "union", getJRDD(y))
+              union.rdd <- RDD(jrdd, "byte")
+            }
+            union.rdd
+          })
+
+#' Zip an RDD with another RDD.
+#'
+#' Zips this RDD with another one, returning key-value pairs with the
+#' first element in each RDD second element in each RDD, etc. Assumes
+#' that the two RDDs have the same number of partitions and the same
+#' number of elements in each partition (e.g. one was made through
+#' a map on the other).
+#'
+#' @param x An RDD to be zipped.
+#' @param other Another RDD to be zipped.
+#' @return An RDD zipped from the two RDDs.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd1 <- parallelize(sc, 0:4)
+#' rdd2 <- parallelize(sc, 1000:1004)
+#' collect(zipRDD(rdd1, rdd2))
+#' # list(list(0, 1000), list(1, 1001), list(2, 1002), list(3, 1003), list(4, 1004))
+#'}
+#' @rdname zipRDD
+#' @aliases zipRDD,RDD
+setMethod("zipRDD",
+          signature(x = "RDD", other = "RDD"),
+          function(x, other) {
+            n1 <- numPartitions(x)
+            n2 <- numPartitions(other)
+            if (n1 != n2) {
+              stop("Can only zip RDDs which have the same number of partitions.")
+            }
+
+            if (getSerializedMode(x) != getSerializedMode(other) || 
+                getSerializedMode(x) == "byte") {
+              # Append the number of elements in each partition to that partition so that we can later
+              # check if corresponding partitions of both RDDs have the same number of elements.
+              #
+              # Note that this appending also serves the purpose of reserialization, because even if 
+              # any RDD is serialized, we need to reserialize it to make sure its partitions are encoded
+              # as a single byte array. For example, partitions of an RDD generated from partitionBy()
+              # may be encoded as multiple byte arrays.          
+              appendLength <- function(part) {
+                part[[length(part) + 1]] <- length(part) + 1
+                part
+              }
+              x <- lapplyPartition(x, appendLength)
+              other <- lapplyPartition(other, appendLength)
+            }
+            
+            zippedJRDD <- callJMethod(getJRDD(x), "zip", getJRDD(other))
+            # The zippedRDD's elements are of scala Tuple2 type. The serialized
+            # flag Here is used for the elements inside the tuples.
+            serializerMode <- getSerializedMode(x)
+            zippedRDD <- RDD(zippedJRDD, serializerMode)
+            
+            partitionFunc <- function(split, part) {
+              len <- length(part)
+              if (len > 0) {
+                if (serializerMode == "byte") {
+                  lengthOfValues <- part[[len]]
+                  lengthOfKeys <- part[[len - lengthOfValues]]
+                  stopifnot(len == lengthOfKeys + lengthOfValues)
+                  
+                  # check if corresponding partitions of both RDDs have the same number of elements.
+                  if (lengthOfKeys != lengthOfValues) {
+                    stop("Can only zip RDDs with same number of elements in each pair of corresponding partitions.")
+                  }
+                  
+                  if (lengthOfKeys > 1) {
+                    keys <- part[1 : (lengthOfKeys - 1)]
+                    values <- part[(lengthOfKeys + 1) : (len - 1)]                    
+                  } else {
+                    keys <- list()
+                    values <- list()
+                  }
+                } else {
+                  # Keys, values must have same length here, because this has
+                  # been validated inside the JavaRDD.zip() function.
+                  keys <- part[c(TRUE, FALSE)]
+                  values <- part[c(FALSE, TRUE)]
+                }
+                mapply(
+                    function(k, v) {
+                      list(k, v)
+                    },
+                    keys,
+                    values,
+                    SIMPLIFY = FALSE,
+                    USE.NAMES = FALSE)
+              } else {
+                part
+              }
+            }
+            
+            PipelinedRDD(zippedRDD, partitionFunc)
+          })
diff --git a/R/pkg/R/SQLContext.R b/R/pkg/R/SQLContext.R
new file mode 100644
index 0000000000000..930ada22f4c38
--- /dev/null
+++ b/R/pkg/R/SQLContext.R
@@ -0,0 +1,520 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# SQLcontext.R: SQLContext-driven functions
+
+#' infer the SQL type
+infer_type <- function(x) {
+  if (is.null(x)) {
+    stop("can not infer type from NULL")
+  }
+
+  # class of POSIXlt is c("POSIXlt" "POSIXt")
+  type <- switch(class(x)[[1]],
+                 integer = "integer",
+                 character = "string",
+                 logical = "boolean",
+                 double = "double",
+                 numeric = "double",
+                 raw = "binary",
+                 list = "array",
+                 environment = "map",
+                 Date = "date",
+                 POSIXlt = "timestamp",
+                 POSIXct = "timestamp",
+                 stop(paste("Unsupported type for DataFrame:", class(x))))
+
+  if (type == "map") {
+    stopifnot(length(x) > 0)
+    key <- ls(x)[[1]]
+    list(type = "map",
+         keyType = "string",
+         valueType = infer_type(get(key, x)),
+         valueContainsNull = TRUE)
+  } else if (type == "array") {
+    stopifnot(length(x) > 0)
+    names <- names(x)
+    if (is.null(names)) {
+      list(type = "array", elementType = infer_type(x[[1]]), containsNull = TRUE)
+    } else {
+      # StructType
+      types <- lapply(x, infer_type)
+      fields <- lapply(1:length(x), function(i) {
+        list(name = names[[i]], type = types[[i]], nullable = TRUE)
+      })
+      list(type = "struct", fields = fields)
+    }
+  } else if (length(x) > 1) {
+    list(type = "array", elementType = type, containsNull = TRUE)
+  } else {
+    type
+  }
+}
+
+#' dump the schema into JSON string
+tojson <- function(x) {
+  if (is.list(x)) {
+    names <- names(x)
+    if (!is.null(names)) {
+      items <- lapply(names, function(n) {
+        safe_n <- gsub('"', '\\"', n)
+        paste(tojson(safe_n), ':', tojson(x[[n]]), sep = '')
+      })
+      d <- paste(items, collapse = ', ')
+      paste('{', d, '}', sep = '')
+    } else {
+      l <- paste(lapply(x, tojson), collapse = ', ')
+      paste('[', l, ']', sep = '')
+    }
+  } else if (is.character(x)) {
+    paste('"', x, '"', sep = '')
+  } else if (is.logical(x)) {
+    if (x) "true" else "false"
+  } else {
+    stop(paste("unexpected type:", class(x)))
+  }
+}
+
+#' Create a DataFrame from an RDD
+#'
+#' Converts an RDD to a DataFrame by infer the types.
+#'
+#' @param sqlCtx A SQLContext
+#' @param data An RDD or list or data.frame
+#' @param schema a list of column names or named list (StructType), optional
+#' @return an DataFrame
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' rdd <- lapply(parallelize(sc, 1:10), function(x) list(a=x, b=as.character(x)))
+#' df <- createDataFrame(sqlCtx, rdd)
+#' }
+
+# TODO(davies): support sampling and infer type from NA
+createDataFrame <- function(sqlCtx, data, schema = NULL, samplingRatio = 1.0) {
+  if (is.data.frame(data)) {
+      # get the names of columns, they will be put into RDD
+      schema <- names(data)
+      n <- nrow(data)
+      m <- ncol(data)
+      # get rid of factor type
+      dropFactor <- function(x) {
+        if (is.factor(x)) {
+          as.character(x)
+        } else {
+          x
+        }
+      }
+      data <- lapply(1:n, function(i) {
+        lapply(1:m, function(j) { dropFactor(data[i,j]) })
+      })
+  }
+  if (is.list(data)) {
+    sc <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "getJavaSparkContext", sqlCtx)
+    rdd <- parallelize(sc, data)
+  } else if (inherits(data, "RDD")) {
+    rdd <- data
+  } else {
+    stop(paste("unexpected type:", class(data)))
+  }
+
+  if (is.null(schema) || is.null(names(schema))) {
+    row <- first(rdd)
+    names <- if (is.null(schema)) {
+      names(row)
+    } else {
+      as.list(schema)
+    }
+    if (is.null(names)) {
+      names <- lapply(1:length(row), function(x) {
+       paste("_", as.character(x), sep = "")
+      })
+    }
+
+    # SPAKR-SQL does not support '.' in column name, so replace it with '_'
+    # TODO(davies): remove this once SPARK-2775 is fixed
+    names <- lapply(names, function(n) {
+      nn <- gsub("[.]", "_", n)
+      if (nn != n) {
+        warning(paste("Use", nn, "instead of", n, " as column name"))
+      }
+      nn
+    })
+
+    types <- lapply(row, infer_type)
+    fields <- lapply(1:length(row), function(i) {
+      list(name = names[[i]], type = types[[i]], nullable = TRUE)
+    })
+    schema <- list(type = "struct", fields = fields)
+  }
+
+  stopifnot(class(schema) == "list")
+  stopifnot(schema$type == "struct")
+  stopifnot(class(schema$fields) == "list")
+  schemaString <- tojson(schema)
+
+  jrdd <- getJRDD(lapply(rdd, function(x) x), "row")
+  srdd <- callJMethod(jrdd, "rdd")
+  sdf <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "createDF",
+                     srdd, schemaString, sqlCtx)
+  dataFrame(sdf)
+}
+
+#' toDF
+#'
+#' Converts an RDD to a DataFrame by infer the types.
+#'
+#' @param x An RDD
+#'
+#' @rdname DataFrame
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' rdd <- lapply(parallelize(sc, 1:10), function(x) list(a=x, b=as.character(x)))
+#' df <- toDF(rdd)
+#' }
+
+setGeneric("toDF", function(x, ...) { standardGeneric("toDF") })
+
+setMethod("toDF", signature(x = "RDD"),
+          function(x, ...) {
+            sqlCtx <- if (exists(".sparkRHivesc", envir = .sparkREnv)) {
+              get(".sparkRHivesc", envir = .sparkREnv)
+            } else if (exists(".sparkRSQLsc", envir = .sparkREnv)) {
+              get(".sparkRSQLsc", envir = .sparkREnv)
+            } else {
+              stop("no SQL context available")
+            }
+            createDataFrame(sqlCtx, x, ...)
+          })
+
+#' Create a DataFrame from a JSON file.
+#'
+#' Loads a JSON file (one object per line), returning the result as a DataFrame 
+#' It goes through the entire dataset once to determine the schema.
+#'
+#' @param sqlCtx SQLContext to use
+#' @param path Path of file to read. A vector of multiple paths is allowed.
+#' @return DataFrame
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' }
+
+jsonFile <- function(sqlCtx, path) {
+  # Allow the user to have a more flexible definiton of the text file path
+  path <- normalizePath(path)
+  # Convert a string vector of paths to a string containing comma separated paths
+  path <- paste(path, collapse = ",")
+  sdf <- callJMethod(sqlCtx, "jsonFile", path)
+  dataFrame(sdf)
+}
+
+
+#' JSON RDD
+#'
+#' Loads an RDD storing one JSON object per string as a DataFrame.
+#'
+#' @param sqlCtx SQLContext to use
+#' @param rdd An RDD of JSON string
+#' @param schema A StructType object to use as schema
+#' @param samplingRatio The ratio of simpling used to infer the schema
+#' @return A DataFrame
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' rdd <- texFile(sc, "path/to/json")
+#' df <- jsonRDD(sqlCtx, rdd)
+#' }
+
+# TODO: support schema
+jsonRDD <- function(sqlCtx, rdd, schema = NULL, samplingRatio = 1.0) {
+  rdd <- serializeToString(rdd)
+  if (is.null(schema)) {
+    sdf <- callJMethod(sqlCtx, "jsonRDD", callJMethod(getJRDD(rdd), "rdd"), samplingRatio)
+    dataFrame(sdf)
+  } else {
+    stop("not implemented")
+  }
+}
+
+
+#' Create a DataFrame from a Parquet file.
+#' 
+#' Loads a Parquet file, returning the result as a DataFrame.
+#'
+#' @param sqlCtx SQLContext to use
+#' @param ... Path(s) of parquet file(s) to read.
+#' @return DataFrame
+#' @export
+
+# TODO: Implement saveasParquetFile and write examples for both
+parquetFile <- function(sqlCtx, ...) {
+  # Allow the user to have a more flexible definiton of the text file path
+  paths <- lapply(list(...), normalizePath)
+  sdf <- callJMethod(sqlCtx, "parquetFile", paths)
+  dataFrame(sdf)
+}
+
+#' SQL Query
+#' 
+#' Executes a SQL query using Spark, returning the result as a DataFrame.
+#'
+#' @param sqlCtx SQLContext to use
+#' @param sqlQuery A character vector containing the SQL query
+#' @return DataFrame
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' registerTempTable(df, "table")
+#' new_df <- sql(sqlCtx, "SELECT * FROM table")
+#' }
+
+sql <- function(sqlCtx, sqlQuery) {
+  sdf <- callJMethod(sqlCtx, "sql", sqlQuery)
+  dataFrame(sdf)
+}
+
+
+#' Create a DataFrame from a SparkSQL Table
+#' 
+#' Returns the specified Table as a DataFrame.  The Table must have already been registered
+#' in the SQLContext.
+#'
+#' @param sqlCtx SQLContext to use
+#' @param tableName The SparkSQL Table to convert to a DataFrame.
+#' @return DataFrame
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' registerTempTable(df, "table")
+#' new_df <- table(sqlCtx, "table")
+#' }
+
+table <- function(sqlCtx, tableName) {
+  sdf <- callJMethod(sqlCtx, "table", tableName)
+  dataFrame(sdf) 
+}
+
+
+#' Tables
+#'
+#' Returns a DataFrame containing names of tables in the given database.
+#'
+#' @param sqlCtx SQLContext to use
+#' @param databaseName name of the database
+#' @return a DataFrame
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' tables(sqlCtx, "hive")
+#' }
+
+tables <- function(sqlCtx, databaseName = NULL) {
+  jdf <- if (is.null(databaseName)) {
+    callJMethod(sqlCtx, "tables")
+  } else {
+    callJMethod(sqlCtx, "tables", databaseName)
+  }
+  dataFrame(jdf)
+}
+
+
+#' Table Names
+#'
+#' Returns the names of tables in the given database as an array.
+#'
+#' @param sqlCtx SQLContext to use
+#' @param databaseName name of the database
+#' @return a list of table names
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' tableNames(sqlCtx, "hive")
+#' }
+
+tableNames <- function(sqlCtx, databaseName = NULL) {
+  if (is.null(databaseName)) {
+    callJMethod(sqlCtx, "tableNames")
+  } else {
+    callJMethod(sqlCtx, "tableNames", databaseName)
+  }
+}
+
+
+#' Cache Table
+#' 
+#' Caches the specified table in-memory.
+#'
+#' @param sqlCtx SQLContext to use
+#' @param tableName The name of the table being cached
+#' @return DataFrame
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' registerTempTable(df, "table")
+#' cacheTable(sqlCtx, "table")
+#' }
+
+cacheTable <- function(sqlCtx, tableName) {
+  callJMethod(sqlCtx, "cacheTable", tableName)  
+}
+
+#' Uncache Table
+#' 
+#' Removes the specified table from the in-memory cache.
+#'
+#' @param sqlCtx SQLContext to use
+#' @param tableName The name of the table being uncached
+#' @return DataFrame
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' registerTempTable(df, "table")
+#' uncacheTable(sqlCtx, "table")
+#' }
+
+uncacheTable <- function(sqlCtx, tableName) {
+  callJMethod(sqlCtx, "uncacheTable", tableName)
+}
+
+#' Clear Cache
+#'
+#' Removes all cached tables from the in-memory cache.
+#'
+#' @param sqlCtx SQLContext to use
+#' @examples
+#' \dontrun{
+#' clearCache(sqlCtx)
+#' }
+
+clearCache <- function(sqlCtx) {
+  callJMethod(sqlCtx, "clearCache")
+}
+
+#' Drop Temporary Table
+#'
+#' Drops the temporary table with the given table name in the catalog.
+#' If the table has been cached/persisted before, it's also unpersisted.
+#'
+#' @param sqlCtx SQLContext to use
+#' @param tableName The name of the SparkSQL table to be dropped.
+#' @examples
+#' \dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' df <- loadDF(sqlCtx, path, "parquet")
+#' registerTempTable(df, "table")
+#' dropTempTable(sqlCtx, "table")
+#' }
+
+dropTempTable <- function(sqlCtx, tableName) {
+  if (class(tableName) != "character") {
+    stop("tableName must be a string.")
+  }
+  callJMethod(sqlCtx, "dropTempTable", tableName)
+}
+
+#' Load an DataFrame
+#'
+#' Returns the dataset in a data source as a DataFrame
+#'
+#' The data source is specified by the `source` and a set of options(...).
+#' If `source` is not specified, the default data source configured by
+#' "spark.sql.sources.default" will be used.
+#'
+#' @param sqlCtx SQLContext to use
+#' @param path The path of files to load
+#' @param source the name of external data source
+#' @return DataFrame
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' df <- load(sqlCtx, "path/to/file.json", source = "json")
+#' }
+
+loadDF <- function(sqlCtx, path = NULL, source = NULL, ...) {
+  options <- varargsToEnv(...)
+  if (!is.null(path)) {
+    options[['path']] <- path
+  }
+  sdf <- callJMethod(sqlCtx, "load", source, options)
+  dataFrame(sdf)
+}
+
+#' Create an external table
+#'
+#' Creates an external table based on the dataset in a data source,
+#' Returns the DataFrame associated with the external table.
+#'
+#' The data source is specified by the `source` and a set of options(...).
+#' If `source` is not specified, the default data source configured by
+#' "spark.sql.sources.default" will be used.
+#'
+#' @param sqlCtx SQLContext to use
+#' @param tableName A name of the table
+#' @param path The path of files to load
+#' @param source the name of external data source
+#' @return DataFrame
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' df <- sparkRSQL.createExternalTable(sqlCtx, "myjson", path="path/to/json", source="json")
+#' }
+
+createExternalTable <- function(sqlCtx, tableName, path = NULL, source = NULL, ...) {
+  options <- varargsToEnv(...)
+  if (!is.null(path)) {
+    options[['path']] <- path
+  }
+  sdf <- callJMethod(sqlCtx, "createExternalTable", tableName, source, options)
+  dataFrame(sdf)
+}
diff --git a/R/pkg/R/SQLTypes.R b/R/pkg/R/SQLTypes.R
new file mode 100644
index 0000000000000..962fba5b3cf03
--- /dev/null
+++ b/R/pkg/R/SQLTypes.R
@@ -0,0 +1,64 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Utility functions for handling SparkSQL DataTypes.
+
+# Handler for StructType
+structType <- function(st) {
+  obj <- structure(new.env(parent = emptyenv()), class = "structType")
+  obj$jobj <- st
+  obj$fields <- function() { lapply(callJMethod(st, "fields"), structField) }
+  obj
+}
+
+#' Print a Spark StructType.
+#'
+#' This function prints the contents of a StructType returned from the
+#' SparkR JVM backend.
+#'
+#' @param x A StructType object
+#' @param ... further arguments passed to or from other methods
+print.structType <- function(x, ...) {
+  fieldsList <- lapply(x$fields(), function(i) { i$print() })
+  print(fieldsList)
+}
+
+# Handler for StructField
+structField <- function(sf) {
+  obj <- structure(new.env(parent = emptyenv()), class = "structField")
+  obj$jobj <- sf
+  obj$name <- function() { callJMethod(sf, "name") }
+  obj$dataType <- function() { callJMethod(sf, "dataType") }
+  obj$dataType.toString <- function() { callJMethod(obj$dataType(), "toString") }
+  obj$dataType.simpleString <- function() { callJMethod(obj$dataType(), "simpleString") }
+  obj$nullable <- function() { callJMethod(sf, "nullable") }
+  obj$print <- function() { paste("StructField(", 
+                     paste(obj$name(), obj$dataType.toString(), obj$nullable(), sep = ", "),
+                     ")", sep = "") }
+  obj
+}
+
+#' Print a Spark StructField.
+#'
+#' This function prints the contents of a StructField returned from the
+#' SparkR JVM backend.
+#'
+#' @param x A StructField object
+#' @param ... further arguments passed to or from other methods
+print.structField <- function(x, ...) {
+  cat(x$print())
+}
diff --git a/R/pkg/R/backend.R b/R/pkg/R/backend.R
new file mode 100644
index 0000000000000..2fb6fae55f28c
--- /dev/null
+++ b/R/pkg/R/backend.R
@@ -0,0 +1,115 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Methods to call into SparkRBackend.
+
+
+# Returns TRUE if object is an instance of given class
+isInstanceOf <- function(jobj, className) {
+  stopifnot(class(jobj) == "jobj")
+  cls <- callJStatic("java.lang.Class", "forName", className)
+  callJMethod(cls, "isInstance", jobj)
+}
+
+# Call a Java method named methodName on the object
+# specified by objId. objId should be a "jobj" returned
+# from the SparkRBackend.
+callJMethod <- function(objId, methodName, ...) {
+  stopifnot(class(objId) == "jobj")
+  if (!isValidJobj(objId)) {
+    stop("Invalid jobj ", objId$id,
+         ". If SparkR was restarted, Spark operations need to be re-executed.")
+  }
+  invokeJava(isStatic = FALSE, objId$id, methodName, ...)
+}
+
+# Call a static method on a specified className
+callJStatic <- function(className, methodName, ...) {
+  invokeJava(isStatic = TRUE, className, methodName, ...)
+}
+
+# Create a new object of the specified class name
+newJObject <- function(className, ...) {
+  invokeJava(isStatic = TRUE, className, methodName = "<init>", ...)
+}
+
+# Remove an object from the SparkR backend. This is done
+# automatically when a jobj is garbage collected.
+removeJObject <- function(objId) {
+  invokeJava(isStatic = TRUE, "SparkRHandler", "rm", objId)
+}
+
+isRemoveMethod <- function(isStatic, objId, methodName) {
+  isStatic == TRUE && objId == "SparkRHandler" && methodName == "rm"
+}
+
+# Invoke a Java method on the SparkR backend. Users
+# should typically use one of the higher level methods like
+# callJMethod, callJStatic etc. instead of using this.
+#
+# isStatic - TRUE if the method to be called is static
+# objId - String that refers to the object on which method is invoked
+#         Should be a jobj id for non-static methods and the classname
+#         for static methods
+# methodName - name of method to be invoked
+invokeJava <- function(isStatic, objId, methodName, ...) {
+  if (!exists(".sparkRCon", .sparkREnv)) {
+    stop("No connection to backend found. Please re-run sparkR.init")
+  }
+
+  # If this isn't a removeJObject call
+  if (!isRemoveMethod(isStatic, objId, methodName)) {
+    objsToRemove <- ls(.toRemoveJobjs)
+    if (length(objsToRemove) > 0) {
+      sapply(objsToRemove,
+            function(e) {
+              removeJObject(e)
+            })
+      rm(list = objsToRemove, envir = .toRemoveJobjs)
+    }
+  }
+
+
+  rc <- rawConnection(raw(0), "r+")
+
+  writeBoolean(rc, isStatic)
+  writeString(rc, objId)
+  writeString(rc, methodName)
+
+  args <- list(...)
+  writeInt(rc, length(args))
+  writeArgs(rc, args)
+
+  # Construct the whole request message to send it once,
+  # avoiding write-write-read pattern in case of Nagle's algorithm.
+  # Refer to http://en.wikipedia.org/wiki/Nagle%27s_algorithm for the details.
+  bytesToSend <- rawConnectionValue(rc)
+  close(rc)
+  rc <- rawConnection(raw(0), "r+")
+  writeInt(rc, length(bytesToSend))
+  writeBin(bytesToSend, rc)
+  requestMessage <- rawConnectionValue(rc)
+  close(rc)
+
+  conn <- get(".sparkRCon", .sparkREnv)
+  writeBin(requestMessage, conn)
+
+  # TODO: check the status code to output error information
+  returnStatus <- readInt(conn)
+  stopifnot(returnStatus == 0)
+  readObject(conn)
+}
diff --git a/R/pkg/R/broadcast.R b/R/pkg/R/broadcast.R
new file mode 100644
index 0000000000000..583fa2e7fdcfd
--- /dev/null
+++ b/R/pkg/R/broadcast.R
@@ -0,0 +1,86 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# S4 class representing Broadcast variables
+
+# Hidden environment that holds values for broadcast variables
+# This will not be serialized / shipped by default
+.broadcastNames <- new.env()
+.broadcastValues <- new.env()
+.broadcastIdToName <- new.env()
+
+#' @title S4 class that represents a Broadcast variable
+#' @description Broadcast variables can be created using the broadcast
+#'              function from a \code{SparkContext}.
+#' @rdname broadcast-class
+#' @seealso broadcast 
+#'
+#' @param id Id of the backing Spark broadcast variable 
+#' @export
+setClass("Broadcast", slots = list(id = "character"))
+
+#' @rdname broadcast-class
+#' @param value Value of the broadcast variable
+#' @param jBroadcastRef reference to the backing Java broadcast object
+#' @param objName name of broadcasted object
+#' @export
+Broadcast <- function(id, value, jBroadcastRef, objName) {
+  .broadcastValues[[id]] <- value
+  .broadcastNames[[as.character(objName)]] <- jBroadcastRef
+  .broadcastIdToName[[id]] <- as.character(objName)
+  new("Broadcast", id = id)
+}
+
+#' @description
+#' \code{value} can be used to get the value of a broadcast variable inside
+#' a distributed function.
+#'
+#' @param bcast The broadcast variable to get
+#' @rdname broadcast
+#' @aliases value,Broadcast-method
+setMethod("value",
+          signature(bcast = "Broadcast"),
+          function(bcast) {
+            if (exists(bcast@id, envir = .broadcastValues)) {
+              get(bcast@id, envir = .broadcastValues)
+            } else {
+              NULL
+            }
+          })
+
+#' Internal function to set values of a broadcast variable.
+#'
+#' This function is used internally by Spark to set the value of a broadcast
+#' variable on workers. Not intended for use outside the package.
+#'
+#' @rdname broadcast-internal
+#' @seealso broadcast, value 
+
+#' @param bcastId The id of broadcast variable to set
+#' @param value The value to be set
+#' @export
+setBroadcastValue <- function(bcastId, value) {
+  bcastIdStr <- as.character(bcastId)
+  .broadcastValues[[bcastIdStr]] <- value
+}
+
+#' Helper function to clear the list of broadcast variables we know about
+#' Should be called when the SparkR JVM backend is shutdown
+clearBroadcastVariables <- function() {
+  bcasts <- ls(.broadcastNames)
+  rm(list = bcasts, envir = .broadcastNames)
+}
diff --git a/R/pkg/R/client.R b/R/pkg/R/client.R
new file mode 100644
index 0000000000000..1281c41213e32
--- /dev/null
+++ b/R/pkg/R/client.R
@@ -0,0 +1,57 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Client code to connect to SparkRBackend
+
+# Creates a SparkR client connection object
+# if one doesn't already exist
+connectBackend <- function(hostname, port, timeout = 6000) {
+  if (exists(".sparkRcon", envir = .sparkREnv)) {
+    if (isOpen(.sparkREnv[[".sparkRCon"]])) {
+      cat("SparkRBackend client connection already exists\n")
+      return(get(".sparkRcon", envir = .sparkREnv))
+    }
+  }
+
+  con <- socketConnection(host = hostname, port = port, server = FALSE,
+                          blocking = TRUE, open = "wb", timeout = timeout)
+
+  assign(".sparkRCon", con, envir = .sparkREnv)
+  con
+}
+
+launchBackend <- function(args, sparkHome, jars, sparkSubmitOpts) {
+  if (.Platform$OS.type == "unix") {
+    sparkSubmitBinName = "spark-submit"
+  } else {
+    sparkSubmitBinName = "spark-submit.cmd"
+  }
+
+  if (sparkHome != "") {
+    sparkSubmitBin <- file.path(sparkHome, "bin", sparkSubmitBinName)
+  } else {
+    sparkSubmitBin <- sparkSubmitBinName
+  }
+
+  if (jars != "") {
+    jars <- paste("--jars", jars)
+  }
+
+  combinedArgs <- paste(jars, sparkSubmitOpts, args, sep = " ")
+  cat("Launching java with spark-submit command", sparkSubmitBin, combinedArgs, "\n")
+  invisible(system2(sparkSubmitBin, combinedArgs, wait = F))
+}
diff --git a/R/pkg/R/column.R b/R/pkg/R/column.R
new file mode 100644
index 0000000000000..e196305186b9a
--- /dev/null
+++ b/R/pkg/R/column.R
@@ -0,0 +1,199 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Column Class
+
+#' @include generics.R jobj.R
+NULL
+
+setOldClass("jobj")
+
+#' @title S4 class that represents a DataFrame column
+#' @description The column class supports unary, binary operations on DataFrame columns
+
+#' @rdname column
+#'
+#' @param jc reference to JVM DataFrame column
+#' @export
+setClass("Column",
+         slots = list(jc = "jobj"))
+
+setMethod("initialize", "Column", function(.Object, jc) {
+  .Object@jc <- jc
+  .Object
+})
+
+column <- function(jc) {
+  new("Column", jc)
+}
+
+col <- function(x) {
+  column(callJStatic("org.apache.spark.sql.functions", "col", x))
+}
+
+#' @rdname show
+setMethod("show", "Column",
+          function(object) {
+            cat("Column", callJMethod(object@jc, "toString"), "\n")
+          })
+
+operators <- list(
+  "+" = "plus", "-" = "minus", "*" = "multiply", "/" = "divide", "%%" = "mod",
+  "==" = "equalTo", ">" = "gt", "<" = "lt", "!=" = "notEqual", "<=" = "leq", ">=" = "geq",
+  # we can not override `&&` and `||`, so use `&` and `|` instead
+  "&" = "and", "|" = "or" #, "!" = "unary_$bang"
+)
+column_functions1 <- c("asc", "desc", "isNull", "isNotNull")
+column_functions2 <- c("like", "rlike", "startsWith", "endsWith", "getField", "getItem", "contains")
+functions <- c("min", "max", "sum", "avg", "mean", "count", "abs", "sqrt",
+               "first", "last", "lower", "upper", "sumDistinct")
+
+createOperator <- function(op) {
+  setMethod(op,
+            signature(e1 = "Column"),
+            function(e1, e2) {
+              jc <- if (missing(e2)) {
+                if (op == "-") {
+                  callJMethod(e1@jc, "unary_$minus")
+                } else {
+                  callJMethod(e1@jc, operators[[op]])
+                }
+              } else {
+                if (class(e2) == "Column") {
+                  e2 <- e2@jc
+                }
+                callJMethod(e1@jc, operators[[op]], e2)
+              }
+              column(jc)
+            })
+}
+
+createColumnFunction1 <- function(name) {
+  setMethod(name,
+            signature(x = "Column"),
+            function(x) {
+              column(callJMethod(x@jc, name))
+            })
+}
+
+createColumnFunction2 <- function(name) {
+  setMethod(name,
+            signature(x = "Column"),
+            function(x, data) {
+              if (class(data) == "Column") {
+                data <- data@jc
+              }
+              jc <- callJMethod(x@jc, name, data)
+              column(jc)
+            })
+}
+
+createStaticFunction <- function(name) {
+  setMethod(name,
+            signature(x = "Column"),
+            function(x) {
+              jc <- callJStatic("org.apache.spark.sql.functions", name, x@jc)
+              column(jc)
+            })
+}
+
+createMethods <- function() {
+  for (op in names(operators)) {
+    createOperator(op)
+  }
+  for (name in column_functions1) {
+    createColumnFunction1(name)
+  }
+  for (name in column_functions2) {
+    createColumnFunction2(name)
+  }
+  for (x in functions) {
+    createStaticFunction(x)
+  }
+}
+
+createMethods()
+
+#' alias
+#'
+#' Set a new name for a column
+setMethod("alias",
+          signature(object = "Column"),
+          function(object, data) {
+            if (is.character(data)) {
+              column(callJMethod(object@jc, "as", data))
+            } else {
+              stop("data should be character")
+            }
+          })
+
+#' An expression that returns a substring.
+#'
+#' @param start starting position
+#' @param stop ending position
+setMethod("substr", signature(x = "Column"),
+          function(x, start, stop) {
+            jc <- callJMethod(x@jc, "substr", as.integer(start - 1), as.integer(stop - start + 1))
+            column(jc)
+          })
+
+#' Casts the column to a different data type.
+#' @examples
+#' \dontrun{
+#'   cast(df$age, "string")
+#'   cast(df$name, list(type="array", elementType="byte", containsNull = TRUE))
+#' }
+setMethod("cast",
+          signature(x = "Column"),
+          function(x, dataType) {
+            if (is.character(dataType)) {
+              column(callJMethod(x@jc, "cast", dataType))
+            } else if (is.list(dataType)) {
+              json <- tojson(dataType)
+              jdataType <- callJStatic("org.apache.spark.sql.types.DataType", "fromJson", json)
+              column(callJMethod(x@jc, "cast", jdataType))
+            } else {
+              stop("dataType should be character or list")
+            }
+          })
+
+#' Approx Count Distinct
+#'
+#' Returns the approximate number of distinct items in a group.
+#'
+setMethod("approxCountDistinct",
+          signature(x = "Column"),
+          function(x, rsd = 0.95) {
+            jc <- callJStatic("org.apache.spark.sql.functions", "approxCountDistinct", x@jc, rsd)
+            column(jc)
+          })
+
+#' Count Distinct
+#'
+#' returns the number of distinct items in a group.
+#'
+setMethod("countDistinct",
+          signature(x = "Column"),
+          function(x, ...) {
+            jcol <- lapply(list(...), function (x) {
+              x@jc
+            })
+            jc <- callJStatic("org.apache.spark.sql.functions", "countDistinct", x@jc,
+                              listToSeq(jcol))
+            column(jc)
+          })
+
diff --git a/R/pkg/R/context.R b/R/pkg/R/context.R
new file mode 100644
index 0000000000000..2fc0bb294bcce
--- /dev/null
+++ b/R/pkg/R/context.R
@@ -0,0 +1,225 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# context.R: SparkContext driven functions
+
+getMinSplits <- function(sc, minSplits) {
+  if (is.null(minSplits)) {
+    defaultParallelism <- callJMethod(sc, "defaultParallelism")
+    minSplits <- min(defaultParallelism, 2)
+  }
+  as.integer(minSplits)
+}
+
+#' Create an RDD from a text file.
+#'
+#' This function reads a text file from HDFS, a local file system (available on all
+#' nodes), or any Hadoop-supported file system URI, and creates an
+#' RDD of strings from it.
+#'
+#' @param sc SparkContext to use
+#' @param path Path of file to read. A vector of multiple paths is allowed.
+#' @param minSplits Minimum number of splits to be created. If NULL, the default
+#'  value is chosen based on available parallelism.
+#' @return RDD where each item is of type \code{character}
+#' @export
+#' @examples
+#'\dontrun{
+#'  sc <- sparkR.init()
+#'  lines <- textFile(sc, "myfile.txt")
+#'}
+textFile <- function(sc, path, minSplits = NULL) {
+  # Allow the user to have a more flexible definiton of the text file path
+  path <- suppressWarnings(normalizePath(path))
+  #' Convert a string vector of paths to a string containing comma separated paths
+  path <- paste(path, collapse = ",")
+
+  jrdd <- callJMethod(sc, "textFile", path, getMinSplits(sc, minSplits))
+  # jrdd is of type JavaRDD[String]
+  RDD(jrdd, "string")
+}
+
+#' Load an RDD saved as a SequenceFile containing serialized objects.
+#'
+#' The file to be loaded should be one that was previously generated by calling
+#' saveAsObjectFile() of the RDD class.
+#'
+#' @param sc SparkContext to use
+#' @param path Path of file to read. A vector of multiple paths is allowed.
+#' @param minSplits Minimum number of splits to be created. If NULL, the default
+#'  value is chosen based on available parallelism.
+#' @return RDD containing serialized R objects.
+#' @seealso saveAsObjectFile
+#' @export
+#' @examples
+#'\dontrun{
+#'  sc <- sparkR.init()
+#'  rdd <- objectFile(sc, "myfile")
+#'}
+objectFile <- function(sc, path, minSplits = NULL) {
+  # Allow the user to have a more flexible definiton of the text file path
+  path <- suppressWarnings(normalizePath(path))
+  #' Convert a string vector of paths to a string containing comma separated paths
+  path <- paste(path, collapse = ",")
+
+  jrdd <- callJMethod(sc, "objectFile", path, getMinSplits(sc, minSplits))
+  # Assume the RDD contains serialized R objects.
+  RDD(jrdd, "byte")
+}
+
+#' Create an RDD from a homogeneous list or vector.
+#'
+#' This function creates an RDD from a local homogeneous list in R. The elements
+#' in the list are split into \code{numSlices} slices and distributed to nodes
+#' in the cluster.
+#'
+#' @param sc SparkContext to use
+#' @param coll collection to parallelize
+#' @param numSlices number of partitions to create in the RDD
+#' @return an RDD created from this collection
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10, 2)
+#' # The RDD should contain 10 elements
+#' length(rdd)
+#'}
+parallelize <- function(sc, coll, numSlices = 1) {
+  # TODO: bound/safeguard numSlices
+  # TODO: unit tests for if the split works for all primitives
+  # TODO: support matrix, data frame, etc
+  if ((!is.list(coll) && !is.vector(coll)) || is.data.frame(coll)) {
+    if (is.data.frame(coll)) {
+      message(paste("context.R: A data frame is parallelized by columns."))
+    } else {
+      if (is.matrix(coll)) {
+        message(paste("context.R: A matrix is parallelized by elements."))
+      } else {
+        message(paste("context.R: parallelize() currently only supports lists and vectors.",
+                      "Calling as.list() to coerce coll into a list."))
+      }
+    }
+    coll <- as.list(coll)
+  }
+
+  if (numSlices > length(coll))
+    numSlices <- length(coll)
+
+  sliceLen <- ceiling(length(coll) / numSlices)
+  slices <- split(coll, rep(1:(numSlices + 1), each = sliceLen)[1:length(coll)])
+
+  # Serialize each slice: obtain a list of raws, or a list of lists (slices) of
+  # 2-tuples of raws
+  serializedSlices <- lapply(slices, serialize, connection = NULL)
+
+  jrdd <- callJStatic("org.apache.spark.api.r.RRDD",
+                      "createRDDFromArray", sc, serializedSlices)
+
+  RDD(jrdd, "byte")
+}
+
+#' Include this specified package on all workers
+#'
+#' This function can be used to include a package on all workers before the
+#' user's code is executed. This is useful in scenarios where other R package
+#' functions are used in a function passed to functions like \code{lapply}.
+#' NOTE: The package is assumed to be installed on every node in the Spark
+#' cluster.
+#'
+#' @param sc SparkContext to use
+#' @param pkg Package name
+#'
+#' @export
+#' @examples
+#'\dontrun{
+#'  library(Matrix)
+#'
+#'  sc <- sparkR.init()
+#'  # Include the matrix library we will be using
+#'  includePackage(sc, Matrix)
+#'
+#'  generateSparse <- function(x) {
+#'    sparseMatrix(i=c(1, 2, 3), j=c(1, 2, 3), x=c(1, 2, 3))
+#'  }
+#'
+#'  rdd <- lapplyPartition(parallelize(sc, 1:2, 2L), generateSparse)
+#'  collect(rdd)
+#'}
+includePackage <- function(sc, pkg) {
+  pkg <- as.character(substitute(pkg))
+  if (exists(".packages", .sparkREnv)) {
+    packages <- .sparkREnv$.packages
+  } else {
+    packages <- list()
+  }
+  packages <- c(packages, pkg)
+  .sparkREnv$.packages <- packages
+}
+
+#' @title Broadcast a variable to all workers
+#'
+#' @description
+#' Broadcast a read-only variable to the cluster, returning a \code{Broadcast}
+#' object for reading it in distributed functions.
+#'
+#' @param sc Spark Context to use
+#' @param object Object to be broadcast
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:2, 2L)
+#'
+#' # Large Matrix object that we want to broadcast
+#' randomMat <- matrix(nrow=100, ncol=10, data=rnorm(1000))
+#' randomMatBr <- broadcast(sc, randomMat)
+#'
+#' # Use the broadcast variable inside the function
+#' useBroadcast <- function(x) {
+#'   sum(value(randomMatBr) * x)
+#' }
+#' sumRDD <- lapply(rdd, useBroadcast)
+#'}
+broadcast <- function(sc, object) {
+  objName <- as.character(substitute(object))
+  serializedObj <- serialize(object, connection = NULL)
+
+  jBroadcast <- callJMethod(sc, "broadcast", serializedObj)
+  id <- as.character(callJMethod(jBroadcast, "id"))
+
+  Broadcast(id, object, jBroadcast, objName)
+}
+
+#' @title Set the checkpoint directory
+#'
+#' Set the directory under which RDDs are going to be checkpointed. The
+#' directory must be a HDFS path if running on a cluster.
+#'
+#' @param sc Spark Context to use
+#' @param dirName Directory path
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' setCheckpointDir(sc, "~/checkpoints")
+#' rdd <- parallelize(sc, 1:2, 2L)
+#' checkpoint(rdd)
+#'}
+setCheckpointDir <- function(sc, dirName) {
+  invisible(callJMethod(sc, "setCheckpointDir", suppressWarnings(normalizePath(dirName))))
+}
diff --git a/R/pkg/R/deserialize.R b/R/pkg/R/deserialize.R
new file mode 100644
index 0000000000000..257b435607ce8
--- /dev/null
+++ b/R/pkg/R/deserialize.R
@@ -0,0 +1,184 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Utility functions to deserialize objects from Java.
+
+# Type mapping from Java to R
+# 
+# void -> NULL
+# Int -> integer
+# String -> character
+# Boolean -> logical
+# Double -> double
+# Long -> double
+# Array[Byte] -> raw
+# Date -> Date
+# Time -> POSIXct
+#
+# Array[T] -> list()
+# Object -> jobj
+
+readObject <- function(con) {
+  # Read type first
+  type <- readType(con)
+  readTypedObject(con, type)
+}
+
+readTypedObject <- function(con, type) {
+  switch (type,
+    "i" = readInt(con),
+    "c" = readString(con),
+    "b" = readBoolean(con),
+    "d" = readDouble(con),
+    "r" = readRaw(con),
+    "D" = readDate(con),
+    "t" = readTime(con),
+    "l" = readList(con),
+    "n" = NULL,
+    "j" = getJobj(readString(con)),
+    stop(paste("Unsupported type for deserialization", type)))
+}
+
+readString <- function(con) {
+  stringLen <- readInt(con)
+  string <- readBin(con, raw(), stringLen, endian = "big")
+  rawToChar(string)
+}
+
+readInt <- function(con) {
+  readBin(con, integer(), n = 1, endian = "big")
+}
+
+readDouble <- function(con) {
+  readBin(con, double(), n = 1, endian = "big")
+}
+
+readBoolean <- function(con) {
+  as.logical(readInt(con))
+}
+
+readType <- function(con) {
+  rawToChar(readBin(con, "raw", n = 1L))
+}
+
+readDate <- function(con) {
+  as.Date(readString(con))
+}
+
+readTime <- function(con) {
+  t <- readDouble(con)
+  as.POSIXct(t, origin = "1970-01-01")
+}
+
+# We only support lists where all elements are of same type
+readList <- function(con) {
+  type <- readType(con)
+  len <- readInt(con)
+  if (len > 0) {
+    l <- vector("list", len)
+    for (i in 1:len) {
+      l[[i]] <- readTypedObject(con, type)
+    }
+    l
+  } else {
+    list()
+  }
+}
+
+readRaw <- function(con) {
+  dataLen <- readInt(con)
+  data <- readBin(con, raw(), as.integer(dataLen), endian = "big")
+}
+
+readRawLen <- function(con, dataLen) {
+  data <- readBin(con, raw(), as.integer(dataLen), endian = "big")
+}
+
+readDeserialize <- function(con) {
+  # We have two cases that are possible - In one, the entire partition is
+  # encoded as a byte array, so we have only one value to read. If so just
+  # return firstData
+  dataLen <- readInt(con)
+  firstData <- unserialize(
+      readBin(con, raw(), as.integer(dataLen), endian = "big"))
+
+  # Else, read things into a list
+  dataLen <- readInt(con)
+  if (length(dataLen) > 0 && dataLen > 0) {
+    data <- list(firstData)
+    while (length(dataLen) > 0 && dataLen > 0) {
+      data[[length(data) + 1L]] <- unserialize(
+          readBin(con, raw(), as.integer(dataLen), endian = "big"))
+      dataLen <- readInt(con)
+    }
+    unlist(data, recursive = FALSE)
+  } else {
+    firstData
+  }
+}
+
+readDeserializeRows <- function(inputCon) {
+  # readDeserializeRows will deserialize a DataOutputStream composed of
+  # a list of lists. Since the DOS is one continuous stream and
+  # the number of rows varies, we put the readRow function in a while loop
+  # that termintates when the next row is empty.
+  data <- list()
+  while(TRUE) {
+    row <- readRow(inputCon)
+    if (length(row) == 0) {
+      break
+    }
+    data[[length(data) + 1L]] <- row
+  }
+  data # this is a list of named lists now
+}
+
+readRowList <- function(obj) {
+  # readRowList is meant for use inside an lapply. As a result, it is
+  # necessary to open a standalone connection for the row and consume
+  # the numCols bytes inside the read function in order to correctly
+  # deserialize the row.
+  rawObj <- rawConnection(obj, "r+")
+  on.exit(close(rawObj))
+  readRow(rawObj)
+}
+
+readRow <- function(inputCon) {
+  numCols <- readInt(inputCon)
+  if (length(numCols) > 0 && numCols > 0) {
+    lapply(1:numCols, function(x) {
+      obj <- readObject(inputCon)
+      if (is.null(obj)) {
+        NA
+      } else {
+        obj
+      }
+    }) # each row is a list now
+  } else {
+    list()
+  }
+}
+
+# Take a single column as Array[Byte] and deserialize it into an atomic vector
+readCol <- function(inputCon, numRows) {
+  # sapply can not work with POSIXlt
+  do.call(c, lapply(1:numRows, function(x) {
+    value <- readObject(inputCon)
+    # Replace NULL with NA so we can coerce to vectors
+    if (is.null(value)) NA else value
+  }))
+}
diff --git a/R/pkg/R/generics.R b/R/pkg/R/generics.R
new file mode 100644
index 0000000000000..5fb1ccaa84ee2
--- /dev/null
+++ b/R/pkg/R/generics.R
@@ -0,0 +1,543 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+############ RDD Actions and Transformations ############
+
+#' @rdname aggregateRDD
+#' @seealso reduce
+#' @export
+setGeneric("aggregateRDD", function(x, zeroValue, seqOp, combOp) { standardGeneric("aggregateRDD") })
+
+#' @rdname cache-methods
+#' @export
+setGeneric("cache", function(x) { standardGeneric("cache") })
+
+#' @rdname coalesce
+#' @seealso repartition
+#' @export
+setGeneric("coalesce", function(x, numPartitions, ...) { standardGeneric("coalesce") })
+
+#' @rdname checkpoint-methods
+#' @export
+setGeneric("checkpoint", function(x) { standardGeneric("checkpoint") })
+
+#' @rdname collect-methods
+#' @export
+setGeneric("collect", function(x, ...) { standardGeneric("collect") })
+
+#' @rdname collect-methods
+#' @export
+setGeneric("collectAsMap", function(x) { standardGeneric("collectAsMap") })
+
+#' @rdname collect-methods
+#' @export
+setGeneric("collectPartition",
+           function(x, partitionId) {
+             standardGeneric("collectPartition")
+           })
+
+#' @rdname count
+#' @export
+setGeneric("count", function(x) { standardGeneric("count") })
+
+#' @rdname countByValue
+#' @export
+setGeneric("countByValue", function(x) { standardGeneric("countByValue") })
+
+#' @rdname distinct
+#' @export
+setGeneric("distinct", function(x, numPartitions = 1L) { standardGeneric("distinct") })
+
+#' @rdname filterRDD
+#' @export
+setGeneric("filterRDD", function(x, f) { standardGeneric("filterRDD") })
+
+#' @rdname first
+#' @export
+setGeneric("first", function(x) { standardGeneric("first") })
+
+#' @rdname flatMap
+#' @export
+setGeneric("flatMap", function(X, FUN) { standardGeneric("flatMap") })
+
+#' @rdname fold
+#' @seealso reduce
+#' @export
+setGeneric("fold", function(x, zeroValue, op) { standardGeneric("fold") })
+
+#' @rdname foreach
+#' @export
+setGeneric("foreach", function(x, func) { standardGeneric("foreach") })
+
+#' @rdname foreach
+#' @export
+setGeneric("foreachPartition", function(x, func) { standardGeneric("foreachPartition") })
+
+# The jrdd accessor function.
+setGeneric("getJRDD", function(rdd, ...) { standardGeneric("getJRDD") })
+
+#' @rdname glom
+#' @export
+setGeneric("glom", function(x) { standardGeneric("glom") })
+
+#' @rdname keyBy
+#' @export
+setGeneric("keyBy", function(x, func) { standardGeneric("keyBy") })
+
+#' @rdname lapplyPartition
+#' @export
+setGeneric("lapplyPartition", function(X, FUN) { standardGeneric("lapplyPartition") })
+
+#' @rdname lapplyPartitionsWithIndex
+#' @export
+setGeneric("lapplyPartitionsWithIndex",
+           function(X, FUN) {
+             standardGeneric("lapplyPartitionsWithIndex")
+           })
+
+#' @rdname lapply
+#' @export
+setGeneric("map", function(X, FUN) { standardGeneric("map") })
+
+#' @rdname lapplyPartition
+#' @export
+setGeneric("mapPartitions", function(X, FUN) { standardGeneric("mapPartitions") })
+
+#' @rdname lapplyPartitionsWithIndex
+#' @export
+setGeneric("mapPartitionsWithIndex",
+           function(X, FUN) { standardGeneric("mapPartitionsWithIndex") })
+
+#' @rdname maximum
+#' @export
+setGeneric("maximum", function(x) { standardGeneric("maximum") })
+
+#' @rdname minimum
+#' @export
+setGeneric("minimum", function(x) { standardGeneric("minimum") })
+
+#' @rdname sumRDD 
+#' @export
+setGeneric("sumRDD", function(x) { standardGeneric("sumRDD") })
+
+#' @rdname name
+#' @export
+setGeneric("name", function(x) { standardGeneric("name") })
+
+#' @rdname numPartitions
+#' @export
+setGeneric("numPartitions", function(x) { standardGeneric("numPartitions") })
+
+#' @rdname persist
+#' @export
+setGeneric("persist", function(x, newLevel) { standardGeneric("persist") })
+
+#' @rdname pipeRDD
+#' @export
+setGeneric("pipeRDD", function(x, command, env = list()) { standardGeneric("pipeRDD")})
+
+#' @rdname reduce
+#' @export
+setGeneric("reduce", function(x, func) { standardGeneric("reduce") })
+
+#' @rdname repartition
+#' @seealso coalesce
+#' @export
+setGeneric("repartition", function(x, numPartitions) { standardGeneric("repartition") })
+
+#' @rdname sampleRDD
+#' @export
+setGeneric("sampleRDD",
+           function(x, withReplacement, fraction, seed) {
+             standardGeneric("sampleRDD")
+           })
+
+#' @rdname saveAsObjectFile
+#' @seealso objectFile
+#' @export
+setGeneric("saveAsObjectFile", function(x, path) { standardGeneric("saveAsObjectFile") })
+
+#' @rdname saveAsTextFile
+#' @export
+setGeneric("saveAsTextFile", function(x, path) { standardGeneric("saveAsTextFile") })
+
+#' @rdname setName
+#' @export
+setGeneric("setName", function(x, name) { standardGeneric("setName") })
+
+#' @rdname sortBy
+#' @export
+setGeneric("sortBy",
+           function(x, func, ascending = TRUE, numPartitions = 1L) {
+             standardGeneric("sortBy")
+           })
+
+#' @rdname take
+#' @export
+setGeneric("take", function(x, num) { standardGeneric("take") })
+
+#' @rdname takeOrdered
+#' @export
+setGeneric("takeOrdered", function(x, num) { standardGeneric("takeOrdered") })
+
+#' @rdname takeSample
+#' @export
+setGeneric("takeSample",
+           function(x, withReplacement, num, seed) {
+             standardGeneric("takeSample")
+           })
+
+#' @rdname top
+#' @export
+setGeneric("top", function(x, num) { standardGeneric("top") })
+
+#' @rdname unionRDD
+#' @export
+setGeneric("unionRDD", function(x, y) { standardGeneric("unionRDD") })
+
+#' @rdname unpersist-methods
+#' @export
+setGeneric("unpersist", function(x, ...) { standardGeneric("unpersist") })
+
+#' @rdname zipRDD
+#' @export
+setGeneric("zipRDD", function(x, other) { standardGeneric("zipRDD") })
+
+#' @rdname zipWithIndex
+#' @seealso zipWithUniqueId
+#' @export
+setGeneric("zipWithIndex", function(x) { standardGeneric("zipWithIndex") })
+
+#' @rdname zipWithUniqueId
+#' @seealso zipWithIndex
+#' @export
+setGeneric("zipWithUniqueId", function(x) { standardGeneric("zipWithUniqueId") })
+
+
+############ Binary Functions #############
+
+#' @rdname countByKey
+#' @export
+setGeneric("countByKey", function(x) { standardGeneric("countByKey") })
+
+#' @rdname flatMapValues
+#' @export
+setGeneric("flatMapValues", function(X, FUN) { standardGeneric("flatMapValues") })
+
+#' @rdname keys
+#' @export
+setGeneric("keys", function(x) { standardGeneric("keys") })
+
+#' @rdname lookup
+#' @export
+setGeneric("lookup", function(x, key) { standardGeneric("lookup") })
+
+#' @rdname mapValues
+#' @export
+setGeneric("mapValues", function(X, FUN) { standardGeneric("mapValues") })
+
+#' @rdname values
+#' @export
+setGeneric("values", function(x) { standardGeneric("values") })
+
+
+
+############ Shuffle Functions ############
+
+#' @rdname aggregateByKey
+#' @seealso foldByKey, combineByKey
+#' @export
+setGeneric("aggregateByKey",
+           function(x, zeroValue, seqOp, combOp, numPartitions) {
+             standardGeneric("aggregateByKey")
+           })
+
+#' @rdname cogroup
+#' @export
+setGeneric("cogroup",
+           function(..., numPartitions) {
+             standardGeneric("cogroup")
+           },
+           signature = "...")
+
+#' @rdname combineByKey
+#' @seealso groupByKey, reduceByKey
+#' @export
+setGeneric("combineByKey",
+           function(x, createCombiner, mergeValue, mergeCombiners, numPartitions) {
+             standardGeneric("combineByKey")
+           })
+
+#' @rdname foldByKey
+#' @seealso aggregateByKey, combineByKey
+#' @export
+setGeneric("foldByKey",
+           function(x, zeroValue, func, numPartitions) {
+             standardGeneric("foldByKey")
+           })
+
+#' @rdname join-methods
+#' @export
+setGeneric("fullOuterJoin", function(x, y, numPartitions) { standardGeneric("fullOuterJoin") })
+
+#' @rdname groupByKey
+#' @seealso reduceByKey
+#' @export
+setGeneric("groupByKey", function(x, numPartitions) { standardGeneric("groupByKey") })
+
+#' @rdname join-methods
+#' @export
+setGeneric("join", function(x, y, ...) { standardGeneric("join") })
+
+#' @rdname join-methods
+#' @export
+setGeneric("leftOuterJoin", function(x, y, numPartitions) { standardGeneric("leftOuterJoin") })
+
+#' @rdname partitionBy
+#' @export
+setGeneric("partitionBy", function(x, numPartitions, ...) { standardGeneric("partitionBy") })
+
+#' @rdname reduceByKey
+#' @seealso groupByKey
+#' @export
+setGeneric("reduceByKey", function(x, combineFunc, numPartitions) { standardGeneric("reduceByKey")})
+
+#' @rdname reduceByKeyLocally
+#' @seealso reduceByKey
+#' @export
+setGeneric("reduceByKeyLocally",
+           function(x, combineFunc) {
+             standardGeneric("reduceByKeyLocally")
+           })
+
+#' @rdname join-methods
+#' @export
+setGeneric("rightOuterJoin", function(x, y, numPartitions) { standardGeneric("rightOuterJoin") })
+
+#' @rdname sortByKey
+#' @export
+setGeneric("sortByKey", function(x, ascending = TRUE, numPartitions = 1L) {
+  standardGeneric("sortByKey")
+})
+
+
+################### Broadcast Variable Methods #################
+
+#' @rdname broadcast
+#' @export
+setGeneric("value", function(bcast) { standardGeneric("value") })
+
+
+
+####################  DataFrame Methods ########################
+
+#' @rdname schema
+#' @export
+setGeneric("columns", function(x) {standardGeneric("columns") })
+
+#' @rdname schema
+#' @export
+setGeneric("dtypes", function(x) { standardGeneric("dtypes") })
+
+#' @rdname explain
+#' @export
+setGeneric("explain", function(x, ...) { standardGeneric("explain") })
+
+#' @rdname filter
+#' @export
+setGeneric("filter", function(x, condition) { standardGeneric("filter") })
+
+#' @rdname DataFrame
+#' @export
+setGeneric("groupBy", function(x, ...) { standardGeneric("groupBy") })
+
+#' @rdname insertInto
+#' @export
+setGeneric("insertInto", function(x, tableName, ...) { standardGeneric("insertInto") })
+
+#' @rdname intersect
+#' @export
+setGeneric("intersect", function(x, y) { standardGeneric("intersect") })
+
+#' @rdname isLocal
+#' @export
+setGeneric("isLocal", function(x) { standardGeneric("isLocal") })
+
+#' @rdname limit
+#' @export
+setGeneric("limit", function(x, num) {standardGeneric("limit") })
+
+#' @rdname sortDF
+#' @export
+setGeneric("orderBy", function(x, col) { standardGeneric("orderBy") })
+
+#' @rdname schema
+#' @export
+setGeneric("printSchema", function(x) { standardGeneric("printSchema") })
+
+#' @rdname registerTempTable
+#' @export
+setGeneric("registerTempTable", function(x, tableName) { standardGeneric("registerTempTable") })
+
+#' @rdname sampleDF
+#' @export
+setGeneric("sampleDF",
+           function(x, withReplacement, fraction, seed) {
+             standardGeneric("sampleDF")
+          })
+
+#' @rdname saveAsParquetFile
+#' @export
+setGeneric("saveAsParquetFile", function(x, path) { standardGeneric("saveAsParquetFile") })
+
+#' @rdname saveAsTable
+#' @export
+setGeneric("saveAsTable", function(df, tableName, source, mode, ...) {
+  standardGeneric("saveAsTable")
+})
+
+#' @rdname saveAsTable
+#' @export
+setGeneric("saveDF", function(df, path, source, mode, ...) { standardGeneric("saveDF") })
+
+#' @rdname schema
+#' @export
+setGeneric("schema", function(x) { standardGeneric("schema") })
+
+#' @rdname select
+#' @export
+setGeneric("select", function(x, col, ...) { standardGeneric("select") } )
+
+#' @rdname select
+#' @export
+setGeneric("selectExpr", function(x, expr, ...) { standardGeneric("selectExpr") })
+
+#' @rdname showDF
+#' @export
+setGeneric("showDF", function(x,...) { standardGeneric("showDF") })
+
+#' @rdname sortDF
+#' @export
+setGeneric("sortDF", function(x, col, ...) { standardGeneric("sortDF") })
+
+#' @rdname subtract
+#' @export
+setGeneric("subtract", function(x, y) { standardGeneric("subtract") })
+
+#' @rdname tojson
+#' @export
+setGeneric("toJSON", function(x) { standardGeneric("toJSON") })
+
+#' @rdname DataFrame
+#' @export
+setGeneric("toRDD", function(x) { standardGeneric("toRDD") })
+
+#' @rdname unionAll
+#' @export
+setGeneric("unionAll", function(x, y) { standardGeneric("unionAll") })
+
+#' @rdname filter
+#' @export
+setGeneric("where", function(x, condition) { standardGeneric("where") })
+
+#' @rdname withColumn
+#' @export
+setGeneric("withColumn", function(x, colName, col) { standardGeneric("withColumn") })
+
+#' @rdname withColumnRenamed
+#' @export
+setGeneric("withColumnRenamed", function(x, existingCol, newCol) {
+  standardGeneric("withColumnRenamed") })
+
+
+###################### Column Methods ##########################
+
+#' @rdname column
+#' @export
+setGeneric("approxCountDistinct", function(x, ...) { standardGeneric("approxCountDistinct") })
+
+#' @rdname column
+#' @export
+setGeneric("asc", function(x) { standardGeneric("asc") })
+
+#' @rdname column
+#' @export
+setGeneric("avg", function(x, ...) { standardGeneric("avg") })
+
+#' @rdname column
+#' @export
+setGeneric("cast", function(x, dataType) { standardGeneric("cast") })
+
+#' @rdname column
+#' @export
+setGeneric("contains", function(x, ...) { standardGeneric("contains") })
+#' @rdname column
+#' @export
+setGeneric("countDistinct", function(x, ...) { standardGeneric("countDistinct") })
+
+#' @rdname column
+#' @export
+setGeneric("desc", function(x) { standardGeneric("desc") })
+
+#' @rdname column
+#' @export
+setGeneric("endsWith", function(x, ...) { standardGeneric("endsWith") })
+
+#' @rdname column
+#' @export
+setGeneric("getField", function(x, ...) { standardGeneric("getField") })
+
+#' @rdname column
+#' @export
+setGeneric("getItem", function(x, ...) { standardGeneric("getItem") })
+
+#' @rdname column
+#' @export
+setGeneric("isNull", function(x) { standardGeneric("isNull") })
+
+#' @rdname column
+#' @export
+setGeneric("isNotNull", function(x) { standardGeneric("isNotNull") })
+
+#' @rdname column
+#' @export
+setGeneric("last", function(x) { standardGeneric("last") })
+
+#' @rdname column
+#' @export
+setGeneric("like", function(x, ...) { standardGeneric("like") })
+
+#' @rdname column
+#' @export
+setGeneric("lower", function(x) { standardGeneric("lower") })
+
+#' @rdname column
+#' @export
+setGeneric("rlike", function(x, ...) { standardGeneric("rlike") })
+
+#' @rdname column
+#' @export
+setGeneric("startsWith", function(x, ...) { standardGeneric("startsWith") })
+
+#' @rdname column
+#' @export
+setGeneric("sumDistinct", function(x) { standardGeneric("sumDistinct") })
+
+#' @rdname column
+#' @export
+setGeneric("upper", function(x) { standardGeneric("upper") })
+
diff --git a/R/pkg/R/group.R b/R/pkg/R/group.R
new file mode 100644
index 0000000000000..09fc0a7abe48a
--- /dev/null
+++ b/R/pkg/R/group.R
@@ -0,0 +1,132 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# group.R - GroupedData class and methods implemented in S4 OO classes
+
+setOldClass("jobj")
+
+#' @title S4 class that represents a GroupedData
+#' @description GroupedDatas can be created using groupBy() on a DataFrame
+#' @rdname GroupedData
+#' @seealso groupBy
+#'
+#' @param sgd A Java object reference to the backing Scala GroupedData
+#' @export
+setClass("GroupedData",
+         slots = list(sgd = "jobj"))
+
+setMethod("initialize", "GroupedData", function(.Object, sgd) {
+  .Object@sgd <- sgd
+  .Object
+})
+
+#' @rdname DataFrame
+groupedData <- function(sgd) {
+  new("GroupedData", sgd)
+}
+
+
+#' @rdname show
+setMethod("show", "GroupedData",
+          function(object) {
+            cat("GroupedData\n")
+          })
+
+#' Count
+#'
+#' Count the number of rows for each group.
+#' The resulting DataFrame will also contain the grouping columns.
+#'
+#' @param x a GroupedData
+#' @return a DataFrame
+#' @export
+#' @examples
+#' \dontrun{
+#'   count(groupBy(df, "name"))
+#' }
+setMethod("count",
+          signature(x = "GroupedData"),
+          function(x) {
+            dataFrame(callJMethod(x@sgd, "count"))
+          })
+
+#' Agg
+#'
+#' Aggregates on the entire DataFrame without groups.
+#' The resulting DataFrame will also contain the grouping columns.
+#'
+#' df2 <- agg(df, <column> = <aggFunction>)
+#' df2 <- agg(df, newColName = aggFunction(column))
+#'
+#' @param x a GroupedData
+#' @return a DataFrame
+#' @rdname agg
+#' @examples
+#' \dontrun{
+#'  df2 <- agg(df, age = "sum")  # new column name will be created as 'SUM(age#0)'
+#'  df2 <- agg(df, ageSum = sum(df$age)) # Creates a new column named ageSum
+#' }
+setGeneric("agg", function (x, ...) { standardGeneric("agg") })
+
+setMethod("agg",
+          signature(x = "GroupedData"),
+          function(x, ...) {
+            cols = list(...)
+            stopifnot(length(cols) > 0)
+            if (is.character(cols[[1]])) {
+              cols <- varargsToEnv(...)
+              sdf <- callJMethod(x@sgd, "agg", cols)
+            } else if (class(cols[[1]]) == "Column") {
+              ns <- names(cols)
+              if (!is.null(ns)) {
+                for (n in ns) {
+                  if (n != "") {
+                    cols[[n]] = alias(cols[[n]], n)
+                  }
+                }
+              }
+              jcols <- lapply(cols, function(c) { c@jc })
+              # the GroupedData.agg(col, cols*) API does not contain grouping Column
+              sdf <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "aggWithGrouping",
+                                 x@sgd, listToSeq(jcols))
+            } else {
+              stop("agg can only support Column or character")
+            }
+            dataFrame(sdf)
+          })
+
+
+# sum/mean/avg/min/max
+methods <- c("sum", "mean", "avg", "min", "max")
+
+createMethod <- function(name) {
+  setMethod(name,
+            signature(x = "GroupedData"),
+            function(x, ...) {
+              sdf <- callJMethod(x@sgd, name, toSeq(...))
+              dataFrame(sdf)
+            })
+}
+
+createMethods <- function() {
+  for (name in methods) {
+    createMethod(name)
+  }
+}
+
+createMethods()
+
diff --git a/R/pkg/R/jobj.R b/R/pkg/R/jobj.R
new file mode 100644
index 0000000000000..4180f146b7fbc
--- /dev/null
+++ b/R/pkg/R/jobj.R
@@ -0,0 +1,101 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# References to objects that exist on the JVM backend
+# are maintained using the jobj. 
+
+# Maintain a reference count of Java object references
+# This allows us to GC the java object when it is safe
+.validJobjs <- new.env(parent = emptyenv())
+
+# List of object ids to be removed
+.toRemoveJobjs <- new.env(parent = emptyenv())
+
+# Check if jobj was created with the current SparkContext
+isValidJobj <- function(jobj) {
+  if (exists(".scStartTime", envir = .sparkREnv)) {
+    jobj$appId == get(".scStartTime", envir = .sparkREnv)
+  } else {
+    FALSE
+  }
+}
+
+getJobj <- function(objId) {
+  newObj <- jobj(objId)
+  if (exists(objId, .validJobjs)) {
+    .validJobjs[[objId]] <- .validJobjs[[objId]] + 1
+  } else {
+    .validJobjs[[objId]] <- 1
+  }
+  newObj
+}
+
+# Handler for a java object that exists on the backend.
+jobj <- function(objId) {
+  if (!is.character(objId)) {
+    stop("object id must be a character")
+  }
+  # NOTE: We need a new env for a jobj as we can only register
+  # finalizers for environments or external references pointers.
+  obj <- structure(new.env(parent = emptyenv()), class = "jobj")
+  obj$id <- objId
+  obj$appId <- get(".scStartTime", envir = .sparkREnv)
+
+  # Register a finalizer to remove the Java object when this reference
+  # is garbage collected in R
+  reg.finalizer(obj, cleanup.jobj)
+  obj
+}
+
+#' Print a JVM object reference.
+#'
+#' This function prints the type and id for an object stored
+#' in the SparkR JVM backend.
+#'
+#' @param x The JVM object reference
+#' @param ... further arguments passed to or from other methods
+print.jobj <- function(x, ...) {
+  cls <- callJMethod(x, "getClass")
+  name <- callJMethod(cls, "getName")
+  cat("Java ref type", name, "id", x$id, "\n", sep = " ")
+}
+
+cleanup.jobj <- function(jobj) {
+  if (isValidJobj(jobj)) {
+    objId <- jobj$id
+    # If we don't know anything about this jobj, ignore it
+    if (exists(objId, envir = .validJobjs)) {
+      .validJobjs[[objId]] <- .validJobjs[[objId]] - 1
+
+      if (.validJobjs[[objId]] == 0) {
+        rm(list = objId, envir = .validJobjs)
+        # NOTE: We cannot call removeJObject here as the finalizer may be run
+        # in the middle of another RPC. Thus we queue up this object Id to be removed
+        # and then run all the removeJObject when the next RPC is called.
+        .toRemoveJobjs[[objId]] <- 1
+      }
+    }
+  }
+}
+
+clearJobjs <- function() {
+  valid <- ls(.validJobjs)
+  rm(list = valid, envir = .validJobjs)
+
+  removeList <- ls(.toRemoveJobjs)
+  rm(list = removeList, envir = .toRemoveJobjs)
+}
diff --git a/R/pkg/R/pairRDD.R b/R/pkg/R/pairRDD.R
new file mode 100644
index 0000000000000..c2396c32a7548
--- /dev/null
+++ b/R/pkg/R/pairRDD.R
@@ -0,0 +1,789 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Operations supported on RDDs contains pairs (i.e key, value)
+
+############ Actions and Transformations ############
+
+#' Look up elements of a key in an RDD
+#'
+#' @description
+#' \code{lookup} returns a list of values in this RDD for key key.
+#'
+#' @param x The RDD to collect
+#' @param key The key to look up for
+#' @return a list of values in this RDD for key key
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' pairs <- list(c(1, 1), c(2, 2), c(1, 3))
+#' rdd <- parallelize(sc, pairs)
+#' lookup(rdd, 1) # list(1, 3)
+#'}
+#' @rdname lookup
+#' @aliases lookup,RDD-method
+setMethod("lookup",
+          signature(x = "RDD", key = "ANY"),
+          function(x, key) {
+            partitionFunc <- function(part) {
+              filtered <- part[unlist(lapply(part, function(i) { identical(key, i[[1]]) }))]
+              lapply(filtered, function(i) { i[[2]] })
+            }
+            valsRDD <- lapplyPartition(x, partitionFunc)
+            collect(valsRDD)
+          })
+
+#' Count the number of elements for each key, and return the result to the
+#' master as lists of (key, count) pairs.
+#'
+#' Same as countByKey in Spark.
+#'
+#' @param x The RDD to count keys.
+#' @return list of (key, count) pairs, where count is number of each key in rdd.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(c("a", 1), c("b", 1), c("a", 1)))
+#' countByKey(rdd) # ("a", 2L), ("b", 1L)
+#'}
+#' @rdname countByKey
+#' @aliases countByKey,RDD-method
+setMethod("countByKey",
+          signature(x = "RDD"),
+          function(x) {
+            keys <- lapply(x, function(item) { item[[1]] })
+            countByValue(keys)
+          })
+
+#' Return an RDD with the keys of each tuple.
+#'
+#' @param x The RDD from which the keys of each tuple is returned.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(list(1, 2), list(3, 4)))
+#' collect(keys(rdd)) # list(1, 3)
+#'}
+#' @rdname keys
+#' @aliases keys,RDD
+setMethod("keys",
+          signature(x = "RDD"),
+          function(x) {
+            func <- function(k) {
+              k[[1]]
+            }
+            lapply(x, func)
+          })
+
+#' Return an RDD with the values of each tuple.
+#'
+#' @param x The RDD from which the values of each tuple is returned.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(list(1, 2), list(3, 4)))
+#' collect(values(rdd)) # list(2, 4)
+#'}
+#' @rdname values
+#' @aliases values,RDD
+setMethod("values",
+          signature(x = "RDD"),
+          function(x) {
+            func <- function(v) {
+              v[[2]]
+            }
+            lapply(x, func)
+          })
+
+#' Applies a function to all values of the elements, without modifying the keys.
+#'
+#' The same as `mapValues()' in Spark.
+#'
+#' @param X The RDD to apply the transformation.
+#' @param FUN the transformation to apply on the value of each element.
+#' @return a new RDD created by the transformation.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:10)
+#' makePairs <- lapply(rdd, function(x) { list(x, x) })
+#' collect(mapValues(makePairs, function(x) { x * 2) })
+#' Output: list(list(1,2), list(2,4), list(3,6), ...)
+#'}
+#' @rdname mapValues
+#' @aliases mapValues,RDD,function-method
+setMethod("mapValues",
+          signature(X = "RDD", FUN = "function"),
+          function(X, FUN) {
+            func <- function(x) {
+              list(x[[1]], FUN(x[[2]]))
+            }
+            lapply(X, func)
+          })
+
+#' Pass each value in the key-value pair RDD through a flatMap function without
+#' changing the keys; this also retains the original RDD's partitioning.
+#'
+#' The same as 'flatMapValues()' in Spark.
+#'
+#' @param X The RDD to apply the transformation.
+#' @param FUN the transformation to apply on the value of each element.
+#' @return a new RDD created by the transformation.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(list(1, c(1,2)), list(2, c(3,4))))
+#' collect(flatMapValues(rdd, function(x) { x }))
+#' Output: list(list(1,1), list(1,2), list(2,3), list(2,4))
+#'}
+#' @rdname flatMapValues
+#' @aliases flatMapValues,RDD,function-method
+setMethod("flatMapValues",
+          signature(X = "RDD", FUN = "function"),
+          function(X, FUN) {
+            flatMapFunc <- function(x) {
+              lapply(FUN(x[[2]]), function(v) { list(x[[1]], v) })
+            }
+            flatMap(X, flatMapFunc)
+          })
+
+############ Shuffle Functions ############
+
+#' Partition an RDD by key
+#'
+#' This function operates on RDDs where every element is of the form list(K, V) or c(K, V).
+#' For each element of this RDD, the partitioner is used to compute a hash
+#' function and the RDD is partitioned using this hash value.
+#'
+#' @param x The RDD to partition. Should be an RDD where each element is
+#'             list(K, V) or c(K, V).
+#' @param numPartitions Number of partitions to create.
+#' @param ... Other optional arguments to partitionBy.
+#'
+#' @param partitionFunc The partition function to use. Uses a default hashCode
+#'                      function if not provided
+#' @return An RDD partitioned using the specified partitioner.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' pairs <- list(list(1, 2), list(1.1, 3), list(1, 4))
+#' rdd <- parallelize(sc, pairs)
+#' parts <- partitionBy(rdd, 2L)
+#' collectPartition(parts, 0L) # First partition should contain list(1, 2) and list(1, 4)
+#'}
+#' @rdname partitionBy
+#' @aliases partitionBy,RDD,integer-method
+setMethod("partitionBy",
+          signature(x = "RDD", numPartitions = "integer"),
+          function(x, numPartitions, partitionFunc = hashCode) {
+
+            #if (missing(partitionFunc)) {
+            #  partitionFunc <- hashCode
+            #}
+
+            partitionFunc <- cleanClosure(partitionFunc)
+            serializedHashFuncBytes <- serialize(partitionFunc, connection = NULL)
+
+            packageNamesArr <- serialize(.sparkREnv$.packages,
+                                         connection = NULL)
+            broadcastArr <- lapply(ls(.broadcastNames), function(name) {
+                                   get(name, .broadcastNames) })
+            jrdd <- getJRDD(x)
+
+            # We create a PairwiseRRDD that extends RDD[(Array[Byte],
+            # Array[Byte])], where the key is the hashed split, the value is
+            # the content (key-val pairs).
+            pairwiseRRDD <- newJObject("org.apache.spark.api.r.PairwiseRRDD",
+                                       callJMethod(jrdd, "rdd"),
+                                       as.integer(numPartitions),
+                                       serializedHashFuncBytes,
+                                       getSerializedMode(x),
+                                       packageNamesArr,
+                                       as.character(.sparkREnv$libname),
+                                       broadcastArr,
+                                       callJMethod(jrdd, "classTag"))
+
+            # Create a corresponding partitioner.
+            rPartitioner <- newJObject("org.apache.spark.HashPartitioner",
+                                       as.integer(numPartitions))
+
+            # Call partitionBy on the obtained PairwiseRDD.
+            javaPairRDD <- callJMethod(pairwiseRRDD, "asJavaPairRDD")
+            javaPairRDD <- callJMethod(javaPairRDD, "partitionBy", rPartitioner)
+
+            # Call .values() on the result to get back the final result, the
+            # shuffled acutal content key-val pairs.
+            r <- callJMethod(javaPairRDD, "values")
+
+            RDD(r, serializedMode = "byte")
+          })
+
+#' Group values by key
+#'
+#' This function operates on RDDs where every element is of the form list(K, V) or c(K, V).
+#' and group values for each key in the RDD into a single sequence.
+#'
+#' @param x The RDD to group. Should be an RDD where each element is
+#'             list(K, V) or c(K, V).
+#' @param numPartitions Number of partitions to create.
+#' @return An RDD where each element is list(K, list(V))
+#' @seealso reduceByKey
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' pairs <- list(list(1, 2), list(1.1, 3), list(1, 4))
+#' rdd <- parallelize(sc, pairs)
+#' parts <- groupByKey(rdd, 2L)
+#' grouped <- collect(parts)
+#' grouped[[1]] # Should be a list(1, list(2, 4))
+#'}
+#' @rdname groupByKey
+#' @aliases groupByKey,RDD,integer-method
+setMethod("groupByKey",
+          signature(x = "RDD", numPartitions = "integer"),
+          function(x, numPartitions) {
+            shuffled <- partitionBy(x, numPartitions)
+            groupVals <- function(part) {
+              vals <- new.env()
+              keys <- new.env()
+              pred <- function(item) exists(item$hash, keys)
+              appendList <- function(acc, i) {
+                addItemToAccumulator(acc, i)
+                acc
+              }
+              makeList <- function(i) {
+                acc <- initAccumulator()
+                addItemToAccumulator(acc, i)
+                acc
+              }
+              # Each item in the partition is list of (K, V)
+              lapply(part,
+                     function(item) {
+                       item$hash <- as.character(hashCode(item[[1]]))
+                       updateOrCreatePair(item, keys, vals, pred,
+                                          appendList, makeList)
+                     })
+              # extract out data field
+              vals <- eapply(vals,
+                             function(i) {
+                               length(i$data) <- i$counter
+                               i$data
+                             })
+              # Every key in the environment contains a list
+              # Convert that to list(K, Seq[V])
+              convertEnvsToList(keys, vals)
+            }
+            lapplyPartition(shuffled, groupVals)
+          })
+
+#' Merge values by key
+#'
+#' This function operates on RDDs where every element is of the form list(K, V) or c(K, V).
+#' and merges the values for each key using an associative reduce function.
+#'
+#' @param x The RDD to reduce by key. Should be an RDD where each element is
+#'             list(K, V) or c(K, V).
+#' @param combineFunc The associative reduce function to use.
+#' @param numPartitions Number of partitions to create.
+#' @return An RDD where each element is list(K, V') where V' is the merged
+#'         value
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' pairs <- list(list(1, 2), list(1.1, 3), list(1, 4))
+#' rdd <- parallelize(sc, pairs)
+#' parts <- reduceByKey(rdd, "+", 2L)
+#' reduced <- collect(parts)
+#' reduced[[1]] # Should be a list(1, 6)
+#'}
+#' @rdname reduceByKey
+#' @aliases reduceByKey,RDD,integer-method
+setMethod("reduceByKey",
+          signature(x = "RDD", combineFunc = "ANY", numPartitions = "integer"),
+          function(x, combineFunc, numPartitions) {
+            reduceVals <- function(part) {
+              vals <- new.env()
+              keys <- new.env()
+              pred <- function(item) exists(item$hash, keys)
+              lapply(part,
+                     function(item) {
+                       item$hash <- as.character(hashCode(item[[1]]))
+                       updateOrCreatePair(item, keys, vals, pred, combineFunc, identity)
+                     })
+              convertEnvsToList(keys, vals)
+            }
+            locallyReduced <- lapplyPartition(x, reduceVals)
+            shuffled <- partitionBy(locallyReduced, numPartitions)
+            lapplyPartition(shuffled, reduceVals)
+          })
+
+#' Merge values by key locally
+#'
+#' This function operates on RDDs where every element is of the form list(K, V) or c(K, V).
+#' and merges the values for each key using an associative reduce function, but return the
+#' results immediately to the driver as an R list.
+#'
+#' @param x The RDD to reduce by key. Should be an RDD where each element is
+#'             list(K, V) or c(K, V).
+#' @param combineFunc The associative reduce function to use.
+#' @return A list of elements of type list(K, V') where V' is the merged value for each key
+#' @seealso reduceByKey
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' pairs <- list(list(1, 2), list(1.1, 3), list(1, 4))
+#' rdd <- parallelize(sc, pairs)
+#' reduced <- reduceByKeyLocally(rdd, "+")
+#' reduced # list(list(1, 6), list(1.1, 3))
+#'}
+#' @rdname reduceByKeyLocally
+#' @aliases reduceByKeyLocally,RDD,integer-method
+setMethod("reduceByKeyLocally",
+          signature(x = "RDD", combineFunc = "ANY"),
+          function(x, combineFunc) {
+            reducePart <- function(part) {
+              vals <- new.env()
+              keys <- new.env()
+              pred <- function(item) exists(item$hash, keys)
+              lapply(part,
+                     function(item) {
+                       item$hash <- as.character(hashCode(item[[1]]))
+                       updateOrCreatePair(item, keys, vals, pred, combineFunc, identity)
+                     })
+              list(list(keys, vals)) # return hash to avoid re-compute in merge
+            }
+            mergeParts <- function(accum, x) {
+              pred <- function(item) {
+                exists(item$hash, accum[[1]])
+              }
+              lapply(ls(x[[1]]),
+                     function(name) {
+                       item <- list(x[[1]][[name]], x[[2]][[name]])
+                       item$hash <- name
+                       updateOrCreatePair(item, accum[[1]], accum[[2]], pred, combineFunc, identity)
+                     })
+              accum
+            }
+            reduced <- mapPartitions(x, reducePart)
+            merged <- reduce(reduced, mergeParts)
+            convertEnvsToList(merged[[1]], merged[[2]])
+          })
+
+#' Combine values by key
+#'
+#' Generic function to combine the elements for each key using a custom set of
+#' aggregation functions. Turns an RDD[(K, V)] into a result of type RDD[(K, C)],
+#' for a "combined type" C. Note that V and C can be different -- for example, one
+#' might group an RDD of type (Int, Int) into an RDD of type (Int, Seq[Int]).
+
+#' Users provide three functions:
+#' \itemize{
+#'   \item createCombiner, which turns a V into a C (e.g., creates a one-element list)
+#'   \item mergeValue, to merge a V into a C (e.g., adds it to the end of a list) -
+#'   \item mergeCombiners, to combine two C's into a single one (e.g., concatentates
+#'    two lists).
+#' }
+#'
+#' @param x The RDD to combine. Should be an RDD where each element is
+#'             list(K, V) or c(K, V).
+#' @param createCombiner Create a combiner (C) given a value (V)
+#' @param mergeValue Merge the given value (V) with an existing combiner (C)
+#' @param mergeCombiners Merge two combiners and return a new combiner
+#' @param numPartitions Number of partitions to create.
+#' @return An RDD where each element is list(K, C) where C is the combined type
+#'
+#' @seealso groupByKey, reduceByKey
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' pairs <- list(list(1, 2), list(1.1, 3), list(1, 4))
+#' rdd <- parallelize(sc, pairs)
+#' parts <- combineByKey(rdd, function(x) { x }, "+", "+", 2L)
+#' combined <- collect(parts)
+#' combined[[1]] # Should be a list(1, 6)
+#'}
+#' @rdname combineByKey
+#' @aliases combineByKey,RDD,ANY,ANY,ANY,integer-method
+setMethod("combineByKey",
+          signature(x = "RDD", createCombiner = "ANY", mergeValue = "ANY",
+                    mergeCombiners = "ANY", numPartitions = "integer"),
+          function(x, createCombiner, mergeValue, mergeCombiners, numPartitions) {
+            combineLocally <- function(part) {
+              combiners <- new.env()
+              keys <- new.env()
+              pred <- function(item) exists(item$hash, keys)
+              lapply(part,
+                     function(item) {
+                       item$hash <- as.character(item[[1]])
+                       updateOrCreatePair(item, keys, combiners, pred, mergeValue, createCombiner)
+                     })
+              convertEnvsToList(keys, combiners)
+            }
+            locallyCombined <- lapplyPartition(x, combineLocally)
+            shuffled <- partitionBy(locallyCombined, numPartitions)
+            mergeAfterShuffle <- function(part) {
+              combiners <- new.env()
+              keys <- new.env()
+              pred <- function(item) exists(item$hash, keys)
+              lapply(part,
+                     function(item) {
+                       item$hash <- as.character(item[[1]])
+                       updateOrCreatePair(item, keys, combiners, pred, mergeCombiners, identity)
+                     })
+              convertEnvsToList(keys, combiners)
+            }
+            lapplyPartition(shuffled, mergeAfterShuffle)
+          })
+
+#' Aggregate a pair RDD by each key.
+#' 
+#' Aggregate the values of each key in an RDD, using given combine functions
+#' and a neutral "zero value". This function can return a different result type,
+#' U, than the type of the values in this RDD, V. Thus, we need one operation
+#' for merging a V into a U and one operation for merging two U's, The former 
+#' operation is used for merging values within a partition, and the latter is 
+#' used for merging values between partitions. To avoid memory allocation, both 
+#' of these functions are allowed to modify and return their first argument 
+#' instead of creating a new U.
+#' 
+#' @param x An RDD.
+#' @param zeroValue A neutral "zero value".
+#' @param seqOp A function to aggregate the values of each key. It may return 
+#'              a different result type from the type of the values.
+#' @param combOp A function to aggregate results of seqOp.
+#' @return An RDD containing the aggregation result.
+#' @seealso foldByKey, combineByKey
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(list(1, 1), list(1, 2), list(2, 3), list(2, 4)))
+#' zeroValue <- list(0, 0)
+#' seqOp <- function(x, y) { list(x[[1]] + y, x[[2]] + 1) }
+#' combOp <- function(x, y) { list(x[[1]] + y[[1]], x[[2]] + y[[2]]) }
+#' aggregateByKey(rdd, zeroValue, seqOp, combOp, 2L) 
+#'   # list(list(1, list(3, 2)), list(2, list(7, 2)))
+#'}
+#' @rdname aggregateByKey
+#' @aliases aggregateByKey,RDD,ANY,ANY,ANY,integer-method
+setMethod("aggregateByKey",
+          signature(x = "RDD", zeroValue = "ANY", seqOp = "ANY",
+                    combOp = "ANY", numPartitions = "integer"),
+          function(x, zeroValue, seqOp, combOp, numPartitions) {
+            createCombiner <- function(v) {
+              do.call(seqOp, list(zeroValue, v))
+            }
+
+            combineByKey(x, createCombiner, seqOp, combOp, numPartitions)
+          })
+
+#' Fold a pair RDD by each key.
+#' 
+#' Aggregate the values of each key in an RDD, using an associative function "func"
+#' and a neutral "zero value" which may be added to the result an arbitrary 
+#' number of times, and must not change the result (e.g., 0 for addition, or 
+#' 1 for multiplication.).
+#' 
+#' @param x An RDD.
+#' @param zeroValue A neutral "zero value".
+#' @param func An associative function for folding values of each key.
+#' @return An RDD containing the aggregation result.
+#' @seealso aggregateByKey, combineByKey
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(list(1, 1), list(1, 2), list(2, 3), list(2, 4)))
+#' foldByKey(rdd, 0, "+", 2L) # list(list(1, 3), list(2, 7))
+#'}
+#' @rdname foldByKey
+#' @aliases foldByKey,RDD,ANY,ANY,integer-method
+setMethod("foldByKey",
+          signature(x = "RDD", zeroValue = "ANY",
+                    func = "ANY", numPartitions = "integer"),
+          function(x, zeroValue, func, numPartitions) {
+            aggregateByKey(x, zeroValue, func, func, numPartitions)
+          })
+
+############ Binary Functions #############
+
+#' Join two RDDs
+#'
+#' @description
+#' \code{join} This function joins two RDDs where every element is of the form list(K, V).
+#' The key types of the two RDDs should be the same.
+#'
+#' @param x An RDD to be joined. Should be an RDD where each element is
+#'             list(K, V).
+#' @param y An RDD to be joined. Should be an RDD where each element is
+#'             list(K, V).
+#' @param numPartitions Number of partitions to create.
+#' @return a new RDD containing all pairs of elements with matching keys in
+#'         two input RDDs.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd1 <- parallelize(sc, list(list(1, 1), list(2, 4)))
+#' rdd2 <- parallelize(sc, list(list(1, 2), list(1, 3)))
+#' join(rdd1, rdd2, 2L) # list(list(1, list(1, 2)), list(1, list(1, 3))
+#'}
+#' @rdname join-methods
+#' @aliases join,RDD,RDD-method
+setMethod("join",
+          signature(x = "RDD", y = "RDD"),
+          function(x, y, numPartitions) {
+            xTagged <- lapply(x, function(i) { list(i[[1]], list(1L, i[[2]])) })
+            yTagged <- lapply(y, function(i) { list(i[[1]], list(2L, i[[2]])) })
+            
+            doJoin <- function(v) {
+              joinTaggedList(v, list(FALSE, FALSE))
+            }
+            
+            joined <- flatMapValues(groupByKey(unionRDD(xTagged, yTagged), numToInt(numPartitions)),
+                                    doJoin)
+          })
+
+#' Left outer join two RDDs
+#'
+#' @description
+#' \code{leftouterjoin} This function left-outer-joins two RDDs where every element is of the form list(K, V).
+#' The key types of the two RDDs should be the same.
+#'
+#' @param x An RDD to be joined. Should be an RDD where each element is
+#'             list(K, V).
+#' @param y An RDD to be joined. Should be an RDD where each element is
+#'             list(K, V).
+#' @param numPartitions Number of partitions to create.
+#' @return For each element (k, v) in x, the resulting RDD will either contain 
+#'         all pairs (k, (v, w)) for (k, w) in rdd2, or the pair (k, (v, NULL)) 
+#'         if no elements in rdd2 have key k.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd1 <- parallelize(sc, list(list(1, 1), list(2, 4)))
+#' rdd2 <- parallelize(sc, list(list(1, 2), list(1, 3)))
+#' leftOuterJoin(rdd1, rdd2, 2L)
+#' # list(list(1, list(1, 2)), list(1, list(1, 3)), list(2, list(4, NULL)))
+#'}
+#' @rdname join-methods
+#' @aliases leftOuterJoin,RDD,RDD-method
+setMethod("leftOuterJoin",
+          signature(x = "RDD", y = "RDD", numPartitions = "integer"),
+          function(x, y, numPartitions) {
+            xTagged <- lapply(x, function(i) { list(i[[1]], list(1L, i[[2]])) })
+            yTagged <- lapply(y, function(i) { list(i[[1]], list(2L, i[[2]])) })
+            
+            doJoin <- function(v) {
+              joinTaggedList(v, list(FALSE, TRUE))
+            }
+            
+            joined <- flatMapValues(groupByKey(unionRDD(xTagged, yTagged), numPartitions), doJoin)
+          })
+
+#' Right outer join two RDDs
+#'
+#' @description
+#' \code{rightouterjoin} This function right-outer-joins two RDDs where every element is of the form list(K, V).
+#' The key types of the two RDDs should be the same.
+#'
+#' @param x An RDD to be joined. Should be an RDD where each element is
+#'             list(K, V).
+#' @param y An RDD to be joined. Should be an RDD where each element is
+#'             list(K, V).
+#' @param numPartitions Number of partitions to create.
+#' @return For each element (k, w) in y, the resulting RDD will either contain
+#'         all pairs (k, (v, w)) for (k, v) in x, or the pair (k, (NULL, w))
+#'         if no elements in x have key k.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd1 <- parallelize(sc, list(list(1, 2), list(1, 3)))
+#' rdd2 <- parallelize(sc, list(list(1, 1), list(2, 4)))
+#' rightOuterJoin(rdd1, rdd2, 2L)
+#' # list(list(1, list(2, 1)), list(1, list(3, 1)), list(2, list(NULL, 4)))
+#'}
+#' @rdname join-methods
+#' @aliases rightOuterJoin,RDD,RDD-method
+setMethod("rightOuterJoin",
+          signature(x = "RDD", y = "RDD", numPartitions = "integer"),
+          function(x, y, numPartitions) {
+            xTagged <- lapply(x, function(i) { list(i[[1]], list(1L, i[[2]])) })
+            yTagged <- lapply(y, function(i) { list(i[[1]], list(2L, i[[2]])) })
+            
+            doJoin <- function(v) {
+              joinTaggedList(v, list(TRUE, FALSE))
+            }
+            
+            joined <- flatMapValues(groupByKey(unionRDD(xTagged, yTagged), numPartitions), doJoin)
+          })
+
+#' Full outer join two RDDs
+#'
+#' @description
+#' \code{fullouterjoin} This function full-outer-joins two RDDs where every element is of the form list(K, V). 
+#' The key types of the two RDDs should be the same.
+#'
+#' @param x An RDD to be joined. Should be an RDD where each element is
+#'             list(K, V).
+#' @param y An RDD to be joined. Should be an RDD where each element is
+#'             list(K, V).
+#' @param numPartitions Number of partitions to create.
+#' @return For each element (k, v) in x and (k, w) in y, the resulting RDD
+#'         will contain all pairs (k, (v, w)) for both (k, v) in x and
+#'         (k, w) in y, or the pair (k, (NULL, w))/(k, (v, NULL)) if no elements 
+#'         in x/y have key k.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd1 <- parallelize(sc, list(list(1, 2), list(1, 3), list(3, 3)))
+#' rdd2 <- parallelize(sc, list(list(1, 1), list(2, 4)))
+#' fullOuterJoin(rdd1, rdd2, 2L) # list(list(1, list(2, 1)),
+#'                               #      list(1, list(3, 1)),
+#'                               #      list(2, list(NULL, 4)))
+#'                               #      list(3, list(3, NULL)),
+#'}
+#' @rdname join-methods
+#' @aliases fullOuterJoin,RDD,RDD-method
+setMethod("fullOuterJoin",
+          signature(x = "RDD", y = "RDD", numPartitions = "integer"),
+          function(x, y, numPartitions) {
+            xTagged <- lapply(x, function(i) { list(i[[1]], list(1L, i[[2]])) })
+            yTagged <- lapply(y, function(i) { list(i[[1]], list(2L, i[[2]])) })
+
+            doJoin <- function(v) {
+              joinTaggedList(v, list(TRUE, TRUE))
+            }
+
+            joined <- flatMapValues(groupByKey(unionRDD(xTagged, yTagged), numPartitions), doJoin)
+          })
+
+#' For each key k in several RDDs, return a resulting RDD that
+#' whose values are a list of values for the key in all RDDs.
+#'
+#' @param ... Several RDDs.
+#' @param numPartitions Number of partitions to create.
+#' @return a new RDD containing all pairs of elements with values in a list
+#' in all RDDs.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd1 <- parallelize(sc, list(list(1, 1), list(2, 4)))
+#' rdd2 <- parallelize(sc, list(list(1, 2), list(1, 3)))
+#' cogroup(rdd1, rdd2, numPartitions = 2L) 
+#' # list(list(1, list(1, list(2, 3))), list(2, list(list(4), list()))
+#'}
+#' @rdname cogroup
+#' @aliases cogroup,RDD-method
+setMethod("cogroup",
+          "RDD",
+          function(..., numPartitions) {
+            rdds <- list(...)
+            rddsLen <- length(rdds)
+            for (i in 1:rddsLen) {
+              rdds[[i]] <- lapply(rdds[[i]], 
+                                  function(x) { list(x[[1]], list(i, x[[2]])) })
+              # TODO(hao): As issue [SparkR-142] mentions, the right value of i
+              # will not be captured into UDF if getJRDD is not invoked.
+              # It should be resolved together with that issue.
+              getJRDD(rdds[[i]])  # Capture the closure.
+            }
+            union.rdd <- Reduce(unionRDD, rdds)
+            group.func <- function(vlist) {
+              res <- list()
+              length(res) <- rddsLen
+              for (x in vlist) {
+                i <- x[[1]]
+                acc <- res[[i]]
+                # Create an accumulator.
+                if (is.null(acc)) {
+                  acc <- initAccumulator()
+                }
+                addItemToAccumulator(acc, x[[2]])
+                res[[i]] <- acc
+              }
+              lapply(res, function(acc) {
+                if (is.null(acc)) {
+                  list()
+                } else {
+                  acc$data
+                }
+              })
+            }
+            cogroup.rdd <- mapValues(groupByKey(union.rdd, numPartitions), 
+                                     group.func)
+          })
+
+#' Sort a (k, v) pair RDD by k.
+#'
+#' @param x A (k, v) pair RDD to be sorted.
+#' @param ascending A flag to indicate whether the sorting is ascending or descending.
+#' @param numPartitions Number of partitions to create.
+#' @return An RDD where all (k, v) pair elements are sorted.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, list(list(3, 1), list(2, 2), list(1, 3)))
+#' collect(sortByKey(rdd)) # list (list(1, 3), list(2, 2), list(3, 1))
+#'}
+#' @rdname sortByKey
+#' @aliases sortByKey,RDD,RDD-method
+setMethod("sortByKey",
+          signature(x = "RDD"),
+          function(x, ascending = TRUE, numPartitions = SparkR::numPartitions(x)) {
+            rangeBounds <- list()
+            
+            if (numPartitions > 1) {
+              rddSize <- count(x)
+              # constant from Spark's RangePartitioner
+              maxSampleSize <- numPartitions * 20
+              fraction <- min(maxSampleSize / max(rddSize, 1), 1.0)
+              
+              samples <- collect(keys(sampleRDD(x, FALSE, fraction, 1L)))
+              
+              # Note: the built-in R sort() function only works on atomic vectors
+              samples <- sort(unlist(samples, recursive = FALSE), decreasing = !ascending)
+              
+              if (length(samples) > 0) {
+                rangeBounds <- lapply(seq_len(numPartitions - 1),
+                                      function(i) {
+                                        j <- ceiling(length(samples) * i / numPartitions)
+                                        samples[j]
+                                      })
+              }
+            }
+
+            rangePartitionFunc <- function(key) {
+              partition <- 0
+              
+              # TODO: Use binary search instead of linear search, similar with Spark
+              while (partition < length(rangeBounds) && key > rangeBounds[[partition + 1]]) {
+                partition <- partition + 1
+              }
+              
+              if (ascending) {
+                partition
+              } else {
+                numPartitions - partition - 1
+              }
+            }
+            
+            partitionFunc <- function(part) {
+              sortKeyValueList(part, decreasing = !ascending)
+            }
+            
+            newRDD <- partitionBy(x, numPartitions, rangePartitionFunc)
+            lapplyPartition(newRDD, partitionFunc)
+          })
+          
diff --git a/R/pkg/R/serialize.R b/R/pkg/R/serialize.R
new file mode 100644
index 0000000000000..8a9c0c652ce24
--- /dev/null
+++ b/R/pkg/R/serialize.R
@@ -0,0 +1,195 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Utility functions to serialize R objects so they can be read in Java.
+
+# Type mapping from R to Java
+#
+# NULL -> Void
+# integer -> Int
+# character -> String
+# logical -> Boolean
+# double, numeric -> Double
+# raw -> Array[Byte]
+# Date -> Date
+# POSIXct,POSIXlt -> Time
+#
+# list[T] -> Array[T], where T is one of above mentioned types
+# environment -> Map[String, T], where T is a native type
+# jobj -> Object, where jobj is an object created in the backend
+
+writeObject <- function(con, object, writeType = TRUE) {
+  # NOTE: In R vectors have same type as objects. So we don't support
+  # passing in vectors as arrays and instead require arrays to be passed
+  # as lists.
+  type <- class(object)[[1]]  # class of POSIXlt is c("POSIXlt", "POSIXt")
+  if (writeType) {
+    writeType(con, type)
+  }
+  switch(type,
+         NULL = writeVoid(con),
+         integer = writeInt(con, object),
+         character = writeString(con, object),
+         logical = writeBoolean(con, object),
+         double = writeDouble(con, object),
+         numeric = writeDouble(con, object),
+         raw = writeRaw(con, object),
+         list = writeList(con, object),
+         jobj = writeJobj(con, object),
+         environment = writeEnv(con, object),
+         Date = writeDate(con, object),
+         POSIXlt = writeTime(con, object),
+         POSIXct = writeTime(con, object),
+         stop(paste("Unsupported type for serialization", type)))
+}
+
+writeVoid <- function(con) {
+  # no value for NULL
+}
+
+writeJobj <- function(con, value) {
+  if (!isValidJobj(value)) {
+    stop("invalid jobj ", value$id)
+  }
+  writeString(con, value$id)
+}
+
+writeString <- function(con, value) {
+  writeInt(con, as.integer(nchar(value) + 1))
+  writeBin(value, con, endian = "big")
+}
+
+writeInt <- function(con, value) {
+  writeBin(as.integer(value), con, endian = "big")
+}
+
+writeDouble <- function(con, value) {
+  writeBin(value, con, endian = "big")
+}
+
+writeBoolean <- function(con, value) {
+  # TRUE becomes 1, FALSE becomes 0
+  writeInt(con, as.integer(value))
+}
+
+writeRawSerialize <- function(outputCon, batch) {
+  outputSer <- serialize(batch, ascii = FALSE, connection = NULL)
+  writeRaw(outputCon, outputSer)
+}
+
+writeRowSerialize <- function(outputCon, rows) {
+  invisible(lapply(rows, function(r) {
+    bytes <- serializeRow(r)
+    writeRaw(outputCon, bytes)
+  }))
+}
+
+serializeRow <- function(row) {
+  rawObj <- rawConnection(raw(0), "wb")
+  on.exit(close(rawObj))
+  writeRow(rawObj, row)
+  rawConnectionValue(rawObj)
+}
+
+writeRow <- function(con, row) {
+  numCols <- length(row)
+  writeInt(con, numCols)
+  for (i in 1:numCols) {
+    writeObject(con, row[[i]])
+  }
+}
+
+writeRaw <- function(con, batch) {
+  writeInt(con, length(batch))
+  writeBin(batch, con, endian = "big")
+}
+
+writeType <- function(con, class) {
+  type <- switch(class,
+                 NULL = "n",
+                 integer = "i",
+                 character = "c",
+                 logical = "b",
+                 double = "d",
+                 numeric = "d",
+                 raw = "r",
+                 list = "l",
+                 jobj = "j",
+                 environment = "e",
+                 Date = "D",
+                 POSIXlt = 't',
+                 POSIXct = 't',
+                 stop(paste("Unsupported type for serialization", class)))
+  writeBin(charToRaw(type), con)
+}
+
+# Used to pass arrays where all the elements are of the same type
+writeList <- function(con, arr) {
+  # All elements should be of same type
+  elemType <- unique(sapply(arr, function(elem) { class(elem) }))
+  stopifnot(length(elemType) <= 1)
+
+  # TODO: Empty lists are given type "character" right now.
+  # This may not work if the Java side expects array of any other type.
+  if (length(elemType) == 0) {
+    elemType <- class("somestring")
+  }
+
+  writeType(con, elemType)
+  writeInt(con, length(arr))
+
+  if (length(arr) > 0) {
+    for (a in arr) {
+      writeObject(con, a, FALSE)
+    }
+  }
+}
+
+# Used to pass in hash maps required on Java side.
+writeEnv <- function(con, env) {
+  len <- length(env)
+
+  writeInt(con, len)
+  if (len > 0) {
+    writeList(con, as.list(ls(env)))
+    vals <- lapply(ls(env), function(x) { env[[x]] })
+    writeList(con, as.list(vals))
+  }
+}
+
+writeDate <- function(con, date) {
+  writeString(con, as.character(date))
+}
+
+writeTime <- function(con, time) {
+  writeDouble(con, as.double(time))
+}
+
+# Used to serialize in a list of objects where each
+# object can be of a different type. Serialization format is
+# <object type> <object> for each object
+writeArgs <- function(con, args) {
+  if (length(args) > 0) {
+    for (a in args) {
+      writeObject(con, a)
+    }
+  }
+}
+
+writeStrings <- function(con, stringList) {
+  writeLines(unlist(stringList), con)
+}
diff --git a/R/pkg/R/sparkR.R b/R/pkg/R/sparkR.R
new file mode 100644
index 0000000000000..bc82df01f0fff
--- /dev/null
+++ b/R/pkg/R/sparkR.R
@@ -0,0 +1,266 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+.sparkREnv <- new.env()
+
+sparkR.onLoad <- function(libname, pkgname) {
+  .sparkREnv$libname <- libname
+}
+
+# Utility function that returns TRUE if we have an active connection to the
+# backend and FALSE otherwise
+connExists <- function(env) {
+  tryCatch({
+    exists(".sparkRCon", envir = env) && isOpen(env[[".sparkRCon"]])
+  }, error = function(err) {
+    return(FALSE)
+  })
+}
+
+#' Stop the Spark context.
+#'
+#' Also terminates the backend this R session is connected to
+sparkR.stop <- function() {
+  env <- .sparkREnv
+  if (exists(".sparkRCon", envir = env)) {
+    # cat("Stopping SparkR\n")
+    if (exists(".sparkRjsc", envir = env)) {
+      sc <- get(".sparkRjsc", envir = env)
+      callJMethod(sc, "stop")
+      rm(".sparkRjsc", envir = env)
+    }
+  
+    if (exists(".backendLaunched", envir = env)) {
+      callJStatic("SparkRHandler", "stopBackend")
+    }
+
+    # Also close the connection and remove it from our env
+    conn <- get(".sparkRCon", envir = env)
+    close(conn)
+
+    rm(".sparkRCon", envir = env)
+    rm(".scStartTime", envir = env)
+  }
+
+  if (exists(".monitorConn", envir = env)) {
+    conn <- get(".monitorConn", envir = env)
+    close(conn)
+    rm(".monitorConn", envir = env)
+  }
+
+  # Clear all broadcast variables we have
+  # as the jobj will not be valid if we restart the JVM
+  clearBroadcastVariables()
+
+  # Clear jobj maps
+  clearJobjs()
+}
+
+#' Initialize a new Spark Context.
+#'
+#' This function initializes a new SparkContext.
+#'
+#' @param master The Spark master URL.
+#' @param appName Application name to register with cluster manager
+#' @param sparkHome Spark Home directory
+#' @param sparkEnvir Named list of environment variables to set on worker nodes.
+#' @param sparkExecutorEnv Named list of environment variables to be used when launching executors.
+#' @param sparkJars Character string vector of jar files to pass to the worker nodes.
+#' @param sparkRLibDir The path where R is installed on the worker nodes.
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init("local[2]", "SparkR", "/home/spark")
+#' sc <- sparkR.init("local[2]", "SparkR", "/home/spark",
+#'                  list(spark.executor.memory="1g"))
+#' sc <- sparkR.init("yarn-client", "SparkR", "/home/spark",
+#'                  list(spark.executor.memory="1g"),
+#'                  list(LD_LIBRARY_PATH="/directory of JVM libraries (libjvm.so) on workers/"),
+#'                  c("jarfile1.jar","jarfile2.jar"))
+#'}
+
+sparkR.init <- function(
+  master = "",
+  appName = "SparkR",
+  sparkHome = Sys.getenv("SPARK_HOME"),
+  sparkEnvir = list(),
+  sparkExecutorEnv = list(),
+  sparkJars = "",
+  sparkRLibDir = "") {
+
+  if (exists(".sparkRjsc", envir = .sparkREnv)) {
+    cat("Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context\n")
+    return(get(".sparkRjsc", envir = .sparkREnv))
+  }
+
+  sparkMem <- Sys.getenv("SPARK_MEM", "512m")
+  jars <- suppressWarnings(normalizePath(as.character(sparkJars)))
+
+  # Classpath separator is ";" on Windows
+  # URI needs four /// as from http://stackoverflow.com/a/18522792
+  if (.Platform$OS.type == "unix") {
+    collapseChar <- ":"
+    uriSep <- "//"
+  } else {
+    collapseChar <- ";"
+    uriSep <- "////"
+  }
+
+  existingPort <- Sys.getenv("EXISTING_SPARKR_BACKEND_PORT", "")
+  if (existingPort != "") {
+    backendPort <- existingPort
+  } else {
+    path <- tempfile(pattern = "backend_port")
+    launchBackend(
+        args = path,
+        sparkHome = sparkHome,
+        jars = jars,
+        sparkSubmitOpts = Sys.getenv("SPARKR_SUBMIT_ARGS", "sparkr-shell"))
+    # wait atmost 100 seconds for JVM to launch
+    wait <- 0.1
+    for (i in 1:25) {
+      Sys.sleep(wait)
+      if (file.exists(path)) {
+        break
+      }
+      wait <- wait * 1.25
+    }
+    if (!file.exists(path)) {
+      stop("JVM is not ready after 10 seconds")
+    }
+    f <- file(path, open='rb')
+    backendPort <- readInt(f)
+    monitorPort <- readInt(f)
+    close(f)
+    file.remove(path)
+    if (length(backendPort) == 0 || backendPort == 0 ||
+        length(monitorPort) == 0 || monitorPort == 0) {
+      stop("JVM failed to launch")
+    }
+    assign(".monitorConn", socketConnection(port = monitorPort), envir = .sparkREnv)
+    assign(".backendLaunched", 1, envir = .sparkREnv)
+  }
+
+  .sparkREnv$backendPort <- backendPort
+  tryCatch({
+    connectBackend("localhost", backendPort)
+  }, error = function(err) {
+    stop("Failed to connect JVM\n")
+  })
+
+  if (nchar(sparkHome) != 0) {
+    sparkHome <- normalizePath(sparkHome)
+  }
+
+  if (nchar(sparkRLibDir) != 0) {
+    .sparkREnv$libname <- sparkRLibDir
+  }
+
+  sparkEnvirMap <- new.env()
+  for (varname in names(sparkEnvir)) {
+    sparkEnvirMap[[varname]] <- sparkEnvir[[varname]]
+  }
+  
+  sparkExecutorEnvMap <- new.env()
+  if (!any(names(sparkExecutorEnv) == "LD_LIBRARY_PATH")) {
+    sparkExecutorEnvMap[["LD_LIBRARY_PATH"]] <- paste0("$LD_LIBRARY_PATH:",Sys.getenv("LD_LIBRARY_PATH"))
+  }
+  for (varname in names(sparkExecutorEnv)) {
+    sparkExecutorEnvMap[[varname]] <- sparkExecutorEnv[[varname]]
+  }
+
+  nonEmptyJars <- Filter(function(x) { x != "" }, jars)
+  localJarPaths <- sapply(nonEmptyJars, function(j) { utils::URLencode(paste("file:", uriSep, j, sep = "")) })
+
+  # Set the start time to identify jobjs
+  # Seconds resolution is good enough for this purpose, so use ints
+  assign(".scStartTime", as.integer(Sys.time()), envir = .sparkREnv)
+
+  assign(
+    ".sparkRjsc",
+    callJStatic(
+      "org.apache.spark.api.r.RRDD",
+      "createSparkContext",
+      master,
+      appName,
+      as.character(sparkHome),
+      as.list(localJarPaths),
+      sparkEnvirMap,
+      sparkExecutorEnvMap),
+    envir = .sparkREnv
+  )
+
+  sc <- get(".sparkRjsc", envir = .sparkREnv)
+
+  # Register a finalizer to sleep 1 seconds on R exit to make RStudio happy
+  reg.finalizer(.sparkREnv, function(x) { Sys.sleep(1) }, onexit = TRUE)
+
+  sc
+}
+
+#' Initialize a new SQLContext.
+#'
+#' This function creates a SparkContext from an existing JavaSparkContext and 
+#' then uses it to initialize a new SQLContext
+#'
+#' @param jsc The existing JavaSparkContext created with SparkR.init()
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#'}
+
+sparkRSQL.init <- function(jsc) {
+  if (exists(".sparkRSQLsc", envir = .sparkREnv)) {
+    return(get(".sparkRSQLsc", envir = .sparkREnv))
+  }
+
+  sqlCtx <- callJStatic("org.apache.spark.sql.api.r.SQLUtils",
+                        "createSQLContext",
+                        jsc)
+  assign(".sparkRSQLsc", sqlCtx, envir = .sparkREnv)
+  sqlCtx
+}
+
+#' Initialize a new HiveContext.
+#'
+#' This function creates a HiveContext from an existing JavaSparkContext
+#'
+#' @param jsc The existing JavaSparkContext created with SparkR.init()
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRHive.init(sc)
+#'}
+
+sparkRHive.init <- function(jsc) {
+  if (exists(".sparkRHivesc", envir = .sparkREnv)) {
+    return(get(".sparkRHivesc", envir = .sparkREnv))
+  }
+
+  ssc <- callJMethod(jsc, "sc")
+  hiveCtx <- tryCatch({
+    newJObject("org.apache.spark.sql.hive.HiveContext", ssc)
+  }, error = function(err) {
+    stop("Spark SQL is not built with Hive support")
+  })
+
+  assign(".sparkRHivesc", hiveCtx, envir = .sparkREnv)
+  hiveCtx
+}
diff --git a/R/pkg/R/utils.R b/R/pkg/R/utils.R
new file mode 100644
index 0000000000000..c337fb0751e72
--- /dev/null
+++ b/R/pkg/R/utils.R
@@ -0,0 +1,467 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Utilities and Helpers
+
+# Given a JList<T>, returns an R list containing the same elements, the number
+# of which is optionally upper bounded by `logicalUpperBound` (by default,
+# return all elements).  Takes care of deserializations and type conversions.
+convertJListToRList <- function(jList, flatten, logicalUpperBound = NULL,
+  serializedMode = "byte") {
+  arrSize <- callJMethod(jList, "size")
+
+  # Datasets with serializedMode == "string" (such as an RDD directly generated by textFile()):
+  # each partition is not dense-packed into one Array[Byte], and `arrSize`
+  # here corresponds to number of logical elements. Thus we can prune here.
+  if (serializedMode == "string" && !is.null(logicalUpperBound)) {
+    arrSize <- min(arrSize, logicalUpperBound)
+  }
+
+  results <- if (arrSize > 0) {
+    lapply(0:(arrSize - 1),
+          function(index) {
+            obj <- callJMethod(jList, "get", as.integer(index))
+
+            # Assume it is either an R object or a Java obj ref.
+            if (inherits(obj, "jobj")) {
+              if (isInstanceOf(obj, "scala.Tuple2")) {
+                # JavaPairRDD[Array[Byte], Array[Byte]].
+
+                keyBytes = callJMethod(obj, "_1")
+                valBytes = callJMethod(obj, "_2")
+                res <- list(unserialize(keyBytes),
+                  unserialize(valBytes))
+              } else {
+                stop(paste("utils.R: convertJListToRList only supports",
+                  "RDD[Array[Byte]] and",
+                  "JavaPairRDD[Array[Byte], Array[Byte]] for now"))
+              }
+            } else {
+              if (inherits(obj, "raw")) {
+                if (serializedMode == "byte") {
+                  # RDD[Array[Byte]]. `obj` is a whole partition.
+                  res <- unserialize(obj)
+                  # For serialized datasets, `obj` (and `rRaw`) here corresponds to
+                  # one whole partition dense-packed together. We deserialize the
+                  # whole partition first, then cap the number of elements to be returned.
+                } else if (serializedMode == "row") {
+                  res <- readRowList(obj)
+                  # For DataFrames that have been converted to RRDDs, we call readRowList
+                  # which will read in each row of the RRDD as a list and deserialize
+                  # each element.
+                  flatten <<- FALSE
+                  # Use global assignment to change the flatten flag. This means
+                  # we don't have to worry about the default argument in other functions
+                  # e.g. collect
+                }
+                # TODO: is it possible to distinguish element boundary so that we can
+                # unserialize only what we need?
+                if (!is.null(logicalUpperBound)) {
+                  res <- head(res, n = logicalUpperBound)
+                }
+              } else {
+                # obj is of a primitive Java type, is simplified to R's
+                # corresponding type.
+                res <- list(obj)
+              }
+            }
+            res
+          })
+  } else {
+    list()
+  }
+
+  if (flatten) {
+    as.list(unlist(results, recursive = FALSE))
+  } else {
+    as.list(results)
+  }
+}
+
+# Returns TRUE if `name` refers to an RDD in the given environment `env`
+isRDD <- function(name, env) {
+  obj <- get(name, envir = env)
+  inherits(obj, "RDD")
+}
+
+#' Compute the hashCode of an object
+#'
+#' Java-style function to compute the hashCode for the given object. Returns
+#' an integer value.
+#'
+#' @details
+#' This only works for integer, numeric and character types right now.
+#'
+#' @param key the object to be hashed
+#' @return the hash code as an integer
+#' @export
+#' @examples
+#' hashCode(1L) # 1
+#' hashCode(1.0) # 1072693248
+#' hashCode("1") # 49
+hashCode <- function(key) {
+  if (class(key) == "integer") {
+    as.integer(key[[1]])
+  } else if (class(key) == "numeric") {
+    # Convert the double to long and then calculate the hash code
+    rawVec <- writeBin(key[[1]], con = raw())
+    intBits <- packBits(rawToBits(rawVec), "integer")
+    as.integer(bitwXor(intBits[2], intBits[1]))
+  } else if (class(key) == "character") {
+    .Call("stringHashCode", key)
+  } else {
+    warning(paste("Could not hash object, returning 0", sep = ""))
+    as.integer(0)
+  }
+}
+
+# Create a new RDD with serializedMode == "byte".
+# Return itself if already in "byte" format.
+serializeToBytes <- function(rdd) {
+  if (!inherits(rdd, "RDD")) {
+    stop("Argument 'rdd' is not an RDD type.")
+  }
+  if (getSerializedMode(rdd) != "byte") {
+    ser.rdd <- lapply(rdd, function(x) { x })
+    return(ser.rdd)
+  } else {
+    return(rdd)
+  }
+}
+
+# Create a new RDD with serializedMode == "string".
+# Return itself if already in "string" format.
+serializeToString <- function(rdd) {
+  if (!inherits(rdd, "RDD")) {
+    stop("Argument 'rdd' is not an RDD type.")
+  }
+  if (getSerializedMode(rdd) != "string") {
+    ser.rdd <- lapply(rdd, function(x) { toString(x) })
+    # force it to create jrdd using "string"
+    getJRDD(ser.rdd, serializedMode = "string")
+    return(ser.rdd)
+  } else {
+    return(rdd)
+  }
+}
+
+# Fast append to list by using an accumulator.
+# http://stackoverflow.com/questions/17046336/here-we-go-again-append-an-element-to-a-list-in-r
+#
+# The accumulator should has three fields size, counter and data.
+# This function amortizes the allocation cost by doubling
+# the size of the list every time it fills up.
+addItemToAccumulator <- function(acc, item) {
+  if(acc$counter == acc$size) {
+    acc$size <- acc$size * 2
+    length(acc$data) <- acc$size
+  }
+  acc$counter <- acc$counter + 1
+  acc$data[[acc$counter]] <- item
+}
+
+initAccumulator <- function() {
+  acc <- new.env()
+  acc$counter <- 0
+  acc$data <- list(NULL)
+  acc$size <- 1
+  acc
+}
+
+# Utility function to sort a list of key value pairs
+# Used in unit tests
+sortKeyValueList <- function(kv_list, decreasing = FALSE) {
+  keys <- sapply(kv_list, function(x) x[[1]])
+  kv_list[order(keys, decreasing = decreasing)]
+}
+
+# Utility function to generate compact R lists from grouped rdd
+# Used in Join-family functions
+# param:
+#   tagged_list R list generated via groupByKey with tags(1L, 2L, ...)
+#   cnull Boolean list where each element determines whether the corresponding list should
+#         be converted to list(NULL)
+genCompactLists <- function(tagged_list, cnull) {
+  len <- length(tagged_list)
+  lists <- list(vector("list", len), vector("list", len))
+  index <- list(1, 1)
+
+  for (x in tagged_list) {
+    tag <- x[[1]]
+    idx <- index[[tag]]
+    lists[[tag]][[idx]] <- x[[2]]
+    index[[tag]] <- idx + 1
+  }
+
+  len <- lapply(index, function(x) x - 1)
+  for (i in (1:2)) {
+    if (cnull[[i]] && len[[i]] == 0) {
+      lists[[i]] <- list(NULL)
+    } else {
+      length(lists[[i]]) <- len[[i]]
+    }
+  }
+
+  lists
+}
+
+# Utility function to merge compact R lists
+# Used in Join-family functions
+# param:
+#   left/right Two compact lists ready for Cartesian product
+mergeCompactLists <- function(left, right) {
+  result <- list()
+  length(result) <- length(left) * length(right)
+  index <- 1
+  for (i in left) {
+    for (j in right) {
+      result[[index]] <- list(i, j)
+      index <- index + 1
+    }
+  }
+  result
+}
+
+# Utility function to wrapper above two operations
+# Used in Join-family functions
+# param (same as genCompactLists):
+#   tagged_list R list generated via groupByKey with tags(1L, 2L, ...)
+#   cnull Boolean list where each element determines whether the corresponding list should
+#         be converted to list(NULL)
+joinTaggedList <- function(tagged_list, cnull) {
+  lists <- genCompactLists(tagged_list, cnull)
+  mergeCompactLists(lists[[1]], lists[[2]])
+}
+
+# Utility function to reduce a key-value list with predicate
+# Used in *ByKey functions
+# param
+#   pair key-value pair
+#   keys/vals env of key/value with hashes
+#   updateOrCreatePred predicate function
+#   updateFn update or merge function for existing pair, similar with `mergeVal` @combineByKey
+#   createFn create function for new pair, similar with `createCombiner` @combinebykey
+updateOrCreatePair <- function(pair, keys, vals, updateOrCreatePred, updateFn, createFn) {
+  # assume hashVal bind to `$hash`, key/val with index 1/2
+  hashVal <- pair$hash
+  key <- pair[[1]]
+  val <- pair[[2]]
+  if (updateOrCreatePred(pair)) {
+    assign(hashVal, do.call(updateFn, list(get(hashVal, envir = vals), val)), envir = vals)
+  } else {
+    assign(hashVal, do.call(createFn, list(val)), envir = vals)
+    assign(hashVal, key, envir = keys)
+  }
+}
+
+# Utility function to convert key&values envs into key-val list
+convertEnvsToList <- function(keys, vals) {
+  lapply(ls(keys),
+         function(name) {
+           list(keys[[name]], vals[[name]])
+         })
+}
+
+# Utility function to capture the varargs into environment object
+varargsToEnv <- function(...) {
+  pairs <- as.list(substitute(list(...)))[-1L]
+  env <- new.env()
+  for (name in names(pairs)) {
+    env[[name]] <- pairs[[name]]
+  }
+  env
+}
+
+getStorageLevel <- function(newLevel = c("DISK_ONLY",
+                                         "DISK_ONLY_2",
+                                         "MEMORY_AND_DISK",
+                                         "MEMORY_AND_DISK_2",
+                                         "MEMORY_AND_DISK_SER",
+                                         "MEMORY_AND_DISK_SER_2",
+                                         "MEMORY_ONLY",
+                                         "MEMORY_ONLY_2",
+                                         "MEMORY_ONLY_SER",
+                                         "MEMORY_ONLY_SER_2",
+                                         "OFF_HEAP")) {
+  match.arg(newLevel)
+  storageLevel <- switch(newLevel,
+                         "DISK_ONLY" = callJStatic("org.apache.spark.storage.StorageLevel", "DISK_ONLY"),
+                         "DISK_ONLY_2" = callJStatic("org.apache.spark.storage.StorageLevel", "DISK_ONLY_2"),
+                         "MEMORY_AND_DISK" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_AND_DISK"),
+                         "MEMORY_AND_DISK_2" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_AND_DISK_2"),
+                         "MEMORY_AND_DISK_SER" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_AND_DISK_SER"),
+                         "MEMORY_AND_DISK_SER_2" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_AND_DISK_SER_2"),
+                         "MEMORY_ONLY" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_ONLY"),
+                         "MEMORY_ONLY_2" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_ONLY_2"),
+                         "MEMORY_ONLY_SER" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_ONLY_SER"),
+                         "MEMORY_ONLY_SER_2" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_ONLY_SER_2"),
+                         "OFF_HEAP" = callJStatic("org.apache.spark.storage.StorageLevel", "OFF_HEAP"))
+}
+
+# Utility function for functions where an argument needs to be integer but we want to allow
+# the user to type (for example) `5` instead of `5L` to avoid a confusing error message.
+numToInt <- function(num) {
+  if (as.integer(num) != num) {
+    warning(paste("Coercing", as.list(sys.call())[[2]], "to integer."))
+  }
+  as.integer(num)
+}
+
+# create a Seq in JVM
+toSeq <- function(...) {
+  callJStatic("org.apache.spark.sql.api.r.SQLUtils", "toSeq", list(...))
+}
+
+# create a Seq in JVM from a list
+listToSeq <- function(l) {
+  callJStatic("org.apache.spark.sql.api.r.SQLUtils", "toSeq", l)
+}
+
+# Utility function to recursively traverse the Abstract Syntax Tree (AST) of a
+# user defined function (UDF), and to examine variables in the UDF to decide 
+# if their values should be included in the new function environment.
+# param
+#   node The current AST node in the traversal.
+#   oldEnv The original function environment.
+#   defVars An Accumulator of variables names defined in the function's calling environment,
+#           including function argument and local variable names.
+#   checkedFunc An environment of function objects examined during cleanClosure. It can 
+#               be considered as a "name"-to-"list of functions" mapping.
+#   newEnv A new function environment to store necessary function dependencies, an output argument.
+processClosure <- function(node, oldEnv, defVars, checkedFuncs, newEnv) {
+  nodeLen <- length(node)
+  
+  if (nodeLen > 1 && typeof(node) == "language") {
+    # Recursive case: current AST node is an internal node, check for its children. 
+    if (length(node[[1]]) > 1) {
+      for (i in 1:nodeLen) {
+        processClosure(node[[i]], oldEnv, defVars, checkedFuncs, newEnv)
+      }
+    } else {  # if node[[1]] is length of 1, check for some R special functions.
+      nodeChar <- as.character(node[[1]])
+      if (nodeChar == "{" || nodeChar == "(") {  # Skip start symbol.
+        for (i in 2:nodeLen) {
+          processClosure(node[[i]], oldEnv, defVars, checkedFuncs, newEnv)
+        }
+      } else if (nodeChar == "<-" || nodeChar == "=" || 
+                   nodeChar == "<<-") { # Assignment Ops.
+        defVar <- node[[2]]
+        if (length(defVar) == 1 && typeof(defVar) == "symbol") {
+          # Add the defined variable name into defVars.
+          addItemToAccumulator(defVars, as.character(defVar))
+        } else {
+          processClosure(node[[2]], oldEnv, defVars, checkedFuncs, newEnv)
+        }
+        for (i in 3:nodeLen) {
+          processClosure(node[[i]], oldEnv, defVars, checkedFuncs, newEnv)
+        }
+      } else if (nodeChar == "function") {  # Function definition.
+        # Add parameter names.
+        newArgs <- names(node[[2]])
+        lapply(newArgs, function(arg) { addItemToAccumulator(defVars, arg) })
+        for (i in 3:nodeLen) {
+          processClosure(node[[i]], oldEnv, defVars, checkedFuncs, newEnv)
+        }
+      } else if (nodeChar == "$") {  # Skip the field.
+        processClosure(node[[2]], oldEnv, defVars, checkedFuncs, newEnv)
+      } else if (nodeChar == "::" || nodeChar == ":::") {
+        processClosure(node[[3]], oldEnv, defVars, checkedFuncs, newEnv)
+      } else {
+        for (i in 1:nodeLen) {
+          processClosure(node[[i]], oldEnv, defVars, checkedFuncs, newEnv)
+        }
+      }
+    }
+  } else if (nodeLen == 1 && 
+               (typeof(node) == "symbol" || typeof(node) == "language")) {
+    # Base case: current AST node is a leaf node and a symbol or a function call.
+    nodeChar <- as.character(node)
+    if (!nodeChar %in% defVars$data) {  # Not a function parameter or local variable.
+      func.env <- oldEnv
+      topEnv <- parent.env(.GlobalEnv)
+      # Search in function environment, and function's enclosing environments 
+      # up to global environment. There is no need to look into package environments
+      # above the global or namespace environment that is not SparkR below the global, 
+      # as they are assumed to be loaded on workers.
+      while (!identical(func.env, topEnv)) {
+        # Namespaces other than "SparkR" will not be searched.
+        if (!isNamespace(func.env) || 
+              (getNamespaceName(func.env) == "SparkR" && 
+              !(nodeChar %in% getNamespaceExports("SparkR")))) {  # Only include SparkR internals.
+          # Set parameter 'inherits' to FALSE since we do not need to search in
+          # attached package environments.
+          if (tryCatch(exists(nodeChar, envir = func.env, inherits = FALSE),
+                       error = function(e) { FALSE })) {
+            obj <- get(nodeChar, envir = func.env, inherits = FALSE)
+            if (is.function(obj)) {  # If the node is a function call.
+              funcList <- mget(nodeChar, envir = checkedFuncs, inherits = F, 
+                               ifnotfound = list(list(NULL)))[[1]]
+              found <- sapply(funcList, function(func) {
+                ifelse(identical(func, obj), TRUE, FALSE)
+              })
+              if (sum(found) > 0) {  # If function has been examined, ignore.
+                break
+              }
+              # Function has not been examined, record it and recursively clean its closure.
+              assign(nodeChar, 
+                     if (is.null(funcList[[1]])) {
+                       list(obj)
+                     } else {
+                       append(funcList, obj)
+                     },
+                     envir = checkedFuncs)
+              obj <- cleanClosure(obj, checkedFuncs)
+            }
+            assign(nodeChar, obj, envir = newEnv)
+            break
+          }
+        }
+        
+        # Continue to search in enclosure.
+        func.env <- parent.env(func.env)
+      }
+    }
+  }
+}
+
+# Utility function to get user defined function (UDF) dependencies (closure). 
+# More specifically, this function captures the values of free variables defined 
+# outside a UDF, and stores them in the function's environment.
+# param
+#   func A function whose closure needs to be captured.
+#   checkedFunc An environment of function objects examined during cleanClosure. It can be
+#               considered as a "name"-to-"list of functions" mapping.
+# return value
+#   a new version of func that has an correct environment (closure).
+cleanClosure <- function(func, checkedFuncs = new.env()) {
+  if (is.function(func)) {
+    newEnv <- new.env(parent = .GlobalEnv)
+    func.body <- body(func)
+    oldEnv <- environment(func)
+    # defVars is an Accumulator of variables names defined in the function's calling 
+    # environment. First, function's arguments are added to defVars.
+    defVars <- initAccumulator()
+    argNames <- names(as.list(args(func)))
+    for (i in 1:(length(argNames) - 1)) {  # Remove the ending NULL in pairlist.
+      addItemToAccumulator(defVars, argNames[i])
+    }
+    # Recursively examine variables in the function body.
+    processClosure(func.body, oldEnv, defVars, checkedFuncs, newEnv)
+    environment(func) <- newEnv
+  }
+  func
+}
diff --git a/R/pkg/R/zzz.R b/R/pkg/R/zzz.R
new file mode 100644
index 0000000000000..80d796d467943
--- /dev/null
+++ b/R/pkg/R/zzz.R
@@ -0,0 +1,21 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+.onLoad <- function(libname, pkgname) {
+  sparkR.onLoad(libname, pkgname)
+}
+
diff --git a/R/pkg/inst/profile/general.R b/R/pkg/inst/profile/general.R
new file mode 100644
index 0000000000000..8fe711b622086
--- /dev/null
+++ b/R/pkg/inst/profile/general.R
@@ -0,0 +1,22 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+.First <- function() {
+  home <- Sys.getenv("SPARK_HOME")
+  .libPaths(c(file.path(home, "R", "lib"), .libPaths()))
+  Sys.setenv(NOAWT=1)
+}
diff --git a/R/pkg/inst/profile/shell.R b/R/pkg/inst/profile/shell.R
new file mode 100644
index 0000000000000..7a7f2031152a0
--- /dev/null
+++ b/R/pkg/inst/profile/shell.R
@@ -0,0 +1,31 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+.First <- function() {
+  home <- Sys.getenv("SPARK_HOME")
+  .libPaths(c(file.path(home, "R", "lib"), .libPaths()))
+  Sys.setenv(NOAWT=1)
+
+  library(utils)
+  library(SparkR)
+  sc <- sparkR.init(Sys.getenv("MASTER", unset = ""))
+  assign("sc", sc, envir=.GlobalEnv)
+  sqlCtx <- sparkRSQL.init(sc)
+  assign("sqlCtx", sqlCtx, envir=.GlobalEnv)
+  cat("\n Welcome to SparkR!")
+  cat("\n Spark context is available as sc, SQL context is available as sqlCtx\n")
+}
diff --git a/R/pkg/inst/tests/test_binaryFile.R b/R/pkg/inst/tests/test_binaryFile.R
new file mode 100644
index 0000000000000..4bb5f58d83dc9
--- /dev/null
+++ b/R/pkg/inst/tests/test_binaryFile.R
@@ -0,0 +1,90 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+context("functions on binary files")
+
+# JavaSparkContext handle
+sc <- sparkR.init()
+
+mockFile = c("Spark is pretty.", "Spark is awesome.")
+
+test_that("saveAsObjectFile()/objectFile() following textFile() works", {
+  fileName1 <- tempfile(pattern="spark-test", fileext=".tmp")
+  fileName2 <- tempfile(pattern="spark-test", fileext=".tmp")
+  writeLines(mockFile, fileName1)
+
+  rdd <- textFile(sc, fileName1)
+  saveAsObjectFile(rdd, fileName2)
+  rdd <- objectFile(sc, fileName2)
+  expect_equal(collect(rdd), as.list(mockFile))
+
+  unlink(fileName1)
+  unlink(fileName2, recursive = TRUE)
+})
+
+test_that("saveAsObjectFile()/objectFile() works on a parallelized list", {
+  fileName <- tempfile(pattern="spark-test", fileext=".tmp")
+
+  l <- list(1, 2, 3)
+  rdd <- parallelize(sc, l)
+  saveAsObjectFile(rdd, fileName)
+  rdd <- objectFile(sc, fileName)
+  expect_equal(collect(rdd), l)
+
+  unlink(fileName, recursive = TRUE)
+})
+
+test_that("saveAsObjectFile()/objectFile() following RDD transformations works", {
+  fileName1 <- tempfile(pattern="spark-test", fileext=".tmp")
+  fileName2 <- tempfile(pattern="spark-test", fileext=".tmp")
+  writeLines(mockFile, fileName1)
+
+  rdd <- textFile(sc, fileName1)
+
+  words <- flatMap(rdd, function(line) { strsplit(line, " ")[[1]] })
+  wordCount <- lapply(words, function(word) { list(word, 1L) })
+
+  counts <- reduceByKey(wordCount, "+", 2L)
+  
+  saveAsObjectFile(counts, fileName2)
+  counts <- objectFile(sc, fileName2)
+    
+  output <- collect(counts)
+  expected <- list(list("awesome.", 1), list("Spark", 2), list("pretty.", 1),
+                    list("is", 2))
+  expect_equal(sortKeyValueList(output), sortKeyValueList(expected))
+  
+  unlink(fileName1)
+  unlink(fileName2, recursive = TRUE)
+})
+
+test_that("saveAsObjectFile()/objectFile() works with multiple paths", {
+  fileName1 <- tempfile(pattern="spark-test", fileext=".tmp")
+  fileName2 <- tempfile(pattern="spark-test", fileext=".tmp")
+
+  rdd1 <- parallelize(sc, "Spark is pretty.")
+  saveAsObjectFile(rdd1, fileName1)
+  rdd2 <- parallelize(sc, "Spark is awesome.")
+  saveAsObjectFile(rdd2, fileName2)
+
+  rdd <- objectFile(sc, c(fileName1, fileName2))
+  expect_true(count(rdd) == 2)
+
+  unlink(fileName1, recursive = TRUE)
+  unlink(fileName2, recursive = TRUE)
+})
+
diff --git a/R/pkg/inst/tests/test_binary_function.R b/R/pkg/inst/tests/test_binary_function.R
new file mode 100644
index 0000000000000..c15553ba28517
--- /dev/null
+++ b/R/pkg/inst/tests/test_binary_function.R
@@ -0,0 +1,68 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+context("binary functions")
+
+# JavaSparkContext handle
+sc <- sparkR.init()
+
+# Data
+nums <- 1:10
+rdd <- parallelize(sc, nums, 2L)
+
+# File content
+mockFile <- c("Spark is pretty.", "Spark is awesome.")
+
+test_that("union on two RDDs", {
+  actual <- collect(unionRDD(rdd, rdd))
+  expect_equal(actual, as.list(rep(nums, 2)))
+  
+  fileName <- tempfile(pattern="spark-test", fileext=".tmp")
+  writeLines(mockFile, fileName)
+
+  text.rdd <- textFile(sc, fileName)
+  union.rdd <- unionRDD(rdd, text.rdd)
+  actual <- collect(union.rdd)
+  expect_equal(actual, c(as.list(nums), mockFile))
+  expect_true(getSerializedMode(union.rdd) == "byte")
+
+  rdd<- map(text.rdd, function(x) {x})
+  union.rdd <- unionRDD(rdd, text.rdd)
+  actual <- collect(union.rdd)
+  expect_equal(actual, as.list(c(mockFile, mockFile)))
+  expect_true(getSerializedMode(union.rdd) == "byte")
+
+  unlink(fileName)
+})
+
+test_that("cogroup on two RDDs", {
+  rdd1 <- parallelize(sc, list(list(1, 1), list(2, 4)))
+  rdd2 <- parallelize(sc, list(list(1, 2), list(1, 3)))
+  cogroup.rdd <- cogroup(rdd1, rdd2, numPartitions = 2L) 
+  actual <- collect(cogroup.rdd)
+  expect_equal(actual, 
+               list(list(1, list(list(1), list(2, 3))), list(2, list(list(4), list()))))
+  
+  rdd1 <- parallelize(sc, list(list("a", 1), list("a", 4)))
+  rdd2 <- parallelize(sc, list(list("b", 2), list("a", 3)))
+  cogroup.rdd <- cogroup(rdd1, rdd2, numPartitions = 2L) 
+  actual <- collect(cogroup.rdd)
+
+  expected <- list(list("b", list(list(), list(2))), list("a", list(list(1, 4), list(3))))
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(expected))
+})
diff --git a/R/pkg/inst/tests/test_broadcast.R b/R/pkg/inst/tests/test_broadcast.R
new file mode 100644
index 0000000000000..fee91a427d6d5
--- /dev/null
+++ b/R/pkg/inst/tests/test_broadcast.R
@@ -0,0 +1,48 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+context("broadcast variables")
+
+# JavaSparkContext handle
+sc <- sparkR.init()
+
+# Partitioned data
+nums <- 1:2
+rrdd <- parallelize(sc, nums, 2L)
+
+test_that("using broadcast variable", {
+  randomMat <- matrix(nrow=10, ncol=10, data=rnorm(100))
+  randomMatBr <- broadcast(sc, randomMat)
+
+  useBroadcast <- function(x) {
+    sum(value(randomMatBr) * x)
+  }
+  actual <- collect(lapply(rrdd, useBroadcast))
+  expected <- list(sum(randomMat) * 1, sum(randomMat) * 2)
+  expect_equal(actual, expected)
+})
+
+test_that("without using broadcast variable", {
+  randomMat <- matrix(nrow=10, ncol=10, data=rnorm(100))
+
+  useBroadcast <- function(x) {
+    sum(randomMat * x)
+  }
+  actual <- collect(lapply(rrdd, useBroadcast))
+  expected <- list(sum(randomMat) * 1, sum(randomMat) * 2)
+  expect_equal(actual, expected)
+})
diff --git a/R/pkg/inst/tests/test_context.R b/R/pkg/inst/tests/test_context.R
new file mode 100644
index 0000000000000..e4aab37436a74
--- /dev/null
+++ b/R/pkg/inst/tests/test_context.R
@@ -0,0 +1,50 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+context("test functions in sparkR.R")
+
+test_that("repeatedly starting and stopping SparkR", {
+  for (i in 1:4) {
+    sc <- sparkR.init()
+    rdd <- parallelize(sc, 1:20, 2L)
+    expect_equal(count(rdd), 20)
+    sparkR.stop()
+  }
+})
+
+test_that("rdd GC across sparkR.stop", {
+  sparkR.stop()
+  sc <- sparkR.init() # sc should get id 0
+  rdd1 <- parallelize(sc, 1:20, 2L) # rdd1 should get id 1
+  rdd2 <- parallelize(sc, 1:10, 2L) # rdd2 should get id 2
+  sparkR.stop()
+
+  sc <- sparkR.init() # sc should get id 0 again
+
+  # GC rdd1 before creating rdd3 and rdd2 after
+  rm(rdd1)
+  gc()
+
+  rdd3 <- parallelize(sc, 1:20, 2L) # rdd3 should get id 1 now
+  rdd4 <- parallelize(sc, 1:10, 2L) # rdd4 should get id 2 now
+
+  rm(rdd2)
+  gc()
+
+  count(rdd3)
+  count(rdd4)
+})
diff --git a/R/pkg/inst/tests/test_includePackage.R b/R/pkg/inst/tests/test_includePackage.R
new file mode 100644
index 0000000000000..8152b448d0870
--- /dev/null
+++ b/R/pkg/inst/tests/test_includePackage.R
@@ -0,0 +1,57 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+context("include R packages")
+
+# JavaSparkContext handle
+sc <- sparkR.init()
+
+# Partitioned data
+nums <- 1:2
+rdd <- parallelize(sc, nums, 2L)
+
+test_that("include inside function", {
+  # Only run the test if plyr is installed.
+  if ("plyr" %in% rownames(installed.packages())) {
+    suppressPackageStartupMessages(library(plyr))
+    generateData <- function(x) {
+      suppressPackageStartupMessages(library(plyr))
+      attach(airquality)
+      result <- transform(Ozone, logOzone = log(Ozone))
+      result
+    }
+
+    data <- lapplyPartition(rdd, generateData)
+    actual <- collect(data)
+  }
+})
+
+test_that("use include package", {
+  # Only run the test if plyr is installed.
+  if ("plyr" %in% rownames(installed.packages())) {
+    suppressPackageStartupMessages(library(plyr))
+    generateData <- function(x) {
+      attach(airquality)
+      result <- transform(Ozone, logOzone = log(Ozone))
+      result
+    }
+
+    includePackage(sc, plyr)
+    data <- lapplyPartition(rdd, generateData)
+    actual <- collect(data)
+  }
+})
diff --git a/R/pkg/inst/tests/test_parallelize_collect.R b/R/pkg/inst/tests/test_parallelize_collect.R
new file mode 100644
index 0000000000000..fff028657db37
--- /dev/null
+++ b/R/pkg/inst/tests/test_parallelize_collect.R
@@ -0,0 +1,109 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+context("parallelize() and collect()")
+
+# Mock data
+numVector <- c(-10:97)
+numList <- list(sqrt(1), sqrt(2), sqrt(3), 4 ** 10)
+strVector <- c("Dexter Morgan: I suppose I should be upset, even feel",
+               "violated, but I'm not. No, in fact, I think this is a friendly",
+               "message, like \"Hey, wanna play?\" and yes, I want to play. ",
+               "I really, really do.")
+strList <- list("Dexter Morgan: Blood. Sometimes it sets my teeth on edge, ",
+                "other times it helps me control the chaos.",
+                "Dexter Morgan: Harry and Dorris Morgan did a wonderful job ",
+                "raising me. But they're both dead now. I didn't kill them. Honest.")
+
+numPairs <- list(list(1, 1), list(1, 2), list(2, 2), list(2, 3))
+strPairs <- list(list(strList, strList), list(strList, strList))
+
+# JavaSparkContext handle
+jsc <- sparkR.init()
+
+# Tests
+
+test_that("parallelize() on simple vectors and lists returns an RDD", {
+  numVectorRDD <- parallelize(jsc, numVector, 1)
+  numVectorRDD2 <- parallelize(jsc, numVector, 10)
+  numListRDD <- parallelize(jsc, numList, 1)
+  numListRDD2 <- parallelize(jsc, numList, 4)
+  strVectorRDD <- parallelize(jsc, strVector, 2)
+  strVectorRDD2 <- parallelize(jsc, strVector, 3)
+  strListRDD <- parallelize(jsc, strList, 4)
+  strListRDD2 <- parallelize(jsc, strList, 1)
+
+  rdds <- c(numVectorRDD,
+             numVectorRDD2,
+             numListRDD,
+             numListRDD2,
+             strVectorRDD,
+             strVectorRDD2,
+             strListRDD,
+             strListRDD2)
+
+  for (rdd in rdds) {
+    expect_true(inherits(rdd, "RDD"))
+    expect_true(.hasSlot(rdd, "jrdd")
+                && inherits(rdd@jrdd, "jobj")
+                && isInstanceOf(rdd@jrdd, "org.apache.spark.api.java.JavaRDD"))
+  }
+})
+
+test_that("collect(), following a parallelize(), gives back the original collections", {
+  numVectorRDD <- parallelize(jsc, numVector, 10)
+  expect_equal(collect(numVectorRDD), as.list(numVector))
+
+  numListRDD <- parallelize(jsc, numList, 1)
+  numListRDD2 <- parallelize(jsc, numList, 4)
+  expect_equal(collect(numListRDD), as.list(numList))
+  expect_equal(collect(numListRDD2), as.list(numList))
+
+  strVectorRDD <- parallelize(jsc, strVector, 2)
+  strVectorRDD2 <- parallelize(jsc, strVector, 3)
+  expect_equal(collect(strVectorRDD), as.list(strVector))
+  expect_equal(collect(strVectorRDD2), as.list(strVector))
+
+  strListRDD <- parallelize(jsc, strList, 4)
+  strListRDD2 <- parallelize(jsc, strList, 1)
+  expect_equal(collect(strListRDD), as.list(strList))
+  expect_equal(collect(strListRDD2), as.list(strList))
+})
+
+test_that("regression: collect() following a parallelize() does not drop elements", {
+  # 10 %/% 6 = 1, ceiling(10 / 6) = 2
+  collLen <- 10
+  numPart <- 6
+  expected <- runif(collLen)
+  actual <- collect(parallelize(jsc, expected, numPart))
+  expect_equal(actual, as.list(expected))
+})
+
+test_that("parallelize() and collect() work for lists of pairs (pairwise data)", {
+  # use the pairwise logical to indicate pairwise data
+  numPairsRDDD1 <- parallelize(jsc, numPairs, 1)
+  numPairsRDDD2 <- parallelize(jsc, numPairs, 2)
+  numPairsRDDD3 <- parallelize(jsc, numPairs, 3)
+  expect_equal(collect(numPairsRDDD1), numPairs)
+  expect_equal(collect(numPairsRDDD2), numPairs)
+  expect_equal(collect(numPairsRDDD3), numPairs)
+  # can also leave out the parameter name, if the params are supplied in order
+  strPairsRDDD1 <- parallelize(jsc, strPairs, 1)
+  strPairsRDDD2 <- parallelize(jsc, strPairs, 2)
+  expect_equal(collect(strPairsRDDD1), strPairs)
+  expect_equal(collect(strPairsRDDD2), strPairs)
+})
diff --git a/R/pkg/inst/tests/test_rdd.R b/R/pkg/inst/tests/test_rdd.R
new file mode 100644
index 0000000000000..f75e0817b9406
--- /dev/null
+++ b/R/pkg/inst/tests/test_rdd.R
@@ -0,0 +1,644 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+context("basic RDD functions")
+
+# JavaSparkContext handle
+sc <- sparkR.init()
+
+# Data
+nums <- 1:10
+rdd <- parallelize(sc, nums, 2L)
+
+intPairs <- list(list(1L, -1), list(2L, 100), list(2L, 1), list(1L, 200))
+intRdd <- parallelize(sc, intPairs, 2L)
+
+test_that("get number of partitions in RDD", {
+  expect_equal(numPartitions(rdd), 2)
+  expect_equal(numPartitions(intRdd), 2)
+})
+
+test_that("first on RDD", {
+  expect_true(first(rdd) == 1)
+  newrdd <- lapply(rdd, function(x) x + 1)
+  expect_true(first(newrdd) == 2)  
+})
+
+test_that("count and length on RDD", {
+   expect_equal(count(rdd), 10)
+   expect_equal(length(rdd), 10)
+})
+
+test_that("count by values and keys", {
+  mods <- lapply(rdd, function(x) { x %% 3 })
+  actual <- countByValue(mods)
+  expected <- list(list(0, 3L), list(1, 4L), list(2, 3L))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+  
+  actual <- countByKey(intRdd)
+  expected <- list(list(2L, 2L), list(1L, 2L))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+})
+
+test_that("lapply on RDD", {
+  multiples <- lapply(rdd, function(x) { 2 * x })
+  actual <- collect(multiples)
+  expect_equal(actual, as.list(nums * 2))
+})
+
+test_that("lapplyPartition on RDD", {
+  sums <- lapplyPartition(rdd, function(part) { sum(unlist(part)) })
+  actual <- collect(sums)
+  expect_equal(actual, list(15, 40))
+})
+
+test_that("mapPartitions on RDD", {
+  sums <- mapPartitions(rdd, function(part) { sum(unlist(part)) })
+  actual <- collect(sums)
+  expect_equal(actual, list(15, 40))
+})
+
+test_that("flatMap() on RDDs", {
+  flat <- flatMap(intRdd, function(x) { list(x, x) })
+  actual <- collect(flat)
+  expect_equal(actual, rep(intPairs, each=2))
+})
+
+test_that("filterRDD on RDD", {
+  filtered.rdd <- filterRDD(rdd, function(x) { x %% 2 == 0 })
+  actual <- collect(filtered.rdd)
+  expect_equal(actual, list(2, 4, 6, 8, 10))
+  
+  filtered.rdd <- Filter(function(x) { x[[2]] < 0 }, intRdd)
+  actual <- collect(filtered.rdd)
+  expect_equal(actual, list(list(1L, -1)))
+  
+  # Filter out all elements.
+  filtered.rdd <- filterRDD(rdd, function(x) { x > 10 })
+  actual <- collect(filtered.rdd)
+  expect_equal(actual, list())
+})
+
+test_that("lookup on RDD", {
+  vals <- lookup(intRdd, 1L)
+  expect_equal(vals, list(-1, 200))
+  
+  vals <- lookup(intRdd, 3L)
+  expect_equal(vals, list())
+})
+
+test_that("several transformations on RDD (a benchmark on PipelinedRDD)", {
+  rdd2 <- rdd
+  for (i in 1:12)
+    rdd2 <- lapplyPartitionsWithIndex(
+              rdd2, function(split, part) {
+                part <- as.list(unlist(part) * split + i)
+              })
+  rdd2 <- lapply(rdd2, function(x) x + x)
+  actual <- collect(rdd2)
+  expected <- list(24, 24, 24, 24, 24, 
+                   168, 170, 172, 174, 176)
+  expect_equal(actual, expected)
+})
+
+test_that("PipelinedRDD support actions: cache(), persist(), unpersist(), checkpoint()", {
+  # RDD
+  rdd2 <- rdd
+  # PipelinedRDD
+  rdd2 <- lapplyPartitionsWithIndex(
+            rdd2,
+            function(split, part) {
+              part <- as.list(unlist(part) * split)
+            })
+
+  cache(rdd2)
+  expect_true(rdd2@env$isCached)
+  rdd2 <- lapply(rdd2, function(x) x)
+  expect_false(rdd2@env$isCached)
+
+  unpersist(rdd2)
+  expect_false(rdd2@env$isCached)
+
+  persist(rdd2, "MEMORY_AND_DISK")
+  expect_true(rdd2@env$isCached)
+  rdd2 <- lapply(rdd2, function(x) x)
+  expect_false(rdd2@env$isCached)
+
+  unpersist(rdd2)
+  expect_false(rdd2@env$isCached)
+
+  setCheckpointDir(sc, "checkpoints")
+  checkpoint(rdd2)
+  expect_true(rdd2@env$isCheckpointed)
+
+  rdd2 <- lapply(rdd2, function(x) x)
+  expect_false(rdd2@env$isCached)
+  expect_false(rdd2@env$isCheckpointed)
+
+  # make sure the data is collectable
+  collect(rdd2)
+
+  unlink("checkpoints")
+})
+
+test_that("reduce on RDD", {
+  sum <- reduce(rdd, "+")
+  expect_equal(sum, 55)
+
+  # Also test with an inline function
+  sumInline <- reduce(rdd, function(x, y) { x + y })
+  expect_equal(sumInline, 55)
+})
+
+test_that("lapply with dependency", {
+  fa <- 5
+  multiples <- lapply(rdd, function(x) { fa * x })
+  actual <- collect(multiples)
+
+  expect_equal(actual, as.list(nums * 5))
+})
+
+test_that("lapplyPartitionsWithIndex on RDDs", {
+  func <- function(splitIndex, part) { list(splitIndex, Reduce("+", part)) }
+  actual <- collect(lapplyPartitionsWithIndex(rdd, func), flatten = FALSE)
+  expect_equal(actual, list(list(0, 15), list(1, 40)))
+
+  pairsRDD <- parallelize(sc, list(list(1, 2), list(3, 4), list(4, 8)), 1L)
+  partitionByParity <- function(key) { if (key %% 2 == 1) 0 else 1 }
+  mkTup <- function(splitIndex, part) { list(splitIndex, part) }
+  actual <- collect(lapplyPartitionsWithIndex(
+                      partitionBy(pairsRDD, 2L, partitionByParity),
+                      mkTup),
+                    FALSE)
+  expect_equal(actual, list(list(0, list(list(1, 2), list(3, 4))),
+                            list(1, list(list(4, 8)))))
+})
+
+test_that("sampleRDD() on RDDs", {
+  expect_equal(unlist(collect(sampleRDD(rdd, FALSE, 1.0, 2014L))), nums)
+})
+
+test_that("takeSample() on RDDs", {
+  # ported from RDDSuite.scala, modified seeds
+  data <- parallelize(sc, 1:100, 2L)
+  for (seed in 4:5) {
+    s <- takeSample(data, FALSE, 20L, seed)
+    expect_equal(length(s), 20L)
+    expect_equal(length(unique(s)), 20L)
+    for (elem in s) {
+      expect_true(elem >= 1 && elem <= 100)
+    }
+  }
+  for (seed in 4:5) {
+    s <- takeSample(data, FALSE, 200L, seed)
+    expect_equal(length(s), 100L)
+    expect_equal(length(unique(s)), 100L)
+    for (elem in s) {
+      expect_true(elem >= 1 && elem <= 100)
+    }
+  }
+  for (seed in 4:5) {
+    s <- takeSample(data, TRUE, 20L, seed)
+    expect_equal(length(s), 20L)
+    for (elem in s) {
+      expect_true(elem >= 1 && elem <= 100)
+    }
+  }
+  for (seed in 4:5) {
+    s <- takeSample(data, TRUE, 100L, seed)
+    expect_equal(length(s), 100L)
+    # Chance of getting all distinct elements is astronomically low, so test we
+    # got < 100
+    expect_true(length(unique(s)) < 100L)
+  }
+  for (seed in 4:5) {
+    s <- takeSample(data, TRUE, 200L, seed)
+    expect_equal(length(s), 200L)
+    # Chance of getting all distinct elements is still quite low, so test we
+    # got < 100
+    expect_true(length(unique(s)) < 100L)
+  }
+})
+
+test_that("mapValues() on pairwise RDDs", {
+  multiples <- mapValues(intRdd, function(x) { x * 2 })
+  actual <- collect(multiples)
+  expected <- lapply(intPairs, function(x) {
+    list(x[[1]], x[[2]] * 2)
+  })
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+})
+
+test_that("flatMapValues() on pairwise RDDs", {
+  l <- parallelize(sc, list(list(1, c(1,2)), list(2, c(3,4))))
+  actual <- collect(flatMapValues(l, function(x) { x }))
+  expect_equal(actual, list(list(1,1), list(1,2), list(2,3), list(2,4)))
+  
+  # Generate x to x+1 for every value
+  actual <- collect(flatMapValues(intRdd, function(x) { x:(x + 1) }))
+  expect_equal(actual, 
+               list(list(1L, -1), list(1L, 0), list(2L, 100), list(2L, 101),
+                    list(2L, 1), list(2L, 2), list(1L, 200), list(1L, 201)))
+})
+
+test_that("reduceByKeyLocally() on PairwiseRDDs", {
+  pairs <- parallelize(sc, list(list(1, 2), list(1.1, 3), list(1, 4)), 2L)
+  actual <- reduceByKeyLocally(pairs, "+")
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(list(list(1, 6), list(1.1, 3))))
+
+  pairs <- parallelize(sc, list(list("abc", 1.2), list(1.1, 0), list("abc", 1.3),
+                                list("bb", 5)), 4L)
+  actual <- reduceByKeyLocally(pairs, "+")
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(list(list("abc", 2.5), list(1.1, 0), list("bb", 5))))
+})
+
+test_that("distinct() on RDDs", {
+  nums.rep2 <- rep(1:10, 2)
+  rdd.rep2 <- parallelize(sc, nums.rep2, 2L)
+  uniques <- distinct(rdd.rep2)
+  actual <- sort(unlist(collect(uniques)))
+  expect_equal(actual, nums)
+})
+
+test_that("maximum() on RDDs", {
+  max <- maximum(rdd)
+  expect_equal(max, 10)
+})
+
+test_that("minimum() on RDDs", {
+  min <- minimum(rdd)
+  expect_equal(min, 1)
+})
+
+test_that("sumRDD() on RDDs", {
+  sum <- sumRDD(rdd)
+  expect_equal(sum, 55)
+})
+
+test_that("keyBy on RDDs", {
+  func <- function(x) { x*x }
+  keys <- keyBy(rdd, func)
+  actual <- collect(keys)
+  expect_equal(actual, lapply(nums, function(x) { list(func(x), x) }))
+})
+
+test_that("repartition/coalesce on RDDs", {
+  rdd <- parallelize(sc, 1:20, 4L) # each partition contains 5 elements
+
+  # repartition
+  r1 <- repartition(rdd, 2)
+  expect_equal(numPartitions(r1), 2L)
+  count <- length(collectPartition(r1, 0L))
+  expect_true(count >= 8 && count <= 12)
+
+  r2 <- repartition(rdd, 6)
+  expect_equal(numPartitions(r2), 6L)
+  count <- length(collectPartition(r2, 0L))
+  expect_true(count >=0 && count <= 4)
+
+  # coalesce
+  r3 <- coalesce(rdd, 1)
+  expect_equal(numPartitions(r3), 1L)
+  count <- length(collectPartition(r3, 0L))
+  expect_equal(count, 20)
+})
+
+test_that("sortBy() on RDDs", {
+  sortedRdd <- sortBy(rdd, function(x) { x * x }, ascending = FALSE)
+  actual <- collect(sortedRdd)
+  expect_equal(actual, as.list(sort(nums, decreasing = TRUE)))
+
+  rdd2 <- parallelize(sc, sort(nums, decreasing = TRUE), 2L)
+  sortedRdd2 <- sortBy(rdd2, function(x) { x * x })
+  actual <- collect(sortedRdd2)
+  expect_equal(actual, as.list(nums))
+})
+
+test_that("takeOrdered() on RDDs", {
+  l <- list(10, 1, 2, 9, 3, 4, 5, 6, 7)
+  rdd <- parallelize(sc, l)
+  actual <- takeOrdered(rdd, 6L)
+  expect_equal(actual, as.list(sort(unlist(l)))[1:6])
+
+  l <- list("e", "d", "c", "d", "a")
+  rdd <- parallelize(sc, l)
+  actual <- takeOrdered(rdd, 3L)
+  expect_equal(actual, as.list(sort(unlist(l)))[1:3])
+})
+
+test_that("top() on RDDs", {
+  l <- list(10, 1, 2, 9, 3, 4, 5, 6, 7)
+  rdd <- parallelize(sc, l)
+  actual <- top(rdd, 6L)
+  expect_equal(actual, as.list(sort(unlist(l), decreasing = TRUE))[1:6])
+  
+  l <- list("e", "d", "c", "d", "a")
+  rdd <- parallelize(sc, l)
+  actual <- top(rdd, 3L)
+  expect_equal(actual, as.list(sort(unlist(l), decreasing = TRUE))[1:3])
+})
+
+test_that("fold() on RDDs", {
+  actual <- fold(rdd, 0, "+")
+  expect_equal(actual, Reduce("+", nums, 0))
+  
+  rdd <- parallelize(sc, list())
+  actual <- fold(rdd, 0, "+")
+  expect_equal(actual, 0)
+})
+
+test_that("aggregateRDD() on RDDs", {
+  rdd <- parallelize(sc, list(1, 2, 3, 4))
+  zeroValue <- list(0, 0)
+  seqOp <- function(x, y) { list(x[[1]] + y, x[[2]] + 1) }
+  combOp <- function(x, y) { list(x[[1]] + y[[1]], x[[2]] + y[[2]]) }
+  actual <- aggregateRDD(rdd, zeroValue, seqOp, combOp)
+  expect_equal(actual, list(10, 4))
+  
+  rdd <- parallelize(sc, list())
+  actual <- aggregateRDD(rdd, zeroValue, seqOp, combOp)
+  expect_equal(actual, list(0, 0))
+})
+
+test_that("zipWithUniqueId() on RDDs", {
+  rdd <- parallelize(sc, list("a", "b", "c", "d", "e"), 3L)
+  actual <- collect(zipWithUniqueId(rdd))
+  expected <- list(list("a", 0), list("b", 3), list("c", 1), 
+                   list("d", 4), list("e", 2))
+  expect_equal(actual, expected)
+  
+  rdd <- parallelize(sc, list("a", "b", "c", "d", "e"), 1L)
+  actual <- collect(zipWithUniqueId(rdd))
+  expected <- list(list("a", 0), list("b", 1), list("c", 2), 
+                   list("d", 3), list("e", 4))
+  expect_equal(actual, expected)
+})
+
+test_that("zipWithIndex() on RDDs", {
+  rdd <- parallelize(sc, list("a", "b", "c", "d", "e"), 3L)
+  actual <- collect(zipWithIndex(rdd))
+  expected <- list(list("a", 0), list("b", 1), list("c", 2), 
+                   list("d", 3), list("e", 4))
+  expect_equal(actual, expected)
+  
+  rdd <- parallelize(sc, list("a", "b", "c", "d", "e"), 1L)
+  actual <- collect(zipWithIndex(rdd))
+  expected <- list(list("a", 0), list("b", 1), list("c", 2), 
+                   list("d", 3), list("e", 4))
+  expect_equal(actual, expected)
+})
+
+test_that("glom() on RDD", {
+  rdd <- parallelize(sc, as.list(1:4), 2L)
+  actual <- collect(glom(rdd))
+  expect_equal(actual, list(list(1, 2), list(3, 4)))
+})
+
+test_that("keys() on RDDs", {
+  keys <- keys(intRdd)
+  actual <- collect(keys)
+  expect_equal(actual, lapply(intPairs, function(x) { x[[1]] }))
+})
+
+test_that("values() on RDDs", {
+  values <- values(intRdd)
+  actual <- collect(values)
+  expect_equal(actual, lapply(intPairs, function(x) { x[[2]] }))
+})
+
+test_that("pipeRDD() on RDDs", {
+  actual <- collect(pipeRDD(rdd, "more"))
+  expected <- as.list(as.character(1:10))
+  expect_equal(actual, expected)
+  
+  trailed.rdd <- parallelize(sc, c("1", "", "2\n", "3\n\r\n"))
+  actual <- collect(pipeRDD(trailed.rdd, "sort"))
+  expected <- list("", "1", "2", "3")
+  expect_equal(actual, expected)
+  
+  rev.nums <- 9:0
+  rev.rdd <- parallelize(sc, rev.nums, 2L)
+  actual <- collect(pipeRDD(rev.rdd, "sort"))
+  expected <- as.list(as.character(c(5:9, 0:4)))
+  expect_equal(actual, expected)
+})
+
+test_that("zipRDD() on RDDs", {
+  rdd1 <- parallelize(sc, 0:4, 2)
+  rdd2 <- parallelize(sc, 1000:1004, 2)
+  actual <- collect(zipRDD(rdd1, rdd2))
+  expect_equal(actual,
+               list(list(0, 1000), list(1, 1001), list(2, 1002), list(3, 1003), list(4, 1004)))
+  
+  mockFile = c("Spark is pretty.", "Spark is awesome.")
+  fileName <- tempfile(pattern="spark-test", fileext=".tmp")
+  writeLines(mockFile, fileName)
+  
+  rdd <- textFile(sc, fileName, 1)
+  actual <- collect(zipRDD(rdd, rdd))
+  expected <- lapply(mockFile, function(x) { list(x ,x) })
+  expect_equal(actual, expected)
+
+  rdd1 <- parallelize(sc, 0:1, 1)
+  actual <- collect(zipRDD(rdd1, rdd))
+  expected <- lapply(0:1, function(x) { list(x, mockFile[x + 1]) })
+  expect_equal(actual, expected)
+
+  rdd1 <- map(rdd, function(x) { x })
+  actual <- collect(zipRDD(rdd, rdd1))
+  expected <- lapply(mockFile, function(x) { list(x, x) })
+  expect_equal(actual, expected)
+ 
+  unlink(fileName)
+})
+
+test_that("join() on pairwise RDDs", {
+  rdd1 <- parallelize(sc, list(list(1,1), list(2,4)))
+  rdd2 <- parallelize(sc, list(list(1,2), list(1,3)))
+  actual <- collect(join(rdd1, rdd2, 2L))
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(list(list(1, list(1, 2)), list(1, list(1, 3)))))
+
+  rdd1 <- parallelize(sc, list(list("a",1), list("b",4)))
+  rdd2 <- parallelize(sc, list(list("a",2), list("a",3)))
+  actual <- collect(join(rdd1, rdd2, 2L))
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(list(list("a", list(1, 2)), list("a", list(1, 3)))))
+
+  rdd1 <- parallelize(sc, list(list(1,1), list(2,2)))
+  rdd2 <- parallelize(sc, list(list(3,3), list(4,4)))
+  actual <- collect(join(rdd1, rdd2, 2L))
+  expect_equal(actual, list())
+
+  rdd1 <- parallelize(sc, list(list("a",1), list("b",2)))
+  rdd2 <- parallelize(sc, list(list("c",3), list("d",4)))
+  actual <- collect(join(rdd1, rdd2, 2L))
+  expect_equal(actual, list())
+})
+
+test_that("leftOuterJoin() on pairwise RDDs", {
+  rdd1 <- parallelize(sc, list(list(1,1), list(2,4)))
+  rdd2 <- parallelize(sc, list(list(1,2), list(1,3)))
+  actual <- collect(leftOuterJoin(rdd1, rdd2, 2L))
+  expected <- list(list(1, list(1, 2)), list(1, list(1, 3)), list(2, list(4, NULL)))
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(expected))
+
+  rdd1 <- parallelize(sc, list(list("a",1), list("b",4)))
+  rdd2 <- parallelize(sc, list(list("a",2), list("a",3)))
+  actual <- collect(leftOuterJoin(rdd1, rdd2, 2L))
+  expected <-  list(list("b", list(4, NULL)), list("a", list(1, 2)), list("a", list(1, 3)))
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(expected))
+
+  rdd1 <- parallelize(sc, list(list(1,1), list(2,2)))
+  rdd2 <- parallelize(sc, list(list(3,3), list(4,4)))
+  actual <- collect(leftOuterJoin(rdd1, rdd2, 2L))
+  expected <- list(list(1, list(1, NULL)), list(2, list(2, NULL)))
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(expected))
+
+  rdd1 <- parallelize(sc, list(list("a",1), list("b",2)))
+  rdd2 <- parallelize(sc, list(list("c",3), list("d",4)))
+  actual <- collect(leftOuterJoin(rdd1, rdd2, 2L))
+  expected <- list(list("b", list(2, NULL)), list("a", list(1, NULL)))
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(expected))
+})
+
+test_that("rightOuterJoin() on pairwise RDDs", {
+  rdd1 <- parallelize(sc, list(list(1,2), list(1,3)))
+  rdd2 <- parallelize(sc, list(list(1,1), list(2,4)))
+  actual <- collect(rightOuterJoin(rdd1, rdd2, 2L))
+  expected <- list(list(1, list(2, 1)), list(1, list(3, 1)), list(2, list(NULL, 4)))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+
+  rdd1 <- parallelize(sc, list(list("a",2), list("a",3)))
+  rdd2 <- parallelize(sc, list(list("a",1), list("b",4)))
+  actual <- collect(rightOuterJoin(rdd1, rdd2, 2L))
+  expected <- list(list("b", list(NULL, 4)), list("a", list(2, 1)), list("a", list(3, 1)))
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(expected))
+
+  rdd1 <- parallelize(sc, list(list(1,1), list(2,2)))
+  rdd2 <- parallelize(sc, list(list(3,3), list(4,4)))
+  actual <- collect(rightOuterJoin(rdd1, rdd2, 2L))
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(list(list(3, list(NULL, 3)), list(4, list(NULL, 4)))))
+
+  rdd1 <- parallelize(sc, list(list("a",1), list("b",2)))
+  rdd2 <- parallelize(sc, list(list("c",3), list("d",4)))
+  actual <- collect(rightOuterJoin(rdd1, rdd2, 2L))
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(list(list("d", list(NULL, 4)), list("c", list(NULL, 3)))))
+})
+
+test_that("fullOuterJoin() on pairwise RDDs", {
+  rdd1 <- parallelize(sc, list(list(1,2), list(1,3), list(3,3)))
+  rdd2 <- parallelize(sc, list(list(1,1), list(2,4)))
+  actual <- collect(fullOuterJoin(rdd1, rdd2, 2L))
+  expected <- list(list(1, list(2, 1)), list(1, list(3, 1)), list(2, list(NULL, 4)), list(3, list(3, NULL)))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+
+  rdd1 <- parallelize(sc, list(list("a",2), list("a",3), list("c", 1)))
+  rdd2 <- parallelize(sc, list(list("a",1), list("b",4)))
+  actual <- collect(fullOuterJoin(rdd1, rdd2, 2L))
+  expected <- list(list("b", list(NULL, 4)), list("a", list(2, 1)), list("a", list(3, 1)), list("c", list(1, NULL)))
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(expected))
+
+  rdd1 <- parallelize(sc, list(list(1,1), list(2,2)))
+  rdd2 <- parallelize(sc, list(list(3,3), list(4,4)))
+  actual <- collect(fullOuterJoin(rdd1, rdd2, 2L))
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(list(list(1, list(1, NULL)), list(2, list(2, NULL)), list(3, list(NULL, 3)), list(4, list(NULL, 4)))))
+
+  rdd1 <- parallelize(sc, list(list("a",1), list("b",2)))
+  rdd2 <- parallelize(sc, list(list("c",3), list("d",4)))
+  actual <- collect(fullOuterJoin(rdd1, rdd2, 2L))
+  expect_equal(sortKeyValueList(actual),
+               sortKeyValueList(list(list("a", list(1, NULL)), list("b", list(2, NULL)), list("d", list(NULL, 4)), list("c", list(NULL, 3)))))
+})
+
+test_that("sortByKey() on pairwise RDDs", {
+  numPairsRdd <- map(rdd, function(x) { list (x, x) })
+  sortedRdd <- sortByKey(numPairsRdd, ascending = FALSE)
+  actual <- collect(sortedRdd)
+  numPairs <- lapply(nums, function(x) { list (x, x) })
+  expect_equal(actual, sortKeyValueList(numPairs, decreasing = TRUE))
+
+  rdd2 <- parallelize(sc, sort(nums, decreasing = TRUE), 2L)
+  numPairsRdd2 <- map(rdd2, function(x) { list (x, x) })
+  sortedRdd2 <- sortByKey(numPairsRdd2)
+  actual <- collect(sortedRdd2)
+  expect_equal(actual, numPairs)
+
+  # sort by string keys
+  l <- list(list("a", 1), list("b", 2), list("1", 3), list("d", 4), list("2", 5))
+  rdd3 <- parallelize(sc, l, 2L)
+  sortedRdd3 <- sortByKey(rdd3)
+  actual <- collect(sortedRdd3)
+  expect_equal(actual, list(list("1", 3), list("2", 5), list("a", 1), list("b", 2), list("d", 4)))
+  
+  # test on the boundary cases
+  
+  # boundary case 1: the RDD to be sorted has only 1 partition
+  rdd4 <- parallelize(sc, l, 1L)
+  sortedRdd4 <- sortByKey(rdd4)
+  actual <- collect(sortedRdd4)
+  expect_equal(actual, list(list("1", 3), list("2", 5), list("a", 1), list("b", 2), list("d", 4)))
+
+  # boundary case 2: the sorted RDD has only 1 partition
+  rdd5 <- parallelize(sc, l, 2L)
+  sortedRdd5 <- sortByKey(rdd5, numPartitions = 1L)
+  actual <- collect(sortedRdd5)
+  expect_equal(actual, list(list("1", 3), list("2", 5), list("a", 1), list("b", 2), list("d", 4)))
+
+  # boundary case 3: the RDD to be sorted has only 1 element
+  l2 <- list(list("a", 1))
+  rdd6 <- parallelize(sc, l2, 2L)
+  sortedRdd6 <- sortByKey(rdd6)
+  actual <- collect(sortedRdd6)
+  expect_equal(actual, l2)
+
+  # boundary case 4: the RDD to be sorted has 0 element
+  l3 <- list()
+  rdd7 <- parallelize(sc, l3, 2L)
+  sortedRdd7 <- sortByKey(rdd7)
+  actual <- collect(sortedRdd7)
+  expect_equal(actual, l3)  
+})
+
+test_that("collectAsMap() on a pairwise RDD", {
+  rdd <- parallelize(sc, list(list(1, 2), list(3, 4)))
+  vals <- collectAsMap(rdd)
+  expect_equal(vals, list(`1` = 2, `3` = 4))
+
+  rdd <- parallelize(sc, list(list("a", 1), list("b", 2)))
+  vals <- collectAsMap(rdd)
+  expect_equal(vals, list(a = 1, b = 2))
+ 
+  rdd <- parallelize(sc, list(list(1.1, 2.2), list(1.2, 2.4)))
+  vals <- collectAsMap(rdd)
+  expect_equal(vals, list(`1.1` = 2.2, `1.2` = 2.4))
+ 
+  rdd <- parallelize(sc, list(list(1, "a"), list(2, "b")))
+  vals <- collectAsMap(rdd)
+  expect_equal(vals, list(`1` = "a", `2` = "b"))
+})
diff --git a/R/pkg/inst/tests/test_shuffle.R b/R/pkg/inst/tests/test_shuffle.R
new file mode 100644
index 0000000000000..d1da8232aea81
--- /dev/null
+++ b/R/pkg/inst/tests/test_shuffle.R
@@ -0,0 +1,209 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+context("partitionBy, groupByKey, reduceByKey etc.")
+
+# JavaSparkContext handle
+sc <- sparkR.init()
+
+# Data
+intPairs <- list(list(1L, -1), list(2L, 100), list(2L, 1), list(1L, 200))
+intRdd <- parallelize(sc, intPairs, 2L)
+
+doublePairs <- list(list(1.5, -1), list(2.5, 100), list(2.5, 1), list(1.5, 200))
+doubleRdd <- parallelize(sc, doublePairs, 2L)
+
+numPairs <- list(list(1L, 100), list(2L, 200), list(4L, -1), list(3L, 1),
+                 list(3L, 0))
+numPairsRdd <- parallelize(sc, numPairs, length(numPairs))
+
+strList <- list("Dexter Morgan: Blood. Sometimes it sets my teeth on edge and ",
+                "Dexter Morgan: Harry and Dorris Morgan did a wonderful job ")
+strListRDD <- parallelize(sc, strList, 4)
+
+test_that("groupByKey for integers", {
+  grouped <- groupByKey(intRdd, 2L)
+
+  actual <- collect(grouped)
+
+  expected <- list(list(2L, list(100, 1)), list(1L, list(-1, 200)))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+})
+
+test_that("groupByKey for doubles", {
+  grouped <- groupByKey(doubleRdd, 2L)
+
+  actual <- collect(grouped)
+
+  expected <- list(list(1.5, list(-1, 200)), list(2.5, list(100, 1)))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+})
+
+test_that("reduceByKey for ints", {
+  reduced <- reduceByKey(intRdd, "+", 2L)
+
+  actual <- collect(reduced)
+
+  expected <- list(list(2L, 101), list(1L, 199))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+})
+
+test_that("reduceByKey for doubles", {
+  reduced <- reduceByKey(doubleRdd, "+", 2L)
+  actual <- collect(reduced)
+
+  expected <- list(list(1.5, 199), list(2.5, 101))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+})
+
+test_that("combineByKey for ints", {
+  reduced <- combineByKey(intRdd, function(x) { x }, "+", "+", 2L)
+
+  actual <- collect(reduced)
+
+  expected <- list(list(2L, 101), list(1L, 199))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+})
+
+test_that("combineByKey for doubles", {
+  reduced <- combineByKey(doubleRdd, function(x) { x }, "+", "+", 2L)
+  actual <- collect(reduced)
+
+  expected <- list(list(1.5, 199), list(2.5, 101))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+})
+
+test_that("aggregateByKey", {
+  # test aggregateByKey for int keys
+  rdd <- parallelize(sc, list(list(1, 1), list(1, 2), list(2, 3), list(2, 4)))
+
+  zeroValue <- list(0, 0)
+  seqOp <- function(x, y) { list(x[[1]] + y, x[[2]] + 1) }
+  combOp <- function(x, y) { list(x[[1]] + y[[1]], x[[2]] + y[[2]]) }
+  aggregatedRDD <- aggregateByKey(rdd, zeroValue, seqOp, combOp, 2L)   
+  
+  actual <- collect(aggregatedRDD)
+  
+  expected <- list(list(1, list(3, 2)), list(2, list(7, 2)))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+
+  # test aggregateByKey for string keys
+  rdd <- parallelize(sc, list(list("a", 1), list("a", 2), list("b", 3), list("b", 4)))
+  
+  zeroValue <- list(0, 0)
+  seqOp <- function(x, y) { list(x[[1]] + y, x[[2]] + 1) }
+  combOp <- function(x, y) { list(x[[1]] + y[[1]], x[[2]] + y[[2]]) }
+  aggregatedRDD <- aggregateByKey(rdd, zeroValue, seqOp, combOp, 2L)   
+
+  actual <- collect(aggregatedRDD)
+  
+  expected <- list(list("a", list(3, 2)), list("b", list(7, 2)))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+})
+
+test_that("foldByKey", {  
+  # test foldByKey for int keys
+  folded <- foldByKey(intRdd, 0, "+", 2L)
+  
+  actual <- collect(folded)
+  
+  expected <- list(list(2L, 101), list(1L, 199))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+
+  # test foldByKey for double keys
+  folded <- foldByKey(doubleRdd, 0, "+", 2L)
+  
+  actual <- collect(folded)
+
+  expected <- list(list(1.5, 199), list(2.5, 101))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+
+  # test foldByKey for string keys
+  stringKeyPairs <- list(list("a", -1), list("b", 100), list("b", 1), list("a", 200))
+  
+  stringKeyRDD <- parallelize(sc, stringKeyPairs)
+  folded <- foldByKey(stringKeyRDD, 0, "+", 2L)
+  
+  actual <- collect(folded)
+  
+  expected <- list(list("b", 101), list("a", 199))
+  expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
+  
+  # test foldByKey for empty pair RDD
+  rdd <- parallelize(sc, list())
+  folded <- foldByKey(rdd, 0, "+", 2L)
+  actual <- collect(folded)
+  expected <- list()
+  expect_equal(actual, expected)
+
+  # test foldByKey for RDD with only 1 pair
+  rdd <- parallelize(sc,  list(list(1, 1)))
+  folded <- foldByKey(rdd, 0, "+", 2L)
+  actual <- collect(folded)
+  expected <- list(list(1, 1))
+  expect_equal(actual, expected)
+})
+
+test_that("partitionBy() partitions data correctly", {
+  # Partition by magnitude
+  partitionByMagnitude <- function(key) { if (key >= 3) 1 else 0 }
+
+  resultRDD <- partitionBy(numPairsRdd, 2L, partitionByMagnitude)
+
+  expected_first <- list(list(1, 100), list(2, 200)) # key < 3
+  expected_second <- list(list(4, -1), list(3, 1), list(3, 0)) # key >= 3
+  actual_first <- collectPartition(resultRDD, 0L)
+  actual_second <- collectPartition(resultRDD, 1L)
+
+  expect_equal(sortKeyValueList(actual_first), sortKeyValueList(expected_first))
+  expect_equal(sortKeyValueList(actual_second), sortKeyValueList(expected_second))
+})
+
+test_that("partitionBy works with dependencies", {
+  kOne <- 1
+  partitionByParity <- function(key) { if (key %% 2 == kOne) 7 else 4 }
+
+  # Partition by parity
+  resultRDD <- partitionBy(numPairsRdd, numPartitions = 2L, partitionByParity)
+
+  # keys even; 100 %% 2 == 0
+  expected_first <- list(list(2, 200), list(4, -1))
+  # keys odd; 3 %% 2 == 1
+  expected_second <- list(list(1, 100), list(3, 1), list(3, 0))
+  actual_first <- collectPartition(resultRDD, 0L)
+  actual_second <- collectPartition(resultRDD, 1L)
+
+  expect_equal(sortKeyValueList(actual_first), sortKeyValueList(expected_first))
+  expect_equal(sortKeyValueList(actual_second), sortKeyValueList(expected_second))
+})
+
+test_that("test partitionBy with string keys", {
+  words <- flatMap(strListRDD, function(line) { strsplit(line, " ")[[1]] })
+  wordCount <- lapply(words, function(word) { list(word, 1L) })
+
+  resultRDD <- partitionBy(wordCount, 2L)
+  expected_first <- list(list("Dexter", 1), list("Dexter", 1))
+  expected_second <- list(list("and", 1), list("and", 1))
+
+  actual_first <- Filter(function(item) { item[[1]] == "Dexter" },
+                         collectPartition(resultRDD, 0L))
+  actual_second <- Filter(function(item) { item[[1]] == "and" },
+                          collectPartition(resultRDD, 1L))
+
+  expect_equal(sortKeyValueList(actual_first), sortKeyValueList(expected_first))
+  expect_equal(sortKeyValueList(actual_second), sortKeyValueList(expected_second))
+})
diff --git a/R/pkg/inst/tests/test_sparkSQL.R b/R/pkg/inst/tests/test_sparkSQL.R
new file mode 100644
index 0000000000000..cf5cf6d1692af
--- /dev/null
+++ b/R/pkg/inst/tests/test_sparkSQL.R
@@ -0,0 +1,695 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+library(testthat)
+
+context("SparkSQL functions")
+
+# Tests for SparkSQL functions in SparkR
+
+sc <- sparkR.init()
+
+sqlCtx <- sparkRSQL.init(sc)
+
+mockLines <- c("{\"name\":\"Michael\"}",
+               "{\"name\":\"Andy\", \"age\":30}",
+               "{\"name\":\"Justin\", \"age\":19}")
+jsonPath <- tempfile(pattern="sparkr-test", fileext=".tmp")
+parquetPath <- tempfile(pattern="sparkr-test", fileext=".parquet")
+writeLines(mockLines, jsonPath)
+
+test_that("infer types", {
+  expect_equal(infer_type(1L), "integer")
+  expect_equal(infer_type(1.0), "double")
+  expect_equal(infer_type("abc"), "string")
+  expect_equal(infer_type(TRUE), "boolean")
+  expect_equal(infer_type(as.Date("2015-03-11")), "date")
+  expect_equal(infer_type(as.POSIXlt("2015-03-11 12:13:04.043")), "timestamp")
+  expect_equal(infer_type(c(1L, 2L)),
+               list(type = 'array', elementType = "integer", containsNull = TRUE))
+  expect_equal(infer_type(list(1L, 2L)),
+               list(type = 'array', elementType = "integer", containsNull = TRUE))
+  expect_equal(infer_type(list(a = 1L, b = "2")),
+               list(type = "struct",
+                    fields = list(list(name = "a", type = "integer", nullable = TRUE),
+                                  list(name = "b", type = "string", nullable = TRUE))))
+  e <- new.env()
+  assign("a", 1L, envir = e)
+  expect_equal(infer_type(e),
+               list(type = "map", keyType = "string", valueType = "integer",
+                    valueContainsNull = TRUE))
+})
+
+test_that("create DataFrame from RDD", {
+  rdd <- lapply(parallelize(sc, 1:10), function(x) { list(x, as.character(x)) })
+  df <- createDataFrame(sqlCtx, rdd, list("a", "b"))
+  expect_true(inherits(df, "DataFrame"))
+  expect_true(count(df) == 10)
+  expect_equal(columns(df), c("a", "b"))
+  expect_equal(dtypes(df), list(c("a", "int"), c("b", "string")))
+
+  df <- createDataFrame(sqlCtx, rdd)
+  expect_true(inherits(df, "DataFrame"))
+  expect_equal(columns(df), c("_1", "_2"))
+
+  fields <- list(list(name = "a", type = "integer", nullable = TRUE),
+                 list(name = "b", type = "string", nullable = TRUE))
+  schema <- list(type = "struct", fields = fields)
+  df <- createDataFrame(sqlCtx, rdd, schema)
+  expect_true(inherits(df, "DataFrame"))
+  expect_equal(columns(df), c("a", "b"))
+  expect_equal(dtypes(df), list(c("a", "int"), c("b", "string")))
+
+  rdd <- lapply(parallelize(sc, 1:10), function(x) { list(a = x, b = as.character(x)) })
+  df <- createDataFrame(sqlCtx, rdd)
+  expect_true(inherits(df, "DataFrame"))
+  expect_true(count(df) == 10)
+  expect_equal(columns(df), c("a", "b"))
+  expect_equal(dtypes(df), list(c("a", "int"), c("b", "string")))
+})
+
+test_that("toDF", {
+  rdd <- lapply(parallelize(sc, 1:10), function(x) { list(x, as.character(x)) })
+  df <- toDF(rdd, list("a", "b"))
+  expect_true(inherits(df, "DataFrame"))
+  expect_true(count(df) == 10)
+  expect_equal(columns(df), c("a", "b"))
+  expect_equal(dtypes(df), list(c("a", "int"), c("b", "string")))
+
+  df <- toDF(rdd)
+  expect_true(inherits(df, "DataFrame"))
+  expect_equal(columns(df), c("_1", "_2"))
+
+  fields <- list(list(name = "a", type = "integer", nullable = TRUE),
+                 list(name = "b", type = "string", nullable = TRUE))
+  schema <- list(type = "struct", fields = fields)
+  df <- toDF(rdd, schema)
+  expect_true(inherits(df, "DataFrame"))
+  expect_equal(columns(df), c("a", "b"))
+  expect_equal(dtypes(df), list(c("a", "int"), c("b", "string")))
+
+  rdd <- lapply(parallelize(sc, 1:10), function(x) { list(a = x, b = as.character(x)) })
+  df <- toDF(rdd)
+  expect_true(inherits(df, "DataFrame"))
+  expect_true(count(df) == 10)
+  expect_equal(columns(df), c("a", "b"))
+  expect_equal(dtypes(df), list(c("a", "int"), c("b", "string")))
+})
+
+test_that("create DataFrame from list or data.frame", {
+  l <- list(list(1, 2), list(3, 4))
+  df <- createDataFrame(sqlCtx, l, c("a", "b"))
+  expect_equal(columns(df), c("a", "b"))
+
+  l <- list(list(a=1, b=2), list(a=3, b=4))
+  df <- createDataFrame(sqlCtx, l)
+  expect_equal(columns(df), c("a", "b"))
+
+  a <- 1:3
+  b <- c("a", "b", "c")
+  ldf <- data.frame(a, b)
+  df <- createDataFrame(sqlCtx, ldf)
+  expect_equal(columns(df), c("a", "b"))
+  expect_equal(dtypes(df), list(c("a", "int"), c("b", "string")))
+  expect_equal(count(df), 3)
+  ldf2 <- collect(df)
+  expect_equal(ldf$a, ldf2$a)
+})
+
+test_that("create DataFrame with different data types", {
+  l <- list(a = 1L, b = 2, c = TRUE, d = "ss", e = as.Date("2012-12-13"),
+            f = as.POSIXct("2015-03-15 12:13:14.056"))
+  df <- createDataFrame(sqlCtx, list(l))
+  expect_equal(dtypes(df), list(c("a", "int"), c("b", "double"), c("c", "boolean"),
+                                c("d", "string"), c("e", "date"), c("f", "timestamp")))
+  expect_equal(count(df), 1)
+  expect_equal(collect(df), data.frame(l, stringsAsFactors = FALSE))
+})
+
+# TODO: enable this test after fix serialization for nested object
+#test_that("create DataFrame with nested array and struct", {
+#  e <- new.env()
+#  assign("n", 3L, envir = e)
+#  l <- list(1:10, list("a", "b"), e, list(a="aa", b=3L))
+#  df <- createDataFrame(sqlCtx, list(l), c("a", "b", "c", "d"))
+#  expect_equal(dtypes(df), list(c("a", "array<int>"), c("b", "array<string>"),
+#                                c("c", "map<string,int>"), c("d", "struct<a:string,b:int>")))
+#  expect_equal(count(df), 1)
+#  ldf <- collect(df)
+#  expect_equal(ldf[1,], l[[1]])
+#})
+
+test_that("jsonFile() on a local file returns a DataFrame", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  expect_true(inherits(df, "DataFrame"))
+  expect_true(count(df) == 3)
+})
+
+test_that("jsonRDD() on a RDD with json string", {
+  rdd <- parallelize(sc, mockLines)
+  expect_true(count(rdd) == 3)
+  df <- jsonRDD(sqlCtx, rdd)
+  expect_true(inherits(df, "DataFrame"))
+  expect_true(count(df) == 3)
+
+  rdd2 <- flatMap(rdd, function(x) c(x, x))
+  df <- jsonRDD(sqlCtx, rdd2)
+  expect_true(inherits(df, "DataFrame"))
+  expect_true(count(df) == 6)
+})
+
+test_that("test cache, uncache and clearCache", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  registerTempTable(df, "table1")
+  cacheTable(sqlCtx, "table1")
+  uncacheTable(sqlCtx, "table1")
+  clearCache(sqlCtx)
+  dropTempTable(sqlCtx, "table1")
+})
+
+test_that("test tableNames and tables", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  registerTempTable(df, "table1")
+  expect_true(length(tableNames(sqlCtx)) == 1)
+  df <- tables(sqlCtx)
+  expect_true(count(df) == 1)
+  dropTempTable(sqlCtx, "table1")
+})
+
+test_that("registerTempTable() results in a queryable table and sql() results in a new DataFrame", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  registerTempTable(df, "table1")
+  newdf <- sql(sqlCtx, "SELECT * FROM table1 where name = 'Michael'")
+  expect_true(inherits(newdf, "DataFrame"))
+  expect_true(count(newdf) == 1)
+  dropTempTable(sqlCtx, "table1")
+})
+
+test_that("insertInto() on a registered table", {
+  df <- loadDF(sqlCtx, jsonPath, "json")
+  saveDF(df, parquetPath, "parquet", "overwrite")
+  dfParquet <- loadDF(sqlCtx, parquetPath, "parquet")
+
+  lines <- c("{\"name\":\"Bob\", \"age\":24}",
+             "{\"name\":\"James\", \"age\":35}")
+  jsonPath2 <- tempfile(pattern="jsonPath2", fileext=".tmp")
+  parquetPath2 <- tempfile(pattern = "parquetPath2", fileext = ".parquet")
+  writeLines(lines, jsonPath2)
+  df2 <- loadDF(sqlCtx, jsonPath2, "json")
+  saveDF(df2, parquetPath2, "parquet", "overwrite")
+  dfParquet2 <- loadDF(sqlCtx, parquetPath2, "parquet")
+
+  registerTempTable(dfParquet, "table1")
+  insertInto(dfParquet2, "table1")
+  expect_true(count(sql(sqlCtx, "select * from table1")) == 5)
+  expect_true(first(sql(sqlCtx, "select * from table1 order by age"))$name == "Michael")
+  dropTempTable(sqlCtx, "table1")
+
+  registerTempTable(dfParquet, "table1")
+  insertInto(dfParquet2, "table1", overwrite = TRUE)
+  expect_true(count(sql(sqlCtx, "select * from table1")) == 2)
+  expect_true(first(sql(sqlCtx, "select * from table1 order by age"))$name == "Bob")
+  dropTempTable(sqlCtx, "table1")
+})
+
+test_that("table() returns a new DataFrame", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  registerTempTable(df, "table1")
+  tabledf <- table(sqlCtx, "table1")
+  expect_true(inherits(tabledf, "DataFrame"))
+  expect_true(count(tabledf) == 3)
+  dropTempTable(sqlCtx, "table1")
+})
+
+test_that("toRDD() returns an RRDD", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  testRDD <- toRDD(df)
+  expect_true(inherits(testRDD, "RDD"))
+  expect_true(count(testRDD) == 3)
+})
+
+test_that("union on two RDDs created from DataFrames returns an RRDD", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  RDD1 <- toRDD(df)
+  RDD2 <- toRDD(df)
+  unioned <- unionRDD(RDD1, RDD2)
+  expect_true(inherits(unioned, "RDD"))
+  expect_true(SparkR:::getSerializedMode(unioned) == "byte")
+  expect_true(collect(unioned)[[2]]$name == "Andy")
+})
+
+test_that("union on mixed serialization types correctly returns a byte RRDD", {
+  # Byte RDD
+  nums <- 1:10
+  rdd <- parallelize(sc, nums, 2L)
+
+  # String RDD
+  textLines <- c("Michael",
+                 "Andy, 30",
+                 "Justin, 19")
+  textPath <- tempfile(pattern="sparkr-textLines", fileext=".tmp")
+  writeLines(textLines, textPath)
+  textRDD <- textFile(sc, textPath)
+
+  df <- jsonFile(sqlCtx, jsonPath)
+  dfRDD <- toRDD(df)
+
+  unionByte <- unionRDD(rdd, dfRDD)
+  expect_true(inherits(unionByte, "RDD"))
+  expect_true(SparkR:::getSerializedMode(unionByte) == "byte")
+  expect_true(collect(unionByte)[[1]] == 1)
+  expect_true(collect(unionByte)[[12]]$name == "Andy")
+
+  unionString <- unionRDD(textRDD, dfRDD)
+  expect_true(inherits(unionString, "RDD"))
+  expect_true(SparkR:::getSerializedMode(unionString) == "byte")
+  expect_true(collect(unionString)[[1]] == "Michael")
+  expect_true(collect(unionString)[[5]]$name == "Andy")
+})
+
+test_that("objectFile() works with row serialization", {
+  objectPath <- tempfile(pattern="spark-test", fileext=".tmp")
+  df <- jsonFile(sqlCtx, jsonPath)
+  dfRDD <- toRDD(df)
+  saveAsObjectFile(coalesce(dfRDD, 1L), objectPath)
+  objectIn <- objectFile(sc, objectPath)
+
+  expect_true(inherits(objectIn, "RDD"))
+  expect_equal(SparkR:::getSerializedMode(objectIn), "byte")
+  expect_equal(collect(objectIn)[[2]]$age, 30)
+})
+
+test_that("lapply() on a DataFrame returns an RDD with the correct columns", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  testRDD <- lapply(df, function(row) {
+    row$newCol <- row$age + 5
+    row
+    })
+  expect_true(inherits(testRDD, "RDD"))
+  collected <- collect(testRDD)
+  expect_true(collected[[1]]$name == "Michael")
+  expect_true(collected[[2]]$newCol == "35")
+})
+
+test_that("collect() returns a data.frame", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  rdf <- collect(df)
+  expect_true(is.data.frame(rdf))
+  expect_true(names(rdf)[1] == "age")
+  expect_true(nrow(rdf) == 3)
+  expect_true(ncol(rdf) == 2)
+})
+
+test_that("limit() returns DataFrame with the correct number of rows", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  dfLimited <- limit(df, 2)
+  expect_true(inherits(dfLimited, "DataFrame"))
+  expect_true(count(dfLimited) == 2)
+})
+
+test_that("collect() and take() on a DataFrame return the same number of rows and columns", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  expect_true(nrow(collect(df)) == nrow(take(df, 10)))
+  expect_true(ncol(collect(df)) == ncol(take(df, 10)))
+})
+
+test_that("multiple pipeline transformations starting with a DataFrame result in an RDD with the correct values", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  first <- lapply(df, function(row) {
+    row$age <- row$age + 5
+    row
+  })
+  second <- lapply(first, function(row) {
+    row$testCol <- if (row$age == 35 && !is.na(row$age)) TRUE else FALSE
+    row
+  })
+  expect_true(inherits(second, "RDD"))
+  expect_true(count(second) == 3)
+  expect_true(collect(second)[[2]]$age == 35)
+  expect_true(collect(second)[[2]]$testCol)
+  expect_false(collect(second)[[3]]$testCol)
+})
+
+test_that("cache(), persist(), and unpersist() on a DataFrame", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  expect_false(df@env$isCached)
+  cache(df)
+  expect_true(df@env$isCached)
+
+  unpersist(df)
+  expect_false(df@env$isCached)
+
+  persist(df, "MEMORY_AND_DISK")
+  expect_true(df@env$isCached)
+
+  unpersist(df)
+  expect_false(df@env$isCached)
+
+  # make sure the data is collectable
+  expect_true(is.data.frame(collect(df)))
+})
+
+test_that("schema(), dtypes(), columns(), names() return the correct values/format", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  testSchema <- schema(df)
+  expect_true(length(testSchema$fields()) == 2)
+  expect_true(testSchema$fields()[[1]]$dataType.toString() == "LongType")
+  expect_true(testSchema$fields()[[2]]$dataType.simpleString() == "string")
+  expect_true(testSchema$fields()[[1]]$name() == "age")
+
+  testTypes <- dtypes(df)
+  expect_true(length(testTypes[[1]]) == 2)
+  expect_true(testTypes[[1]][1] == "age")
+
+  testCols <- columns(df)
+  expect_true(length(testCols) == 2)
+  expect_true(testCols[2] == "name")
+
+  testNames <- names(df)
+  expect_true(length(testNames) == 2)
+  expect_true(testNames[2] == "name")
+})
+
+test_that("head() and first() return the correct data", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  testHead <- head(df)
+  expect_true(nrow(testHead) == 3)
+  expect_true(ncol(testHead) == 2)
+
+  testHead2 <- head(df, 2)
+  expect_true(nrow(testHead2) == 2)
+  expect_true(ncol(testHead2) == 2)
+
+  testFirst <- first(df)
+  expect_true(nrow(testFirst) == 1)
+})
+
+test_that("distinct() on DataFrames", {
+  lines <- c("{\"name\":\"Michael\"}",
+             "{\"name\":\"Andy\", \"age\":30}",
+             "{\"name\":\"Justin\", \"age\":19}",
+             "{\"name\":\"Justin\", \"age\":19}")
+  jsonPathWithDup <- tempfile(pattern="sparkr-test", fileext=".tmp")
+  writeLines(lines, jsonPathWithDup)
+
+  df <- jsonFile(sqlCtx, jsonPathWithDup)
+  uniques <- distinct(df)
+  expect_true(inherits(uniques, "DataFrame"))
+  expect_true(count(uniques) == 3)
+})
+
+test_that("sampleDF on a DataFrame", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  sampled <- sampleDF(df, FALSE, 1.0)
+  expect_equal(nrow(collect(sampled)), count(df))
+  expect_true(inherits(sampled, "DataFrame"))
+  sampled2 <- sampleDF(df, FALSE, 0.1)
+  expect_true(count(sampled2) < 3)
+})
+
+test_that("select operators", {
+  df <- select(jsonFile(sqlCtx, jsonPath), "name", "age")
+  expect_true(inherits(df$name, "Column"))
+  expect_true(inherits(df[[2]], "Column"))
+  expect_true(inherits(df[["age"]], "Column"))
+
+  expect_true(inherits(df[,1], "DataFrame"))
+  expect_equal(columns(df[,1]), c("name"))
+  expect_equal(columns(df[,"age"]), c("age"))
+  df2 <- df[,c("age", "name")]
+  expect_true(inherits(df2, "DataFrame"))
+  expect_equal(columns(df2), c("age", "name"))
+
+  df$age2 <- df$age
+  expect_equal(columns(df), c("name", "age", "age2"))
+  expect_equal(count(where(df, df$age2 == df$age)), 2)
+  df$age2 <- df$age * 2
+  expect_equal(columns(df), c("name", "age", "age2"))
+  expect_equal(count(where(df, df$age2 == df$age * 2)), 2)
+})
+
+test_that("select with column", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  df1 <- select(df, "name")
+  expect_true(columns(df1) == c("name"))
+  expect_true(count(df1) == 3)
+
+  df2 <- select(df, df$age)
+  expect_true(columns(df2) == c("age"))
+  expect_true(count(df2) == 3)
+})
+
+test_that("selectExpr() on a DataFrame", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  selected <- selectExpr(df, "age * 2")
+  expect_true(names(selected) == "(age * 2)")
+  expect_equal(collect(selected), collect(select(df, df$age * 2L)))
+
+  selected2 <- selectExpr(df, "name as newName", "abs(age) as age")
+  expect_equal(names(selected2), c("newName", "age"))
+  expect_true(count(selected2) == 3)
+})
+
+test_that("column calculation", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  d <- collect(select(df, alias(df$age + 1, "age2")))
+  expect_true(names(d) == c("age2"))
+  df2 <- select(df, lower(df$name), abs(df$age))
+  expect_true(inherits(df2, "DataFrame"))
+  expect_true(count(df2) == 3)
+})
+
+test_that("load() from json file", {
+  df <- loadDF(sqlCtx, jsonPath, "json")
+  expect_true(inherits(df, "DataFrame"))
+  expect_true(count(df) == 3)
+})
+
+test_that("save() as parquet file", {
+  df <- loadDF(sqlCtx, jsonPath, "json")
+  saveDF(df, parquetPath, "parquet", mode="overwrite")
+  df2 <- loadDF(sqlCtx, parquetPath, "parquet")
+  expect_true(inherits(df2, "DataFrame"))
+  expect_true(count(df2) == 3)
+})
+
+test_that("test HiveContext", {
+  hiveCtx <- tryCatch({
+    newJObject("org.apache.spark.sql.hive.test.TestHiveContext", ssc)
+  }, error = function(err) {
+    skip("Hive is not build with SparkSQL, skipped")
+  })
+  df <- createExternalTable(hiveCtx, "json", jsonPath, "json")
+  expect_true(inherits(df, "DataFrame"))
+  expect_true(count(df) == 3)
+  df2 <- sql(hiveCtx, "select * from json")
+  expect_true(inherits(df2, "DataFrame"))
+  expect_true(count(df2) == 3)
+
+  jsonPath2 <- tempfile(pattern="sparkr-test", fileext=".tmp")
+  saveAsTable(df, "json", "json", "append", path = jsonPath2)
+  df3 <- sql(hiveCtx, "select * from json")
+  expect_true(inherits(df3, "DataFrame"))
+  expect_true(count(df3) == 6)
+})
+
+test_that("column operators", {
+  c <- SparkR:::col("a")
+  c2 <- (- c + 1 - 2) * 3 / 4.0
+  c3 <- (c + c2 - c2) * c2 %% c2
+  c4 <- (c > c2) & (c2 <= c3) | (c == c2) & (c2 != c3)
+})
+
+test_that("column functions", {
+  c <- SparkR:::col("a")
+  c2 <- min(c) + max(c) + sum(c) + avg(c) + count(c) + abs(c) + sqrt(c)
+  c3 <- lower(c) + upper(c) + first(c) + last(c)
+  c4 <- approxCountDistinct(c) + countDistinct(c) + cast(c, "string")
+})
+
+test_that("string operators", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  expect_equal(count(where(df, like(df$name, "A%"))), 1)
+  expect_equal(count(where(df, startsWith(df$name, "A"))), 1)
+  expect_equal(first(select(df, substr(df$name, 1, 2)))[[1]], "Mi")
+  expect_equal(collect(select(df, cast(df$age, "string")))[[2, 1]], "30")
+})
+
+test_that("group by", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  df1 <- agg(df, name = "max", age = "sum")
+  expect_true(1 == count(df1))
+  df1 <- agg(df, age2 = max(df$age))
+  expect_true(1 == count(df1))
+  expect_equal(columns(df1), c("age2"))
+
+  gd <- groupBy(df, "name")
+  expect_true(inherits(gd, "GroupedData"))
+  df2 <- count(gd)
+  expect_true(inherits(df2, "DataFrame"))
+  expect_true(3 == count(df2))
+
+  df3 <- agg(gd, age = "sum")
+  expect_true(inherits(df3, "DataFrame"))
+  expect_true(3 == count(df3))
+
+  df3 <- agg(gd, age = sum(df$age))
+  expect_true(inherits(df3, "DataFrame"))
+  expect_true(3 == count(df3))
+  expect_equal(columns(df3), c("name", "age"))
+
+  df4 <- sum(gd, "age")
+  expect_true(inherits(df4, "DataFrame"))
+  expect_true(3 == count(df4))
+  expect_true(3 == count(mean(gd, "age")))
+  expect_true(3 == count(max(gd, "age")))
+})
+
+test_that("sortDF() and orderBy() on a DataFrame", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  sorted <- sortDF(df, df$age)
+  expect_true(collect(sorted)[1,2] == "Michael")
+
+  sorted2 <- sortDF(df, "name")
+  expect_true(collect(sorted2)[2,"age"] == 19)
+
+  sorted3 <- orderBy(df, asc(df$age))
+  expect_true(is.na(first(sorted3)$age))
+  expect_true(collect(sorted3)[2, "age"] == 19)
+
+  sorted4 <- orderBy(df, desc(df$name))
+  expect_true(first(sorted4)$name == "Michael")
+  expect_true(collect(sorted4)[3,"name"] == "Andy")
+})
+
+test_that("filter() on a DataFrame", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  filtered <- filter(df, "age > 20")
+  expect_true(count(filtered) == 1)
+  expect_true(collect(filtered)$name == "Andy")
+  filtered2 <- where(df, df$name != "Michael")
+  expect_true(count(filtered2) == 2)
+  expect_true(collect(filtered2)$age[2] == 19)
+})
+
+test_that("join() on a DataFrame", {
+  df <- jsonFile(sqlCtx, jsonPath)
+
+  mockLines2 <- c("{\"name\":\"Michael\", \"test\": \"yes\"}",
+                  "{\"name\":\"Andy\",  \"test\": \"no\"}",
+                  "{\"name\":\"Justin\", \"test\": \"yes\"}",
+                  "{\"name\":\"Bob\", \"test\": \"yes\"}")
+  jsonPath2 <- tempfile(pattern="sparkr-test", fileext=".tmp")
+  writeLines(mockLines2, jsonPath2)
+  df2 <- jsonFile(sqlCtx, jsonPath2)
+
+  joined <- join(df, df2)
+  expect_equal(names(joined), c("age", "name", "name", "test"))
+  expect_true(count(joined) == 12)
+
+  joined2 <- join(df, df2, df$name == df2$name)
+  expect_equal(names(joined2), c("age", "name", "name", "test"))
+  expect_true(count(joined2) == 3)
+
+  joined3 <- join(df, df2, df$name == df2$name, "right_outer")
+  expect_equal(names(joined3), c("age", "name", "name", "test"))
+  expect_true(count(joined3) == 4)
+  expect_true(is.na(collect(orderBy(joined3, joined3$age))$age[2]))
+
+  joined4 <- select(join(df, df2, df$name == df2$name, "outer"),
+                    alias(df$age + 5, "newAge"), df$name, df2$test)
+  expect_equal(names(joined4), c("newAge", "name", "test"))
+  expect_true(count(joined4) == 4)
+  expect_equal(collect(orderBy(joined4, joined4$name))$newAge[3], 24)
+})
+
+test_that("toJSON() returns an RDD of the correct values", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  testRDD <- toJSON(df)
+  expect_true(inherits(testRDD, "RDD"))
+  expect_true(SparkR:::getSerializedMode(testRDD) == "string")
+  expect_equal(collect(testRDD)[[1]], mockLines[1])
+})
+
+test_that("showDF()", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  expect_output(showDF(df), "age  name   \nnull Michael\n30   Andy   \n19   Justin ")
+})
+
+test_that("isLocal()", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  expect_false(isLocal(df))
+})
+
+test_that("unionAll(), subtract(), and intersect() on a DataFrame", {
+  df <- jsonFile(sqlCtx, jsonPath)
+
+  lines <- c("{\"name\":\"Bob\", \"age\":24}",
+             "{\"name\":\"Andy\", \"age\":30}",
+             "{\"name\":\"James\", \"age\":35}")
+  jsonPath2 <- tempfile(pattern="sparkr-test", fileext=".tmp")
+  writeLines(lines, jsonPath2)
+  df2 <- loadDF(sqlCtx, jsonPath2, "json")
+
+  unioned <- sortDF(unionAll(df, df2), df$age)
+  expect_true(inherits(unioned, "DataFrame"))
+  expect_true(count(unioned) == 6)
+  expect_true(first(unioned)$name == "Michael")
+
+  subtracted <- sortDF(subtract(df, df2), desc(df$age))
+  expect_true(inherits(unioned, "DataFrame"))
+  expect_true(count(subtracted) == 2)
+  expect_true(first(subtracted)$name == "Justin")
+
+  intersected <- sortDF(intersect(df, df2), df$age)
+  expect_true(inherits(unioned, "DataFrame"))
+  expect_true(count(intersected) == 1)
+  expect_true(first(intersected)$name == "Andy")
+})
+
+test_that("withColumn() and withColumnRenamed()", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  newDF <- withColumn(df, "newAge", df$age + 2)
+  expect_true(length(columns(newDF)) == 3)
+  expect_true(columns(newDF)[3] == "newAge")
+  expect_true(first(filter(newDF, df$name != "Michael"))$newAge == 32)
+
+  newDF2 <- withColumnRenamed(df, "age", "newerAge")
+  expect_true(length(columns(newDF2)) == 2)
+  expect_true(columns(newDF2)[1] == "newerAge")
+})
+
+test_that("saveDF() on DataFrame and works with parquetFile", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  saveDF(df, parquetPath, "parquet", mode="overwrite")
+  parquetDF <- parquetFile(sqlCtx, parquetPath)
+  expect_true(inherits(parquetDF, "DataFrame"))
+  expect_equal(count(df), count(parquetDF))
+})
+
+test_that("parquetFile works with multiple input paths", {
+  df <- jsonFile(sqlCtx, jsonPath)
+  saveDF(df, parquetPath, "parquet", mode="overwrite")
+  parquetPath2 <- tempfile(pattern = "parquetPath2", fileext = ".parquet")
+  saveDF(df, parquetPath2, "parquet", mode="overwrite")
+  parquetDF <- parquetFile(sqlCtx, parquetPath, parquetPath2)
+  expect_true(inherits(parquetDF, "DataFrame"))
+  expect_true(count(parquetDF) == count(df)*2)
+})
+
+unlink(parquetPath)
+unlink(jsonPath)
diff --git a/R/pkg/inst/tests/test_take.R b/R/pkg/inst/tests/test_take.R
new file mode 100644
index 0000000000000..7f4c7c315d787
--- /dev/null
+++ b/R/pkg/inst/tests/test_take.R
@@ -0,0 +1,67 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+context("tests RDD function take()")
+
+# Mock data
+numVector <- c(-10:97)
+numList <- list(sqrt(1), sqrt(2), sqrt(3), 4 ** 10)
+strVector <- c("Dexter Morgan: I suppose I should be upset, even feel",
+               "violated, but I'm not. No, in fact, I think this is a friendly",
+               "message, like \"Hey, wanna play?\" and yes, I want to play. ",
+               "I really, really do.")
+strList <- list("Dexter Morgan: Blood. Sometimes it sets my teeth on edge, ",
+                "other times it helps me control the chaos.",
+                "Dexter Morgan: Harry and Dorris Morgan did a wonderful job ",
+                "raising me. But they're both dead now. I didn't kill them. Honest.")
+
+# JavaSparkContext handle
+jsc <- sparkR.init()
+
+test_that("take() gives back the original elements in correct count and order", {
+  numVectorRDD <- parallelize(jsc, numVector, 10)
+  # case: number of elements to take is less than the size of the first partition
+  expect_equal(take(numVectorRDD, 1), as.list(head(numVector, n = 1)))
+  # case: number of elements to take is the same as the size of the first partition
+  expect_equal(take(numVectorRDD, 11), as.list(head(numVector, n = 11)))
+  # case: number of elements to take is greater than all elements
+  expect_equal(take(numVectorRDD, length(numVector)), as.list(numVector))
+  expect_equal(take(numVectorRDD, length(numVector) + 1), as.list(numVector))
+
+  numListRDD <- parallelize(jsc, numList, 1)
+  numListRDD2 <- parallelize(jsc, numList, 4)
+  expect_equal(take(numListRDD, 3), take(numListRDD2, 3))
+  expect_equal(take(numListRDD, 5), take(numListRDD2, 5))
+  expect_equal(take(numListRDD, 1), as.list(head(numList, n = 1)))
+  expect_equal(take(numListRDD2, 999), numList)
+
+  strVectorRDD <- parallelize(jsc, strVector, 2)
+  strVectorRDD2 <- parallelize(jsc, strVector, 3)
+  expect_equal(take(strVectorRDD, 4), as.list(strVector))
+  expect_equal(take(strVectorRDD2, 2), as.list(head(strVector, n = 2)))
+
+  strListRDD <- parallelize(jsc, strList, 4)
+  strListRDD2 <- parallelize(jsc, strList, 1)
+  expect_equal(take(strListRDD, 3), as.list(head(strList, n = 3)))
+  expect_equal(take(strListRDD2, 1), as.list(head(strList, n = 1)))
+
+  expect_true(length(take(strListRDD, 0)) == 0)
+  expect_true(length(take(strVectorRDD, 0)) == 0)
+  expect_true(length(take(numListRDD, 0)) == 0)
+  expect_true(length(take(numVectorRDD, 0)) == 0)
+})
+
diff --git a/R/pkg/inst/tests/test_textFile.R b/R/pkg/inst/tests/test_textFile.R
new file mode 100644
index 0000000000000..7bb3e8003131d
--- /dev/null
+++ b/R/pkg/inst/tests/test_textFile.R
@@ -0,0 +1,162 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+context("the textFile() function")
+
+# JavaSparkContext handle
+sc <- sparkR.init()
+
+mockFile = c("Spark is pretty.", "Spark is awesome.")
+
+test_that("textFile() on a local file returns an RDD", {
+  fileName <- tempfile(pattern="spark-test", fileext=".tmp")
+  writeLines(mockFile, fileName)
+
+  rdd <- textFile(sc, fileName)
+  expect_true(inherits(rdd, "RDD"))
+  expect_true(count(rdd) > 0)
+  expect_true(count(rdd) == 2)
+
+  unlink(fileName)
+})
+
+test_that("textFile() followed by a collect() returns the same content", {
+  fileName <- tempfile(pattern="spark-test", fileext=".tmp")
+  writeLines(mockFile, fileName)
+
+  rdd <- textFile(sc, fileName)
+  expect_equal(collect(rdd), as.list(mockFile))
+
+  unlink(fileName)
+})
+
+test_that("textFile() word count works as expected", {
+  fileName <- tempfile(pattern="spark-test", fileext=".tmp")
+  writeLines(mockFile, fileName)
+
+  rdd <- textFile(sc, fileName)
+
+  words <- flatMap(rdd, function(line) { strsplit(line, " ")[[1]] })
+  wordCount <- lapply(words, function(word) { list(word, 1L) })
+
+  counts <- reduceByKey(wordCount, "+", 2L)
+  output <- collect(counts)
+  expected <- list(list("pretty.", 1), list("is", 2), list("awesome.", 1),
+                   list("Spark", 2))
+  expect_equal(sortKeyValueList(output), sortKeyValueList(expected))
+  
+  unlink(fileName)
+})
+
+test_that("several transformations on RDD created by textFile()", {
+  fileName <- tempfile(pattern="spark-test", fileext=".tmp")
+  writeLines(mockFile, fileName)
+
+  rdd <- textFile(sc, fileName) # RDD
+  for (i in 1:10) {
+    # PipelinedRDD initially created from RDD
+    rdd <- lapply(rdd, function(x) paste(x, x))
+  }
+  collect(rdd)
+
+  unlink(fileName)
+})
+
+test_that("textFile() followed by a saveAsTextFile() returns the same content", {
+  fileName1 <- tempfile(pattern="spark-test", fileext=".tmp")
+  fileName2 <- tempfile(pattern="spark-test", fileext=".tmp")
+  writeLines(mockFile, fileName1)
+
+  rdd <- textFile(sc, fileName1)
+  saveAsTextFile(rdd, fileName2)
+  rdd <- textFile(sc, fileName2)
+  expect_equal(collect(rdd), as.list(mockFile))
+
+  unlink(fileName1)
+  unlink(fileName2)
+})
+
+test_that("saveAsTextFile() on a parallelized list works as expected", {
+  fileName <- tempfile(pattern="spark-test", fileext=".tmp")
+  l <- list(1, 2, 3)
+  rdd <- parallelize(sc, l)
+  saveAsTextFile(rdd, fileName)
+  rdd <- textFile(sc, fileName)
+  expect_equal(collect(rdd), lapply(l, function(x) {toString(x)}))
+
+  unlink(fileName)
+})
+
+test_that("textFile() and saveAsTextFile() word count works as expected", {
+  fileName1 <- tempfile(pattern="spark-test", fileext=".tmp")
+  fileName2 <- tempfile(pattern="spark-test", fileext=".tmp")
+  writeLines(mockFile, fileName1)
+
+  rdd <- textFile(sc, fileName1)
+
+  words <- flatMap(rdd, function(line) { strsplit(line, " ")[[1]] })
+  wordCount <- lapply(words, function(word) { list(word, 1L) })
+
+  counts <- reduceByKey(wordCount, "+", 2L)
+
+  saveAsTextFile(counts, fileName2)
+  rdd <- textFile(sc, fileName2)
+   
+  output <- collect(rdd)
+  expected <- list(list("awesome.", 1), list("Spark", 2),
+                   list("pretty.", 1), list("is", 2))
+  expectedStr <- lapply(expected, function(x) { toString(x) })
+  expect_equal(sortKeyValueList(output), sortKeyValueList(expectedStr))
+  
+  unlink(fileName1)
+  unlink(fileName2)
+})
+
+test_that("textFile() on multiple paths", {
+  fileName1 <- tempfile(pattern="spark-test", fileext=".tmp")
+  fileName2 <- tempfile(pattern="spark-test", fileext=".tmp")
+  writeLines("Spark is pretty.", fileName1)
+  writeLines("Spark is awesome.", fileName2)
+
+  rdd <- textFile(sc, c(fileName1, fileName2))
+  expect_true(count(rdd) == 2)
+
+  unlink(fileName1)
+  unlink(fileName2)
+})
+
+test_that("Pipelined operations on RDDs created using textFile", {
+  fileName <- tempfile(pattern="spark-test", fileext=".tmp")
+  writeLines(mockFile, fileName)
+
+  rdd <- textFile(sc, fileName)
+
+  lengths <- lapply(rdd, function(x) { length(x) })
+  expect_equal(collect(lengths), list(1, 1))
+
+  lengthsPipelined <- lapply(lengths, function(x) { x + 10 })
+  expect_equal(collect(lengthsPipelined), list(11, 11))
+
+  lengths30 <- lapply(lengthsPipelined, function(x) { x + 20 })
+  expect_equal(collect(lengths30), list(31, 31))
+
+  lengths20 <- lapply(lengths, function(x) { x + 20 })
+  expect_equal(collect(lengths20), list(21, 21))
+
+  unlink(fileName)
+})
+
diff --git a/R/pkg/inst/tests/test_utils.R b/R/pkg/inst/tests/test_utils.R
new file mode 100644
index 0000000000000..9c5bb427932b4
--- /dev/null
+++ b/R/pkg/inst/tests/test_utils.R
@@ -0,0 +1,137 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+context("functions in utils.R")
+
+# JavaSparkContext handle
+sc <- sparkR.init()
+
+test_that("convertJListToRList() gives back (deserializes) the original JLists
+          of strings and integers", {
+  # It's hard to manually create a Java List using rJava, since it does not
+  # support generics well. Instead, we rely on collect() returning a
+  # JList.
+  nums <- as.list(1:10)
+  rdd <- parallelize(sc, nums, 1L)
+  jList <- callJMethod(rdd@jrdd, "collect")
+  rList <- convertJListToRList(jList, flatten = TRUE)
+  expect_equal(rList, nums)
+
+  strs <- as.list("hello", "spark")
+  rdd <- parallelize(sc, strs, 2L)
+  jList <- callJMethod(rdd@jrdd, "collect")
+  rList <- convertJListToRList(jList, flatten = TRUE)
+  expect_equal(rList, strs)
+})
+
+test_that("serializeToBytes on RDD", {
+  # File content
+  mockFile <- c("Spark is pretty.", "Spark is awesome.")
+  fileName <- tempfile(pattern="spark-test", fileext=".tmp")
+  writeLines(mockFile, fileName)
+  
+  text.rdd <- textFile(sc, fileName)
+  expect_true(getSerializedMode(text.rdd) == "string")
+  ser.rdd <- serializeToBytes(text.rdd)
+  expect_equal(collect(ser.rdd), as.list(mockFile))
+  expect_true(getSerializedMode(ser.rdd) == "byte")
+  
+  unlink(fileName)
+})
+
+test_that("cleanClosure on R functions", {
+  y <- c(1, 2, 3)
+  g <- function(x) { x + 1 }
+  f <- function(x) { g(x) + y }
+  newF <- cleanClosure(f)
+  env <- environment(newF)
+  expect_equal(length(ls(env)), 2)  # y, g
+  actual <- get("y", envir = env, inherits = FALSE)
+  expect_equal(actual, y)
+  actual <- get("g", envir = env, inherits = FALSE)
+  expect_equal(actual, g)
+  
+  # Test for nested enclosures and package variables.
+  env2 <- new.env()
+  funcEnv <- new.env(parent = env2)
+  f <- function(x) { log(g(x) + y) }
+  environment(f) <- funcEnv  # enclosing relationship: f -> funcEnv -> env2 -> .GlobalEnv
+  newF <- cleanClosure(f)
+  env <- environment(newF)
+  expect_equal(length(ls(env)), 2)  # "min" should not be included
+  actual <- get("y", envir = env, inherits = FALSE)
+  expect_equal(actual, y)
+  actual <- get("g", envir = env, inherits = FALSE)
+  expect_equal(actual, g)
+
+  base <- c(1, 2, 3)
+  l <- list(field = matrix(1))
+  field <- matrix(2)
+  defUse <- 3
+  g <- function(x) { x + y }
+  f <- function(x) {
+    defUse <- base::as.integer(x) + 1  # Test for access operators `::`.
+    lapply(x, g) + 1  # Test for capturing function call "g"'s closure as a argument of lapply.
+    l$field[1,1] <- 3  # Test for access operators `$`.
+    res <- defUse + l$field[1,]  # Test for def-use chain of "defUse", and "" symbol.
+    f(res)  # Test for recursive calls.
+  }
+  newF <- cleanClosure(f)
+  env <- environment(newF)
+  expect_equal(length(ls(env)), 3)  # Only "g", "l" and "f". No "base", "field" or "defUse".
+  expect_true("g" %in% ls(env))
+  expect_true("l" %in% ls(env))
+  expect_true("f" %in% ls(env))
+  expect_equal(get("l", envir = env, inherits = FALSE), l)
+  # "y" should be in the environemnt of g.
+  newG <- get("g", envir = env, inherits = FALSE)
+  env <- environment(newG)
+  expect_equal(length(ls(env)), 1)
+  actual <- get("y", envir = env, inherits = FALSE)
+  expect_equal(actual, y)
+  
+  # Test for function (and variable) definitions.
+  f <- function(x) {
+    g <- function(y) { y * 2 }
+    g(x)
+  }
+  newF <- cleanClosure(f)
+  env <- environment(newF)
+  expect_equal(length(ls(env)), 0)  # "y" and "g" should not be included.
+  
+  # Test for overriding variables in base namespace (Issue: SparkR-196).
+  nums <- as.list(1:10)
+  rdd <- parallelize(sc, nums, 2L)
+  t = 4  # Override base::t in .GlobalEnv.
+  f <- function(x) { x > t }
+  newF <- cleanClosure(f)
+  env <- environment(newF)
+  expect_equal(ls(env), "t")
+  expect_equal(get("t", envir = env, inherits = FALSE), t)
+  actual <- collect(lapply(rdd, f))
+  expected <- as.list(c(rep(FALSE, 4), rep(TRUE, 6)))
+  expect_equal(actual, expected)
+  
+  # Test for broadcast variables.
+  a <- matrix(nrow=10, ncol=10, data=rnorm(100))
+  aBroadcast <- broadcast(sc, a)
+  normMultiply <- function(x) { norm(aBroadcast$value) * x }
+  newnormMultiply <- SparkR:::cleanClosure(normMultiply)
+  env <- environment(newnormMultiply)
+  expect_equal(ls(env), "aBroadcast")
+  expect_equal(get("aBroadcast", envir = env, inherits = FALSE), aBroadcast)
+})
diff --git a/R/pkg/inst/worker/daemon.R b/R/pkg/inst/worker/daemon.R
new file mode 100644
index 0000000000000..3584b418a71a9
--- /dev/null
+++ b/R/pkg/inst/worker/daemon.R
@@ -0,0 +1,52 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Worker daemon
+
+rLibDir <- Sys.getenv("SPARKR_RLIBDIR")
+script <- paste(rLibDir, "SparkR/worker/worker.R", sep = "/")
+
+# preload SparkR package, speedup worker
+.libPaths(c(rLibDir, .libPaths()))
+suppressPackageStartupMessages(library(SparkR))
+
+port <- as.integer(Sys.getenv("SPARKR_WORKER_PORT"))
+inputCon <- socketConnection(port = port, open = "rb", blocking = TRUE, timeout = 3600)
+
+while (TRUE) {
+  ready <- socketSelect(list(inputCon))
+  if (ready) {
+    port <- SparkR:::readInt(inputCon)
+    # There is a small chance that it could be interrupted by signal, retry one time
+    if (length(port) == 0) {
+      port <- SparkR:::readInt(inputCon)
+      if (length(port) == 0) {
+        cat("quitting daemon\n")
+        quit(save = "no")
+      }
+    }
+    p <- parallel:::mcfork()
+    if (inherits(p, "masterProcess")) {
+      close(inputCon)
+      Sys.setenv(SPARKR_WORKER_PORT = port)
+      source(script)
+      # Set SIGUSR1 so that child can exit
+      tools::pskill(Sys.getpid(), tools::SIGUSR1)
+      parallel:::mcexit(0L)
+    }
+  }
+}
diff --git a/R/pkg/inst/worker/worker.R b/R/pkg/inst/worker/worker.R
new file mode 100644
index 0000000000000..c6542928e8ddd
--- /dev/null
+++ b/R/pkg/inst/worker/worker.R
@@ -0,0 +1,128 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Worker class
+
+rLibDir <- Sys.getenv("SPARKR_RLIBDIR")
+# Set libPaths to include SparkR package as loadNamespace needs this
+# TODO: Figure out if we can avoid this by not loading any objects that require
+# SparkR namespace
+.libPaths(c(rLibDir, .libPaths()))
+suppressPackageStartupMessages(library(SparkR))
+
+port <- as.integer(Sys.getenv("SPARKR_WORKER_PORT"))
+inputCon <- socketConnection(port = port, blocking = TRUE, open = "rb")
+outputCon <- socketConnection(port = port, blocking = TRUE, open = "wb")
+
+# read the index of the current partition inside the RDD
+partition <- SparkR:::readInt(inputCon)
+
+deserializer <- SparkR:::readString(inputCon)
+serializer <- SparkR:::readString(inputCon)
+
+# Include packages as required
+packageNames <- unserialize(SparkR:::readRaw(inputCon))
+for (pkg in packageNames) {
+  suppressPackageStartupMessages(require(as.character(pkg), character.only=TRUE))
+}
+
+# read function dependencies
+funcLen <- SparkR:::readInt(inputCon)
+computeFunc <- unserialize(SparkR:::readRawLen(inputCon, funcLen))
+env <- environment(computeFunc)
+parent.env(env) <- .GlobalEnv  # Attach under global environment.
+
+# Read and set broadcast variables
+numBroadcastVars <- SparkR:::readInt(inputCon)
+if (numBroadcastVars > 0) {
+  for (bcast in seq(1:numBroadcastVars)) {
+    bcastId <- SparkR:::readInt(inputCon)
+    value <- unserialize(SparkR:::readRaw(inputCon))
+    setBroadcastValue(bcastId, value)
+  }
+}
+
+# If -1: read as normal RDD; if >= 0, treat as pairwise RDD and treat the int
+# as number of partitions to create.
+numPartitions <- SparkR:::readInt(inputCon)
+
+isEmpty <- SparkR:::readInt(inputCon)
+
+if (isEmpty != 0) {
+
+  if (numPartitions == -1) {
+    if (deserializer == "byte") {
+      # Now read as many characters as described in funcLen
+      data <- SparkR:::readDeserialize(inputCon)
+    } else if (deserializer == "string") {
+      data <- as.list(readLines(inputCon))
+    } else if (deserializer == "row") {
+      data <- SparkR:::readDeserializeRows(inputCon)
+    }
+    output <- computeFunc(partition, data)
+    if (serializer == "byte") {
+      SparkR:::writeRawSerialize(outputCon, output)
+    } else if (serializer == "row") {
+      SparkR:::writeRowSerialize(outputCon, output)
+    } else {
+      SparkR:::writeStrings(outputCon, output)
+    }
+  } else {
+    if (deserializer == "byte") {
+      # Now read as many characters as described in funcLen
+      data <- SparkR:::readDeserialize(inputCon)
+    } else if (deserializer == "string") {
+      data <- readLines(inputCon)
+    } else if (deserializer == "row") {
+      data <- SparkR:::readDeserializeRows(inputCon)
+    }
+
+    res <- new.env()
+
+    # Step 1: hash the data to an environment
+    hashTupleToEnvir <- function(tuple) {
+      # NOTE: execFunction is the hash function here
+      hashVal <- computeFunc(tuple[[1]])
+      bucket <- as.character(hashVal %% numPartitions)
+      acc <- res[[bucket]]
+      # Create a new accumulator
+      if (is.null(acc)) {
+        acc <- SparkR:::initAccumulator()
+      }
+      SparkR:::addItemToAccumulator(acc, tuple)
+      res[[bucket]] <- acc
+    }
+    invisible(lapply(data, hashTupleToEnvir))
+
+    # Step 2: write out all of the environment as key-value pairs.
+    for (name in ls(res)) {
+      SparkR:::writeInt(outputCon, 2L)
+      SparkR:::writeInt(outputCon, as.integer(name))
+      # Truncate the accumulator list to the number of elements we have
+      length(res[[name]]$data) <- res[[name]]$counter
+      SparkR:::writeRawSerialize(outputCon, res[[name]]$data)
+    }
+  }
+}
+
+# End of output
+if (serializer %in% c("byte", "row")) {
+  SparkR:::writeInt(outputCon, 0L)
+}
+
+close(outputCon)
+close(inputCon)
diff --git a/R/pkg/src/Makefile b/R/pkg/src/Makefile
new file mode 100644
index 0000000000000..a55a56fe80e10
--- /dev/null
+++ b/R/pkg/src/Makefile
@@ -0,0 +1,27 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+all: sharelib
+
+sharelib: string_hash_code.c
+	R CMD SHLIB -o SparkR.so string_hash_code.c
+
+clean:
+	rm -f *.o
+	rm -f *.so
+       
+.PHONY: all clean
diff --git a/R/pkg/src/Makefile.win b/R/pkg/src/Makefile.win
new file mode 100644
index 0000000000000..aa486d8228371
--- /dev/null
+++ b/R/pkg/src/Makefile.win
@@ -0,0 +1,27 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+all: sharelib
+
+sharelib: string_hash_code.c
+	R CMD SHLIB -o SparkR.dll string_hash_code.c
+
+clean:
+	rm -f *.o
+	rm -f *.dll
+       
+.PHONY: all clean
diff --git a/R/pkg/src/string_hash_code.c b/R/pkg/src/string_hash_code.c
new file mode 100644
index 0000000000000..e3274b9a0c547
--- /dev/null
+++ b/R/pkg/src/string_hash_code.c
@@ -0,0 +1,49 @@
+/*
+ Licensed to the Apache Software Foundation (ASF) under one or more
+ contributor license agreements.  See the NOTICE file distributed with
+ this work for additional information regarding copyright ownership.
+ The ASF licenses this file to You under the Apache License, Version 2.0
+ (the "License"); you may not use this file except in compliance with
+ the License.  You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+*/
+
+/*
+ * A C function for R extension which implements the Java String hash algorithm.
+ * Refer to http://en.wikipedia.org/wiki/Java_hashCode%28%29#The_java.lang.String_hash_function
+ *
+ */
+
+#include <R.h>
+#include <Rinternals.h>
+
+/* for compatibility with R before 3.1 */
+#ifndef IS_SCALAR
+#define IS_SCALAR(x, type) (TYPEOF(x) == (type) && XLENGTH(x) == 1)
+#endif
+
+SEXP stringHashCode(SEXP string) {
+  const char* str;
+  R_xlen_t len, i;
+  int hashCode = 0;
+  
+  if (!IS_SCALAR(string, STRSXP)) {
+    error("invalid input");
+  }
+  
+  str = CHAR(asChar(string));
+  len = XLENGTH(asChar(string));
+  
+  for (i = 0; i < len; i++) {
+    hashCode = (hashCode << 5) - hashCode + *str++;
+  }
+
+  return ScalarInteger(hashCode);
+}
diff --git a/R/pkg/tests/run-all.R b/R/pkg/tests/run-all.R
new file mode 100644
index 0000000000000..4f8a1ed2d83ef
--- /dev/null
+++ b/R/pkg/tests/run-all.R
@@ -0,0 +1,21 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+library(testthat)
+library(SparkR)
+
+test_package("SparkR")
diff --git a/R/run-tests.sh b/R/run-tests.sh
new file mode 100755
index 0000000000000..e82ad0ba2cd06
--- /dev/null
+++ b/R/run-tests.sh
@@ -0,0 +1,39 @@
+#!/bin/bash
+
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+FWDIR="$(cd `dirname $0`; pwd)"
+
+FAILED=0
+LOGFILE=$FWDIR/unit-tests.out
+rm -f $LOGFILE
+
+SPARK_TESTING=1 $FWDIR/../bin/sparkR --driver-java-options "-Dlog4j.configuration=file:$FWDIR/log4j.properties" $FWDIR/pkg/tests/run-all.R 2>&1 | tee -a $LOGFILE
+FAILED=$((PIPESTATUS[0]||$FAILED))
+
+if [[ $FAILED != 0 ]]; then
+    cat $LOGFILE
+    echo -en "\033[31m"  # Red
+    echo "Had test failures; see logs."
+    echo -en "\033[0m"  # No color
+    exit -1
+else
+    echo -en "\033[32m"  # Green
+    echo "Tests passed."
+    echo -en "\033[0m"  # No color
+fi
diff --git a/bin/sparkR b/bin/sparkR
new file mode 100755
index 0000000000000..8c918e2b09aef
--- /dev/null
+++ b/bin/sparkR
@@ -0,0 +1,39 @@
+#!/bin/bash
+
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Figure out where Spark is installed
+export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
+
+source "$SPARK_HOME"/bin/load-spark-env.sh
+
+function usage() {
+  if [ -n "$1" ]; then
+    echo $1
+  fi
+  echo "Usage: ./bin/sparkR [options]" 1>&2
+  "$SPARK_HOME"/bin/spark-submit --help 2>&1 | grep -v Usage 1>&2
+  exit $2
+}
+export -f usage
+
+if [[ "$@" = *--help ]] || [[ "$@" = *-h ]]; then
+  usage
+fi
+
+exec "$SPARK_HOME"/bin/spark-submit sparkr-shell-main "$@"
diff --git a/bin/sparkR.cmd b/bin/sparkR.cmd
new file mode 100644
index 0000000000000..d7b60183ca8e0
--- /dev/null
+++ b/bin/sparkR.cmd
@@ -0,0 +1,23 @@
+@echo off
+
+rem
+rem Licensed to the Apache Software Foundation (ASF) under one or more
+rem contributor license agreements.  See the NOTICE file distributed with
+rem this work for additional information regarding copyright ownership.
+rem The ASF licenses this file to You under the Apache License, Version 2.0
+rem (the "License"); you may not use this file except in compliance with
+rem the License.  You may obtain a copy of the License at
+rem
+rem    http://www.apache.org/licenses/LICENSE-2.0
+rem
+rem Unless required by applicable law or agreed to in writing, software
+rem distributed under the License is distributed on an "AS IS" BASIS,
+rem WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+rem See the License for the specific language governing permissions and
+rem limitations under the License.
+rem
+
+rem This is the entry point for running SparkR. To avoid polluting the
+rem environment, it just launches a new cmd to do the real work.
+
+cmd /V /E /C %~dp0sparkR2.cmd %*
diff --git a/bin/sparkR2.cmd b/bin/sparkR2.cmd
new file mode 100644
index 0000000000000..e47f22c7300bb
--- /dev/null
+++ b/bin/sparkR2.cmd
@@ -0,0 +1,26 @@
+@echo off
+
+rem
+rem Licensed to the Apache Software Foundation (ASF) under one or more
+rem contributor license agreements.  See the NOTICE file distributed with
+rem this work for additional information regarding copyright ownership.
+rem The ASF licenses this file to You under the Apache License, Version 2.0
+rem (the "License"); you may not use this file except in compliance with
+rem the License.  You may obtain a copy of the License at
+rem
+rem    http://www.apache.org/licenses/LICENSE-2.0
+rem
+rem Unless required by applicable law or agreed to in writing, software
+rem distributed under the License is distributed on an "AS IS" BASIS,
+rem WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+rem See the License for the specific language governing permissions and
+rem limitations under the License.
+rem
+
+rem Figure out where the Spark framework is installed
+set SPARK_HOME=%~dp0..
+
+call %SPARK_HOME%\bin\load-spark-env.cmd
+
+
+call %SPARK_HOME%\bin\spark-submit2.cmd sparkr-shell-main %*
diff --git a/core/pom.xml b/core/pom.xml
index 6cd1965ec37c2..e80829b7a7f3d 100644
--- a/core/pom.xml
+++ b/core/pom.xml
@@ -442,4 +442,55 @@
     </resources>
   </build>
 
+  <profiles>
+    <profile>
+      <id>Windows</id>
+      <activation>
+        <os>
+          <family>Windows</family>
+        </os>
+      </activation>
+      <properties>
+        <path.separator>\</path.separator>
+        <script.extension>.bat</script.extension>
+      </properties>
+    </profile>
+    <profile>
+      <id>unix</id>
+      <activation>
+        <os>
+          <family>unix</family>
+        </os>
+      </activation>
+      <properties>
+        <path.separator>/</path.separator>
+        <script.extension>.sh</script.extension>
+      </properties>
+    </profile>
+    <profile>
+      <id>sparkr</id>
+      <build>
+        <plugins>
+          <plugin>
+            <groupId>org.codehaus.mojo</groupId>
+            <artifactId>exec-maven-plugin</artifactId>
+            <version>1.3.2</version>
+            <executions>
+              <execution>
+                <id>sparkr-pkg</id>
+                <phase>compile</phase>
+                <goals>
+                  <goal>exec</goal>
+                </goals>
+              </execution>
+            </executions>
+            <configuration>
+              <executable>..${path.separator}R${path.separator}install-dev${script.extension}</executable>
+            </configuration>
+          </plugin>
+        </plugins>
+      </build>
+    </profile>
+  </profiles>
+
 </project>
diff --git a/core/src/main/scala/org/apache/spark/api/r/RBackend.scala b/core/src/main/scala/org/apache/spark/api/r/RBackend.scala
new file mode 100644
index 0000000000000..3a2c94bd9d875
--- /dev/null
+++ b/core/src/main/scala/org/apache/spark/api/r/RBackend.scala
@@ -0,0 +1,145 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.api.r
+
+import java.io.{DataOutputStream, File, FileOutputStream, IOException}
+import java.net.{InetSocketAddress, ServerSocket}
+import java.util.concurrent.TimeUnit
+
+import io.netty.bootstrap.ServerBootstrap
+import io.netty.channel.{ChannelFuture, ChannelInitializer, EventLoopGroup}
+import io.netty.channel.nio.NioEventLoopGroup
+import io.netty.channel.socket.SocketChannel
+import io.netty.channel.socket.nio.NioServerSocketChannel
+import io.netty.handler.codec.LengthFieldBasedFrameDecoder
+import io.netty.handler.codec.bytes.{ByteArrayDecoder, ByteArrayEncoder}
+
+import org.apache.spark.Logging
+
+/**
+ * Netty-based backend server that is used to communicate between R and Java.
+ */
+private[spark] class RBackend {
+
+  private[this] var channelFuture: ChannelFuture = null
+  private[this] var bootstrap: ServerBootstrap = null
+  private[this] var bossGroup: EventLoopGroup = null
+
+  def init(): Int = {
+    bossGroup = new NioEventLoopGroup(2)
+    val workerGroup = bossGroup
+    val handler = new RBackendHandler(this)
+  
+    bootstrap = new ServerBootstrap()
+      .group(bossGroup, workerGroup)
+      .channel(classOf[NioServerSocketChannel])
+  
+    bootstrap.childHandler(new ChannelInitializer[SocketChannel]() {
+      def initChannel(ch: SocketChannel): Unit = {
+        ch.pipeline()
+          .addLast("encoder", new ByteArrayEncoder())
+          .addLast("frameDecoder",
+            // maxFrameLength = 2G
+            // lengthFieldOffset = 0
+            // lengthFieldLength = 4
+            // lengthAdjustment = 0
+            // initialBytesToStrip = 4, i.e. strip out the length field itself
+            new LengthFieldBasedFrameDecoder(Integer.MAX_VALUE, 0, 4, 0, 4))
+          .addLast("decoder", new ByteArrayDecoder())
+          .addLast("handler", handler)
+      }
+    })
+
+    channelFuture = bootstrap.bind(new InetSocketAddress(0))
+    channelFuture.syncUninterruptibly()
+    channelFuture.channel().localAddress().asInstanceOf[InetSocketAddress].getPort()
+  }
+
+  def run(): Unit = {
+    channelFuture.channel.closeFuture().syncUninterruptibly()
+  }
+
+  def close(): Unit = {
+    if (channelFuture != null) {
+      // close is a local operation and should finish within milliseconds; timeout just to be safe
+      channelFuture.channel().close().awaitUninterruptibly(10, TimeUnit.SECONDS)
+      channelFuture = null
+    }
+    if (bootstrap != null && bootstrap.group() != null) {
+      bootstrap.group().shutdownGracefully()
+    }
+    if (bootstrap != null && bootstrap.childGroup() != null) {
+      bootstrap.childGroup().shutdownGracefully()
+    }
+    bootstrap = null
+  }
+
+}
+
+private[spark] object RBackend extends Logging {
+  def main(args: Array[String]): Unit = {
+    if (args.length < 1) {
+      System.err.println("Usage: RBackend <tempFilePath>")
+      System.exit(-1)
+    }
+    val sparkRBackend = new RBackend()
+    try {
+      // bind to random port
+      val boundPort = sparkRBackend.init()
+      val serverSocket = new ServerSocket(0, 1)
+      val listenPort = serverSocket.getLocalPort()
+
+      // tell the R process via temporary file
+      val path = args(0)
+      val f = new File(path + ".tmp")
+      val dos = new DataOutputStream(new FileOutputStream(f))
+      dos.writeInt(boundPort)
+      dos.writeInt(listenPort)
+      dos.close()
+      f.renameTo(new File(path))
+
+      // wait for the end of stdin, then exit
+      new Thread("wait for socket to close") {
+        setDaemon(true)
+        override def run(): Unit = {
+          // any un-catched exception will also shutdown JVM
+          val buf = new Array[Byte](1024)
+          // shutdown JVM if R does not connect back in 10 seconds
+          serverSocket.setSoTimeout(10000)
+          try {
+            val inSocket = serverSocket.accept()
+            serverSocket.close()
+            // wait for the end of socket, closed if R process die
+            inSocket.getInputStream().read(buf)
+          } finally {
+            sparkRBackend.close()
+            System.exit(0)
+          }
+        }
+      }.start()
+
+      sparkRBackend.run()
+    } catch {
+      case e: IOException =>
+        logError("Server shutting down: failed with exception ", e)
+        sparkRBackend.close()
+        System.exit(1)
+    }
+    System.exit(0)
+  }
+}
diff --git a/core/src/main/scala/org/apache/spark/api/r/RBackendHandler.scala b/core/src/main/scala/org/apache/spark/api/r/RBackendHandler.scala
new file mode 100644
index 0000000000000..0075d963711f1
--- /dev/null
+++ b/core/src/main/scala/org/apache/spark/api/r/RBackendHandler.scala
@@ -0,0 +1,223 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.api.r
+
+import java.io.{ByteArrayInputStream, ByteArrayOutputStream, DataInputStream, DataOutputStream}
+
+import scala.collection.mutable.HashMap
+
+import io.netty.channel.ChannelHandler.Sharable
+import io.netty.channel.{ChannelHandlerContext, SimpleChannelInboundHandler}
+
+import org.apache.spark.Logging
+import org.apache.spark.api.r.SerDe._
+
+/**
+ * Handler for RBackend
+ * TODO: This is marked as sharable to get a handle to RBackend. Is it safe to re-use
+ * this across connections ?
+ */
+@Sharable
+private[r] class RBackendHandler(server: RBackend)
+  extends SimpleChannelInboundHandler[Array[Byte]] with Logging {
+
+  override def channelRead0(ctx: ChannelHandlerContext, msg: Array[Byte]): Unit = {
+    val bis = new ByteArrayInputStream(msg)
+    val dis = new DataInputStream(bis)
+
+    val bos = new ByteArrayOutputStream()
+    val dos = new DataOutputStream(bos)
+
+    // First bit is isStatic
+    val isStatic = readBoolean(dis)
+    val objId = readString(dis)
+    val methodName = readString(dis)
+    val numArgs = readInt(dis)
+
+    if (objId == "SparkRHandler") {
+      methodName match {
+        case "stopBackend" =>
+          writeInt(dos, 0)
+          writeType(dos, "void")
+          server.close()
+        case "rm" =>
+          try {
+            val t = readObjectType(dis)
+            assert(t == 'c')
+            val objToRemove = readString(dis)
+            JVMObjectTracker.remove(objToRemove)
+            writeInt(dos, 0)
+            writeObject(dos, null)
+          } catch {
+            case e: Exception =>
+              logError(s"Removing $objId failed", e)
+              writeInt(dos, -1)
+          }
+        case _ => dos.writeInt(-1)
+      }
+    } else {
+      handleMethodCall(isStatic, objId, methodName, numArgs, dis, dos)
+    }
+
+    val reply = bos.toByteArray
+    ctx.write(reply)
+  }
+  
+  override def channelReadComplete(ctx: ChannelHandlerContext): Unit = {
+    ctx.flush()
+  }
+
+  override def exceptionCaught(ctx: ChannelHandlerContext, cause: Throwable): Unit = {
+    // Close the connection when an exception is raised.
+    cause.printStackTrace()
+    ctx.close()
+  }
+
+  def handleMethodCall(
+      isStatic: Boolean,
+      objId: String,
+      methodName: String,
+      numArgs: Int,
+      dis: DataInputStream,
+      dos: DataOutputStream): Unit = {
+    var obj: Object = null
+    try {
+      val cls = if (isStatic) {
+        Class.forName(objId)
+      } else {
+        JVMObjectTracker.get(objId) match {
+          case None => throw new IllegalArgumentException("Object not found " + objId)
+          case Some(o) =>
+            obj = o
+            o.getClass
+        }
+      }
+
+      val args = readArgs(numArgs, dis)
+
+      val methods = cls.getMethods
+      val selectedMethods = methods.filter(m => m.getName == methodName)
+      if (selectedMethods.length > 0) {
+        val methods = selectedMethods.filter { x =>
+          matchMethod(numArgs, args, x.getParameterTypes)
+        }
+        if (methods.isEmpty) {
+          logWarning(s"cannot find matching method ${cls}.$methodName. "
+            + s"Candidates are:")
+          selectedMethods.foreach { method =>
+            logWarning(s"$methodName(${method.getParameterTypes.mkString(",")})")
+          }
+          throw new Exception(s"No matched method found for $cls.$methodName")
+        }
+        val ret = methods.head.invoke(obj, args:_*)
+
+        // Write status bit
+        writeInt(dos, 0)
+        writeObject(dos, ret.asInstanceOf[AnyRef])
+      } else if (methodName == "<init>") {
+        // methodName should be "<init>" for constructor
+        val ctor = cls.getConstructors.filter { x =>
+          matchMethod(numArgs, args, x.getParameterTypes)
+        }.head
+
+        val obj = ctor.newInstance(args:_*)
+
+        writeInt(dos, 0)
+        writeObject(dos, obj.asInstanceOf[AnyRef])
+      } else {
+        throw new IllegalArgumentException("invalid method " + methodName + " for object " + objId)
+      }
+    } catch {
+      case e: Exception =>
+        logError(s"$methodName on $objId failed", e)
+        writeInt(dos, -1)
+    }
+  }
+
+  // Read a number of arguments from the data input stream
+  def readArgs(numArgs: Int, dis: DataInputStream): Array[java.lang.Object] = {
+    (0 until numArgs).map { arg =>
+      readObject(dis)
+    }.toArray
+  }
+
+  // Checks if the arguments passed in args matches the parameter types.
+  // NOTE: Currently we do exact match. We may add type conversions later.
+  def matchMethod(
+      numArgs: Int,
+      args: Array[java.lang.Object],
+      parameterTypes: Array[Class[_]]): Boolean = {
+    if (parameterTypes.length != numArgs) {
+      return false
+    }
+
+    for (i <- 0 to numArgs - 1) {
+      val parameterType = parameterTypes(i)
+      var parameterWrapperType = parameterType
+
+      // Convert native parameters to Object types as args is Array[Object] here
+      if (parameterType.isPrimitive) {
+        parameterWrapperType = parameterType match {
+          case java.lang.Integer.TYPE => classOf[java.lang.Integer]
+          case java.lang.Double.TYPE => classOf[java.lang.Double]
+          case java.lang.Boolean.TYPE => classOf[java.lang.Boolean]
+          case _ => parameterType
+        }
+      }
+      if (!parameterWrapperType.isInstance(args(i))) {
+        return false
+      }
+    }
+    true
+  }
+}
+
+/**
+ * Helper singleton that tracks JVM objects returned to R.
+ * This is useful for referencing these objects in RPC calls.
+ */
+private[r] object JVMObjectTracker {
+
+  // TODO: This map should be thread-safe if we want to support multiple
+  // connections at the same time
+  private[this] val objMap = new HashMap[String, Object]
+
+  // TODO: We support only one connection now, so an integer is fine.
+  // Investigate using use atomic integer in the future.
+  private[this] var objCounter: Int = 0
+
+  def getObject(id: String): Object = {
+    objMap(id)
+  }
+
+  def get(id: String): Option[Object] = {
+    objMap.get(id)
+  }
+
+  def put(obj: Object): String = {
+    val objId = objCounter.toString
+    objCounter = objCounter + 1
+    objMap.put(objId, obj)
+    objId
+  }
+
+  def remove(id: String): Option[Object] = {
+    objMap.remove(id)
+  }
+
+}
diff --git a/core/src/main/scala/org/apache/spark/api/r/RRDD.scala b/core/src/main/scala/org/apache/spark/api/r/RRDD.scala
new file mode 100644
index 0000000000000..5fa4d483b8342
--- /dev/null
+++ b/core/src/main/scala/org/apache/spark/api/r/RRDD.scala
@@ -0,0 +1,450 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.api.r
+
+import java.io._
+import java.net.ServerSocket
+import java.util.{Map => JMap}
+
+import scala.collection.JavaConversions._
+import scala.io.Source
+import scala.reflect.ClassTag
+import scala.util.Try
+
+import org.apache.spark._
+import org.apache.spark.api.java.{JavaPairRDD, JavaRDD, JavaSparkContext}
+import org.apache.spark.broadcast.Broadcast
+import org.apache.spark.rdd.RDD
+import org.apache.spark.util.Utils
+
+private abstract class BaseRRDD[T: ClassTag, U: ClassTag](
+    parent: RDD[T],
+    numPartitions: Int,
+    func: Array[Byte],
+    deserializer: String,
+    serializer: String,
+    packageNames: Array[Byte],
+    rLibDir: String,
+    broadcastVars: Array[Broadcast[Object]])
+  extends RDD[U](parent) with Logging {
+  override def getPartitions: Array[Partition] = parent.partitions
+
+  override def compute(partition: Partition, context: TaskContext): Iterator[U] = {
+
+    // The parent may be also an RRDD, so we should launch it first.
+    val parentIterator = firstParent[T].iterator(partition, context)
+
+    // we expect two connections
+    val serverSocket = new ServerSocket(0, 2)
+    val listenPort = serverSocket.getLocalPort()
+
+    // The stdout/stderr is shared by multiple tasks, because we use one daemon
+    // to launch child process as worker.
+    val errThread = RRDD.createRWorker(rLibDir, listenPort)
+
+    // We use two sockets to separate input and output, then it's easy to manage
+    // the lifecycle of them to avoid deadlock.
+    // TODO: optimize it to use one socket
+
+    // the socket used to send out the input of task
+    serverSocket.setSoTimeout(10000)
+    val inSocket = serverSocket.accept()
+    startStdinThread(inSocket.getOutputStream(), parentIterator, partition.index)
+
+    // the socket used to receive the output of task
+    val outSocket = serverSocket.accept()
+    val inputStream = new BufferedInputStream(outSocket.getInputStream)
+    val dataStream = openDataStream(inputStream)
+    serverSocket.close()
+
+    try {
+
+      return new Iterator[U] {
+        def next(): U = {
+          val obj = _nextObj
+          if (hasNext) {
+            _nextObj = read()
+          }
+          obj
+        }
+
+        var _nextObj = read()
+
+        def hasNext(): Boolean = {
+          val hasMore = (_nextObj != null)
+          if (!hasMore) {
+            dataStream.close()
+          }
+          hasMore
+        }
+      }
+    } catch {
+      case e: Exception =>
+        throw new SparkException("R computation failed with\n " + errThread.getLines())
+    }
+  }
+
+  /**
+   * Start a thread to write RDD data to the R process.
+   */
+  private def startStdinThread[T](
+    output: OutputStream,
+    iter: Iterator[T],
+    partition: Int): Unit = {
+
+    val env = SparkEnv.get
+    val bufferSize = System.getProperty("spark.buffer.size", "65536").toInt
+    val stream = new BufferedOutputStream(output, bufferSize)
+
+    new Thread("writer for R") {
+      override def run(): Unit = {
+        try {
+          SparkEnv.set(env)
+          val dataOut = new DataOutputStream(stream)
+          dataOut.writeInt(partition)
+
+          SerDe.writeString(dataOut, deserializer)
+          SerDe.writeString(dataOut, serializer)
+
+          dataOut.writeInt(packageNames.length)
+          dataOut.write(packageNames)
+
+          dataOut.writeInt(func.length)
+          dataOut.write(func)
+
+          dataOut.writeInt(broadcastVars.length)
+          broadcastVars.foreach { broadcast =>
+            // TODO(shivaram): Read a Long in R to avoid this cast
+            dataOut.writeInt(broadcast.id.toInt)
+            // TODO: Pass a byte array from R to avoid this cast ?
+            val broadcastByteArr = broadcast.value.asInstanceOf[Array[Byte]]
+            dataOut.writeInt(broadcastByteArr.length)
+            dataOut.write(broadcastByteArr)
+          }
+
+          dataOut.writeInt(numPartitions)
+
+          if (!iter.hasNext) {
+            dataOut.writeInt(0)
+          } else {
+            dataOut.writeInt(1)
+          }
+
+          val printOut = new PrintStream(stream)
+
+          def writeElem(elem: Any): Unit = {
+            if (deserializer == SerializationFormats.BYTE) {
+              val elemArr = elem.asInstanceOf[Array[Byte]]
+              dataOut.writeInt(elemArr.length)
+              dataOut.write(elemArr)
+            } else if (deserializer == SerializationFormats.ROW) {
+              dataOut.write(elem.asInstanceOf[Array[Byte]])
+            } else if (deserializer == SerializationFormats.STRING) {
+              printOut.println(elem)
+            }
+          }
+
+          for (elem <- iter) {
+            elem match {
+              case (key, value) =>
+                writeElem(key)
+                writeElem(value)
+              case _ =>
+                writeElem(elem)
+            }
+          }
+          stream.flush()
+        } catch {
+          // TODO: We should propogate this error to the task thread
+          case e: Exception =>
+            logError("R Writer thread got an exception", e)
+        } finally {
+          Try(output.close())
+        }
+      }
+    }.start()
+  }
+
+  protected def openDataStream(input: InputStream): Closeable
+
+  protected def read(): U
+}
+
+/**
+ * Form an RDD[(Int, Array[Byte])] from key-value pairs returned from R.
+ * This is used by SparkR's shuffle operations.
+ */
+private class PairwiseRRDD[T: ClassTag](
+    parent: RDD[T],
+    numPartitions: Int,
+    hashFunc: Array[Byte],
+    deserializer: String,
+    packageNames: Array[Byte],
+    rLibDir: String,
+    broadcastVars: Array[Object])
+  extends BaseRRDD[T, (Int, Array[Byte])](
+    parent, numPartitions, hashFunc, deserializer,
+    SerializationFormats.BYTE, packageNames, rLibDir,
+    broadcastVars.map(x => x.asInstanceOf[Broadcast[Object]])) {
+
+  private var dataStream: DataInputStream = _
+
+  override protected def openDataStream(input: InputStream): Closeable = {
+    dataStream = new DataInputStream(input)
+    dataStream
+  }
+
+  override protected def read(): (Int, Array[Byte]) = {
+    try {
+      val length = dataStream.readInt()
+
+      length match {
+        case length if length == 2 =>
+          val hashedKey = dataStream.readInt()
+          val contentPairsLength = dataStream.readInt()
+          val contentPairs = new Array[Byte](contentPairsLength)
+          dataStream.readFully(contentPairs)
+          (hashedKey, contentPairs)
+        case _ => null   // End of input
+      }
+    } catch {
+      case eof: EOFException => {
+        throw new SparkException("R worker exited unexpectedly (crashed)", eof)
+      }
+    }
+  }
+
+  lazy val asJavaPairRDD : JavaPairRDD[Int, Array[Byte]] = JavaPairRDD.fromRDD(this)
+}
+
+/**
+ * An RDD that stores serialized R objects as Array[Byte].
+ */
+private class RRDD[T: ClassTag](
+    parent: RDD[T],
+    func: Array[Byte],
+    deserializer: String,
+    serializer: String,
+    packageNames: Array[Byte],
+    rLibDir: String,
+    broadcastVars: Array[Object])
+  extends BaseRRDD[T, Array[Byte]](
+    parent, -1, func, deserializer, serializer, packageNames, rLibDir,
+    broadcastVars.map(x => x.asInstanceOf[Broadcast[Object]])) {
+
+  private var dataStream: DataInputStream = _
+
+  override protected def openDataStream(input: InputStream): Closeable = {
+    dataStream = new DataInputStream(input)
+    dataStream
+  }
+
+  override protected def read(): Array[Byte] = {
+    try {
+      val length = dataStream.readInt()
+
+      length match {
+        case length if length > 0 =>
+          val obj = new Array[Byte](length)
+          dataStream.readFully(obj, 0, length)
+          obj
+        case _ => null
+      }
+    } catch {
+      case eof: EOFException => {
+        throw new SparkException("R worker exited unexpectedly (crashed)", eof)
+      }
+    }
+  }
+
+  lazy val asJavaRDD : JavaRDD[Array[Byte]] = JavaRDD.fromRDD(this)
+}
+
+/**
+ * An RDD that stores R objects as Array[String].
+ */
+private class StringRRDD[T: ClassTag](
+    parent: RDD[T],
+    func: Array[Byte],
+    deserializer: String,
+    packageNames: Array[Byte],
+    rLibDir: String,
+    broadcastVars: Array[Object])
+  extends BaseRRDD[T, String](
+    parent, -1, func, deserializer, SerializationFormats.STRING, packageNames, rLibDir,
+    broadcastVars.map(x => x.asInstanceOf[Broadcast[Object]])) {
+
+  private var dataStream: BufferedReader = _
+
+  override protected def openDataStream(input: InputStream): Closeable = {
+    dataStream = new BufferedReader(new InputStreamReader(input))
+    dataStream
+  }
+
+  override protected def read(): String = {
+    try {
+      dataStream.readLine()
+    } catch {
+      case e: IOException => {
+        throw new SparkException("R worker exited unexpectedly (crashed)", e)
+      }
+    }
+  }
+
+  lazy val asJavaRDD : JavaRDD[String] = JavaRDD.fromRDD(this)
+}
+
+private[r] class BufferedStreamThread(
+    in: InputStream,
+    name: String,
+    errBufferSize: Int) extends Thread(name) with Logging {
+  val lines = new Array[String](errBufferSize)
+  var lineIdx = 0
+  override def run() {
+    for (line <- Source.fromInputStream(in).getLines) {
+      synchronized {
+        lines(lineIdx) = line
+        lineIdx = (lineIdx + 1) % errBufferSize
+      }
+      logInfo(line)
+    }
+  }
+
+  def getLines(): String = synchronized {
+    (0 until errBufferSize).filter { x =>
+      lines((x + lineIdx) % errBufferSize) != null
+    }.map { x =>
+      lines((x + lineIdx) % errBufferSize)
+    }.mkString("\n")
+  }
+}
+
+private[r] object RRDD {
+  // Because forking processes from Java is expensive, we prefer to launch
+  // a single R daemon (daemon.R) and tell it to fork new workers for our tasks.
+  // This daemon currently only works on UNIX-based systems now, so we should
+  // also fall back to launching workers (worker.R) directly.
+  private[this] var errThread: BufferedStreamThread = _
+  private[this] var daemonChannel: DataOutputStream = _
+
+  def createSparkContext(
+      master: String,
+      appName: String,
+      sparkHome: String,
+      jars: Array[String],
+      sparkEnvirMap: JMap[Object, Object],
+      sparkExecutorEnvMap: JMap[Object, Object]): JavaSparkContext = {
+
+    val sparkConf = new SparkConf().setAppName(appName)
+                                   .setSparkHome(sparkHome)
+                                   .setJars(jars)
+
+    // Override `master` if we have a user-specified value
+    if (master != "") {
+      sparkConf.setMaster(master)
+    } else {
+      // If conf has no master set it to "local" to maintain
+      // backwards compatibility
+      sparkConf.setIfMissing("spark.master", "local")
+    }
+
+    for ((name, value) <- sparkEnvirMap) {
+      sparkConf.set(name.asInstanceOf[String], value.asInstanceOf[String])
+    }
+    for ((name, value) <- sparkExecutorEnvMap) {
+      sparkConf.setExecutorEnv(name.asInstanceOf[String], value.asInstanceOf[String])
+    }
+
+    new JavaSparkContext(sparkConf)
+  }
+
+  /**
+   * Start a thread to print the process's stderr to ours
+   */
+  private def startStdoutThread(proc: Process): BufferedStreamThread = {
+    val BUFFER_SIZE = 100
+    val thread = new BufferedStreamThread(proc.getInputStream, "stdout reader for R", BUFFER_SIZE)
+    thread.setDaemon(true)
+    thread.start()
+    thread
+  }
+
+  private def createRProcess(rLibDir: String, port: Int, script: String): BufferedStreamThread = {
+    val rCommand = "Rscript"
+    val rOptions = "--vanilla"
+    val rExecScript = rLibDir + "/SparkR/worker/" + script
+    val pb = new ProcessBuilder(List(rCommand, rOptions, rExecScript))
+    // Unset the R_TESTS environment variable for workers.
+    // This is set by R CMD check as startup.Rs
+    // (http://svn.r-project.org/R/trunk/src/library/tools/R/testing.R)
+    // and confuses worker script which tries to load a non-existent file
+    pb.environment().put("R_TESTS", "")
+    pb.environment().put("SPARKR_RLIBDIR", rLibDir)
+    pb.environment().put("SPARKR_WORKER_PORT", port.toString)
+    pb.redirectErrorStream(true)  // redirect stderr into stdout
+    val proc = pb.start()
+    val errThread = startStdoutThread(proc)
+    errThread
+  }
+
+  /**
+   * ProcessBuilder used to launch worker R processes.
+   */
+  def createRWorker(rLibDir: String, port: Int): BufferedStreamThread = {
+    val useDaemon = SparkEnv.get.conf.getBoolean("spark.sparkr.use.daemon", true)
+    if (!Utils.isWindows && useDaemon) {
+      synchronized {
+        if (daemonChannel == null) {
+          // we expect one connections
+          val serverSocket = new ServerSocket(0, 1)
+          val daemonPort = serverSocket.getLocalPort
+          errThread = createRProcess(rLibDir, daemonPort, "daemon.R")
+          // the socket used to send out the input of task
+          serverSocket.setSoTimeout(10000)
+          val sock = serverSocket.accept()
+          daemonChannel = new DataOutputStream(new BufferedOutputStream(sock.getOutputStream))
+          serverSocket.close()
+        }
+        try {
+          daemonChannel.writeInt(port)
+          daemonChannel.flush()
+        } catch {
+          case e: IOException =>
+            // daemon process died
+            daemonChannel.close()
+            daemonChannel = null
+            errThread = null
+            // fail the current task, retry by scheduler
+            throw e
+        }
+        errThread
+      }
+    } else {
+      createRProcess(rLibDir, port, "worker.R")
+    }
+  }
+
+  /**
+   * Create an RRDD given a sequence of byte arrays. Used to create RRDD when `parallelize` is
+   * called from R.
+   */
+  def createRDDFromArray(jsc: JavaSparkContext, arr: Array[Array[Byte]]): JavaRDD[Array[Byte]] = {
+    JavaRDD.fromRDD(jsc.sc.parallelize(arr, arr.length))
+  }
+
+}
diff --git a/core/src/main/scala/org/apache/spark/api/r/SerDe.scala b/core/src/main/scala/org/apache/spark/api/r/SerDe.scala
new file mode 100644
index 0000000000000..ccb2a371f4e48
--- /dev/null
+++ b/core/src/main/scala/org/apache/spark/api/r/SerDe.scala
@@ -0,0 +1,340 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.api.r
+
+import java.io.{DataInputStream, DataOutputStream}
+import java.sql.{Date, Time}
+
+import scala.collection.JavaConversions._
+
+/**
+ * Utility functions to serialize, deserialize objects to / from R
+ */
+private[spark] object SerDe {
+
+  // Type mapping from R to Java
+  //
+  // NULL -> void
+  // integer -> Int
+  // character -> String
+  // logical -> Boolean
+  // double, numeric -> Double
+  // raw -> Array[Byte]
+  // Date -> Date
+  // POSIXlt/POSIXct -> Time
+  //
+  // list[T] -> Array[T], where T is one of above mentioned types
+  // environment -> Map[String, T], where T is a native type
+  // jobj -> Object, where jobj is an object created in the backend
+
+  def readObjectType(dis: DataInputStream): Char = {
+    dis.readByte().toChar
+  }
+
+  def readObject(dis: DataInputStream): Object = {
+    val dataType = readObjectType(dis)
+    readTypedObject(dis, dataType)
+  }
+
+  def readTypedObject(
+      dis: DataInputStream,
+      dataType: Char): Object = {
+    dataType match {
+      case 'n' => null
+      case 'i' => new java.lang.Integer(readInt(dis))
+      case 'd' => new java.lang.Double(readDouble(dis))
+      case 'b' => new java.lang.Boolean(readBoolean(dis))
+      case 'c' => readString(dis)
+      case 'e' => readMap(dis)
+      case 'r' => readBytes(dis)
+      case 'l' => readList(dis)
+      case 'D' => readDate(dis)
+      case 't' => readTime(dis)
+      case 'j' => JVMObjectTracker.getObject(readString(dis))
+      case _ => throw new IllegalArgumentException(s"Invalid type $dataType")
+    }
+  }
+
+  def readBytes(in: DataInputStream): Array[Byte] = {
+    val len = readInt(in)
+    val out = new Array[Byte](len)
+    val bytesRead = in.readFully(out)
+    out
+  }
+
+  def readInt(in: DataInputStream): Int = {
+    in.readInt()
+  }
+
+  def readDouble(in: DataInputStream): Double = {
+    in.readDouble()
+  }
+
+  def readString(in: DataInputStream): String = {
+    val len = in.readInt()
+    val asciiBytes = new Array[Byte](len)
+    in.readFully(asciiBytes)
+    assert(asciiBytes(len - 1) == 0)
+    val str = new String(asciiBytes.dropRight(1).map(_.toChar))
+    str
+  }
+
+  def readBoolean(in: DataInputStream): Boolean = {
+    val intVal = in.readInt()
+    if (intVal == 0) false else true
+  }
+
+  def readDate(in: DataInputStream): Date = {
+    Date.valueOf(readString(in))
+  }
+
+  def readTime(in: DataInputStream): Time = {
+    val t = in.readDouble()
+    new Time((t * 1000L).toLong)
+  }
+
+  def readBytesArr(in: DataInputStream): Array[Array[Byte]] = {
+    val len = readInt(in)
+    (0 until len).map(_ => readBytes(in)).toArray
+  }
+
+  def readIntArr(in: DataInputStream): Array[Int] = {
+    val len = readInt(in)
+    (0 until len).map(_ => readInt(in)).toArray
+  }
+
+  def readDoubleArr(in: DataInputStream): Array[Double] = {
+    val len = readInt(in)
+    (0 until len).map(_ => readDouble(in)).toArray
+  }
+
+  def readBooleanArr(in: DataInputStream): Array[Boolean] = {
+    val len = readInt(in)
+    (0 until len).map(_ => readBoolean(in)).toArray
+  }
+
+  def readStringArr(in: DataInputStream): Array[String] = {
+    val len = readInt(in)
+    (0 until len).map(_ => readString(in)).toArray
+  }
+
+  def readList(dis: DataInputStream): Array[_] = {
+    val arrType = readObjectType(dis)
+    arrType match {
+      case 'i' => readIntArr(dis)
+      case 'c' => readStringArr(dis)
+      case 'd' => readDoubleArr(dis)
+      case 'b' => readBooleanArr(dis)
+      case 'j' => readStringArr(dis).map(x => JVMObjectTracker.getObject(x))
+      case 'r' => readBytesArr(dis)
+      case _ => throw new IllegalArgumentException(s"Invalid array type $arrType")
+    }
+  }
+
+  def readMap(in: DataInputStream): java.util.Map[Object, Object] = {
+    val len = readInt(in)
+    if (len > 0) {
+      val keysType = readObjectType(in)
+      val keysLen = readInt(in)
+      val keys = (0 until keysLen).map(_ => readTypedObject(in, keysType))
+
+      val valuesType = readObjectType(in)
+      val valuesLen = readInt(in)
+      val values = (0 until valuesLen).map(_ => readTypedObject(in, valuesType))
+      mapAsJavaMap(keys.zip(values).toMap)
+    } else {
+      new java.util.HashMap[Object, Object]()
+    }
+  }
+
+  // Methods to write out data from Java to R
+  //
+  // Type mapping from Java to R
+  //
+  // void -> NULL
+  // Int -> integer
+  // String -> character
+  // Boolean -> logical
+  // Double -> double
+  // Long -> double
+  // Array[Byte] -> raw
+  // Date -> Date
+  // Time -> POSIXct
+  //
+  // Array[T] -> list()
+  // Object -> jobj
+
+  def writeType(dos: DataOutputStream, typeStr: String): Unit = {
+    typeStr match {
+      case "void" => dos.writeByte('n')
+      case "character" => dos.writeByte('c')
+      case "double" => dos.writeByte('d')
+      case "integer" => dos.writeByte('i')
+      case "logical" => dos.writeByte('b')
+      case "date" => dos.writeByte('D')
+      case "time" => dos.writeByte('t')
+      case "raw" => dos.writeByte('r')
+      case "list" => dos.writeByte('l')
+      case "jobj" => dos.writeByte('j')
+      case _ => throw new IllegalArgumentException(s"Invalid type $typeStr")
+    }
+  }
+
+  def writeObject(dos: DataOutputStream, value: Object): Unit = {
+    if (value == null) {
+      writeType(dos, "void")
+    } else {
+      value.getClass.getName match {
+        case "java.lang.String" =>
+          writeType(dos, "character")
+          writeString(dos, value.asInstanceOf[String])
+        case "long" | "java.lang.Long" =>
+          writeType(dos, "double")
+          writeDouble(dos, value.asInstanceOf[Long].toDouble)
+        case "double" | "java.lang.Double" =>
+          writeType(dos, "double")
+          writeDouble(dos, value.asInstanceOf[Double])
+        case "int" | "java.lang.Integer" =>
+          writeType(dos, "integer")
+          writeInt(dos, value.asInstanceOf[Int])
+        case "boolean" | "java.lang.Boolean" =>
+          writeType(dos, "logical")
+          writeBoolean(dos, value.asInstanceOf[Boolean])
+        case "java.sql.Date" =>
+          writeType(dos, "date")
+          writeDate(dos, value.asInstanceOf[Date])
+        case "java.sql.Time" =>
+          writeType(dos, "time")
+          writeTime(dos, value.asInstanceOf[Time])
+        case "[B" =>
+          writeType(dos, "raw")
+          writeBytes(dos, value.asInstanceOf[Array[Byte]])
+        // TODO: Types not handled right now include
+        // byte, char, short, float
+
+        // Handle arrays
+        case "[Ljava.lang.String;" =>
+          writeType(dos, "list")
+          writeStringArr(dos, value.asInstanceOf[Array[String]])
+        case "[I" =>
+          writeType(dos, "list")
+          writeIntArr(dos, value.asInstanceOf[Array[Int]])
+        case "[J" =>
+          writeType(dos, "list")
+          writeDoubleArr(dos, value.asInstanceOf[Array[Long]].map(_.toDouble))
+        case "[D" =>
+          writeType(dos, "list")
+          writeDoubleArr(dos, value.asInstanceOf[Array[Double]])
+        case "[Z" =>
+          writeType(dos, "list")
+          writeBooleanArr(dos, value.asInstanceOf[Array[Boolean]])
+        case "[[B" =>
+          writeType(dos, "list")
+          writeBytesArr(dos, value.asInstanceOf[Array[Array[Byte]]])
+        case otherName =>
+          // Handle array of objects
+          if (otherName.startsWith("[L")) {
+            val objArr = value.asInstanceOf[Array[Object]]
+            writeType(dos, "list")
+            writeType(dos, "jobj")
+            dos.writeInt(objArr.length)
+            objArr.foreach(o => writeJObj(dos, o))
+          } else {
+            writeType(dos, "jobj")
+            writeJObj(dos, value)
+          }
+      }
+    }
+  }
+
+  def writeInt(out: DataOutputStream, value: Int): Unit = {
+    out.writeInt(value)
+  }
+
+  def writeDouble(out: DataOutputStream, value: Double): Unit = {
+    out.writeDouble(value)
+  }
+
+  def writeBoolean(out: DataOutputStream, value: Boolean): Unit = {
+    val intValue = if (value) 1 else 0
+    out.writeInt(intValue)
+  }
+
+  def writeDate(out: DataOutputStream, value: Date): Unit = {
+    writeString(out, value.toString)
+  }
+
+  def writeTime(out: DataOutputStream, value: Time): Unit = {
+    out.writeDouble(value.getTime.toDouble / 1000.0)
+  }
+
+
+  // NOTE: Only works for ASCII right now
+  def writeString(out: DataOutputStream, value: String): Unit = {
+    val len = value.length
+    out.writeInt(len + 1) // For the \0
+    out.writeBytes(value)
+    out.writeByte(0)
+  }
+
+  def writeBytes(out: DataOutputStream, value: Array[Byte]): Unit = {
+    out.writeInt(value.length)
+    out.write(value)
+  }
+
+  def writeJObj(out: DataOutputStream, value: Object): Unit = {
+    val objId = JVMObjectTracker.put(value)
+    writeString(out, objId)
+  }
+
+  def writeIntArr(out: DataOutputStream, value: Array[Int]): Unit = {
+    writeType(out, "integer")
+    out.writeInt(value.length)
+    value.foreach(v => out.writeInt(v))
+  }
+
+  def writeDoubleArr(out: DataOutputStream, value: Array[Double]): Unit = {
+    writeType(out, "double")
+    out.writeInt(value.length)
+    value.foreach(v => out.writeDouble(v))
+  }
+
+  def writeBooleanArr(out: DataOutputStream, value: Array[Boolean]): Unit = {
+    writeType(out, "logical")
+    out.writeInt(value.length)
+    value.foreach(v => writeBoolean(out, v))
+  }
+
+  def writeStringArr(out: DataOutputStream, value: Array[String]): Unit = {
+    writeType(out, "character")
+    out.writeInt(value.length)
+    value.foreach(v => writeString(out, v))
+  }
+
+  def writeBytesArr(out: DataOutputStream, value: Array[Array[Byte]]): Unit = {
+    writeType(out, "raw")
+    out.writeInt(value.length)
+    value.foreach(v => writeBytes(out, v))
+  }
+}
+
+private[r] object SerializationFormats {
+  val BYTE = "byte"
+  val STRING = "string"
+  val ROW = "row"
+}
diff --git a/core/src/main/scala/org/apache/spark/deploy/RRunner.scala b/core/src/main/scala/org/apache/spark/deploy/RRunner.scala
new file mode 100644
index 0000000000000..e99779f299785
--- /dev/null
+++ b/core/src/main/scala/org/apache/spark/deploy/RRunner.scala
@@ -0,0 +1,92 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.deploy
+
+import java.io._
+import java.util.concurrent.{Semaphore, TimeUnit}
+
+import scala.collection.JavaConversions._
+
+import org.apache.hadoop.fs.Path
+
+import org.apache.spark.api.r.RBackend
+import org.apache.spark.util.RedirectThread
+
+/**
+ * Main class used to launch SparkR applications using spark-submit. It executes R as a
+ * subprocess and then has it connect back to the JVM to access system properties etc.
+ */
+object RRunner {
+  def main(args: Array[String]): Unit = {
+    val rFile = PythonRunner.formatPath(args(0))
+
+    val otherArgs = args.slice(1, args.length)
+
+    // Time to wait for SparkR backend to initialize in seconds
+    val backendTimeout = sys.env.getOrElse("SPARKR_BACKEND_TIMEOUT", "120").toInt
+    val rCommand = "Rscript"
+
+    // Check if the file path exists.
+    // If not, change directory to current working directory for YARN cluster mode
+    val rF = new File(rFile)
+    val rFileNormalized = if (!rF.exists()) {
+      new Path(rFile).getName
+    } else {
+      rFile
+    }
+
+    // Launch a SparkR backend server for the R process to connect to; this will let it see our
+    // Java system properties etc.
+    val sparkRBackend = new RBackend()
+    @volatile var sparkRBackendPort = 0
+    val initialized = new Semaphore(0)
+    val sparkRBackendThread = new Thread("SparkR backend") {
+      override def run() {
+        sparkRBackendPort = sparkRBackend.init()
+        initialized.release()
+        sparkRBackend.run()
+      }
+    }
+
+    sparkRBackendThread.start()
+    // Wait for RBackend initialization to finish
+    if (initialized.tryAcquire(backendTimeout, TimeUnit.SECONDS)) {
+      // Launch R
+      val returnCode = try {
+        val builder = new ProcessBuilder(Seq(rCommand, rFileNormalized) ++ otherArgs)
+        val env = builder.environment()
+        env.put("EXISTING_SPARKR_BACKEND_PORT", sparkRBackendPort.toString)
+        val sparkHome = System.getenv("SPARK_HOME")
+        env.put("R_PROFILE_USER",
+          Seq(sparkHome, "R", "lib", "SparkR", "profile", "general.R").mkString(File.separator))
+        builder.redirectErrorStream(true) // Ugly but needed for stdout and stderr to synchronize
+        val process = builder.start()
+
+        new RedirectThread(process.getInputStream, System.out, "redirect R output").start()
+
+        process.waitFor()
+      } finally {
+        sparkRBackend.close()
+      }
+      System.exit(returnCode)
+    } else {
+      System.err.println("SparkR backend did not initialize in " + backendTimeout + " seconds")
+      System.exit(-1)
+    }
+  }
+}
diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala
index 660307d19eab4..60bc243ebf40a 100644
--- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala
+++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala
@@ -77,6 +77,7 @@ object SparkSubmit {
   // Special primary resource names that represent shells rather than application jars.
   private val SPARK_SHELL = "spark-shell"
   private val PYSPARK_SHELL = "pyspark-shell"
+  private val SPARKR_SHELL = "sparkr-shell"
 
   private val CLASS_NOT_FOUND_EXIT_STATUS = 101
 
@@ -284,6 +285,13 @@ object SparkSubmit {
       }
     }
 
+    // Require all R files to be local
+    if (args.isR && !isYarnCluster) {
+      if (Utils.nonLocalPaths(args.primaryResource).nonEmpty) {
+        printErrorAndExit(s"Only local R files are supported: $args.primaryResource")
+      }
+    }
+
     // The following modes are not supported or applicable
     (clusterManager, deployMode) match {
       case (MESOS, CLUSTER) =>
@@ -291,6 +299,9 @@ object SparkSubmit {
       case (STANDALONE, CLUSTER) if args.isPython =>
         printErrorAndExit("Cluster deploy mode is currently not supported for python " +
           "applications on standalone clusters.")
+      case (STANDALONE, CLUSTER) if args.isR =>
+        printErrorAndExit("Cluster deploy mode is currently not supported for R " +
+          "applications on standalone clusters.")
       case (_, CLUSTER) if isShell(args.primaryResource) =>
         printErrorAndExit("Cluster deploy mode is not applicable to Spark shells.")
       case (_, CLUSTER) if isSqlShell(args.mainClass) =>
@@ -317,11 +328,32 @@ object SparkSubmit {
       }
     }
 
-    // In yarn-cluster mode for a python app, add primary resource and pyFiles to files
-    // that can be distributed with the job
-    if (args.isPython && isYarnCluster) {
-      args.files = mergeFileLists(args.files, args.primaryResource)
-      args.files = mergeFileLists(args.files, args.pyFiles)
+    // If we're running a R app, set the main class to our specific R runner
+    if (args.isR && deployMode == CLIENT) {
+      if (args.primaryResource == SPARKR_SHELL) {
+        args.mainClass = "org.apache.spark.api.r.RBackend"
+      } else {
+        // If a R file is provided, add it to the child arguments and list of files to deploy.
+        // Usage: RRunner <main R file> [app arguments]
+        args.mainClass = "org.apache.spark.deploy.RRunner"
+        args.childArgs = ArrayBuffer(args.primaryResource) ++ args.childArgs
+        args.files = mergeFileLists(args.files, args.primaryResource)
+      }
+    }
+
+    if (isYarnCluster) {
+      // In yarn-cluster mode for a python app, add primary resource and pyFiles to files
+      // that can be distributed with the job
+      if (args.isPython) {
+        args.files = mergeFileLists(args.files, args.primaryResource)
+        args.files = mergeFileLists(args.files, args.pyFiles)
+      }
+
+      // In yarn-cluster mode for a R app, add primary resource to files
+      // that can be distributed with the job
+      if (args.isR) {
+        args.files = mergeFileLists(args.files, args.primaryResource)
+      }
     }
 
     // Special flag to avoid deprecation warnings at the client
@@ -405,8 +437,8 @@ object SparkSubmit {
 
     // Add the application jar automatically so the user doesn't have to call sc.addJar
     // For YARN cluster mode, the jar is already distributed on each node as "app.jar"
-    // For python files, the primary resource is already distributed as a regular file
-    if (!isYarnCluster && !args.isPython) {
+    // For python and R files, the primary resource is already distributed as a regular file
+    if (!isYarnCluster && !args.isPython && !args.isR) {
       var jars = sysProps.get("spark.jars").map(x => x.split(",").toSeq).getOrElse(Seq.empty)
       if (isUserJar(args.primaryResource)) {
         jars = jars ++ Seq(args.primaryResource)
@@ -447,6 +479,10 @@ object SparkSubmit {
           childArgs += ("--py-files", pyFilesNames)
         }
         childArgs += ("--class", "org.apache.spark.deploy.PythonRunner")
+      } else if (args.isR) {
+        val mainFile = new Path(args.primaryResource).getName
+        childArgs += ("--primary-r-file", mainFile)
+        childArgs += ("--class", "org.apache.spark.deploy.RRunner")
       } else {
         if (args.primaryResource != SPARK_INTERNAL) {
           childArgs += ("--jar", args.primaryResource)
@@ -591,15 +627,15 @@ object SparkSubmit {
   /**
    * Return whether the given primary resource represents a user jar.
    */
-  private def isUserJar(primaryResource: String): Boolean = {
-    !isShell(primaryResource) && !isPython(primaryResource) && !isInternal(primaryResource)
+  private[deploy] def isUserJar(res: String): Boolean = {
+    !isShell(res) && !isPython(res) && !isInternal(res) && !isR(res)
   }
 
   /**
    * Return whether the given primary resource represents a shell.
    */
-  private[deploy] def isShell(primaryResource: String): Boolean = {
-    primaryResource == SPARK_SHELL || primaryResource == PYSPARK_SHELL
+  private[deploy] def isShell(res: String): Boolean = {
+    (res == SPARK_SHELL || res == PYSPARK_SHELL || res == SPARKR_SHELL)
   }
 
   /**
@@ -619,12 +655,19 @@ object SparkSubmit {
   /**
    * Return whether the given primary resource requires running python.
    */
-  private[deploy] def isPython(primaryResource: String): Boolean = {
-    primaryResource.endsWith(".py") || primaryResource == PYSPARK_SHELL
+  private[deploy] def isPython(res: String): Boolean = {
+    res != null && res.endsWith(".py") || res == PYSPARK_SHELL
+  }
+
+  /**
+   * Return whether the given primary resource requires running R.
+   */
+  private[deploy] def isR(res: String): Boolean = {
+    res != null && res.endsWith(".R") || res == SPARKR_SHELL
   }
 
-  private[deploy] def isInternal(primaryResource: String): Boolean = {
-    primaryResource == SPARK_INTERNAL
+  private[deploy] def isInternal(res: String): Boolean = {
+    res == SPARK_INTERNAL
   }
 
   /**
diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala
index 6eb73c43470a5..03ecf3fd99ec5 100644
--- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala
+++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala
@@ -59,6 +59,7 @@ private[deploy] class SparkSubmitArguments(args: Seq[String], env: Map[String, S
   var verbose: Boolean = false
   var isPython: Boolean = false
   var pyFiles: String = null
+  var isR: Boolean = false
   var action: SparkSubmitAction = null
   val sparkProperties: HashMap[String, String] = new HashMap[String, String]()
   var proxyUser: String = null
@@ -158,7 +159,7 @@ private[deploy] class SparkSubmitArguments(args: Seq[String], env: Map[String, S
       .getOrElse(sparkProperties.get("spark.executor.instances").orNull)
 
     // Try to set main class from JAR if no --class argument is given
-    if (mainClass == null && !isPython && primaryResource != null) {
+    if (mainClass == null && !isPython && !isR && primaryResource != null) {
       val uri = new URI(primaryResource)
       val uriScheme = uri.getScheme()
 
@@ -211,9 +212,9 @@ private[deploy] class SparkSubmitArguments(args: Seq[String], env: Map[String, S
       printUsageAndExit(-1)
     }
     if (primaryResource == null) {
-      SparkSubmit.printErrorAndExit("Must specify a primary resource (JAR or Python file)")
+      SparkSubmit.printErrorAndExit("Must specify a primary resource (JAR or Python or R file)")
     }
-    if (mainClass == null && !isPython) {
+    if (mainClass == null && SparkSubmit.isUserJar(primaryResource)) {
       SparkSubmit.printErrorAndExit("No main class set in JAR; please specify one with --class")
     }
     if (pyFiles != null && !isPython) {
@@ -414,6 +415,7 @@ private[deploy] class SparkSubmitArguments(args: Seq[String], env: Map[String, S
         opt
       }
     isPython = SparkSubmit.isPython(opt)
+    isR = SparkSubmit.isR(opt)
     false
   }
 
diff --git a/dev/run-tests b/dev/run-tests
index 561d7fc9e7b1f..1b6cf78b5da01 100755
--- a/dev/run-tests
+++ b/dev/run-tests
@@ -236,3 +236,18 @@ echo "========================================================================="
 CURRENT_BLOCK=$BLOCK_PYSPARK_UNIT_TESTS
 
 ./python/run-tests
+
+echo ""
+echo "========================================================================="
+echo "Running SparkR tests"
+echo "========================================================================="
+
+CURRENT_BLOCK=$BLOCK_SPARKR_UNIT_TESTS
+
+if [ $(command -v R) ]; then
+  ./R/install-dev.sh
+  ./R/run-tests.sh
+else
+  echo "Ignoring SparkR tests as R was not found in PATH"
+fi
+
diff --git a/dev/run-tests-codes.sh b/dev/run-tests-codes.sh
index 8ab6db6925d6e..154e01255b2ef 100644
--- a/dev/run-tests-codes.sh
+++ b/dev/run-tests-codes.sh
@@ -25,3 +25,4 @@ readonly BLOCK_BUILD=14
 readonly BLOCK_MIMA=15
 readonly BLOCK_SPARK_UNIT_TESTS=16
 readonly BLOCK_PYSPARK_UNIT_TESTS=17
+readonly BLOCK_SPARKR_UNIT_TESTS=18
diff --git a/dev/run-tests-jenkins b/dev/run-tests-jenkins
index f10aa6b59e1af..f6372835a6dbf 100755
--- a/dev/run-tests-jenkins
+++ b/dev/run-tests-jenkins
@@ -210,6 +210,8 @@ done
       failing_test="Spark unit tests"
     elif [ "$test_result" -eq "$BLOCK_PYSPARK_UNIT_TESTS" ]; then
       failing_test="PySpark unit tests"
+    elif [ "$test_result" -eq "$BLOCK_SPARKR_UNIT_TESTS" ]; then
+      failing_test="SparkR unit tests"
     else
       failing_test="some tests"
     fi
diff --git a/docs/README.md b/docs/README.md
index 3773ea25c8b67..5852f972a051d 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -58,13 +58,19 @@ phase, use the following sytax:
 We use Sphinx to generate Python API docs, so you will need to install it by running
 `sudo pip install sphinx`.
 
-## API Docs (Scaladoc and Sphinx)
+## knitr, devtools
+
+SparkR documentation is written using `roxygen2` and we use `knitr`, `devtools` to generate
+documentation. To install these packages you can run `install.packages(c("knitr", "devtools"))` from a
+R console.
+
+## API Docs (Scaladoc, Sphinx, roxygen2)
 
 You can build just the Spark scaladoc by running `build/sbt unidoc` from the SPARK_PROJECT_ROOT directory.
 
 Similarly, you can build just the PySpark docs by running `make html` from the
 SPARK_PROJECT_ROOT/python/docs directory. Documentation is only generated for classes that are listed as
-public in `__init__.py`.
+public in `__init__.py`. The SparkR docs can be built by running SPARK_PROJECT_ROOT/R/create-docs.sh.
 
 When you run `jekyll` in the `docs` directory, it will also copy over the scaladoc for the various
 Spark subprojects into the `docs` directory (and then also into the `_site` directory). We use a
@@ -72,5 +78,5 @@ jekyll plugin to run `build/sbt unidoc` before building the site so if you haven
 may take some time as it generates all of the scaladoc.  The jekyll plugin also generates the
 PySpark docs [Sphinx](http://sphinx-doc.org/).
 
-NOTE: To skip the step of building and copying over the Scala and Python API docs, run `SKIP_API=1
+NOTE: To skip the step of building and copying over the Scala, Python, R API docs, run `SKIP_API=1
 jekyll`.
diff --git a/docs/_layouts/global.html b/docs/_layouts/global.html
index 2e88b3093652d..b92c75f90b11c 100755
--- a/docs/_layouts/global.html
+++ b/docs/_layouts/global.html
@@ -84,6 +84,7 @@
                                 <li><a href="api/scala/index.html#org.apache.spark.package">Scala</a></li>
                                 <li><a href="api/java/index.html">Java</a></li>
                                 <li><a href="api/python/index.html">Python</a></li>
+                                <li><a href="api/R/index.html">R</a></li>
                             </ul>
                         </li>
 
diff --git a/docs/_plugins/copy_api_dirs.rb b/docs/_plugins/copy_api_dirs.rb
index 3c626a0b7f54b..0ea3f8eab461b 100644
--- a/docs/_plugins/copy_api_dirs.rb
+++ b/docs/_plugins/copy_api_dirs.rb
@@ -78,5 +78,18 @@
   puts "cp -r python/docs/_build/html/. docs/api/python"
   cp_r("python/docs/_build/html/.", "docs/api/python")
 
-  cd("..")
+  # Build SparkR API docs
+  puts "Moving to R directory and building roxygen docs."
+  cd("R")
+  puts `./create-docs.sh`
+
+  puts "Moving back into home dir."
+  cd("../")
+
+  puts "Making directory api/R"
+  mkdir_p "docs/api/R"
+
+  puts "cp -r R/pkg/html/. docs/api/R"
+  cp_r("R/pkg/html/.", "docs/api/R")
+
 end
diff --git a/examples/src/main/r/kmeans.R b/examples/src/main/r/kmeans.R
new file mode 100644
index 0000000000000..6e6b5cb93789c
--- /dev/null
+++ b/examples/src/main/r/kmeans.R
@@ -0,0 +1,93 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+library(SparkR)
+
+# Logistic regression in Spark.
+# Note: unlike the example in Scala, a point here is represented as a vector of
+# doubles.
+
+parseVectors <-  function(lines) {
+  lines <- strsplit(as.character(lines) , " ", fixed = TRUE)
+  list(matrix(as.numeric(unlist(lines)), ncol = length(lines[[1]])))
+}
+
+dist.fun <- function(P, C) {
+  apply(
+    C,
+    1, 
+    function(x) { 
+      colSums((t(P) - x)^2)
+    }
+  )
+}
+
+closestPoint <-  function(P, C) {
+  max.col(-dist.fun(P, C))
+}
+# Main program
+
+args <- commandArgs(trailing = TRUE) 
+
+if (length(args) != 3) {
+  print("Usage: kmeans <file> <K> <convergeDist>")
+  q("no")
+}
+
+sc <- sparkR.init(appName = "RKMeans")
+K <- as.integer(args[[2]])
+convergeDist <- as.double(args[[3]])
+
+lines <- textFile(sc, args[[1]])
+points <- cache(lapplyPartition(lines, parseVectors))
+# kPoints <- take(points, K)
+kPoints <- do.call(rbind, takeSample(points, FALSE, K, 16189L))
+tempDist <- 1.0
+
+while (tempDist > convergeDist) {
+  closest <- lapplyPartition(
+    lapply(points,
+           function(p) {
+             cp <- closestPoint(p, kPoints); 
+             mapply(list, unique(cp), split.data.frame(cbind(1, p), cp), SIMPLIFY=FALSE)
+           }),
+    function(x) {do.call(c, x)
+    })
+  
+  pointStats <- reduceByKey(closest,
+                            function(p1, p2) {
+                              t(colSums(rbind(p1, p2)))
+                            },
+                            2L)
+  
+  newPoints <- do.call(
+    rbind,
+    collect(lapply(pointStats,
+                   function(tup) {
+                     point.sum <- tup[[2]][, -1]
+                     point.count <- tup[[2]][, 1]
+                     point.sum/point.count
+                   })))
+  
+  D <- dist.fun(kPoints, newPoints)
+  tempDist <- sum(D[cbind(1:3, max.col(-D))])
+  kPoints <- newPoints
+  cat("Finished iteration (delta = ", tempDist, ")\n")
+}
+
+cat("Final centers:\n")
+writeLines(unlist(lapply(kPoints, paste, collapse = " ")))
diff --git a/examples/src/main/r/linear_solver_mnist.R b/examples/src/main/r/linear_solver_mnist.R
new file mode 100644
index 0000000000000..c864a4232d010
--- /dev/null
+++ b/examples/src/main/r/linear_solver_mnist.R
@@ -0,0 +1,107 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Instructions: https://github.com/amplab-extras/SparkR-pkg/wiki/SparkR-Example:-Digit-Recognition-on-EC2
+
+library(SparkR)
+library(Matrix)
+
+args <- commandArgs(trailing = TRUE)
+
+# number of random features; default to 1100
+D <- ifelse(length(args) > 0, as.integer(args[[1]]), 1100)
+# number of partitions for training dataset
+trainParts <- 12
+# dimension of digits
+d <- 784
+# number of test examples
+NTrain <- 60000
+# number of training examples
+NTest <- 10000
+# scale of features
+gamma <- 4e-4
+
+sc <- sparkR.init(appName = "SparkR-LinearSolver")
+
+# You can also use HDFS path to speed things up:
+# hdfs://<master>/train-mnist-dense-with-labels.data
+file <- textFile(sc, "/data/train-mnist-dense-with-labels.data", trainParts)
+
+W <- gamma * matrix(nrow=D, ncol=d, data=rnorm(D*d))
+b <- 2 * pi * matrix(nrow=D, ncol=1, data=runif(D))
+broadcastW <- broadcast(sc, W)
+broadcastB <- broadcast(sc, b)
+
+includePackage(sc, Matrix)
+numericLines <- lapplyPartitionsWithIndex(file,
+                       function(split, part) {
+                         matList <- sapply(part, function(line) {
+                           as.numeric(strsplit(line, ",", fixed=TRUE)[[1]])
+                         }, simplify=FALSE)
+                         mat <- Matrix(ncol=d+1, data=unlist(matList, F, F),
+                                       sparse=T, byrow=T)
+                         mat
+                       })
+
+featureLabels <- cache(lapplyPartition(
+    numericLines,
+    function(part) {
+      label <- part[,1]
+      mat <- part[,-1]
+      ones <- rep(1, nrow(mat))
+      features <- cos(
+        mat %*% t(value(broadcastW)) + (matrix(ncol=1, data=ones) %*% t(value(broadcastB))))
+      onesMat <- Matrix(ones)
+      featuresPlus <- cBind(features, onesMat)
+      labels <- matrix(nrow=nrow(mat), ncol=10, data=-1)
+      for (i in 1:nrow(mat)) {
+        labels[i, label[i]] <- 1
+      }
+      list(label=labels, features=featuresPlus)
+  }))
+
+FTF <- Reduce("+", collect(lapplyPartition(featureLabels,
+    function(part) {
+      t(part$features) %*% part$features
+    }), flatten=F))
+
+FTY <- Reduce("+", collect(lapplyPartition(featureLabels,
+    function(part) {
+      t(part$features) %*% part$label
+    }), flatten=F))
+
+# solve for the coefficient matrix
+C <- solve(FTF, FTY)
+
+test <- Matrix(as.matrix(read.csv("/data/test-mnist-dense-with-labels.data",
+                         header=F), sparse=T))
+testData <- test[,-1]
+testLabels <- matrix(ncol=1, test[,1])
+
+err <- 0
+
+# contstruct the feature maps for all examples from this digit
+featuresTest <- cos(testData %*% t(value(broadcastW)) +
+    (matrix(ncol=1, data=rep(1, NTest)) %*% t(value(broadcastB))))
+featuresTest <- cBind(featuresTest, Matrix(rep(1, NTest)))
+
+# extract the one vs. all assignment
+results <- featuresTest %*% C
+labelsGot <- apply(results, 1, which.max)
+err <- sum(testLabels != labelsGot) / nrow(testLabels)
+
+cat("\nFinished running. The error rate is: ", err, ".\n")
diff --git a/examples/src/main/r/logistic_regression.R b/examples/src/main/r/logistic_regression.R
new file mode 100644
index 0000000000000..2a86aa98160d3
--- /dev/null
+++ b/examples/src/main/r/logistic_regression.R
@@ -0,0 +1,62 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+library(SparkR)
+
+args <- commandArgs(trailing = TRUE)
+
+if (length(args) != 3) {
+  print("Usage: logistic_regression <file> <iters> <dimension>")
+  q("no")
+}
+
+# Initialize Spark context
+sc <- sparkR.init(appName = "LogisticRegressionR")
+iterations <- as.integer(args[[2]])
+D <- as.integer(args[[3]])
+
+readPartition <- function(part){
+  part = strsplit(part, " ", fixed = T)
+  list(matrix(as.numeric(unlist(part)), ncol = length(part[[1]])))
+}
+
+# Read data points and convert each partition to a matrix
+points <- cache(lapplyPartition(textFile(sc, args[[1]]), readPartition))
+
+# Initialize w to a random value
+w <- runif(n=D, min = -1, max = 1)
+cat("Initial w: ", w, "\n")
+
+# Compute logistic regression gradient for a matrix of data points
+gradient <- function(partition) {
+  partition = partition[[1]]
+  Y <- partition[, 1]  # point labels (first column of input file)
+  X <- partition[, -1] # point coordinates
+
+  # For each point (x, y), compute gradient function
+  dot <- X %*% w
+  logit <- 1 / (1 + exp(-Y * dot))
+  grad <- t(X) %*% ((logit - 1) * Y)
+  list(grad)
+}
+
+for (i in 1:iterations) {
+  cat("On iteration ", i, "\n")
+  w <- w - reduce(lapplyPartition(points, gradient), "+")
+}
+
+cat("Final w: ", w, "\n")
diff --git a/examples/src/main/r/pi.R b/examples/src/main/r/pi.R
new file mode 100644
index 0000000000000..aa7a833e147a0
--- /dev/null
+++ b/examples/src/main/r/pi.R
@@ -0,0 +1,46 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+library(SparkR)
+
+args <- commandArgs(trailing = TRUE)
+
+sc <- sparkR.init(appName = "PiR")
+
+slices <- ifelse(length(args) > 1, as.integer(args[[2]]), 2)
+
+n <- 100000 * slices
+
+piFunc <- function(elem) {
+  rands <- runif(n = 2, min = -1, max = 1)
+  val <- ifelse((rands[1]^2 + rands[2]^2) < 1, 1.0, 0.0)
+  val
+}
+
+
+piFuncVec <- function(elems) {
+  message(length(elems))
+  rands1 <- runif(n = length(elems), min = -1, max = 1)
+  rands2 <- runif(n = length(elems), min = -1, max = 1)
+  val <- ifelse((rands1^2 + rands2^2) < 1, 1.0, 0.0)
+  sum(val)
+}
+
+rdd <- parallelize(sc, 1:n, slices)
+count <- reduce(lapplyPartition(rdd, piFuncVec), sum)
+cat("Pi is roughly", 4.0 * count / n, "\n")
+cat("Num elements in RDD ", count(rdd), "\n")
diff --git a/examples/src/main/r/wordcount.R b/examples/src/main/r/wordcount.R
new file mode 100644
index 0000000000000..b734cb0ecf55b
--- /dev/null
+++ b/examples/src/main/r/wordcount.R
@@ -0,0 +1,42 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+library(SparkR)
+
+args <- commandArgs(trailing = TRUE)
+
+if (length(args) != 1) {
+  print("Usage: wordcount <file>")
+  q("no")
+}
+
+# Initialize Spark context
+sc <- sparkR.init(appName = "RwordCount")
+lines <- textFile(sc, args[[1]])
+
+words <- flatMap(lines,
+                 function(line) {
+                   strsplit(line, " ")[[1]]
+                 })
+wordCount <- lapply(words, function(word) { list(word, 1L) })
+
+counts <- reduceByKey(wordCount, "+", 2L)
+output <- collect(counts)
+
+for (wordcount in output) {
+  cat(wordcount[[1]], ": ", wordcount[[2]], "\n")
+}
diff --git a/launcher/src/main/java/org/apache/spark/launcher/CommandBuilderUtils.java b/launcher/src/main/java/org/apache/spark/launcher/CommandBuilderUtils.java
index 9b04732afee14..f4ebc25bdd32b 100644
--- a/launcher/src/main/java/org/apache/spark/launcher/CommandBuilderUtils.java
+++ b/launcher/src/main/java/org/apache/spark/launcher/CommandBuilderUtils.java
@@ -274,14 +274,14 @@ static String quoteForBatchScript(String arg) {
   }
 
   /**
-   * Quotes a string so that it can be used in a command string and be parsed back into a single
-   * argument by python's "shlex.split()" function.
-   *
+   * Quotes a string so that it can be used in a command string.
    * Basically, just add simple escapes. E.g.:
    *    original single argument : ab "cd" ef
    *    after: "ab \"cd\" ef"
+   *
+   * This can be parsed back into a single argument by python's "shlex.split()" function.
    */
-  static String quoteForPython(String s) {
+  static String quoteForCommandString(String s) {
     StringBuilder quoted = new StringBuilder().append('"');
     for (int i = 0; i < s.length(); i++) {
       int cp = s.codePointAt(i);
diff --git a/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitCommandBuilder.java b/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitCommandBuilder.java
index 91dcf70f105db..a73c9c87e3126 100644
--- a/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitCommandBuilder.java
+++ b/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitCommandBuilder.java
@@ -17,14 +17,9 @@
 
 package org.apache.spark.launcher;
 
+import java.io.File;
 import java.io.IOException;
-import java.util.ArrayList;
-import java.util.Arrays;
-import java.util.Collections;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import java.util.Properties;
+import java.util.*;
 
 import static org.apache.spark.launcher.CommandBuilderUtils.*;
 
@@ -53,6 +48,20 @@ class SparkSubmitCommandBuilder extends AbstractCommandBuilder {
    */
   static final String PYSPARK_SHELL_RESOURCE = "pyspark-shell";
 
+  /**
+   * Name of the app resource used to identify the SparkR shell. The command line parser expects
+   * the resource name to be the very first argument to spark-submit in this case.
+   *
+   * NOTE: this cannot be "sparkr-shell" since that identifies the SparkR shell to SparkSubmit
+   * (see sparkR.R), and can cause this code to enter into an infinite loop.
+   */
+  static final String SPARKR_SHELL = "sparkr-shell-main";
+
+  /**
+   * This is the actual resource name that identifies the SparkR shell to SparkSubmit.
+   */
+  static final String SPARKR_SHELL_RESOURCE = "sparkr-shell";
+
   /**
    * This map must match the class names for available special classes, since this modifies the way
    * command line parsing works. This maps the class name to the resource to use when calling
@@ -87,6 +96,10 @@ class SparkSubmitCommandBuilder extends AbstractCommandBuilder {
       this.allowsMixedArguments = true;
       appResource = PYSPARK_SHELL_RESOURCE;
       submitArgs = args.subList(1, args.size());
+    } else if (args.size() > 0 && args.get(0).equals(SPARKR_SHELL)) {
+      this.allowsMixedArguments = true;
+      appResource = SPARKR_SHELL_RESOURCE;
+      submitArgs = args.subList(1, args.size());
     } else {
       this.allowsMixedArguments = false;
     }
@@ -98,6 +111,8 @@ class SparkSubmitCommandBuilder extends AbstractCommandBuilder {
   public List<String> buildCommand(Map<String, String> env) throws IOException {
     if (PYSPARK_SHELL_RESOURCE.equals(appResource)) {
       return buildPySparkShellCommand(env);
+    } else if (SPARKR_SHELL_RESOURCE.equals(appResource)) {
+      return buildSparkRCommand(env);
     } else {
       return buildSparkSubmitCommand(env);
     }
@@ -213,36 +228,62 @@ private List<String> buildPySparkShellCommand(Map<String, String> env) throws IO
       return buildCommand(env);
     }
 
-    // When launching the pyspark shell, the spark-submit arguments should be stored in the
-    // PYSPARK_SUBMIT_ARGS env variable. The executable is the PYSPARK_DRIVER_PYTHON env variable
-    // set by the pyspark script, followed by PYSPARK_DRIVER_PYTHON_OPTS.
     checkArgument(appArgs.isEmpty(), "pyspark does not support any application options.");
 
+    // When launching the pyspark shell, the spark-submit arguments should be stored in the
+    // PYSPARK_SUBMIT_ARGS env variable.
+    constructEnvVarArgs(env, "PYSPARK_SUBMIT_ARGS");
+
+    // The executable is the PYSPARK_DRIVER_PYTHON env variable set by the pyspark script,
+    // followed by PYSPARK_DRIVER_PYTHON_OPTS.
+    List<String> pyargs = new ArrayList<String>();
+    pyargs.add(firstNonEmpty(System.getenv("PYSPARK_DRIVER_PYTHON"), "python"));
+    String pyOpts = System.getenv("PYSPARK_DRIVER_PYTHON_OPTS");
+    if (!isEmpty(pyOpts)) {
+      pyargs.addAll(parseOptionString(pyOpts));
+    }
+
+    return pyargs;
+  }
+
+  private List<String> buildSparkRCommand(Map<String, String> env) throws IOException {
+    if (!appArgs.isEmpty() && appArgs.get(0).endsWith(".R")) {
+      appResource = appArgs.get(0);
+      appArgs.remove(0);
+      return buildCommand(env);
+    }
+    // When launching the SparkR shell, store the spark-submit arguments in the SPARKR_SUBMIT_ARGS
+    // env variable.
+    constructEnvVarArgs(env, "SPARKR_SUBMIT_ARGS");
+
+    // Set shell.R as R_PROFILE_USER to load the SparkR package when the shell comes up.
+    String sparkHome = System.getenv("SPARK_HOME");
+    env.put("R_PROFILE_USER",
+            join(File.separator, sparkHome, "R", "lib", "SparkR", "profile", "shell.R"));
+
+    List<String> args = new ArrayList<String>();
+    args.add(firstNonEmpty(System.getenv("SPARKR_DRIVER_R"), "R"));
+    return args;
+  }
+
+  private void constructEnvVarArgs(
+      Map<String, String> env,
+      String submitArgsEnvVariable) throws IOException {
     Properties props = loadPropertiesFile();
     mergeEnvPathList(env, getLibPathEnvName(),
       firstNonEmptyValue(SparkLauncher.DRIVER_EXTRA_LIBRARY_PATH, conf, props));
 
-    // Store spark-submit arguments in an environment variable, since there's no way to pass
-    // them to shell.py on the comand line.
     StringBuilder submitArgs = new StringBuilder();
     for (String arg : buildSparkSubmitArgs()) {
       if (submitArgs.length() > 0) {
         submitArgs.append(" ");
       }
-      submitArgs.append(quoteForPython(arg));
+      submitArgs.append(quoteForCommandString(arg));
     }
-    env.put("PYSPARK_SUBMIT_ARGS", submitArgs.toString());
-
-    List<String> pyargs = new ArrayList<String>();
-    pyargs.add(firstNonEmpty(System.getenv("PYSPARK_DRIVER_PYTHON"), "python"));
-    String pyOpts = System.getenv("PYSPARK_DRIVER_PYTHON_OPTS");
-    if (!isEmpty(pyOpts)) {
-      pyargs.addAll(parseOptionString(pyOpts));
-    }
-
-    return pyargs;
+    env.put(submitArgsEnvVariable, submitArgs.toString());
   }
 
+
   private boolean isClientMode(Properties userProps) {
     String userMaster = firstNonEmpty(master, (String) userProps.get(SparkLauncher.SPARK_MASTER));
     // Default master is "local[*]", so assume client mode in that case.
diff --git a/launcher/src/test/java/org/apache/spark/launcher/CommandBuilderUtilsSuite.java b/launcher/src/test/java/org/apache/spark/launcher/CommandBuilderUtilsSuite.java
index dba0203867372..1ae42eed8a3af 100644
--- a/launcher/src/test/java/org/apache/spark/launcher/CommandBuilderUtilsSuite.java
+++ b/launcher/src/test/java/org/apache/spark/launcher/CommandBuilderUtilsSuite.java
@@ -79,9 +79,9 @@ public void testWindowsBatchQuoting() {
 
   @Test
   public void testPythonArgQuoting() {
-    assertEquals("\"abc\"", quoteForPython("abc"));
-    assertEquals("\"a b c\"", quoteForPython("a b c"));
-    assertEquals("\"a \\\"b\\\" c\"", quoteForPython("a \"b\" c"));
+    assertEquals("\"abc\"", quoteForCommandString("abc"));
+    assertEquals("\"a b c\"", quoteForCommandString("a b c"));
+    assertEquals("\"a \\\"b\\\" c\"", quoteForCommandString("a \"b\" c"));
   }
 
   private void testOpt(String opts, List<String> expected) {
diff --git a/pom.xml b/pom.xml
index 42bd926a2fcb8..70e297c4f082a 100644
--- a/pom.xml
+++ b/pom.xml
@@ -1749,5 +1749,8 @@
     <profile>
       <id>parquet-provided</id>
     </profile>
+    <profile>
+      <id>sparkr</id>
+    </profile>
   </profiles>
 </project>
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala b/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala
index a5e6b638d2150..53ad67372e024 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala
@@ -34,7 +34,7 @@ import org.apache.spark.sql.types.NumericType
 @Experimental
 class GroupedData protected[sql](df: DataFrame, groupingExprs: Seq[Expression]) {
 
-  private[this] implicit def toDF(aggExprs: Seq[NamedExpression]): DataFrame = {
+  private[sql] implicit def toDF(aggExprs: Seq[NamedExpression]): DataFrame = {
     val namedGroupingExprs = groupingExprs.map {
       case expr: NamedExpression => expr
       case expr: Expression => Alias(expr, expr.prettyString)()
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
new file mode 100644
index 0000000000000..d1ea7cc3e9162
--- /dev/null
+++ b/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
@@ -0,0 +1,127 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.api.r
+
+import java.io.{ByteArrayInputStream, ByteArrayOutputStream, DataInputStream, DataOutputStream}
+
+import org.apache.spark.api.java.{JavaRDD, JavaSparkContext}
+import org.apache.spark.api.r.SerDe
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.expressions.{Alias, Expression, NamedExpression}
+import org.apache.spark.sql.types.{DataType, StructType}
+import org.apache.spark.sql.{Column, DataFrame, GroupedData, Row, SQLContext, SaveMode}
+
+private[r] object SQLUtils {
+  def createSQLContext(jsc: JavaSparkContext): SQLContext = {
+    new SQLContext(jsc)
+  }
+
+  def getJavaSparkContext(sqlCtx: SQLContext): JavaSparkContext = {
+    new JavaSparkContext(sqlCtx.sparkContext)
+  }
+
+  def toSeq[T](arr: Array[T]): Seq[T] = {
+    arr.toSeq
+  }
+
+  def createDF(rdd: RDD[Array[Byte]], schemaString: String, sqlContext: SQLContext): DataFrame = {
+    val schema = DataType.fromJson(schemaString).asInstanceOf[StructType]
+    val num = schema.fields.size
+    val rowRDD = rdd.map(bytesToRow)
+    sqlContext.createDataFrame(rowRDD, schema)
+  }
+
+  // A helper to include grouping columns in Agg()
+  def aggWithGrouping(gd: GroupedData, exprs: Column*): DataFrame = {
+    val aggExprs = exprs.map { col =>
+      col.expr match {
+        case expr: NamedExpression => expr
+        case expr: Expression => Alias(expr, expr.simpleString)()
+      }
+    }
+    gd.toDF(aggExprs)
+  }
+
+  def dfToRowRDD(df: DataFrame): JavaRDD[Array[Byte]] = {
+    df.map(r => rowToRBytes(r))
+  }
+
+  private[this] def bytesToRow(bytes: Array[Byte]): Row = {
+    val bis = new ByteArrayInputStream(bytes)
+    val dis = new DataInputStream(bis)
+    val num = SerDe.readInt(dis)
+    Row.fromSeq((0 until num).map { i =>
+      SerDe.readObject(dis)
+    }.toSeq)
+  }
+
+  private[this] def rowToRBytes(row: Row): Array[Byte] = {
+    val bos = new ByteArrayOutputStream()
+    val dos = new DataOutputStream(bos)
+
+    SerDe.writeInt(dos, row.length)
+    (0 until row.length).map { idx =>
+      val obj: Object = row(idx).asInstanceOf[Object]
+      SerDe.writeObject(dos, obj)
+    }
+    bos.toByteArray()
+  }
+
+  def dfToCols(df: DataFrame): Array[Array[Byte]] = {
+    // localDF is Array[Row]
+    val localDF = df.collect()
+    val numCols = df.columns.length
+    // dfCols is Array[Array[Any]]
+    val dfCols = convertRowsToColumns(localDF, numCols)
+
+    dfCols.map { col =>
+      colToRBytes(col)
+    } 
+  }
+
+  def convertRowsToColumns(localDF: Array[Row], numCols: Int): Array[Array[Any]] = {
+    (0 until numCols).map { colIdx =>
+      localDF.map { row =>
+        row(colIdx)
+      }
+    }.toArray
+  }
+
+  def colToRBytes(col: Array[Any]): Array[Byte] = {
+    val numRows = col.length
+    val bos = new ByteArrayOutputStream()
+    val dos = new DataOutputStream(bos)
+    
+    SerDe.writeInt(dos, numRows)
+
+    col.map { item =>
+      val obj: Object = item.asInstanceOf[Object]
+      SerDe.writeObject(dos, obj)
+    }
+    bos.toByteArray()
+  }
+
+  def saveMode(mode: String): SaveMode = {
+    mode match {
+      case "append" => SaveMode.Append
+      case "overwrite" => SaveMode.Overwrite
+      case "error" => SaveMode.ErrorIfExists
+      case "ignore" => SaveMode.Ignore
+    }
+  }
+}
diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
index 24a1e02795218..32bc4e5663062 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
@@ -469,6 +469,9 @@ private[spark] class ApplicationMaster(
       System.setProperty("spark.submit.pyFiles",
         PythonRunner.formatPaths(args.pyFiles).mkString(","))
     }
+    if (args.primaryRFile != null && args.primaryRFile.endsWith(".R")) {
+      // TODO(davies): add R dependencies here
+    }
     val mainMethod = userClassLoader.loadClass(args.userClass)
       .getMethod("main", classOf[Array[String]])
 
diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMasterArguments.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMasterArguments.scala
index e1a992af3aae7..ae6dc1094d724 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMasterArguments.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMasterArguments.scala
@@ -25,6 +25,7 @@ class ApplicationMasterArguments(val args: Array[String]) {
   var userJar: String = null
   var userClass: String = null
   var primaryPyFile: String = null
+  var primaryRFile: String = null
   var pyFiles: String = null
   var userArgs: Seq[String] = Seq[String]()
   var executorMemory = 1024
@@ -54,6 +55,10 @@ class ApplicationMasterArguments(val args: Array[String]) {
           primaryPyFile = value
           args = tail
 
+        case ("--primary-r-file") :: value :: tail =>
+          primaryRFile = value
+          args = tail
+
         case ("--py-files") :: value :: tail =>
           pyFiles = value
           args = tail
@@ -79,6 +84,11 @@ class ApplicationMasterArguments(val args: Array[String]) {
       }
     }
 
+    if (primaryPyFile != null && primaryRFile != null) {
+      System.err.println("Cannot have primary-py-file and primary-r-file at the same time")
+      System.exit(-1)
+    }
+
     userArgs = userArgsBuffer.readOnly
   }
 
@@ -92,6 +102,7 @@ class ApplicationMasterArguments(val args: Array[String]) {
       |  --jar JAR_PATH       Path to your application's JAR file
       |  --class CLASS_NAME   Name of your application's main class
       |  --primary-py-file    A main Python file
+      |  --primary-r-file     A main R file
       |  --py-files PY_FILES  Comma-separated list of .zip, .egg, or .py files to
       |                       place on the PYTHONPATH for Python apps.
       |  --args ARGS          Arguments to be passed to your application's main class.
diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
index 7219852c0a752..c1effd3c8a718 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
@@ -491,6 +491,12 @@ private[spark] class Client(
       } else {
         Nil
       }
+    val primaryRFile =
+      if (args.primaryRFile != null) {
+        Seq("--primary-r-file", args.primaryRFile)
+      } else {
+        Nil
+      }
     val amClass =
       if (isClusterMode) {
         Class.forName("org.apache.spark.deploy.yarn.ApplicationMaster").getName
@@ -500,12 +506,15 @@ private[spark] class Client(
     if (args.primaryPyFile != null && args.primaryPyFile.endsWith(".py")) {
       args.userArgs = ArrayBuffer(args.primaryPyFile, args.pyFiles) ++ args.userArgs
     }
+    if (args.primaryRFile != null && args.primaryRFile.endsWith(".R")) {
+      args.userArgs = ArrayBuffer(args.primaryRFile) ++ args.userArgs
+    }
     val userArgs = args.userArgs.flatMap { arg =>
       Seq("--arg", YarnSparkHadoopUtil.escapeForShell(arg))
     }
     val amArgs =
-      Seq(amClass) ++ userClass ++ userJar ++ primaryPyFile ++ pyFiles ++ userArgs ++
-        Seq(
+      Seq(amClass) ++ userClass ++ userJar ++ primaryPyFile ++ pyFiles ++ primaryRFile ++
+        userArgs ++ Seq(
           "--executor-memory", args.executorMemory.toString + "m",
           "--executor-cores", args.executorCores.toString,
           "--num-executors ", args.numExecutors.toString)
diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala
index 3bc7eb1abf341..da6798cb1b279 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala
@@ -32,6 +32,7 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf)
   var userClass: String = null
   var pyFiles: String = null
   var primaryPyFile: String = null
+  var primaryRFile: String = null
   var userArgs: ArrayBuffer[String] = new ArrayBuffer[String]()
   var executorMemory = 1024 // MB
   var executorCores = 1
@@ -150,6 +151,10 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf)
           primaryPyFile = value
           args = tail
 
+        case ("--primary-r-file") :: value :: tail =>
+          primaryRFile = value
+          args = tail
+
         case ("--args" | "--arg") :: value :: tail =>
           if (args(0) == "--args") {
             println("--args is deprecated. Use --arg instead.")
@@ -228,6 +233,11 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf)
           throw new IllegalArgumentException(getUsageMessage(args))
       }
     }
+
+    if (primaryPyFile != null && primaryRFile != null) {
+      throw new IllegalArgumentException("Cannot have primary-py-file and primary-r-file" +
+        " at the same time")
+    }
   }
 
   private def getUsageMessage(unknownParam: List[String] = null): String = {
@@ -240,6 +250,7 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf)
       |                           mode)
       |  --class CLASS_NAME       Name of your application's main class (required)
       |  --primary-py-file        A main Python file
+      |  --primary-r-file         A main R file
       |  --arg ARG                Argument to be passed to your application's main class.
       |                           Multiple invocations are possible, each will be passed in order.
       |  --num-executors NUM      Number of executors to start (Default: 2)

From b9c51c04932efeeda790752276078314db440634 Mon Sep 17 00:00:00 2001
From: Peter Parente <pparent@us.ibm.com>
Date: Thu, 9 Apr 2015 06:37:20 -0400
Subject: [PATCH 25/95] [SPARK-6343] Doc driver-worker network reqs

Attempt at making the driver-worker networking requirement more explicit and up-front in the documentation (see https://issues.apache.org/jira/browse/SPARK-6343).

Update cluster overview diagram to show connections from workers to driver. Add a bullet below about how driver listens / accepts connections from workers.

Author: Peter Parente <pparent@us.ibm.com>

Closes #5382 from parente/SPARK-6343 and squashes the following commits:

0b2fb9d [Peter Parente] [SPARK-6343] Doc driver-worker network reqs
---
 docs/cluster-overview.md       |   6 +++++-
 docs/img/cluster-overview.png  | Bin 28011 -> 33565 bytes
 docs/img/cluster-overview.pptx | Bin 51771 -> 28133 bytes
 3 files changed, 5 insertions(+), 1 deletion(-)

diff --git a/docs/cluster-overview.md b/docs/cluster-overview.md
index 6a75d5c457f02..7079de546e2f5 100644
--- a/docs/cluster-overview.md
+++ b/docs/cluster-overview.md
@@ -33,7 +33,11 @@ There are several useful things to note about this architecture:
 2. Spark is agnostic to the underlying cluster manager. As long as it can acquire executor
    processes, and these communicate with each other, it is relatively easy to run it even on a
    cluster manager that also supports other applications (e.g. Mesos/YARN).
-3. Because the driver schedules tasks on the cluster, it should be run close to the worker
+3. The driver program must listen for and accept incoming connections from its executors throughout 
+   its lifetime (e.g., see [spark.driver.port and spark.fileserver.port in the network config 
+   section](configuration.html#networking)). As such, the driver program must be network 
+   addressable from the worker nodes.
+4. Because the driver schedules tasks on the cluster, it should be run close to the worker
    nodes, preferably on the same local area network. If you'd like to send requests to the
    cluster remotely, it's better to open an RPC to the driver and have it submit operations
    from nearby than to run a driver far away from the worker nodes.
diff --git a/docs/img/cluster-overview.png b/docs/img/cluster-overview.png
index 368274068e7548517e3f5572916e38b3a63b355f..317554c5f2a5b1022ac594f4bcae774e2ca62521 100644
GIT binary patch
literal 33565
zcmcG0g<F)}`t<+<4C&Af11Kro-O?ROBZz=>Nq2WQ(jlFKbcld-r<4dtr*wP|9^Z4`
z-yiUKU0yS@=ZV?-+56t>UTfWisVGTfpc12kKp+fR8A&w|2wnpOf+L3@0WAu35$(VW
z*i1}O3<Ro)LA!m82z-W_$fzlTK<+dkkZ&LebPY85{sMuVSwWy3BM^u`6$B!%%WPH^
z1TLg)q4CP;m7)T_iLEvB>o>N>rp&I^cEA}Rkf19+@YdSY={3yN+RDa}-&Kg}&k_8<
z`^RP$D%hVxoGgW?UMZ@;By1f_VO-3d%&b(xs4y5z(BaKnel^J#e@_QK2~n9lIoa{E
zu(-ImFuQOt+d7!Bu<`Nnv9PkUu(LA(M=&|M**Lv+WwLRk{?A4JxsIf%qltrsos)&F
z4ear{uZ?Y;orI{U9&hyDfB*TNP8M(fcPAUizuf{l$ny9N3mY>l%YUy8oGSR(%CGET
zVG7*&@%qASf`5+uKW%^SBgpc2^MC!A|Mc`vE6`P8R6&;i4x2ElLN~282qX%Ul@!x(
zh1=6doWqgE$!fp_y6@r=u5172l}?4Op0_Y@0{_pa*?6CowUu@36ItPJDL*sZvIdv-
z4=P$+zO|*LeYoq*3zP)IiHSm?;J+`ok)4g+?P|=p|1|t*Hv$K$d<%d<An^Xau>ZV>
zU_r$<ltCK~|2`WyisS#|QINIK-T&PX)`=CHIthnaqVWp^zv6isg-|F$fQOOvCH5QQ
ze}5+MYhO{rh#4#ee=7W^moNxc^|ZpaW80JNO4&*Ba9?eb!kFXMZIcyDT}YB`T)e~I
zll{Vd(>T}WT6152sJif5AS(I3jx`pD;?cG(woW>l#+*OdwuqK{f=Tub=RbpG#}Drs
zhsUTj1k+GD^yMThhk`708g0lDifudYW?-t(vGgFCK!#UB-0ZLZjG7(=9F)OIx6#J=
zZba_M61ks0BHBdA6N+CghwbY%sj^AbIt-K=HV<_Dpg)h{h!o73)@>jOwZn&pX<VnB
zMl?OS!xi5sZ+W)=uSYXT38F$2M}$k8AZ92KFg{PHMqzfbER^`uFR&r_2zxT!e>K8C
z@_QO&)$Qi;nELKw#pi5$l2$~-NBm=^+iU^T-=|9P_>`$7)nL9@tO@iT@$QrwaGvS~
z{QvpduT$FSbaPmv_KmFj^;wCg$z-we)>+xhDxJcrS2g|vDJ-MJkTP_`ERFJ4aqssR
zHU=lW8E4A1IZD-wF)ih-ED70+!5D<Bo!s+lrwp2<V-41er0pXKEFeGsw{n)nw{pLN
zRNPL~sZ9Qia3==V(J&g5YMx}h#U#x_n@8g`#OG>*K&g+@weI$~kK*iPL;gI5t@!5L
zb-g#r>EYgM1^+^w586;DpE8lkX42k#-xG%8^s_&%YJyC0uGSQ7sm)_{d{D5x)qC@7
znFRq~e1l->C-L9j!K7f?wQq1)3<MXN9E-<eq+`g(YfSn+>NPol;osn!n|fcaAv?y)
zlhZ0?rXoEdSJ)c);P~y{?Om~G!L3A*Zv>P<*^B>;-k))I<%O3D$IT@Zcu$xg*vnu#
zkT~_(-o#%PN<-SeF_@ywsNU*oFC3y(=CnP5E8^`rkR>F5LBbtL79V%DH_ri#CB;&+
zb40Vtp%M}Mn^j9Iks`&6UhsZ*5L)K%A79blEjBPUX49+F?2P9lxA{C|or<17Kb~Ek
zZcP=);xMQeMOr)ex(%mu(fi!rPSsne+ZrBK8MNgoec-o$5bZA2s*r1DX=Y!A!zN<X
zdOncGL0h5UqGd+p0aZN1c$LVcn><rxX#4Y<p9ut#>wwNe&-9;Yuu28NWztE+B;^%7
zTy9$@x1Ou^lS`x%gXzF{7bKA;pp@d^fn+9<n<se8dZ{^UI<;?5K3UF2(<o;tU=VYz
z^0O{luC#ki)tE?g)B3N@4fMxRmndfoPj&eC$i-11Ca_JpZ4BV0^EuLBkntyKRT(Hc
z@6K$<ixr&j%}W4RDgqXa+QvYVbs6Ufo1zaey}rA|a(lq%h1OJQ*9Cvl?zq2ZOz11u
zu8Th>lTevbE0kkf^KYtC%;27Cb#vtQ*x~mhsCUC-(8w_zOjgYjbo&S#Qtx&1USIM&
z8kVD>NA*uM5sjtJ3H6u4A|709v}Iy&{}glA<bBsHCDqtKS4WYe>8*(`_2%-Gh1>J+
z%Om?Q!5B>8J%rogoJTeHD)(A?F(>M^blqS2<RadP`P2tukj$KHW&7w{pYL0SkqI<x
z{2I^aA7uBr_mt1%wSR8A+{!kQs1>=(=eQXug@r48@V%)n&h`+dn9ivuazdk+{sx6Y
zxOHRUlciq0R)r4!hQ?@LI80kS7~P`D^_VJq9pQ7Ka`ti_r*39Zz0wOeeHn}L&lKS@
z4r<BIwVw~Peynq=f)q(v9F|WA-aQ3whyT3_=$9_Jh_{vMf=I*!v(D6zNSRqDE$P$h
zV(LBh0o4D5|Ig^~DA-SPp325o&$GN8O0}9{)c6R!c#_U=soHghgrV7Jvosg@{?`~~
z?euNu^K&4&Om+nzyV1ZHd@V+}KT<0Mgv->Vsl*W=gxuX+oU(C>z7_j0c21Yq^DXu3
zmag9w6my43r`||0@rvJkL#<e8Scm&Vw5ht0+|<bBFIvx<A@~Zdk1DymvT<7e`5sdr
zRVx&N#%e8wv#xab&WYeCHH1x`KKr|)>EXh~f_aOiBMIZYViIY>JWzc~*1m*rXse_@
zKYu1(PMLZp9)fAjMJ(BiG!FVU2A@r(+x02+S%@755JXHU7!$jk<uZCUMNYZeJT7RU
zEcIwLFN>R6uL!-;g*>?FnXrd5ct$h7?$1ZVA;uQ<fgYF&zt%Qm(()^^e1ca?=d@7E
zCsjy=<+C#8J)vrs7KJ1o*2KsEom0%gpxZ)VlTf4-4>ZclZ%Lt+#-t$(T>(=e<bk@#
z*H98s6bT9wXq9ViRhyl*BRQwc7()>>b41~0Zs{f|EbDT-{MY$I@h9rF(7g3=XqBD@
zy7;OK_85F<uudIS<+-h2^~97076jxv><Aj#g~#XcW*s|HJ_gPs^GlO{1iMJBEz!uD
zIubi#vFGJW3%@VInTtUR7LuMF1lQXh<pl+Q_xlJ+kT_!Tp=Oy@&08s#Cp4_)Rf#@0
zmc>r|3O;t%FZg9f=j+U5uU=t62>au0C2>ggkoVQ^u77WTOQ0?AEP&*akPEtY7QNtg
z?~5Xt<<WH4M&iK0p;0j3po?D39_ybjdl{3s@+3hFD$SecvcHhDD^5Ycq$BCLHS%m@
z@#|BRI*MU`c8Os0wa@xv=3S(yw4O$^KX~EAKa%z-RQ|;;c35C2Hq3gVo|G77(i^GO
z=5K)skCTian{&M0$8m*1z)WiCoztb$<WR_L{5;z7=|=?fl=^d&K$DS7zP$j>*WKW7
zTzc%+y`&I~YlMm^AbO^KUL&?@AHU4OSagt)(4Di)L#U(SG=|xmqv<dVG51&r4^0JV
zR2h62j)%pLy)YfgOnW!=u}fIpo%CqZ|2^vXq$=(CXUssw9(!=R-)!@G$~V0K#*<De
z-&rhAm(?;bHrVW>6IT*F2A_#opa5Az05S_w1J`b%yWL%Ly^bIkYEBtmYH|z-%VN@=
zBmlWc`XLjcNBe&^LBoG;gu`|_wyGS0f(WZlhu$EiR7Lf)H^~kB7ZTV+`=a_lSE+ru
z`_tfu<KOpOl<MP6bd^0<LbiZZz8TOpA|1j_$PVz8wg0>C|9P<jHh<HI&`h-dp+49u
z>~X}w3gQ25G>Y(rGU!VF)cYTf1j8XeLI;?U+W%?P1%Tu{71h>1Bk+hOc|(D-k>L`4
z{JU|E3KlqkkHtsuFC5w_2As_YNyYs?jrhQFZwT#g`a4hmykI__E!J7^`QMEVz{XW8
zB{_olFTiUD1<uBVr}_Ht#%d{GjWSU=F#j9x20#Mss$2heYds`CsvxwujY%KoNs5<;
z{a?`t=sf3CDwl^ryDMcphugjTEpS@dE_f*a2O?U4MT@vuvUexEoC-(qm<$8BhlzIN
z^iikU3m8|}Rd#t^GSi4~5Ia2o_q{2gz)&KO{lxzF(-{J~!=6vs_wP}=gaf+c4N_#r
z`uDI!`tlZLjK`Y%Jv&A$$K){gZ0EOS%X%1z01d{@{J2e49S((%xA^NXfw`=&#RXa{
zELcETPz+6wKfNZ(->{Dff0}Y9brVDSvS4TU<zhzTp<Z78%c_-vDL1)^d|GAwJdp{M
zjz_fJVM6=zpUr|7UXwAg$XkEmvlR=4h}VnJtPZ>Rd)YqE7+>>`o-s*@e^ZSkR`4d1
zzSwVFmrqn&UubS6g^**oU%2n=A-<ccMBbp+jC#j&D0zcP#&u$Mbo*7lo9kIAcR{dq
z%VfCbZq%)TMDG}dPZigQ{g}y^`St0Fv(xT~{tkx~>DH%xw%8e~h2B0^xIBfflTRNN
zhG{rWX9Ta$wsE%B@?}G^>P-&eu4@eBOBZW7mf9{l`_Uo;${G*G^L!e{!lPQY4+8q&
z7J4c?o>;6L*TLzSsb~T?{$p&)`@ho$p3Lv!aG7HbZkx^aaHV6bVenQZl-p)SaS18%
zr(<k(mr0RY6SmaV?dmvAV!rD$_v<~rPZnw^%k3W0L5wqniaW%Ros#c4T*LbHnFF{i
z3Kr^xIoH<BY_G-d7ls9X{Y-P@<plR^Pc=p03hVI>d=Nq_CKyPGz@`nA1~%@(TT{yk
ziih&Tfekse>nZw@l~5FoD$SSc*CO`@#i9CUsALR@JEI=q_*}Jd1hL3BG1>WVzLKbx
zP7Hs1NW9W$*`<@y%0p4qy;Sz)I_+!zpiy@E5md%P$B3O^sFKHG{dcj08Q}AaZWZRN
zO!ro^rrNa;!pWH!hSNCX8K$ho5KlJ?Fxx^@Ix4N{d=B<JWk<VA=+v7z>y4M4gsXHb
zsJLua)Gexe$NZugagVj7k)tzn21B?Rjd6ko10ly`)+=7VC~?*;o2N2Z)GAl;QWkTU
z*&ox{6?<byGI|w0NTpO76kAF+s%E}oYjSNE+D=pXWT|C{RXvoM%wndc!|oB^)C>|5
zcHhKKvKY@UO&(Gf%FrzCIW`_YO{uczwq^Xdn>w!n^Kc(XWsvo4*gi-?$#u98pu77U
zPL8nsik!<-6Pl+x29%*Z(Q#U(uf*QXSL5Rp!iUTJJ^-L;fV#)Xb0Uk*{;(GdCL5yO
zw`Y9UK>9=`;1*o_R>3ls9(U(^X^ra4ctAewh)QpL2|9bwt~?%-43M5;i0KxgXhxS4
zkyR|@o-iRR<xa`|n4D^_KmlW6vw6PSS!w3Bp7)3>dVZPl7Gv9J3dMS+Bx1JTxJD&7
zQI<|RIPnEJra`;Agus*Rygp?^m2dF#bUHsnwXUj?-rC$9P@nyrM;l1tA}drN9c7>>
z>LNo{o**fV8_amdRH)|V$b}`o@y<o^n)*MH1!@H82_uWBHI+Lw@j8A`t`-lz&H9GM
z>{@KFY&&h$38bvaS?Q#GIP{aGkhzRT+wJou53A<W8aQ>o7>YK7p{wJ`;=t=+Y&LP%
zaHue8+rv?pOmr@%rQfquIJdJsylYc)<N$^32GPBSk%u3KNGp}^$b!db5NPR?i>93R
zN4)rbeseopXru+Zyz5W-(C+#Hb!PX)3Oy+YeT7!teS(EX%8RK68^jTx`yH;0is>|Q
z`aKFkZ>7eh?3wsuq3u3nH(sClh5f05L&<P5Ayg@Jf@B?x^cP<QxN}BIF<xR*YE(M$
z6tMh_k4n<3zrrRtji#Ow&lGcD5b;D6jbtgaRt2Hr#T)lUjw}|e-9>tTXtN8eTxrdh
zQF4`wXN9{FAWGXYT5r(bli+fm5=FhbyO0w&eTI+E$vbPa%udkAuawM7$#lDJJL4S$
zIljWf7{<NrU@ulS(d4dH!u-(OpI*fI4f}eoXJ;ST;&*g_(_U3JdWG8Tc-^mJsR!b~
zQqM9th3KMl%Zl4}@!9~7#at29DE6Sw_XKht(>31D-o0w#ZPYD)t(;zSY1qEG{DpQ(
z53BmznQ<Z(^LN@Fv-YPX;`1!gucxM(3)MZs=i}OlJ@iZ3GV%id>vl~#o6GSDR|`o!
z<Cy5Q^|aI#J6^7hb;fvTyM9SX`kIRlUz7y#Ou0CtmMv@M*z1F`SB-^hP6l-jeCKY&
zB3_u5^-y@YpXhJU(kq^#tWTC==x%=<Oc7MKo%)%*{UszufmFrkV=QG2bx*!ON{x4v
z94Uw8(A4~1PBf9HN%62&yMd}_p~d>Z?bY$YLwdDs688Wt{Yze2q3>;p-=<nFDCYJq
zj@N0qhv8Njc@8IrJz_q3OukbnQZcM>2-@xsFToWWFsoZ}S@Dwp&ETB{24TGVc02#;
z$8Uk}XV>~6n)(zU%inFq%eA=fbDPR%`{zlbOP4hqT$Fey4HIA_sjnsX{>=q4!#eBv
z&`>gjn!FqcFvu=&mV7Q#xvL2KrF3{I^SepQU&nuP*=OIGu6d^4;hZ5iYo2$TZagL-
zHFmPuFPD$xv~^;k{;ZhDBt)gfAi#X;XW9VzW%MfRa+^NK$l-i0Vp7R;qH)oP;%o7c
zJi&KbhH<w|=yg<_YGF9N`FTk@s<YgR=AWsY5~R<HD-m8mWr*u_LwDNkuLS*ZS~#9s
zroZ_<lqSzZclr=Byua*orV;nm7MC)-r^oKZKZ(<4gQnT@l>AvF&Ie=q6J$T`gR{b2
zPf`&r&gFH40(#Z&uX^3e&EvLP4ux+lDA_#cSO;3K;!d$@;eID-VxBZOytJs&lMPg9
znplc${|gSmgz(ah_a=B9-x_{=RHahinu#j0O_>o~d~)SF|4?^iMx(SNG&0zA%kNxI
z#jpR%f5ORBE+w5xy7v7?8;urJO?tz4B|7QfxUx9vLxhI?5}W82+Y^4nP8xhw5`%%a
z$l;w`FVV1d;>r^Qv?iM(Uedii8=dVEDSMxE!tlM@O-VkB6Dwt!g7$rRo_Xn^-!oMz
zsT^=kJ|pe%mvY5g>*A6VvjxXJ^reMn-y-_S<$mpsNlw!d#w;GjuWH^(j>%Q|ceEpn
zRFc7`SL<dh(<l6f$urvdLxJ;?g{!3<lvP}>+45fGLBp-|mswM&q|t2`@lyB+60+r&
zFt;QB0}n+-DPv&<r0<V{6B^qvXqp0#*NNZAHIf+c`O<0?@n5P~gq3A3qLoymHoTGB
z`eH9=SZSpNyn7whF34BQnkKFj`AfB;UXe0so+TiCo<RP}(n8G3EvaZQS%H$m3$r-0
z4nh5ei=}wP{gRyH!!33J?mp$`Eq>ErOPx=+3Ek8Tt>V`|!#>&s87ma!C|<h^nyG*9
zd$`Yc`i8?0rEY$0vV@u6qI*G6T)H2k%{Nby#*Lgh9^#%{eouOaJHJ)6oM+xtHVK3n
zD>>x-67!G#_&yf;|H0y&NPaCYhYJP$C3RRI^#rrSMKq&yFf--WH}7SerqSC!geZ;U
znffy(i7;Z=yo_nlXcSjvSa}EgM9!IX_i=`f_IL4sA36M_QTJyy3#VC{ski;g^)_3S
za#flAVp9uK%+klkUX-z(ejlFnH1E86kltbSq^VE^qt3G2yO3-Qq=paR4!zzA&ymL#
z$8(yKAN(7a-a~)Q*U^3u_DVlkYLTun_B#GlqplGTkL4#8&dF7(=ifjdHBm`jJkQo@
zexRVyprVvNjs31@DH_q_SCyj2ubqmUsUjt}r0jrUUzVx7saP6Kc{QEFl55L#^6NKO
zl0J(2wml^SANaU#Oo;GG12V&(Q||dEtLl^BEG*?H#8v@8o+w~Jb&ZtBsbO%hLv@GG
zbOZM<Y(7GRf1r2li6CJ4Rha(u_s%q<NsP(jX(NLTRx*QIaWV^=?I!2YnfQlP%Anz8
zHt&YDU4(?Bmn4~<ujM9m={_lh3HKUghhUH-R|lyN=KN~gw|C_-VNxrQ8CcnhcoJz?
zeX>m)iDtsARsh*wZp&CC<*^~<vYHzklt&{NQqD*j{mpL3UXDel(~e}F&N0P59xytQ
zWGid-a7cJK&3d{qC=H~2t6L<ayzL|_Wp)IYm}?%v!#q^P3@bTLO@Uz7xsC;*biX{x
zojzafLU2F(g(alfg`X|t(d)6eK3mn%LwMp8d*lySbMh_%$T+29$Ujs!E{V=~GB(<-
zZ02>gT1*zzn~zgH(r(XW<9ix4W%$H8w;!oL{+|;$z`Ef@gNrQ?a5;c_I#kbQ2#3hZ
zCeWD&-!hD?8U?)VYn?CJ_UX7pwpy<5g;+o~AwS@U6P6dr*Yzx`TNf>d3C<h(u5SV2
zq+Aw(ZAyo0(ZqaJ)W&ywy)VYi5tlI%>nS5ZEa3{gx8mNIKZpz2-yF`+ng*b5+C;Ik
zvP1}GAto6=E4LQnPk;=E1Jc5#PQ_T}$C$PbS$*cS-iu+<0x)y-k!JwAUXl}K>!r_T
zaLH!eV}yZL|9q3l;b(t&QrGf1uW?UkJ2%Q@GY7K{^sO9}(P}hXgeTe_bC|5&ZBA6}
zcg=D@r-iu3-W*$qbZA41^X?1z<mb5n)uA4YUb!W)ew6bQK1LkK7p0e!h$3ODd=OuB
z{WkX`X2bTO#U#d;k?WSTl{HoI%K3=0;W)IImXbprUg#KMG)mE_1)lF_)lYN9CUu@l
z_dyg1LuUXsOxpyq5918l6oL>8dC~1Ak@7o*)|!nf3Avx;2zy<-YAQ@1!WB~k`R#VB
zd;qYTa<DohP5~C!>HgNuq{V3)8;7>lybUL|5R8KT${GcShI3^7Yeb*Uv%{TO!7WNC
zjRN8Nvg<TM=ETF*7DcJv)gU^{Vl8VxGJ|F~yV(e-6=y&LVSkh5V+zf67;z>CJ)#2}
z`G4WO1gMzfA{5*q2Llv?Oqhaf0?h^n=C^BJfRHcOKH1Tcbuk3Dy3??~9g+c<-5h|J
zth1Q$lBN^7&;Xv0+s=n1dlYyvUywm?vC@ay1<``lJu79=bkRh$A_dtJwZb1>CqKWX
z@qUe=$o^2fuTN`{72!KiNw)cw-+6~M&R@Mb6t+6>I0ZLasJ(E&0I@d&FJS)z+|_gm
zP^YcPaoy$o9@t#(G~`m4$qJP|qyxWDB@BmlQ``EyGOm6#43s&?s97p$Hk!3zhE|{p
zOdaIMsq;lYUKkZ#EEGf<B$m!;-%akVbZ!hU9fln=QKUHd69p`1n<_+01-V4>1IVn?
zI?X&ulyQ}7Bv#}>&r^K}!_4QZfR|0S$0=1Sd=;mFfP(ai^C{%BFg)aq+tI3+iGbZI
zXmp@<pRXQ?b-as>SG`D~wU6_Cs<|W>?g8d&HYmc@bvyaq?(_ReL$rV|tWj+E6%+lu
zn0pA68h%mLQ!J3rbnv0n^*#^Yj3;kKDS5>MAzD2sVAOQlp<0~3G3zoCU{Tz#!G1=*
zpdrW9*NtYQ<O?k>EQh0+e5XnCnCgplZ-)o$y`j6vB$+*4Ey<d!zG}gAf06-xU=-$q
zq_7d;E?$7@c0{wzkgyS>619zVzQsR7+ZallgsIpO_tnx+{f*wyl)&U*Yb~gUt;R!)
zygq#paG5yYU$p3pCIi$JEQ8(Q@7j`xqY1Q6Y?~animc{qkKG+M+5cfRR(XIMUSaSw
z$w47%;A%nSe&9i|uB0LA&_IhkuTHS~aYAwZ--Q2zQ7{3{2_E@ni6#`H0)}Ro4JI?y
zyPdvWW;SRw*L(o9E9EAKjXXd+Q}csIqywS^F0&qQ8M_13-&DsHm^7$@R)ufHI!7U`
zuE+kLl+#5iLyNSlV{PwmuQ1?~0M<3l*$hc08qx28T4k?~|IO85e%}wj&uYR!;!yNV
z$D1G(K4dcsDd-WtAD~WP84FkFHb(Q1QY)fys*Ldis$XO{KGT5GPfGFr*_Z3o9%7x0
zk5mu9?r1hF7T?gw6dSE(E<W$*AL-K8!2-97gDjIP3_G$=rh+j@%HOVaA*0qEa{9ri
zq2e)2y>yoG|4Ut2!XDS*LBJUmA?)b>&SRm$ngmd0l6iW9*wJP_0rMI6^|vT0sc<O#
zyMG4kGcvq4mB#tZkweUy9E&~%obnSww~GUPoi=x_yPLxfFw;~9k8PwbNQ5r+P%ioT
zH{FQ>*(gE2e^^u&Fe#13TlT`3-^*>m%xxH`U{1dYkGs8Jr#ZjWMH|A7NrgRAQKm{Y
z%P!~id;l7y1bD&<InV)6yXrqv<RHek3MI+=c$;$l`*P8#DGMYO3-p@ZmVXp@whC?;
z+}3%(ps~g^`#iLhlaICrP-p-TF;xaw{VV+m2!FY%QL)b1zyZNGQ2N%VoVn~<-)dm1
zWbmn9kwPr3(iOJbTxOee$dm20>)v7{(50Rkba-1kvDtk8tdJ#|XEgEU+V!8GlNIHg
zje^%dHB+H0L_$WS?@Q&IlRzQt2@_gcQ7AnUY~rs0q&4yiy{7p4>s^)^nMX+!Nf?mY
za^#X2#$!b8Wr#T5a!zdg)yiS6uvOOF2_5=9DKMNgw3FlXcs&K=0aK||DgcBUiNO?>
z;uW8V4+O+Bqe9owruv*=-RMGCK(~(2!Ab_7<p2P3>cFZ>6;zBH_QNghP`x+o^d-H{
zPY5p0Th8ooB<=esfhWI40{RRZVpcjyiPYSIV~}=yj(0E$6|=^Q^K23hS#!Jl&*Z;a
zzn~{`CIaW=`ilw#btcWV5SN^UOLqAIGyO+-P^n5TJg~nnnc5{q0}D#DlTxMXhLGQD
zJ2(X|nJG2kK67Do&@-ET$B9geYXG-En91@=gR}pnm_=I(K#AL?H!I#Z7;Svb6OTs~
zG2e!~Cli(uAc#6G`MCH~K;h%j36A&%_r+`>fA|&>ap__EP4u@!?_|BMsV%ZF2K{DE
zKr@H}^h;$xb#b9rDC7Ww2=oZDr^g#DtSwxnQT_S?t905FcmKhQ>X{-mg9I(t`-`AH
zQhkX;Tl!0$U?L%9MdFzn;ZGk`du0+3EFUN5Ov+#yY?ToHNB|Iu6X^RYG3O?LWmzb4
ze;I%es0IS>_gL@gL~(*Z8Gx`rfQ?rjD{t-Zs|$lNTbbu)zn1VZ$b|t35-z3QE9$%H
z-NyREOTK3JUFNT$#AzpQW%Gwzv7&CxSPZcG=gMYn=@e@N6FE#6s7KFN2Zmcpvpf<x
zBpBEmt#wDzwsOV2mFI@A`QOMeqQ|<d_PFtTTp^_lXVMTAD%^g>4PUt#zKNdvy?8;d
z+M1fk<4BB3vWeEP+3YvFHc3FQ?a!OYYNOzoyhwTzrh=FpjJlhm-|jgNVgWEpqM)0D
zzYl6X@iK}*bgGzEjj<Fe*}^@>>4AI4PbU55sU3E69qgwvqJU0quR~GJzxsnVUD854
z=m2S^?k65Dq&y6k0aH!=P)s%$B<U8ETJXr^F~RqZ7!=7_huArUOWIqE)^I4$HQaKC
zPZY}xf%8R|Dsk1ZDlTjCCJ*w>J}PwW)jNsXE|&fpD?!u9lcjiP(8h`PEor;V^Q9sv
zw|v4Ivi~xWLHat;=|x<rM@-g4qA*iQ(}Z!G$Ae!u&w&&{<x)|(MZ%<NkTzIKj^~cw
z{|CLo5InnPtpx?@l^5jNrPs(YS(ogw_cIW);dH5vyK|Cf3YYV;`(Gmn&W_e3Xfyz!
z$jI97rL|$p`>36%5(z+IbRbR>^8la+B~+w8UpmHBi2IC!Wgl<`xKA$`WmKXhE(;()
zVrhE9bUxcrhVYG1Vv71=&Ex<!1R&6uh7%qScF3EZ$uB^`{y6Y}iy<FCzG``rVV6AQ
z9SLjQL5}heB!x6(*&lssKaHMVJPa?oB<9F?rC-d_5HD4r+}+*~%O!BaSsSt@pI*?3
zPv>mCnh}2%O)yA!8pn}>8~00oe@83F&w7`5`@pVxHG8=JVvdi$@h$$>aPpuQy^1fa
z>9t3;G#ZOfvNYc8!Y?g1_~tPndm1HnD7{>0e&C&^H=H8;5%IFBMB&sMSIMIC{@x;I
z(EL{<CcoXPS|IA3QW66mnTYpyLU<Xuhx<D>?&;nrk`lYM?iX2CFu-e2Z#l~xPRv!x
z$2S&p^Ltl%f3b1veU96FhmQ!d{oYgwj^z-18^VNd3S^b<`uD7%HVL9}<uly|D}_8j
z!4j)6@i`A0bE^f|QNK<x5S*>Y`JRO)-+iS2D~otU43UOJ`a5Bdp;A9le!n7s1{&o^
zHY`nhN6TW6|CudsVv>NR=_|O#WNc4lW@2nRqC|ZBd!lq&^GMa**HWI;Z65n&Lya~K
zxJGJqLYcaE15Dz-h2#n#13c#<&8~Oc3Ax3ihR3|?ec`?Mq0ISas!OO+C89G<PUcs*
zjOYdoj^=5bcX&2czgE9v;ch-`YL<!HIQ?({G@};t@w{<h8vFtbEmOG?$o%j32$w$F
z2fRP{F8k@-^pCG^b3cefzXFn~13E00*wc-zP#=wx%C*Tq7RYo06KWb3fRq%)k8q76
zfQ9|%P#TBRS~ntKpg{NQX><P_UaC>j?Y8V?)T;x;`6k1$U{OqR!G0aa=Nz@(ckY-c
zp<iuty>5VAwuvc~a~%KrHU9J0wWfpkO5Lwmm3XDL`r`s_Foxv;pF-MaKN(}IC**>#
zRH`b&j**C6V{V-yh3x5m>1fh5&(x<_@+i@BcAsB({i4O+|4Jyz8UIZF?Lqh=>3aK@
zOk~9^0NX}-2iQsA1eqbdee<}v*fGOj-UA8i;K0z6ml#%?BICK@LB@`)jviaDEHB7~
zbG;L`CL0j?whz7(C$gCuyWj2wojkcCRe}%~18bM{HF2Jd=H9Qk63t<UsWuDE`zR?(
zM(%?@RCV)*5J<suPu>eu(Cvy(wyWph?4jD5ooIIJ7wY$#uM;^Q%+ObPxP3HU?o`?7
zoE>VRlI?h0*Ss=FAFJcDEcfk78{{Dhkmos=sBwHr=TbB!^IrFAM&EroM+^Z#__!?0
z5iEv)g~noUt_JMj&owDpt5a{@^>YKr{WR*{D!SiZ*02f2mIEI-a^advbsL#;m7q^r
zeQSCbmfJj<1mTl00mICqFFhokMH<{g3&3Pg6k|d^=#RbvgEsfuFL1R;Y8-Z}qTN55
zINlDyz`>F&I>4HdhP{SGA2Bfk*|_ueL{Ku5Zm*Q++}qKt;es0b^<Jm*J#BuUd%?$y
z!W*y~xu5S5CDdf{Io8gg6WpDSicIB8Kj}rc?!qGJ;=VcC{?fDay~$CbH>az~>!#r#
zeDJX549yP7t!IK+zvaCtdyr2DlWxP$OI6snF&fk~hpR<;vNIL%Q3#gLbt?||PU=YS
zmd)9e9$;bg+wDWViDtsc4-CX_QWWz7?TzEp5k{9Vv3>{;&lj>SEjEP$kvqPWUU9^?
z1a0o=$G++Mcd`rIKAbni&J>mvZ4;(?ZY#DYg6TDHxPDt}CsbNx$`j0v<_>&4)yCS~
zDMXvlHpLda8g(L`Xcw+nvX9llxXvq-D;+9A#(lqmwpGyE);GE6a;WdtFMK|{!KL92
zUZ|22s0eu8RYJ((ZC;bpGy&h|^!&o_(==dp=>C>E{QJujk?JtBE`P*FkWRzHpA3~j
z9PqCf6I~di;S^q;zY@z5oq>%-i|!&SDg!`}7lYy#?aqtr;{Z5o+=ZZXlsj-&nPG=;
z3LKk11);_|%ssX8iI{eeXg6U!Z0>3Od!0IPEm#q+UU4CeLK17_8m0v`KNckwONYT6
zMDEUT`~r<L$1=Z$Vg-bezHMr%B^7c{l->C8H6l$kuZoZdp8`occ!vE=e{7{7csm0I
zeGc`-NA*EEMxJ5pav|`EJlYy31<jS6h$UfWXV<;7nHU9_qMGk%O(e5`hV{0iEb+$!
z$M=ON8A^?ZLU|%I7n*es6SdzCFSrDL^)4a5Xk71&l#8PdF8=1FYyT>k;n^w4Z=xW*
zOQVkTwO3DHz9`jhV7<Vm8N+CKQg`(P#m9O<f(#dv_CBjiOhtVvLYmbvtJyAUa2=tJ
zN}@C^P#qU(d!SK6r^Ai2NLQVDWeM|pu*x<|YBU1aaTdsY(-h|YqqV(Rb^Ywj#e-NF
z>Xl+e9&Qr=)?nnPxFMP`+q)^c02NBm##D)V+cWjg?*X*W>2~s_5=m*~l3=F6T9=sL
z>0@R3ho8BM2x;BVIa2RM;m?R|KUcaOE-ToG{>({&FByM>ink_>bZ`3BPeO3PFAdZG
zc$-Ze4e3W91#5i?B3M3wzM$(C#X5~9YOLHZr+a8S+@I@Alr#4OLhgkBhJk2a4hs1F
zBOHg;Lsof6cJ)WHMY5Mj&TK!o8LaU@bzE-e16fKL(Zp$C)mznR^1r^FrjYJ?9G6z$
zDoY9ZT>d0-A>%l&eYr2n#gDONhqCx2(`X-!le+=FLg{N>(?{(UStqNF`l@d1xn!55
zQ=M=bXVPPi-)WbOU&F|gjIKTIPq^Atyj2fZd~zIu9Mnc@99@eH3n@;<e+yh#Y^Phl
z!#66c3Wn-lWk>BVCq9y-N#6Z~PtSmzC3clNa0i$_3ZzC8e#waN*gun2H&B1GXD$F1
zx`8^xnh|2K4q!55*1np9kqK)oC_pgO%3m42HG!>UMN)_?+sQSi#Bg37{!+ml6Bff}
z?4Ymv<(SHx>s&Y6z@*ywT)d5$e5d;pYfyJ0GOhBe$*vQ|1GsKAWa#~Sk_kOUQFgJs
zBbJM$mQi_e$#C2-#YWh0t#?-065F=2ofK#WUWf?X(E+_JT2-d}PQEIDN}*KOshIn2
zx>ReE%F$beoK~JNq?xNyTs4tfb})18!>_|(4~xlV69%v-=e6YmNUG9cELdOqGen%0
zRG%&BE+4bB8Ztjom?Il5^NYw^F-gJ&X~U(^w07Xj9<RAw&bWgV9Mb$mF>CY8M+cN>
z0z^{L0(Z``USSoJ&D-4Dfh@b_=pYk3nh?$Br6zJD1kq;4cq3_XyT0!k=N}LXso;JK
zd7fmB7&dLx5)uYn{ODwY;3*h8ZVtWnFHqE;TZ~6IB?K^;d>EdEANS5c663AuG%;nt
z7cjTiwbMHGEu+8N6G_xSMa%9;_<LT~Sv;2ItsFC$n;p`uzavD3EEJ2|eC^D2T;x*5
zVv=kiefKM$%u`OqF}Wa&8$J-3XTf((JCRkrXbN5P@AbG08lmaj)&seitsY2DZu0;}
z7G0(C)vh07^^-}X4d^V!IY5W7<@?;^!13Ue(yJHQrFHJ-u2}Y^dr1gzSC@i{ngOM~
zGlP%%WiN};bcyC1*y_B%t1VpX+t?WT?%Wu|@U)T@8w7~j3~3@HwwvwgeOT1*o|fvj
zLu@zMd6_j~E!No1mTJGtI9=o}tr#8F$k!uK^FXH~M{8fmcIeytS#P?0P#+@eMb!}%
zLuT+P$-E^mkr7YuQ{mM@h=N$*c3fp(@~lf;w@8X;o<6ICfuHqs-i~B`6V|!@zD%yP
zF*abqj)?7_=3iMU-bjX4uX+g=%#Gdth7g(a{Sg*IiKGJk&<qZ{X+$Pq_Zg7@(Fpb|
ze(52LeWs8Om)89z7BCo&w|m`Oj#^wCEMc$*EhjzKo`BeLIQ*1h-fcCImj{N7a@B#D
zp_O&AP`;14caO>3W|b6^*5Oi!j|!$5fP`V(K?B8La@AfB0nxDWx(C#Etw5Ca-r}S)
zQ;d0B>UY@_uLmNbyiu)s781Gy)1pHNIR(h0+9K2ihR7}fN7B%_SW1bxC+NZ|5H2_$
z`pcNKyBc_RK{!<k$Wt0LQOi&wH)tfDFdpD>U2mJ2L6r1R3js)!OAI)L%&tRhcxUkl
zbUzAO@oG-1xmW~N4<2C6)EwCd6`^uC07<;ESZ5&wujqk*PNlOGUupIT$3IL-z<`<q
zn3YyY?5L#(vCN*|)?Vf#dP|O}bY1i-NU9JRbG_aqecRJDgfx*$okhT?wa2(ZtzYaG
zb3XJ|z%fg>SAoyGeaN3sIRumJ$GqF6J$#A8Wk@PpN4a6(_WdPo2(LCFPCxF5b2)?g
z%FxK>M+%+iiDDmMrek)Lp8ma{biT#=_j_~Wb~3YG;53BZ5$L6EPBtq6ESw#Df#$6W
z3CJ}G;LB&32nKpOCk^s(J<33tMH4C`dWPj&r<(u53a<M1Y`x*+))e5tJY~RHPKpy0
z>s*4`(TfMoQMZSQ!2f3dA(MvqbI@vL(rt4!i(m0j%*pB-=E)KDT82#9`NE|0uF%`D
zd7MjrH@xS#_v$cX7|~dfSdLuZ6C#D6SilT@ynO5D<K2*p34H-q#14@ut~hOIJNB4n
zan!x%>qVF2E$aS8+M|Y6@63wldnu+4P^l1jv4~E9F-()}vKD_>>#`-_RJcUg%UH4W
zpzb{U1Q5Lzkk7ceC!BV7{N(1QIbr@LLbo_a5=f3u?@_4cid#?>K96~K)fbzoch`^$
zJB;-g$|m&chtS;Ng9VY`E|a@6k*#rQ&dmLOgPx-Le6G(f8cApa#s~^{KE{hd50K+S
zsOrR8Kc)zk%QJOC1Y_sd+ay-dp?iy^W-iNB=*@styz{s&)e<&X5FhS#zDo`jrW%@1
zOuGd*$U`2ER!1{in58#rcodN~9UeL9Cf$=J2^b;diSIBO;#;9uaVR~MfhqJX`kC(|
zF<5t&$%Z1@$m9Wl^y(KNzrZy#)QV#u3E{;_5UE}O*Q*}wbKX?x7&4gwTcptoKv5vV
z;5+Amzf=u&6f_?E-r^FoE3vB56D9r`;paB2_})f=;gPSS5s$unx+V}ljU-wyREA-M
zhZswDX>E*@6$<p0Hy9v=`;Ou#3}C)o_<&8lp9W#S6*c=KkOd!u;V<=m4yKGols(f1
z#KK$u&Q3oBzCE<$ZzoF7_lQM;;N_klU)+fZhhQ%hc%UVKgWCON(Bh`oU(S2+e5E+r
z#8WuTXcb2sF5&R>10?l*0sa#y&}%XPRrl4M*RLQBxkFAu?4W=4eO`!BFAF@pgg}r8
z$NA7!s8q-_lF`H@vB_r~V9UZroXjdl?q52a?e1)Xv(YF6_|lALfdhQJ9vY07jS<=*
zFtr5{RFTbBsf3m&-A*v$C|{b4nGy#YV2S$y<lGSh{AXgCR=^T|f{Ml~o%7?Fd@^g?
zM1p86X0Zc!SrT2K4IO;~Sm|OgBfwCH$I9F6#q`Q<uGpuPb))MI>)Rnh10&*q7pxkA
zg64}26;=MZ%|a^PguZDC+a_%n63z~?tP-7q2>5*v3y^xVc1}?Dg(E;8D^wm8Bl{E8
zhbkgdZB*6;4zDMgh;=4C+8+m8`eePnJYiD+y^>iVt<dL*G2eZKjr11r_9h61?E%Oj
zmmxaF6Xpf&%Nb!f(fihhhR^8zJI%nNIYT6GM~wYLDnv~pG5odNUa{b&e*~!E{-;pg
zYQSg-c?wYIh}hK!8rC=G`)*7Umv17;g%*BYFSWR&N%|?gwibmX7l{3I245s>Pa$at
zll#iNmZetw=-DcY3W0x+25ky@&H`*`ACBM=`aDoy(W|Cr$KH6+*T2jaPXjDaxDa1x
zsqdEwCQJV?P}eOCrUa7*C^pkN@*xj*Zs?EKzxU?VNr&(3Qn<ppy?19Syg!ODqf|nS
z_-J~Z7MmPtGY$Z~>gO}uqquJWoj((R^O1)q{;r=ltzN8D^N?_Wj<3rMB-UgAoy<kg
z%4LKP4Nct78@MK(zrlo4EcJY;BZmT?jn(N`2XGlci9-7ERxhI!P$lvLAZxhsRW3?1
z9~mvtRe&UCu(NZ%(lKoJlm+<4XT13th!J=JGF@Sx00l6SL6gC;f%FEjN2)*CBVU7$
z_Kdda%XvXKf)E^h<vw6NaJk>#Hu>QWP#KxcR_aI9ui70AH?F9TGer4+Q4z9<1ju3y
z;<*dIX6~n1Pt3xg3}%%3#`{LrooEEibNhHdCSiF^GM$vZDIb97MF5VcQ5--EF~PU#
zkEP^W#!U|KGsN>G;c99INP=o7(Un@~3`3(NOFfVuu&qu2*wOs>$5-Ytk_Q(tNYVqF
zQwuRr-|+%aI!<d>`U3*^i}WHM+1oLowkH}2Ir`B3R(|M95L(|Gv@+~a2>d}{=c9HS
zRy$i|s1C3}SA6e_?-zG>8_%(y4Lf3q!j!-(XG%sdjx6ZW4l7eytFWrQu)Ouf)xdB!
zkkxqr-S?e5pYM}ZTSD^#ywY{Sc%!GlcKf~T)Zk1Dl0?wyYRrC*)!C$pe0ORSdHwpL
zGV&+j3l&|Z&XG-omUQ;%=-6SxyApJ<sGyZo0Seo6u~_Xauro}$=49N4<1$MoD`)4Q
zUl->)R6JmT;=;)|_`il@Ma|_SKfG71xW2qKsTdVGl*eaz>*B?_nAN$hd`oDh8t3@9
zSRv7ps4P5Kqf#KBxz{_B{$`#>t6hR6;>C#5%Oax&IXDclCBuVTNO;^6l{nB?B5oy+
zcKRPNqZ0vIJ*~7&DJG9-SPG;+yHAVv#qwCcNhHv>xzr>0DSaf}k4^lSpLkRfgyzy0
zj<;LZB_<!_%m5UZ+-qiWV2ge{+nhZIR4Y8bCZ)fHWSv;P??r7xai4Sz&RAV@QXsn`
z7j%nCgXF2Z5I2Br!m|oc`o0~{Kr^|4Y3aAzZqr#FhKfZ6rX&sXJ|A*xZdLXGN);%d
zUI8Khv20FB3dF)ut{-aZQvDj`xfOq4Ae5naIa<_W4-lLaxh%CRJ?5%kCvsaah+6cu
z$bEW&Dk+D<K(?+3Npk6z&H8hVN0K||6WFy$%q}`5o6j>)7hRHn`x*SECO@>E+v(Ss
zK{7@;`kmg|{6qn2-=l_Ny9k)1{$2ML?du)3_7$m%kGu7#ep{JS!_S)pz6~yxjtNjS
zgwjTx-Hi@@I|d77akYg7Gq9?rH2<~1W`_HEf6G-RHJN-fP(l{h3y%T!Jih?3Z-hpp
z+4|0NyKP2gjWq9~xz)vET*WOU`f&z5_M8_3uC*1g;rF>Vt?3;)XHD`y#Xuy6KhmDa
z8@9gwp5~#LTFpaoQ~1R2#m|(ojlcC-KpY2Qb;>K^(B8#=Y4V;&G*Va7gi?X93laM^
z9X}ilwY6;x8l<~;VT*5&@yF8w0}R}4)d@Vr!cM8K6tc37@s1;7lBB_6?DqToo2wm-
znUhmI1vQz!kCzU5bSTeEcm3QNNf|6DfhTy_5~=g&yGAilnWV+<42CXKp33%C!WYiZ
zn6*?mHJIN^6#Qend%TtRBQWUjpb^6VpB<Y(0?2iy0r}11XF-}qo2<Zfu7lUkoClrt
zV%rM6O2e=3Dd!Zzo7TF3Pdca2ry_4==~_Ma<Wq_FZe_j2jg4*9vE}CPjK(|nlBHev
zX5p5oTM?|m7p*=I%PmwkDIw+^wkz$<?>cIhHIo=L=>UQpm(5u6v7T!<jUyyqW;Yrr
zFbnd&zcTaMsS--Q{p@|m&vLU?6>i0B(CkEyN3Rz6B9icR!s$l+izs5fO<?L7VsAW-
z$#-%%p#&U+W3VGd@7hV=&UW2aVwDv}y5KGkYN5Z+Mt{8DIjNxdqbs|lZp#GSkKxq&
zA%fYkWzCdCIZHTS9Pgd_B6+~CtB4ehdL!~?hdY|2%JD#N{nqb;ySMS<m0K`kF1I2>
z=1(4qA<GixJv~J4PvO~*0hb7;{SQfgho6uofV+m3VV*QUN^F3-4}d-zzMxl%S%PVg
zwRqv!&rqW%M6$eZ_IU;p>2UzMH+-Sq!erI{?AK%UOuYR;b^znc$|FMC??=}jt0~v2
zE74>E=0mA$Zw!LPXFmZ7yH2|&Uy9rDk07PwN4yAuXAbin6ez6HtBV`S?2z2Lu+9M=
z{~&~MA5Mi_N2Q7~5l=l0tayUzc5_aaRJ#1iLSJ}n`im~T-skG?QE*EOsuzCwA00c^
zH1cG;!$}0Re4P$|Bv~eMs``UU(3138J)^JzgR{}^c`fkpFhDk20M$(7(gi~%h_Zn%
zAnSWTH6NGla^_1Vo)nbOb-<FO252AV07d%9ZRZaF;-u>L&-N&2k$L;iwQC98D!rjX
z?oQDnbq*VHr3P)ynl3(fzhBZs^hLW>Q8qNoDE+ZQLa4xc1`^H}_Y#F^*I9Xz;pT{{
z*&`JtF2!2qc;dYU**^J*gIW`xv%O!}>3(TgvH(1=TC;kp=|x)lH|l_g{xdo!=LLlz
z`@odVa@hL=AsJIk?n3v9=CS-f<w!x&&a?4P50D)`SI!KPb9(jFIGkdOu1I^Nv<U+A
zz2&U*sgf7JI+B-eo~TC^?bDkb4``HWOLsRV2S_VJIaT_UvT~c51k|(CrY}i}S^MWK
z>bB=f>gv6BmHdg+&=ewAgEpD9lZYD+Wm78kww^zyT4<j&B4)QqXO<f~f34?p+m>w4
z?{LCt{k=UR-FeSC5hWA>N^fqJ(*!qu#95K}lF-69$X<dPd00;rm6PwWnhgLI-kR0`
zos+7vM)WBO$UN16>ZOW!9_xjkBF+!ICcWqe`(!jdiS+6dK#3xs<#MarqmU$A3Fxbj
zP{>gHk$SAcr=V3L<rd2l_FCwF6zBIBK1F;|ex<scX@;wY9Ga|GWgrCa#*UVi3y53l
z`7fe|zImemNauHc7Y?O_&k*vsIIvC?5aUM1AeICi8+pK#PzUB`3Bcu?0amX3ECArC
z*BF1L1GsTq!0W=GUHeoFt$1U5viPy86HxPs3gwc*X%tdL0k(NV1i5(#&|OO;!?5*y
z0C&VI^^d1He59;Kp#ASn3A;0|c03>X4qr2>)sw(dhbHXSJ<$U-O^cx^Z6^&Z!Z`z+
zXQ9$d3*7nUs`*DB<~>#+IH5s4w~7@RQ@K!vlXqX;nJi}8B{F@smc0fvJ`4Kg)LUw0
zKb9~sYE=|3F!2+)yua$$y%c<xC=)JtC#^~)&3>}_pe~K|p<~uMk6Ur)xMQacIYuq;
zXpPRY*XaeH7nIwIkeK6Raa^NYA31|w4Q89?Rr&&Vg*1y{TM?DWOrg)L?V7yJN}F;A
zP%pxTH~#3<o-VtmX1ei+I_cZ#y_)AR%OM=kQ~Lov-VW)$;<Y}`eo$#z7^aVRugOt@
z_CA+lWGxZTsi#2Q$fq<Zo=8_*{Omc%eD`Y%@E|t75)=1g%a_g%JpQ2;mWRl@(m~;h
z(*1OUf-1;kcY1T>o^RK^we=Vt3DcDb8Mnrts0vV=-czHR6uvj_14P^7Y1Y@t_0KqC
zC`4#t;UWE+E${a)-D5FgIb!1<D@-f(nqKV&IRF|!K{y`ckJ!h`VL-qv0&pO9z5Ezw
z7sU>M%QK%;VD}H-UY(}J`Z>8h14@AlfdA0z5=3XfFp?aO4pf2t^S1y9SSk}-pJ2}d
zC9?;NkU=1gORKK{YF|&+b`e)<00Ddwn6>6WB&-KaK?k&`g6?ObqUS&QVn*-o0ii1G
z$mQUBT2&tfR^&Q>k-+hM0LgX@2pdgGLJdGkp$d@XJnD*p?*WuA|0pBY<YA|>^VlvA
zNwRrepK0|Zk;FX#65Asgu-@{|6e<hjg-`DE&Lphi*D;xrUcphtk0l)&wa?7oJlJRz
zY<+StSZQ{kl!}CAy}Nyt{7FJ6k=tUcw9x6`2VUu`Qo=iS3-GoS(W4H`h=F-vXD_AY
zopyG$($v2GaCaeV@xFN?Y;vo~+qzr8;TAX7r#&v(D_CtDzR6-beqOH?aG+~cYH{r3
z4f$`#;jVF}LW`q`MZcnMZk)zEcohJZLMQfXo=u6{tTY+7rJ8iZ1^Jc_aT>*PZs}b1
zyeTC>t%_v>Qp^YO4n-0PyeU_b>C$eUri1<T$$?K9=7$TW<%*1nJhWfci)2!7RkD4+
zER;ZS!30#pEo)7np5TOgC4pV69PpEj^dO}3$2vSf>gfvQZw?LSEh!}728D5-zlx22
zDk~0y19WB+fW+p6ZGGT(&SN(nQ2EglhC)or8(*dKDIA4-C(z^;faBU6;CKW-YCf49
z<%lftMW7m+o91aJ8hjKU=gaftd_o?Z%-kmbhgTimcfSDbNu$9^yB(jGMZ31goWN@=
z5Urp>=hM4#vA|$7`1niUiJ!7TX3{v!egPIeT*etQb+2G_qE{UKh*QW52x0zj(f!-k
zM|%M3v1wEWAuJ#mGf+bk008YTI&nTs=x3>{aTmy@W!~!xMi|gnj9{9^2hiJ|`>$9e
zOkD37+zEV*#ELr9%Gyf<5@+3)dRHvJ$%M0p;b2b@9n6ZoLZZh@90`7X4;rku8N}Q`
zzcC=#@``?*Rz70y&u_ETB)yJwQF{^+PC$z<(C_2yrwG5mTee`SGrAyMp!Y4WT=UCw
zF($s+H&Y?yLf1!Y)E5*iTy@`Dy;8^p-4$4XigxcWw1nEQu#o5voFjctwiUG_w4Oqn
zQ6z3uiq0$|TYdRE2@r~C9<YObcVfz>1Bjl(knTTx!=`?LZaZ8&nk8g{L);%rt=8`8
zMx$ymQ9ubbfR<7C+{R55-sqf$yXWR!9jzf)`V4WP<lgzs$jAc`9z!jEvUTB0Ju(Ly
z1P`(dupinjX1eV_p}JKT5Yo9X5DGSc>7n%%@J5<X+W@=wv~3?FGeRw77?0C9^{HQt
zXa*t`3Ljt;%n;^E6DPLgG4W$R(k|1kqp8&<7xt7PVAg}}QNr@XiwIG#0Luaf{EV#y
z0qJ?(#zS@56a9cm7kbl5;<C`;8tVu4Z+<9B^0hrEzbOyxF+=RFSVIcG>8hpmr;iUz
zlO!EVzA?SN*3rejd!UhYl!{Aw&|0K%P71c7^6NMMmZ#w5av+pLz+$-bwCt`LMP$5r
zSU?7cCUtfQUL2`wP*(o(L7-t>FM*CDVRob5XSQ+0vur4&Dw3&~>J6U!Lr#S1ud!UZ
zcZvO;<WxN_FWg1ReV=!}fyY3-^*n+<k!!G78emaqb!Bx#+hh$?10lgo#cFb`v$?CT
zH<lFmFAqgC;LRL{IwvnC8Ld3!lz~41@Om@jWjx@7nQ3)RvQ^?qFdQQM-e^nlXu#uA
zWVIJNMM%gJ8qZ}}%?Bg9wsBcZ^o)(IHUs9T`IhfC#NE`ZS6!DzG=Ve7>5RI5__%>6
z|F5;T?y9o;zK7v(fI|p}76fUP?(RmqyBkDGLAtx8JEXe>lm_XN7Lk+|=@jAF-1q(Y
z{@%bd#u@y<IOmFeU3>4f=9+V^XHsW4iBCnLV;{ICw>W(;tB4iqC^X+wNl~2<lRRg7
zoGG*(^`{2e5?(JJ_rxph85^DGs~J+_&(+!&4`KZ>tfeh<ubFm)F6*S|>a;nxGCs77
z-lY%*G?h=NeMYK%`q{9?4cipT5}uo?A#VSQ2Mk4?xI>K&V$+tTqloDk&9N%xM!wyz
z9ekQ}+6i1{V*;1?v+}-cxYutiH^?WQr+xDSg!pv~k*T<B&hSaT)-WV%2+Nr!#f^9t
z;ryu^CCY_o4a5>>e_&X7Aw#=+KV;tjwyaEhAf<m32qZN#J}CEJ*P>1DPR;If=6MP1
z@te>P4CQ93J^OR(xby;F6xFmR*mN51{rc>ea07=E0vF!u?1ERoO$iR1?uw(y=4&7q
zEo(%E@t|+jlh~<A(txY3_lt~^^@1KJ!4mXo)6STQ-%qzEsuIS8HA}Ir1mj6;O2HD+
z;}drOp1V7pWp0t=iYndbBcNjS#V&thBpvr*cuy^}Ro6X(dS3uSZeLfrJDsjdls5%#
zqcSA@2l@fhkM0a6{cRD`X9DX2>_K5)5jGmkiez`smWCi!>J-=1wG_dB&J`PNI8XTi
zqB=P~M6k1YRs?QK(vzc!*5eJ_NF3i*O&*P5-+pLZYH<zQs%TMl4=_dfQJCJTHa5J;
z`y_*$H^cA#?>4zdFlL&tHO}_+mSxx^W<zq#RPlk=PHM==)u%onaccaEWZM$C2@UhG
zsWIyCmU4=AoPQPX!W^fpxbMq-+MT+~LI4p*rTNie-RTm!VsfRt%jVuJL&_YD6QH#A
zT&wOa8@G=g9y!cn$S!7QwGPkV(co<Du}Gb<)?sYb3+*|DUl_#$Pv~b-Z`xkXe-(r?
zw82>bV?1_f*|w6j>U;8tdDf(?=@RS}g3PghlFQ~W8z46ez_oZydPl<$(m^CZlePdB
z*aw2L&jZ0Jvtv~`STs-1gk7QqnYU!)oBstoc6QQT?2LDn=<Vs2Vjx--sNr}&8nt3c
z4kbMPAbQoft1y2s_|*JrGu3#(Z^&M0+SUI`90?lce8m{BgJ69|9t>ac%7xCGdmp{`
z1Tyq)Yjh~Oxqk}oK_I+W23?QUW)wb7>3wx1J$n=u)XNW}sSb+M0+pVt=AjofsCVKB
zlDgaz1EL}{)$TQ}E2N7R0atP}ammP;H{DI8<Q!2a4M(%CA?QCFZr|Ovb$<NP@Jw$e
zS|I9%jgz}5zy6o*=h4z;&oAtRo8%S|cnrm~(r2ZF=h$DTTHG{82E4XgM!&W1GYtnU
zeIQ+A+MO<JEKSoQwB-MJgXL&6Wa%_E^(`@m|Er^=a4lmN-?HrfO#OSQv0n`aLiJ;^
zPv%OZXf;m?4N|F$+F0}`;x^X<6s6NkQnB^RlURm4>dd6K?`F#l#!r4<*fKW&4eR(H
zr^`y`7$q;iZOjtICqm&PdAW`bIgLxgt=~^1^4qdPk6(;s7Aei56V4pp4y(%7)1Wcg
zr4*{J6a{6rDy)oG@x8uT=$7`Wam?Zz=JV`yifhNSoNFj$g+v#j|FltM5sjKc(3!yi
zG5>QyOW$?tk<a`FT!(wJ6@*f(jCS1QaRVQ7eXqwC=1heLE|vKt^poPSR|LGDCru;)
zqYq)N0|rzVrQW8UAS#C2(Y0@?SU(A+P+C^_jo(Ah?Sr}YH1ZJ`BOkj=w}{YN1WJWy
z)V`SNw~dt5NotM$E=`_PJp4hHWP42lharl}slT-y$)s2|^L<Di-J2|__r%nS=^CxZ
zsMt?`asnFd2L;z9<ue(+F8!p|^oivA6yyz+;OUm9sCLCUQt7CCia6p??3ykf-rBR3
zFQZ(lx2^FWi-Ew`Om&ebib|D`pg1ts&~mEbMdH)#4GG&R#^K6=^HSm<LIRy+Kce>~
zW+A#s&v3%-QrbLD^^zP@q;L$PrY`i7(zCuJYTfXBTZw7WLH0CQ*!VX6q@OW!+a&K9
z>+vOOC;6W8%lH-jzgg+IBBTOTD|xk!kJFfoNml*p!n*@$S-lf_kWZ(#HsAQrZ&i5P
z_`{cQJ5;wQa$6odXH&c>iT+SPpQ1i&5%Fk+a{TIkVD}Btb*@cD(vbT{a!z4YO?T*(
z_1a@$4bvX)uZ$E-87E>>R^qo&AuIURXf@)`(l)E*L@F93Clx3wgM_*tR~vMSrB4;r
zx#We-?dC^%Sw2l|=WGmc0UAOcZ<p%w!Cy`p6Df2;nLJ;atuUAUuEHgl(gsdf*UUZd
z*Mz=A;bnfdt`YY7d%;{~lPuln`bX(7(#Z%o)bJW%duyA7_7oc(h4#9MW-fdGQbEA?
z7m2x{@+2O_TX`bW$<c8z2SW90U8OYEe8W!i@1F1&(kEt$-|(W5p6QMHo>rL)^rIN_
zE~#5bc$VSz2#Zpe<`UcNk?taq?yyN$`2-cCnUdr+1sapyHaH!sh&UnkA7KX*PBKnL
zcN-AvB(N9@-;L+xdIo(YU3qelSi%OY6y|L(`kNz`$@}rg+fN*SXkH^@K_>Bg-(r1D
z6oZt|*1VcsAv;~Z@G3fOtKO84J<KNUFu=2rIo{}hX1|P<Rr{vmo39aCc)0E;wBNgO
zWTAL%V6<Xqz0Uj#h5d4bwmHIX-D`m8wR4+z_E{0Gn$+aVd08{}|2;38&?36pfMS;`
ztMB|(^@%sw%SL)@@(#u^Mv9|o*8WNQue!yX9PR6iDQ9IeO7@FAC(cI}5G%e0-bGaC
zIcF62Zh(&EL{4_Ee-|b?1n?_Ga|BIUETl{l=-%81erE$}gc>_>f~9_P(teE1;1sK|
zjO!catd3`Smq)ZsGQ~%jHz^ve1o`MT2t~qRbAm%hVO=7aY-OuXu?zZFY#{|VfRSU)
zo0T~-;@kxwbNq`m0><@pn5aa^;S=bqguNkVF*d#6NW|{mTrR<PS8sOpaV>w>48Z9(
zu`Qmal0Ky96symnwcJ$PHWhiZL0Wo!tuPz4%_Xg(rqxJ<93D9RuVWw7^r>LEL!Y1+
z@WZ}H+<&AY6nXGTt1ka?<-KDeh<jZG3^Fc>5RCp4%}T`H9fgcieWzk1Ows9C-c-uJ
z0J7*Ll|NBBygaWRb=>BMcN`flGvW`CGvq`=RzzgH*S9yA==tb70@UaKp|=mPsy^ka
zF?&cidcI4AK65s~zi=l4<nnN(1c<eKipIpdv<ow>-{%X8TT+mbz&c@p3sefyCg_24
zIU;_`4tVs!BrN8ZJktS^&=0N_u864RZr?vl%C5B@#krve5s7bpjPrl{ua(GzWS2eG
ziCu8GMO-rC=*WwFMk{M7A5aC;N{t2JUn<X(`bHJIk8^^EpYLM5WfY6tO}i|B0^O_R
z7+ozG=-pXr((N*T@3f*@$?wnCygREmQD5en$k8@|<)5Gvzx=Nn;G_$MpW#n`*9`V9
zh;t`4L!+%MvoWf{K^Cojz#0oGE1q_xqDHy>(M;Sb-*7qiUHf*7o!)Z=1VuN7DR=)3
zj&}$G)prRz%V!#_BV|R^uzjWsG=iyG<^nzO!BSMq?Xk>(MUvC?H4080WT=>-DTxFo
zyH}uK5>T3@ynpm&10)_|c6`)E*6P+237x;658E%)idp+K$#C9*%zP50>z%_5ie1Af
zJLGf8jn?!~y55#L>1Ri^GLPd!k$VD=8-2&AT(&x(P3oVRs(pnn(`wOtkwvTjXIZBV
zHR*UD|Hh05l>*gF8nEh;2e{V;ZR7{(nBibVrGfB{*ef$YDW#U|m)7uROp2i`gimT#
znGQ+9Hnpk^hN3KkbSPIqM*HNaLe=>o6x{=86Y~Iq@y1`S(fNE&^Feho?{RzOthO)V
z^29D%MlSK$Bg(NH6TTE2YH1aaalNd{e+js(AGM=_GnIHaYxP`$MNF37VZsCdQ}s?v
zrIrR?A>8h-#&8A~LmY=@xrSh-qINhtm)(rX3OnNmtow41^-cpcCE7Cmt?su!(GS)l
z{jzfZApR7v7K#V&HOi({F2|jxFijw8q60=kZF2<|9)Ydc?^|X+tSe}N65y9$lwF<A
zI6q+-ls5H^Z+|VkCuA{F0GQy^%QkHcO+2bs=It`^%r?V7cqFS+Zu70)@&QqqW9{C4
z$uu*T!E69~etq}%PeU<!-xmQOp?p*()z+%ywOMW4sT4!PMb!l7>0Yq|44MaK<jwVV
zZu-Jn2C$T47Yi&9kR^aU9VD5nm|-{RLU3zDMd?D{K<Fmrb17t|@<M&EfI-kv)A*+V
zA=c#z_vc35x9!P7VTXRu0D`pN6t_i<wvUSW4n#sMl|W)I1GH+}E;<et03L>_lit=e
zayl%f0V<U>0UdcCk_Eb60kAiE;xS41k5n%6nLF33ISclWZU=hRxW$}s`ZPKpm*}ui
zG%J31K7d2_n2Eh?rfUcJWHSkQ$F!^Tl2e_<NCqkT{X4`bi<wjd-LMz=M~x&q155#y
z;coB!-kUcV&=0~^6MDen^#G+;2O^}P3}^DNfPx*pO`geIpubMHBP=5y7;DuNq8AIK
z?VGr8$VWeBgJBp_a|RH?$@O<<D~Ry$8(jehoBBxxS=y1P(HTll=!JLrbZOrf!iGNz
z+MUTxgRY7-aBf<lTgi%b-o42CBA3oy#FzO&CeESq<@MFEdEnvW!J^+B7dCkF{3EHu
z<v|X<RKdezj(Km5!H5R3KqxR^PY`5w083{2WOF2l?D0`S;4{?47ggC1*raUtC^82r
z=~%vQAU8%vHo$0g*P!c21I}=ECJLR8kWR*U&NO^em+3-kr7T_pk=rW!W*|^~JiAaa
zJ=pkWvgwt!TmlVRH`IpkY}yTTP$uIk65&(nO6CTWtVKj}AH=6esr3h^z<teU=0o~^
z^2P)V`bqtUXT?`Ws)7@@EeM9lYqs2Z@86-ix9r%dxsUI2S~YgO%{i`aS<6aOOeH|o
zGC&1J8SV~SMMiyt*NB}q=K6by@0r?Ubegq%_gDTFwA<1=&48N3Z-vO>h@E9(K`3>E
z7#&LR_-asGY>?oAAzN&Xrr&-?ZAgCyp$b_U0KRjz1((5ScsfB)@=7p2>#b0sFn~G9
zk_ATGXqv<Z@3L5rXF<0;e^J_CLrIPcIU^)jA4=Kv=7Pf%hM7FQ!DvA=zj>C?;2?*S
zHYH&+?hq_lD*zy9<*dZ#0J^PhEvxHm++8O9=Ii=Gd<;gYiOfKfPA(Lit9ZYMNb~`8
zGC+C|T}}fse^q#5dyZ5%JOI!jELcVgrUBO4%`vsA5cAE$>Z@dl@826~cB{z;o57)%
z00U1e?LkHN)c_3c&G0>GQx+`InY^mK@69ZKbOX}5{Lrk#uV}>bh<hDbtRUj*TiO9{
zJi*MY8Z-j|RvND+u&gxK68j#k8=7{ET15!G(@Sd#7dFje-RSl(Oq5L`=CZ>Nh==e9
z3cxZEa#_Bcl)YeB=YRxM=byA<s8QA8bYZhwHC&w)IV{xX$Cq_=5UX`Q*k`@|{;>#D
zl~0nq4w<D&5o|aEGfhS(@l7vCAf6e>owgu&<n$-Bi5DeZ{S_k;Pa)`}hx#%=G!x0%
zG3|I12-8n<$DRs#I&oWl>s~=q+M`fq75RYG7dqt%F#q`dv)wz2UyvT61@yru;qh*T
zGQz&|IFX34XW=rlpWiw5xO168TE$-=+mx{?MSEQxt&v(mg5iNewO!;6Hp2O{;_ZNk
zu;G2}gc;zNv^ch&DgTyjA=)$!<;Wc-wS<HSb?EIRczxP@z@^~hRNt4%S_^$2b4-oL
z|JEjugO2;QOEd)QAg!d-XY6Xti+Y8agUaO>401KT8WMhpt{`|}<-L2e>J&|^H>tPt
zVx51&@Z!YBIaOfu-nVB(9<LcNqV(Qt-p~Kmd34nw3It<`z9P1lL^8{Y>q);K|8~$P
zu`|9MIhH$`3LE}D7xA^?B;moPYg|n9KCf3}w!_DZ<w*$PE5LC6MTB%u$*Xt|Ha9Kj
zu(mcG_6J@33Mk2*@C5%>N7U%KD2A9roiwu8Ezv7NaPo<;V*i;!XE4B`7HZVEdiovR
zJH&(yAgUaIN)(-{5P*j6D>P|9xz0^mcQA(8P$dt{#H=aus*G$fCO$q72Y#O|Q5~d6
z3a?aNg<=qm??qBdgieC;%ePkCX=@x)q6;@(E;IVN@Ozx2By!AqYDz9%U^1(+_BeKO
zQY#%<X@FH9uy``85qhkx0Ez|;d##W>fcqk?9XU~Wo!gX~)Y}hehQ%mW;V|E)(THK$
z`g70^!BRY?SpI#{#EJ0d$g!EM*j*7glIYXUYhAD^0;`xj1@Mr6xQtfM*!J~wi*Wos
zR5&y&i<=^v7f0|5t~Jg0{A_Dda!sJZoKy_Sk`U_Nhw_@EQB6mbXrz!L6qj)13yN9j
z3euIqn&-Ro&+KvfKqH$c*`=(s%ZhDF@J7YWXz@Y-qC<$-jZgv{Nipme=Yn^ej#{Vi
zuvxuO)ZejTe9`K)^s3U{4nH<?lN+#4T3t`7CY#0y$00$oPg@E&#61bt@i?D>PP~Ob
zhrfW+@eY{vULt#)zT47ndJ9`ergUj`gw|!i5%7M3Dwt-Qdu<1n`XQS-{3rVU8uAzN
z7v9)s@1&jy?+R?BdrA7uC+5{I=fyga;}<-7QSz2jL(KWoAWyOK2lO7jkM!7q{tyHw
z={ly}%CK;P6mij?Mt$whlA@(>Nu`MolfiQLr*romWM$K{BkRcd#<&#96si=O3+BBe
zNSWb)nTN1~Y_BH}a##w`?L*A!fKKY$LQ(<{vu~UM$>?b)MZVtTQ!|DD1InF(oS33h
zq*pba3|9_-`NWuHSYSk{u_wGkgh17`mx}BVcfG*nkb2hh9O^XTEpH~;RXhC2sEkx(
zC+%gh4%0FY`w!H{pbK~jvU-<Tac#OHamPVa^)%VVjaPtBhX94<mSQ5^PrwTzLG&g%
zD}I^0{EEG(lf|>9=6wI@*Lkt(yms+4f>Vx&)r3XPG~f-}$-TDWdgBFlKAF;`4g@pn
z?p$mL5nftukX)dGL<p);C%o|*;$<&8fB~@_HSW)Yyj*<b4z0})@UD#|<?BiAjVs7U
ze-`%Wl|{PL{p1F+zvBJKTrtM&#+=8^rfJ7AUhMg$sNeH5a@=;FZLc18OH9Nd|GVEN
zHJ#L+j(-flS|Sy1PBg7rq9#(n2#wryZlp0rIVTNFCEmUUi3Y(;9CE~K<P}tJo(G%2
z4Zdv{X=IVtFQH~o!+H)?as3FT%kM$LJ_!z6Zu{0jll3UFaa#~-0+D=c#@j3oCw?6J
z8?b*HBDE_0Zjaf!MC{|~Pm7IlOM91zFn515X0V!KW@vo-{lmk1>at5p)X&fUa!U*8
zj~5bqh|Lm(wvz+TKzUHE=I&IHu2+apq3run!_$+;EUdR$t8r<%!7Axrk485DpUl|?
z+X=N{m9Ia6hfb}K^|`<%?;wmox+EfTPQ!K#f9iashwg<ewODKy5GL`B2D(Lt@L}&;
zJ@66czlftAOMUHonaNZ;Z+jDxcPS=Zitrnu15fX)Zh8MLsKy#mn%o(=yZ)MOLd=fc
zz5wOCP}@mTPsA15QM1`%F~(*yWx#*v9cib)UPM=T`!(?9_$kh#Wa&PROC2TK{%B&Y
zAc-WuN_03rZecJwcDwHpSL@U^0@46gHwL0jIUEV~-h%SV`OA$ia3d}Rr9qNAiVR89
zxYQtzQ;WWz0&7F>=C92;@EEq6?~1+vzC`T=L8JDSddOu!3MMf-Yb&ICIDs}wsTh=y
zP6`RL{gFM{z9N5Ep%yRY<j-mC^f-N1BVXF2;hqyDCx9Frl%$f6<bHJUdJqq-14b(1
zn*}aWf<dd2HJr<vsW$$FuLf5DBtLM6C}<hg_@~9sKz}dlqn|@~y@%)xVdqf7X!HiC
zSY_?nCE{`I=tFRvqsSOM935#*ZeGkg$VKy_N!?~;HyAxe{HQBaDv>_hDzj$VlDrMx
z0^Be%A$5^_3O#UzUg^AUV3YAgQm%k1SdJQi$X$PNx*{=v;E}CSyF>Q`1u+;0(MZAf
zx8J=F2c)W~=MN<~^3JPx9C}U%`3(CBRcT2$0^}&w|CIkO0svE?VgbeIA~_%(F`dqf
zr}NN)A_9uqA?lSOB`MOK$r?{LL%<=eFUwIvGOvbF{!hN$Ni|T*W*_t};Y<*dD}DRi
zf(3R(h?s^1PbO0;1@+>s5g_L664nA1zi0`iqa6pIlR%;t;4g+yoDJeCPkmj0uJUrq
z1G9|iWRkYed9rKb7T0IG7{3kqhW<o%{bxeSj5vVGHH{rCP)IKBc;$vrv)oqlr1{WO
z-vE}}d?Z_3LFG@kkT%5Td+Q#k3l9w6*J)`2WP$!sQSF1yGkFko-G(BV5ttoJ60sP$
z>mzc`9knjinTOTDG}i*JZBI{Hm*?oxjp6_K)11i%hLIOBtR##ZefoXy0x43(=K}NM
zBi#@_6oQ4wC@}p&3WMM4g7Gg%cu47pL~5Nh6hBaHa%(u-f@m4X>5-h`1G<3=Gci=*
zNbl*xA4RwWZr)`;eZ&dekd3m)D%efPRB;}7>##KkvXnbd6v!1(c>xpk&z^-ka}TRk
z;Qau5LOKruXk}mpz2UBz!)8YuLIL;2aR+L>^TU<g2c-N7gm+O|H|$zQpa|8t(BkLs
zNRXerYk%`}<`BsFrVcyrmBMW~0N2PU1tE&vTt4Xq4kgS0xB&Z*g?tOjd!G-3JPks4
zmTv+~Hv|a~*{*@7iEFQO_fH<%DVm-s=%fxUa00J3{45Qux~VJ4QOGMmmE`l<VB!C4
zk8)zc8I?PG9e9Nq>!V@&6v{^pf!ElSM8(Rv<HdoX01Stq%C%tew6#uIigiW61l_OF
zev7zUyz{#KS%&9DrHK4sS%Mt)`B$-d@HG8xC0z3w3_<V_ItVoi&-dpW95sQ9%D42t
zUkhX$_{DcWg3Js03{rNQly^mZ`uzubN)17p;-60rqrRlV&ip?<-%rlZ%ZklQ0>=5P
zWuo2WM-Z_5ZLH>nR||MwIT;xcY;^(g<Z(TrPCPLN*8>UlfuEiy6_oMTX4=^JHN%!7
z4-rQF2A=i!beC!(8e6*L(i31q`rGF|(C`otT;u>_W&5#Kcw6+UUwC;Na1|QP6%nx<
z%SZ+=niR;c(cKmX{Q-q=^%c~tKU|4;s`$oE{yirfQHR$d;*S<fvUakqE{1sr9Zff2
z>ABcuKB2w)3GN$)Markd^Eyy={SzqL?whsE+fFL|`1B@j8aVhVP8hdw4zFd9d0|fi
z^3g7E){*ANs{YX;1zgHY)U8=2XZLxkPJYttJW#<OjH&KK5w^O3P<N{H{!X4q<EJri
zb&$QOvlXLpz!#mhJ}mY82Sz;%tj@KT^G0$h?Jr(0eT<3{^tg#;Ct_Bne(qz`Ley8J
zJFuKY^9tv|v$SZ~FtD7<p&~`$`lRIbW=0G?law31dIMe2gmH!oVU5DkN?=mOkF00o
zwOE3BpQQ0J*u8`eRV_+w2aF7=<qEjZ{tVB03vSGRNup3kEZ6Ad+GH}!{=U?72;W|#
zHt%+saqWT)s}(|uMm294#BK1;wh_g37=b6C9%h;XF@0m9!K{EvT-}?U?hWg^%IlF$
zAmuGa5gPD$>9j!&8Vh)z7VZOfwY?}~Ir<xlIrNci0iGIc<mVT_&I6~1{r2{BLQ4!8
zSpXoKu%|Hlg-?l|kBCoaKYHDpqU339o@lh2+1f3))=b%V784rYsP)0tY}ac$vP2wi
zSQ<5Ova>5vCYuVr+s^M5z5O+#OCsn-zbzrJ@mcEm-j6aaL+$H#N(XBT9!S!PXE>`#
zLkW`^MQ>V`0v<7x+Wy#UJe*YBoAiPK<IPA1((hv0Sg-T5bUD<To*nFbJ7rPb5?jZz
zze;qgxz5Jzi`p>Pk0tCX%q2uBR@v{K-r3x5o&o-e!?{dCOok0H!%e@G$wg2`T}0*`
zS4x00CjX*PDkDqqFs)<M+hG=1muWk|e;VIxD?QK*n;d>*u$mtM0)#gyU~{?I6B#pf
z<}u6znsr1M$o{|CqfDoJcpdFDpr93GaC^d0fdziq)2hYV<djjcllBB}Ax`An3(VHs
z6;N@dUkS>jL`PoD<h4eno?d%OE#US?$^ZDyweia7M-TBvnJH7}mnFTnTVr%0ZcNu#
z-;?&E$QVM)Kl2HBp9Rl3ERVllFUZ+b2keCxUR#*bdZJIy(yyK{-M+(koyL(x7`v;a
zSe{boER=D4J%llD`zvc=1ACDBM>{jxuifA8RBjxJ0>HL?BtH7UG6KB@rU9qZ<27p~
zbvP5)XdYN&4_a!eD8exZvV;dmpx<$#e@T+dj8nOnv1q_k<@{i*Z8upg(DYg@b*kj$
z(B|4_Xl`llHdB#qq>k-ZO8q=G{^~}}p+uS~-8SVE8cNgCsH{%!kjS4Cz}MW{L&$n8
zEtX0qQZ}{5_jq3};YEOP`Q<s+>D{8NA&FM8{jQphVIq~PpdM@SlaQ<50@QzZ(&ahb
z7peF?j?2-l3ltLQ@TO~(9?`i@vG|bkyyN@Z;6W~=)?sRiu~|6RG^`5D>F(#3J-X(-
z+x>1;BZSOoaTw|@=aOzm8_iPG@F`#0X}y}!(vy0RQZ=hZ_u5aBda+ZD%Z_uVSVX@x
z8SYhB8vOYFl+U|{0aq*`^RWFot0Tv|^HN~KBlnMsh|l<&9CMHUz!mY$hQm8$=KD8_
zdvm2P62n|m8L=f_za3S)cE2&u?eGngTxp|oE!U3ELkvh5pbgvf<@hxzVHs*<LZ%jt
zFo)HLehC;<i9x8?4~7l2z^Ew22OAqZyWImolEWcmy4-YgINq#iX=w<M;ga!NqZ0;4
zxS%o&F4H~5J3g+&Uij`E+P!h<7uH79ksPLqyRV&3t#L8eE8y<2ftDZFvEmFPJUL|z
zjjvXfW9`4aooqd4>vI)rBVgV!<;xPAWhz1sU1K(Ar5Dy5>HiZsZ&Xb?w(qt7=KVIa
zTou;eFG9x5>3@g*oE(3?bKw<K<Hx$4aXEC_JP4E-sd3{<KM_;@R(I$~mTGAL_qa<?
z$U1Gn{Jp4k(>bf>tJ|P^<HtY3%T%@eq$=)wcS*dTKL6wPq;uJK+xWizjQtgRbb9$z
z=Yg+iCI_{7c@%seCxu3P{Sy<)pRd{UYk_8iKfc|#(-+g?-5Cqyy9~q`7M*?;LMrSj
z{;|@4hF~N`E2li*W(6gj(mgDtT94teCx?Ci<*DWB;4!~exl2g>$$Sn{-006IJl6~!
zP3G^iy?MRnDqT*_dUb=3+_OJBeN9NaLO#dB-|*Wh*JNh#!Xm}R)FeUfjXa9fR6VSh
z`u653*jMqZc*KBJcDuWjr>jkI$dq4saw68)zP#f-Vg0>quy23N&SNw!v%RRe<>dSy
zi!Xf+<=9^-7!M^fgk`B;l5E}=$G~AtfGZ|j5h`47e)w0DO}zOqxk>+Wa0cg4*5s9l
z$B&wijJbSzv65L|j}7|&S}h2l(PiXwS0bS;_#@oa;6c#cfa5^><J0C9Uj|cCQ+C%q
zjn`n>rt++Kt9vyAbkaIV@0fr_6hbFva$K)T-_+Hc&%Xao;m#uXm&jRj^xt3d=^R|L
z9;F7GnL`_eYVB6Ig0E9BfByhh%8y^LG-Ji5>bs`+^XLtA_sUqT6E$pZ9~SS+AUAp`
zKAX7GGO}Ng^L+OxUOu&Euu)fJFwR(cYPn2%@6X^4+H_GV$%m25=glPi1{4nT$w8_o
zKgWySg~esl7z%V!wnP5T!Z*B+ZKsqx-(kd0(^o-+-yO_o4X4mMETw$VuL*RxxyG>`
zmw!0{QT8SZg^rZwx6|%_97Lr3&=Z?GBen(iKe{De|0SY1qMNg!+okAx^)`O9LH?pr
zt?Pg?5uH|Wvw8C1=Jt23dB#Ru=N;wgOteIS#Yn<Sk8-8Q<cf7gVZ-=8y5tH85kdPS
zVpbFXU*DUR0q3Y(ow=o@WoLpn_6!50h>0GjTWrmmcCNT9@{oy_tLIxWg$hGv{ML9=
z<b6$EF3Kr2SjhqHpJc=4#?JL4iI}K3p2fbGkck~?+MoY2@HxX?|2#40CC|oZ4;P6s
z_dl=i7;SIle0+qS_1fz_rK-x{PLh(>8q`fb_TG)-VB8M7*rhB8yGWc={GRkW`DH=a
z%g!9fmm#RmdTIGQuD4<QsI%`k))J(U3lDYLbr#zeb$qW6-l2&U&2f`)X%r*JG^*H~
z+EE|Vt4*HpwZ4<{B1potE5(D*b)0NWxw5mmrwqptFrdas%hrVk@Mrf#48B?aqh{&R
zyit+z9gY{0z$Vcnk)%uBC#UOBzt~!AWyCK~H2<NhQJa#@-YJz^ZQ}EX+2pcLd2G$S
zOT<?uxDeSogiK!N595x=H3V~*oS4TtfUr8lf%b&k{z`VT^kqhuT|5Gs4o(`IZS-u(
z)jJui-=_;`_uNcSD|{N15LAZzKu(Me5$_%6x(?=c^yPj`(KJ<(nQGf#d#^A3FCZM~
zfj@(UBkw(0tWr)s6j_L6|Me~(-d<r!!5Z6pxop74R1?(YA+qy|&S*h`33;p1Ja_4&
zW$+@Nj(-`G$d{i%(%5f%+|Y+im{gFEa+yGWe?wKfMn1}jeBV^uXBEwFmGX0uS<zm*
zj;ftTi-<15at$$tZ=(3`EfS%;ust-gA$8kCgu6Jr-T;_}h|f)94%5!T0TUY=+d~JI
z_6`a)*0a4?d7!mP;-;*d1+xuHadltSXXc)>gMw-KT8FTL!nsd?Nv~B5HQe|wkKS0l
zmwt1n%AGgAztG;|U&#{v%V1qK`o0&~gizJj1o~VQHYvZB?wdv9W3srltBpD-3FJL!
zhii3(9FLvGm|*rR6=t8!l1iLMQ%@}h`}hL$#W@Jj={e3(_RaVqX*l8DT2FW!lBi{3
z2TN583W16P(1HlsKbnAQOW(+dJm6nZ0Y6So!@s(exD<%E?oT1DhV>)sw&W4kV(&b(
zX)hU<C`8AWFjAuIE>`Mmgg=fV{K^j;93fy}l=4RE8!KslOD3#~nzxaCufB_~(m^(F
z%x?KMMepEGlnj}lkiymMz~Sz~3!iShJB#ro)f8_wwG#ExJ5R?U{f2Bt!)DEn>%v^o
z(e$!H^=gh}uD}qe?5Zxz<Ygu(9@)hawCP9#tRx&b^GE{^yNY=N&e%8d5Sn;i#9LC+
zR=iR7-dax^8=DV2vlXZ0x__n%<UiARs*`l&iJiLDTe+=E<U8Y#iMVRjTaVoi9_5~M
zr5050BIo=#S;nrH5#>*T^(wq9Fi<_#Xr5&?=~%)JgU1LDuokGU3xvK&)%b)~n8&(o
zYH(lpx^+v4M&XNxP}$Yh)y~jM*uKBzXqsxtsA#r|-#)kCF5j7oPz2V*dr=4!^rWJZ
zB_VnGwEB&K>0eQ8ZSB7vJ;7+6t(m|KVq`L3!gcNf`n0zfyd5+qM9{XRl3{+Z)D^9L
zttaFUeGJ}w?eSl6;dEI+I(3BVXk@+4G$)O|sIlo~Dk|w^JUT?5sr~&h?dGei)R|0}
zx`A|6F7Bxiw2Tns#gyIM-D(BWj{;gqIBnwX0pOM3*Z-Sj1U(S}4a__mS^q$KF-}1-
z$b>Y)@7H}Apr4T<6*V=;tGMFAD}XS@_BiC%FSsGVZ#1T39fiKjyK_DKFy5aI4V=AR
zUx&`?If652)?*me(lf;aYH%q49~lY3AUazN1V@|g4c3|DqoI+kuE^qHe7HqX$i++l
zz+vG(F-;$-A#m--gu!8ZAp5L0AHX6O_HIdH&{m2n1qYA=)%bIgAW-t0qQdMA`QMKv
zz>j@zBDq}Q5MYg(0vLgNTu9jD!j<zxKwMmGRBQ_B%u~&d#$<0oHXY+**Cs^nXSPWT
zukBGDuAG+!5uHBlmlpT1(L>KEjho9u7O)(}b6AfLf{?Zd&}|bGt9av@klD;@LC)%F
zQ)@mD>xq^HR5Oe6r#i|H(?XU5+H$6lv1`XY^9vd;2}1tyMKg2rChNU<W53yvRp1q)
zLCC0+_lN_dLZghz*VlK^$a9yLImrBC-14uiKa?~FK}Z8@<%@lu5U!J(TguJ({=O?R
zHW@z+AV<y6JqAxJ@5{8Y-(Ok)9851)0M6u2kqdCM%~$7IF!$26ez=O-caSrcZ(i8-
zcea6|5xBI4Ao5xKP*C8CVq0kFPl<)GkJY2X8ojf>U-76n<jA}3;lUxm3gr)JIs$s9
zF{Af+92P69@HMz4#)#g7PG5srd<`bt6qvMBRN{c=M+@M!$<`XyL^$`GEd`&a-3LeZ
zViuIjTA*pxx$_+*7zZ!t9Ai#qG0Bg-bA9etEXc`YDyLF3@$As}@8!VBWU<zlaEhIx
z>_z=Y$Hm5%K&xN!8fdCKUsnMP-ZlW)8ANPM=#@#kgu=;CS&A5(ygWH`vhgi`Zp6xn
z&4Ys~&<M=b1rQJ0mtrVuKRT{3haw{*@47bDGE?>uxL9`cO71MI;Cze)KemLas1#vp
zg99muAygDo$D(t4p4nu};?t4Dx02~Yn-3S8<ev!YyZ~jGnV#Vz6AurM^bbsx(1*7o
zEgb<lIo&JFl{&!Ung6X;%oCouP??n$XNiyY->3k=V;+L>2j&vyb2`RzbC4z#-dDg{
zXwzjj0X*|wZe<)h|1)`4pf5^)eZJT6!j;8Egi%8)dsX7^?SLDVo&lxAA7DAP2@0G1
zM1(G8`6hJPpaN;*jQk!s0J(<n#QdL!BdSL$DweF}m2>bcz#T?$Ptc}P8-Rqm#}Kc9
z--Eu)U=M1G6{%z2K-W5oO9DAy|5XGAQmx(7H46A(D&%gE<H{;RI+z58+Xb4{8_?-)
z916u`?YEv17upc%JXI326ze9#r3ko!i9YVW{rmUa788%EmJEUssvDxijmoCWS^)am
zNw5~csW8%i)P<UYGG0^INK2?buB<HtuKvm@?&a=$;o@oTvl4vbg<`K4rS`q)j+BUD
zl>VkYpIrCtI7l8U#!QtI)tH~1)&jA7Wf0m_;WTk;;^7RV%)y`_s#;@cW6;a=FzO4`
zU@m(7;+ji`DoA&YjVS^HmGZGtJqwFMDFf4Il%X)dNPNv_We~<>g)458%%racs0Srg
z8f9t_#D4LA))G;$96a@maHT;Mpiu!GtpWh?xJT^|u+G$9uc4?l`Ez-g3PjDXI8r9M
zAHiG(*!e@d0v8@y*_jYO?X&-9*!|PNyYtUditFSA0XxlHl(6}lb%BYMsg6$C_?GW#
z7a~(FMSZO|7G&LYP8{QMb0XJxg0b(H_^Y6jk)eqDN@Dv1XRrM^rv7i=%m?bmd;C1E
zXde~|O-Pz<_?mE<t60h<ATiknSi+cKEHFlBcdxjFM3p0sMI;N@&@Sw|KO+ZNw!1nz
zd;IkDWhD;)tCj)iQ^yqE{n_UaH*)>;r*JMge*|Prh>3d|c->vmD16Zo_gVJ?&(V8(
z!FbBXNER;S@Vm-+eO&z!Sz}^qBVhsh(aElp2pSJId`a+xu72SRuCG(F1lqqslkUJW
zZMu$hXigvk@~pb(IxTpEw<r-<@Y|GXfo4-ktu8I?@j<t^0-<E`IpH6mW=|CIy0G#3
z*^f$2QA|;enZLQVM)~{q@0+x9LXjH<3lj3~LUIW!--0X=KcoIwG6t}6C4vTXvVfcO
zWnv=k*CWxTj7Tue%02}pKdc?-0Sf8tx`7KDURa^;DH<PktLMr&-lKpQ^CB%9CJ|c|
zj4nxL#Vu}O8iic6K@uF`j0uU(sR_0b_FU3aA+`o$i044tK8;eN3FZYYE33*wT4T_|
zgjUFph+eL72+{I~%64f%kB~4=FD_y)lVRcgwfU4E;U%shIU=jEY!4~HprbHR)~}5<
z1I@dToedWB4xbFL(nJtPqY=CKcLRSf6MB|MX4$J`x1cb`6bh|%76HqwVYN{^{r&B!
zavLE50c{%EO(8B04kfwwQ8)DnrO@upHs8GUFKyhX9?aeP#+5p9p{{<^-KP=R?vA5G
zY9*c?w$r6bW~s%C*Y|hz(!P4<)`5r0HEpdTie&Fsultm||C}DW94)*=BY~$a6uG_0
z2^@C#6iGk}Mh#3u`hKVN#AW1TgaG8;T6{r$W%h7bINIYj;~~{mS_vPVSA;8s+ong+
zx|!!}GaF!(j!DdBqu;<Y(r8TDxh^P+SH<cz1FrhuCaKJZY6=>JPGi)&Gkz~{N+w3?
z&%YN*G<YU(eE<8F%)!HjwyZV(`$eSJa-k6QO9J=EOhXq7ya~wf6o$^MP6hAsr1z0U
zk$dK#?I+V5+{|vn_z%;>yI?YOdYK)mj{#uxi=nKIJG;AO2ew9-rVv$R?C7;@wu`D}
zxWSxJ_SHo}K>@NEYN(Hn9Z_FmK*XAE5YgDez}!v4T6UCU)aHYkIAe8nbsQJkq5GeM
zW>*D*P!;uh%)P1plPiKJZZ=|EZ8BbTTD+Z`Ed__1HHS>B1)?fVo?m2^&;4e3`(Bem
z@HL$MkEkD(8yX%&_wZHS09tJ}LCJpZYSf{{UZ@z+B}Z&`L+~eEud2#+-F`mzuJzME
z;$=32R8r(~v380cif1u_=M*K%xz+QboUuh)gy&hUPOXdvbz-r({0!9|28Fgih%9Sy
z%>cNP@oI7u?&{la(22uj8AXtSbNDviZc|QB>$Tu3lOsmHcXV<cw?~FUDO{)K^J(W@
z#rI_KtB!<2-38BS%~7n&v^s*lr+7q9wm-ADr!uhJl&!<7+q`p-4QTT=M{ti88IHNF
zyB&dt@wO(eU}=TMi(TSFE-MjPG0TgmW)FddEX7ku=wQTl(hqWRRuQNspi5iaULErz
z{7`71r=;p1*P*~eaea@QgKTk-V#t0o;;~*FtU3QN#!_n#J)L#?c{+P#7{1d4gE7Og
zrie+cWau5mw+5@aGweQ%X6%x|@)!Zj^DJjK+F~~{!SY2;$(y%!ls-sC>L2LEIU;Vh
zKivwx4ki`wkk)JG(F=8Z&CtPBF}P)jTKHW?omROzYpQZNiV$T%x5c|1>U-2WO8kAo
z;S2tvm>4qpe*s=GrGEs{<6+5u?{NAC0(bM`m>s&inw!1y*(z1Bl)rU~ZXrJ={5~Ga
zw%{}TWUeB)ku8oUF4X(BK2@tl5E0XEZW}qJb~0YNs~7$E_;1O&=8<Vz!X_2op+Sp_
z=Ca=@7xCqtJ|PN#tA>_}E{P;Wys6YY_9WTtD5NkpiE_&=T@|#x@*Ws8o+x{GU2UI8
z9Eo}yZ0bF8a9-Ce$dk*$sR8TyL-a)%5FZaezP#iqN`r(7XY23f3y%g%IGuO&KK~hy
z3r`-wpHAYZ%Rm3SKD(}3QowmuMj!J^J2gd)@#pBB)1%>C5$5EP;Y_@RPx(J0=r~UZ
zXyNU%_5-<oE2Zt~rUS}DpO`*>Ny}0BtmnZsqbobiy`LZS?Fk)9RdQEw3p@JnV{&}P
zoTt@Og-VY$YJWH+TCaY0$ef7$H?mKQ5%m_^wJP5T{uY&_vcqg#CVHU5HNtk}DpIB~
zJfikxk3PlbFrh}nF2v16)x*V;URmRMOX%UkrJYsR?S@f>EH0EQe#X7_itcr5_)#yQ
zAn1c+u~Wz=XONSKvYcFKnD{B>#(FH_<z1G5m{sf^)3wWI*~v;cQ}q_J;j7kX{97r)
ze%HCL*j*N}Q#LL>Nr+k22n~4tdwC04q7R6t(;hbar+3f4@j50zv42r9`Mesw9#M6X
zL7oA7FGXk@3bdozydd^oSjJ3aFT!KwZgTq=Rl*d&-d~L}ne7JmSDvt?yt%05u)8rJ
zurM~jV*aCN6|>9W*kt#jnS4}O>Mu5F1RQhQ)ozX9^!cOr9Q)hD3|tH&N%wbVwnoY9
zQs>t%B|Z&X1HholtA}y>mvb11CcI)?pZ)WQWeFhTN=gayv|(VzOHIf|$Fx@k)@@g$
z+Y|lVs?sqmVdcVHuyv~aLhX9fW7&%1BQJ-4>|QyZsJVIrDnk}Wec$4;IZgv^t6MkK
zX1F3+J><3DRFVAdWfTfR#G-=vd>ww|8EQMz<hN-yqe*8}*kwK@&X{p1pG@PlV4bop
z<o2G7G%v3{NXd-gC79d(&{46jA-eYH1ERc!@a>u(swZ=HCBf>2XYK_NzkK0IcS?V(
z0v~_Ka6C&~T7Erq;j_C~{J!zkt&{Aijbg_V-)2Mp4~yaq;ueQ}hmG3Z=D#cUOyiLu
z70O;i#-D>QRRf(q$ay$PJlZe~HU739Vmae=$L`)^KXj@lK&MlaXz|u<j)QvR)e;f;
zd4l>j^RUeDAM2VBvE7TsH<dgOOKiMoB%Y{>$IM5#kp6@_u^>Gw=DtU1mi!=Dh@f%k
zyJtZe$l<2Uq<;i%8?pEYMnwzkG13{8=%d<I`MDkQtXsPOSk6IE=FWpm7C$-FOVZ;6
zTiPs<|IFE2XzLh%8RAAEMvvM0Dc(}JS>8?lwEt|E@g3WvBQd)5wP)Kr<ISK`#Kw=I
zCN9TAT5XJL(uZjZKJH2oS-lKC^?vt5<}w!*V&oy!1`FR82~MN~azsoP24>%=lEs%2
zXx|jKgejc!QKBF(od~N<TrJ`l%fV<wWArPfte4(g9HmS6UQEhY{<D`n+^c`tLk|4O
zONZ~j6Hy>~QHY9JVz>A4Cp@HD51+J*hmhxUSTglL*YdD%pn^T=|EB}RS<lsn={3au
zn^@Bv;X|j2-r=rvttmSf`4|OW&}t1*u!#@75kAh5&AB|H`|o=uZy>J-Cz`GW#xBI!
zYZc?11}C_)t_lC|Hc+35ifwjfj}*WE-)$^}g4=k_d&>0R5de~<03z=IfmFr+cVmx0
zIRD*gOaEaX`sYKMhG2co=d@jK`|z{X9q3ehyb(#G@5tB8p$nnsh~6UhnjnRc$~Xi8
zAs8B2H^}}SO!30{B!K2f5X$@WQgFr{`@fL{gQ)`&#QMN)!~eU`2Y?D+V?rY4^54;Z
z`0GyqE`#Cm5{Q=mef}UzeIS(nlvY=vC8i|*2ZNxA&w?gw3^4KS_gWV{f?O@rZhn>#
zOXlu)ZcqEa^8xH8fxh@i2fZA+dcyj@|N3v>`KNiVg%CB;O6jm+CvW&^FNi;!sg?oK
zAEyU^w72btATnjeH?I&m!bYPBK<Kc3aizq^$49HHQKXLj>7GeZyvUv5zXQ@FBlyOe
z0GdKF0N!Nn?JK`HtaMbxt&#eDOpwdC4Dw$~4@?W>6A*aCA^fCg8EzDzS`bFhCN8M_
zkpIw_s6+a(bwT?Crgbz4cDOn#ek6USTSRaB=vAy~)FCmZIJ&;~yh@IiEV0vzQcT>X
zf8R_HA#ccxUa3liIAMyo%`MZRAE1@IML<Agcqu8S0b*zR&(;3NLcN45ToSUT<W^aJ
zDbi{xLKsX&0B(CYEgm>+c3p@+`{*-*Rrx6>qIV}|1ED%^sF{5(3JUV<w8}cyzwZj2
z5`u^k9Fz@omL|^Rirk3`hlp0ato~+mT;vjfZ#Lj=od55eT{kjgp5!dWwQ|n4SoeV~
zD|DQ^zw26Z@q&7EeIszzJ^p>9nRt0N^?WWJM~DH|1ZpU}p8xO0(n7mV?@H5)5i4ag
zsJj$)ZL3GVnf&j43HS+K?BpfMYr+5f52p-(z{Xtpo+$itU*Oi_mp~eykoh84=Kub)
r^?)t3GFu1zy9$GsJ0Y{{9_cnK$N&6iV>9qjKzJ#oBv~zP68QfC2l@U&

literal 28011
zcmb?>V|1lW)9#LKO>En?ZQI7gww;M>CllM4U}AH^i8--z_B_vrcdfI|zmp$Xz3=Yo
z?yBytx(ZQB3X%x0IIsW!06|(xOa%Y{#RRrrph1EEo%u4=007tyYf(`pX;D!kC1*zq
zYddoQKnkHY%|i`s4Qq5;&bt^QQQ^1;4jftP7zDipwg~l`kQH+{I7$O?3~hZ;q*PO3
zj0!j{QA~8CiFkwYHn7pjfN59pMo~Y^-*>z5>F+r0bL+M3aWw7cahU4@LUd&c7lvJr
z3djU)pdy)#XeDCE3-<wc8Y_jb@6VhXM`alr5*_GkMe+cU>2_O_-rm<)eEJAyPE70p
z0AZvP(wlS&6oaFQ27@Tk!+?S>kq+H@bScbO#_A}jM1$Nc3Ymwf*p%|Om(<x6(1yd1
ze?lmm){4*pQokY<CJsx8{H0VvFCaG6KmcZDNBuEFmZZJojbCb5S<`=VAsOG61UyMU
zLp7~QJLlWEN9UA32J=OAuQIaBW(*iGvp)wQW@4j~8LG-7VUKH{BoUA4V~lGfMqChb
z5BU<vK1`Ll7Oqm7gsc9jslYyz4KA|O`bIF7vwK%c?Cc{v-(8QLn|u)S+kf4XL6F8h
zyn|2h6C0C0E^))sT=M6=Uhh>mb~c-PJ>80GLxVW<`&4(V(6dk2o|9KjaIDu&4_OT8
zZ;tL7!dHyj;$VxnNO5K7?B9!k<=AN~h;cXLkwrm%j1VbQ;u$bSWcnH6^b5)v`fIQc
zBJ>U`A{;IdpB(_+a5r89o#%GxAV$$5dT+*vm;zuXYXsHFuGTvK0Z~E7J<p5-(A~xB
zra<KOhE!|A4*19&YkPf<I1C@&unQ|8dyTNDfesAj0O)&gqbff%3pSsJgNPMGnyH{2
zgOC~_+69t2fe-`+iQ&Qz3ZX}W#ehIv3sWEm9S|YafQ1!&v4h+YVqb-L2nO3B;sRY4
z#^M5-4w=~DX-6OcP=5ho9Qg7Cpdf-C6h@DPwHA3vgfWBQ7I7VeyNM7fgr-822~{Bi
zAq%=GxL0CUgH#vwDS$j?as}l9(+`C#@R>zsgY60H?Wf9suO95Ir?!JyFs8r*l^lrK
zLHESYfy3(0-jQiXbO_(rVZAng;-CvN9Nec0Bq>}}hNQwp$3KXH75!2CO_^lTMh&G3
zR6W8**sbVAiBnl+k#^CN4O3oxVV1)R$rYIgXG)k+v`!+upn48!*8bSwPW}$r8~z<%
zbl}*ihUxMPrUeKEL=&EBWM%)NX}syQv4g1u6Jfnp4bL+CSv11ni19)_Z3Fo#{;Gx@
zr#pZ*7JqctDT|9Xhmrw)bR_C)SUZg#>m}PIqyzXPjN;(gKK>t&C(mv`enMS8=bqxO
z<4*oACA17US}-qhY(IGoQ3~n<3J=T*G-)VI5zAccv2-j+8OjO@Z4~{m%W%Z72N~*k
z;%|v8MH%v1a`kVBNeqeMQu*UFX0nZp+(C52jwDx<9?4fp+sahvs<0ubiYTfa$~aV(
z)Ctu2=oPT7uyhdL2XVr1!Z^ZkVe2qpqA8-~e*B2;h{lMP#Hge0RUx6uq<N-kNY$WS
zqRLgmQNz(Jqv55Bptht*r{bhBRP+BHtjetZM{~Cdz2aP*yP8E#Tsf|yR}ImP-;MAd
z&rJ-Y+NSKMio7bl27kqR9Zy+V5r;0l1ifUf#6?M#8h)um)wIft5~I3ck-y~o1l=#~
zN$qZJT+5cpPUf@X@K#9CkaFdcxvH<a`!N*q3x=%vE-@Behotn)X{F1)wFf%9Ez{OL
z^BPMJvxin#)`WAtbzo;&r((x7i)+;`;+A@vikwQC6}qK98jq=Yodlwc@^yMwDO(i+
z>f5q{>V0~j%^z@CIC0Vw1?uzO)~1j=kiw9tA^ec<kZ9o+;d9~7;kDrjv5^w4#b(9M
z#RSF7rhfY!BVHr&BaiaX6s~B!<L=1<$q8i^WesJxavSpb+142ilg?9FlLT3+lRZ=E
znJbywjr}^a^z-!YT6%4v^ttrUY3yk$HAb{p)oRuF8eq#`Y&mU%+;Z;=5Z1!2lkFGG
zSk0;(aBZ?3HymEqr&k%a9AfnIe|h*=zQVuyJs{z!;RWO0;Pc>b@#ye4<Jsalax3S6
z<}7o$arI={vuAVq9G!Pfs~vSr<L3C}^mVj%M(XM4N$AJvqv_k~L!DIJIeEjp2jh-R
zjoQcQrf*n!V0kpWqCEET+40Tu<M8LrFlP^CH#tt%mlslQxFnP>#vG;|w`|Cs+V4y~
ze82S{WHNEWzK^w(gR{VC%6wiQ-IDz6vUyZo*L6j+?I4(9SYViB*w+^w&>Yb6xepi$
zObILtY!Eu?PYwDdoKcWiKrb9Zr;i!2)Q<z_j$nYXi7SE_1z(Big=&LM1ACDJH-nJZ
z<#svbMR5y$yFMiJh1Sk?wb-fY+I+WfYIGVY-;njwI#g85K+KSg-C5eq^mhbRe#LwR
z)ZF3Rx8uAoKQcly!ZQ*Y{2R<0<{{kSH0ay$$}!S$R!|aR5~Au72n~<>oHhoNz>h))
zLwRE+F%RfE+qG=Jj_f7NqNmrV<H-+`jZkn<_?t&GoUQIl*OaW6Fvl}m@*a_=56~aQ
z-|%^vcUz9<jhm0psPd_{mc`!mJY&3RR`ymdRXWZG&%2lU$sx&Z=L=+_WY1+q&B#si
z5i6mTz<H;i(obpg5H+J>!j?{KrrYasP{5)rSqf{%H1Z5rN$om|n=m{}v!q<4>L<Tj
zdrjUHbN}QH&Y`8H)3nq3L&r(<xRQFDnv=@!1?hEm6RyFmd7+I^tDy6%X~ar?AS<aQ
z$QG%F^t-H~2m7`_AKmBs%j$hDL??tTTzCNNTV<tEp^_R``+(`t_xw4*@{i5FIcw9U
zkt^}dBH14gKQMk6%5ssX`+t2Zy-6RJAJ2Y~)tB*b7;(U~>uvhsGZDmc(74&STkF!+
zn!4~a=I6GfZsUc?kMn5#ji?RsjndS@RDAUj_3Y|ijoWI+m8Zq#<<munn)mjQuKf{(
zk?A!3&aP+=zqQ=X*UP+qetWkvHw>Q!pQcBFUsz3bSDG(%2=_YoKkm05;2va=#PE*o
zo$Rfw7Om;*gR{xxi>F|wR*+us&#fA)*A}X_bbO)lzTtU)<@$4-OG+&19Y3GYipR>W
z;gjRtU4dYuJIAp+?U?R9>;|6$EikumGUxTixv~A=f$h4KqsFW49qn1Qv-taDb7BA2
z;H9Re$~62V-HDfz`@ouR&#lkvOju5rlfcf~nt;Xj30xjlCqt(p-`6Pr%J;^JgI3yU
z&3Hq%UhnSh(!PtVvzGWXhZSC^L-?G|UBCTF`M&HU#|8)eUjD0x{@i0;4=6OqQjZRg
z{OyVM$3y>z_b4b^LK6Z^eid)EKUzm$e_dhrwaMt0P)59kf9H$xy)nvQeY;7h5$uge
z=PTu_^(_0W+3ncB{XQ2scgBd>`^Agem-|oEwc>%GtzmYbzysEP9jz(ch{RUpmRv8r
zSNXHU=j+;)&&bdyVZhiM)1QXp<im2X{FD6G-eG?)j)phdOWOm^7{}ag(O$uv$($VY
zM)C7X9Y9#DlQRpz@excY3M|kYA5b*t+QVxOBENDBEgImF`DVzck2Zmshy#kJ2bTy6
z3OI5AAhH6Ogb!iI`0#eAAOmxAe&Z{f)6=eve}yGd;Z?~}lT+vwwGqpK0Bl22Qc|u{
zQuZy8x;^^=ItArc)>v#yEdXEmD1I^DRo$*sj(&2#L4~K^hS@;iiUI&2xz=i0u3GYP
zJf@EJ48~@TCgu#D_D(>M3jpwW@&KFm=B~y>p7wSQE<B$6B>#-y0k;2sW+Wl{XNapU
zKZ%yS5|OB*vpEqv12Y2)i2y7S5fPuWnFWuEn8bgP1Ap<8Sh>17@h~!acz7^)urfG0
zTQV|pb8|B?u`sf*&;v)%yLdUc8hg?^xRCxk$$!ryX6|C@Z0+P~?dU-CcV1%?M>kh~
z5|Y0Q{m<XO`!x5o{@;}xT>gtKAcKs5dl;D+m>B<OZXhY&->*DM)}H2eT4L7r<_<2v
zH3ZmM+4%k$|9|!T?~4CHsr|o{EbL7GN%<c=|3%5i_?LnIVCY|I{qq$lE&*6R#{Ut$
z0BrIi!8ZUv2p}yctmX-Ft`EnzsQoI~!~4bjTM1lCvwoV0qc`ovcN?{6`h_rtRR@`M
zofP>$2{QD*WF4`ZH8^S3SUQixi=3&eh{?W1GyEK*B5kVsynTJofE3*q7~;;);_h?F
zyXBjC&ik6T%{|lMT2)aY#AO7|1o{Oe79dfu3;kBTEA9jXYy(IGQTm~gp=X)k|LvPX
z>0cnW-vURanXOc%RF<(55u5A(`j<)_W#{&}qocz}upY)*eG`{lPFuS}v(CUsq(bOV
zKShbM)}9D(4j~t!Yv2pQ<8iI<xZ0W;fWNg81_uWnczwJw?DqUq7w~?T?bsWn$V5hj
zl%0qPj^8u_Z3KQQ43Ho&H#gU9wQFc=tBZiQlm-LUV`vNb{3tCgbv7%Qvr54jpb*2+
zfjSFBIWB<Sd8Wm-@wBQ*AQYTGah=6JhXRi@LL(8Sk5vBw-AoH!AR9dUy=rlb7Oa=H
z9*+s}dHeGN${xx^+f&)m$I(Sk@E_)9<)8y4!9mRhsnS+M+0dFZ5dM*f)fKeTh^Xs%
zq`cIBj5UEaLYp_4H5vI=Qaz-Bf4hzUd#e9;cOV^U|Iy*m;o)tcT96{23&bG!w*sM1
zp$t`4k{t}8@vKS&zeAT@F-(+aF|Th8WHf3pq#5YGm7?m6bpEDjBr&z&ZX?jH=-_#w
zZ&jtGU&{*`d%IJLajwsiNzUu9&I3c2X2^~cxP#DI*bq7A!msD!ZLO`{3{hy*0CZAD
zibiirHx#?2_{;NI8N<olp?4}KXe2%MA?!my$wSKLAP{X%R5TMSUT%^waeuwlHpj{f
z*uW*GoCrd-`<AAvB>wUf6?r+PGY2&3!m)#~^=A!nNxzs}r(VyGD)XP?)TAZrfuKt=
zvMZvhe^S1$8`%RdTF^rnK!2ehv2fz6qJHcm^4=DYA1Jdn)w<xvnu5JOB+VGK_?X)b
z)A1NAOVM=r_B1`s1-~bq?J~MNBw#=hu`h5$PGg#j(CHy}H;{1_8dhbHfuayZ0#hRK
zr(&<~gNd9?rO8#p!jb$OnD7$p^rQPM1>$`L=5oBgqt0o$CN2KgrlB>geO5zScU(Sy
z%n7SNSoK)LMCS)HvC}gWd9dYn19OsY8(FOJln<(}g8;;TPjw09=_o%SCpUMuWXqd8
zJr4wT@Qxb1Xz+_)XfRifJ#>RFcj7e%WDylf9be3ajC<<~9cFUu>M$Bav|j<>jTH3k
z&VXY6k^XxH)l7^T3N;6_SE&#h_*+m_Rf(mUL0qu3QW*`pi*HnL4m5J{6^^n(3D)Z%
z)i7mLWN#@~NT#W>iL?X8!OZGnaa^u`DNm$$BL;2m4w-#neSN*{%J&2Ue(#5KY`itN
zBYKhBpl?#^=s#ZmK5cw(ka0OFaZF=TE$LE>AIy2PewONL$lG#;#~=Irg`y9Ww2G89
zfC<Wk(>ZS8P-&;Q&}sg}dW@GKX(J38E-^*IjC3sNFW6<4JSlZ7BE8a~1C<q2{QKbW
z`uXaNQWom|i4>vZ)OBO9%^(~Cp{1x<iO#KP#PPY}jSN#H&7un02M2a4eHm?J$<8#n
zOvEWLHRSqg1<k`}EX1o=p!Ts~z^6sj18s$vABvovJSrapC(c19AL=^lQ*<0j*&Pg3
zi03!+C-%-W;CPB3voaa&7M{OaN^`g)12*rr(S(Wl6$_^#d1*mtE{2VbLX7nH*}lw_
zd{27-R3i%m!4{%%et<I~RN>P~Hx7htu&O~cB;97KJRvuZ_aVtoeo(e<%^lUpO-F&i
zoUI}xtrMh>l89%%ttL+?4~nuqqFKn*D-c|%(9ROo4wgSr@{w|EXd0-bvtLmPtPvy9
zU&qdpG())DYj%w&)Lci;NZrNmTA&ddIp)%;UF8C_Q%lQWijg3GE=;Ihl0@S#OvBuq
z<9n!XIW@jo_WERsgm!ssKYF-1oA@81^hV=Ah-W5#y<f7NA!=Uvx*f)XkR%7;wHs38
ztQcCfjgILH7z*tzVO=D~kHt0j1>RBZ3-aIOwJ5M=)=P+IVL**-1a6fjN9mW=L(VM8
zh6+g>itwBocCNk5<a5BI6=$%HJ5ONVEex4*#Upr5gj<=lEP|*p=kU5QBhFOL>od5%
zBq^7`xR`8;?C_{AFp4mi6hg#l^LQd+?-tgq6J|>}3#mo+Tra_;(<q#fPn3VIaK*P%
zG?zkP%}Gjp#2Y6-Zq!nQ)_$3K;xUsWQ9+AdA?j^U=x4t>|1DUOczzyL3+b=PKm@lM
z$`~<A`w_ra*=CTMR5nXHBsJj5bhmse2)RZSV4FKN(148%^O~0F?UZ;_mKpk0=$QXm
z+8<pt#(ODtCD7+!nB;xduD7)kAFV+$qeHyZ%#za3ppf0zUP*vlv}6YhlidUoQ6Pno
z5M>{81f5cIxHZ4!CnGm0>1pH!^eft!LxVu>fZlm%5k8hZ;?&qw9Dk!t4b)^QN+H1s
zdJw#?OiUBxSrAa7u1w%$uH|4fi_sK^tzU>me&h%p8)*0b=An|JpSl6jRl?w#K|X7t
zlH{aKjMgj(am>|A690`pg0|(PK}6T;osBM*McT-;5T#QF@!i8%IJlQ4@zT|XS>0U4
znrFACZoY(1pnkqgh-88K8vA4y>fOW_CY=ZS?!rz;9oMEXo$Ew>u;iqR!NZ$Usj<rB
z3HKk%+)M!K^c)%!GtnOemVI{V3X(rcD;^CG*)za;2TG7mSwLOIlx2!4-G6i=W8HF3
z6h_6OW>dLRGp}0)vU};enns9)wNfgJ1sO8e;bQ6K<<&k=KOof>>zzUSuce~_W#e(3
zi8B>3tx)=i8NsMCh?dYqsg}$YIi0MS*2KxLXB5NHg*XfS=hB&hg4l_e6=l|c`$t;}
z;h^*bZSw!W?ruggiYyq~D3oI-=<~Iv>>=WKN;}TorD{#aJi+vjQ!5)AgXng;!o1Z`
zDQI+xzxGQ9BS;YGlY7C}*%0A0=RpJGm&o9BV?M%L>(TE&raF-UP4#}7TFv`AU&pnL
z(MY&8GEjk%wc-coaXV%6tE$ZVu5cD*XDpqNZ{|^44B=ANTAxGF5b!|KCrknUDv|}x
z$q@Sw?>sD^tD&yHmq*=3fy*+1%8LN96DbBF;7tDltDyK;00%LC$Nkq|%zt5)P%<(Q
z6G>n14*qLbNdKY*Ne4eYkAHy&88{F{q58Hn{c{Y*W6(Q(|4V%$Qb5J{DE-l;c;L*>
z_KLJ*#3s@a+|AefO-IoDSt7+=48=|a2Ly*97`U@$X3#eeFE73zybD<*4F=>fX77Lv
z(ZV=(+vX>vOx*O1%h*p91CN(0%hskBzskMznoiSvk+{R}+DDouoFxufhm+PB?o-s*
zw}b!i6(>&gezg>Swr7*(Zl2x&UzfS6HzSUHd7GdB_drm(sD~&1+`Yy#<8C<;h#z!$
z3*VB0eD$zB8eq`3&=~Ofw0$Rj(u<SMDQ0@0TW9LXFKt-MP4QP_F@d6z5K$r}^G!?V
zbm&8Xin*IEQi%=j#Sx)(_cZZ8oZxwrM*H`SEkv5?vdmru@unx739ESETHc>U`4DsX
zd^cM^LDCR{Sj)K{`#sslCw?GMoFQS+*+W&vNU(|6^Kk5jjbrz;kP{_Jb*3>!+wPJ(
z6dzDJuj#YSwqIDaoj9C-DWTVuao4Q|jAd4ilj+OMuDDg_gLW;PjY1un05>=v1wcZ$
zC|s&rX?thyy^wsvoi#+WXpnJ6MS6w!HT^6_LoXEv&x_|<D<s6%Bh%Gjds~L#u<;PF
z&4{uref{C?nb@^a#-8n0SJo3`CagSC*<Zg%(g>f@>2abZR#iYndp(998m$18(}9G~
zAu@BN59VMC?GS~|S!8tGGTd%!;E??gQLd4O1zW|bGI>B^=5SwZ)%G!UcabEnxDxnI
z<&C@^Fb_LgFDGuE(mrb0+9BS*uh@U3{DhdBdA4~KphV~Q+p4YRF>QlLEhtFkv4*vw
zOG)R&CZ_!8I0-5rwF(`AE_+h1ffbCpphlE+(y}IQtX7j$nzaEY37uLl0(haM&_J1B
zcmIHc3iQc6A$7`-w@kOKbl~8g2gECl_n4B>;Z1j|Y7`cZ?q)ap=Ulm`Z{r{EG8$Ft
zKndr^&Az^~M&L3!$xGfTdi0dNb2+c{Jicx6!fEj8jTgltd*}XcTBK<Re7yNtSPfk&
ziPv}2uH_^+`*oH~cSk}}F$YVlBJ1-WmbhpKR+p4@Lp}mDN3oo9IMi3B6FUYTs(K{@
zqevM|CI3qAT6lfJg~7}I?V?RK6U0ewfBP$=vi5^Txl^;}ZPyMv?&r1is!8ZaXT}Q(
z%7gqyTC$hfHlcx{!YWD1eJ^}ZC)%MW!gIJGcgvPTw&D4b8zhtl-UOLcHjYijrkZ;@
z-@h6X1H7|9(m=<?ps2C?dnwnaq{k=1Rr0>RW*2d(C{*Iy2vLMGn{e7=aNyVPly#kN
z(08`>{wnWt&vibkSfs5kbT=m3ZUk_*B5>^fI4AC0?m?uxiJFPkW^|O>2ngy%cenvG
z16>ox*QA^ui}ccL+I|X-_YJz2`^GwFE7ZL@HE~^}6ppiGunHUK-an1e^BJwiVzFu!
z1w-e5p4Ic*Se%&}9v+na>h>e2<YZ>p1r-@K?i0VtBW^Z*p^}+Zs-C*CAnp{=Mn#Hi
zVSb4}UsqRC4@9oIIn<^Q3my`IEmF=5<`X2vE(EEQL5BaD^#!PyNCMlrfZWegK=)G(
zypZ`+$#AbplBgNPvq8CosHcQ$k6tOT>G=T)u^UD)s|TKlZa<{Q+THxH-VLw`DZ-0(
zPh{p*O}#R*8}mNE4m6Js-1np4RCX*OqiT`z&vz!CE65(l<wN7wV+&s{1x)EViRy4?
zI;4`RIKB3ij@46-5l(du*!x15#m<uxFiE3u)WU<i>{gOD%|9PwZZ1L~6^Ik7Y^_+#
zp{0ovWMB<SNXQJ$Pmy238JeN;KMS>>?Z4rvgreW8Y}r21925(*o~0Kji03ETSVlL_
z<s(#C7MJb>|Erk2PymL|3wGxTCWa4PRqo}X<4OEE1#hf>w4V0Z=R$5!SXOsz3OMS!
zHeHNvL_LfdrBsn6D)&qTt)1%+M9K+8SB)25aS8`%<{LXlP}RXr`q=LzNt<0Xk&jYx
zo!*za&~V-JelmHiP4mM&n0DGuJFqfENF`?e(WHBcO?g4Wj!`;<BY4SU0wb?H-#R=J
zG4UI|f$9QjF*y9QA*Es~>@Xit>@~!mZ6hdz`4F}U!lm%nVKzep8HllU!300foca<m
zjm;AgRHs{+4ypFTe4!QJ0N35q>*~7kIsW@*Ih4LaA*Z+Ni?FgezoTP*u@Sx+=n#$x
zNlc?W;r{p0LKz>i614HqT<N~I#Oofk!sEFpt&*i?x8`52@}ii<aJrfq_Aot}S?@cS
zaV;9Go2;{YU>YITY!LRL27P{MnreyJt!};aa%RN!Ci*W^S)qulUSWJ=KB*IHCyi)@
ze}>q5V`ZccXavI*EKZ8d4oN<FJFW~$wpxvOI(#f($(S>W^oD<AheUAoav}VSddNWG
z@2LKGT45z2Y#!tvKuvRK3Np=bKxn%JcXvrt*=lpyy?8w#-tNA}&C0-4JFW?+LKVYp
z$Y~G=N1*vXZ<)0cWO15@Ile7pJ7;3W_3V$>yIs{jTjPn)B0;^68jB1dY^SCpvyh%C
zBW@kF7lW+$H*svSqjT$W!FS$`mh^V_yJ2!BO?xc_RWMb;+(Sf+J}35$TKc>Uzlk?6
zukK#eyOJ2c(Jk}lwf-^2fe`XNy*Z$rEd=9ilBt2*xD-%6cWClF)GG>XeeO73^Najq
zZ8YYHgFpw%{il@Y#kYOb@i31<?nXt|{x&88EBLeY1SC7L%ruhwubHe(0NlkMX)y3>
z%Gb|HT+9$VB+P!d?F&G{M$;hB_cR&^o?3AE(8Iw~KkqgnpD-g=78<2pwfr#Jxi%e+
z^IP7>hi61_c>X%!@orrmV-;)<Wrv_?$Hv!)(oHQpIh#MsE2uJ$*9%_gcV<WU)3C>T
z*X9pwa;e2gVtnHGu5CcZUD=-)n8xpmo7kCi{Rs{hZ~?Rp+8TE#c1xTxKXb!+T>1#<
z_E@Kgb0w~7N&wk>HLc1uT~^=M@w<Fk6BwUF9C7jBCh9AM2#qvuQdk0|<UQsq%SXrw
z1z=`5f2Cv_!^WV_RTdQ$$>4qby~{w3Bl<r-9tE+m(u2UD);Bg*(yDk}kCprQr+hqk
z`hJU60;p-IH6Pv6zs5X8N@yyhc5?Qc-Xu+6QMs#@9X3@hhOiHR&K{>Sp!v^5sEC=m
zo{^lNRgVn^)ZIRTT`G7OIFJhH@~8k2v1pTcH>y^x61`K09zA_+dwV;BekaqH*y&u}
ziHV8NGsDks^_NSYyHNkYG@=;j*#XbUIbGq>?8rX_(8u~}!-@09BqI?93;mJCzb=#O
zd3%0wGJhwM0AgV(Mn**$85vpGWQl`%1t83nBt{htg8|~fAPOQSEv=_|8a~f!B6fCl
zB4pRo#qrI}ZWz6<a~u*tAj#nXpd%oi6-G8{THCpOddu7_niD?V1gVOmY~&Fl-KQ}D
zF98IJ$6$&}NK{p#Z0tK(aYFAXOLbYx=%K_0Hj`d2C<>BOP#_WtbXQc^@a8vHZ|1xV
z)cop*Jf`Gk%ucp;xutoQ$^oJC0z!7@8Yc3;`dtlNA&(E{0gPt>u|3ylT%=kU?1d9!
z0F&YK(r@>|hx!{FFy{8(gUP@LhlW<_43X%3{rsAmn%W$<x5(TZH9Um^=$|MLbdG)t
zJR+e7%$8_PHNc?2!6^&_&o&D?C?y5m*4B1aq1|SQhL@Lj=X-H+lk3U61!l-v3j+{S
zH#2N$;YbvSk|-%DG1;#-fBW{0TD9zawIO8C=;Q5Kvu==IfoqHj)KfeSo|8ZWpOgp<
zx?f}qo7Lj?;o)HY{$i!-wl7#YpE{(Q+kF+)N18McTPKZM49S>+n?VPePo(|o_3QF^
zyxf6P*3d{Jo@%Hv6bC4p`C*XA{f&OI5rAa0@;Lv7j+1~xKnO#_z@3St%k;eZ5dIVj
zExC1CRj3YVT3NwWDUPSEJn8!Mk<!sDaMS5^-91i%WOq$_L&-)SZx~GZi~5I<+dcp6
zb-JAuOa^?u8d4;$)er7fIQ}5-^~)99@GWYe<WS%x@TT51aJENt=6oJ#%E^If3UDxe
zAC3}q5ny>x0OcUws~@obJ6Sf#_3>P>*X`i|DjgIQRKsWorwH$=QW2}vgm;=X>CaZz
zBwjbi@+XC+I@i;;<39@&gTa2p^5Do=e?638qU+0FyjsCO_Ww}GXEpmgIxwSiRq7J~
z{g5sz2|bwDKsI6kRL4vfJ1r%p<@L@0F)?wGY<-Eee2pwC(Y2dlWV3frR^biH0I0+z
zOCcpN8bTztvtk$!7Zs(ftjrzo;oIi$EA)hG{sXyUA=LNf?j%3pqwpN6mBfDOIyySK
zJ_VvAgm|E}q*e!H!X6pa=i&VMc1Cd518yJbOBh=P9Yq>9_;7Y&m&X+j4vtE0`lNd0
zFDm#npW#RpPKV7vxai8jTHpoWe9%dnNN23mZi2Kq+TUmWx;OlwBd^Cu47w)|%{4GN
zIcbDUQ!<paEV=V%f3(SRhJl_wl@yE$5Du=JwCo5?rz`?Kzp!vLoeS55RsR8d*hoef
zHg1Lk!b|~f;BSndC%01diwX$=gf$u#7FLP0p75f~pq=Cb38Z}mGtJ2F>3U#w^^1E@
zb06#;PL#M%EDVZl1lk5Hh(JCPDbkmSK<<I!#8w*!x;B6C9ZXj^I5@68{D=H}ZkMv!
zqkh4@F?y=<x!=e%SkTBt<HCZJ$SDh*zSVQ`gA8><j0trm%Zl2)AJLqq4s+R@VZK3l
zaT2HSIw2py&LFj25{xjZ4t}|XFQ|KKu|mcg2%>;x$)6JwA@BV$I5?1aWe(!t8sGJ>
z@$nIk3<u6RbHbLQzx{}M$tWGtqhJ_%I9Le#R*UqCZo}p=#nXq{l~tY^X}UpY-QCZO
zdAY|`E9hhWs}Fn6*`}nWcRCdK7#FP|D}BKCgDxT#TVOS$z=2QW=JqyZim+TUe|dQs
zbKJVvDn00AuKXv8e3FK<>&YO~;WFzjRN5^><g&Q5N!)LQIj!gAa{}y`JrQjt*un*s
zc&{meyIrxT);XFAwZP8Dv|)c_3|qHcn8Mm96k?>mnzn$S*y&=Oy<G&>23&WRQZbJX
zUp@J%yi(YvXub{i^n2NIohGA9L$IBKr<wDiZeEddzOo!Ct3J!S=~iiE`*5tLR0q<6
z*<SmVExcOv_poi>kB%$47!-DvthUBq-uFdMShlXh6*0>N27b_lRG_(FCF+(+NIq8C
zkCuTQ#^5~2pqZJO^;XDfMgs>SPRMC@OL|HaMXGZlvmePCT;b+4G{wXG0!>r&pacOT
z$5RqL9ZmWSDKu2wvDeRQt~x?Abydilwu8J4-s|w?xj#;gVs$tJ(V&P=R<IL9bRI2(
zN{zwS;eZ(ptTZDG42(Ej&P!lKN5!yq#)ILB=;DAoy=GBp<skV8vGtwzvee#Cm_(!x
z%3*`+JC+Ws%kk+HL>*ibgK)4wAM{$ongINB4!`5;)p9ElSsqIPD+jTe?Cw7iH)801
zRJtz#{ZzlZu6kczulkIC7>UZX!PIuIy{x8tby#yc8jg?4$I7+`&Z;Si6~+*V@M3A7
zv$3u5Ev=ee#25A$VJuTZKt`{f5`-jPR)N`@2?}vz&vrmiG(PFI@3Q2>i<Jm*(bT+m
z?H(N+-j4mzx#$irhlahW20s#|<IJCM<U-Q}1){ho9?<ysc%ZqsT5qAH8&FYKfA<EV
zE*OLVbTlNzO%^|UFr2#FLV81(6%XOna?$m+iX3HBjrrbLXUOS22_A86H%4sP4_}5;
zw8-Bz<Sf{h`Z8bVa+{58u>O^vo*sb(IVn${7rU-AX8>aXvO5At2gfIQ*gUH6LkE@7
zI$k2x2qDti+Ep{Bm%Ez)?twj?ix9Xg<dFVC(FjBWKIpC#py}f_ld7io!6=p%{kE0s
z1}nUv?~*q%0@dZH*OvGt*jFN$GpCl<1ZsUXw-a4A#d*)e{x1FMon&l}SRW}ub%64)
z$S(V!unvc$^4ZE<=;)A>SPC%>g=y`?%klQ+CeNH)9I~<KG3(S7Y3e&Wh0-||imSzo
zk#u^EU#ao$-<>2SS3fBr(7yTQX4oMu7lsDcp%1SCHGkkRw3xWKa-K{39A>=mw|2d3
zw0U%+o<C=8GdIz&&I_&6ZDCP#U&3aUPSW~(4;_sJfBHP09!#WTLnB-X*S=rGe+Wx0
zyxuvde6><{vY^#0$VsFG<7rD_EU8QD#L4X!(svPB-EfTaQK;YaY`uG$Y`%uGnlw9z
zy#=w{p4#S9G?1=j-J^_%5LCyuH)ac@3RH5pvl<+|sx9kBCl`FaS&Lz=ERF6NRmkTQ
zNAlGZq8l985YA2!!3drC$a-H|S{#?WH{aqVeTZ+*xi-1qSs_M&NG`Lcgn%0M{c>{3
z5|)qR#_{Ivplp3LV5;3zW~HIS>|kd#7WaE|-XY{@ie*yPvrN!OM$teft}*yLG%|)$
z)ey_=jNfx}re+RI4SX}UKGKqO)b<x5mwTJq*Nok}4hz4lP`tjpm%_Hg`uy5SD7NHO
zbPY5~CQ$oeA)wtaEhXm?!KBw|_P#&mm@8}$>C&$8;IrQ!VuJ-Bs-`m<1|j0NXR4c+
zr#bbz-$myZD_)XuDK^SGVJnK(t5ma8#5Hp@JXKA3*V&?hQrri#>(CSa#t?>VC?*&W
zoTfJyL0(ldKKgFay@eq@dizuPnchQIQYakkQyY^(u+}6~XS8pr*UJ9HF<t$VGf;`r
z=TmE<Cy!Y})pKB?Q|Fb`4^uYv;^JcW7(4UGVX|UmU|}}~ol1xFdh0MyS-66Ya(z7u
zSr$C)D#xiUpsCw<7&Nx0rw1QvZ5WGyuvTS<v!|RNm)ZWj(?GAJ4^t}h&q5hfRl0sw
z{S~jM(U0b)g}}zKBy7Vk>|{q(<UjJQhr9z!>e@z0L{Jw-AW^&}pD@GeRf$!c`k{eX
z%jpAyZXmd+-v8x<($LUQyF%J>V@GR)M*Q{N2qoXz;I1L|AM8KUZ-bl3zUXQ!U4~II
zBpcAiuoy*A1aVMaC#cfc8!bB#fYjo|*ieB^`p(nVFP6p?xdgdU0L=IBEn;}P#`_zo
z7>J8!1i^xG;_1ha=)nj|ex99#ZUm>Jc3~B=YLLR2AO*c&%hULN!NgQo_8yVmHXZ!X
zQ_B^-Z}agqkqiwBkBA5lha_AR=qabps9F<5B0gH~H}iCcm8BIK#Rq>KxEZIV{DS2Y
zjLc))MjD-s4E->anv3DK$#`yToQQuspQ>dpGC851il95v15?M8=SW-h_7<OB4n=~V
zn>bWzrL{pqTNEF`Kj{qNeb~z9$wlx3rdjxWA#;^jG%zv*o)nNRcsQAvoRkD&FaiW0
zKPOc6YipJwDYoS^h1U~KvyxBLABw#-vIV8vrs+9gD}#KnU5f<oObfbx%z|ARS_w_D
ztD`dCl?k=^Fr5#u@E12n@=FD5go51V#CQ<#?(gkhtPD)g#yI!mRrDSfvV6tsl`{3w
zYOKz?vj=^2Y`_sZDn+L5rOdfgBO<s$O2_u3Q=zP$o^6VDZOL<DzBj&_fbL*mEvHye
zE2F;^{xDXLrI{Ek4w9YU;O<Z~Wi;##;H2vpl>(r=ijVv@of(iD&Jjqe+ATm4BzDz#
z!QzY703T%rZ9xgNuBO%ePDM=}77<ZhnY2M+gSMLzA0c!WE7Cq!ZX7O^nYCs@lRR-!
zWn9ZWlm6omS2pdKW!=GQ4SR$&;mt+<^QAc~%H@{d_V&_v)N`g}O$*v+kP(zc^hq-K
zD2hgS#3&YywZ^z{{36K+o%-2IA04^Ig4w{H6AwJcosUOdQCcx1VQNCE`7Sl-VsZJh
z&`^UdsY~KXU7q^y>#1{X_OFr*P&JdpekLSpT+t|r!r*_sA;)b2tzZm1yqfZI$`JN`
znl^M$dUn_(Qaq7VVp7)#Q?^E!x5AfZRdtT%T26cBM$2b>wL6KIq~vB|`FP>Px*Ki>
zA@`}^&5B>;a4kz1^Hr(U&w!Z5Q>44^JwZFlBe>wVR$^mFykinoWm3XmU-61>@h8W3
zhlY-!GsZ|@!~}0<w7f}IBAx4~!JVFWA0DKFTz#TYce(ySJ-3Hb7_=HfasAIwy@?NM
z?0V^Cq_ZLvWIQBve2N5qA9_!TJ)`^JP?#GI%|Yo{gOt|>HOr?Gy>w<*$8mPS{zQ`F
z>t*h8Z0@0%x+Mv<7SG8Sq;l`~ercV^VLx1m)&}WTG=pCfggM66b;=o|8`u*2I!C8N
zLikKAaBPr_i_qw@)z9T!4w}}=;+gOvi<5DJ@Un-u<0fX6U!5M2L}kaO{c<9D>x4CK
zQ4+*$NP_dt!GnNUa5{?}&H*n&FrYUE?)iw4G|QA-7b*yoh1jarT>Z0p#`*qN_xy6s
z4Zl$BOR|AYmG^a?;XP&@%hc9V-o-_SmC8YAV)WceNkJ)T4dwCBDRl;wb2PVcxk$}j
z)kx5usQ*vq9a-U;Z4isfP*K?MrQI5j+;kqDgi<~1JWH-i38R)p26J()X*TmX2oHgU
z@%RobUkWi~`f3i!c}lC`eJ%W=iri{iG=oXHfZPY8Ug&@#q5Ihun}-^27XLwLDNfKI
zKYlQsdwzbrXE2+-z0-aYl<1n*=-ZOczEOl0w$&7wXye}-(Z!&S7vqMit3gvQm3ykI
zdBPA97g-o#XfS7w9>7>d)4>01oUQ(fTv~R9kF`sYH8iWMrQC2W3+opcVz^i*z-K_M
zV#ah#2KlzB^%)c90E6LQl5;+5?(@Dal!Rl>9*0kmwjnId9S*BJJCv%6*f}Tm#EL25
zhoZrVW5_nh4D{@Y0d0$u*_@2@^cNeBef%Dmcy6zaY*b$K6n}DW3Fix>5%5uyRVA@M
zlt`1jyK|q6qSQ{`h{#Pp7`LOAv<HWQpac~*EhBbBsW1l<H9avlQ38teIxK}^)XlZo
z9ljmA*(?05$t5lRV=SsxG1k@wV(!~g<|4@tm@gpO;zm<h?CA{pr}L$7bOWdAZrc*s
znik(7swF*AVebx>nx@oIX_&t5l~7YGHp&^}pfG=WvFKUSw(uw#;i#*&1tHBlir{D!
zj(l5KoQi2OLA-d}K1A%2&d3W&qQ$~7b;W_BWT4!D28V<k#8AoQapUoSd#X1cDk*32
z^L~8!5q&NEQ|Y*HUH{NE4bNax+J7LLxqr+&AqkG>gB)fQCmv8!;owQES0s)Mz@3He
z1$v~75iQ}+?|()KSuG~5z@hX?_W!!Pqt<7bbtgbqbJdPxvM_|q##SLFW*F3l7+^89
zxTvPDpW8@?&_Xhk$DhsZa(Fb8Ut3e7ryrG!3ABfcA;8q$ePBovPI!M99G208>CY5u
z1lsV*Y>c3cj4$nq$cPK?;qdi@O3t(@Dk>%p4hFzThWFiZAYhM61dj>y{%`W{{b^?t
zk_fPmgoc)^-{sC;08e4>0M5tHZwx<hbX#d!)9){3B~tKg^c%!d`0iqZla4M{0ZZF{
zepAN8{{j-2cwLuQZT%{KJ*ke%85rrwL=3EqGU7IZ7KsxfYan5=htNcJzud&OAoY2q
zK>TX8KMQ03tB25c&b~$h3e9km)><j90md3xFXIa-5g2s8g>yX#6Kv9(%&qBYy#01B
zKHbz@u_OXKd`aOqUXRP*uC-EOH0?Q%k)-;R>DATtfB-I(o<GL%80V>JY`{`0YL$%3
zYUrI7EyJ)1H|PT59Xt19B{Dpmksm+S)=*Y(?be&e2a8UtqL=4d9H@8HhWuMPcTtjA
zeID!(Bf#7rfxdb@u^PNM99he>bPs(2mqipX7_%4zFy|&~KAy=Jj7aSQR)jg>M|O4j
z;M09=Y$gRv5KiZCgXsk0!Y_;YzCAU#u{lgq{eHOEaPm|*J6=I4IX*kHwX$*z&D!IU
z!3CY26Y>Bm*zC`@BS9u868lqQKQb|Zf~rBUZ%5+O?ob2=2Zs}D2AKepapj0Oj-AMk
z{g1IRD^M4^{olJP?8u(aEcx8Vdjla*wk7+Lu|l$>fT0va|7VC!+*L7923K+MBwQRF
z9gf3oUubAWRZMdj+tZJ$&ySgj>h;QyBJe2;$9kBce0)02z9-JD!C!pxJFiC#l8QS5
zhQM1<8`uAGf42K3R*z>S*dN{8>Pc6}jT{J5SgBe*X#KM#bAWjd=&Q7}wtmlDils*2
zAfBSaZTg#}U55o}4@mSD4|}G~_+dlKUcXsJ3b+DE*`}qTfn|USfpDW#$SGKD9mIG9
zmbLXjFhj)##u6tcCK}n=!pZn}dIn<kAhbkKBXG?Drr81bMljmAHuH#LA&PJ|Ny*9k
z=jWT}OCXFrtM(E=dfvqhVhN!t6wl|IgS(T3Ldn20XkdJ1wY5{klGFdqQwcJsral*9
znWU{&fQA13<NbAfe4O9=E^w)bUO7p<T4QcZ=t8qp3|Kvfs$`n?1%z6BXQ5n?4)g5(
zY-K0{DdHluw%(+ifJn&u@$%Pb94-_Ec(4!=FnvzY-kSx%@x>}7H5FvO4wW+)KnE3z
zW9$qs5T*g1ohU&R6$8wKpn_yD8`c|vbXN>MlRG7$=a|nQE(PX6Z`tn3h(!jz0}zOt
zJ2Y6T0B%iWcUQmw?UVsT{UdTg=FS)xG;-nJeVr?rhX36cpsZFzR1|n5T7O_HsareJ
zX32vPXAgwI;bB^Gd#75y=|fZ`GlM9$+cuKh2(Kc~M*~B!vi&h$!00Sa5Rj=M;@*Ni
zU>FR>vO_lNyIQ)KpG=fYV>M)ku@b=u6utKxzp=!a5J;FLapP;qK$a;unfT6Dk53FH
zJ*W*QXIt796;Y*vx~p11=uutOwbfgjle6>}YreWpSrMNo3t-t^G-SLf_&PD@^YinL
zNW}iOG4XO5y>3ZUI6Du;iJA&UGwADFmeHOmrum*`Q0g$WR5SqZHZMJ$vIKGh<N>T^
z45(a<Mzw9-8AR}%O7Q<GCSC_Uy_Wb$K#eVE8x+@M<xfWKMlx#ZO3RtNdhqJ7?izd)
zbG;)P@M|#*3{+rU%B%r0fVR<MDr<974>AM<DsV`|p9`#bi6PO7k!sIdDio+KQ3n>Y
z#2_Fb2nBq<a5)*-!rF(@5hQr*kHlFol(84pSfLpBkA%cpZq7)RmZyF1ZIwAt{Fa}u
zJ2tCi*}Tq}GBf3;O1IL{)rljj#xGXtaZ&o6#MC3|YP&DLDzdNd6G`w*saEBwke@_|
zUfSxQ<EKW}7>!qM_7@Lc9*RHy76g6VIEqSl6t6#ggz;<I85^m-Rx%1K3X_zMS5{UQ
zOT>BK{EkXFr7XfcCx?7IZ?)eLo5#U92=B!9SenJ=9Y`^^;c*XD@ZjE`MQ0cYdz@91
z-A9gym7Pw_zc^~;rfFjqWd1i05tm1>w)BJiJR9PqEP_x&F)fpl>(b<0%a=W5vN?T{
zdL5RcgwA^#RUMy{w8=|V3p2cUl&ZR&qPM#GHXXe`W#KmBIDdDEf>Fke^Ru<Bmzmrl
zw0A2Y4T9e>wmCubkzV^thK{btJ2eDSh+Itw&g!jtBe0H^q?=yA=Rr;blWWkR-tBC8
zDqoNgk*kUjv!O#ddsNq3a^qQ|m!7^3ScWK@P%k={_JTM*``y|39mVF_R`6oM+A(2q
zL_dO}T!^OQ(Ii;v45m@BHZJ_`<EOJpHPL(2)mBeP`ZwJ+2kE{lEm3W;f*<nGg7mIG
z!>eyOAo#|mKd)(WhaQ$ig(c##aBhpJK<jgSIoVQ_&t`aLY^&BDv~u+eH4Xc`U;Zq;
zPjuO<is)HhDxg!-XscbD9EDetBU}x`CJ#9t7D;UW0y|0_eE-VCOP1+xuSkx^NGRx!
zr|>hxG##f*Rd|sGDZbaTWShm5okvb{Zn35OT<%8vc=(>J2(27GC@>qvn~bmTlpNT=
zz{`{S@O+|HF5KYk>agD;@Xci62@Xz~4P<KPAf`FD^0b504$k-G{vx%>an+ThB2+c1
zh=?T5uwy<7*;TuqPJF3(>`BuqgR@7Wzp2}!v3VZ4<F^rX@Zcwj+6coBgAh{e49600
z=dOEj*viONC8U*?j*D?FNsWvnUMW^Tq1fA<K(s}Wmzd;)?MzjyuB)pCI32NYaY1|N
z=m@ivz1ygG{{Yc28w`bUBGI_7+M$dUVkMddrqUc;3`y7ySAHb-k}KLj``6qL$nQ$v
z5*)!Otw^qr+@#)j{?6}tLw3XEvfsK>ey{L*Hm_t((sU^6W)P>z+RmO~S-L1BqWTHl
zbGO&^as2YktB+ubo#aM|h#^YFd#Iwu<MCxeg#GJhndBJx-Re)6o-sW2!=g`KY(l1)
z*G<z1<?RKOPko8iZOw1aF>2mOtZi9U8(>w2X<rBoO1QfxlFy9C9o5((rm|S?UmcG9
z$4;{QNr-l8f)*x?d%(rD3(FZrguSnfIc|djHNGW#-kc^AQ!E6WBk{ngkTMSUoS2l*
zV!8G}^G6FH*Dwb>c(RYrhIx1au@JDRHHim}uv{V68<>R9WdT->Lo1YkBv9G$mumQ`
z`hoi{6IKdhl_bJP-bPkPiJpi{68!n|Cj<&9JcJMCf*fwM{E-Vfx1ow-bdX6)!@!2T
zfH{#U!bCO8Wyx7t=#9?BZC*6V#Vxg^*xoqoBX`OIjj!llo8#rj))oOYx408lUu$#3
zmp#wbCi~#%IJRlVGn<QqJ8e33j#(~miNg+DR)-E<9#paGeDmECrFZfH3aX0ymisL-
z#oM`1F5%yX@na(k$ww&i@r|&k5BF@L^K!hr2<<aa+${TW#o>YB%iyvlj;7@^U+*3e
zrQ&>#&10Xit2<8vAxzfR3Oz-nyI8gTF~L|wG*7fHAzIGwVzk3;3-MfZyBi)7jhNS~
z`r5lz=JUQl3SYN4m6F^Cz_z6hyi^18OWXBnSPE*PfHtHhL*%2MJfMsD_1C|?r&f`k
z3xuK^&lT{7WY>pM7olibAo^)zKX!zE3Xq+X*sv_VI8nWhC#NKkK<u|=DW$qPx#dZW
zd>ryo?+ftv=|JU;Otrdc3xvqE%F}v&e2hr2DEMbwbT;|G<D9++z4Bcg!;)BcT-jdU
zKK<&S%~Dm;ZwsbOnMHzm9UJ69thT?8%s`}O@DntTpUohLqxRF_+ZEvM$e9HR9@?!)
zI2j#5Q7$6F#&+R;w_b~py^Rzj^8ff)mxzqpK+i%wmvffzwwTV*Tv|e|Y^QP+;BB?C
zwMEM@6YNL0Mnps`>Pz$9lkTNE)=!o>Bchf!A^DxGrZpM#6^6C4{aft*gxE{(4~#H@
zM0+%;R0=I-Ke(Wh6fikIsna&*(Bu)$D5>yRR)rVn4uNVaL~z&=!i*HjvVdnIh&8f<
zuXf0drf4ov7-7srX1ef{W01^#--w8<ahd-3%3{(eB7sY&<B*hDg3FBvNB&uqd=VgO
z;Tng6rc&sKYbMS}DF+KM!xB@cijmiXNK;h7U)ON*g>g<(G{XRt#Ci)Fg|b=A60HXN
z-yJJw^ab;i4DQ37(MPbF69n~re&G7kGm+0`u_vALW8c}>6(Hp$xpD;z&+E(52TKu{
z;&ISFO--Nc@_b9C9Km~aETO|Mi^Zd;J2qvpmHiEse--ReKEvyDABi#7@I9|=VT104
zpYWcfysF$Dmj8eWHa^VXodw;EQ8xOH-N4Ccy)3yL&%dNFp>U;+gw!z($E}Du5ysrO
z3$MSQtmk?;?9Z%Y6XpYFb_@Al$Trz90PZNqedsFyp_YA(V~pn6Eox9sG2c2uZuYX8
zm#&$i9eZ2MXoLd*;%s>Q-Gt42V=2LB@?ra0fP2fW1y_Z~6@YCI@BF1STmk}LYEE#h
z8^etLnePLb;oSK_%+IeM*-%+Y-40C4UjoZLfhi!lI1wWvP{s`8iZ=Ks^ti~8Af(K-
z$~>us6JvDHo>V2vFJW&lXLUPcC}oR;mFzIu($hzOtYYiF51CjYEJ*rbQ9BRv*;^)j
zT5Fy(f{^VT{Jz6tPP*Isz<-)-_w;;qbE*Oc)r>X^U$P>81`fJ>ihwmdb{~%4FE+V|
zoBmqkox+DDRTLx54l!-s<0NAHrZm$}esYnsS>BM&xYdV?DHQ7&YTSF^dFruJYZ(w4
znU6QrU)Vgmr>$Uje9`<na$(B|#z-$Y+Zz;qrqTMkIE1O+t{35Ex>|Q*8k(Xm#}_Y_
z+Pkpbo5V>#MMDF#W(*p(=wlE0&3Q*jyxml$x#x5@u!#xu8>!IyIeEDwIJx}FV1wPu
z;JIYN6$PcCz)_2%=w>hS5oH@5$_upRgI3^spwNmzquXTusA2m2RJ>C@pQ3CR4nbPx
zpKA$EfC$ClrNzx~VL<~bv)dN#4+pmRuy4!2Dru0QWl6NcMHU<P7^w=(Eq+*GZ{1p$
zSCGQ&@B7QllnGdAA~_Kw?<_$~NYM9-=P^nw#PN!*qCfI?o6gl4#IEqTkE_QRRSRyT
z@;(^u#HGwL+}<w5hL)g^vrv5O8gNQT)eI!$w7_)7<)PoE%1cW6>1O|C$G<`8^!jqs
zrTM)*G1JXDdw4`(!)WawNxH=3HOMKq?ozhfhw7uA8}d5s2!&W|v`FBP{`P!?nGsSf
z@%cRxe<`3L$n^fCH<#rmK4=Iym9dzeeB_hM$M!y?+ZdY5k}`If=sG2_!5q^>JnTxR
zz7jxr&VB9T;id)_;iIX@neY7)x1+);V7~QDYJ0!%joA$O7-Lt-rtoNrW+Pn`9YwVZ
z>Wxbd1I8EaoVQ{p%}#BhadVnYuHk<6@M%t@Ane(lm%Xutd6D3-$O!%h<0l+egXBK#
zzUOH^@PJH5R_*e^XbIhBQWVn17oHpPcLVxrQQ7BYi%`ierr<j3xdv%pPP=H?Fy>OA
z;BnbKlHQZ9kEA2)=Zf_?S#}e!y>-2a+j9>JX_XU2uaFpV+5S&sUmX=k_ifpD<Be-@
zhv4os?(S~Ef;$9v3+@sK9w0b$LV^c^gb*Bp6WoLQ6yLYrtlzAeS?~Q>-Bo>Wox11L
zJ?HGbdq;kz1qn-_X&2dg5R6Ktb-C%9tWd;HR#6nrum3S$Yn;?3+^Sxb8Rumf+Il!4
z`<db!Q}~aQ8Q3<y&@KJA8acN65xFwilE2?Gg&(f#SKJcfi?&X@O$r6(g6kEwymjmD
z_p|UyVhT9K%=j+7#k<#r?k*3{&dv~M;bb_m>e6)_xvShU661Xi7rd`eER{TmTCLA1
zF<mz=k9tf}xk(Q2$Rinu9Z@I$#ExY?G&OKjb7Uv!tl5f7_?>O3v{oMlzD3a6eXWlF
z^-@NQo)Jmtz55^H6VJWR!zcw0GJ>nTjp~#yoV}a4q86Rxfd;c{9xId+f=C&8EJ_>%
zUQzt}GxWhN3biI?@CwF}&yS(RI%V&N6YX$t`1((VnGufn;!oT8zq_0$$axnO7<BXV
zu1wHiy>JP8!^*ZY!vKz6ohGI)Zn3yV1_s^u@(D%DEG$@qKqLRdO7SD7v1&{fKlRQg
zA4hw6%yEL(zLC*GaX{H_DCKQ>d*;&RAYxAR-dm*!_IeB{cKOn7OUPdPj3q-e7ModV
z37Pu!gMaX+v7zZ#cAni-)R+iVZ+|~#@7&f149>ucF#PKlOWPT)Ma@w4@v`ar&FNLN
zUM%8N>+1XWazi%InyZ(eA$!h(4R(FxV%~hZ>r0v^>k9=)Z~?D)21-1m$1G`d@%bdZ
zQ6cFrc6KN{`X4@g;I@Po!;k9%42l~4dP42odWP!6%h0&swxFxs{L(ZY4^N)n2fbak
zzw))+h6}v{0Wz}_F>*^C62wgJ@3V4yi9rD-c_wW!D9UyY_E04sAEm#2bSV`}`C;FU
zf4j&Qs45K2^0!*kT!MMpnWz*yzd)UO7mD8ukB8K$>%Akgj}WvN5v`1Sn*tHiiR~iG
zPR&n++$JC!NM_s#)-T7)EqzH(%P%}=KVX!{3V3&#^ZQKRZQ$DY=R5^zK7{PEP7FDe
zxj3MuF1zbmMOJnXvyz)gML`<#i(jW80j&ml81OXE<dg+yb}a8+&Qk`^o|>&kS-d+<
zr?UNq9kCV!*}@C2okbK2E+jf^x80@xvo6?)Qp(75vpzkdFMCWmSV$r<gpSNAyH04{
ztNh~pjKQU2i<<X1yIa41H0|5U$gdkrLI#%*S&2~?rLRNMjY7M;{gCF}vBU7j_L!vn
z!3zY}u7GUc>7TX^;JmASrc9$)9ftAUuMlC%5L)57e!n=r&wm<hR$32cU0q^a$SgMx
zt}wQ$m#;^gRi$R6q{QW=^@|}fs%xJ#+U|J}^lYMJmbZgReofI!s|dq-aq;kaaA+9R
zhtn*g9{~87#M8ZJ=>@j|VGjPE>YtZ6oKSgX<rv$p>`l@PqR%M-QOL?tUp6K$z6Kq>
z|5_Jj75+d*Nh#vdTA!z_7y05Wvb^N6JM4CbLI|jjZ{_j!U%QBxeQf3T68)*oC0vN#
zAAeZ{q62yZxoTWEK02OP$40YEI5xOa$97IZy~YxSc_i9ZDth^NyQP$eTzc}#gX2xj
zKmncFb;Mlz38m|g5*ib$zHFVu&)<sgtR<w(omRnj>JotqJD!(D$R3F3eShH#Z|hsh
zodjoaKLsp=((COc?oG9^a_u=<6n~@$hprZftCNwD&3Q~oQq;*~ai~Bn2(YnK<w1FM
z<vn!y$~JkC0fY~cj=UT3Y{V*}pIV$2#yPqazRr)G3iUgd(^<h0km_f)+W0cnHn40|
zJRK^PrAyiMxd@0E5PI`w8O?iN`v|udFz<$<`i-rmj}#O&E`|CHSz4`X4SapN()&F;
z(LbAG+M{2S6;^J(tkij)I<MSTRMy`UU+dn%q4`>onc<Wp^ylPAJ`*2*=azWf!b8+{
z%k*6lf#^0lgTdivpLc9I!Cus&xiXugA^y&^{T4TRY(0PWpDbjv3YWAr@1sr=6ERFp
zms(nQ1rMqk8X)Z1SzG0NC(U8IYygwH<Ple134NtADoQ%)+f*I{*XFQt0y=tvQ~ff_
zO9p7+H?Z2KhL(vYmlmB8jV^T?6bh=_BT`G%VKKuB$k6{{dv`12R^@F)K;VyaVmwc1
zelbVB;Ihzy8qD8KNUr0ig*AsA+s8(Duc@rlGeaM4sByBmI?e{}uH|mwQ?cPgZ(mS}
z#vp<J3W3e6+MrzrRt7T{uA-O4BP+xuCZ3<30-&xh_QC`xgq%UAjjIlawYS>W^pr|S
z3U8OAyrS`1s>3|x3YxDWF3e1~p*zD$=C3$XivJ*}OKKm?$kNpXUru`>*_!lTNdX8<
zttG`U#QS8?PDxG0T(_Z+m*8t#Frk-b#(lC$r=-r4urm7ab-3$J8aPz9GK3=VoNo3f
zc16DvvRh>zzKnuGtk>sBrz&)b{Ls))`DBX2`Q}PF!eD%<(0#kb7hl+l!tCUHLXJn8
z>}bi<PEQ^2UeQb?#r94|o@9$y^@AJePe#Jtg5F|>_7PeN4FK4Pq(qk427z$TW}>i_
z(S=s0yNmtyXBeX0G8{>fSRf&xXEK=p7U}2t8f<hKZ!fP^Z^B?rP7anYcY5K$ExBGL
z()Ff=x;J)_X#Nd;isktp7vwV9S|2^*tC6ec<nzLn1aizEc=qS)X_VRWr3sv=U#L{2
zxX-BN#0sXCaWo8lnCp|D9=qN;Uxw26sfjDPbn%xy6p!<8a$Y}NtyBx%SEC>y^`N~z
zG3u$MO_VL$o-rPW)Pm3Ddvn__mv3JhOXL_M!;P=M3}ZZr9JswcrEO(L7!aN+t}G9t
zzL2UAP7!kT==xkyzRwzW#tGk)05V-#>|tfwvqWla8tIYj<-s7;GPm7yJhnMm0GC4M
zED-k_DphjfQ7CyM4M!%R^;1pooL8@8L2X%m`>}2`=zi_xs5d_04>(tfQ{qXl>KI-{
z0~LB5Y0$Fz+AzeRR#QiZ*I|M#$F(+VNe+81xCQ4Vi3t5Jshd_=2+G9n>;NS-$2R$g
zZbb#(FhTT&&Uzp*Oq&QOPBY;Vq474vzbGu=9(wti12HkC>H*Z>h`PHYA!73MHX<}F
zO-n`w(QjeRz*ewB|L>%|FqRCg0#g=%%0|;f?{dL&CxT##A5A{JudKXU|AuaDZEc|Z
zvM;megEAZdV^ff#wIBdW?6Dy75Vwchi{q{*aYjaz0UFn3ouamhcoqxILzL&1in{T7
zo&_SEO!0HI^J*VJO+|c_UnTN?dUUeuRQOJm-pUMLw~AhED)AcXXdSN234cfl2V0~E
z3hiwdJr3h;8zcwT*<-?Ip8#(B4GkmtX`Ef^Mub8*JWjaqKJ_!bTez8ibk)-`urT(`
zd*UGjT!Ifa5S3077sE`JbWVF^1`vn}_N)c4G8g&XrrENb3tm-TQd=9ZR^gp^P+EGr
zWtW0t+>T<2s@;kx`TwSXr;%}NRw0XuM1n;QL`0}8FL+SjmTe%aO-%?c%8>Oci(tvm
z{ht(Yw6h5;CkIuP@H1mu37~;<=N#(<FyYwX5m2xYyJGY5NKH&Jh%$Qz8V5Wat34tZ
z#*k;OxLKUPr;D_M6&YQ`YYuwPTm$>cO|lT^1?{BOqzHCdl_d>aO~0SzrFLz0&apHj
z%cpSRq%Vi6PI!1UTxqw$A?;09IrET3Fus0i*y<zwdvD35tWs2o@;&-s?>aC#8RF`J
zD9j3^XSejl-xI))x?#oZEU`gnc^jm6JQe{44QwhYaQ_^&-=@U=>Do@DwUwlbiWZ-p
zw@4I2xG6lbs(G#5GeId3n_?u7Pc~ifB=;S8FkDh@ZGpS^>VZffoH>LLzbw*J1&WZ!
zmPnQP?#<1?x11@hZ_7YMCjUK3_y>Z5<3lQsCrNr>TRxkgb-Oz)*ow;iX@2b>;WW3N
zpaYXaBEgoo_-_?Mu+;E;I!<+c0xzb)MgUH>wocT-M2!dO^%6s83UWR~ka@Gd>oIL1
zcM{oZ`SMRh3`T@lpL0FROfdrO$#KXN8P*m;m+%~}va&Mlol^V}QHg_Ulk{UY9*n(I
z7gi1Tiz&AGrd(X)V5>Q5ApnWwYSk>;`IdBk%>}`blj4_Mqt1UKeu77qCUA@hV<G$J
z%ftMHf8-7ARYDQit^aQI^6H#4eVlo;QEY2(k14gYDeB;oZYhqcl)f-laJCYhAv;%f
z7PX`ESFN6jA(T-)MlI+WZCq~tDmFutmj9Vb;7to5dP_rNbBDcyy*g7bO)Cy-;b)s-
zEn|l#_&#0Q?ybH6tiXDyL`q|<Ff7lxz!9lA9HBnAuTC?yVL!GTLLgY*!b?9@ANHGn
zqv7W#R6C2pLazmrho9@-R^WBNK{go-+!-&qHMA`Za|g3lx4ah|z!P4pjYnJ0-$jpk
z8Vu|OFZ0xkzF>j?e09;tt{gl>_1llB1O(sQdWd8Y(*H^#4iatU!=L@7S$j{^e;$cW
zPyHon9$CFpamxR$+^!(BWWRY2Np_lb>l$jQ<}XXQs2rVw?XD5R)icM4>OyECg0ntn
zNVh-11{L{}p=&nAaFO7z?7>nwVW{}cTak!hF7z5`!%0$*TTF&><EHl(q5?hJs8V+e
zc^0;{2qE>oBh&+QxKa0KV&k~F!~<fp0p|~p9XGpC3;33h8BW&onhtiK^PfETKHWha
zbw4C*sL*ZE2FdQJn_+nJAdR<&O!qTZN46lL+63m&LaZ|S7==6)_!T+ctgM8Kn)G#a
zGAp0J1yHxBdNuH^?>F_qnfh2*3H06xP!r%wW#W)UAawa%kxY&$=2^YZhKjq)dQu&D
zBtR*t=K2ez_8jHzob%maAR+edSicTA;sWSS%mN`!BioBbpFtd8{l&fNRkA`fLV%ld
zQ21fh<9v2``NvDyDfS^ABX7&i?^E&@3V*&>>p@biS5R5sFXC46GUf@ZR8Dx#pOgmA
zvvmy}^EhuciYsz*hD~LVI1dY`elEKUY+^Eg-5B-d(2jMxI=XxOsHQghQ?yrKv$U8A
zkNaci?EwiaWBxy>@7#+$qz@Ghs|Z}_m-K}tSi2UBOdHz9pT9eDP;;QtWK6sM;%Rbp
z(sZV%_u*IT0n9Fp5C7`bD^5yoyD{<*pgW!Ge!R?r0wsGdIcX!j+kEgcPUw9qCz$&6
z_j)#)pW*q^h94uQcgnv~9|E8q8_AoGXMI>rsUI9(W?B*)wsk$2AbNgoW~?<0>Oa4R
ziU}dF`Iv8dE{2i|fjvrn-my>V=_}Oe!hGPJLuJ#jogz!=1tkn5q{Qb7m;JkCOPR$c
zT;!l*zNA4)-Hx)1ZcD6_$3;S_rdcL2URs$8f6KU$lA&cyh7DT8VQtbD0Avi<)I_02
zt?p^*>(91n%P{5gCpxHz8{EsM2kh&TIG}yyPQ+J1k#?<nv`)eN+deZ-PM)8d+Tfa7
zje_FulBY<F5-H=eO!Pmb%2N#~EXIUIsMAaK!=kvp4G}aR+SUD49{V0Eyw2bIh}dLY
zt8T|hBvN8OD4Q=0B#+j~wWR2?NvQx)e!Wc5nv^0+!Mf&qm0CmM_FSX&)$vNU=ELup
zh27m<Hz#3YP|mphc|mk$CV`1N=9@N`B{XXsZ0zJVBzbFMZOTL4C4MuQp2IlyWRFyD
z9#7hv6+43$V*#`N)uk5(N}4};$bEayBwsJ@ue5p;DXWz@>Au_{G~RH&$9!3+P7w1_
zv=G0=EAj#{$Y30ae~5W2vJj1h=%s<K()G(f2+VmDyHd--GqGP*btV^i#33Z?O_Wkt
z%Q<RcVIrd?>C?PdZ%-e1XO`1ccPd@&`pzY!NP!g7eIhE{hH7H9W74)*?NC-Ww?pIw
zp#vQ~eGenzo+Ih5`%qgp<+s^=xK{{AuxLF0wRJB8OQdYo9@VO(W_lDXa)VDE^s$SL
z)-fjxOZ84vTu5vLp6>2phe<y+eQ{3w-O}4=B7U9ZS0ahB13P3LOWr}cw9ucMnG=rt
zQfQhsRa08^{$=k({c&GQn5fS~eJlIg?qM*&Yf~;_jJ--ER~GNLP>W4HH@Aj<31pSI
zd$0zIJDzJ=p)jAs72zt_ctY+iIjU>D8y`b0efi9NYbg0>lQ`n)EIdB~8wv(mb)!Pi
z)WuevK_mP!vPB#xB5^{u_18bn?-Wa=uNDRQ>@f(2Lw>>5r<H&0uvlGGX)6?xOy4MN
zr2FB)lj((Aub~LufU;twi?gtlOK%TND*?uhq%Y`&6y9C9UUyuJm&`U&G-6BCBl<Fz
zu@pO@CK+5e<&km>L-7Emsy|X#4~hX!&iC8H_Lc5<HnT6VHo=04R2+ya6ae5N74iBN
z-k<N{dCv<MrP@E3qfRqx*Qcu<qZ>(u>^%^Pm!KoGp1M{La1ybG-)?GfP(p~5Y5m`K
zbcmcItl}Gf_F_ID4Xef-8nGJAk^^C(F*8xkFiJ~n>vu_7iv`_gq@f>sy3u(i>`@Iw
zf<r=12obu7uc@^<fR-Hgs0kbVI1$3*_=`Se`u=Yd3hFe|#+qV8ZIsTx*{968b|m?f
z@G`?_r7hUt>od^_*+RwPvR?D0QnN3cfV&g9Udt1G?ITtrA?6Gf#KOpX1V9mPGm@S|
zxFhn3s3kViF|t3(wd&Jh@(^@$Wyap*&?XuSXkIyoJyKNl3ie}93-8p$nd_xF`fCUr
zD}25zfKc&0S`?ZS*Xn{7Z1;wQYG(oP7wll58DA0I4{!zAS{^`g7rBrRPvK+eJ8sDu
zrT#{1se4GP+Pp2{i?49tgayzkM`Z#ap?$U8@!bO#hRv@`VQz43P0GnGFAVX3jI_9z
zO3>DD>P`?CX~r=A<#MECpoS?(MM=XsLRDe^NlrG<@|WMfQ#id9A_$Hcf`W`3o`8?_
zi(5dT%VQIbye29&6&bNYH6MA5#eiCs83CQPq})ipQCJlmOLW*Kvr$({lJzV{pg;zH
zqK3-x#X{ENFXC2{#jmX@&C)W}p|{o8Y+sN|DW2s%_yG_Wtkwu6=2k^v-#)bbnF7ci
z34$q9Yl2PK;b%8{r$4zZDJbty;^3s_=Fa05{ElZN@4~)|GFJPXmWB(HvoNcP6Y*<l
zZT<S?3*D6V=#dwyvK5dL$QAd|fYflbwY6b8klR`^0heyICOJvXrz0=Zr4s2*$~o!Q
zKw3d%yVUFcz?I@BOfuoB%_)RrX*|2ccx7=pndP<2H?<{n*(1(#N9UxQr?mf&z#%lC
z-xximSR;yS6W*{RP6h_#F=m`Ce)Tf=I@4CDx_+fUOc5^In<B)kly-Zw-&9wNtmx}^
z6g-+w0TZ3ml7I6ol%6NY2Y_ht1QUk3yH|lGhucMfi;Ihs(qK~=B9M!el~Fg462r|)
zgRndilff#TU4EzVwP5cL`3JfPPK$`oiV^UBFecz0X^TI6K-+IZ#-_lCaqL!01*mvF
zehR{bAV8s__Hv;08<<xF-mQ$Hc4Tj*OM*=RzDvQ<(y}?B8>5`?d89Un1}kE?Tq)4l
zUj){Pc2{#)=wg3A;@D$4$#mm;RcRp0s#uFrepa@igKt;|QV{?Tu(rTuaBQrl6&|(=
zewM<*F(R48p&cg$W03NK?`fV9KOKjw-!bPzCP=j!6ZxNWHU20{^g(b72VykV3pA$|
zfEb5-hq>0vD;WPJXuAHJlXgZnKunwXAyOdk&!@heso^7Kww!=nhaw`rD%0!JWAn_0
zkO5;*ij!X^bbpi<Y;w3fm@g?QnQ~acCCJK&ePZWGW=x^|iBpM|iH_)zxV&<yk&+XW
zffM|F5w_@KcTZI3RrwVBN~FfTPk2|oM9y=z_KdaBY1ALi+(wzauM`qj(i{0aiVZlC
zLhN?^TSB3TZ}iz?ZC%~d%{JxGFkdJOpobxik%+vTjPpoK@ucJgN{CJ)w1wq&FtlYP
zZ2y??w~#<S0E_<Revs3=y-6^BRT+KQBHHgzmG?K=zV=PusG78F>_mGJoo2P*Tfj$J
zToDr!6T5>|fKX0Hho~kU);yT+=cA1Y`}2ncEX3%(<wF3ja!Rh!RKRR{^#=c6d5nTA
zA<&gWf8$G%ovZG`k--Zp?<4-Py;-~~=<7?9p_WO?+EBD6p|#YZTvz}2;UGD#q*1Rx
zP2IrLRiB+!`TCJ@i@tYTD&+5FDhU6g9hq!5Y?xP{PZ#n3@T+3+wi~SMz?o%d5aZC*
zD71IvR?Nno(uq7_Dys&s|9!TP0is1Rc+{$As1w+@m;wkogFFVhzvJT+Mh^i&zs)y(
z2lscuJ@8o)*3dDYHkgkelJ8|mN;%rht*tsC!9&MtTF5&1U5(b-oI|c3IIK~7?tZUH
z9l7MsyuSRJcZvKRQI@0<zE3ORJGaK(a=A55b@=<*Zdx}FonO15JXa-sayvI)ow}Vd
zd+I!Fp!gV_S;W3SMw}-fPo{?dM*gXfv0^8p_N<|l?YMBQa7|_l_>6oY|NrD~!B-^r
z`tFRHYzIF@Snblvci4VyUqmiJ15`Tf3gecdCMNWaMaATkMXxh7%9$+YZMNbINfh90
zU*uVeTRY2~kt;-~exEfa(tZwGNzx!WYM@&gX)Jetf3H_(G%d*Boe{1HPG*Fh+}QSp
zjO(&gdv|^vo1U|H@{CkEdO>En=C)PXgoY`GwNiGm@ut1w{)lPCA5M8%7<~IWa{2h3
z(4t?MlkoeH&-;9bgQ*=yU$?iH4I38Ll=L<=TkF%`WEs&Do|u^lc@dPH$8P9T5TPHT
z2xH~hpfB$1#GS#T>z;L)QOn?)SUTCf>e$r?J=;Bx&Ph>M6tGTRv$!B_hVnW>_s$B@
z#T5em$LQ;mx*mL(c`R6<A%kCKZ0GX}dw;F}I1ZnEec#7unSgV<Z?z{cGbi9|thSXJ
z6yhf)WSO8bbH{zYr<Sw9_lGQab1I<2Ik-`OmW15Eoh_Zp*|Dm`LwkPhdDVdAB=O;3
z^h9#hXWKtxe$QIU)eOkuy9H)4xl6B`j?;3yY;~M9@-tO-e@s4lBwJ=2?D*&-trUYr
zRhlG)Rcas3c8mnKVWMv4eS;%Y+j^sTA-~;qq-vTtH`e$)A!yd0Z4~|G)U`v|@3lFk
zw~^9jQXjR5gl=5ytKdsluC-B@P32-JKb=;(D83)s^9-m-Uh<&Co;2!GJDs+2UVOpj
zAHksMwooyyja7R6MoRkC7yF=F>I^-znCVmjW6C>j4uQk1Lsp?raqg%@5O~(`_+>F^
z`@wU~jN%f#{FNV2uc#(E3Q{NQ^B422HB}!#)H<6#c-FTvR~u5o?R6@se*RRDv+u6K
zMU*aJKz<F)15>d-2Y@$7a3@uL6gU7K+SS$dq_N(-tBB=U-Yo{3vX?o@oS8$MOb&I1
zab8<@ct{+#<gZ7WPy_ln3ug1%l|p;iEeOhEmHbjK;#6wuAw9)?|CassE4R1`hHT$t
zW?ALHUrqsAu?Ljl`tgy&0X(9z?w=UAtSRa~C!23{((e8+K;@kWG=hBJHD-~e%qDG{
zlqqK9i@GzNe^5F{_OAPzx6(sQb2%iRkSc@8BHd%!wy${9^mHeCb18*T2~n8l<IUxc
zEK8B6N8-@JNvr4f1_wzKEkyjx+$W0USHxn5y8qw88{0~jNe_-1Vq~m{+0U{~!u;^c
zS!`i&gRWf<TSrG&);M-{+b@mVB;Nq+-y|gDH`FT4jS}%e^T$TsnwjMDeW=4jLAX&I
zW_V&uiGdjWFw!c_1NJNOocnRpIrItq$X@|1?}vtH%O;bl4;prZl2T4g8lDw7F5F}k
zq(gY2BECrOYV*7LIGrMmmfO`Bp4o?s%@z_B9a{(d2%fQsxg;Uq-v3mneoAQs+jg#&
z9Ha7RqzxZA2eZ@7RDSSFI@YSX;7(qVOEW_ENPi^zLH2Q8=MIj$fujt0{2J$3QVQpp
ziTla<H^0RLK)h5h5(Pvl`|~+dbt}`tiDtLhz~emmTv&xXURVe}KWTAb7W>S%ILFLJ
zzc5=C`SQB6l=W&?DqDLeiJ~xALuY93@=^$GMv9)ZmYSi7>GwI;Q2;saC&5$&h69z`
z&6vpJLa=PIT0c!)MP2D(g%fELvFY6B-q*@IKc)^)d|hi>^VW*O2q_y#RZ5xdY0qyD
zo4>pdUu>y6bGD>G4<p#0aGjy^>K<eLBeh&(GNzVY2u`B>cxtNyWzoOk^5Rw|qURyH
zSs4ntqPb|poE%!>(WZ*)!QZ4|UnUprKmGPhPzN?N$nfm!?3|^o?i+G*J!-amYY=?o
zfDAv;7IeSq8t9GPO<41fY3zR*Vg*#kA5-^?2(j{mDLVV!TnE#(O!V#<xBZ;z+3Dp^
z&y*iui!|>P$gPXnQZ-y7>++5^*^;$BhPfLr1v&+j#*7d5Nj<seXt?$HZqi4NDxhwz
z2E7#_bvqPr+Ax()ZI0?IRt{0w8$ma*bI02)5O@)bmi~d)p<h5ybS&mvO#JsG;}*vU
zSPxc6OgSFvhF#<GX-g9JBok=;KgfT4b3RvbR=)Y)c(!qoT7LYL{dpwauYe#OJZW#C
z`8|$f`qy@!STN5OuO$VeN6QZm3N!Fyb_ELH*>9=0p2Y+J^y}gQrapOm8b1J25!?8b
zsr)m}17Z8q<u(N9FV42Ebj2j1vL>^OHdyp*?FxmkW4>kaF>6e-ZAxP*-XJ*O3E_0R
z=2{;R-#^8Q&IY&N!!|n}Tc%}sd)g4%qFMP#Ddxe;8T7Aq)Yl6snH{jq!^b<l+pst5
z&Az&|`b7<C@mMR!fB$pRDxnfEdHoI1P~Y(=anycQUZ6RuD|3#G^%mT=M@GLn*1P;^
z1)K0RcPmA$)K^a{RFy)n-yRD}^h3A9I@@*Y6v=$YIl|hKgpgndVN|I|3mH<qt0sIg
z1^d&-2zOhN@4=&DsYxR&RjL=)xAO05D2IfK?IjR#i2EGmRDqBq8iVe90s{ko$*_F<
z@8moz;ty%FIW!I`RDRg$R--t@K9&4pHD$Pek6j)+urnh&H>;l-_mq{{F^Tzu@Knj7
z724Xp>9NN7N>H*{Ih%dlv4IV0X7*_QbekRNT|a;>@%(Zo4vVH~0D#JPjA~O%(~-b#
zN)1<R0uc0|*3sByuo7j04<I7oD&zeeds;Hf%V}lMen$uN1cLB3&;UR;eArTlZ(k?^
zLleLkK=rMY2zk7psWW!_RieWblL^$#0c<>>kO|ha?^D6M*|<t@Cz9|W$A2{YN=kl!
z`6q0s9323q>wjKAaEbty1^`tD1DkJ~s>X&7|GpYOL%Q({C#ES3$ew-a1uY~y!{g*T
ziNi+=>UNmao+aJ{6^xVXpA5vF4qm%bh3(;d*MY)c&W+Z;#gEHOF)kchcj4fj@QtC&
z<+U5uzh{ag2H#rp-aCm0zwBjZyz(C{>_}@K==?8@if7SZ4NPDnA9}(l0UQ1ElJ<C(
z%phk~d8S}ITW<PUy^fUp8V<O*=TGS5K^>FygJ{~%DrwG%Ai==CF>@Dd`aMEdA!{S^
zq+x{FC>{Tsdg-xfbjtFVy?MenA}{~;ev@;ER#hmq=!<%O7;TcE1NoDol*Z^M7xXpr
zR1)v~BCYH(Wup11;*P&hhf5(Ucy`1nCqzO<N_<o#yX2hP0|jWW9%D;Mf2}c~hpV*@
zKsGQwYR={`lX}DO>D{GrUPr$kc!@5IX+6p{m@=i(PHamyj7tzg#sA)VLbv~u8l*wY
z%k{T|0`q)p#MRNl@q=cd@A1;vmv>jN!49Xj80)*skW;N;-sDZKoQLYput(%gOef4>
z#t7VXffxLdAVe8R@kQzQbsISBiS^Ikk7Mj9o4qr<vfQ%{qz>d^!&MJabR2NhD@Z5^
zk!qDW6nC9D+#f6nf`>quLUCyzXg{bxaA3)9Z4iCGHsaYor%`Eu=w+zz^Q3^YLPIM-
zO0kvTE$ZjfB#VIqNhaP1;Kx94>Tqv3{=F!46zO2rc;N*(kz8!VHtJgMj{n>37X`ON
zb4+2CUwjhE?fg{Ul!cQ-)zuyPU{embe=KmA;SE{t@%+_D8m8F%Gj|<)ZZi-o`8@vP
zyY3~{4Q+k@-%*_xjy@Uf1P@u>x)nCgqYo{fn~}ja(e_e<%e$XNUGMlQcsJEZ*PN3E
zxi5u8@FY=BiIGR4Ab4&f4Mr1Ty)~+W`2EFpnhuuMlYLv%w-iNgdu!o=72|1!Xjzqm
zI3xQk=H>d-Yl}AzND01Arh29sqG?`dbhqx*7k%?wTS6icO}riheTcxVTf`#apO#vi
zQp*j<rtakA_$3XzX#9F(a*<s5LqJ3)wbV>OH8=Z@QShvlu!;VP4Si~<)}&d{L&0EF
z{Gt8D>B^yd{eDG2E%Bn6j05k{!%Cbk-uvJ^!yinuEAPsMvX%JkSV9MPBLaynTmh?l
zAzlXtc{CQ*k@NUoEU+}Qq)i>O8Gez}5BQXj(smzbm>@9i#hO_cqs%?Aoo%+`2h(Jt
zeqp=6%`wc}d4~8>?lt2rBnGm(omc~Di$Qu1Jj-?PTu3!D^#;bQin5hGe6)Vkz+P9i
z)AZo!Mda%_;|vL7Y5vYESg`S3(r>z<`N+9?%DKkFIu<RDlayfGeYACGn$#E*^~cm+
zbVMr1Dtx^Ez=EE#^2X`AuC5s^bKeiqDJl!L<pDI*-$uN@Ewni2dQL3Qr&g7`>)q3O
zOT~zGrUprCamiM=h+trhC~&7`?GAAn7XudGON)<>OzgG}3x5}rlX>L_C$}-r@l`2N
zlG#7&_*;yS<+joK4=n!K<*2K6sc<s!?XIwK9EvKW)N7qv3bc4)c_`3?&QTJ?g5kgo
zL@;m8ZIB`CW?_0EebfKu)BKn+L}cyv7{O7Ms=?=`UL7Y9^EONJ`LiJsGSg|Pw6@x6
zCXNxBAIg}SdY3oCw8K<(84!0YOqnPU;vAaWuzTbp>?Z%)%<_Z*Ohw(*=2s2mtyfoj
zrOo`zF}snAp|P=XJ~;P2=dQWyS6Oz-uistV07hwl_{ZyJdMrCpl0S*Kz1Q86f`Iqn
zhcOkpJ5LNvOl90yYv~sjzBZ_%=Nqi|a!gY{oG`y`5)`uib$z}V|LImc-|XNnR`6Bc
z$Acesj)_R}zwKo$xtVn$s|r@C7`eZHswcpEffxq(VYdPm)ZDBlgqSrr`l!r5?C?m8
zUDOJe7Hr|GnChf!72s3pk7}y+G)Y<R^CXwvNyb7*Dsjv!zBn@elwUQnKlMN+cPmsH
ziSd9F1_oB145FZH#;kcD-?#^JnV5zP!b`h+9v7R&3pw8BxB*8Oii;~55%=*qhFGwM
z;`Yvv{d$feh$$c?1rR2~XL!I{LhC?EU}IOA=Rg6Gguj;2`{$c5Ng_W0L!Wz=tt?)X
zVj<6A=2Da;y5wY)v{f@PdUO7%;vB|h=1B;H{8s>4M;}!!w7uzbe5f(L*SWPVo_4hR
zajpe@HKyS5np>G?TT#2B>__fWJ*zky;Qnyvsz9J}M`B<|da?-Ygb7`f2EFc`{Dx#4
zw4}s-c*-WjP8%iq9Lp5cfFS1~9Ul2S_wTa6!T;}@<jGBLt?zj7J@k?iU3Z7nll7H9
zk@efZ9Uaz5xZY*JE5)jt*kizfIdKgdJ!GY&BQ`6})WKF(%od!)kulP!I4)6HKwJ|E
zD=6?j2&Yc#g7+g_uP1N&$2RBiOw>{#V9-CIwhK6T9JUmBwzCumVCVA~p!W{U?;5c4
ze_R5XbDR<$6dLLWe?CH~tE;P5qx%IPVwfVSudlD5@JylFVJ)O^#)HP3{K8oN=SeZR
z0Zih70lD-c8(&qROY4Q&yaWDI6Dn6a^!<BmY^+AjG)pE68{4R%rUvwlw@e@q@-z^4
zhGMcXjl@3#499=~ax9d>7a3yKjMCJS=*WZaYinyQ!AzM-w?$@eSLJ3jG_2nN>xT+%
zTPSv8=O(tO$ggNnH<pSomGoB+8YX5r5vAAn9luY_lBhTiybwa*7A4gck9bm{CB@qe
zz7O3&I71XfUSD=(<m1)OlSI@Pzo#AeQFDP2J3~7x#`Ul8uU}+^U^|?;5e54aNTH@a
zrMyRhq<jL^QF0$kxs^Zd;70n8(bK^OD82%|OT`%r{{(uNlA^OJewYCMT>_*it0wai
IY7zdw01+G|`~Uy|

diff --git a/docs/img/cluster-overview.pptx b/docs/img/cluster-overview.pptx
index af3c462cd904d459a433ee6a8b97daab63e547b8..1b90d7ec5a7ae022db7f11402cd93f11c863b60c 100644
GIT binary patch
literal 28133
zcmeF3bx>eSlCPn0cZbH^-D#k4cN%whcXxMaym5DThsNFA-Q6F3XEyfUdE0MxWB!}B
zL~x=`5r>GZI{8&*)~}9?I1n&00000u062JvP|q#3>GsE+%qIW<C;(&tEn5R~J6f7w
zS3m&xk3anNr!00{42Tap=$xl7+RdpRMId)tQ{X^S-@}_O?$wWz5g#ef!!5}7fS=s=
zbKJ|-B}nxu?zTCP$WVNopTo3o){foxsf~>~H`P@?@=)@PG$eL5S)W(SXMRRg4f5^Y
zJ_R8PSRqBv%KC>Gf<zL=JdVQ}ff>~yZH!keSbbItH=|urphO8faM&IAIqhbo>GcJc
zSY2Mh<C=-kJj*btTg2%s=v-L-yYV`Wv5@@OE=|;>7frJJ*PTQ9=X()RT9-*#auCS*
zgy_eV$x|;(YNU0B5mS}InLYMbVturz%9cl9nZJzB6QF2A-^UnG0s;Uae2kC2m7a{P
zm9-tMo|UZujkAUMe>F-LQNyM^ywHO8uaG%y)SNzY5@{#RV)zrN%{WZOj5F8TxpRl>
zPP(BrgK{f&aLO$`ebTdVMmF@&6U@{K*kr0`{eWxh8ONlB0+N-6p*~;_20lHW!bJt&
zALI45N+a_qGVr+b0LO}pgpoOFSf`K);x8Btt!mR;di4*6!^2bSJp{&0OJ)6(b<&jx
zUnr@|hHlae1hpYtbjSHXTJn3aO48a^sHq0UG<(ZtxW-3YH5#i6d!mxIj~Ut>H=j7^
zH{Lek{yGkv=n(D+ALFq9@eBXwanP~0{@pO7kF`N|(;)|Lu9kosS;^xFh)vUMoye?y
zwS58_75y2K*XBm(i?;D_+1)d5pQ_dy8e=348EF9WY0#N-x^QE1JroLDDy3ADE6W!L
zqq)9G7?&;|Lq*^FTUWeXVV*u?*0lPbL=!X*NBUKG&P@*;R;%l^t%ztw@e!4cxCp8R
zf+wDPpR441_FU@t7tcGlpBd(GR(~}s*~U2~^J8iwzyUstLI$w5wx_kWHLx?VwAZmW
zv9kP~X`_i6R=yvmo!?WYtkJ0Qwi9Ku4p$Q|S4-RjHQUO>%896@KO8Gx<d}|Z5j)+q
z?t47n!~>JmSPV{r=2B3^=sF!}1N$nf;3ty5X>!5ohR5d<<g_A2Z-F9bNRm3piOb+I
z&GrXN1j|53UWy%a;0sit#4Es*VERv9i6tte=BdX@Olcu$+HSE+iHNC!yI%~uy(ng&
zL1$3Z(~RCd!$Y)g%amj*4b(nm)LzT0<JAc(aJdzT`MHm-#kUv#AP}$Ge~Q74;$N2#
zC9&uu10<P-Xfi-c0KL^34HO89RzpQ{e{3~^=w=LF;7_|Ba|*VQ=W_H|w;9o>A?ee>
z?mhKQvxe0W&N}8$Z7zqlZQgSQRO6n92|DyAaqn4uk|)TaJ{WgT()|)V!fQjBvNd0D
zvNTc(G9_t2@ZBZrvpD@mb3`7*1SQ~sruLDTwkd64K9{_vw-qm1csAU(udIMA%<TA|
zjoaR)T@xK=yq03}Zl9%()s}v|*ZSnaJWFG#E)~Al#^gnOG}V@D-c1H@sGDvF@shqE
zOb31W>m+}#=-$NrnB-ev007*-Px9Y5_m5Nkd+x<giuL@OZ;#Muw^YX?>}qpxf)jrD
zGC26@X_oIK_=EW#ZjA9MkqE6ncOPxXGNX`wx;`_D*aIB<D<LZjh9HoYV`XuKt{)8y
zqX>;L&e9d3$Z+}gERQ~c5MAr^-gdJgGsNdK-mk47Y&pXL*#)rt=oT$G?Q|!z5Qg5y
zEd{D38z!!@0nISV*7#br%8Vj(YrOGgvDpG72yFBoh|FsbQkSaHsHDfB(6Amz`qDo%
zI&jb>L{KWk&wCsx1R{^9+*Zt*8$0UkzI~pBA^AFf%s~oge2uvENtS;Hu`B+kq!a?F
zAdvKkOQjb9LYjjDd6~i7tG`Mxiyf7h_S7azf#1~Ul|xekwqp^~vg(e7LABQ@QQr~I
zlF>fazm7NXuwro42PXvn&dmRCsz1Q_JCBNpYJu&hgBEmZ&%S~shXz;lpbAa~<iRst
zWs%brwsC&t-XsQ;7andF-j5%hT|5crgO&#w7KFu+8&1#4^4->9UFRi{l`o)1QnLQ)
zlTYKZ2?QxOLl1M0FOD9|uT0l}0F{@EGijnyDJ<5J;Wtg6t|Ox{k>u~BRCeWFmc{~n
z?(w~PznzuZvWdHi=)xDcRvHN-A_;C(I?Kc9g^ZiPU`IT(W+WuRuUPz6OLP3}uQn$j
z#hsOX*i8B-n;lIIoc`Z7NB^hIQu65V#ZTzGBhVLsvd8r?n4F<sp}eG>Va#zVO6}Yo
z!k#P#^!aH6i~J>1_<U!q%?fEZUD?a-qeUiWj$$ChoqzCZpwMJOj~QhOq!G;%L*qB9
zlbe9ns>(TvT+UTBaP%Iy&AM_6m*LE^3_A{)e!bXzMa*a!V{+cvGmPmL-m;m&S4!$)
zdt6*WOuZ(Pz0QB99PGUIIXw>P73EbdA^oep^T0Jp1t0ceeb|focc0R;vat97C!d48
zv6ZdeZzp<e_+wRo57=yzMyPHmqWM@A2!bh-o&fOES$y;n8H$n`Se;cGk8RQ4qNeZQ
z&KF=17rkSxic=VQaX`c3cIJmo+V;b%yZM^D@g9+a?=`TnPT}lW@YBg_bn%$QY~$?A
z{qZb1DU11msXFM1Ds0)Oi2`%a`tGF6k6lSytABQQs7?jh)M7^Rjen-|iUyY2t<DUO
zxS8HUq$c^%-Fn<1nyuCb@K<v|%kaqQK>+}GDFFcR|8B0Gxrx4kq>i1vfvp|wpKj=X
zXZfkBh1D_({9C&gzHw(ebU9I|YZY2SWn2^Ggd<=2D}ZXYMb^x)$dZHVO~*M|Nc|3(
z-I9H}MK3PVl`|K&Q!D4^WcAjS+>vkcG_hP*DPvH}Ovb3YHnG%!ds+=~n#P#?u~Z~f
z;|CM1Io<9qF0#<TVe5$a<gC2>B%u1nG<j5@iNx8&k|EA9XiR=pE@ScpS;J^bBZI=x
zX$(+{^;UUAgCnjyUL!B=JkkWN>B1%PhSiAO<b;S5VFq&G)Md`$wZ8Izx<iZ9B4QoJ
zL%O#a)W!QS9j$mkF*QUPMBxcI?cX)%ElVM=QsS<RRFlw@!bYd!sHw$~8`9)vhvq7r
z>8WSP+%Hz20<lD)OSCaDM7tKmRM}-}RAzIlbxtL<4oEP}_qY_TDif<PQYv$uj!eig
zS49YmgC`>~sozgFA`&~Ctks@?l(uukN+4G}9HNzsnu$P|CzMJO#f~(nU|f^|3M7bf
z^5?4S*QDwXl#ty3OLdC)a2I{%=hy@a&zI{+B8`GzuhgER`MLt!1+QmhBC-Zeh$IC`
zk6HPZN>c=5R1DpLWyt`FiZe+lu)oEALRNb<y`(C!@kWj??u*NMe1wFL`c$!gEu1mk
z6Nz&tM2K};PD<#ezdfjk8`a@`63^y*5fhi~eb5x}xb4oUqc7W(k<+GGwQBdm6yi*C
z)#Q$_Yl6eKu_sH3j#F^;0!io2+adllk;R2RI@RX$IytrBMIee{1*2@rnvVp2D$d%;
zND5A@;4t<lp4e6<bx=Nb)j{_R5xoo}TTBE{%?$-1rf)3N+4oGEg4H8(OXVoOw#5Ev
zL!3gxAhbh4zV(KoDh_%aUU0~l5V?WN0Y$5Yt}{L8%XQDg!<2~vxX{U1OrZJ>&6FNU
zwgm1{gN0OmlrDKiwINhE$Z$b{%djx_2w7S2EIL<0WzR?iy*}S~>tAW<xA18f7LVA4
zJdMM#)xI?z$b2hAq0Hg0?fyg+-^c17ckdQU1yd9-?DDCcJmQLq1zkh_4jK9Y0^KqR
z;vE)#g_QUE4kb;J^niD!FMhHU|3e~C$g(Kn7Xnd!n<vYJ6ynkjWq&`vId&uuhp`*(
z@mbO7fqGp3#&o8b?dIj&5chDdmu=fUuQui|euE#P1h_-g25zI+yDa|HcyO0)o_?l+
zpUX3PuADktK^J8*jCQNXM1jRQw;*(GKSf)*5;Y%g(VSvdGA#@hCeSFhWNmvsQ4x=+
zs5c+%Pjp~z)3=|2C=)i!H_)F2_<T7F$l|=aAiD9}cnWK}9V5!ecqq8F=Ka=U=Uc}a
zE)d>996+ze_BBp)VR{Et^%Bf@6jfw0IvZcm4>g2<Z5=>(bpkn;T<x>6yt-spiZ65D
zG_th3yX2*$-eBwrka_8mLAPVyTOoL}q98T!9+quV#m;f#3bR`LQSHVCKu~$q^F}_9
z;AVxMy_I9wd<|CX8K7oCR~XzyHfV*D_q@f$6PUA&A1hnuF|%_IP^+h3gO@j}@dd{n
z;9lk63AVOnd0GzA*=s^lnm&PST^K&(hLj0(Bud5bRd%_hqIx_&*-$-28}3gI3LOmi
zfd+k+*V;1sdj?sRmG=sjJo9WM-w4ObRV3fjGwtn<wo_%>NBdO!nG|?=y$e<f+_BOR
zCj<V(8mz^Ozw%koL(ce&M^FV~eK}OFd%cqnJg1!ljtC>(MdtjTDN9~bRzQ!VLXA~U
z0mP=V?8<4oX7*-UlIR#J;#8CuM&e4sv4mYsgBpUBz!`c}%X1A6D{H+tE6_*7o(oIQ
zpcl{HuhRq*fp2sRI}8EmzA?P9LsD7DK6+Z%Lb=xF;UqMw4AYbn)DnR7B_E{=<u#{j
ztLkyf6G2`DK^?(O*sSmJq0ziiOLmsUf7{HuH^bTdvQ=wi_PItc=+%hQ)2>ZLZSvYf
zIQ>>lNx|QUk|+PAtTfnSr+HlI<;k>F)(g!~orc`&g5zo9a?1zG^mc%+xh*>pYoGpp
zx+7mDY7myN5KxSx^am)xB{xmnnB43cRAG%m-SgBDmEvjp0f)F^3+=!k-F3gZ5zl^g
zH*$(AHtY)4WLKtm1yp0cKe;|m|3esy@Ibi<@v+?Yg8=|g{a0(y-(uQ-T#0@g)Ar4_
znfB1ZgI%;q<6Bk`bB1jDlc{`UsYSVPcsti%b;N|^d7jUZpNIqTIFKz74sxH5Sr1_g
z&TX`{4&1FG{JD@iCydqZ^Aj#?Ts+FXAAd-cftty5hkuqD=;4H==tW(>jWeR}afZ+U
zpU$wW;KWWCKk+BYV491d=q)pQ%)KcvjX~p&Us*NkWQa>QgE&*)@1(i*_ZqC1oHlc>
zdg922fXmpxzte?QDDT6=AGS<bPBEf~d(acQ%!K}O!`xo9sM+($PFYJ`Y)C1-nt)hM
zen^RYF;K2vYEVpUk%V|zZfGdJG&|lxz8WX5RBX_ePjs2sg#A#9GL~hD{elzxLHFfz
zrsqE_^>hb#9B&{10B?%_nG)I?8(0|7{&D^N>aMQ#vAQFBu2;a{aMU(`yCN=B>m3Y-
z72zZttTa;1H)lr9i?L7HnLm$?b*S2z5sfQ5h=f^ab>Cs<dT}QE%;9psNn<cajlwYa
zFmt!oTrcPnUxwJ8vE-#Wz8-ENPSLIGZ;&Q+>PB%2cfKBjRF_3w_k%f!RNvGpen=Wy
zSV%@<XPK%1`)ErdSAb8cG(7=ND{DTUz5N(AJ)UTVW;sl6$;c*6;D#%#o_x3XKtM(a
z*_eh^l*S?~4q1V#fPRs|Kw0&zztEDvfv>k$QD5QQSD7{AEmpUUORu|`*xa;b&w%rM
zogKxyh{n=VleiqX)ba)P%szKr(aUpE3k?nSrsZfHKm@squDROpaUnH5X#uoQ#PONO
z?klVDHr6W~$HSmG3lu5!%a49AoR<Y0&;m~=+?j{UlJ}FF6Z3`cAZE{nx?5ug=p|>M
zrAq(xn=x%>Miip4g#pb6_ciZ%vI4&JY;I++koZ{I<nKV;BQ$jJYDYX^yuh7N@vCwP
z0s_N$r19A0VLMqIM$#fF7lcHrnTLryB=vv?Ng9A@i4p}S@Ol|Hl@43}Rg@0n2LVh+
zL*c|F?8qtMCW@m%?LPYC6#;5cx>JciXS70=)Gb6{ZMg__sE5nvr-m3Iuq)y2ELsJ+
z6`M{ROK>IxJcg76FMk|@6kAGIQm6WYHv8!XzzD6Aj!=3Fi(Pknnr!Awr3EtU5PuUm
zhgzGU6;NX!2rsW)4TE)@z6zD!X^LQ9ibgplw+tV@CcSXAF$<KI+cF40aST7PS4P@C
zO}j<Gc0LHIM~QJa9oWFeOWvEv+%a1wFo(hN$_)kdbfZ3taGn~c7>9vXX(J{;lS@Zx
zB3Df=Ud<RVdwr#waCA-vWE-E=rMr9kN}cvvlxHJB=<p+Vj9+6?)arEDFP&#J@%Rz$
z<i^j4dP!C00(k(z-y>3w;gJU=(nb@;#`8V+m5yspa#z5D>J>0oTA<gsu1?D+iSAix
zmynvdZaq9Kw-7Sv$8{q;+v;pbonQFs{JIlX|7UEv`s4P<s-DkkK~bqohcvPUm+(fm
z={XAZFQ2N1Njc>S?0%wz1RRuK`R(VSo_G&?wYJP59H3V~0_8WvGq=5DC@)9oB$u6`
z@ypA|kHoq#N&gs!BAE3B&ps@Kn>d1d2vz}YHZmBhXGwNGpqzJRyXG&m@IY}5zdENz
zn5kblS9goI-s$R6V`j`wR$*auPt7nGA^WtHtly*z(I<f#>o1H~v5;MAK@)o`q-aL+
zWwqEmBc6~}$b64~PRdJg8)N~Wc&pnUJVZQB<N=aQ7M#8XuZ9{xD{gnzZ*r1WksjVd
zijA4>6N66YQ>AT}(N;gSHqbZ^gcfZ*SMiLW2W=E2caGqU3$*=G@M5IzB>&(Qcq5@u
z%^j0c)W*=#E-IO$hcdjO+pP@oZBxOJ`xqOus9++9S9lXmm%2FP0dWlS=aa%gbSXRI
zPx;HT#ScmZO<B!nL%Bb8vaI9i^jb(*mzhLsXa&W~w+X3Se&Cv^9ZF}IJh2XXI3Ly$
zU{imy<BN_fqoE0E_3D0M-nH7WpXXLNf?RS+nMH}AYTNR7DyuQn8P%|rt-elld1NGG
zzw`wlf0UQ4mW+u-Cl+?!0k_SKBJ>=M0kj2XpBjka8;t>A_r*Tk7Ll<d5{SeTequwM
z!^R*GjwbZL#`tLA|E)EPjY0Ug);xAH-XE>xofdn-UP>p3ep(ZA;*yrB&OU=4PZj)9
zKVU{>gMNU#jM-Oh2g%NdH4i=m;8xIyOOJ2Cexlcy+SM(fWM+w@DWn=eg=543<2S^-
zFBC}t2eO{FQNDaGx!|C?F@)&x!jalCpV>b;cK+Id-SvaZc1IX?NV&?{;lAug>wZ)-
z-y<l6Br*!B_|%oOp8E6qJ)>K|mulgC?~jX^E*CDl@1=YAKA|vOMih3JGmkCs_Tx{4
zf9R+{7^m%dkh*`rIeAMOf7W^f{A;>6PAru6_)$?$`6w&?C0&%zaj|l+|9iUlx0~NC
zC~Zp1wo7#I9_Px&H&XhY3$RGB5V<?V4dgdK{?wHP)um$H^oKX=EwL6f<e~=>YM)PL
zP4A7z&s2x|6cg+e81icP!>#W}dV)h5MHs3uH!H49NV`R_C=iFBx`dp2nA)3LqrZ;E
zaW<3BfdcwYeC6maqPG<Zj+9T7_fQfc(Y8`4OvC(Ej3SEc0lJeGm$45*RFK>m(ZSKz
z@r|bD`zrD!hf((oUZ{;Jo@=_HT!ZlyGE>oaQ1pEd^w>p_4O5DZ4Ak*^1+08S@5NPR
zuDp4I;j*bc!i-B`h!nqdF2=MhjB&)h`r0(g{!*eLHDaSHQTC{yE72?}o60&;l2IW&
zAyZP)XyvmKrQ9CVBHQP{n;)kBS%Fy3L`nk`ep{*-=e0IZ&b=&BUvR5PP674LWrmAk
z&zv~;#ElZ=24yM@9C!!Y4VLnk@}V23PDvIA<_1DQC-JUKL05m?`&nE6WQXp_IA>OO
z%~;2|0R;;`kfE@!REZ&^46oF!>Qa&(=Cm-Kp6l()O%0Y{riqQHQ}0}!%>G(FI%3Xd
z2X**48d1|WRkTH7;R?$5CJbi5tY$g71b4Ll+)Yw;WY^#5l2sqFH+JMl^JDZdx_gRs
zS|1&(=&Uo%6bt`U;?b#ZKoAI&G}(89h_0sU)#n0-<GUWq3FLBILB4Uf*;2sDsQLg-
zxck^!X{i03SSO1`+v2m8py&`_O9)cAc3(9HmLZ(FZ{wPKC`ElH_#=*&08Ye<C@W&k
z-p|@8HfN}&b>FQ6#30KMnzX)JjfbDC46>A}u0h?$v$(yxkH7M8ynl<kbHnxR_$oCU
zY<1J1N&99PCLBclIelV_Zu9dTyQ4%$MUih|O60l6%H{jHrp*vBG_LryFtSAd+d{{o
zf84R>{>t^M6f)?x6!Pr=kQXM1j`KB=6-IY3VrNWix<YlTR&ItZjg9)M{Np!{@}`o7
z-Xfy#dk%It5`f~uiDaBw5%FL~BM5g%(L=G07XErK3YsskpZ@Ag>->!eH6N8GmXFZ)
zFJbS0_|l)k-amQNZ^Pb*@n5?VA7Srm0eC}dEiA!QZ5TK#O*Wi0(LBon2|k+O`dT<D
zHum}P{eH?Bv-Fl|h{gq`sfrJtm9K;6gmug3c~1DWNwqXzQWz`UgQY!wq&?g2oG_};
zO_iSSb}N*9hPfCjfg<e^Ptk@Wc@lo1#%FBNOA50}c~(G)`D`jMhx%sl^G>;5ClmK$
z6Zqc;BzWF~Ww_YIjdmo8D!+pcVdlP^(I%Rz5b)MTsJ1Sb^Za!{d`3RErhmX?_rC!b
zhTqkqW|g{r!KLk<lBpR9!@A3WpTUQzi3kSi0IaYc+l)fIm<W4X>b;F}QOY}uTHe)|
zw!U@A!}VOn?D3_V2Bi3VmHHt0S*9R5eR6U5Z~^&SWAh;~x{9!YP(ZACDC@}9aF`u;
z6+uf5R-Gd_d~W&#IZfI$62G}>W$Y4TUb26adU7m>Gm|tC;|)f%I3K7i69MrqV#Dp;
zch`h{E`xarjU<U?&|W$|oXQ4}`TDQZ13yf9s5<?RG{h`(_)1Fn+_EyxiyTI%0BbsM
zz9B2eCh;7+iX;(yjZKtk*pi|H&d6$tg;fHFP^y5|^CT)!%Sm$8;a?3h)qx-X<SZX0
z$~l=IlTQZyQ}a=tH8+lfHLt@@v@k>0IS$K<n5W+~Xo}=}yU_I3Ca<Mx>z8QBW{{tA
z*_w)9&%DzLr)#JR4GVGG4wevh&zldZ?&mh83Nne759$+&BODqe5`MzvFI3LBNs!hy
z*OcQg=K%vR&$YPbS4WJ$0N?ZaO8Gm8Hy}`P9asZGWFu-ed5wH~14np95g?Y`7ZT5F
zs-3pMt|Ms<YuY$8+CkREa4KA6AUp62^xfqOgc8Z`f|B42%&oaY1HHe8KEu_ioR7$A
zy?Z|GxOHKBNFVp?0ZToN9G`$-P?PzJ`%xbjHVIOG2i6o%q<8=ZSE9Fp4C;cwRsv!5
z^69<+hGaFhP`BX-dO(Kd`XaI!)ofWg@8Cz+3=2C9cZ>+8t2H;%iE5E*eL>5t1HNY+
z>5{b`JL!%(zID9j?8$u67Pi%x6fRt&84GP>wVkTZ^jXVmfELoFpU9Z#OG85IXWv|Q
zIzOB475P^gkTL_~br*1x2YKU>MKM5`uX(#~BSK0*<FN+llckXBKJyhz!|#KAskncA
z-~Z<T_~Whr_XR*uJzg|1(8r!V#6OQN7=H(Vx{v50^>5LIvlB2n&}HvnuT(luu4um0
z7hcdsIu!l{{Q;?h_q7Dz_J}y=lteK2sk6z9)tcb262-oWSTV&p_YDxE_8_wHqt=~k
zpZiyn6;bY7rcHJo<^muq$pj|{7yPHtT_=4FTBc9H<xlz>D5_yR{S=hOf-@@AWI=T*
z)Rftqieol3gN%5}&_V6E+oAC*W-q(sZ@1=3hBx_Rs3^NjJ|aWGfd`7Rkh9q#@)Q2K
zklLm9o+7T)-X)rV_t~CrV)6O5pT2jU_3GJ-4i8DBxa%V&5=v2Aq)v?RX4A&+C@d)w
zXAtEX_9ivRN%ZE_O5G0&hYYO{a2mm}LPcOWN;!JNt?Zvh-zYPxB$Micmw|qcx3M@|
z7@15EN=_ZAuTi<Q?q#9m!L8~)1$8!(?->Gd@|T*qN=6ot0Y0a$;FjAX4`o@;Gn_GV
zNfB%fE02_y?5@P}PyCAfc-iFD$srm`cLg*+a?qcZd2`1W(;h9hKGn=`NOwUrGtPLe
z?^009Xd!7XQ5+&t5$Mp)k|^)|$)UR@8<f}#?UTG~_I&u#Wh_Yd_eypq%$f)GbPvCx
zB5E%oUTuH+=mjX5%U71`hytv0JV-YnFFHDhCE*(^0a%M;JU@G&Mg6JOwGi){+uh)V
zMYvoufonNJQZM~s5L__u0d3Q;lWt@dNefr&l6cmeDb5M;bKth`xo#Wn43l2GESpWZ
zq<r_(i#P6HM8@A6%=0UT^9ioTQ0sQs-D{RyDPv#`OEI`j0}}lgr<k)W=L^CHho>Q1
zHXHXo_Tb?lyEwP#``{!msm(`++|?NjwRYS&bf+w0mr7QR%mUSZbfBCIl~|phFCVwP
z!X>=f*iPZM&mjwasVAKoNG0Gg4t?;?_qKcVlx;$NYr;eHHFYI&?+|`V$iCMPkD6VU
z8r%5EB;b{IX^ak&lPbl~eC9azN_Lbh%5{=!;<OOfZ<0pD+R+BngQyC?wlzN;+8|8h
zXjCJK9j6uI{7tnyfqLPm6vP9$&EO(Epp0lE#i>d;aIebb%2y(-r6H>?9I0Aa!_r>=
zP#OB4gXj<M`}YNrT3>P+;|GXLq5e6Dn0^PM(Z8fQ?p=WpgTPZe#Ax{wa55GMZl=Q@
zk%;jx4w(<|iVnx?=W{JwiMidS&C*Og?l%9F?aLh!<LQ581S9O<{wSSIqkCzt+z@;S
zD!8&-1{cw-zIP{~?d#@V?L=A*B?x(U&IU)?6xX36WN*czD5NL&+I&|_tp0(?vx_83
z^pWTgkd|*li|{c<VtKiQdo`&W(znoTD|R)O^AQaff!<M!`kPMn(i`(LfY8mkCB?3R
zPZZDp;HJ(zFPf4V`v^uXzUL`(QHD?M5N7N{Y}EpE^x1{v6VH2F6vTfM=^qJJZjc-4
zlTeKcG9{5s{I;-!6la*N@{#Cp;<=qkpGHT{iK~2P%>^qPK)<ur%jjKLP|ay%=}%{t
z!i6i1n2rKdiemv-gfvx{-GTiXqRM?84;i@8GFwMD)GD|{!a2>}QzpeIT0f~ss3?+W
zrJ{nzh^{xN8>h#SJ)1toyyzGrC==14DLtgGr{w9=K+GrHG-cN|nEVQV2Z(q@!8$Z*
z)SZ~wnca>hE0r1%DE4Zc@3C$YTS%Mlg6bvMEI>8LR2&AP;xQoxKc;OQMr6h{Tx%e*
zH1mev)zbzH7bQ|T8PVloadcYYvPMb%1w4z}yzB-na+||#c9&C=$vUMNVg>J{dX}JV
zcx=%o;T~&FtQV=?T!^tuMo@<qj8?t*u`Jzzvs_Jv&R&ukSz#^0hRxoW&im#PxY;$_
z?ek0Lg%IB=P2oJqX-mer+oYp{2p9SqS@FE!Z9{gTW!t>Q3?5yh74qzPHmHU|1MVWK
zYek_?gqS1cer=)^Q0v-NKBxIWNqS;X{pMh}n5%d3L;A1a$PP7$i;unJn<pgLJuqw-
zQ=AoV7pG6RWK%2$ce<Y!WRST_baw|fKzWTDK;sw!7{JQHXC;vO-uALWe?*HhpnES4
zr!pIeByz$VVW#g=FCkv5PzB1GRtFEBw2)wNn#eA3ogE>dI?k_19b_XL<3LQY^V4F@
z&*()~7A!VRtp!_E)v8d-?eb=b)*5ATHFdze#Jd!XXu`R`7gXPT5hN*|zf9m%(kAVM
z!FBx0So*^k|9!F4o>|9#`jH@!{WlUM=HFqdO>x<BnGV`xT^Za}+JG~38&ookMB{l%
zywV=`$AXx}NFuYSO*-uJy=-;5+A=e5Roeoxpd1%hytAV$8hdf$lnQzO!k0_BEdrW2
z39g9C`+;Lk{}>htA}U%C+->IhhpiWhNc)VHYKJBUZ~|~{UA;6+LSg>{wq1~E(!8Bd
zcZqov-+l622|{$o;hTPnZn)r+e<QIzu86#(O&X@!Q#NR&Xrz;b@3S++bNeX2I8E-*
zPv&l6cC($o#*e6eQj!O{t95VJTe4;j`u<j~o2VIDS}CR$<(xq(Qu*m6-vB>($ew&9
zGBGODjxyv(Xs{`beBWAY6nO{{t<I)5chz`QWP1nLcH?a(#9V<^QRiI-M<I${rm<d2
z*P)e#%rgE`39A6kYN7vdp0!le31E?ZCfhXD4Tcn)gX=n8G*WwYa|y`co#E6pJvnU~
zwqTX0W%71e=1?2FlpVSYFZ=~)LKZ$PP!p>EK1h}g{2s3=Mqz2?qMBC;U9V5iuPj5c
zVTma}Jw#lz0V3H|j>OEY$-CogpHLHvUCmgNn#jFR%8sI?xJeR(mM2hzr;j~B1*KJ3
z*<<Z;yel=j9nWaZ0~iDGmZ+i3wEIsK=yDQlBRzC9QRYkae2u`|?IYUoTR8M%+^+9^
z5nXNdFfR~W?n}56(Pxap+((bHGjyycnR4sz!oBz;Tebf4Mn3m!_O=PniCw-$YEI+~
zF`a&sRYe9|o5M;e7!eep5^yZ7miK5SkHdPBn3v7ShBb{r$_Xd6{n;-1KY%_pL(J?=
z{^Wdo&Fe#@S%<?sz12ByNHyqpNPTl}ne=na5w67=NqttF)PJ_?LnfMa)Vi>_f9+5^
zix)=+K|QD-OOrbA*Srm!9`-z+$*Dzy=@F$3eToBYi|pRKIAUGH8~M=!K<Ls@s?RAU
z!f2<yY3nes^L4ipHL|iuUKG7v(#BB&uTYoY$ngZ98h_lE6um0fcEqaU+ORj%>k;T*
zO}PH>qJLkYP=VgZseJ&Y_G4S{pOtf2ehU<ZF56|iUlkYhGuY~Ekx)`clKNEj*ai6(
zTwY>x6Ug9CN~MlZ=Ni%R3q{LMGhyBa_m^vGU8AR()(VUkLt>Ga7X+QbgQY{_O*q@*
z$IpDBF;xnC@yf9gHa*bo=_`dXn~#JR#p#0Hc%vUNj!qdSf^M}hgeeV0AJK^g1$ALS
z-de2sG#W2znm->r5}$ZTi>rr}N8MsPMym3n6rG70{3u&p=NfVz19u7sn52mzK)*7s
ze09X9GDo<ju%q1&%;6hIx}YE*0~=EDP2aI7^FBMGBJXAg6ZWrAgIFDUGpdYxhSi=E
zrg@1=Xk7E+5ko6E^#R}Qu{1DE!e0DaDcA4hIhL$ytqB|b?)0Fk%~z5d(U;ZY>$*;;
zQ&7T?np7??1y~N@@W6sN6seomcl~WDj1*=1;7i>!gtJ!)L)XmqG0q&CC2fN(rNkr3
z5f7Hg+f2|k2lxu~(6xeeVzG;|2=gL5v=ewO8TwNUP+Qo_a3d__pOMG=?bS~_Rd*wX
zUq0oa2?(z&Bv`OrL+yUi2CHb&+e>6$cJ~c_gtedg;Zz?t>)Cut2FXG1$gpj2hq4G+
z)mmHldLDfbX-SN|Pgg2DMV(=^#7N|k`ZiU%qfryfm;&PT?m}8=^lTx_9Np~=S|9Xo
zx%pnR3dU+poj!qU!j&pCZOkKL=#=Dlj28-Of+!7U;>z9@dN$1_y7%R>q?^GAktz1e
zve;TVi^+KhYveI$F>2jBg?o=7PwvL1*(kdRpp0Z5`6`ls_@@ltUG&M;yL2b3uWHv%
zD^ff!|8l|fk9YRp*L@+<Ost+hs>h!`^uPbieOZ6!z7g`va?5nc?!R_pERp#|BtUyM
zaxc1x8MAQl^x5xzs1f%qoZhUv5iR4_a$V?(4j3u79B&UFD?!d!ADfmjxVtiR1ykmS
zsh%>tY(KJy(%WVf`$CpE2XdZW+|K5yaLBGqOPzCn0^Lny>Pfga6b;rxNt#JF?m=m#
ztV@{bnLHEGImDt9=gW^9OcPP1<k~n@zG$X0>z_|KC01@Htx}hPJJL|ZVy#ZDsKgll
z*qy!+7HwzTm~Gf-o3etNaj|UZba7Q*P+%=i%tF7?R+GgOB;K&)n>C~2xHe~p<D6Yl
zsbR*#a>GrH5OhF*aDyi43CoJO`O%2~-s!ZRNV7aORLM_QI7;W<M#CjqcsWNnhqmaJ
zpeUVrQ+@PIx~kvmjje&He!KP7z}SZVYEEg&=6ii`>{nEoVj7G=a%e+~zo>=r)>MF+
z-PZ}Kn(u6ni?{P2#R{xldhMhxj?98lpXP#nRNLg#-auC`0Lr@Ik$RjBl}=kJWMWUA
zw*Dk_;Y@c4*e^f`%bsu%<2Si}=$<fswaB4TYB?4gHfWxh8|IRcd#K{c(;~Sa*7pR*
z!&VAa-norOMuCA6%_DQgL!FzMkDgWuH^ap|SrV?-5K0WxA&WaE3l*(etd0YU$qvLp
zOiPz7ScAyy2D3e<2m9rGwxQ!+T^#>-rT%@r>xEh<{Ox0L-1%=*BiVlEU4Px{)WhPG
z5Fv>sp%v}%zX3v4)0VbSN$>~yaIcnFIzTZfY6~rMmo_*1F->y~b?Rb7W{KkLJ)o0J
z7j*iJIh8IWpqI<X`Z(=erd<qbvoTQTLFA9UPIwPR!+U#`apqseNPBO)GQmvvguT-2
zqf*rHo)!~o%HmDgF%gnON<3xaLs!ixh1v~g6xyheih^kZ16Bu)3iNqcf$CUO?TRb@
zLR3j?KN2E&0KJ?B^20oUGFQN*>!({EiqRclx>v~_wvIhPgK!eu!`u=00+ike({ezx
zHdGE_LJH{iTiGoY21BLRrZ`=K{;5Du<9<Yx<US|(@1>fhE5T6JP}N90W=XXj--m`)
z@THCEJ7q@lnh^E$pd#dqB-Tq!-Wms3N7v6UNlroa_2hGgVxDECD(4sni?qQr)HKwx
zM>KXU=AbkfR*slx2T7WjXqm%x3)gwteD;ZbaM^J@(FNKY$^!2K6rLhyQ5eDi6RBnw
z7EJ6aYV9mEsIcm`ve9}t)G)`<8vTrirdtE0JZ+H0@<?4(7+NgFw9u1mLH(3eU&19b
zJ8!lykB0&L{1cal*2`F}{o8nv+0e_D*)n=A<Cw=NG|sA>7?<Xga;inX;A;>jqF^??
z3DqOgy;j!nO`(p{BeKAic}}r((W+*(Ohc{`s&?t4e0}J)ep`(M&t|(Km`7Y?qZ=-3
z4|ZRV%2D*X&nDuEdQ;RgX9i-I=>xiDtnfR_8p4RFw>B-Y{gGj$M{zg}i)cb_ad{=Z
z!K`C4%BWBsm{4GSkkPrxPP?P^13ry+vpz%o0V-_-pDW-i{i^t8)E?VH^7ckBdtgm>
zkjrj6N9Mi)e^_~cvzv42`#QYpHnQio(7}8zD`sHNMLtqgx!+h5T3|ZS84RZ=B6Q9L
z%VFQ;C~K?IH~nxwp{wiK*ajc~n|+YfMmZjt%Y|=c2{`L9%n)p3O*`g|0EM~gD0?D4
z@c<bp!*tmydL2Mk>w~wKCs(UZ|0-eraI1e~!kiLio_`R=;lGj3v;U4TbxIa?*>v!4
zo*e{n=PZTbGexHgZl_7@Y)0o`0>Rzb{_2QDcYANo7Kk!8=Eo8RTG}-yJc~y6KGrsM
zG`0%#Mb)uUf2b)g8zmUpu{Sfv8`8lE^T?%*HEmhCvGOlwcLUIixta=6ZSxTDteJBO
z(@d!Y{R`O)KopJgw6Qa&#Z+Wq#G8mha%sKQcXIb#0LhK}ZPIC_2Wip5s0>*@^7%gq
zlV)0|nU^dBlfnifDUuJ+Z+M=R%lfJDh}l|tI0>wnDUPx8q#kGbCdDYgCdIS2hKnx^
zHJWu)w=EXBO`k&$=>stle;|fRb5)ccN!~;rx1>lwMfVa1nB>-vBfOEwEZXnJKyPZ(
z6(7njh$rh7yoZi;Pb@sDj5#!&am{7>=1{~u&GQSQWD1Ok*~g9t%Kex0w;!8~;va~a
zgZZ`PK{J(qoIHkM>6{Xj8}YH_aT>VarirYA=m{Km18WTTLUz%Xk;4e?TZwyWll>Jx
zp<U0wC!D@Jwht5QOW9e1W0quandmIa;ccS?3yCeP(+??^w8S6#O(l5BuKBF&HI4~R
z0T6>p7tOn<Uv$E7H&QrV+9K(|s}7xT&QCsaTC|_O0F3D#*yEe_In+|COit|07&u46
zq8WW1(KHC+3=wHVG3j9LK-xxrxzrgYA`3iBFQSA2PQVD*-~?=Z@cAX^Q={=;^1}FV
z^Vi_kCk1zsXVDI~B<VjYj>}mFTt4TrjMBtg^lCG63X}@6-yOU-r&q5ZP4AvsNyb{K
zo7QMPZ{|p<ZdF!ad?BoW^PgSYun<k&Qxhy27pLHgR&e&s-MDa7M>zv|Xv;<nEk>Dp
z{-&dq4Q5+<I@jcF*9ZTK1QJ*E<<5#@bEkQo{ocI;DWIznN$~Zuvm?TnuJtjj0h)0F
z(VEDrA>l-dXbYBZxl#RtDGDm(0XPf2&A@3Z<?Lnf015FWBWX4w5QR0`5JF5vCp%6R
zCwE?(SIb}iRiymkNB_P^=~ZUT&;3Bk@dr`}{;Z|`4^hb<D(b(>N$7sZlvyQ7yJbA&
z)_Y~T6&!uFIuz+Ni4&%#ogSo?HhBm^2?UwW&=sk7H(U|16Q*R>qt8oWz;J8TEn7ZP
zV@Gm7LNSID(zf1Y{So4dh8o?!Z$*_1Yx>4GC>Sb`4dy%dQ1NhbPa;uPn>EXt1p)9a
zL8NbWvvcG3=7Ufcam%HMq7NsK7x|UD;3a28d8<P*1ZN|VlP5KfvOe#WaP5<~$Q(B7
zPch>KLL7OwQ8(7(q^yBSVi^LG=%35kV!^0tz$`)CI)5$GGlcm5dfJ)ImehK~cP`wF
zj1gPw--_boi+=&_q1%5M4_T{Q2Q^))iP7&auB0qPd)w`QviwU((TxZLNpi}|8Nno)
z#iyD3#a@!5$WH!=^;^IZdEj}|rSz5_@25OTI*-WwzEw)Q>8&2h8qo%TMb()S)1R*t
zM$RjTDyRyKz^_vCk!0_4f<~>Z@J<}Bc#A>}WeOIhExN@5?eu+td24zcS+jKxFpHLA
zyp<O1B}Np>56PLEI3g1vm6nGrz5$W2aM5@an+eaB{a0?m3sx5qv4wUyc~e|Vn{1J)
zNUMkH7dKG0kX7NFGv?UHH+(8xwx4@Ih^99{@^QXSsXW(r+0>d@W1s%gQsB4!Us?*8
zKeQC*T6i&$Q?M0pfUSvCiq`PIv=rb$U4Z|gr2v3T`lY2{3wnTu<?>4C##PjK7o5Gl
zFXU)su$m`^?QJhF@}XWr-Q3Wk=!PHJWVz<=AkBHC%IHIDyL@q9;EeoFEyelv@GmXJ
zOQ-bTv=mm$Vi~l2Q|hT*Y&w>O?Ipf*4Dsh&{!A~lOnc^%f74Rz{il{<zw^52?k36h
z>Fghl?frQRlls4U@BeQx)gN#Fzb^^il{Uv0KS&Vrk-q#>68u)H`Abgqp{DplPQ}^n
zO|P@1uUjxkY{FHw+yZH<P2o>5*lYP~6VtobakamUGyM=GclPY4&7-t;v9EZi&`=C5
z0e$l=BnSb?Bmrg1#(#ah!i`>NNhU^C6N07NEdR3aF<F9X-14wl6%!c4U+MsSzyGH{
zeEME#?o)28MCVer95FMUVib}54Fp3{+Cv6fOf2fBhRdVq2h%DtIY-63;aG@iBH3_x
zpaTa@kyV4ZApN*d6Orxg2K?kY;BrHdmFuI!NYkDfXxlqhnCTZe<UHmj*IdR7d_M8u
z=gxR?xuMBcx-@*U&nYztHkPVmD0+@WM_9y0w#Di<Ew05fF-_DdRNrf%%CJm)SG-UB
zzc_wPDMc-=wIV}Nji5Vds+ZQa0Qi&_LGMwO|M>cOoyn_ZAk`i#Izp1V1au|JzWc{E
z<8YBa_#RFLwcH)`b@@fTW#hI9+MuChTc#=UV?kC!Qsp^JpyeQ9h&Hm@8!AqUNZu$+
ziI_eZVd*zhkQ|6It2z^PPBbv#2JI13bpx~GM})OV1j$Ag#+tnm$y_&HZs$>I2F}ri
zEkLR#DDcm28YXI*qd6L|Un_|9#z<Q~@)UXeL=;eFEqvQP-_HT3=CIogMI@PDm+*<w
zr8;CNS7a%<c&Uf6zCH|jwsugevY|hf8NShl`#P&N{yfg?AMb|Q!VB(x7ijGCl4KK~
zI?QkI2f8Cjl@r8uWQc*CLM?woXf&iM+pym%HGDybenUXtbIE%9<i7z9K0hm${NfC~
zNsk`drwQ&g)9;tg@)>)g-#V*9EpY+xxiuG(XR^NJb-v|kojHq<W~01Lpre0MA3L(A
zWX;+Z<3_5D?xe5BcqMFGn+v>R+nBBODKHZQ6$7a==B2fCXE&5&H17;@U=}CgzHVE!
z`7WI;&c7o$pACy9T0u4o>RHRD7C4RgS88%P=98p%^@w})GW!2WP5zts_`_xXeeq$n
zkj1h6fe$L!|Ew)qTG<=e{l~%JKi&M69;->RRv+{jSidKy>X0gfhz8D{5}U4foLW*8
zzXw#`23FAHS~d{<@;c@XG+12ZmMW9?z?MmS|2*I%N?Y!jzzZ{<UuqC&v=1nxUd=(f
z%hL1ZGfyTlI)=D`lpwWB;Qh)*$uLx1Y~Ai&BIYo&FZNWaaUhi0Y$$vWq^7K$CMAuI
zmHct2s`HFmtl1Nkt+KB_UnL$2HSyW_aYI@KYijIe6ti1-W32|_C`g@52f3JmJIigN
zxtJZ0$<nkiF*|=fYLi-o>qJ_^$Y`CCnM1|$Y0I8w4g=UMU2N?q8@fZ*C%P#dQy5!Y
z_hZTCB@6pqCGD>*&^^MHP8Ge64`T##?28))eGSUGDwl@|##`&&;cGLp4t=j7NVHtz
z%|Aj3o$u6zWh@mzs@*`cgm$!wsqcPRCWTL@&Z`*JutEAp>c))3Z2)s-(Dpd4ZwlCa
z2koLq)*!byVXmOu35PZtqjL0Ia%ZlGy2ZDU%&+))#xwJ{CdkvhWILHa=V)>7+W=SW
z0jMZI2uiP*+LuY9IoNT~#5HO62+FM?IpIQ!@%AXe%!CoBE>-E3$d=w`Q(=wWwO-VF
zjVJMy)&?3^<jPA-B2bFxs~tm@RS|#GvPxh;fK)AK<rQh==Z387fH5=<+;8#p2Ts8U
zFy|0$`|wCE(mUK$_q}V3_Zdz1RIOmHh46XqzT`Wo;VgBHhuCXJmVBJTYJ93TnDlnG
zJMP!Kxbw8_K&njv>XduXISbr1g<0JW6AY5mnvGw9)81iCR$d|C26RRS?_4d&{3!3*
zV~x7+l6*4Et(V4;?W(&Z8g%YvjrRk?0+(ZD?FTYlv?P@Ul)nwk5(dIn#j_vm9Eqcz
zJxRi|V@K!E+rqI4?ilk%4*Yzz&Lptq!W$p>>3Jaq@4|ye+y67D;u?a17IbeH!LBw<
z(!rY=Y;PwR!@Gc^E7pgdTUV-EznG9p@oj$RU>=<PiS+zx^&dXFqE5<WTlt~sCj678
z`%jKyNBg%h<WF7yBaGk(<eH!%G>dt7N2^b3U-KdMwYT}uK*G|1ISsr!sV{e&@MoaM
zT}FPDq{KVORqi)|ZMdxd@<~*MjTrSjx+fIksl08Az&0dz(O)2R6ETQ=-&&Vy5Ti_F
z2F%`o@zGe2#$tvF+yxC&MP3mM^$W}c%is^TUcOo0e&&rY^_e7umnXYD*~4F?D%GpM
z@gguA!p2+1m9f-1cQz+_yw07j{WUxLCnpYntKmNV-xG)bd*bkaPaOX5iNpUrarpoJ
zi9>wOEb-Wn6n4-V008CBiT&Tt8vZu+Jk?OM%V9(HT-V}zbfAPmY|igz+$Bn1D@(~Z
zOSw7YqC{UdZ=}{HO)h&qr-TTu;$P7Ob4n9%u?C((;Fx;6vB?E`xf#|#<SeNq%b~)F
z>IAde@i&Q<%(3VB{JOoo3xUOMKs;3xT*LJ7?WrEyo8j><y9EYZ4!P#48KIZPvWkyI
z$BA785(1C-!#xUnqtyfm30zcrXSMJR)ni1CS^EgA2(lceJ7F3-HH%b`-C<PUNOV+Z
z6OeVNC>GCb5q1sK)Y`=@To4kgF{#@Yb8TZ*Jy8u%P?f7mCb%yh=tXk`(iNV-lrI(T
zzrK}$e@zfm&J2B_cvn3*Sy$46B278skc;_Qj@2Y7BtKFXVBgK$yKf<vwl*3n@S4QE
zu@WI{>wPv`Q8E_blz=ot>UX=SeVJEaUiq*fzhptX;YhPY)Ib)1Tl=J-KfDq%;Aaem
z*F93P4CBGiEy2PJ60bL+T?Poy35I^2??4UF9BV8N7a#Ey<sjTT`)Z1RH4!sVcGebJ
zVRoYU2z+pt;k}CNFpsh$sNw-x(<>WtSqScDnmZOYTVbGxW)W66ZGb8~JxmsP%SYeA
z69r{NymfgX_s(2rg&Zco@5r@<uDb}2k3b(6jb%|WI_>3AS2U*{Y%7~Itx`8Nzey2p
z=EFAIMwcpTk&D@!lL#3Zc337~99dN2H1zE7l>hk-i~B4xc;A+$<ukjW(kp@@6t@J&
zK8Gf12NZi??|_&kW>MrdMj_me1h9$5uDt5uTf}uh;dpm>v4c&zr*SpUk@0rDV|1pH
zlhNXhW(n=P_;xe30$kF&W+(wR`{nwy9BZ>Fl3;41CDI`S`?xOmKrquceK{Xj`ziD4
z(rT5N?|dGB+&>H)6jukb&hFITe^L&VG)~*`DISRBZ=N_MtGtoZdgIQ_lsVN^wkUO5
zAY3z9RyKrSo#0@zwv&P#Bv*<u8nmBb!tgEzLj*|`5yk4A_l8o)pg{&2G?ZC}tJis{
z2y9P!jnM}ng+4+gYg_wz4@i+9!DXncOSOgs(TuZmJXf?D698~1vc!q&zLM;YSGNp*
z8!;OOrp7PUjbft@@g<<FQMtwc85^ih3<QeB1;Z;D>Ttaavh?nz!qAOeIhT^^m+fY~
z%I!Q=J*=*Bw>zC!HeG^F*0R=@ky`E0EFS~`TLW4j0&b)Fj*bRjFguPWNOWGARw2kj
zE09fel(FJV*zmP$eOFiCnjSMS%p=g_r^;v_@~3sZs2`x*OLP<gz}o9Swm@?{)S<b%
zIb*eHDf%bA%WYieBR|Z<6WrcNa8o0xk*xLip4QsMtDj(XUIqcc_A2ljKsn<@v);^H
zUD97%uHC&rVmxqZQoyY}QpwT7g>905$3&I@vkme%0*W-XrtkC^g0a`xp$|8+*TKby
zd?s()t%U_MlkFgECI!>eqv-Oprdtu6^s~O`8yM`{A!A?gIIYdw6-3FCa>xu~L=dS-
zMve(iokV@z_p5$)cgeglXgm$b6pihzG-vQP0QwZOZ&77=V8h=?EGiyL8<gB5f2Bwh
zntDxDwle`eHqg7gqqhaqGXRY5>+GkO`DsKl=^H;<RiFak7O?D03)gDTfGV=1;HIbl
zNVrKDO!XM(Gm~HxQ=MkjZ75tFj|aH$!oo<`%ZB!3*i`S;Gp9zpr|6f3M?y-=T%4Cg
z$(~Koc~+5m++ch97_T}cXfmsNixzQ-b|UY+GnG|N`FhHIQ_&7W(fe%mPb@|VpI{ln
zZjMbnHgZUdly~nC_2dIO{jh3i3mnGFp*kqVPC%lbgWDIP{H0}CWf6BlIq&F?qO7I|
zTIixRI9`sJ@j-3kbb?a}q^fKKXR}drft^8Z#KBUYYLh>q<KH4z4sX>Z65)te<605w
z6@Lx-)^etNjaTd8=`&ub(d>CIKHs|#kMCzbL>CC|u~dKBU8m9L`3yC`F5tq*1!Cvt
z`^ekQhz~7Va2NbBjf^OD$mZk^)H0P-FkiptX^VFy`bH)AlCR`yLxNrTR!KW=gWS_-
z$@?}&-DhhPhh#{0%{bHfxq@YB&wkS-Uy!?i%h5J9AC|EugFIWP|Md^7GJVGbuxB^f
z(Xp_@gQAwN0CljP*CUp%yzEy{nKK4|yupPoS4%T4HkQq!HV8(fV}-(A(Ou>=Qa{sG
zMJ&7O*{H>1<PHaZJV}55d6l`t{nuj`KYIHuem!z@ipfbHztl)A9>QXIJlbzTzfG(T
z4UO9nz;#5(8)ZKI9aGvu#*#JSH1rnhTa{tI67=;+ew9X5J>}d$v&l%flNCLa`^ub+
z935i@qRxa|W!^>uZ&yDH^ffhz8e~1Pdo8kgt6SLQ=61bnQiT?mWf%sW3!V9PJrzg?
z2qa6r0eY2<TB0vCNXNI8In+W-Y4%F)3|nhMoA~#dx61w$Pj<cUwN{xVpS}A_Xd#Tx
z(v#0c-<>(Fx5;1{02_oT^}laPs!k@U`|Cc@rypHnMNzOj9&*8^(xAw$WX^Xwr=Ff`
zpPs$9*+68{t#y#RbA*(9K32rYI-u7|K#2Fadv2i93{XT41~l@p^uM{-54hp=1?U-V
zk>`fwUSDUz%N)+&FLfzn_5GeqYXF&O24w;xoHkZqAx5>NV4d`#iIx~tF<FC^$Ve!r
zZ<tQ;L!D+}kx5)8i=5<uH#fp(Uq2@l+$fi`RA%n;l=7&No$aT<kX0=X4Jo0PR|v~5
z6*Cn9%m%m4A|WsS_+%KO!nSM*O2|{COw6jkD?yT<9M!CFaQjNFMv{KXg<3vk$y^tn
z1G59tJhAVt19Dn`m*X%}en#>CsqDPNn#k5Lp3r-5A{e?{r3i=-6he^>B26jMi=tEs
zaRVyoD#)(%Mfyq;kg5_PfC`96mtKq_MT#_otcalCjiAfSFg(w_;ji#K-;Z}rhMALd
zzV{t3+`Uw~8J5t;Qd2aF`c*b20eyiYp6|q}6RIDbV~<FAd&p$MU5fi+q6z7VpC@tG
zH@pwscqpfSYOM2@QEGKrIhAoCf+O!pugjuel9zc$gPVQ3TvE>c8~j1PG5RnY_PR|g
zK1uo{Bcd$Ax_lGUq4unsag2yJVa^)N)Ac(#5!#K*j1y&xZ5ZctT~u%=cU|-xSBva#
zB!-Za4qhW47G{ZmDo=J(Azd@LuF}XCUrH5U9WWu77(KF#Fy?-6dvA5p!G5X3!MWPg
z&hM2!&Z&F!>g8%jFpjog5EG|yIjf1+2#<4R2uDgf&8DW1L%XNum#u9@Fkey$%}9ZA
zN6nzTeC)t*L*T%j7S^$`vZk7%gG8=1lc9jihO&kOB6B>k34CI*;!BYZd2Nz^$NQ;X
zc#aL+qgNLxIPP&uw|_nHJ0wbCcH(;r;ivsw1U#_=?A82V%Oe!ad#?^noxvw$)HsRm
zwZwSVU<EpxmcH@p>RRRG!r!_dv!2WS#`>s8BL-ckI((iue0)}z;pKbTsJi&DWC1qs
zfV-RlDx-Bed<_dl&P^&G5?quzugg%pb5i#D+>_?H4mt<f=M20H&J}i7AdM{2io>ww
z$~RvNO{0!r)0MC+lPa+t7%`scm)*2e3vD+VdM)}zCN73Nux#Z*7I^oL4dIp`qrk3>
zkhi3?Z_arl5ZpgU0qgAI<!*t+d%5qJH94Pd=9_((vam|F5UB}9y4G5@mee}U8{`EK
z&d(n)5YbfRKn~ynN#rYRIo??g$NgGm3CYKpc;-G1Hh&XXPst%;)OpOSjb^1v4N=Kt
zmYlm2RiyEWe!Y-4Ol>j!1cOQgH>+Ir)!T>OzYAY(HmQztB>5_?6?-bXXM6c@q2@`r
zknGv^phP}{e@aMscU2Ru0%Hj?9YKY@Gvf}g<Z_O))OY<UA>Z{NL@g&I!F@$FvS8_s
zj&1pqSk(lB!f(E~m8Y5{srE~s66ek8{pS(k<+IK+0t%ncy1ArsX%Sr+k1##W?n%za
z7YsO}3zR1K_C|TSwAe3+5hIhirI~a2b)RwUQGP<sCocq>=Lg~mJU&bHZ`VrVrsoZD
zdIJ^gYl!_Qt8-QO3YD~$f`@Bq9=1>M3udv2Rzt!*GxLA6+EyFoMBn;w^)H*Xd-XNw
zAi?{nH8=E|-f-b$5AO=uN5M<E+@}Kj`kUYCCEGT?y<s@HJJx8$MY>BZN;_To^?=E4
z$@UW8fpo2*b4A_NmY;>)Uin7t>0QC0%l4bf5&Et;m`1S`6_gkMfw#wh7L`xE6n`aU
zAf0>f>QJfC!qlt+DatHCjqRepmz)?H=NMIt!S$PtSz+>;3>A_t1=VrWR<lWm7q6Rs
zEMX6j^-$o)63=&haI3UMJD6OpDqEi9nt3URoIwPJR?%ifF?ob_`Td<{eoV^bYh@LE
z#$)pg>o%GU#ED7T7RF<$<%km^+Q|s%fcvbW50hB#X5U;d+GXDvP24Rg#jM?StG2<C
zD90wO?etR1#U|F7sZIk!<)+C-(<FGcNIGh$$vXFn#C6`_4AkZyMCqmThh@%Ry+X6f
ziJ%Qtq&}g6xyC~KNgUBa*wv!3CVdheblpbC?zDAM6=!3cq*VE7zOGtPQBexup$I*d
zTcqag5zeWPVoTzj|Cv<ijHVogs>Tpaet=rIY6gnJ)j(#nA$U5YMYNG?455nNVTy!x
z{R1w#qV?Bah~^@d{hh*)<uvTa=4|=?d{<G7O6YS|uCC<4r}n3`F{8SAoY$!@huH}u
z<3@EGC3e*pN3oJeZ|mvJSodWAE{9|5aNj4wZ;hp8VxZYiGwV{LO*2q>CcC`uMb4=+
zg^K=S#$KyE_LaFKyMtANjFzigS)Qt>f8@ASI@N++c-#5#S*UepgqoJIvFzR#Z4aou
z1fnK5#M$z1W|SkwWjY%*Ukd*7TB>fevW=X3>+y6riAqB_gYCq{g9X}s2uoJPJ_Il3
zI#WJ<Xc5&662Yro_Q%z8Q7NbZfr%vD+~4oHDz?d(I@Ook2r=)87_2<0e1_|lzo3B0
zSc}AgRgC+n%IRb_-FTvs=q;&FX9y_)LSOxk#(uT$MoH$eEwyLHP+2p`(C|?)hnFqL
z_T4*u#GlWSllnQ{{yDxt>`P@Fr{7qMQvAS)$JA*8brH-#u~$Burl@~gM1$9EBRdT3
zxGDQTZ`e04Om^D7K3GZ!uA?R1&pp6?r_Pb~M0;P-W`4NX@JWf<@{&}BK7!Awula-z
z^u%U^F}d}a%NYygi$bJ*Ix88HXDgAfCh;BduD>^oT@Y_|V(n)vb~(hHCxb|MZ<&A8
zBgE&aiJbLFOyOUNwwi6_BZCtc{L7R_s9X~Mw7Gg#T_@IvDdx=$QfO9!v0Za)*r8|^
z)AdE6tQBm~9!XnK>9mXvr`85uw@X$o3xV1_N7$d)EVwVLIPUX!lVmO-<f*b)XeNFp
z6DvGodp8&tPhS?(G^13)@gn`vDWXyg*@~kZLrQP9<H$~7#0(q1G3?R*vf?4eZzDcB
zmCEQPdOzWSXMdMn4XMrG$%m1%RvOHeACA(oR^KZ#mWY{glVoI!sCoF!fp93uqN?4D
zH|;^K#VJIFO#RGI;;PQD^nP=OlFEiVr_FtiwLR*4(X~>+;p4D+Hk!V#hg)0I$*i`=
zY`#dpOJ1J1oHJ5=TPw)P+x0-!+rwIgOnL*Q;bw(*+>PXVMHQ{k$DPe-mv?ol)L<g&
zEd1_hX5F2_l-}>e`9)4mUzTg~HTn|ynv0JAp3brjF-|JPFC0tVPhXaqe(u$i^vv@-
zxYEY+mI{}76LkHe?ekgb$Xc>rGt%*c@jY`dH0g#{PL_7|(dRvQ<zCb8sjih*A&w0~
zYvnDAV^vX^J>i_H_P08x-!Y_n^e7mvbvQ1PWHG4Ex1$R%Q?2Ol6jLXXN}Y0RgMTsu
z<=3Fs=DmMoUlm#ieq;f#N`$iAvh4u|&~k9nKd@Yya-RQN{xkO<S`7}=2UdTlRR2l>
z2gd6|3E;GLAYq&`0r)}KJa*XZb|?%SMGk~nQqr7%$@w>=8(I!d^#+#fQ$jd@l!G$9
zq2=I^Y+(6eO5fR!^6in?PzE@88pzm7S?>G600e$+&!L9mz#*bQTp{HOwhafEVs36|
zZ%s6zWbiH)kj%xoN#4lM1f*y}3E<Q;AmJoGKpR|(-jC}n6bI~ek^#~XS%NS)z@b88
zq@ZMQ0uvBjwi|{F=q23P%Y))}7Mi^W2DeS<R@@Dg3{Hvx3MHUm$N-@m$rVuC&O&9x
zVQ|}oZpC3h$>1ajpingl7&1WUhL;_R+gWJ+UKrdqp<4!dC>iW62MX<#h9LulZg^y&
zxSfUaP)^x@{~dpw^4o-N8E>IvuxAx0R8kg(3=q2E287~v7TO~ZgWD!_%VG#6gWY*R
zq2mW&$N-@m#wsXoXQ2v8Ft}|(x7=D#GT7(@6smO)h71t8;m?5Lb`~0shQVzUx@G!+
zlD~oc5<sCjhhfM7p&MP_P~6T!Cy&73wh7&8C5Mv1UD!aO%SU0z0HF#SU8ztWP$}gk
z2fWA_7~VFen^f3I6}U|lKt>=nVbDOS8@J5=U8>wM7~XcNJKu=GEonfh8akV3KwnLO
zJm3wiQgE*h5Qo!;!EGvqLSe^r=NZFwgH1AE#sGWg1n+tRwKbUnMiICN3jH9!>uW$n
zrVR)I_y~3$d+<6Hkd|lr^N_%+R!}+M?~_1)h9d$2^X>A45iMmVO9?xn{GeG7h$QD9
G@BRyj$kC7h

literal 51771
zcmeFZWpE^2b0yqjW@ct)W@hFQGcz+YGc#+%Fk%`pGxLmCBW7AXkG*Sq{YKbd#P`el
z){nYXx4JvxW@Mgw@?=&k%7B2P0>A-~004jp@II##Fb4zxbix7vC;&)c9T9sw7gIYI
zeN|5fQ)gXz4_h0;B2Zw;0s!#W=l^;9KWu@?^bO?!M#Qko+-p4Uc2|o&5^hum-fx~+
zNCbqfFro{j$+VRAm#u^@m?gxf=W>~dZlCs_C58*_Z?bBP;76r%NY<fp=mBwZ#P@_o
z4BZ>z*<kpg@*&LF#Oy#b^qsHXx!XU35Gb`@BjAuOz>fIwg{gfkXf3i%aMGbm3UM50
z_T8BPeycWlH>(z)v2c@4^>#<tFGeMdKb}kK%1KeDgQ`z1nJXiptW#sakSS-(p2vT1
zzyy~HW||E=|2)mms7x1*(l*YeMO$Qi?};H|x~42;7C!4+Fpo>4#+Ig@;R7LVKlTT>
z7QC5Nxmg)XCbp*#NS`5?sq@Zbb7u-(k>c`4q`)356Eif1p2@w76h?Ops!HmDAD|&^
z!zldm(8Fx5BB%NFfwmB1#(`@Jx`xchW$e2|KZ%l#6hr279%7L9BL;A?3&;~_(+}a5
zt1R+RyNW>pOMQ)tUNl907VkzuVHsG%&w+2{D16#qC{#s!p;<6odTjzOE5>HVTS+)6
z36m{nGvTf#Qt1qnJz_JlVmpJp*QeleEq~VMX4`;g=Q!+Kn=Haf>p*d!G_>vH(kS`k
z>D*tMhuv5$2s{RDo2Sp$q5tK?pPwKA#s7c=#pglfa9>EU{}t#kUr3<uWNPEgK>yeI
zp9t{(aM=I5rPn0&%MUWbhFwZ_iTrxavLg(co!3R2w}VWDV2s=VUniC3ZSLkX3{RCV
z&H^1-z0SX!xx6<MxZ6)QYTTyML??rETE{ul2CKVY*vA(&asl_gl<W^gwy8R+zK6LV
z^`vxVCrwoQraa3O4ndXt$D&X5Ns!(hn*idMPt14N3W0jEcIpWpEPpFOwmDRtVnVwq
zxQG|Tn+gB9G!Q0ilazG{?U0Ny;*E2$MNAzdu;H_#Z}KBJVrAf-_{R@UggdP23&ks)
zfw=kCw3ai!U^6{QVGZLfp7TXj4zK-%4X}tyZGL6E;?ABr73@43PR4X@T^-IokW5j1
zSE=(rSoAX|r^wdw{fd$Q96iS0NSgb<OvUl_l<;eGaByL8wy`uZb!PaNK>GWJ>976t
z?~n?K@3$IcL=?RYeG6XoCgllNjxyC3CQMLq<TprMZjGRW`i^|sTNlR;>Xn0cI3>UE
zPT%CAWQ5Tbrmapmnr)Cvz_$51aSa1%eusXvD>Wz$tLyz_;b$@YO_;ZRv`CTHI>RY$
zN4g=?LMV+WiD4RXKB#?^wJPE;kfc&Y&9|!ARIt-Hs(LA*wiSG?u7UM)27YiCHaFOl
z{?~0b^iWfi%OD%CbH5Qbm34xX_tEzXQ%?fbjf$<!2ZVpLe73^Nc#5y3JAncK1OP~&
zzn1?m>vnK5b^hWLhAx)&cK>JfUw{JiMJc|%@c;Hvv#6vH%!mka<&M$|a?*)fCT|Sx
z%|!0a$Ykdi01t0LYrDWx?&F<p3M5Y6a~Jxn_Uba;$*|?aQq2VrK7Slj>Nr3=8%kAL
z%kt3R-R^0Elr&qaC@wP0E!a9;SEqhi0QwwWpNLM9U&Le#m*~5X8x5`<*w9e$E^Yda
zW;DI_P#rbD2)su!iOl@~HZ9*&Je%3rPG!5%VnwU>_H(VQ$^>Yp?8!=KA(ZZit1`+D
zI>cuTQ3ASea48LA19!u$+cHy6rhB@YM7!B650h?ILm#xC!kgiuxTHP`h`!eF4X}}f
z0wRn)g~ns?D=yPlh>L^|(5;J90{8DVv$HwDB}7COCQx<2?^o~%N+{128GQL-4$Gh}
zMR$;X59Oo&Uk>u0L+!HBPg?V9lWO^*tf>DQYX7&Fou}>CWiz4<Us7D)(eB7o`3naW
zB}kv4Rw`47$-MyRb4V+O2{-CX6ndQ@v1k`c_yO*#M>#VOmp;sT{5jHN+OuU9s^i@}
z=`4y`sTijTH!E9S=+0&}itP!hK`HtDSK&)53=`ayY?zAbnzW{r#j?c8e$B1&xFaSK
zl%eg_R*IM#8Xc(U;V-+twBLlEmAQM)!sMx-hhDwjGheKF8JM4xOywdc^hH@m?FbGv
z7Z0n{{l#s4qI%m*L}4}#rvh{}#<5EVGc9cHHB(hh*u~6n-Xz;6G)4zU-^v-$?^Hf)
z&Zl5$Zc<+L5W%i_VG*n3Ex?`m{?w#R`;U((D?E#tAjMU^7kcG%z8kDj{eIL#{6YV~
z%2Uo8gW<?ge}v6r$qZKzw2*^(DyoJqtN%ceJYI{fs}AoyC)pXCytUpGvZPGP*|v84
zab{YaiE4tc*tBBX*6A2!Q>tMsPj$x<Xe^9B>ygBgvKHBPAu%2-7Bbx@qP<oc;Gw>A
z@4W)BYB~+iaQay~E0Zm5nzmo8i>Z2Z)tA#9Om3e{J|ssL?V~HX1~*!MMagCjR%@n^
z?zU;-TFt!Qih<Sms$P}Z?82EC@B=E~2Pm^M%IIVO2$$iC*!(Ra(c2vas|F+rLD2kd
zCV~%rYtGw(^w%{MIR7^9jj+?F31QJZh;|HM$Zt~@0p+h7Xb8a`g5p4Oh`nxERWHFg
zNJZ4iPJ*Rhe?5zW5EO;jAy~j$l>WNwAOM2Km~)YGS0E^w?+*U-HQGP$c$3zD2meQ&
z_;FkjPWY8a_3;A$X#eVo{|fs52KVPWI`$jvn7#z{pM=MJEft+H+#(0;8v!jer*^((
zWb5cfIFxHr?B~6g35!E+CFCtDrZOqvt4RV$1Pn)=xJeBDKcrA>Cp@r@)?_IdV0DeP
zG9(;Zvrc+_yLfM1zt>ox&ymio%J!O;ehfZ8?sU_ZnIc<K=BBD}FRZAk$x<XUe``uf
zW4H-2eX`BGO;PvwRW0@Ngw0AWInomI4{51m*~;%{k@2GmQ{2WC&mU4+>Xp)*G8SM{
z6RzJ<<ZOpTtY|oClwxVS%jdbg(CL#TebR;`rZb+>Z2f-?6?x43p1EwjY)6;CWYC?k
zh%%g`xJPKo@R=kGV@M9(uP!6!?$)}wdn3y&vR|K)9ogN9`lJ*sKQEgXzGpt)4m;EL
zHW|Fn#y^o-0I*u%pmi(rb!^~uo=iia8%=9KE!4D{3%|*?WpPV$vC4VdhDTWP^n@x2
zL&#3t!;WlR;$8!fT+i9hi3vxD;i^bBS1nlfPn=4mm1jLMFL0?Y3_Z<WFqoE#;vijj
zOeS-7#3YOINBkZ=gj#83%{<B1D5>>PpdM>J%f#m_1L2zozSTCX)}Hx|d{IcGq|;N0
zsb5oUec{}=M?eXxJHb@oiwd(un_mG@W4^%hGrxAu1k6A!vi7>`1y$p0C<|SaDeOFC
zwo8Sfa4+>#N4chQ9?L+8O;>=3F1%b#oWDU{LAEsu&PTlsDvcqRd<~-YXVj1rvndF2
z`BtB(##EoAl#)p#kqt~@kFeAdYL%%NQ>mnm;=NOSi@J7ehPj#!V{B8-W6OGFhw2To
zfvZBarK@wIL|akE%oC_=b$%0avWyK*a(}f+o-t8`=h%R2Tx8XvD1~VYVsU8Ta8mN8
zqNbdlrXyKMV!2A(BUB&Lf|lFE2JqoE0_~O;)|Ird8jXr9O>u@N8}NXvskW<5JsBL+
zt3ZRvL=|VrI!~)%)kFPT5r8nTEEIg{*&2V)%=*%^XP*_#q8}Iyc;7rt?2@XS0KcFd
z@zY%O3_CT-0JH%<dn`dl88g>#;b5DMFAftO^T2(>ST_DQPZ}A3Qa0Wkc>;2gk;4tG
zY=re&GtJjTM}{zwL)UMtDar6D3UhHUS_y0P5B*l-JR9jJrVF~M<EZO$171knwy435
zzR*>QOavoObSMM7kmoBYz>c2*KkmkrA#=&I1MP;}`@-aio}|+*lO-mxrfaEyEc?j@
zFE=E-!7xW<1gvS!!R1d_Te<n>3pQqp`e8&Ph7b?Z^9jWgZhh1g{VAlgK1VzR_1|mY
zn@%3dbf+Z-^gZ}xTxQvrwAAtkOC9rij(PgliZmiVInGn($f2#!pa*F9s%4-N<4-E%
zV}zy8P=v|76&A|eZ>`XY+^$lK)7EJFRUsle<c`;!qr;-SDo4uX!u*5kfL7R@Rv$~m
zjxOqY;02+PkXH^lQYw9y57Vvd){&})KvGeni90-dhEl}S3!-|k@&Q}d1&aoX7Bg0_
zWHDxL(Y|rx%&Ze)ODXk^G{%rjs^}EoDvKOmMa)9^q_K#GG5nv1xQYCfw~NQym#^L|
zf$u?smZJ6_4f;<Jszo?|@>GEj5ZUW3dQCQR$s+ntiCPPQME5J+W*GUo-51pxqT|6q
z-S_r<Q9L+nFEoi?(5mwj`r1r>Z1oRvKr+p>21o!5b;4!_=dK|UO^3X0&)!R4V1a<q
zulWNc%`A3a1Yil-W1cMGO-5|b_ls7(P6KVSGpT*}j!fKfS;6bBxPv|rv}cCH`_K@6
ztUG(eAPpcg*e;|DKh<gs&1Vy*eze+CN6Xu+x;)}1`w=X0X9yI`kryS*VtX#=qQ6Am
zmL&zhF(j0%m*?mQ9($xqoIm}PqTT%j7n2rb$6bew+&!=jJJ?6)r!nH4EnM~Cf&`8<
zH`D-q<)DUk0lCDtch4VNov?;)BtRpLC6(wTSe&brAmz~A%llPUe5kNPfi=uyLD|5z
z+(rScK=DA^4Dt<r<-Qayt)r2HgLX3@nzN#5BlCy*hImP@(<21`8_ff~WIPK+xu^3C
zJnx9cC@Yc)@&O<d-;oz)TMw{sqq~w2dEkKgLKk4k!Fs^|8ZlbD)nG%!-xxndezyXA
z>$o-&-`w@`2((ld&Ew;jPJrKp2Pts0p;zz}hom_3EZWBcni3l7kIAj=)O&ioItSv5
z8K6QCgV!HJScJ=`>ibZ^^7?+K&oK1<DTzjaq39eXqW9Smja+g-RCI2Ka88NQGPtYx
z^B!d027J-{RUBMGJn>+xO=9A>CnfaVSyak<@}iQ7)2&lsb*P1rlwz)j2Q}_D=<0Qv
zop1O99#u{^OP|6j0)g+MYlfRAJ!%{$rPD}mz8k<beV_qurg032Spxc~9dPRi@=K!7
z;T&Hcm5^s_=|Yi{q~Pb;_lH)|%fe)e^OHQ10xwRbfOAyA3uVskh6BmH7<_2A!wuco
zfm5`NfSsg)_RDkfX};yeo!vFLYMHsyrfg)_kv!Q4U;>EX>};u8p~>KEsUJ}#7AiZ;
zw2EyOwjRdzyzb97GrHr&>r-&1oA3!MsxY389)ky&A4fxCyIIbk`{zNc>E;h-eLUW-
zC*0=g`#s}t1O9An+i#@@vsew~MCLclcQaF^c3oZ0iQKUwdFjuMUPy;0pcEI5B;Lxu
zR$?$bX&FpWihI`R7>ZWQEKz=-7t!BKZ`Eh~E?-o~O{-?m35W8RiPmpp#u~zN+Ef~l
zg6yJpu>K|pD9VjE=ApOzg!@O7Vreevy61~Z{FO)2{(DLxYv^h3>hd45$$yz*|36vP
zS5682CD4gp27Mwv*v)$(CYI@mUhRtAfuxyifNzkR6d&(o8-w*9oHN?HWxZQt4<#da
z?y@a50t;<}p83@6x$)Ju5^@%|ae^ygZ~v^fPmewnCOJgj?-xT4-PamSaNeXEGAn@6
z3X|;N)RjazBvz>-&f<9}SypRNvYZZhh^CTP7vWyR{&|llbL;PR%x!**IB86r@2^UU
zpIge}RHj;=;q^spb9OxGt+ciwme^0N?Oy*O$!DEvpC<TvG6L~`*+I_G*~Qf9KiJ`4
zrv5Fr{<*YeHAsjFzI)sMN2up^D5LcRfsGF<cpy&P9SFJitzI;Ey<zjcgi+GK85KAW
z65Gf32LJf_Zpr-@N~~?meqRzQWR>!S`V#Io1A_t&;W8ANSUH*#=G;J~hYx3uAw|xP
zNw!=4&vMF%LPtAJMXL#LZ$lKmf*XBmTd%#h#YGpy-{BRBW|mnhEK>nSX;RZk!CW%K
z0pEuE3EusG)K<0rG}qPhR{fLCQgNXjS!cAUabz4?Ip-*ubkdP4k16wp0C*ovqqB7G
zVa=(uqq$=b!;@kDQ%kuxTLiX6Ga=llHaV?Mw8mX#gO_A$G|o<>g|CtpZnBZlXe)VW
z|KNdfMo+pil5!!!e7G~>QQB}fB5poofBpZH!*TwPbh!WTfyebf-VSvCEdXNrx5)dS
zgh2n^A^w|&VEiBN5&yj{iQ}Jk_<Ofz{-+)OwgbyQ?eMo9SpR8<zwN;GPdof=hyR%y
z=M5(p6V_K9==+yGPyCM<#NXQJza%gJ!X275HsUte5q%kE{RtP%zyHyw!P9L0hPrxA
zZ$xn!BU%@#SR_3cmrE?@SN)#jBNd)<JmsakxZ$erQ^*<4ax@7mv10GWCZ;pc8O262
z*xm>yniZ6)cFV}T&2VI9Qy{-v_A`ae#N=GcybJ5|ZNW9$t+}h;yA=tNF^hhP#F$Pr
zTU%YDMk=<GW;qEw?>lB)LqP9aKQ-3}>?&K!w+;C3*c!1+tGCYQYgTG#Cc{y3a@cdh
z4#Ew9&ra7RH|+0x5Z`~7fMA-wFOoIb6KNBQ)6xiyl~ASgfK<Nwz$oAv!=j?XXcvL6
z)L#L$s)LnDUP$y|YA59?ZgjYfK_!AuJ!ovxuY1?l*tb36s(q=Iim=umj5aF%IIG|S
zH6*tXu^|gvQ7Z@5Ilw#?9L$10yWc=ba)MAQjxnM~mW+JejqDqy70z4lfOh-$6lZ%c
zNWAdlst37<hqyvkHVpcH7!H-gv%vzV@!mP2x9P-E2d5u3TQ6D@m*9gNbpikOiUhCr
zt1gn#agVaP_zWyybV1qqW9dZlRk<zy*6xN_d6d*Z2%pmjw@8Ey1%Fbwp?c1&{)cRV
zU=Ig0Rf>ffGOhoyz8M9kp<MI?sAdmUI0#`?wt<#)KI0NY(V`_oIj9g3;^L==boD+8
zGHhZa@-f{X&^<{dfGJeM3SnHpCMKbj%C>Rb4jz$=x+642@XoqET9C;@zUy7y8D-N+
z-hNOG7F|D@hB#zs0obcTlJtHYYG`9X&eF3(Pop2Akg?LUzx3*?TaqUKXKzTTkBEy5
z0(6hEg;d*oyEm~5Lzyxv|6O9#cZ^@lL8!3nsAM|AGXWaPy#T-V+NbAZJ$-8PTQ+kX
z`ek#T%U;wT?Of4tKd(9DTi3{`dO`(i8Kj%_acVG^R0an$qYmb<Eah%7SE)6vrFepk
z(kk;UQWq7K+%r!co&I}@%Q}Jm%KXs8qwLI!!!q;N%*>%$YqR9l{9kb>>(_79OfFZ*
z!f0x8hf9ND$(^xXq%&t>k!V_Rj~UetJ*?d|q=9KB(;4Tj0<Ao$;&o`IWFB?nmpGGq
zpmdYHE}iL+&RXKaQ=>uZWI}D(F9%2rr*1xU42+7vcT!fWm+cPIhtH&OL0U%BUA!#G
zllfU|v<Pw|Gv>FP@wbF-@LU^Xqc~T8HdWt0E@t$5{9n(2+pFlU_yh++9TxgScdFX$
z25BgJXk~=mu|>wXJ~r>nrA*`x4GpG2W**D6cr(48H5|HJ-<o$t<vM#)2N&U@XUKnd
zP;;KGN`FJEX?;oDuv#-8&{40f+-L}&^NrrCb?zpW?xK_>UNi02zf$(6u{V^88@Ey}
zc%!qsY@PLTfM$S7_*7|G9IzI$*X6ZKY&ctqx!(DLjsINu>pRHGc=^%;4(b2uT>E!5
z_W!L3{0%JsP7OHM*0nnjNA}YvbSKOh5hS_JM;3>t)f$K2m5o{D5{$OdilIu{u<<+x
z1v-TH4&Eg0wC5VnAyr%2LN%3PxmnlK3<MG(@5~<h^V0K@y6xxPH2K|{{<MZRto63c
zT&GKNoRx+?{6PU@LEc8E#YAlUrg2x~HErdgO+x?uz?QAz_Rd>fhMqP-X%U3I8ADk;
z*se_;-Dm8S!*mEHBRkz_jC3<<!j5_sBB6V-)2<G~EuEIe=Dln6=-G*X2H8)Uyqb)m
z1ew@ln)JL^&qU3(MD10w8njLbman^^l!Q~?DX;v=->s70|Cck3jJ=>tcb+jpw<!oW
z1;NokhuQONo-ViB<FPFULEz8}G(l}OOh1<%+R9GkX%{z&M{-v$KMEm==(>7;T7f>Q
zAc_~(7J9ub)V9alyrfZZcDv?&oFE_iIih0Mkb*}9+*52bGFwKCMDh@V&N6xQSlW{A
zEik9{tuk*a_uTuzk3&w3%*l4ww5AY-abB?6gs9_?Q>IxXS8Z~Q7PS-yGu2RTYRVDF
z;oF1is!%d}n%N}L2Cv+#kX*E>m#jN$_AQGc1Y$zG%Hi0z*=UY?lukQ=pPq|J2Tytk
zb`A{ILa7zM-MhYNdoVSFDUc!s>gF#i)3M1w`nDum5!#EJdPN&d?g|*dqeILvNMA?W
z{=SUzvUtSX33r$2D9l|?vzVD=H#6a<4|KW$r9n<$X-1*4U;xwHxRy@4mA#bgM%K?;
zx%swzm}3F7+W=I7#&00PB@%ojc2w@XA<aS*Nu}PMa*)H~0GB0uW07M%mP#fQU7p$8
z3_&Q^rxf6@m`?gV(Lt}oT(+LTy+@=v_RjPU)PmaSqAX)Y5%zh@EF-#rFU_!mRVVw^
zIN}gcoZwR8WE_bjdkeyG9KJnaj;;J#=oc_e^NqC;6`nuO+Cv$pRXnD;y&~+fxT-qA
zVd^h2w`=bSni)@J^vcv*>%2>%JkAHeHAb}TIYaK~72ssSiR_or<<x6btoI<()S*tP
zh{c-S=4Y|g>u`xe#wILwNy12$3pG*dGgue>#L;>)lsGgVrU5>th%iGyFHhM8cisvp
z5(6wQhsSeTH<HMxs$5Ayg<~#{#W-zm2xr0uXW9*ymy2q7@E^F5Q|6g@%d{hxV5(hi
zwj>T}<0LI2wMJC1v#a%AN~rAGPJOLQ*%rV)P<EoaXNqB$#1r{PRHn+k!^Zxo;(0q*
z_nT59XV1mckhpf{F1W8FC=j?#yzg+pbY#d>jB;i&{8RKAL7(-?dvAJzoBNC}TNP&>
z)*3*UBi+2;#XyIN%S<C9-FPMw(FB&s4-;4sqdv8nfb3`83X71+RA1LakACz>)wbe@
zZz6mwhZ)|~rJG|bOpMJs+~7{;>Rf6}tl^m@jd;_t6n22lZH!9&^iNoT5AJ*A<@)@i
zr;`fK5T6yhk|!H?K*@RHF5fj)u|V*AFnw%-?1t;_#2ia;O&XCqY`rqt1-u%F?@nO;
zesVyd@Bi|YPjR)ZnwepQ&#YYWTEE)2=|a|6_<m-wh_K}dD>QOlj`vwY;2KwMIGYKc
zcNs5neZ89f298sQ>z@EA|2^Ej(k`%Xx4U(SSw>VV-T9fEDqVN!^H}{i1br295mmEb
zPTrqlMT`L`;9dluKR7&r-AZ=GZZHyz-(yKJcACb6hQUDHpyVJU7DRZugR0j`qm32E
zCUAa8*X>4;LAl5ng!V9!FxH7@vE^X}GRw*J_uqwLK}|x6a<QRhAzd*=^U~A`Vm-~Y
z9-4kAuo=`cRu|zfQgza4+~`&%0(uR_DG40#1a6EO?p_rY5b9Tmw@W*q8m#F^UC&xN
zayHx1U6w|dJWr=v3i8dq$L;W}1RZ9ztQY_J29xRB#NJh&3C9OoaA9V97upga(v;Rg
zhJ(G6g4446&`XGs6&3p}ocVYLavL!160Th}+c$x8YP%>2V<j<5=LMO|aSDol&<vJ$
z6*M(X<jW>UM5M+O+O%Lq8sHf~(~1V;3zMQL7!T@|ZeC5C$Qj>wMvY}y9bY?*oVz)n
zNa(3MGp&AE=r7&wIsqdx0r5-EF|d2Z_trv9x24g9lgKVbd7aB;J?w#FBA=&S6p@g`
z)SaAD1x3o&oVe1_NMpLYQtjALIQ&;$RJv>qyzPwpt4DnefCH}TGy_OQn78diD7EUy
z2_o1M>NkYhhqT-Xv2nZdunn6YqaoQ9Q?r2Yn{I4tfil!jXF;{|psM5ZfU093bZVon
zXtL}e5@62RQZ|Plj)3179=f`7-5#7Dz6kIfe)JQb!kma87Xe*txMeMy1B0=ZtlXHq
zf3m}0ZSu~ct_2ZU@%>;Bwu<-+cw1K?xckf_X%!+Mf(ou7mpy)T6B4t3e_t|O8_ECd
zzO01@g8wNvh}60ZiJRZGP&m*)mt`DuwLb+SH0vQs$NQ2f(tnADAg$h;04Y$|Dg5=*
z*VqWD8+Iic;lFF)m-!JvV<mb+C2+$R&%ImXKbw3BAr~#JQp1)CQefz_gpsJLSVFUE
zzpo4MT2v`?|3v*$72}x}RI0W|Rp*s}mS<_i>kH&)@v^4pG#78J_YCsTTnu_c{8l*b
z>;eiOE4X2eOyOoM-JwTkBate|HA55J_tUN9BC$?8q7HUFQ9@*1-1M_L$c?ns5V4!v
z(#nn_(~PG*<dSV=2WaoH`S9^X;vaVmCCHP_=YM4+U`YQLaroawm4Ba+{FR$dYJL$1
zc0@mhSsujGCgQVv^dwqh9eQY!WP@Bj0LffKeM*IL^NL+VpI$ZJbe@Sh<(OL|l@+S^
z9!7Ri*r5GkHj%l@vz-c5<6#w@sjq1}21)c4ce<FCfW8(1fjN7NWVMzqBayYAsja7V
zcjw1*`2@M8nBzpNQz_JO#YTv(mdy9;pN{K3V>HWpqhTvoc0_7Jth`m`<%;Jl$F(5`
zvEqp;4UMfY_oo^6P7RdK{Hf1X`z?P`DCsl6-!2+$)`fJOV_L<p(HAq87>G`6L6%RI
zVeF7d%9a`Tv{wu~`7yvMwZKr~DTNM;Xn%MvvByU_qgJi-R+(+{Qa0_|y%$Jo6@>Yf
z{=Q@IV!G7~#)Qq$n8=5aqg|s_b@d%Xb^u-brq#EC?r(@B^CX_!l|A{`^nCLHx8{@C
zO>_Z^0|?qG6LekBx+~_|HjqDpbT?O{7&kciJ}J;rl4d}WwUe2?^Buy}f~Cqnt>o6L
zHg#?}+U+t{CXDR6<5_^~QA|Xb%cAE`=Xa&uP=<Hpkp_$cfY%7z{#->eXLE<j7O7YA
zxKXs8Z;<~Ww2Wx=kr&O6YxbuQvH)Da0G)nDV-H*Z9FbvFFJjK%nA6O;6%?hz{D`y=
zj8gJTt?G8-by0<AY6hSX@I&v^E_(b7BLY23@uLP%H*j}YNW<0Z+Zozt5SiO0m9}zs
z=%V!{6$w;P_K>Z<i|defzjJXuWByX494H2?=m2_=N<&(BzLY;Xvt&U`J<<971oq5f
ztdT7aL=KWei{Hm`8tDmNrxGH~4Pb~78Zl98{_Hlh&|>%ik?xw%5KWkuA|3+8bMhla
z)no<)8wFE<FlsJ$WJeCp!B=r1D6Q7J7eM^Ly&J3_3HLHMz9<AYjL9Q93daz7@ObCj
zZotW4<q_zDY#hNkzy33D^#&jr$9M1mWOyx>3_Syhr||7sAgta}n*7lUV=Ouc8i5En
z=o47T5lP`Q=zxf^m|;CZG)3_60dPVaJ3r*>!;(llt0Fw|6$$jaB0T>7bUlC=j1@4=
zN`~ln>PaaI$Ql$Fn$owRbovND&W;4zlsSC3q&KVi7W?SH$PxGR<tM7*Yu4{69xr`0
zx`Lizqh|$fsCmi<5FR|wOgJ)KtMbL$^Sdx`j!c*#kX+w}myQO2imTSO)^nHgn_ns2
zuZxU*oAaM>XO}XJs|4wJt&lJf(q_s=*Y1+i4$#Wzirtv%e)>#cJg`6CWOTvp1hO&~
zyhyQmjb136+N$#Oo`+DcW*y+R2K-Mc3Y5T>>^p{2`pa54btlc%;9>_)R`Xu8tl}38
zjLH{i8@C9vr!B;r5;{6FY#W?wfVLV6UoOt{dwpJC9-)kuQl>@PpuZp3!n{iuXN{&(
z6Ftwn;CiA!Qyqb`@MOdpznY<kKG5C;8zjwVN9Owi?Z)Dew(plke|$gg^vrlG1gRVU
zHl|L0Cq_?GZv8t~-0!d|QIS)G<1+3=0l2K{L08%sTTxnW%Dz5x*<28Y+<+mj-nnqQ
z>Cg`jf<tEa0OY3t>L%k--x2sZrd~wB#o$r&+2ub>i{L8luUkL>fHau@8r}X@q-)go
z?7rld4*`QqL5p5At+ew|;q!r{QbWNkP}dhgjHuW*szegYl|PCFbuE1I`6d$5(%Fk(
zIcxqV(H*ZIk6YIVy4`DRu(pw^DQ(Upy_j4P&0q|cubl4NJ4bfE2umGxjD~fX-5*4`
z?9qEaoXCuZ#;v=KaAE<)YD{@NEz86YylRUj{ii`N^8;;B6X4b!squPL*Ajhp865br
zWqQGuXLlbrnErZd&4e_1HrVs0@S@0JY(ML)s22ms<AhL>C<7X{XGG?`f!1!q1@KH_
zf1&I7nge-aSgRMIbJRO1u#rHn3Q^g!5o&>u{UIY7Zr=K!AJX2GI&*L8PL4<eFMo9J
z`Vg@<)7N1P7TAV)907tF>6B)VrojclvfywpF!R0zrNB+j6&GvM^wFU^-2iD7%f+jI
z2!kUGDwiwVESfkTaTylj#>4wiQO~6UU$NHnQLOl#P%hOgQ}<&H-hkX3gu!Z&sSd8G
zTlaD9hG~^%cQL8d9g5+R{2Jn^C7RPry6!#?Nd__`))){DF*{RlX*1t(xiY&NE05Jb
z`^4wzmB_5^BbY^^tQ@;-R2nJDj>!oQ@B}-zpp-|DTEBspdHVy_IEFA%&jQLP3hB=S
z?JsY_h`8pC(qa6Akj<P7l!-r9U0YZMb}~Oui4tI>^B}qv37g&80$Obj>rSgpy~ku@
zx!@tDv{JI`Ada<$>;~Fp`hs@#$d)=%3{e(WCphyge)@8}JGe5ia7xHcIi}^!gX`rT
z%I3MenueILBn0=7u9t!xcS|wrGf530y3E?ix2Vn@^CPE(08O$-=}&Jlt87`i&@p+j
z;~{u4qhqoKuUoPyDm}|ieq7O8(?YZ+RHfB=LJq$jY5P{j84&fSFfIJp>}2QN+pbRC
zz{l`?7g;7O*%%iG^JDk=Dm!-zWonwP+Q+&96c21DS21jEdg4jnXx3a(LAKoORZ#kv
zCH1DR9U~Xeosd<{Lr%MSlMR-xygG|Jnn@&&%)p|Y`r6|CpiQcTR*D?)XQg@SSXbzA
zob6Jb{>SshS-StsZ1qDJt~kXH#9Fk?<^g$D9I3r4vN0QOc@j=1zl_d3E4LH++moMD
z6hfF~Qq8i#=PaP~Z;bS$4aQpprUH5c`v@e4A~0iUb$4R@ICa@{eEkB*RGcjbr2?ns
zi*#X~(*$DutRW+l%|Jh4l;C^WwKbU!3ZXg;Zs@*bxdeRNK~~uJ{B<&*Tl=H;+{iKC
zjB<?6f7l*z4P_Q{{>5mt{u_+u@9N8>=Eh%)=3gaNvB&7p)#%Z*4d6A>iY9_SNf%mL
zS1K{@3v`%s`<DDB{dp|u=3JYojy1wj8RF!@OcoaNQKFe0TN-(GSr=24c(|iUcF5}6
zGRm{phU+~yyJ7GX((f?i*;%o%cxN&0$prqK_Q`P==`JfZWI%YX>9Y+DNsV%})e{;u
zMO#`6jo622u@w~|`TN_{pzoj^G<NN+c-m-m*2bC)@>)Bz>88_Way_-0blzk^j?_T@
zZPXj`*47Gh%h1b#*ex$ar0v%I8*#sT8MQG*p`zemxrRY~W-z)4*}fYX^gFT2D<(j(
zZM3unF{M;<2t>QhZ9}#kTRD?_ahfE<217WM;EWfoU`!v)__Q5sIo36LF*dGpDA8b>
z5pYu5@Gnjyx2m4hMKFm_{CxTXwdRw`M`UXW5@2ADdb9O_?|T+kz12=fX8v={dnsC3
z(`)S)0gp1rE=9*qXS%*^GxHtRQX9>DxL#3}P;I{I_3TY<R3&&vyy&lvyn{-Iryjhx
za|xlyqS1T91Op3P2A2y;Me$~G#`$VHly<pnqi~|H#^VGo?W1aNO=?FlIS&d9rxBu=
ztL{B`LgJJi5iCaoAUWvPH@L74fno3r&}?_=Ypzg8#c7D9L21cHkyu2VEJ4X#1j;?s
zv&5ytaIi&Vvho}yMph3B3KhLWf=C-k8fmHR1$ky6RmegwAQG$e@i67F)BP~$sH-?O
zV|5GQG$QDAZ#2Zo$=-5;{jKx?I;YF9g`Dr$@I!*%T#&28j-It-`;KuG+50Tza?Fti
z@YW1Le<_YFsNEzW2HNsCvYM1JG^#*4uAKQqA)=wBR|!sZ1muDXFqONX(X7g&C6Q$H
zrL8Ks!!bmAj&Y4wZKcSy6XJ{q`s!>35$2lGy(U5$(2xt>JPc5$N_ZL6wv~`S)Tk`F
zCU)>C3q%0GLS8|C$iGE7Adz&yjdp`<CW4syQEy(M?GX<H)%pjVc_ao?%EK^tl|f!X
z+XyCrZ0|zapATpJYWpHi@E(I8dMmL+UG_)}LAY1q5*{QwJl&gm$q0~6eK-VH#H$Nu
z7i`zWqd=F(koK6O_D$P}CcP*Gu1Keo5_k1u7YOdZmv6lRyvM3AvwX)udCt?XFFE;2
zWB56@r;6{}&OHgU>w-<qMLv}?uOFI&;+ml_0_fCEzS(6RFk6+!{BpTfFSP0cs^7k%
z!uaytocDf#@y3UxWoz=zMu2T$)phEQ_<?~Lg8kUzV-0hC7WiAL>CoZtckTMK7S;sQ
z@)Bbcv9trcAovHzlZjTnK>4vQ%lh9uc0F(D7CmXocUsTBa$uUXk<an+=bxm9rX<Lx
z5wr!NM!&3dxA>x>t)6<*YaE`zmK4Io*}7-hdq~Zj&WYoK)<$zYwXEWl{jJKHXj$<D
zvZoGcr-N44oLfa^tOebv)q4G&&&t1`(hsP%%1%q)&+x4Me0O=SiswW-MbXES8+ywU
zmh9-sc_BZR_|^y?{E+v`$3JTrLxtfLwohk7!Kr_7>TSiygD9Zi-tJy4GrG(=?S|H#
zy4oMVe*F*y#TEpQxeJl=;cBvA-JAn9s4v>4t@n}2=5(NVE(pe>Q{xexetY4;tGLy`
zV;1lsf&(u?$7=`}Qo17y>N%rG925A5^hl3RM|I+h9!-7GqyMrT^>+tHjk?lT$3CLp
zSI54f#Y_~fj++UQo8j6#BcWW-+7^$D5|WbiqU3rD2kP<8x}UuNSX@fRbR`UDtiDM!
zw_n%mpFam%U27}27Zs|qtSk&&*d7t=qNp{VIi8p7?F8PEmYb*<(P7hFAZpv$&ocsB
z&5`><bo>$D#RKLlKxew7&)A`W#i+H7UCFf9``VO8vH#*nLPTHusMeDa7nWQoR_oyY
z^*7h6m=?3JMv#s5`Z2tyava-J9rZGG_;OzGvUC+-_z%CE6oGaGdc<6IcX&<iX210D
z6p>5gA()i|91KnwmzW^p3rGxBKd$Yuo({{B9cihVNYkrY>)C_Q`j&eqM5LzStQRW7
zvA~_#Lkkeg6AJIf$8mx~BZDblZ$DIh&;tuXk~^cqY6yx0aH3tJk1pBLJCu&HDMby4
zJHX@0h4NST1@Q}eP9aP=37Jn+70Xcly?O!yG#l_f>z?~wVrMQ03lq*$tFSI~^Iluq
z8NW7vPB*YTot9UA)V=|*KSHk?62-TZ7JdgSD4;e+;N2_03l}?@JkIA9Hg(ssj69Qz
zph8|A0~ZNF0(u0xY;l{WC3T`J_zMuBeE=TZ*a?xP3a>$=zkis`{vcEitUM3Gp1s80
zV<avYal92YpM$IgnFmlUEQ3&O;kbw}vqeztI$wnhC3bpdI-{Kls3Il1JkF*3HNuIo
z&q#iRpDDj=;)Y8_v5!lR&i>wBT(eMj0qAlH<gvB9drCf#J<AR7libj+=i}nIxu)mw
zA@$Q!o1^0Nfu<W$?&E1O9wMjQ`hhHbwg58Fl2ywQgi4vh!spMRYT(=X)SgrT4YPQZ
zUMV}-Hx%)s&$x6Y?sj}JKW<F34-3RnKWv0>zmAAvG4!xxp&b7kuQ3`z)hVm2rjhR@
zk2=noITYFpyWEfx`qpUE96AiyNewbm^dU$?pVdip#Vh2ci;WZG`8u?Fpy?R|NTrvf
zv!+;?oZ`zlXsBDZXOA-;So*@>4R?W$lNU8F+8w6M)`)xX>&iZ?Qc6EqW7GUP#>xFK
zO{;mQ_ib>)71*j}f5CaU+g18Kzs)e{^M85=YPURA;xz9H|4?&aXmk5mlLntkFIyOM
zz!I4VRr(`QebUl9N?|NO5MN}GIUN0)@)b0$%`gQ~>Vox2XHKEC{%ML-i-kB8xwMD4
z2)-kc)nZ73TBrY96&wC#&Mkbe7Dw1Seq_(&v;?fHd3?Vs6mjw^hRDD53|+j#mq1W3
zii*55TqwgBH(^o4$;zJF!RCK{m5Kgy0qG)XKhXP&HCZ74*O}7ay&C8LK?f?*pJ+@l
zL0WTCBFqLoI|ssyj9V%dO)bImjs|<szHodX#ZxXi;GAB!yU9owE#rqb?|I&{kQbn(
zi9!#FPFgZgbKlpFSmdG^fBBev@!@GThJlJa16EN_X0a9vx!-$R(U;E_o!v*STm43y
zpcD<7uf;<3B?F1_lc1qf)DW?CWi#s;LJ2%~t2n#?8fi|SYH_&G=&h?aW)Rk9$`+U@
zNYZ9#z8Y5{DNto*^(V*0F)gQv=CS2LBj!5ut4KBAG-(J{@3->N=Q(=<&}O(H7H*;F
z6k};LfA|_$j9Nh%-O<c#Itimz=)Fy6OF0kT$5ju(NthOry717Id(ZXX&0rf`?b_J(
zawIu4=G>gVp;GjLYUgR~)~CL}WIG6_A^*NG`uLGGQ|oSUtJMl}kpUtYd|$YGR@QRd
z&eg+o)S8k)Xm6_q^92P-zx6?@uvRN4?WZQ{(8V(vwIc1!DvEU@PaQ5~ro#JSc2$$f
z(y3_F$FF#v>M$IILvu#a$g&U>aVQ9JKLGEj)fMC|@1DR)x?@CSm_<D#3V8^Ynf^ja
zM9L}1zCVSL<4Rg(C=<*3;y{mFh^2Hl4dMiBrPLqxK;^+pW5cdim7kas1Bn`=$z4Po
z<;`Ny3qn4*wTCoD!DY+QMF~T~ulr#(sXJPWXwUD7^j#}F6VIy5r|O`7%)%LIwk1G!
z)*n5BD;3~bkXiz3bKuCkdCBF<VJt3K1}6u}qIFCA3)mrm*>M1_jxYPdvNb^fHuWH9
zc1Cc3`aS2GM^T8c344NN008G=5F23d`dSYTSoQd8f@d|{7AWeBJ~zeKg}q-M6nWY5
zcKlo!sU%s3cdV8@xHWz;&|6ekL2~*OSgDcl4sgvq5r^o{L-V{h?<$N-<U4uzZ5m#k
z--hMJz&&Q-ME=Afy30}*#$SDfmBJxEYhriw%&5B7^7EuxSPlEV-qZZN%32At7lZxB
z*WVcE+~}<?$If~i@)Q`JWe%_pB=MdsyHI_6s(rT&f`Q^YRo^MYyK@TUDWl38z=(Ol
zedfUrvs^?F=5c+Wgx_RrSy+9%xFd#VU`AN)_IR5*<-P@$O*Iu8{{5bleAfPQ7)WDV
z4YIwYgOJm602ZIlm{Zr<bD@iZl^%no(*0@%v*oP|v&C&n?Rl2kdzdi@RaUsYphR$x
z(Pmm=kC{2!NO)|ew`F^c+zrOS2m_eosa$iWA`qG4Hv1wme;&m_yirXm`6LGmbK@FE
z9|mk#<C-|nhPJuQLL0llFW}*p2zEZ7FGe2ycL>#8(U@)l$1V(DKK$%2EWXn+l0B?=
zq92T5DYpX+cyZvquSU4{=Z*}JgNE4pu)*gzl-nMLNzO$OX#S{MeW2+1a9mZ)N3!*m
zyklCwn-`GF4G}^(Y8F9IW-iL;VPNHa5J!L#ev3DJd|T)^Sst^1A+N9uSLP{yBeAQ+
znAO<>J>)_B6zN{<6NPxID2PWi?aV~X{l~~Pe#=QB@I_+Uzuq?d52f#apkV*~LO_kW
zj@<?$;@jT}b{p}Tp#-`SL>e6i*o|;5Zb0F&CZt#+>BTx7@UJi6a!R77qLNBRg;e}p
zMQ-oh%*6Y1dhDUY(p)I55ftBbRd7T!9!W{#$8u9kf8=*cWXs6Fgpw22g}1bQ{d5pc
zl4+@)x0|bp1IqMc`f5}Mi=>Hg)<n#@1|g&b_aRMqX|=Dq14=rySL8ekOsS3o((0RI
z-Mz-;HO7Rg*s*Mat6aNf5aoD%;M;vwQb#oT4vHLg6;aIX2M<|Oa=@}`*qrmU8@^MS
z6-aa;2l$;yzw}Q>IGFThXfBq{;@_o3i~QG9=42Q*!d&4^Q=!6YmLSb>db4)TW`9zH
zv3NllHtjnkIXCFl`1l8~90FTO5Tsk1dUr!uI@lsuqkmbZ)=clzlU47-ofYr^m_2wG
zi>wg4!%$ouu<-{ZRAaxy9TXuuwtZj+?I$>1r`D4otx5K-Z-wSR+uWwg4vL#r`YK5#
zY@C(;&|X<TxkqyvuhUM(DM>(<#Iiub3kV7fs;{KHYQW68+Lpx_&HBpZVJT>d*(D-H
zq@@a#YvNQTr~qvOLwbUqV^YfFB;DKq)4bh_nM5O)J1~=OnL@_Hg?^GV|B1*k6qy4X
z45<aBAquu2$Vmey{0y)TT$=|W3X&Fv*i^EHxzfjF*yGo9{gf@2;^&M(5x5i!C3sBQ
zoLQi}xs}S2jbg;Tn}5z-LGJ*qD62Z@>d>O`>S5pZmSKa14`%eEhRm_oebh-Rp&9!I
zNfUY`7Wt@@QmQ1U*7Lm~2&H4dCEWyJe}{qOJuVTfS~_Za`Tib8FUj``co0mu_p5md
z)_d7TNp^nl!{&HqpZGD{lllHui|J~xBx7oUnC`{$sY1&((RuVwx3ce#&-;_Tk4OCG
z(+)`vy@Hi|i(~P5*Y}pH-J9Rf4v2CpKb#DiACuRvX7eW@eEqlMlTEV9lP$k(3hgt?
zG8a{3`{<9m0T1q1S88d9LeZri21IaM4BHb9xmT4`Y=XjjUtsPSfYX^GmO2Vxi{}Or
z$*gE~*Z>9P=Ca!kEK;Q%;aKo-1|xvaelF5UJ&9U`|4fb?+V*vd`TU0|gqE;j&>9#3
zz>fQ0N8jJQjptfhcE#eTJ#~xjf_GUh5R3*i)6^f;)TYT5*Zh5$!%Vsc$Bb@C>NFSD
zE%8kX^UmPI!~UH=$A+ZuV`HyJMxHZo9XXw^Kd9tl&``uCn|h?STjYXGiQ@Oq3+?@K
z<ZJp^p{1H4$a#%@Z!^&jUnlbYJ4U_5kaZW#ds4t1OvK_Jrb1IZ>z1eoz+^11<Bn*9
zKM%i^s17Jx&qjgzg8pH(T)Svpk+#gqT)HnByZ7Ob7h&JuV>ZpCl>(Ki0DX-X%fZN^
zvmZ!<Q3u3!cx{kA=LEOiBr4>W#lN{dgj-V9YxY|j=>>i6`66Rs$?g42DCa_R>}R=G
zNK^nbju=z#je6tnML7-1Udm<MhlHwvnNq)(08<fQ3FsHHKDvRJ67^PaPSn$z#TOm)
zIL%IIHh&9=wutAGBB50X%Wm4+e*mz5i$N&Rc>y=*e<@42?7Fkq!PDtvi8UR7ZG5N-
zQT}n46`l`Ga`2_Q=yzaj*RW!}#N0g(R0zkbqSd~s42c}TL{vhj`CwliW8vlZw{c5(
zOA%fEb_S*jI8YN-1-4)?y4{(WU6v1SbLHfe@-~3>5o|<`a_wV2JK$Rsq7H{DR-{m?
z`2CwPa!?`c7kIRhrB6Yq$v^@%G#Iu6&^fZQmQo{aM{!UPlFlS1+<GuiaP&F>CoPB{
z@A)+MdB$yLNSIB3G9+#N4lxL(0!kW94OwnINo1eJ1+7%ufk<Grs}#3<I3k4HdX0SB
zMXMBGKgfE~xud7tCX6vfbo|{(>Nw&U7KarE19#C#U3s}lgKR^x@`t)Bk~tD8C;tAH
z`2>z4lc{7oddz-Zk7cLDiEO8q4$kRp*pdp8RULLi>!Vg8^aX$=7tT8U$9NEV4e6@6
zSXI>0Rz30v1%43D9Q7|Z$b{;mi$x0%9!2&X>F950-`fgXE&#F~p)I3ob1!V#JFbh|
zyi3}@sw{%x=$zOU)&f_FHN-Z)&w1f}s!@s1my+FQDMp2H1gf>A(Yrn_puvMlKz(Z{
zbttdMs8+KXWr1qxATyC>+f}M2KxObrF>qzDV6HQ%Nx}4~sbbs{diM;1;-WWZzuxM*
z^br}(u?rV;BrJ-Iqr$49u)36LQ7TVr1P>6QBX=bmMAkND1Jr91TWOY(TGxOB)K`4*
zqN|-^mjHdIM*LBK4bXgl4~;y358B*+4QXISJV0prWJ%ULelgI>QvjdiBDI+vjApV&
z+Fx2Gq&7oIAYdIbb*KAacMD>)Sxp)WAHz{Bdon~Av9azGQ8w}fGYE|$_BUl)S`ugL
zE^Rz2==t<krvBgD%qboG=_><To8~#uY?r7xmN{oGnr#^|xEqYSv9E=mr@OUxcpt51
z8S=ebdQRR5yxA12*9-OJTExpI)_YQ@a(T7J<L<3-sCXW&F>fzEjyCJ?GEaPNW6j$N
zxgV`Lg=u!c-HmUHAFO+pTai+2&d3%A;cs0GX<l0-2LO(*t|=*(suDXAOS<mm`VLMk
z^{N7kukW~KbDUZqJeVCIGw$E4XIn?o7Th3~3F~dG9ngMg7y~ci%kpP0C9nZ&nC3J}
zz15?hyHUxR*fXOax4xk}vR|S*_;=me>R4bRq}|>_9dT-YkLP@ElN|phywUZ!OSF^e
z-b2b{kCRv%H|mQlG5JHQtSR?L#r2>y293=H;J$y>$2{yNX|`tN+`|VfIaO%|o9iHO
z3Gau9H6yk+y5mT(6eIj_Za~e7O<<n6f$l=-%l(8vuh09<B~FbRTgtKy&z0a0dV|*d
zYP|H)h{7lE;97G85K69nd0O|y`|s6}D-Gm$Bd+1WyH>|B0>OJ+j^2d^Ry!wc73-ft
z$==@TmblP*SM5F+H_d8xel1QPqoUKsEuUiROXTZO11|AD7%km#i*zU$l`p6*jQc@0
zTa}&CA`n=6bpsU_@Xwcp0^yb_aUYHdV<EQ$XI;B@+@A^l;l6O|uEvG>wJ$LJH}c89
z-xjO+k1G7KF8V$#v3}IQsqi&+r4}RGMuG3&ADka#xJ4pcQ#o}<s?&d#g@-%yvHbcS
zE|-_ccHpXwPBPVnX%T|vm{~HkAo+U7xBwEn7=#WrH69e(Ojq54pz&3B(+YJ>+nlv+
zM+Rk#;w~Yvr4mKM7RO`Il0S=XGy;2TrSy~s^ZBhHK5)WfaFl5X2cDO>&^){T{+9Co
z+bD6^MtQh82dxNbkG2^2t}fkDji&h&wK=K@+u+xqT4^Jlz!o)Z0UK80p(ku~*$Zge
z_#-W0=&Zp3U+ic!^Iu$OGR$RYr$nZwr-3YC^FuH0dQ;Wj^ljU<mt0aPAy!1J#qWh^
z$@(ye!3e|A7YfjkVcB3ab@Y~y_(a)>;DH<a`m3TMtw^MH=m+msU0poHI1J?yC2+0)
zi+UbZBRw|sZuSx7L*5c%<DZ*aOA*SeUMj=+*2*b=wHIVy?9`%RuE$(0C9(d&fLt19
z6Oi_&eAa$ZrRum1IYFSK3Frcw$OSaoTn*6FqIkg5BHzWHdG_Fqil8Fn&I@W3u8NvA
zily@p_($N<?VCbnzC`d?WGorcw_^Ro;;&;tVI^ku4pJT`gt5q|AIh&+^~bVIxODhc
z+~`ArAoOQHAlec#E<m83tynX%W>#RT5ZRe&8WZeknbeVOdj5$8iOf)ndQ?IiW;oIX
zcahE_>{vLDh)64OQ$=2>Qp6+%3~tY)UU!XlE8yCL=eQNRgF5&%X4po{42sgQFuFif
zHDE>>s6r5K9L!0JY|=AwH#6<BQ*Kt()#av-NlrFR1!ZsQ_$Xy()JirQv;s`Ph>}2~
ztuNncMM!=%0reu%_Mw2*r<pMkn{wn{DJmz({DRIxNSoI?o`V%H^NnJ!&?FfrAe@jc
zuW5wEcIPKDkDL%~5FTMsbHE=U1Hh6u{$H2d_=u|jR9+boQA?nA5W$_qM4myDuj^nw
z!lGRKlsE*WQZQV6fLE=*nIhtEPKx^pytw^1h?)_R{dy)5zckK-x<JN2k91a@W?W(_
zsRu+$684pLRt=^eD<FyNNNbU53$LM`AvZ}<OhIc)cqPft1zA!Y+%v+<eZ(e};?=-)
z7tUmnNq7n($!K@-@QhrSi$IYuJ{3ubItcKS-Frboye|Bw;@}k!Uze+GGXzOeU^x?x
zj?rdr{{f--1Q7YHOo!=Aqi;i^DAbzakvaSslt^_Rqc&NDH#17aNpIzcjBMU+$HIPz
z$@{>6h&}S3crba85L1dJK&-3&7kTd;*VM8-j&1}*KtMo1L5PhaRgV;<MMOYEK<Pz@
z2neAnHAo;TT|^WF6a++?bQMCRB|s=g5s@xIN`lf$A`l{JZ*$JQ=iK}K+|Rq;&-;De
z`{(U^*n2Uv_RLyqX4b5=W-=M)lpiQ;eYY{MeXF`uPJQ7z)z;T!iR-c${PWEP(QB|(
zyYqNOsO%v_yw>H&wU9Fq40ZgFu2`C*Bk5e^SDEkow`y11jvz!caCT4eygt7(+MfQ(
zYu#89hDCVf74sg$R4^!Uux9-<G1W~VYDfd>ows(oSJkU@aH%z1-Z1Kh<*}#(XWjL(
zFY8T&l%zYJ6etO}z8X|-+{6E6b!caYcm5Q(!yA)uEyLxS%ly4N0Y2}oZGYyqkWTD}
z?HADVJ#_BF^Us&V<qToCyohT3VE^ueCT*Kv^P;&sl?Hj;KYvfgLrm#EIg)E!m42$v
zdb+4~7+sq+USD>z`Eh#2_W8#wq2Mq2`IRT$l>6T~*D-QSp;Z2hMBUTTv&AaP#HP3x
zmA|o`*oFI=wvn%J{(@$jiRt#9J9ITf?S6elX<o&DHnl%gw4@1vj;<FN!255G?jK(>
zth8kZ5Kiu6p#~<8d}LV|M(;n*Wy963Ugq2H4QUNMl(_gc&;Nj5`OqjqrquFXZF-&a
zxM@Zg^zpUT&s$MbzXC$)YszYmS=qiwnV2q`(~fm>weiyntEmxpC23zeW_S4G!Glda
zufElOpobrOqUiLZkaNn1C+K9xtG7-4PDR)na{SQ6+*<|*kV*}ePvY$xsQgJ-gVpS9
zx0=x{Uz<~yl&rv{IZsEo-{ug`q9r-U)2<X1M5D`M7vCjeJiwg{7u^fls-_UGmn{W}
z6OE5T({)aAt#Un{5mPx7?{m^)1b-moeOl}@`FgrS=OyLh&6ck!#nxhS^(nWRRKum4
zu!Ha0V%W;a3D5Hj*r%Hwu~siz$5LIcEMAX3vZvUiM*7<UO1fB}DvZ*Z!w?I^=>UqL
zi~ACEabrcpZp~g4^)eNfld|AHnma9gT{P}+&)IIwN4G<VrQ{@wXg5ZGXpnnNZ_KC<
zNk~er=_Dq4FYH1As&B5V7<P^6hfw(D>vb2Sx{_mv-*>aBgo|w!GW4(9XxMc@LB+t}
z*vC{4aWAI9{zyl)Pc5${yj(M53$o195!pNjxGd$>Z`BHS%PX>#%Qx-PdaB~X&XsZ9
zD-f7&-#6=0^K#XxPr=|;fm6hW$Gi~Zup~#1q#|a{dBWlC1(B$T%(gEvRto!1hTWZh
zD?Brmb|LpT|7VRolu`xasS792em1`vjYKTwV;8vmZ5V29zh6C=q+@JXr<fT0wkj}>
zA|f3laUkyTwylryTIQ3PO}{+L^tJ`$d~c!ddc33V`n!n9t@~&4)zWl7Sf)?E^~x~#
z{IU^Kzldk{2?=fC9(}2(_iQTLb8PXN!8*TAW&OMRJz1Xk=rd;1AGs;*$#eL7S}q%w
zEuHZF-L=ZkKfhuK@<|xHxM8~df@M=j-}O-KCep?2gP7VT?<{&snIA?Dyujx=7A3qv
zD6TaOS&qk_*^_Q?fS`HzPQj(frAD7NkCK)XQr5o?CiO@^lzG~ICx(^pn0_~IM6ga?
zBBsUpar)GMG*AMRDm!gK1EuYMVW9l+wf;{I6G0@+{n)k3QwB4xI>xN-bPxI2(!u9`
zX(yIB_c(Kf`}bsU-wO-739E>D5tSzML7byqRqlgPU~8gf{%7{tksk@6PYT6;gm!&Y
z;)HGNz0ea|?Dz}eiOhb~`{f+^u;-;9y8$J4L*E(vW*^kW?rLr+#si<Zi^Igx<oid5
zJy(q~ZRPo$9&g{bt&3&PK9so7YRU30exb_|{=_+~X3m-W!==KBzNTfb^@z+bN6a$0
zRg4VV;TBxK!_?lDkNDY2)IS)M^d4G`deTv{%YSS+b%Ah>ugm_;-4x$1y3fC#P&DP>
z=d|Oye$Mi_!%L2`qC<Sv_SP0<7qTi~5gKJO?+JG>ccvB0WNppd99AGImzl~OyM;#D
zs3yG^UTwaR7|lAqEBWPS2FIiE-z~phINB(#02fc68}_)3;>uArHu;jN4;=q0!>3;(
znc`aR?i*V2{Pz>>&Q+2M_o^_;zpfRg-OICL8n=88DE?6NISuRdvWs!v3jKc8(o-m<
zCc_;4(%J02EAY1XlN*mkpU#`4!KFCCu)W7sV%`Q~5?xZHW)(%2o)t^M`wt>xW-dNg
zKESnD`8L=!IqB>7>6;=yDh|b*OZ=Yt*z_zHN0OB`TRL+QSG{*1uSYh#6N4b1(p@9p
zjWgv6yDRiHTl9HiojTO~urU9r-%oIC+sWV7`@Q!2X_3AC>Z0?<%D8`k=d%rnA5ULC
zpIe{+f3CmJqUcJ~rvb6!_tV?3PF@JVW@c1=jPO?N^bvVpmp8iHN0u>0=Q7VT77s71
zBD?u@7p^?t+ugk8_K>3=F~zUPW2m6MsKr}66hOM-d_EFZJW^fZlm$T$p7f7iSp}y1
z17<?C6x&@u*KXwO{m}5Yl7Pe39y{Z4yWIjnWjJ32$K6d!H_!!aI{~6->c)Z29o5oJ
zs`c%m`?-4#)PMNd^&(Bfw%Dd6%i4VM_4j*1QAK>;P7ff?i`tbalqzM1zqD@%-OUVn
zLRno_Jo5QEq*gXzb<`GNzkBxV#u!6Er>-Hq>SlHIP3wil39FL5yZm98a(j)_V+Jo{
z4V4@oBLiCZ0^Am7tu!<ogNE=IjGC3PK?^1m0!@z+a&%Dvzam$9H|g)^a1E^m_sPy0
zH#|J~1|K1xzUs{kKe=BqaCJz%*}l}n@~Ok`7aS*@6ekLGC@aH*F_L3HH{U8*8s*Zc
zJ~IZ={=eRcUdJi9v3byT>v3TUW>NASTQtGN+dW?6M-sOru`$_IzjoQ9tJZ($yk1ht
zKfbj5ST9P*2RFOkG9AjIp*DDa_tP_f&0+YcVJg2u*Ci?b!k3myMLu)RN>>$KhmL%^
z%>UDW#{0<qL#UDIdEKJ&yV)*t<e=lQTP#7IfMuRXzFm5e9@=_ZnloSOduehZfyO8A
zY_(G)3UfEDuh@EUOM9i7S*&H9w|%C1?A8>Y^0IEY`5Bn_i!FaaY}kiqr_SD3tLL%Q
ztixz~sv>4GpjokaUjLX@dE@EeL+e;^-Z~?>h)k;xjPgyMFv=8O^;QosWMUrtDk9H4
z+yB!eV=cF70s8EhgPk{_VLUf=5B-u0Gr`|J!)M}}h&knK)@%0IqRTn!3X{5-55q<=
zx1?{_+6qVEf%T960)Y`3cPOx*d(+e&(Xo1aj{JC|qdDOQJsH@A^?Ib&9m;bXar%}q
z>>Qb|>1umf<E~#S{xvtQQ#v<IpUA!#_ES|Av2*CvduaPs{-aW6S;c{GzH7mDTqUbm
zsc9K1=Zfq;EAul>4qwhq7QX)U;g^ZkM9t7kK*D4nixX|rW-I*u>iPU5R-sXwA<Tbu
z8u>u|ymK7^#0VF3kC_3$&YuLB;t}Y6B`EM#uv&<BsQ--sH@Kgw&n-_c_E+{au<w$w
zsWHI8!2w(ZKLDG=^WN0Z5O&4N(%AH}5tso0Jg?nu-SXRY7y$eOLV~PJ&L4JgbUMs4
z2A<b`5Io0O65w}p558q^<;vxq>UVH=p8tMPNB%sDbx`F$=l?tQ|M-s|Jmc0K062Ee
zlMnO=cJ~Ki1i07U&;3?V2mtK<4yK<854i=xJYf73*dGKE2*M|KV6Q*n3p?<QKVgSI
zaBQp$L7W|01>L>fJU|!;!pb-PCEe>^;6G^qF~D+6JOey~;O>WaWC2R{Cfv{SkBmQW
z|0VlhF#qpBf4@+W=RYnP@V+<L*BWe2Kw*b>@1ToT|A1e*yBS%7@NqEx_gf+7chcoR
zcsbP9)&PVR0brNN%^+jjKk;|z-to4v2VrqA-2)zCYV(iuI{`N=EI}B2ch@W5K(n24
zc5r@o4>km4xwEfj*QB?n=}sGi^l$<mo)?TjSQ&(6yhAVkqkPUw!C}@r>3@`S$J@{X
zgu!w+gM8dBT>)W95KasVwA!f)q?z-Tr=Q7AU10f~UAIE6{DTJ0`2atQow`7Nxdc6f
z|KJfUlXE`A+Xn2XJMVI7h6LIC<6SPNn{Z>(f8Zl;`TfxsLE5;Af<mo!XamdV`r;O3
zWCFrqIb1(I18jHX2EyD2Jlrnq$QJz4C$~Oe$KeKe0)fB{@a_%-08HR8U<H@}=fUSK
zAPCI43BUnAFvSzh^#oJk90GtZnD(FXuKa=X=R1F6c>VGA{Lb58E&mzk&l(o~ffL9j
z!F7`BH29~(b(u?#>kQXf;4l}I>l~Lp*99>3ESJt-6kPciIu8S0zye6=pXJ;JLcyAM
z=&%FMKb8zt`0Jg+_k&<?_r6pzNX_3|2L7E7mh%_KAkBgQDghuEl)yi^Q~6gpbt9V(
z{FQTfnCtzu!M)u`!1BMzm-{>SJohkoALIV^_xs%A+~2^@7+?UlfZrb!`GZu!|7eNe
zzwlK4jfXZ6GX!u0??ezU5Tx~=l>S?b-VAsw`FGBaBs>!=s20F|<-b!;j-FgOIefC<
zWYNi`f2-r~68}v~oavls&KAxF&PL8pz+ui-&NfaQXBTG;XVYJ0{^z#;vy{Ku{tte4
z(ssDrX@!5*_ph?{1pEZg3rYzd6TBb@5tJ3Y{1?_?K?%WAf)@ql!5pc-+Rg9p{D0#G
z4mg6c`lnR?b6q<l01nuKl)!;-5H|>v>W+j1fC#YEe;p_Ppp;97>lByi|LC=6cKY%^
zsn~6_`@(Jm;P7t6-Dh{7+I?vU{^!WsEf40M1@A_GQUB-2`3vLUIPm-zEKn+cm80@U
zuiNRXJ8y@9bo+sHdxm%-z_|ke3<GaP1i`($Lk|CT@}$;b18^$yJZu`^uBv?4&Cl=f
zA6dbNca9qm3iI?(1$O4ao%aA>-Rh6|jYGWe@3ate0MJ_nb=H@^)0{#9pfVVomev1G
zQvh|MSUv!}*K`jJ3j4D>aN_L+fZ&^_fBWNqj=kqW-89K&uY>xECk+6YPuOhwD>j>1
z2$ug1JRjJPO$0)W5b&D-U~ayn^}%0X;o^`4K-cUK%Jey;{(_A;6hH;OlfDZ865s&W
zKX7(*_0F}UUpfAI?s~cFpBNm#OU{47Kr4s=u*U(z9qZx$=-Mgd|EPeSm)Wg=@E)L*
z1K{Kk26hQ^a0+v<JHV6T0S@jz%ibY(=i=DK$;G{!XAdtQKZt<d2kheD<lM!@$<56L
z3W6gF%m=uHxkZkgGT1G8)s5%q?ft*qds49H*!j0@Vpjd+<EL)~-RI>KmpE`xQdUl0
z;e?{PhNjk;v)YCijEqe#nqIQDv9+@Yo7dgL^QM<K+$T6BG%OquaVI7=E<PbK=|Nih
z(~QilXV0@=6&4kjl)f%2e^*<FuE)G@Xl%!Kbar+B{^8@m;Lz~M=+`j<ku>xD$L!qv
z!XoA8`o<=8i}q`Khp!zz|9SmKzCa;x?Be3$<l@=ki(^;#4&%aH+(%CB7BRTW<91v0
z=x_J->_7jc;B6c4vC~#$u^U1CeB#H|iL#U(*8bq^f5+JU|3{qt#n|6`5rDm%V5b!3
z6b7IGi=_a(+;x`^Gy(p9{SeC1hem&e?Pdcv*Tj)}WQkNi)+t(6H)=mphr-jz+DnGD
zsf|s|jIIcia@Kf}%0pNgZ>&DWxcC*4j}}bfqvIQS5<*jxA%b-kDfS&#;bB=$sSh^B
z&GpS1;y#YwMQky2^QW_z!YG=8JWC0};uB^AU&hYy{C}S;gC+}6duU2@6U1P5z5s(i
zkdlCh>|;qGyjmwUC|>ulTC6^Z49Y7|Y@DV=vM8JB6>4);8mNOl!U<w!rfBK-?MXDb
zr#t(S4^}$arml7fsSyQ#Z3;h4sA}aIwgIkioZ|-1^#8Aq=xF2xHt@78x|<D9Q~PKq
zcv#>D0+H&wXUec=S(B5J6l_D_YgS()Dw)Aq+B0LWV>qlnF4e1LJ6h9xB)E(gj1Sk+
zB)G7FB-J`PBsqI4E_=(c#a~rVr%hYFqi-(_)0qV)=JV3-E4>k*s}a<w{qIIb`dpc5
zy}j{GGx>4i*&3@EB>sivjeH*3AaORon)X8@Vr3(_qDjx1*q2O2z^sPRk<!o$xM7W@
zuKG+pNL$wSqaqFz_<cDx;GZurMYDAIqR%-$DNknAl5>dF7*Z<ld{ty<1x<%kUB=T{
zvkx(T&OdB1QYSaK{Z4ci5x1LWL0z{XH|NO@>e^P)0+uYuvo)oNQac$DpuLe<g7OQc
zBqXR*qC9n)*nohmPyf6&Mn-v%pd>{X5VHD$j8d(5jffC6A7Gf?YOKDmdve6SaSb0n
zys`;<z+d!%*lT9m2r%Wr5e-#mNU?zvG0bAz$|2~RELL3&WB-G@P_zI2cxOa0n;E{O
z!1yV2U@Yq>P0dPM>mibp4RA%Vf&1-<(e^v7=yzCc`=n+S$}tviZuPv=<99<<YwAmQ
z_i_iqL{uhgVDaP3$DaXJbN9X{rH|p{G%8$QPqU;M3KY9y;#6F={R8N9aX#i@{=Q~s
zGNyI%%y89V3QueO1BGUj0?S}#ZTUAi?j3y|EA?g=tpe#d1@|w%wvaiBk#u2}WXq-v
zTulEV|H3^z=TfTTi&rh({mV5vA1W#cD=u0Mn^!-)Q873>I`{OL{91Q;zzSXGI3c5Y
zczOBGIICCYL~7u3Ho&dOtRMW8dBz&mkvi5A-m96fS+&=!i5ezVoOKD4Z~f?0R=VYV
z-{IYpT2I{RfzpI57Jt+VgSoM(Mi=E|Y~sis+DnZ5)B0*-Y``{q{n{W26izN{>>Z4D
z<EOt)N2V{uj0*Ry+Rd6W8`Nk@*1O3;*ZtM#Ka5SOn%}M@Pb&XrRJxcQ_5HycSA*jT
z)DfupiAX}tgqd@Fbqh1p96qekpG=qF2x}>Ju3`g`{G}e7Tk8F#HOBeYM4h#GHXybJ
z_3k6owzJNHHD{vQ4C(?CrnuCn#wPpPkF`$;V-I{?l)&VR>FQPZ*lP~Jv7$6?*{KH%
zqZ&l!`lT-ntx~x5g>7uHZlh~*$=KA?w{z(cj+p&7-$Tnx1oj^Pk@)DSHMQ=C=W-Ex
zmip!4kpsb(g3{mFKP^fd9QsJ}QtXTha>#!6zFSCJIH9&o3g;_Ps#ti|A}Hr-?2Vjs
zpHmi=uI;c`Co%NXt?Vp@SPzvA^vl*JTSgfgQy?n`$=&#9#ev!3s=3C2jTKm1BO7Q_
z(do=K#*`WQ-|`EQwlu06S^XaGaQ#i1hj;fAR>SRMaAj2y`<CLp8t}oi)J}z=_@g#I
z#G-B%kuZLnxFME|X~T`%w|z4yd2&zXWjwywlzqPc!c$4d_^MUd9oO0F1iJo*85fO!
zW`3{(++^Z(t@XCz)pTu(@h@3}kUgQk6}cjWpK}+}9nGX*F+mg3+N0Od@B6D)J?^=o
zM^vgqDoP%(c&i4yx|$75(e?tdrJxe*<99t_TCD2aNNq~CGOKh-YYbP^J^0whbg<(_
z$v5eXuSu^zye}dB@HA$W!#lBQ7HT&ABd9ht)-lBRjL-@{8Bdz(Xo;TbL<wV0pxSuY
zz;r51xEV#t>51gm!HLkuyI9K1CS7w<RrKQErMfo*D*+n0;nuhzFU+8yU*+M<AFpcb
z>M;&P%Tdur%f^OZI{i4i=q>Ag|5Y9TLt~@l!Op}6eAmEjbZGmP8v6CIB^)>7G%<B7
zfvCk00q3rDB6Q4`noJH%M)ye|+^GeaR1$RA{3X(1RNWU;bCW_puhYUwP@Z|$11;%B
zgP|yXn6G_fRbOng|4a>kE~EqVVVQYgWNA3sYvRsi1D(6AnDH9~!UlXG_wxDmk4;AR
zKm=Kb5T$MUXK6KL&h}{e23jZy!hwjN+!G5ER#A;UN>f#FH>bsre#h183REG^```Jv
zdSI<OR4Gco_d3mJGr4bUpiH5B;DzS_n>1^yWV-%x<&3mkaX_a3)M^giNoE9n#=QTb
z>_Lkc9@F4(&7Vve`cZk!8H;&$M(GS{I(0;pc0bZ`+>Gj<#JEb7mTGnCM-gz-{-3h+
zh5AFB^<)GDm6}?@B9|^?o1ZotepCz(-HmpOa;NHvS`Reqy<XCmDK(#Q!3En-q-QgG
zEtBfkFgdR9rLc5sBwx$h{VnsaaZ`gdD>OPPJTN+`h!CZk;0Ef|YD#{}vVYywxWqKH
zLr4;_M6#$LS<+0dGfVV$FKyR!2qoc!W3#yjoV~Nnx2SQS3rUWfUV~MP6GVqPrjl*m
z&(X`0(%;0l{WIPLb#`g@mmTQh)1umnJUp@%urV+?8y?v-xeUMlL)K^G#|iU~lZ2e$
z7aL<b7^U$HZz{S@AHgh&)<*D8cdrD}Z5Otyo9L=YqkgQCQ*>WyIU?AB*@We0^`Z8$
zBxn^xt@w%MjR}+iCG|lwbOt4Ws2<t26r@ezwd+%4Uo=L&V95+`Fs<}VixMn<QX0&W
zo!1u!DwK8b?ahI@Do&IN$$`46o`dJF+@6h{IX+aQfc9r9%lR9sWvXU4-Kwtm97}L$
zw2`;4DJ=d~EcqlmOL<0Nta~CYgZhgwM@?sDuj!g<Jq%zSWc7x-D!;ceOBK0>YV*MI
znpa;t`~^ysc<;EWMe7<37BDf0%++yNmvyf)dA;~^vFqoI!?0}Ak899puOl^{85l&x
zWmsm-%sE9$!F4V{KMqCs_eh24vH{g#YU-{DlV)%@6ntV%nnXnUE{PA-P+YH#2Bk-5
zkh7@iw16p*CoInBK2)tfj*`_mDMdlWhD6D?;>gx&V@=(zrzqk%WmAhdk!DNxBARhu
z7h!k=gTUBnXC+pb)DBc@=txVMWlkz3yKtJ*HL#)Y!=<&aWvnap#}-^IyROuA>eho|
z@$Usvvf_m|m&cndEM}h~61e%QLw?&_DdojabbonKe9&|_zv=U@e2pKGXOCBfin%X9
zXvf-hVf%1i7mN6gr?Lc=z^Or@=$^y71alMWq#a+!3D3QP2g=jVwtiOH9Da3?QP5OR
zZ_4i%+x3@6z$mcfLV7TZp?;R*YIrreNAzGmSF-^5v=xnqsK!APnnvO{)KP+Xp=6c-
z9I_8-TII6^-KWpVFrnyIR4+DeC8~;;B{444YZ5{;bG_V4oqnA*y~XjC4eXsZd4R@o
znS$Eaj@hunuqI9^_(~ehC9?q!`iUypEVF@7yq{bXGtCX%(2VIvGdb;W@9N&?tyv7B
zR|L1N#1p0*20a>p@nov`ND2B)3yh{{x$?Q5kef=)h^<9TQ7>TVws-gRg^FB@{wRF$
zM)D^Eo&7R~ZysGw{rQDQOJaG;UoAz~kW2<A8+&MgGfEO+V@y~}SZj8pE5JuH?`=%&
zT@w1C#|D<4`1?nXWP7C`r6bBzbM?mIR}nRM6yZicy7yGTIqh&}8v6B9-F&i5-}nO!
zUmbHJM@AGKa<o4Gweg?>Y}eGgXS+XB_ec1v-uoHgZk#3&YITll1oloS5v^1asiMQ;
zOQwgwCMO-)fH%R(5iv(S-`LprW_*8s0Or2Xn6ar>?U=3*^;v(xxVkw`<j8d)rBQ|~
zrGo0htY!l@%=t#CJ<L*lO@#bR_rqv)1P@8*uKrmwvZy1uw>LEb%a6z+?Y>vJU`^wk
z*21UmhdZ&-NkRgSza;Ef$LRu{ag&8!s8W|oir#ykCG`I^-Z_31Q`S49<(O~vPtdZc
zvNR2nfIA+?%McHtK?C|8>5C7k*0q=!^>4Olk2(zEJWz4bvV%Y37x6PfotA>IvBi9G
zq;27ZVL3yLrdCPlDVcynMfBwv`XdZ=j&%vfe*SjsL9%=Ylc!Ce|BE_`4*_k5kPTC5
z%BXl<B_c`)PHnV^Ax;U-yB-7kFdUw(n(%7D?v$Zd$%2zzu5X}w=~sfGSW9uGu)$uq
zq+%>J`k`;=BJT7@l)EMW{N!QUJ^IZSY7DW(**c~Z_U;|rnwD&Y9$r}q@C3^XV|~!S
z`b5sMF6!y$$LJxu!M5Z5CBsi3zBMF<?O7Aidv&Gz$-@y1$4P{3sv^rCy%L%K?$)Pc
zy84=w*y7FXu;2$7`9rsIH_=<BHCB+l(L>Sv7%aIawmFJ^#sQbS*<wg6$*qLZtclDj
zOgvIAm~#5kz-IE9()y8=5{lp}^-zjL!p8HP{r;h*8Uju;_Ul#ZW)MMNd%HZB%L2yb
zHpLI4Kl9Z-D6?(oy_%j3@BCTqb@0-_?Mu4YjTfZ+VoNEDjfLTMHMo|6>0nXA;iazM
zOv@tIvhswtY-;3{e!e!XM5S&|#j+Hm+gV(+2A+0bNPIRMNYp<Q-G#BwJ2cdMx)iQ2
zORlf-rTZd<`Zry)zZXB0uv^7wV$RFk?IN`!Jnb_N4o}r6Je>F1cpVw;w9lcg^kBpJ
zB3B;a<0Dmi!*rd^v!~(bu}0Ry%VGyVI~WrcWY1`%793O>(;FNukM?>M-RHDBUn?H!
zUnA^<uxul2J*dNtYf;fn1F#O3bc|y>$zP}Qr>pbVZxP<v4<BFZIexX%Kj_gr^A@or
z&+rZr6yfRhMVp7RacyNm=A9Moz13Np=YM~d=j`gUf9?$F?IT^vtkb0hDB7#KFD!!0
ztZo)|FI<uY{gh=Kvt}kmsGW5j_hLSe<6R7%kd<6#xffAtUq_D5ExGn}67hb~=}`sI
zY~EOXDOYp6Jsplc)jU#FI1(};6JVb;9GvVhZk2ISw%4|yJg96><0I4Zu&ZSfjp=2*
z=0-n1n%Ivn6e~1KXgIX{{~WkhT?GH^!>6L1_4MUPufmz3plkif%TVvv&C=E0us8Xs
z&3e=R(6&KZDHTmSQo+1$DYVe2mAHXGqqvZUEjb3G$I$f;d{vyyGvXd$O4L)RdR7CZ
zk@IVT&D2|Lpze`pa<TTKQaK?psr5@&(jS&pBkDIFX1>jGXxcopzG>kYAXy174?t9^
zR}v3=*6n}&&C|aqFU`Kc<O<l`4NxC0GxJd^FevRPj+KiF-~(Me2Uh&+zk)zQAE&sG
zUNjgT8a;p`+rS>+4lvwHXrir>LLGfyw=NGg8<v|y-4<EIs?mhVJ#E<i{maWCP0mbv
z+YzK0sTXyDJR4KEV5ilXS5@UxuN|6Fxn+N<>jQfKcY>)>{f4Q^c$CNlrhXZ&Ibd2p
zk>*rC`9WpeZyk0ZdKf~!90)-)(mVA}(t2i?VT3i3<$dfa!)f|d%#>7Wtoqu6XpTW$
z;g|FJXY1ajPQL<wqOOcM1$b-k&CIT@E%UzR&{NS@0@seNsF+;*&2#f1l)(lH*+2|v
zTz!y?<YNQtvo$RK{9iIU?xZQ&vCRBR#4-DXZkFCN8h;0w)^uqw6cPtYS^RC$<l+~z
z!fzKEi}R|;_h}zW(UZ?3g2PL{_PF_$VG<bzf#tF*DZ{zN_x`;Wo;NjYK;H*6-W%A!
zlSO?!W&v(G4JHzbJ4h?+V97VUrv#?z8U>S5P@P{GyJ$mL`7EpVw9`VZ&kB;Aa;Aqn
z7Y6*0!v4N0naQEDBUv&y-`!Ozm7SOOM!5^I0q8tf@>kSPgJmT)(3g#)siM9ko>RgZ
zB3<iUPJKz6sMM)_0n4lEY(OGaV9Wu@Pa7**(mzDe>PU^h<JCTu=&Hd6V(&v@txbZf
ze6<BL{8i(M7qT^Dh>+cVvOlmf#P@!xvuO9F1E^nYz=RF##<PJmAvYKcISkH~!EE5z
zsQx}=B-oj*Acco?RVoqkB>RWP7~-C~J?bsK)-)Z;$eeYW&|ZWu2^Cw1P^(sn7WkU{
zOl1R-?5bGnU2mM0SZ5NdR@8oNy9>fX^@F9pVFTY|zS@J9xCV-RjSc+1k)J#zsV~9$
z0;^MFh!m1a+xiYHV0FlX4U{En!N3L^*thUx%Go$Ha1Vo%)-(<JE#6!8lEuaG6~(^#
zQWU$mN?N4LfQGY_irJ;%jh=D-afg7zPj;7;$sQjxchM+^FApx}Eo^@4Ey*!gAB2|{
zng?XxDao5#Dn7*xM5B=Y%$F#i5N25=^d@R7hlp8b12twP44{^_Fk^Xu5k`AXk!Tn0
z0u^b8i+igKgxnXet_C30D0o+0e`1xd%}A)fy*=ppMX7%7v3QZw^sMz5YYY@xIq3YJ
z0iRJQ;u5nE^{e#@2eTHmgKXKrtJ|Opu+0YWqjY1ir`~(XN%vy$Rj`2zGc4XsHjq$5
zO<@CboacC`eGD;sR#G=Z6twGvU@Ksx=kxBnLM!<+#Tuq)DouWrC4(bqv4Ix?Km_g)
z8-QDmk4_6EVRyqA2%0JV$RdQFrHG8AMUb^RBv8Eirx-V}l(mFX+OzHItXGJ1lL4eV
z+4=$)*b>jGc3$W$U&v~le7wG3HTeOK#5^(B+bYvdw?&52Vkb|KN0*<_)h55Htr$`Q
z4bnR#Q&ZGJ=0n#6qkCXnPAnHG81q$gWbtM5%)$!vcP-XIP;YEmd$57H3d*I4nfGy6
z8H5xmvw`?VsDQ=6;H5><wUEl>(RQ`?Fncm096xiVrDb??!q`8&lci39C2B}jMRuX~
zHAj(r-!cnGeTn*d6yt(&T1^-B#L)Aa%{5`4#`uD>mS=A~<Xm^B{vv;$Jj1L)a+7B)
zhmp`C&~ZdDL=0Jc6!J`aIwIex_KSLC>VDcF3C0kGp8v8Eu&Fa5>})8z^4<Tof}^XH
z!`%Cyxo&Qzi}{6;Venty7*m6+L(xM7%S2s+nZN{=1hYw>(-$Hf0*kYxK-yt@q24gs
zQIkZZ#A`$oF~5xs>|#jOQv|cv0DoKbZ#0})CL3s<5@JBbHe+Q@XPNjmIR^SIR~0wC
zhew-<;%{|b66qwqK|Hs%jypS4m0BvxJDlrk_lEZ1WHi%M=Y4~(Z{3s4XVJ$ph0Wb=
zpZTQgbLMl=5fe_U-(JAmvwlN75G$#XylsBs=R%}Q(+2b_8^Gi<_rqu>U@RFmnpQd+
z$khl&mC+#E64#;RQcX56J5$IE=t6zLgMN7I7&s139k{cFhY@<ZPrQUf_pjonU*(H3
zgo_aC#G2GiXaegnZ42zH2gs~@Brs4J2S)EsQMB-PjGHPLI^^*C$lJb!mL$}k`IYk2
zy$B4RP}O_?nv?TleO}~6&4TuglW1F{rVyubox9b^@`_pOThymNE}0uws}^hil0V)+
zlnsx(_7NvK+-V(h`@pAApWiahTI3XD8CZ@Dr8tx-Iyi-j%*8tYc;Sq$x!D_u<BA^I
z4t$7}N8}J)pMztGgC<{qw5Fw#QXdey@i<P_7bw{fB7!ixNJ&VM!!%Qjx?)}<ulGmG
zBd9tm)>iT6X3N^Rlu$%vX+yREbh(~C5Y7vWKXId2@>!)Szp$P9j3wc7y&LZt!;A8g
z2eNH8oLmgFM%J!gCHXw_{&>L8PBZSTO$N+M@+^{6s^>9OK`b8{Uh>k+GCS6d^0rLL
zuPa@COGb6!Wb}0yVc_V0f{-Ah@Jx+RsEF@6(h8iRqR|x@j@3tN-wtl1aN?)9H(|nv
zRF~nvYLyKp<lGnaDl^C7z||w@H}CSi_#N25zc*jtX4647V7M2>67_^JIzphl8mJTq
zWF!ABq)u%d7cfOgAZo-{yhMi4oL?a@Gi-n%%-PQ3rl?j<9vlTH3qD_MI#Rx0UkLoI
zPXE1#wAIBWyc!87I6?5OhmGkg4w{WEN*YWi?6q$H7~D?0<#4CARMDbH>89B60=XAy
zDM)jlJ3ouVcaIw9m1xj15wE)rRN85_oawc(nKR+o)6i*Z)NlnqP*!?6%-XbNHMIdX
z{XBZli2i=o;G_t+)=<$W_>HzSjbZHDV)06oQ%PdDxMrggT7~fdBb>a}1@_^DxMtfD
z$EEDc@5X#Iso7o6Lo!F-WIUpRXZR*vuos?N7J3Z5^Dl<X9EJ)`{b}j+U=-mpZaN0H
z{blM6GuR#Vje?>Iz}SHK<ppqTV%<>7atW;5q-`%s<jh>GKA%q>=NrnS9Fn2?%!HH6
zQ8iHqXKxD4881>&Ok^q^)U~bhy)&62P}G>Qm87h)AuV;u+^b{qSf12UpwRrC+=&Wj
zO#As4<>0wth>EeP=kwz~Om)WO#>33aS}dD#9R_dDT26*xGo6Yn{C&P<q%{{;rF&&8
z!7!!ExI#xu9mKlbkcI+7tQx@@#cM)^SVz>7HX(wv@D3C?adDun$VXpd@OxcjE#;U|
zsq6TX2t2{;J_6nA2F{9t5+foblC^ZjZy&YhQmO~jhD}$~30rr--yD;Xdq6kG+A9Tp
zrdnpq&rG#cH4R!9zhPEK3om98Y7&(p9iuqGy4nIlX{R*Q$i=xmdlEzP2i-D7@@fn*
z1#+<kM@uC+gF!yrKICbVi@alhGfxCj#l*NV`{!Us`X1@aji>D_J_f8kX|YOv>hXQ5
zVSllBcF?S42sDr<yy5`{n?d^a)FbWE&+vy}yeGmb@>v!RW53)~y5tm{5=l|<$JK2L
z9h|2+b#})w-2933D)-jx)CBd3NQ<{40U-zcHDLK2Zzkc}nU4tZNw48|w35&|{#PrT
z^~!p=qg>HBKgNvEz2XBI1b>)0+M-u8-QH(uNj)$i`knpljGScCF|-#pMKjxc@<ZNR
za^DONZ~0IXm$;Fi(1<Ol){3j^JqE7%97O8XcyBw^SCGI%V|eo~)i;f*ubi3i&6B2p
z_R~RHcqie)RjEFH-$omPDq6avN^Cfz+2X}Q(QMkRzl!x8g^$}>g%3$2YFfCxQ}+2H
zMa@^^KWYPdRXi04D?UR7va-!iwL>iTXmQZ;xrh}<SX0+%9CU?6C?5(gVAcVx-C6;)
zE4Mcd^r6LQ^3yz>xTI}V;&QZdbpI4aHGx>AM9hi@LvUJM(I;s!GB4a3QDTT>!~T4O
z{!o5Bd!t9IY~TvHJ4F-^3BAV#g4@}^S3L;xsC>ISZt4__D(uV#EH1JhvjO6F7`M;_
z?KD^&5J>OxV(b@2ZFntz%deSnF;PI_f7joe-$b@#@c~m?DVF0CJDFrK^BjZ=Bwhy<
zn9mKaH$bOf!RiuHbtS+M_GtT8mH>li80F;>e3|xkdLp=8!fCdaTuOaIYber6($y16
zRPU9tql*{2$tH~=q1E05wFk}IGkX|@(=gG6eTz;U*r9V!OARPttNo6|BQUlZ6^?g$
zluKj-GDz4cmWO822^-Hllt*3fb`>91)77d*`5?qJxGC|^iK7$`J8iiqBn9;eOUq2@
z^P?^legw>TxLH1&^jJ`Ej>Tt4*Klt9q=pQ<U8EIjnPPz!iV5X7&|l3kBd@pXA9@nv
zSd`Eiglc!M0V7v+Wb{WwR2|boNRXCpP50Bjpl!~o25=If6<z?{!xE-hx8-RzlKWDd
z4T-qKDIxvSh|$*YdM9;l^~vKSSP@@+&i+b<ka#}Hx8>N?!A;A=lo{tLvv%#-QaGIG
z(cgTca?xqzZ3#Z20OfNx1e_Z%Ys(Yi!BtL<v}9OQj^St>Ztt}op?D4G@_0&k2Ucp7
z0h_MUA9Q)*{>91i5G@>^9bZ5!^BPuJnY5HQAD$fuy_wm*Ptctu<3g8{GLt@sXzENU
zUCa|qC&^`nL-46mz0AUC2aO4@wk=nMy4nPzbgQ(Feceui#nTl{a_?LM1a1mP6JU&^
zD{O#w4?weL3Gy)u7>;z!=vHu15(QV=g$OnpW;m1ksPCB>jHm*dGfAc}kf^eoI@{AF
z;)+e45da+^tAR?!34gr`OE**nY%y$vpz`T{#E;v&CIDTF#T!NJRk8-(7NTGD8O@4T
zrj65Gyz^veOO$m|SXBhk#rX=QG-b0zhTm6D3E!A?zu5?k)blwbrD;)x_`vD4dss;_
z=7C0y(0sn2vU*O<ihzAb_Gr>3)0=a{>8`HMjQw&iT_<`#oWNb$%?9q_c(LjRMAOiN
z&8oQl`Z6@jZZCY=62C`d)4U}qO5Qr^@M1;DLPZ(#?l`j<PCdHROP9rEa;$?>rS=kw
z7c9c~G+hBjyhj5^&nGkhAurX?<RQ!heai)GAfAU9$Oe8J0#NvB-1H07hCB3K0_y-I
z4#()Z!T~B~a8>I*Xy5lgWPOCtuJ4Tfb(M4AT6>!zYB~o(ww&UNZq2V}1IfCl=@QYO
zB!!X~C+J6_2e5MF&$uGwUK+e~Ns=eAPAx`8V`#%A*ks5bd0K2Tw|v1V1>Hi;f9+&0
zFr54C)HUaxL$9j={X8<bp1#K7{hhUsT$e%@i2leuOQxo%S4RU3<%#2i@R6UrO8GP+
zEL`>p!Sv9N+_C3L$FqTL_vxDDDzK?Pi~3?90G5j(N7K-HAkwLO5e(ZRIf#Lrxe+0?
zAtC*hsCJFwg+eP<A3bX8D|T#73RdqDA*J81N*0R#drJv)7tTAChsFlFT%n){Qq=G;
z0Fh5hNMwl8L5a1=U{ARsAZ><5S)Gl2G0{AT8LAl#PZ4g`fs+Kh&JAiv!!DDB?(3RX
zj4fFCj9?@y>-kF^B1X3~M}E#E#g-G722&c!uU71t7z?%#dC;^HUZIH}N>MiAdxule
z9xA^?z&cp`7UtrTUSEnq%*>QzP)?}-pn$C^YDWD;iEY#(<QO(ngjxgRBufg3ziM1R
zIw#|Ve8OSk--pztw%!kh^q_GAs(x!nTL#s~zm}S{=zsQ(b~>x?CiU~ZF`ZCVgWdLR
zn%vg<ww>g47P-<ZnN~kq1g`cpOz4SMI9F_(X_4qe@gnv7O9}H+WK&CmQ@frTeiSSE
z7J>8ZyJtKL5m-z&3a;>u|7n?&8m^jKIe`~jMf<A{m{h`!PA;BboR2_TDt?+6&kjfS
zZLN`<<m(r_n^c6AG<)oZ=3d=q?F|c9K{{(ytZv@P4#x>cAMy!WT=#*JF9{I>SpL!c
z$u42eQ)9u?Mnl=d=vlNE$*d{LagLU`@){pXQh{2IR=YQyKE6F1mszF|x#S?9qFnl$
zT^*^a935U*n=<Mz<(g9UY%(yjY4XLyR?7jMi78m5i!C$sTWtiztTj7jxMdX_0$df$
zGPN52<HN=1re@|d*6wfL#?5M69Tz3PKep8B7|lGWk;BxnY#GkevKtCm_E%NgJLr6V
z9_4Y<3~uDl2GsJ+8$+5fzP}QvSQlJvF6i-QomyOFjoMeNevWBJK|-cD%p$bzftDj1
zsE6F29a2`$Rb;_<!38OvW*ynpte2+c<^^y}U?Ib{);C8$(m&WK%e3}c3pQ7-rmUst
z7Mj_gVJ81cmU70-j=5O1xDsAIF$QbNa;uzEOZnw)rDdvP^`Oxnu4CpI9xxg;_H(LT
z4M5=Aq5D8}pPh~Az{P8?fs?5uZIH#s3C@`}XoV#-uP$nyOlo%{1i$tuT9sJ^&dK7V
zuKJK+h9SJz#n)AUViFg+VrY=y+z_R|i0}_pAPrR(#|yp2TW2Wi@mXUuv~7q=I@R8t
z@?N9Xv!^tU*$cZ?2KHE0nRadKT=K7|Xz`=x_e%#{-_P-Df;e&7d;mIKrvKZ!fe^a1
zY9H%>L~A(CW3cM*yL$S~Qo1?v`p~8l?kM5RE4oEtnXAj9#NhIJz*=>+>Z*+CT&6KV
zkGw*=O<uQe992WZIB2J>TPV6$+DOj5hV9$ZE2D`oF@vh=&WO;S<eY;yhhN1QH#ZHq
zJz}nksQk7_YTHHVQ@+fRJ;lQkQI`m-B4dbyPK&~L0cI^i9&gM)?@t<hiFvRpT5@33
z{l364)A;?*UEGt+1`E%XdHNj%76Nr;i7v)cW>JQCeFzrw=Kjx-F8*FAi^lkm<5z9W
z&rc4VSjhzsAHO)`{JWdYqaW@@&#x)o<>)gZXA!SyN>*nG;h_or@H;Cri`tVpkQm)F
znUY-v$F;%+U_SM}CCO3ef0{+o=VfMB&z5=z29Uf?1poG)M+dYX#+Ig0ahn2OHvRhI
z2-Oj~YfC+DNIvHRdT3X#SMij0=56?!MYHhTNp4<+i+3`g!;9zNE^PZ(#TTM{xr=U1
zUMqSD0nMFjENL)aG1rzqh9P1)`uM#kwa7vbQ2}5DmL?QftgexlOyNr~hLY8V3Hmm_
zJ(+XHH_FTu`!iG8(7egiZ<F6R^YhPxD_+?WKzjR~E^t!^*8oL6L0=59WHS_+Pm}L^
zh|X1N$8koV@Xf+#XBN;8AWB`DV=j~Xz%Udg_!>6Tw<2{62OC=TR~Nbq6Wh#rE=6=L
z4K8Mg)8byE+Rp})mpZ&Tw#&{zp5oAft+<$}x^Tw+K&l1}PMINg$6{3&dbP|X+;l<S
z*?KbU(MB?AAMK{vL2r~aIJ&ZTr;y_MYcichs~4Q)laW`876>`#N5k%*5<_#GBis|L
znjFvRBkE|5Am!$$gNrQA5$KJzm^{hRjXfG4&~?K&FQ(*A0TsrH61l<|smMa&GhKsQ
za%A_m8VA~2QhnyAK~@_}WoT{n26;9`uHo?RksNY3Ymf8mMXhaTRxcZ<)yxX_nt^a4
zj!tN#-ZL-#P`<N(dQ2#VAr$H9uN99S4}1ykMq7z|4bNV!^(}^vYDYg0uI@gK@L4k+
z*}TH5Yd}_F?LiY$g7E~4xAcPyvASAHI3C5tup{FVy_k6`Dj~Vy?fTj{N^af@KjpQ$
zCYUH22y}F&DQ-D5lF{7>FDc^1g^N!9b8&T3!Wy{5BVSsj%aHrQN$k)(>uA63*$UPt
zNNv{>`9uw+HKB#=`nPmlA8pM<B&?)5L$!E1DR488*HMfTo$O!Mdz;iNe#SGW7524p
zvnF-Co$%-dH3(2+?1!*;!GH|c7TIfAh#pA8x97jbEpHLm_S3AX2Fzll8L<jwO7kU-
z>)9KQZh*7D`mlPGyLoebzbAS~z1MhzK>a)`=Xkgw{_K_bE8d(7Q+vQ!RS{HJIivdf
z$(^0u%cgWKbG`0_I>(Ys%eYBNxNNqICc*T0m}Z1m_|2Q{A8wc~os%)8pG1n#Oz2vu
zwyQWFSR9T+Uj|`Ml)y(>Qw5m`jL6pra2v!m85wfbR0>)xb&7l?UuaQZDeJ-;VfY*j
z_l0qm$duc%-N)Zk1-&p(C7*fGPsQq_(CFe{J4`u=`42%$2RcTd(drZuVcZzrtRbki
zM(a|FQxp7<UQuKnY6G)eAArj!>x&Me-Xis0(-PWI-1?_z{Oxy28cOEdRit$d!e5zI
z^%Xn8x1)v`)a=lQSAd8qhBj`Rhbayj2Lqzw;I=?+9yT!l>?J2l8b;=1B@3;9vq`cl
z*mf~&VB_*17Fi7qw9AYVs9?mkGYj-$*ub`&0sw|t?HS<x6`mf2BK6>=U$OzF=zh?y
zt6%}Bem5o-NAU!iN3oI~0L!ccsJ1gGubMd2{^o;}WJ?OqitJ2{6jD$7dmewzOyEj5
z-5QDf!q5mMnIDbfaU80H@iBZs$8L>(A-i`qIXJXfv%#~lt+KOZ66VkrC04ch-TH3S
z8n}xRiJ_m5?ts1BT5*3(3wH!J2i}C<gUE!Y?)f?i&yyHtsUQ`}CaIe+p@r<Yj_`0o
zK<aB+so}7i`ilPQqC$1G--_IWN#Dc~_%ZnIMc~&s>(DUR(O$8EqEJ>BjF!R%z@GB!
z2`Hog_cH`XiK7gW9u{vWIiZVnh?YUFr9zmQENSF<GPvGCEsbmTpU%IB6KFm~suA+h
zzcA9ZWjtC36BzT!_U{?LcFkFLB>c+n)b(EeQ;+QJ0J>MFz8Jah5%LrX!i^ZjZ>uHi
zf(KoTT9Zc~=&F$PH2WOM;2LMMUX`PH$&#cDrpRaCHwT|=i?Y&h-yD6!B_5mmhWo0&
zu@voEF5+DGZH-o>XfZ^`yRc$3UP@$#<mdyGyPAwI0TzS02}#XU8d}rH4V;EN&}e#J
zx5mfnf!6Un2t8Y^7T7Fb?%M0SGrQExgeM04$hXNfKRun$v2vAx#0fQDr8w-$T5+Q&
zPJw%B#>u`j0+Z>QExzPJ7Vl0kb)jVh7dTH8$916tr(q9a<jau#=0$B$%37z!dS7=J
zqhHtuIe(LF`c$j?Tls#sCOMY7Q(aSSPY7%uYZM~VtN~Vh@B`SaIIwGbz#I|XW-{va
zl3OcH6q&iJDl_9vQ_?;d?ZiOZapt15z0)Z2YUR@8k&J)<i(=5cb{tw=4OG*RYN|*T
zcU%?u?RE%7%e-{edO`=)H#6oau4-y(gLg93h#1C}Z?onXWYeji^5!g>bN*CX_{?>a
z_g?}wavGokmPs|i#S;i;)A}#SQ^BPcpru==@|1Px%kuJu3!k&sBlBaX==#ArDyH_n
zf-NfWI=GTCDbEIgVm8o|z>IkaF8(|VWC((*XD3va8cSC&q+}g)oemt?Jdh?Am{>;_
zfL<C<_S2XeuO;QxczG6kJJ}~~NQ+*sLk~fx(=q#;;oJHNGl2)a3ARraG6~Tcq$$yb
zktcYs8lN{4`Qu-qzqXRtK<f$A&uLa$7pm`*7K;ZAbwAD5Lio;DuJBYKZ_+Br-6o(U
zucF#C{F;Nw>PY3L(akw#t*)29`)N=)2QA9%O~-3j)i6Zf`Ma9dsc>FQz4UxdIV5w?
z3iP!#sw)faQ<J4T8v<NkYj50sx831$N#=9zK}YMfhYbyH_tpAOIA<?~Js-PIyxc9b
zRIc&nDpe%bYsJUjKJ@7KhKQ5vji$cQE@9Xomg9|<v=eM#rI0Si@MAs?f!@o1x3dgY
z&Tt_cW2Tn^AGmUZq&{Q>42KE`N(Z&inGG$YYxaWOs_m3|kJ>>5v_sN-1&q+I@qY8k
zRws1DmAQ5o`?3y=x(_f6ihr?zC6+lGIQJ`y#fwL+yG^kQ<{%rQnc&p149ewHUNKpM
zG{x9YpEha5B|!G-n$gche*}N{Z7Ly}cQ7PS7->tp2lin_+QjV{HOP{7R6&*_MYBp8
z!w?zstAyBKeV;F@n~A71c`P*Vs3dC?$EtRN$~GPKMc)&o{MHoXtI*x`(D2O{7#!s-
zjM3#A-2pwsvvQVx>jT|1buWY~l_1L6(*t(zx3p>91EDoEQ=wRs&eR7e@)aQ&a1G@o
z@`8F54;?WN83zZTi4zOok3;K!psp=f>GaVLL2qMQ`jR4RsjvQ*-*ezhr_9}DNKj1L
zToq}zDN^kOi4+F+ObU+;8TU~42+3b_+yT@pNxC{!PG;`q^V?m|BM#M%)=P|}n{koN
zrIeJ?PPU!|Sk}#6(?a7pL@22LuP{`Yuh!~%-KiEd6v)aAko6i`Aa&0uI$v@Od4V=w
zfz-y(66g|^GqN<|j4Y;ZL}LPVVX#{N0K&H&Lttp#`GytluNx$#iqK}dr^wl~nGX0r
zH&HHPpOAG(HOZCHLJSkKTJi={1WE%J*8l_r+#<h?PJ`an^~3U08rx=;Kt~g7Mvuv(
z&-!Ly0@uvliV@?)*Dc_hkM?9wM=helG;`eiElu7^crLaOHTBVIYARJdYGi08Fy6Tf
zC5lmMLft9*d@cQ98nfd@^=Ol-BYosn21~ZCAlfA&Gud@~8nsfHzSJ8@zXBh9>xytT
z7(nVC>0b_+-++ia(d?vkY$>0p6ohuf<~_{{=?%;2r55uL7e{m=(iP(hI!tH1UinzB
zD8T8Z6fG6!=7^lDw7LNTVLND|Of$c>re-a@`9@}DT~%e>qef;{VasaO%_K5}ip%eq
zR2ZJ3CdU{LG{eEg4RJ*I`sIPOK(snJH4a@P<m~MPxyw-5jV79^T#lA>(Ye_8h9dBQ
zW|M0-XfqmEr((R-vE8iBEao@aGJoHtxMl%A;quuoi_m1Q@2_0lU@cKw^JxnG?rE`H
zdSIrCqp=q3=7%Y>rutk0=-CI*=E$dsLMsvUV1xu1q*@Um<EOO}84)j8-7-q#xSCFA
zqGmLZ-pvvrV-w0t6GLc$^4QuDSi9?~bbR9$9yGqQjAE{62Tl3D;&%bpelNct_)cC&
z%Bcw}H&#P<5<Aa7J@xp->#G?sPb+@~vkNmTCmM|F+~lffr0Vidt^9CkR^fhT)#0w-
z=4FL2ZL_N^i@a!{r7(e3z4YQ;@mV9C6K19w9~t+zs92hTeodqxXmWDvF;kHz$lH-o
zntc{znR}G>_K^O%A@V0GWb8H~wIfTC)ubCOL(wk|uP*+aAN;a3rLI@WnA|&&5Tov2
zPYBF>w`{LC`{DG#;pP|RJ^V@^)=NJT#rDw250b6ss8&zQ<?ZZeH(cH0XORsfFh0u+
z#oL`mKdX(a`t&2PrXM~o;0ax)Vr*uLqC|;aD-HCsv}3M0EYTX8B4oLjBGnp(6Kpmo
zjtlHsC)MCzYdGo}Ma<|-SmU#+3!=GOI#;@qr^i$ny4%l(tK!x#Ql`8|e{*zNQh9Vt
zscR@<^__00WOb$7?3>LO5n}44`_b<*%s!Z85Js)-Z)+4hpDr`oYMA6h%U-&5HFUl#
zxbe}I^vsm^gIkBHYocy^i^wlWwMhqq0Z?!U(ahtID3VM*?P$F1@RK1XjymzX$Mu5_
zG6x-YTR%Q`wq`=Sryr8oGF8Fon@@Xo|9`7%DAp`KFq9}e38SAcWr%}KVhy3m4a?VV
zxI5R_{>oQo93bO5P>)>CG7FA@hNT((Dvh&kic1;%s*)uajk7hMn*lE7!Or#TYQ1K4
z!fMw#Rl<Mo->3n6^^a0CTPhLV-THDvKN_&jBcTzU!+9wspv~{}f3^43VNrEm-ykI|
z9U`D~gLEU^HFP5qL$^Z<h=71dDI%q`bW3+g_W;rek^)jg2=4)(`&PO0d%o-Y>w6Cu
zb4~5vti8@UYwxx8KI`Y6LbOD(3^r!X56TG62=bjt(kqSg^#1B{JngA46T3*<CXKW4
zqQpU~f7IEw;+d%e9tcO9fWlNOiC#KFia6UxJxKdYw!C^wlAQ2IPwHpG&B@p>?L}c;
z#gRQf7z4#-gf(|q1n#i%P%UU@QF)v9DXaad3c3NzXdEKiK8txOywF)7q-Go8HlJ-V
zXcp7TleVcRFw+!@9S0KV16MJaY)8h)b*VO=$kL#I8^Fpy^ocE3@8Gn`#5tH1v&4;W
zPG-;I!bhDIdH}M|EIWsLs1-|h(w4_Y;bU_%EgIG`Ux<Io0ppkhf{VGz&9)O=$P5i^
z_=Ht=)p$F`TXVZVycT=G7z?s{kO))SUT+s53K0_Z+dku}t{f5KT`<0}LYfiOF<x$X
z=U8q4*f(5+JX^}ryYoJ=D;b3-xVcH5FHW5!bzYs7SZ~y1kw$bm{6Ru>G*qX~!-Y8)
z^+|VDMDv0ZDAw}HC+C7JW%*3T2!<S~VeLap`m&8hmQ8AVh(e2zAgt!y8Pu4tp6U$R
zP=Ou9<p=LOl5(pSCk+NfU16@@*jhwx0Q)mKK*if<LFq7;CL>&!dA?1xfBEo6GO)h$
zo}s{IGBeH1FWYdcZ|J^YuZyh~Hi-;sP+Fk1j<?X3UV?L+d`_3LCZlG!=EssT4mq0o
zg1bG1*x}94wgsC-yl1qvEYj}b;2~=cwJbFCn3B;3Po;{FY`PH8JPQy8VL!bC3{`Qy
z&>|hysGRj^9c$w<tjKgo0XpVQxoW7JX4N)N?)I1d_KL}fXOWgJIR;ixQbf<@NlA+n
zcrC*zHi5p_BXV@K*}D;AL<yK(@=S-t*{fxrMm(yH95VVwW0tVU&f$#O^k0C$3$fNT
z#8q8;OG+9_Qv7`HclGrN>ZxF&9VrO4YA1BC6JVaZ8Fr#_DmhROB*n?E!+aKQp>#Ch
zdDHA*&(A&+p@8f*HryCH8(Z##k#i?A7=2V4<MOeQ8rdk!+uE=#*x0Hqyvtux68@1O
zvUP!d{2j3sy{V1HA$?bzjz)%nJ2XWmH$07c&yL%RyY02PjyD$RGdfITJUSsMdf%^Q
z*275xML9nF+$wU?YT#+wq)K4IjTitdFTXkwIft99_uH28`zCNUMR2@x#PALC-`;V7
z4-YE_Tru4f{m95<NgO$$U10V`C^}ch-hx3t)Xh}_WExS6qT2ASNIpf&n1qC&3*LB#
zN~!K8D$QNJZ~W>Ayq$8e4zt--XrCoK)t;kx=C`fP7DkQ&`)md{)J2Jra$w&_aHC&P
zGQ;-L=RiMmiU4C|A-Q>A!BA9xkbA6jBp=uX4OJasDPS(Ifw6M+%73uO?N)vAwTl9<
zsDJ{n`s1l$J`dF_t?;+o+}1h9czPv?7FoAQvtyJ6vvL)`(J}Rd&5H_=$haZU9OaUi
z&>VHA3i1d#5^2>JIYahq%Bvd*{HT85{s~rx8(?yVm=-`pmx2{u5$x*0!r)WFmig!i
z0b_XZvGU7#mD0%q=Er)5$-!A{&&M_~H&$JIvS~&S-een0yZGf!ykvf}e|%c1iU0CI
z@GwqS9#m8J?K55emomBZXuy{`m{0BG?30phAK0^<7=kxq%~TZhr_~~r^lEDC>M*^4
zEtk9t4gqKI-{OS`7E@rfevMl})pTu<6Tm($9P1%K`MM$~u(giHdUTlSiNvWOtYzV*
z9o0P_azh)C#^5R4J20^9v|pcVo;9iBl)36&vZ^Osjc(|eC>r`Ep1HlA3NQ3sn(-^<
ziVS|uBt>C))GCIrSspp^$}C;IH6Nyz!ulP@!|RqttmcbG60@Bv<A-xd9Wz3+3^Rzx
zE%H%_J6_Sa#=Xt+q<C@;XFnTEfg&V#q6m=@hcyBAHVkXp-daf6#NG*BNC`SMq&Ou2
zSgRftx*4OK>b@@>6D`?qKwks0s`Ufh`Ls4kGExl+!VaK{_(_@UacgtdD9Xf+U>ghK
zr#cxRJaMNt(ys%%*G86-@S%63vtwh1<ahKZ@>$o}`d3ZpHCy;hbKBk4H9)#SjNSwJ
zmX<`w3u8HxD%GCJ+#Wz`qJuPIrqIW4ZVN_-x!G5jWvwSt0QK9}1J=S`qWYw-9X|}=
z@=;KFL83cPsI8~+)NPYt?irWVP&x9@B5GEXjU8fMAg4i&1#wU}4gE(tPkGk6>a%Y2
z(sElpg>@gZl9%#7)M6rkN;LPL7R+I2%jLG=>r*SQC$h`)w8%NJ_NInK<oI^iBQ?N)
z2`u6ijA=V<&a&MY#am|7`yQ|>P8oJ<M*=kLeS3SoiJWKHwI9=poGeVfY_z;r`Rq_*
zu*^=_q4pjS*I5l2^h55KDtNdxJ|NiUOO$4H<KRn(%ht^5EIE#?%F=VRw>S90AwLvT
zW;m;4ZywoiW#%~I7?t&;WjI4GN%>(s=-mi|I9N(1PF|@Zx;E}b<xu~|ER34yG`4@@
z@N5*grURJH;Z~ssbA`i^z1S<(|8j}|mx}$g0US9&)#i8ejKP}<Hoe_&@CsIZa@Sh}
zCIti{i)_ug*f^&=+l7r=q!W;s`NIxToKw7=hv9oFH&!UfeDS<BhqRU{aD4j#jX0DU
z8cS3Ty4|FIJ7)WZwyt7SsKyZ+7dT;L-wGO58D`6P&!~VsaDZz|{rU(SX4*fweiof{
zBH_2d4O|(5K!ObWB0={5@aqVpq878`!)>!j^}ODS-%`)$&qgQ+M8PScv$*v{-pnw5
zky0Qmqd+*tvzhOQJEh!_X=@;XXv+?iIrz__)e~B6F(*^Ppo?L3Aoa1lav$k6{<3aa
z`}};@Pfx|LYkq7G`rljMf2`5|e#_6lzc={*{+rn66RHXbi1={GKrIb8xZ7~1>a;1m
zK-Exqpa2p+@Q$OSD^OC)+|K;_BgX}=^M-D}JsCG~1Jw@J*wn`jdmb>Z8_1luhNTRg
z_CS9m?O}V(Vml}K#0+(JvClQchgh-(s_>zAurO;C;neu{2w=ATJ(Ie@nQDkA(GoR_
zM?UB0u+q;5NsHlcB<@fzdC*zU*h+?c;!v>?S(S_o4!miD6OHy6)k26a$x8ZxtL1JB
zw*4YzTy!{PYX1`Q7s(v;w)Uaua8r`**R_=VwKrX&Opzk*m&9K8M)c;a7_sKkdU;oI
z_xchaLPcb|87Usu2y<HRQ;(D;vx0P^kXPf-yigg_q7U~#RG$<N;>CjF-R?Y(*-pF7
zuZ448hY>OuO1jLZH(6Wvm{<NzX5SmP73Af@bSBj3z!y;rv}t-)E(1ml<%YYwaG8Wo
z-+UXO4r8Yna2*^v)^1K76(}~n_HD!P6DeV}UJ-H9A3Fq3UlO?*ZMoMlt!J>l$N@gt
zL^{<oE3X^<x{dr`hY20#{xBD+zkl%}7ai7=zdu?L$(tHGcxnQlk03xCJ7v=uU+Q%a
zM%oA^rSX0iV4Gd45JtRffaHw1PZ>iUp~f_njUl>tA5QgKW6@iF_0oWFCyb+78hQ)8
z8#9#Sx|IsW20BA`qr#C`H0X}sH>#4j*gL2g)e9fN*9jk;?H%O~e-=%uhd3Rd3U+r>
z)duf|D!@KR7M>j+Q)9%kZuhSD`+hsxWxpYBRnX-CF#UF{v-$ZQ5vbN4Er-Fiy=bI*
z+3XZl$V3tvHur=fleM5jN}R(}_Sv=O6UO~UY|Hq0xB>-l8DX3OcJaoVVawzfCpqzq
zq;n9_UZFXj<mDP_6$w?AuANoK1eNBJwvo0?Q*UD2>6R*@p0lz?(sB~aUJN^BQ|5fy
z5OL?X&wV?vucKO>#;W({3vv+}d@UANVOYCQy4U&qS?$Oxyy-NO$L56UH{Na@S$sxa
zb0#eDd`)&N+xhL?a;@Y|+~ukr)?~)SARR2Hc7tHiMn+7ADp9=Ruyq9*F#%JueY`v7
zA<I#4UP-C59RqIzOlM6?dt}h0u*HQaO!^Ez@rbTu@G*&x`=C{=be_wSJNB_pE-@m`
z&ineWScV|<^<y65$=5ojXdgzdwt^lc6CU?!tn39o+bD;IFGK5iR9`~t#x^RTbqCeZ
z>fK?tLKc({VF!~QUO|1iyefic38sALz0DTa$U*G~qv25~Ll{lCJRuL@!V>xt5#)S$
z7}a6A74F!)IO7A9O`~)g87B;^CXeh%QSo$3l4Ug<QDyi_$v))=HQy-MfOnLlz_jg%
z)!E!`Wo27mT0>MV<+$0`O2)}_uREbhDu`v4@m0XYOPsM0c|#q&;cSaO!sN2a2O;xs
z!9_Y=c(mAvyJ!#(0_6ogE;3<us?dX)Y2Vx;t3s`YLO#ii(Xr?FbgfT1_1$YHxQcVt
zI}MP;<dMV=eP{COkd?hEacNol`cu#as_v`uj}bdnB<Oq@17dbHIz3}>z9fCS6dh?x
z6rQgI5~9+YE@mm})Lg6lc%F|XOTwKb{aW(AceGP<i6C|(5+d<;cFdrg61(p(2)fIu
zbNy_9y_=iX7)7C;0Er2dQtFJ8g;M5pAbKahwF|SN^sSF2MYnQi*3*!0T>RoxJOp0E
z&DbKN2h<wP)BX%r-{6RhCO<C6&FXh6FB)-@BpP<)$vRE2><7tdIuY8dmyb0G@vr&Y
z-J6bZ+H!bW0L#7GrnGqeiosLx5#E{eTdEr^KDmvuP#d}h@eHzR)u<r|rO7OB9YP5b
ztI|9-ABDY7?|A^(+PPh?E_r6&d}rpt3L+}n$545s+cg6(6c6eGbxWr_nH99|-X&Se
zW<t+B2qDAe84-5WJe<3p@q8`wb*x?ET;Foaxq;Sz)muya%9&bnb%&%1<g?ADHbPEf
zV6WN0k^WJG)*z&t!hpH%cHx06^v1XQA~fZ>@3wgw_V?9CXf)q<B5!PzSD3NrOzGvs
z2GX<YVTA1qff|J|ht3<%WTbjF=n(7PU>%X~X(1XT=AGYou#Y)CN*U-HSk@rTemE}m
zS}`Hc&5l3Ox={1=K7q=;@+r=~u>?cvnXT0g&ycTe9_5g@K33t4qsfA#b?cCg3EZFz
zCpRn(e~#JYseTFXJ&bF0n9wbdg(&fdYsreY@N3v<wWwrEky@$+`E-RJppx!9s9<`o
zn%8mL1}=1$Zz;7QIZrYAE|}M*m-F_b;iHpMBIYkmZ%;L_$MuNIB)B<yLg18@h$}f^
z)KW#O`C9PZABaDrJwNs~FQ26{lZ-K2@p5n8?Y>!WIf_6;$sNl2D4~-)du?Dc8IGb<
z{w;3qhYc(vJm7{K7clpv>|>U6TCSJw=Xvi$tVzw?LiH8)3mKi6ABtOfJG3kYH3=Dv
zD;?B;%(=TG_BadB^fvI4w+d2Id=?bmE8fy(3^vsAL`$sHxxS5~VZz6_`TDWH(g1BD
z!<*g)pw84ES@aAWzR6VppM(QdssQ@o%YoJ%Z2s`Fisi*98?Js&xrO~kEs%BUekiMc
zk6sOgDDHUgT24?+ab=F$eSM?KbRXe$Y8F+`xn;wxp1yG5D)8%s{HC;u%uf>@T_nWd
zI3CRp#-Fh*&HC7{r%Bpj#(E=kI%H<i;c4e_d)Gsx5s}f=zM5Yzkj0HvutH4MM|tvv
zaE$kk>T0f}$Bta9Qd0O3mkQ|{Op5I@QAmxB73!f@0V(?%x*gRpu?44`TVKYf{KgYe
zs1vZhDGbH-yrQr1U1wp<pPfM!P1Ajvij!}@M~EL8D2bbgvX2<n=%_$qw44@8C%Uyf
z=B5oLS`=DT%nPW~q+r6J*`ke^J-LH#lb>o#p}?OzN{Jld=yI}B{?uyhW&aihCBo2w
zax9qzlv?j;g5;r3c$@1TG+Pqk!~GD>`yYmsk=%IwYSQh*s+v6w!7Y=~DdrQJeG|0F
zLt!f~mY?LSIh5ZyQXxLDl-5CeJrh*&sYiE6pzG`HY<q93XB{<)^>TNPMEvcc_e9!}
z8~MxTWgg6SAbcF$!kI<cTx>^`%Y2A-_zVmSdHj?dy!<#_w4XY|T}m|YIyJ{$he)N{
zVRxo6a0>r;lE=SAMCJjXQ~>{Y|2fI7ruS{lL9QOQ<}Mef8KXxID}bF?Y`!k^q1BlW
zi-a0AelsQ0!!>xu*xRdOR%y74)8<ECquF{z<=?*4*?7Q(a6Si*Tg^S4j)ENN6=)_l
z<}~dDE;A`YL-(kd%@A@@@o>q-*IpmUw0iA`oaW*p9%3i+=Dl#d?#kxAh1!%|6-K%~
z%xgG~+W+&d(1jS}k<jEO-gf~26+vTG_fiO07Qw)itKCUsY_uxp8zZx?Sc&MLcFrJC
z245Ml;838#+HV%@2o#R{-Ga-W_gVuM{CF#<K5)=5>VcrU?R^wM_csF)Serl<Y-PkT
z?C7r``PsT=Cj|+%s=bQtyQQ-|o-R0Mj`!Q0Y0$+8i4hgu-+gvAepCsidw<Q}P2<2-
zBbs0?Nw<iBf?`Yn`b3xZmYY#Er$28rPZkm%UzW>b+lM9rlR-m@#~)L}Q~L@nB0VMg
z&-{tiLYx8+mv8~}NFz*yEuFOLv~4(Tyq5ORR`T~1v-Zd2m9zZz&*dqi4X47~cJawD
z*&1bD(|!cV?BnOG(9Ljzi~1%>X)#09!%+*G_wXQ?p}WZ+pCz2>4hY+LeIZ?2AsbCO
zpF^D?F&~{HOu}7BzyrHkNHd8@(LlbeOLkl{dDO+7!0tfuIz)pHl_}mL7p+|_zUiGk
zsSb41`W5wUBiz%LPGnEA>DF<pGh>K$PmYr4nZ1u?7u%mI-`6GjDFUE)TcDoX4Y=#@
zzt_J7YR_Jn73Et*c>2`K5_drR|9_8kjV6G>52FryT=cq#U9hARDTY*PHnBQBKeNK4
z_tUyDD?0HksL?NYPL2n)lK2#gTb75ZjufLJW5=fzKrslg)O_6sN04Y7_8~^QgRqTa
z2=TN9wWMimcD}!q`{U=+JBM52WBMo}*4Gh1@kO2Qh^G^WD4DDziOt4M(#z^`aFiOd
zDwxY3dolU(nA}NHrcI%*m1IX7=}f}4U|2l8an7AnQj*UmL?9E4<f1iBzb4MxxO?i}
zwK8Ebo2Tus;v$WAKP4%*93O{Z-iD<Pvm*QfOFGZslc%<uoUnYUu)*6zH2#l#-26mb
z?RFzbkXGR_CNvLTdB^uUh}=C!j<O3P@?tX}fcOT+mVR(A*Lq|xZH#kbO(j4ZPTQ!Z
z$G~2w=4w1{TW2&j>2^w9l7!FAtVU(@Q~)khgnt}OQt&)~K*Z5KWEY{+N*MK+$i9)8
zYF6rz)`XP%4I^|swfPq>!m*&NlKtogNIen74<0(o-n=htqc6!C(0~gnD9~45(UE|i
zQ%$;nUPBHt;8sJFLa9O>Ryc004aU6~k=3-Xj-%5SPo(B|z#}PW)0COMUQ{9aPIs~$
z)upu&)n{;72I3l2M}%{{V<a$9fJ=@)(<<WYUPPcg2DOVer|BWr=&!;md$`0POfHlX
zK?iet`1Y_ocSaQNlozo2Ke}X5o+eIPz-yIVdaa)>95V-J^Z&haet3%TXk(RTcKo(k
zrBf`0SsDFpY%ViuYe@8C$?zwYnRQ}|W2~ETO_h~5+3)#m7Ylwq^Zc?}@}Yn^ngwQ(
zcnfdFj2b>Sk;h$_wlEAVKrJT*E@w^*;+T-2j5$4K1jVWLwM^BZ36Wlxqn@DD;HJIV
zDz8d9f-FzsIcS>p-nl-OIMP>%DM#cJsZ~m`px!lk7PTSdc&%GeWKnu<oomBHEMiP(
zNU<gysxymwAH(Llw?B*JCh{u;o-lrK4fpCBTcdRUV#uCUT(E8=Y-QGZnpoeTY&@w6
zGJ9Qs|6FKTKDFuE*Q(s6{-omg9^uFFI`^3c(~{D57_o7a`Ymyrs1>TBW;(}Q)Dzm#
zNgN3&EX~D4H~bR(ZYGdm>krr3_vuRa_wP(rM72z(#=KAC<8oG?L5@@jWB70qj;+ok
zKjGN)-h`@Y>!s5BFd*`53I0mF<JT&JS7|V{&AEX3yfT#Syz~_P&rEdXlic7JU|LuT
z6o3Y5Ltjn}9i74UuIA1lb5~cey`>A=mDe1s_rdm`bbFlv5|_-Xrki`q&L~ljpOh^=
ze{&<V=Xon$DyOhHzWy8K@TFoY(6Ovf!%R&H3)Lynq=dC#a1Woj-sV<i?sTAD{sHot
zZ(aWA$Swtw!jZB;fBJ#$ZqYQDv2`rRbh5j2`M!vK5>NjL=Kl1GC*S!yL;7dto{EEn
zDVZ^EhHP(hIg*7@awSCK+X=ktB}nxjXww9Nea(7~LI#G1K{s~|?UD*$(%4{Dw~%fg
z5an0^f?Xhq(tFy}`WCD_(#*c&i0Wfm9v?~^To;333p-4<5AoGZ7%4APa%|4hd0NIW
zcQjfLTZ*?K#~v1Ik&nyWUYbZ7I%O7kVsx@)tdp-87HLb(J4AT0%Ed&DHoEOtDB$n<
z`P1;x$9JXf)aoQ&XSdt;l41NR$~SHBOy~&-i9UqH3Gw7!=mWVaUm2-|Vapq+Sen%1
zT5XfNFW$Q=U2`{?(_AQ#{WLOcUL^5U)nHNFF1Uu2`6+{iKt*F*uGy1#F*V9ZXXr#I
z#&AoD>|z<)^itWK*MlUfnjCvvx*}ys0;I<1Wo04jH6G6`Z((?xkCkn$+C74;7Nr|n
zPs%QO1&>f_L!??o7+lVj$R~K;d=7BGn+Da4x>?l~k*e(9|48u}zPEyov?8h*B4ebT
z=Iy=?n<O!_%`&d~Uh!ffqsVBUDPo{h`zZ8n|LRm*h2;^y*Rr-~J-mGWsjy@;b8$RF
z8+-dyx`Ki8re!B(&c}9^T)29Q$daTXFB73WVQGwdh=i+_H1RPneAOFj$G~&Rq?<DF
zrzruvT~6ApeRGc+PU|0*lrqDQbeqj3TL&a+ILU-4#P1=_Lh@UNZ!HG#^y+-s9}=Ex
z`QqFp1gF8_uZN_Eo*})MZu1#c3pr%wYeSI}4TmQiYRsFXH8BB0l_I@cu`?>I>1?$E
z@$O`4)v8G}iHJ}sNL{Oo63ptB6`qyWHbYCrV=Uv^B;}Lq)?J$?yj!OIJkLhZulKiZ
z?Zt4bOu00yQw}~eYVmkT?LpwM&zI|=@j$ulh&t`QC(dUL_IG#uXonog8e5kird`8(
zjWY^mBE~|*m8k6_lg~GKLgh_mo$-m`y%pzcAH<k|xX9L2?j9NHPL3}$bW5*?EDTNQ
zGxq&T$Ss>A9^D@~4INWw8-(fDA#XXylR!+8ZoBoAU=KS>Eld(>g8ZfV<dS(MtnYaN
zW1c#)+*7Z%r3GZuFA0=>>UycF#IFlFAavOy>;#o!;_sXhTk*9A2%X+M0Fm8t_nIDF
zjIl4|b6F;qJu+0c)n*pMRd>qm%pdI8D^_BjXb&5@n{_-};;W-qYqG>t(^uNIMe+Nv
z27iqO$kG0mx&1b%|7Z{x*lIAo#~MF8`NcDR2?xM`*t;5QcsQE77+wr?stUgXq-_My
zVgdjQz{m*rrJoKoV3KL<Y;Nnq#(MF1wV{~-Raq18bzYz`<xkCkD$777`67etVhaYi
z1=zl0T)wzWB>yQI_nWOqIsnNT_|c2L{y1cS6!it#cbJP%1L%;cE7-yQqC0;IwpHRQ
zuLJa_98k(dI{U{_3UEnWfL(>T+PSlp>|jdZhZ{wJ3f4cG1J8spf9c$hZe4{K9gN<o
z2O3=H2dLNo)A1ZY{9Ql4kx>7nrSETDQc?eD_qcki`hYUYa2<f2e?^W52nl{iRx)(~
z#*Sa~|NX7MJ_~;>Gd%H6$bTvGB@fb{%KX>Js3iXe`H}+iACXyp(lQX90_Del*T!GU
z%<=Ek@hddx&3^^W{+A~D*ZQCWh(7*V>P!B%f7HjX*1>e^-yq-pFJ$Hf){XvIX3qZt
zSrBjr|BTG_Um#0R{u|^=O6vbZJuBS)H^_f&c3=7UIY<CMm=CzGJHJ>o2zdDiZCtvb
z@8<p8malrE#>IsAW58D|12iCjXg?i!K+*l*@qY6cmv}#UimPzXm1%}j0P&E3^v|zw
zOTZ8O4)@yy_p^8xr|BvjW{$&7IWX^i0gOJs!nJVzJ=~?GUWMC1wFut;q|^O_bd^A8
z_;=D>n&(wGBNly)Za}(TK)PSg#e&e^!*N_*{8#ZdqZj<W0P(DFul9CR?C<d|ZTu=+
z*DfEGC?H-HFjoDlyexpL=I?rYIlNqjyGqvn!&GPh3Yx!zySz@W!d>O~{Q)Nou;Kh2
z+@-s}3U`&?@(0{=fb8e*;4Z!8Rk*7Je?Q=603M;ggS#B&zQg@BH`Na~XT!f_s=6xE
z)rI&UAYIwtWxBd7e-+{C3d0Ws&Z6%KzpOW0ZGJU({i8W?$$td+HIsc6;A(#O2f+S+
z0Dj39Uv2(thVw^bU}jkMlNSGz@4VXj*EG-1t#d1XYW-W%=W6q-A@~mf<?8R9zY>7|
ZX+W;3fP{R}k{0+&1KdWy#Vio+e*mTV$`1el


From 53f6bb1dfec74cbe8be9ae6a670d82eb6759cc8c Mon Sep 17 00:00:00 2001
From: raschild <raschild@users.noreply.github.com>
Date: Thu, 9 Apr 2015 07:04:18 -0400
Subject: [PATCH 26/95] SPARK-4924 addendum. Minor assembly directory fix in
 load-spark-env-sh

Set the current dir path $FWDIR and same at $ASSEMBLY_DIR1, $ASSEMBLY_DIR2
otherwise $SPARK_HOME cannot be visible from spark-env.sh -- no SPARK_HOME variable is assigned there.
I am using the Spark-1.3.0 source code package and I come across with this when trying to start the master: sbin/start-master.sh

Author: raschild <raschild@users.noreply.github.com>

Closes #5261 from raschild/patch-1 and squashes the following commits:

b9babcd [raschild] Update load-spark-env.sh
---
 bin/load-spark-env.sh | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/bin/load-spark-env.sh b/bin/load-spark-env.sh
index 2d7070c25d328..95779e9ddbb18 100644
--- a/bin/load-spark-env.sh
+++ b/bin/load-spark-env.sh
@@ -20,6 +20,7 @@
 # This script loads spark-env.sh if it exists, and ensures it is only loaded once.
 # spark-env.sh is loaded from SPARK_CONF_DIR if set, or within the current directory's
 # conf/ subdirectory.
+FWDIR="$(cd "`dirname "$0"`"/..; pwd)"
 
 if [ -z "$SPARK_ENV_LOADED" ]; then
   export SPARK_ENV_LOADED=1
@@ -41,8 +42,8 @@ fi
 
 if [ -z "$SPARK_SCALA_VERSION" ]; then
 
-    ASSEMBLY_DIR2="$SPARK_HOME/assembly/target/scala-2.11"
-    ASSEMBLY_DIR1="$SPARK_HOME/assembly/target/scala-2.10"
+    ASSEMBLY_DIR2="$FWDIR/assembly/target/scala-2.11"
+    ASSEMBLY_DIR1="$FWDIR/assembly/target/scala-2.10"
 
     if [[ -d "$ASSEMBLY_DIR2" && -d "$ASSEMBLY_DIR1" ]]; then
         echo -e "Presence of build for both scala versions(SCALA 2.10 and SCALA 2.11) detected." 1>&2

From 470d7453a56c56a41b2851551fe1830065f88b2c Mon Sep 17 00:00:00 2001
From: Marcelo Vanzin <vanzin@cloudera.com>
Date: Thu, 9 Apr 2015 07:07:50 -0400
Subject: [PATCH 27/95] [minor] [examples] Avoid packaging duplicate classes.

Add exclusions and explicit dependencies so that the examples
assembly does not duplicate classes already packaged in the main
assembly.

Also avoid relocating the commons-math3 package since it's already
a dependency of spark-core, and thus is already available in the
main assembly.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #5379 from vanzin/examples-deps and squashes the following commits:

12c258e [Marcelo Vanzin] [minor] [examples] Avoid re-packaging unneeded classes.
---
 examples/pom.xml | 52 ++++++++++++++++++++++++++++++++++++++++++------
 1 file changed, 46 insertions(+), 6 deletions(-)

diff --git a/examples/pom.xml b/examples/pom.xml
index 7e93f0eec0b91..afd7c6d52f0dd 100644
--- a/examples/pom.xml
+++ b/examples/pom.xml
@@ -90,6 +90,12 @@
       <groupId>org.apache.spark</groupId>
       <artifactId>spark-streaming-zeromq_${scala.binary.version}</artifactId>
       <version>${project.version}</version>
+      <exclusions>
+        <exclusion>
+          <groupId>org.spark-project.protobuf</groupId>
+          <artifactId>protobuf-java</artifactId>
+        </exclusion>
+      </exclusions>
     </dependency>
     <dependency>
       <groupId>org.apache.hbase</groupId>
@@ -234,6 +240,7 @@
     <dependency>
       <groupId>org.apache.commons</groupId>
       <artifactId>commons-math3</artifactId>
+      <scope>provided</scope>
     </dependency>
     <dependency>
       <groupId>com.twitter</groupId>
@@ -262,6 +269,22 @@
           <groupId>com.ning</groupId>
           <artifactId>compress-lzf</artifactId>
         </exclusion>
+        <exclusion>
+          <groupId>commons-cli</groupId>
+          <artifactId>commons-cli</artifactId>
+        </exclusion>
+        <exclusion>
+          <groupId>commons-codec</groupId>
+          <artifactId>commons-codec</artifactId>
+        </exclusion>
+        <exclusion>
+          <groupId>commons-lang</groupId>
+          <artifactId>commons-lang</artifactId>
+        </exclusion>
+        <exclusion>
+          <groupId>commons-logging</groupId>
+          <artifactId>commons-logging</artifactId>
+        </exclusion>
         <exclusion>
           <groupId>io.netty</groupId>
           <artifactId>netty</artifactId>
@@ -270,10 +293,22 @@
           <groupId>jline</groupId>
           <artifactId>jline</artifactId>
         </exclusion>
+        <exclusion>
+          <groupId>net.jpountz.lz4</groupId>
+          <artifactId>lz4</artifactId>
+        </exclusion>
         <exclusion>
           <groupId>org.apache.cassandra.deps</groupId>
           <artifactId>avro</artifactId>
         </exclusion>
+        <exclusion>
+          <groupId>org.apache.commons</groupId>
+          <artifactId>commons-math3</artifactId>
+        </exclusion>
+        <exclusion>
+          <groupId>org.apache.thrift</groupId>
+          <artifactId>libthrift</artifactId>
+        </exclusion>
       </exclusions>
     </dependency>
     <dependency>
@@ -281,6 +316,17 @@
       <artifactId>scopt_${scala.binary.version}</artifactId>
       <version>3.2.0</version>
     </dependency>
+
+    <!--
+      The following dependencies are already present in the Spark assembly, so we want to force
+      them to be provided.
+    -->
+    <dependency>
+      <groupId>org.scala-lang</groupId>
+      <artifactId>scala-library</artifactId>
+      <scope>provided</scope>
+    </dependency>
+
   </dependencies>
 
   <build>
@@ -322,12 +368,6 @@
               </excludes>
             </filter>
           </filters>
-          <relocations combine.children="append">
-            <relocation>
-              <pattern>org.apache.commons.math3</pattern>
-              <shadedPattern>org.spark-project.commons.math3</shadedPattern>
-            </relocation>
-          </relocations>
           <transformers>
             <transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer" />
             <transformer implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">

From 7d92db342e01fa694d3522fb8d2254d6297a4203 Mon Sep 17 00:00:00 2001
From: WangTaoTheTonic <wangtao111@huawei.com>
Date: Thu, 9 Apr 2015 17:44:08 -0400
Subject: [PATCH 28/95] [SPARK-6758]block the right jetty package in log

https://issues.apache.org/jira/browse/SPARK-6758

I am not sure if it is ok to block them in test resources too (as we shade jetty in assembly?).

Author: WangTaoTheTonic <wangtao111@huawei.com>

Closes #5406 from WangTaoTheTonic/SPARK-6758 and squashes the following commits:

e09605b [WangTaoTheTonic] block the right jetty package
---
 bagel/src/test/resources/log4j.properties                     | 2 +-
 conf/log4j.properties.template                                | 4 ++--
 .../main/resources/org/apache/spark/log4j-defaults.properties | 4 ++--
 core/src/test/resources/log4j.properties                      | 4 ++--
 external/flume-sink/src/test/resources/log4j.properties       | 2 +-
 external/flume/src/test/resources/log4j.properties            | 2 +-
 external/kafka/src/test/resources/log4j.properties            | 2 +-
 external/mqtt/src/test/resources/log4j.properties             | 2 +-
 external/twitter/src/test/resources/log4j.properties          | 2 +-
 external/zeromq/src/test/resources/log4j.properties           | 2 +-
 extras/java8-tests/src/test/resources/log4j.properties        | 4 ++--
 extras/kinesis-asl/src/main/resources/log4j.properties        | 4 ++--
 extras/kinesis-asl/src/test/resources/log4j.properties        | 2 +-
 graphx/src/test/resources/log4j.properties                    | 4 ++--
 launcher/src/test/resources/log4j.properties                  | 4 ++--
 mllib/src/test/resources/log4j.properties                     | 2 +-
 repl/src/test/resources/log4j.properties                      | 2 +-
 sql/catalyst/src/test/resources/log4j.properties              | 4 ++--
 streaming/src/test/resources/log4j.properties                 | 2 +-
 yarn/src/test/resources/log4j.properties                      | 2 +-
 20 files changed, 28 insertions(+), 28 deletions(-)

diff --git a/bagel/src/test/resources/log4j.properties b/bagel/src/test/resources/log4j.properties
index 853ef0ed2986f..edbecdae92096 100644
--- a/bagel/src/test/resources/log4j.properties
+++ b/bagel/src/test/resources/log4j.properties
@@ -24,4 +24,4 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
+log4j.logger.org.spark-project.jetty=WARN
diff --git a/conf/log4j.properties.template b/conf/log4j.properties.template
index 89eec7d4b7f61..3a2a88219818f 100644
--- a/conf/log4j.properties.template
+++ b/conf/log4j.properties.template
@@ -6,7 +6,7 @@ log4j.appender.console.layout=org.apache.log4j.PatternLayout
 log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{1}: %m%n
 
 # Settings to quiet third party logs that are too verbose
-log4j.logger.org.eclipse.jetty=WARN
-log4j.logger.org.eclipse.jetty.util.component.AbstractLifeCycle=ERROR
+log4j.logger.org.spark-project.jetty=WARN
+log4j.logger.org.spark-project.jetty.util.component.AbstractLifeCycle=ERROR
 log4j.logger.org.apache.spark.repl.SparkIMain$exprTyper=INFO
 log4j.logger.org.apache.spark.repl.SparkILoop$SparkILoopInterpreter=INFO
diff --git a/core/src/main/resources/org/apache/spark/log4j-defaults.properties b/core/src/main/resources/org/apache/spark/log4j-defaults.properties
index 89eec7d4b7f61..3a2a88219818f 100644
--- a/core/src/main/resources/org/apache/spark/log4j-defaults.properties
+++ b/core/src/main/resources/org/apache/spark/log4j-defaults.properties
@@ -6,7 +6,7 @@ log4j.appender.console.layout=org.apache.log4j.PatternLayout
 log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{1}: %m%n
 
 # Settings to quiet third party logs that are too verbose
-log4j.logger.org.eclipse.jetty=WARN
-log4j.logger.org.eclipse.jetty.util.component.AbstractLifeCycle=ERROR
+log4j.logger.org.spark-project.jetty=WARN
+log4j.logger.org.spark-project.jetty.util.component.AbstractLifeCycle=ERROR
 log4j.logger.org.apache.spark.repl.SparkIMain$exprTyper=INFO
 log4j.logger.org.apache.spark.repl.SparkILoop$SparkILoopInterpreter=INFO
diff --git a/core/src/test/resources/log4j.properties b/core/src/test/resources/log4j.properties
index 287c8e3563503..eb3b1999eb996 100644
--- a/core/src/test/resources/log4j.properties
+++ b/core/src/test/resources/log4j.properties
@@ -24,5 +24,5 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
-org.eclipse.jetty.LEVEL=WARN
+log4j.logger.org.spark-project.jetty=WARN
+org.spark-project.jetty.LEVEL=WARN
diff --git a/external/flume-sink/src/test/resources/log4j.properties b/external/flume-sink/src/test/resources/log4j.properties
index 2a58e99817224..42df8792f147f 100644
--- a/external/flume-sink/src/test/resources/log4j.properties
+++ b/external/flume-sink/src/test/resources/log4j.properties
@@ -24,5 +24,5 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
+log4j.logger.org.spark-project.jetty=WARN
 
diff --git a/external/flume/src/test/resources/log4j.properties b/external/flume/src/test/resources/log4j.properties
index 9697237bfa1a3..75e3b53a093f6 100644
--- a/external/flume/src/test/resources/log4j.properties
+++ b/external/flume/src/test/resources/log4j.properties
@@ -24,5 +24,5 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
+log4j.logger.org.spark-project.jetty=WARN
 
diff --git a/external/kafka/src/test/resources/log4j.properties b/external/kafka/src/test/resources/log4j.properties
index 9697237bfa1a3..75e3b53a093f6 100644
--- a/external/kafka/src/test/resources/log4j.properties
+++ b/external/kafka/src/test/resources/log4j.properties
@@ -24,5 +24,5 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
+log4j.logger.org.spark-project.jetty=WARN
 
diff --git a/external/mqtt/src/test/resources/log4j.properties b/external/mqtt/src/test/resources/log4j.properties
index 9697237bfa1a3..75e3b53a093f6 100644
--- a/external/mqtt/src/test/resources/log4j.properties
+++ b/external/mqtt/src/test/resources/log4j.properties
@@ -24,5 +24,5 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
+log4j.logger.org.spark-project.jetty=WARN
 
diff --git a/external/twitter/src/test/resources/log4j.properties b/external/twitter/src/test/resources/log4j.properties
index 64bfc5745088f..9a3569789d2e0 100644
--- a/external/twitter/src/test/resources/log4j.properties
+++ b/external/twitter/src/test/resources/log4j.properties
@@ -24,5 +24,5 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
+log4j.logger.org.spark-project.jetty=WARN
 
diff --git a/external/zeromq/src/test/resources/log4j.properties b/external/zeromq/src/test/resources/log4j.properties
index 9697237bfa1a3..75e3b53a093f6 100644
--- a/external/zeromq/src/test/resources/log4j.properties
+++ b/external/zeromq/src/test/resources/log4j.properties
@@ -24,5 +24,5 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
+log4j.logger.org.spark-project.jetty=WARN
 
diff --git a/extras/java8-tests/src/test/resources/log4j.properties b/extras/java8-tests/src/test/resources/log4j.properties
index 287c8e3563503..eb3b1999eb996 100644
--- a/extras/java8-tests/src/test/resources/log4j.properties
+++ b/extras/java8-tests/src/test/resources/log4j.properties
@@ -24,5 +24,5 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
-org.eclipse.jetty.LEVEL=WARN
+log4j.logger.org.spark-project.jetty=WARN
+org.spark-project.jetty.LEVEL=WARN
diff --git a/extras/kinesis-asl/src/main/resources/log4j.properties b/extras/kinesis-asl/src/main/resources/log4j.properties
index 97348fb5b6123..6cdc9286c5d76 100644
--- a/extras/kinesis-asl/src/main/resources/log4j.properties
+++ b/extras/kinesis-asl/src/main/resources/log4j.properties
@@ -31,7 +31,7 @@ log4j.appender.console.layout=org.apache.log4j.PatternLayout
 log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{1}: %m%n
 
 # Settings to quiet third party logs that are too verbose
-log4j.logger.org.eclipse.jetty=WARN
-log4j.logger.org.eclipse.jetty.util.component.AbstractLifeCycle=ERROR
+log4j.logger.org.spark-project.jetty=WARN
+log4j.logger.org.spark-project.jetty.util.component.AbstractLifeCycle=ERROR
 log4j.logger.org.apache.spark.repl.SparkIMain$exprTyper=INFO
 log4j.logger.org.apache.spark.repl.SparkILoop$SparkILoopInterpreter=INFO
\ No newline at end of file
diff --git a/extras/kinesis-asl/src/test/resources/log4j.properties b/extras/kinesis-asl/src/test/resources/log4j.properties
index 853ef0ed2986f..edbecdae92096 100644
--- a/extras/kinesis-asl/src/test/resources/log4j.properties
+++ b/extras/kinesis-asl/src/test/resources/log4j.properties
@@ -24,4 +24,4 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
+log4j.logger.org.spark-project.jetty=WARN
diff --git a/graphx/src/test/resources/log4j.properties b/graphx/src/test/resources/log4j.properties
index 287c8e3563503..eb3b1999eb996 100644
--- a/graphx/src/test/resources/log4j.properties
+++ b/graphx/src/test/resources/log4j.properties
@@ -24,5 +24,5 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
-org.eclipse.jetty.LEVEL=WARN
+log4j.logger.org.spark-project.jetty=WARN
+org.spark-project.jetty.LEVEL=WARN
diff --git a/launcher/src/test/resources/log4j.properties b/launcher/src/test/resources/log4j.properties
index 00c20ad69cd4d..67a6a98217118 100644
--- a/launcher/src/test/resources/log4j.properties
+++ b/launcher/src/test/resources/log4j.properties
@@ -27,5 +27,5 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
-org.eclipse.jetty.LEVEL=WARN
+log4j.logger.org.spark-project.jetty=WARN
+org.spark-project.jetty.LEVEL=WARN
diff --git a/mllib/src/test/resources/log4j.properties b/mllib/src/test/resources/log4j.properties
index 9697237bfa1a3..75e3b53a093f6 100644
--- a/mllib/src/test/resources/log4j.properties
+++ b/mllib/src/test/resources/log4j.properties
@@ -24,5 +24,5 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
+log4j.logger.org.spark-project.jetty=WARN
 
diff --git a/repl/src/test/resources/log4j.properties b/repl/src/test/resources/log4j.properties
index e7e4a4113174a..e2ee9c963a4da 100644
--- a/repl/src/test/resources/log4j.properties
+++ b/repl/src/test/resources/log4j.properties
@@ -24,4 +24,4 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
+log4j.logger.org.spark-project.jetty=WARN
diff --git a/sql/catalyst/src/test/resources/log4j.properties b/sql/catalyst/src/test/resources/log4j.properties
index 287c8e3563503..eb3b1999eb996 100644
--- a/sql/catalyst/src/test/resources/log4j.properties
+++ b/sql/catalyst/src/test/resources/log4j.properties
@@ -24,5 +24,5 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
-org.eclipse.jetty.LEVEL=WARN
+log4j.logger.org.spark-project.jetty=WARN
+org.spark-project.jetty.LEVEL=WARN
diff --git a/streaming/src/test/resources/log4j.properties b/streaming/src/test/resources/log4j.properties
index 9697237bfa1a3..75e3b53a093f6 100644
--- a/streaming/src/test/resources/log4j.properties
+++ b/streaming/src/test/resources/log4j.properties
@@ -24,5 +24,5 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
+log4j.logger.org.spark-project.jetty=WARN
 
diff --git a/yarn/src/test/resources/log4j.properties b/yarn/src/test/resources/log4j.properties
index aab41fa49430f..6b8a5dbf6373e 100644
--- a/yarn/src/test/resources/log4j.properties
+++ b/yarn/src/test/resources/log4j.properties
@@ -24,5 +24,5 @@ log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 
 # Ignore messages below warning level from Jetty, because it's a bit verbose
-log4j.logger.org.eclipse.jetty=WARN
+log4j.logger.org.spark-project.jetty=WARN
 log4j.logger.org.apache.hadoop=WARN

From a0411aebee7c134f0426f0c2b2cb4c1c7856a291 Mon Sep 17 00:00:00 2001
From: Yanbo Liang <ybliang8@gmail.com>
Date: Thu, 9 Apr 2015 15:10:10 -0700
Subject: [PATCH 29/95] [SPARK-6264] [MLLIB] Support FPGrowth algorithm in
 Python API

Support FPGrowth algorithm in Python API.
Should we remove "Experimental" which were marked for FPGrowth and FPGrowthModel in Scala? jkbradley

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #5213 from yanboliang/spark-6264 and squashes the following commits:

ed62ead [Yanbo Liang] trigger jenkins
8ce0359 [Yanbo Liang] fix docstring style
544c725 [Yanbo Liang] address comments
a2d7cf7 [Yanbo Liang] add doc for FPGrowth.train()
dcf7d73 [Yanbo Liang] add python doc
b18fd07 [Yanbo Liang] trigger jenkins
2c951b8 [Yanbo Liang] fix typos
7f62c8f [Yanbo Liang] add fpm to __init__.py
b96206a [Yanbo Liang] Support FPGrowth algorithm in Python API
---
 .../api/python/FPGrowthModelWrapper.scala     | 33 ++++++++
 .../mllib/api/python/PythonMLLibAPI.scala     | 23 +++++-
 python/docs/pyspark.mllib.rst                 |  7 ++
 python/pyspark/mllib/__init__.py              |  2 +-
 python/pyspark/mllib/fpm.py                   | 81 +++++++++++++++++++
 python/run-tests                              |  1 +
 6 files changed, 143 insertions(+), 4 deletions(-)
 create mode 100644 mllib/src/main/scala/org/apache/spark/mllib/api/python/FPGrowthModelWrapper.scala
 create mode 100644 python/pyspark/mllib/fpm.py

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/api/python/FPGrowthModelWrapper.scala b/mllib/src/main/scala/org/apache/spark/mllib/api/python/FPGrowthModelWrapper.scala
new file mode 100644
index 0000000000000..ee933f4cfcafd
--- /dev/null
+++ b/mllib/src/main/scala/org/apache/spark/mllib/api/python/FPGrowthModelWrapper.scala
@@ -0,0 +1,33 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.mllib.api.python
+
+import org.apache.spark.api.java.JavaRDD
+import org.apache.spark.mllib.fpm.{FPGrowth, FPGrowthModel}
+import org.apache.spark.rdd.RDD
+
+/**
+ * A Wrapper of FPGrowthModel to provide helper method for Python
+ */
+private[python] class FPGrowthModelWrapper(model: FPGrowthModel[Any])
+  extends FPGrowthModel(model.freqItemsets) {
+
+  def getFreqItemsets: RDD[Array[Any]] = {
+    SerDe.fromTuple2RDD(model.freqItemsets.map(x => (x.javaItems, x.freq)))
+  }
+}
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
index 6c386cacfb7ca..1faa3def0e042 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
@@ -34,6 +34,7 @@ import org.apache.spark.api.python.SerDeUtil
 import org.apache.spark.mllib.classification._
 import org.apache.spark.mllib.clustering._
 import org.apache.spark.mllib.feature._
+import org.apache.spark.mllib.fpm.{FPGrowth, FPGrowthModel}
 import org.apache.spark.mllib.linalg._
 import org.apache.spark.mllib.optimization._
 import org.apache.spark.mllib.random.{RandomRDDs => RG}
@@ -358,9 +359,7 @@ private[python] class PythonMLLibAPI extends Serializable {
       val model = new GaussianMixtureModel(weight, gaussians)
       model.predictSoft(data)
   }
-
-
-
+  
   /**
    * Java stub for Python mllib ALS.train().  This stub returns a handle
    * to the Java object instead of the content of the Java object.  Extra care
@@ -420,6 +419,24 @@ private[python] class PythonMLLibAPI extends Serializable {
     new MatrixFactorizationModelWrapper(model)
   }
 
+  /**
+   * Java stub for Python mllib FPGrowth.train().  This stub returns a handle
+   * to the Java object instead of the content of the Java object.  Extra care
+   * needs to be taken in the Python code to ensure it gets freed on exit; see
+   * the Py4J documentation.
+   */
+  def trainFPGrowthModel(
+      data: JavaRDD[java.lang.Iterable[Any]],
+      minSupport: Double,
+      numPartitions: Int): FPGrowthModel[Any] = {
+    val fpg = new FPGrowth()
+      .setMinSupport(minSupport)
+      .setNumPartitions(numPartitions)
+
+    val model = fpg.run(data.rdd.map(_.asScala.toArray))
+    new FPGrowthModelWrapper(model)
+  }
+
   /**
    * Java stub for Normalizer.transform()
    */
diff --git a/python/docs/pyspark.mllib.rst b/python/docs/pyspark.mllib.rst
index 15101470afc07..26ece4c2c389a 100644
--- a/python/docs/pyspark.mllib.rst
+++ b/python/docs/pyspark.mllib.rst
@@ -31,6 +31,13 @@ pyspark.mllib.feature module
     :undoc-members:
     :show-inheritance:
 
+pyspark.mllib.fpm module
+------------------------
+
+.. automodule:: pyspark.mllib.fpm
+    :members:
+    :undoc-members:
+
 pyspark.mllib.linalg module
 ---------------------------
 
diff --git a/python/pyspark/mllib/__init__.py b/python/pyspark/mllib/__init__.py
index 6449800d9c120..f2ef573fe9f6f 100644
--- a/python/pyspark/mllib/__init__.py
+++ b/python/pyspark/mllib/__init__.py
@@ -25,7 +25,7 @@
 if numpy.version.version < '1.4':
     raise Exception("MLlib requires NumPy 1.4+")
 
-__all__ = ['classification', 'clustering', 'feature', 'linalg', 'random',
+__all__ = ['classification', 'clustering', 'feature', 'fpm', 'linalg', 'random',
            'recommendation', 'regression', 'stat', 'tree', 'util']
 
 import sys
diff --git a/python/pyspark/mllib/fpm.py b/python/pyspark/mllib/fpm.py
new file mode 100644
index 0000000000000..3aa6d79d7093c
--- /dev/null
+++ b/python/pyspark/mllib/fpm.py
@@ -0,0 +1,81 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+from pyspark import SparkContext
+from pyspark.mllib.common import JavaModelWrapper, callMLlibFunc, inherit_doc
+
+__all__ = ['FPGrowth', 'FPGrowthModel']
+
+
+@inherit_doc
+class FPGrowthModel(JavaModelWrapper):
+
+    """
+    .. note:: Experimental
+
+    A FP-Growth model for mining frequent itemsets
+    using the Parallel FP-Growth algorithm.
+
+    >>> data = [["a", "b", "c"], ["a", "b", "d", "e"], ["a", "c", "e"], ["a", "c", "f"]]
+    >>> rdd = sc.parallelize(data, 2)
+    >>> model = FPGrowth.train(rdd, 0.6, 2)
+    >>> sorted(model.freqItemsets().collect())
+    [([u'a'], 4), ([u'c'], 3), ([u'c', u'a'], 3)]
+    """
+
+    def freqItemsets(self):
+        """
+        Get the frequent itemsets of this model
+        """
+        return self.call("getFreqItemsets")
+
+
+class FPGrowth(object):
+    """
+    .. note:: Experimental
+
+    A Parallel FP-growth algorithm to mine frequent itemsets.
+    """
+
+    @classmethod
+    def train(cls, data, minSupport=0.3, numPartitions=-1):
+        """
+        Computes an FP-Growth model that contains frequent itemsets.
+        :param data:            The input data set, each element
+                                contains a transaction.
+        :param minSupport:      The minimal support level
+                                (default: `0.3`).
+        :param numPartitions:   The number of partitions used by parallel
+                                FP-growth (default: same as input data).
+        """
+        model = callMLlibFunc("trainFPGrowthModel", data, float(minSupport), int(numPartitions))
+        return FPGrowthModel(model)
+
+
+def _test():
+    import doctest
+    import pyspark.mllib.fpm
+    globs = pyspark.mllib.fpm.__dict__.copy()
+    globs['sc'] = SparkContext('local[4]', 'PythonTest')
+    (failure_count, test_count) = doctest.testmod(globs=globs, optionflags=doctest.ELLIPSIS)
+    globs['sc'].stop()
+    if failure_count:
+        exit(-1)
+
+
+if __name__ == "__main__":
+    _test()
diff --git a/python/run-tests b/python/run-tests
index b7630c356cfae..f569a56fb7a9a 100755
--- a/python/run-tests
+++ b/python/run-tests
@@ -77,6 +77,7 @@ function run_mllib_tests() {
     run_test "pyspark/mllib/clustering.py"
     run_test "pyspark/mllib/evaluation.py"
     run_test "pyspark/mllib/feature.py"
+    run_test "pyspark/mllib/fpm.py"
     run_test "pyspark/mllib/linalg.py"
     run_test "pyspark/mllib/rand.py"
     run_test "pyspark/mllib/recommendation.py"

From 9c67049b4ef416a80803ccb958bbac1dd02cc380 Mon Sep 17 00:00:00 2001
From: Yuhao Yang <hhbyyh@gmail.com>
Date: Thu, 9 Apr 2015 15:37:45 -0700
Subject: [PATCH 30/95] [Spark-6693][MLlib]add tostring with max lines and
 width for matrix

jira: https://issues.apache.org/jira/browse/SPARK-6693

It's kind of annoying when debugging and found you cannot print out the matrix as you want.

original toString of Matrix only print like following,
0.17810102596909183    0.5616906241468385    ... (10 total)
0.9692861997823815     0.015558159784155756  ...
0.8513015122819192     0.031523763918528847  ...
0.5396875653953941     0.3267864552779176    ...

The   def toString(maxLines : Int, maxWidth : Int) is useful when debuging, logging and saving matrix to files.

Author: Yuhao Yang <hhbyyh@gmail.com>

Closes #5344 from hhbyyh/addToString and squashes the following commits:

19a6836 [Yuhao Yang] remove extra line
6314b21 [Yuhao Yang] add exclude
736c324 [Yuhao Yang] add ut and exclude
420da39 [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into addToString
c22f352 [Yuhao Yang] style change
64a9e0f [Yuhao Yang] add specific to string to matrix
---
 .../org/apache/spark/mllib/linalg/Matrices.scala |  3 +++
 .../spark/mllib/linalg/MatricesSuite.scala       | 16 ++++++++++++++++
 project/MimaExcludes.scala                       |  4 ++++
 3 files changed, 23 insertions(+)

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala
index d1a174063caba..3fa5e068d16d4 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala
@@ -87,6 +87,9 @@ sealed trait Matrix extends Serializable {
   /** A human readable representation of the matrix */
   override def toString: String = toBreeze.toString()
 
+  /** A human readable representation of the matrix with maximum lines and width */
+  def toString(maxLines: Int, maxLineWidth: Int): String = toBreeze.toString(maxLines, maxLineWidth)
+
   /** Map the values of this matrix using a function. Generates a new matrix. Performs the
     * function on only the backing array. For example, an operation such as addition or
     * subtraction will only be performed on the non-zero values in a `SparseMatrix`. */
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala
index 0d2cec58e2c03..86119ec38101e 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala
@@ -439,4 +439,20 @@ class MatricesSuite extends FunSuite {
     assert(mUDT.typeName == "matrix")
     assert(mUDT.simpleString == "matrix")
   }
+
+  test("toString") {
+    val empty = Matrices.ones(0, 0)
+    empty.toString(0, 0)
+
+    val mat = Matrices.rand(5, 10, new Random())
+    mat.toString(-1, -5)
+    mat.toString(0, 0)
+    mat.toString(Int.MinValue, Int.MinValue)
+    mat.toString(Int.MaxValue, Int.MaxValue)
+    var lines = mat.toString(6, 50).lines.toArray
+    assert(lines.size == 5 && lines.forall(_.size <= 50))
+
+    lines = mat.toString(5, 100).lines.toArray
+    assert(lines.size == 5 && lines.forall(_.size <= 100))
+  }
 }
diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala
index c2d828f982fe0..1564babefa62f 100644
--- a/project/MimaExcludes.scala
+++ b/project/MimaExcludes.scala
@@ -64,6 +64,10 @@ object MimaExcludes {
             // SPARK-6492 Fix deadlock in SparkContext.stop()
             ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.SparkContext.org$" +
                 "apache$spark$SparkContext$$SPARK_CONTEXT_CONSTRUCTOR_LOCK")
+          )++ Seq(
+            // SPARK-6693 add tostring with max lines and width for matrix
+            ProblemFilters.exclude[MissingMethodProblem](
+              "org.apache.spark.mllib.linalg.Matrix.toString")
           )
 
         case v if v.startsWith("1.3") =>

From b5c51c8df480f1a82a82e4d597d8eea631bffb4e Mon Sep 17 00:00:00 2001
From: Davies Liu <davies.liu@gmail.com>
Date: Thu, 9 Apr 2015 17:07:23 -0700
Subject: [PATCH 31/95] [SPARK-3074] [PySpark] support groupByKey() with single
 huge key

This patch change groupByKey() to use external sort based approach, so it can support single huge key.

For example, it can group by a dataset including one hot key with 40 millions values (strings), using 500M memory for Python worker, finished in about 2 minutes. (it will need 6G memory in hash based approach).

During groupByKey(), it will do in-memory groupBy first. If the dataset can not fit in memory, then data will be partitioned by hash. If one partition still can not fit in memory, it will switch to sort based groupBy().

Author: Davies Liu <davies.liu@gmail.com>
Author: Davies Liu <davies@databricks.com>

Closes #1977 from davies/groupby and squashes the following commits:

af3713a [Davies Liu] make sure it's iterator
67772dd [Davies Liu] fix tests
e78c15c [Davies Liu] address comments
0b0fde8 [Davies Liu] address comments
0dcf320 [Davies Liu] address comments, rollback changes in ResultIterable
e3b8eab [Davies Liu] fix narrow dependency
2a1857a [Davies Liu] typo
d2f053b [Davies Liu] add repr for FlattedValuesSerializer
c6a2f8d [Davies Liu] address comments
9e2df24 [Davies Liu] Merge branch 'master' of github.com:apache/spark into groupby
2b9c261 [Davies Liu] fix typo in comments
70aadcd [Davies Liu] Merge branch 'master' of github.com:apache/spark into groupby
a14b4bd [Davies Liu] Merge branch 'master' of github.com:apache/spark into groupby
ab5515b [Davies Liu] Merge branch 'master' into groupby
651f891 [Davies Liu] simplify GroupByKey
1578f2e [Davies Liu] Merge branch 'master' of github.com:apache/spark into groupby
1f69f93 [Davies Liu] fix tests
0d3395f [Davies Liu] Merge branch 'master' of github.com:apache/spark into groupby
341f1e0 [Davies Liu] add comments, refactor
47918b8 [Davies Liu] remove unused code
6540948 [Davies Liu] address comments:
17f4ec6 [Davies Liu] Merge branch 'master' of github.com:apache/spark into groupby
4d4bc86 [Davies Liu] bugfix
8ef965e [Davies Liu] Merge branch 'master' into groupby
fbc504a [Davies Liu] Merge branch 'master' into groupby
779ed03 [Davies Liu] fix merge conflict
2c1d05b [Davies Liu] refactor, minor turning
b48cda5 [Davies Liu] Merge branch 'master' into groupby
85138e6 [Davies Liu] Merge branch 'master' into groupby
acd8e1b [Davies Liu] fix memory when groupByKey().count()
905b233 [Davies Liu] Merge branch 'sort' into groupby
1f075ed [Davies Liu] Merge branch 'master' into sort
4b07d39 [Davies Liu] compress the data while spilling
0a081c6 [Davies Liu] Merge branch 'master' into groupby
f157fe7 [Davies Liu] Merge branch 'sort' into groupby
eb53ca6 [Davies Liu] Merge branch 'master' into sort
b2dc3bf [Davies Liu] Merge branch 'sort' into groupby
644abaf [Davies Liu] add license in LICENSE
19f7873 [Davies Liu] improve tests
11ba318 [Davies Liu] typo
085aef8 [Davies Liu] Merge branch 'master' into groupby
3ee58e5 [Davies Liu] switch to sort based groupBy, based on size of data
1ea0669 [Davies Liu] choose sort based groupByKey() automatically
b40bae7 [Davies Liu] bugfix
efa23df [Davies Liu] refactor, add spark.shuffle.sort=False
250be4e [Davies Liu] flatten the combined values when dumping into disks
d05060d [Davies Liu] group the same key before shuffle, reduce the comparison during sorting
083d842 [Davies Liu] sorted based groupByKey()
55602ee [Davies Liu] use external sort in sortBy() and sortByKey()
---
 python/pyspark/join.py           |  13 +-
 python/pyspark/rdd.py            |  48 ++-
 python/pyspark/resultiterable.py |   7 +-
 python/pyspark/serializers.py    |  25 +-
 python/pyspark/shuffle.py        | 531 ++++++++++++++++++++++++-------
 python/pyspark/tests.py          |  50 ++-
 6 files changed, 531 insertions(+), 143 deletions(-)

diff --git a/python/pyspark/join.py b/python/pyspark/join.py
index efc1ef9396412..c3491defb2b29 100644
--- a/python/pyspark/join.py
+++ b/python/pyspark/join.py
@@ -48,7 +48,7 @@ def dispatch(seq):
                 vbuf.append(v)
             elif n == 2:
                 wbuf.append(v)
-        return [(v, w) for v in vbuf for w in wbuf]
+        return ((v, w) for v in vbuf for w in wbuf)
     return _do_python_join(rdd, other, numPartitions, dispatch)
 
 
@@ -62,7 +62,7 @@ def dispatch(seq):
                 wbuf.append(v)
         if not vbuf:
             vbuf.append(None)
-        return [(v, w) for v in vbuf for w in wbuf]
+        return ((v, w) for v in vbuf for w in wbuf)
     return _do_python_join(rdd, other, numPartitions, dispatch)
 
 
@@ -76,7 +76,7 @@ def dispatch(seq):
                 wbuf.append(v)
         if not wbuf:
             wbuf.append(None)
-        return [(v, w) for v in vbuf for w in wbuf]
+        return ((v, w) for v in vbuf for w in wbuf)
     return _do_python_join(rdd, other, numPartitions, dispatch)
 
 
@@ -104,8 +104,9 @@ def make_mapper(i):
     rdd_len = len(vrdds)
 
     def dispatch(seq):
-        bufs = [[] for i in range(rdd_len)]
-        for (n, v) in seq:
+        bufs = [[] for _ in range(rdd_len)]
+        for n, v in seq:
             bufs[n].append(v)
-        return tuple(map(ResultIterable, bufs))
+        return tuple(ResultIterable(vs) for vs in bufs)
+
     return union_vrdds.groupByKey(numPartitions).mapValues(dispatch)
diff --git a/python/pyspark/rdd.py b/python/pyspark/rdd.py
index 2d05611321ed6..1b18789040360 100644
--- a/python/pyspark/rdd.py
+++ b/python/pyspark/rdd.py
@@ -41,7 +41,7 @@
 from pyspark.storagelevel import StorageLevel
 from pyspark.resultiterable import ResultIterable
 from pyspark.shuffle import Aggregator, InMemoryMerger, ExternalMerger, \
-    get_used_memory, ExternalSorter
+    get_used_memory, ExternalSorter, ExternalGroupBy
 from pyspark.traceback_utils import SCCallSiteSync
 
 from py4j.java_collections import ListConverter, MapConverter
@@ -573,8 +573,8 @@ def sortByKey(self, ascending=True, numPartitions=None, keyfunc=lambda x: x):
         if numPartitions is None:
             numPartitions = self._defaultReducePartitions()
 
-        spill = (self.ctx._conf.get("spark.shuffle.spill", 'True').lower() == 'true')
-        memory = _parse_memory(self.ctx._conf.get("spark.python.worker.memory", "512m"))
+        spill = self._can_spill()
+        memory = self._memory_limit()
         serializer = self._jrdd_deserializer
 
         def sortPartition(iterator):
@@ -1699,10 +1699,8 @@ def combineByKey(self, createCombiner, mergeValue, mergeCombiners,
             numPartitions = self._defaultReducePartitions()
 
         serializer = self.ctx.serializer
-        spill = (self.ctx._conf.get("spark.shuffle.spill", 'True').lower()
-                 == 'true')
-        memory = _parse_memory(self.ctx._conf.get(
-            "spark.python.worker.memory", "512m"))
+        spill = self._can_spill()
+        memory = self._memory_limit()
         agg = Aggregator(createCombiner, mergeValue, mergeCombiners)
 
         def combineLocally(iterator):
@@ -1755,21 +1753,28 @@ def createZero():
 
         return self.combineByKey(lambda v: func(createZero(), v), func, func, numPartitions)
 
+    def _can_spill(self):
+        return self.ctx._conf.get("spark.shuffle.spill", "True").lower() == "true"
+
+    def _memory_limit(self):
+        return _parse_memory(self.ctx._conf.get("spark.python.worker.memory", "512m"))
+
     # TODO: support variant with custom partitioner
     def groupByKey(self, numPartitions=None):
         """
         Group the values for each key in the RDD into a single sequence.
-        Hash-partitions the resulting RDD with into numPartitions partitions.
+        Hash-partitions the resulting RDD with numPartitions partitions.
 
         Note: If you are grouping in order to perform an aggregation (such as a
         sum or average) over each key, using reduceByKey or aggregateByKey will
         provide much better performance.
 
         >>> x = sc.parallelize([("a", 1), ("b", 1), ("a", 1)])
-        >>> map((lambda (x,y): (x, list(y))), sorted(x.groupByKey().collect()))
+        >>> sorted(x.groupByKey().mapValues(len).collect())
+        [('a', 2), ('b', 1)]
+        >>> sorted(x.groupByKey().mapValues(list).collect())
         [('a', [1, 1]), ('b', [1])]
         """
-
         def createCombiner(x):
             return [x]
 
@@ -1781,8 +1786,27 @@ def mergeCombiners(a, b):
             a.extend(b)
             return a
 
-        return self.combineByKey(createCombiner, mergeValue, mergeCombiners,
-                                 numPartitions).mapValues(lambda x: ResultIterable(x))
+        spill = self._can_spill()
+        memory = self._memory_limit()
+        serializer = self._jrdd_deserializer
+        agg = Aggregator(createCombiner, mergeValue, mergeCombiners)
+
+        def combine(iterator):
+            merger = ExternalMerger(agg, memory * 0.9, serializer) \
+                if spill else InMemoryMerger(agg)
+            merger.mergeValues(iterator)
+            return merger.iteritems()
+
+        locally_combined = self.mapPartitions(combine, preservesPartitioning=True)
+        shuffled = locally_combined.partitionBy(numPartitions)
+
+        def groupByKey(it):
+            merger = ExternalGroupBy(agg, memory, serializer)\
+                if spill else InMemoryMerger(agg)
+            merger.mergeCombiners(it)
+            return merger.iteritems()
+
+        return shuffled.mapPartitions(groupByKey, True).mapValues(ResultIterable)
 
     def flatMapValues(self, f):
         """
diff --git a/python/pyspark/resultiterable.py b/python/pyspark/resultiterable.py
index ef04c82866e6c..1ab5ce14c3531 100644
--- a/python/pyspark/resultiterable.py
+++ b/python/pyspark/resultiterable.py
@@ -15,15 +15,16 @@
 # limitations under the License.
 #
 
-__all__ = ["ResultIterable"]
-
 import collections
 
+__all__ = ["ResultIterable"]
+
 
 class ResultIterable(collections.Iterable):
 
     """
-    A special result iterable. This is used because the standard iterator can not be pickled
+    A special result iterable. This is used because the standard
+    iterator can not be pickled
     """
 
     def __init__(self, data):
diff --git a/python/pyspark/serializers.py b/python/pyspark/serializers.py
index 0ffb41d02f6f6..4afa82f4b2973 100644
--- a/python/pyspark/serializers.py
+++ b/python/pyspark/serializers.py
@@ -220,6 +220,29 @@ def __repr__(self):
         return "BatchedSerializer(%s, %d)" % (str(self.serializer), self.batchSize)
 
 
+class FlattenedValuesSerializer(BatchedSerializer):
+
+    """
+    Serializes a stream of list of pairs, split the list of values
+    which contain more than a certain number of objects to make them
+    have similar sizes.
+    """
+    def __init__(self, serializer, batchSize=10):
+        BatchedSerializer.__init__(self, serializer, batchSize)
+
+    def _batched(self, iterator):
+        n = self.batchSize
+        for key, values in iterator:
+            for i in xrange(0, len(values), n):
+                yield key, values[i:i + n]
+
+    def load_stream(self, stream):
+        return self.serializer.load_stream(stream)
+
+    def __repr__(self):
+        return "FlattenedValuesSerializer(%d)" % self.batchSize
+
+
 class AutoBatchedSerializer(BatchedSerializer):
     """
     Choose the size of batch automatically based on the size of object
@@ -251,7 +274,7 @@ def __eq__(self, other):
         return (isinstance(other, AutoBatchedSerializer) and
                 other.serializer == self.serializer and other.bestSize == self.bestSize)
 
-    def __str__(self):
+    def __repr__(self):
         return "AutoBatchedSerializer(%s)" % str(self.serializer)
 
 
diff --git a/python/pyspark/shuffle.py b/python/pyspark/shuffle.py
index 10a7ccd502000..8a6fc627eb383 100644
--- a/python/pyspark/shuffle.py
+++ b/python/pyspark/shuffle.py
@@ -16,28 +16,35 @@
 #
 
 import os
-import sys
 import platform
 import shutil
 import warnings
 import gc
 import itertools
+import operator
 import random
 
 import pyspark.heapq3 as heapq
-from pyspark.serializers import AutoBatchedSerializer, PickleSerializer
+from pyspark.serializers import BatchedSerializer, PickleSerializer, FlattenedValuesSerializer, \
+    CompressedSerializer, AutoBatchedSerializer
+
 
 try:
     import psutil
 
+    process = None
+
     def get_used_memory():
         """ Return the used memory in MB """
-        process = psutil.Process(os.getpid())
+        global process
+        if process is None or process._pid != os.getpid():
+            process = psutil.Process(os.getpid())
         if hasattr(process, "memory_info"):
             info = process.memory_info()
         else:
             info = process.get_memory_info()
         return info.rss >> 20
+
 except ImportError:
 
     def get_used_memory():
@@ -46,6 +53,7 @@ def get_used_memory():
             for line in open('/proc/self/status'):
                 if line.startswith('VmRSS:'):
                     return int(line.split()[1]) >> 10
+
         else:
             warnings.warn("Please install psutil to have better "
                           "support with spilling")
@@ -54,6 +62,7 @@ def get_used_memory():
                 rss = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss
                 return rss >> 20
             # TODO: support windows
+
         return 0
 
 
@@ -148,10 +157,16 @@ def mergeCombiners(self, iterator):
             d[k] = comb(d[k], v) if k in d else v
 
     def iteritems(self):
-        """ Return the merged items ad iterator """
+        """ Return the merged items as iterator """
         return self.data.iteritems()
 
 
+def _compressed_serializer(self, serializer=None):
+    # always use PickleSerializer to simplify implementation
+    ser = PickleSerializer()
+    return AutoBatchedSerializer(CompressedSerializer(ser))
+
+
 class ExternalMerger(Merger):
 
     """
@@ -173,7 +188,7 @@ class ExternalMerger(Merger):
       dict. Repeat this again until combine all the items.
 
     - Before return any items, it will load each partition and
-      combine them seperately. Yield them before loading next
+      combine them separately. Yield them before loading next
       partition.
 
     - During loading a partition, if the memory goes over limit,
@@ -182,7 +197,7 @@ class ExternalMerger(Merger):
 
     `data` and `pdata` are used to hold the merged items in memory.
     At first, all the data are merged into `data`. Once the used
-    memory goes over limit, the items in `data` are dumped indo
+    memory goes over limit, the items in `data` are dumped into
     disks, `data` will be cleared, all rest of items will be merged
     into `pdata` and then dumped into disks. Before returning, all
     the items in `pdata` will be dumped into disks.
@@ -193,16 +208,16 @@ class ExternalMerger(Merger):
     >>> agg = SimpleAggregator(lambda x, y: x + y)
     >>> merger = ExternalMerger(agg, 10)
     >>> N = 10000
-    >>> merger.mergeValues(zip(xrange(N), xrange(N)) * 10)
+    >>> merger.mergeValues(zip(xrange(N), xrange(N)))
     >>> assert merger.spills > 0
     >>> sum(v for k,v in merger.iteritems())
-    499950000
+    49995000
 
     >>> merger = ExternalMerger(agg, 10)
-    >>> merger.mergeCombiners(zip(xrange(N), xrange(N)) * 10)
+    >>> merger.mergeCombiners(zip(xrange(N), xrange(N)))
     >>> assert merger.spills > 0
     >>> sum(v for k,v in merger.iteritems())
-    499950000
+    49995000
     """
 
     # the max total partitions created recursively
@@ -212,8 +227,7 @@ def __init__(self, aggregator, memory_limit=512, serializer=None,
                  localdirs=None, scale=1, partitions=59, batch=1000):
         Merger.__init__(self, aggregator)
         self.memory_limit = memory_limit
-        # default serializer is only used for tests
-        self.serializer = serializer or AutoBatchedSerializer(PickleSerializer())
+        self.serializer = _compressed_serializer(serializer)
         self.localdirs = localdirs or _get_local_dirs(str(id(self)))
         # number of partitions when spill data into disks
         self.partitions = partitions
@@ -221,7 +235,7 @@ def __init__(self, aggregator, memory_limit=512, serializer=None,
         self.batch = batch
         # scale is used to scale down the hash of key for recursive hash map
         self.scale = scale
-        # unpartitioned merged data
+        # un-partitioned merged data
         self.data = {}
         # partitioned merged data, list of dicts
         self.pdata = []
@@ -244,72 +258,63 @@ def _next_limit(self):
 
     def mergeValues(self, iterator):
         """ Combine the items by creator and combiner """
-        iterator = iter(iterator)
         # speedup attribute lookup
         creator, comb = self.agg.createCombiner, self.agg.mergeValue
-        d, c, batch = self.data, 0, self.batch
+        c, data, pdata, hfun, batch = 0, self.data, self.pdata, self._partition, self.batch
+        limit = self.memory_limit
 
         for k, v in iterator:
+            d = pdata[hfun(k)] if pdata else data
             d[k] = comb(d[k], v) if k in d else creator(v)
 
             c += 1
-            if c % batch == 0 and get_used_memory() > self.memory_limit:
-                self._spill()
-                self._partitioned_mergeValues(iterator, self._next_limit())
-                break
+            if c >= batch:
+                if get_used_memory() >= limit:
+                    self._spill()
+                    limit = self._next_limit()
+                    batch /= 2
+                    c = 0
+                else:
+                    batch *= 1.5
+
+        if get_used_memory() >= limit:
+            self._spill()
 
     def _partition(self, key):
         """ Return the partition for key """
         return hash((key, self._seed)) % self.partitions
 
-    def _partitioned_mergeValues(self, iterator, limit=0):
-        """ Partition the items by key, then combine them """
-        # speedup attribute lookup
-        creator, comb = self.agg.createCombiner, self.agg.mergeValue
-        c, pdata, hfun, batch = 0, self.pdata, self._partition, self.batch
-
-        for k, v in iterator:
-            d = pdata[hfun(k)]
-            d[k] = comb(d[k], v) if k in d else creator(v)
-            if not limit:
-                continue
-
-            c += 1
-            if c % batch == 0 and get_used_memory() > limit:
-                self._spill()
-                limit = self._next_limit()
+    def _object_size(self, obj):
+        """ How much of memory for this obj, assume that all the objects
+        consume similar bytes of memory
+        """
+        return 1
 
-    def mergeCombiners(self, iterator, check=True):
+    def mergeCombiners(self, iterator, limit=None):
         """ Merge (K,V) pair by mergeCombiner """
-        iterator = iter(iterator)
+        if limit is None:
+            limit = self.memory_limit
         # speedup attribute lookup
-        d, comb, batch = self.data, self.agg.mergeCombiners, self.batch
-        c = 0
-        for k, v in iterator:
-            d[k] = comb(d[k], v) if k in d else v
-            if not check:
-                continue
-
-            c += 1
-            if c % batch == 0 and get_used_memory() > self.memory_limit:
-                self._spill()
-                self._partitioned_mergeCombiners(iterator, self._next_limit())
-                break
-
-    def _partitioned_mergeCombiners(self, iterator, limit=0):
-        """ Partition the items by key, then merge them """
-        comb, pdata = self.agg.mergeCombiners, self.pdata
-        c, hfun = 0, self._partition
+        comb, hfun, objsize = self.agg.mergeCombiners, self._partition, self._object_size
+        c, data, pdata, batch = 0, self.data, self.pdata, self.batch
         for k, v in iterator:
-            d = pdata[hfun(k)]
+            d = pdata[hfun(k)] if pdata else data
             d[k] = comb(d[k], v) if k in d else v
             if not limit:
                 continue
 
-            c += 1
-            if c % self.batch == 0 and get_used_memory() > limit:
-                self._spill()
-                limit = self._next_limit()
+            c += objsize(v)
+            if c > batch:
+                if get_used_memory() > limit:
+                    self._spill()
+                    limit = self._next_limit()
+                    batch /= 2
+                    c = 0
+                else:
+                    batch *= 1.5
+
+        if limit and get_used_memory() >= limit:
+            self._spill()
 
     def _spill(self):
         """
@@ -335,7 +340,7 @@ def _spill(self):
 
             for k, v in self.data.iteritems():
                 h = self._partition(k)
-                # put one item in batch, make it compatitable with load_stream
+                # put one item in batch, make it compatible with load_stream
                 # it will increase the memory if dump them in batch
                 self.serializer.dump_stream([(k, v)], streams[h])
 
@@ -344,7 +349,7 @@ def _spill(self):
                 s.close()
 
             self.data.clear()
-            self.pdata = [{} for i in range(self.partitions)]
+            self.pdata.extend([{} for i in range(self.partitions)])
 
         else:
             for i in range(self.partitions):
@@ -370,29 +375,12 @@ def _external_items(self):
         assert not self.data
         if any(self.pdata):
             self._spill()
-        hard_limit = self._next_limit()
+        # disable partitioning and spilling when merge combiners from disk
+        self.pdata = []
 
         try:
             for i in range(self.partitions):
-                self.data = {}
-                for j in range(self.spills):
-                    path = self._get_spill_dir(j)
-                    p = os.path.join(path, str(i))
-                    # do not check memory during merging
-                    self.mergeCombiners(self.serializer.load_stream(open(p)),
-                                        False)
-
-                    # limit the total partitions
-                    if (self.scale * self.partitions < self.MAX_TOTAL_PARTITIONS
-                            and j < self.spills - 1
-                            and get_used_memory() > hard_limit):
-                        self.data.clear()  # will read from disk again
-                        gc.collect()  # release the memory as much as possible
-                        for v in self._recursive_merged_items(i):
-                            yield v
-                        return
-
-                for v in self.data.iteritems():
+                for v in self._merged_items(i):
                     yield v
                 self.data.clear()
 
@@ -400,53 +388,56 @@ def _external_items(self):
                 for j in range(self.spills):
                     path = self._get_spill_dir(j)
                     os.remove(os.path.join(path, str(i)))
-
         finally:
             self._cleanup()
 
-    def _cleanup(self):
-        """ Clean up all the files in disks """
-        for d in self.localdirs:
-            shutil.rmtree(d, True)
+    def _merged_items(self, index):
+        self.data = {}
+        limit = self._next_limit()
+        for j in range(self.spills):
+            path = self._get_spill_dir(j)
+            p = os.path.join(path, str(index))
+            # do not check memory during merging
+            self.mergeCombiners(self.serializer.load_stream(open(p)), 0)
+
+            # limit the total partitions
+            if (self.scale * self.partitions < self.MAX_TOTAL_PARTITIONS
+                    and j < self.spills - 1
+                    and get_used_memory() > limit):
+                self.data.clear()  # will read from disk again
+                gc.collect()  # release the memory as much as possible
+                return self._recursive_merged_items(index)
 
-    def _recursive_merged_items(self, start):
+        return self.data.iteritems()
+
+    def _recursive_merged_items(self, index):
         """
         merge the partitioned items and return the as iterator
 
         If one partition can not be fit in memory, then them will be
         partitioned and merged recursively.
         """
-        # make sure all the data are dumps into disks.
-        assert not self.data
-        if any(self.pdata):
-            self._spill()
-        assert self.spills > 0
-
-        for i in range(start, self.partitions):
-            subdirs = [os.path.join(d, "parts", str(i))
-                       for d in self.localdirs]
-            m = ExternalMerger(self.agg, self.memory_limit, self.serializer,
-                               subdirs, self.scale * self.partitions, self.partitions)
-            m.pdata = [{} for _ in range(self.partitions)]
-            limit = self._next_limit()
-
-            for j in range(self.spills):
-                path = self._get_spill_dir(j)
-                p = os.path.join(path, str(i))
-                m._partitioned_mergeCombiners(
-                    self.serializer.load_stream(open(p)))
-
-                if get_used_memory() > limit:
-                    m._spill()
-                    limit = self._next_limit()
+        subdirs = [os.path.join(d, "parts", str(index)) for d in self.localdirs]
+        m = ExternalMerger(self.agg, self.memory_limit, self.serializer, subdirs,
+                           self.scale * self.partitions, self.partitions, self.batch)
+        m.pdata = [{} for _ in range(self.partitions)]
+        limit = self._next_limit()
+
+        for j in range(self.spills):
+            path = self._get_spill_dir(j)
+            p = os.path.join(path, str(index))
+            m.mergeCombiners(self.serializer.load_stream(open(p)), 0)
+
+            if get_used_memory() > limit:
+                m._spill()
+                limit = self._next_limit()
 
-            for v in m._external_items():
-                yield v
+        return m._external_items()
 
-            # remove the merged partition
-            for j in range(self.spills):
-                path = self._get_spill_dir(j)
-                os.remove(os.path.join(path, str(i)))
+    def _cleanup(self):
+        """ Clean up all the files in disks """
+        for d in self.localdirs:
+            shutil.rmtree(d, True)
 
 
 class ExternalSorter(object):
@@ -457,6 +448,7 @@ class ExternalSorter(object):
     The spilling will only happen when the used memory goes above
     the limit.
 
+
     >>> sorter = ExternalSorter(1)  # 1M
     >>> import random
     >>> l = range(1024)
@@ -469,7 +461,7 @@ class ExternalSorter(object):
     def __init__(self, memory_limit, serializer=None):
         self.memory_limit = memory_limit
         self.local_dirs = _get_local_dirs("sort")
-        self.serializer = serializer or AutoBatchedSerializer(PickleSerializer())
+        self.serializer = _compressed_serializer(serializer)
 
     def _get_path(self, n):
         """ Choose one directory for spill by number n """
@@ -515,6 +507,7 @@ def sorted(self, iterator, key=None, reverse=False):
                 limit = self._next_limit()
                 MemoryBytesSpilled += (used_memory - get_used_memory()) << 20
                 DiskBytesSpilled += os.path.getsize(path)
+                os.unlink(path)  # data will be deleted after close
 
             elif not chunks:
                 batch = min(batch * 2, 10000)
@@ -529,6 +522,310 @@ def sorted(self, iterator, key=None, reverse=False):
         return heapq.merge(chunks, key=key, reverse=reverse)
 
 
+class ExternalList(object):
+    """
+    ExternalList can have many items which cannot be hold in memory in
+    the same time.
+
+    >>> l = ExternalList(range(100))
+    >>> len(l)
+    100
+    >>> l.append(10)
+    >>> len(l)
+    101
+    >>> for i in range(20240):
+    ...     l.append(i)
+    >>> len(l)
+    20341
+    >>> import pickle
+    >>> l2 = pickle.loads(pickle.dumps(l))
+    >>> len(l2)
+    20341
+    >>> list(l2)[100]
+    10
+    """
+    LIMIT = 10240
+
+    def __init__(self, values):
+        self.values = values
+        self.count = len(values)
+        self._file = None
+        self._ser = None
+
+    def __getstate__(self):
+        if self._file is not None:
+            self._file.flush()
+            f = os.fdopen(os.dup(self._file.fileno()))
+            f.seek(0)
+            serialized = f.read()
+        else:
+            serialized = ''
+        return self.values, self.count, serialized
+
+    def __setstate__(self, item):
+        self.values, self.count, serialized = item
+        if serialized:
+            self._open_file()
+            self._file.write(serialized)
+        else:
+            self._file = None
+            self._ser = None
+
+    def __iter__(self):
+        if self._file is not None:
+            self._file.flush()
+            # read all items from disks first
+            with os.fdopen(os.dup(self._file.fileno()), 'r') as f:
+                f.seek(0)
+                for v in self._ser.load_stream(f):
+                    yield v
+
+        for v in self.values:
+            yield v
+
+    def __len__(self):
+        return self.count
+
+    def append(self, value):
+        self.values.append(value)
+        self.count += 1
+        # dump them into disk if the key is huge
+        if len(self.values) >= self.LIMIT:
+            self._spill()
+
+    def _open_file(self):
+        dirs = _get_local_dirs("objects")
+        d = dirs[id(self) % len(dirs)]
+        if not os.path.exists(d):
+            os.makedirs(d)
+        p = os.path.join(d, str(id))
+        self._file = open(p, "w+", 65536)
+        self._ser = BatchedSerializer(CompressedSerializer(PickleSerializer()), 1024)
+        os.unlink(p)
+
+    def _spill(self):
+        """ dump the values into disk """
+        global MemoryBytesSpilled, DiskBytesSpilled
+        if self._file is None:
+            self._open_file()
+
+        used_memory = get_used_memory()
+        pos = self._file.tell()
+        self._ser.dump_stream(self.values, self._file)
+        self.values = []
+        gc.collect()
+        DiskBytesSpilled += self._file.tell() - pos
+        MemoryBytesSpilled += (used_memory - get_used_memory()) << 20
+
+
+class ExternalListOfList(ExternalList):
+    """
+    An external list for list.
+
+    >>> l = ExternalListOfList([[i, i] for i in range(100)])
+    >>> len(l)
+    200
+    >>> l.append(range(10))
+    >>> len(l)
+    210
+    >>> len(list(l))
+    210
+    """
+
+    def __init__(self, values):
+        ExternalList.__init__(self, values)
+        self.count = sum(len(i) for i in values)
+
+    def append(self, value):
+        ExternalList.append(self, value)
+        # already counted 1 in ExternalList.append
+        self.count += len(value) - 1
+
+    def __iter__(self):
+        for values in ExternalList.__iter__(self):
+            for v in values:
+                yield v
+
+
+class GroupByKey(object):
+    """
+    Group a sorted iterator as [(k1, it1), (k2, it2), ...]
+
+    >>> k = [i/3 for i in range(6)]
+    >>> v = [[i] for i in range(6)]
+    >>> g = GroupByKey(iter(zip(k, v)))
+    >>> [(k, list(it)) for k, it in g]
+    [(0, [0, 1, 2]), (1, [3, 4, 5])]
+    """
+
+    def __init__(self, iterator):
+        self.iterator = iter(iterator)
+        self.next_item = None
+
+    def __iter__(self):
+        return self
+
+    def next(self):
+        key, value = self.next_item if self.next_item else next(self.iterator)
+        values = ExternalListOfList([value])
+        try:
+            while True:
+                k, v = next(self.iterator)
+                if k != key:
+                    self.next_item = (k, v)
+                    break
+                values.append(v)
+        except StopIteration:
+            self.next_item = None
+        return key, values
+
+
+class ExternalGroupBy(ExternalMerger):
+
+    """
+    Group by the items by key. If any partition of them can not been
+    hold in memory, it will do sort based group by.
+
+    This class works as follows:
+
+    - It repeatedly group the items by key and save them in one dict in
+      memory.
+
+    - When the used memory goes above memory limit, it will split
+      the combined data into partitions by hash code, dump them
+      into disk, one file per partition. If the number of keys
+      in one partitions is smaller than 1000, it will sort them
+      by key before dumping into disk.
+
+    - Then it goes through the rest of the iterator, group items
+      by key into different dict by hash. Until the used memory goes over
+      memory limit, it dump all the dicts into disks, one file per
+      dict. Repeat this again until combine all the items. It
+      also will try to sort the items by key in each partition
+      before dumping into disks.
+
+    - It will yield the grouped items partitions by partitions.
+      If the data in one partitions can be hold in memory, then it
+      will load and combine them in memory and yield.
+
+    - If the dataset in one partition cannot be hold in memory,
+      it will sort them first. If all the files are already sorted,
+      it merge them by heap.merge(), so it will do external sort
+      for all the files.
+
+    - After sorting, `GroupByKey` class will put all the continuous
+      items with the same key as a group, yield the values as
+      an iterator.
+    """
+    SORT_KEY_LIMIT = 1000
+
+    def flattened_serializer(self):
+        assert isinstance(self.serializer, BatchedSerializer)
+        ser = self.serializer
+        return FlattenedValuesSerializer(ser, 20)
+
+    def _object_size(self, obj):
+        return len(obj)
+
+    def _spill(self):
+        """
+        dump already partitioned data into disks.
+        """
+        global MemoryBytesSpilled, DiskBytesSpilled
+        path = self._get_spill_dir(self.spills)
+        if not os.path.exists(path):
+            os.makedirs(path)
+
+        used_memory = get_used_memory()
+        if not self.pdata:
+            # The data has not been partitioned, it will iterator the
+            # data once, write them into different files, has no
+            # additional memory. It only called when the memory goes
+            # above limit at the first time.
+
+            # open all the files for writing
+            streams = [open(os.path.join(path, str(i)), 'w')
+                       for i in range(self.partitions)]
+
+            # If the number of keys is small, then the overhead of sort is small
+            # sort them before dumping into disks
+            self._sorted = len(self.data) < self.SORT_KEY_LIMIT
+            if self._sorted:
+                self.serializer = self.flattened_serializer()
+                for k in sorted(self.data.keys()):
+                    h = self._partition(k)
+                    self.serializer.dump_stream([(k, self.data[k])], streams[h])
+            else:
+                for k, v in self.data.iteritems():
+                    h = self._partition(k)
+                    self.serializer.dump_stream([(k, v)], streams[h])
+
+            for s in streams:
+                DiskBytesSpilled += s.tell()
+                s.close()
+
+            self.data.clear()
+            # self.pdata is cached in `mergeValues` and `mergeCombiners`
+            self.pdata.extend([{} for i in range(self.partitions)])
+
+        else:
+            for i in range(self.partitions):
+                p = os.path.join(path, str(i))
+                with open(p, "w") as f:
+                    # dump items in batch
+                    if self._sorted:
+                        # sort by key only (stable)
+                        sorted_items = sorted(self.pdata[i].iteritems(), key=operator.itemgetter(0))
+                        self.serializer.dump_stream(sorted_items, f)
+                    else:
+                        self.serializer.dump_stream(self.pdata[i].iteritems(), f)
+                self.pdata[i].clear()
+                DiskBytesSpilled += os.path.getsize(p)
+
+        self.spills += 1
+        gc.collect()  # release the memory as much as possible
+        MemoryBytesSpilled += (used_memory - get_used_memory()) << 20
+
+    def _merged_items(self, index):
+        size = sum(os.path.getsize(os.path.join(self._get_spill_dir(j), str(index)))
+                   for j in range(self.spills))
+        # if the memory can not hold all the partition,
+        # then use sort based merge. Because of compression,
+        # the data on disks will be much smaller than needed memory
+        if (size >> 20) >= self.memory_limit / 10:
+            return self._merge_sorted_items(index)
+
+        self.data = {}
+        for j in range(self.spills):
+            path = self._get_spill_dir(j)
+            p = os.path.join(path, str(index))
+            # do not check memory during merging
+            self.mergeCombiners(self.serializer.load_stream(open(p)), 0)
+        return self.data.iteritems()
+
+    def _merge_sorted_items(self, index):
+        """ load a partition from disk, then sort and group by key """
+        def load_partition(j):
+            path = self._get_spill_dir(j)
+            p = os.path.join(path, str(index))
+            return self.serializer.load_stream(open(p, 'r', 65536))
+
+        disk_items = [load_partition(j) for j in range(self.spills)]
+
+        if self._sorted:
+            # all the partitions are already sorted
+            sorted_items = heapq.merge(disk_items, key=operator.itemgetter(0))
+
+        else:
+            # Flatten the combined values, so it will not consume huge
+            # memory during merging sort.
+            ser = self.flattened_serializer()
+            sorter = ExternalSorter(self.memory_limit, ser)
+            sorted_items = sorter.sorted(itertools.chain(*disk_items),
+                                         key=operator.itemgetter(0))
+        return ((k, vs) for k, vs in GroupByKey(sorted_items))
+
+
 if __name__ == "__main__":
     import doctest
     doctest.testmod()
diff --git a/python/pyspark/tests.py b/python/pyspark/tests.py
index dd8d3b1c53733..0bd5d20f7877f 100644
--- a/python/pyspark/tests.py
+++ b/python/pyspark/tests.py
@@ -31,6 +31,7 @@
 import time
 import zipfile
 import random
+import itertools
 import threading
 import hashlib
 
@@ -76,7 +77,7 @@
 class MergerTests(unittest.TestCase):
 
     def setUp(self):
-        self.N = 1 << 14
+        self.N = 1 << 12
         self.l = [i for i in xrange(self.N)]
         self.data = zip(self.l, self.l)
         self.agg = Aggregator(lambda x: [x],
@@ -108,7 +109,7 @@ def test_small_dataset(self):
                          sum(xrange(self.N)))
 
     def test_medium_dataset(self):
-        m = ExternalMerger(self.agg, 10)
+        m = ExternalMerger(self.agg, 30)
         m.mergeValues(self.data)
         self.assertTrue(m.spills >= 1)
         self.assertEqual(sum(sum(v) for k, v in m.iteritems()),
@@ -124,10 +125,36 @@ def test_huge_dataset(self):
         m = ExternalMerger(self.agg, 10, partitions=3)
         m.mergeCombiners(map(lambda (k, v): (k, [str(v)]), self.data * 10))
         self.assertTrue(m.spills >= 1)
-        self.assertEqual(sum(len(v) for k, v in m._recursive_merged_items(0)),
+        self.assertEqual(sum(len(v) for k, v in m.iteritems()),
                          self.N * 10)
         m._cleanup()
 
+    def test_group_by_key(self):
+
+        def gen_data(N, step):
+            for i in range(1, N + 1, step):
+                for j in range(i):
+                    yield (i, [j])
+
+        def gen_gs(N, step=1):
+            return shuffle.GroupByKey(gen_data(N, step))
+
+        self.assertEqual(1, len(list(gen_gs(1))))
+        self.assertEqual(2, len(list(gen_gs(2))))
+        self.assertEqual(100, len(list(gen_gs(100))))
+        self.assertEqual(range(1, 101), [k for k, _ in gen_gs(100)])
+        self.assertTrue(all(range(k) == list(vs) for k, vs in gen_gs(100)))
+
+        for k, vs in gen_gs(50002, 10000):
+            self.assertEqual(k, len(vs))
+            self.assertEqual(range(k), list(vs))
+
+        ser = PickleSerializer()
+        l = ser.loads(ser.dumps(list(gen_gs(50002, 30000))))
+        for k, vs in l:
+            self.assertEqual(k, len(vs))
+            self.assertEqual(range(k), list(vs))
+
 
 class SorterTests(unittest.TestCase):
     def test_in_memory_sort(self):
@@ -702,6 +729,21 @@ def test_distinct(self):
         self.assertEquals(result.getNumPartitions(), 5)
         self.assertEquals(result.count(), 3)
 
+    def test_external_group_by_key(self):
+        self.sc._conf.set("spark.python.worker.memory", "5m")
+        N = 200001
+        kv = self.sc.parallelize(range(N)).map(lambda x: (x % 3, x))
+        gkv = kv.groupByKey().cache()
+        self.assertEqual(3, gkv.count())
+        filtered = gkv.filter(lambda (k, vs): k == 1)
+        self.assertEqual(1, filtered.count())
+        self.assertEqual([(1, N/3)], filtered.mapValues(len).collect())
+        self.assertEqual([(N/3, N/3)],
+                         filtered.values().map(lambda x: (len(x), len(list(x)))).collect())
+        result = filtered.collect()[0][1]
+        self.assertEqual(N/3, len(result))
+        self.assertTrue(isinstance(result.data, shuffle.ExternalList))
+
     def test_sort_on_empty_rdd(self):
         self.assertEqual([], self.sc.parallelize(zip([], [])).sortByKey().collect())
 
@@ -752,9 +794,9 @@ def test_narrow_dependency_in_join(self):
         self.assertEqual(rdd.getNumPartitions() + 2, parted.union(rdd).getNumPartitions())
         self.assertEqual(rdd.getNumPartitions() + 2, rdd.union(parted).getNumPartitions())
 
-        self.sc.setJobGroup("test1", "test", True)
         tracker = self.sc.statusTracker()
 
+        self.sc.setJobGroup("test1", "test", True)
         d = sorted(parted.join(parted).collect())
         self.assertEqual(10, len(d))
         self.assertEqual((0, (0, 0)), d[0])

From e2360810f50de77f79d372cc9b46db117d451cfc Mon Sep 17 00:00:00 2001
From: MechCoder <manojkumarsivaraj334@gmail.com>
Date: Thu, 9 Apr 2015 23:10:13 -0700
Subject: [PATCH 32/95] [SPARK-6577] [MLlib] [PySpark] SparseMatrix should be
 supported in PySpark

Supporting of SparseMatrix in PySpark.

Author: MechCoder <manojkumarsivaraj334@gmail.com>

Closes #5355 from MechCoder/spark-6577 and squashes the following commits:

7492190 [MechCoder] More readable code for densifying
ea2c54b [MechCoder] Check bounds for indexing
454ef2c [MechCoder] Made the following changes 1. Used convert_to_array for array conversion. 2. Used F order for toArray 3. Minor improvements in speed.
db76caf [MechCoder] Add support for CSR matrix
29653e7 [MechCoder] Renamed indices to rowIndices and indptr to colPtrs
b6384fe [MechCoder] [SPARK-6577] SparseMatrix should be supported in PySpark
---
 python/pyspark/mllib/linalg.py | 110 +++++++++++++++++++++++++++++++--
 python/pyspark/mllib/tests.py  |  52 +++++++++++++++-
 2 files changed, 154 insertions(+), 8 deletions(-)

diff --git a/python/pyspark/mllib/linalg.py b/python/pyspark/mllib/linalg.py
index 51c1490b1618d..a80320c52d1d0 100644
--- a/python/pyspark/mllib/linalg.py
+++ b/python/pyspark/mllib/linalg.py
@@ -640,6 +640,15 @@ def toArray(self):
         """
         raise NotImplementedError
 
+    @staticmethod
+    def _convert_to_array(array_like, dtype):
+        """
+        Convert Matrix attributes which are array-like or buffer to array.
+        """
+        if isinstance(array_like, basestring):
+            return np.frombuffer(array_like, dtype=dtype)
+        return np.asarray(array_like, dtype=dtype)
+
 
 class DenseMatrix(Matrix):
     """
@@ -647,13 +656,8 @@ class DenseMatrix(Matrix):
     """
     def __init__(self, numRows, numCols, values):
         Matrix.__init__(self, numRows, numCols)
-        if isinstance(values, basestring):
-            values = np.frombuffer(values, dtype=np.float64)
-        elif not isinstance(values, np.ndarray):
-            values = np.array(values, dtype=np.float64)
+        values = self._convert_to_array(values, np.float64)
         assert len(values) == numRows * numCols
-        if values.dtype != np.float64:
-            values.astype(np.float64)
         self.values = values
 
     def __reduce__(self):
@@ -670,6 +674,17 @@ def toArray(self):
         """
         return self.values.reshape((self.numRows, self.numCols), order='F')
 
+    def toSparse(self):
+        """Convert to SparseMatrix"""
+        indices = np.nonzero(self.values)[0]
+        colCounts = np.bincount(indices / self.numRows)
+        colPtrs = np.cumsum(np.hstack(
+            (0, colCounts, np.zeros(self.numCols - colCounts.size))))
+        values = self.values[indices]
+        rowIndices = indices % self.numRows
+
+        return SparseMatrix(self.numRows, self.numCols, colPtrs, rowIndices, values)
+
     def __getitem__(self, indices):
         i, j = indices
         if i < 0 or i >= self.numRows:
@@ -687,6 +702,82 @@ def __eq__(self, other):
                 all(self.values == other.values))
 
 
+class SparseMatrix(Matrix):
+    """Sparse Matrix stored in CSC format."""
+    def __init__(self, numRows, numCols, colPtrs, rowIndices, values,
+                 isTransposed=False):
+        Matrix.__init__(self, numRows, numCols)
+        self.isTransposed = isTransposed
+        self.colPtrs = self._convert_to_array(colPtrs, np.int32)
+        self.rowIndices = self._convert_to_array(rowIndices, np.int32)
+        self.values = self._convert_to_array(values, np.float64)
+
+        if self.isTransposed:
+            if self.colPtrs.size != numRows + 1:
+                raise ValueError("Expected colPtrs of size %d, got %d."
+                                 % (numRows + 1, self.colPtrs.size))
+        else:
+            if self.colPtrs.size != numCols + 1:
+                raise ValueError("Expected colPtrs of size %d, got %d."
+                                 % (numCols + 1, self.colPtrs.size))
+        if self.rowIndices.size != self.values.size:
+            raise ValueError("Expected rowIndices of length %d, got %d."
+                             % (self.rowIndices.size, self.values.size))
+
+    def __reduce__(self):
+        return SparseMatrix, (
+            self.numRows, self.numCols, self.colPtrs.tostring(),
+            self.rowIndices.tostring(), self.values.tostring(),
+            self.isTransposed)
+
+    def __getitem__(self, indices):
+        i, j = indices
+        if i < 0 or i >= self.numRows:
+            raise ValueError("Row index %d is out of range [0, %d)"
+                             % (i, self.numRows))
+        if j < 0 or j >= self.numCols:
+            raise ValueError("Column index %d is out of range [0, %d)"
+                             % (j, self.numCols))
+
+        # If a CSR matrix is given, then the row index should be searched
+        # for in ColPtrs, and the column index should be searched for in the
+        # corresponding slice obtained from rowIndices.
+        if self.isTransposed:
+            j, i = i, j
+
+        colStart = self.colPtrs[j]
+        colEnd = self.colPtrs[j + 1]
+        nz = self.rowIndices[colStart: colEnd]
+        ind = np.searchsorted(nz, i) + colStart
+        if ind < colEnd and self.rowIndices[ind] == i:
+            return self.values[ind]
+        else:
+            return 0.0
+
+    def toArray(self):
+        """
+        Return an numpy.ndarray
+        """
+        A = np.zeros((self.numRows, self.numCols), dtype=np.float64, order='F')
+        for k in xrange(self.colPtrs.size - 1):
+            startptr = self.colPtrs[k]
+            endptr = self.colPtrs[k + 1]
+            if self.isTransposed:
+                A[k, self.rowIndices[startptr:endptr]] = self.values[startptr:endptr]
+            else:
+                A[self.rowIndices[startptr:endptr], k] = self.values[startptr:endptr]
+        return A
+
+    def toDense(self):
+        densevals = np.reshape(
+            self.toArray(), (self.numRows * self.numCols), order='F')
+        return DenseMatrix(self.numRows, self.numCols, densevals)
+
+    # TODO: More efficient implementation:
+    def __eq__(self, other):
+        return np.all(self.toArray == other.toArray)
+
+
 class Matrices(object):
     @staticmethod
     def dense(numRows, numCols, values):
@@ -695,6 +786,13 @@ def dense(numRows, numCols, values):
         """
         return DenseMatrix(numRows, numCols, values)
 
+    @staticmethod
+    def sparse(numRows, numCols, colPtrs, rowIndices, values):
+        """
+        Create a SparseMatrix
+        """
+        return SparseMatrix(numRows, numCols, colPtrs, rowIndices, values)
+
 
 def _test():
     import doctest
diff --git a/python/pyspark/mllib/tests.py b/python/pyspark/mllib/tests.py
index 61ef398487c0c..3b40158c12b74 100644
--- a/python/pyspark/mllib/tests.py
+++ b/python/pyspark/mllib/tests.py
@@ -24,7 +24,7 @@
 import tempfile
 import array as pyarray
 
-from numpy import array, array_equal
+from numpy import array, array_equal, zeros
 from py4j.protocol import Py4JJavaError
 
 if sys.version_info[:2] <= (2, 6):
@@ -38,7 +38,7 @@
 
 from pyspark.mllib.common import _to_java_object_rdd
 from pyspark.mllib.linalg import Vector, SparseVector, DenseVector, VectorUDT, _convert_to_vector,\
-    DenseMatrix, Vectors, Matrices
+    DenseMatrix, SparseMatrix, Vectors, Matrices
 from pyspark.mllib.regression import LabeledPoint
 from pyspark.mllib.random import RandomRDDs
 from pyspark.mllib.stat import Statistics
@@ -144,6 +144,54 @@ def test_matrix_indexing(self):
             for j in range(2):
                 self.assertEquals(mat[i, j], expected[i][j])
 
+    def test_sparse_matrix(self):
+        # Test sparse matrix creation.
+        sm1 = SparseMatrix(
+            3, 4, [0, 2, 2, 4, 4], [1, 2, 1, 2], [1.0, 2.0, 4.0, 5.0])
+        self.assertEquals(sm1.numRows, 3)
+        self.assertEquals(sm1.numCols, 4)
+        self.assertEquals(sm1.colPtrs.tolist(), [0, 2, 2, 4, 4])
+        self.assertEquals(sm1.rowIndices.tolist(), [1, 2, 1, 2])
+        self.assertEquals(sm1.values.tolist(), [1.0, 2.0, 4.0, 5.0])
+
+        # Test indexing
+        expected = [
+            [0, 0, 0, 0],
+            [1, 0, 4, 0],
+            [2, 0, 5, 0]]
+
+        for i in range(3):
+            for j in range(4):
+                self.assertEquals(expected[i][j], sm1[i, j])
+        self.assertTrue(array_equal(sm1.toArray(), expected))
+
+        # Test conversion to dense and sparse.
+        smnew = sm1.toDense().toSparse()
+        self.assertEquals(sm1.numRows, smnew.numRows)
+        self.assertEquals(sm1.numCols, smnew.numCols)
+        self.assertTrue(array_equal(sm1.colPtrs, smnew.colPtrs))
+        self.assertTrue(array_equal(sm1.rowIndices, smnew.rowIndices))
+        self.assertTrue(array_equal(sm1.values, smnew.values))
+
+        sm1t = SparseMatrix(
+            3, 4, [0, 2, 3, 5], [0, 1, 2, 0, 2], [3.0, 2.0, 4.0, 9.0, 8.0],
+            isTransposed=True)
+        self.assertEquals(sm1t.numRows, 3)
+        self.assertEquals(sm1t.numCols, 4)
+        self.assertEquals(sm1t.colPtrs.tolist(), [0, 2, 3, 5])
+        self.assertEquals(sm1t.rowIndices.tolist(), [0, 1, 2, 0, 2])
+        self.assertEquals(sm1t.values.tolist(), [3.0, 2.0, 4.0, 9.0, 8.0])
+
+        expected = [
+            [3, 2, 0, 0],
+            [0, 0, 4, 0],
+            [9, 0, 8, 0]]
+
+        for i in range(3):
+            for j in range(4):
+                self.assertEquals(expected[i][j], sm1t[i, j])
+        self.assertTrue(array_equal(sm1t.toArray(), expected))
+
 
 class ListTests(PySparkTestCase):
 

From 3290d2d13bb4bd875aec14425c8e3766f9cc644b Mon Sep 17 00:00:00 2001
From: jerryshao <saisai.shao@intel.com>
Date: Thu, 9 Apr 2015 23:14:24 -0700
Subject: [PATCH 33/95] [SPARK-6211][Streaming] Add Python Kafka API unit test

Refactor the Kafka unit test and add Python API support. CC tdas davies please help to review, thanks a lot.

Author: jerryshao <saisai.shao@intel.com>
Author: Saisai Shao <saisai.shao@intel.com>

Closes #4961 from jerryshao/SPARK-6211 and squashes the following commits:

ee4b919 [jerryshao] Fixed newly merged issue
82c756e [jerryshao] Address the comments
92912d1 [jerryshao] Address the commits
0708bb1 [jerryshao] Fix rebase issue
40b47a3 [Saisai Shao] Style fix
f889657 [Saisai Shao] Update the code according
8a2f3e2 [jerryshao] Address the issues
0f1b7ce [jerryshao] Still fix the bug
61a04f0 [jerryshao] Fix bugs and address the issues
64d9877 [jerryshao] Fix rebase bugs
8ad442f [jerryshao] Add kafka-assembly in run-tests
6020b00 [jerryshao] Add more debug info in Shell
8102d6e [jerryshao] Fix bug in Jenkins test
fde1213 [jerryshao] Code style changes
5536f95 [jerryshao] Refactor the Kafka unit test and add Python Kafka unittest support
---
 dev/run-tests                                 |   2 +-
 .../streaming/kafka/KafkaTestUtils.scala      | 261 ++++++++++++++++++
 .../kafka/JavaDirectKafkaStreamSuite.java     |  28 +-
 .../streaming/kafka/JavaKafkaRDDSuite.java    |  28 +-
 .../streaming/kafka/JavaKafkaStreamSuite.java |  34 ++-
 .../kafka/DirectKafkaStreamSuite.scala        |  56 ++--
 .../streaming/kafka/KafkaClusterSuite.scala   |  29 +-
 .../spark/streaming/kafka/KafkaRDDSuite.scala |  40 +--
 .../streaming/kafka/KafkaStreamSuite.scala    | 211 ++------------
 .../kafka/ReliableKafkaStreamSuite.scala      |  62 +++--
 python/pyspark/streaming/tests.py             |  43 ++-
 python/run-tests                              |  19 +-
 12 files changed, 502 insertions(+), 311 deletions(-)
 create mode 100644 external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaTestUtils.scala

diff --git a/dev/run-tests b/dev/run-tests
index 1b6cf78b5da01..bb21ab6c9aa04 100755
--- a/dev/run-tests
+++ b/dev/run-tests
@@ -173,7 +173,7 @@ CURRENT_BLOCK=$BLOCK_BUILD
     build/mvn $HIVE_BUILD_ARGS clean package -DskipTests
   else
     echo -e "q\n" \
-      | build/sbt $HIVE_BUILD_ARGS package assembly/assembly  \
+      | build/sbt $HIVE_BUILD_ARGS package assembly/assembly streaming-kafka-assembly/assembly \
       | grep -v -e "info.*Resolving" -e "warn.*Merging" -e "info.*Including"
   fi
 }
diff --git a/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaTestUtils.scala b/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaTestUtils.scala
new file mode 100644
index 0000000000000..13e9475065979
--- /dev/null
+++ b/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaTestUtils.scala
@@ -0,0 +1,261 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.kafka
+
+import java.io.File
+import java.lang.{Integer => JInt}
+import java.net.InetSocketAddress
+import java.util.{Map => JMap}
+import java.util.Properties
+import java.util.concurrent.TimeoutException
+
+import scala.annotation.tailrec
+import scala.language.postfixOps
+import scala.util.control.NonFatal
+
+import kafka.admin.AdminUtils
+import kafka.producer.{KeyedMessage, Producer, ProducerConfig}
+import kafka.serializer.StringEncoder
+import kafka.server.{KafkaConfig, KafkaServer}
+import kafka.utils.ZKStringSerializer
+import org.apache.zookeeper.server.{NIOServerCnxnFactory, ZooKeeperServer}
+import org.I0Itec.zkclient.ZkClient
+
+import org.apache.spark.{Logging, SparkConf}
+import org.apache.spark.streaming.Time
+import org.apache.spark.util.Utils
+
+/**
+ * This is a helper class for Kafka test suites. This has the functionality to set up
+ * and tear down local Kafka servers, and to push data using Kafka producers.
+ *
+ * The reason to put Kafka test utility class in src is to test Python related Kafka APIs.
+ */
+private class KafkaTestUtils extends Logging {
+
+  // Zookeeper related configurations
+  private val zkHost = "localhost"
+  private var zkPort: Int = 0
+  private val zkConnectionTimeout = 6000
+  private val zkSessionTimeout = 6000
+
+  private var zookeeper: EmbeddedZookeeper = _
+
+  private var zkClient: ZkClient = _
+
+  // Kafka broker related configurations
+  private val brokerHost = "localhost"
+  private var brokerPort = 9092
+  private var brokerConf: KafkaConfig = _
+
+  // Kafka broker server
+  private var server: KafkaServer = _
+
+  // Kafka producer
+  private var producer: Producer[String, String] = _
+
+  // Flag to test whether the system is correctly started
+  private var zkReady = false
+  private var brokerReady = false
+
+  def zkAddress: String = {
+    assert(zkReady, "Zookeeper not setup yet or already torn down, cannot get zookeeper address")
+    s"$zkHost:$zkPort"
+  }
+
+  def brokerAddress: String = {
+    assert(brokerReady, "Kafka not setup yet or already torn down, cannot get broker address")
+    s"$brokerHost:$brokerPort"
+  }
+
+  def zookeeperClient: ZkClient = {
+    assert(zkReady, "Zookeeper not setup yet or already torn down, cannot get zookeeper client")
+    Option(zkClient).getOrElse(
+      throw new IllegalStateException("Zookeeper client is not yet initialized"))
+  }
+
+  // Set up the Embedded Zookeeper server and get the proper Zookeeper port
+  private def setupEmbeddedZookeeper(): Unit = {
+    // Zookeeper server startup
+    zookeeper = new EmbeddedZookeeper(s"$zkHost:$zkPort")
+    // Get the actual zookeeper binding port
+    zkPort = zookeeper.actualPort
+    zkClient = new ZkClient(s"$zkHost:$zkPort", zkSessionTimeout, zkConnectionTimeout,
+      ZKStringSerializer)
+    zkReady = true
+  }
+
+  // Set up the Embedded Kafka server
+  private def setupEmbeddedKafkaServer(): Unit = {
+    assert(zkReady, "Zookeeper should be set up beforehand")
+
+    // Kafka broker startup
+    Utils.startServiceOnPort(brokerPort, port => {
+      brokerPort = port
+      brokerConf = new KafkaConfig(brokerConfiguration)
+      server = new KafkaServer(brokerConf)
+      server.startup()
+      (server, port)
+    }, new SparkConf(), "KafkaBroker")
+
+    brokerReady = true
+  }
+
+  /** setup the whole embedded servers, including Zookeeper and Kafka brokers */
+  def setup(): Unit = {
+    setupEmbeddedZookeeper()
+    setupEmbeddedKafkaServer()
+  }
+
+  /** Teardown the whole servers, including Kafka broker and Zookeeper */
+  def teardown(): Unit = {
+    brokerReady = false
+    zkReady = false
+
+    if (producer != null) {
+      producer.close()
+      producer = null
+    }
+
+    if (server != null) {
+      server.shutdown()
+      server = null
+    }
+
+    brokerConf.logDirs.foreach { f => Utils.deleteRecursively(new File(f)) }
+
+    if (zkClient != null) {
+      zkClient.close()
+      zkClient = null
+    }
+
+    if (zookeeper != null) {
+      zookeeper.shutdown()
+      zookeeper = null
+    }
+  }
+
+  /** Create a Kafka topic and wait until it propagated to the whole cluster */
+  def createTopic(topic: String): Unit = {
+    AdminUtils.createTopic(zkClient, topic, 1, 1)
+    // wait until metadata is propagated
+    waitUntilMetadataIsPropagated(topic, 0)
+  }
+
+  /** Java-friendly function for sending messages to the Kafka broker */
+  def sendMessages(topic: String, messageToFreq: JMap[String, JInt]): Unit = {
+    import scala.collection.JavaConversions._
+    sendMessages(topic, Map(messageToFreq.mapValues(_.intValue()).toSeq: _*))
+  }
+
+  /** Send the messages to the Kafka broker */
+  def sendMessages(topic: String, messageToFreq: Map[String, Int]): Unit = {
+    val messages = messageToFreq.flatMap { case (s, freq) => Seq.fill(freq)(s) }.toArray
+    sendMessages(topic, messages)
+  }
+
+  /** Send the array of messages to the Kafka broker */
+  def sendMessages(topic: String, messages: Array[String]): Unit = {
+    producer = new Producer[String, String](new ProducerConfig(producerConfiguration))
+    producer.send(messages.map { new KeyedMessage[String, String](topic, _ ) }: _*)
+    producer.close()
+    producer = null
+  }
+
+  private def brokerConfiguration: Properties = {
+    val props = new Properties()
+    props.put("broker.id", "0")
+    props.put("host.name", "localhost")
+    props.put("port", brokerPort.toString)
+    props.put("log.dir", Utils.createTempDir().getAbsolutePath)
+    props.put("zookeeper.connect", zkAddress)
+    props.put("log.flush.interval.messages", "1")
+    props.put("replica.socket.timeout.ms", "1500")
+    props
+  }
+
+  private def producerConfiguration: Properties = {
+    val props = new Properties()
+    props.put("metadata.broker.list", brokerAddress)
+    props.put("serializer.class", classOf[StringEncoder].getName)
+    props
+  }
+
+  // A simplified version of scalatest eventually, rewritten here to avoid adding extra test
+  // dependency
+  def eventually[T](timeout: Time, interval: Time)(func: => T): T = {
+    def makeAttempt(): Either[Throwable, T] = {
+      try {
+        Right(func)
+      } catch {
+        case e if NonFatal(e) => Left(e)
+      }
+    }
+
+    val startTime = System.currentTimeMillis()
+    @tailrec
+    def tryAgain(attempt: Int): T = {
+      makeAttempt() match {
+        case Right(result) => result
+        case Left(e) =>
+          val duration = System.currentTimeMillis() - startTime
+          if (duration < timeout.milliseconds) {
+            Thread.sleep(interval.milliseconds)
+          } else {
+            throw new TimeoutException(e.getMessage)
+          }
+
+          tryAgain(attempt + 1)
+      }
+    }
+
+    tryAgain(1)
+  }
+
+  private def waitUntilMetadataIsPropagated(topic: String, partition: Int): Unit = {
+    eventually(Time(10000), Time(100)) {
+      assert(
+        server.apis.metadataCache.containsTopicAndPartition(topic, partition),
+        s"Partition [$topic, $partition] metadata not propagated after timeout"
+      )
+    }
+  }
+
+  private class EmbeddedZookeeper(val zkConnect: String) {
+    val snapshotDir = Utils.createTempDir()
+    val logDir = Utils.createTempDir()
+
+    val zookeeper = new ZooKeeperServer(snapshotDir, logDir, 500)
+    val (ip, port) = {
+      val splits = zkConnect.split(":")
+      (splits(0), splits(1).toInt)
+    }
+    val factory = new NIOServerCnxnFactory()
+    factory.configure(new InetSocketAddress(ip, port), 16)
+    factory.startup(zookeeper)
+
+    val actualPort = factory.getLocalPort
+
+    def shutdown() {
+      factory.shutdown()
+      Utils.deleteRecursively(snapshotDir)
+      Utils.deleteRecursively(logDir)
+    }
+  }
+}
+
diff --git a/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaDirectKafkaStreamSuite.java b/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaDirectKafkaStreamSuite.java
index d6ca6d58b5665..4c1d6a03eb2b8 100644
--- a/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaDirectKafkaStreamSuite.java
+++ b/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaDirectKafkaStreamSuite.java
@@ -41,24 +41,28 @@
 
 public class JavaDirectKafkaStreamSuite implements Serializable {
   private transient JavaStreamingContext ssc = null;
-  private transient KafkaStreamSuiteBase suiteBase = null;
+  private transient KafkaTestUtils kafkaTestUtils = null;
 
   @Before
   public void setUp() {
-      suiteBase = new KafkaStreamSuiteBase() { };
-      suiteBase.setupKafka();
-      System.clearProperty("spark.driver.port");
-      SparkConf sparkConf = new SparkConf()
-              .setMaster("local[4]").setAppName(this.getClass().getSimpleName());
-      ssc = new JavaStreamingContext(sparkConf, Durations.milliseconds(200));
+    kafkaTestUtils = new KafkaTestUtils();
+    kafkaTestUtils.setup();
+    SparkConf sparkConf = new SparkConf()
+      .setMaster("local[4]").setAppName(this.getClass().getSimpleName());
+    ssc = new JavaStreamingContext(sparkConf, Durations.milliseconds(200));
   }
 
   @After
   public void tearDown() {
+    if (ssc != null) {
       ssc.stop();
       ssc = null;
-      System.clearProperty("spark.driver.port");
-      suiteBase.tearDownKafka();
+    }
+
+    if (kafkaTestUtils != null) {
+      kafkaTestUtils.teardown();
+      kafkaTestUtils = null;
+    }
   }
 
   @Test
@@ -74,7 +78,7 @@ public void testKafkaStream() throws InterruptedException {
     sent.addAll(Arrays.asList(topic2data));
 
     HashMap<String, String> kafkaParams = new HashMap<String, String>();
-    kafkaParams.put("metadata.broker.list", suiteBase.brokerAddress());
+    kafkaParams.put("metadata.broker.list", kafkaTestUtils.brokerAddress());
     kafkaParams.put("auto.offset.reset", "smallest");
 
     JavaDStream<String> stream1 = KafkaUtils.createDirectStream(
@@ -147,8 +151,8 @@ private HashMap<TopicAndPartition, Long> topicOffsetToMap(String topic, Long off
 
   private  String[] createTopicAndSendData(String topic) {
     String[] data = { topic + "-1", topic + "-2", topic + "-3"};
-    suiteBase.createTopic(topic);
-    suiteBase.sendMessages(topic, data);
+    kafkaTestUtils.createTopic(topic);
+    kafkaTestUtils.sendMessages(topic, data);
     return data;
   }
 }
diff --git a/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaKafkaRDDSuite.java b/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaKafkaRDDSuite.java
index 4477b81827c70..a9dc6e50613ca 100644
--- a/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaKafkaRDDSuite.java
+++ b/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaKafkaRDDSuite.java
@@ -37,13 +37,12 @@
 
 public class JavaKafkaRDDSuite implements Serializable {
   private transient JavaSparkContext sc = null;
-  private transient KafkaStreamSuiteBase suiteBase = null;
+  private transient KafkaTestUtils kafkaTestUtils = null;
 
   @Before
   public void setUp() {
-    suiteBase = new KafkaStreamSuiteBase() { };
-    suiteBase.setupKafka();
-    System.clearProperty("spark.driver.port");
+    kafkaTestUtils = new KafkaTestUtils();
+    kafkaTestUtils.setup();
     SparkConf sparkConf = new SparkConf()
       .setMaster("local[4]").setAppName(this.getClass().getSimpleName());
     sc = new JavaSparkContext(sparkConf);
@@ -51,10 +50,15 @@ public void setUp() {
 
   @After
   public void tearDown() {
-    sc.stop();
-    sc = null;
-    System.clearProperty("spark.driver.port");
-    suiteBase.tearDownKafka();
+    if (sc != null) {
+      sc.stop();
+      sc = null;
+    }
+
+    if (kafkaTestUtils != null) {
+      kafkaTestUtils.teardown();
+      kafkaTestUtils = null;
+    }
   }
 
   @Test
@@ -66,7 +70,7 @@ public void testKafkaRDD() throws InterruptedException {
     String[] topic2data = createTopicAndSendData(topic2);
 
     HashMap<String, String> kafkaParams = new HashMap<String, String>();
-    kafkaParams.put("metadata.broker.list", suiteBase.brokerAddress());
+    kafkaParams.put("metadata.broker.list", kafkaTestUtils.brokerAddress());
 
     OffsetRange[] offsetRanges = {
       OffsetRange.create(topic1, 0, 0, 1),
@@ -75,7 +79,7 @@ public void testKafkaRDD() throws InterruptedException {
 
     HashMap<TopicAndPartition, Broker> emptyLeaders = new HashMap<TopicAndPartition, Broker>();
     HashMap<TopicAndPartition, Broker> leaders = new HashMap<TopicAndPartition, Broker>();
-    String[] hostAndPort = suiteBase.brokerAddress().split(":");
+    String[] hostAndPort = kafkaTestUtils.brokerAddress().split(":");
     Broker broker = Broker.create(hostAndPort[0], Integer.parseInt(hostAndPort[1]));
     leaders.put(new TopicAndPartition(topic1, 0), broker);
     leaders.put(new TopicAndPartition(topic2, 0), broker);
@@ -144,8 +148,8 @@ public String call(MessageAndMetadata<String, String> msgAndMd) throws Exception
 
   private  String[] createTopicAndSendData(String topic) {
     String[] data = { topic + "-1", topic + "-2", topic + "-3"};
-    suiteBase.createTopic(topic);
-    suiteBase.sendMessages(topic, data);
+    kafkaTestUtils.createTopic(topic);
+    kafkaTestUtils.sendMessages(topic, data);
     return data;
   }
 }
diff --git a/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaKafkaStreamSuite.java b/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaKafkaStreamSuite.java
index bad0a93eb2e84..540f4ceabab47 100644
--- a/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaKafkaStreamSuite.java
+++ b/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaKafkaStreamSuite.java
@@ -22,9 +22,7 @@
 import java.util.List;
 import java.util.Random;
 
-import scala.Predef;
 import scala.Tuple2;
-import scala.collection.JavaConverters;
 
 import kafka.serializer.StringDecoder;
 import org.junit.After;
@@ -44,13 +42,12 @@
 public class JavaKafkaStreamSuite implements Serializable {
   private transient JavaStreamingContext ssc = null;
   private transient Random random = new Random();
-  private transient KafkaStreamSuiteBase suiteBase = null;
+  private transient KafkaTestUtils kafkaTestUtils = null;
 
   @Before
   public void setUp() {
-    suiteBase = new KafkaStreamSuiteBase() { };
-    suiteBase.setupKafka();
-    System.clearProperty("spark.driver.port");
+    kafkaTestUtils = new KafkaTestUtils();
+    kafkaTestUtils.setup();
     SparkConf sparkConf = new SparkConf()
       .setMaster("local[4]").setAppName(this.getClass().getSimpleName());
     ssc = new JavaStreamingContext(sparkConf, new Duration(500));
@@ -58,10 +55,15 @@ public void setUp() {
 
   @After
   public void tearDown() {
-    ssc.stop();
-    ssc = null;
-    System.clearProperty("spark.driver.port");
-    suiteBase.tearDownKafka();
+    if (ssc != null) {
+      ssc.stop();
+      ssc = null;
+    }
+
+    if (kafkaTestUtils != null) {
+      kafkaTestUtils.teardown();
+      kafkaTestUtils = null;
+    }
   }
 
   @Test
@@ -75,15 +77,11 @@ public void testKafkaStream() throws InterruptedException {
     sent.put("b", 3);
     sent.put("c", 10);
 
-    suiteBase.createTopic(topic);
-    HashMap<String, Object> tmp = new HashMap<String, Object>(sent);
-    suiteBase.sendMessages(topic,
-        JavaConverters.mapAsScalaMapConverter(tmp).asScala().toMap(
-            Predef.<Tuple2<String, Object>>conforms())
-    );
+    kafkaTestUtils.createTopic(topic);
+    kafkaTestUtils.sendMessages(topic, sent);
 
     HashMap<String, String> kafkaParams = new HashMap<String, String>();
-    kafkaParams.put("zookeeper.connect", suiteBase.zkAddress());
+    kafkaParams.put("zookeeper.connect", kafkaTestUtils.zkAddress());
     kafkaParams.put("group.id", "test-consumer-" + random.nextInt(10000));
     kafkaParams.put("auto.offset.reset", "smallest");
 
@@ -126,6 +124,7 @@ public Void call(JavaPairRDD<String, Long> rdd) throws Exception {
     );
 
     ssc.start();
+
     long startTime = System.currentTimeMillis();
     boolean sizeMatches = false;
     while (!sizeMatches && System.currentTimeMillis() - startTime < 20000) {
@@ -136,6 +135,5 @@ public Void call(JavaPairRDD<String, Long> rdd) throws Exception {
     for (String k : sent.keySet()) {
       Assert.assertEquals(sent.get(k).intValue(), result.get(k).intValue());
     }
-    ssc.stop();
   }
 }
diff --git a/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/DirectKafkaStreamSuite.scala b/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/DirectKafkaStreamSuite.scala
index 17ca9d145d665..415730f5559c5 100644
--- a/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/DirectKafkaStreamSuite.scala
+++ b/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/DirectKafkaStreamSuite.scala
@@ -27,31 +27,41 @@ import scala.language.postfixOps
 import kafka.common.TopicAndPartition
 import kafka.message.MessageAndMetadata
 import kafka.serializer.StringDecoder
-import org.scalatest.{BeforeAndAfter, BeforeAndAfterAll}
+import org.scalatest.{BeforeAndAfter, BeforeAndAfterAll, FunSuite}
 import org.scalatest.concurrent.Eventually
 
-import org.apache.spark.{SparkConf, SparkContext}
+import org.apache.spark.{Logging, SparkConf, SparkContext}
 import org.apache.spark.rdd.RDD
 import org.apache.spark.streaming.{Milliseconds, StreamingContext, Time}
 import org.apache.spark.streaming.dstream.DStream
 import org.apache.spark.util.Utils
 
-class DirectKafkaStreamSuite extends KafkaStreamSuiteBase
-  with BeforeAndAfter with BeforeAndAfterAll with Eventually {
+class DirectKafkaStreamSuite
+  extends FunSuite
+  with BeforeAndAfter
+  with BeforeAndAfterAll
+  with Eventually
+  with Logging {
   val sparkConf = new SparkConf()
     .setMaster("local[4]")
     .setAppName(this.getClass.getSimpleName)
 
-  var sc: SparkContext = _
-  var ssc: StreamingContext = _
-  var testDir: File = _
+  private var sc: SparkContext = _
+  private var ssc: StreamingContext = _
+  private var testDir: File = _
+
+  private var kafkaTestUtils: KafkaTestUtils = _
 
   override def beforeAll {
-    setupKafka()
+    kafkaTestUtils = new KafkaTestUtils
+    kafkaTestUtils.setup()
   }
 
   override def afterAll {
-    tearDownKafka()
+    if (kafkaTestUtils != null) {
+      kafkaTestUtils.teardown()
+      kafkaTestUtils = null
+    }
   }
 
   after {
@@ -72,12 +82,12 @@ class DirectKafkaStreamSuite extends KafkaStreamSuiteBase
     val topics = Set("basic1", "basic2", "basic3")
     val data = Map("a" -> 7, "b" -> 9)
     topics.foreach { t =>
-      createTopic(t)
-      sendMessages(t, data)
+      kafkaTestUtils.createTopic(t)
+      kafkaTestUtils.sendMessages(t, data)
     }
     val totalSent = data.values.sum * topics.size
     val kafkaParams = Map(
-      "metadata.broker.list" -> s"$brokerAddress",
+      "metadata.broker.list" -> kafkaTestUtils.brokerAddress,
       "auto.offset.reset" -> "smallest"
     )
 
@@ -121,9 +131,9 @@ class DirectKafkaStreamSuite extends KafkaStreamSuiteBase
     val topic = "largest"
     val topicPartition = TopicAndPartition(topic, 0)
     val data = Map("a" -> 10)
-    createTopic(topic)
+    kafkaTestUtils.createTopic(topic)
     val kafkaParams = Map(
-      "metadata.broker.list" -> s"$brokerAddress",
+      "metadata.broker.list" -> kafkaTestUtils.brokerAddress,
       "auto.offset.reset" -> "largest"
     )
     val kc = new KafkaCluster(kafkaParams)
@@ -132,7 +142,7 @@ class DirectKafkaStreamSuite extends KafkaStreamSuiteBase
     }
 
     // Send some initial messages before starting context
-    sendMessages(topic, data)
+    kafkaTestUtils.sendMessages(topic, data)
     eventually(timeout(10 seconds), interval(20 milliseconds)) {
       assert(getLatestOffset() > 3)
     }
@@ -154,7 +164,7 @@ class DirectKafkaStreamSuite extends KafkaStreamSuiteBase
     stream.map { _._2 }.foreachRDD { rdd => collectedData ++= rdd.collect() }
     ssc.start()
     val newData = Map("b" -> 10)
-    sendMessages(topic, newData)
+    kafkaTestUtils.sendMessages(topic, newData)
     eventually(timeout(10 seconds), interval(50 milliseconds)) {
       collectedData.contains("b")
     }
@@ -166,9 +176,9 @@ class DirectKafkaStreamSuite extends KafkaStreamSuiteBase
     val topic = "offset"
     val topicPartition = TopicAndPartition(topic, 0)
     val data = Map("a" -> 10)
-    createTopic(topic)
+    kafkaTestUtils.createTopic(topic)
     val kafkaParams = Map(
-      "metadata.broker.list" -> s"$brokerAddress",
+      "metadata.broker.list" -> kafkaTestUtils.brokerAddress,
       "auto.offset.reset" -> "largest"
     )
     val kc = new KafkaCluster(kafkaParams)
@@ -177,7 +187,7 @@ class DirectKafkaStreamSuite extends KafkaStreamSuiteBase
     }
 
     // Send some initial messages before starting context
-    sendMessages(topic, data)
+    kafkaTestUtils.sendMessages(topic, data)
     eventually(timeout(10 seconds), interval(20 milliseconds)) {
       assert(getLatestOffset() >= 10)
     }
@@ -200,7 +210,7 @@ class DirectKafkaStreamSuite extends KafkaStreamSuiteBase
     stream.foreachRDD { rdd => collectedData ++= rdd.collect() }
     ssc.start()
     val newData = Map("b" -> 10)
-    sendMessages(topic, newData)
+    kafkaTestUtils.sendMessages(topic, newData)
     eventually(timeout(10 seconds), interval(50 milliseconds)) {
       collectedData.contains("b")
     }
@@ -210,18 +220,18 @@ class DirectKafkaStreamSuite extends KafkaStreamSuiteBase
   // Test to verify the offset ranges can be recovered from the checkpoints
   test("offset recovery") {
     val topic = "recovery"
-    createTopic(topic)
+    kafkaTestUtils.createTopic(topic)
     testDir = Utils.createTempDir()
 
     val kafkaParams = Map(
-      "metadata.broker.list" -> s"$brokerAddress",
+      "metadata.broker.list" -> kafkaTestUtils.brokerAddress,
       "auto.offset.reset" -> "smallest"
     )
 
     // Send data to Kafka and wait for it to be received
     def sendDataAndWaitForReceive(data: Seq[Int]) {
       val strings = data.map { _.toString}
-      sendMessages(topic, strings.map { _ -> 1}.toMap)
+      kafkaTestUtils.sendMessages(topic, strings.map { _ -> 1}.toMap)
       eventually(timeout(10 seconds), interval(50 milliseconds)) {
         assert(strings.forall { DirectKafkaStreamSuite.collectedData.contains })
       }
diff --git a/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaClusterSuite.scala b/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaClusterSuite.scala
index fc9275b7207be..2b33d2a220b2b 100644
--- a/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaClusterSuite.scala
+++ b/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaClusterSuite.scala
@@ -20,28 +20,35 @@ package org.apache.spark.streaming.kafka
 import scala.util.Random
 
 import kafka.common.TopicAndPartition
-import org.scalatest.BeforeAndAfterAll
+import org.scalatest.{BeforeAndAfterAll, FunSuite}
 
-class KafkaClusterSuite extends KafkaStreamSuiteBase with BeforeAndAfterAll {
-  val topic = "kcsuitetopic" + Random.nextInt(10000)
-  val topicAndPartition = TopicAndPartition(topic, 0)
-  var kc: KafkaCluster = null
+class KafkaClusterSuite extends FunSuite with BeforeAndAfterAll {
+  private val topic = "kcsuitetopic" + Random.nextInt(10000)
+  private val topicAndPartition = TopicAndPartition(topic, 0)
+  private var kc: KafkaCluster = null
+
+  private var kafkaTestUtils: KafkaTestUtils = _
 
   override def beforeAll() {
-    setupKafka()
-    createTopic(topic)
-    sendMessages(topic, Map("a" -> 1))
-    kc = new KafkaCluster(Map("metadata.broker.list" -> s"$brokerAddress"))
+    kafkaTestUtils = new KafkaTestUtils
+    kafkaTestUtils.setup()
+
+    kafkaTestUtils.createTopic(topic)
+    kafkaTestUtils.sendMessages(topic, Map("a" -> 1))
+    kc = new KafkaCluster(Map("metadata.broker.list" -> kafkaTestUtils.brokerAddress))
   }
 
   override def afterAll() {
-    tearDownKafka()
+    if (kafkaTestUtils != null) {
+      kafkaTestUtils.teardown()
+      kafkaTestUtils = null
+    }
   }
 
   test("metadata apis") {
     val leader = kc.findLeaders(Set(topicAndPartition)).right.get(topicAndPartition)
     val leaderAddress = s"${leader._1}:${leader._2}"
-    assert(leaderAddress === brokerAddress, "didn't get leader")
+    assert(leaderAddress === kafkaTestUtils.brokerAddress, "didn't get leader")
 
     val parts = kc.getPartitions(Set(topic)).right.get
     assert(parts(topicAndPartition), "didn't get partitions")
diff --git a/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaRDDSuite.scala b/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaRDDSuite.scala
index a223da70b043f..7d26ce50875b3 100644
--- a/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaRDDSuite.scala
+++ b/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaRDDSuite.scala
@@ -22,18 +22,22 @@ import scala.util.Random
 import kafka.serializer.StringDecoder
 import kafka.common.TopicAndPartition
 import kafka.message.MessageAndMetadata
-import org.scalatest.BeforeAndAfterAll
+import org.scalatest.{BeforeAndAfterAll, FunSuite}
 
 import org.apache.spark._
-import org.apache.spark.SparkContext._
 
-class KafkaRDDSuite extends KafkaStreamSuiteBase with BeforeAndAfterAll {
-  val sparkConf = new SparkConf().setMaster("local[4]").setAppName(this.getClass.getSimpleName)
-  var sc: SparkContext = _
+class KafkaRDDSuite extends FunSuite with BeforeAndAfterAll {
+
+  private var kafkaTestUtils: KafkaTestUtils = _
+
+  private val sparkConf = new SparkConf().setMaster("local[4]")
+    .setAppName(this.getClass.getSimpleName)
+  private var sc: SparkContext = _
+
   override def beforeAll {
     sc = new SparkContext(sparkConf)
-
-    setupKafka()
+    kafkaTestUtils = new KafkaTestUtils
+    kafkaTestUtils.setup()
   }
 
   override def afterAll {
@@ -41,17 +45,21 @@ class KafkaRDDSuite extends KafkaStreamSuiteBase with BeforeAndAfterAll {
       sc.stop
       sc = null
     }
-    tearDownKafka()
+
+    if (kafkaTestUtils != null) {
+      kafkaTestUtils.teardown()
+      kafkaTestUtils = null
+    }
   }
 
   test("basic usage") {
     val topic = "topicbasic"
-    createTopic(topic)
+    kafkaTestUtils.createTopic(topic)
     val messages = Set("the", "quick", "brown", "fox")
-    sendMessages(topic, messages.toArray)
+    kafkaTestUtils.sendMessages(topic, messages.toArray)
 
 
-    val kafkaParams = Map("metadata.broker.list" -> brokerAddress,
+    val kafkaParams = Map("metadata.broker.list" -> kafkaTestUtils.brokerAddress,
       "group.id" -> s"test-consumer-${Random.nextInt(10000)}")
 
     val offsetRanges = Array(OffsetRange(topic, 0, 0, messages.size))
@@ -67,15 +75,15 @@ class KafkaRDDSuite extends KafkaStreamSuiteBase with BeforeAndAfterAll {
     // the idea is to find e.g. off-by-one errors between what kafka has available and the rdd
     val topic = "topic1"
     val sent = Map("a" -> 5, "b" -> 3, "c" -> 10)
-    createTopic(topic)
+    kafkaTestUtils.createTopic(topic)
 
-    val kafkaParams = Map("metadata.broker.list" -> brokerAddress,
+    val kafkaParams = Map("metadata.broker.list" -> kafkaTestUtils.brokerAddress,
       "group.id" -> s"test-consumer-${Random.nextInt(10000)}")
 
     val kc = new KafkaCluster(kafkaParams)
 
     // this is the "lots of messages" case
-    sendMessages(topic, sent)
+    kafkaTestUtils.sendMessages(topic, sent)
     // rdd defined from leaders after sending messages, should get the number sent
     val rdd = getRdd(kc, Set(topic))
 
@@ -92,14 +100,14 @@ class KafkaRDDSuite extends KafkaStreamSuiteBase with BeforeAndAfterAll {
     // shouldn't get anything, since message is sent after rdd was defined
     val sentOnlyOne = Map("d" -> 1)
 
-    sendMessages(topic, sentOnlyOne)
+    kafkaTestUtils.sendMessages(topic, sentOnlyOne)
     assert(rdd2.isDefined)
     assert(rdd2.get.count === 0, "got messages when there shouldn't be any")
 
     // this is the "exactly 1 message" case, namely the single message from sentOnlyOne above
     val rdd3 = getRdd(kc, Set(topic))
     // send lots of messages after rdd was defined, they shouldn't show up
-    sendMessages(topic, Map("extra" -> 22))
+    kafkaTestUtils.sendMessages(topic, Map("extra" -> 22))
 
     assert(rdd3.isDefined)
     assert(rdd3.get.count === sentOnlyOne.values.sum, "didn't get exactly one message")
diff --git a/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaStreamSuite.scala b/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaStreamSuite.scala
index e4966eebb9b34..24699dfc33adb 100644
--- a/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaStreamSuite.scala
+++ b/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaStreamSuite.scala
@@ -17,209 +17,38 @@
 
 package org.apache.spark.streaming.kafka
 
-import java.io.File
-import java.net.InetSocketAddress
-import java.util.Properties
-
 import scala.collection.mutable
 import scala.concurrent.duration._
 import scala.language.postfixOps
 import scala.util.Random
 
-import kafka.admin.AdminUtils
-import kafka.common.{KafkaException, TopicAndPartition}
-import kafka.producer.{KeyedMessage, Producer, ProducerConfig}
-import kafka.serializer.{StringDecoder, StringEncoder}
-import kafka.server.{KafkaConfig, KafkaServer}
-import kafka.utils.ZKStringSerializer
-import org.I0Itec.zkclient.ZkClient
-import org.apache.zookeeper.server.{NIOServerCnxnFactory, ZooKeeperServer}
-import org.scalatest.{BeforeAndAfter, FunSuite}
+import kafka.serializer.StringDecoder
+import org.scalatest.{BeforeAndAfterAll, FunSuite}
 import org.scalatest.concurrent.Eventually
 
-import org.apache.spark.{Logging, SparkConf}
+import org.apache.spark.SparkConf
 import org.apache.spark.storage.StorageLevel
 import org.apache.spark.streaming.{Milliseconds, StreamingContext}
-import org.apache.spark.util.Utils
-
-/**
- * This is an abstract base class for Kafka testsuites. This has the functionality to set up
- * and tear down local Kafka servers, and to push data using Kafka producers.
- */
-abstract class KafkaStreamSuiteBase extends FunSuite with Eventually with Logging {
-
-  private val zkHost = "localhost"
-  private var zkPort: Int = 0
-  private val zkConnectionTimeout = 6000
-  private val zkSessionTimeout = 6000
-  private var zookeeper: EmbeddedZookeeper = _
-  private val brokerHost = "localhost"
-  private var brokerPort = 9092
-  private var brokerConf: KafkaConfig = _
-  private var server: KafkaServer = _
-  private var producer: Producer[String, String] = _
-  private var zkReady = false
-  private var brokerReady = false
-
-  protected var zkClient: ZkClient = _
-
-  def zkAddress: String = {
-    assert(zkReady, "Zookeeper not setup yet or already torn down, cannot get zookeeper address")
-    s"$zkHost:$zkPort"
-  }
 
-  def brokerAddress: String = {
-    assert(brokerReady, "Kafka not setup yet or already torn down, cannot get broker address")
-    s"$brokerHost:$brokerPort"
-  }
-
-  def setupKafka() {
-    // Zookeeper server startup
-    zookeeper = new EmbeddedZookeeper(s"$zkHost:$zkPort")
-    // Get the actual zookeeper binding port
-    zkPort = zookeeper.actualPort
-    zkReady = true
-    logInfo("==================== Zookeeper Started ====================")
+class KafkaStreamSuite extends FunSuite with Eventually with BeforeAndAfterAll {
+  private var ssc: StreamingContext = _
+  private var kafkaTestUtils: KafkaTestUtils = _
 
-    zkClient = new ZkClient(zkAddress, zkSessionTimeout, zkConnectionTimeout, ZKStringSerializer)
-    logInfo("==================== Zookeeper Client Created ====================")
-
-    // Kafka broker startup
-    var bindSuccess: Boolean = false
-    while(!bindSuccess) {
-      try {
-        val brokerProps = getBrokerConfig()
-        brokerConf = new KafkaConfig(brokerProps)
-        server = new KafkaServer(brokerConf)
-        server.startup()
-        logInfo("==================== Kafka Broker Started ====================")
-        bindSuccess = true
-      } catch {
-        case e: KafkaException =>
-          if (e.getMessage != null && e.getMessage.contains("Socket server failed to bind to")) {
-            brokerPort += 1
-          }
-        case e: Exception => throw new Exception("Kafka server create failed", e)
-      }
-    }
-
-    Thread.sleep(2000)
-    logInfo("==================== Kafka + Zookeeper Ready ====================")
-    brokerReady = true
+  override def beforeAll(): Unit = {
+    kafkaTestUtils = new KafkaTestUtils
+    kafkaTestUtils.setup()
   }
 
-  def tearDownKafka() {
-    brokerReady = false
-    zkReady = false
-    if (producer != null) {
-      producer.close()
-      producer = null
-    }
-
-    if (server != null) {
-      server.shutdown()
-      server = null
-    }
-
-    brokerConf.logDirs.foreach { f => Utils.deleteRecursively(new File(f)) }
-
-    if (zkClient != null) {
-      zkClient.close()
-      zkClient = null
-    }
-
-    if (zookeeper != null) {
-      zookeeper.shutdown()
-      zookeeper = null
-    }
-  }
-
-  def createTopic(topic: String) {
-    AdminUtils.createTopic(zkClient, topic, 1, 1)
-    // wait until metadata is propagated
-    waitUntilMetadataIsPropagated(topic, 0)
-    logInfo(s"==================== Topic $topic Created ====================")
-  }
-
-  def sendMessages(topic: String, messageToFreq: Map[String, Int]) {
-    val messages = messageToFreq.flatMap { case (s, freq) => Seq.fill(freq)(s) }.toArray
-    sendMessages(topic, messages)
-  }
-  
-  def sendMessages(topic: String, messages: Array[String]) {
-    producer = new Producer[String, String](new ProducerConfig(getProducerConfig()))
-    producer.send(messages.map { new KeyedMessage[String, String](topic, _ ) }: _*)
-    producer.close()
-    logInfo(s"==================== Sent Messages: ${messages.mkString(", ")} ====================")
-  }
-
-  private def getBrokerConfig(): Properties = {
-    val props = new Properties()
-    props.put("broker.id", "0")
-    props.put("host.name", "localhost")
-    props.put("port", brokerPort.toString)
-    props.put("log.dir", Utils.createTempDir().getAbsolutePath)
-    props.put("zookeeper.connect", zkAddress)
-    props.put("log.flush.interval.messages", "1")
-    props.put("replica.socket.timeout.ms", "1500")
-    props
-  }
-
-  private def getProducerConfig(): Properties = {
-    val brokerAddr = brokerConf.hostName + ":" + brokerConf.port
-    val props = new Properties()
-    props.put("metadata.broker.list", brokerAddr)
-    props.put("serializer.class", classOf[StringEncoder].getName)
-    props
-  }
-
-  private def waitUntilMetadataIsPropagated(topic: String, partition: Int) {
-    eventually(timeout(10000 milliseconds), interval(100 milliseconds)) {
-      assert(
-        server.apis.metadataCache.containsTopicAndPartition(topic, partition),
-        s"Partition [$topic, $partition] metadata not propagated after timeout"
-      )
-    }
-  }
-
-  class EmbeddedZookeeper(val zkConnect: String) {
-    val random = new Random()
-    val snapshotDir = Utils.createTempDir()
-    val logDir = Utils.createTempDir()
-
-    val zookeeper = new ZooKeeperServer(snapshotDir, logDir, 500)
-    val (ip, port) = {
-      val splits = zkConnect.split(":")
-      (splits(0), splits(1).toInt)
-    }
-    val factory = new NIOServerCnxnFactory()
-    factory.configure(new InetSocketAddress(ip, port), 16)
-    factory.startup(zookeeper)
-
-    val actualPort = factory.getLocalPort
-
-    def shutdown() {
-      factory.shutdown()
-      Utils.deleteRecursively(snapshotDir)
-      Utils.deleteRecursively(logDir)
-    }
-  }
-}
-
-
-class KafkaStreamSuite extends KafkaStreamSuiteBase with BeforeAndAfter {
-  var ssc: StreamingContext = _
-
-  before {
-    setupKafka()
-  }
-
-  after {
+  override def afterAll(): Unit = {
     if (ssc != null) {
       ssc.stop()
       ssc = null
     }
-    tearDownKafka()
+
+    if (kafkaTestUtils != null) {
+      kafkaTestUtils.teardown()
+      kafkaTestUtils = null
+    }
   }
 
   test("Kafka input stream") {
@@ -227,10 +56,10 @@ class KafkaStreamSuite extends KafkaStreamSuiteBase with BeforeAndAfter {
     ssc = new StreamingContext(sparkConf, Milliseconds(500))
     val topic = "topic1"
     val sent = Map("a" -> 5, "b" -> 3, "c" -> 10)
-    createTopic(topic)
-    sendMessages(topic, sent)
+    kafkaTestUtils.createTopic(topic)
+    kafkaTestUtils.sendMessages(topic, sent)
 
-    val kafkaParams = Map("zookeeper.connect" -> zkAddress,
+    val kafkaParams = Map("zookeeper.connect" -> kafkaTestUtils.zkAddress,
       "group.id" -> s"test-consumer-${Random.nextInt(10000)}",
       "auto.offset.reset" -> "smallest")
 
@@ -244,14 +73,14 @@ class KafkaStreamSuite extends KafkaStreamSuiteBase with BeforeAndAfter {
         result.put(kv._1, count)
       }
     }
+
     ssc.start()
+
     eventually(timeout(10000 milliseconds), interval(100 milliseconds)) {
       assert(sent.size === result.size)
       sent.keys.foreach { k =>
         assert(sent(k) === result(k).toInt)
       }
     }
-    ssc.stop()
   }
 }
-
diff --git a/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/ReliableKafkaStreamSuite.scala b/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/ReliableKafkaStreamSuite.scala
index 3cd960d1fd1d4..38548dd73b82c 100644
--- a/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/ReliableKafkaStreamSuite.scala
+++ b/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/ReliableKafkaStreamSuite.scala
@@ -17,7 +17,6 @@
 
 package org.apache.spark.streaming.kafka
 
-
 import java.io.File
 
 import scala.collection.mutable
@@ -27,7 +26,7 @@ import scala.util.Random
 
 import kafka.serializer.StringDecoder
 import kafka.utils.{ZKGroupTopicDirs, ZkUtils}
-import org.scalatest.BeforeAndAfter
+import org.scalatest.{BeforeAndAfter, BeforeAndAfterAll, FunSuite}
 import org.scalatest.concurrent.Eventually
 
 import org.apache.spark.SparkConf
@@ -35,47 +34,61 @@ import org.apache.spark.storage.StorageLevel
 import org.apache.spark.streaming.{Milliseconds, StreamingContext}
 import org.apache.spark.util.Utils
 
-class ReliableKafkaStreamSuite extends KafkaStreamSuiteBase with BeforeAndAfter with Eventually {
+class ReliableKafkaStreamSuite extends FunSuite
+    with BeforeAndAfterAll with BeforeAndAfter with Eventually {
 
-  val sparkConf = new SparkConf()
+  private val sparkConf = new SparkConf()
     .setMaster("local[4]")
     .setAppName(this.getClass.getSimpleName)
     .set("spark.streaming.receiver.writeAheadLog.enable", "true")
-  val data = Map("a" -> 10, "b" -> 10, "c" -> 10)
+  private val data = Map("a" -> 10, "b" -> 10, "c" -> 10)
 
+  private var kafkaTestUtils: KafkaTestUtils = _
 
-  var groupId: String = _
-  var kafkaParams: Map[String, String] = _
-  var ssc: StreamingContext = _
-  var tempDirectory: File = null
+  private var groupId: String = _
+  private var kafkaParams: Map[String, String] = _
+  private var ssc: StreamingContext = _
+  private var tempDirectory: File = null
+
+  override def beforeAll() : Unit = {
+    kafkaTestUtils = new KafkaTestUtils
+    kafkaTestUtils.setup()
 
-  before {
-    setupKafka()
     groupId = s"test-consumer-${Random.nextInt(10000)}"
     kafkaParams = Map(
-      "zookeeper.connect" -> zkAddress,
+      "zookeeper.connect" -> kafkaTestUtils.zkAddress,
       "group.id" -> groupId,
       "auto.offset.reset" -> "smallest"
     )
 
-    ssc = new StreamingContext(sparkConf, Milliseconds(500))
     tempDirectory = Utils.createTempDir()
+  }
+
+  override def afterAll(): Unit = {
+    Utils.deleteRecursively(tempDirectory)
+
+    if (kafkaTestUtils != null) {
+      kafkaTestUtils.teardown()
+      kafkaTestUtils = null
+    }
+  }
+
+  before {
+    ssc = new StreamingContext(sparkConf, Milliseconds(500))
     ssc.checkpoint(tempDirectory.getAbsolutePath)
   }
 
   after {
     if (ssc != null) {
       ssc.stop()
+      ssc = null
     }
-    Utils.deleteRecursively(tempDirectory)
-    tearDownKafka()
   }
 
-
   test("Reliable Kafka input stream with single topic") {
-    var topic = "test-topic"
-    createTopic(topic)
-    sendMessages(topic, data)
+    val topic = "test-topic"
+    kafkaTestUtils.createTopic(topic)
+    kafkaTestUtils.sendMessages(topic, data)
 
     // Verify whether the offset of this group/topic/partition is 0 before starting.
     assert(getCommitOffset(groupId, topic, 0) === None)
@@ -91,6 +104,7 @@ class ReliableKafkaStreamSuite extends KafkaStreamSuiteBase with BeforeAndAfter
         }
       }
     ssc.start()
+
     eventually(timeout(20000 milliseconds), interval(200 milliseconds)) {
       // A basic process verification for ReliableKafkaReceiver.
       // Verify whether received message number is equal to the sent message number.
@@ -100,14 +114,13 @@ class ReliableKafkaStreamSuite extends KafkaStreamSuiteBase with BeforeAndAfter
       // Verify the offset number whether it is equal to the total message number.
       assert(getCommitOffset(groupId, topic, 0) === Some(29L))
     }
-    ssc.stop()
   }
 
   test("Reliable Kafka input stream with multiple topics") {
     val topics = Map("topic1" -> 1, "topic2" -> 1, "topic3" -> 1)
     topics.foreach { case (t, _) =>
-      createTopic(t)
-      sendMessages(t, data)
+      kafkaTestUtils.createTopic(t)
+      kafkaTestUtils.sendMessages(t, data)
     }
 
     // Before started, verify all the group/topic/partition offsets are 0.
@@ -118,19 +131,18 @@ class ReliableKafkaStreamSuite extends KafkaStreamSuiteBase with BeforeAndAfter
       ssc, kafkaParams, topics, StorageLevel.MEMORY_ONLY)
     stream.foreachRDD(_ => Unit)
     ssc.start()
+
     eventually(timeout(20000 milliseconds), interval(100 milliseconds)) {
       // Verify the offset for each group/topic to see whether they are equal to the expected one.
       topics.foreach { case (t, _) => assert(getCommitOffset(groupId, t, 0) === Some(29L)) }
     }
-    ssc.stop()
   }
 
 
   /** Getting partition offset from Zookeeper. */
   private def getCommitOffset(groupId: String, topic: String, partition: Int): Option[Long] = {
-    assert(zkClient != null, "Zookeeper client is not initialized")
     val topicDirs = new ZKGroupTopicDirs(groupId, topic)
     val zkPath = s"${topicDirs.consumerOffsetDir}/$partition"
-    ZkUtils.readDataMaybeNull(zkClient, zkPath)._1.map(_.toLong)
+    ZkUtils.readDataMaybeNull(kafkaTestUtils.zookeeperClient, zkPath)._1.map(_.toLong)
   }
 }
diff --git a/python/pyspark/streaming/tests.py b/python/pyspark/streaming/tests.py
index 608f8e26473a6..9b4635e49020b 100644
--- a/python/pyspark/streaming/tests.py
+++ b/python/pyspark/streaming/tests.py
@@ -23,13 +23,16 @@
 import tempfile
 import struct
 
+from py4j.java_collections import MapConverter
+
 from pyspark.context import SparkConf, SparkContext, RDD
 from pyspark.streaming.context import StreamingContext
+from pyspark.streaming.kafka import KafkaUtils
 
 
 class PySparkStreamingTestCase(unittest.TestCase):
 
-    timeout = 10  # seconds
+    timeout = 20  # seconds
     duration = 1
 
     def setUp(self):
@@ -556,5 +559,43 @@ def check_output(n):
         check_output(3)
 
 
+class KafkaStreamTests(PySparkStreamingTestCase):
+
+    def setUp(self):
+        super(KafkaStreamTests, self).setUp()
+
+        kafkaTestUtilsClz = self.ssc._jvm.java.lang.Thread.currentThread().getContextClassLoader()\
+            .loadClass("org.apache.spark.streaming.kafka.KafkaTestUtils")
+        self._kafkaTestUtils = kafkaTestUtilsClz.newInstance()
+        self._kafkaTestUtils.setup()
+
+    def tearDown(self):
+        if self._kafkaTestUtils is not None:
+            self._kafkaTestUtils.teardown()
+            self._kafkaTestUtils = None
+
+        super(KafkaStreamTests, self).tearDown()
+
+    def test_kafka_stream(self):
+        """Test the Python Kafka stream API."""
+        topic = "topic1"
+        sendData = {"a": 3, "b": 5, "c": 10}
+        jSendData = MapConverter().convert(sendData,
+                                           self.ssc.sparkContext._gateway._gateway_client)
+
+        self._kafkaTestUtils.createTopic(topic)
+        self._kafkaTestUtils.sendMessages(topic, jSendData)
+
+        stream = KafkaUtils.createStream(self.ssc, self._kafkaTestUtils.zkAddress(),
+                                         "test-streaming-consumer", {topic: 1},
+                                         {"auto.offset.reset": "smallest"})
+
+        result = {}
+        for i in chain.from_iterable(self._collect(stream.map(lambda x: x[1]),
+                                                   sum(sendData.values()))):
+            result[i] = result.get(i, 0) + 1
+
+        self.assertEqual(sendData, result)
+
 if __name__ == "__main__":
     unittest.main()
diff --git a/python/run-tests b/python/run-tests
index f569a56fb7a9a..f3a07d8aba562 100755
--- a/python/run-tests
+++ b/python/run-tests
@@ -21,6 +21,8 @@
 # Figure out where the Spark framework is installed
 FWDIR="$(cd "`dirname "$0"`"; cd ../; pwd)"
 
+. "$FWDIR"/bin/load-spark-env.sh
+
 # CD into the python directory to find things on the right path
 cd "$FWDIR/python"
 
@@ -57,7 +59,7 @@ function run_core_tests() {
     PYSPARK_DOC_TEST=1 run_test "pyspark/broadcast.py"
     PYSPARK_DOC_TEST=1 run_test "pyspark/accumulators.py"
     run_test "pyspark/serializers.py"
-    run_test "pyspark/profiler.py" 
+    run_test "pyspark/profiler.py"
     run_test "pyspark/shuffle.py"
     run_test "pyspark/tests.py"
 }
@@ -97,6 +99,21 @@ function run_ml_tests() {
 
 function run_streaming_tests() {
     echo "Run streaming tests ..."
+
+    KAFKA_ASSEMBLY_DIR="$FWDIR"/external/kafka-assembly
+    JAR_PATH="${KAFKA_ASSEMBLY_DIR}/target/scala-${SPARK_SCALA_VERSION}"
+    for f in "${JAR_PATH}"/spark-streaming-kafka-assembly-*.jar; do
+      if [[ ! -e "$f" ]]; then
+        echo "Failed to find Spark Streaming Kafka assembly jar in $KAFKA_ASSEMBLY_DIR" 1>&2
+        echo "You need to build Spark with " \
+             "'build/sbt assembly/assembly streaming-kafka-assembly/assembly' or" \
+             "'build/mvn package' before running this program" 1>&2
+        exit 1
+      fi
+      KAFKA_ASSEMBLY_JAR="$f"
+    done
+
+    export PYSPARK_SUBMIT_ARGS="--jars ${KAFKA_ASSEMBLY_JAR} pyspark-shell"
     run_test "pyspark/streaming/util.py"
     run_test "pyspark/streaming/tests.py"
 }

From 18ca089bed41ce3e87deeb14206317863518c12c Mon Sep 17 00:00:00 2001
From: zsxwing <zsxwing@gmail.com>
Date: Fri, 10 Apr 2015 01:51:42 -0700
Subject: [PATCH 34/95] [SPARK-6766][Streaming] Fix issue about
 StreamingListenerBatchSubmitted and StreamingListenerBatchStarted

This PR includes:

1. Send `StreamingListenerBatchSubmitted` when `JobSet` is submitted
1. Fix `StreamingListenerBatchStarted.batchInfo.processingStartTime`
1. Fix a type: `completedaBatchInfos` -> `completedBatchInfos`

Author: zsxwing <zsxwing@gmail.com>

Closes #5414 from zsxwing/SPARK-6766 and squashes the following commits:

2f85060 [zsxwing] Update tests
ca0955b [zsxwing] Combine unit tests
79b4fed [zsxwing] Add StreamingJobProgressListenerSuite to test StreamingJobProgressListener
fc3a2a1 [zsxwing] Add unit tests for SPARK-6766
74aed99 [zsxwing] Refactor as per TD's suggestion
493f978 [zsxwing] Send StreamingListenerBatchSubmitted when JobSet is submitted; fix StreamingListenerBatchStarted.batchInfo.processingStartTime; fix a typo
---
 .../streaming/scheduler/JobScheduler.scala    |   8 +-
 .../ui/StreamingJobProgressListener.scala     |  16 +--
 .../streaming/StreamingListenerSuite.scala    |  55 ++++++--
 .../StreamingJobProgressListenerSuite.scala   | 119 ++++++++++++++++++
 4 files changed, 180 insertions(+), 18 deletions(-)
 create mode 100644 streaming/src/test/scala/org/apache/spark/streaming/ui/StreamingJobProgressListenerSuite.scala

diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala
index d6a93acbe711b..95f1857b4c377 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala
@@ -105,6 +105,7 @@ class JobScheduler(val ssc: StreamingContext) extends Logging {
     if (jobSet.jobs.isEmpty) {
       logInfo("No jobs added for time " + jobSet.time)
     } else {
+      listenerBus.post(StreamingListenerBatchSubmitted(jobSet.toBatchInfo))
       jobSets.put(jobSet.time, jobSet)
       jobSet.jobs.foreach(job => jobExecutor.execute(new JobHandler(job)))
       logInfo("Added jobs for time " + jobSet.time)
@@ -134,10 +135,13 @@ class JobScheduler(val ssc: StreamingContext) extends Logging {
 
   private def handleJobStart(job: Job) {
     val jobSet = jobSets.get(job.time)
-    if (!jobSet.hasStarted) {
+    val isFirstJobOfJobSet = !jobSet.hasStarted
+    jobSet.handleJobStart(job)
+    if (isFirstJobOfJobSet) {
+      // "StreamingListenerBatchStarted" should be posted after calling "handleJobStart" to get the
+      // correct "jobSet.processingStartTime".
       listenerBus.post(StreamingListenerBatchStarted(jobSet.toBatchInfo))
     }
-    jobSet.handleJobStart(job)
     logInfo("Starting job " + job.id + " from job set of time " + jobSet.time)
   }
 
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala
index e4bd067cacb77..84f80e638f638 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala
@@ -33,7 +33,7 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext)
 
   private val waitingBatchInfos = new HashMap[Time, BatchInfo]
   private val runningBatchInfos = new HashMap[Time, BatchInfo]
-  private val completedaBatchInfos = new Queue[BatchInfo]
+  private val completedBatchInfos = new Queue[BatchInfo]
   private val batchInfoLimit = ssc.conf.getInt("spark.streaming.ui.retainedBatches", 100)
   private var totalCompletedBatches = 0L
   private var totalReceivedRecords = 0L
@@ -62,7 +62,7 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext)
 
   override def onBatchSubmitted(batchSubmitted: StreamingListenerBatchSubmitted): Unit = {
     synchronized {
-      runningBatchInfos(batchSubmitted.batchInfo.batchTime) = batchSubmitted.batchInfo
+      waitingBatchInfos(batchSubmitted.batchInfo.batchTime) = batchSubmitted.batchInfo
     }
   }
 
@@ -79,8 +79,8 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext)
     synchronized {
       waitingBatchInfos.remove(batchCompleted.batchInfo.batchTime)
       runningBatchInfos.remove(batchCompleted.batchInfo.batchTime)
-      completedaBatchInfos.enqueue(batchCompleted.batchInfo)
-      if (completedaBatchInfos.size > batchInfoLimit) completedaBatchInfos.dequeue()
+      completedBatchInfos.enqueue(batchCompleted.batchInfo)
+      if (completedBatchInfos.size > batchInfoLimit) completedBatchInfos.dequeue()
       totalCompletedBatches += 1L
 
       batchCompleted.batchInfo.receivedBlockInfo.foreach { case (_, infos) =>
@@ -118,7 +118,7 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext)
   }
 
   def retainedCompletedBatches: Seq[BatchInfo] = synchronized {
-    completedaBatchInfos.toSeq
+    completedBatchInfos.toSeq
   }
 
   def processingDelayDistribution: Option[Distribution] = synchronized {
@@ -165,7 +165,7 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext)
   }
 
   def lastCompletedBatch: Option[BatchInfo] = {
-    completedaBatchInfos.sortBy(_.batchTime)(Time.ordering).lastOption
+    completedBatchInfos.sortBy(_.batchTime)(Time.ordering).lastOption
   }
 
   def lastReceivedBatch: Option[BatchInfo] = {
@@ -174,10 +174,10 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext)
 
   private def retainedBatches: Seq[BatchInfo] = synchronized {
     (waitingBatchInfos.values.toSeq ++
-      runningBatchInfos.values.toSeq ++ completedaBatchInfos).sortBy(_.batchTime)(Time.ordering)
+      runningBatchInfos.values.toSeq ++ completedBatchInfos).sortBy(_.batchTime)(Time.ordering)
   }
 
   private def extractDistribution(getMetric: BatchInfo => Option[Long]): Option[Distribution] = {
-    Distribution(completedaBatchInfos.flatMap(getMetric(_)).map(_.toDouble))
+    Distribution(completedBatchInfos.flatMap(getMetric(_)).map(_.toDouble))
   }
 }
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala
index 852e8bb71d4f6..7210439509541 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala
@@ -46,10 +46,38 @@ class StreamingListenerSuite extends TestSuiteBase with Matchers {
     val collector = new BatchInfoCollector
     ssc.addStreamingListener(collector)
     runStreams(ssc, input.size, input.size)
-    val batchInfos = collector.batchInfos
-    batchInfos should have size 4
 
-    batchInfos.foreach(info => {
+    // SPARK-6766: batch info should be submitted
+    val batchInfosSubmitted = collector.batchInfosSubmitted
+    batchInfosSubmitted should have size 4
+
+    batchInfosSubmitted.foreach(info => {
+      info.schedulingDelay should be (None)
+      info.processingDelay should be (None)
+      info.totalDelay should be (None)
+    })
+
+    isInIncreasingOrder(batchInfosSubmitted.map(_.submissionTime)) should be (true)
+
+    // SPARK-6766: processingStartTime of batch info should not be None when starting
+    val batchInfosStarted = collector.batchInfosStarted
+    batchInfosStarted should have size 4
+
+    batchInfosStarted.foreach(info => {
+      info.schedulingDelay should not be None
+      info.schedulingDelay.get should be >= 0L
+      info.processingDelay should be (None)
+      info.totalDelay should be (None)
+    })
+
+    isInIncreasingOrder(batchInfosStarted.map(_.submissionTime)) should be (true)
+    isInIncreasingOrder(batchInfosStarted.map(_.processingStartTime.get)) should be (true)
+
+    // test onBatchCompleted
+    val batchInfosCompleted = collector.batchInfosCompleted
+    batchInfosCompleted should have size 4
+
+    batchInfosCompleted.foreach(info => {
       info.schedulingDelay should not be None
       info.processingDelay should not be None
       info.totalDelay should not be None
@@ -58,9 +86,9 @@ class StreamingListenerSuite extends TestSuiteBase with Matchers {
       info.totalDelay.get should be >= 0L
     })
 
-    isInIncreasingOrder(batchInfos.map(_.submissionTime)) should be (true)
-    isInIncreasingOrder(batchInfos.map(_.processingStartTime.get)) should be (true)
-    isInIncreasingOrder(batchInfos.map(_.processingEndTime.get)) should be (true)
+    isInIncreasingOrder(batchInfosCompleted.map(_.submissionTime)) should be (true)
+    isInIncreasingOrder(batchInfosCompleted.map(_.processingStartTime.get)) should be (true)
+    isInIncreasingOrder(batchInfosCompleted.map(_.processingEndTime.get)) should be (true)
   }
 
   test("receiver info reporting") {
@@ -99,9 +127,20 @@ class StreamingListenerSuite extends TestSuiteBase with Matchers {
 
 /** Listener that collects information on processed batches */
 class BatchInfoCollector extends StreamingListener {
-  val batchInfos = new ArrayBuffer[BatchInfo]
+  val batchInfosCompleted = new ArrayBuffer[BatchInfo]
+  val batchInfosStarted = new ArrayBuffer[BatchInfo]
+  val batchInfosSubmitted = new ArrayBuffer[BatchInfo]
+
+  override def onBatchSubmitted(batchSubmitted: StreamingListenerBatchSubmitted) {
+    batchInfosSubmitted += batchSubmitted.batchInfo
+  }
+
+  override def onBatchStarted(batchStarted: StreamingListenerBatchStarted) {
+    batchInfosStarted += batchStarted.batchInfo
+  }
+
   override def onBatchCompleted(batchCompleted: StreamingListenerBatchCompleted) {
-    batchInfos += batchCompleted.batchInfo
+    batchInfosCompleted += batchCompleted.batchInfo
   }
 }
 
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ui/StreamingJobProgressListenerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ui/StreamingJobProgressListenerSuite.scala
new file mode 100644
index 0000000000000..2b9d164500b72
--- /dev/null
+++ b/streaming/src/test/scala/org/apache/spark/streaming/ui/StreamingJobProgressListenerSuite.scala
@@ -0,0 +1,119 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.ui
+
+import org.scalatest.Matchers
+
+import org.apache.spark.streaming.dstream.DStream
+import org.apache.spark.streaming.scheduler._
+import org.apache.spark.streaming.{Time, Milliseconds, TestSuiteBase}
+
+class StreamingJobProgressListenerSuite extends TestSuiteBase with Matchers {
+
+  val input = (1 to 4).map(Seq(_)).toSeq
+  val operation = (d: DStream[Int]) => d.map(x => x)
+
+  override def batchDuration = Milliseconds(100)
+
+  test("onBatchSubmitted, onBatchStarted, onBatchCompleted, " +
+    "onReceiverStarted, onReceiverError, onReceiverStopped") {
+    val ssc = setupStreams(input, operation)
+    val listener = new StreamingJobProgressListener(ssc)
+
+    val receivedBlockInfo = Map(
+      0 -> Array(ReceivedBlockInfo(0, 100, null), ReceivedBlockInfo(0, 200, null)),
+      1 -> Array(ReceivedBlockInfo(1, 300, null))
+    )
+
+    // onBatchSubmitted
+    val batchInfoSubmitted = BatchInfo(Time(1000), receivedBlockInfo, 1000, None, None)
+    listener.onBatchSubmitted(StreamingListenerBatchSubmitted(batchInfoSubmitted))
+    listener.waitingBatches should be (List(batchInfoSubmitted))
+    listener.runningBatches should be (Nil)
+    listener.retainedCompletedBatches should be (Nil)
+    listener.lastCompletedBatch should be (None)
+    listener.numUnprocessedBatches should be (1)
+    listener.numTotalCompletedBatches should be (0)
+    listener.numTotalProcessedRecords should be (0)
+    listener.numTotalReceivedRecords should be (0)
+
+    // onBatchStarted
+    val batchInfoStarted = BatchInfo(Time(1000), receivedBlockInfo, 1000, Some(2000), None)
+    listener.onBatchStarted(StreamingListenerBatchStarted(batchInfoStarted))
+    listener.waitingBatches should be (Nil)
+    listener.runningBatches should be (List(batchInfoStarted))
+    listener.retainedCompletedBatches should be (Nil)
+    listener.lastCompletedBatch should be (None)
+    listener.numUnprocessedBatches should be (1)
+    listener.numTotalCompletedBatches should be (0)
+    listener.numTotalProcessedRecords should be (0)
+    listener.numTotalReceivedRecords should be (600)
+
+    // onBatchCompleted
+    val batchInfoCompleted = BatchInfo(Time(1000), receivedBlockInfo, 1000, Some(2000), None)
+    listener.onBatchCompleted(StreamingListenerBatchCompleted(batchInfoCompleted))
+    listener.waitingBatches should be (Nil)
+    listener.runningBatches should be (Nil)
+    listener.retainedCompletedBatches should be (List(batchInfoCompleted))
+    listener.lastCompletedBatch should be (Some(batchInfoCompleted))
+    listener.numUnprocessedBatches should be (0)
+    listener.numTotalCompletedBatches should be (1)
+    listener.numTotalProcessedRecords should be (600)
+    listener.numTotalReceivedRecords should be (600)
+
+    // onReceiverStarted
+    val receiverInfoStarted = ReceiverInfo(0, "test", null, true, "localhost")
+    listener.onReceiverStarted(StreamingListenerReceiverStarted(receiverInfoStarted))
+    listener.receiverInfo(0) should be (Some(receiverInfoStarted))
+    listener.receiverInfo(1) should be (None)
+
+    // onReceiverError
+    val receiverInfoError = ReceiverInfo(1, "test", null, true, "localhost")
+    listener.onReceiverError(StreamingListenerReceiverError(receiverInfoError))
+    listener.receiverInfo(0) should be (Some(receiverInfoStarted))
+    listener.receiverInfo(1) should be (Some(receiverInfoError))
+    listener.receiverInfo(2) should be (None)
+
+    // onReceiverStopped
+    val receiverInfoStopped = ReceiverInfo(2, "test", null, true, "localhost")
+    listener.onReceiverStopped(StreamingListenerReceiverStopped(receiverInfoStopped))
+    listener.receiverInfo(0) should be (Some(receiverInfoStarted))
+    listener.receiverInfo(1) should be (Some(receiverInfoError))
+    listener.receiverInfo(2) should be (Some(receiverInfoStopped))
+    listener.receiverInfo(3) should be (None)
+  }
+
+  test("Remove the old completed batches when exceeding the limit") {
+    val ssc = setupStreams(input, operation)
+    val limit = ssc.conf.getInt("spark.streaming.ui.retainedBatches", 100)
+    val listener = new StreamingJobProgressListener(ssc)
+
+    val receivedBlockInfo = Map(
+      0 -> Array(ReceivedBlockInfo(0, 100, null), ReceivedBlockInfo(0, 200, null)),
+      1 -> Array(ReceivedBlockInfo(1, 300, null))
+    )
+    val batchInfoCompleted = BatchInfo(Time(1000), receivedBlockInfo, 1000, Some(2000), None)
+
+    for(_ <- 0 until (limit + 10)) {
+      listener.onBatchCompleted(StreamingListenerBatchCompleted(batchInfoCompleted))
+    }
+
+    listener.retainedCompletedBatches.size should be (limit)
+    listener.numTotalCompletedBatches should be(limit + 10)
+  }
+}

From 9f5ed99d644949443d19c4895de6e0ece4be24d0 Mon Sep 17 00:00:00 2001
From: "June.He" <jun.hejun@huawei.com>
Date: Fri, 10 Apr 2015 20:02:35 +0100
Subject: [PATCH 35/95] [SPARK-6773][Tests]Fix RAT checks still passed issue
 when download rat jar failed

check -license will passed in next time when rat jar download failed.

Add 2 step to fix this:
1. Clean the rat.jar if download failed.
2. Add a check logic after run rat checking.

Author: June.He <jun.hejun@huawei.com>

Closes #5421 from sisihj/rat-issue and squashes the following commits:

4958302 [June.He] delete redundant check and add quoted
66f7088 [June.He] Fix RAT checks still passed issue when download rat jar failed
7311e83 [June.He] Fix RAT checks still passed issue when download rat jar failed
---
 dev/check-license | 45 ++++++++++++++++++++++++---------------------
 1 file changed, 24 insertions(+), 21 deletions(-)

diff --git a/dev/check-license b/dev/check-license
index 39943f882b6ca..10740cfdc5242 100755
--- a/dev/check-license
+++ b/dev/check-license
@@ -24,29 +24,27 @@ acquire_rat_jar () {
 
   JAR="$rat_jar"
 
-  if [[ ! -f "$rat_jar" ]]; then
-    # Download rat launch jar if it hasn't been downloaded yet
-    if [ ! -f "$JAR" ]; then
-      # Download
-      printf "Attempting to fetch rat\n"
-      JAR_DL="${JAR}.part"
-      if [ $(command -v curl) ]; then
-        curl -L --silent "${URL}" > "$JAR_DL" && mv "$JAR_DL" "$JAR"
-      elif [ $(command -v wget) ]; then
-        wget --quiet ${URL} -O "$JAR_DL" && mv "$JAR_DL" "$JAR"
-      else
-        printf "You do not have curl or wget installed, please install rat manually.\n"
-        exit -1
-      fi
-    fi
-
-    unzip -tq $JAR &> /dev/null
-    if [ $? -ne 0 ]; then
-      # We failed to download
-      printf "Our attempt to download rat locally to ${JAR} failed. Please install rat manually.\n"
+  # Download rat launch jar if it hasn't been downloaded yet
+  if [ ! -f "$JAR" ]; then
+    # Download
+    printf "Attempting to fetch rat\n"
+    JAR_DL="${JAR}.part"
+    if [ $(command -v curl) ]; then
+      curl -L --silent "${URL}" > "$JAR_DL" && mv "$JAR_DL" "$JAR"
+    elif [ $(command -v wget) ]; then
+      wget --quiet ${URL} -O "$JAR_DL" && mv "$JAR_DL" "$JAR"
+    else
+      printf "You do not have curl or wget installed, please install rat manually.\n"
       exit -1
     fi
-    printf "Launching rat from ${JAR}\n"
+  fi
+
+  unzip -tq "$JAR" &> /dev/null
+  if [ $? -ne 0 ]; then 
+    # We failed to download
+    rm "$JAR"
+    printf "Our attempt to download rat locally to ${JAR} failed. Please install rat manually.\n"
+    exit -1
   fi
 }
 
@@ -71,6 +69,11 @@ mkdir -p "$FWDIR"/lib
 
 $java_cmd -jar "$rat_jar" -E "$FWDIR"/.rat-excludes  -d "$FWDIR" > rat-results.txt
 
+if [ $? -ne 0 ]; then
+   echo "RAT exited abnormally"
+   exit 1
+fi
+
 ERRORS="$(cat rat-results.txt | grep -e "??")"
 
 if test ! -z "$ERRORS"; then 

From b9baa4cd9f6e9fc58161f79744b6b7729894d920 Mon Sep 17 00:00:00 2001
From: Volodymyr Lyubinets <vlyubin@gmail.com>
Date: Fri, 10 Apr 2015 12:09:54 -0700
Subject: [PATCH 36/95] [SQL] [SPARK-6794] Use kryo-based SparkSqlSerializer
 for GeneralHashedRelation

Benchmarking results: http://pastie.org/private/1dneo1mta5zpsw6gmsoeq

Author: Volodymyr Lyubinets <vlyubin@gmail.com>

Closes #5433 from vlyubin/joins and squashes the following commits:

d70c829 [Volodymyr Lyubinets] Addressed review feedback
527eac6 [Volodymyr Lyubinets] Use kryo-based SparkSqlSerializer for GeneralHashedRelation
---
 .../sql/execution/SparkSqlSerializer.scala    |  3 +-
 .../sql/execution/joins/HashedRelation.scala  | 47 +++++++++++++++++--
 2 files changed, 44 insertions(+), 6 deletions(-)

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala
index 967bd76b302d8..347e2f4a1a1af 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala
@@ -26,14 +26,13 @@ import scala.reflect.ClassTag
 import com.clearspring.analytics.stream.cardinality.HyperLogLog
 import com.esotericsoftware.kryo.io.{Input, Output}
 import com.esotericsoftware.kryo.{Serializer, Kryo}
-import com.twitter.chill.{AllScalaRegistrar, ResourcePool}
+import com.twitter.chill.ResourcePool
 
 import org.apache.spark.{SparkEnv, SparkConf}
 import org.apache.spark.serializer.{SerializerInstance, KryoSerializer}
 import org.apache.spark.sql.catalyst.expressions.GenericRow
 import org.apache.spark.util.collection.OpenHashSet
 import org.apache.spark.util.MutablePair
-import org.apache.spark.util.Utils
 
 import org.apache.spark.sql.catalyst.expressions.codegen.{IntegerHashSet, LongHashSet}
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashedRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashedRelation.scala
index 2fa1cf5add3b5..ab84c123e0c0b 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashedRelation.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashedRelation.scala
@@ -17,9 +17,11 @@
 
 package org.apache.spark.sql.execution.joins
 
+import java.io.{ObjectInput, ObjectOutput, Externalizable}
 import java.util.{HashMap => JavaHashMap}
 
 import org.apache.spark.sql.catalyst.expressions.{Projection, Row}
+import org.apache.spark.sql.execution.SparkSqlSerializer
 import org.apache.spark.util.collection.CompactBuffer
 
 
@@ -29,16 +31,43 @@ import org.apache.spark.util.collection.CompactBuffer
  */
 private[joins] sealed trait HashedRelation {
   def get(key: Row): CompactBuffer[Row]
+
+  // This is a helper method to implement Externalizable, and is used by
+  // GeneralHashedRelation and UniqueKeyHashedRelation
+  protected def writeBytes(out: ObjectOutput, serialized: Array[Byte]): Unit = {
+    out.writeInt(serialized.length) // Write the length of serialized bytes first
+    out.write(serialized)
+  }
+
+  // This is a helper method to implement Externalizable, and is used by
+  // GeneralHashedRelation and UniqueKeyHashedRelation
+  protected def readBytes(in: ObjectInput): Array[Byte] = {
+    val serializedSize = in.readInt() // Read the length of serialized bytes first
+    val bytes = new Array[Byte](serializedSize)
+    in.readFully(bytes)
+    bytes
+  }
 }
 
 
 /**
  * A general [[HashedRelation]] backed by a hash map that maps the key into a sequence of values.
  */
-private[joins] final class GeneralHashedRelation(hashTable: JavaHashMap[Row, CompactBuffer[Row]])
-  extends HashedRelation with Serializable {
+private[joins] final class GeneralHashedRelation(
+    private var hashTable: JavaHashMap[Row, CompactBuffer[Row]])
+  extends HashedRelation with Externalizable {
+
+  def this() = this(null) // Needed for serialization
 
   override def get(key: Row): CompactBuffer[Row] = hashTable.get(key)
+
+  override def writeExternal(out: ObjectOutput): Unit = {
+    writeBytes(out, SparkSqlSerializer.serialize(hashTable))
+  }
+
+  override def readExternal(in: ObjectInput): Unit = {
+    hashTable = SparkSqlSerializer.deserialize(readBytes(in))
+  }
 }
 
 
@@ -46,8 +75,10 @@ private[joins] final class GeneralHashedRelation(hashTable: JavaHashMap[Row, Com
  * A specialized [[HashedRelation]] that maps key into a single value. This implementation
  * assumes the key is unique.
  */
-private[joins] final class UniqueKeyHashedRelation(hashTable: JavaHashMap[Row, Row])
-  extends HashedRelation with Serializable {
+private[joins] final class UniqueKeyHashedRelation(private var hashTable: JavaHashMap[Row, Row])
+  extends HashedRelation with Externalizable {
+
+  def this() = this(null) // Needed for serialization
 
   override def get(key: Row): CompactBuffer[Row] = {
     val v = hashTable.get(key)
@@ -55,6 +86,14 @@ private[joins] final class UniqueKeyHashedRelation(hashTable: JavaHashMap[Row, R
   }
 
   def getValue(key: Row): Row = hashTable.get(key)
+
+  override def writeExternal(out: ObjectOutput): Unit = {
+    writeBytes(out, SparkSqlSerializer.serialize(hashTable))
+  }
+
+  override def readExternal(in: ObjectInput): Unit = {
+    hashTable = SparkSqlSerializer.deserialize(readBytes(in))
+  }
 }
 
 

From 0375134f42197f2e29aa865a513cda381f0a1445 Mon Sep 17 00:00:00 2001
From: Milan Straka <fox@ucw.cz>
Date: Fri, 10 Apr 2015 13:50:32 -0700
Subject: [PATCH 37/95] [SPARK-5969][PySpark] Fix descending
 pyspark.rdd.sortByKey.

The samples should always be sorted in ascending order, because bisect.bisect_left is used on it. The reverse order of the result is already achieved in rangePartitioner by reversing the found index.

The current implementation also work, but always uses only two partitions -- the first one and the last one (because the bisect_left return returns either "beginning" or "end" for a descending sequence).

Author: Milan Straka <fox@ucw.cz>

This patch had conflicts when merged, resolved by
Committer: Josh Rosen <joshrosen@databricks.com>

Closes #4761 from foxik/fix-descending-sort and squashes the following commits:

95896b5 [Milan Straka] Add regression test for SPARK-5969.
5757490 [Milan Straka] Fix descending pyspark.rdd.sortByKey.
---
 python/pyspark/rdd.py   |  2 +-
 python/pyspark/tests.py | 11 +++++++++++
 2 files changed, 12 insertions(+), 1 deletion(-)

diff --git a/python/pyspark/rdd.py b/python/pyspark/rdd.py
index 1b18789040360..c8e54ed5c6b2c 100644
--- a/python/pyspark/rdd.py
+++ b/python/pyspark/rdd.py
@@ -595,7 +595,7 @@ def sortPartition(iterator):
         maxSampleSize = numPartitions * 20.0  # constant from Spark's RangePartitioner
         fraction = min(maxSampleSize / max(rddSize, 1), 1.0)
         samples = self.sample(False, fraction, 1).map(lambda (k, v): k).collect()
-        samples = sorted(samples, reverse=(not ascending), key=keyfunc)
+        samples = sorted(samples, key=keyfunc)
 
         # we have numPartitions many parts but one of the them has
         # an implicit boundary
diff --git a/python/pyspark/tests.py b/python/pyspark/tests.py
index 0bd5d20f7877f..0e3721b55adf7 100644
--- a/python/pyspark/tests.py
+++ b/python/pyspark/tests.py
@@ -829,6 +829,17 @@ def test_take_on_jrdd(self):
         rdd = self.sc.parallelize(range(1 << 20)).map(lambda x: str(x))
         rdd._jrdd.first()
 
+    def test_sortByKey_uses_all_partitions_not_only_first_and_last(self):
+        # Regression test for SPARK-5969
+        seq = [(i * 59 % 101, i) for i in range(101)]  # unsorted sequence
+        rdd = self.sc.parallelize(seq)
+        for ascending in [True, False]:
+            sort = rdd.sortByKey(ascending=ascending, numPartitions=5)
+            self.assertEqual(sort.collect(), sorted(seq, reverse=not ascending))
+            sizes = sort.glom().map(len).collect()
+            for size in sizes:
+                self.assertGreater(size, 0)
+
 
 class ProfilerTests(PySparkTestCase):
 

From 4740d6a158cb4d35408a95265c5b950b9e9628a3 Mon Sep 17 00:00:00 2001
From: Davies Liu <davies@databricks.com>
Date: Fri, 10 Apr 2015 14:04:53 -0700
Subject: [PATCH 38/95] [SPARK-6216] [PySpark] check the python version in
 worker

Author: Davies Liu <davies@databricks.com>

Closes #5404 from davies/check_version and squashes the following commits:

e559248 [Davies Liu] add tests
ec33b5f [Davies Liu] check the python version in worker
---
 python/pyspark/rdd.py    |  2 +-
 python/pyspark/tests.py  | 16 ++++++++++++++++
 python/pyspark/worker.py |  6 +++++-
 3 files changed, 22 insertions(+), 2 deletions(-)

diff --git a/python/pyspark/rdd.py b/python/pyspark/rdd.py
index c8e54ed5c6b2c..c9ac95d117574 100644
--- a/python/pyspark/rdd.py
+++ b/python/pyspark/rdd.py
@@ -2233,7 +2233,7 @@ def toLocalIterator(self):
 def _prepare_for_python_RDD(sc, command, obj=None):
     # the serialized command will be compressed by broadcast
     ser = CloudPickleSerializer()
-    pickled_command = ser.dumps(command)
+    pickled_command = ser.dumps((command, sys.version_info[:2]))
     if len(pickled_command) > (1 << 20):  # 1M
         broadcast = sc.broadcast(pickled_command)
         pickled_command = ser.dumps(broadcast)
diff --git a/python/pyspark/tests.py b/python/pyspark/tests.py
index 0e3721b55adf7..b938b9ce12395 100644
--- a/python/pyspark/tests.py
+++ b/python/pyspark/tests.py
@@ -35,6 +35,8 @@
 import threading
 import hashlib
 
+from py4j.protocol import Py4JJavaError
+
 if sys.version_info[:2] <= (2, 6):
     try:
         import unittest2 as unittest
@@ -1494,6 +1496,20 @@ def count():
         self.assertTrue(not t.isAlive())
         self.assertEqual(100000, rdd.count())
 
+    def test_with_different_versions_of_python(self):
+        rdd = self.sc.parallelize(range(10))
+        rdd.count()
+        version = sys.version_info
+        sys.version_info = (2, 0, 0)
+        log4j = self.sc._jvm.org.apache.log4j
+        old_level = log4j.LogManager.getRootLogger().getLevel()
+        log4j.LogManager.getRootLogger().setLevel(log4j.Level.FATAL)
+        try:
+            self.assertRaises(Py4JJavaError, lambda: rdd.count())
+        finally:
+            sys.version_info = version
+            log4j.LogManager.getRootLogger().setLevel(old_level)
+
 
 class SparkSubmitTests(unittest.TestCase):
 
diff --git a/python/pyspark/worker.py b/python/pyspark/worker.py
index 8a93c320ec5d3..452d6fabdcc17 100644
--- a/python/pyspark/worker.py
+++ b/python/pyspark/worker.py
@@ -88,7 +88,11 @@ def main(infile, outfile):
         command = pickleSer._read_with_length(infile)
         if isinstance(command, Broadcast):
             command = pickleSer.loads(command.value)
-        (func, profiler, deserializer, serializer) = command
+        (func, profiler, deserializer, serializer), version = command
+        if version != sys.version_info[:2]:
+            raise Exception(("Python in worker has different version %s than that in " +
+                            "driver %s, PySpark cannot run with different minor versions") %
+                            (sys.version_info[:2], version))
         init_time = time.time()
 
         def process():

From 68ecdb7f99ae30f7c04c33a47ab7f59a3836f2a4 Mon Sep 17 00:00:00 2001
From: Davies Liu <davies@databricks.com>
Date: Fri, 10 Apr 2015 15:35:45 -0700
Subject: [PATCH 39/95] [SPARK-6850] [SparkR] use one partition when we need to
 compare the whole result

Author: Davies Liu <davies@databricks.com>

Closes #5460 from davies/r_test and squashes the following commits:

0a593ce [Davies Liu] use one partition when we need to compare the whole result
---
 R/pkg/inst/tests/test_binaryFile.R | 4 ++--
 R/pkg/inst/tests/test_textFile.R   | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/R/pkg/inst/tests/test_binaryFile.R b/R/pkg/inst/tests/test_binaryFile.R
index 4bb5f58d83dc9..ca4218f3819f8 100644
--- a/R/pkg/inst/tests/test_binaryFile.R
+++ b/R/pkg/inst/tests/test_binaryFile.R
@@ -27,7 +27,7 @@ test_that("saveAsObjectFile()/objectFile() following textFile() works", {
   fileName2 <- tempfile(pattern="spark-test", fileext=".tmp")
   writeLines(mockFile, fileName1)
 
-  rdd <- textFile(sc, fileName1)
+  rdd <- textFile(sc, fileName1, 1)
   saveAsObjectFile(rdd, fileName2)
   rdd <- objectFile(sc, fileName2)
   expect_equal(collect(rdd), as.list(mockFile))
@@ -40,7 +40,7 @@ test_that("saveAsObjectFile()/objectFile() works on a parallelized list", {
   fileName <- tempfile(pattern="spark-test", fileext=".tmp")
 
   l <- list(1, 2, 3)
-  rdd <- parallelize(sc, l)
+  rdd <- parallelize(sc, l, 1)
   saveAsObjectFile(rdd, fileName)
   rdd <- objectFile(sc, fileName)
   expect_equal(collect(rdd), l)
diff --git a/R/pkg/inst/tests/test_textFile.R b/R/pkg/inst/tests/test_textFile.R
index 7bb3e8003131d..6b87b4b3e0b08 100644
--- a/R/pkg/inst/tests/test_textFile.R
+++ b/R/pkg/inst/tests/test_textFile.R
@@ -81,7 +81,7 @@ test_that("textFile() followed by a saveAsTextFile() returns the same content",
   fileName2 <- tempfile(pattern="spark-test", fileext=".tmp")
   writeLines(mockFile, fileName1)
 
-  rdd <- textFile(sc, fileName1)
+  rdd <- textFile(sc, fileName1, 1L)
   saveAsTextFile(rdd, fileName2)
   rdd <- textFile(sc, fileName2)
   expect_equal(collect(rdd), as.list(mockFile))
@@ -93,7 +93,7 @@ test_that("textFile() followed by a saveAsTextFile() returns the same content",
 test_that("saveAsTextFile() on a parallelized list works as expected", {
   fileName <- tempfile(pattern="spark-test", fileext=".tmp")
   l <- list(1, 2, 3)
-  rdd <- parallelize(sc, l)
+  rdd <- parallelize(sc, l, 1L)
   saveAsTextFile(rdd, fileName)
   rdd <- textFile(sc, fileName)
   expect_equal(collect(rdd), lapply(l, function(x) {toString(x)}))

From 23d5f8864f7d665a74b1d38118700139854dbb1c Mon Sep 17 00:00:00 2001
From: Michael Armbrust <michael@databricks.com>
Date: Fri, 10 Apr 2015 16:05:14 -0700
Subject: [PATCH 40/95] [SPARK-6851][SQL] Create new instance for each
 converted parquet relation

Otherwise we end up rewriting predicates to be trivially equal (i.e. `a#1 = a#2` -> `a#3 = a#3`), at which point the query is no longer valid.

Author: Michael Armbrust <michael@databricks.com>

Closes #5458 from marmbrus/selfJoinParquet and squashes the following commits:

22df77c [Michael Armbrust] [SPARK-6851][SQL] Create new instance for each converted parquet relation
---
 .../spark/sql/hive/HiveMetastoreCatalog.scala |  4 +-
 .../sql/hive/execution/SQLQuerySuite.scala    | 78 ++++++++++++++++++-
 2 files changed, 80 insertions(+), 2 deletions(-)

diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala
index 315fab673da5c..3ed5c5b031736 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala
@@ -279,7 +279,7 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with
       }
     }
 
-    if (metastoreRelation.hiveQlTable.isPartitioned) {
+    val result = if (metastoreRelation.hiveQlTable.isPartitioned) {
       val partitionSchema = StructType.fromAttributes(metastoreRelation.partitionKeys)
       val partitionColumnDataTypes = partitionSchema.map(_.dataType)
       val partitions = metastoreRelation.hiveQlPartitions.map { p =>
@@ -314,6 +314,8 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with
 
       parquetRelation
     }
+
+    result.newInstance()
   }
 
   override def getTables(databaseName: Option[String]): Seq[(String, Boolean)] = synchronized {
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
index 7811bd2e9effb..4c369c0634bda 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
@@ -34,6 +34,17 @@ case class Nested3(f3: Int)
 case class NestedArray2(b: Seq[Int])
 case class NestedArray1(a: NestedArray2)
 
+case class Order(
+    id: Int,
+    make: String,
+    `type`: String,
+    price: Int,
+    pdate: String,
+    customer: String,
+    city: String,
+    state: String,
+    month: Int)
+
 /**
  * A collection of hive query tests where we generate the answers ourselves instead of depending on
  * Hive to generate them (in contrast to HiveQuerySuite).  Often this is because the query is
@@ -41,6 +52,72 @@ case class NestedArray1(a: NestedArray2)
  */
 class SQLQuerySuite extends QueryTest {
 
+  test("SPARK-6851: Self-joined converted parquet tables") {
+    val orders = Seq(
+      Order(1, "Atlas", "MTB", 234, "2015-01-07", "John D", "Pacifica", "CA", 20151),
+      Order(3, "Swift", "MTB", 285, "2015-01-17", "John S", "Redwood City", "CA", 20151),
+      Order(4, "Atlas", "Hybrid", 303, "2015-01-23", "Jones S", "San Mateo", "CA", 20151),
+      Order(7, "Next", "MTB", 356, "2015-01-04", "Jane D", "Daly City", "CA", 20151),
+      Order(10, "Next", "YFlikr", 187, "2015-01-09", "John D", "Fremont", "CA", 20151),
+      Order(11, "Swift", "YFlikr", 187, "2015-01-23", "John D", "Hayward", "CA", 20151),
+      Order(2, "Next", "Hybrid", 324, "2015-02-03", "Jane D", "Daly City", "CA", 20152),
+      Order(5, "Next", "Street", 187, "2015-02-08", "John D", "Fremont", "CA", 20152),
+      Order(6, "Atlas", "Street", 154, "2015-02-09", "John D", "Pacifica", "CA", 20152),
+      Order(8, "Swift", "Hybrid", 485, "2015-02-19", "John S", "Redwood City", "CA", 20152),
+      Order(9, "Atlas", "Split", 303, "2015-02-28", "Jones S", "San Mateo", "CA", 20152))
+
+    val orderUpdates = Seq(
+      Order(1, "Atlas", "MTB", 434, "2015-01-07", "John D", "Pacifica", "CA", 20151),
+      Order(11, "Swift", "YFlikr", 137, "2015-01-23", "John D", "Hayward", "CA", 20151))
+
+    orders.toDF.registerTempTable("orders1")
+    orderUpdates.toDF.registerTempTable("orderupdates1")
+
+    sql(
+      """CREATE TABLE orders(
+        |  id INT,
+        |  make String,
+        |  type String,
+        |  price INT,
+        |  pdate String,
+        |  customer String,
+        |  city String)
+        |PARTITIONED BY (state STRING, month INT)
+        |STORED AS PARQUET
+      """.stripMargin)
+
+    sql(
+      """CREATE TABLE orderupdates(
+        |  id INT,
+        |  make String,
+        |  type String,
+        |  price INT,
+        |  pdate String,
+        |  customer String,
+        |  city String)
+        |PARTITIONED BY (state STRING, month INT)
+        |STORED AS PARQUET
+      """.stripMargin)
+
+    sql("set hive.exec.dynamic.partition.mode=nonstrict")
+    sql("INSERT INTO TABLE orders PARTITION(state, month) SELECT * FROM orders1")
+    sql("INSERT INTO TABLE orderupdates PARTITION(state, month) SELECT * FROM orderupdates1")
+
+    checkAnswer(
+      sql(
+        """
+          |select orders.state, orders.month
+          |from orders
+          |join (
+          |  select distinct orders.state,orders.month
+          |  from orders
+          |  join orderupdates
+          |    on orderupdates.id = orders.id) ao
+          |  on ao.state = orders.state and ao.month = orders.month
+        """.stripMargin),
+      (1 to 6).map(_ => Row("CA", 20151)))
+  }
+
   test("SPARK-5371: union with null and sum") {
     val df = Seq((1, 1)).toDF("c1", "c2")
     df.registerTempTable("table1")
@@ -478,5 +555,4 @@ class SQLQuerySuite extends QueryTest {
     sql("select d from dn union all select d * 2 from dn")
       .queryExecution.analyzed
   }
-
 }

From 67d06880e47e0324409cf7e5b21db1dcb0107b82 Mon Sep 17 00:00:00 2001
From: Volodymyr Lyubinets <vlyubin@gmail.com>
Date: Fri, 10 Apr 2015 16:27:56 -0700
Subject: [PATCH 41/95] [SQL] [SPARK-6620] Speed up toDF() and rdd() functions
 by constructing converters in ScalaReflection

cc marmbrus

Author: Volodymyr Lyubinets <vlyubin@gmail.com>

Closes #5279 from vlyubin/speedup and squashes the following commits:

e75a387 [Volodymyr Lyubinets] Changes to ScalaUDF
11a20ec [Volodymyr Lyubinets] Avoid creating a tuple
c327bc9 [Volodymyr Lyubinets] Moved the only remaining function from DataTypeConversions to DateUtils
dec6802 [Volodymyr Lyubinets] Addresed review feedback
74301fa [Volodymyr Lyubinets] Addressed review comments
afa3aa5 [Volodymyr Lyubinets] Minor refactoring, added license, removed debug output
881dc60 [Volodymyr Lyubinets] Moved to a separate module; addressed review comments; one extra place of usage; changed behaviour for Java
8cad6e2 [Volodymyr Lyubinets] Addressed review commments
41b2aa9 [Volodymyr Lyubinets] Creating converters for ScalaReflection stuff, and more
---
 .../spark/ml/feature/TokenizerSuite.scala     |  17 +-
 .../sql/catalyst/CatalystTypeConverters.scala | 295 +++++++
 .../spark/sql/catalyst/ScalaReflection.scala  |  55 --
 .../sql/catalyst/expressions/ScalaUdf.scala   | 819 ++++++++++++------
 .../plans/logical/LocalRelation.scala         |   7 +-
 .../spark/sql/types/DataTypeConversions.scala |  77 --
 .../apache/spark/sql/types/DateUtils.scala    |  29 +
 .../sql/catalyst/ScalaReflectionSuite.scala   |   4 +-
 .../org/apache/spark/sql/DataFrame.scala      |  11 +-
 .../org/apache/spark/sql/SQLContext.scala     |   9 +-
 .../spark/sql/execution/ExistingRDD.scala     |  14 +-
 .../spark/sql/execution/LocalTableScan.scala  |  16 +-
 .../spark/sql/execution/SparkPlan.scala       |  11 +-
 .../spark/sql/execution/basicOperators.scala  |   9 +-
 .../org/apache/spark/sql/json/JsonRDD.scala   |   4 +-
 .../apache/spark/sql/JavaDataFrameSuite.java  |  10 +-
 .../org/apache/spark/sql/json/JsonSuite.scala |   3 +-
 17 files changed, 929 insertions(+), 461 deletions(-)
 create mode 100644 sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/CatalystTypeConverters.scala
 delete mode 100644 sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeConversions.scala

diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/TokenizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/TokenizerSuite.scala
index bf862b912d326..d186ead8f542f 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/TokenizerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/TokenizerSuite.scala
@@ -25,10 +25,7 @@ import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.{DataFrame, Row, SQLContext}
 
 @BeanInfo
-case class TokenizerTestData(rawText: String, wantedTokens: Seq[String]) {
-  /** Constructor used in [[org.apache.spark.ml.feature.JavaTokenizerSuite]] */
-  def this(rawText: String, wantedTokens: Array[String]) = this(rawText, wantedTokens.toSeq)
-}
+case class TokenizerTestData(rawText: String, wantedTokens: Array[String])
 
 class RegexTokenizerSuite extends FunSuite with MLlibTestSparkContext {
   import org.apache.spark.ml.feature.RegexTokenizerSuite._
@@ -46,14 +43,14 @@ class RegexTokenizerSuite extends FunSuite with MLlibTestSparkContext {
       .setOutputCol("tokens")
 
     val dataset0 = sqlContext.createDataFrame(Seq(
-      TokenizerTestData("Test for tokenization.", Seq("Test", "for", "tokenization", ".")),
-      TokenizerTestData("Te,st. punct", Seq("Te", ",", "st", ".", "punct"))
+      TokenizerTestData("Test for tokenization.", Array("Test", "for", "tokenization", ".")),
+      TokenizerTestData("Te,st. punct", Array("Te", ",", "st", ".", "punct"))
     ))
     testRegexTokenizer(tokenizer, dataset0)
 
     val dataset1 = sqlContext.createDataFrame(Seq(
-      TokenizerTestData("Test for tokenization.", Seq("Test", "for", "tokenization")),
-      TokenizerTestData("Te,st. punct", Seq("punct"))
+      TokenizerTestData("Test for tokenization.", Array("Test", "for", "tokenization")),
+      TokenizerTestData("Te,st. punct", Array("punct"))
     ))
 
     tokenizer.setMinTokenLength(3)
@@ -64,8 +61,8 @@ class RegexTokenizerSuite extends FunSuite with MLlibTestSparkContext {
       .setGaps(true)
       .setMinTokenLength(0)
     val dataset2 = sqlContext.createDataFrame(Seq(
-      TokenizerTestData("Test for tokenization.", Seq("Test", "for", "tokenization.")),
-      TokenizerTestData("Te,st.  punct", Seq("Te,st.", "", "punct"))
+      TokenizerTestData("Test for tokenization.", Array("Test", "for", "tokenization.")),
+      TokenizerTestData("Te,st.  punct", Array("Te,st.", "", "punct"))
     ))
     testRegexTokenizer(tokenizer, dataset2)
   }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/CatalystTypeConverters.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/CatalystTypeConverters.scala
new file mode 100644
index 0000000000000..91976fef6dc0d
--- /dev/null
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/CatalystTypeConverters.scala
@@ -0,0 +1,295 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.catalyst
+
+import java.util.{Map => JavaMap}
+
+import scala.collection.mutable.HashMap
+
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.types._
+
+/**
+ * Functions to convert Scala types to Catalyst types and vice versa.
+ */
+object CatalystTypeConverters {
+  // The Predef.Map is scala.collection.immutable.Map.
+  // Since the map values can be mutable, we explicitly import scala.collection.Map at here.
+  import scala.collection.Map
+
+  /**
+   * Converts Scala objects to catalyst rows / types. This method is slow, and for batch
+   * conversion you should be using converter produced by createToCatalystConverter.
+   * Note: This is always called after schemaFor has been called.
+   *       This ordering is important for UDT registration.
+   */
+  def convertToCatalyst(a: Any, dataType: DataType): Any = (a, dataType) match {
+    // Check UDT first since UDTs can override other types
+    case (obj, udt: UserDefinedType[_]) =>
+      udt.serialize(obj)
+
+    case (o: Option[_], _) =>
+      o.map(convertToCatalyst(_, dataType)).orNull
+
+    case (s: Seq[_], arrayType: ArrayType) =>
+      s.map(convertToCatalyst(_, arrayType.elementType))
+
+    case (s: Array[_], arrayType: ArrayType) =>
+      s.toSeq.map(convertToCatalyst(_, arrayType.elementType))
+
+    case (m: Map[_, _], mapType: MapType) =>
+      m.map { case (k, v) =>
+        convertToCatalyst(k, mapType.keyType) -> convertToCatalyst(v, mapType.valueType)
+      }
+
+    case (jmap: JavaMap[_, _], mapType: MapType) =>
+      val iter = jmap.entrySet.iterator
+      var listOfEntries: List[(Any, Any)] = List()
+      while (iter.hasNext) {
+        val entry = iter.next()
+        listOfEntries :+= (convertToCatalyst(entry.getKey, mapType.keyType),
+          convertToCatalyst(entry.getValue, mapType.valueType))
+      }
+      listOfEntries.toMap
+
+    case (p: Product, structType: StructType) =>
+      val ar = new Array[Any](structType.size)
+      val iter = p.productIterator
+      var idx = 0
+      while (idx < structType.size) {
+        ar(idx) = convertToCatalyst(iter.next(), structType.fields(idx).dataType)
+        idx += 1
+      }
+      new GenericRowWithSchema(ar, structType)
+
+    case (d: BigDecimal, _) =>
+      Decimal(d)
+
+    case (d: java.math.BigDecimal, _) =>
+      Decimal(d)
+
+    case (d: java.sql.Date, _) =>
+      DateUtils.fromJavaDate(d)
+
+    case (r: Row, structType: StructType) =>
+      val converters = structType.fields.map {
+        f => (item: Any) => convertToCatalyst(item, f.dataType)
+      }
+      convertRowWithConverters(r, structType, converters)
+
+    case (other, _) =>
+      other
+  }
+
+  /**
+   * Creates a converter function that will convert Scala objects to the specified catalyst type.
+   * Typical use case would be converting a collection of rows that have the same schema. You will
+   * call this function once to get a converter, and apply it to every row.
+   */
+  private[sql] def createToCatalystConverter(dataType: DataType): Any => Any = {
+    def extractOption(item: Any): Any = item match {
+      case opt: Option[_] => opt.orNull
+      case other => other
+    }
+
+    dataType match {
+      // Check UDT first since UDTs can override other types
+      case udt: UserDefinedType[_] =>
+        (item) => extractOption(item) match {
+          case null => null
+          case other => udt.serialize(other)
+        }
+
+      case arrayType: ArrayType =>
+        val elementConverter = createToCatalystConverter(arrayType.elementType)
+        (item: Any) => {
+          extractOption(item) match {
+            case a: Array[_] => a.toSeq.map(elementConverter)
+            case s: Seq[_] => s.map(elementConverter)
+            case null => null
+          }
+        }
+
+      case mapType: MapType =>
+        val keyConverter = createToCatalystConverter(mapType.keyType)
+        val valueConverter = createToCatalystConverter(mapType.valueType)
+        (item: Any) => {
+          extractOption(item) match {
+            case m: Map[_, _] =>
+              m.map { case (k, v) =>
+                keyConverter(k) -> valueConverter(v)
+              }
+
+            case jmap: JavaMap[_, _] =>
+              val iter = jmap.entrySet.iterator
+              val convertedMap: HashMap[Any, Any] = HashMap()
+              while (iter.hasNext) {
+                val entry = iter.next()
+                convertedMap(keyConverter(entry.getKey)) = valueConverter(entry.getValue)
+              }
+              convertedMap
+
+            case null => null
+          }
+        }
+
+      case structType: StructType =>
+        val converters = structType.fields.map(f => createToCatalystConverter(f.dataType))
+        (item: Any) => {
+          extractOption(item) match {
+            case r: Row =>
+              convertRowWithConverters(r, structType, converters)
+
+            case p: Product =>
+              val ar = new Array[Any](structType.size)
+              val iter = p.productIterator
+              var idx = 0
+              while (idx < structType.size) {
+                ar(idx) = converters(idx)(iter.next())
+                idx += 1
+              }
+              new GenericRowWithSchema(ar, structType)
+
+            case null =>
+              null
+          }
+        }
+
+      case dateType: DateType => (item: Any) => extractOption(item) match {
+        case d: java.sql.Date => DateUtils.fromJavaDate(d)
+        case other => other
+      }
+
+      case _ =>
+        (item: Any) => extractOption(item) match {
+          case d: BigDecimal => Decimal(d)
+          case d: java.math.BigDecimal => Decimal(d)
+          case other => other
+        }
+    }
+  }
+
+  /** 
+   * Converts Catalyst types used internally in rows to standard Scala types
+   * This method is slow, and for batch conversion you should be using converter
+   * produced by createToScalaConverter.
+   */
+  def convertToScala(a: Any, dataType: DataType): Any = (a, dataType) match {
+    // Check UDT first since UDTs can override other types
+    case (d, udt: UserDefinedType[_]) =>
+      udt.deserialize(d)
+
+    case (s: Seq[_], arrayType: ArrayType) =>
+      s.map(convertToScala(_, arrayType.elementType))
+
+    case (m: Map[_, _], mapType: MapType) =>
+      m.map { case (k, v) =>
+        convertToScala(k, mapType.keyType) -> convertToScala(v, mapType.valueType)
+      }
+
+    case (r: Row, s: StructType) =>
+      convertRowToScala(r, s)
+
+    case (d: Decimal, _: DecimalType) =>
+      d.toJavaBigDecimal
+
+    case (i: Int, DateType) =>
+      DateUtils.toJavaDate(i)
+
+    case (other, _) =>
+      other
+  }
+
+  /**
+   * Creates a converter function that will convert Catalyst types to Scala type.
+   * Typical use case would be converting a collection of rows that have the same schema. You will
+   * call this function once to get a converter, and apply it to every row.
+   */
+  private[sql] def createToScalaConverter(dataType: DataType): Any => Any = dataType match {
+    // Check UDT first since UDTs can override other types
+    case udt: UserDefinedType[_] =>
+      (item: Any) => if (item == null) null else udt.deserialize(item)
+
+    case arrayType: ArrayType =>
+      val elementConverter = createToScalaConverter(arrayType.elementType)
+      (item: Any) => if (item == null) null else item.asInstanceOf[Seq[_]].map(elementConverter)
+
+    case mapType: MapType =>
+      val keyConverter = createToScalaConverter(mapType.keyType)
+      val valueConverter = createToScalaConverter(mapType.valueType)
+      (item: Any) => if (item == null) {
+        null
+      } else {
+        item.asInstanceOf[Map[_, _]].map { case (k, v) =>
+          keyConverter(k) -> valueConverter(v)
+        }
+      }
+
+    case s: StructType =>
+      val converters = s.fields.map(f => createToScalaConverter(f.dataType))
+      (item: Any) => {
+        if (item == null) {
+          null
+        } else {
+          convertRowWithConverters(item.asInstanceOf[Row], s, converters)
+        }
+      }
+
+    case _: DecimalType =>
+      (item: Any) => item match {
+        case d: Decimal => d.toJavaBigDecimal
+        case other => other
+      }
+
+    case DateType =>
+      (item: Any) => item match {
+        case i: Int => DateUtils.toJavaDate(i)
+        case other => other
+      }
+
+    case other =>
+      (item: Any) => item
+  }
+
+  def convertRowToScala(r: Row, schema: StructType): Row = {
+    val ar = new Array[Any](r.size)
+    var idx = 0
+    while (idx < r.size) {
+      ar(idx) = convertToScala(r(idx), schema.fields(idx).dataType)
+      idx += 1
+    }
+    new GenericRowWithSchema(ar, schema)
+  }
+
+  /**
+   * Converts a row by applying the provided set of converter functions. It is used for both
+   * toScala and toCatalyst conversions.
+   */
+  private[sql] def convertRowWithConverters(
+      row: Row,
+      schema: StructType,
+      converters: Array[Any => Any]): Row = {
+    val ar = new Array[Any](row.size)
+    var idx = 0
+    while (idx < row.size) {
+      ar(idx) = converters(idx)(row(idx))
+      idx += 1
+    }
+    new GenericRowWithSchema(ar, schema)
+  }
+}
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala
index 8bfd0471d9c7a..01d5c1512201a 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala
@@ -46,61 +46,6 @@ trait ScalaReflection {
 
   case class Schema(dataType: DataType, nullable: Boolean)
 
-  /**
-   * Converts Scala objects to catalyst rows / types.
-   * Note: This is always called after schemaFor has been called.
-   *       This ordering is important for UDT registration.
-   */
-  def convertToCatalyst(a: Any, dataType: DataType): Any = (a, dataType) match {
-    // Check UDT first since UDTs can override other types
-    case (obj, udt: UserDefinedType[_]) => udt.serialize(obj)
-    case (o: Option[_], _) => o.map(convertToCatalyst(_, dataType)).orNull
-    case (s: Seq[_], arrayType: ArrayType) => s.map(convertToCatalyst(_, arrayType.elementType))
-    case (s: Array[_], arrayType: ArrayType) => if (arrayType.elementType.isPrimitive) {
-      s.toSeq
-    } else {
-      s.toSeq.map(convertToCatalyst(_, arrayType.elementType))
-    }
-    case (m: Map[_, _], mapType: MapType) => m.map { case (k, v) =>
-      convertToCatalyst(k, mapType.keyType) -> convertToCatalyst(v, mapType.valueType)
-    }
-    case (p: Product, structType: StructType) =>
-      new GenericRow(
-        p.productIterator.toSeq.zip(structType.fields).map { case (elem, field) =>
-          convertToCatalyst(elem, field.dataType)
-        }.toArray)
-    case (d: BigDecimal, _) => Decimal(d)
-    case (d: java.math.BigDecimal, _) => Decimal(d)
-    case (d: java.sql.Date, _) => DateUtils.fromJavaDate(d)
-    case (r: Row, structType: StructType) =>
-      new GenericRow(
-        r.toSeq.zip(structType.fields).map { case (elem, field) =>
-          convertToCatalyst(elem, field.dataType)
-        }.toArray)
-    case (other, _) => other
-  }
-
-  /** Converts Catalyst types used internally in rows to standard Scala types */
-  def convertToScala(a: Any, dataType: DataType): Any = (a, dataType) match {
-    // Check UDT first since UDTs can override other types
-    case (d, udt: UserDefinedType[_]) => udt.deserialize(d)
-    case (s: Seq[_], arrayType: ArrayType) => s.map(convertToScala(_, arrayType.elementType))
-    case (m: Map[_, _], mapType: MapType) => m.map { case (k, v) =>
-      convertToScala(k, mapType.keyType) -> convertToScala(v, mapType.valueType)
-    }
-    case (r: Row, s: StructType) => convertRowToScala(r, s)
-    case (d: Decimal, _: DecimalType) => d.toJavaBigDecimal
-    case (i: Int, DateType) => DateUtils.toJavaDate(i)
-    case (other, _) => other
-  }
-
-  def convertRowToScala(r: Row, schema: StructType): Row = {
-    // TODO: This is very slow!!!
-    new GenericRowWithSchema(
-      r.toSeq.zip(schema.fields.map(_.dataType))
-        .map(r_dt => convertToScala(r_dt._1, r_dt._2)).toArray, schema)
-  }
-
   /** Returns a Sequence of attributes for the given case class type. */
   def attributesFor[T: TypeTag]: Seq[Attribute] = schemaFor[T] match {
     case Schema(s: StructType, _) =>
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUdf.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUdf.scala
index 389dc4f745723..9a77ca624ebe2 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUdf.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUdf.scala
@@ -17,7 +17,7 @@
 
 package org.apache.spark.sql.catalyst.expressions
 
-import org.apache.spark.sql.catalyst.ScalaReflection
+import org.apache.spark.sql.catalyst.CatalystTypeConverters
 import org.apache.spark.sql.types.DataType
 
 /**
@@ -39,12 +39,14 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
 
     (1 to 22).map { x =>
       val anys = (1 to x).map(x => "Any").reduce(_ + ", " + _)
-      val childs = (0 to x - 1).map(x => s"val child$x = children($x)").reduce(_ + "\n      " + _)
-      val evals = (0 to x - 1).map(x => s"ScalaReflection.convertToScala(child$x.eval(input), child$x.dataType)").reduce(_ + ",\n          " + _)
+      val childs = (0 to x - 1).map(x => s"val child$x = children($x)").reduce(_ + "\n  " + _)
+      lazy val converters = (0 to x - 1).map(x => s"lazy val converter$x = CatalystTypeConverters.createToScalaConverter(child$x.dataType)").reduce(_ + "\n  " + _)
+      val evals = (0 to x - 1).map(x => s"converter$x(child$x.eval(input))").reduce(_ + ",\n      " + _)
 
-      s"""    case $x =>
+      s"""case $x =>
       val func = function.asInstanceOf[($anys) => Any]
       $childs
+      $converters
       (input: Row) => {
         func(
           $evals)
@@ -60,51 +62,61 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       (input: Row) => {
         func()
       }
-      
+
     case 1 =>
       val func = function.asInstanceOf[(Any) => Any]
       val child0 = children(0)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType))
+          converter0(child0.eval(input)))
       }
-      
+
     case 2 =>
       val func = function.asInstanceOf[(Any, Any) => Any]
       val child0 = children(0)
       val child1 = children(1)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)))
       }
-      
+
     case 3 =>
       val func = function.asInstanceOf[(Any, Any, Any) => Any]
       val child0 = children(0)
       val child1 = children(1)
       val child2 = children(2)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)))
       }
-      
+
     case 4 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any) => Any]
       val child0 = children(0)
       val child1 = children(1)
       val child2 = children(2)
       val child3 = children(3)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)))
       }
-      
+
     case 5 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -112,15 +124,20 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child2 = children(2)
       val child3 = children(3)
       val child4 = children(4)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)))
       }
-      
+
     case 6 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -129,16 +146,22 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child3 = children(3)
       val child4 = children(4)
       val child5 = children(5)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)))
       }
-      
+
     case 7 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -148,17 +171,24 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child4 = children(4)
       val child5 = children(5)
       val child6 = children(6)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)))
       }
-      
+
     case 8 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -169,18 +199,26 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child5 = children(5)
       val child6 = children(6)
       val child7 = children(7)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)))
       }
-      
+
     case 9 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -192,19 +230,28 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child6 = children(6)
       val child7 = children(7)
       val child8 = children(8)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
+      lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType),
-          ScalaReflection.convertToScala(child8.eval(input), child8.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)),
+          converter8(child8.eval(input)))
       }
-      
+
     case 10 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -217,20 +264,30 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child7 = children(7)
       val child8 = children(8)
       val child9 = children(9)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
+      lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType)
+      lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType),
-          ScalaReflection.convertToScala(child8.eval(input), child8.dataType),
-          ScalaReflection.convertToScala(child9.eval(input), child9.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)),
+          converter8(child8.eval(input)),
+          converter9(child9.eval(input)))
       }
-      
+
     case 11 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -244,21 +301,32 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child8 = children(8)
       val child9 = children(9)
       val child10 = children(10)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
+      lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType)
+      lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType)
+      lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType),
-          ScalaReflection.convertToScala(child8.eval(input), child8.dataType),
-          ScalaReflection.convertToScala(child9.eval(input), child9.dataType),
-          ScalaReflection.convertToScala(child10.eval(input), child10.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)),
+          converter8(child8.eval(input)),
+          converter9(child9.eval(input)),
+          converter10(child10.eval(input)))
       }
-      
+
     case 12 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -273,22 +341,34 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child9 = children(9)
       val child10 = children(10)
       val child11 = children(11)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
+      lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType)
+      lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType)
+      lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType)
+      lazy val converter11 = CatalystTypeConverters.createToScalaConverter(child11.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType),
-          ScalaReflection.convertToScala(child8.eval(input), child8.dataType),
-          ScalaReflection.convertToScala(child9.eval(input), child9.dataType),
-          ScalaReflection.convertToScala(child10.eval(input), child10.dataType),
-          ScalaReflection.convertToScala(child11.eval(input), child11.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)),
+          converter8(child8.eval(input)),
+          converter9(child9.eval(input)),
+          converter10(child10.eval(input)),
+          converter11(child11.eval(input)))
       }
-      
+
     case 13 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -304,23 +384,36 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child10 = children(10)
       val child11 = children(11)
       val child12 = children(12)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
+      lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType)
+      lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType)
+      lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType)
+      lazy val converter11 = CatalystTypeConverters.createToScalaConverter(child11.dataType)
+      lazy val converter12 = CatalystTypeConverters.createToScalaConverter(child12.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType),
-          ScalaReflection.convertToScala(child8.eval(input), child8.dataType),
-          ScalaReflection.convertToScala(child9.eval(input), child9.dataType),
-          ScalaReflection.convertToScala(child10.eval(input), child10.dataType),
-          ScalaReflection.convertToScala(child11.eval(input), child11.dataType),
-          ScalaReflection.convertToScala(child12.eval(input), child12.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)),
+          converter8(child8.eval(input)),
+          converter9(child9.eval(input)),
+          converter10(child10.eval(input)),
+          converter11(child11.eval(input)),
+          converter12(child12.eval(input)))
       }
-      
+
     case 14 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -337,24 +430,38 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child11 = children(11)
       val child12 = children(12)
       val child13 = children(13)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
+      lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType)
+      lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType)
+      lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType)
+      lazy val converter11 = CatalystTypeConverters.createToScalaConverter(child11.dataType)
+      lazy val converter12 = CatalystTypeConverters.createToScalaConverter(child12.dataType)
+      lazy val converter13 = CatalystTypeConverters.createToScalaConverter(child13.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType),
-          ScalaReflection.convertToScala(child8.eval(input), child8.dataType),
-          ScalaReflection.convertToScala(child9.eval(input), child9.dataType),
-          ScalaReflection.convertToScala(child10.eval(input), child10.dataType),
-          ScalaReflection.convertToScala(child11.eval(input), child11.dataType),
-          ScalaReflection.convertToScala(child12.eval(input), child12.dataType),
-          ScalaReflection.convertToScala(child13.eval(input), child13.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)),
+          converter8(child8.eval(input)),
+          converter9(child9.eval(input)),
+          converter10(child10.eval(input)),
+          converter11(child11.eval(input)),
+          converter12(child12.eval(input)),
+          converter13(child13.eval(input)))
       }
-      
+
     case 15 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -372,25 +479,40 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child12 = children(12)
       val child13 = children(13)
       val child14 = children(14)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
+      lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType)
+      lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType)
+      lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType)
+      lazy val converter11 = CatalystTypeConverters.createToScalaConverter(child11.dataType)
+      lazy val converter12 = CatalystTypeConverters.createToScalaConverter(child12.dataType)
+      lazy val converter13 = CatalystTypeConverters.createToScalaConverter(child13.dataType)
+      lazy val converter14 = CatalystTypeConverters.createToScalaConverter(child14.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType),
-          ScalaReflection.convertToScala(child8.eval(input), child8.dataType),
-          ScalaReflection.convertToScala(child9.eval(input), child9.dataType),
-          ScalaReflection.convertToScala(child10.eval(input), child10.dataType),
-          ScalaReflection.convertToScala(child11.eval(input), child11.dataType),
-          ScalaReflection.convertToScala(child12.eval(input), child12.dataType),
-          ScalaReflection.convertToScala(child13.eval(input), child13.dataType),
-          ScalaReflection.convertToScala(child14.eval(input), child14.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)),
+          converter8(child8.eval(input)),
+          converter9(child9.eval(input)),
+          converter10(child10.eval(input)),
+          converter11(child11.eval(input)),
+          converter12(child12.eval(input)),
+          converter13(child13.eval(input)),
+          converter14(child14.eval(input)))
       }
-      
+
     case 16 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -409,26 +531,42 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child13 = children(13)
       val child14 = children(14)
       val child15 = children(15)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
+      lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType)
+      lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType)
+      lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType)
+      lazy val converter11 = CatalystTypeConverters.createToScalaConverter(child11.dataType)
+      lazy val converter12 = CatalystTypeConverters.createToScalaConverter(child12.dataType)
+      lazy val converter13 = CatalystTypeConverters.createToScalaConverter(child13.dataType)
+      lazy val converter14 = CatalystTypeConverters.createToScalaConverter(child14.dataType)
+      lazy val converter15 = CatalystTypeConverters.createToScalaConverter(child15.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType),
-          ScalaReflection.convertToScala(child8.eval(input), child8.dataType),
-          ScalaReflection.convertToScala(child9.eval(input), child9.dataType),
-          ScalaReflection.convertToScala(child10.eval(input), child10.dataType),
-          ScalaReflection.convertToScala(child11.eval(input), child11.dataType),
-          ScalaReflection.convertToScala(child12.eval(input), child12.dataType),
-          ScalaReflection.convertToScala(child13.eval(input), child13.dataType),
-          ScalaReflection.convertToScala(child14.eval(input), child14.dataType),
-          ScalaReflection.convertToScala(child15.eval(input), child15.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)),
+          converter8(child8.eval(input)),
+          converter9(child9.eval(input)),
+          converter10(child10.eval(input)),
+          converter11(child11.eval(input)),
+          converter12(child12.eval(input)),
+          converter13(child13.eval(input)),
+          converter14(child14.eval(input)),
+          converter15(child15.eval(input)))
       }
-      
+
     case 17 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -448,27 +586,44 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child14 = children(14)
       val child15 = children(15)
       val child16 = children(16)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
+      lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType)
+      lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType)
+      lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType)
+      lazy val converter11 = CatalystTypeConverters.createToScalaConverter(child11.dataType)
+      lazy val converter12 = CatalystTypeConverters.createToScalaConverter(child12.dataType)
+      lazy val converter13 = CatalystTypeConverters.createToScalaConverter(child13.dataType)
+      lazy val converter14 = CatalystTypeConverters.createToScalaConverter(child14.dataType)
+      lazy val converter15 = CatalystTypeConverters.createToScalaConverter(child15.dataType)
+      lazy val converter16 = CatalystTypeConverters.createToScalaConverter(child16.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType),
-          ScalaReflection.convertToScala(child8.eval(input), child8.dataType),
-          ScalaReflection.convertToScala(child9.eval(input), child9.dataType),
-          ScalaReflection.convertToScala(child10.eval(input), child10.dataType),
-          ScalaReflection.convertToScala(child11.eval(input), child11.dataType),
-          ScalaReflection.convertToScala(child12.eval(input), child12.dataType),
-          ScalaReflection.convertToScala(child13.eval(input), child13.dataType),
-          ScalaReflection.convertToScala(child14.eval(input), child14.dataType),
-          ScalaReflection.convertToScala(child15.eval(input), child15.dataType),
-          ScalaReflection.convertToScala(child16.eval(input), child16.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)),
+          converter8(child8.eval(input)),
+          converter9(child9.eval(input)),
+          converter10(child10.eval(input)),
+          converter11(child11.eval(input)),
+          converter12(child12.eval(input)),
+          converter13(child13.eval(input)),
+          converter14(child14.eval(input)),
+          converter15(child15.eval(input)),
+          converter16(child16.eval(input)))
       }
-      
+
     case 18 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -489,28 +644,46 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child15 = children(15)
       val child16 = children(16)
       val child17 = children(17)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
+      lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType)
+      lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType)
+      lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType)
+      lazy val converter11 = CatalystTypeConverters.createToScalaConverter(child11.dataType)
+      lazy val converter12 = CatalystTypeConverters.createToScalaConverter(child12.dataType)
+      lazy val converter13 = CatalystTypeConverters.createToScalaConverter(child13.dataType)
+      lazy val converter14 = CatalystTypeConverters.createToScalaConverter(child14.dataType)
+      lazy val converter15 = CatalystTypeConverters.createToScalaConverter(child15.dataType)
+      lazy val converter16 = CatalystTypeConverters.createToScalaConverter(child16.dataType)
+      lazy val converter17 = CatalystTypeConverters.createToScalaConverter(child17.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType),
-          ScalaReflection.convertToScala(child8.eval(input), child8.dataType),
-          ScalaReflection.convertToScala(child9.eval(input), child9.dataType),
-          ScalaReflection.convertToScala(child10.eval(input), child10.dataType),
-          ScalaReflection.convertToScala(child11.eval(input), child11.dataType),
-          ScalaReflection.convertToScala(child12.eval(input), child12.dataType),
-          ScalaReflection.convertToScala(child13.eval(input), child13.dataType),
-          ScalaReflection.convertToScala(child14.eval(input), child14.dataType),
-          ScalaReflection.convertToScala(child15.eval(input), child15.dataType),
-          ScalaReflection.convertToScala(child16.eval(input), child16.dataType),
-          ScalaReflection.convertToScala(child17.eval(input), child17.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)),
+          converter8(child8.eval(input)),
+          converter9(child9.eval(input)),
+          converter10(child10.eval(input)),
+          converter11(child11.eval(input)),
+          converter12(child12.eval(input)),
+          converter13(child13.eval(input)),
+          converter14(child14.eval(input)),
+          converter15(child15.eval(input)),
+          converter16(child16.eval(input)),
+          converter17(child17.eval(input)))
       }
-      
+
     case 19 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -532,29 +705,48 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child16 = children(16)
       val child17 = children(17)
       val child18 = children(18)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
+      lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType)
+      lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType)
+      lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType)
+      lazy val converter11 = CatalystTypeConverters.createToScalaConverter(child11.dataType)
+      lazy val converter12 = CatalystTypeConverters.createToScalaConverter(child12.dataType)
+      lazy val converter13 = CatalystTypeConverters.createToScalaConverter(child13.dataType)
+      lazy val converter14 = CatalystTypeConverters.createToScalaConverter(child14.dataType)
+      lazy val converter15 = CatalystTypeConverters.createToScalaConverter(child15.dataType)
+      lazy val converter16 = CatalystTypeConverters.createToScalaConverter(child16.dataType)
+      lazy val converter17 = CatalystTypeConverters.createToScalaConverter(child17.dataType)
+      lazy val converter18 = CatalystTypeConverters.createToScalaConverter(child18.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType),
-          ScalaReflection.convertToScala(child8.eval(input), child8.dataType),
-          ScalaReflection.convertToScala(child9.eval(input), child9.dataType),
-          ScalaReflection.convertToScala(child10.eval(input), child10.dataType),
-          ScalaReflection.convertToScala(child11.eval(input), child11.dataType),
-          ScalaReflection.convertToScala(child12.eval(input), child12.dataType),
-          ScalaReflection.convertToScala(child13.eval(input), child13.dataType),
-          ScalaReflection.convertToScala(child14.eval(input), child14.dataType),
-          ScalaReflection.convertToScala(child15.eval(input), child15.dataType),
-          ScalaReflection.convertToScala(child16.eval(input), child16.dataType),
-          ScalaReflection.convertToScala(child17.eval(input), child17.dataType),
-          ScalaReflection.convertToScala(child18.eval(input), child18.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)),
+          converter8(child8.eval(input)),
+          converter9(child9.eval(input)),
+          converter10(child10.eval(input)),
+          converter11(child11.eval(input)),
+          converter12(child12.eval(input)),
+          converter13(child13.eval(input)),
+          converter14(child14.eval(input)),
+          converter15(child15.eval(input)),
+          converter16(child16.eval(input)),
+          converter17(child17.eval(input)),
+          converter18(child18.eval(input)))
       }
-      
+
     case 20 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -577,30 +769,50 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child17 = children(17)
       val child18 = children(18)
       val child19 = children(19)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
+      lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType)
+      lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType)
+      lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType)
+      lazy val converter11 = CatalystTypeConverters.createToScalaConverter(child11.dataType)
+      lazy val converter12 = CatalystTypeConverters.createToScalaConverter(child12.dataType)
+      lazy val converter13 = CatalystTypeConverters.createToScalaConverter(child13.dataType)
+      lazy val converter14 = CatalystTypeConverters.createToScalaConverter(child14.dataType)
+      lazy val converter15 = CatalystTypeConverters.createToScalaConverter(child15.dataType)
+      lazy val converter16 = CatalystTypeConverters.createToScalaConverter(child16.dataType)
+      lazy val converter17 = CatalystTypeConverters.createToScalaConverter(child17.dataType)
+      lazy val converter18 = CatalystTypeConverters.createToScalaConverter(child18.dataType)
+      lazy val converter19 = CatalystTypeConverters.createToScalaConverter(child19.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType),
-          ScalaReflection.convertToScala(child8.eval(input), child8.dataType),
-          ScalaReflection.convertToScala(child9.eval(input), child9.dataType),
-          ScalaReflection.convertToScala(child10.eval(input), child10.dataType),
-          ScalaReflection.convertToScala(child11.eval(input), child11.dataType),
-          ScalaReflection.convertToScala(child12.eval(input), child12.dataType),
-          ScalaReflection.convertToScala(child13.eval(input), child13.dataType),
-          ScalaReflection.convertToScala(child14.eval(input), child14.dataType),
-          ScalaReflection.convertToScala(child15.eval(input), child15.dataType),
-          ScalaReflection.convertToScala(child16.eval(input), child16.dataType),
-          ScalaReflection.convertToScala(child17.eval(input), child17.dataType),
-          ScalaReflection.convertToScala(child18.eval(input), child18.dataType),
-          ScalaReflection.convertToScala(child19.eval(input), child19.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)),
+          converter8(child8.eval(input)),
+          converter9(child9.eval(input)),
+          converter10(child10.eval(input)),
+          converter11(child11.eval(input)),
+          converter12(child12.eval(input)),
+          converter13(child13.eval(input)),
+          converter14(child14.eval(input)),
+          converter15(child15.eval(input)),
+          converter16(child16.eval(input)),
+          converter17(child17.eval(input)),
+          converter18(child18.eval(input)),
+          converter19(child19.eval(input)))
       }
-      
+
     case 21 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -624,31 +836,52 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child18 = children(18)
       val child19 = children(19)
       val child20 = children(20)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
+      lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType)
+      lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType)
+      lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType)
+      lazy val converter11 = CatalystTypeConverters.createToScalaConverter(child11.dataType)
+      lazy val converter12 = CatalystTypeConverters.createToScalaConverter(child12.dataType)
+      lazy val converter13 = CatalystTypeConverters.createToScalaConverter(child13.dataType)
+      lazy val converter14 = CatalystTypeConverters.createToScalaConverter(child14.dataType)
+      lazy val converter15 = CatalystTypeConverters.createToScalaConverter(child15.dataType)
+      lazy val converter16 = CatalystTypeConverters.createToScalaConverter(child16.dataType)
+      lazy val converter17 = CatalystTypeConverters.createToScalaConverter(child17.dataType)
+      lazy val converter18 = CatalystTypeConverters.createToScalaConverter(child18.dataType)
+      lazy val converter19 = CatalystTypeConverters.createToScalaConverter(child19.dataType)
+      lazy val converter20 = CatalystTypeConverters.createToScalaConverter(child20.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType),
-          ScalaReflection.convertToScala(child8.eval(input), child8.dataType),
-          ScalaReflection.convertToScala(child9.eval(input), child9.dataType),
-          ScalaReflection.convertToScala(child10.eval(input), child10.dataType),
-          ScalaReflection.convertToScala(child11.eval(input), child11.dataType),
-          ScalaReflection.convertToScala(child12.eval(input), child12.dataType),
-          ScalaReflection.convertToScala(child13.eval(input), child13.dataType),
-          ScalaReflection.convertToScala(child14.eval(input), child14.dataType),
-          ScalaReflection.convertToScala(child15.eval(input), child15.dataType),
-          ScalaReflection.convertToScala(child16.eval(input), child16.dataType),
-          ScalaReflection.convertToScala(child17.eval(input), child17.dataType),
-          ScalaReflection.convertToScala(child18.eval(input), child18.dataType),
-          ScalaReflection.convertToScala(child19.eval(input), child19.dataType),
-          ScalaReflection.convertToScala(child20.eval(input), child20.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)),
+          converter8(child8.eval(input)),
+          converter9(child9.eval(input)),
+          converter10(child10.eval(input)),
+          converter11(child11.eval(input)),
+          converter12(child12.eval(input)),
+          converter13(child13.eval(input)),
+          converter14(child14.eval(input)),
+          converter15(child15.eval(input)),
+          converter16(child16.eval(input)),
+          converter17(child17.eval(input)),
+          converter18(child18.eval(input)),
+          converter19(child19.eval(input)),
+          converter20(child20.eval(input)))
       }
-      
+
     case 22 =>
       val func = function.asInstanceOf[(Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any) => Any]
       val child0 = children(0)
@@ -673,35 +906,57 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi
       val child19 = children(19)
       val child20 = children(20)
       val child21 = children(21)
+      lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType)
+      lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType)
+      lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType)
+      lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType)
+      lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType)
+      lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType)
+      lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType)
+      lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType)
+      lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType)
+      lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType)
+      lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType)
+      lazy val converter11 = CatalystTypeConverters.createToScalaConverter(child11.dataType)
+      lazy val converter12 = CatalystTypeConverters.createToScalaConverter(child12.dataType)
+      lazy val converter13 = CatalystTypeConverters.createToScalaConverter(child13.dataType)
+      lazy val converter14 = CatalystTypeConverters.createToScalaConverter(child14.dataType)
+      lazy val converter15 = CatalystTypeConverters.createToScalaConverter(child15.dataType)
+      lazy val converter16 = CatalystTypeConverters.createToScalaConverter(child16.dataType)
+      lazy val converter17 = CatalystTypeConverters.createToScalaConverter(child17.dataType)
+      lazy val converter18 = CatalystTypeConverters.createToScalaConverter(child18.dataType)
+      lazy val converter19 = CatalystTypeConverters.createToScalaConverter(child19.dataType)
+      lazy val converter20 = CatalystTypeConverters.createToScalaConverter(child20.dataType)
+      lazy val converter21 = CatalystTypeConverters.createToScalaConverter(child21.dataType)
       (input: Row) => {
         func(
-          ScalaReflection.convertToScala(child0.eval(input), child0.dataType),
-          ScalaReflection.convertToScala(child1.eval(input), child1.dataType),
-          ScalaReflection.convertToScala(child2.eval(input), child2.dataType),
-          ScalaReflection.convertToScala(child3.eval(input), child3.dataType),
-          ScalaReflection.convertToScala(child4.eval(input), child4.dataType),
-          ScalaReflection.convertToScala(child5.eval(input), child5.dataType),
-          ScalaReflection.convertToScala(child6.eval(input), child6.dataType),
-          ScalaReflection.convertToScala(child7.eval(input), child7.dataType),
-          ScalaReflection.convertToScala(child8.eval(input), child8.dataType),
-          ScalaReflection.convertToScala(child9.eval(input), child9.dataType),
-          ScalaReflection.convertToScala(child10.eval(input), child10.dataType),
-          ScalaReflection.convertToScala(child11.eval(input), child11.dataType),
-          ScalaReflection.convertToScala(child12.eval(input), child12.dataType),
-          ScalaReflection.convertToScala(child13.eval(input), child13.dataType),
-          ScalaReflection.convertToScala(child14.eval(input), child14.dataType),
-          ScalaReflection.convertToScala(child15.eval(input), child15.dataType),
-          ScalaReflection.convertToScala(child16.eval(input), child16.dataType),
-          ScalaReflection.convertToScala(child17.eval(input), child17.dataType),
-          ScalaReflection.convertToScala(child18.eval(input), child18.dataType),
-          ScalaReflection.convertToScala(child19.eval(input), child19.dataType),
-          ScalaReflection.convertToScala(child20.eval(input), child20.dataType),
-          ScalaReflection.convertToScala(child21.eval(input), child21.dataType))
+          converter0(child0.eval(input)),
+          converter1(child1.eval(input)),
+          converter2(child2.eval(input)),
+          converter3(child3.eval(input)),
+          converter4(child4.eval(input)),
+          converter5(child5.eval(input)),
+          converter6(child6.eval(input)),
+          converter7(child7.eval(input)),
+          converter8(child8.eval(input)),
+          converter9(child9.eval(input)),
+          converter10(child10.eval(input)),
+          converter11(child11.eval(input)),
+          converter12(child12.eval(input)),
+          converter13(child13.eval(input)),
+          converter14(child14.eval(input)),
+          converter15(child15.eval(input)),
+          converter16(child16.eval(input)),
+          converter17(child17.eval(input)),
+          converter18(child18.eval(input)),
+          converter19(child19.eval(input)),
+          converter20(child20.eval(input)),
+          converter21(child21.eval(input)))
       }
   }
-  
+
   // scalastyle:on
-  
-  override def eval(input: Row): Any = ScalaReflection.convertToCatalyst(f(input), dataType)
+
+  override def eval(input: Row): Any = CatalystTypeConverters.convertToCatalyst(f(input), dataType)
 
 }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LocalRelation.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LocalRelation.scala
index bb79dc340553b..e3e070f0ff307 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LocalRelation.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LocalRelation.scala
@@ -18,9 +18,9 @@
 package org.apache.spark.sql.catalyst.plans.logical
 
 import org.apache.spark.sql.Row
-import org.apache.spark.sql.catalyst.analysis
+import org.apache.spark.sql.catalyst.{CatalystTypeConverters, analysis}
 import org.apache.spark.sql.catalyst.expressions.Attribute
-import org.apache.spark.sql.types.{DataTypeConversions, StructType, StructField}
+import org.apache.spark.sql.types.{StructType, StructField}
 
 object LocalRelation {
   def apply(output: Attribute*): LocalRelation = new LocalRelation(output)
@@ -31,7 +31,8 @@ object LocalRelation {
 
   def fromProduct(output: Seq[Attribute], data: Seq[Product]): LocalRelation = {
     val schema = StructType.fromAttributes(output)
-    LocalRelation(output, data.map(row => DataTypeConversions.productToRow(row, schema)))
+    val converter = CatalystTypeConverters.createToCatalystConverter(schema)
+    LocalRelation(output, data.map(converter(_).asInstanceOf[Row]))
   }
 }
 
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeConversions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeConversions.scala
deleted file mode 100644
index a9d63e784963d..0000000000000
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeConversions.scala
+++ /dev/null
@@ -1,77 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License.  You may obtain a copy of the License at
- *
- *    http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package org.apache.spark.sql.types
-
-import java.text.SimpleDateFormat
-
-import org.apache.spark.sql.Row
-import org.apache.spark.sql.catalyst.ScalaReflection
-import org.apache.spark.sql.catalyst.expressions.GenericMutableRow
-
-
-private[sql] object DataTypeConversions {
-
-  def productToRow(product: Product, schema: StructType): Row = {
-    val mutableRow = new GenericMutableRow(product.productArity)
-    val schemaFields = schema.fields.toArray
-
-    var i = 0
-    while (i < mutableRow.length) {
-      mutableRow(i) =
-        ScalaReflection.convertToCatalyst(product.productElement(i), schemaFields(i).dataType)
-      i += 1
-    }
-
-    mutableRow
-  }
-
-  def stringToTime(s: String): java.util.Date = {
-    if (!s.contains('T')) {
-      // JDBC escape string
-      if (s.contains(' ')) {
-        java.sql.Timestamp.valueOf(s)
-      } else {
-        java.sql.Date.valueOf(s)
-      }
-    } else if (s.endsWith("Z")) {
-      // this is zero timezone of ISO8601
-      stringToTime(s.substring(0, s.length - 1) + "GMT-00:00")
-    } else if (s.indexOf("GMT") == -1) {
-      // timezone with ISO8601
-      val inset = "+00.00".length
-      val s0 = s.substring(0, s.length - inset)
-      val s1 = s.substring(s.length - inset, s.length)
-      if (s0.substring(s0.lastIndexOf(':')).contains('.')) {
-        stringToTime(s0 + "GMT" + s1)
-      } else {
-        stringToTime(s0 + ".0GMT" + s1)
-      }
-    } else {
-      // ISO8601 with GMT insert
-      val ISO8601GMT: SimpleDateFormat = new SimpleDateFormat( "yyyy-MM-dd'T'HH:mm:ss.SSSz" )
-      ISO8601GMT.parse(s)
-    }
-  }
-
-  /** Converts Java objects to catalyst rows / types */
-  def convertJavaToCatalyst(a: Any, dataType: DataType): Any = (a, dataType) match {
-    case (obj, udt: UserDefinedType[_]) => ScalaReflection.convertToCatalyst(obj, udt) // Scala type
-    case (d: java.math.BigDecimal, _) => Decimal(d)
-    case (other, _) => other
-  }
-}
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DateUtils.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DateUtils.scala
index 8a1a3b81b3d2c..504fb05842505 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DateUtils.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DateUtils.scala
@@ -18,6 +18,7 @@
 package org.apache.spark.sql.types
 
 import java.sql.Date
+import java.text.SimpleDateFormat
 import java.util.{Calendar, TimeZone}
 
 import org.apache.spark.sql.catalyst.expressions.Cast
@@ -57,4 +58,32 @@ object DateUtils {
   }
 
   def toString(days: Int): String = Cast.threadLocalDateFormat.get.format(toJavaDate(days))
+
+  def stringToTime(s: String): java.util.Date = {
+    if (!s.contains('T')) {
+      // JDBC escape string
+      if (s.contains(' ')) {
+        java.sql.Timestamp.valueOf(s)
+      } else {
+        java.sql.Date.valueOf(s)
+      }
+    } else if (s.endsWith("Z")) {
+      // this is zero timezone of ISO8601
+      stringToTime(s.substring(0, s.length - 1) + "GMT-00:00")
+    } else if (s.indexOf("GMT") == -1) {
+      // timezone with ISO8601
+      val inset = "+00.00".length
+      val s0 = s.substring(0, s.length - inset)
+      val s1 = s.substring(s.length - inset, s.length)
+      if (s0.substring(s0.lastIndexOf(':')).contains('.')) {
+        stringToTime(s0 + "GMT" + s1)
+      } else {
+        stringToTime(s0 + ".0GMT" + s1)
+      }
+    } else {
+      // ISO8601 with GMT insert
+      val ISO8601GMT: SimpleDateFormat = new SimpleDateFormat( "yyyy-MM-dd'T'HH:mm:ss.SSSz" )
+      ISO8601GMT.parse(s)
+    }
+  }
 }
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/ScalaReflectionSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/ScalaReflectionSuite.scala
index eee00e3f7ea76..bbc0b661a0c0c 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/ScalaReflectionSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/ScalaReflectionSuite.scala
@@ -260,7 +260,7 @@ class ScalaReflectionSuite extends FunSuite {
     val data = PrimitiveData(1, 1, 1, 1, 1, 1, true)
     val convertedData = Row(1, 1.toLong, 1.toDouble, 1.toFloat, 1.toShort, 1.toByte, true)
     val dataType = schemaFor[PrimitiveData].dataType
-    assert(convertToCatalyst(data, dataType) === convertedData)
+    assert(CatalystTypeConverters.convertToCatalyst(data, dataType) === convertedData)
   }
 
   test("convert Option[Product] to catalyst") {
@@ -270,7 +270,7 @@ class ScalaReflectionSuite extends FunSuite {
     val dataType = schemaFor[OptionalData].dataType
     val convertedData = Row(2, 2.toLong, 2.toDouble, 2.toFloat, 2.toShort, 2.toByte, true,
       Row(1, 1, 1, 1, 1, 1, true))
-    assert(convertToCatalyst(data, dataType) === convertedData)
+    assert(CatalystTypeConverters.convertToCatalyst(data, dataType) === convertedData)
   }
 
   test("infer schema from case class with multiple constructors") {
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
index 5c6016a4a2ce2..9b9adf855077a 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
@@ -33,7 +33,7 @@ import org.apache.spark.api.java.JavaRDD
 import org.apache.spark.api.python.SerDeUtil
 import org.apache.spark.rdd.RDD
 import org.apache.spark.storage.StorageLevel
-import org.apache.spark.sql.catalyst.{ScalaReflection, SqlParser}
+import org.apache.spark.sql.catalyst.{CatalystTypeConverters, ScalaReflection, SqlParser}
 import org.apache.spark.sql.catalyst.analysis.{UnresolvedRelation, ResolvedStar}
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.plans.{JoinType, Inner}
@@ -713,7 +713,7 @@ class DataFrame private[sql](
     val schema = ScalaReflection.schemaFor[A].dataType.asInstanceOf[StructType]
     val attributes = schema.toAttributes
     val rowFunction =
-      f.andThen(_.map(ScalaReflection.convertToCatalyst(_, schema).asInstanceOf[Row]))
+      f.andThen(_.map(CatalystTypeConverters.convertToCatalyst(_, schema).asInstanceOf[Row]))
     val generator = UserDefinedGenerator(attributes, rowFunction, input.map(_.expr))
 
     Generate(generator, join = true, outer = false, None, logicalPlan)
@@ -734,7 +734,7 @@ class DataFrame private[sql](
     val dataType = ScalaReflection.schemaFor[B].dataType
     val attributes = AttributeReference(outputColumn, dataType)() :: Nil
     def rowFunction(row: Row): TraversableOnce[Row] = {
-      f(row(0).asInstanceOf[A]).map(o => Row(ScalaReflection.convertToCatalyst(o, dataType)))
+      f(row(0).asInstanceOf[A]).map(o => Row(CatalystTypeConverters.convertToCatalyst(o, dataType)))
     }
     val generator = UserDefinedGenerator(attributes, rowFunction, apply(inputColumn).expr :: Nil)
 
@@ -961,7 +961,10 @@ class DataFrame private[sql](
   lazy val rdd: RDD[Row] = {
     // use a local variable to make sure the map closure doesn't capture the whole DataFrame
     val schema = this.schema
-    queryExecution.executedPlan.execute().map(ScalaReflection.convertRowToScala(_, schema))
+    queryExecution.executedPlan.execute().mapPartitions { rows =>
+      val converter = CatalystTypeConverters.createToScalaConverter(schema)
+      rows.map(converter(_).asInstanceOf[Row])
+    }
   }
 
   /**
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
index 39dd14e796f06..c25ef58e6f62a 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
@@ -31,9 +31,9 @@ import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.catalyst.analysis._
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.optimizer.{DefaultOptimizer, Optimizer}
-import org.apache.spark.sql.catalyst.plans.logical.{LocalRelation, LogicalPlan, OneRowRelation}
+import org.apache.spark.sql.catalyst.plans.logical.{LocalRelation, LogicalPlan}
 import org.apache.spark.sql.catalyst.rules.RuleExecutor
-import org.apache.spark.sql.catalyst.{ScalaReflection, expressions}
+import org.apache.spark.sql.catalyst.{CatalystTypeConverters, ScalaReflection, expressions}
 import org.apache.spark.sql.execution.{Filter, _}
 import org.apache.spark.sql.jdbc.{JDBCPartition, JDBCPartitioningInfo, JDBCRelation}
 import org.apache.spark.sql.json._
@@ -404,7 +404,8 @@ class SQLContext(@transient val sparkContext: SparkContext)
     // TODO: use MutableProjection when rowRDD is another DataFrame and the applied
     // schema differs from the existing schema on any field data type.
     val catalystRows = if (needsConversion) {
-      rowRDD.map(ScalaReflection.convertToCatalyst(_, schema).asInstanceOf[Row])
+      val converter = CatalystTypeConverters.createToCatalystConverter(schema)
+      rowRDD.map(converter(_).asInstanceOf[Row])
     } else {
       rowRDD
     }
@@ -459,7 +460,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
       iter.map { row =>
         new GenericRow(
           extractors.zip(attributeSeq).map { case (e, attr) =>
-            DataTypeConversions.convertJavaToCatalyst(e.invoke(row), attr.dataType)
+            CatalystTypeConverters.convertToCatalyst(e.invoke(row), attr.dataType)
           }.toArray[Any]
         ) : Row
       }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala
index d8955725e59b1..656bdd7212f56 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala
@@ -20,14 +20,12 @@ package org.apache.spark.sql.execution
 import org.apache.spark.annotation.DeveloperApi
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.{Row, SQLContext}
-import org.apache.spark.sql.catalyst.ScalaReflection
+import org.apache.spark.sql.catalyst.CatalystTypeConverters
 import org.apache.spark.sql.catalyst.analysis.MultiInstanceRelation
-import org.apache.spark.sql.catalyst.expressions.{Attribute, GenericMutableRow}
+import org.apache.spark.sql.catalyst.expressions.{SpecificMutableRow, Attribute}
 import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Statistics}
 import org.apache.spark.sql.types.StructType
 
-import scala.collection.immutable
-
 /**
  * :: DeveloperApi ::
  */
@@ -39,13 +37,15 @@ object RDDConversions {
         Iterator.empty
       } else {
         val bufferedIterator = iterator.buffered
-        val mutableRow = new GenericMutableRow(bufferedIterator.head.productArity)
+        val mutableRow = new SpecificMutableRow(schema.fields.map(_.dataType))
         val schemaFields = schema.fields.toArray
+        val converters = schemaFields.map {
+          f => CatalystTypeConverters.createToCatalystConverter(f.dataType)
+        }
         bufferedIterator.map { r =>
           var i = 0
           while (i < mutableRow.length) {
-            mutableRow(i) =
-              ScalaReflection.convertToCatalyst(r.productElement(i), schemaFields(i).dataType)
+            mutableRow(i) = converters(i)(r.productElement(i))
             i += 1
           }
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/LocalTableScan.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/LocalTableScan.scala
index 5bd699a2fa949..8a8c3a404323a 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/LocalTableScan.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/LocalTableScan.scala
@@ -19,7 +19,7 @@ package org.apache.spark.sql.execution
 
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.Row
-import org.apache.spark.sql.catalyst.ScalaReflection
+import org.apache.spark.sql.catalyst.CatalystTypeConverters
 import org.apache.spark.sql.catalyst.expressions.Attribute
 
 
@@ -32,9 +32,15 @@ case class LocalTableScan(output: Seq[Attribute], rows: Seq[Row]) extends LeafNo
 
   override def execute(): RDD[Row] = rdd
 
-  override def executeCollect(): Array[Row] =
-    rows.map(ScalaReflection.convertRowToScala(_, schema)).toArray
 
-  override def executeTake(limit: Int): Array[Row] =
-    rows.map(ScalaReflection.convertRowToScala(_, schema)).take(limit).toArray
+  override def executeCollect(): Array[Row] = {
+    val converter = CatalystTypeConverters.createToScalaConverter(schema)
+    rows.map(converter(_).asInstanceOf[Row]).toArray
+  }
+
+
+  override def executeTake(limit: Int): Array[Row] = {
+    val converter = CatalystTypeConverters.createToScalaConverter(schema)
+    rows.map(converter(_).asInstanceOf[Row]).take(limit).toArray
+  }
 }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala
index d239637cd4b4e..fabcf6b4a0570 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala
@@ -21,7 +21,7 @@ import org.apache.spark.annotation.DeveloperApi
 import org.apache.spark.Logging
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.SQLContext
-import org.apache.spark.sql.catalyst.{ScalaReflection, trees}
+import org.apache.spark.sql.catalyst.{CatalystTypeConverters, trees}
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.expressions.codegen._
 import org.apache.spark.sql.catalyst.plans.QueryPlan
@@ -80,8 +80,12 @@ abstract class SparkPlan extends QueryPlan[SparkPlan] with Logging with Serializ
   /**
    * Runs this query returning the result as an array.
    */
+
   def executeCollect(): Array[Row] = {
-    execute().map(ScalaReflection.convertRowToScala(_, schema)).collect()
+    execute().mapPartitions { iter =>
+      val converter = CatalystTypeConverters.createToScalaConverter(schema)
+      iter.map(converter(_).asInstanceOf[Row])
+    }.collect()
   }
 
   /**
@@ -125,7 +129,8 @@ abstract class SparkPlan extends QueryPlan[SparkPlan] with Logging with Serializ
       partsScanned += numPartsToTry
     }
 
-    buf.toArray.map(ScalaReflection.convertRowToScala(_, this.schema))
+    val converter = CatalystTypeConverters.createToScalaConverter(schema)
+    buf.toArray.map(converter(_).asInstanceOf[Row])
   }
 
   protected def newProjection(
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala
index 1f5251a20376f..6eec520abff53 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala
@@ -21,7 +21,7 @@ import org.apache.spark.{SparkEnv, HashPartitioner, SparkConf}
 import org.apache.spark.annotation.DeveloperApi
 import org.apache.spark.rdd.{RDD, ShuffledRDD}
 import org.apache.spark.shuffle.sort.SortShuffleManager
-import org.apache.spark.sql.catalyst.ScalaReflection
+import org.apache.spark.sql.catalyst.CatalystTypeConverters
 import org.apache.spark.sql.catalyst.errors._
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.plans.physical._
@@ -139,9 +139,10 @@ case class TakeOrdered(limit: Int, sortOrder: Seq[SortOrder], child: SparkPlan)
 
   private def collectData(): Array[Row] = child.execute().map(_.copy()).takeOrdered(limit)(ord)
 
-  // TODO: Is this copying for no reason?
-  override def executeCollect(): Array[Row] =
-    collectData().map(ScalaReflection.convertRowToScala(_, this.schema))
+  override def executeCollect(): Array[Row] = {
+    val converter = CatalystTypeConverters.createToScalaConverter(schema)
+    collectData().map(converter(_).asInstanceOf[Row])
+  }
 
   // TODO: Terminal split should be implemented differently from non-terminal split.
   // TODO: Pick num splits based on |limit|.
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala
index 0b770f2251943..b1e8521383756 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala
@@ -391,7 +391,7 @@ private[sql] object JsonRDD extends Logging {
     value match {
       // only support string as date
       case value: java.lang.String =>
-        DateUtils.millisToDays(DataTypeConversions.stringToTime(value).getTime)
+        DateUtils.millisToDays(DateUtils.stringToTime(value).getTime)
       case value: java.sql.Date => DateUtils.fromJavaDate(value)
     }
   }
@@ -400,7 +400,7 @@ private[sql] object JsonRDD extends Logging {
     value match {
       case value: java.lang.Integer => new Timestamp(value.asInstanceOf[Int].toLong)
       case value: java.lang.Long => new Timestamp(value)
-      case value: java.lang.String => toTimestamp(DataTypeConversions.stringToTime(value).getTime)
+      case value: java.lang.String => toTimestamp(DateUtils.stringToTime(value).getTime)
     }
   }
 
diff --git a/sql/core/src/test/java/test/org/apache/spark/sql/JavaDataFrameSuite.java b/sql/core/src/test/java/test/org/apache/spark/sql/JavaDataFrameSuite.java
index 1ff2d5a190521..6d0fbe83c2f36 100644
--- a/sql/core/src/test/java/test/org/apache/spark/sql/JavaDataFrameSuite.java
+++ b/sql/core/src/test/java/test/org/apache/spark/sql/JavaDataFrameSuite.java
@@ -20,6 +20,8 @@
 import java.io.Serializable;
 import java.util.Arrays;
 
+import scala.collection.Seq;
+
 import org.junit.After;
 import org.junit.Assert;
 import org.junit.Before;
@@ -127,6 +129,12 @@ public void testCreateDataFrameFromJavaBeans() {
       schema.apply("b"));
     Row first = df.select("a", "b").first();
     Assert.assertEquals(bean.getA(), first.getDouble(0), 0.0);
-    Assert.assertArrayEquals(bean.getB(), first.<Integer[]>getAs(1));
+    // Now Java lists and maps are converetd to Scala Seq's and Map's. Once we get a Seq below,
+    // verify that it has the expected length, and contains expected elements.
+    Seq<Integer> result = first.getAs(1);
+    Assert.assertEquals(bean.getB().length, result.length());
+    for (int i = 0; i < result.length(); i++) {
+      Assert.assertEquals(bean.getB()[i], result.apply(i));
+    }
   }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala
index 1fe0b76c00be3..fd0e2746dc045 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala
@@ -895,8 +895,7 @@ class JsonSuite extends QueryTest {
     )
   }
 
-  test("SPARK-4228 DataFrame to JSON")
-  {
+  test("SPARK-4228 DataFrame to JSON") {
     val schema1 = StructType(
       StructField("f1", IntegerType, false) ::
       StructField("f2", StringType, false) ::

From 95a07591b3e23782a7021ef2bbf07a67a1e4a83a Mon Sep 17 00:00:00 2001
From: Liang-Chi Hsieh <viirya@gmail.com>
Date: Sat, 11 Apr 2015 13:07:41 +0100
Subject: [PATCH 42/95] [Minor][Core] Fix typo

Author: Liang-Chi Hsieh <viirya@gmail.com>

Closes #5466 from viirya/fix_ShuffleMapTask_typo and squashes the following commits:

2789fd5 [Liang-Chi Hsieh] fix typo.
---
 .../main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala  | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala b/core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala
index fd0d484b45460..6c7d00069acb2 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala
@@ -33,7 +33,7 @@ import org.apache.spark.shuffle.ShuffleWriter
 * See [[org.apache.spark.scheduler.Task]] for more information.
 *
  * @param stageId id of the stage this task belongs to
- * @param taskBinary broadcast version of of the RDD and the ShuffleDependency. Once deserialized,
+ * @param taskBinary broadcast version of the RDD and the ShuffleDependency. Once deserialized,
  *                   the type should be (RDD[_], ShuffleDependency[_, _, _]).
  * @param partition partition of the RDD this task is associated with
  * @param locs preferred task execution locations for locality scheduling

From 694aef0d71d2683eaf63cbd1d8e95c2da423b72e Mon Sep 17 00:00:00 2001
From: Marcelo Vanzin <vanzin@cloudera.com>
Date: Sat, 11 Apr 2015 13:10:01 +0100
Subject: [PATCH 43/95] [hotfix] [build] Make sure JAVA_HOME is set for tests.

This is needed at least for YARN integration tests, since `$JAVA_HOME` is used to launch the executors.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #5441 from vanzin/yarn-test-test and squashes the following commits:

3eeec30 [Marcelo Vanzin] Use JAVA_HOME when available, java.home otherwise.
d71f1bb [Marcelo Vanzin] And sbt too.
6bda399 [Marcelo Vanzin] WIP: Testing to see whether this fixes the yarn test issue.
---
 pom.xml                  | 14 ++++++++++++++
 project/SparkBuild.scala | 10 +++++++---
 2 files changed, 21 insertions(+), 3 deletions(-)

diff --git a/pom.xml b/pom.xml
index 70e297c4f082a..d8881c213bf07 100644
--- a/pom.xml
+++ b/pom.xml
@@ -159,6 +159,8 @@
     <snappy.version>1.1.1.6</snappy.version>
     <netlib.java.version>1.1.2</netlib.java.version>
 
+    <test.java.home>${java.home}</test.java.home>
+
     <!--
       Dependency scopes that can be overridden by enabling certain profiles. These profiles are
       declared in the projects that build assemblies.
@@ -1194,6 +1196,7 @@
                 launched by the tests have access to the correct test-time classpath.
               -->
               <SPARK_DIST_CLASSPATH>${test_classpath}</SPARK_DIST_CLASSPATH>
+              <JAVA_HOME>${test.java.home}</JAVA_HOME>
             </environmentVariables>
             <systemProperties>
               <java.awt.headless>true</java.awt.headless>
@@ -1224,6 +1227,7 @@
                 launched by the tests have access to the correct test-time classpath.
               -->
               <SPARK_DIST_CLASSPATH>${test_classpath}</SPARK_DIST_CLASSPATH>
+              <JAVA_HOME>${test.java.home}</JAVA_HOME>
             </environmentVariables>
             <systemProperties>
               <java.awt.headless>true</java.awt.headless>
@@ -1716,6 +1720,16 @@
       </modules>
     </profile>
 
+    <profile>
+      <id>test-java-home</id>
+      <activation>
+        <property><name>env.JAVA_HOME</name></property>
+      </activation>
+      <properties>
+        <test.java.home>${env.JAVA_HOME}</test.java.home>
+      </properties>
+    </profile>
+
     <profile>
       <id>scala-2.11</id>
       <activation>
diff --git a/project/SparkBuild.scala b/project/SparkBuild.scala
index d3faa551a4b14..5f51f4b58f97a 100644
--- a/project/SparkBuild.scala
+++ b/project/SparkBuild.scala
@@ -119,7 +119,9 @@ object SparkBuild extends PomBuild {
   lazy val publishLocalBoth = TaskKey[Unit]("publish-local", "publish local for m2 and ivy")
 
   lazy val sharedSettings = graphSettings ++ genjavadocSettings ++ Seq (
-    javaHome   := Properties.envOrNone("JAVA_HOME").map(file),
+    javaHome := sys.env.get("JAVA_HOME")
+      .orElse(sys.props.get("java.home").map { p => new File(p).getParentFile().getAbsolutePath() })
+      .map(file),
     incOptions := incOptions.value.withNameHashing(true),
     retrieveManaged := true,
     retrievePattern := "[type]s/[artifact](-[revision])(-[classifier]).[ext]",
@@ -426,8 +428,10 @@ object TestSettings {
     fork := true,
     // Setting SPARK_DIST_CLASSPATH is a simple way to make sure any child processes
     // launched by the tests have access to the correct test-time classpath.
-    envVars in Test += ("SPARK_DIST_CLASSPATH" ->
-      (fullClasspath in Test).value.files.map(_.getAbsolutePath).mkString(":").stripSuffix(":")),
+    envVars in Test ++= Map(
+      "SPARK_DIST_CLASSPATH" -> 
+        (fullClasspath in Test).value.files.map(_.getAbsolutePath).mkString(":").stripSuffix(":"),
+      "JAVA_HOME" -> sys.env.get("JAVA_HOME").getOrElse(sys.props("java.home"))),
     javaOptions in Test += "-Dspark.test.home=" + sparkHome,
     javaOptions in Test += "-Dspark.testing=1",
     javaOptions in Test += "-Dspark.port.maxRetries=100",

From 3ceb810aa8e69bc4abb69cbe713a624cb351cb35 Mon Sep 17 00:00:00 2001
From: Cheng Hao <hao.cheng@intel.com>
Date: Sat, 11 Apr 2015 22:11:03 +0800
Subject: [PATCH 44/95] [SPARK-6835] [SQL] Fix bug of Hive UDTF in Lateral View
 (ClassNotFound)

```SQL
select key, v from src lateral view stack(3, 1+1, 2+2, 3) d as v;
```
Will cause exception
```
java.lang.ClassNotFoundException: stack
at java.net.URLClassLoader$1.run(URLClassLoader.java:366)
at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
at java.lang.ClassLoader.loadClass(ClassLoader.java:425)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:308)
at java.lang.ClassLoader.loadClass(ClassLoader.java:358)
at org.apache.spark.sql.hive.HiveFunctionWrapper.createFunction(Shim13.scala:148)
at org.apache.spark.sql.hive.HiveGenericUdtf.function$lzycompute(hiveUdfs.scala:274)
at org.apache.spark.sql.hive.HiveGenericUdtf.function(hiveUdfs.scala:274)
at org.apache.spark.sql.hive.HiveGenericUdtf.outputInspector$lzycompute(hiveUdfs.scala:280)
at org.apache.spark.sql.hive.HiveGenericUdtf.outputInspector(hiveUdfs.scala:280)
at org.apache.spark.sql.hive.HiveGenericUdtf.outputDataTypes$lzycompute(hiveUdfs.scala:285)
at org.apache.spark.sql.hive.HiveGenericUdtf.outputDataTypes(hiveUdfs.scala:285)
at org.apache.spark.sql.hive.HiveGenericUdtf.makeOutput(hiveUdfs.scala:291)
at org.apache.spark.sql.catalyst.expressions.Generator.output(generators.scala:60)
at org.apache.spark.sql.catalyst.plans.logical.Generate$$anonfun$2.apply(basicOperators.scala:60)
at org.apache.spark.sql.catalyst.plans.logical.Generate$$anonfun$2.apply(basicOperators.scala:60)
at scala.Option.map(Option.scala:145)
at org.apache.spark.sql.catalyst.plans.logical.Generate.generatorOutput(basicOperators.scala:60)
at org.apache.spark.sql.catalyst.plans.logical.Generate.output(basicOperators.scala:70)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveChildren$1.apply(LogicalPlan.scala:117)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveChildren$1.apply(LogicalPlan.scala:117)
```

Author: Cheng Hao <hao.cheng@intel.com>

Closes #5444 from chenghao-intel/hive_udtf and squashes the following commits:

065a98c [Cheng Hao] fix bug of Hive UDTF in Lateral View (ClassNotFound)
---
 .../main/scala/org/apache/spark/sql/hive/HiveQl.scala    | 9 ++++++++-
 .../apache/spark/sql/hive/execution/SQLQuerySuite.scala  | 6 ++++++
 2 files changed, 14 insertions(+), 1 deletion(-)

diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
index 077e64133faad..0bdaf5f7ef8ef 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
@@ -20,6 +20,8 @@ package org.apache.spark.sql.hive
 import java.sql.Date
 
 
+import org.apache.hadoop.hive.ql.exec.{FunctionRegistry, FunctionInfo}
+
 import scala.collection.mutable.ArrayBuffer
 
 import org.apache.hadoop.hive.conf.HiveConf
@@ -1284,8 +1286,13 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
         Explode(attributes, nodeToExpr(child))
 
       case Token("TOK_FUNCTION", Token(functionName, Nil) :: children) =>
+        val functionInfo: FunctionInfo =
+          Option(FunctionRegistry.getFunctionInfo(functionName.toLowerCase)).getOrElse(
+            sys.error(s"Couldn't find function $functionName"))
+        val functionClassName = functionInfo.getFunctionClass.getName
+
         HiveGenericUdtf(
-          new HiveFunctionWrapper(functionName),
+          new HiveFunctionWrapper(functionClassName),
           attributes,
           children.map(nodeToExpr))
 
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
index 4c369c0634bda..47b4cb9ca61ff 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
@@ -51,6 +51,12 @@ case class Order(
  * valid, but Hive currently cannot execute it.
  */
 class SQLQuerySuite extends QueryTest {
+  test("SPARK-6835: udtf in lateral view") {
+    val df = Seq((1, 1)).toDF("c1", "c2")
+    df.registerTempTable("table1")
+    val query = sql("SELECT c1, v FROM table1 LATERAL VIEW stack(3, 1, c1 + 1, c1 + 2) d AS v")
+    checkAnswer(query, Row(1, 1) :: Row(1, 2) :: Row(1, 3) :: Nil)
+  }
 
   test("SPARK-6851: Self-joined converted parquet tables") {
     val orders = Seq(

From 198cf2a3fa9babb5e8b7b44da0471b63b9f3ec04 Mon Sep 17 00:00:00 2001
From: Liang-Chi Hsieh <viirya@gmail.com>
Date: Sat, 11 Apr 2015 14:50:50 -0700
Subject: [PATCH 45/95] [SPARK-6858][SQL] Register Java HashMap for
 SparkSqlSerializer

Since now kyro serializer is used for `GeneralHashedRelation` whether kyro is enabled or not, it is better to register Java `HashMap` in `SparkSqlSerializer`.

Author: Liang-Chi Hsieh <viirya@gmail.com>

Closes #5465 from viirya/register_hashmap and squashes the following commits:

9062601 [Liang-Chi Hsieh] Register Java HashMap for SparkSqlSerializer.
---
 .../org/apache/spark/sql/execution/SparkSqlSerializer.scala     | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala
index 347e2f4a1a1af..914f387dec78f 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala
@@ -18,6 +18,7 @@
 package org.apache.spark.sql.execution
 
 import java.nio.ByteBuffer
+import java.util.{HashMap => JavaHashMap}
 
 import org.apache.spark.sql.types.Decimal
 
@@ -54,6 +55,7 @@ private[sql] class SparkSqlSerializer(conf: SparkConf) extends KryoSerializer(co
     kryo.register(classOf[org.apache.spark.util.collection.OpenHashSet[_]],
                   new OpenHashSetSerializer)
     kryo.register(classOf[Decimal])
+    kryo.register(classOf[JavaHashMap[_, _]])
 
     kryo.setReferences(false)
     kryo

From 5f7b7cdab41002ad291f0a1ba7777cfff21d0019 Mon Sep 17 00:00:00 2001
From: "Santiago M. Mola" <santiago.mola@sap.com>
Date: Sat, 11 Apr 2015 14:52:49 -0700
Subject: [PATCH 46/95] [SPARK-6611][SQL] Add support for INTEGER as synonym of
 INT.

https://issues.apache.org/jira/browse/SPARK-6611

Author: Santiago M. Mola <santiago.mola@sap.com>

Closes #5271 from smola/features/integer-parse and squashes the following commits:

f5c1c64 [Santiago M. Mola] [SPARK-6611] Add support for INTEGER as synonym of INT.
---
 .../main/scala/org/apache/spark/sql/types/DataTypeParser.scala  | 2 +-
 .../scala/org/apache/spark/sql/types/DataTypeParserSuite.scala  | 2 ++
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeParser.scala
index 34270d0ca7cd7..5163f05879e42 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeParser.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeParser.scala
@@ -40,7 +40,7 @@ private[sql] trait DataTypeParser extends StandardTokenParsers {
   protected lazy val primitiveType: Parser[DataType] =
     "(?i)string".r ^^^ StringType |
     "(?i)float".r ^^^ FloatType |
-    "(?i)int".r ^^^ IntegerType |
+    "(?i)(?:int|integer)".r ^^^ IntegerType |
     "(?i)tinyint".r ^^^ ByteType |
     "(?i)smallint".r ^^^ ShortType |
     "(?i)double".r ^^^ DoubleType |
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/types/DataTypeParserSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/types/DataTypeParserSuite.scala
index 1ba21b64603ac..169125264a803 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/types/DataTypeParserSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/types/DataTypeParserSuite.scala
@@ -34,10 +34,12 @@ class DataTypeParserSuite extends FunSuite {
   }
 
   checkDataType("int", IntegerType)
+  checkDataType("integer", IntegerType)
   checkDataType("BooLean", BooleanType)
   checkDataType("tinYint", ByteType)
   checkDataType("smallINT", ShortType)
   checkDataType("INT", IntegerType)
+  checkDataType("INTEGER", IntegerType)
   checkDataType("bigint", LongType)
   checkDataType("float", FloatType)
   checkDataType("dOUBle", DoubleType)

From 6437e7cc3bd405ebd4ad7d8f9c7a5e703652ad36 Mon Sep 17 00:00:00 2001
From: "Santiago M. Mola" <santiago.mola@sap.com>
Date: Sat, 11 Apr 2015 15:42:03 -0700
Subject: [PATCH 47/95] [SPARK-6863] Fix formatting on SQL programming guide.

https://issues.apache.org/jira/browse/SPARK-6863

Author: Santiago M. Mola <santiago.mola@sap.com>

Closes #5472 from smola/fix/sql-docs and squashes the following commits:

42503d4 [Santiago M. Mola] [SPARK-6863] Fix formatting on SQL programming guide.
---
 docs/sql-programming-guide.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md
index 663f656883721..332618edf0c55 100644
--- a/docs/sql-programming-guide.md
+++ b/docs/sql-programming-guide.md
@@ -1784,6 +1784,7 @@ in Hive deployments.
 
 
 **Esoteric Hive Features**
+
 * `UNION` type
 * Unique join
 * Column statistics collecting: Spark SQL does not piggyback scans to collect column statistics at

From 7dbd37160ff57f80cc7abdcaef95f8c6df20a0f0 Mon Sep 17 00:00:00 2001
From: "Guancheng (G.C.) Chen" <chenguancheng@gmail.com>
Date: Sat, 11 Apr 2015 15:43:12 -0700
Subject: [PATCH 48/95] [Minor][SQL] Fix typo in sql

In this PR, "analyser" is changed to "analyzer" to keep a consistent naming. Some other typos are also fixed.

Author: Guancheng (G.C.) Chen <chenguancheng@gmail.com>

Closes #5474 from gchen/sql-typo and squashes the following commits:

70e6e76 [Guancheng (G.C.) Chen] Merge branch 'sql-typo' of github.com:gchen/spark into sql-typo
fb7a6e2 [Guancheng (G.C.) Chen] fix typo in sql
37e3da1 [Guancheng (G.C.) Chen] fix type in sql
---
 .../org/apache/spark/sql/catalyst/analysis/Analyzer.scala     | 2 +-
 .../org/apache/spark/sql/catalyst/analysis/Catalog.scala      | 4 ++--
 .../apache/spark/sql/catalyst/analysis/FunctionRegistry.scala | 4 ++--
 3 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
index b3aba4f68ddf9..524c73c31bbe1 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
@@ -27,7 +27,7 @@ import org.apache.spark.sql.types._
 
 /**
  * A trivial [[Analyzer]] with an [[EmptyCatalog]] and [[EmptyFunctionRegistry]]. Used for testing
- * when all relations are already filled in and the analyser needs only to resolve attribute
+ * when all relations are already filled in and the analyzer needs only to resolve attribute
  * references.
  */
 object SimpleAnalyzer extends Analyzer(EmptyCatalog, EmptyFunctionRegistry, true)
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Catalog.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Catalog.scala
index 5eb7dff0cede8..b2f8157a1a61f 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Catalog.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Catalog.scala
@@ -22,7 +22,7 @@ import scala.collection.mutable
 import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Subquery}
 
 /**
- * Thrown by a catalog when a table cannot be found.  The analzyer will rethrow the exception
+ * Thrown by a catalog when a table cannot be found.  The analyzer will rethrow the exception
  * as an AnalysisException with the correct position information.
  */
 class NoSuchTableException extends Exception
@@ -201,7 +201,7 @@ trait OverrideCatalog extends Catalog {
 
 /**
  * A trivial catalog that returns an error when a relation is requested.  Used for testing when all
- * relations are already filled in and the analyser needs only to resolve attribute references.
+ * relations are already filled in and the analyzer needs only to resolve attribute references.
  */
 object EmptyCatalog extends Catalog {
 
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala
index c43ea55899695..16ca5bcd57a72 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala
@@ -57,8 +57,8 @@ class SimpleFunctionRegistry(val caseSensitive: Boolean) extends FunctionRegistr
 }
 
 /**
- * A trivial catalog that returns an error when a function is requested.  Used for testing when all
- * functions are already filled in and the analyser needs only to resolve attribute references.
+ * A trivial catalog that returns an error when a function is requested. Used for testing when all
+ * functions are already filled in and the analyzer needs only to resolve attribute references.
  */
 object EmptyFunctionRegistry extends FunctionRegistry {
   override def registerFunction(name: String, builder: FunctionBuilder): Unit = {

From 2f53588738e95a2191f9844818e47f0d2ebbfd54 Mon Sep 17 00:00:00 2001
From: haiyang <huhaiyang@huawei.com>
Date: Sat, 11 Apr 2015 18:30:17 -0700
Subject: [PATCH 49/95] [SPARK-6199] [SQL] Support CTE in HiveContext and
 SQLContext

Author: haiyang <huhaiyang@huawei.com>

Closes #4929 from haiyangsea/cte and squashes the following commits:

220b67d [haiyang] add golden files for cte test
d3c7681 [haiyang] Merge branch 'master' into cte-repair
0ba2070 [haiyang] modify code style
9ce6b58 [haiyang] fix conflict
ff74741 [haiyang] add comment for With plan
0d56af4 [haiyang] code indention
776a440 [haiyang] add comments for resolve relation strategy
2fccd7e [haiyang] add comments for resolve relation strategy
241bbe2 [haiyang] fix cte problem of view
e9e1237 [haiyang] fix test case problem
614182f [haiyang] add test cases for CTE feature
32e415b [haiyang] add comment
1cc8c15 [haiyang] support with
03f1097 [haiyang] support with
e960099 [haiyang] support with
9aaa874 [haiyang] support with
0566978 [haiyang] support with
a99ecd2 [haiyang] support with
c3fa4c2 [haiyang] support with
3b6077f [haiyang] support with
5f8abe3 [haiyang] support with
4572b05 [haiyang] support with
f801f54 [haiyang] support with
---
 .../apache/spark/sql/catalyst/SqlParser.scala |  7 +++++
 .../sql/catalyst/analysis/Analyzer.scala      | 31 ++++++++++++++-----
 .../plans/logical/basicOperators.scala        | 12 +++++++
 .../org/apache/spark/sql/SQLQuerySuite.scala  | 14 +++++++++
 .../org/apache/spark/sql/hive/HiveQl.scala    | 27 ++++++++++++----
 ...ture #1-0-eedabbfe6ba8799f7b7782fb47a82768 |  3 ++
 ...ture #2-0-aa03d104251f97e36bc52279cb9931c9 |  4 +++
 ...ture #3-0-b5d4bf3c0ee92b2fda0ca24f422383f2 |  1 +
 .../sql/hive/execution/HiveQuerySuite.scala   | 15 +++++++++
 9 files changed, 100 insertions(+), 14 deletions(-)
 create mode 100644 sql/hive/src/test/resources/golden/CTE feature #1-0-eedabbfe6ba8799f7b7782fb47a82768
 create mode 100644 sql/hive/src/test/resources/golden/CTE feature #2-0-aa03d104251f97e36bc52279cb9931c9
 create mode 100644 sql/hive/src/test/resources/golden/CTE feature #3-0-b5d4bf3c0ee92b2fda0ca24f422383f2

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala
index 89f4a19add1c6..ee04cb579deb6 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala
@@ -111,6 +111,7 @@ class SqlParser extends AbstractSparkSQLParser with DataTypeParser {
   protected val UPPER = Keyword("UPPER")
   protected val WHEN = Keyword("WHEN")
   protected val WHERE = Keyword("WHERE")
+  protected val WITH = Keyword("WITH")
 
   protected def assignAliases(exprs: Seq[Expression]): Seq[NamedExpression] = {
     exprs.zipWithIndex.map {
@@ -127,6 +128,7 @@ class SqlParser extends AbstractSparkSQLParser with DataTypeParser {
       | UNION ~ DISTINCT.? ^^^ { (q1: LogicalPlan, q2: LogicalPlan) => Distinct(Union(q1, q2)) }
       )
     | insert
+    | cte
     )
 
   protected lazy val select: Parser[LogicalPlan] =
@@ -156,6 +158,11 @@ class SqlParser extends AbstractSparkSQLParser with DataTypeParser {
       case o ~ r ~ s => InsertIntoTable(r, Map.empty[String, Option[String]], s, o)
     }
 
+  protected lazy val cte: Parser[LogicalPlan] =
+    WITH ~> rep1sep(ident ~ ( AS ~ "(" ~> start <~ ")"), ",") ~ start ^^ {
+      case r ~ s => With(s, r.map({case n ~ s => (n, Subquery(n, s))}).toMap)
+    }
+
   protected lazy val projection: Parser[Expression] =
     expression ~ (AS.? ~> ident.?) ^^ {
       case e ~ a => a.fold(e)(Alias(e, _)())
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
index 524c73c31bbe1..b83f18abdd239 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
@@ -169,21 +169,36 @@ class Analyzer(
    * Replaces [[UnresolvedRelation]]s with concrete relations from the catalog.
    */
   object ResolveRelations extends Rule[LogicalPlan] {
-    def getTable(u: UnresolvedRelation): LogicalPlan = {
+    def getTable(u: UnresolvedRelation, cteRelations: Map[String, LogicalPlan]) = {
       try {
-        catalog.lookupRelation(u.tableIdentifier, u.alias)
+        // In hive, if there is same table name in database and CTE definition,
+        // hive will use the table in database, not the CTE one.
+        // Taking into account the reasonableness and the implementation complexity,
+        // here use the CTE definition first, check table name only and ignore database name
+        cteRelations.get(u.tableIdentifier.last)
+          .map(relation => u.alias.map(Subquery(_, relation)).getOrElse(relation))
+          .getOrElse(catalog.lookupRelation(u.tableIdentifier, u.alias))
       } catch {
         case _: NoSuchTableException =>
           u.failAnalysis(s"no such table ${u.tableName}")
       }
     }
 
-    def apply(plan: LogicalPlan): LogicalPlan = plan transform {
-      case i @ InsertIntoTable(u: UnresolvedRelation, _, _, _) =>
-        i.copy(
-          table = EliminateSubQueries(getTable(u)))
-      case u: UnresolvedRelation =>
-        getTable(u)
+    def apply(plan: LogicalPlan): LogicalPlan = {
+      val (realPlan, cteRelations) = plan match {
+        // TODO allow subquery to define CTE
+        // Add cte table to a temp relation map,drop `with` plan and keep its child
+        case With(child, relations) => (child, relations)
+        case other => (other, Map.empty[String, LogicalPlan])
+      }
+
+      realPlan transform {
+        case i@InsertIntoTable(u: UnresolvedRelation, _, _, _) =>
+          i.copy(
+            table = EliminateSubQueries(getTable(u, cteRelations)))
+        case u: UnresolvedRelation =>
+          getTable(u, cteRelations)
+      }
     }
   }
 
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala
index 8633e06093cf3..3bd5aa5964221 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala
@@ -147,6 +147,18 @@ case class CreateTableAsSelect[T](
   override lazy val resolved: Boolean = databaseName != None && childrenResolved
 }
 
+/**
+ * A container for holding named common table expressions (CTEs) and a query plan.
+ * This operator will be removed during analysis and the relations will be substituted into child.
+ * @param child The final query of this CTE.
+ * @param cteRelations Queries that this CTE defined,
+ *                     key is the alias of the CTE definition,
+ *                     value is the CTE definition.
+ */
+case class With(child: LogicalPlan, cteRelations: Map[String, Subquery]) extends UnaryNode {
+  override def output = child.output
+}
+
 case class WriteToFile(
     path: String,
     child: LogicalPlan) extends UnaryNode {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
index 1392b4819131b..fb8fc6dbd1e1e 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
@@ -407,6 +407,20 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll {
       mapData.collect().take(1).map(Row.fromTuple).toSeq)
   }
 
+  test("CTE feature") {
+    checkAnswer(
+      sql("with q1 as (select * from testData limit 10) select * from q1"),
+      testData.take(10).toSeq)
+
+    checkAnswer(
+      sql("""
+        |with q1 as (select * from testData where key= '5'),
+        |q2 as (select * from testData where key = '4')
+        |select * from q1 union all select * from q2""".stripMargin),
+      Row(5, "5") :: Row(4, "4") :: Nil)
+
+  }
+
   test("date row") {
     checkAnswer(sql(
       """select cast("2015-01-28" as date) from testData limit 1"""),
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
index 0bdaf5f7ef8ef..2fb2e7c4a5370 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
@@ -576,11 +576,23 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
     case Token("TOK_QUERY", queryArgs)
         if Seq("TOK_FROM", "TOK_INSERT").contains(queryArgs.head.getText) =>
 
-      val (fromClause: Option[ASTNode], insertClauses) = queryArgs match {
-        case Token("TOK_FROM", args: Seq[ASTNode]) :: insertClauses =>
-          (Some(args.head), insertClauses)
-        case Token("TOK_INSERT", _) :: Nil => (None, queryArgs)
-      }
+      val (fromClause: Option[ASTNode], insertClauses, cteRelations) =
+        queryArgs match {
+          case Token("TOK_FROM", args: Seq[ASTNode]) :: insertClauses =>
+            // check if has CTE
+            insertClauses.last match {
+              case Token("TOK_CTE", cteClauses) =>
+                val cteRelations = cteClauses.map(node => {
+                  val relation = nodeToRelation(node).asInstanceOf[Subquery]
+                  (relation.alias, relation)
+                }).toMap
+                (Some(args.head), insertClauses.init, Some(cteRelations))
+
+              case _ => (Some(args.head), insertClauses, None)
+            }
+
+          case Token("TOK_INSERT", _) :: Nil => (None, queryArgs, None)
+        }
 
       // Return one query for each insert clause.
       val queries = insertClauses.map { case Token("TOK_INSERT", singleInsert) =>
@@ -794,7 +806,10 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
       }
 
       // If there are multiple INSERTS just UNION them together into on query.
-      queries.reduceLeft(Union)
+      val query = queries.reduceLeft(Union)
+
+      // return With plan if there is CTE
+      cteRelations.map(With(query, _)).getOrElse(query)
 
     case Token("TOK_UNION", left :: right :: Nil) => Union(nodeToPlan(left), nodeToPlan(right))
 
diff --git a/sql/hive/src/test/resources/golden/CTE feature #1-0-eedabbfe6ba8799f7b7782fb47a82768 b/sql/hive/src/test/resources/golden/CTE feature #1-0-eedabbfe6ba8799f7b7782fb47a82768
new file mode 100644
index 0000000000000..f6ba75da254ca
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/CTE feature #1-0-eedabbfe6ba8799f7b7782fb47a82768	
@@ -0,0 +1,3 @@
+5
+5
+5
diff --git a/sql/hive/src/test/resources/golden/CTE feature #2-0-aa03d104251f97e36bc52279cb9931c9 b/sql/hive/src/test/resources/golden/CTE feature #2-0-aa03d104251f97e36bc52279cb9931c9
new file mode 100644
index 0000000000000..ca7b591095e28
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/CTE feature #2-0-aa03d104251f97e36bc52279cb9931c9	
@@ -0,0 +1,4 @@
+val_4
+val_5
+val_5
+val_5
diff --git a/sql/hive/src/test/resources/golden/CTE feature #3-0-b5d4bf3c0ee92b2fda0ca24f422383f2 b/sql/hive/src/test/resources/golden/CTE feature #3-0-b5d4bf3c0ee92b2fda0ca24f422383f2
new file mode 100644
index 0000000000000..b8626c4cff284
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/CTE feature #3-0-b5d4bf3c0ee92b2fda0ca24f422383f2	
@@ -0,0 +1 @@
+4
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
index af781a502e9f3..1222fbabd8b33 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
@@ -542,6 +542,21 @@ class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter {
   createQueryTest("select null from table",
     "SELECT null FROM src LIMIT 1")
 
+  createQueryTest("CTE feature #1",
+    "with q1 as (select key from src) select * from q1 where key = 5")
+
+  createQueryTest("CTE feature #2",
+    """with q1 as (select * from src where key= 5),
+      |q2 as (select * from src s2 where key = 4)
+      |select value from q1 union all select value from q2
+    """.stripMargin)
+
+  createQueryTest("CTE feature #3",
+    """with q1 as (select key from src)
+      |from q1
+      |select * where key = 4
+    """.stripMargin)
+
   test("predicates contains an empty AttributeSet() references") {
     sql(
       """

From 1f39a61118184e136f38381a9f3ba0b2d5d589d9 Mon Sep 17 00:00:00 2001
From: lazymam500 <lazyman500@gmail.com>
Date: Sat, 11 Apr 2015 18:33:14 -0700
Subject: [PATCH 50/95] [Spark-5068][SQL]Fix bug query data when path doesn't
 exist for HiveContext

This PR follow up PR #3907 & #3891 & #4356.
According to  marmbrus  liancheng 's comments, I try to use fs.globStatus to retrieve all FileStatus objects under path(s), and then do the filtering locally.

[1]. get pathPattern by path, and put it into pathPatternSet. (hdfs://cluster/user/demo/2016/08/12 -> hdfs://cluster/user/demo/*/*/*)
[2]. retrieve all FileStatus objects ,and cache them by undating existPathSet.
[3]. do the filtering locally
[4]. if we have new pathPattern,do 1,2 step again. (external table maybe have more than one partition pathPattern)

chenghao-intel jeanlyn

Author: lazymam500 <lazyman500@gmail.com>
Author: lazyman <lazyman500@gmail.com>

Closes #5059 from lazyman500/SPARK-5068 and squashes the following commits:

5bfcbfd [lazyman] move spark.sql.hive.verifyPartitionPath to SQLConf,fix scala style
e1d6386 [lazymam500] fix scala style
f23133f [lazymam500] bug fix
47e0023 [lazymam500] fix scala style,add config flag,break the chaining
04c443c [lazyman] SPARK-5068: fix bug when partition path doesn't exists #2
41f60ce [lazymam500] Merge pull request #1 from apache/master
---
 .../scala/org/apache/spark/sql/SQLConf.scala  |  6 ++
 .../apache/spark/sql/hive/TableReader.scala   | 41 +++++++++++-
 .../spark/sql/hive/QueryPartitionSuite.scala  | 64 +++++++++++++++++++
 3 files changed, 110 insertions(+), 1 deletion(-)
 create mode 100644 sql/hive/src/test/scala/org/apache/spark/sql/hive/QueryPartitionSuite.scala

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala
index 4815620c6fe57..ee641bdfeb2d7 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala
@@ -39,6 +39,8 @@ private[spark] object SQLConf {
   val PARQUET_FILTER_PUSHDOWN_ENABLED = "spark.sql.parquet.filterPushdown"
   val PARQUET_USE_DATA_SOURCE_API = "spark.sql.parquet.useDataSourceApi"
 
+  val HIVE_VERIFY_PARTITIONPATH = "spark.sql.hive.verifyPartitionPath"
+
   val COLUMN_NAME_OF_CORRUPT_RECORD = "spark.sql.columnNameOfCorruptRecord"
   val BROADCAST_TIMEOUT = "spark.sql.broadcastTimeout"
 
@@ -119,6 +121,10 @@ private[sql] class SQLConf extends Serializable {
   private[spark] def parquetUseDataSourceApi =
     getConf(PARQUET_USE_DATA_SOURCE_API, "true").toBoolean
 
+  /** When true uses verifyPartitionPath to prune the path which is not exists. */
+  private[spark] def verifyPartitionPath =
+    getConf(HIVE_VERIFY_PARTITIONPATH, "true").toBoolean
+
   /** When true the planner will use the external sort, which may spill to disk. */
   private[spark] def externalSortEnabled: Boolean = getConf(EXTERNAL_SORT, "false").toBoolean
 
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala
index 3563472c7ae81..d35291543c9f9 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala
@@ -142,7 +142,46 @@ class HadoopTableReader(
       partitionToDeserializer: Map[HivePartition,
       Class[_ <: Deserializer]],
       filterOpt: Option[PathFilter]): RDD[Row] = {
-    val hivePartitionRDDs = partitionToDeserializer.map { case (partition, partDeserializer) =>
+        
+    // SPARK-5068:get FileStatus and do the filtering locally when the path is not exists
+    def verifyPartitionPath(
+        partitionToDeserializer: Map[HivePartition, Class[_ <: Deserializer]]):
+        Map[HivePartition, Class[_ <: Deserializer]] = {
+      if (!sc.conf.verifyPartitionPath) {
+        partitionToDeserializer
+      } else {
+        var existPathSet = collection.mutable.Set[String]()
+        var pathPatternSet = collection.mutable.Set[String]()
+        partitionToDeserializer.filter {
+          case (partition, partDeserializer) =>
+            def updateExistPathSetByPathPattern(pathPatternStr: String) {
+              val pathPattern = new Path(pathPatternStr)
+              val fs = pathPattern.getFileSystem(sc.hiveconf)
+              val matches = fs.globStatus(pathPattern)
+              matches.foreach(fileStatus => existPathSet += fileStatus.getPath.toString)
+            }
+            // convert  /demo/data/year/month/day  to  /demo/data/*/*/*/
+            def getPathPatternByPath(parNum: Int, tempPath: Path): String = {
+              var path = tempPath
+              for (i <- (1 to parNum)) path = path.getParent
+              val tails = (1 to parNum).map(_ => "*").mkString("/", "/", "/")
+              path.toString + tails
+            }
+
+            val partPath = HiveShim.getDataLocationPath(partition)
+            val partNum = Utilities.getPartitionDesc(partition).getPartSpec.size();
+            var pathPatternStr = getPathPatternByPath(partNum, partPath)
+            if (!pathPatternSet.contains(pathPatternStr)) {
+              pathPatternSet += pathPatternStr
+              updateExistPathSetByPathPattern(pathPatternStr)
+            }
+            existPathSet.contains(partPath.toString)
+        }
+      }
+    }
+
+    val hivePartitionRDDs = verifyPartitionPath(partitionToDeserializer)
+      .map { case (partition, partDeserializer) =>
       val partDesc = Utilities.getPartitionDesc(partition)
       val partPath = HiveShim.getDataLocationPath(partition)
       val inputPathStr = applyFilterIfNeeded(partPath, filterOpt)
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/QueryPartitionSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/QueryPartitionSuite.scala
new file mode 100644
index 0000000000000..83f97128c5e83
--- /dev/null
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/QueryPartitionSuite.scala
@@ -0,0 +1,64 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.hive
+
+import java.io.File
+
+import com.google.common.io.Files
+import org.apache.spark.sql.{QueryTest, _}
+import org.apache.spark.sql.hive.test.TestHive
+import org.apache.spark.util.Utils
+/* Implicits */
+import org.apache.spark.sql.hive.test.TestHive._
+
+
+
+class QueryPartitionSuite extends QueryTest {
+  import org.apache.spark.sql.hive.test.TestHive.implicits._
+
+  test("SPARK-5068: query data when path doesn't exists"){
+    val testData = TestHive.sparkContext.parallelize(
+      (1 to 10).map(i => TestData(i, i.toString))).toDF()
+    testData.registerTempTable("testData")
+
+    val tmpDir = Files.createTempDir()
+    //create the table for test
+    sql(s"CREATE TABLE table_with_partition(key int,value string) PARTITIONED by (ds string) location '${tmpDir.toURI.toString}' ")
+    sql("INSERT OVERWRITE TABLE table_with_partition  partition (ds='1') SELECT key,value FROM testData")
+    sql("INSERT OVERWRITE TABLE table_with_partition  partition (ds='2') SELECT key,value FROM testData")
+    sql("INSERT OVERWRITE TABLE table_with_partition  partition (ds='3') SELECT key,value FROM testData")
+    sql("INSERT OVERWRITE TABLE table_with_partition  partition (ds='4') SELECT key,value FROM testData")
+
+    //test for the exist path
+    checkAnswer(sql("select key,value from table_with_partition"),
+      testData.toSchemaRDD.collect ++ testData.toSchemaRDD.collect
+        ++ testData.toSchemaRDD.collect ++ testData.toSchemaRDD.collect)
+
+    //delect the path of one partition
+    val folders = tmpDir.listFiles.filter(_.isDirectory)
+    Utils.deleteRecursively(folders(0))
+
+    //test for affter delete the path
+    checkAnswer(sql("select key,value from table_with_partition"),
+      testData.toSchemaRDD.collect ++ testData.toSchemaRDD.collect
+        ++ testData.toSchemaRDD.collect)
+
+    sql("DROP TABLE table_with_partition")
+    sql("DROP TABLE createAndInsertTest")
+  }
+}

From 48cc840021c43fcb4c5bb365d2c80512678cf120 Mon Sep 17 00:00:00 2001
From: DoingDone9 <799203320@qq.com>
Date: Sat, 11 Apr 2015 18:34:17 -0700
Subject: [PATCH 51/95] [SPARK-6179][SQL] Add token for "SHOW PRINCIPALS
 role_name" and "SHOW TRANSACTIONS" and "SHOW COMPACTIONS"

[SHOW PRINCIPALS role_name]
Lists all roles and users who belong to this role.
Only the admin role has privilege for this.

[SHOW COMPACTIONS]
It returns a list of all tables and partitions currently being compacted or scheduled for compaction when Hive transactions are being used.

[SHOW TRANSACTIONS]
It is for use by administrators when Hive transactions are being used. It returns a list of all currently open and aborted transactions in the system.

Author: DoingDone9 <799203320@qq.com>
Author: Zhongshuai Pei <799203320@qq.com>
Author: Xu Tingjun <xutingjun@huawei.com>

Closes #4902 from DoingDone9/SHOW_PRINCIPALS and squashes the following commits:

4add42f [Zhongshuai Pei] for test
311f806 [Zhongshuai Pei] for test
0c7550a [DoingDone9] Update HiveQl.scala
c8aeb1c [Xu Tingjun] aa
802261c [DoingDone9] Merge pull request #7 from apache/master
d00303b [DoingDone9] Merge pull request #6 from apache/master
98b134f [DoingDone9] Merge pull request #5 from apache/master
161cae3 [DoingDone9] Merge pull request #4 from apache/master
c87e8b6 [DoingDone9] Merge pull request #3 from apache/master
cb1852d [DoingDone9] Merge pull request #2 from apache/master
c3f046f [DoingDone9] Merge pull request #1 from apache/master
---
 sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
index 2fb2e7c4a5370..b2ae74efeb097 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
@@ -113,13 +113,16 @@ private[hive] object HiveQl {
     
     "TOK_REVOKE",
     
+    "TOK_SHOW_COMPACTIONS",
     "TOK_SHOW_CREATETABLE",
     "TOK_SHOW_GRANT",
     "TOK_SHOW_ROLE_GRANT",
+    "TOK_SHOW_ROLE_PRINCIPALS",
     "TOK_SHOW_ROLES",
     "TOK_SHOW_SET_ROLE",
     "TOK_SHOW_TABLESTATUS",
     "TOK_SHOW_TBLPROPERTIES",
+    "TOK_SHOW_TRANSACTIONS",
     "TOK_SHOWCOLUMNS",
     "TOK_SHOWDATABASES",
     "TOK_SHOWFUNCTIONS",

From 352a5da421d61379f2a8bcd7548ccc5d2647120a Mon Sep 17 00:00:00 2001
From: Takeshi YAMAMURO <linguin.m.s@gmail.com>
Date: Sat, 11 Apr 2015 18:41:12 -0700
Subject: [PATCH 52/95] [SPARK-6379][SQL] Support a functon to call
 user-defined functions registered in SQLContext

This is useful for using pre-defined UDFs in SQLContext;

val df = Seq(("id1", 1), ("id2", 4), ("id3", 5)).toDF("id", "value")
val sqlctx = df.sqlContext
sqlctx.udf.register("simpleUdf", (v: Int) => v * v)
df.select($"id", sqlctx.callUdf("simpleUdf", $"value"))

Author: Takeshi YAMAMURO <linguin.m.s@gmail.com>

Closes #5061 from maropu/SupportUDFConversionInSparkContext and squashes the following commits:

f858aff [Takeshi YAMAMURO] Move the function into functions.scala
afd0380 [Takeshi YAMAMURO] Add a return type of callUDF
599b76c [Takeshi YAMAMURO] Remove the implicit conversion and add SqlContext#callUdf
8b56f10 [Takeshi YAMAMURO] Support an implicit conversion from udf"name" to an UDF defined in SQLContext
---
 .../org/apache/spark/sql/functions.scala      | 21 ++++++++++++++++++-
 .../org/apache/spark/sql/DataFrameSuite.scala |  9 ++++++++
 2 files changed, 29 insertions(+), 1 deletion(-)

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/functions.scala b/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
index 111e751588a8b..ff91e1d74bc2c 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
@@ -22,7 +22,7 @@ import scala.reflect.runtime.universe.{TypeTag, typeTag}
 
 import org.apache.spark.annotation.Experimental
 import org.apache.spark.sql.catalyst.ScalaReflection
-import org.apache.spark.sql.catalyst.analysis.Star
+import org.apache.spark.sql.catalyst.analysis.{UnresolvedFunction, Star}
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.types._
 
@@ -605,4 +605,23 @@ object functions {
   }
 
   // scalastyle:on
+
+  /**
+   * Call an user-defined function.
+   * Example:
+   * {{{
+   *  import org.apache.spark.sql._
+   *
+   *  val df = Seq(("id1", 1), ("id2", 4), ("id3", 5)).toDF("id", "value")
+   *  val sqlContext = df.sqlContext
+   *  sqlContext.udf.register("simpleUdf", (v: Int) => v * v)
+   *  df.select($"id", callUdf("simpleUdf", $"value"))
+   * }}}
+   *
+   * @group udf_funcs
+   */
+  def callUdf(udfName: String, cols: Column*): Column = {
+     UnresolvedFunction(udfName, cols.map(_.expr))
+  }
+
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
index f5df8c6a59f10..b26e22f6229fe 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
@@ -440,6 +440,15 @@ class DataFrameSuite extends QueryTest {
     )
   }
 
+  test("call udf in SQLContext") {
+    val df = Seq(("id1", 1), ("id2", 4), ("id3", 5)).toDF("id", "value")
+    val sqlctx = df.sqlContext
+    sqlctx.udf.register("simpleUdf", (v: Int) => v * v)
+    checkAnswer(
+      df.select($"id", callUdf("simpleUdf", $"value")),
+      Row("id1", 1) :: Row("id2", 16) :: Row("id3", 25) :: Nil)
+  }
+
   test("withColumn") {
     val df = testData.toDF().withColumn("newCol", col("key") + 1)
     checkAnswer(

From d2383fb5ffafd6b3a56b1ee6e0e035594473e2c8 Mon Sep 17 00:00:00 2001
From: Yin Huai <yhuai@databricks.com>
Date: Sat, 11 Apr 2015 18:44:54 -0700
Subject: [PATCH 53/95] [SQL] Handle special characters in the authority of a
 Path's URI.

Author: Yin Huai <yhuai@databricks.com>

Closes #5381 from yhuai/parquetPath2 and squashes the following commits:

fe296b4 [Yin Huai] Create new Path to take care special characters in the authority of a Path's URI.
---
 .../apache/spark/sql/parquet/newParquet.scala | 30 +++++++++++++++++--
 1 file changed, 27 insertions(+), 3 deletions(-)

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala
index 0dce3623a66df..20fdf5e58ef82 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala
@@ -432,7 +432,10 @@ private[sql] case class ParquetRelation2(
 
     // FileInputFormat cannot handle empty lists.
     if (selectedFiles.nonEmpty) {
-      FileInputFormat.setInputPaths(job, selectedFiles.map(_.getPath): _*)
+      // In order to encode the authority of a Path containning special characters such as /,
+      // we need to use the string retruned by the URI of the path to create a new Path.
+      val selectedPaths = selectedFiles.map(status => new Path(status.getPath.toUri.toString))
+      FileInputFormat.setInputPaths(job, selectedPaths: _*)
     }
 
     // Try to push down filters when filter push-down is enabled.
@@ -484,10 +487,31 @@ private[sql] case class ParquetRelation2(
         val cacheMetadata = useCache
 
         @transient
-        val cachedStatus = selectedFiles
+        val cachedStatus = selectedFiles.map { st =>
+          // In order to encode the authority of a Path containning special characters such as /,
+          // we need to use the string retruned by the URI of the path to create a new Path.
+          val newPath = new Path(st.getPath.toUri.toString)
+
+          new FileStatus(
+            st.getLen,
+            st.isDir,
+            st.getReplication,
+            st.getBlockSize,
+            st.getModificationTime,
+            st.getAccessTime,
+            st.getPermission,
+            st.getOwner,
+            st.getGroup,
+            newPath)
+        }
 
         @transient
-        val cachedFooters = selectedFooters
+        val cachedFooters = selectedFooters.map { f =>
+          // In order to encode the authority of a Path containning special characters such as /,
+          // we need to use the string retruned by the URI of the path to create a new Path.
+          new Footer(new Path(f.getFile.toUri.toString), f.getParquetMetadata)
+        }
+
 
         // Overridden so we can inject our own cached files statuses.
         override def getPartitions: Array[SparkPartition] = {

From 6d4e854ffbd7dee9a3cd7b44a00fd9c0e551f5b8 Mon Sep 17 00:00:00 2001
From: Yin Huai <yhuai@databricks.com>
Date: Sat, 11 Apr 2015 19:26:15 -0700
Subject: [PATCH 54/95] [SPARK-6367][SQL] Use the proper data type for those
 expressions that are hijacking existing data types.

This PR adds internal UDTs for expressions that are hijacking existing data types.
The following UDTs are added:
* `HyperLogLogUDT` (`BinaryType` as the SQL type) for `ApproxCountDistinctPartition`
* `OpenHashSetUDT` (`ArrayType` as the SQL type) for `CollectHashSet`, `NewSet`, `AddItemToSet`, and `CombineSets`.

I am also adding more unit tests for aggregation with code gen enabled.

JIRA: https://issues.apache.org/jira/browse/SPARK-6367

Author: Yin Huai <yhuai@databricks.com>

Closes #5094 from yhuai/expressionType and squashes the following commits:

8bcd11a [Yin Huai] Return types.
61a1d66 [Yin Huai] Merge remote-tracking branch 'upstream/master' into expressionType
e8b4599 [Yin Huai] Merge remote-tracking branch 'upstream/master' into expressionType
2753156 [Yin Huai] Ignore aggregations having sum functions for now.
b5eb259 [Yin Huai] Case object for HyperLogLog type.
00ebdbd [Yin Huai] deserialize/serialize.
54b87ae [Yin Huai] Add UDTs for expressions that return HyperLogLog and OpenHashSet.
---
 .../sql/catalyst/expressions/aggregates.scala | 24 +++++++++++--
 .../expressions/codegen/CodeGenerator.scala   |  4 +--
 .../spark/sql/catalyst/expressions/sets.scala | 35 ++++++++++++++++---
 .../sql/execution/GeneratedAggregate.scala    | 12 ++++---
 .../org/apache/spark/sql/SQLQuerySuite.scala  | 12 ++++---
 .../spark/sql/UserDefinedTypeSuite.scala      | 24 ++++++++++++-
 6 files changed, 91 insertions(+), 20 deletions(-)

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala
index 406de38d1c483..14a855054b94d 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala
@@ -189,9 +189,10 @@ case class CollectHashSet(expressions: Seq[Expression]) extends AggregateExpress
 
   override def children: Seq[Expression] = expressions
   override def nullable: Boolean = false
-  override def dataType: ArrayType = ArrayType(expressions.head.dataType)
+  override def dataType: OpenHashSetUDT = new OpenHashSetUDT(expressions.head.dataType)
   override def toString: String = s"AddToHashSet(${expressions.mkString(",")})"
-  override def newInstance(): CollectHashSetFunction = new CollectHashSetFunction(expressions, this)
+  override def newInstance(): CollectHashSetFunction =
+    new CollectHashSetFunction(expressions, this)
 }
 
 case class CollectHashSetFunction(
@@ -250,11 +251,28 @@ case class CombineSetsAndCountFunction(
   override def eval(input: Row): Any = seen.size.toLong
 }
 
+/** The data type of ApproxCountDistinctPartition since its output is a HyperLogLog object. */
+private[sql] case object HyperLogLogUDT extends UserDefinedType[HyperLogLog] {
+
+  override def sqlType: DataType = BinaryType
+
+  /** Since we are using HyperLogLog internally, usually it will not be called. */
+  override def serialize(obj: Any): Array[Byte] =
+    obj.asInstanceOf[HyperLogLog].getBytes
+
+
+  /** Since we are using HyperLogLog internally, usually it will not be called. */
+  override def deserialize(datum: Any): HyperLogLog =
+    HyperLogLog.Builder.build(datum.asInstanceOf[Array[Byte]])
+
+  override def userClass: Class[HyperLogLog] = classOf[HyperLogLog]
+}
+
 case class ApproxCountDistinctPartition(child: Expression, relativeSD: Double)
   extends AggregateExpression with trees.UnaryNode[Expression] {
 
   override def nullable: Boolean = false
-  override def dataType: DataType = child.dataType
+  override def dataType: DataType = HyperLogLogUDT
   override def toString: String = s"APPROXIMATE COUNT(DISTINCT $child)"
   override def newInstance(): ApproxCountDistinctPartitionFunction = {
     new ApproxCountDistinctPartitionFunction(child, this, relativeSD)
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
index d1abf3c0b64a5..aac56e1568332 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
@@ -464,7 +464,7 @@ abstract class CodeGenerator[InType <: AnyRef, OutType <: AnyRef] extends Loggin
         val itemEval = expressionEvaluator(item)
         val setEval = expressionEvaluator(set)
 
-        val ArrayType(elementType, _) = set.dataType
+        val elementType = set.dataType.asInstanceOf[OpenHashSetUDT].elementType
 
         itemEval.code ++ setEval.code ++
         q"""
@@ -482,7 +482,7 @@ abstract class CodeGenerator[InType <: AnyRef, OutType <: AnyRef] extends Loggin
         val leftEval = expressionEvaluator(left)
         val rightEval = expressionEvaluator(right)
 
-        val ArrayType(elementType, _) = left.dataType
+        val elementType = left.dataType.asInstanceOf[OpenHashSetUDT].elementType
 
         leftEval.code ++ rightEval.code ++
         q"""
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/sets.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/sets.scala
index 35faa00782e80..4c44182278207 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/sets.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/sets.scala
@@ -20,6 +20,33 @@ package org.apache.spark.sql.catalyst.expressions
 import org.apache.spark.sql.types._
 import org.apache.spark.util.collection.OpenHashSet
 
+/** The data type for expressions returning an OpenHashSet as the result. */
+private[sql] class OpenHashSetUDT(
+    val elementType: DataType) extends UserDefinedType[OpenHashSet[Any]] {
+
+  override def sqlType: DataType = ArrayType(elementType)
+
+  /** Since we are using OpenHashSet internally, usually it will not be called. */
+  override def serialize(obj: Any): Seq[Any] = {
+    obj.asInstanceOf[OpenHashSet[Any]].iterator.toSeq
+  }
+
+  /** Since we are using OpenHashSet internally, usually it will not be called. */
+  override def deserialize(datum: Any): OpenHashSet[Any] = {
+    val iterator = datum.asInstanceOf[Seq[Any]].iterator
+    val set = new OpenHashSet[Any]
+    while(iterator.hasNext) {
+      set.add(iterator.next())
+    }
+
+    set
+  }
+
+  override def userClass: Class[OpenHashSet[Any]] = classOf[OpenHashSet[Any]]
+
+  private[spark] override def asNullable: OpenHashSetUDT = this
+}
+
 /**
  * Creates a new set of the specified type
  */
@@ -28,9 +55,7 @@ case class NewSet(elementType: DataType) extends LeafExpression {
 
   override def nullable: Boolean = false
 
-  // We are currently only using these Expressions internally for aggregation.  However, if we ever
-  // expose these to users we'll want to create a proper type instead of hijacking ArrayType.
-  override def dataType: DataType = ArrayType(elementType)
+  override def dataType: OpenHashSetUDT = new OpenHashSetUDT(elementType)
 
   override def eval(input: Row): Any = {
     new OpenHashSet[Any]()
@@ -50,7 +75,7 @@ case class AddItemToSet(item: Expression, set: Expression) extends Expression {
 
   override def nullable: Boolean = set.nullable
 
-  override def dataType: DataType = set.dataType
+  override def dataType: OpenHashSetUDT = set.dataType.asInstanceOf[OpenHashSetUDT]
 
   override def eval(input: Row): Any = {
     val itemEval = item.eval(input)
@@ -80,7 +105,7 @@ case class CombineSets(left: Expression, right: Expression) extends BinaryExpres
 
   override def nullable: Boolean = left.nullable || right.nullable
 
-  override def dataType: DataType = left.dataType
+  override def dataType: OpenHashSetUDT = left.dataType.asInstanceOf[OpenHashSetUDT]
 
   override def symbol: String = "++="
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
index 861a2c21ad9a0..3c58e93b45e9d 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
@@ -68,6 +68,8 @@ case class GeneratedAggregate(
       a.collect { case agg: AggregateExpression => agg}
     }
 
+    // If you add any new function support, please add tests in org.apache.spark.sql.SQLQuerySuite
+    // (in test "aggregation with codegen").
     val computeFunctions = aggregatesToCompute.map {
       case c @ Count(expr) =>
         // If we're evaluating UnscaledValue(x), we can do Count on x directly, since its
@@ -208,7 +210,8 @@ case class GeneratedAggregate(
           currentMax)
 
       case CollectHashSet(Seq(expr)) =>
-        val set = AttributeReference("hashSet", ArrayType(expr.dataType), nullable = false)()
+        val set =
+          AttributeReference("hashSet", new OpenHashSetUDT(expr.dataType), nullable = false)()
         val initialValue = NewSet(expr.dataType)
         val addToSet = AddItemToSet(expr, set)
 
@@ -219,9 +222,10 @@ case class GeneratedAggregate(
           set)
 
       case CombineSetsAndCount(inputSet) =>
-        val ArrayType(inputType, _) = inputSet.dataType
-        val set = AttributeReference("hashSet", inputSet.dataType, nullable = false)()
-        val initialValue = NewSet(inputType)
+        val elementType = inputSet.dataType.asInstanceOf[OpenHashSetUDT].elementType
+        val set =
+          AttributeReference("hashSet", new OpenHashSetUDT(elementType), nullable = false)()
+        val initialValue = NewSet(elementType)
         val collectSets = CombineSets(set, inputSet)
 
         AggregateEvaluation(
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
index fb8fc6dbd1e1e..5e453e05e2ac7 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
@@ -17,6 +17,7 @@
 
 package org.apache.spark.sql
 
+import org.apache.spark.sql.execution.GeneratedAggregate
 import org.apache.spark.sql.test.TestSQLContext
 import org.scalatest.BeforeAndAfterAll
 
@@ -151,10 +152,10 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll {
       "SELECT count(distinct key) FROM testData3x",
       Row(100) :: Nil)
     // SUM
-     testCodeGen(
-       "SELECT value, sum(key) FROM testData3x GROUP BY value",
-       (1 to 100).map(i => Row(i.toString, 3 * i)))
-     testCodeGen(
+    testCodeGen(
+      "SELECT value, sum(key) FROM testData3x GROUP BY value",
+      (1 to 100).map(i => Row(i.toString, 3 * i)))
+    testCodeGen(
       "SELECT sum(key), SUM(CAST(key as Double)) FROM testData3x",      
       Row(5050 * 3, 5050 * 3.0) :: Nil)
     // AVERAGE
@@ -192,10 +193,11 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll {
     testCodeGen(
       "SELECT  sum('a'), avg('a'), count(null) FROM testData",
       Row(0, null, 0) :: Nil)
-      
+
     dropTempTable("testData3x")
     setConf(SQLConf.CODEGEN_ENABLED, originalValue.toString)
   }
+
   test("Add Parser of SQL COALESCE()") {
     checkAnswer(
       sql("""SELECT COALESCE(1, 2)"""),
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala
index 902da5c3ba6d6..2672e20deadc5 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala
@@ -23,13 +23,16 @@ import org.apache.spark.util.Utils
 
 import scala.beans.{BeanInfo, BeanProperty}
 
+import com.clearspring.analytics.stream.cardinality.HyperLogLog
+
 import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.expressions.{OpenHashSetUDT, HyperLogLogUDT}
 import org.apache.spark.sql.functions._
 import org.apache.spark.sql.test.TestSQLContext
 import org.apache.spark.sql.test.TestSQLContext.{sparkContext, sql}
 import org.apache.spark.sql.test.TestSQLContext.implicits._
 import org.apache.spark.sql.types._
-
+import org.apache.spark.util.collection.OpenHashSet
 
 @SQLUserDefinedType(udt = classOf[MyDenseVectorUDT])
 private[sql] class MyDenseVector(val data: Array[Double]) extends Serializable {
@@ -119,4 +122,23 @@ class UserDefinedTypeSuite extends QueryTest {
     df.limit(1).groupBy('int).agg(first('vec)).collect()(0).getAs[MyDenseVector](0)
     df.orderBy('int).limit(1).groupBy('int).agg(first('vec)).collect()(0).getAs[MyDenseVector](0)
   }
+
+  test("HyperLogLogUDT") {
+    val hyperLogLogUDT = HyperLogLogUDT
+    val hyperLogLog = new HyperLogLog(0.4)
+    (1 to 10).foreach(i => hyperLogLog.offer(Row(i)))
+
+    val actual = hyperLogLogUDT.deserialize(hyperLogLogUDT.serialize(hyperLogLog))
+    assert(actual.cardinality() === hyperLogLog.cardinality())
+    assert(java.util.Arrays.equals(actual.getBytes, hyperLogLog.getBytes))
+  }
+
+  test("OpenHashSetUDT") {
+    val openHashSetUDT = new OpenHashSetUDT(IntegerType)
+    val set = new OpenHashSet[Int]
+    (1 to 10).foreach(i => set.add(i))
+
+    val actual = openHashSetUDT.deserialize(openHashSetUDT.serialize(set))
+    assert(actual.iterator.toSet === set.iterator.toSet)
+  }
 }

From 5c2844c51aca6a0da9251a3fd346a6f872cf17f8 Mon Sep 17 00:00:00 2001
From: Wenchen Fan <cloud0fan@outlook.com>
Date: Sat, 11 Apr 2015 19:35:56 -0700
Subject: [PATCH 55/95] [SQL][minor] move `resolveGetField` into a object

The method `resolveGetField` isn't belong to `LogicalPlan` logically and didn't access any members of it.

Author: Wenchen Fan <cloud0fan@outlook.com>

Closes #5435 from cloud-fan/tmp and squashes the following commits:

9a66c83 [Wenchen Fan] code clean up
---
 .../sql/catalyst/analysis/Analyzer.scala      |  2 +-
 .../catalyst/expressions/complexTypes.scala   | 37 +++++++++++++++++++
 .../catalyst/plans/logical/LogicalPlan.scala  | 35 +-----------------
 3 files changed, 39 insertions(+), 35 deletions(-)

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
index b83f18abdd239..fd1ceb1f77931 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
@@ -308,7 +308,7 @@ class Analyzer(
             logDebug(s"Resolving $u to $result")
             result
           case UnresolvedGetField(child, fieldName) if child.resolved =>
-            q.resolveGetField(child, fieldName, resolver)
+            GetField(child, fieldName, resolver)
         }
     }
 
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala
index 3b2b9211268a9..fc1f69655963d 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala
@@ -19,6 +19,8 @@ package org.apache.spark.sql.catalyst.expressions
 
 import scala.collection.Map
 
+import org.apache.spark.sql.AnalysisException
+import org.apache.spark.sql.catalyst.analysis.Resolver
 import org.apache.spark.sql.types._
 
 /**
@@ -81,6 +83,41 @@ trait GetField extends UnaryExpression {
   def field: StructField
 }
 
+object GetField {
+  /**
+   * Returns the resolved `GetField`, and report error if no desired field or over one
+   * desired fields are found.
+   */
+  def apply(
+      expr: Expression,
+      fieldName: String,
+      resolver: Resolver): GetField = {
+    def findField(fields: Array[StructField]): Int = {
+      val checkField = (f: StructField) => resolver(f.name, fieldName)
+      val ordinal = fields.indexWhere(checkField)
+      if (ordinal == -1) {
+        throw new AnalysisException(
+          s"No such struct field $fieldName in ${fields.map(_.name).mkString(", ")}")
+      } else if (fields.indexWhere(checkField, ordinal + 1) != -1) {
+        throw new AnalysisException(
+          s"Ambiguous reference to fields ${fields.filter(checkField).mkString(", ")}")
+      } else {
+        ordinal
+      }
+    }
+    expr.dataType match {
+      case StructType(fields) =>
+        val ordinal = findField(fields)
+        StructGetField(expr, fields(ordinal), ordinal)
+      case ArrayType(StructType(fields), containsNull) =>
+        val ordinal = findField(fields)
+        ArrayGetField(expr, fields(ordinal), ordinal, containsNull)
+      case otherType =>
+        throw new AnalysisException(s"GetField is not valid on fields of type $otherType")
+    }
+  }
+}
+
 /**
  * Returns the value of fields in the Struct `child`.
  */
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LogicalPlan.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LogicalPlan.scala
index d8f5858f5033e..579a0fb8d3f93 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LogicalPlan.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LogicalPlan.scala
@@ -210,7 +210,7 @@ abstract class LogicalPlan extends QueryPlan[LogicalPlan] with Logging {
           // For example, consider "a.b.c", where "a" is resolved to an existing attribute.
           // Then this will add GetField("c", GetField("b", a)), and alias
           // the final expression as "c".
-          val fieldExprs = nestedFields.foldLeft(a: Expression)(resolveGetField(_, _, resolver))
+          val fieldExprs = nestedFields.foldLeft(a: Expression)(GetField(_, _, resolver))
           val aliasName = nestedFields.last
           Some(Alias(fieldExprs, aliasName)())
         } catch {
@@ -229,39 +229,6 @@ abstract class LogicalPlan extends QueryPlan[LogicalPlan] with Logging {
           s"Reference '$name' is ambiguous, could be: $referenceNames.")
     }
   }
-
-  /**
-   * Returns the resolved `GetField`, and report error if no desired field or over one
-   * desired fields are found.
-   */
-  def resolveGetField(
-      expr: Expression,
-      fieldName: String,
-      resolver: Resolver): Expression = {
-    def findField(fields: Array[StructField]): Int = {
-      val checkField = (f: StructField) => resolver(f.name, fieldName)
-      val ordinal = fields.indexWhere(checkField)
-      if (ordinal == -1) {
-        throw new AnalysisException(
-          s"No such struct field $fieldName in ${fields.map(_.name).mkString(", ")}")
-      } else if (fields.indexWhere(checkField, ordinal + 1) != -1) {
-        throw new AnalysisException(
-          s"Ambiguous reference to fields ${fields.filter(checkField).mkString(", ")}")
-      } else {
-        ordinal
-      }
-    }
-    expr.dataType match {
-      case StructType(fields) =>
-        val ordinal = findField(fields)
-        StructGetField(expr, fields(ordinal), ordinal)
-      case ArrayType(StructType(fields), containsNull) =>
-        val ordinal = findField(fields)
-        ArrayGetField(expr, fields(ordinal), ordinal, containsNull)
-      case otherType =>
-        throw new AnalysisException(s"GetField is not valid on fields of type $otherType")
-    }
-  }
 }
 
 /**

From dea5dacc5d701c3dfe433360b2e17e50edec31e8 Mon Sep 17 00:00:00 2001
From: Josh Rosen <joshrosen@databricks.com>
Date: Sat, 11 Apr 2015 20:12:40 -0700
Subject: [PATCH 56/95] [HOTFIX] Add explicit return types to fix lint errors

---
 .../scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala | 2 +-
 .../spark/sql/catalyst/plans/logical/basicOperators.scala       | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
index fd1ceb1f77931..50702ac6832ec 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
@@ -169,7 +169,7 @@ class Analyzer(
    * Replaces [[UnresolvedRelation]]s with concrete relations from the catalog.
    */
   object ResolveRelations extends Rule[LogicalPlan] {
-    def getTable(u: UnresolvedRelation, cteRelations: Map[String, LogicalPlan]) = {
+    def getTable(u: UnresolvedRelation, cteRelations: Map[String, LogicalPlan]): LogicalPlan = {
       try {
         // In hive, if there is same table name in database and CTE definition,
         // hive will use the table in database, not the CTE one.
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala
index 3bd5aa5964221..5d31a6eecfce2 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala
@@ -156,7 +156,7 @@ case class CreateTableAsSelect[T](
  *                     value is the CTE definition.
  */
 case class With(child: LogicalPlan, cteRelations: Map[String, Subquery]) extends UnaryNode {
-  override def output = child.output
+  override def output: Seq[Attribute] = child.output
 }
 
 case class WriteToFile(

From 1205f7ea6165089985edf46ea4d2d53975d0f1f4 Mon Sep 17 00:00:00 2001
From: Michael Malak <michaelmalak@yahoo.com>
Date: Sat, 11 Apr 2015 21:01:23 -0700
Subject: [PATCH 57/95] SPARK-6710 GraphX Fixed Wrong initial bias in GraphX
 SVDPlusPlus

Author: Michael Malak <michaelmalak@yahoo.com>

Closes #5464 from michaelmalak/master and squashes the following commits:

9d942ba [Michael Malak] SPARK-6710 GraphX Fixed Wrong initial bias in GraphX SVDPlusPlus
---
 .../main/scala/org/apache/spark/graphx/lib/SVDPlusPlus.scala    | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/graphx/src/main/scala/org/apache/spark/graphx/lib/SVDPlusPlus.scala b/graphx/src/main/scala/org/apache/spark/graphx/lib/SVDPlusPlus.scala
index 1a7178b82e3af..3b0e1628d86b5 100644
--- a/graphx/src/main/scala/org/apache/spark/graphx/lib/SVDPlusPlus.scala
+++ b/graphx/src/main/scala/org/apache/spark/graphx/lib/SVDPlusPlus.scala
@@ -93,7 +93,7 @@ object SVDPlusPlus {
     val gJoinT0 = g.outerJoinVertices(t0) {
       (vid: VertexId, vd: (Array[Double], Array[Double], Double, Double),
        msg: Option[(Long, Double)]) =>
-        (vd._1, vd._2, msg.get._2 / msg.get._1, 1.0 / scala.math.sqrt(msg.get._1))
+        (vd._1, vd._2, msg.get._2 / msg.get._1 - u, 1.0 / scala.math.sqrt(msg.get._1))
     }.cache()
     materialize(gJoinT0)
     g.unpersist()

From 0cc8fcb4cd20cb90a1fac50b1a3ffed833ce5eac Mon Sep 17 00:00:00 2001
From: Patrick Wendell <patrick@databricks.com>
Date: Sat, 11 Apr 2015 22:12:56 -0700
Subject: [PATCH 58/95] MAINTENANCE: Automated closing of pull requests.

This commit exists to close the following pull requests on Github:

Closes #4994 (close requested by 'marmbrus')
Closes #4995 (close requested by 'marmbrus')
Closes #4491 (close requested by 'srowen')
Closes #3597 (close requested by 'srowen')
Closes #4693 (close requested by 'marmbrus')
Closes #3855 (close requested by 'marmbrus')
Closes #4398 (close requested by 'marmbrus')
Closes #4246 (close requested by 'marmbrus')
Closes #5153 (close requested by 'srowen')
Closes #3626 (close requested by 'srowen')
Closes #5166 (close requested by 'marmbrus')
Closes #5040 (close requested by 'marmbrus')
Closes #5044 (close requested by 'marmbrus')
Closes #5440 (close requested by 'JoshRosen')
Closes #4039 (close requested by 'marmbrus')
Closes #1237 (close requested by 'srowen')
Closes #216 (close requested by 'mengxr')
Closes #5092 (close requested by 'srowen')
Closes #5100 (close requested by 'marmbrus')
Closes #4469 (close requested by 'marmbrus')
Closes #5246 (close requested by 'srowen')
Closes #5013 (close requested by 'marmbrus')

From 5d8f7b9e87e8066d54717a1a78b06e8531d8b0d4 Mon Sep 17 00:00:00 2001
From: Davies Liu <davies@databricks.com>
Date: Sat, 11 Apr 2015 22:33:23 -0700
Subject: [PATCH 59/95] [SPARK-6677] [SQL] [PySpark] fix cached classes

It's possible to have two DataType object with same id (memory address) at different time, we should check the cached classes to verify that it's generated by given datatype.

This PR also change `__FIELDS__` and `__DATATYPE__` to lower case to match Python code style.

Author: Davies Liu <davies@databricks.com>

Closes #5445 from davies/fix_type_cache and squashes the following commits:

63b3238 [Davies Liu] typo
47bdede [Davies Liu] fix cached classes
---
 python/pyspark/sql/types.py | 39 +++++++++++++++++++------------------
 1 file changed, 20 insertions(+), 19 deletions(-)

diff --git a/python/pyspark/sql/types.py b/python/pyspark/sql/types.py
index 7e0124b13671b..ef76d84c00481 100644
--- a/python/pyspark/sql/types.py
+++ b/python/pyspark/sql/types.py
@@ -567,8 +567,8 @@ def _infer_schema(row):
     elif isinstance(row, (tuple, list)):
         if hasattr(row, "_fields"):  # namedtuple
             items = zip(row._fields, tuple(row))
-        elif hasattr(row, "__FIELDS__"):  # Row
-            items = zip(row.__FIELDS__, tuple(row))
+        elif hasattr(row, "__fields__"):  # Row
+            items = zip(row.__fields__, tuple(row))
         else:
             names = ['_%d' % i for i in range(1, len(row) + 1)]
             items = zip(names, row)
@@ -647,7 +647,7 @@ def converter(obj):
             if isinstance(obj, dict):
                 return tuple(c(obj.get(n)) for n, c in zip(names, converters))
             elif isinstance(obj, tuple):
-                if hasattr(obj, "_fields") or hasattr(obj, "__FIELDS__"):
+                if hasattr(obj, "_fields") or hasattr(obj, "__fields__"):
                     return tuple(c(v) for c, v in zip(converters, obj))
                 elif all(isinstance(x, tuple) and len(x) == 2 for x in obj):  # k-v pairs
                     d = dict(obj)
@@ -997,12 +997,13 @@ def _restore_object(dataType, obj):
     # same object in most cases.
     k = id(dataType)
     cls = _cached_cls.get(k)
-    if cls is None:
+    if cls is None or cls.__datatype is not dataType:
         # use dataType as key to avoid create multiple class
         cls = _cached_cls.get(dataType)
         if cls is None:
             cls = _create_cls(dataType)
             _cached_cls[dataType] = cls
+        cls.__datatype = dataType
         _cached_cls[k] = cls
     return cls(obj)
 
@@ -1119,8 +1120,8 @@ def Dict(d):
     class Row(tuple):
 
         """ Row in DataFrame """
-        __DATATYPE__ = dataType
-        __FIELDS__ = tuple(f.name for f in dataType.fields)
+        __datatype = dataType
+        __fields__ = tuple(f.name for f in dataType.fields)
         __slots__ = ()
 
         # create property for fast access
@@ -1128,22 +1129,22 @@ class Row(tuple):
 
         def asDict(self):
             """ Return as a dict """
-            return dict((n, getattr(self, n)) for n in self.__FIELDS__)
+            return dict((n, getattr(self, n)) for n in self.__fields__)
 
         def __repr__(self):
             # call collect __repr__ for nested objects
             return ("Row(%s)" % ", ".join("%s=%r" % (n, getattr(self, n))
-                                          for n in self.__FIELDS__))
+                                          for n in self.__fields__))
 
         def __reduce__(self):
-            return (_restore_object, (self.__DATATYPE__, tuple(self)))
+            return (_restore_object, (self.__datatype, tuple(self)))
 
     return Row
 
 
 def _create_row(fields, values):
     row = Row(*values)
-    row.__FIELDS__ = fields
+    row.__fields__ = fields
     return row
 
 
@@ -1183,7 +1184,7 @@ def __new__(self, *args, **kwargs):
             # create row objects
             names = sorted(kwargs.keys())
             row = tuple.__new__(self, [kwargs[n] for n in names])
-            row.__FIELDS__ = names
+            row.__fields__ = names
             return row
 
         else:
@@ -1193,11 +1194,11 @@ def asDict(self):
         """
         Return as an dict
         """
-        if not hasattr(self, "__FIELDS__"):
+        if not hasattr(self, "__fields__"):
             raise TypeError("Cannot convert a Row class into dict")
-        return dict(zip(self.__FIELDS__, self))
+        return dict(zip(self.__fields__, self))
 
-    # let obect acs like class
+    # let object acts like class
     def __call__(self, *args):
         """create new Row object"""
         return _create_row(self, args)
@@ -1208,21 +1209,21 @@ def __getattr__(self, item):
         try:
             # it will be slow when it has many fields,
             # but this will not be used in normal cases
-            idx = self.__FIELDS__.index(item)
+            idx = self.__fields__.index(item)
             return self[idx]
         except IndexError:
             raise AttributeError(item)
 
     def __reduce__(self):
-        if hasattr(self, "__FIELDS__"):
-            return (_create_row, (self.__FIELDS__, tuple(self)))
+        if hasattr(self, "__fields__"):
+            return (_create_row, (self.__fields__, tuple(self)))
         else:
             return tuple.__reduce__(self)
 
     def __repr__(self):
-        if hasattr(self, "__FIELDS__"):
+        if hasattr(self, "__fields__"):
             return "Row(%s)" % ", ".join("%s=%r" % (k, v)
-                                         for k, v in zip(self.__FIELDS__, self))
+                                         for k, v in zip(self.__fields__, tuple(self)))
         else:
             return "<Row(%s)>" % ", ".join(self)
 

From e9445b187e8f5c3703771b775e60164166309570 Mon Sep 17 00:00:00 2001
From: "Guancheng (G.C.) Chen" <chenguancheng@gmail.com>
Date: Sun, 12 Apr 2015 11:36:41 +0100
Subject: [PATCH 60/95] [SPARK-6866][Build] Remove duplicated dependency in
 launcher/pom.xml

JIRA: https://issues.apache.org/jira/browse/SPARK-6866

Remove duplicated dependency of scalatest in launcher/pom.xml since it already inherited the dependency from the parent pom.xml.

Author: Guancheng (G.C.) Chen <chenguancheng@gmail.com>

Closes #5476 from gchen/SPARK-6866 and squashes the following commits:

1ab484b [Guancheng (G.C.) Chen] remove duplicated dependency in launcher/pom.xml
---
 launcher/pom.xml | 5 -----
 1 file changed, 5 deletions(-)

diff --git a/launcher/pom.xml b/launcher/pom.xml
index 0fe2814135d88..182e5f60218db 100644
--- a/launcher/pom.xml
+++ b/launcher/pom.xml
@@ -52,11 +52,6 @@
       <artifactId>mockito-all</artifactId>
       <scope>test</scope>
     </dependency>
-    <dependency>
-      <groupId>org.scalatest</groupId>
-      <artifactId>scalatest_${scala.binary.version}</artifactId>
-      <scope>test</scope>
-    </dependency>
     <dependency>
       <groupId>org.slf4j</groupId>
       <artifactId>slf4j-api</artifactId>

From ddc17431a4108ab6efe0cd329d69e1f2fca5ac12 Mon Sep 17 00:00:00 2001
From: lisurprise <zhichao.li@intel.com>
Date: Sun, 12 Apr 2015 13:41:44 +0100
Subject: [PATCH 61/95] [SPARK-6843][core]Add volatile for the "state"

Fix potential visibility problem for the "state" of Executor

The field of "state" is shared and modified by multiple threads. i.e:

```scala
Within ExecutorRunner.scala

(1) workerThread = new Thread("ExecutorRunner for " + fullId) {
  override def run() { fetchAndRunExecutor() }
}
 workerThread.start()
// Shutdown hook that kills actors on shutdown.

(2)shutdownHook = new Thread() {
  override def run() {
    killProcess(Some("Worker shutting down"))
  }
}

(3)and also the "Actor thread" for worker.

```
I think we should at lease add volatile to ensure the visibility among threads otherwise the worker might send an out-of-date status to the master.

https://issues.apache.org/jira/browse/SPARK-6843

Author: lisurprise <zhichao.li@intel.com>

Closes #5448 from zhichao-li/state and squashes the following commits:

a2386e7 [lisurprise] add volatile for state field
---
 .../scala/org/apache/spark/deploy/worker/ExecutorRunner.scala   | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/core/src/main/scala/org/apache/spark/deploy/worker/ExecutorRunner.scala b/core/src/main/scala/org/apache/spark/deploy/worker/ExecutorRunner.scala
index 83e24a7a1f80c..7d5acabb95a48 100644
--- a/core/src/main/scala/org/apache/spark/deploy/worker/ExecutorRunner.scala
+++ b/core/src/main/scala/org/apache/spark/deploy/worker/ExecutorRunner.scala
@@ -50,7 +50,7 @@ private[deploy] class ExecutorRunner(
     val workerUrl: String,
     conf: SparkConf,
     val appLocalDirs: Seq[String],
-    var state: ExecutorState.Value)
+    @volatile var state: ExecutorState.Value)
   extends Logging {
 
   private val fullId = appId + "/" + execId

From 6ac8eea2fc6b782015236e4e7106e59d0d9e1b38 Mon Sep 17 00:00:00 2001
From: cody koeninger <cody@koeninger.org>
Date: Sun, 12 Apr 2015 17:37:30 +0100
Subject: [PATCH 62/95] [SPARK-6431][Streaming][Kafka] Error message for
 partition metadata requ...

...ests

The original reported problem was misdiagnosed; the topic just didn't exist yet.  Agreed upon solution was to improve error handling / message

Author: cody koeninger <cody@koeninger.org>

Closes #5454 from koeninger/spark-6431-master and squashes the following commits:

44300f8 [cody koeninger] [SPARK-6431][Streaming][Kafka] Error message for partition metadata requests
---
 .../spark/streaming/kafka/KafkaCluster.scala       | 14 +++++++++++---
 .../spark/streaming/kafka/KafkaClusterSuite.scala  |  3 +++
 2 files changed, 14 insertions(+), 3 deletions(-)

diff --git a/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaCluster.scala b/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaCluster.scala
index 2f7e0ab39fefd..bd767031c1849 100644
--- a/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaCluster.scala
+++ b/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaCluster.scala
@@ -123,9 +123,17 @@ class KafkaCluster(val kafkaParams: Map[String, String]) extends Serializable {
     val errs = new Err
     withBrokers(Random.shuffle(config.seedBrokers), errs) { consumer =>
       val resp: TopicMetadataResponse = consumer.send(req)
-      // error codes here indicate missing / just created topic,
-      // repeating on a different broker wont be useful
-      return Right(resp.topicsMetadata.toSet)
+      val respErrs = resp.topicsMetadata.filter(m => m.errorCode != ErrorMapping.NoError)
+
+      if (respErrs.isEmpty) {
+        return Right(resp.topicsMetadata.toSet)
+      } else {
+        respErrs.foreach { m =>
+          val cause = ErrorMapping.exceptionFor(m.errorCode)
+          val msg = s"Error getting partition metadata for '${m.topic}'. Does the topic exist?"
+          errs.append(new SparkException(msg, cause))
+        }
+      }
     }
     Left(errs)
   }
diff --git a/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaClusterSuite.scala b/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaClusterSuite.scala
index 2b33d2a220b2b..7fb841b79cb65 100644
--- a/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaClusterSuite.scala
+++ b/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaClusterSuite.scala
@@ -52,6 +52,9 @@ class KafkaClusterSuite extends FunSuite with BeforeAndAfterAll {
 
     val parts = kc.getPartitions(Set(topic)).right.get
     assert(parts(topicAndPartition), "didn't get partitions")
+
+    val err = kc.getPartitions(Set(topic + "BAD"))
+    assert(err.isLeft, "getPartitions for a nonexistant topic should be an error")
   }
 
   test("leader offset apis") {

From 04bcd67cfc50f847559a9ff59a31aa93028b3628 Mon Sep 17 00:00:00 2001
From: Daoyuan Wang <daoyuan.wang@intel.com>
Date: Sun, 12 Apr 2015 18:58:53 +0100
Subject: [PATCH 63/95] [MINOR] a typo: coalesce

Author: Daoyuan Wang <daoyuan.wang@intel.com>

Closes #5482 from adrian-wang/typo and squashes the following commits:

e65ef6f [Daoyuan Wang] typo
---
 .../org/apache/spark/sql/execution/GeneratedAggregate.scala     | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
index 3c58e93b45e9d..95176e425132d 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
@@ -97,7 +97,7 @@ case class GeneratedAggregate(
         val currentSum = AttributeReference("currentSum", calcType, nullable = true)()
         val initialValue = Literal.create(null, calcType)
 
-        // Coalasce avoids double calculation...
+        // Coalesce avoids double calculation...
         // but really, common sub expression elimination would be better....
         val zero = Cast(Literal(0), calcType)
         val updateFunction = Coalesce(

From a1fe59dae50f551d02dd18676308eca054ff6b07 Mon Sep 17 00:00:00 2001
From: Reynold Xin <rxin@databricks.com>
Date: Sun, 12 Apr 2015 20:50:49 -0700
Subject: [PATCH 64/95] [SPARK-6765] Fix test code style for core.

Author: Reynold Xin <rxin@databricks.com>

Closes #5484 from rxin/test-style-core and squashes the following commits:

e0b0100 [Reynold Xin] [SPARK-6765] Fix test code style for core.
---
 .../org/apache/spark/AccumulatorSuite.scala   |  30 ++---
 .../org/apache/spark/CacheManagerSuite.scala  |   7 +-
 .../org/apache/spark/CheckpointSuite.scala    |  15 ++-
 .../apache/spark/ContextCleanerSuite.scala    |   4 +-
 .../scala/org/apache/spark/FileSuite.scala    |  26 +++--
 .../apache/spark/ImplicitOrderingSuite.scala  |   6 +-
 .../apache/spark/JobCancellationSuite.scala   |   2 +-
 .../org/apache/spark/LocalSparkContext.scala  |   4 +-
 .../org/apache/spark/PartitioningSuite.scala  |  30 ++---
 .../org/apache/spark/SSLOptionsSuite.scala    |  15 ++-
 .../org/apache/spark/SSLSampleConfigs.scala   |   7 +-
 .../scala/org/apache/spark/ShuffleSuite.scala |   8 +-
 .../org/apache/spark/SparkContextSuite.scala  |   6 +-
 .../org/apache/spark/StatusTrackerSuite.scala |   5 +-
 .../spark/broadcast/BroadcastSuite.scala      |   2 +-
 .../spark/deploy/JsonProtocolSuite.scala      |   6 +-
 .../spark/deploy/LogUrlsStandaloneSuite.scala |   2 +-
 .../deploy/history/HistoryServerSuite.scala   |   4 +-
 .../rest/StandaloneRestSubmitSuite.scala      |   4 +-
 .../deploy/rest/SubmitRestProtocolSuite.scala |   3 +-
 .../deploy/worker/ExecutorRunnerTest.scala    |   3 +-
 .../deploy/worker/WorkerArgumentsTest.scala   |   4 +-
 .../spark/deploy/worker/WorkerSuite.scala     |   6 +-
 .../metrics/InputOutputMetricsSuite.scala     |   2 +-
 .../spark/metrics/MetricsConfigSuite.scala    |  15 ++-
 .../org/apache/spark/rdd/JdbcRDDSuite.scala   |   4 +-
 .../spark/rdd/PairRDDFunctionsSuite.scala     |  41 +++----
 .../rdd/ParallelCollectionSplitSuite.scala    |  20 ++--
 .../spark/rdd/PartitionPruningRDDSuite.scala  |   7 +-
 .../rdd/PartitionwiseSampledRDDSuite.scala    |   2 +-
 .../scala/org/apache/spark/rdd/RDDSuite.scala |  22 ++--
 .../org/apache/spark/rdd/RDDSuiteUtils.scala  |   4 +-
 .../org/apache/spark/rpc/RpcEnvSuite.scala    |  40 +++----
 .../spark/scheduler/DAGSchedulerSuite.scala   | 103 ++++++++++--------
 .../scheduler/EventLoggingListenerSuite.scala |   4 +-
 .../scheduler/NotSerializableFakeTask.scala   |   4 +-
 .../spark/scheduler/SparkListenerSuite.scala  |  21 ++--
 .../scheduler/TaskSchedulerImplSuite.scala    |  10 +-
 .../spark/scheduler/TaskSetManagerSuite.scala |  26 +++--
 .../mesos/MesosSchedulerBackendSuite.scala    |  14 ++-
 .../serializer/KryoSerializerSuite.scala      |  15 ++-
 .../ProactiveClosureSerializationSuite.scala  |   8 +-
 .../spark/serializer/TestSerializer.scala     |   5 +-
 .../hash/HashShuffleManagerSuite.scala        |   4 +-
 .../spark/storage/BlockManagerSuite.scala     |  32 +++---
 .../apache/spark/storage/LocalDirsSuite.scala |   2 +-
 .../org/apache/spark/ui/UISeleniumSuite.scala |   2 +-
 .../ui/jobs/JobProgressListenerSuite.scala    |   4 +-
 .../spark/ui/storage/StorageTabSuite.scala    |   3 +-
 .../spark/util/ClosureCleanerSuite.scala      |   6 +-
 .../apache/spark/util/FileAppenderSuite.scala |  13 ++-
 .../apache/spark/util/NextIteratorSuite.scala |   2 +-
 .../spark/util/SizeEstimatorSuite.scala       |   6 +-
 .../spark/util/TimeStampedHashMapSuite.scala  |   4 +-
 .../org/apache/spark/util/UtilsSuite.scala    |   5 +-
 .../org/apache/spark/util/VectorSuite.scala   |   2 +-
 .../ExternalAppendOnlyMapSuite.scala          |   2 +-
 .../util/collection/ExternalSorterSuite.scala |  35 +++---
 .../util/random/XORShiftRandomSuite.scala     |   2 +-
 59 files changed, 386 insertions(+), 304 deletions(-)

diff --git a/core/src/test/scala/org/apache/spark/AccumulatorSuite.scala b/core/src/test/scala/org/apache/spark/AccumulatorSuite.scala
index bd0f8bdefa171..75399461f2a5f 100644
--- a/core/src/test/scala/org/apache/spark/AccumulatorSuite.scala
+++ b/core/src/test/scala/org/apache/spark/AccumulatorSuite.scala
@@ -27,19 +27,20 @@ import org.scalatest.Matchers
 class AccumulatorSuite extends FunSuite with Matchers with LocalSparkContext {
 
 
-  implicit def setAccum[A] = new AccumulableParam[mutable.Set[A], A] {
-    def addInPlace(t1: mutable.Set[A], t2: mutable.Set[A]) : mutable.Set[A] = {
-      t1 ++= t2
-      t1
-    }
-    def addAccumulator(t1: mutable.Set[A], t2: A) : mutable.Set[A] = {
-      t1 += t2
-      t1
-    }
-    def zero(t: mutable.Set[A]) : mutable.Set[A] = {
-      new mutable.HashSet[A]()
+  implicit def setAccum[A]: AccumulableParam[mutable.Set[A], A] =
+    new AccumulableParam[mutable.Set[A], A] {
+      def addInPlace(t1: mutable.Set[A], t2: mutable.Set[A]) : mutable.Set[A] = {
+        t1 ++= t2
+        t1
+      }
+      def addAccumulator(t1: mutable.Set[A], t2: A) : mutable.Set[A] = {
+        t1 += t2
+        t1
+      }
+      def zero(t: mutable.Set[A]) : mutable.Set[A] = {
+        new mutable.HashSet[A]()
+      }
     }
-  }
 
   test ("basic accumulation"){
     sc = new SparkContext("local", "test")
@@ -49,11 +50,10 @@ class AccumulatorSuite extends FunSuite with Matchers with LocalSparkContext {
     d.foreach{x => acc += x}
     acc.value should be (210)
 
-
-    val longAcc = sc.accumulator(0l)
+    val longAcc = sc.accumulator(0L)
     val maxInt = Integer.MAX_VALUE.toLong
     d.foreach{x => longAcc += maxInt + x}
-    longAcc.value should be (210l + maxInt * 20)
+    longAcc.value should be (210L + maxInt * 20)
   }
 
   test ("value not assignable from tasks") {
diff --git a/core/src/test/scala/org/apache/spark/CacheManagerSuite.scala b/core/src/test/scala/org/apache/spark/CacheManagerSuite.scala
index 4b25c200a695a..70529d9216591 100644
--- a/core/src/test/scala/org/apache/spark/CacheManagerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/CacheManagerSuite.scala
@@ -45,16 +45,17 @@ class CacheManagerSuite extends FunSuite with LocalSparkContext with BeforeAndAf
     rdd = new RDD[Int](sc, Nil) {
       override def getPartitions: Array[Partition] = Array(split)
       override val getDependencies = List[Dependency[_]]()
-      override def compute(split: Partition, context: TaskContext) = Array(1, 2, 3, 4).iterator
+      override def compute(split: Partition, context: TaskContext): Iterator[Int] =
+        Array(1, 2, 3, 4).iterator
     }
     rdd2 = new RDD[Int](sc, List(new OneToOneDependency(rdd))) {
       override def getPartitions: Array[Partition] = firstParent[Int].partitions
-      override def compute(split: Partition, context: TaskContext) =
+      override def compute(split: Partition, context: TaskContext): Iterator[Int] =
         firstParent[Int].iterator(split, context)
     }.cache()
     rdd3 = new RDD[Int](sc, List(new OneToOneDependency(rdd2))) {
       override def getPartitions: Array[Partition] = firstParent[Int].partitions
-      override def compute(split: Partition, context: TaskContext) =
+      override def compute(split: Partition, context: TaskContext): Iterator[Int] =
         firstParent[Int].iterator(split, context)
     }.cache()
   }
diff --git a/core/src/test/scala/org/apache/spark/CheckpointSuite.scala b/core/src/test/scala/org/apache/spark/CheckpointSuite.scala
index 32abc65385267..e1faddeabec79 100644
--- a/core/src/test/scala/org/apache/spark/CheckpointSuite.scala
+++ b/core/src/test/scala/org/apache/spark/CheckpointSuite.scala
@@ -75,7 +75,8 @@ class CheckpointSuite extends FunSuite with LocalSparkContext with Logging {
     assert(sc.checkpointFile[Int](parCollection.getCheckpointFile.get).collect() === result)
     assert(parCollection.dependencies != Nil)
     assert(parCollection.partitions.length === numPartitions)
-    assert(parCollection.partitions.toList === parCollection.checkpointData.get.getPartitions.toList)
+    assert(parCollection.partitions.toList ===
+      parCollection.checkpointData.get.getPartitions.toList)
     assert(parCollection.collect() === result)
   }
 
@@ -102,13 +103,13 @@ class CheckpointSuite extends FunSuite with LocalSparkContext with Logging {
   }
 
   test("UnionRDD") {
-    def otherRDD = sc.makeRDD(1 to 10, 1)
+    def otherRDD: RDD[Int] = sc.makeRDD(1 to 10, 1)
     testRDD(_.union(otherRDD))
     testRDDPartitions(_.union(otherRDD))
   }
 
   test("CartesianRDD") {
-    def otherRDD = sc.makeRDD(1 to 10, 1)
+    def otherRDD: RDD[Int] = sc.makeRDD(1 to 10, 1)
     testRDD(new CartesianRDD(sc, _, otherRDD))
     testRDDPartitions(new CartesianRDD(sc, _, otherRDD))
 
@@ -223,7 +224,8 @@ class CheckpointSuite extends FunSuite with LocalSparkContext with Logging {
     val partitionAfterCheckpoint =  serializeDeserialize(
       unionRDD.partitions.head.asInstanceOf[PartitionerAwareUnionRDDPartition])
     assert(
-      partitionBeforeCheckpoint.parents.head.getClass != partitionAfterCheckpoint.parents.head.getClass,
+      partitionBeforeCheckpoint.parents.head.getClass !=
+        partitionAfterCheckpoint.parents.head.getClass,
       "PartitionerAwareUnionRDDPartition.parents not updated after parent RDD is checkpointed"
     )
   }
@@ -358,7 +360,7 @@ class CheckpointSuite extends FunSuite with LocalSparkContext with Logging {
    * Generate an pair RDD (with partitioner) such that both the RDD and its partitions
    * have large size.
    */
-  def generateFatPairRDD() = {
+  def generateFatPairRDD(): RDD[(Int, Int)] = {
     new FatPairRDD(sc.makeRDD(1 to 100, 4), partitioner).mapValues(x => x)
   }
 
@@ -445,7 +447,8 @@ class FatPairRDD(parent: RDD[Int], _partitioner: Partitioner) extends RDD[(Int,
 object CheckpointSuite {
   // This is a custom cogroup function that does not use mapValues like
   // the PairRDDFunctions.cogroup()
-  def cogroup[K, V](first: RDD[(K, V)], second: RDD[(K, V)], part: Partitioner) = {
+  def cogroup[K, V](first: RDD[(K, V)], second: RDD[(K, V)], part: Partitioner)
+    : RDD[(K, Array[Iterable[V]])] = {
     new CoGroupedRDD[K](
       Seq(first.asInstanceOf[RDD[(K, _)]], second.asInstanceOf[RDD[(K, _)]]),
       part
diff --git a/core/src/test/scala/org/apache/spark/ContextCleanerSuite.scala b/core/src/test/scala/org/apache/spark/ContextCleanerSuite.scala
index cdfaacee7da40..1de169d964d23 100644
--- a/core/src/test/scala/org/apache/spark/ContextCleanerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/ContextCleanerSuite.scala
@@ -64,7 +64,7 @@ abstract class ContextCleanerSuiteBase(val shuffleManager: Class[_] = classOf[Ha
     }
   }
 
-  //------ Helper functions ------
+  // ------ Helper functions ------
 
   protected def newRDD() = sc.makeRDD(1 to 10)
   protected def newPairRDD() = newRDD().map(_ -> 1)
@@ -370,7 +370,7 @@ class CleanerTester(
   val cleanerListener = new CleanerListener {
     def rddCleaned(rddId: Int): Unit = {
       toBeCleanedRDDIds -= rddId
-      logInfo("RDD "+ rddId + " cleaned")
+      logInfo("RDD " + rddId + " cleaned")
     }
 
     def shuffleCleaned(shuffleId: Int): Unit = {
diff --git a/core/src/test/scala/org/apache/spark/FileSuite.scala b/core/src/test/scala/org/apache/spark/FileSuite.scala
index 7acd27c735727..c8f08eed47c76 100644
--- a/core/src/test/scala/org/apache/spark/FileSuite.scala
+++ b/core/src/test/scala/org/apache/spark/FileSuite.scala
@@ -222,7 +222,7 @@ class FileSuite extends FunSuite with LocalSparkContext {
     val nums = sc.makeRDD(1 to 3).map(x => (new IntWritable(x), new Text("a" * x)))
     nums.saveAsSequenceFile(outputDir)
     val output =
-        sc.newAPIHadoopFile[IntWritable, Text, SequenceFileInputFormat[IntWritable, Text]](outputDir)
+      sc.newAPIHadoopFile[IntWritable, Text, SequenceFileInputFormat[IntWritable, Text]](outputDir)
     assert(output.map(_.toString).collect().toList === List("(1,a)", "(2,aa)", "(3,aaa)"))
   }
 
@@ -451,7 +451,8 @@ class FileSuite extends FunSuite with LocalSparkContext {
 
   test ("prevent user from overwriting the empty directory (new Hadoop API)") {
     sc = new SparkContext("local", "test")
-    val randomRDD = sc.parallelize(Array(("key1", "a"), ("key2", "a"), ("key3", "b"), ("key4", "c")), 1)
+    val randomRDD = sc.parallelize(
+      Array(("key1", "a"), ("key2", "a"), ("key3", "b"), ("key4", "c")), 1)
     intercept[FileAlreadyExistsException] {
       randomRDD.saveAsNewAPIHadoopFile[NewTextOutputFormat[String, String]](tempDir.getPath)
     }
@@ -459,8 +460,10 @@ class FileSuite extends FunSuite with LocalSparkContext {
 
   test ("prevent user from overwriting the non-empty directory (new Hadoop API)") {
     sc = new SparkContext("local", "test")
-    val randomRDD = sc.parallelize(Array(("key1", "a"), ("key2", "a"), ("key3", "b"), ("key4", "c")), 1)
-    randomRDD.saveAsNewAPIHadoopFile[NewTextOutputFormat[String, String]](tempDir.getPath + "/output")
+    val randomRDD = sc.parallelize(
+      Array(("key1", "a"), ("key2", "a"), ("key3", "b"), ("key4", "c")), 1)
+    randomRDD.saveAsNewAPIHadoopFile[NewTextOutputFormat[String, String]](
+      tempDir.getPath + "/output")
     assert(new File(tempDir.getPath + "/output/part-r-00000").exists() === true)
     intercept[FileAlreadyExistsException] {
       randomRDD.saveAsNewAPIHadoopFile[NewTextOutputFormat[String, String]](tempDir.getPath)
@@ -471,16 +474,20 @@ class FileSuite extends FunSuite with LocalSparkContext {
     val sf = new SparkConf()
     sf.setAppName("test").setMaster("local").set("spark.hadoop.validateOutputSpecs", "false")
     sc = new SparkContext(sf)
-    val randomRDD = sc.parallelize(Array(("key1", "a"), ("key2", "a"), ("key3", "b"), ("key4", "c")), 1)
-    randomRDD.saveAsNewAPIHadoopFile[NewTextOutputFormat[String, String]](tempDir.getPath + "/output")
+    val randomRDD = sc.parallelize(
+      Array(("key1", "a"), ("key2", "a"), ("key3", "b"), ("key4", "c")), 1)
+    randomRDD.saveAsNewAPIHadoopFile[NewTextOutputFormat[String, String]](
+      tempDir.getPath + "/output")
     assert(new File(tempDir.getPath + "/output/part-r-00000").exists() === true)
-    randomRDD.saveAsNewAPIHadoopFile[NewTextOutputFormat[String, String]](tempDir.getPath + "/output")
+    randomRDD.saveAsNewAPIHadoopFile[NewTextOutputFormat[String, String]](
+      tempDir.getPath + "/output")
     assert(new File(tempDir.getPath + "/output/part-r-00000").exists() === true)
   }
 
   test ("save Hadoop Dataset through old Hadoop API") {
     sc = new SparkContext("local", "test")
-    val randomRDD = sc.parallelize(Array(("key1", "a"), ("key2", "a"), ("key3", "b"), ("key4", "c")), 1)
+    val randomRDD = sc.parallelize(
+      Array(("key1", "a"), ("key2", "a"), ("key3", "b"), ("key4", "c")), 1)
     val job = new JobConf()
     job.setOutputKeyClass(classOf[String])
     job.setOutputValueClass(classOf[String])
@@ -492,7 +499,8 @@ class FileSuite extends FunSuite with LocalSparkContext {
 
   test ("save Hadoop Dataset through new Hadoop API") {
     sc = new SparkContext("local", "test")
-    val randomRDD = sc.parallelize(Array(("key1", "a"), ("key2", "a"), ("key3", "b"), ("key4", "c")), 1)
+    val randomRDD = sc.parallelize(
+      Array(("key1", "a"), ("key2", "a"), ("key3", "b"), ("key4", "c")), 1)
     val job = new Job(sc.hadoopConfiguration)
     job.setOutputKeyClass(classOf[String])
     job.setOutputValueClass(classOf[String])
diff --git a/core/src/test/scala/org/apache/spark/ImplicitOrderingSuite.scala b/core/src/test/scala/org/apache/spark/ImplicitOrderingSuite.scala
index d895230ecf330..51348c039b5c9 100644
--- a/core/src/test/scala/org/apache/spark/ImplicitOrderingSuite.scala
+++ b/core/src/test/scala/org/apache/spark/ImplicitOrderingSuite.scala
@@ -51,7 +51,7 @@ private object ImplicitOrderingSuite {
     override def compare(o: OrderedClass): Int = ???
   }
   
-  def basicMapExpectations(rdd: RDD[Int]) = {
+  def basicMapExpectations(rdd: RDD[Int]): List[(Boolean, String)] = {
     List((rdd.map(x => (x, x)).keyOrdering.isDefined, 
             "rdd.map(x => (x, x)).keyOrdering.isDefined"),
           (rdd.map(x => (1, x)).keyOrdering.isDefined, 
@@ -68,7 +68,7 @@ private object ImplicitOrderingSuite {
             "rdd.map(x => (new OrderedClass, x)).keyOrdering.isDefined"))
   }
   
-  def otherRDDMethodExpectations(rdd: RDD[Int]) = {
+  def otherRDDMethodExpectations(rdd: RDD[Int]): List[(Boolean, String)] = {
     List((rdd.groupBy(x => x).keyOrdering.isDefined, 
            "rdd.groupBy(x => x).keyOrdering.isDefined"),
          (rdd.groupBy(x => new NonOrderedClass).keyOrdering.isEmpty, 
@@ -82,4 +82,4 @@ private object ImplicitOrderingSuite {
          (rdd.groupBy((x: Int) => x, new HashPartitioner(5)).keyOrdering.isDefined,
            "rdd.groupBy((x: Int) => x, new HashPartitioner(5)).keyOrdering.isDefined"))
   }
-}
\ No newline at end of file
+}
diff --git a/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala b/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala
index 21487bc24d58a..4d3e09793faff 100644
--- a/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala
+++ b/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala
@@ -188,7 +188,7 @@ class JobCancellationSuite extends FunSuite with Matchers with BeforeAndAfter
     val rdd = sc.parallelize(1 to 10, 2).map { i =>
       JobCancellationSuite.twoJobsSharingStageSemaphore.acquire()
       (i, i)
-    }.reduceByKey(_+_)
+    }.reduceByKey(_ + _)
     val f1 = rdd.collectAsync()
     val f2 = rdd.countAsync()
 
diff --git a/core/src/test/scala/org/apache/spark/LocalSparkContext.scala b/core/src/test/scala/org/apache/spark/LocalSparkContext.scala
index 53e367a61715b..8bf2e55defd02 100644
--- a/core/src/test/scala/org/apache/spark/LocalSparkContext.scala
+++ b/core/src/test/scala/org/apache/spark/LocalSparkContext.scala
@@ -37,7 +37,7 @@ trait LocalSparkContext extends BeforeAndAfterEach with BeforeAndAfterAll { self
     super.afterEach()
   }
 
-  def resetSparkContext() = {
+  def resetSparkContext(): Unit = {
     LocalSparkContext.stop(sc)
     sc = null
   }
@@ -54,7 +54,7 @@ object LocalSparkContext {
   }
 
   /** Runs `f` by passing in `sc` and ensures that `sc` is stopped. */
-  def withSpark[T](sc: SparkContext)(f: SparkContext => T) = {
+  def withSpark[T](sc: SparkContext)(f: SparkContext => T): T = {
     try {
       f(sc)
     } finally {
diff --git a/core/src/test/scala/org/apache/spark/PartitioningSuite.scala b/core/src/test/scala/org/apache/spark/PartitioningSuite.scala
index b7532314ada01..47e3bf6e1ac41 100644
--- a/core/src/test/scala/org/apache/spark/PartitioningSuite.scala
+++ b/core/src/test/scala/org/apache/spark/PartitioningSuite.scala
@@ -92,7 +92,7 @@ class PartitioningSuite extends FunSuite with SharedSparkContext with PrivateMet
   test("RangePartitioner for keys that are not Comparable (but with Ordering)") {
     // Row does not extend Comparable, but has an implicit Ordering defined.
     implicit object RowOrdering extends Ordering[Row] {
-      override def compare(x: Row, y: Row) = x.value - y.value
+      override def compare(x: Row, y: Row): Int = x.value - y.value
     }
 
     val rdd = sc.parallelize(1 to 4500).map(x => (Row(x), Row(x)))
@@ -212,20 +212,24 @@ class PartitioningSuite extends FunSuite with SharedSparkContext with PrivateMet
     val arrPairs: RDD[(Array[Int], Int)] =
       sc.parallelize(Array(1, 2, 3, 4), 2).map(x => (Array(x), x))
 
-    assert(intercept[SparkException]{ arrs.distinct() }.getMessage.contains("array"))
+    def verify(testFun: => Unit): Unit = {
+      intercept[SparkException](testFun).getMessage.contains("array")
+    }
+
+    verify(arrs.distinct())
     // We can't catch all usages of arrays, since they might occur inside other collections:
     // assert(fails { arrPairs.distinct() })
-    assert(intercept[SparkException]{ arrPairs.partitionBy(new HashPartitioner(2)) }.getMessage.contains("array"))
-    assert(intercept[SparkException]{ arrPairs.join(arrPairs) }.getMessage.contains("array"))
-    assert(intercept[SparkException]{ arrPairs.leftOuterJoin(arrPairs) }.getMessage.contains("array"))
-    assert(intercept[SparkException]{ arrPairs.rightOuterJoin(arrPairs) }.getMessage.contains("array"))
-    assert(intercept[SparkException]{ arrPairs.fullOuterJoin(arrPairs) }.getMessage.contains("array"))
-    assert(intercept[SparkException]{ arrPairs.groupByKey() }.getMessage.contains("array"))
-    assert(intercept[SparkException]{ arrPairs.countByKey() }.getMessage.contains("array"))
-    assert(intercept[SparkException]{ arrPairs.countByKeyApprox(1) }.getMessage.contains("array"))
-    assert(intercept[SparkException]{ arrPairs.cogroup(arrPairs) }.getMessage.contains("array"))
-    assert(intercept[SparkException]{ arrPairs.reduceByKeyLocally(_ + _) }.getMessage.contains("array"))
-    assert(intercept[SparkException]{ arrPairs.reduceByKey(_ + _) }.getMessage.contains("array"))
+    verify(arrPairs.partitionBy(new HashPartitioner(2)))
+    verify(arrPairs.join(arrPairs))
+    verify(arrPairs.leftOuterJoin(arrPairs))
+    verify(arrPairs.rightOuterJoin(arrPairs))
+    verify(arrPairs.fullOuterJoin(arrPairs))
+    verify(arrPairs.groupByKey())
+    verify(arrPairs.countByKey())
+    verify(arrPairs.countByKeyApprox(1))
+    verify(arrPairs.cogroup(arrPairs))
+    verify(arrPairs.reduceByKeyLocally(_ + _))
+    verify(arrPairs.reduceByKey(_ + _))
   }
 
   test("zero-length partitions should be correctly handled") {
diff --git a/core/src/test/scala/org/apache/spark/SSLOptionsSuite.scala b/core/src/test/scala/org/apache/spark/SSLOptionsSuite.scala
index 444a33371bd71..93f46ef11c0e2 100644
--- a/core/src/test/scala/org/apache/spark/SSLOptionsSuite.scala
+++ b/core/src/test/scala/org/apache/spark/SSLOptionsSuite.scala
@@ -36,7 +36,8 @@ class SSLOptionsSuite extends FunSuite with BeforeAndAfterAll {
     conf.set("spark.ssl.keyPassword", "password")
     conf.set("spark.ssl.trustStore", trustStorePath)
     conf.set("spark.ssl.trustStorePassword", "password")
-    conf.set("spark.ssl.enabledAlgorithms", "TLS_RSA_WITH_AES_128_CBC_SHA, TLS_RSA_WITH_AES_256_CBC_SHA")
+    conf.set("spark.ssl.enabledAlgorithms",
+      "TLS_RSA_WITH_AES_128_CBC_SHA, TLS_RSA_WITH_AES_256_CBC_SHA")
     conf.set("spark.ssl.protocol", "SSLv3")
 
     val opts = SSLOptions.parse(conf, "spark.ssl")
@@ -52,7 +53,8 @@ class SSLOptionsSuite extends FunSuite with BeforeAndAfterAll {
     assert(opts.keyStorePassword === Some("password"))
     assert(opts.keyPassword === Some("password"))
     assert(opts.protocol === Some("SSLv3"))
-    assert(opts.enabledAlgorithms === Set("TLS_RSA_WITH_AES_128_CBC_SHA", "TLS_RSA_WITH_AES_256_CBC_SHA"))
+    assert(opts.enabledAlgorithms ===
+      Set("TLS_RSA_WITH_AES_128_CBC_SHA", "TLS_RSA_WITH_AES_256_CBC_SHA"))
   }
 
   test("test resolving property with defaults specified ") {
@@ -66,7 +68,8 @@ class SSLOptionsSuite extends FunSuite with BeforeAndAfterAll {
     conf.set("spark.ssl.keyPassword", "password")
     conf.set("spark.ssl.trustStore", trustStorePath)
     conf.set("spark.ssl.trustStorePassword", "password")
-    conf.set("spark.ssl.enabledAlgorithms", "TLS_RSA_WITH_AES_128_CBC_SHA, TLS_RSA_WITH_AES_256_CBC_SHA")
+    conf.set("spark.ssl.enabledAlgorithms",
+      "TLS_RSA_WITH_AES_128_CBC_SHA, TLS_RSA_WITH_AES_256_CBC_SHA")
     conf.set("spark.ssl.protocol", "SSLv3")
 
     val defaultOpts = SSLOptions.parse(conf, "spark.ssl", defaults = None)
@@ -83,7 +86,8 @@ class SSLOptionsSuite extends FunSuite with BeforeAndAfterAll {
     assert(opts.keyStorePassword === Some("password"))
     assert(opts.keyPassword === Some("password"))
     assert(opts.protocol === Some("SSLv3"))
-    assert(opts.enabledAlgorithms === Set("TLS_RSA_WITH_AES_128_CBC_SHA", "TLS_RSA_WITH_AES_256_CBC_SHA"))
+    assert(opts.enabledAlgorithms ===
+      Set("TLS_RSA_WITH_AES_128_CBC_SHA", "TLS_RSA_WITH_AES_256_CBC_SHA"))
   }
 
   test("test whether defaults can be overridden ") {
@@ -99,7 +103,8 @@ class SSLOptionsSuite extends FunSuite with BeforeAndAfterAll {
     conf.set("spark.ssl.keyPassword", "password")
     conf.set("spark.ssl.trustStore", trustStorePath)
     conf.set("spark.ssl.trustStorePassword", "password")
-    conf.set("spark.ssl.enabledAlgorithms", "TLS_RSA_WITH_AES_128_CBC_SHA, TLS_RSA_WITH_AES_256_CBC_SHA")
+    conf.set("spark.ssl.enabledAlgorithms",
+      "TLS_RSA_WITH_AES_128_CBC_SHA, TLS_RSA_WITH_AES_256_CBC_SHA")
     conf.set("spark.ui.ssl.enabledAlgorithms", "ABC, DEF")
     conf.set("spark.ssl.protocol", "SSLv3")
 
diff --git a/core/src/test/scala/org/apache/spark/SSLSampleConfigs.scala b/core/src/test/scala/org/apache/spark/SSLSampleConfigs.scala
index ace8123a8961f..308b9ea17708d 100644
--- a/core/src/test/scala/org/apache/spark/SSLSampleConfigs.scala
+++ b/core/src/test/scala/org/apache/spark/SSLSampleConfigs.scala
@@ -21,10 +21,11 @@ import java.io.File
 
 object SSLSampleConfigs {
   val keyStorePath = new File(this.getClass.getResource("/keystore").toURI).getAbsolutePath
-  val untrustedKeyStorePath = new File(this.getClass.getResource("/untrusted-keystore").toURI).getAbsolutePath
+  val untrustedKeyStorePath = new File(
+    this.getClass.getResource("/untrusted-keystore").toURI).getAbsolutePath
   val trustStorePath = new File(this.getClass.getResource("/truststore").toURI).getAbsolutePath
 
-  def sparkSSLConfig() = {
+  def sparkSSLConfig(): SparkConf = {
     val conf = new SparkConf(loadDefaults = false)
     conf.set("spark.ssl.enabled", "true")
     conf.set("spark.ssl.keyStore", keyStorePath)
@@ -38,7 +39,7 @@ object SSLSampleConfigs {
     conf
   }
 
-  def sparkSSLConfigUntrusted() = {
+  def sparkSSLConfigUntrusted(): SparkConf = {
     val conf = new SparkConf(loadDefaults = false)
     conf.set("spark.ssl.enabled", "true")
     conf.set("spark.ssl.keyStore", untrustedKeyStorePath)
diff --git a/core/src/test/scala/org/apache/spark/ShuffleSuite.scala b/core/src/test/scala/org/apache/spark/ShuffleSuite.scala
index 30b6184c77839..d7180516029d5 100644
--- a/core/src/test/scala/org/apache/spark/ShuffleSuite.scala
+++ b/core/src/test/scala/org/apache/spark/ShuffleSuite.scala
@@ -142,7 +142,7 @@ abstract class ShuffleSuite extends FunSuite with Matchers with LocalSparkContex
   test("shuffle on mutable pairs") {
     // Use a local cluster with 2 processes to make sure there are both local and remote blocks
     sc = new SparkContext("local-cluster[2,1,512]", "test", conf)
-    def p[T1, T2](_1: T1, _2: T2) = MutablePair(_1, _2)
+    def p[T1, T2](_1: T1, _2: T2): MutablePair[T1, T2] = MutablePair(_1, _2)
     val data = Array(p(1, 1), p(1, 2), p(1, 3), p(2, 1))
     val pairs: RDD[MutablePair[Int, Int]] = sc.parallelize(data, 2)
     val results = new ShuffledRDD[Int, Int, Int](pairs,
@@ -155,7 +155,7 @@ abstract class ShuffleSuite extends FunSuite with Matchers with LocalSparkContex
     // This is not in SortingSuite because of the local cluster setup.
     // Use a local cluster with 2 processes to make sure there are both local and remote blocks
     sc = new SparkContext("local-cluster[2,1,512]", "test", conf)
-    def p[T1, T2](_1: T1, _2: T2) = MutablePair(_1, _2)
+    def p[T1, T2](_1: T1, _2: T2): MutablePair[T1, T2] = MutablePair(_1, _2)
     val data = Array(p(1, 11), p(3, 33), p(100, 100), p(2, 22))
     val pairs: RDD[MutablePair[Int, Int]] = sc.parallelize(data, 2)
     val results = new OrderedRDDFunctions[Int, Int, MutablePair[Int, Int]](pairs)
@@ -169,7 +169,7 @@ abstract class ShuffleSuite extends FunSuite with Matchers with LocalSparkContex
   test("cogroup using mutable pairs") {
     // Use a local cluster with 2 processes to make sure there are both local and remote blocks
     sc = new SparkContext("local-cluster[2,1,512]", "test", conf)
-    def p[T1, T2](_1: T1, _2: T2) = MutablePair(_1, _2)
+    def p[T1, T2](_1: T1, _2: T2): MutablePair[T1, T2] = MutablePair(_1, _2)
     val data1 = Seq(p(1, 1), p(1, 2), p(1, 3), p(2, 1))
     val data2 = Seq(p(1, "11"), p(1, "12"), p(2, "22"), p(3, "3"))
     val pairs1: RDD[MutablePair[Int, Int]] = sc.parallelize(data1, 2)
@@ -196,7 +196,7 @@ abstract class ShuffleSuite extends FunSuite with Matchers with LocalSparkContex
   test("subtract mutable pairs") {
     // Use a local cluster with 2 processes to make sure there are both local and remote blocks
     sc = new SparkContext("local-cluster[2,1,512]", "test", conf)
-    def p[T1, T2](_1: T1, _2: T2) = MutablePair(_1, _2)
+    def p[T1, T2](_1: T1, _2: T2): MutablePair[T1, T2] = MutablePair(_1, _2)
     val data1 = Seq(p(1, 1), p(1, 2), p(1, 3), p(2, 1), p(3, 33))
     val data2 = Seq(p(1, "11"), p(1, "12"), p(2, "22"))
     val pairs1: RDD[MutablePair[Int, Int]] = sc.parallelize(data1, 2)
diff --git a/core/src/test/scala/org/apache/spark/SparkContextSuite.scala b/core/src/test/scala/org/apache/spark/SparkContextSuite.scala
index c7301a30d8b11..94be1c6d6397c 100644
--- a/core/src/test/scala/org/apache/spark/SparkContextSuite.scala
+++ b/core/src/test/scala/org/apache/spark/SparkContextSuite.scala
@@ -114,11 +114,13 @@ class SparkContextSuite extends FunSuite with LocalSparkContext {
 
         if (length1 != gotten1.length()) {
           throw new SparkException(
-            s"file has different length $length1 than added file ${gotten1.length()} : " + absolutePath1)
+            s"file has different length $length1 than added file ${gotten1.length()} : " +
+              absolutePath1)
         }
         if (length2 != gotten2.length()) {
           throw new SparkException(
-            s"file has different length $length2 than added file ${gotten2.length()} : " + absolutePath2)
+            s"file has different length $length2 than added file ${gotten2.length()} : " +
+              absolutePath2)
         }
 
         if (absolutePath1 == gotten1.getAbsolutePath) {
diff --git a/core/src/test/scala/org/apache/spark/StatusTrackerSuite.scala b/core/src/test/scala/org/apache/spark/StatusTrackerSuite.scala
index 41d6ea29d5b06..084eb237d70d1 100644
--- a/core/src/test/scala/org/apache/spark/StatusTrackerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/StatusTrackerSuite.scala
@@ -82,7 +82,8 @@ class StatusTrackerSuite extends FunSuite with Matchers with LocalSparkContext {
       secondJobFuture.jobIds.head
     }
     eventually(timeout(10 seconds)) {
-      sc.statusTracker.getJobIdsForGroup("my-job-group").toSet should be (Set(firstJobId, secondJobId))
+      sc.statusTracker.getJobIdsForGroup("my-job-group").toSet should be (
+        Set(firstJobId, secondJobId))
     }
   }
-}
\ No newline at end of file
+}
diff --git a/core/src/test/scala/org/apache/spark/broadcast/BroadcastSuite.scala b/core/src/test/scala/org/apache/spark/broadcast/BroadcastSuite.scala
index af3272692d7a1..c8fdfa693912e 100644
--- a/core/src/test/scala/org/apache/spark/broadcast/BroadcastSuite.scala
+++ b/core/src/test/scala/org/apache/spark/broadcast/BroadcastSuite.scala
@@ -33,7 +33,7 @@ class DummyBroadcastClass(rdd: RDD[Int]) extends Serializable {
   val broadcast = rdd.context.broadcast(list)
   val bid = broadcast.id
 
-  def doSomething() = {
+  def doSomething(): Set[(Int, Boolean)] = {
     rdd.map { x =>
       val bm = SparkEnv.get.blockManager
       // Check if broadcast block was fetched
diff --git a/core/src/test/scala/org/apache/spark/deploy/JsonProtocolSuite.scala b/core/src/test/scala/org/apache/spark/deploy/JsonProtocolSuite.scala
index 68b5776fc6515..2071701b313db 100644
--- a/core/src/test/scala/org/apache/spark/deploy/JsonProtocolSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/JsonProtocolSuite.scala
@@ -100,13 +100,13 @@ class JsonProtocolSuite extends FunSuite {
     appInfo
   }
 
-  def createDriverCommand() = new Command(
+  def createDriverCommand(): Command = new Command(
     "org.apache.spark.FakeClass", Seq("some arg --and-some options -g foo"),
     Map(("K1", "V1"), ("K2", "V2")), Seq("cp1", "cp2"), Seq("lp1", "lp2"), Seq("-Dfoo")
   )
 
-  def createDriverDesc() = new DriverDescription("hdfs://some-dir/some.jar", 100, 3,
-    false, createDriverCommand())
+  def createDriverDesc(): DriverDescription =
+    new DriverDescription("hdfs://some-dir/some.jar", 100, 3, false, createDriverCommand())
 
   def createDriverInfo(): DriverInfo = new DriverInfo(3, "driver-3",
     createDriverDesc(), new Date())
diff --git a/core/src/test/scala/org/apache/spark/deploy/LogUrlsStandaloneSuite.scala b/core/src/test/scala/org/apache/spark/deploy/LogUrlsStandaloneSuite.scala
index 54dd7c9c45c61..9cdb42814ca32 100644
--- a/core/src/test/scala/org/apache/spark/deploy/LogUrlsStandaloneSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/LogUrlsStandaloneSuite.scala
@@ -56,7 +56,7 @@ class LogUrlsStandaloneSuite extends FunSuite with LocalSparkContext {
   test("verify that log urls reflect SPARK_PUBLIC_DNS (SPARK-6175)") {
     val SPARK_PUBLIC_DNS = "public_dns"
     class MySparkConf extends SparkConf(false) {
-      override def getenv(name: String) = {
+      override def getenv(name: String): String = {
         if (name == "SPARK_PUBLIC_DNS") SPARK_PUBLIC_DNS
         else super.getenv(name)
       }
diff --git a/core/src/test/scala/org/apache/spark/deploy/history/HistoryServerSuite.scala b/core/src/test/scala/org/apache/spark/deploy/history/HistoryServerSuite.scala
index 3a9963a5ce7b7..20de46fdab909 100644
--- a/core/src/test/scala/org/apache/spark/deploy/history/HistoryServerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/history/HistoryServerSuite.scala
@@ -42,10 +42,10 @@ class HistoryServerSuite extends FunSuite with Matchers with MockitoSugar {
     when(historyServer.getProviderConfig()).thenReturn(Map[String, String]())
     val page = new HistoryPage(historyServer)
 
-    //when
+    // when
     val response = page.render(request)
 
-    //then
+    // then
     val links = response \\ "a"
     val justHrefs = for {
       l <- links
diff --git a/core/src/test/scala/org/apache/spark/deploy/rest/StandaloneRestSubmitSuite.scala b/core/src/test/scala/org/apache/spark/deploy/rest/StandaloneRestSubmitSuite.scala
index 2fa90e3bd1c63..8e09976636386 100644
--- a/core/src/test/scala/org/apache/spark/deploy/rest/StandaloneRestSubmitSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/rest/StandaloneRestSubmitSuite.scala
@@ -508,7 +508,7 @@ private class DummyMaster(
     exception: Option[Exception] = None)
   extends Actor {
 
-  override def receive = {
+  override def receive: PartialFunction[Any, Unit] = {
     case RequestSubmitDriver(driverDesc) =>
       sender ! SubmitDriverResponse(success = true, Some(submitId), submitMessage)
     case RequestKillDriver(driverId) =>
@@ -531,7 +531,7 @@ private class SmarterMaster extends Actor {
   private var counter: Int = 0
   private val submittedDrivers = new mutable.HashMap[String, DriverState]
 
-  override def receive = {
+  override def receive: PartialFunction[Any, Unit] = {
     case RequestSubmitDriver(driverDesc) =>
       val driverId = s"driver-$counter"
       submittedDrivers(driverId) = RUNNING
diff --git a/core/src/test/scala/org/apache/spark/deploy/rest/SubmitRestProtocolSuite.scala b/core/src/test/scala/org/apache/spark/deploy/rest/SubmitRestProtocolSuite.scala
index 1d64ec201e647..61071ee17256c 100644
--- a/core/src/test/scala/org/apache/spark/deploy/rest/SubmitRestProtocolSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/rest/SubmitRestProtocolSuite.scala
@@ -129,7 +129,8 @@ class SubmitRestProtocolSuite extends FunSuite {
     assert(newMessage.sparkProperties("spark.files") === "fireball.png")
     assert(newMessage.sparkProperties("spark.driver.memory") === "512m")
     assert(newMessage.sparkProperties("spark.driver.cores") === "180")
-    assert(newMessage.sparkProperties("spark.driver.extraJavaOptions") === " -Dslices=5 -Dcolor=mostly_red")
+    assert(newMessage.sparkProperties("spark.driver.extraJavaOptions") ===
+      " -Dslices=5 -Dcolor=mostly_red")
     assert(newMessage.sparkProperties("spark.driver.extraClassPath") === "food-coloring.jar")
     assert(newMessage.sparkProperties("spark.driver.extraLibraryPath") === "pickle.jar")
     assert(newMessage.sparkProperties("spark.driver.supervise") === "false")
diff --git a/core/src/test/scala/org/apache/spark/deploy/worker/ExecutorRunnerTest.scala b/core/src/test/scala/org/apache/spark/deploy/worker/ExecutorRunnerTest.scala
index 6fca6321e5a1b..a8b9df227c996 100644
--- a/core/src/test/scala/org/apache/spark/deploy/worker/ExecutorRunnerTest.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/worker/ExecutorRunnerTest.scala
@@ -35,7 +35,8 @@ class ExecutorRunnerTest extends FunSuite {
     val er = new ExecutorRunner(appId, 1, appDesc, 8, 500, null, "blah", "worker321", 123,
       "publicAddr", new File(sparkHome), new File("ooga"), "blah", new SparkConf, Seq("localDir"),
       ExecutorState.RUNNING)
-    val builder = CommandUtils.buildProcessBuilder(appDesc.command, 512, sparkHome, er.substituteVariables)
+    val builder = CommandUtils.buildProcessBuilder(
+      appDesc.command, 512, sparkHome, er.substituteVariables)
     assert(builder.command().last === appId)
   }
 }
diff --git a/core/src/test/scala/org/apache/spark/deploy/worker/WorkerArgumentsTest.scala b/core/src/test/scala/org/apache/spark/deploy/worker/WorkerArgumentsTest.scala
index 372d7aa453008..7cc2104281464 100644
--- a/core/src/test/scala/org/apache/spark/deploy/worker/WorkerArgumentsTest.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/worker/WorkerArgumentsTest.scala
@@ -37,7 +37,7 @@ class WorkerArgumentsTest extends FunSuite {
     val args = Array("spark://localhost:0000  ")
 
     class MySparkConf extends SparkConf(false) {
-      override def getenv(name: String) = {
+      override def getenv(name: String): String = {
         if (name == "SPARK_WORKER_MEMORY") "50000"
         else super.getenv(name)
       }
@@ -56,7 +56,7 @@ class WorkerArgumentsTest extends FunSuite {
     val args = Array("spark://localhost:0000  ")
 
     class MySparkConf extends SparkConf(false) {
-      override def getenv(name: String) = {
+      override def getenv(name: String): String = {
         if (name == "SPARK_WORKER_MEMORY") "5G"
         else super.getenv(name)
       }
diff --git a/core/src/test/scala/org/apache/spark/deploy/worker/WorkerSuite.scala b/core/src/test/scala/org/apache/spark/deploy/worker/WorkerSuite.scala
index 84e2fd7ad936d..450fba21f4b5c 100644
--- a/core/src/test/scala/org/apache/spark/deploy/worker/WorkerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/worker/WorkerSuite.scala
@@ -24,8 +24,10 @@ import org.scalatest.{Matchers, FunSuite}
 
 class WorkerSuite extends FunSuite with Matchers {
 
-  def cmd(javaOpts: String*) = Command("", Seq.empty, Map.empty, Seq.empty, Seq.empty, Seq(javaOpts:_*))
-  def conf(opts: (String, String)*) = new SparkConf(loadDefaults = false).setAll(opts)
+  def cmd(javaOpts: String*): Command = {
+    Command("", Seq.empty, Map.empty, Seq.empty, Seq.empty, Seq(javaOpts:_*))
+  }
+  def conf(opts: (String, String)*): SparkConf = new SparkConf(loadDefaults = false).setAll(opts)
 
   test("test isUseLocalNodeSSLConfig") {
     Worker.isUseLocalNodeSSLConfig(cmd("-Dasdf=dfgh")) shouldBe false
diff --git a/core/src/test/scala/org/apache/spark/metrics/InputOutputMetricsSuite.scala b/core/src/test/scala/org/apache/spark/metrics/InputOutputMetricsSuite.scala
index 78fa98a3b9065..190b08d950a02 100644
--- a/core/src/test/scala/org/apache/spark/metrics/InputOutputMetricsSuite.scala
+++ b/core/src/test/scala/org/apache/spark/metrics/InputOutputMetricsSuite.scala
@@ -238,7 +238,7 @@ class InputOutputMetricsSuite extends FunSuite with SharedSparkContext
 
     sc.textFile(tmpFilePath, 4)
       .map(key => (key, 1))
-      .reduceByKey(_+_)
+      .reduceByKey(_ + _)
       .saveAsTextFile("file://" + tmpFile.getAbsolutePath)
 
     sc.listenerBus.waitUntilEmpty(500)
diff --git a/core/src/test/scala/org/apache/spark/metrics/MetricsConfigSuite.scala b/core/src/test/scala/org/apache/spark/metrics/MetricsConfigSuite.scala
index 37e528435aa5d..100ac77dec1f7 100644
--- a/core/src/test/scala/org/apache/spark/metrics/MetricsConfigSuite.scala
+++ b/core/src/test/scala/org/apache/spark/metrics/MetricsConfigSuite.scala
@@ -35,7 +35,8 @@ class MetricsConfigSuite extends FunSuite with BeforeAndAfter {
 
     val property = conf.getInstance("random")
     assert(property.size() === 2)
-    assert(property.getProperty("sink.servlet.class") === "org.apache.spark.metrics.sink.MetricsServlet")
+    assert(property.getProperty("sink.servlet.class") ===
+      "org.apache.spark.metrics.sink.MetricsServlet")
     assert(property.getProperty("sink.servlet.path") === "/metrics/json")
   }
 
@@ -47,16 +48,20 @@ class MetricsConfigSuite extends FunSuite with BeforeAndAfter {
     assert(masterProp.size() === 5)
     assert(masterProp.getProperty("sink.console.period") === "20")
     assert(masterProp.getProperty("sink.console.unit") === "minutes")
-    assert(masterProp.getProperty("source.jvm.class") === "org.apache.spark.metrics.source.JvmSource")
-    assert(masterProp.getProperty("sink.servlet.class") === "org.apache.spark.metrics.sink.MetricsServlet")
+    assert(masterProp.getProperty("source.jvm.class") ===
+      "org.apache.spark.metrics.source.JvmSource")
+    assert(masterProp.getProperty("sink.servlet.class") ===
+      "org.apache.spark.metrics.sink.MetricsServlet")
     assert(masterProp.getProperty("sink.servlet.path") === "/metrics/master/json")
 
     val workerProp = conf.getInstance("worker")
     assert(workerProp.size() === 5)
     assert(workerProp.getProperty("sink.console.period") === "10")
     assert(workerProp.getProperty("sink.console.unit") === "seconds")
-    assert(workerProp.getProperty("source.jvm.class") === "org.apache.spark.metrics.source.JvmSource")
-    assert(workerProp.getProperty("sink.servlet.class") === "org.apache.spark.metrics.sink.MetricsServlet")
+    assert(workerProp.getProperty("source.jvm.class") ===
+      "org.apache.spark.metrics.source.JvmSource")
+    assert(workerProp.getProperty("sink.servlet.class") ===
+      "org.apache.spark.metrics.sink.MetricsServlet")
     assert(workerProp.getProperty("sink.servlet.path") === "/metrics/json")
   }
 
diff --git a/core/src/test/scala/org/apache/spark/rdd/JdbcRDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/JdbcRDDSuite.scala
index 0dc59888f7304..be8467354b222 100644
--- a/core/src/test/scala/org/apache/spark/rdd/JdbcRDDSuite.scala
+++ b/core/src/test/scala/org/apache/spark/rdd/JdbcRDDSuite.scala
@@ -80,7 +80,7 @@ class JdbcRDDSuite extends FunSuite with BeforeAndAfter with LocalSparkContext {
       (r: ResultSet) => { r.getInt(1) } ).cache()
 
     assert(rdd.count === 100)
-    assert(rdd.reduce(_+_) === 10100)
+    assert(rdd.reduce(_ + _) === 10100)
   }
   
   test("large id overflow") {
@@ -92,7 +92,7 @@ class JdbcRDDSuite extends FunSuite with BeforeAndAfter with LocalSparkContext {
       1131544775L, 567279358897692673L, 20,
       (r: ResultSet) => { r.getInt(1) } ).cache()
     assert(rdd.count === 100)
-    assert(rdd.reduce(_+_) === 5050)
+    assert(rdd.reduce(_ + _) === 5050)
   }
 
   after {
diff --git a/core/src/test/scala/org/apache/spark/rdd/PairRDDFunctionsSuite.scala b/core/src/test/scala/org/apache/spark/rdd/PairRDDFunctionsSuite.scala
index 108f70af43f37..ca0d953d306d8 100644
--- a/core/src/test/scala/org/apache/spark/rdd/PairRDDFunctionsSuite.scala
+++ b/core/src/test/scala/org/apache/spark/rdd/PairRDDFunctionsSuite.scala
@@ -168,13 +168,13 @@ class PairRDDFunctionsSuite extends FunSuite with SharedSparkContext {
 
   test("reduceByKey") {
     val pairs = sc.parallelize(Array((1, 1), (1, 2), (1, 3), (1, 1), (2, 1)))
-    val sums = pairs.reduceByKey(_+_).collect()
+    val sums = pairs.reduceByKey(_ + _).collect()
     assert(sums.toSet === Set((1, 7), (2, 1)))
   }
 
   test("reduceByKey with collectAsMap") {
     val pairs = sc.parallelize(Array((1, 1), (1, 2), (1, 3), (1, 1), (2, 1)))
-    val sums = pairs.reduceByKey(_+_).collectAsMap()
+    val sums = pairs.reduceByKey(_ + _).collectAsMap()
     assert(sums.size === 2)
     assert(sums(1) === 7)
     assert(sums(2) === 1)
@@ -182,7 +182,7 @@ class PairRDDFunctionsSuite extends FunSuite with SharedSparkContext {
 
   test("reduceByKey with many output partitons") {
     val pairs = sc.parallelize(Array((1, 1), (1, 2), (1, 3), (1, 1), (2, 1)))
-    val sums = pairs.reduceByKey(_+_, 10).collect()
+    val sums = pairs.reduceByKey(_ + _, 10).collect()
     assert(sums.toSet === Set((1, 7), (2, 1)))
   }
 
@@ -192,7 +192,7 @@ class PairRDDFunctionsSuite extends FunSuite with SharedSparkContext {
       def getPartition(key: Any) = key.asInstanceOf[Int]
     }
     val pairs = sc.parallelize(Array((1, 1), (1, 2), (1, 1), (0, 1))).partitionBy(p)
-    val sums = pairs.reduceByKey(_+_)
+    val sums = pairs.reduceByKey(_ + _)
     assert(sums.collect().toSet === Set((1, 4), (0, 1)))
     assert(sums.partitioner === Some(p))
     // count the dependencies to make sure there is only 1 ShuffledRDD
@@ -208,7 +208,7 @@ class PairRDDFunctionsSuite extends FunSuite with SharedSparkContext {
   }
 
   test("countApproxDistinctByKey") {
-    def error(est: Long, size: Long) = math.abs(est - size) / size.toDouble
+    def error(est: Long, size: Long): Double = math.abs(est - size) / size.toDouble
 
     /* Since HyperLogLog unique counting is approximate, and the relative standard deviation is
      * only a statistical bound, the tests can fail for large values of relativeSD. We will be using
@@ -465,7 +465,7 @@ class PairRDDFunctionsSuite extends FunSuite with SharedSparkContext {
 
   test("foldByKey") {
     val pairs = sc.parallelize(Array((1, 1), (1, 2), (1, 3), (1, 1), (2, 1)))
-    val sums = pairs.foldByKey(0)(_+_).collect()
+    val sums = pairs.foldByKey(0)(_ + _).collect()
     assert(sums.toSet === Set((1, 7), (2, 1)))
   }
 
@@ -505,7 +505,8 @@ class PairRDDFunctionsSuite extends FunSuite with SharedSparkContext {
     conf.setOutputCommitter(classOf[FakeOutputCommitter])
 
     FakeOutputCommitter.ran = false
-    pairs.saveAsHadoopFile("ignored", pairs.keyClass, pairs.valueClass, classOf[FakeOutputFormat], conf)
+    pairs.saveAsHadoopFile(
+      "ignored", pairs.keyClass, pairs.valueClass, classOf[FakeOutputFormat], conf)
 
     assert(FakeOutputCommitter.ran, "OutputCommitter was never called")
   }
@@ -552,7 +553,7 @@ class PairRDDFunctionsSuite extends FunSuite with SharedSparkContext {
   }
 
   private object StratifiedAuxiliary {
-    def stratifier (fractionPositive: Double) = {
+    def stratifier (fractionPositive: Double): (Int) => String = {
       (x: Int) => if (x % 10 < (10 * fractionPositive).toInt) "1" else "0"
     }
 
@@ -572,7 +573,7 @@ class PairRDDFunctionsSuite extends FunSuite with SharedSparkContext {
     def testSampleExact(stratifiedData: RDD[(String, Int)],
         samplingRate: Double,
         seed: Long,
-        n: Long) = {
+        n: Long): Unit = {
       testBernoulli(stratifiedData, true, samplingRate, seed, n)
       testPoisson(stratifiedData, true, samplingRate, seed, n)
     }
@@ -580,7 +581,7 @@ class PairRDDFunctionsSuite extends FunSuite with SharedSparkContext {
     def testSample(stratifiedData: RDD[(String, Int)],
         samplingRate: Double,
         seed: Long,
-        n: Long) = {
+        n: Long): Unit = {
       testBernoulli(stratifiedData, false, samplingRate, seed, n)
       testPoisson(stratifiedData, false, samplingRate, seed, n)
     }
@@ -590,7 +591,7 @@ class PairRDDFunctionsSuite extends FunSuite with SharedSparkContext {
         exact: Boolean,
         samplingRate: Double,
         seed: Long,
-        n: Long) = {
+        n: Long): Unit = {
       val expectedSampleSize = stratifiedData.countByKey()
         .mapValues(count => math.ceil(count * samplingRate).toInt)
       val fractions = Map("1" -> samplingRate, "0" -> samplingRate)
@@ -612,7 +613,7 @@ class PairRDDFunctionsSuite extends FunSuite with SharedSparkContext {
         exact: Boolean,
         samplingRate: Double,
         seed: Long,
-        n: Long) = {
+        n: Long): Unit = {
       val expectedSampleSize = stratifiedData.countByKey().mapValues(count =>
         math.ceil(count * samplingRate).toInt)
       val fractions = Map("1" -> samplingRate, "0" -> samplingRate)
@@ -701,27 +702,27 @@ class FakeOutputFormat() extends OutputFormat[Integer, Integer]() {
  */
 class NewFakeWriter extends NewRecordWriter[Integer, Integer] {
 
-  def close(p1: NewTaskAttempContext) = ()
+  def close(p1: NewTaskAttempContext): Unit = ()
 
-  def write(p1: Integer, p2: Integer) = ()
+  def write(p1: Integer, p2: Integer): Unit = ()
 
 }
 
 class NewFakeCommitter extends NewOutputCommitter {
-  def setupJob(p1: NewJobContext) = ()
+  def setupJob(p1: NewJobContext): Unit = ()
 
   def needsTaskCommit(p1: NewTaskAttempContext): Boolean = false
 
-  def setupTask(p1: NewTaskAttempContext) = ()
+  def setupTask(p1: NewTaskAttempContext): Unit = ()
 
-  def commitTask(p1: NewTaskAttempContext) = ()
+  def commitTask(p1: NewTaskAttempContext): Unit = ()
 
-  def abortTask(p1: NewTaskAttempContext) = ()
+  def abortTask(p1: NewTaskAttempContext): Unit = ()
 }
 
 class NewFakeFormat() extends NewOutputFormat[Integer, Integer]() {
 
-  def checkOutputSpecs(p1: NewJobContext)  = ()
+  def checkOutputSpecs(p1: NewJobContext): Unit = ()
 
   def getRecordWriter(p1: NewTaskAttempContext): NewRecordWriter[Integer, Integer] = {
     new NewFakeWriter()
@@ -735,7 +736,7 @@ class NewFakeFormat() extends NewOutputFormat[Integer, Integer]() {
 class ConfigTestFormat() extends NewFakeFormat() with Configurable {
 
   var setConfCalled = false
-  def setConf(p1: Configuration) = {
+  def setConf(p1: Configuration): Unit = {
     setConfCalled = true
     ()
   }
diff --git a/core/src/test/scala/org/apache/spark/rdd/ParallelCollectionSplitSuite.scala b/core/src/test/scala/org/apache/spark/rdd/ParallelCollectionSplitSuite.scala
index cd193ae4f5238..1880364581c1a 100644
--- a/core/src/test/scala/org/apache/spark/rdd/ParallelCollectionSplitSuite.scala
+++ b/core/src/test/scala/org/apache/spark/rdd/ParallelCollectionSplitSuite.scala
@@ -100,7 +100,7 @@ class ParallelCollectionSplitSuite extends FunSuite with Checkers {
     val data = 1 until 100
     val slices = ParallelCollectionRDD.slice(data, 3)
     assert(slices.size === 3)
-    assert(slices.map(_.size).reduceLeft(_+_) === 99)
+    assert(slices.map(_.size).reduceLeft(_ + _) === 99)
     assert(slices.forall(_.isInstanceOf[Range]))
   }
 
@@ -108,7 +108,7 @@ class ParallelCollectionSplitSuite extends FunSuite with Checkers {
     val data = 1 to 100
     val slices = ParallelCollectionRDD.slice(data, 3)
     assert(slices.size === 3)
-    assert(slices.map(_.size).reduceLeft(_+_) === 100)
+    assert(slices.map(_.size).reduceLeft(_ + _) === 100)
     assert(slices.forall(_.isInstanceOf[Range]))
   }
 
@@ -139,7 +139,7 @@ class ParallelCollectionSplitSuite extends FunSuite with Checkers {
       assert(slices(i).isInstanceOf[Range])
       val range = slices(i).asInstanceOf[Range]
       assert(range.start === i * (N / 40), "slice " + i + " start")
-      assert(range.end   === (i+1) * (N / 40), "slice " + i + " end")
+      assert(range.end   === (i + 1) * (N / 40), "slice " + i + " end")
       assert(range.step  === 1, "slice " + i + " step")
     }
   }
@@ -156,7 +156,7 @@ class ParallelCollectionSplitSuite extends FunSuite with Checkers {
         val slices = ParallelCollectionRDD.slice(d, n)
         ("n slices"    |: slices.size == n) &&
         ("concat to d" |: Seq.concat(slices: _*).mkString(",") == d.mkString(",")) &&
-        ("equal sizes" |: slices.map(_.size).forall(x => x==d.size/n || x==d.size/n+1))
+        ("equal sizes" |: slices.map(_.size).forall(x => x == d.size / n || x == d.size /n + 1))
     }
     check(prop)
   }
@@ -174,7 +174,7 @@ class ParallelCollectionSplitSuite extends FunSuite with Checkers {
         ("n slices"    |: slices.size == n) &&
         ("all ranges"  |: slices.forall(_.isInstanceOf[Range])) &&
         ("concat to d" |: Seq.concat(slices: _*).mkString(",") == d.mkString(",")) &&
-        ("equal sizes" |: slices.map(_.size).forall(x => x==d.size/n || x==d.size/n+1))
+        ("equal sizes" |: slices.map(_.size).forall(x => x == d.size / n || x == d.size / n + 1))
     }
     check(prop)
   }
@@ -192,7 +192,7 @@ class ParallelCollectionSplitSuite extends FunSuite with Checkers {
         ("n slices"    |: slices.size == n) &&
         ("all ranges"  |: slices.forall(_.isInstanceOf[Range])) &&
         ("concat to d" |: Seq.concat(slices: _*).mkString(",") == d.mkString(",")) &&
-        ("equal sizes" |: slices.map(_.size).forall(x => x==d.size/n || x==d.size/n+1))
+        ("equal sizes" |: slices.map(_.size).forall(x => x == d.size / n || x == d.size / n + 1))
     }
     check(prop)
   }
@@ -201,7 +201,7 @@ class ParallelCollectionSplitSuite extends FunSuite with Checkers {
     val data = 1L until 100L
     val slices = ParallelCollectionRDD.slice(data, 3)
     assert(slices.size === 3)
-    assert(slices.map(_.size).reduceLeft(_+_) === 99)
+    assert(slices.map(_.size).reduceLeft(_ + _) === 99)
     assert(slices.forall(_.isInstanceOf[NumericRange[_]]))
   }
 
@@ -209,7 +209,7 @@ class ParallelCollectionSplitSuite extends FunSuite with Checkers {
     val data = 1L to 100L
     val slices = ParallelCollectionRDD.slice(data, 3)
     assert(slices.size === 3)
-    assert(slices.map(_.size).reduceLeft(_+_) === 100)
+    assert(slices.map(_.size).reduceLeft(_ + _) === 100)
     assert(slices.forall(_.isInstanceOf[NumericRange[_]]))
   }
 
@@ -217,7 +217,7 @@ class ParallelCollectionSplitSuite extends FunSuite with Checkers {
     val data = 1.0 until 100.0 by 1.0
     val slices = ParallelCollectionRDD.slice(data, 3)
     assert(slices.size === 3)
-    assert(slices.map(_.size).reduceLeft(_+_) === 99)
+    assert(slices.map(_.size).reduceLeft(_ + _) === 99)
     assert(slices.forall(_.isInstanceOf[NumericRange[_]]))
   }
 
@@ -225,7 +225,7 @@ class ParallelCollectionSplitSuite extends FunSuite with Checkers {
     val data = 1.0 to 100.0 by 1.0
     val slices = ParallelCollectionRDD.slice(data, 3)
     assert(slices.size === 3)
-    assert(slices.map(_.size).reduceLeft(_+_) === 100)
+    assert(slices.map(_.size).reduceLeft(_ + _) === 100)
     assert(slices.forall(_.isInstanceOf[NumericRange[_]]))
   }
 
diff --git a/core/src/test/scala/org/apache/spark/rdd/PartitionPruningRDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/PartitionPruningRDDSuite.scala
index 8408d7e785c65..465068c6cbb16 100644
--- a/core/src/test/scala/org/apache/spark/rdd/PartitionPruningRDDSuite.scala
+++ b/core/src/test/scala/org/apache/spark/rdd/PartitionPruningRDDSuite.scala
@@ -23,7 +23,6 @@ import org.apache.spark.{Partition, SharedSparkContext, TaskContext}
 
 class PartitionPruningRDDSuite extends FunSuite with SharedSparkContext {
 
-
   test("Pruned Partitions inherit locality prefs correctly") {
 
     val rdd = new RDD[Int](sc, Nil) {
@@ -74,8 +73,6 @@ class PartitionPruningRDDSuite extends FunSuite with SharedSparkContext {
 }
 
 class TestPartition(i: Int, value: Int) extends Partition with Serializable {
-  def index = i
-
-  def testValue = this.value
-
+  def index: Int = i
+  def testValue: Int = this.value
 }
diff --git a/core/src/test/scala/org/apache/spark/rdd/PartitionwiseSampledRDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/PartitionwiseSampledRDDSuite.scala
index a0483886f8db3..0d1369c19c69e 100644
--- a/core/src/test/scala/org/apache/spark/rdd/PartitionwiseSampledRDDSuite.scala
+++ b/core/src/test/scala/org/apache/spark/rdd/PartitionwiseSampledRDDSuite.scala
@@ -35,7 +35,7 @@ class MockSampler extends RandomSampler[Long, Long] {
     Iterator(s)
   }
 
-  override def clone = new MockSampler
+  override def clone: MockSampler = new MockSampler
 }
 
 class PartitionwiseSampledRDDSuite extends FunSuite with SharedSparkContext {
diff --git a/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala
index bede1ffb3e2d0..df42faab64505 100644
--- a/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala
+++ b/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala
@@ -82,7 +82,7 @@ class RDDSuite extends FunSuite with SharedSparkContext {
 
   test("countApproxDistinct") {
 
-    def error(est: Long, size: Long) = math.abs(est - size) / size.toDouble
+    def error(est: Long, size: Long): Double = math.abs(est - size) / size.toDouble
 
     val size = 1000
     val uniformDistro = for (i <- 1 to 5000) yield i % size
@@ -100,7 +100,7 @@ class RDDSuite extends FunSuite with SharedSparkContext {
   }
 
   test("partitioner aware union") {
-    def makeRDDWithPartitioner(seq: Seq[Int]) = {
+    def makeRDDWithPartitioner(seq: Seq[Int]): RDD[Int] = {
       sc.makeRDD(seq, 1)
         .map(x => (x, null))
         .partitionBy(new HashPartitioner(2))
@@ -159,8 +159,8 @@ class RDDSuite extends FunSuite with SharedSparkContext {
 
   test("treeAggregate") {
     val rdd = sc.makeRDD(-1000 until 1000, 10)
-    def seqOp = (c: Long, x: Int) => c + x
-    def combOp = (c1: Long, c2: Long) => c1 + c2
+    def seqOp: (Long, Int) => Long = (c: Long, x: Int) => c + x
+    def combOp: (Long, Long) => Long = (c1: Long, c2: Long) => c1 + c2
     for (depth <- 1 until 10) {
       val sum = rdd.treeAggregate(0L)(seqOp, combOp, depth)
       assert(sum === -1000L)
@@ -204,7 +204,7 @@ class RDDSuite extends FunSuite with SharedSparkContext {
     assert(empty.collect().size === 0)
 
     val thrown = intercept[UnsupportedOperationException]{
-      empty.reduce(_+_)
+      empty.reduce(_ + _)
     }
     assert(thrown.getMessage.contains("empty"))
 
@@ -321,7 +321,7 @@ class RDDSuite extends FunSuite with SharedSparkContext {
     assert(list3.sorted === Array("a","b","c"), "Locality preferences are dropped")
 
     // RDD with locality preferences spread (non-randomly) over 6 machines, m0 through m5
-    val data = sc.makeRDD((1 to 9).map(i => (i, (i to (i+2)).map{ j => "m" + (j%6)})))
+    val data = sc.makeRDD((1 to 9).map(i => (i, (i to (i + 2)).map{ j => "m" + (j%6)})))
     val coalesced1 = data.coalesce(3)
     assert(coalesced1.collect().toList.sorted === (1 to 9).toList, "Data got *lost* in coalescing")
 
@@ -921,15 +921,17 @@ class RDDSuite extends FunSuite with SharedSparkContext {
   test("task serialization exception should not hang scheduler") {
     class BadSerializable extends Serializable {
       @throws(classOf[IOException])
-      private def writeObject(out: ObjectOutputStream): Unit = throw new KryoException("Bad serialization")
+      private def writeObject(out: ObjectOutputStream): Unit =
+        throw new KryoException("Bad serialization")
 
       @throws(classOf[IOException])
       private def readObject(in: ObjectInputStream): Unit = {}
     }
-    // Note that in the original bug, SPARK-4349, that this verifies, the job would only hang if there were
-    // more threads in the Spark Context than there were number of objects in this sequence.
+    // Note that in the original bug, SPARK-4349, that this verifies, the job would only hang if
+    // there were more threads in the Spark Context than there were number of objects in this
+    // sequence.
     intercept[Throwable] {
-      sc.parallelize(Seq(new BadSerializable, new BadSerializable)).collect
+      sc.parallelize(Seq(new BadSerializable, new BadSerializable)).collect()
     }
     // Check that the context has not crashed
     sc.parallelize(1 to 100).map(x => x*2).collect
diff --git a/core/src/test/scala/org/apache/spark/rdd/RDDSuiteUtils.scala b/core/src/test/scala/org/apache/spark/rdd/RDDSuiteUtils.scala
index 4762fc17855ce..fe695d85e29dd 100644
--- a/core/src/test/scala/org/apache/spark/rdd/RDDSuiteUtils.scala
+++ b/core/src/test/scala/org/apache/spark/rdd/RDDSuiteUtils.scala
@@ -21,11 +21,11 @@ object RDDSuiteUtils {
   case class Person(first: String, last: String, age: Int)
 
   object AgeOrdering extends Ordering[Person] {
-    def compare(a:Person, b:Person) = a.age compare b.age
+    def compare(a:Person, b:Person): Int = a.age.compare(b.age)
   }
 
   object NameOrdering extends Ordering[Person] {
-    def compare(a:Person, b:Person) =
+    def compare(a:Person, b:Person): Int =
       implicitly[Ordering[Tuple2[String,String]]].compare((a.last, a.first), (b.last, b.first))
   }
 }
diff --git a/core/src/test/scala/org/apache/spark/rpc/RpcEnvSuite.scala b/core/src/test/scala/org/apache/spark/rpc/RpcEnvSuite.scala
index 5a734ec5ba5ec..ada07ef11cd7a 100644
--- a/core/src/test/scala/org/apache/spark/rpc/RpcEnvSuite.scala
+++ b/core/src/test/scala/org/apache/spark/rpc/RpcEnvSuite.scala
@@ -70,7 +70,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     env.setupEndpoint("send-remotely", new RpcEndpoint {
       override val rpcEnv = env
 
-      override def receive = {
+      override def receive: PartialFunction[Any, Unit] = {
         case msg: String => message = msg
       }
     })
@@ -109,7 +109,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     val rpcEndpointRef = env.setupEndpoint("ask-locally", new RpcEndpoint {
       override val rpcEnv = env
 
-      override def receiveAndReply(context: RpcCallContext) = {
+      override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
         case msg: String => {
           context.reply(msg)
         }
@@ -123,7 +123,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     env.setupEndpoint("ask-remotely", new RpcEndpoint {
       override val rpcEnv = env
 
-      override def receiveAndReply(context: RpcCallContext) = {
+      override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
         case msg: String => {
           context.reply(msg)
         }
@@ -146,7 +146,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     env.setupEndpoint("ask-timeout", new RpcEndpoint {
       override val rpcEnv = env
 
-      override def receiveAndReply(context: RpcCallContext) = {
+      override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
         case msg: String => {
           Thread.sleep(100)
           context.reply(msg)
@@ -182,7 +182,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
         calledMethods += "start"
       }
 
-      override def receive = {
+      override def receive: PartialFunction[Any, Unit] = {
         case msg: String =>
       }
 
@@ -206,7 +206,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
         throw new RuntimeException("Oops!")
       }
 
-      override def receive = {
+      override def receive: PartialFunction[Any, Unit] = {
         case m =>
       }
 
@@ -225,7 +225,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     val endpointRef = env.setupEndpoint("onError-onStop", new RpcEndpoint {
       override val rpcEnv = env
 
-      override def receive = {
+      override def receive: PartialFunction[Any, Unit] = {
         case m =>
       }
 
@@ -250,8 +250,8 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     val endpointRef = env.setupEndpoint("onError-receive", new RpcEndpoint {
       override val rpcEnv = env
 
-      override def receive = {
-        case m =>  throw new RuntimeException("Oops!")
+      override def receive: PartialFunction[Any, Unit] = {
+        case m => throw new RuntimeException("Oops!")
       }
 
       override def onError(cause: Throwable): Unit = {
@@ -277,7 +277,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
         callSelfSuccessfully = true
       }
 
-      override def receive = {
+      override def receive: PartialFunction[Any, Unit] = {
         case m =>
       }
     })
@@ -294,7 +294,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     val endpointRef = env.setupEndpoint("self-receive", new RpcEndpoint {
       override val rpcEnv = env
 
-      override def receive = {
+      override def receive: PartialFunction[Any, Unit] = {
         case m => {
           self
           callSelfSuccessfully = true
@@ -316,7 +316,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     val endpointRef = env.setupEndpoint("self-onStop", new RpcEndpoint {
       override val rpcEnv = env
 
-      override def receive = {
+      override def receive: PartialFunction[Any, Unit] = {
         case m =>
       }
 
@@ -343,7 +343,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
       val endpointRef = env.setupEndpoint(s"receive-in-sequence-$i", new ThreadSafeRpcEndpoint {
         override val rpcEnv = env
 
-        override def receive = {
+        override def receive: PartialFunction[Any, Unit] = {
           case m => result += 1
         }
 
@@ -372,7 +372,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     val endpointRef = env.setupEndpoint("stop-reentrant", new RpcEndpoint {
       override val rpcEnv = env
 
-      override def receive = {
+      override def receive: PartialFunction[Any, Unit] = {
         case m =>
       }
 
@@ -394,7 +394,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     val endpointRef = env.setupEndpoint("sendWithReply", new RpcEndpoint {
       override val rpcEnv = env
 
-      override def receiveAndReply(context: RpcCallContext) = {
+      override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
         case m => context.reply("ack")
       }
     })
@@ -410,7 +410,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     env.setupEndpoint("sendWithReply-remotely", new RpcEndpoint {
       override val rpcEnv = env
 
-      override def receiveAndReply(context: RpcCallContext) = {
+      override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
         case m => context.reply("ack")
       }
     })
@@ -432,7 +432,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     val endpointRef = env.setupEndpoint("sendWithReply-error", new RpcEndpoint {
       override val rpcEnv = env
 
-      override def receiveAndReply(context: RpcCallContext) = {
+      override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
         case m => context.sendFailure(new SparkException("Oops"))
       }
     })
@@ -450,7 +450,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     env.setupEndpoint("sendWithReply-remotely-error", new RpcEndpoint {
       override val rpcEnv = env
 
-      override def receiveAndReply(context: RpcCallContext) = {
+      override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
         case msg: String => context.sendFailure(new SparkException("Oops"))
       }
     })
@@ -476,7 +476,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     env.setupEndpoint("network-events", new ThreadSafeRpcEndpoint {
       override val rpcEnv = env
 
-      override def receive = {
+      override def receive: PartialFunction[Any, Unit] = {
         case "hello" =>
         case m => events += "receive" -> m
       }
@@ -519,7 +519,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll {
     env.setupEndpoint("sendWithReply-unserializable-error", new RpcEndpoint {
       override val rpcEnv = env
 
-      override def receiveAndReply(context: RpcCallContext) = {
+      override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
         case msg: String => context.sendFailure(new UnserializableException)
       }
     })
diff --git a/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala
index eb759f0807a17..3c52a8c4460c6 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala
@@ -57,20 +57,18 @@ class MyRDD(
     locations: Seq[Seq[String]] = Nil) extends RDD[(Int, Int)](sc, dependencies) with Serializable {
   override def compute(split: Partition, context: TaskContext): Iterator[(Int, Int)] =
     throw new RuntimeException("should not be reached")
-  override def getPartitions = (0 until numPartitions).map(i => new Partition {
-    override def index = i
+  override def getPartitions: Array[Partition] = (0 until numPartitions).map(i => new Partition {
+    override def index: Int = i
   }).toArray
   override def getPreferredLocations(split: Partition): Seq[String] =
-    if (locations.isDefinedAt(split.index))
-      locations(split.index)
-    else
-      Nil
+    if (locations.isDefinedAt(split.index)) locations(split.index) else Nil
   override def toString: String = "DAGSchedulerSuiteRDD " + id
 }
 
 class DAGSchedulerSuiteDummyException extends Exception
 
-class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSparkContext with Timeouts {
+class DAGSchedulerSuite
+  extends FunSuiteLike with BeforeAndAfter with LocalSparkContext with Timeouts {
 
   val conf = new SparkConf
   /** Set of TaskSets the DAGScheduler has requested executed. */
@@ -209,7 +207,8 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     assert(taskSet.tasks.size >= results.size)
     for ((result, i) <- results.zipWithIndex) {
       if (i < taskSet.tasks.size) {
-        runEvent(CompletionEvent(taskSet.tasks(i), result._1, result._2, null, createFakeTaskInfo(), null))
+        runEvent(CompletionEvent(
+          taskSet.tasks(i), result._1, result._2, null, createFakeTaskInfo(), null))
       }
     }
   }
@@ -269,21 +268,23 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     submit(new MyRDD(sc, 1, Nil), Array(0))
     complete(taskSets(0), List((Success, 42)))
     assert(results === Map(0 -> 42))
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("local job") {
     val rdd = new PairOfIntsRDD(sc, Nil) {
       override def compute(split: Partition, context: TaskContext): Iterator[(Int, Int)] =
         Array(42 -> 0).iterator
-      override def getPartitions = Array( new Partition { override def index = 0 } )
-      override def getPreferredLocations(split: Partition) = Nil
-      override def toString = "DAGSchedulerSuite Local RDD"
+      override def getPartitions: Array[Partition] =
+        Array( new Partition { override def index: Int = 0 } )
+      override def getPreferredLocations(split: Partition): List[String] = Nil
+      override def toString: String = "DAGSchedulerSuite Local RDD"
     }
     val jobId = scheduler.nextJobId.getAndIncrement()
-    runEvent(JobSubmitted(jobId, rdd, jobComputeFunc, Array(0), true, CallSite("", ""), jobListener))
+    runEvent(
+      JobSubmitted(jobId, rdd, jobComputeFunc, Array(0), true, CallSite("", ""), jobListener))
     assert(results === Map(0 -> 42))
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("local job oom") {
@@ -295,9 +296,10 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
       override def toString = "DAGSchedulerSuite Local RDD"
     }
     val jobId = scheduler.nextJobId.getAndIncrement()
-    runEvent(JobSubmitted(jobId, rdd, jobComputeFunc, Array(0), true, CallSite("", ""), jobListener))
+    runEvent(
+      JobSubmitted(jobId, rdd, jobComputeFunc, Array(0), true, CallSite("", ""), jobListener))
     assert(results.size == 0)
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("run trivial job w/ dependency") {
@@ -306,7 +308,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     submit(finalRdd, Array(0))
     complete(taskSets(0), Seq((Success, 42)))
     assert(results === Map(0 -> 42))
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("cache location preferences w/ dependency") {
@@ -319,7 +321,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     assertLocations(taskSet, Seq(Seq("hostA", "hostB")))
     complete(taskSet, Seq((Success, 42)))
     assert(results === Map(0 -> 42))
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("regression test for getCacheLocs") {
@@ -335,7 +337,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
   }
 
   test("avoid exponential blowup when getting preferred locs list") {
-    // Build up a complex dependency graph with repeated zip operations, without preferred locations.
+    // Build up a complex dependency graph with repeated zip operations, without preferred locations
     var rdd: RDD[_] = new MyRDD(sc, 1, Nil)
     (1 to 30).foreach(_ => rdd = rdd.zip(rdd))
     // getPreferredLocs runs quickly, indicating that exponential graph traversal is avoided.
@@ -357,7 +359,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     assert(sc.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS))
     assert(sparkListener.failedStages.contains(0))
     assert(sparkListener.failedStages.size === 1)
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("trivial job failure") {
@@ -367,7 +369,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     assert(sc.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS))
     assert(sparkListener.failedStages.contains(0))
     assert(sparkListener.failedStages.size === 1)
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("trivial job cancellation") {
@@ -378,7 +380,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     assert(sc.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS))
     assert(sparkListener.failedStages.contains(0))
     assert(sparkListener.failedStages.size === 1)
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("job cancellation no-kill backend") {
@@ -387,18 +389,20 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     val noKillTaskScheduler = new TaskScheduler() {
       override def rootPool: Pool = null
       override def schedulingMode: SchedulingMode = SchedulingMode.NONE
-      override def start() = {}
-      override def stop() = {}
-      override def submitTasks(taskSet: TaskSet) = {
+      override def start(): Unit = {}
+      override def stop(): Unit = {}
+      override def submitTasks(taskSet: TaskSet): Unit = {
         taskSets += taskSet
       }
       override def cancelTasks(stageId: Int, interruptThread: Boolean) {
         throw new UnsupportedOperationException
       }
-      override def setDAGScheduler(dagScheduler: DAGScheduler) = {}
-      override def defaultParallelism() = 2
-      override def executorHeartbeatReceived(execId: String, taskMetrics: Array[(Long, TaskMetrics)],
-        blockManagerId: BlockManagerId): Boolean = true
+      override def setDAGScheduler(dagScheduler: DAGScheduler): Unit = {}
+      override def defaultParallelism(): Int = 2
+      override def executorHeartbeatReceived(
+          execId: String,
+          taskMetrics: Array[(Long, TaskMetrics)],
+          blockManagerId: BlockManagerId): Boolean = true
       override def executorLost(executorId: String, reason: ExecutorLossReason): Unit = {}
     }
     val noKillScheduler = new DAGScheduler(
@@ -422,7 +426,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     // When the task set completes normally, state should be correctly updated.
     complete(taskSets(0), Seq((Success, 42)))
     assert(results === Map(0 -> 42))
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
 
     assert(sc.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS))
     assert(sparkListener.failedStages.isEmpty)
@@ -442,7 +446,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
            Array(makeBlockManagerId("hostA"), makeBlockManagerId("hostB")))
     complete(taskSets(1), Seq((Success, 42)))
     assert(results === Map(0 -> 42))
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("run trivial shuffle with fetch failure") {
@@ -465,10 +469,11 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     // have the 2nd attempt pass
     complete(taskSets(2), Seq((Success, makeMapStatus("hostA", 1))))
     // we can see both result blocks now
-    assert(mapOutputTracker.getServerStatuses(shuffleId, 0).map(_._1.host) === Array("hostA", "hostB"))
+    assert(mapOutputTracker.getServerStatuses(shuffleId, 0).map(_._1.host) ===
+      Array("hostA", "hostB"))
     complete(taskSets(3), Seq((Success, 43)))
     assert(results === Map(0 -> 42, 1 -> 43))
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("trivial shuffle with multiple fetch failures") {
@@ -521,19 +526,23 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     assert(newEpoch > oldEpoch)
     val taskSet = taskSets(0)
     // should be ignored for being too old
-    runEvent(CompletionEvent(taskSet.tasks(0), Success, makeMapStatus("hostA", 1), null, createFakeTaskInfo(), null))
+    runEvent(CompletionEvent(
+      taskSet.tasks(0), Success, makeMapStatus("hostA", 1), null, createFakeTaskInfo(), null))
     // should work because it's a non-failed host
-    runEvent(CompletionEvent(taskSet.tasks(0), Success, makeMapStatus("hostB", 1), null, createFakeTaskInfo(), null))
+    runEvent(CompletionEvent(
+      taskSet.tasks(0), Success, makeMapStatus("hostB", 1), null, createFakeTaskInfo(), null))
     // should be ignored for being too old
-    runEvent(CompletionEvent(taskSet.tasks(0), Success, makeMapStatus("hostA", 1), null, createFakeTaskInfo(), null))
+    runEvent(CompletionEvent(
+      taskSet.tasks(0), Success, makeMapStatus("hostA", 1), null, createFakeTaskInfo(), null))
     // should work because it's a new epoch
     taskSet.tasks(1).epoch = newEpoch
-    runEvent(CompletionEvent(taskSet.tasks(1), Success, makeMapStatus("hostA", 1), null, createFakeTaskInfo(), null))
+    runEvent(CompletionEvent(
+      taskSet.tasks(1), Success, makeMapStatus("hostA", 1), null, createFakeTaskInfo(), null))
     assert(mapOutputTracker.getServerStatuses(shuffleId, 0).map(_._1) ===
            Array(makeBlockManagerId("hostB"), makeBlockManagerId("hostA")))
     complete(taskSets(1), Seq((Success, 42), (Success, 43)))
     assert(results === Map(0 -> 42, 1 -> 43))
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("run shuffle with map stage failure") {
@@ -552,7 +561,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     assert(sc.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS))
     assert(sparkListener.failedStages.toSet === Set(0))
 
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   /**
@@ -586,7 +595,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     class FailureRecordingJobListener() extends JobListener {
       var failureMessage: String = _
       override def taskSucceeded(index: Int, result: Any) {}
-      override def jobFailed(exception: Exception) = { failureMessage = exception.getMessage }
+      override def jobFailed(exception: Exception): Unit = { failureMessage = exception.getMessage }
     }
     val listener1 = new FailureRecordingJobListener()
     val listener2 = new FailureRecordingJobListener()
@@ -606,7 +615,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
 
     assert(listener1.failureMessage === s"Job aborted due to stage failure: $stageFailureMessage")
     assert(listener2.failureMessage === s"Job aborted due to stage failure: $stageFailureMessage")
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("run trivial shuffle with out-of-band failure and retry") {
@@ -629,7 +638,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
            Array(makeBlockManagerId("hostC"), makeBlockManagerId("hostB")))
     complete(taskSets(2), Seq((Success, 42)))
     assert(results === Map(0 -> 42))
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("recursive shuffle failures") {
@@ -658,7 +667,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     complete(taskSets(4), Seq((Success, makeMapStatus("hostA", 1))))
     complete(taskSets(5), Seq((Success, 42)))
     assert(results === Map(0 -> 42))
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("cached post-shuffle") {
@@ -690,7 +699,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
     complete(taskSets(3), Seq((Success, makeMapStatus("hostD", 1))))
     complete(taskSets(4), Seq((Success, 42)))
     assert(results === Map(0 -> 42))
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   test("misbehaved accumulator should not crash DAGScheduler and SparkContext") {
@@ -742,7 +751,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
   }
 
   test("accumulator not calculated for resubmitted result stage") {
-    //just for register
+    // just for register
     val accum = new Accumulator[Int](0, AccumulatorParam.IntAccumulatorParam)
     val finalRdd = new MyRDD(sc, 1, Nil)
     submit(finalRdd, Array(0))
@@ -754,7 +763,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
 
     assert(accVal === 1)
 
-    assertDataStructuresEmpty
+    assertDataStructuresEmpty()
   }
 
   /**
@@ -774,7 +783,7 @@ class DAGSchedulerSuite extends FunSuiteLike  with BeforeAndAfter with LocalSpar
   private def makeBlockManagerId(host: String): BlockManagerId =
     BlockManagerId("exec-" + host, host, 12345)
 
-  private def assertDataStructuresEmpty = {
+  private def assertDataStructuresEmpty(): Unit = {
     assert(scheduler.activeJobs.isEmpty)
     assert(scheduler.failedStages.isEmpty)
     assert(scheduler.jobIdToActiveJob.isEmpty)
diff --git a/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala
index 30ee63e78d9d8..6d25edb7d20dc 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala
@@ -268,7 +268,7 @@ class EventLoggingListenerSuite extends FunSuite with LocalSparkContext with Bef
 object EventLoggingListenerSuite {
 
   /** Get a SparkConf with event logging enabled. */
-  def getLoggingConf(logDir: Path, compressionCodec: Option[String] = None) = {
+  def getLoggingConf(logDir: Path, compressionCodec: Option[String] = None): SparkConf = {
     val conf = new SparkConf
     conf.set("spark.eventLog.enabled", "true")
     conf.set("spark.eventLog.testing", "true")
@@ -280,5 +280,5 @@ object EventLoggingListenerSuite {
     conf
   }
 
-  def getUniqueApplicationId = "test-" + System.currentTimeMillis
+  def getUniqueApplicationId: String = "test-" + System.currentTimeMillis
 }
diff --git a/core/src/test/scala/org/apache/spark/scheduler/NotSerializableFakeTask.scala b/core/src/test/scala/org/apache/spark/scheduler/NotSerializableFakeTask.scala
index 6b75c98839e03..9b92f8de56759 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/NotSerializableFakeTask.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/NotSerializableFakeTask.scala
@@ -24,7 +24,9 @@ import org.apache.spark.TaskContext
 /**
  * A Task implementation that fails to serialize.
  */
-private[spark] class NotSerializableFakeTask(myId: Int, stageId: Int) extends Task[Array[Byte]](stageId, 0) {
+private[spark] class NotSerializableFakeTask(myId: Int, stageId: Int)
+  extends Task[Array[Byte]](stageId, 0) {
+
   override def runTask(context: TaskContext): Array[Byte] = Array.empty[Byte]
   override def preferredLocations: Seq[TaskLocation] = Seq[TaskLocation]()
 
diff --git a/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala
index 627c9a4ddfffc..825c616c0c3e0 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala
@@ -85,7 +85,7 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers
     val stopperReturned = new Semaphore(0)
 
     class BlockingListener extends SparkListener {
-      override def onJobEnd(jobEnd: SparkListenerJobEnd) = {
+      override def onJobEnd(jobEnd: SparkListenerJobEnd): Unit = {
         listenerStarted.release()
         listenerWait.acquire()
         drained = true
@@ -206,8 +206,9 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers
     sc.addSparkListener(new StatsReportListener)
     // just to make sure some of the tasks take a noticeable amount of time
     val w = { i: Int =>
-      if (i == 0)
+      if (i == 0) {
         Thread.sleep(100)
+      }
       i
     }
 
@@ -247,12 +248,12 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers
       */
 
       taskInfoMetrics.foreach { case (taskInfo, taskMetrics) =>
-        taskMetrics.resultSize should be > (0l)
+        taskMetrics.resultSize should be > (0L)
         if (stageInfo.rddInfos.exists(info => info.name == d2.name || info.name == d3.name)) {
           taskMetrics.inputMetrics should not be ('defined)
           taskMetrics.outputMetrics should not be ('defined)
           taskMetrics.shuffleWriteMetrics should be ('defined)
-          taskMetrics.shuffleWriteMetrics.get.shuffleBytesWritten should be > (0l)
+          taskMetrics.shuffleWriteMetrics.get.shuffleBytesWritten should be > (0L)
         }
         if (stageInfo.rddInfos.exists(_.name == d4.name)) {
           taskMetrics.shuffleReadMetrics should be ('defined)
@@ -260,7 +261,7 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers
           sm.totalBlocksFetched should be (128)
           sm.localBlocksFetched should be (128)
           sm.remoteBlocksFetched should be (0)
-          sm.remoteBytesRead should be (0l)
+          sm.remoteBytesRead should be (0L)
         }
       }
     }
@@ -406,12 +407,12 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers
     val startedGettingResultTasks = new mutable.HashSet[Int]()
     val endedTasks = new mutable.HashSet[Int]()
 
-    override def onTaskStart(taskStart: SparkListenerTaskStart) = synchronized {
+    override def onTaskStart(taskStart: SparkListenerTaskStart): Unit = synchronized {
       startedTasks += taskStart.taskInfo.index
       notify()
     }
 
-    override def onTaskEnd(taskEnd: SparkListenerTaskEnd) = synchronized {
+    override def onTaskEnd(taskEnd: SparkListenerTaskEnd): Unit = synchronized {
       endedTasks += taskEnd.taskInfo.index
       notify()
     }
@@ -425,7 +426,7 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers
    * A simple listener that throws an exception on job end.
    */
   private class BadListener extends SparkListener {
-    override def onJobEnd(jobEnd: SparkListenerJobEnd) = { throw new Exception }
+    override def onJobEnd(jobEnd: SparkListenerJobEnd): Unit = { throw new Exception }
   }
 
 }
@@ -438,10 +439,10 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers
  */
 private class BasicJobCounter extends SparkListener {
   var count = 0
-  override def onJobEnd(job: SparkListenerJobEnd) = count += 1
+  override def onJobEnd(job: SparkListenerJobEnd): Unit = count += 1
 }
 
 private class ListenerThatAcceptsSparkConf(conf: SparkConf) extends SparkListener {
   var count = 0
-  override def onJobEnd(job: SparkListenerJobEnd) = count += 1
+  override def onJobEnd(job: SparkListenerJobEnd): Unit = count += 1
 }
diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala
index add13f5b21765..ffa4381969b68 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala
@@ -17,8 +17,6 @@
 
 package org.apache.spark.scheduler
 
-import java.util.Properties
-
 import org.scalatest.FunSuite
 
 import org.apache.spark._
@@ -27,7 +25,7 @@ class FakeSchedulerBackend extends SchedulerBackend {
   def start() {}
   def stop() {}
   def reviveOffers() {}
-  def defaultParallelism() = 1
+  def defaultParallelism(): Int = 1
 }
 
 class TaskSchedulerImplSuite extends FunSuite with LocalSparkContext with Logging {
@@ -115,7 +113,8 @@ class TaskSchedulerImplSuite extends FunSuite with LocalSparkContext with Loggin
     }
     val numFreeCores = 1
     taskScheduler.setDAGScheduler(dagScheduler)
-    var taskSet = new TaskSet(Array(new NotSerializableFakeTask(1, 0), new NotSerializableFakeTask(0, 1)), 0, 0, 0, null)
+    val taskSet = new TaskSet(
+      Array(new NotSerializableFakeTask(1, 0), new NotSerializableFakeTask(0, 1)), 0, 0, 0, null)
     val multiCoreWorkerOffers = Seq(new WorkerOffer("executor0", "host0", taskCpus),
       new WorkerOffer("executor1", "host1", numFreeCores))
     taskScheduler.submitTasks(taskSet)
@@ -123,7 +122,8 @@ class TaskSchedulerImplSuite extends FunSuite with LocalSparkContext with Loggin
     assert(0 === taskDescriptions.length)
 
     // Now check that we can still submit tasks
-    // Even if one of the tasks has not-serializable tasks, the other task set should still be processed without error
+    // Even if one of the tasks has not-serializable tasks, the other task set should
+    // still be processed without error
     taskScheduler.submitTasks(taskSet)
     taskScheduler.submitTasks(FakeTask.createTaskSet(1))
     taskDescriptions = taskScheduler.resourceOffers(multiCoreWorkerOffers).flatten
diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala
index 12330d8f63c40..716d12c0762cf 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala
@@ -67,7 +67,7 @@ object FakeRackUtil {
     hostToRack(host) = rack
   }
 
-  def getRackForHost(host: String) = {
+  def getRackForHost(host: String): Option[String] = {
     hostToRack.get(host)
   }
 }
@@ -327,8 +327,8 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
     // First offer host1: first task should be chosen
     assert(manager.resourceOffer("exec1", "host1", ANY).get.index === 0)
 
-    // After this, nothing should get chosen, because we have separated tasks with unavailable preference
-    // from the noPrefPendingTasks
+    // After this, nothing should get chosen, because we have separated tasks with unavailable
+    // preference from the noPrefPendingTasks
     assert(manager.resourceOffer("exec1", "host1", ANY) === None)
 
     // Now mark host2 as dead
@@ -499,7 +499,8 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
     sched.addExecutor("execC", "host2")
     manager.executorAdded()
     // Valid locality should contain PROCESS_LOCAL, NODE_LOCAL, RACK_LOCAL and ANY
-    assert(manager.myLocalityLevels.sameElements(Array(PROCESS_LOCAL, NODE_LOCAL, NO_PREF, RACK_LOCAL, ANY)))
+    assert(manager.myLocalityLevels.sameElements(
+      Array(PROCESS_LOCAL, NODE_LOCAL, NO_PREF, RACK_LOCAL, ANY)))
     // test if the valid locality is recomputed when the executor is lost
     sched.removeExecutor("execC")
     manager.executorLost("execC", "host2")
@@ -569,7 +570,8 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
     sc = new SparkContext("local", "test")
     val sched = new FakeTaskScheduler(sc, ("exec1", "host1"))
 
-    val taskSet = new TaskSet(Array(new NotSerializableFakeTask(1, 0), new NotSerializableFakeTask(0, 1)), 0, 0, 0, null)
+    val taskSet = new TaskSet(
+      Array(new NotSerializableFakeTask(1, 0), new NotSerializableFakeTask(0, 1)), 0, 0, 0, null)
     val manager = new TaskSetManager(sched, taskSet, MAX_TASK_FAILURES)
 
     intercept[TaskNotSerializableException] {
@@ -582,7 +584,7 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
     val conf = new SparkConf().set("spark.driver.maxResultSize", "2m")
     sc = new SparkContext("local", "test", conf)
 
-    def genBytes(size: Int) = { (x: Int) =>
+    def genBytes(size: Int): (Int) => Array[Byte] = { (x: Int) =>
       val bytes = Array.ofDim[Byte](size)
       scala.util.Random.nextBytes(bytes)
       bytes
@@ -605,7 +607,8 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
 
   test("speculative and noPref task should be scheduled after node-local") {
     sc = new SparkContext("local", "test")
-    val sched = new FakeTaskScheduler(sc, ("execA", "host1"), ("execB", "host2"), ("execC", "host3"))
+    val sched = new FakeTaskScheduler(
+      sc, ("execA", "host1"), ("execB", "host2"), ("execC", "host3"))
     val taskSet = FakeTask.createTaskSet(4,
       Seq(TaskLocation("host1", "execA")),
       Seq(TaskLocation("host2"), TaskLocation("host1")),
@@ -629,9 +632,11 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
     assert(manager.resourceOffer("execB", "host2", ANY).get.index === 3)
   }
 
-  test("node-local tasks should be scheduled right away when there are only node-local and no-preference tasks") {
+  test("node-local tasks should be scheduled right away " +
+    "when there are only node-local and no-preference tasks") {
     sc = new SparkContext("local", "test")
-    val sched = new FakeTaskScheduler(sc, ("execA", "host1"), ("execB", "host2"), ("execC", "host3"))
+    val sched = new FakeTaskScheduler(
+      sc, ("execA", "host1"), ("execB", "host2"), ("execC", "host3"))
     val taskSet = FakeTask.createTaskSet(4,
       Seq(TaskLocation("host1")),
       Seq(TaskLocation("host2")),
@@ -650,7 +655,8 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
     assert(manager.resourceOffer("execA", "host3", NO_PREF).get.index === 2)
   }
 
-  test("SPARK-4939: node-local tasks should be scheduled right after process-local tasks finished") {
+  test("SPARK-4939: node-local tasks should be scheduled right after process-local tasks finished")
+  {
     sc = new SparkContext("local", "test")
     val sched = new FakeTaskScheduler(sc, ("execA", "host1"), ("execB", "host2"))
     val taskSet = FakeTask.createTaskSet(4,
diff --git a/core/src/test/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackendSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackendSuite.scala
index f1a4380d349b3..a311512e82c5e 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackendSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackendSuite.scala
@@ -63,16 +63,18 @@ class MesosSchedulerBackendSuite extends FunSuite with LocalSparkContext with Mo
 
     // uri is null.
     val executorInfo = mesosSchedulerBackend.createExecutorInfo("test-id")
-    assert(executorInfo.getCommand.getValue === s" /mesos-home/bin/spark-class ${classOf[MesosExecutorBackend].getName}")
+    assert(executorInfo.getCommand.getValue ===
+      s" /mesos-home/bin/spark-class ${classOf[MesosExecutorBackend].getName}")
 
     // uri exists.
     conf.set("spark.executor.uri", "hdfs:///test-app-1.0.0.tgz")
     val executorInfo1 = mesosSchedulerBackend.createExecutorInfo("test-id")
-    assert(executorInfo1.getCommand.getValue === s"cd test-app-1*;  ./bin/spark-class ${classOf[MesosExecutorBackend].getName}")
+    assert(executorInfo1.getCommand.getValue ===
+      s"cd test-app-1*;  ./bin/spark-class ${classOf[MesosExecutorBackend].getName}")
   }
 
   test("mesos resource offers result in launching tasks") {
-    def createOffer(id: Int, mem: Int, cpu: Int) = {
+    def createOffer(id: Int, mem: Int, cpu: Int): Offer = {
       val builder = Offer.newBuilder()
       builder.addResourcesBuilder()
         .setName("mem")
@@ -82,8 +84,10 @@ class MesosSchedulerBackendSuite extends FunSuite with LocalSparkContext with Mo
         .setName("cpus")
         .setType(Value.Type.SCALAR)
         .setScalar(Scalar.newBuilder().setValue(cpu))
-      builder.setId(OfferID.newBuilder().setValue(s"o${id.toString}").build()).setFrameworkId(FrameworkID.newBuilder().setValue("f1"))
-        .setSlaveId(SlaveID.newBuilder().setValue(s"s${id.toString}")).setHostname(s"host${id.toString}").build()
+      builder.setId(OfferID.newBuilder().setValue(s"o${id.toString}").build())
+        .setFrameworkId(FrameworkID.newBuilder().setValue("f1"))
+        .setSlaveId(SlaveID.newBuilder().setValue(s"s${id.toString}"))
+        .setHostname(s"host${id.toString}").build()
     }
 
     val driver = mock[SchedulerDriver]
diff --git a/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala b/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala
index 6198df84fab3d..b070a54aa989b 100644
--- a/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala
@@ -106,7 +106,9 @@ class KryoSerializerSuite extends FunSuite with SharedSparkContext {
     check(mutable.HashMap(1 -> "one", 2 -> "two"))
     check(mutable.HashMap("one" -> 1, "two" -> 2))
     check(List(Some(mutable.HashMap(1->1, 2->2)), None, Some(mutable.HashMap(3->4))))
-    check(List(mutable.HashMap("one" -> 1, "two" -> 2),mutable.HashMap(1->"one",2->"two",3->"three")))
+    check(List(
+      mutable.HashMap("one" -> 1, "two" -> 2),
+      mutable.HashMap(1->"one",2->"two",3->"three")))
   }
 
   test("ranges") {
@@ -169,7 +171,10 @@ class KryoSerializerSuite extends FunSuite with SharedSparkContext {
 
   test("kryo with collect") {
     val control = 1 :: 2 :: Nil
-    val result = sc.parallelize(control, 2).map(new ClassWithoutNoArgConstructor(_)).collect().map(_.x)
+    val result = sc.parallelize(control, 2)
+      .map(new ClassWithoutNoArgConstructor(_))
+      .collect()
+      .map(_.x)
     assert(control === result.toSeq)
   }
 
@@ -237,7 +242,7 @@ class KryoSerializerSuite extends FunSuite with SharedSparkContext {
 
     // Set a special, broken ClassLoader and make sure we get an exception on deserialization
     ser.setDefaultClassLoader(new ClassLoader() {
-      override def loadClass(name: String) = throw new UnsupportedOperationException
+      override def loadClass(name: String): Class[_] = throw new UnsupportedOperationException
     })
     intercept[UnsupportedOperationException] {
       ser.newInstance().deserialize[ClassLoaderTestingObject](bytes)
@@ -287,14 +292,14 @@ object KryoTest {
 
   class ClassWithNoArgConstructor {
     var x: Int = 0
-    override def equals(other: Any) = other match {
+    override def equals(other: Any): Boolean = other match {
       case c: ClassWithNoArgConstructor => x == c.x
       case _ => false
     }
   }
 
   class ClassWithoutNoArgConstructor(val x: Int) {
-    override def equals(other: Any) = other match {
+    override def equals(other: Any): Boolean = other match {
       case c: ClassWithoutNoArgConstructor => x == c.x
       case _ => false
     }
diff --git a/core/src/test/scala/org/apache/spark/serializer/ProactiveClosureSerializationSuite.scala b/core/src/test/scala/org/apache/spark/serializer/ProactiveClosureSerializationSuite.scala
index d037e2c19a64d..433fd6bb4a11d 100644
--- a/core/src/test/scala/org/apache/spark/serializer/ProactiveClosureSerializationSuite.scala
+++ b/core/src/test/scala/org/apache/spark/serializer/ProactiveClosureSerializationSuite.scala
@@ -24,14 +24,16 @@ import org.apache.spark.rdd.RDD
 
 /* A trivial (but unserializable) container for trivial functions */
 class UnserializableClass {
-  def op[T](x: T) = x.toString
+  def op[T](x: T): String = x.toString
   
-  def pred[T](x: T) = x.toString.length % 2 == 0
+  def pred[T](x: T): Boolean = x.toString.length % 2 == 0
 }
 
 class ProactiveClosureSerializationSuite extends FunSuite with SharedSparkContext {
 
-  def fixture = (sc.parallelize(0 until 1000).map(_.toString), new UnserializableClass)
+  def fixture: (RDD[String], UnserializableClass) = {
+    (sc.parallelize(0 until 1000).map(_.toString), new UnserializableClass)
+  }
 
   test("throws expected serialization exceptions on actions") {
     val (data, uc) = fixture
diff --git a/core/src/test/scala/org/apache/spark/serializer/TestSerializer.scala b/core/src/test/scala/org/apache/spark/serializer/TestSerializer.scala
index 0ade1bab18d7e..963264cef3a71 100644
--- a/core/src/test/scala/org/apache/spark/serializer/TestSerializer.scala
+++ b/core/src/test/scala/org/apache/spark/serializer/TestSerializer.scala
@@ -27,7 +27,7 @@ import scala.reflect.ClassTag
  * A serializer implementation that always return a single element in a deserialization stream.
  */
 class TestSerializer extends Serializer {
-  override def newInstance() = new TestSerializerInstance
+  override def newInstance(): TestSerializerInstance = new TestSerializerInstance
 }
 
 
@@ -36,7 +36,8 @@ class TestSerializerInstance extends SerializerInstance {
 
   override def serializeStream(s: OutputStream): SerializationStream = ???
 
-  override def deserializeStream(s: InputStream) = new TestDeserializationStream
+  override def deserializeStream(s: InputStream): TestDeserializationStream =
+    new TestDeserializationStream
 
   override def deserialize[T: ClassTag](bytes: ByteBuffer): T = ???
 
diff --git a/core/src/test/scala/org/apache/spark/shuffle/hash/HashShuffleManagerSuite.scala b/core/src/test/scala/org/apache/spark/shuffle/hash/HashShuffleManagerSuite.scala
index b834dc0e735eb..7d76435cd75e7 100644
--- a/core/src/test/scala/org/apache/spark/shuffle/hash/HashShuffleManagerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/shuffle/hash/HashShuffleManagerSuite.scala
@@ -85,8 +85,8 @@ class HashShuffleManagerSuite extends FunSuite with LocalSparkContext {
     // Now comes the test :
     // Write to shuffle 3; and close it, but before registering it, check if the file lengths for
     // previous task (forof shuffle1) is the same as 'segments'. Earlier, we were inferring length
-    // of block based on remaining data in file : which could mess things up when there is concurrent read
-    // and writes happening to the same shuffle group.
+    // of block based on remaining data in file : which could mess things up when there is
+    // concurrent read and writes happening to the same shuffle group.
 
     val shuffle3 = shuffleBlockManager.forMapTask(1, 3, 1, new JavaSerializer(testConf),
       new ShuffleWriteMetrics)
diff --git a/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala b/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala
index 6dc5bc4cb08c4..545722b050ee8 100644
--- a/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala
@@ -60,7 +60,7 @@ class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfterEach
 
   // Implicitly convert strings to BlockIds for test clarity.
   implicit def StringToBlockId(value: String): BlockId = new TestBlockId(value)
-  def rdd(rddId: Int, splitId: Int) = RDDBlockId(rddId, splitId)
+  def rdd(rddId: Int, splitId: Int): RDDBlockId = RDDBlockId(rddId, splitId)
 
   private def makeBlockManager(
       maxMem: Long,
@@ -107,8 +107,10 @@ class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfterEach
 
   test("StorageLevel object caching") {
     val level1 = StorageLevel(false, false, false, false, 3)
-    val level2 = StorageLevel(false, false, false, false, 3) // this should return the same object as level1
-    val level3 = StorageLevel(false, false, false, false, 2) // this should return a different object
+    // this should return the same object as level1
+    val level2 = StorageLevel(false, false, false, false, 3)
+    // this should return a different object
+    val level3 = StorageLevel(false, false, false, false, 2)
     assert(level2 === level1, "level2 is not same as level1")
     assert(level2.eq(level1), "level2 is not the same object as level1")
     assert(level3 != level1, "level3 is same as level1")
@@ -802,7 +804,7 @@ class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfterEach
 
     // Create a non-trivial (not all zeros) byte array
     var counter = 0.toByte
-    def incr = {counter = (counter + 1).toByte; counter;}
+    def incr: Byte = {counter = (counter + 1).toByte; counter;}
     val bytes = Array.fill[Byte](1000)(incr)
     val byteBuffer = ByteBuffer.wrap(bytes)
 
@@ -956,8 +958,10 @@ class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfterEach
     store.putIterator("list3", list.iterator, StorageLevel.MEMORY_AND_DISK, tellMaster = true)
 
     // getLocations and getBlockStatus should yield the same locations
-    assert(store.master.getMatchingBlockIds(_.toString.contains("list"), askSlaves = false).size === 3)
-    assert(store.master.getMatchingBlockIds(_.toString.contains("list1"), askSlaves = false).size === 1)
+    assert(store.master.getMatchingBlockIds(_.toString.contains("list"), askSlaves = false).size
+      === 3)
+    assert(store.master.getMatchingBlockIds(_.toString.contains("list1"), askSlaves = false).size
+      === 1)
 
     // insert some more blocks
     store.putIterator("newlist1", list.iterator, StorageLevel.MEMORY_AND_DISK, tellMaster = true)
@@ -965,8 +969,10 @@ class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfterEach
     store.putIterator("newlist3", list.iterator, StorageLevel.MEMORY_AND_DISK, tellMaster = false)
 
     // getLocations and getBlockStatus should yield the same locations
-    assert(store.master.getMatchingBlockIds(_.toString.contains("newlist"), askSlaves = false).size === 1)
-    assert(store.master.getMatchingBlockIds(_.toString.contains("newlist"), askSlaves = true).size === 3)
+    assert(store.master.getMatchingBlockIds(_.toString.contains("newlist"), askSlaves = false).size
+      === 1)
+    assert(store.master.getMatchingBlockIds(_.toString.contains("newlist"), askSlaves = true).size
+      === 3)
 
     val blockIds = Seq(RDDBlockId(1, 0), RDDBlockId(1, 1), RDDBlockId(2, 0))
     blockIds.foreach { blockId =>
@@ -1090,8 +1096,8 @@ class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfterEach
     val memoryStore = store.memoryStore
     val smallList = List.fill(40)(new Array[Byte](100))
     val bigList = List.fill(40)(new Array[Byte](1000))
-    def smallIterator = smallList.iterator.asInstanceOf[Iterator[Any]]
-    def bigIterator = bigList.iterator.asInstanceOf[Iterator[Any]]
+    def smallIterator: Iterator[Any] = smallList.iterator.asInstanceOf[Iterator[Any]]
+    def bigIterator: Iterator[Any] = bigList.iterator.asInstanceOf[Iterator[Any]]
     assert(memoryStore.currentUnrollMemoryForThisThread === 0)
 
     // Unroll with plenty of space. This should succeed and cache both blocks.
@@ -1144,8 +1150,8 @@ class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfterEach
     val diskStore = store.diskStore
     val smallList = List.fill(40)(new Array[Byte](100))
     val bigList = List.fill(40)(new Array[Byte](1000))
-    def smallIterator = smallList.iterator.asInstanceOf[Iterator[Any]]
-    def bigIterator = bigList.iterator.asInstanceOf[Iterator[Any]]
+    def smallIterator: Iterator[Any] = smallList.iterator.asInstanceOf[Iterator[Any]]
+    def bigIterator: Iterator[Any] = bigList.iterator.asInstanceOf[Iterator[Any]]
     assert(memoryStore.currentUnrollMemoryForThisThread === 0)
 
     store.putIterator("b1", smallIterator, memAndDisk)
@@ -1187,7 +1193,7 @@ class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfterEach
     val memOnly = StorageLevel.MEMORY_ONLY
     val memoryStore = store.memoryStore
     val smallList = List.fill(40)(new Array[Byte](100))
-    def smallIterator = smallList.iterator.asInstanceOf[Iterator[Any]]
+    def smallIterator: Iterator[Any] = smallList.iterator.asInstanceOf[Iterator[Any]]
     assert(memoryStore.currentUnrollMemoryForThisThread === 0)
 
     // All unroll memory used is released because unrollSafely returned an array
diff --git a/core/src/test/scala/org/apache/spark/storage/LocalDirsSuite.scala b/core/src/test/scala/org/apache/spark/storage/LocalDirsSuite.scala
index 82a82e23eecf2..b47157f8331cc 100644
--- a/core/src/test/scala/org/apache/spark/storage/LocalDirsSuite.scala
+++ b/core/src/test/scala/org/apache/spark/storage/LocalDirsSuite.scala
@@ -47,7 +47,7 @@ class LocalDirsSuite extends FunSuite with BeforeAndAfter {
     assert(!new File("/NONEXISTENT_DIR").exists())
     // SPARK_LOCAL_DIRS is a valid directory:
     class MySparkConf extends SparkConf(false) {
-      override def getenv(name: String) = {
+      override def getenv(name: String): String = {
         if (name == "SPARK_LOCAL_DIRS") System.getProperty("java.io.tmpdir")
         else super.getenv(name)
       }
diff --git a/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala b/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala
index 0d155982a8c54..1cb594633f331 100644
--- a/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala
+++ b/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala
@@ -137,7 +137,7 @@ class UISeleniumSuite extends FunSuite with WebBrowser with Matchers with Before
       new SparkContext(conf)
     }
 
-    def hasKillLink = find(className("kill-link")).isDefined
+    def hasKillLink: Boolean = find(className("kill-link")).isDefined
     def runSlowJob(sc: SparkContext) {
       sc.parallelize(1 to 10).map{x => Thread.sleep(10000); x}.countAsync()
     }
diff --git a/core/src/test/scala/org/apache/spark/ui/jobs/JobProgressListenerSuite.scala b/core/src/test/scala/org/apache/spark/ui/jobs/JobProgressListenerSuite.scala
index c0c28cb60e21d..21d8267114133 100644
--- a/core/src/test/scala/org/apache/spark/ui/jobs/JobProgressListenerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/ui/jobs/JobProgressListenerSuite.scala
@@ -269,7 +269,7 @@ class JobProgressListenerSuite extends FunSuite with LocalSparkContext with Matc
     val taskType = Utils.getFormattedClassName(new ShuffleMapTask(0))
     val execId = "exe-1"
 
-    def makeTaskMetrics(base: Int) = {
+    def makeTaskMetrics(base: Int): TaskMetrics = {
       val taskMetrics = new TaskMetrics()
       val shuffleReadMetrics = new ShuffleReadMetrics()
       val shuffleWriteMetrics = new ShuffleWriteMetrics()
@@ -291,7 +291,7 @@ class JobProgressListenerSuite extends FunSuite with LocalSparkContext with Matc
       taskMetrics
     }
 
-    def makeTaskInfo(taskId: Long, finishTime: Int = 0) = {
+    def makeTaskInfo(taskId: Long, finishTime: Int = 0): TaskInfo = {
       val taskInfo = new TaskInfo(taskId, 0, 1, 0L, execId, "host1", TaskLocality.NODE_LOCAL,
         false)
       taskInfo.finishTime = finishTime
diff --git a/core/src/test/scala/org/apache/spark/ui/storage/StorageTabSuite.scala b/core/src/test/scala/org/apache/spark/ui/storage/StorageTabSuite.scala
index e1bc1379b5d80..3744e479d2f05 100644
--- a/core/src/test/scala/org/apache/spark/ui/storage/StorageTabSuite.scala
+++ b/core/src/test/scala/org/apache/spark/ui/storage/StorageTabSuite.scala
@@ -107,7 +107,8 @@ class StorageTabSuite extends FunSuite with BeforeAndAfter {
     val myRddInfo0 = rddInfo0
     val myRddInfo1 = rddInfo1
     val myRddInfo2 = rddInfo2
-    val stageInfo0 = new StageInfo(0, 0, "0", 100, Seq(myRddInfo0, myRddInfo1, myRddInfo2), "details")
+    val stageInfo0 = new StageInfo(
+      0, 0, "0", 100, Seq(myRddInfo0, myRddInfo1, myRddInfo2), "details")
     bus.postToAll(SparkListenerBlockManagerAdded(1L, bm1, 1000L))
     bus.postToAll(SparkListenerStageSubmitted(stageInfo0))
     assert(storageListener._rddInfoMap.size === 3)
diff --git a/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala b/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala
index 054ef54e746a5..c47162779bbba 100644
--- a/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala
@@ -83,7 +83,7 @@ object TestObject {
 class TestClass extends Serializable {
   var x = 5
 
-  def getX = x
+  def getX: Int = x
 
   def run(): Int = {
     var nonSer = new NonSerializable
@@ -95,7 +95,7 @@ class TestClass extends Serializable {
 }
 
 class TestClassWithoutDefaultConstructor(x: Int) extends Serializable {
-  def getX = x
+  def getX: Int = x
 
   def run(): Int = {
     var nonSer = new NonSerializable
@@ -164,7 +164,7 @@ object TestObjectWithNesting {
 }
 
 class TestClassWithNesting(val y: Int) extends Serializable {
-  def getY = y
+  def getY: Int = y
 
   def run(): Int = {
     var nonSer = new NonSerializable
diff --git a/core/src/test/scala/org/apache/spark/util/FileAppenderSuite.scala b/core/src/test/scala/org/apache/spark/util/FileAppenderSuite.scala
index 43b6a405cb68c..c05317534cddf 100644
--- a/core/src/test/scala/org/apache/spark/util/FileAppenderSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/FileAppenderSuite.scala
@@ -109,7 +109,8 @@ class FileAppenderSuite extends FunSuite with BeforeAndAfter with Logging {
 
     // verify whether the earliest file has been deleted
     val rolledOverFiles = allGeneratedFiles.filter { _ != testFile.toString }.toArray.sorted
-    logInfo(s"All rolled over files generated:${rolledOverFiles.size}\n" + rolledOverFiles.mkString("\n"))
+    logInfo(s"All rolled over files generated:${rolledOverFiles.size}\n" +
+      rolledOverFiles.mkString("\n"))
     assert(rolledOverFiles.size > 2)
     val earliestRolledOverFile = rolledOverFiles.head
     val existingRolledOverFiles = RollingFileAppender.getSortedRolledOverFiles(
@@ -135,7 +136,7 @@ class FileAppenderSuite extends FunSuite with BeforeAndAfter with Logging {
       val testOutputStream = new PipedOutputStream()
       val testInputStream = new PipedInputStream(testOutputStream)
       val appender = FileAppender(testInputStream, testFile, conf)
-      //assert(appender.getClass === classTag[ExpectedAppender].getClass)
+      // assert(appender.getClass === classTag[ExpectedAppender].getClass)
       assert(appender.getClass.getSimpleName ===
         classTag[ExpectedAppender].runtimeClass.getSimpleName)
       if (appender.isInstanceOf[RollingFileAppender]) {
@@ -153,9 +154,11 @@ class FileAppenderSuite extends FunSuite with BeforeAndAfter with Logging {
 
     import RollingFileAppender._
 
-    def rollingStrategy(strategy: String) = Seq(STRATEGY_PROPERTY -> strategy)
-    def rollingSize(size: String) = Seq(SIZE_PROPERTY -> size)
-    def rollingInterval(interval: String) = Seq(INTERVAL_PROPERTY -> interval)
+    def rollingStrategy(strategy: String): Seq[(String, String)] =
+      Seq(STRATEGY_PROPERTY -> strategy)
+    def rollingSize(size: String): Seq[(String, String)] = Seq(SIZE_PROPERTY -> size)
+    def rollingInterval(interval: String): Seq[(String, String)] =
+      Seq(INTERVAL_PROPERTY -> interval)
 
     val msInDay = 24 * 60 * 60 * 1000L
     val msInHour = 60 * 60 * 1000L
diff --git a/core/src/test/scala/org/apache/spark/util/NextIteratorSuite.scala b/core/src/test/scala/org/apache/spark/util/NextIteratorSuite.scala
index 72e81f3f1a884..403dcb03bd6e5 100644
--- a/core/src/test/scala/org/apache/spark/util/NextIteratorSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/NextIteratorSuite.scala
@@ -71,7 +71,7 @@ class NextIteratorSuite extends FunSuite with Matchers {
   class StubIterator(ints: Buffer[Int])  extends NextIterator[Int] {
     var closeCalled = 0
 
-    override def getNext() = {
+    override def getNext(): Int = {
       if (ints.size == 0) {
         finished = true
         0
diff --git a/core/src/test/scala/org/apache/spark/util/SizeEstimatorSuite.scala b/core/src/test/scala/org/apache/spark/util/SizeEstimatorSuite.scala
index 7424c2e91d4f2..67a9f75ff2187 100644
--- a/core/src/test/scala/org/apache/spark/util/SizeEstimatorSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/SizeEstimatorSuite.scala
@@ -98,8 +98,10 @@ class SizeEstimatorSuite
 
     // If an array contains the *same* element many times, we should only count it once.
     val d1 = new DummyClass1
-    assertResult(72)(SizeEstimator.estimate(Array.fill(10)(d1))) // 10 pointers plus 8-byte object
-    assertResult(432)(SizeEstimator.estimate(Array.fill(100)(d1))) // 100 pointers plus 8-byte object
+    // 10 pointers plus 8-byte object
+    assertResult(72)(SizeEstimator.estimate(Array.fill(10)(d1)))
+    // 100 pointers plus 8-byte object
+    assertResult(432)(SizeEstimator.estimate(Array.fill(100)(d1)))
 
     // Same thing with huge array containing the same element many times. Note that this won't
     // return exactly 4032 because it can't tell that *all* the elements will equal the first
diff --git a/core/src/test/scala/org/apache/spark/util/TimeStampedHashMapSuite.scala b/core/src/test/scala/org/apache/spark/util/TimeStampedHashMapSuite.scala
index c1c605cdb487b..8b72fe665c214 100644
--- a/core/src/test/scala/org/apache/spark/util/TimeStampedHashMapSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/TimeStampedHashMapSuite.scala
@@ -63,7 +63,7 @@ class TimeStampedHashMapSuite extends FunSuite {
     assert(map1.getTimestamp("k1").get < threshTime1)
     assert(map1.getTimestamp("k2").isDefined)
     assert(map1.getTimestamp("k2").get >= threshTime1)
-    map1.clearOldValues(threshTime1) //should only clear k1
+    map1.clearOldValues(threshTime1) // should only clear k1
     assert(map1.get("k1") === None)
     assert(map1.get("k2").isDefined)
   }
@@ -93,7 +93,7 @@ class TimeStampedHashMapSuite extends FunSuite {
     assert(map1.getTimestamp("k1").get < threshTime1)
     assert(map1.getTimestamp("k2").isDefined)
     assert(map1.getTimestamp("k2").get >= threshTime1)
-    map1.clearOldValues(threshTime1) //should only clear k1
+    map1.clearOldValues(threshTime1) // should only clear k1
     assert(map1.get("k1") === None)
     assert(map1.get("k2").isDefined)
   }
diff --git a/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
index 5d93086082189..449fb87f111c4 100644
--- a/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
@@ -106,7 +106,7 @@ class UtilsSuite extends FunSuite with ResetSystemProperties {
     val second = 1000
     val minute = second * 60
     val hour = minute * 60
-    def str = Utils.msDurationToString(_)
+    def str: (Long) => String = Utils.msDurationToString(_)
 
     val sep = new DecimalFormatSymbols(Locale.getDefault()).getDecimalSeparator()
 
@@ -199,7 +199,8 @@ class UtilsSuite extends FunSuite with ResetSystemProperties {
   test("doesDirectoryContainFilesNewerThan") {
     // create some temporary directories and files
     val parent: File = Utils.createTempDir()
-    val child1: File = Utils.createTempDir(parent.getCanonicalPath) // The parent directory has two child directories
+    // The parent directory has two child directories
+    val child1: File = Utils.createTempDir(parent.getCanonicalPath)
     val child2: File = Utils.createTempDir(parent.getCanonicalPath)
     val child3: File = Utils.createTempDir(child1.getCanonicalPath)
     // set the last modified time of child1 to 30 secs old
diff --git a/core/src/test/scala/org/apache/spark/util/VectorSuite.scala b/core/src/test/scala/org/apache/spark/util/VectorSuite.scala
index 794a55d61750b..ce2968728a996 100644
--- a/core/src/test/scala/org/apache/spark/util/VectorSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/VectorSuite.scala
@@ -27,7 +27,7 @@ import org.scalatest.FunSuite
 @deprecated("suppress compile time deprecation warning", "1.0.0")
 class VectorSuite extends FunSuite {
 
-  def verifyVector(vector: Vector, expectedLength: Int) = {
+  def verifyVector(vector: Vector, expectedLength: Int): Unit = {
     assert(vector.length == expectedLength)
     assert(vector.elements.min > 0.0)
     assert(vector.elements.max < 1.0)
diff --git a/core/src/test/scala/org/apache/spark/util/collection/ExternalAppendOnlyMapSuite.scala b/core/src/test/scala/org/apache/spark/util/collection/ExternalAppendOnlyMapSuite.scala
index 48f79ea651018..dff8f3ddc816f 100644
--- a/core/src/test/scala/org/apache/spark/util/collection/ExternalAppendOnlyMapSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/collection/ExternalAppendOnlyMapSuite.scala
@@ -185,7 +185,7 @@ class ExternalAppendOnlyMapSuite extends FunSuite with LocalSparkContext {
 
     // reduceByKey
     val rdd = sc.parallelize(1 to 10).map(i => (i%2, 1))
-    val result1 = rdd.reduceByKey(_+_).collect()
+    val result1 = rdd.reduceByKey(_ + _).collect()
     assert(result1.toSet === Set[(Int, Int)]((0, 5), (1, 5)))
 
     // groupByKey
diff --git a/core/src/test/scala/org/apache/spark/util/collection/ExternalSorterSuite.scala b/core/src/test/scala/org/apache/spark/util/collection/ExternalSorterSuite.scala
index 72d96798b1141..9ff067f86af44 100644
--- a/core/src/test/scala/org/apache/spark/util/collection/ExternalSorterSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/collection/ExternalSorterSuite.scala
@@ -553,10 +553,10 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe
     conf.set("spark.shuffle.memoryFraction", "0.001")
     sc = new SparkContext("local-cluster[1,1,512]", "test", conf)
 
-    def createCombiner(i: String) = ArrayBuffer[String](i)
-    def mergeValue(buffer: ArrayBuffer[String], i: String) = buffer += i
-    def mergeCombiners(buffer1: ArrayBuffer[String], buffer2: ArrayBuffer[String]) =
-      buffer1 ++= buffer2
+    def createCombiner(i: String): ArrayBuffer[String] = ArrayBuffer[String](i)
+    def mergeValue(buffer: ArrayBuffer[String], i: String): ArrayBuffer[String] = buffer += i
+    def mergeCombiners(buffer1: ArrayBuffer[String], buffer2: ArrayBuffer[String])
+      : ArrayBuffer[String] = buffer1 ++= buffer2
 
     val agg = new Aggregator[String, String, ArrayBuffer[String]](
       createCombiner _, mergeValue _, mergeCombiners _)
@@ -633,14 +633,17 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe
     conf.set("spark.shuffle.memoryFraction", "0.001")
     sc = new SparkContext("local-cluster[1,1,512]", "test", conf)
 
-    def createCombiner(i: Int) = ArrayBuffer[Int](i)
-    def mergeValue(buffer: ArrayBuffer[Int], i: Int) = buffer += i
-    def mergeCombiners(buf1: ArrayBuffer[Int], buf2: ArrayBuffer[Int]) = buf1 ++= buf2
+    def createCombiner(i: Int): ArrayBuffer[Int] = ArrayBuffer[Int](i)
+    def mergeValue(buffer: ArrayBuffer[Int], i: Int): ArrayBuffer[Int] = buffer += i
+    def mergeCombiners(buf1: ArrayBuffer[Int], buf2: ArrayBuffer[Int]): ArrayBuffer[Int] = {
+      buf1 ++= buf2
+    }
 
     val agg = new Aggregator[Int, Int, ArrayBuffer[Int]](createCombiner, mergeValue, mergeCombiners)
     val sorter = new ExternalSorter[Int, Int, ArrayBuffer[Int]](Some(agg), None, None, None)
 
-    sorter.insertAll((1 to 100000).iterator.map(i => (i, i)) ++ Iterator((Int.MaxValue, Int.MaxValue)))
+    sorter.insertAll(
+      (1 to 100000).iterator.map(i => (i, i)) ++ Iterator((Int.MaxValue, Int.MaxValue)))
 
     val it = sorter.iterator
     while (it.hasNext) {
@@ -654,9 +657,10 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe
     conf.set("spark.shuffle.memoryFraction", "0.001")
     sc = new SparkContext("local-cluster[1,1,512]", "test", conf)
 
-    def createCombiner(i: String) = ArrayBuffer[String](i)
-    def mergeValue(buffer: ArrayBuffer[String], i: String) = buffer += i
-    def mergeCombiners(buf1: ArrayBuffer[String], buf2: ArrayBuffer[String]) = buf1 ++= buf2
+    def createCombiner(i: String): ArrayBuffer[String] = ArrayBuffer[String](i)
+    def mergeValue(buffer: ArrayBuffer[String], i: String): ArrayBuffer[String] = buffer += i
+    def mergeCombiners(buf1: ArrayBuffer[String], buf2: ArrayBuffer[String]): ArrayBuffer[String] =
+      buf1 ++= buf2
 
     val agg = new Aggregator[String, String, ArrayBuffer[String]](
       createCombiner, mergeValue, mergeCombiners)
@@ -720,7 +724,7 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe
     // Using wrongOrdering to show integer overflow introduced exception.
     val rand = new Random(100L)
     val wrongOrdering = new Ordering[String] {
-      override def compare(a: String, b: String) = {
+      override def compare(a: String, b: String): Int = {
         val h1 = if (a == null) 0 else a.hashCode()
         val h2 = if (b == null) 0 else b.hashCode()
         h1 - h2
@@ -742,9 +746,10 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe
 
     // Using aggregation and external spill to make sure ExternalSorter using
     // partitionKeyComparator.
-    def createCombiner(i: String) = ArrayBuffer(i)
-    def mergeValue(c: ArrayBuffer[String], i: String) = c += i
-    def mergeCombiners(c1: ArrayBuffer[String], c2: ArrayBuffer[String]) = c1 ++= c2
+    def createCombiner(i: String): ArrayBuffer[String] = ArrayBuffer(i)
+    def mergeValue(c: ArrayBuffer[String], i: String): ArrayBuffer[String] = c += i
+    def mergeCombiners(c1: ArrayBuffer[String], c2: ArrayBuffer[String]): ArrayBuffer[String] =
+      c1 ++= c2
 
     val agg = new Aggregator[String, String, ArrayBuffer[String]](
       createCombiner, mergeValue, mergeCombiners)
diff --git a/core/src/test/scala/org/apache/spark/util/random/XORShiftRandomSuite.scala b/core/src/test/scala/org/apache/spark/util/random/XORShiftRandomSuite.scala
index ef7178bcdf5c2..03f5f2d1b8528 100644
--- a/core/src/test/scala/org/apache/spark/util/random/XORShiftRandomSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/random/XORShiftRandomSuite.scala
@@ -28,7 +28,7 @@ import scala.language.reflectiveCalls
 
 class XORShiftRandomSuite extends FunSuite with Matchers {
 
-  def fixture = new {
+  def fixture: Object {val seed: Long; val hundMil: Int; val xorRand: XORShiftRandom} = new {
     val seed = 1L
     val xorRand = new XORShiftRandom(seed)
     val hundMil = 1e8.toInt

From fc17661475443d9f0a8d28e3439feeb7a7bca67b Mon Sep 17 00:00:00 2001
From: lewuathe <lewuathe@me.com>
Date: Sun, 12 Apr 2015 22:17:16 -0700
Subject: [PATCH 65/95] [SPARK-6643][MLLIB] Implement StandardScalerModel
 missing methods

This is the sub-task of SPARK-6254.
Wrap missing method for `StandardScalerModel`.

Author: lewuathe <lewuathe@me.com>

Closes #5310 from Lewuathe/SPARK-6643 and squashes the following commits:

fafd690 [lewuathe] Fix for lint-python
bd31a64 [lewuathe] Merge branch 'master' into SPARK-6643
578f5ee [lewuathe] Remove unnecessary class
a38f155 [lewuathe] Merge master
66bb2ab [lewuathe] Fix typos
82683a0 [lewuathe] [SPARK-6643] Implement StandardScalerModel missing methods
---
 .../mllib/api/python/PythonMLLibAPI.scala     |  4 ++--
 python/pyspark/mllib/feature.py               | 16 +++++++++++++
 python/pyspark/mllib/tests.py                 | 24 +++++++++++++++++++
 3 files changed, 42 insertions(+), 2 deletions(-)

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
index 1faa3def0e042..ab15f0f36a14b 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
@@ -450,9 +450,9 @@ private[python] class PythonMLLibAPI extends Serializable {
   def normalizeVector(p: Double, rdd: JavaRDD[Vector]): JavaRDD[Vector] = {
     new Normalizer(p).transform(rdd)
   }
-
+  
   /**
-   * Java stub for IDF.fit(). This stub returns a
+   * Java stub for StandardScaler.fit(). This stub returns a
    * handle to the Java object instead of the content of the Java object.
    * Extra care needs to be taken in the Python code to ensure it gets freed on
    * exit; see the Py4J documentation.
diff --git a/python/pyspark/mllib/feature.py b/python/pyspark/mllib/feature.py
index 3cda1205e1391..8be819aceec24 100644
--- a/python/pyspark/mllib/feature.py
+++ b/python/pyspark/mllib/feature.py
@@ -132,6 +132,22 @@ def transform(self, vector):
         """
         return JavaVectorTransformer.transform(self, vector)
 
+    def setWithMean(self, withMean):
+        """
+        Setter of the boolean which decides
+        whether it uses mean or not
+        """
+        self.call("setWithMean", withMean)
+        return self
+
+    def setWithStd(self, withStd):
+        """
+        Setter of the boolean which decides
+        whether it uses std or not
+        """
+        self.call("setWithStd", withStd)
+        return self
+
 
 class StandardScaler(object):
     """
diff --git a/python/pyspark/mllib/tests.py b/python/pyspark/mllib/tests.py
index 3b40158c12b74..8eaddcf8b9b5e 100644
--- a/python/pyspark/mllib/tests.py
+++ b/python/pyspark/mllib/tests.py
@@ -44,6 +44,7 @@
 from pyspark.mllib.stat import Statistics
 from pyspark.mllib.feature import Word2Vec
 from pyspark.mllib.feature import IDF
+from pyspark.mllib.feature import StandardScaler
 from pyspark.serializers import PickleSerializer
 from pyspark.sql import SQLContext
 from pyspark.tests import ReusedPySparkTestCase as PySparkTestCase
@@ -745,6 +746,29 @@ def test_word2vec_get_vectors(self):
         model = Word2Vec().fit(self.sc.parallelize(data))
         self.assertEquals(len(model.getVectors()), 3)
 
+
+class StandardScalerTests(PySparkTestCase):
+    def test_model_setters(self):
+        data = [
+            [1.0, 2.0, 3.0],
+            [2.0, 3.0, 4.0],
+            [3.0, 4.0, 5.0]
+        ]
+        model = StandardScaler().fit(self.sc.parallelize(data))
+        self.assertIsNotNone(model.setWithMean(True))
+        self.assertIsNotNone(model.setWithStd(True))
+        self.assertEqual(model.transform([1.0, 2.0, 3.0]), DenseVector([-1.0, -1.0, -1.0]))
+
+    def test_model_transform(self):
+        data = [
+            [1.0, 2.0, 3.0],
+            [2.0, 3.0, 4.0],
+            [3.0, 4.0, 5.0]
+        ]
+        model = StandardScaler().fit(self.sc.parallelize(data))
+        self.assertEqual(model.transform([1.0, 2.0, 3.0]), DenseVector([1.0, 2.0, 3.0]))
+
+
 if __name__ == "__main__":
     if not _have_scipy:
         print "NOTE: Skipping SciPy tests as it does not seem to be installed"

From d3792f54974e16cbe8f10b3091d248e0bdd48986 Mon Sep 17 00:00:00 2001
From: "Joseph K. Bradley" <joseph@databricks.com>
Date: Sun, 12 Apr 2015 22:38:27 -0700
Subject: [PATCH 66/95] [SPARK-4081] [mllib]  VectorIndexer

**Ready for review!**

Since the original PR, I moved the code to the spark.ml API and renamed this to VectorIndexer.

This introduces a VectorIndexer class which does the following:
* VectorIndexer.fit(): collect statistics about how many values each feature in a dataset (RDD[Vector]) can take (limited by maxCategories)
  * Feature which exceed maxCategories are declared continuous, and the Model will treat them as such.
* VectorIndexerModel.transform(): Convert categorical feature values to corresponding 0-based indices

Design notes:
* This maintains sparsity in vectors by ensuring that categorical feature value 0.0 gets index 0.
* This does not yet support transforming data with new (unknown) categorical feature values.  That can be added later.
* This is necessary for DecisionTree and tree ensembles.

Reviewers: Please check my use of metadata and my unit tests for it; I'm not sure if I covered everything in the tests.

Other notes:
* This also adds a public toMetadata method to AttributeGroup (for simpler construction of metadata).

CC: mengxr

Author: Joseph K. Bradley <joseph@databricks.com>

Closes #3000 from jkbradley/indexer and squashes the following commits:

5956d91 [Joseph K. Bradley] minor cleanups
f5c57a8 [Joseph K. Bradley] added Java test suite
643b444 [Joseph K. Bradley] removed FeatureTests
02236c3 [Joseph K. Bradley] Updated VectorIndexer, ready for PR
286d221 [Joseph K. Bradley] Reworked DatasetIndexer for spark.ml API, and renamed it to VectorIndexer
12e6cf2 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into indexer
6d8f3f1 [Joseph K. Bradley] Added partly done DatasetIndexer to spark.ml
6a2f553 [Joseph K. Bradley] Updated TODO for allowUnknownCategories
3f041f8 [Joseph K. Bradley] Final cleanups for DatasetIndexer
038b9e3 [Joseph K. Bradley] DatasetIndexer now maintains sparsity in SparseVector
3a4a0bd [Joseph K. Bradley] Added another test for DatasetIndexer
2006923 [Joseph K. Bradley] DatasetIndexer now passes tests
f409987 [Joseph K. Bradley] partly done with DatasetIndexerSuite
5e7c874 [Joseph K. Bradley] working on DatasetIndexer
---
 .../scala/org/apache/spark/ml/Pipeline.scala  |   3 +
 .../spark/ml/attribute/AttributeGroup.scala   |  21 +-
 .../spark/ml/feature/VectorIndexer.scala      | 393 ++++++++++++++++++
 .../org/apache/spark/ml/param/params.scala    |  20 +-
 .../ml/feature/JavaVectorIndexerSuite.java    |  70 ++++
 .../ml/attribute/AttributeGroupSuite.scala    |   8 +-
 .../spark/ml/feature/NormalizerSuite.scala    |   7 +-
 .../spark/ml/feature/VectorIndexerSuite.scala | 255 ++++++++++++
 .../apache/spark/ml/util/TestingUtils.scala   |  60 +++
 9 files changed, 818 insertions(+), 19 deletions(-)
 create mode 100644 mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala
 create mode 100644 mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorIndexerSuite.java
 create mode 100644 mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala
 create mode 100644 mllib/src/test/scala/org/apache/spark/ml/util/TestingUtils.scala

diff --git a/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala b/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala
index c4a36103303a2..a455341a1f723 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala
@@ -47,6 +47,9 @@ abstract class PipelineStage extends Serializable with Logging {
 
   /**
    * Derives the output schema from the input schema and parameters, optionally with logging.
+   *
+   * This should be optimistic.  If it is unclear whether the schema will be valid, then it should
+   * be assumed valid until proven otherwise.
    */
   protected def transformSchema(
       schema: StructType,
diff --git a/mllib/src/main/scala/org/apache/spark/ml/attribute/AttributeGroup.scala b/mllib/src/main/scala/org/apache/spark/ml/attribute/AttributeGroup.scala
index 970e6ad5514d1..aa27a668f1695 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/attribute/AttributeGroup.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/attribute/AttributeGroup.scala
@@ -106,7 +106,7 @@ class AttributeGroup private (
   def getAttr(attrIndex: Int): Attribute = this(attrIndex)
 
   /** Converts to metadata without name. */
-  private[attribute] def toMetadata: Metadata = {
+  private[attribute] def toMetadataImpl: Metadata = {
     import AttributeKeys._
     val bldr = new MetadataBuilder()
     if (attributes.isDefined) {
@@ -142,17 +142,24 @@ class AttributeGroup private (
     bldr.build()
   }
 
-  /** Converts to a StructField with some existing metadata. */
-  def toStructField(existingMetadata: Metadata): StructField = {
-    val newMetadata = new MetadataBuilder()
+  /** Converts to ML metadata with some existing metadata. */
+  def toMetadata(existingMetadata: Metadata): Metadata = {
+    new MetadataBuilder()
       .withMetadata(existingMetadata)
-      .putMetadata(AttributeKeys.ML_ATTR, toMetadata)
+      .putMetadata(AttributeKeys.ML_ATTR, toMetadataImpl)
       .build()
-    StructField(name, new VectorUDT, nullable = false, newMetadata)
+  }
+
+  /** Converts to ML metadata */
+  def toMetadata: Metadata = toMetadata(Metadata.empty)
+
+  /** Converts to a StructField with some existing metadata. */
+  def toStructField(existingMetadata: Metadata): StructField = {
+    StructField(name, new VectorUDT, nullable = false, toMetadata(existingMetadata))
   }
 
   /** Converts to a StructField. */
-  def toStructField(): StructField = toStructField(Metadata.empty)
+  def toStructField: StructField = toStructField(Metadata.empty)
 
   override def equals(other: Any): Boolean = {
     other match {
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala
new file mode 100644
index 0000000000000..8760960e19272
--- /dev/null
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala
@@ -0,0 +1,393 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.feature
+
+import org.apache.spark.annotation.AlphaComponent
+import org.apache.spark.ml.{Estimator, Model}
+import org.apache.spark.ml.attribute.{BinaryAttribute, NumericAttribute, NominalAttribute,
+  Attribute, AttributeGroup}
+import org.apache.spark.ml.param.{HasInputCol, HasOutputCol, IntParam, ParamMap, Params}
+import org.apache.spark.mllib.linalg.{SparseVector, DenseVector, Vector, VectorUDT}
+import org.apache.spark.sql.{Row, DataFrame}
+import org.apache.spark.sql.functions.callUDF
+import org.apache.spark.sql.types.{StructField, StructType}
+import org.apache.spark.util.collection.OpenHashSet
+
+
+/** Private trait for params for VectorIndexer and VectorIndexerModel */
+private[ml] trait VectorIndexerParams extends Params with HasInputCol with HasOutputCol {
+
+  /**
+   * Threshold for the number of values a categorical feature can take.
+   * If a feature is found to have > maxCategories values, then it is declared continuous.
+   *
+   * (default = 20)
+   */
+  val maxCategories = new IntParam(this, "maxCategories",
+    "Threshold for the number of values a categorical feature can take." +
+      " If a feature is found to have > maxCategories values, then it is declared continuous.",
+    Some(20))
+
+  /** @group getParam */
+  def getMaxCategories: Int = get(maxCategories)
+}
+
+/**
+ * :: AlphaComponent ::
+ *
+ * Class for indexing categorical feature columns in a dataset of [[Vector]].
+ *
+ * This has 2 usage modes:
+ *  - Automatically identify categorical features (default behavior)
+ *     - This helps process a dataset of unknown vectors into a dataset with some continuous
+ *       features and some categorical features. The choice between continuous and categorical
+ *       is based upon a maxCategories parameter.
+ *     - Set maxCategories to the maximum number of categorical any categorical feature should have.
+ *     - E.g.: Feature 0 has unique values {-1.0, 0.0}, and feature 1 values {1.0, 3.0, 5.0}.
+ *       If maxCategories = 2, then feature 0 will be declared categorical and use indices {0, 1},
+ *       and feature 1 will be declared continuous.
+ *  - Index all features, if all features are categorical
+ *     - If maxCategories is set to be very large, then this will build an index of unique
+ *       values for all features.
+ *     - Warning: This can cause problems if features are continuous since this will collect ALL
+ *       unique values to the driver.
+ *     - E.g.: Feature 0 has unique values {-1.0, 0.0}, and feature 1 values {1.0, 3.0, 5.0}.
+ *       If maxCategories >= 3, then both features will be declared categorical.
+ *
+ * This returns a model which can transform categorical features to use 0-based indices.
+ *
+ * Index stability:
+ *  - This is not guaranteed to choose the same category index across multiple runs.
+ *  - If a categorical feature includes value 0, then this is guaranteed to map value 0 to index 0.
+ *    This maintains vector sparsity.
+ *  - More stability may be added in the future.
+ *
+ * TODO: Future extensions: The following functionality is planned for the future:
+ *  - Preserve metadata in transform; if a feature's metadata is already present, do not recompute.
+ *  - Specify certain features to not index, either via a parameter or via existing metadata.
+ *  - Add warning if a categorical feature has only 1 category.
+ *  - Add option for allowing unknown categories.
+ */
+@AlphaComponent
+class VectorIndexer extends Estimator[VectorIndexerModel] with VectorIndexerParams {
+
+  /** @group setParam */
+  def setMaxCategories(value: Int): this.type = {
+    require(value > 1,
+      s"DatasetIndexer given maxCategories = value, but requires maxCategories > 1.")
+    set(maxCategories, value)
+  }
+
+  /** @group setParam */
+  def setInputCol(value: String): this.type = set(inputCol, value)
+
+  /** @group setParam */
+  def setOutputCol(value: String): this.type = set(outputCol, value)
+
+  override def fit(dataset: DataFrame, paramMap: ParamMap): VectorIndexerModel = {
+    transformSchema(dataset.schema, paramMap, logging = true)
+    val map = this.paramMap ++ paramMap
+    val firstRow = dataset.select(map(inputCol)).take(1)
+    require(firstRow.length == 1, s"VectorIndexer cannot be fit on an empty dataset.")
+    val numFeatures = firstRow(0).getAs[Vector](0).size
+    val vectorDataset = dataset.select(map(inputCol)).map { case Row(v: Vector) => v }
+    val maxCats = map(maxCategories)
+    val categoryStats: VectorIndexer.CategoryStats = vectorDataset.mapPartitions { iter =>
+      val localCatStats = new VectorIndexer.CategoryStats(numFeatures, maxCats)
+      iter.foreach(localCatStats.addVector)
+      Iterator(localCatStats)
+    }.reduce((stats1, stats2) => stats1.merge(stats2))
+    val model = new VectorIndexerModel(this, map, numFeatures, categoryStats.getCategoryMaps)
+    Params.inheritValues(map, this, model)
+    model
+  }
+
+  override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = {
+    // We do not transfer feature metadata since we do not know what types of features we will
+    // produce in transform().
+    val map = this.paramMap ++ paramMap
+    val dataType = new VectorUDT
+    require(map.contains(inputCol), s"VectorIndexer requires input column parameter: $inputCol")
+    require(map.contains(outputCol), s"VectorIndexer requires output column parameter: $outputCol")
+    checkInputColumn(schema, map(inputCol), dataType)
+    addOutputColumn(schema, map(outputCol), dataType)
+  }
+}
+
+private object VectorIndexer {
+
+  /**
+   * Helper class for tracking unique values for each feature.
+   *
+   * TODO: Track which features are known to be continuous already; do not update counts for them.
+   *
+   * @param numFeatures  This class fails if it encounters a Vector whose length is not numFeatures.
+   * @param maxCategories  This class caps the number of unique values collected at maxCategories.
+   */
+  class CategoryStats(private val numFeatures: Int, private val maxCategories: Int)
+    extends Serializable {
+
+    /** featureValueSets[feature index] = set of unique values */
+    private val featureValueSets =
+      Array.fill[OpenHashSet[Double]](numFeatures)(new OpenHashSet[Double]())
+
+    /** Merge with another instance, modifying this instance. */
+    def merge(other: CategoryStats): CategoryStats = {
+      featureValueSets.zip(other.featureValueSets).foreach { case (thisValSet, otherValSet) =>
+        otherValSet.iterator.foreach { x =>
+          // Once we have found > maxCategories values, we know the feature is continuous
+          // and do not need to collect more values for it.
+          if (thisValSet.size <= maxCategories) thisValSet.add(x)
+        }
+      }
+      this
+    }
+
+    /** Add a new vector to this index, updating sets of unique feature values */
+    def addVector(v: Vector): Unit = {
+      require(v.size == numFeatures, s"VectorIndexer expected $numFeatures features but" +
+        s" found vector of size ${v.size}.")
+      v match {
+        case dv: DenseVector => addDenseVector(dv)
+        case sv: SparseVector => addSparseVector(sv)
+      }
+    }
+
+    /**
+     * Based on stats collected, decide which features are categorical,
+     * and choose indices for categories.
+     *
+     * Sparsity: This tries to maintain sparsity by treating value 0.0 specially.
+     *           If a categorical feature takes value 0.0, then value 0.0 is given index 0.
+     *
+     * @return  Feature value index.  Keys are categorical feature indices (column indices).
+     *          Values are mappings from original features values to 0-based category indices.
+     */
+    def getCategoryMaps: Map[Int, Map[Double, Int]] = {
+      // Filter out features which are declared continuous.
+      featureValueSets.zipWithIndex.filter(_._1.size <= maxCategories).map {
+        case (featureValues: OpenHashSet[Double], featureIndex: Int) =>
+          var sortedFeatureValues = featureValues.iterator.filter(_ != 0.0).toArray.sorted
+          val zeroExists = sortedFeatureValues.length + 1 == featureValues.size
+          if (zeroExists) {
+            sortedFeatureValues = 0.0 +: sortedFeatureValues
+          }
+          val categoryMap: Map[Double, Int] = sortedFeatureValues.zipWithIndex.toMap
+          (featureIndex, categoryMap)
+      }.toMap
+    }
+
+    private def addDenseVector(dv: DenseVector): Unit = {
+      var i = 0
+      while (i < dv.size) {
+        if (featureValueSets(i).size <= maxCategories) {
+          featureValueSets(i).add(dv(i))
+        }
+        i += 1
+      }
+    }
+
+    private def addSparseVector(sv: SparseVector): Unit = {
+      // TODO: This might be able to handle 0's more efficiently.
+      var vecIndex = 0 // index into vector
+      var k = 0 // index into non-zero elements
+      while (vecIndex < sv.size) {
+        val featureValue = if (k < sv.indices.length && vecIndex == sv.indices(k)) {
+          k += 1
+          sv.values(k - 1)
+        } else {
+          0.0
+        }
+        if (featureValueSets(vecIndex).size <= maxCategories) {
+          featureValueSets(vecIndex).add(featureValue)
+        }
+        vecIndex += 1
+      }
+    }
+  }
+}
+
+/**
+ * :: AlphaComponent ::
+ *
+ * Transform categorical features to use 0-based indices instead of their original values.
+ *  - Categorical features are mapped to indices.
+ *  - Continuous features (columns) are left unchanged.
+ * This also appends metadata to the output column, marking features as Numeric (continuous),
+ * Nominal (categorical), or Binary (either continuous or categorical).
+ *
+ * This maintains vector sparsity.
+ *
+ * @param numFeatures  Number of features, i.e., length of Vectors which this transforms
+ * @param categoryMaps  Feature value index.  Keys are categorical feature indices (column indices).
+ *                      Values are maps from original features values to 0-based category indices.
+ *                      If a feature is not in this map, it is treated as continuous.
+ */
+@AlphaComponent
+class VectorIndexerModel private[ml] (
+    override val parent: VectorIndexer,
+    override val fittingParamMap: ParamMap,
+    val numFeatures: Int,
+    val categoryMaps: Map[Int, Map[Double, Int]])
+  extends Model[VectorIndexerModel] with VectorIndexerParams {
+
+  /**
+   * Pre-computed feature attributes, with some missing info.
+   * In transform(), set attribute name and other info, if available.
+   */
+  private val partialFeatureAttributes: Array[Attribute] = {
+    val attrs = new Array[Attribute](numFeatures)
+    var categoricalFeatureCount = 0 // validity check for numFeatures, categoryMaps
+    var featureIndex = 0
+    while (featureIndex < numFeatures) {
+      if (categoryMaps.contains(featureIndex)) {
+        // categorical feature
+        val featureValues: Array[String] =
+          categoryMaps(featureIndex).toArray.sortBy(_._1).map(_._1).map(_.toString)
+        if (featureValues.length == 2) {
+          attrs(featureIndex) = new BinaryAttribute(index = Some(featureIndex),
+            values = Some(featureValues))
+        } else {
+          attrs(featureIndex) = new NominalAttribute(index = Some(featureIndex),
+            isOrdinal = Some(false), values = Some(featureValues))
+        }
+        categoricalFeatureCount += 1
+      } else {
+        // continuous feature
+        attrs(featureIndex) = new NumericAttribute(index = Some(featureIndex))
+      }
+      featureIndex += 1
+    }
+    require(categoricalFeatureCount == categoryMaps.size, "VectorIndexerModel given categoryMaps" +
+      s" with keys outside expected range [0,...,numFeatures), where numFeatures=$numFeatures")
+    attrs
+  }
+
+  // TODO: Check more carefully about whether this whole class will be included in a closure.
+
+  private val transformFunc: Vector => Vector = {
+    val sortedCategoricalFeatureIndices = categoryMaps.keys.toArray.sorted
+    val localVectorMap = categoryMaps
+    val f: Vector => Vector = {
+      case dv: DenseVector =>
+        val tmpv = dv.copy
+        localVectorMap.foreach { case (featureIndex: Int, categoryMap: Map[Double, Int]) =>
+          tmpv.values(featureIndex) = categoryMap(tmpv(featureIndex))
+        }
+        tmpv
+      case sv: SparseVector =>
+        // We use the fact that categorical value 0 is always mapped to index 0.
+        val tmpv = sv.copy
+        var catFeatureIdx = 0 // index into sortedCategoricalFeatureIndices
+        var k = 0 // index into non-zero elements of sparse vector
+        while (catFeatureIdx < sortedCategoricalFeatureIndices.length && k < tmpv.indices.length) {
+          val featureIndex = sortedCategoricalFeatureIndices(catFeatureIdx)
+          if (featureIndex < tmpv.indices(k)) {
+            catFeatureIdx += 1
+          } else if (featureIndex > tmpv.indices(k)) {
+            k += 1
+          } else {
+            tmpv.values(k) = localVectorMap(featureIndex)(tmpv.values(k))
+            catFeatureIdx += 1
+            k += 1
+          }
+        }
+        tmpv
+    }
+    f
+  }
+
+  /** @group setParam */
+  def setInputCol(value: String): this.type = set(inputCol, value)
+
+  /** @group setParam */
+  def setOutputCol(value: String): this.type = set(outputCol, value)
+
+  override def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame = {
+    transformSchema(dataset.schema, paramMap, logging = true)
+    val map = this.paramMap ++ paramMap
+    val newField = prepOutputField(dataset.schema, map)
+    val newCol = callUDF(transformFunc, new VectorUDT, dataset(map(inputCol)))
+    // For now, just check the first row of inputCol for vector length.
+    val firstRow = dataset.select(map(inputCol)).take(1)
+    if (firstRow.length != 0) {
+      val actualNumFeatures = firstRow(0).getAs[Vector](0).size
+      require(numFeatures == actualNumFeatures, "VectorIndexerModel expected vector of length" +
+        s" $numFeatures but found length $actualNumFeatures")
+    }
+    dataset.withColumn(map(outputCol), newCol.as(map(outputCol), newField.metadata))
+  }
+
+  override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = {
+    val map = this.paramMap ++ paramMap
+    val dataType = new VectorUDT
+    require(map.contains(inputCol),
+      s"VectorIndexerModel requires input column parameter: $inputCol")
+    require(map.contains(outputCol),
+      s"VectorIndexerModel requires output column parameter: $outputCol")
+    checkInputColumn(schema, map(inputCol), dataType)
+
+    val origAttrGroup = AttributeGroup.fromStructField(schema(map(inputCol)))
+    val origNumFeatures: Option[Int] = if (origAttrGroup.attributes.nonEmpty) {
+      Some(origAttrGroup.attributes.get.length)
+    } else {
+      origAttrGroup.numAttributes
+    }
+    require(origNumFeatures.forall(_ == numFeatures), "VectorIndexerModel expected" +
+      s" $numFeatures features, but input column ${map(inputCol)} had metadata specifying" +
+      s" ${origAttrGroup.numAttributes.get} features.")
+
+    val newField = prepOutputField(schema, map)
+    val outputFields = schema.fields :+ newField
+    StructType(outputFields)
+  }
+
+  /**
+   * Prepare the output column field, including per-feature metadata.
+   * @param schema  Input schema
+   * @param map  Parameter map (with this class' embedded parameter map folded in)
+   * @return  Output column field
+   */
+  private def prepOutputField(schema: StructType, map: ParamMap): StructField = {
+    val origAttrGroup = AttributeGroup.fromStructField(schema(map(inputCol)))
+    val featureAttributes: Array[Attribute] = if (origAttrGroup.attributes.nonEmpty) {
+      // Convert original attributes to modified attributes
+      val origAttrs: Array[Attribute] = origAttrGroup.attributes.get
+      origAttrs.zip(partialFeatureAttributes).map {
+        case (origAttr: Attribute, featAttr: BinaryAttribute) =>
+          if (origAttr.name.nonEmpty) {
+            featAttr.withName(origAttr.name.get)
+          } else {
+            featAttr
+          }
+        case (origAttr: Attribute, featAttr: NominalAttribute) =>
+          if (origAttr.name.nonEmpty) {
+            featAttr.withName(origAttr.name.get)
+          } else {
+            featAttr
+          }
+        case (origAttr: Attribute, featAttr: NumericAttribute) =>
+          origAttr.withIndex(featAttr.index.get)
+      }
+    } else {
+      partialFeatureAttributes
+    }
+    val newAttributeGroup = new AttributeGroup(map(outputCol), featureAttributes)
+    newAttributeGroup.toStructField(schema(map(inputCol)).metadata)
+  }
+}
diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/params.scala b/mllib/src/main/scala/org/apache/spark/ml/param/params.scala
index 17ece897a6c55..7d5178d0abb2d 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/param/params.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/param/params.scala
@@ -198,23 +198,31 @@ trait Params extends Identifiable with Serializable {
 
   /**
    * Check whether the given schema contains an input column.
-   * @param colName  Parameter name for the input column.
-   * @param dataType  SQL DataType of the input column.
+   * @param colName  Input column name
+   * @param dataType  Input column DataType
    */
   protected def checkInputColumn(schema: StructType, colName: String, dataType: DataType): Unit = {
     val actualDataType = schema(colName).dataType
-    require(actualDataType.equals(dataType),
-      s"Input column $colName must be of type $dataType" +
-        s" but was actually $actualDataType.  Column param description: ${getParam(colName)}")
+    require(actualDataType.equals(dataType), s"Input column $colName must be of type $dataType" +
+      s" but was actually $actualDataType.  Column param description: ${getParam(colName)}")
   }
 
+  /**
+   * Add an output column to the given schema.
+   * This fails if the given output column already exists.
+   * @param schema  Initial schema (not modified)
+   * @param colName  Output column name.  If this column name is an empy String "", this method
+   *                 returns the initial schema, unchanged.  This allows users to disable output
+   *                 columns.
+   * @param dataType  Output column DataType
+   */
   protected def addOutputColumn(
       schema: StructType,
       colName: String,
       dataType: DataType): StructType = {
     if (colName.length == 0) return schema
     val fieldNames = schema.fieldNames
-    require(!fieldNames.contains(colName), s"Prediction column $colName already exists.")
+    require(!fieldNames.contains(colName), s"Output column $colName already exists.")
     val outputFields = schema.fields ++ Seq(StructField(colName, dataType, nullable = false))
     StructType(outputFields)
   }
diff --git a/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorIndexerSuite.java b/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorIndexerSuite.java
new file mode 100644
index 0000000000000..161100134c92d
--- /dev/null
+++ b/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorIndexerSuite.java
@@ -0,0 +1,70 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.feature;
+
+import java.io.Serializable;
+import java.util.List;
+
+import org.junit.After;
+import org.junit.Assert;
+import org.junit.Before;
+import org.junit.Test;
+
+import com.google.common.collect.Lists;
+
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.ml.feature.VectorIndexerSuite.FeatureData;
+import org.apache.spark.mllib.linalg.Vectors;
+import org.apache.spark.sql.DataFrame;
+import org.apache.spark.sql.SQLContext;
+
+
+public class JavaVectorIndexerSuite implements Serializable {
+  private transient JavaSparkContext sc;
+
+  @Before
+  public void setUp() {
+    sc = new JavaSparkContext("local", "JavaVectorIndexerSuite");
+  }
+
+  @After
+  public void tearDown() {
+    sc.stop();
+    sc = null;
+  }
+
+  @Test
+  public void vectorIndexerAPI() {
+    // The tests are to check Java compatibility.
+    List<FeatureData> points = Lists.newArrayList(
+      new FeatureData(Vectors.dense(0.0, -2.0)),
+      new FeatureData(Vectors.dense(1.0, 3.0)),
+      new FeatureData(Vectors.dense(1.0, 4.0))
+    );
+    SQLContext sqlContext = new SQLContext(sc);
+    DataFrame data = sqlContext.createDataFrame(sc.parallelize(points, 2), FeatureData.class);
+    VectorIndexer indexer = new VectorIndexer()
+      .setInputCol("features")
+      .setOutputCol("indexed")
+      .setMaxCategories(2);
+    VectorIndexerModel model = indexer.fit(data);
+    Assert.assertEquals(model.numFeatures(), 2);
+    Assert.assertEquals(model.categoryMaps().size(), 1);
+    DataFrame indexedData = model.transform(data);
+  }
+}
diff --git a/mllib/src/test/scala/org/apache/spark/ml/attribute/AttributeGroupSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/attribute/AttributeGroupSuite.scala
index 3fb6e2ec46468..0dcfe5a2002dc 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/attribute/AttributeGroupSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/attribute/AttributeGroupSuite.scala
@@ -43,8 +43,8 @@ class AttributeGroupSuite extends FunSuite {
     intercept[NoSuchElementException] {
       group("abc")
     }
-    assert(group === AttributeGroup.fromMetadata(group.toMetadata, group.name))
-    assert(group === AttributeGroup.fromStructField(group.toStructField()))
+    assert(group === AttributeGroup.fromMetadata(group.toMetadataImpl, group.name))
+    assert(group === AttributeGroup.fromStructField(group.toStructField))
   }
 
   test("attribute group without attributes") {
@@ -53,8 +53,8 @@ class AttributeGroupSuite extends FunSuite {
     assert(group0.numAttributes === Some(10))
     assert(group0.size === 10)
     assert(group0.attributes.isEmpty)
-    assert(group0 === AttributeGroup.fromMetadata(group0.toMetadata, group0.name))
-    assert(group0 === AttributeGroup.fromStructField(group0.toStructField()))
+    assert(group0 === AttributeGroup.fromMetadata(group0.toMetadataImpl, group0.name))
+    assert(group0 === AttributeGroup.fromStructField(group0.toStructField))
 
     val group1 = new AttributeGroup("item")
     assert(group1.name === "item")
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala
index a18c335952b96..9d09f24709e23 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala
@@ -24,7 +24,6 @@ import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.{DataFrame, Row, SQLContext}
 
-private case class DataSet(features: Vector)
 
 class NormalizerSuite extends FunSuite with MLlibTestSparkContext {
 
@@ -63,7 +62,7 @@ class NormalizerSuite extends FunSuite with MLlibTestSparkContext {
     )
 
     val sqlContext = new SQLContext(sc)
-    dataFrame = sqlContext.createDataFrame(sc.parallelize(data, 2).map(DataSet))
+    dataFrame = sqlContext.createDataFrame(sc.parallelize(data, 2).map(NormalizerSuite.FeatureData))
     normalizer = new Normalizer()
       .setInputCol("features")
       .setOutputCol("normalized_features")
@@ -107,3 +106,7 @@ class NormalizerSuite extends FunSuite with MLlibTestSparkContext {
     assertValues(result, l1Normalized)
   }
 }
+
+private object NormalizerSuite {
+  case class FeatureData(features: Vector)
+}
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala
new file mode 100644
index 0000000000000..61c46c85a78b5
--- /dev/null
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala
@@ -0,0 +1,255 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.feature
+
+import scala.beans.{BeanInfo, BeanProperty}
+
+import org.scalatest.FunSuite
+
+import org.apache.spark.SparkException
+import org.apache.spark.ml.attribute._
+import org.apache.spark.ml.util.TestingUtils
+import org.apache.spark.mllib.linalg.{SparseVector, Vector, Vectors}
+import org.apache.spark.mllib.util.MLlibTestSparkContext
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.{DataFrame, SQLContext}
+
+
+class VectorIndexerSuite extends FunSuite with MLlibTestSparkContext {
+
+  import VectorIndexerSuite.FeatureData
+
+  @transient var sqlContext: SQLContext = _
+
+  // identical, of length 3
+  @transient var densePoints1: DataFrame = _
+  @transient var sparsePoints1: DataFrame = _
+  @transient var point1maxes: Array[Double] = _
+
+  // identical, of length 2
+  @transient var densePoints2: DataFrame = _
+  @transient var sparsePoints2: DataFrame = _
+
+  // different lengths
+  @transient var badPoints: DataFrame = _
+
+  override def beforeAll(): Unit = {
+    super.beforeAll()
+
+    val densePoints1Seq = Seq(
+      Vectors.dense(1.0, 2.0, 0.0),
+      Vectors.dense(0.0, 1.0, 2.0),
+      Vectors.dense(0.0, 0.0, -1.0),
+      Vectors.dense(1.0, 3.0, 2.0))
+    val sparsePoints1Seq = Seq(
+      Vectors.sparse(3, Array(0, 1), Array(1.0, 2.0)),
+      Vectors.sparse(3, Array(1, 2), Array(1.0, 2.0)),
+      Vectors.sparse(3, Array(2), Array(-1.0)),
+      Vectors.sparse(3, Array(0, 1, 2), Array(1.0, 3.0, 2.0)))
+    point1maxes = Array(1.0, 3.0, 2.0)
+
+    val densePoints2Seq = Seq(
+      Vectors.dense(1.0, 1.0, 0.0, 1.0),
+      Vectors.dense(0.0, 1.0, 1.0, 1.0),
+      Vectors.dense(-1.0, 1.0, 2.0, 0.0))
+    val sparsePoints2Seq = Seq(
+      Vectors.sparse(4, Array(0, 1, 3), Array(1.0, 1.0, 1.0)),
+      Vectors.sparse(4, Array(1, 2, 3), Array(1.0, 1.0, 1.0)),
+      Vectors.sparse(4, Array(0, 1, 2), Array(-1.0, 1.0, 2.0)))
+
+    val badPointsSeq = Seq(
+      Vectors.sparse(2, Array(0, 1), Array(1.0, 1.0)),
+      Vectors.sparse(3, Array(2), Array(-1.0)))
+
+    // Sanity checks for assumptions made in tests
+    assert(densePoints1Seq.head.size == sparsePoints1Seq.head.size)
+    assert(densePoints2Seq.head.size == sparsePoints2Seq.head.size)
+    assert(densePoints1Seq.head.size != densePoints2Seq.head.size)
+    def checkPair(dvSeq: Seq[Vector], svSeq: Seq[Vector]): Unit = {
+      assert(dvSeq.zip(svSeq).forall { case (dv, sv) => dv.toArray === sv.toArray },
+        "typo in unit test")
+    }
+    checkPair(densePoints1Seq, sparsePoints1Seq)
+    checkPair(densePoints2Seq, sparsePoints2Seq)
+
+    sqlContext = new SQLContext(sc)
+    densePoints1 = sqlContext.createDataFrame(sc.parallelize(densePoints1Seq, 2).map(FeatureData))
+    sparsePoints1 = sqlContext.createDataFrame(sc.parallelize(sparsePoints1Seq, 2).map(FeatureData))
+    densePoints2 = sqlContext.createDataFrame(sc.parallelize(densePoints2Seq, 2).map(FeatureData))
+    sparsePoints2 = sqlContext.createDataFrame(sc.parallelize(sparsePoints2Seq, 2).map(FeatureData))
+    badPoints = sqlContext.createDataFrame(sc.parallelize(badPointsSeq, 2).map(FeatureData))
+  }
+
+  private def getIndexer: VectorIndexer =
+    new VectorIndexer().setInputCol("features").setOutputCol("indexed")
+
+  test("Cannot fit an empty DataFrame") {
+    val rdd = sqlContext.createDataFrame(sc.parallelize(Array.empty[Vector], 2).map(FeatureData))
+    val vectorIndexer = getIndexer
+    intercept[IllegalArgumentException] {
+      vectorIndexer.fit(rdd)
+    }
+  }
+
+  test("Throws error when given RDDs with different size vectors") {
+    val vectorIndexer = getIndexer
+    val model = vectorIndexer.fit(densePoints1) // vectors of length 3
+    model.transform(densePoints1) // should work
+    model.transform(sparsePoints1) // should work
+    intercept[IllegalArgumentException] {
+      model.transform(densePoints2)
+      println("Did not throw error when fit, transform were called on vectors of different lengths")
+    }
+    intercept[SparkException] {
+      vectorIndexer.fit(badPoints)
+      println("Did not throw error when fitting vectors of different lengths in same RDD.")
+    }
+  }
+
+  test("Same result with dense and sparse vectors") {
+    def testDenseSparse(densePoints: DataFrame, sparsePoints: DataFrame): Unit = {
+      val denseVectorIndexer = getIndexer.setMaxCategories(2)
+      val sparseVectorIndexer = getIndexer.setMaxCategories(2)
+      val denseModel = denseVectorIndexer.fit(densePoints)
+      val sparseModel = sparseVectorIndexer.fit(sparsePoints)
+      val denseMap = denseModel.categoryMaps
+      val sparseMap = sparseModel.categoryMaps
+      assert(denseMap.keys.toSet == sparseMap.keys.toSet,
+        "Categorical features chosen from dense vs. sparse vectors did not match.")
+      assert(denseMap == sparseMap,
+        "Categorical feature value indexes chosen from dense vs. sparse vectors did not match.")
+    }
+    testDenseSparse(densePoints1, sparsePoints1)
+    testDenseSparse(densePoints2, sparsePoints2)
+  }
+
+  test("Builds valid categorical feature value index, transform correctly, check metadata") {
+    def checkCategoryMaps(
+        data: DataFrame,
+        maxCategories: Int,
+        categoricalFeatures: Set[Int]): Unit = {
+      val collectedData = data.collect().map(_.getAs[Vector](0))
+      val errMsg = s"checkCategoryMaps failed for input with maxCategories=$maxCategories," +
+        s" categoricalFeatures=${categoricalFeatures.mkString(", ")}"
+      try {
+        val vectorIndexer = getIndexer.setMaxCategories(maxCategories)
+        val model = vectorIndexer.fit(data)
+        val categoryMaps = model.categoryMaps
+        assert(categoryMaps.keys.toSet === categoricalFeatures) // Chose correct categorical features
+        val transformed = model.transform(data).select("indexed")
+        val indexedRDD: RDD[Vector] = transformed.map(_.getAs[Vector](0))
+        val featureAttrs = AttributeGroup.fromStructField(transformed.schema("indexed"))
+        assert(featureAttrs.name === "indexed")
+        assert(featureAttrs.attributes.get.length === model.numFeatures)
+        categoricalFeatures.foreach { feature: Int =>
+          val origValueSet = collectedData.map(_(feature)).toSet
+          val targetValueIndexSet = Range(0, origValueSet.size).toSet
+          val catMap = categoryMaps(feature)
+          assert(catMap.keys.toSet === origValueSet) // Correct categories
+          assert(catMap.values.toSet === targetValueIndexSet) // Correct category indices
+          if (origValueSet.contains(0.0)) {
+            assert(catMap(0.0) === 0) // value 0 gets index 0
+          }
+          // Check transformed data
+          assert(indexedRDD.map(_(feature)).collect().toSet === targetValueIndexSet)
+          // Check metadata
+          val featureAttr = featureAttrs(feature)
+          assert(featureAttr.index.get === feature)
+          featureAttr match {
+            case attr: BinaryAttribute =>
+              assert(attr.values.get === origValueSet.toArray.sorted.map(_.toString))
+            case attr: NominalAttribute =>
+              assert(attr.values.get === origValueSet.toArray.sorted.map(_.toString))
+              assert(attr.isOrdinal.get === false)
+            case _ =>
+              throw new RuntimeException(errMsg + s". Categorical feature $feature failed" +
+                s" metadata check. Found feature attribute: $featureAttr.")
+          }
+        }
+        // Check numerical feature metadata.
+        Range(0, model.numFeatures).filter(feature => !categoricalFeatures.contains(feature))
+          .foreach { feature: Int =>
+          val featureAttr = featureAttrs(feature)
+          featureAttr match {
+            case attr: NumericAttribute =>
+              assert(featureAttr.index.get === feature)
+            case _ =>
+              throw new RuntimeException(errMsg + s". Numerical feature $feature failed" +
+                s" metadata check. Found feature attribute: $featureAttr.")
+          }
+        }
+      } catch {
+        case e: org.scalatest.exceptions.TestFailedException =>
+          println(errMsg)
+          throw e
+      }
+    }
+    checkCategoryMaps(densePoints1, maxCategories = 2, categoricalFeatures = Set(0))
+    checkCategoryMaps(densePoints1, maxCategories = 3, categoricalFeatures = Set(0, 2))
+    checkCategoryMaps(densePoints2, maxCategories = 2, categoricalFeatures = Set(1, 3))
+  }
+
+  test("Maintain sparsity for sparse vectors") {
+    def checkSparsity(data: DataFrame, maxCategories: Int): Unit = {
+      val points = data.collect().map(_.getAs[Vector](0))
+      val vectorIndexer = getIndexer.setMaxCategories(maxCategories)
+      val model = vectorIndexer.fit(data)
+      val indexedPoints = model.transform(data).select("indexed").map(_.getAs[Vector](0)).collect()
+      points.zip(indexedPoints).foreach {
+        case (orig: SparseVector, indexed: SparseVector) =>
+          assert(orig.indices.length == indexed.indices.length)
+        case _ => throw new UnknownError("Unit test has a bug in it.") // should never happen
+      }
+    }
+    checkSparsity(sparsePoints1, maxCategories = 2)
+    checkSparsity(sparsePoints2, maxCategories = 2)
+  }
+
+  test("Preserve metadata") {
+    // For continuous features, preserve name and stats.
+    val featureAttributes: Array[Attribute] = point1maxes.zipWithIndex.map { case (maxVal, i) =>
+      NumericAttribute.defaultAttr.withName(i.toString).withMax(maxVal)
+    }
+    val attrGroup = new AttributeGroup("features", featureAttributes)
+    val densePoints1WithMeta =
+      densePoints1.select(densePoints1("features").as("features", attrGroup.toMetadata))
+    val vectorIndexer = getIndexer.setMaxCategories(2)
+    val model = vectorIndexer.fit(densePoints1WithMeta)
+    // Check that ML metadata are preserved.
+    val indexedPoints = model.transform(densePoints1WithMeta)
+    val transAttributes: Array[Attribute] =
+      AttributeGroup.fromStructField(indexedPoints.schema("indexed")).attributes.get
+    featureAttributes.zip(transAttributes).foreach { case (orig, trans) =>
+      assert(orig.name === trans.name)
+      (orig, trans) match {
+        case (orig: NumericAttribute, trans: NumericAttribute) =>
+          assert(orig.max.nonEmpty && orig.max === trans.max)
+        case _ =>
+          // do nothing
+          // TODO: Once input features marked as categorical are handled correctly, check that here.
+      }
+    }
+    // Check that non-ML metadata are preserved.
+    TestingUtils.testPreserveMetadata(densePoints1WithMeta, model, "features", "indexed")
+  }
+}
+
+private[feature] object VectorIndexerSuite {
+  @BeanInfo
+  case class FeatureData(@BeanProperty features: Vector)
+}
diff --git a/mllib/src/test/scala/org/apache/spark/ml/util/TestingUtils.scala b/mllib/src/test/scala/org/apache/spark/ml/util/TestingUtils.scala
new file mode 100644
index 0000000000000..c44cb61b34171
--- /dev/null
+++ b/mllib/src/test/scala/org/apache/spark/ml/util/TestingUtils.scala
@@ -0,0 +1,60 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.util
+
+import org.apache.spark.ml.Transformer
+import org.apache.spark.sql.DataFrame
+import org.apache.spark.sql.types.MetadataBuilder
+import org.scalatest.FunSuite
+
+private[ml] object TestingUtils extends FunSuite {
+
+  /**
+   * Test whether unrelated metadata are preserved for this transformer.
+   * This attaches extra metadata to a column, transforms the column, and check to ensure the
+   * extra metadata have not changed.
+   * @param data  Input dataset
+   * @param transformer  Transformer to test
+   * @param inputCol  Unique input column for Transformer.  This must be the ONLY input column.
+   * @param outputCol  Output column to test for metadata presence.
+   */
+  def testPreserveMetadata(
+      data: DataFrame,
+      transformer: Transformer,
+      inputCol: String,
+      outputCol: String): Unit = {
+    // Create some fake metadata
+    val origMetadata = data.schema(inputCol).metadata
+    val metaKey = "__testPreserveMetadata__fake_key"
+    val metaValue = 12345
+    assert(!origMetadata.contains(metaKey),
+      s"Unit test with testPreserveMetadata will fail since metadata key was present: $metaKey")
+    val newMetadata =
+      new MetadataBuilder().withMetadata(origMetadata).putLong(metaKey, metaValue).build()
+    // Add metadata to the inputCol
+    val withMetadata = data.select(data(inputCol).as(inputCol, newMetadata))
+    // Transform, and ensure extra metadata was not affected
+    val transformed = transformer.transform(withMetadata)
+    val transMetadata = transformed.schema(outputCol).metadata
+    assert(transMetadata.contains(metaKey),
+      "Unit test with testPreserveMetadata failed; extra metadata key was not present.")
+    assert(transMetadata.getLong(metaKey) === metaValue,
+      "Unit test with testPreserveMetadata failed; extra metadata value was wrong." +
+        s" Expected $metaValue but found ${transMetadata.getLong(metaKey)}")
+  }
+}

From 685ddcf5253c0ecb39853802431e22b0c7b61dee Mon Sep 17 00:00:00 2001
From: Xiangrui Meng <meng@databricks.com>
Date: Sun, 12 Apr 2015 22:41:05 -0700
Subject: [PATCH 67/95] [SPARK-5886][ML] Add StringIndexer as a feature
 transformer

This PR adds string indexer, which takes a column of string labels and outputs a double column with labels indexed by their frequency.

TODOs:
- [x] store feature to index map in output metadata

Author: Xiangrui Meng <meng@databricks.com>

Closes #4735 from mengxr/SPARK-5886 and squashes the following commits:

d82575f [Xiangrui Meng] fix test
700e70f [Xiangrui Meng] rename LabelIndexer to StringIndexer
16a6f8c [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-5886
457166e [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-5886
f8b30f4 [Xiangrui Meng] update label indexer to output metadata
e81ec28 [Xiangrui Meng] Merge branch 'openhashmap-contains' into SPARK-5886-2
d6e6f1f [Xiangrui Meng] add contains to primitivekeyopenhashmap
748a69b [Xiangrui Meng] add contains to OpenHashMap
def3c5c [Xiangrui Meng] add LabelIndexer
---
 .../spark/ml/feature/StringIndexer.scala      | 126 ++++++++++++++++++
 .../spark/ml/feature/StringIndexerSuite.scala |  52 ++++++++
 2 files changed, 178 insertions(+)
 create mode 100644 mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
 create mode 100644 mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala

diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
new file mode 100644
index 0000000000000..61e6742e880d8
--- /dev/null
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
@@ -0,0 +1,126 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.feature
+
+import org.apache.spark.SparkException
+import org.apache.spark.annotation.AlphaComponent
+import org.apache.spark.ml.{Estimator, Model}
+import org.apache.spark.ml.attribute.NominalAttribute
+import org.apache.spark.ml.param._
+import org.apache.spark.sql.DataFrame
+import org.apache.spark.sql.functions._
+import org.apache.spark.sql.types.{StringType, StructType}
+import org.apache.spark.util.collection.OpenHashMap
+
+/**
+ * Base trait for [[StringIndexer]] and [[StringIndexerModel]].
+ */
+private[feature] trait StringIndexerBase extends Params with HasInputCol with HasOutputCol {
+
+  /** Validates and transforms the input schema. */
+  protected def validateAndTransformSchema(schema: StructType, paramMap: ParamMap): StructType = {
+    val map = this.paramMap ++ paramMap
+    checkInputColumn(schema, map(inputCol), StringType)
+    val inputFields = schema.fields
+    val outputColName = map(outputCol)
+    require(inputFields.forall(_.name != outputColName),
+      s"Output column $outputColName already exists.")
+    val attr = NominalAttribute.defaultAttr.withName(map(outputCol))
+    val outputFields = inputFields :+ attr.toStructField()
+    StructType(outputFields)
+  }
+}
+
+/**
+ * :: AlphaComponent ::
+ * A label indexer that maps a string column of labels to an ML column of label indices.
+ * The indices are in [0, numLabels), ordered by label frequencies.
+ * So the most frequent label gets index 0.
+ */
+@AlphaComponent
+class StringIndexer extends Estimator[StringIndexerModel] with StringIndexerBase {
+
+  /** @group setParam */
+  def setInputCol(value: String): this.type = set(inputCol, value)
+
+  /** @group setParam */
+  def setOutputCol(value: String): this.type = set(outputCol, value)
+
+  // TODO: handle unseen labels
+
+  override def fit(dataset: DataFrame, paramMap: ParamMap): StringIndexerModel = {
+    val map = this.paramMap ++ paramMap
+    val counts = dataset.select(map(inputCol)).map(_.getString(0)).countByValue()
+    val labels = counts.toSeq.sortBy(-_._2).map(_._1).toArray
+    val model = new StringIndexerModel(this, map, labels)
+    Params.inheritValues(map, this, model)
+    model
+  }
+
+  override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = {
+    validateAndTransformSchema(schema, paramMap)
+  }
+}
+
+/**
+ * :: AlphaComponent ::
+ * Model fitted by [[StringIndexer]].
+ */
+@AlphaComponent
+class StringIndexerModel private[ml] (
+    override val parent: StringIndexer,
+    override val fittingParamMap: ParamMap,
+    labels: Array[String]) extends Model[StringIndexerModel] with StringIndexerBase {
+
+  private val labelToIndex: OpenHashMap[String, Double] = {
+    val n = labels.length
+    val map = new OpenHashMap[String, Double](n)
+    var i = 0
+    while (i < n) {
+      map.update(labels(i), i)
+      i += 1
+    }
+    map
+  }
+
+  /** @group setParam */
+  def setInputCol(value: String): this.type = set(inputCol, value)
+
+  /** @group setParam */
+  def setOutputCol(value: String): this.type = set(outputCol, value)
+
+  override def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame = {
+    val map = this.paramMap ++ paramMap
+    val indexer = udf { label: String =>
+      if (labelToIndex.contains(label)) {
+        labelToIndex(label)
+      } else {
+        // TODO: handle unseen labels
+        throw new SparkException(s"Unseen label: $label.")
+      }
+    }
+    val outputColName = map(outputCol)
+    val metadata = NominalAttribute.defaultAttr
+      .withName(outputColName).withValues(labels).toStructField().metadata
+    dataset.select(col("*"), indexer(dataset(map(inputCol))).as(outputColName, metadata))
+  }
+
+  override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = {
+    validateAndTransformSchema(schema, paramMap)
+  }
+}
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala
new file mode 100644
index 0000000000000..00b5d094d82f1
--- /dev/null
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala
@@ -0,0 +1,52 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.feature
+
+import org.scalatest.FunSuite
+
+import org.apache.spark.ml.attribute.{Attribute, NominalAttribute}
+import org.apache.spark.mllib.util.MLlibTestSparkContext
+import org.apache.spark.sql.SQLContext
+
+class StringIndexerSuite extends FunSuite with MLlibTestSparkContext {
+  private var sqlContext: SQLContext = _
+
+  override def beforeAll(): Unit = {
+    super.beforeAll()
+    sqlContext = new SQLContext(sc)
+  }
+
+  test("StringIndexer") {
+    val data = sc.parallelize(Seq((0, "a"), (1, "b"), (2, "c"), (3, "a"), (4, "a"), (5, "c")), 2)
+    val df = sqlContext.createDataFrame(data).toDF("id", "label")
+    val indexer = new StringIndexer()
+      .setInputCol("label")
+      .setOutputCol("labelIndex")
+      .fit(df)
+    val transformed = indexer.transform(df)
+    val attr = Attribute.fromStructField(transformed.schema("labelIndex"))
+      .asInstanceOf[NominalAttribute]
+    assert(attr.values.get === Array("a", "c", "b"))
+    val output = transformed.select("id", "labelIndex").map { r =>
+      (r.getInt(0), r.getDouble(1))
+    }.collect().toSet
+    // a -> 0, b -> 2, c -> 1
+    val expected = Set((0, 0.0), (1, 2.0), (2, 1.0), (3, 0.0), (4, 0.0), (5, 1.0))
+    assert(output === expected)
+  }
+}

From 929404498506c34180e2eaaa1a4d4a3c4ed51daa Mon Sep 17 00:00:00 2001
From: Xiangrui Meng <meng@databricks.com>
Date: Sun, 12 Apr 2015 22:42:01 -0700
Subject: [PATCH 68/95] [SPARK-5885][MLLIB] Add VectorAssembler as a feature
 transformer

VectorAssembler merges multiple columns into a vector column. This PR contains content from #5195.

~~carry ML attributes~~ (moved to a follow-up PR)

Author: Xiangrui Meng <meng@databricks.com>

Closes #5196 from mengxr/SPARK-5885 and squashes the following commits:

a52b101 [Xiangrui Meng] recognize more types
35daac2 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-5885
bb5e64b [Xiangrui Meng] add TODO for null
976a3d6 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-5885
0859311 [Xiangrui Meng] Revert "add CreateStruct"
29fb6ac [Xiangrui Meng] use CreateStruct
adb71c4 [Xiangrui Meng] Merge branch 'SPARK-6542' into SPARK-5885
85f3106 [Xiangrui Meng] add CreateStruct
4ff16ce [Xiangrui Meng] add VectorAssembler
---
 .../org/apache/spark/ml/Identifiable.scala    |   2 +-
 .../spark/ml/feature/VectorAssembler.scala    | 111 ++++++++++++++++++
 .../apache/spark/ml/param/sharedParams.scala  |  10 ++
 .../ml/feature/VectorAssemblerSuite.scala     |  63 ++++++++++
 4 files changed, 185 insertions(+), 1 deletion(-)
 create mode 100644 mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala
 create mode 100644 mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala

diff --git a/mllib/src/main/scala/org/apache/spark/ml/Identifiable.scala b/mllib/src/main/scala/org/apache/spark/ml/Identifiable.scala
index cd84b05bfb496..a50090671ae48 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/Identifiable.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/Identifiable.scala
@@ -29,5 +29,5 @@ private[ml] trait Identifiable extends Serializable {
    * random hex chars.
    */
   private[ml] val uid: String =
-    this.getClass.getSimpleName + "-" + UUID.randomUUID().toString.take(8)
+    this.getClass.getSimpleName + "_" + UUID.randomUUID().toString.take(8)
 }
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala
new file mode 100644
index 0000000000000..d1b8f7e6e9295
--- /dev/null
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala
@@ -0,0 +1,111 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.feature
+
+import scala.collection.mutable.ArrayBuilder
+
+import org.apache.spark.SparkException
+import org.apache.spark.annotation.AlphaComponent
+import org.apache.spark.ml.Transformer
+import org.apache.spark.ml.param.{HasInputCols, HasOutputCol, ParamMap}
+import org.apache.spark.mllib.linalg.{Vector, VectorUDT, Vectors}
+import org.apache.spark.sql.{Column, DataFrame, Row}
+import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute
+import org.apache.spark.sql.catalyst.expressions.{Alias, Cast, CreateStruct}
+import org.apache.spark.sql.functions._
+import org.apache.spark.sql.types._
+
+/**
+ * :: AlphaComponent ::
+ * A feature transformer than merge multiple columns into a vector column.
+ */
+@AlphaComponent
+class VectorAssembler extends Transformer with HasInputCols with HasOutputCol {
+
+  /** @group setParam */
+  def setInputCols(value: Array[String]): this.type = set(inputCols, value)
+
+  /** @group setParam */
+  def setOutputCol(value: String): this.type = set(outputCol, value)
+
+  override def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame = {
+    val map = this.paramMap ++ paramMap
+    val assembleFunc = udf { r: Row =>
+      VectorAssembler.assemble(r.toSeq: _*)
+    }
+    val schema = dataset.schema
+    val inputColNames = map(inputCols)
+    val args = inputColNames.map { c =>
+      schema(c).dataType match {
+        case DoubleType => UnresolvedAttribute(c)
+        case t if t.isInstanceOf[VectorUDT] => UnresolvedAttribute(c)
+        case _: NativeType => Alias(Cast(UnresolvedAttribute(c), DoubleType), s"${c}_double_$uid")()
+      }
+    }
+    dataset.select(col("*"), assembleFunc(new Column(CreateStruct(args))).as(map(outputCol)))
+  }
+
+  override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = {
+    val map = this.paramMap ++ paramMap
+    val inputColNames = map(inputCols)
+    val outputColName = map(outputCol)
+    val inputDataTypes = inputColNames.map(name => schema(name).dataType)
+    inputDataTypes.foreach {
+      case _: NativeType =>
+      case t if t.isInstanceOf[VectorUDT] =>
+      case other =>
+        throw new IllegalArgumentException(s"Data type $other is not supported.")
+    }
+    if (schema.fieldNames.contains(outputColName)) {
+      throw new IllegalArgumentException(s"Output column $outputColName already exists.")
+    }
+    StructType(schema.fields :+ new StructField(outputColName, new VectorUDT, false))
+  }
+}
+
+@AlphaComponent
+object VectorAssembler {
+
+  private[feature] def assemble(vv: Any*): Vector = {
+    val indices = ArrayBuilder.make[Int]
+    val values = ArrayBuilder.make[Double]
+    var cur = 0
+    vv.foreach {
+      case v: Double =>
+        if (v != 0.0) {
+          indices += cur
+          values += v
+        }
+        cur += 1
+      case vec: Vector =>
+        vec.foreachActive { case (i, v) =>
+          if (v != 0.0) {
+            indices += cur + i
+            values += v
+          }
+        }
+        cur += vec.size
+      case null =>
+        // TODO: output Double.NaN?
+        throw new SparkException("Values to assemble cannot be null.")
+      case o =>
+        throw new SparkException(s"$o of type ${o.getClass.getName} is not supported.")
+    }
+    Vectors.sparse(cur, indices.result(), values.result())
+  }
+}
diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/sharedParams.scala b/mllib/src/main/scala/org/apache/spark/ml/param/sharedParams.scala
index 0739fdbfcbaae..07e6eb417763d 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/param/sharedParams.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/param/sharedParams.scala
@@ -140,6 +140,16 @@ private[ml] trait HasInputCol extends Params {
   def getInputCol: String = get(inputCol)
 }
 
+private[ml] trait HasInputCols extends Params {
+  /**
+   * Param for input column names.
+   */
+  val inputCols: Param[Array[String]] = new Param(this, "inputCols", "input column names")
+
+  /** @group getParam */
+  def getInputCols: Array[String] = get(inputCols)
+}
+
 private[ml] trait HasOutputCol extends Params {
   /**
    * param for output column name
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala
new file mode 100644
index 0000000000000..57d0278e03639
--- /dev/null
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala
@@ -0,0 +1,63 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.feature
+
+import org.scalatest.FunSuite
+
+import org.apache.spark.SparkException
+import org.apache.spark.mllib.linalg.{Vector, Vectors}
+import org.apache.spark.mllib.util.MLlibTestSparkContext
+import org.apache.spark.sql.{Row, SQLContext}
+
+class VectorAssemblerSuite extends FunSuite with MLlibTestSparkContext {
+
+  @transient var sqlContext: SQLContext = _
+
+  override def beforeAll(): Unit = {
+    super.beforeAll()
+    sqlContext = new SQLContext(sc)
+  }
+
+  test("assemble") {
+    import org.apache.spark.ml.feature.VectorAssembler.assemble
+    assert(assemble(0.0) === Vectors.sparse(1, Array.empty, Array.empty))
+    assert(assemble(0.0, 1.0) === Vectors.sparse(2, Array(1), Array(1.0)))
+    val dv = Vectors.dense(2.0, 0.0)
+    assert(assemble(0.0, dv, 1.0) === Vectors.sparse(4, Array(1, 3), Array(2.0, 1.0)))
+    val sv = Vectors.sparse(2, Array(0, 1), Array(3.0, 4.0))
+    assert(assemble(0.0, dv, 1.0, sv) ===
+      Vectors.sparse(6, Array(1, 3, 4, 5), Array(2.0, 1.0, 3.0, 4.0)))
+    for (v <- Seq(1, "a", null)) {
+      intercept[SparkException](assemble(v))
+      intercept[SparkException](assemble(1.0, v))
+    }
+  }
+
+  test("VectorAssembler") {
+    val df = sqlContext.createDataFrame(Seq(
+      (0, 0.0, Vectors.dense(1.0, 2.0), "a", Vectors.sparse(2, Array(1), Array(3.0)), 10L)
+    )).toDF("id", "x", "y", "name", "z", "n")
+    val assembler = new VectorAssembler()
+      .setInputCols(Array("x", "y", "z", "n"))
+      .setOutputCol("features")
+    assembler.transform(df).select("features").collect().foreach {
+      case Row(v: Vector) =>
+        assert(v === Vectors.sparse(6, Array(1, 2, 4, 5), Array(1.0, 2.0, 3.0, 10.0)))
+    }
+  }
+}

From 68d1faa3c04e9412bbc2b60421dc12bd19c396b2 Mon Sep 17 00:00:00 2001
From: Reynold Xin <rxin@databricks.com>
Date: Sun, 12 Apr 2015 22:56:12 -0700
Subject: [PATCH 69/95] [SPARK-6562][SQL] DataFrame.replace

Supports replacing values with other values in DataFrames.

Python support should be in a separate pull request.

Author: Reynold Xin <rxin@databricks.com>

Closes #5282 from rxin/df-na-replace and squashes the following commits:

4b72434 [Reynold Xin] Removed println.
c8d9946 [Reynold Xin] col -> cols
fbb3c21 [Reynold Xin] [SPARK-6562][SQL] DataFrame.replace
---
 .../spark/sql/DataFrameNaFunctions.scala      | 144 ++++++++++++++++++
 .../spark/sql/DataFrameNaFunctionsSuite.scala |  34 +++++
 2 files changed, 178 insertions(+)

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
index bf3c3fe876873..481ed4924857e 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
@@ -192,6 +192,127 @@ final class DataFrameNaFunctions private[sql](df: DataFrame) {
    */
   def fill(valueMap: Map[String, Any]): DataFrame = fill0(valueMap.toSeq)
 
+  /**
+   * Replaces values matching keys in `replacement` map with the corresponding values.
+   * Key and value of `replacement` map must have the same type, and can only be doubles or strings.
+   * If `col` is "*", then the replacement is applied on all string columns or numeric columns.
+   *
+   * {{{
+   *   import com.google.common.collect.ImmutableMap;
+   *
+   *   // Replaces all occurrences of 1.0 with 2.0 in column "height".
+   *   df.replace("height", ImmutableMap.of(1.0, 2.0));
+   *
+   *   // Replaces all occurrences of "UNKNOWN" with "unnamed" in column "name".
+   *   df.replace("name", ImmutableMap.of("UNKNOWN", "unnamed"));
+   *
+   *   // Replaces all occurrences of "UNKNOWN" with "unnamed" in all string columns.
+   *   df.replace("*", ImmutableMap.of("UNKNOWN", "unnamed"));
+   * }}}
+   *
+   * @param col name of the column to apply the value replacement
+   * @param replacement value replacement map, as explained above
+   */
+  def replace[T](col: String, replacement: java.util.Map[T, T]): DataFrame = {
+    replace[T](col, replacement.toMap : Map[T, T])
+  }
+
+  /**
+   * Replaces values matching keys in `replacement` map with the corresponding values.
+   * Key and value of `replacement` map must have the same type, and can only be doubles or strings.
+   *
+   * {{{
+   *   import com.google.common.collect.ImmutableMap;
+   *
+   *   // Replaces all occurrences of 1.0 with 2.0 in column "height" and "weight".
+   *   df.replace(new String[] {"height", "weight"}, ImmutableMap.of(1.0, 2.0));
+   *
+   *   // Replaces all occurrences of "UNKNOWN" with "unnamed" in column "firstname" and "lastname".
+   *   df.replace(new String[] {"firstname", "lastname"}, ImmutableMap.of("UNKNOWN", "unnamed"));
+   * }}}
+   *
+   * @param cols list of columns to apply the value replacement
+   * @param replacement value replacement map, as explained above
+   */
+  def replace[T](cols: Array[String], replacement: java.util.Map[T, T]): DataFrame = {
+    replace(cols.toSeq, replacement.toMap)
+  }
+
+  /**
+   * (Scala-specific) Replaces values matching keys in `replacement` map.
+   * Key and value of `replacement` map must have the same type, and can only be doubles or strings.
+   * If `col` is "*", then the replacement is applied on all string columns or numeric columns.
+   *
+   * {{{
+   *   // Replaces all occurrences of 1.0 with 2.0 in column "height".
+   *   df.replace("height", Map(1.0 -> 2.0))
+   *
+   *   // Replaces all occurrences of "UNKNOWN" with "unnamed" in column "name".
+   *   df.replace("name", Map("UNKNOWN" -> "unnamed")
+   *
+   *   // Replaces all occurrences of "UNKNOWN" with "unnamed" in all string columns.
+   *   df.replace("*", Map("UNKNOWN" -> "unnamed")
+   * }}}
+   *
+   * @param col name of the column to apply the value replacement
+   * @param replacement value replacement map, as explained above
+   */
+  def replace[T](col: String, replacement: Map[T, T]): DataFrame = {
+    if (col == "*") {
+      replace0(df.columns, replacement)
+    } else {
+      replace0(Seq(col), replacement)
+    }
+  }
+
+  /**
+   * (Scala-specific) Replaces values matching keys in `replacement` map.
+   * Key and value of `replacement` map must have the same type, and can only be doubles or strings.
+   *
+   * {{{
+   *   // Replaces all occurrences of 1.0 with 2.0 in column "height" and "weight".
+   *   df.replace("height" :: "weight" :: Nil, Map(1.0 -> 2.0));
+   *
+   *   // Replaces all occurrences of "UNKNOWN" with "unnamed" in column "firstname" and "lastname".
+   *   df.replace("firstname" :: "lastname" :: Nil, Map("UNKNOWN" -> "unnamed");
+   * }}}
+   *
+   * @param cols list of columns to apply the value replacement
+   * @param replacement value replacement map, as explained above
+   */
+  def replace[T](cols: Seq[String], replacement: Map[T, T]): DataFrame = replace0(cols, replacement)
+
+  private def replace0[T](cols: Seq[String], replacement: Map[T, T]): DataFrame = {
+    if (replacement.isEmpty || cols.isEmpty) {
+      return df
+    }
+
+    // replacementMap is either Map[String, String] or Map[Double, Double]
+    val replacementMap: Map[_, _] = replacement.head._2 match {
+      case v: String => replacement
+      case _ => replacement.map { case (k, v) => (convertToDouble(k), convertToDouble(v)) }
+    }
+
+    // targetColumnType is either DoubleType or StringType
+    val targetColumnType = replacement.head._1 match {
+      case _: jl.Double | _: jl.Float | _: jl.Integer | _: jl.Long => DoubleType
+      case _: String => StringType
+    }
+
+    val columnEquals = df.sqlContext.analyzer.resolver
+    val projections = df.schema.fields.map { f =>
+      val shouldReplace = cols.exists(colName => columnEquals(colName, f.name))
+      if (f.dataType.isInstanceOf[NumericType] && targetColumnType == DoubleType && shouldReplace) {
+        replaceCol(f, replacementMap)
+      } else if (f.dataType == targetColumnType && shouldReplace) {
+        replaceCol(f, replacementMap)
+      } else {
+        df.col(f.name)
+      }
+    }
+    df.select(projections : _*)
+  }
+
   private def fill0(values: Seq[(String, Any)]): DataFrame = {
     // Error handling
     values.foreach { case (colName, replaceValue) =>
@@ -228,4 +349,27 @@ final class DataFrameNaFunctions private[sql](df: DataFrame) {
   private def fillCol[T](col: StructField, replacement: T): Column = {
     coalesce(df.col(col.name), lit(replacement).cast(col.dataType)).as(col.name)
   }
+
+  /**
+   * Returns a [[Column]] expression that replaces value matching key in `replacementMap` with
+   * value in `replacementMap`, using [[CaseWhen]].
+   *
+   * TODO: This can be optimized to use broadcast join when replacementMap is large.
+   */
+  private def replaceCol(col: StructField, replacementMap: Map[_, _]): Column = {
+    val branches: Seq[Expression] = replacementMap.flatMap { case (source, target) =>
+      df.col(col.name).equalTo(lit(source).cast(col.dataType)).expr ::
+        lit(target).cast(col.dataType).expr :: Nil
+    }.toSeq
+    new Column(CaseWhen(branches ++ Seq(df.col(col.name).expr))).as(col.name)
+  }
+
+  private def convertToDouble(v: Any): Double = v match {
+    case v: Float => v.toDouble
+    case v: Double => v
+    case v: Long => v.toDouble
+    case v: Int => v.toDouble
+    case v => throw new IllegalArgumentException(
+      s"Unsupported value type ${v.getClass.getName} ($v).")
+  }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala
index 0896f175c056f..41b4f02e6a294 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala
@@ -154,4 +154,38 @@ class DataFrameNaFunctionsSuite extends QueryTest {
       ))),
       Row("test", null, 1, 2.2))
   }
+
+  test("replace") {
+    val input = createDF()
+
+    // Replace two numeric columns: age and height
+    val out = input.na.replace(Seq("age", "height"), Map(
+      16 -> 61,
+      60 -> 6,
+      164.3 -> 461.3  // Alice is really tall
+    ))
+
+    checkAnswer(
+      out,
+      Row("Bob", 61, 176.5) ::
+        Row("Alice", null, 461.3) ::
+        Row("David", 6, null) ::
+        Row("Amy", null, null) ::
+        Row(null, null, null) :: Nil)
+
+    // Replace only the age column
+    val out1 = input.na.replace("age", Map(
+      16 -> 61,
+      60 -> 6,
+      164.3 -> 461.3  // Alice is really tall
+    ))
+
+    checkAnswer(
+      out1,
+      Row("Bob", 61, 176.5) ::
+        Row("Alice", null, 164.3) ::
+        Row("David", 6, null) ::
+        Row("Amy", null, null) ::
+        Row(null, null, null) :: Nil)
+  }
 }

From 950645d597dbc5a8c5010bcb1a9b51c6abad86ea Mon Sep 17 00:00:00 2001
From: Dean Chen <deanchen5@gmail.com>
Date: Mon, 13 Apr 2015 12:08:55 +0100
Subject: [PATCH 70/95] [SPARK-6868][YARN] Fix broken container log link on
 executor page when HTTPS_ONLY.

Correct http schema in YARN container log link in Spark UI when container logs when YARN is configured to be HTTPS_ONLY.

Uses the same logic as the YARN jobtracker webapp. Entry point is [JobBlock](https://github.com/apache/hadoop/blob/e1109fb65608a668cd53dc324dadc6f63a74eeb9/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-app/src/main/java/org/apache/hadoop/mapreduce/v2/app/webapp/JobBlock.java#L108) and logic is in [MRWebAppUtil](https://github.com/apache/hadoop/blob/e1109fb65608a668cd53dc324dadc6f63a74eeb9/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-common/src/main/java/org/apache/hadoop/mapreduce/v2/util/MRWebAppUtil.java#L75).

I chose to migrate the logic over instead of importing MRWebAppUtil(but can update the PR to do so) since the class is designated as private and the logic was straightforward.

Author: Dean Chen <deanchen5@gmail.com>

Closes #5477 from deanchen/container-url and squashes the following commits:

91d3090 [Dean Chen] Correct http schema in YARN container log link in Spark UI when container logs when YARN is configured to be HTTPS_ONLY.
---
 .../apache/spark/deploy/yarn/ExecutorRunnable.scala | 13 +++++++++++--
 1 file changed, 11 insertions(+), 2 deletions(-)

diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnable.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnable.scala
index 1ce10d906ab23..b06069c07f451 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnable.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnable.scala
@@ -290,10 +290,19 @@ class ExecutorRunnable(
       YarnSparkHadoopUtil.setEnvFromInputString(env, userEnvs)
     }
 
+    // lookup appropriate http scheme for container log urls
+    val yarnHttpPolicy = yarnConf.get(
+      YarnConfiguration.YARN_HTTP_POLICY_KEY,
+      YarnConfiguration.YARN_HTTP_POLICY_DEFAULT
+    )
+    val httpScheme = if (yarnHttpPolicy == "HTTPS_ONLY") "https://" else "http://"
+
     // Add log urls
     sys.env.get("SPARK_USER").foreach { user =>
-      val baseUrl = "http://%s/node/containerlogs/%s/%s"
-        .format(container.getNodeHttpAddress, ConverterUtils.toString(container.getId), user)
+      val containerId = ConverterUtils.toString(container.getId)
+      val address = container.getNodeHttpAddress
+      val baseUrl = s"$httpScheme$address/node/containerlogs/$containerId/$user"
+
       env("SPARK_LOG_URL_STDERR") = s"$baseUrl/stderr?start=0"
       env("SPARK_LOG_URL_STDOUT") = s"$baseUrl/stdout?start=0"
     }

From cadd7d72c52ccc8d2def405a77dcf807fb5c17c2 Mon Sep 17 00:00:00 2001
From: lisurprise <zhichao.li@intel.com>
Date: Mon, 13 Apr 2015 12:18:05 +0100
Subject: [PATCH 71/95] [SPARK-6762]Fix potential resource leaks in CheckPoint
 CheckpointWriter and CheckpointReader

The close action should be placed within finally block to avoid the potential resource leaks

Author: lisurprise <zhichao.li@intel.com>

Closes #5407 from zhichao-li/master and squashes the following commits:

065999f [lisurprise] add guard for null
ef862d6 [lisurprise] remove fs.close
a754adc [lisurprise] refactor with tryWithSafeFinally
824adb3 [lisurprise] close before validation
c877da7 [lisurprise] Fix potential resource leaks
---
 .../apache/spark/streaming/Checkpoint.scala   | 47 ++++++++++++-------
 .../spark/streaming/util/RawTextSender.scala  |  3 +-
 2 files changed, 31 insertions(+), 19 deletions(-)

diff --git a/streaming/src/main/scala/org/apache/spark/streaming/Checkpoint.scala b/streaming/src/main/scala/org/apache/spark/streaming/Checkpoint.scala
index 28703ef8129b3..0a50485118588 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/Checkpoint.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/Checkpoint.scala
@@ -26,7 +26,7 @@ import org.apache.hadoop.conf.Configuration
 
 import org.apache.spark.{SparkException, SparkConf, Logging}
 import org.apache.spark.io.CompressionCodec
-import org.apache.spark.util.MetadataCleaner
+import org.apache.spark.util.{MetadataCleaner, Utils}
 import org.apache.spark.streaming.scheduler.JobGenerator
 
 
@@ -139,8 +139,11 @@ class CheckpointWriter(
           // Write checkpoint to temp file
           fs.delete(tempFile, true)   // just in case it exists
           val fos = fs.create(tempFile)
-          fos.write(bytes)
-          fos.close()
+          Utils.tryWithSafeFinally {
+            fos.write(bytes)
+          } {
+            fos.close()
+          }
 
           // If the checkpoint file exists, back it up
           // If the backup exists as well, just delete it, otherwise rename will fail
@@ -187,9 +190,11 @@ class CheckpointWriter(
     val bos = new ByteArrayOutputStream()
     val zos = compressionCodec.compressedOutputStream(bos)
     val oos = new ObjectOutputStream(zos)
-    oos.writeObject(checkpoint)
-    oos.close()
-    bos.close()
+    Utils.tryWithSafeFinally {
+      oos.writeObject(checkpoint)
+    } {
+      oos.close()
+    }
     try {
       executor.execute(new CheckpointWriteHandler(
         checkpoint.checkpointTime, bos.toByteArray, clearCheckpointDataLater))
@@ -248,18 +253,24 @@ object CheckpointReader extends Logging {
     checkpointFiles.foreach(file => {
       logInfo("Attempting to load checkpoint from file " + file)
       try {
-        val fis = fs.open(file)
-        // ObjectInputStream uses the last defined user-defined class loader in the stack
-        // to find classes, which maybe the wrong class loader. Hence, a inherited version
-        // of ObjectInputStream is used to explicitly use the current thread's default class
-        // loader to find and load classes. This is a well know Java issue and has popped up
-        // in other places (e.g., http://jira.codehaus.org/browse/GROOVY-1627)
-        val zis = compressionCodec.compressedInputStream(fis)
-        val ois = new ObjectInputStreamWithLoader(zis,
-          Thread.currentThread().getContextClassLoader)
-        val cp = ois.readObject.asInstanceOf[Checkpoint]
-        ois.close()
-        fs.close()
+        var ois: ObjectInputStreamWithLoader = null
+        var cp: Checkpoint = null
+        Utils.tryWithSafeFinally {
+          val fis = fs.open(file)
+          // ObjectInputStream uses the last defined user-defined class loader in the stack
+          // to find classes, which maybe the wrong class loader. Hence, a inherited version
+          // of ObjectInputStream is used to explicitly use the current thread's default class
+          // loader to find and load classes. This is a well know Java issue and has popped up
+          // in other places (e.g., http://jira.codehaus.org/browse/GROOVY-1627)
+          val zis = compressionCodec.compressedInputStream(fis)
+          ois = new ObjectInputStreamWithLoader(zis,
+            Thread.currentThread().getContextClassLoader)
+          cp = ois.readObject.asInstanceOf[Checkpoint]
+        } {
+          if (ois != null) {
+            ois.close()
+          }
+        }
         cp.validate()
         logInfo("Checkpoint successfully loaded from file " + file)
         logInfo("Checkpoint was generated at time " + cp.checkpointTime)
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/util/RawTextSender.scala b/streaming/src/main/scala/org/apache/spark/streaming/util/RawTextSender.scala
index a7850812bd612..ca2f319f174a2 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/util/RawTextSender.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/util/RawTextSender.scala
@@ -72,7 +72,8 @@ object RawTextSender extends Logging {
       } catch {
         case e: IOException =>
           logError("Client disconnected")
-          socket.close()
+      } finally {
+        socket.close()
       }
     }
   }

From 14ce3ea2c9546c58203af85aceb76b1bfc1f650a Mon Sep 17 00:00:00 2001
From: zsxwing <zsxwing@gmail.com>
Date: Mon, 13 Apr 2015 12:21:29 +0100
Subject: [PATCH 72/95] [SPARK-6860][Streaming][WebUI] Fix the possible
 inconsistency of StreamingPage

Because `StreamingPage.render` doesn't hold the `listener` lock when generating the content, the different parts of content may have some inconsistent values if `listener` updates its status at the same time. And it will confuse people.

This PR added `listener.synchronized` to make sure we have a consistent view of StreamingJobProgressListener when creating the content.

Author: zsxwing <zsxwing@gmail.com>

Closes #5470 from zsxwing/SPARK-6860 and squashes the following commits:

cec6f92 [zsxwing] Add missing 'synchronized' in StreamingJobProgressListener
7182498 [zsxwing] Add synchronized to make sure we have a consistent view of StreamingJobProgressListener when creating the content
---
 .../streaming/ui/StreamingJobProgressListener.scala    | 10 +++++-----
 .../org/apache/spark/streaming/ui/StreamingPage.scala  |  3 ++-
 2 files changed, 7 insertions(+), 6 deletions(-)

diff --git a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala
index 84f80e638f638..be1e8686cf9fa 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala
@@ -149,7 +149,7 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext)
     }.toMap
   }
 
-  def lastReceivedBatchRecords: Map[Int, Long] = {
+  def lastReceivedBatchRecords: Map[Int, Long] = synchronized {
     val lastReceivedBlockInfoOption = lastReceivedBatch.map(_.receivedBlockInfo)
     lastReceivedBlockInfoOption.map { lastReceivedBlockInfo =>
       (0 until numReceivers).map { receiverId =>
@@ -160,19 +160,19 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext)
     }
   }
 
-  def receiverInfo(receiverId: Int): Option[ReceiverInfo] = {
+  def receiverInfo(receiverId: Int): Option[ReceiverInfo] = synchronized {
     receiverInfos.get(receiverId)
   }
 
-  def lastCompletedBatch: Option[BatchInfo] = {
+  def lastCompletedBatch: Option[BatchInfo] = synchronized {
     completedBatchInfos.sortBy(_.batchTime)(Time.ordering).lastOption
   }
 
-  def lastReceivedBatch: Option[BatchInfo] = {
+  def lastReceivedBatch: Option[BatchInfo] = synchronized {
     retainedBatches.lastOption
   }
 
-  private def retainedBatches: Seq[BatchInfo] = synchronized {
+  private def retainedBatches: Seq[BatchInfo] = {
     (waitingBatchInfos.values.toSeq ++
       runningBatchInfos.values.toSeq ++ completedBatchInfos).sortBy(_.batchTime)(Time.ordering)
   }
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingPage.scala b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingPage.scala
index bfe8086fcf8fe..b6dcb62bfeec8 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingPage.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingPage.scala
@@ -37,11 +37,12 @@ private[ui] class StreamingPage(parent: StreamingTab)
 
   /** Render the page */
   def render(request: HttpServletRequest): Seq[Node] = {
-    val content =
+    val content = listener.synchronized {
       generateBasicStats() ++ <br></br> ++
       <h4>Statistics over last {listener.retainedCompletedBatches.size} processed batches</h4> ++
       generateReceiverStats() ++
       generateBatchStatsTable()
+    }
     UIUtils.headerSparkPage("Streaming", content, parent, Some(5000))
   }
 

From 9d117cee0be2c73a25702d98f78211055d50babe Mon Sep 17 00:00:00 2001
From: nyaapa <nyaapa@gmail.com>
Date: Mon, 13 Apr 2015 12:55:25 +0100
Subject: [PATCH 73/95] [SPARK-6440][CORE]Handle IPv6 addresses properly when
 constructing URI

Author: nyaapa <nyaapa@gmail.com>

Closes #5424 from nyaapa/master and squashes the following commits:

6b717aa [nyaapa] [SPARK-6440][CORE] Remove Utils.localIpAddressHostname, Utils.localIpAddressURI and Utils.getAddressHostName; make Utils.localIpAddress private; rename Utils.localHostURI into Utils.localHostNameForURI; use Utils.localHostName in org.apache.spark.streaming.kinesis.KinesisReceiver and org.apache.spark.sql.hive.thriftserver.SparkSQLEnv
2098081 [nyaapa] [SPARK-6440][CORE] style fixes and use getHostAddress instead of getHostName
84763d7 [nyaapa] [SPARK-6440][CORE]Handle IPv6 addresses properly when constructing URI
---
 .../scala/org/apache/spark/HttpServer.scala   |  2 +-
 .../spark/deploy/LocalSparkCluster.scala      |  2 +-
 .../spark/deploy/client/TestClient.scala      |  2 +-
 .../scala/org/apache/spark/ui/WebUI.scala     |  2 +-
 .../scala/org/apache/spark/util/Utils.scala   | 34 ++++++++++++-------
 .../streaming/kinesis/KinesisReceiver.scala   |  3 +-
 .../sql/hive/thriftserver/SparkSQLEnv.scala   |  3 +-
 7 files changed, 29 insertions(+), 19 deletions(-)

diff --git a/core/src/main/scala/org/apache/spark/HttpServer.scala b/core/src/main/scala/org/apache/spark/HttpServer.scala
index 09a9ccc226721..8de3a6c04df34 100644
--- a/core/src/main/scala/org/apache/spark/HttpServer.scala
+++ b/core/src/main/scala/org/apache/spark/HttpServer.scala
@@ -160,7 +160,7 @@ private[spark] class HttpServer(
       throw new ServerStateException("Server is not started")
     } else {
       val scheme = if (securityManager.fileServerSSLOptions.enabled) "https" else "http"
-      s"$scheme://${Utils.localIpAddress}:$port"
+      s"$scheme://${Utils.localHostNameForURI()}:$port"
     }
   }
 }
diff --git a/core/src/main/scala/org/apache/spark/deploy/LocalSparkCluster.scala b/core/src/main/scala/org/apache/spark/deploy/LocalSparkCluster.scala
index 3ab425aab84c8..f0e77c2ba982b 100644
--- a/core/src/main/scala/org/apache/spark/deploy/LocalSparkCluster.scala
+++ b/core/src/main/scala/org/apache/spark/deploy/LocalSparkCluster.scala
@@ -53,7 +53,7 @@ class LocalSparkCluster(
     /* Start the Master */
     val (masterSystem, masterPort, _, _) = Master.startSystemAndActor(localHostname, 0, 0, _conf)
     masterActorSystems += masterSystem
-    val masterUrl = "spark://" + localHostname + ":" + masterPort
+    val masterUrl = "spark://" + Utils.localHostNameForURI() + ":" + masterPort
     val masters = Array(masterUrl)
 
     /* Start the Workers */
diff --git a/core/src/main/scala/org/apache/spark/deploy/client/TestClient.scala b/core/src/main/scala/org/apache/spark/deploy/client/TestClient.scala
index c1c4812f17fbe..40835b9550586 100644
--- a/core/src/main/scala/org/apache/spark/deploy/client/TestClient.scala
+++ b/core/src/main/scala/org/apache/spark/deploy/client/TestClient.scala
@@ -46,7 +46,7 @@ private[spark] object TestClient {
   def main(args: Array[String]) {
     val url = args(0)
     val conf = new SparkConf
-    val (actorSystem, _) = AkkaUtils.createActorSystem("spark", Utils.localIpAddress, 0,
+    val (actorSystem, _) = AkkaUtils.createActorSystem("spark", Utils.localHostName(), 0,
       conf = conf, securityManager = new SecurityManager(conf))
     val desc = new ApplicationDescription("TestClient", Some(1), 512,
       Command("spark.deploy.client.TestExecutor", Seq(), Map(), Seq(), Seq(), Seq()), "ignored")
diff --git a/core/src/main/scala/org/apache/spark/ui/WebUI.scala b/core/src/main/scala/org/apache/spark/ui/WebUI.scala
index ea548f23120d9..f9860d1a5ce76 100644
--- a/core/src/main/scala/org/apache/spark/ui/WebUI.scala
+++ b/core/src/main/scala/org/apache/spark/ui/WebUI.scala
@@ -48,7 +48,7 @@ private[spark] abstract class WebUI(
   protected val handlers = ArrayBuffer[ServletContextHandler]()
   protected val pageToHandlers = new HashMap[WebUIPage, ArrayBuffer[ServletContextHandler]]
   protected var serverInfo: Option[ServerInfo] = None
-  protected val localHostName = Utils.localHostName()
+  protected val localHostName = Utils.localHostNameForURI()
   protected val publicHostName = Option(conf.getenv("SPARK_PUBLIC_DNS")).getOrElse(localHostName)
   private val className = Utils.getFormattedClassName(this)
 
diff --git a/core/src/main/scala/org/apache/spark/util/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala
index 0fdfaf300e95d..a541d660cd5c6 100644
--- a/core/src/main/scala/org/apache/spark/util/Utils.scala
+++ b/core/src/main/scala/org/apache/spark/util/Utils.scala
@@ -34,6 +34,7 @@ import scala.util.Try
 import scala.util.control.{ControlThrowable, NonFatal}
 
 import com.google.common.io.{ByteStreams, Files}
+import com.google.common.net.InetAddresses
 import com.google.common.util.concurrent.ThreadFactoryBuilder
 import org.apache.commons.lang3.SystemUtils
 import org.apache.hadoop.conf.Configuration
@@ -789,13 +790,12 @@ private[spark] object Utils extends Logging {
    * Get the local host's IP address in dotted-quad format (e.g. 1.2.3.4).
    * Note, this is typically not used from within core spark.
    */
-  lazy val localIpAddress: String = findLocalIpAddress()
-  lazy val localIpAddressHostname: String = getAddressHostName(localIpAddress)
+  private lazy val localIpAddress: InetAddress = findLocalInetAddress()
 
-  private def findLocalIpAddress(): String = {
+  private def findLocalInetAddress(): InetAddress = {
     val defaultIpOverride = System.getenv("SPARK_LOCAL_IP")
     if (defaultIpOverride != null) {
-      defaultIpOverride
+      InetAddress.getByName(defaultIpOverride)
     } else {
       val address = InetAddress.getLocalHost
       if (address.isLoopbackAddress) {
@@ -806,15 +806,20 @@ private[spark] object Utils extends Logging {
         // It's more proper to pick ip address following system output order.
         val activeNetworkIFs = NetworkInterface.getNetworkInterfaces.toList
         val reOrderedNetworkIFs = if (isWindows) activeNetworkIFs else activeNetworkIFs.reverse
+
         for (ni <- reOrderedNetworkIFs) {
-          for (addr <- ni.getInetAddresses if !addr.isLinkLocalAddress &&
-               !addr.isLoopbackAddress && addr.isInstanceOf[Inet4Address]) {
+          val addresses = ni.getInetAddresses.toList
+            .filterNot(addr => addr.isLinkLocalAddress || addr.isLoopbackAddress)
+          if (addresses.nonEmpty) {
+            val addr = addresses.find(_.isInstanceOf[Inet4Address]).getOrElse(addresses.head)
+            // because of Inet6Address.toHostName may add interface at the end if it knows about it
+            val strippedAddress = InetAddress.getByAddress(addr.getAddress)
             // We've found an address that looks reasonable!
             logWarning("Your hostname, " + InetAddress.getLocalHost.getHostName + " resolves to" +
-              " a loopback address: " + address.getHostAddress + "; using " + addr.getHostAddress +
-              " instead (on interface " + ni.getName + ")")
+              " a loopback address: " + address.getHostAddress + "; using " +
+              strippedAddress.getHostAddress + " instead (on interface " + ni.getName + ")")
             logWarning("Set SPARK_LOCAL_IP if you need to bind to another address")
-            return addr.getHostAddress
+            return strippedAddress
           }
         }
         logWarning("Your hostname, " + InetAddress.getLocalHost.getHostName + " resolves to" +
@@ -822,7 +827,7 @@ private[spark] object Utils extends Logging {
           " external IP address!")
         logWarning("Set SPARK_LOCAL_IP if you need to bind to another address")
       }
-      address.getHostAddress
+      address
     }
   }
 
@@ -842,11 +847,14 @@ private[spark] object Utils extends Logging {
    * Get the local machine's hostname.
    */
   def localHostName(): String = {
-    customHostname.getOrElse(localIpAddressHostname)
+    customHostname.getOrElse(localIpAddress.getHostAddress)
   }
 
-  def getAddressHostName(address: String): String = {
-    InetAddress.getByName(address).getHostName
+  /**
+   * Get the local machine's URI.
+   */
+  def localHostNameForURI(): String = {
+    customHostname.getOrElse(InetAddresses.toUriString(localIpAddress))
   }
 
   def checkHost(host: String, message: String = "") {
diff --git a/extras/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisReceiver.scala b/extras/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisReceiver.scala
index 1bd1f324298e7..a7fe4476cacb8 100644
--- a/extras/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisReceiver.scala
+++ b/extras/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisReceiver.scala
@@ -23,6 +23,7 @@ import org.apache.spark.Logging
 import org.apache.spark.storage.StorageLevel
 import org.apache.spark.streaming.Duration
 import org.apache.spark.streaming.receiver.Receiver
+import org.apache.spark.util.Utils
 
 import com.amazonaws.auth.AWSCredentialsProvider
 import com.amazonaws.auth.DefaultAWSCredentialsProviderChain
@@ -118,7 +119,7 @@ private[kinesis] class KinesisReceiver(
    *    method.
    */
   override def onStart() {
-    workerId = InetAddress.getLocalHost.getHostAddress() + ":" + UUID.randomUUID()
+    workerId = Utils.localHostName() + ":" + UUID.randomUUID()
     credentialsProvider = new DefaultAWSCredentialsProviderChain()
     kinesisClientLibConfiguration = new KinesisClientLibConfiguration(appName, streamName,
       credentialsProvider, workerId).withKinesisEndpoint(endpointUrl)
diff --git a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLEnv.scala b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLEnv.scala
index 158c225159720..97b46a01ba5b4 100644
--- a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLEnv.scala
+++ b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLEnv.scala
@@ -22,6 +22,7 @@ import scala.collection.JavaConversions._
 import org.apache.spark.scheduler.StatsReportListener
 import org.apache.spark.sql.hive.{HiveShim, HiveContext}
 import org.apache.spark.{Logging, SparkConf, SparkContext}
+import org.apache.spark.util.Utils
 
 /** A singleton object for the master program. The slaves should not access this. */
 private[hive] object SparkSQLEnv extends Logging {
@@ -37,7 +38,7 @@ private[hive] object SparkSQLEnv extends Logging {
       val maybeKryoReferenceTracking = sparkConf.getOption("spark.kryo.referenceTracking")
 
       sparkConf
-        .setAppName(s"SparkSQL::${java.net.InetAddress.getLocalHost.getHostName}")
+        .setAppName(s"SparkSQL::${Utils.localHostName()}")
         .set("spark.sql.hive.version", HiveShim.version)
         .set(
           "spark.serializer",

From 240ea03faea005306e73c10253716b95487325ff Mon Sep 17 00:00:00 2001
From: Pradeep Chanumolu <pchanumolu@maprtech.com>
Date: Mon, 13 Apr 2015 13:02:55 +0100
Subject: [PATCH 74/95] [SPARK-6671] Add status command for spark daemons

SPARK-6671
Currently using the spark-daemon.sh script we can start and stop the spark demons. But we cannot get the status of the daemons. It will be nice to include the status command in the spark-daemon.sh script, through which we can know if the spark demon is alive or not.

Author: Pradeep Chanumolu <pchanumolu@maprtech.com>

Closes #5327 from pchanumolu/master and squashes the following commits:

d3a1f05 [Pradeep Chanumolu] Make status command check consistent with Stop command
5062926 [Pradeep Chanumolu] Fix indentation in spark-daemon.sh
3e66bc8 [Pradeep Chanumolu] SPARK-6671 : Add status command to spark daemons
1ac3918 [Pradeep Chanumolu] Add status command to spark-daemon
---
 sbin/spark-daemon.sh | 19 ++++++++++++++++++-
 1 file changed, 18 insertions(+), 1 deletion(-)

diff --git a/sbin/spark-daemon.sh b/sbin/spark-daemon.sh
index 92e76a3fe6ca2..d8e0facb81169 100755
--- a/sbin/spark-daemon.sh
+++ b/sbin/spark-daemon.sh
@@ -29,7 +29,7 @@
 #   SPARK_NICENESS The scheduling priority for daemons. Defaults to 0.
 ##
 
-usage="Usage: spark-daemon.sh [--config <conf-dir>] (start|stop) <spark-command> <spark-instance-number> <args...>"
+usage="Usage: spark-daemon.sh [--config <conf-dir>] (start|stop|status) <spark-command> <spark-instance-number> <args...>"
 
 # if no args specified, show usage
 if [ $# -le 1 ]; then
@@ -195,6 +195,23 @@ case $option in
     fi
     ;;
 
+  (status)
+
+    if [ -f $pid ]; then
+      TARGET_ID="$(cat "$pid")"
+      if [[ $(ps -p "$TARGET_ID" -o comm=) =~ "java" ]]; then
+        echo $command is running.
+        exit 0
+      else
+        echo $pid file is present but $command not running
+        exit 1
+      fi  
+    else
+      echo $command not running.
+      exit 2
+    fi  
+    ;;
+  
   (*)
     echo $usage
     exit 1

From 202ebf06e0f2d5df8b712e604fd95fa58e34ea20 Mon Sep 17 00:00:00 2001
From: linweizhong <linweizhong@huawei.com>
Date: Mon, 13 Apr 2015 13:06:54 +0100
Subject: [PATCH 75/95] [SPARK-6870][Yarn] Catch InterruptedException when yarn
 application state monitor thread been interrupted

On PR #5305 we interrupt the monitor thread but forget to catch the InterruptedException, then in the log will print the stack info, so we need to catch it.

Author: linweizhong <linweizhong@huawei.com>

Closes #5479 from Sephiroth-Lin/SPARK-6870 and squashes the following commits:

f775f93 [linweizhong] Update, don't need to call Thread.currentThread() on monitor thread
0e2ef1f [linweizhong] Update
0d8958a [linweizhong] Update
3513fdb [linweizhong] Catch InterruptedException
---
 .../cluster/YarnClientSchedulerBackend.scala          | 11 +++++++----
 1 file changed, 7 insertions(+), 4 deletions(-)

diff --git a/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala b/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala
index 407dc1ac4d37d..99c05329b4d73 100644
--- a/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala
+++ b/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala
@@ -128,10 +128,13 @@ private[spark] class YarnClientSchedulerBackend(
     assert(client != null && appId != null, "Application has not been submitted yet!")
     val t = new Thread {
       override def run() {
-        val (state, _) = client.monitorApplication(appId, logApplicationReport = false)
-        logError(s"Yarn application has already exited with state $state!")
-        sc.stop()
-        Thread.currentThread().interrupt()
+        try {
+          val (state, _) = client.monitorApplication(appId, logApplicationReport = false)
+          logError(s"Yarn application has already exited with state $state!")
+          sc.stop()
+        } catch {
+          case e: InterruptedException => logInfo("Interrupting monitor thread")
+        }
       }
     }
     t.setName("Yarn application state monitor")

From b29663eeea440b1d1a288d41b5ddf67e77c5bd54 Mon Sep 17 00:00:00 2001
From: Pei-Lun Lee <pllee@appier.com>
Date: Mon, 13 Apr 2015 21:52:00 +0800
Subject: [PATCH 76/95] [SPARK-6352] [SQL] Add DirectParquetOutputCommitter

Add a DirectParquetOutputCommitter class that skips _temporary directory when saving to s3. Add new config value "spark.sql.parquet.useDirectParquetOutputCommitter" (default false) to choose between the default output committer.

Author: Pei-Lun Lee <pllee@appier.com>

Closes #5042 from ypcat/spark-6352 and squashes the following commits:

e17bf47 [Pei-Lun Lee] Merge branch 'master' of https://github.com/apache/spark into spark-6352
9ae7545 [Pei-Lun Lee] [SPARL-6352] [SQL] Change to allow custom parquet output committer.
0d540b9 [Pei-Lun Lee] [SPARK-6352] [SQL] add license
c42468c [Pei-Lun Lee] [SPARK-6352] [SQL] add test case
0fc03ca [Pei-Lun Lee] [SPARK-6532] [SQL] hide class DirectParquetOutputCommitter
769bd67 [Pei-Lun Lee] DirectParquetOutputCommitter
f75e261 [Pei-Lun Lee] DirectParquetOutputCommitter
---
 .../DirectParquetOutputCommitter.scala        | 66 +++++++++++++++++++
 .../sql/parquet/ParquetTableOperations.scala  | 22 +++++++
 .../spark/sql/parquet/ParquetIOSuite.scala    | 21 ++++++
 3 files changed, 109 insertions(+)
 create mode 100644 sql/core/src/main/scala/org/apache/spark/sql/parquet/DirectParquetOutputCommitter.scala

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/DirectParquetOutputCommitter.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/DirectParquetOutputCommitter.scala
new file mode 100644
index 0000000000000..25a66cb488103
--- /dev/null
+++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/DirectParquetOutputCommitter.scala
@@ -0,0 +1,66 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.parquet
+
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.mapreduce.{JobContext, TaskAttemptContext}
+import org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter
+
+import parquet.Log
+import parquet.hadoop.util.ContextUtil
+import parquet.hadoop.{ParquetFileReader, ParquetFileWriter, ParquetOutputCommitter}
+
+private[parquet] class DirectParquetOutputCommitter(outputPath: Path, context: TaskAttemptContext)
+  extends ParquetOutputCommitter(outputPath, context) {
+  val LOG = Log.getLog(classOf[ParquetOutputCommitter])
+
+  override def getWorkPath(): Path = outputPath
+  override def abortTask(taskContext: TaskAttemptContext): Unit = {}
+  override def commitTask(taskContext: TaskAttemptContext): Unit = {}
+  override def needsTaskCommit(taskContext: TaskAttemptContext): Boolean = true
+  override def setupJob(jobContext: JobContext): Unit = {}
+  override def setupTask(taskContext: TaskAttemptContext): Unit = {}
+
+  override def commitJob(jobContext: JobContext) {
+    try {
+      val configuration = ContextUtil.getConfiguration(jobContext)
+      val fileSystem = outputPath.getFileSystem(configuration)
+      val outputStatus = fileSystem.getFileStatus(outputPath)
+      val footers = ParquetFileReader.readAllFootersInParallel(configuration, outputStatus)
+      try {
+        ParquetFileWriter.writeMetadataFile(configuration, outputPath, footers)
+        if (configuration.getBoolean("mapreduce.fileoutputcommitter.marksuccessfuljobs", true)) {
+          val successPath = new Path(outputPath, FileOutputCommitter.SUCCEEDED_FILE_NAME)
+          fileSystem.create(successPath).close()
+        }
+      } catch {
+        case e: Exception => {
+          LOG.warn("could not write summary file for " + outputPath, e)
+          val metadataPath = new Path(outputPath, ParquetFileWriter.PARQUET_METADATA_FILE)
+          if (fileSystem.exists(metadataPath)) {
+            fileSystem.delete(metadataPath, true)
+          }
+        }
+      }
+    } catch {
+      case e: Exception => LOG.warn("could not write summary file for " + outputPath, e)
+    }
+  }
+
+}
+
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala
index 1c868da23e060..3724bda829d30 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala
@@ -379,6 +379,8 @@ private[sql] case class InsertIntoParquetTable(
  */
 private[parquet] class AppendingParquetOutputFormat(offset: Int)
   extends parquet.hadoop.ParquetOutputFormat[Row] {
+  var committer: OutputCommitter = null
+
   // override to accept existing directories as valid output directory
   override def checkOutputSpecs(job: JobContext): Unit = {}
 
@@ -403,6 +405,26 @@ private[parquet] class AppendingParquetOutputFormat(offset: Int)
   private def getTaskAttemptID(context: TaskAttemptContext): TaskAttemptID = {
     context.getClass.getMethod("getTaskAttemptID").invoke(context).asInstanceOf[TaskAttemptID]
   }
+
+  // override to create output committer from configuration
+  override def getOutputCommitter(context: TaskAttemptContext): OutputCommitter = {
+    if (committer == null) {
+      val output = getOutputPath(context)
+      val cls = context.getConfiguration.getClass("spark.sql.parquet.output.committer.class",
+        classOf[ParquetOutputCommitter], classOf[ParquetOutputCommitter])
+      val ctor = cls.getDeclaredConstructor(classOf[Path], classOf[TaskAttemptContext])
+      committer = ctor.newInstance(output, context).asInstanceOf[ParquetOutputCommitter]
+    }
+    committer
+  }
+
+  // FileOutputFormat.getOutputPath takes JobConf in hadoop-1 but JobContext in hadoop-2
+  private def getOutputPath(context: TaskAttemptContext): Path = {
+    context.getConfiguration().get("mapred.output.dir") match {
+      case null => null
+      case name => new Path(name)
+    }
+  }
 }
 
 /**
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala
index 97c0f439acf13..4d0bf7cf99cdf 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala
@@ -381,6 +381,27 @@ class ParquetIOSuiteBase extends QueryTest with ParquetTest {
       }
     }
   }
+
+  test("SPARK-6352 DirectParquetOutputCommitter") {
+    // Write to a parquet file and let it fail.
+    // _temporary should be missing if direct output committer works.
+    try {
+      configuration.set("spark.sql.parquet.output.committer.class",
+        "org.apache.spark.sql.parquet.DirectParquetOutputCommitter")
+      sqlContext.udf.register("div0", (x: Int) => x / 0)
+      withTempPath { dir =>
+        intercept[org.apache.spark.SparkException] {
+          sqlContext.sql("select div0(1)").saveAsParquetFile(dir.getCanonicalPath)
+        }
+        val path = new Path(dir.getCanonicalPath, "_temporary")
+        val fs = path.getFileSystem(configuration)
+        assert(!fs.exists(path))
+      }
+    }
+    finally {
+      configuration.unset("spark.sql.parquet.output.committer.class")
+    }
+  }
 }
 
 class ParquetDataSourceOnIOSuite extends ParquetIOSuiteBase with BeforeAndAfterAll {

From 77620be76e82b6cdaae406cd752d3272656f5fe0 Mon Sep 17 00:00:00 2001
From: Doug Balog <doug.balog@target.com>
Date: Mon, 13 Apr 2015 09:49:58 -0500
Subject: [PATCH 77/95] [SPARK-6207] [YARN] [SQL] Adds delegation tokens for
 metastore to conf.

Adds hive2-metastore delegation token to conf when running in secure mode.
Without this change, running on YARN in cluster mode fails with a
GSS exception.

This is a rough patch that adds a dependency to spark/yarn on hive-exec.
I'm looking for suggestions on how to make this patch better.

This contribution is my original work and that I licenses the work to the
Apache Spark project under the project's open source licenses.

Author: Doug Balog <doug.balogtarget.com>

Author: Doug Balog <doug.balog@target.com>

Closes #5031 from dougb/SPARK-6207 and squashes the following commits:

3e9ac16 [Doug Balog] [SPARK-6207] Fixes minor code spacing issues.
e260765 [Doug Balog] [SPARK-6207] Second pass at adding Hive delegation token to conf. - Use reflection instead of adding dependency on hive. - Tested on Hive 0.13 and Hadoop 2.4.1
1ab1729 [Doug Balog] Merge branch 'master' of git://github.com/apache/spark into SPARK-6207
bf356d2 [Doug Balog] [SPARK-6207] [YARN] [SQL] Adds delegation tokens for metastore to conf. Adds hive2-metastore delagations token to conf when running in securemode. Without this change, runing on YARN in cluster mode fails with a GSS exception.
---
 .../org/apache/spark/deploy/yarn/Client.scala | 63 +++++++++++++++++++
 1 file changed, 63 insertions(+)

diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
index c1effd3c8a718..1091ff54b0463 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
@@ -22,17 +22,21 @@ import java.nio.ByteBuffer
 
 import scala.collection.JavaConversions._
 import scala.collection.mutable.{ArrayBuffer, HashMap, ListBuffer, Map}
+import scala.reflect.runtime.universe
 import scala.util.{Try, Success, Failure}
 
 import com.google.common.base.Objects
 
 import org.apache.hadoop.io.DataOutputBuffer
 import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.hdfs.security.token.delegation.DelegationTokenIdentifier
 import org.apache.hadoop.fs._
 import org.apache.hadoop.fs.permission.FsPermission
+import org.apache.hadoop.io.Text
 import org.apache.hadoop.mapred.Master
 import org.apache.hadoop.mapreduce.MRJobConfig
 import org.apache.hadoop.security.{Credentials, UserGroupInformation}
+import org.apache.hadoop.security.token.Token
 import org.apache.hadoop.util.StringUtils
 import org.apache.hadoop.yarn.api._
 import org.apache.hadoop.yarn.api.ApplicationConstants.Environment
@@ -220,6 +224,7 @@ private[spark] class Client(
     val dst = new Path(fs.getHomeDirectory(), appStagingDir)
     val nns = getNameNodesToAccess(sparkConf) + dst
     obtainTokensForNamenodes(nns, hadoopConf, credentials)
+    obtainTokenForHiveMetastore(hadoopConf, credentials)
 
     val replication = sparkConf.getInt("spark.yarn.submit.file.replication",
       fs.getDefaultReplication(dst)).toShort
@@ -936,6 +941,64 @@ object Client extends Logging {
     }
   }
 
+  /**
+   * Obtains token for the Hive metastore and adds them to the credentials.
+   */
+  private def obtainTokenForHiveMetastore(conf: Configuration, credentials: Credentials) {
+    if (UserGroupInformation.isSecurityEnabled) {
+      val mirror = universe.runtimeMirror(getClass.getClassLoader)
+
+      try {
+        val hiveClass = mirror.classLoader.loadClass("org.apache.hadoop.hive.ql.metadata.Hive")
+        val hive = hiveClass.getMethod("get").invoke(null)
+
+        val hiveConf = hiveClass.getMethod("getConf").invoke(hive)
+        val hiveConfClass = mirror.classLoader.loadClass("org.apache.hadoop.hive.conf.HiveConf")
+
+        val hiveConfGet = (param:String) => Option(hiveConfClass
+          .getMethod("get", classOf[java.lang.String])
+          .invoke(hiveConf, param))
+
+        val metastore_uri = hiveConfGet("hive.metastore.uris")
+
+        // Check for local metastore
+        if (metastore_uri != None && metastore_uri.get.toString.size > 0) {
+          val metastore_kerberos_principal_conf_var = mirror.classLoader
+            .loadClass("org.apache.hadoop.hive.conf.HiveConf$ConfVars")
+            .getField("METASTORE_KERBEROS_PRINCIPAL").get("varname").toString
+
+          val principal = hiveConfGet(metastore_kerberos_principal_conf_var)
+
+          val username = Option(UserGroupInformation.getCurrentUser().getUserName)
+          if (principal != None && username != None) {
+            val tokenStr = hiveClass.getMethod("getDelegationToken",
+              classOf[java.lang.String], classOf[java.lang.String])
+              .invoke(hive, username.get, principal.get).asInstanceOf[java.lang.String]
+
+            val hive2Token = new Token[DelegationTokenIdentifier]()
+            hive2Token.decodeFromUrlString(tokenStr)
+            credentials.addToken(new Text("hive.server2.delegation.token"),hive2Token)
+            logDebug("Added hive.Server2.delegation.token to conf.")
+            hiveClass.getMethod("closeCurrent").invoke(null)
+          } else {
+            logError("Username or principal == NULL")
+            logError(s"""username=${username.getOrElse("(NULL)")}""")
+            logError(s"""principal=${principal.getOrElse("(NULL)")}""")
+            throw new IllegalArgumentException("username and/or principal is equal to null!")
+          }
+        } else {
+          logDebug("HiveMetaStore configured in localmode")
+        }
+      } catch {
+        case e:java.lang.NoSuchMethodException => { logInfo("Hive Method not found " + e); return }
+        case e:java.lang.ClassNotFoundException => { logInfo("Hive Class not found " + e); return }
+        case e:Exception => { logError("Unexpected Exception " + e)
+          throw new RuntimeException("Unexpected exception", e)
+        }
+      }
+    }
+  }
+
   /**
    * Return whether the two file systems are the same.
    */

From c5b0b296b842926b5c07531a5affe8984bc799c5 Mon Sep 17 00:00:00 2001
From: Reynold Xin <rxin@databricks.com>
Date: Mon, 13 Apr 2015 09:29:04 -0700
Subject: [PATCH 78/95] [SPARK-6765] Enable scalastyle on test code.

Turn scalastyle on for all test code. Most of the violations have been resolved in my previous pull requests:

Core: https://github.com/apache/spark/pull/5484
SQL: https://github.com/apache/spark/pull/5412
MLlib: https://github.com/apache/spark/pull/5411
GraphX: https://github.com/apache/spark/pull/5410
Streaming: https://github.com/apache/spark/pull/5409

Author: Reynold Xin <rxin@databricks.com>

Closes #5486 from rxin/test-style-enable and squashes the following commits:

01683de [Reynold Xin] Fixed new code.
a4ab46e [Reynold Xin] Fixed tests.
20adbc8 [Reynold Xin] Missed one violation.
5e36521 [Reynold Xin] [SPARK-6765] Enable scalastyle on test code.
---
 .../org/apache/spark/deploy/ClientSuite.scala |  1 -
 dev/scalastyle                                |  5 ++--
 .../spark/ml/feature/VectorIndexerSuite.scala |  3 +-
 .../sql/hive/thriftserver/CliSuite.scala      | 15 +++++-----
 .../HiveThriftServer2Suites.scala             |  7 +++--
 .../spark/sql/hive/QueryPartitionSuite.scala  | 30 ++++++++++---------
 .../StreamingJobProgressListenerSuite.scala   |  4 +--
 .../spark/deploy/yarn/ClientSuite.scala       | 19 ++++++++----
 .../deploy/yarn/YarnAllocatorSuite.scala      |  6 ++--
 .../yarn/YarnSparkHadoopUtilSuite.scala       |  2 +-
 10 files changed, 52 insertions(+), 40 deletions(-)

diff --git a/core/src/test/scala/org/apache/spark/deploy/ClientSuite.scala b/core/src/test/scala/org/apache/spark/deploy/ClientSuite.scala
index 518073dcbb64e..745f9eeee7536 100644
--- a/core/src/test/scala/org/apache/spark/deploy/ClientSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/ClientSuite.scala
@@ -46,5 +46,4 @@ class ClientSuite extends FunSuite with Matchers {
     // Invalid syntax.
     ClientArguments.isValidJarUrl("hdfs:") should be (false)
   }
-
 }
diff --git a/dev/scalastyle b/dev/scalastyle
index 86919227ed1ab..4e03f89ed5d5d 100755
--- a/dev/scalastyle
+++ b/dev/scalastyle
@@ -18,9 +18,10 @@
 #
 
 echo -e "q\n" | build/sbt -Phive -Phive-thriftserver scalastyle > scalastyle.txt
+echo -e "q\n" | build/sbt -Phive -Phive-thriftserver test:scalastyle >> scalastyle.txt
 # Check style with YARN built too
-echo -e "q\n" | build/sbt -Pyarn -Phadoop-2.2 -Dhadoop.version=2.2.0 scalastyle \
-  >> scalastyle.txt
+echo -e "q\n" | build/sbt -Pyarn -Phadoop-2.2 -Dhadoop.version=2.2.0 scalastyle >> scalastyle.txt
+echo -e "q\n" | build/sbt -Pyarn -Phadoop-2.2 -Dhadoop.version=2.2.0 test:scalastyle >> scalastyle.txt
 
 ERRORS=$(cat scalastyle.txt | awk '{if($1~/error/)print}')
 rm scalastyle.txt
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala
index 61c46c85a78b5..81ef831c42e55 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala
@@ -150,7 +150,8 @@ class VectorIndexerSuite extends FunSuite with MLlibTestSparkContext {
         val vectorIndexer = getIndexer.setMaxCategories(maxCategories)
         val model = vectorIndexer.fit(data)
         val categoryMaps = model.categoryMaps
-        assert(categoryMaps.keys.toSet === categoricalFeatures) // Chose correct categorical features
+        // Chose correct categorical features
+        assert(categoryMaps.keys.toSet === categoricalFeatures)
         val transformed = model.transform(data).select("indexed")
         val indexedRDD: RDD[Vector] = transformed.map(_.getAs[Vector](0))
         val featureAttrs = AttributeGroup.fromStructField(transformed.schema("indexed"))
diff --git a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/CliSuite.scala b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/CliSuite.scala
index 75738fa22b572..6d1d7c3a4e698 100644
--- a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/CliSuite.scala
+++ b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/CliSuite.scala
@@ -1,13 +1,12 @@
 /*
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements.  See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership.  The ASF licenses this file
- * to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance
- * with the License.  You may obtain a copy of the License at
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
  *
- *     http://www.apache.org/licenses/LICENSE-2.0
+ *    http://www.apache.org/licenses/LICENSE-2.0
  *
  * Unless required by applicable law or agreed to in writing, software
  * distributed under the License is distributed on an "AS IS" BASIS,
diff --git a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala
index bf20acecb1f32..4cf95e7bdfb2b 100644
--- a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala
+++ b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala
@@ -18,6 +18,7 @@
 package org.apache.spark.sql.hive.thriftserver
 
 import java.io.File
+import java.net.URL
 import java.sql.{Date, DriverManager, Statement}
 
 import scala.collection.mutable.ArrayBuffer
@@ -41,7 +42,7 @@ import org.apache.spark.sql.hive.HiveShim
 import org.apache.spark.util.Utils
 
 object TestData {
-  def getTestDataFilePath(name: String) = {
+  def getTestDataFilePath(name: String): URL = {
     Thread.currentThread().getContextClassLoader.getResource(s"data/files/$name")
   }
 
@@ -50,7 +51,7 @@ object TestData {
 }
 
 class HiveThriftBinaryServerSuite extends HiveThriftJdbcTest {
-  override def mode = ServerMode.binary
+  override def mode: ServerMode.Value = ServerMode.binary
 
   private def withCLIServiceClient(f: ThriftCLIServiceClient => Unit): Unit = {
     // Transport creation logics below mimics HiveConnection.createBinaryTransport
@@ -337,7 +338,7 @@ class HiveThriftBinaryServerSuite extends HiveThriftJdbcTest {
 }
 
 class HiveThriftHttpServerSuite extends HiveThriftJdbcTest {
-  override def mode = ServerMode.http
+  override def mode: ServerMode.Value = ServerMode.http
 
   test("JDBC query execution") {
     withJdbcStatement { statement =>
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/QueryPartitionSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/QueryPartitionSuite.scala
index 83f97128c5e83..a787fa5546e76 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/QueryPartitionSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/QueryPartitionSuite.scala
@@ -17,15 +17,12 @@
 
 package org.apache.spark.sql.hive
 
-import java.io.File
-
 import com.google.common.io.Files
+
 import org.apache.spark.sql.{QueryTest, _}
 import org.apache.spark.sql.hive.test.TestHive
-import org.apache.spark.util.Utils
-/* Implicits */
 import org.apache.spark.sql.hive.test.TestHive._
-
+import org.apache.spark.util.Utils
 
 
 class QueryPartitionSuite extends QueryTest {
@@ -37,23 +34,28 @@ class QueryPartitionSuite extends QueryTest {
     testData.registerTempTable("testData")
 
     val tmpDir = Files.createTempDir()
-    //create the table for test
-    sql(s"CREATE TABLE table_with_partition(key int,value string) PARTITIONED by (ds string) location '${tmpDir.toURI.toString}' ")
-    sql("INSERT OVERWRITE TABLE table_with_partition  partition (ds='1') SELECT key,value FROM testData")
-    sql("INSERT OVERWRITE TABLE table_with_partition  partition (ds='2') SELECT key,value FROM testData")
-    sql("INSERT OVERWRITE TABLE table_with_partition  partition (ds='3') SELECT key,value FROM testData")
-    sql("INSERT OVERWRITE TABLE table_with_partition  partition (ds='4') SELECT key,value FROM testData")
+    // create the table for test
+    sql(s"CREATE TABLE table_with_partition(key int,value string) " +
+      s"PARTITIONED by (ds string) location '${tmpDir.toURI.toString}' ")
+    sql("INSERT OVERWRITE TABLE table_with_partition  partition (ds='1') " +
+      "SELECT key,value FROM testData")
+    sql("INSERT OVERWRITE TABLE table_with_partition  partition (ds='2') " +
+      "SELECT key,value FROM testData")
+    sql("INSERT OVERWRITE TABLE table_with_partition  partition (ds='3') " +
+      "SELECT key,value FROM testData")
+    sql("INSERT OVERWRITE TABLE table_with_partition  partition (ds='4') " +
+      "SELECT key,value FROM testData")
 
-    //test for the exist path
+    // test for the exist path
     checkAnswer(sql("select key,value from table_with_partition"),
       testData.toSchemaRDD.collect ++ testData.toSchemaRDD.collect
         ++ testData.toSchemaRDD.collect ++ testData.toSchemaRDD.collect)
 
-    //delect the path of one partition
+    // delete the path of one partition
     val folders = tmpDir.listFiles.filter(_.isDirectory)
     Utils.deleteRecursively(folders(0))
 
-    //test for affter delete the path
+    // test for after delete the path
     checkAnswer(sql("select key,value from table_with_partition"),
       testData.toSchemaRDD.collect ++ testData.toSchemaRDD.collect
         ++ testData.toSchemaRDD.collect)
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ui/StreamingJobProgressListenerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ui/StreamingJobProgressListenerSuite.scala
index 2b9d164500b72..94b1985116feb 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/ui/StreamingJobProgressListenerSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/ui/StreamingJobProgressListenerSuite.scala
@@ -21,14 +21,14 @@ import org.scalatest.Matchers
 
 import org.apache.spark.streaming.dstream.DStream
 import org.apache.spark.streaming.scheduler._
-import org.apache.spark.streaming.{Time, Milliseconds, TestSuiteBase}
+import org.apache.spark.streaming.{Duration, Time, Milliseconds, TestSuiteBase}
 
 class StreamingJobProgressListenerSuite extends TestSuiteBase with Matchers {
 
   val input = (1 to 4).map(Seq(_)).toSeq
   val operation = (d: DStream[Int]) => d.map(x => x)
 
-  override def batchDuration = Milliseconds(100)
+  override def batchDuration: Duration = Milliseconds(100)
 
   test("onBatchSubmitted, onBatchStarted, onBatchCompleted, " +
     "onReceiverStarted, onReceiverError, onReceiverStopped") {
diff --git a/yarn/src/test/scala/org/apache/spark/deploy/yarn/ClientSuite.scala b/yarn/src/test/scala/org/apache/spark/deploy/yarn/ClientSuite.scala
index 92f04b4b859b3..c1b94ac9c5bdd 100644
--- a/yarn/src/test/scala/org/apache/spark/deploy/yarn/ClientSuite.scala
+++ b/yarn/src/test/scala/org/apache/spark/deploy/yarn/ClientSuite.scala
@@ -232,19 +232,26 @@ class ClientSuite extends FunSuite with Matchers with BeforeAndAfterAll {
     testCode(conf)
   }
 
-  def newEnv = MutableHashMap[String, String]()
+  def newEnv: MutableHashMap[String, String] = MutableHashMap[String, String]()
 
-  def classpath(env: MutableHashMap[String, String]) = env(Environment.CLASSPATH.name).split(":|;|<CPS>")
+  def classpath(env: MutableHashMap[String, String]): Array[String] =
+    env(Environment.CLASSPATH.name).split(":|;|<CPS>")
 
-  def flatten(a: Option[Seq[String]], b: Option[Seq[String]]) = (a ++ b).flatten.toArray
+  def flatten(a: Option[Seq[String]], b: Option[Seq[String]]): Array[String] =
+    (a ++ b).flatten.toArray
 
-  def getFieldValue[A, B](clazz: Class[_], field: String, defaults: => B)(mapTo: A => B): B =
-    Try(clazz.getField(field)).map(_.get(null).asInstanceOf[A]).toOption.map(mapTo).getOrElse(defaults)
+  def getFieldValue[A, B](clazz: Class[_], field: String, defaults: => B)(mapTo: A => B): B = {
+    Try(clazz.getField(field))
+      .map(_.get(null).asInstanceOf[A])
+      .toOption
+      .map(mapTo)
+      .getOrElse(defaults)
+  }
 
   def getFieldValue2[A: ClassTag, A1: ClassTag, B](
         clazz: Class[_],
         field: String,
-        defaults: => B)(mapTo:  A => B)(mapTo1: A1 => B) : B = {
+        defaults: => B)(mapTo:  A => B)(mapTo1: A1 => B): B = {
     Try(clazz.getField(field)).map(_.get(null)).map {
       case v: A => mapTo(v)
       case v1: A1 => mapTo1(v1)
diff --git a/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnAllocatorSuite.scala b/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnAllocatorSuite.scala
index c09b01bafce37..455f1019d86dd 100644
--- a/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnAllocatorSuite.scala
+++ b/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnAllocatorSuite.scala
@@ -79,7 +79,7 @@ class YarnAllocatorSuite extends FunSuite with Matchers with BeforeAndAfterEach
   }
 
   class MockSplitInfo(host: String) extends SplitInfo(null, host, null, 1, null) {
-    override def equals(other: Any) = false
+    override def equals(other: Any): Boolean = false
   }
 
   def createAllocator(maxExecutors: Int = 5): YarnAllocator = {
@@ -118,7 +118,9 @@ class YarnAllocatorSuite extends FunSuite with Matchers with BeforeAndAfterEach
     handler.getNumExecutorsRunning should be (1)
     handler.allocatedContainerToHostMap.get(container.getId).get should be ("host1")
     handler.allocatedHostToContainersMap.get("host1").get should contain (container.getId)
-    rmClient.getMatchingRequests(container.getPriority, "host1", containerResource).size should be (0)
+
+    val size = rmClient.getMatchingRequests(container.getPriority, "host1", containerResource).size
+    size should be (0)
   }
 
   test("some containers allocated") {
diff --git a/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtilSuite.scala b/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtilSuite.scala
index 4194f36499e66..9395316b71ff4 100644
--- a/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtilSuite.scala
+++ b/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtilSuite.scala
@@ -46,7 +46,7 @@ class YarnSparkHadoopUtilSuite extends FunSuite with Matchers with Logging {
     logWarning("Cannot execute bash, skipping bash tests.")
   }
 
-  def bashTest(name: String)(fn: => Unit) =
+  def bashTest(name: String)(fn: => Unit): Unit =
     if (hasBash) test(name)(fn) else ignore(name)(fn)
 
   bashTest("shell script escaping") {

From 6cc5b3ed3c0c729f97956fa017d8eb7d6b43f90f Mon Sep 17 00:00:00 2001
From: Cheolsoo Park <cheolsoop@netflix.com>
Date: Mon, 13 Apr 2015 13:45:10 -0500
Subject: [PATCH 79/95] [SPARK-6662][YARN] Allow variable substitution in
 spark.yarn.historyServer.address

In Spark on YARN, explicit hostname and port number need to be set for "spark.yarn.historyServer.address" in SparkConf to make the HISTORY link. If the history server address is known and static, this is usually not a problem.

But in cloud, that is usually not true. Particularly in EMR, the history server always runs on the same node as with RM. So I could simply set it to ${yarn.resourcemanager.hostname}:18080 if variable substitution is allowed.

In fact, Hadoop configuration already implements variable substitution, so if this property is read via YarnConf, this can be easily achievable.

Author: Cheolsoo Park <cheolsoop@netflix.com>

Closes #5321 from piaozhexiu/SPARK-6662 and squashes the following commits:

e37de75 [Cheolsoo Park] Preserve the space between the Hadoop and Spark imports
79757c6 [Cheolsoo Park] Incorporate review comments
10e2917 [Cheolsoo Park] Add helper function that substitutes hadoop vars to SparkHadoopUtil
589b52c [Cheolsoo Park] Revert "Allow variable substitution for spark.yarn. properties"
ff9c35d [Cheolsoo Park] Allow variable substitution for spark.yarn. properties
---
 .../apache/spark/deploy/SparkHadoopUtil.scala | 38 +++++++++++++++++--
 docs/running-on-yarn.md                       |  3 +-
 .../spark/deploy/yarn/ApplicationMaster.scala |  1 +
 3 files changed, 37 insertions(+), 5 deletions(-)

diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala
index c2568eb4b60ac..cfaebf9ea5050 100644
--- a/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala
+++ b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala
@@ -24,11 +24,10 @@ import org.apache.hadoop.conf.Configuration
 import org.apache.hadoop.fs.{FileStatus, FileSystem, Path}
 import org.apache.hadoop.fs.FileSystem.Statistics
 import org.apache.hadoop.mapred.JobConf
-import org.apache.hadoop.mapreduce.{JobContext, TaskAttemptContext}
-import org.apache.hadoop.security.Credentials
-import org.apache.hadoop.security.UserGroupInformation
+import org.apache.hadoop.mapreduce.JobContext
+import org.apache.hadoop.security.{Credentials, UserGroupInformation}
 
-import org.apache.spark.{Logging, SparkContext, SparkConf, SparkException}
+import org.apache.spark.{Logging, SparkConf, SparkException}
 import org.apache.spark.annotation.DeveloperApi
 import org.apache.spark.util.Utils
 
@@ -201,6 +200,37 @@ class SparkHadoopUtil extends Logging {
     val baseStatus = fs.getFileStatus(basePath)
     if (baseStatus.isDir) recurse(basePath) else Array(baseStatus)
   }
+
+  private val HADOOP_CONF_PATTERN = "(\\$\\{hadoopconf-[^\\}\\$\\s]+\\})".r.unanchored
+
+  /**
+   * Substitute variables by looking them up in Hadoop configs. Only variables that match the
+   * ${hadoopconf- .. } pattern are substituted.
+   */
+  def substituteHadoopVariables(text: String, hadoopConf: Configuration): String = {
+    text match {
+      case HADOOP_CONF_PATTERN(matched) => {
+        logDebug(text + " matched " + HADOOP_CONF_PATTERN)
+        val key = matched.substring(13, matched.length() - 1) // remove ${hadoopconf- .. }
+        val eval = Option[String](hadoopConf.get(key))
+          .map { value =>
+            logDebug("Substituted " + matched + " with " + value)
+            text.replace(matched, value)
+          }
+        if (eval.isEmpty) {
+          // The variable was not found in Hadoop configs, so return text as is.
+          text
+        } else {
+          // Continue to substitute more variables.
+          substituteHadoopVariables(eval.get, hadoopConf)
+        }
+      }
+      case _ => {
+        logDebug(text + " didn't match " + HADOOP_CONF_PATTERN)
+        text
+      }
+    }
+  }
 }
 
 object SparkHadoopUtil {
diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md
index b7e68d4f71714..ed5bb263a5809 100644
--- a/docs/running-on-yarn.md
+++ b/docs/running-on-yarn.md
@@ -87,7 +87,8 @@ Most of the configs are the same for Spark on YARN as for other deployment modes
   <td><code>spark.yarn.historyServer.address</code></td>
   <td>(none)</td>
   <td>
-    The address of the Spark history server (i.e. host.com:18080). The address should not contain a scheme (http://). Defaults to not being set since the history server is an optional service. This address is given to the YARN ResourceManager when the Spark application finishes to link the application from the ResourceManager UI to the Spark history server UI.
+    The address of the Spark history server (i.e. host.com:18080). The address should not contain a scheme (http://). Defaults to not being set since the history server is an optional service. This address is given to the YARN ResourceManager when the Spark application finishes to link the application from the ResourceManager UI to the Spark history server UI. 
+    For this property, YARN properties can be used as variables, and these are substituted by Spark at runtime. For eg, if the Spark history server runs on the same node as the YARN ResourceManager, it can be set to `${hadoopconf-yarn.resourcemanager.hostname}:18080`. 
   </td>
 </tr>
 <tr>
diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
index 32bc4e5663062..26259cee77151 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
@@ -223,6 +223,7 @@ private[spark] class ApplicationMaster(
     val appId = client.getAttemptId().getApplicationId().toString()
     val historyAddress =
       sparkConf.getOption("spark.yarn.historyServer.address")
+        .map { text => SparkHadoopUtil.get.substituteHadoopVariables(text, yarnConf) }
         .map { address => s"${address}${HistoryServer.UI_PATH_PREFIX}/${appId}" }
         .getOrElse("")
 

From 1e340c3ae4d5361d048a3d6990f144cfc923666f Mon Sep 17 00:00:00 2001
From: Xusen Yin <yinxusen@gmail.com>
Date: Mon, 13 Apr 2015 11:53:17 -0700
Subject: [PATCH 80/95] [SPARK-5988][MLlib] add save/load for
 PowerIterationClusteringModel

See JIRA issue [SPARK-5988](https://issues.apache.org/jira/browse/SPARK-5988).

Author: Xusen Yin <yinxusen@gmail.com>

Closes #5450 from yinxusen/SPARK-5988 and squashes the following commits:

cb1ecfa [Xusen Yin] change Assignment into case class
b1dd24c [Xusen Yin] add test suite
63c3923 [Xusen Yin] add save load for power iteration clustering
---
 .../clustering/PowerIterationClustering.scala | 68 +++++++++++++++++--
 .../PowerIterationClusteringSuite.scala       | 34 ++++++++++
 2 files changed, 97 insertions(+), 5 deletions(-)

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
index 180023922a9b0..aa53e88d59856 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
@@ -17,15 +17,20 @@
 
 package org.apache.spark.mllib.clustering
 
-import org.apache.spark.{Logging, SparkException}
+import org.json4s.JsonDSL._
+import org.json4s._
+import org.json4s.jackson.JsonMethods._
+
 import org.apache.spark.annotation.Experimental
 import org.apache.spark.api.java.JavaRDD
 import org.apache.spark.graphx._
 import org.apache.spark.graphx.impl.GraphImpl
 import org.apache.spark.mllib.linalg.Vectors
-import org.apache.spark.mllib.util.MLUtils
+import org.apache.spark.mllib.util.{Loader, MLUtils, Saveable}
 import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.{Row, SQLContext}
 import org.apache.spark.util.random.XORShiftRandom
+import org.apache.spark.{Logging, SparkContext, SparkException}
 
 /**
  * :: Experimental ::
@@ -38,7 +43,60 @@ import org.apache.spark.util.random.XORShiftRandom
 @Experimental
 class PowerIterationClusteringModel(
     val k: Int,
-    val assignments: RDD[PowerIterationClustering.Assignment]) extends Serializable
+    val assignments: RDD[PowerIterationClustering.Assignment]) extends Saveable with Serializable {
+
+  override def save(sc: SparkContext, path: String): Unit = {
+    PowerIterationClusteringModel.SaveLoadV1_0.save(sc, this, path)
+  }
+
+  override protected def formatVersion: String = "1.0"
+}
+
+object PowerIterationClusteringModel extends Loader[PowerIterationClusteringModel] {
+  override def load(sc: SparkContext, path: String): PowerIterationClusteringModel = {
+    PowerIterationClusteringModel.SaveLoadV1_0.load(sc, path)
+  }
+
+  private[clustering]
+  object SaveLoadV1_0 {
+
+    private val thisFormatVersion = "1.0"
+
+    private[clustering]
+    val thisClassName = "org.apache.spark.mllib.clustering.PowerIterationClusteringModel"
+
+    def save(sc: SparkContext, model: PowerIterationClusteringModel, path: String): Unit = {
+      val sqlContext = new SQLContext(sc)
+      import sqlContext.implicits._
+
+      val metadata = compact(render(
+        ("class" -> thisClassName) ~ ("version" -> thisFormatVersion) ~ ("k" -> model.k)))
+      sc.parallelize(Seq(metadata), 1).saveAsTextFile(Loader.metadataPath(path))
+
+      val dataRDD = model.assignments.toDF()
+      dataRDD.saveAsParquetFile(Loader.dataPath(path))
+    }
+
+    def load(sc: SparkContext, path: String): PowerIterationClusteringModel = {
+      implicit val formats = DefaultFormats
+      val sqlContext = new SQLContext(sc)
+
+      val (className, formatVersion, metadata) = Loader.loadMetadata(sc, path)
+      assert(className == thisClassName)
+      assert(formatVersion == thisFormatVersion)
+
+      val k = (metadata \ "k").extract[Int]
+      val assignments = sqlContext.parquetFile(Loader.dataPath(path))
+      Loader.checkSchema[PowerIterationClustering.Assignment](assignments.schema)
+
+      val assignmentsRDD = assignments.map {
+        case Row(id: Long, cluster: Int) => PowerIterationClustering.Assignment(id, cluster)
+      }
+
+      new PowerIterationClusteringModel(k, assignmentsRDD)
+    }
+  }
+}
 
 /**
  * :: Experimental ::
@@ -135,7 +193,7 @@ class PowerIterationClustering private[clustering] (
     val v = powerIter(w, maxIterations)
     val assignments = kMeans(v, k).mapPartitions({ iter =>
       iter.map { case (id, cluster) =>
-        new Assignment(id, cluster)
+        Assignment(id, cluster)
       }
     }, preservesPartitioning = true)
     new PowerIterationClusteringModel(k, assignments)
@@ -152,7 +210,7 @@ object PowerIterationClustering extends Logging {
    * @param cluster assigned cluster id
    */
   @Experimental
-  class Assignment(val id: Long, val cluster: Int) extends Serializable
+  case class Assignment(id: Long, cluster: Int)
 
   /**
    * Normalizes the affinity matrix (A) by row sums and returns the normalized affinity matrix (W).
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/clustering/PowerIterationClusteringSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/clustering/PowerIterationClusteringSuite.scala
index 6315c03a700f1..6d6fe6fe46bab 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/clustering/PowerIterationClusteringSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/clustering/PowerIterationClusteringSuite.scala
@@ -18,12 +18,15 @@
 package org.apache.spark.mllib.clustering
 
 import scala.collection.mutable
+import scala.util.Random
 
 import org.scalatest.FunSuite
 
+import org.apache.spark.SparkContext
 import org.apache.spark.graphx.{Edge, Graph}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.mllib.util.TestingUtils._
+import org.apache.spark.util.Utils
 
 class PowerIterationClusteringSuite extends FunSuite with MLlibTestSparkContext {
 
@@ -110,4 +113,35 @@ class PowerIterationClusteringSuite extends FunSuite with MLlibTestSparkContext
       assert(x ~== u1(i.toInt) absTol 1e-14)
     }
   }
+
+  test("model save/load") {
+    val tempDir = Utils.createTempDir()
+    val path = tempDir.toURI.toString
+    val model = PowerIterationClusteringSuite.createModel(sc, 3, 10)
+    try {
+      model.save(sc, path)
+      val sameModel = PowerIterationClusteringModel.load(sc, path)
+      PowerIterationClusteringSuite.checkEqual(model, sameModel)
+    } finally {
+      Utils.deleteRecursively(tempDir)
+    }
+  }
+}
+
+object PowerIterationClusteringSuite extends FunSuite {
+  def createModel(sc: SparkContext, k: Int, nPoints: Int): PowerIterationClusteringModel = {
+    val assignments = sc.parallelize(
+      (0 until nPoints).map(p => PowerIterationClustering.Assignment(p, Random.nextInt(k))))
+    new PowerIterationClusteringModel(k, assignments)
+  }
+
+  def checkEqual(a: PowerIterationClusteringModel, b: PowerIterationClusteringModel): Unit = {
+    assert(a.k === b.k)
+
+    val aAssignments = a.assignments.map(x => (x.id, x.cluster))
+    val bAssignments = b.assignments.map(x => (x.id, x.cluster))
+    val unequalElements = aAssignments.join(bAssignments).filter {
+      case (id, (c1, c2)) => c1 != c2 }.count()
+    assert(unequalElements === 0L)
+  }
 }

From 85ee0cabe87a27b6947c2d3e8525f04c77f80f6f Mon Sep 17 00:00:00 2001
From: Daoyuan Wang <daoyuan.wang@intel.com>
Date: Mon, 13 Apr 2015 14:29:07 -0700
Subject: [PATCH 81/95] [SPARK-6130] [SQL] support if not exists for insert
 overwrite into partition in hiveQl
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Standard syntax:
INSERT OVERWRITE TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...) [IF NOT EXISTS]] select_statement1 FROM from_statement;
INSERT INTO TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...)] select_statement1 FROM from_statement;
 
Hive extension (multiple inserts):
FROM from_statement
INSERT OVERWRITE TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...) [IF NOT EXISTS]] select_statement1
[INSERT OVERWRITE TABLE tablename2 [PARTITION ... [IF NOT EXISTS]] select_statement2]
[INSERT INTO TABLE tablename2 [PARTITION ...] select_statement2] ...;
FROM from_statement
INSERT INTO TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...)] select_statement1
[INSERT INTO TABLE tablename2 [PARTITION ...] select_statement2]
[INSERT OVERWRITE TABLE tablename2 [PARTITION ... [IF NOT EXISTS]] select_statement2] ...;
 
Hive extension (dynamic partition inserts):
INSERT OVERWRITE TABLE tablename PARTITION (partcol1[=val1], partcol2[=val2] ...) select_statement FROM from_statement;
INSERT INTO TABLE tablename PARTITION (partcol1[=val1], partcol2[=val2] ...) select_statement FROM from_statement;

Author: Daoyuan Wang <daoyuan.wang@intel.com>

Closes #4865 from adrian-wang/insertoverwrite and squashes the following commits:

2fce94f [Daoyuan Wang] add assert
10ea6f3 [Daoyuan Wang] add name for boolean parameter
0bbe9b9 [Daoyuan Wang] fix failure
4391154 [Daoyuan Wang] support if not exists for insert overwrite into partition in hiveQl
---
 .../apache/spark/sql/catalyst/SqlParser.scala |  2 +-
 .../sql/catalyst/analysis/Analyzer.scala      |  2 +-
 .../spark/sql/catalyst/dsl/package.scala      |  2 +-
 .../plans/logical/basicOperators.scala        |  4 ++-
 .../org/apache/spark/sql/DataFrame.scala      |  2 +-
 .../spark/sql/execution/SparkStrategies.scala |  3 +-
 .../sql/sources/DataSourceStrategy.scala      |  2 +-
 .../org/apache/spark/sql/sources/rules.scala  |  7 +++--
 .../execution/HiveCompatibilitySuite.scala    |  1 +
 .../spark/sql/hive/HiveMetastoreCatalog.scala | 19 ++++++------
 .../org/apache/spark/sql/hive/HiveQl.scala    | 22 ++++++++++++-
 .../spark/sql/hive/HiveStrategies.scala       | 10 +++---
 .../hive/execution/CreateTableAsSelect.scala  |  2 +-
 .../hive/execution/InsertIntoHiveTable.scala  | 31 +++++++++++++------
 ...titions-0-d5edc0daa94b33915df794df3b710774 |  0
 ...titions-1-9eb9372f4855928fae16f5fa554b3a62 |  0
 ...itions-10-ec2cef3d37146c450c60202a572f5cab |  0
 ...itions-11-8854d6001200fc11529b2e2da755e5a2 |  0
 ...itions-12-71ff68fda0aa7a36cb50d8fab0d70d25 |  0
 ...titions-13-7e4e7d7003fc6ef17bc19c3461ad899 |  0
 ...itions-14-ec2cef3d37146c450c60202a572f5cab |  0
 ...itions-15-a3b2e230efde74e970ae8a3b55f383fc |  0
 ...titions-2-8396c17a66e3d9a374d4361873b9bfe3 |  0
 ...titions-3-3876bb356dd8af7e78d061093d555457 |  0
 ...rtitions-4-528e23afb272c2e69004c86ddaa70ee |  0
 ...titions-5-de5d56456c28d63775554e56355911d2 |  0
 ...titions-6-3efdc331b3b4bdac3e60c757600fff53 |  5 +++
 ...titions-7-92f6af82704504968de078c133f222f8 |  0
 ...titions-8-316cad7c63ddd4fb043be2affa5b0a67 |  0
 ...titions-9-3efdc331b3b4bdac3e60c757600fff53 |  5 +++
 30 files changed, 84 insertions(+), 35 deletions(-)
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-0-d5edc0daa94b33915df794df3b710774
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-1-9eb9372f4855928fae16f5fa554b3a62
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-10-ec2cef3d37146c450c60202a572f5cab
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-11-8854d6001200fc11529b2e2da755e5a2
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-12-71ff68fda0aa7a36cb50d8fab0d70d25
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-13-7e4e7d7003fc6ef17bc19c3461ad899
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-14-ec2cef3d37146c450c60202a572f5cab
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-15-a3b2e230efde74e970ae8a3b55f383fc
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-2-8396c17a66e3d9a374d4361873b9bfe3
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-3-3876bb356dd8af7e78d061093d555457
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-4-528e23afb272c2e69004c86ddaa70ee
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-5-de5d56456c28d63775554e56355911d2
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-6-3efdc331b3b4bdac3e60c757600fff53
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-7-92f6af82704504968de078c133f222f8
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-8-316cad7c63ddd4fb043be2affa5b0a67
 create mode 100644 sql/hive/src/test/resources/golden/insert1_overwrite_partitions-9-3efdc331b3b4bdac3e60c757600fff53

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala
index ee04cb579deb6..bc8d3751f6616 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala
@@ -155,7 +155,7 @@ class SqlParser extends AbstractSparkSQLParser with DataTypeParser {
 
   protected lazy val insert: Parser[LogicalPlan] =
     INSERT ~> (OVERWRITE ^^^ true | INTO ^^^ false) ~ (TABLE ~> relation) ~ select ^^ {
-      case o ~ r ~ s => InsertIntoTable(r, Map.empty[String, Option[String]], s, o)
+      case o ~ r ~ s => InsertIntoTable(r, Map.empty[String, Option[String]], s, o, false)
     }
 
   protected lazy val cte: Parser[LogicalPlan] =
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
index 50702ac6832ec..8b68b0df35f48 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
@@ -193,7 +193,7 @@ class Analyzer(
       }
 
       realPlan transform {
-        case i@InsertIntoTable(u: UnresolvedRelation, _, _, _) =>
+        case i@InsertIntoTable(u: UnresolvedRelation, _, _, _, _) =>
           i.copy(
             table = EliminateSubQueries(getTable(u, cteRelations)))
         case u: UnresolvedRelation =>
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala
index 145f062dd6817..21c15ad14fd19 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala
@@ -293,7 +293,7 @@ package object dsl {
 
     def insertInto(tableName: String, overwrite: Boolean = false): LogicalPlan =
       InsertIntoTable(
-        analysis.UnresolvedRelation(Seq(tableName)), Map.empty, logicalPlan, overwrite)
+        analysis.UnresolvedRelation(Seq(tableName)), Map.empty, logicalPlan, overwrite, false)
 
     def analyze: LogicalPlan = EliminateSubQueries(analysis.SimpleAnalyzer(logicalPlan))
   }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala
index 5d31a6eecfce2..17522976dc2c9 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala
@@ -125,12 +125,14 @@ case class InsertIntoTable(
     table: LogicalPlan,
     partition: Map[String, Option[String]],
     child: LogicalPlan,
-    overwrite: Boolean)
+    overwrite: Boolean,
+    ifNotExists: Boolean)
   extends LogicalPlan {
 
   override def children: Seq[LogicalPlan] = child :: Nil
   override def output: Seq[Attribute] = child.output
 
+  assert(overwrite || !ifNotExists)
   override lazy val resolved: Boolean = childrenResolved && child.output.zip(table.output).forall {
     case (childAttr, tableAttr) =>
       DataType.equalsIgnoreCompatibleNullability(childAttr.dataType, tableAttr.dataType)
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
index 9b9adf855077a..94ae2d65fd0e4 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
@@ -1209,7 +1209,7 @@ class DataFrame private[sql](
   @Experimental
   def insertInto(tableName: String, overwrite: Boolean): Unit = {
     sqlContext.executePlan(InsertIntoTable(UnresolvedRelation(Seq(tableName)),
-      Map.empty, logicalPlan, overwrite)).toRdd
+      Map.empty, logicalPlan, overwrite, ifNotExists = false)).toRdd
   }
 
   /**
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
index 23f7e5609414b..5268b7334051a 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
@@ -211,7 +211,8 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
           ParquetRelation.create(path, child, sparkContext.hadoopConfiguration, sqlContext)
         // Note: overwrite=false because otherwise the metadata we just created will be deleted
         InsertIntoParquetTable(relation, planLater(child), overwrite = false) :: Nil
-      case logical.InsertIntoTable(table: ParquetRelation, partition, child, overwrite) =>
+      case logical.InsertIntoTable(
+          table: ParquetRelation, partition, child, overwrite, ifNotExists) =>
         InsertIntoParquetTable(table, planLater(child), overwrite) :: Nil
       case PhysicalOperation(projectList, filters: Seq[Expression], relation: ParquetRelation) =>
         val prunePushedDownFilters =
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/DataSourceStrategy.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/DataSourceStrategy.scala
index e13759b7feb7b..34d048e426d10 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/sources/DataSourceStrategy.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/DataSourceStrategy.scala
@@ -56,7 +56,7 @@ private[sql] object DataSourceStrategy extends Strategy {
       execution.PhysicalRDD(l.output, t.buildScan()) :: Nil
 
     case i @ logical.InsertIntoTable(
-      l @ LogicalRelation(t: InsertableRelation), part, query, overwrite) if part.isEmpty =>
+      l @ LogicalRelation(t: InsertableRelation), part, query, overwrite, false) if part.isEmpty =>
       execution.ExecutedCommand(InsertIntoDataSource(l, query, overwrite)) :: Nil
 
     case _ => Nil
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/rules.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/rules.scala
index 5a78001117d1b..6ed68d179edc9 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/sources/rules.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/rules.scala
@@ -37,7 +37,7 @@ private[sql] object PreInsertCastAndRename extends Rule[LogicalPlan] {
 
       // We are inserting into an InsertableRelation.
       case i @ InsertIntoTable(
-      l @ LogicalRelation(r: InsertableRelation), partition, child, overwrite) => {
+      l @ LogicalRelation(r: InsertableRelation), partition, child, overwrite, ifNotExists) => {
         // First, make sure the data to be inserted have the same number of fields with the
         // schema of the relation.
         if (l.output.size != child.output.size) {
@@ -84,7 +84,7 @@ private[sql] case class PreWriteCheck(catalog: Catalog) extends (LogicalPlan =>
   def apply(plan: LogicalPlan): Unit = {
     plan.foreach {
       case i @ logical.InsertIntoTable(
-        l @ LogicalRelation(t: InsertableRelation), partition, query, overwrite) =>
+        l @ LogicalRelation(t: InsertableRelation), partition, query, overwrite, ifNotExists) =>
         // Right now, we do not support insert into a data source table with partition specs.
         if (partition.nonEmpty) {
           failAnalysis(s"Insert into a partition is not allowed because $l is not partitioned.")
@@ -102,7 +102,8 @@ private[sql] case class PreWriteCheck(catalog: Catalog) extends (LogicalPlan =>
         }
 
       case i @ logical.InsertIntoTable(
-        l: LogicalRelation, partition, query, overwrite) if !l.isInstanceOf[InsertableRelation] =>
+        l: LogicalRelation, partition, query, overwrite, ifNotExists)
+          if !l.isInstanceOf[InsertableRelation] =>
         // The relation in l is not an InsertableRelation.
         failAnalysis(s"$l does not allow insertion.")
 
diff --git a/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala b/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala
index 2ae9d018e1b1b..81ee48ef4152f 100644
--- a/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala
+++ b/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala
@@ -532,6 +532,7 @@ class HiveCompatibilitySuite extends HiveQueryFileTest with BeforeAndAfter {
     "inputddl7",
     "inputddl8",
     "insert1",
+    "insert1_overwrite_partitions",
     "insert2_overwrite_partitions",
     "insert_compressed",
     "join0",
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala
index 3ed5c5b031736..f1c0bd92aa23d 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala
@@ -527,7 +527,7 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with
       // Collects all `MetastoreRelation`s which should be replaced
       val toBeReplaced = plan.collect {
         // Write path
-        case InsertIntoTable(relation: MetastoreRelation, _, _, _)
+        case InsertIntoTable(relation: MetastoreRelation, _, _, _, _)
             // Inserting into partitioned table is not supported in Parquet data source (yet).
             if !relation.hiveQlTable.isPartitioned &&
               hive.convertMetastoreParquet &&
@@ -538,7 +538,7 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with
           (relation, parquetRelation, attributedRewrites)
 
         // Write path
-        case InsertIntoHiveTable(relation: MetastoreRelation, _, _, _)
+        case InsertIntoHiveTable(relation: MetastoreRelation, _, _, _, _)
           // Inserting into partitioned table is not supported in Parquet data source (yet).
           if !relation.hiveQlTable.isPartitioned &&
             hive.convertMetastoreParquet &&
@@ -569,15 +569,15 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with
           val alias = r.alias.getOrElse(r.tableName)
           Subquery(alias, parquetRelation)
 
-        case InsertIntoTable(r: MetastoreRelation, partition, child, overwrite)
+        case InsertIntoTable(r: MetastoreRelation, partition, child, overwrite, ifNotExists)
           if relationMap.contains(r) =>
           val parquetRelation = relationMap(r)
-          InsertIntoTable(parquetRelation, partition, child, overwrite)
+          InsertIntoTable(parquetRelation, partition, child, overwrite, ifNotExists)
 
-        case InsertIntoHiveTable(r: MetastoreRelation, partition, child, overwrite)
+        case InsertIntoHiveTable(r: MetastoreRelation, partition, child, overwrite, ifNotExists)
           if relationMap.contains(r) =>
           val parquetRelation = relationMap(r)
-          InsertIntoTable(parquetRelation, partition, child, overwrite)
+          InsertIntoTable(parquetRelation, partition, child, overwrite, ifNotExists)
 
         case other => other.transformExpressions {
           case a: Attribute if a.resolved => attributedRewrites.getOrElse(a, a)
@@ -698,7 +698,7 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with
       // Wait until children are resolved.
       case p: LogicalPlan if !p.childrenResolved => p
 
-      case p @ InsertIntoTable(table: MetastoreRelation, _, child, _) =>
+      case p @ InsertIntoTable(table: MetastoreRelation, _, child, _, _) =>
         castChildOutput(p, table, child)
     }
 
@@ -715,7 +715,7 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with
           .forall { case (left, right) => left.sameType(right) }) {
         // If both types ignoring nullability of ArrayType, MapType, StructType are the same,
         // use InsertIntoHiveTable instead of InsertIntoTable.
-        InsertIntoHiveTable(p.table, p.partition, p.child, p.overwrite)
+        InsertIntoHiveTable(p.table, p.partition, p.child, p.overwrite, p.ifNotExists)
       } else {
         // Only do the casting when child output data types differ from table output data types.
         val castedChildOutput = child.output.zip(table.output).map {
@@ -753,7 +753,8 @@ private[hive] case class InsertIntoHiveTable(
     table: LogicalPlan,
     partition: Map[String, Option[String]],
     child: LogicalPlan,
-    overwrite: Boolean)
+    overwrite: Boolean,
+    ifNotExists: Boolean)
   extends LogicalPlan {
 
   override def children: Seq[LogicalPlan] = child :: Nil
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
index b2ae74efeb097..53a204b8c2932 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
@@ -1002,7 +1002,27 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
           cleanIdentifier(key.toLowerCase) -> None
       }.toMap).getOrElse(Map.empty)
 
-      InsertIntoTable(UnresolvedRelation(tableIdent, None), partitionKeys, query, overwrite)
+      InsertIntoTable(UnresolvedRelation(tableIdent, None), partitionKeys, query, overwrite, false)
+
+    case Token(destinationToken(),
+           Token("TOK_TAB",
+             tableArgs) ::
+           Token("TOK_IFNOTEXISTS",
+             ifNotExists) :: Nil) =>
+      val Some(tableNameParts) :: partitionClause :: Nil =
+        getClauses(Seq("TOK_TABNAME", "TOK_PARTSPEC"), tableArgs)
+
+      val tableIdent = extractTableIdent(tableNameParts)
+
+      val partitionKeys = partitionClause.map(_.getChildren.map {
+        // Parse partitions. We also make keys case insensitive.
+        case Token("TOK_PARTVAL", Token(key, Nil) :: Token(value, Nil) :: Nil) =>
+          cleanIdentifier(key.toLowerCase) -> Some(PlanUtils.stripQuotes(value))
+        case Token("TOK_PARTVAL", Token(key, Nil) :: Nil) =>
+          cleanIdentifier(key.toLowerCase) -> None
+      }.toMap).getOrElse(Map.empty)
+
+      InsertIntoTable(UnresolvedRelation(tableIdent, None), partitionKeys, query, overwrite, true)
 
     case a: ASTNode =>
       throw new NotImplementedError(s"No parse rules for:\n ${dumpTree(a).toString} ")
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala
index 5f7e897295117..1ccb0c279c60e 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala
@@ -184,12 +184,14 @@ private[hive] trait HiveStrategies {
 
   object DataSinks extends Strategy {
     def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match {
-      case logical.InsertIntoTable(table: MetastoreRelation, partition, child, overwrite) =>
+      case logical.InsertIntoTable(
+          table: MetastoreRelation, partition, child, overwrite, ifNotExists) =>
         execution.InsertIntoHiveTable(
-          table, partition, planLater(child), overwrite) :: Nil
-      case hive.InsertIntoHiveTable(table: MetastoreRelation, partition, child, overwrite) =>
+          table, partition, planLater(child), overwrite, ifNotExists) :: Nil
+      case hive.InsertIntoHiveTable(
+          table: MetastoreRelation, partition, child, overwrite, ifNotExists) =>
         execution.InsertIntoHiveTable(
-          table, partition, planLater(child), overwrite) :: Nil
+          table, partition, planLater(child), overwrite, ifNotExists) :: Nil
       case _ => Nil
     }
   }
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala
index fade9e5852eaa..76a1965f3cb25 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala
@@ -67,7 +67,7 @@ case class CreateTableAsSelect(
           new org.apache.hadoop.hive.metastore.api.AlreadyExistsException(s"$database.$tableName")
       }
     } else {
-      hiveContext.executePlan(InsertIntoTable(metastoreRelation, Map(), query, true)).toRdd
+      hiveContext.executePlan(InsertIntoTable(metastoreRelation, Map(), query, true, false)).toRdd
     }
 
     Seq.empty[Row]
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala
index 6c96747439683..89995a91b1a92 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala
@@ -45,7 +45,8 @@ case class InsertIntoHiveTable(
     table: MetastoreRelation,
     partition: Map[String, Option[String]],
     child: SparkPlan,
-    overwrite: Boolean) extends UnaryNode with HiveInspectors {
+    overwrite: Boolean,
+    ifNotExists: Boolean) extends UnaryNode with HiveInspectors {
 
   @transient val sc: HiveContext = sqlContext.asInstanceOf[HiveContext]
   @transient lazy val outputClass = newSerializer(table.tableDesc).getSerializedClass
@@ -219,15 +220,25 @@ case class InsertIntoHiveTable(
             isSkewedStoreAsSubdir)
         }
       } else {
-        catalog.synchronized {
-          catalog.client.loadPartition(
-            outputPath,
-            qualifiedTableName,
-            orderedPartitionSpec,
-            overwrite,
-            holdDDLTime,
-            inheritTableSpecs,
-            isSkewedStoreAsSubdir)
+        // scalastyle:off
+        // ifNotExists is only valid with static partition, refer to
+        // https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DML#LanguageManualDML-InsertingdataintoHiveTablesfromqueries
+        // scalastyle:on
+        val oldPart = catalog.synchronized {
+          catalog.client.getPartition(
+            catalog.client.getTable(qualifiedTableName), partitionSpec, false)
+        }
+        if (oldPart == null || !ifNotExists) {
+          catalog.synchronized {
+            catalog.client.loadPartition(
+              outputPath,
+              qualifiedTableName,
+              orderedPartitionSpec,
+              overwrite,
+              holdDDLTime,
+              inheritTableSpecs,
+              isSkewedStoreAsSubdir)
+          }
         }
       }
     } else {
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-0-d5edc0daa94b33915df794df3b710774 b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-0-d5edc0daa94b33915df794df3b710774
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-1-9eb9372f4855928fae16f5fa554b3a62 b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-1-9eb9372f4855928fae16f5fa554b3a62
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-10-ec2cef3d37146c450c60202a572f5cab b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-10-ec2cef3d37146c450c60202a572f5cab
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-11-8854d6001200fc11529b2e2da755e5a2 b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-11-8854d6001200fc11529b2e2da755e5a2
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-12-71ff68fda0aa7a36cb50d8fab0d70d25 b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-12-71ff68fda0aa7a36cb50d8fab0d70d25
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-13-7e4e7d7003fc6ef17bc19c3461ad899 b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-13-7e4e7d7003fc6ef17bc19c3461ad899
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-14-ec2cef3d37146c450c60202a572f5cab b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-14-ec2cef3d37146c450c60202a572f5cab
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-15-a3b2e230efde74e970ae8a3b55f383fc b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-15-a3b2e230efde74e970ae8a3b55f383fc
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-2-8396c17a66e3d9a374d4361873b9bfe3 b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-2-8396c17a66e3d9a374d4361873b9bfe3
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-3-3876bb356dd8af7e78d061093d555457 b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-3-3876bb356dd8af7e78d061093d555457
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-4-528e23afb272c2e69004c86ddaa70ee b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-4-528e23afb272c2e69004c86ddaa70ee
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-5-de5d56456c28d63775554e56355911d2 b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-5-de5d56456c28d63775554e56355911d2
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-6-3efdc331b3b4bdac3e60c757600fff53 b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-6-3efdc331b3b4bdac3e60c757600fff53
new file mode 100644
index 0000000000000..185a91c110d6f
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-6-3efdc331b3b4bdac3e60c757600fff53
@@ -0,0 +1,5 @@
+98	val_98
+98	val_98
+97	val_97
+97	val_97
+96	val_96
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-7-92f6af82704504968de078c133f222f8 b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-7-92f6af82704504968de078c133f222f8
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-8-316cad7c63ddd4fb043be2affa5b0a67 b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-8-316cad7c63ddd4fb043be2affa5b0a67
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-9-3efdc331b3b4bdac3e60c757600fff53 b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-9-3efdc331b3b4bdac3e60c757600fff53
new file mode 100644
index 0000000000000..185a91c110d6f
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/insert1_overwrite_partitions-9-3efdc331b3b4bdac3e60c757600fff53
@@ -0,0 +1,5 @@
+98	val_98
+98	val_98
+97	val_97
+97	val_97
+96	val_96

From 3a205bbd9e352668a020c3146391e1e4441467af Mon Sep 17 00:00:00 2001
From: Yash Datta <Yash.Datta@guavus.com>
Date: Mon, 13 Apr 2015 14:43:07 -0700
Subject: [PATCH 82/95] [SQL][SPARK-6742]: Don't push down predicates which
 reference partition column(s)

cc liancheng

Author: Yash Datta <Yash.Datta@guavus.com>

Closes #5390 from saucam/fpush and squashes the following commits:

3f026d6 [Yash Datta] SPARK-6742: Fix scalastyle
ce3d702 [Yash Datta] SPARK-6742: Add test case, fix scalastyle
8592acc [Yash Datta] SPARK-6742: Don't push down predicates which reference partition column(s)
---
 .../spark/sql/execution/SparkStrategies.scala | 11 ++++++++-
 .../sql/parquet/ParquetFilterSuite.scala      | 24 ++++++++++++++++++-
 2 files changed, 33 insertions(+), 2 deletions(-)

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
index 5268b7334051a..f0d92ffffcda3 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
@@ -215,6 +215,11 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
           table: ParquetRelation, partition, child, overwrite, ifNotExists) =>
         InsertIntoParquetTable(table, planLater(child), overwrite) :: Nil
       case PhysicalOperation(projectList, filters: Seq[Expression], relation: ParquetRelation) =>
+        val partitionColNames = relation.partitioningAttributes.map(_.name).toSet
+        val filtersToPush = filters.filter { pred =>
+            val referencedColNames = pred.references.map(_.name).toSet
+            referencedColNames.intersect(partitionColNames).isEmpty
+          }
         val prunePushedDownFilters =
           if (sqlContext.conf.parquetFilterPushDown) {
             (predicates: Seq[Expression]) => {
@@ -226,6 +231,10 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
               // "A AND B" in the higher-level filter, not just "B".
               predicates.map(p => p -> ParquetFilters.createFilter(p)).collect {
                 case (predicate, None) => predicate
+                // Filter needs to be applied above when it contains partitioning
+                // columns
+                case (predicate, _) if(!predicate.references.map(_.name).toSet
+                  .intersect (partitionColNames).isEmpty) => predicate
               }
             }
           } else {
@@ -238,7 +247,7 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
           ParquetTableScan(
             _,
             relation,
-            if (sqlContext.conf.parquetFilterPushDown) filters else Nil)) :: Nil
+            if (sqlContext.conf.parquetFilterPushDown) filtersToPush else Nil)) :: Nil
 
       case _ => Nil
     }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala
index 6a2c2a7c4080a..10d0ede4dc0dc 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala
@@ -22,7 +22,7 @@ import parquet.filter2.predicate.Operators._
 import parquet.filter2.predicate.{FilterPredicate, Operators}
 
 import org.apache.spark.sql.catalyst.dsl.expressions._
-import org.apache.spark.sql.catalyst.expressions.{Attribute, Cast, Literal, Predicate, Row}
+import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.planning.PhysicalOperation
 import org.apache.spark.sql.sources.LogicalRelation
 import org.apache.spark.sql.test.TestSQLContext
@@ -350,4 +350,26 @@ class ParquetDataSourceOffFilterSuite extends ParquetFilterSuiteBase with Before
   override protected def afterAll(): Unit = {
     sqlContext.setConf(SQLConf.PARQUET_USE_DATA_SOURCE_API, originalConf.toString)
   }
+  
+  test("SPARK-6742: don't push down predicates which reference partition columns") {
+    import sqlContext.implicits._
+
+    withSQLConf(SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED -> "true") {
+      withTempPath { dir =>
+        val path = s"${dir.getCanonicalPath}/part=1"
+        (1 to 3).map(i => (i, i.toString)).toDF("a", "b").saveAsParquetFile(path)
+
+        // If the "part = 1" filter gets pushed down, this query will throw an exception since
+        // "part" is not a valid column in the actual Parquet file
+        val df = DataFrame(sqlContext, org.apache.spark.sql.parquet.ParquetRelation(
+          path,
+          Some(sqlContext.sparkContext.hadoopConfiguration), sqlContext,
+          Seq(AttributeReference("part", IntegerType, false)()) ))
+       
+        checkAnswer(
+          df.filter("a = 1 or part = 1"),
+          (1 to 3).map(i => Row(1, i, i.toString)))
+      }
+    }
+  }
 }

From 2a55cb41bf7da1786be2c76b8af398da8fedb44b Mon Sep 17 00:00:00 2001
From: MechCoder <manojkumarsivaraj334@gmail.com>
Date: Mon, 13 Apr 2015 15:36:33 -0700
Subject: [PATCH 83/95] [SPARK-5972] [MLlib] Cache residuals and gradient in
 GBT during training and validation

The previous PR https://github.com/apache/spark/pull/4906 helped to extract the learning curve giving the error for each iteration. This continues the work refactoring some code and extending the same logic during training and validation.

Author: MechCoder <manojkumarsivaraj334@gmail.com>

Closes #5330 from MechCoder/spark-5972 and squashes the following commits:

0b5d659 [MechCoder] minor
32d409d [MechCoder] EvaluateeachIteration and training cache should follow different paths
d542bb0 [MechCoder] Remove unused imports and docs
58f4932 [MechCoder] Remove unpersist
70d3b4c [MechCoder] Broadcast for each tree
5869533 [MechCoder] Access broadcasted values locally and other minor changes
923dbf6 [MechCoder] [SPARK-5972] Cache residuals and gradient in GBT during training and validation
---
 .../mllib/tree/GradientBoostedTrees.scala     | 42 ++++++----
 .../spark/mllib/tree/loss/AbsoluteError.scala | 10 +--
 .../spark/mllib/tree/loss/LogLoss.scala       | 11 +--
 .../apache/spark/mllib/tree/loss/Loss.scala   |  8 +-
 .../spark/mllib/tree/loss/SquaredError.scala  | 10 +--
 .../mllib/tree/model/treeEnsembleModels.scala | 77 +++++++++++++++----
 6 files changed, 105 insertions(+), 53 deletions(-)

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/GradientBoostedTrees.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/GradientBoostedTrees.scala
index a9c93e181e3ce..c02c79f094b66 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/GradientBoostedTrees.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/GradientBoostedTrees.scala
@@ -157,7 +157,6 @@ object GradientBoostedTrees extends Logging {
       validationInput: RDD[LabeledPoint],
       boostingStrategy: BoostingStrategy,
       validate: Boolean): GradientBoostedTreesModel = {
-
     val timer = new TimeTracker()
     timer.start("total")
     timer.start("init")
@@ -192,20 +191,29 @@ object GradientBoostedTrees extends Logging {
     // Initialize tree
     timer.start("building tree 0")
     val firstTreeModel = new DecisionTree(treeStrategy).run(data)
+    val firstTreeWeight = 1.0
     baseLearners(0) = firstTreeModel
-    baseLearnerWeights(0) = 1.0
-    val startingModel = new GradientBoostedTreesModel(Regression, Array(firstTreeModel), Array(1.0))
-    logDebug("error of gbt = " + loss.computeError(startingModel, input))
+    baseLearnerWeights(0) = firstTreeWeight
+    val startingModel = new GradientBoostedTreesModel(
+      Regression, Array(firstTreeModel), baseLearnerWeights.slice(0, 1))
+
+    var predError: RDD[(Double, Double)] = GradientBoostedTreesModel.
+      computeInitialPredictionAndError(input, firstTreeWeight, firstTreeModel, loss)
+    logDebug("error of gbt = " + predError.values.mean())
 
     // Note: A model of type regression is used since we require raw prediction
     timer.stop("building tree 0")
 
-    var bestValidateError = if (validate) loss.computeError(startingModel, validationInput) else 0.0
+    var validatePredError: RDD[(Double, Double)] = GradientBoostedTreesModel.
+      computeInitialPredictionAndError(validationInput, firstTreeWeight, firstTreeModel, loss)
+    var bestValidateError = if (validate) validatePredError.values.mean() else 0.0
     var bestM = 1
 
-    // psuedo-residual for second iteration
-    data = input.map(point => LabeledPoint(loss.gradient(startingModel, point),
-      point.features))
+    // pseudo-residual for second iteration
+    data = predError.zip(input).map { case ((pred, _), point) =>
+      LabeledPoint(-loss.gradient(pred, point.label), point.features)
+    }
+
     var m = 1
     while (m < numIterations) {
       timer.start(s"building tree $m")
@@ -222,15 +230,22 @@ object GradientBoostedTrees extends Logging {
       baseLearnerWeights(m) = learningRate
       // Note: A model of type regression is used since we require raw prediction
       val partialModel = new GradientBoostedTreesModel(
-        Regression, baseLearners.slice(0, m + 1), baseLearnerWeights.slice(0, m + 1))
-      logDebug("error of gbt = " + loss.computeError(partialModel, input))
+        Regression, baseLearners.slice(0, m + 1),
+        baseLearnerWeights.slice(0, m + 1))
+
+      predError = GradientBoostedTreesModel.updatePredictionError(
+        input, predError, baseLearnerWeights(m), baseLearners(m), loss)
+      logDebug("error of gbt = " + predError.values.mean())
 
       if (validate) {
         // Stop training early if
         // 1. Reduction in error is less than the validationTol or
         // 2. If the error increases, that is if the model is overfit.
         // We want the model returned corresponding to the best validation error.
-        val currentValidateError = loss.computeError(partialModel, validationInput)
+
+        validatePredError = GradientBoostedTreesModel.updatePredictionError(
+          validationInput, validatePredError, baseLearnerWeights(m), baseLearners(m), loss)
+        val currentValidateError = validatePredError.values.mean()
         if (bestValidateError - currentValidateError < validationTol) {
           return new GradientBoostedTreesModel(
             boostingStrategy.treeStrategy.algo,
@@ -242,8 +257,9 @@ object GradientBoostedTrees extends Logging {
         }
       }
       // Update data with pseudo-residuals
-      data = input.map(point => LabeledPoint(-loss.gradient(partialModel, point),
-        point.features))
+      data = predError.zip(input).map { case ((pred, _), point) =>
+        LabeledPoint(-loss.gradient(pred, point.label), point.features)
+      }
       m += 1
     }
 
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/AbsoluteError.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/AbsoluteError.scala
index 793dd664c5d5a..6f570b4e09c79 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/AbsoluteError.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/AbsoluteError.scala
@@ -37,14 +37,12 @@ object AbsoluteError extends Loss {
    * Method to calculate the gradients for the gradient boosting calculation for least
    * absolute error calculation.
    * The gradient with respect to F(x) is: sign(F(x) - y)
-   * @param model Ensemble model
-   * @param point Instance of the training dataset
+   * @param prediction Predicted label.
+   * @param label True label.
    * @return Loss gradient
    */
-  override def gradient(
-      model: TreeEnsembleModel,
-      point: LabeledPoint): Double = {
-    if ((point.label - model.predict(point.features)) < 0) 1.0 else -1.0
+  override def gradient(prediction: Double, label: Double): Double = {
+    if (label - prediction < 0) 1.0 else -1.0
   }
 
   override def computeError(prediction: Double, label: Double): Double = {
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/LogLoss.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/LogLoss.scala
index 51b1aed167b66..24ee9f3d51293 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/LogLoss.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/LogLoss.scala
@@ -39,15 +39,12 @@ object LogLoss extends Loss {
    * Method to calculate the loss gradients for the gradient boosting calculation for binary
    * classification
    * The gradient with respect to F(x) is: - 4 y / (1 + exp(2 y F(x)))
-   * @param model Ensemble model
-   * @param point Instance of the training dataset
+   * @param prediction Predicted label.
+   * @param label True label.
    * @return Loss gradient
    */
-  override def gradient(
-      model: TreeEnsembleModel,
-      point: LabeledPoint): Double = {
-    val prediction = model.predict(point.features)
-    - 4.0 * point.label / (1.0 + math.exp(2.0 * point.label * prediction))
+  override def gradient(prediction: Double, label: Double): Double = {
+    - 4.0 * label / (1.0 + math.exp(2.0 * label * prediction))
   }
 
   override def computeError(prediction: Double, label: Double): Double = {
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/Loss.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/Loss.scala
index 357869ff6b333..d3b82b752fa0d 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/Loss.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/Loss.scala
@@ -31,13 +31,11 @@ trait Loss extends Serializable {
 
   /**
    * Method to calculate the gradients for the gradient boosting calculation.
-   * @param model Model of the weak learner.
-   * @param point Instance of the training dataset.
+   * @param prediction Predicted feature
+   * @param label true label.
    * @return Loss gradient.
    */
-  def gradient(
-      model: TreeEnsembleModel,
-      point: LabeledPoint): Double
+  def gradient(prediction: Double, label: Double): Double
 
   /**
    * Method to calculate error of the base learner for the gradient boosting calculation.
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/SquaredError.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/SquaredError.scala
index b990707ca4525..58857ae15e93e 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/SquaredError.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/SquaredError.scala
@@ -37,14 +37,12 @@ object SquaredError extends Loss {
    * Method to calculate the gradients for the gradient boosting calculation for least
    * squares error calculation.
    * The gradient with respect to F(x) is: - 2 (y - F(x))
-   * @param model Ensemble model
-   * @param point Instance of the training dataset
+   * @param prediction Predicted label.
+   * @param label True label.
    * @return Loss gradient
    */
-  override def gradient(
-    model: TreeEnsembleModel,
-    point: LabeledPoint): Double = {
-    2.0 * (model.predict(point.features) - point.label)
+  override def gradient(prediction: Double, label: Double): Double = {
+    2.0 * (prediction - label)
   }
 
   override def computeError(prediction: Double, label: Double): Double = {
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/model/treeEnsembleModels.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/model/treeEnsembleModels.scala
index 1950254b2aa6d..fef3d2acb202a 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/model/treeEnsembleModels.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/model/treeEnsembleModels.scala
@@ -130,35 +130,28 @@ class GradientBoostedTreesModel(
 
     val numIterations = trees.length
     val evaluationArray = Array.fill(numIterations)(0.0)
+    val localTreeWeights = treeWeights
+
+    var predictionAndError = GradientBoostedTreesModel.computeInitialPredictionAndError(
+      remappedData, localTreeWeights(0), trees(0), loss)
 
-    var predictionAndError: RDD[(Double, Double)] = remappedData.map { i =>
-      val pred = treeWeights(0) * trees(0).predict(i.features)
-      val error = loss.computeError(pred, i.label)
-      (pred, error)
-    }
     evaluationArray(0) = predictionAndError.values.mean()
 
-    // Avoid the model being copied across numIterations.
     val broadcastTrees = sc.broadcast(trees)
-    val broadcastWeights = sc.broadcast(treeWeights)
-
     (1 until numIterations).map { nTree =>
       predictionAndError = remappedData.zip(predictionAndError).mapPartitions { iter =>
         val currentTree = broadcastTrees.value(nTree)
-        val currentTreeWeight = broadcastWeights.value(nTree)
-        iter.map {
-          case (point, (pred, error)) => {
-            val newPred = pred + currentTree.predict(point.features) * currentTreeWeight
-            val newError = loss.computeError(newPred, point.label)
-            (newPred, newError)
-          }
+        val currentTreeWeight = localTreeWeights(nTree)
+        iter.map { case (point, (pred, error)) =>
+          val newPred = pred + currentTree.predict(point.features) * currentTreeWeight
+          val newError = loss.computeError(newPred, point.label)
+          (newPred, newError)
         }
       }
       evaluationArray(nTree) = predictionAndError.values.mean()
     }
 
     broadcastTrees.unpersist()
-    broadcastWeights.unpersist()
     evaluationArray
   }
 
@@ -166,6 +159,58 @@ class GradientBoostedTreesModel(
 
 object GradientBoostedTreesModel extends Loader[GradientBoostedTreesModel] {
 
+  /**
+   * Compute the initial predictions and errors for a dataset for the first
+   * iteration of gradient boosting.
+   * @param data: training data.
+   * @param initTreeWeight: learning rate assigned to the first tree.
+   * @param initTree: first DecisionTreeModel.
+   * @param loss: evaluation metric.
+   * @return a RDD with each element being a zip of the prediction and error
+   *         corresponding to every sample.
+   */
+  def computeInitialPredictionAndError(
+      data: RDD[LabeledPoint],
+      initTreeWeight: Double,
+      initTree: DecisionTreeModel,
+      loss: Loss): RDD[(Double, Double)] = {
+    data.map { lp =>
+      val pred = initTreeWeight * initTree.predict(lp.features)
+      val error = loss.computeError(pred, lp.label)
+      (pred, error)
+    }
+  }
+
+  /**
+   * Update a zipped predictionError RDD
+   * (as obtained with computeInitialPredictionAndError)
+   * @param data: training data.
+   * @param predictionAndError: predictionError RDD
+   * @param treeWeight: Learning rate.
+   * @param tree: Tree using which the prediction and error should be updated.
+   * @param loss: evaluation metric.
+   * @return a RDD with each element being a zip of the prediction and error
+   *         corresponding to each sample.
+   */
+  def updatePredictionError(
+    data: RDD[LabeledPoint],
+    predictionAndError: RDD[(Double, Double)],
+    treeWeight: Double,
+    tree: DecisionTreeModel,
+    loss: Loss): RDD[(Double, Double)] = {
+
+    val newPredError = data.zip(predictionAndError).mapPartitions { iter =>
+      iter.map {
+        case (lp, (pred, error)) => {
+          val newPred = pred + tree.predict(lp.features) * treeWeight
+          val newError = loss.computeError(newPred, lp.label)
+          (newPred, newError)
+        }
+      }
+    }
+    newPredError
+  }
+
   override def load(sc: SparkContext, path: String): GradientBoostedTreesModel = {
     val (loadedClassName, version, jsonMetadata) = Loader.loadMetadata(sc, path)
     val classNameV1_0 = SaveLoadV1_0.thisClassName

From e63a86abe2794332cdad71d87b72a7c56327a43d Mon Sep 17 00:00:00 2001
From: Daoyuan Wang <daoyuan.wang@intel.com>
Date: Mon, 13 Apr 2015 16:00:58 -0700
Subject: [PATCH 84/95] [SPARK-6872] [SQL] add copy in external sort

We need add copy before call externalsort.

Author: Daoyuan Wang <daoyuan.wang@intel.com>

Closes #5481 from adrian-wang/extsort and squashes the following commits:

9611586 [Daoyuan Wang] fix bug in external sort
---
 .../scala/org/apache/spark/sql/execution/basicOperators.scala   | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala
index 6eec520abff53..f8221f41bc6c3 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala
@@ -194,7 +194,7 @@ case class ExternalSort(
     child.execute().mapPartitions( { iterator =>
       val ordering = newOrdering(sortOrder, child.output)
       val sorter = new ExternalSorter[Row, Null, Row](ordering = Some(ordering))
-      sorter.insertAll(iterator.map(r => (r, null)))
+      sorter.insertAll(iterator.map(r => (r.copy, null)))
       val baseIterator = sorter.iterator.map(_._1)
       // TODO(marmbrus): The complex type signature below thwarts inference for no reason.
       CompletionIterator[Row, Iterator[Row]](baseIterator, sorter.stop())

From c5602bdc310cc8f82dc304500bebe40217cba785 Mon Sep 17 00:00:00 2001
From: Cheng Hao <hao.cheng@intel.com>
Date: Mon, 13 Apr 2015 16:02:18 -0700
Subject: [PATCH 85/95] [SPARK-5941] [SQL] Unit Test loads the table `src`
 twice for leftsemijoin.q

In `leftsemijoin.q`, there is a data loading command for table `sales` already, but in `TestHive`, it also created the table `sales`, which causes duplicated records inserted into the `sales`.

Author: Cheng Hao <hao.cheng@intel.com>

Closes #4506 from chenghao-intel/df_table and squashes the following commits:

0be05f7 [Cheng Hao] Remove the table `sales` creating from TestHive
---
 .../sql/columnar/InMemoryColumnarQuerySuite.scala |  2 +-
 .../org/apache/spark/sql/hive/test/TestHive.scala |  6 ------
 ...ftsemijoin-10-89737a8857b5b61cc909e0c797f86aea |  2 --
 .../leftsemijoin-8-73cad58a10a1483ccb15e94a857013 |  2 --
 .../spark/sql/hive/execution/HiveSerDeSuite.scala | 15 +++++++++++----
 5 files changed, 12 insertions(+), 15 deletions(-)

diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala
index 27dfabca90217..479210d1c9c43 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala
@@ -42,7 +42,7 @@ class InMemoryColumnarQuerySuite extends QueryTest {
       .toDF().registerTempTable("sizeTst")
     cacheTable("sizeTst")
     assert(
-      table("sizeTst").queryExecution.logical.statistics.sizeInBytes >
+      table("sizeTst").queryExecution.analyzed.statistics.sizeInBytes >
         conf.autoBroadcastJoinThreshold)
   }
 
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/test/TestHive.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/test/TestHive.scala
index a3497eadd67f6..6570fa1043900 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/test/TestHive.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/test/TestHive.scala
@@ -262,12 +262,6 @@ class TestHiveContext(sc: SparkContext) extends HiveContext(sc) {
          |WITH SERDEPROPERTIES ('field.delim'='\\t')
        """.stripMargin.cmd,
       "INSERT OVERWRITE TABLE serdeins SELECT * FROM src".cmd),
-    TestTable("sales",
-      s"""CREATE TABLE IF NOT EXISTS sales (key STRING, value INT)
-         |ROW FORMAT SERDE '${classOf[RegexSerDe].getCanonicalName}'
-         |WITH SERDEPROPERTIES ("input.regex" = "([^ ]*)\t([^ ]*)")
-       """.stripMargin.cmd,
-      s"LOAD DATA LOCAL INPATH '${getHiveFile("data/files/sales.txt")}' INTO TABLE sales".cmd),
     TestTable("episodes",
       s"""CREATE TABLE episodes (title STRING, air_date STRING, doctor INT)
          |ROW FORMAT SERDE '${classOf[AvroSerDe].getCanonicalName}'
diff --git a/sql/hive/src/test/resources/golden/leftsemijoin-10-89737a8857b5b61cc909e0c797f86aea b/sql/hive/src/test/resources/golden/leftsemijoin-10-89737a8857b5b61cc909e0c797f86aea
index 25ce912507d55..a1963ba81e0da 100644
--- a/sql/hive/src/test/resources/golden/leftsemijoin-10-89737a8857b5b61cc909e0c797f86aea
+++ b/sql/hive/src/test/resources/golden/leftsemijoin-10-89737a8857b5b61cc909e0c797f86aea
@@ -1,4 +1,2 @@
 Hank	2
-Hank	2
-Joe	2
 Joe	2
diff --git a/sql/hive/src/test/resources/golden/leftsemijoin-8-73cad58a10a1483ccb15e94a857013 b/sql/hive/src/test/resources/golden/leftsemijoin-8-73cad58a10a1483ccb15e94a857013
index 25ce912507d55..a1963ba81e0da 100644
--- a/sql/hive/src/test/resources/golden/leftsemijoin-8-73cad58a10a1483ccb15e94a857013
+++ b/sql/hive/src/test/resources/golden/leftsemijoin-8-73cad58a10a1483ccb15e94a857013
@@ -1,4 +1,2 @@
 Hank	2
-Hank	2
-Joe	2
 Joe	2
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveSerDeSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveSerDeSuite.scala
index d05e11fcf281b..5586a793618bd 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveSerDeSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveSerDeSuite.scala
@@ -25,18 +25,25 @@ import org.apache.spark.sql.hive.test.TestHive
  * A set of tests that validates support for Hive SerDe.
  */
 class HiveSerDeSuite extends HiveComparisonTest with BeforeAndAfterAll {
-
   override def beforeAll(): Unit = {
+    import TestHive._
+    import org.apache.hadoop.hive.serde2.RegexSerDe
+      super.beforeAll()
     TestHive.cacheTables = false
-    super.beforeAll()
+    sql(s"""CREATE TABLE IF NOT EXISTS sales (key STRING, value INT)
+       |ROW FORMAT SERDE '${classOf[RegexSerDe].getCanonicalName}'
+       |WITH SERDEPROPERTIES ("input.regex" = "([^ ]*)\t([^ ]*)")
+       """.stripMargin)
+    sql(s"LOAD DATA LOCAL INPATH '${getHiveFile("data/files/sales.txt")}' INTO TABLE sales")
   }
 
+  // table sales is not a cache table, and will be clear after reset
+  createQueryTest("Read with RegexSerDe", "SELECT * FROM sales", false)
+
   createQueryTest(
     "Read and write with LazySimpleSerDe (tab separated)",
     "SELECT * from serdeins")
 
-  createQueryTest("Read with RegexSerDe", "SELECT * FROM sales")
-
   createQueryTest("Read with AvroSerDe", "SELECT * FROM episodes")
 
   createQueryTest("Read Partitioned with AvroSerDe", "SELECT * FROM episodes_part")

From c4ab255e94366ba9b9023d5431f9d2412e0d6dc7 Mon Sep 17 00:00:00 2001
From: Ilya Ganelin <ilya.ganelin@capitalone.com>
Date: Mon, 13 Apr 2015 16:28:07 -0700
Subject: [PATCH 86/95] [SPARK-5931][CORE] Use consistent naming for time
 properties

I've added new utility methods to do the conversion from times specified as e.g. 120s, 240ms, 360us to convert to a consistent internal representation. I've updated usage of these constants throughout the code to be consistent.

I believe I've captured all usages of time-based properties throughout the code. I've also updated variable names in a number of places to reflect their units for clarity and updated documentation where appropriate.

Author: Ilya Ganelin <ilya.ganelin@capitalone.com>
Author: Ilya Ganelin <ilganeli@gmail.com>

Closes #5236 from ilganeli/SPARK-5931 and squashes the following commits:

4526c81 [Ilya Ganelin] Update configuration.md
de3bff9 [Ilya Ganelin] Fixing style errors
f5fafcd [Ilya Ganelin] Doc updates
951ca2d [Ilya Ganelin] Made the most recent round of changes
bc04e05 [Ilya Ganelin] Minor fixes and doc updates
25d3f52 [Ilya Ganelin] Minor nit fixes
642a06d [Ilya Ganelin] Fixed logic for invalid suffixes and addid matching test
8927e66 [Ilya Ganelin] Fixed handling of -1
69fedcc [Ilya Ganelin] Added test for zero
dc7bd08 [Ilya Ganelin] Fixed error in exception handling
7d19cdd [Ilya Ganelin] Added fix for possible NPE
6f651a8 [Ilya Ganelin] Now using regexes to simplify code in parseTimeString. Introduces getTimeAsSec and getTimeAsMs methods in SparkConf. Updated documentation
cbd2ca6 [Ilya Ganelin] Formatting error
1a1122c [Ilya Ganelin] Formatting fixes and added m for use as minute formatter
4e48679 [Ilya Ganelin] Fixed priority order and mixed up conversions in a couple spots
d4efd26 [Ilya Ganelin] Added time conversion for yarn.scheduler.heartbeat.interval-ms
cbf41db [Ilya Ganelin] Got rid of thrown exceptions
1465390 [Ilya Ganelin] Nit
28187bf [Ilya Ganelin] Convert straight to seconds
ff40bfe [Ilya Ganelin] Updated tests to fix small bugs
19c31af [Ilya Ganelin] Added cleaner computation of time conversions in tests
6387772 [Ilya Ganelin] Updated suffix handling to handle overlap of units more gracefully
5193d5f [Ilya Ganelin] Resolved merge conflicts
76cfa27 [Ilya Ganelin] [SPARK-5931] Minor nit fixes'
bf779b0 [Ilya Ganelin] Special handling of overlapping usffixes for java
dd0a680 [Ilya Ganelin] Updated scala code to call into java
b2fc965 [Ilya Ganelin] replaced get or default since it's not present in this version of java
39164f9 [Ilya Ganelin] [SPARK-5931] Updated Java conversion to be similar to scala conversion. Updated conversions to clean up code a little using TimeUnit.convert. Added Unit tests
3b126e1 [Ilya Ganelin] Fixed conversion to US from seconds
1858197 [Ilya Ganelin] Fixed bug where all time was being converted to us instead of the appropriate units
bac9edf [Ilya Ganelin] More whitespace
8613631 [Ilya Ganelin] Whitespace
1c0c07c [Ilya Ganelin] Updated Java code to add day, minutes, and hours
647b5ac [Ilya Ganelin] Udpated time conversion to use map iterator instead of if fall through
70ac213 [Ilya Ganelin] Fixed remaining usages to be consistent. Updated Java-side time conversion
68f4e93 [Ilya Ganelin] Updated more files to clean up usage of default time strings
3a12dd8 [Ilya Ganelin] Updated host revceiver
5232a36 [Ilya Ganelin] [SPARK-5931] Changed default behavior of time string conversion.
499bdf0 [Ilya Ganelin] Merge branch 'SPARK-5931' of github.com:ilganeli/spark into SPARK-5931
9e2547c [Ilya Ganelin] Reverting doc changes
8f741e1 [Ilya Ganelin] Update JavaUtils.java
34f87c2 [Ilya Ganelin] Update Utils.scala
9a29d8d [Ilya Ganelin] Fixed misuse of time in streaming context test
42477aa [Ilya Ganelin] Updated configuration doc with note on specifying time properties
cde9bff [Ilya Ganelin] Updated spark.streaming.blockInterval
c6a0095 [Ilya Ganelin] Updated spark.core.connection.auth.wait.timeout
5181597 [Ilya Ganelin] Updated spark.dynamicAllocation.schedulerBacklogTimeout
2fcc91c [Ilya Ganelin] Updated spark.dynamicAllocation.executorIdleTimeout
6d1518e [Ilya Ganelin] Upated spark.speculation.interval
3f1cfc8 [Ilya Ganelin] Updated spark.scheduler.revive.interval
3352d34 [Ilya Ganelin] Updated spark.scheduler.maxRegisteredResourcesWaitingTime
272c215 [Ilya Ganelin] Updated spark.locality.wait
7320c87 [Ilya Ganelin] updated spark.akka.heartbeat.interval
064ebd6 [Ilya Ganelin] Updated usage of spark.cleaner.ttl
21ef3dd [Ilya Ganelin] updated spark.shuffle.sasl.timeout
c9f5cad [Ilya Ganelin] Updated spark.shuffle.io.retryWait
4933fda [Ilya Ganelin] Updated usage of spark.storage.blockManagerSlaveTimeout
7db6d2a [Ilya Ganelin] Updated usage of spark.akka.timeout
404f8c3 [Ilya Ganelin] Updated usage of spark.core.connection.ack.wait.timeout
59bf9e1 [Ilya Ganelin] [SPARK-5931] Updated Utils and JavaUtils classes to add helper methods to handle time strings. Updated time strings in a few places to properly parse time
---
 .../spark/ExecutorAllocationManager.scala     | 34 ++++----
 .../org/apache/spark/HeartbeatReceiver.scala  | 15 ++--
 .../scala/org/apache/spark/SparkConf.scala    | 36 ++++++++
 .../org/apache/spark/executor/Executor.scala  |  6 +-
 .../spark/network/nio/ConnectionManager.scala |  3 +-
 .../spark/scheduler/TaskSchedulerImpl.scala   | 10 +--
 .../spark/scheduler/TaskSetManager.scala      | 21 +++--
 .../CoarseGrainedSchedulerBackend.scala       | 13 +--
 .../org/apache/spark/util/AkkaUtils.scala     | 14 +--
 .../apache/spark/util/MetadataCleaner.scala   |  2 +-
 .../scala/org/apache/spark/util/Utils.scala   | 26 +++++-
 .../ExecutorAllocationManagerSuite.scala      |  7 +-
 .../network/nio/ConnectionManagerSuite.scala  |  8 +-
 .../spark/scheduler/TaskSetManagerSuite.scala | 25 +++---
 .../BlockManagerReplicationSuite.scala        |  2 +-
 .../org/apache/spark/util/UtilsSuite.scala    | 44 ++++++++++
 docs/configuration.md                         | 86 ++++++++++---------
 docs/running-on-yarn.md                       |  4 +-
 .../apache/spark/network/util/JavaUtils.java  | 66 ++++++++++++++
 .../spark/network/util/TransportConf.java     | 15 +++-
 .../streaming/receiver/BlockGenerator.scala   |  8 +-
 .../streaming/scheduler/JobGenerator.scala    | 12 ++-
 .../spark/streaming/ReceiverSuite.scala       | 14 +--
 .../streaming/StreamingContextSuite.scala     | 22 ++---
 .../spark/deploy/yarn/ApplicationMaster.scala |  9 +-
 25 files changed, 345 insertions(+), 157 deletions(-)

diff --git a/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala b/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala
index 9385f557c4614..4e7bf51fc0622 100644
--- a/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala
+++ b/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala
@@ -80,16 +80,16 @@ private[spark] class ExecutorAllocationManager(
     Integer.MAX_VALUE)
 
   // How long there must be backlogged tasks for before an addition is triggered (seconds)
-  private val schedulerBacklogTimeout = conf.getLong(
-    "spark.dynamicAllocation.schedulerBacklogTimeout", 5)
+  private val schedulerBacklogTimeoutS = conf.getTimeAsSeconds(
+    "spark.dynamicAllocation.schedulerBacklogTimeout", "5s")
 
-  // Same as above, but used only after `schedulerBacklogTimeout` is exceeded
-  private val sustainedSchedulerBacklogTimeout = conf.getLong(
-    "spark.dynamicAllocation.sustainedSchedulerBacklogTimeout", schedulerBacklogTimeout)
+  // Same as above, but used only after `schedulerBacklogTimeoutS` is exceeded
+  private val sustainedSchedulerBacklogTimeoutS = conf.getTimeAsSeconds(
+    "spark.dynamicAllocation.sustainedSchedulerBacklogTimeout", s"${schedulerBacklogTimeoutS}s")
 
   // How long an executor must be idle for before it is removed (seconds)
-  private val executorIdleTimeout = conf.getLong(
-    "spark.dynamicAllocation.executorIdleTimeout", 600)
+  private val executorIdleTimeoutS = conf.getTimeAsSeconds(
+    "spark.dynamicAllocation.executorIdleTimeout", "600s")
 
   // During testing, the methods to actually kill and add executors are mocked out
   private val testing = conf.getBoolean("spark.dynamicAllocation.testing", false)
@@ -150,14 +150,14 @@ private[spark] class ExecutorAllocationManager(
       throw new SparkException(s"spark.dynamicAllocation.minExecutors ($minNumExecutors) must " +
         s"be less than or equal to spark.dynamicAllocation.maxExecutors ($maxNumExecutors)!")
     }
-    if (schedulerBacklogTimeout <= 0) {
+    if (schedulerBacklogTimeoutS <= 0) {
       throw new SparkException("spark.dynamicAllocation.schedulerBacklogTimeout must be > 0!")
     }
-    if (sustainedSchedulerBacklogTimeout <= 0) {
+    if (sustainedSchedulerBacklogTimeoutS <= 0) {
       throw new SparkException(
         "spark.dynamicAllocation.sustainedSchedulerBacklogTimeout must be > 0!")
     }
-    if (executorIdleTimeout <= 0) {
+    if (executorIdleTimeoutS <= 0) {
       throw new SparkException("spark.dynamicAllocation.executorIdleTimeout must be > 0!")
     }
     // Require external shuffle service for dynamic allocation
@@ -262,8 +262,8 @@ private[spark] class ExecutorAllocationManager(
     } else if (addTime != NOT_SET && now >= addTime) {
       val delta = addExecutors(maxNeeded)
       logDebug(s"Starting timer to add more executors (to " +
-        s"expire in $sustainedSchedulerBacklogTimeout seconds)")
-      addTime += sustainedSchedulerBacklogTimeout * 1000
+        s"expire in $sustainedSchedulerBacklogTimeoutS seconds)")
+      addTime += sustainedSchedulerBacklogTimeoutS * 1000
       delta
     } else {
       0
@@ -351,7 +351,7 @@ private[spark] class ExecutorAllocationManager(
     val removeRequestAcknowledged = testing || client.killExecutor(executorId)
     if (removeRequestAcknowledged) {
       logInfo(s"Removing executor $executorId because it has been idle for " +
-        s"$executorIdleTimeout seconds (new desired total will be ${numExistingExecutors - 1})")
+        s"$executorIdleTimeoutS seconds (new desired total will be ${numExistingExecutors - 1})")
       executorsPendingToRemove.add(executorId)
       true
     } else {
@@ -407,8 +407,8 @@ private[spark] class ExecutorAllocationManager(
   private def onSchedulerBacklogged(): Unit = synchronized {
     if (addTime == NOT_SET) {
       logDebug(s"Starting timer to add executors because pending tasks " +
-        s"are building up (to expire in $schedulerBacklogTimeout seconds)")
-      addTime = clock.getTimeMillis + schedulerBacklogTimeout * 1000
+        s"are building up (to expire in $schedulerBacklogTimeoutS seconds)")
+      addTime = clock.getTimeMillis + schedulerBacklogTimeoutS * 1000
     }
   }
 
@@ -431,8 +431,8 @@ private[spark] class ExecutorAllocationManager(
     if (executorIds.contains(executorId)) {
       if (!removeTimes.contains(executorId) && !executorsPendingToRemove.contains(executorId)) {
         logDebug(s"Starting idle timer for $executorId because there are no more tasks " +
-          s"scheduled to run on the executor (to expire in $executorIdleTimeout seconds)")
-        removeTimes(executorId) = clock.getTimeMillis + executorIdleTimeout * 1000
+          s"scheduled to run on the executor (to expire in $executorIdleTimeoutS seconds)")
+        removeTimes(executorId) = clock.getTimeMillis + executorIdleTimeoutS * 1000
       }
     } else {
       logWarning(s"Attempted to mark unknown executor $executorId idle")
diff --git a/core/src/main/scala/org/apache/spark/HeartbeatReceiver.scala b/core/src/main/scala/org/apache/spark/HeartbeatReceiver.scala
index 5871b8c869f03..e3bd16f1cbf24 100644
--- a/core/src/main/scala/org/apache/spark/HeartbeatReceiver.scala
+++ b/core/src/main/scala/org/apache/spark/HeartbeatReceiver.scala
@@ -62,14 +62,17 @@ private[spark] class HeartbeatReceiver(sc: SparkContext)
 
   // "spark.network.timeout" uses "seconds", while `spark.storage.blockManagerSlaveTimeoutMs` uses
   // "milliseconds"
-  private val executorTimeoutMs = sc.conf.getOption("spark.network.timeout").map(_.toLong * 1000).
-    getOrElse(sc.conf.getLong("spark.storage.blockManagerSlaveTimeoutMs", 120000))
-
+  private val slaveTimeoutMs = 
+    sc.conf.getTimeAsMs("spark.storage.blockManagerSlaveTimeoutMs", "120s")
+  private val executorTimeoutMs = 
+    sc.conf.getTimeAsSeconds("spark.network.timeout", s"${slaveTimeoutMs}ms") * 1000
+  
   // "spark.network.timeoutInterval" uses "seconds", while
   // "spark.storage.blockManagerTimeoutIntervalMs" uses "milliseconds"
-  private val checkTimeoutIntervalMs =
-    sc.conf.getOption("spark.network.timeoutInterval").map(_.toLong * 1000).
-      getOrElse(sc.conf.getLong("spark.storage.blockManagerTimeoutIntervalMs", 60000))
+  private val timeoutIntervalMs = 
+    sc.conf.getTimeAsMs("spark.storage.blockManagerTimeoutIntervalMs", "60s")
+  private val checkTimeoutIntervalMs = 
+    sc.conf.getTimeAsSeconds("spark.network.timeoutInterval", s"${timeoutIntervalMs}ms") * 1000
   
   private var timeoutCheckingTask: ScheduledFuture[_] = null
 
diff --git a/core/src/main/scala/org/apache/spark/SparkConf.scala b/core/src/main/scala/org/apache/spark/SparkConf.scala
index 0c123c96b8d7b..390e631647bd6 100644
--- a/core/src/main/scala/org/apache/spark/SparkConf.scala
+++ b/core/src/main/scala/org/apache/spark/SparkConf.scala
@@ -174,6 +174,42 @@ class SparkConf(loadDefaults: Boolean) extends Cloneable with Logging {
     getOption(key).getOrElse(defaultValue)
   }
 
+  /** 
+   * Get a time parameter as seconds; throws a NoSuchElementException if it's not set. If no 
+   * suffix is provided then seconds are assumed.
+   * @throws NoSuchElementException
+   */
+  def getTimeAsSeconds(key: String): Long = {
+    Utils.timeStringAsSeconds(get(key))
+  }
+
+  /** 
+   * Get a time parameter as seconds, falling back to a default if not set. If no 
+   * suffix is provided then seconds are assumed.
+   * 
+   */
+  def getTimeAsSeconds(key: String, defaultValue: String): Long = {
+    Utils.timeStringAsSeconds(get(key, defaultValue))
+  }
+
+  /** 
+   * Get a time parameter as milliseconds; throws a NoSuchElementException if it's not set. If no 
+   * suffix is provided then milliseconds are assumed. 
+   * @throws NoSuchElementException
+   */
+  def getTimeAsMs(key: String): Long = {
+    Utils.timeStringAsMs(get(key))
+  }
+
+  /** 
+   * Get a time parameter as milliseconds, falling back to a default if not set. If no 
+   * suffix is provided then milliseconds are assumed. 
+   */
+  def getTimeAsMs(key: String, defaultValue: String): Long = {
+    Utils.timeStringAsMs(get(key, defaultValue))
+  }
+  
+
   /** Get a parameter as an Option */
   def getOption(key: String): Option[String] = {
     Option(settings.get(key))
diff --git a/core/src/main/scala/org/apache/spark/executor/Executor.scala b/core/src/main/scala/org/apache/spark/executor/Executor.scala
index 14f99a464b6e9..516f619529c48 100644
--- a/core/src/main/scala/org/apache/spark/executor/Executor.scala
+++ b/core/src/main/scala/org/apache/spark/executor/Executor.scala
@@ -436,14 +436,14 @@ private[spark] class Executor(
    * This thread stops running when the executor is stopped.
    */
   private def startDriverHeartbeater(): Unit = {
-    val interval = conf.getInt("spark.executor.heartbeatInterval", 10000)
+    val intervalMs = conf.getTimeAsMs("spark.executor.heartbeatInterval", "10s")
     val thread = new Thread() {
       override def run() {
         // Sleep a random interval so the heartbeats don't end up in sync
-        Thread.sleep(interval + (math.random * interval).asInstanceOf[Int])
+        Thread.sleep(intervalMs + (math.random * intervalMs).asInstanceOf[Int])
         while (!isStopped) {
           reportHeartBeat()
-          Thread.sleep(interval)
+          Thread.sleep(intervalMs)
         }
       }
     }
diff --git a/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala b/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala
index 741fe3e1ea750..8e3c30fc3d781 100644
--- a/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala
+++ b/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala
@@ -82,7 +82,8 @@ private[nio] class ConnectionManager(
     new HashedWheelTimer(Utils.namedThreadFactory("AckTimeoutMonitor"))
 
   private val ackTimeout =
-    conf.getInt("spark.core.connection.ack.wait.timeout", conf.getInt("spark.network.timeout", 120))
+    conf.getTimeAsSeconds("spark.core.connection.ack.wait.timeout",
+      conf.get("spark.network.timeout", "120s"))
 
   // Get the thread counts from the Spark Configuration.
   // 
diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala
index 076b36e86c0ce..2362cc7240039 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala
@@ -62,10 +62,10 @@ private[spark] class TaskSchedulerImpl(
   val conf = sc.conf
 
   // How often to check for speculative tasks
-  val SPECULATION_INTERVAL = conf.getLong("spark.speculation.interval", 100)
+  val SPECULATION_INTERVAL_MS = conf.getTimeAsMs("spark.speculation.interval", "100ms")
 
   // Threshold above which we warn user initial TaskSet may be starved
-  val STARVATION_TIMEOUT = conf.getLong("spark.starvation.timeout", 15000)
+  val STARVATION_TIMEOUT_MS = conf.getTimeAsMs("spark.starvation.timeout", "15s")
 
   // CPUs to request per task
   val CPUS_PER_TASK = conf.getInt("spark.task.cpus", 1)
@@ -143,8 +143,8 @@ private[spark] class TaskSchedulerImpl(
     if (!isLocal && conf.getBoolean("spark.speculation", false)) {
       logInfo("Starting speculative execution thread")
       import sc.env.actorSystem.dispatcher
-      sc.env.actorSystem.scheduler.schedule(SPECULATION_INTERVAL milliseconds,
-            SPECULATION_INTERVAL milliseconds) {
+      sc.env.actorSystem.scheduler.schedule(SPECULATION_INTERVAL_MS milliseconds,
+            SPECULATION_INTERVAL_MS milliseconds) {
         Utils.tryOrStopSparkContext(sc) { checkSpeculatableTasks() }
       }
     }
@@ -173,7 +173,7 @@ private[spark] class TaskSchedulerImpl(
               this.cancel()
             }
           }
-        }, STARVATION_TIMEOUT, STARVATION_TIMEOUT)
+        }, STARVATION_TIMEOUT_MS, STARVATION_TIMEOUT_MS)
       }
       hasReceivedTask = true
     }
diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala
index d509881c74fef..7dc325283d961 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala
@@ -848,15 +848,18 @@ private[spark] class TaskSetManager(
   }
 
   private def getLocalityWait(level: TaskLocality.TaskLocality): Long = {
-    val defaultWait = conf.get("spark.locality.wait", "3000")
-    level match {
-      case TaskLocality.PROCESS_LOCAL =>
-        conf.get("spark.locality.wait.process", defaultWait).toLong
-      case TaskLocality.NODE_LOCAL =>
-        conf.get("spark.locality.wait.node", defaultWait).toLong
-      case TaskLocality.RACK_LOCAL =>
-        conf.get("spark.locality.wait.rack", defaultWait).toLong
-      case _ => 0L
+    val defaultWait = conf.get("spark.locality.wait", "3s")
+    val localityWaitKey = level match {
+      case TaskLocality.PROCESS_LOCAL => "spark.locality.wait.process"
+      case TaskLocality.NODE_LOCAL => "spark.locality.wait.node"
+      case TaskLocality.RACK_LOCAL => "spark.locality.wait.rack"
+      case _ => null
+    }
+    
+    if (localityWaitKey != null) {
+      conf.getTimeAsMs(localityWaitKey, defaultWait)  
+    } else {
+      0L
     }
   }
 
diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
index 4c49da87af9dc..63987dfb32695 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
@@ -52,8 +52,8 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp
     math.min(1, conf.getDouble("spark.scheduler.minRegisteredResourcesRatio", 0))
   // Submit tasks after maxRegisteredWaitingTime milliseconds
   // if minRegisteredRatio has not yet been reached
-  val maxRegisteredWaitingTime =
-    conf.getInt("spark.scheduler.maxRegisteredResourcesWaitingTime", 30000)
+  val maxRegisteredWaitingTimeMs =
+    conf.getTimeAsMs("spark.scheduler.maxRegisteredResourcesWaitingTime", "30s")
   val createTime = System.currentTimeMillis()
 
   private val executorDataMap = new HashMap[String, ExecutorData]
@@ -77,12 +77,13 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp
 
     override def onStart() {
       // Periodically revive offers to allow delay scheduling to work
-      val reviveInterval = conf.getLong("spark.scheduler.revive.interval", 1000)
+      val reviveIntervalMs = conf.getTimeAsMs("spark.scheduler.revive.interval", "1s")
+ 
       reviveThread.scheduleAtFixedRate(new Runnable {
         override def run(): Unit = Utils.tryLogNonFatalError {
           Option(self).foreach(_.send(ReviveOffers))
         }
-      }, 0, reviveInterval, TimeUnit.MILLISECONDS)
+      }, 0, reviveIntervalMs, TimeUnit.MILLISECONDS)
     }
 
     override def receive: PartialFunction[Any, Unit] = {
@@ -301,9 +302,9 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp
         s"reached minRegisteredResourcesRatio: $minRegisteredRatio")
       return true
     }
-    if ((System.currentTimeMillis() - createTime) >= maxRegisteredWaitingTime) {
+    if ((System.currentTimeMillis() - createTime) >= maxRegisteredWaitingTimeMs) {
       logInfo("SchedulerBackend is ready for scheduling beginning after waiting " +
-        s"maxRegisteredResourcesWaitingTime: $maxRegisteredWaitingTime(ms)")
+        s"maxRegisteredResourcesWaitingTime: $maxRegisteredWaitingTimeMs(ms)")
       return true
     }
     false
diff --git a/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala b/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala
index 6c2c5261306e7..8e8cc7cc6389e 100644
--- a/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala
+++ b/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala
@@ -20,7 +20,6 @@ package org.apache.spark.util
 import scala.collection.JavaConversions.mapAsJavaMap
 import scala.concurrent.Await
 import scala.concurrent.duration.{Duration, FiniteDuration}
-import scala.util.Try
 
 import akka.actor.{ActorRef, ActorSystem, ExtendedActorSystem}
 import akka.pattern.ask
@@ -66,7 +65,8 @@ private[spark] object AkkaUtils extends Logging {
 
     val akkaThreads   = conf.getInt("spark.akka.threads", 4)
     val akkaBatchSize = conf.getInt("spark.akka.batchSize", 15)
-    val akkaTimeout = conf.getInt("spark.akka.timeout", conf.getInt("spark.network.timeout", 120))
+    val akkaTimeoutS = conf.getTimeAsSeconds("spark.akka.timeout",
+      conf.get("spark.network.timeout", "120s"))
     val akkaFrameSize = maxFrameSizeBytes(conf)
     val akkaLogLifecycleEvents = conf.getBoolean("spark.akka.logLifecycleEvents", false)
     val lifecycleEvents = if (akkaLogLifecycleEvents) "on" else "off"
@@ -78,8 +78,8 @@ private[spark] object AkkaUtils extends Logging {
 
     val logAkkaConfig = if (conf.getBoolean("spark.akka.logAkkaConfig", false)) "on" else "off"
 
-    val akkaHeartBeatPauses = conf.getInt("spark.akka.heartbeat.pauses", 6000)
-    val akkaHeartBeatInterval = conf.getInt("spark.akka.heartbeat.interval", 1000)
+    val akkaHeartBeatPausesS = conf.getTimeAsSeconds("spark.akka.heartbeat.pauses", "6000s")
+    val akkaHeartBeatIntervalS = conf.getTimeAsSeconds("spark.akka.heartbeat.interval", "1000s")
 
     val secretKey = securityManager.getSecretKey()
     val isAuthOn = securityManager.isAuthenticationEnabled()
@@ -102,14 +102,14 @@ private[spark] object AkkaUtils extends Logging {
       |akka.jvm-exit-on-fatal-error = off
       |akka.remote.require-cookie = "$requireCookie"
       |akka.remote.secure-cookie = "$secureCookie"
-      |akka.remote.transport-failure-detector.heartbeat-interval = $akkaHeartBeatInterval s
-      |akka.remote.transport-failure-detector.acceptable-heartbeat-pause = $akkaHeartBeatPauses s
+      |akka.remote.transport-failure-detector.heartbeat-interval = $akkaHeartBeatIntervalS s
+      |akka.remote.transport-failure-detector.acceptable-heartbeat-pause = $akkaHeartBeatPausesS s
       |akka.actor.provider = "akka.remote.RemoteActorRefProvider"
       |akka.remote.netty.tcp.transport-class = "akka.remote.transport.netty.NettyTransport"
       |akka.remote.netty.tcp.hostname = "$host"
       |akka.remote.netty.tcp.port = $port
       |akka.remote.netty.tcp.tcp-nodelay = on
-      |akka.remote.netty.tcp.connection-timeout = $akkaTimeout s
+      |akka.remote.netty.tcp.connection-timeout = $akkaTimeoutS s
       |akka.remote.netty.tcp.maximum-frame-size = ${akkaFrameSize}B
       |akka.remote.netty.tcp.execution-pool-size = $akkaThreads
       |akka.actor.default-dispatcher.throughput = $akkaBatchSize
diff --git a/core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala b/core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala
index 375ed430bde45..2bbfc988a99a8 100644
--- a/core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala
+++ b/core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala
@@ -76,7 +76,7 @@ private[spark] object MetadataCleanerType extends Enumeration {
 // initialization of StreamingContext. It's okay for users trying to configure stuff themselves.
 private[spark] object MetadataCleaner {
   def getDelaySeconds(conf: SparkConf): Int = {
-    conf.getInt("spark.cleaner.ttl", -1)
+    conf.getTimeAsSeconds("spark.cleaner.ttl", "-1").toInt
   }
 
   def getDelaySeconds(
diff --git a/core/src/main/scala/org/apache/spark/util/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala
index a541d660cd5c6..1029b0f9fce1e 100644
--- a/core/src/main/scala/org/apache/spark/util/Utils.scala
+++ b/core/src/main/scala/org/apache/spark/util/Utils.scala
@@ -22,7 +22,7 @@ import java.lang.management.ManagementFactory
 import java.net._
 import java.nio.ByteBuffer
 import java.util.{Properties, Locale, Random, UUID}
-import java.util.concurrent.{ThreadFactory, ConcurrentHashMap, Executors, ThreadPoolExecutor}
+import java.util.concurrent._
 import javax.net.ssl.HttpsURLConnection
 
 import scala.collection.JavaConversions._
@@ -47,6 +47,7 @@ import tachyon.client.{TachyonFS, TachyonFile}
 
 import org.apache.spark._
 import org.apache.spark.deploy.SparkHadoopUtil
+import org.apache.spark.network.util.JavaUtils
 import org.apache.spark.serializer.{DeserializationStream, SerializationStream, SerializerInstance}
 
 /** CallSite represents a place in user code. It can have a short and a long form. */
@@ -612,9 +613,10 @@ private[spark] object Utils extends Logging {
         }
         Utils.setupSecureURLConnection(uc, securityMgr)
 
-        val timeout = conf.getInt("spark.files.fetchTimeout", 60) * 1000
-        uc.setConnectTimeout(timeout)
-        uc.setReadTimeout(timeout)
+        val timeoutMs = 
+          conf.getTimeAsSeconds("spark.files.fetchTimeout", "60s").toInt * 1000
+        uc.setConnectTimeout(timeoutMs)
+        uc.setReadTimeout(timeoutMs)
         uc.connect()
         val in = uc.getInputStream()
         downloadFile(url, in, targetFile, fileOverwrite)
@@ -1018,6 +1020,22 @@ private[spark] object Utils extends Logging {
     )
   }
 
+  /**
+   * Convert a time parameter such as (50s, 100ms, or 250us) to microseconds for internal use. If
+   * no suffix is provided, the passed number is assumed to be in ms.
+   */
+  def timeStringAsMs(str: String): Long = {
+    JavaUtils.timeStringAsMs(str)
+  }
+
+  /**
+   * Convert a time parameter such as (50s, 100ms, or 250us) to microseconds for internal use. If
+   * no suffix is provided, the passed number is assumed to be in seconds.
+   */
+  def timeStringAsSeconds(str: String): Long = {
+    JavaUtils.timeStringAsSec(str)
+  }
+
   /**
    * Convert a Java memory parameter passed to -Xmx (such as 300m or 1g) to a number of megabytes.
    */
diff --git a/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala b/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala
index 3ded1e4af8742..6b3049b28cd5e 100644
--- a/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala
@@ -684,10 +684,11 @@ class ExecutorAllocationManagerSuite extends FunSuite with LocalSparkContext wit
       .set("spark.dynamicAllocation.enabled", "true")
       .set("spark.dynamicAllocation.minExecutors", minExecutors.toString)
       .set("spark.dynamicAllocation.maxExecutors", maxExecutors.toString)
-      .set("spark.dynamicAllocation.schedulerBacklogTimeout", schedulerBacklogTimeout.toString)
+      .set("spark.dynamicAllocation.schedulerBacklogTimeout",
+          s"${schedulerBacklogTimeout.toString}s")
       .set("spark.dynamicAllocation.sustainedSchedulerBacklogTimeout",
-        sustainedSchedulerBacklogTimeout.toString)
-      .set("spark.dynamicAllocation.executorIdleTimeout", executorIdleTimeout.toString)
+        s"${sustainedSchedulerBacklogTimeout.toString}s")
+      .set("spark.dynamicAllocation.executorIdleTimeout", s"${executorIdleTimeout.toString}s")
       .set("spark.dynamicAllocation.testing", "true")
     val sc = new SparkContext(conf)
     contexts += sc
diff --git a/core/src/test/scala/org/apache/spark/network/nio/ConnectionManagerSuite.scala b/core/src/test/scala/org/apache/spark/network/nio/ConnectionManagerSuite.scala
index 716f875d30b8a..02424c59d6831 100644
--- a/core/src/test/scala/org/apache/spark/network/nio/ConnectionManagerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/network/nio/ConnectionManagerSuite.scala
@@ -260,8 +260,8 @@ class ConnectionManagerSuite extends FunSuite {
   test("sendMessageReliably timeout") {
     val clientConf = new SparkConf
     clientConf.set("spark.authenticate", "false")
-    val ackTimeout = 30
-    clientConf.set("spark.core.connection.ack.wait.timeout", s"${ackTimeout}")
+    val ackTimeoutS = 30
+    clientConf.set("spark.core.connection.ack.wait.timeout", s"${ackTimeoutS}s")
 
     val clientSecurityManager = new SecurityManager(clientConf)
     val manager = new ConnectionManager(0, clientConf, clientSecurityManager)
@@ -272,7 +272,7 @@ class ConnectionManagerSuite extends FunSuite {
     val managerServer = new ConnectionManager(0, serverConf, serverSecurityManager)
     managerServer.onReceiveMessage((msg: Message, id: ConnectionManagerId) => {
       // sleep 60 sec > ack timeout for simulating server slow down or hang up
-      Thread.sleep(ackTimeout * 3 * 1000)
+      Thread.sleep(ackTimeoutS * 3 * 1000)
       None
     })
 
@@ -287,7 +287,7 @@ class ConnectionManagerSuite extends FunSuite {
     // Otherwise TimeoutExcepton is thrown from Await.result.
     // We expect TimeoutException is not thrown.
     intercept[IOException] {
-      Await.result(future, (ackTimeout * 2) second)
+      Await.result(future, (ackTimeoutS * 2) second)
     }
 
     manager.stop()
diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala
index 716d12c0762cf..6198cea46ddf8 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala
@@ -17,7 +17,6 @@
 
 package org.apache.spark.scheduler
 
-import java.io.{ObjectInputStream, ObjectOutputStream, IOException}
 import java.util.Random
 
 import scala.collection.mutable.ArrayBuffer
@@ -27,7 +26,7 @@ import org.scalatest.FunSuite
 
 import org.apache.spark._
 import org.apache.spark.executor.TaskMetrics
-import org.apache.spark.util.ManualClock
+import org.apache.spark.util.{ManualClock, Utils}
 
 class FakeDAGScheduler(sc: SparkContext, taskScheduler: FakeTaskScheduler)
   extends DAGScheduler(sc) {
@@ -152,7 +151,7 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
 
   private val conf = new SparkConf
 
-  val LOCALITY_WAIT = conf.getLong("spark.locality.wait", 3000)
+  val LOCALITY_WAIT_MS = conf.getTimeAsMs("spark.locality.wait", "3s")
   val MAX_TASK_FAILURES = 4
 
   override def beforeEach() {
@@ -240,7 +239,7 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
     assert(manager.resourceOffer("exec1", "host1", ANY).get.index === 0)
     assert(manager.resourceOffer("exec1", "host1", PROCESS_LOCAL) == None)
 
-    clock.advance(LOCALITY_WAIT)
+    clock.advance(LOCALITY_WAIT_MS)
     // Offer host1, exec1 again, at NODE_LOCAL level: the node local (task 2) should
     // get chosen before the noPref task
     assert(manager.resourceOffer("exec1", "host1", NODE_LOCAL).get.index == 2)
@@ -251,7 +250,7 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
     // Offer host2, exec3 again, at NODE_LOCAL level: we should get noPref task
     // after failing to find a node_Local task
     assert(manager.resourceOffer("exec2", "host2", NODE_LOCAL) == None)
-    clock.advance(LOCALITY_WAIT)
+    clock.advance(LOCALITY_WAIT_MS)
     assert(manager.resourceOffer("exec2", "host2", NO_PREF).get.index == 3)
   }
 
@@ -292,7 +291,7 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
     // Offer host1 again: nothing should get chosen
     assert(manager.resourceOffer("exec1", "host1", ANY) === None)
 
-    clock.advance(LOCALITY_WAIT)
+    clock.advance(LOCALITY_WAIT_MS)
 
     // Offer host1 again: second task (on host2) should get chosen
     assert(manager.resourceOffer("exec1", "host1", ANY).get.index === 1)
@@ -306,7 +305,7 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
     // Now that we've launched a local task, we should no longer launch the task for host3
     assert(manager.resourceOffer("exec2", "host2", ANY) === None)
 
-    clock.advance(LOCALITY_WAIT)
+    clock.advance(LOCALITY_WAIT_MS)
 
     // After another delay, we can go ahead and launch that task non-locally
     assert(manager.resourceOffer("exec2", "host2", ANY).get.index === 3)
@@ -338,7 +337,7 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
     // nothing should be chosen
     assert(manager.resourceOffer("exec1", "host1", ANY) === None)
 
-    clock.advance(LOCALITY_WAIT * 2)
+    clock.advance(LOCALITY_WAIT_MS * 2)
 
     // task 1 and 2 would be scheduled as nonLocal task
     assert(manager.resourceOffer("exec1", "host1", ANY).get.index === 1)
@@ -528,7 +527,7 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
 
     assert(manager.myLocalityLevels.sameElements(Array(PROCESS_LOCAL, NODE_LOCAL, RACK_LOCAL, ANY)))
     // Set allowed locality to ANY
-    clock.advance(LOCALITY_WAIT * 3)
+    clock.advance(LOCALITY_WAIT_MS * 3)
     // Offer host3
     // No task is scheduled if we restrict locality to RACK_LOCAL
     assert(manager.resourceOffer("execC", "host3", RACK_LOCAL) === None)
@@ -622,12 +621,12 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
     assert(manager.resourceOffer("execA", "host1", NO_PREF).get.index == 1)
 
     manager.speculatableTasks += 1
-    clock.advance(LOCALITY_WAIT)
+    clock.advance(LOCALITY_WAIT_MS)
     // schedule the nonPref task
     assert(manager.resourceOffer("execA", "host1", NO_PREF).get.index === 2)
     // schedule the speculative task
     assert(manager.resourceOffer("execB", "host2", NO_PREF).get.index === 1)
-    clock.advance(LOCALITY_WAIT * 3)
+    clock.advance(LOCALITY_WAIT_MS * 3)
     // schedule non-local tasks
     assert(manager.resourceOffer("execB", "host2", ANY).get.index === 3)
   }
@@ -716,13 +715,13 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging {
     // Valid locality should contain PROCESS_LOCAL, NODE_LOCAL and ANY
     assert(manager.myLocalityLevels.sameElements(Array(PROCESS_LOCAL, NODE_LOCAL, ANY)))
     assert(manager.resourceOffer("execA", "host1", ANY) !== None)
-    clock.advance(LOCALITY_WAIT * 4)
+    clock.advance(LOCALITY_WAIT_MS * 4)
     assert(manager.resourceOffer("execB.2", "host2", ANY) !== None)
     sched.removeExecutor("execA")
     sched.removeExecutor("execB.2")
     manager.executorLost("execA", "host1")
     manager.executorLost("execB.2", "host2")
-    clock.advance(LOCALITY_WAIT * 4)
+    clock.advance(LOCALITY_WAIT_MS * 4)
     sched.addExecutor("execC", "host3")
     manager.executorAdded()
     // Prior to the fix, this line resulted in an ArrayIndexOutOfBoundsException:
diff --git a/core/src/test/scala/org/apache/spark/storage/BlockManagerReplicationSuite.scala b/core/src/test/scala/org/apache/spark/storage/BlockManagerReplicationSuite.scala
index b4de90b65d545..ffa5162a31841 100644
--- a/core/src/test/scala/org/apache/spark/storage/BlockManagerReplicationSuite.scala
+++ b/core/src/test/scala/org/apache/spark/storage/BlockManagerReplicationSuite.scala
@@ -76,7 +76,7 @@ class BlockManagerReplicationSuite extends FunSuite with Matchers with BeforeAnd
     conf.set("spark.storage.unrollMemoryThreshold", "512")
 
     // to make a replication attempt to inactive store fail fast
-    conf.set("spark.core.connection.ack.wait.timeout", "1")
+    conf.set("spark.core.connection.ack.wait.timeout", "1s")
     // to make cached peers refresh frequently
     conf.set("spark.storage.cachedPeersTtl", "10")
 
diff --git a/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
index 449fb87f111c4..fb97e650ff95c 100644
--- a/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
@@ -23,6 +23,7 @@ import java.io.{File, ByteArrayOutputStream, ByteArrayInputStream, FileOutputStr
 import java.net.{BindException, ServerSocket, URI}
 import java.nio.{ByteBuffer, ByteOrder}
 import java.text.DecimalFormatSymbols
+import java.util.concurrent.TimeUnit
 import java.util.Locale
 
 import com.google.common.base.Charsets.UTF_8
@@ -35,7 +36,50 @@ import org.apache.hadoop.fs.Path
 import org.apache.spark.SparkConf
 
 class UtilsSuite extends FunSuite with ResetSystemProperties {
+  
+  test("timeConversion") {
+    // Test -1
+    assert(Utils.timeStringAsSeconds("-1") === -1)
+    
+    // Test zero
+    assert(Utils.timeStringAsSeconds("0") === 0)
+    
+    assert(Utils.timeStringAsSeconds("1") === 1)
+    assert(Utils.timeStringAsSeconds("1s") === 1)
+    assert(Utils.timeStringAsSeconds("1000ms") === 1)
+    assert(Utils.timeStringAsSeconds("1000000us") === 1)
+    assert(Utils.timeStringAsSeconds("1m") === TimeUnit.MINUTES.toSeconds(1))
+    assert(Utils.timeStringAsSeconds("1min") === TimeUnit.MINUTES.toSeconds(1))
+    assert(Utils.timeStringAsSeconds("1h") === TimeUnit.HOURS.toSeconds(1))
+    assert(Utils.timeStringAsSeconds("1d") === TimeUnit.DAYS.toSeconds(1))
+    
+    assert(Utils.timeStringAsMs("1") === 1)
+    assert(Utils.timeStringAsMs("1ms") === 1)
+    assert(Utils.timeStringAsMs("1000us") === 1)
+    assert(Utils.timeStringAsMs("1s") === TimeUnit.SECONDS.toMillis(1))
+    assert(Utils.timeStringAsMs("1m") === TimeUnit.MINUTES.toMillis(1))
+    assert(Utils.timeStringAsMs("1min") === TimeUnit.MINUTES.toMillis(1))
+    assert(Utils.timeStringAsMs("1h") === TimeUnit.HOURS.toMillis(1))
+    assert(Utils.timeStringAsMs("1d") === TimeUnit.DAYS.toMillis(1))
+    
+    // Test invalid strings
+    intercept[NumberFormatException] {
+      Utils.timeStringAsMs("This breaks 600s")
+    }
+
+    intercept[NumberFormatException] {
+      Utils.timeStringAsMs("This breaks 600ds")
+    }
 
+    intercept[NumberFormatException] {
+      Utils.timeStringAsMs("600s This breaks")
+    }
+
+    intercept[NumberFormatException] {
+      Utils.timeStringAsMs("This 123s breaks")
+    }
+  }
+  
   test("bytesToString") {
     assert(Utils.bytesToString(10) === "10.0 B")
     assert(Utils.bytesToString(1500) === "1500.0 B")
diff --git a/docs/configuration.md b/docs/configuration.md
index 7fe11475212b3..7169ec295ef7f 100644
--- a/docs/configuration.md
+++ b/docs/configuration.md
@@ -35,9 +35,19 @@ val conf = new SparkConf()
 val sc = new SparkContext(conf)
 {% endhighlight %}
 
-Note that we can have more than 1 thread in local mode, and in cases like spark streaming, we may actually
-require one to prevent any sort of starvation issues.
+Note that we can have more than 1 thread in local mode, and in cases like Spark Streaming, we may 
+actually require one to prevent any sort of starvation issues.
 
+Properties that specify some time duration should be configured with a unit of time. 
+The following format is accepted:
+ 
+    25ms (milliseconds)
+    5s (seconds)
+    10m or 10min (minutes)
+    3h (hours)
+    5d (days)
+    1y (years)
+    
 ## Dynamically Loading Spark Properties
 In some cases, you may want to avoid hard-coding certain configurations in a `SparkConf`. For
 instance, if you'd like to run the same application with different masters or different
@@ -429,10 +439,10 @@ Apart from these, the following properties are also available, and may be useful
 </tr>
 <tr>
   <td><code>spark.shuffle.io.retryWait</code></td>
-  <td>5</td>
+  <td>5s</td>
   <td>
-    (Netty only) Seconds to wait between retries of fetches. The maximum delay caused by retrying
-    is simply <code>maxRetries * retryWait</code>, by default 15 seconds.
+    (Netty only) How long to wait between retries of fetches. The maximum delay caused by retrying
+    is 15 seconds by default, calculated as <code>maxRetries * retryWait</code>.
   </td>
 </tr>
 <tr>
@@ -732,17 +742,17 @@ Apart from these, the following properties are also available, and may be useful
 </tr>
 <tr>
     <td><code>spark.executor.heartbeatInterval</code></td>
-    <td>10000</td>
-    <td>Interval (milliseconds) between each executor's heartbeats to the driver.  Heartbeats let
+    <td>10s</td>
+    <td>Interval between each executor's heartbeats to the driver.  Heartbeats let
     the driver know that the executor is still alive and update it with metrics for in-progress
     tasks.</td>
 </tr>
 <tr>
   <td><code>spark.files.fetchTimeout</code></td>
-  <td>60</td>
+  <td>60s</td>
   <td>
     Communication timeout to use when fetching files added through SparkContext.addFile() from
-    the driver, in seconds.
+    the driver.
   </td>
 </tr>
 <tr>
@@ -853,11 +863,11 @@ Apart from these, the following properties are also available, and may be useful
 </tr>
 <tr>
   <td><code>spark.akka.heartbeat.interval</code></td>
-  <td>1000</td>
+  <td>1000s</td>
   <td>
     This is set to a larger value to disable the transport failure detector that comes built in to 
     Akka. It can be enabled again, if you plan to use this feature (Not recommended). A larger 
-    interval value in seconds reduces network overhead and a smaller value ( ~ 1 s) might be more 
+    interval value reduces network overhead and a smaller value ( ~ 1 s) might be more 
     informative for Akka's failure detector. Tune this in combination of `spark.akka.heartbeat.pauses` 
     if you need to. A likely positive use case for using failure detector would be: a sensistive 
     failure detector can help evict rogue executors quickly. However this is usually not the case 
@@ -868,11 +878,11 @@ Apart from these, the following properties are also available, and may be useful
 </tr>
 <tr>
   <td><code>spark.akka.heartbeat.pauses</code></td>
-  <td>6000</td>
+  <td>6000s</td>
   <td>
      This is set to a larger value to disable the transport failure detector that comes built in to Akka.
      It can be enabled again, if you plan to use this feature (Not recommended). Acceptable heart 
-     beat pause in seconds for Akka. This can be used to control sensitivity to GC pauses. Tune
+     beat pause for Akka. This can be used to control sensitivity to GC pauses. Tune
      this along with `spark.akka.heartbeat.interval` if you need to.
   </td>
 </tr>
@@ -886,9 +896,9 @@ Apart from these, the following properties are also available, and may be useful
 </tr>
 <tr>
   <td><code>spark.akka.timeout</code></td>
-  <td>100</td>
+  <td>100s</td>
   <td>
-    Communication timeout between Spark nodes, in seconds.
+    Communication timeout between Spark nodes.
   </td>
 </tr>
 <tr>
@@ -938,10 +948,10 @@ Apart from these, the following properties are also available, and may be useful
 </tr>
 <tr>
   <td><code>spark.network.timeout</code></td>
-  <td>120</td>
+  <td>120s</td>
   <td>
-    Default timeout for all network interactions, in seconds. This config will be used in
-    place of <code>spark.core.connection.ack.wait.timeout</code>, <code>spark.akka.timeout</code>,
+    Default timeout for all network interactions. This config will be used in place of 
+    <code>spark.core.connection.ack.wait.timeout</code>, <code>spark.akka.timeout</code>,
     <code>spark.storage.blockManagerSlaveTimeoutMs</code> or
     <code>spark.shuffle.io.connectionTimeout</code>, if they are not configured.
   </td>
@@ -989,9 +999,9 @@ Apart from these, the following properties are also available, and may be useful
 </tr>
 <tr>
   <td><code>spark.locality.wait</code></td>
-  <td>3000</td>
+  <td>3s</td>
   <td>
-    Number of milliseconds to wait to launch a data-local task before giving up and launching it
+    How long to wait to launch a data-local task before giving up and launching it
     on a less-local node. The same wait will be used to step through multiple locality levels
     (process-local, node-local, rack-local and then any). It is also possible to customize the
     waiting time for each level by setting <code>spark.locality.wait.node</code>, etc.
@@ -1024,10 +1034,9 @@ Apart from these, the following properties are also available, and may be useful
 </tr>
 <tr>
   <td><code>spark.scheduler.maxRegisteredResourcesWaitingTime</code></td>
-  <td>30000</td>
+  <td>30s</td>
   <td>
-    Maximum amount of time to wait for resources to register before scheduling begins
-    (in milliseconds).
+    Maximum amount of time to wait for resources to register before scheduling begins.
   </td>
 </tr>
 <tr>
@@ -1054,10 +1063,9 @@ Apart from these, the following properties are also available, and may be useful
 </tr>
 <tr>
   <td><code>spark.scheduler.revive.interval</code></td>
-  <td>1000</td>
+  <td>1s</td>
   <td>
-    The interval length for the scheduler to revive the worker resource offers to run tasks
-    (in milliseconds).
+    The interval length for the scheduler to revive the worker resource offers to run tasks.
   </td>
 </tr>
 <tr>
@@ -1070,9 +1078,9 @@ Apart from these, the following properties are also available, and may be useful
 </tr>
 <tr>
   <td><code>spark.speculation.interval</code></td>
-  <td>100</td>
+  <td>100ms</td>
   <td>
-    How often Spark will check for tasks to speculate, in milliseconds.
+    How often Spark will check for tasks to speculate.
   </td>
 </tr>
 <tr>
@@ -1127,10 +1135,10 @@ Apart from these, the following properties are also available, and may be useful
 </tr>
 <tr>
   <td><code>spark.dynamicAllocation.executorIdleTimeout</code></td>
-  <td>600</td>
+  <td>600s</td>
   <td>
-    If dynamic allocation is enabled and an executor has been idle for more than this duration
-    (in seconds), the executor will be removed. For more detail, see this
+    If dynamic allocation is enabled and an executor has been idle for more than this duration, 
+    the executor will be removed. For more detail, see this
     <a href="job-scheduling.html#resource-allocation-policy">description</a>.
   </td>
 </tr>
@@ -1157,10 +1165,10 @@ Apart from these, the following properties are also available, and may be useful
 </tr>
 <tr>
   <td><code>spark.dynamicAllocation.schedulerBacklogTimeout</code></td>
-  <td>5</td>
+  <td>5s</td>
   <td>
     If dynamic allocation is enabled and there have been pending tasks backlogged for more than
-    this duration (in seconds), new executors will be requested. For more detail, see this
+    this duration, new executors will be requested. For more detail, see this
     <a href="job-scheduling.html#resource-allocation-policy">description</a>.
   </td>
 </tr>
@@ -1215,18 +1223,18 @@ Apart from these, the following properties are also available, and may be useful
 </tr>
 <tr>
   <td><code>spark.core.connection.ack.wait.timeout</code></td>
-  <td>60</td>
+  <td>60s</td>
   <td>
-    Number of seconds for the connection to wait for ack to occur before timing
+    How long for the connection to wait for ack to occur before timing
     out and giving up. To avoid unwilling timeout caused by long pause like GC,
     you can set larger value.
   </td>
 </tr>
 <tr>
   <td><code>spark.core.connection.auth.wait.timeout</code></td>
-  <td>30</td>
+  <td>30s</td>
   <td>
-    Number of seconds for the connection to wait for authentication to occur before timing
+    How long for the connection to wait for authentication to occur before timing
     out and giving up.
   </td>
 </tr>
@@ -1347,9 +1355,9 @@ Apart from these, the following properties are also available, and may be useful
 <tr><th>Property Name</th><th>Default</th><th>Meaning</th></tr>
 <tr>
   <td><code>spark.streaming.blockInterval</code></td>
-  <td>200</td>
+  <td>200ms</td>
   <td>
-    Interval (milliseconds) at which data received by Spark Streaming receivers is chunked
+    Interval at which data received by Spark Streaming receivers is chunked
     into blocks of data before storing them in Spark. Minimum recommended - 50 ms. See the
     <a href="streaming-programming-guide.html#level-of-parallelism-in-data-receiving">performance
      tuning</a> section in the Spark Streaming programing guide for more details.
diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md
index ed5bb263a5809..853c9f26b0ec9 100644
--- a/docs/running-on-yarn.md
+++ b/docs/running-on-yarn.md
@@ -48,9 +48,9 @@ Most of the configs are the same for Spark on YARN as for other deployment modes
 </tr>
 <tr>
   <td><code>spark.yarn.am.waitTime</code></td>
-  <td>100000</td>
+  <td>100s</td>
   <td>
-    In yarn-cluster mode, time in milliseconds for the application master to wait for the
+    In yarn-cluster mode, time for the application master to wait for the
     SparkContext to be initialized. In yarn-client mode, time for the application master to wait
     for the driver to connect to it.
   </td>
diff --git a/network/common/src/main/java/org/apache/spark/network/util/JavaUtils.java b/network/common/src/main/java/org/apache/spark/network/util/JavaUtils.java
index 73da9b7346f4d..b6fbace509a0e 100644
--- a/network/common/src/main/java/org/apache/spark/network/util/JavaUtils.java
+++ b/network/common/src/main/java/org/apache/spark/network/util/JavaUtils.java
@@ -21,9 +21,13 @@
 import java.io.File;
 import java.io.IOException;
 import java.nio.ByteBuffer;
+import java.util.concurrent.TimeUnit;
+import java.util.regex.Matcher;
+import java.util.regex.Pattern;
 
 import com.google.common.base.Charsets;
 import com.google.common.base.Preconditions;
+import com.google.common.collect.ImmutableMap;
 import io.netty.buffer.Unpooled;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
@@ -121,4 +125,66 @@ private static boolean isSymlink(File file) throws IOException {
     }
     return !fileInCanonicalDir.getCanonicalFile().equals(fileInCanonicalDir.getAbsoluteFile());
   }
+
+  private static ImmutableMap<String, TimeUnit> timeSuffixes = 
+    ImmutableMap.<String, TimeUnit>builder()
+      .put("us", TimeUnit.MICROSECONDS)
+      .put("ms", TimeUnit.MILLISECONDS)
+      .put("s", TimeUnit.SECONDS)
+      .put("m", TimeUnit.MINUTES)
+      .put("min", TimeUnit.MINUTES)
+      .put("h", TimeUnit.HOURS)
+      .put("d", TimeUnit.DAYS)
+      .build();
+
+  /**
+   * Convert a passed time string (e.g. 50s, 100ms, or 250us) to a time count for
+   * internal use. If no suffix is provided a direct conversion is attempted.
+   */
+  private static long parseTimeString(String str, TimeUnit unit) {
+    String lower = str.toLowerCase().trim();
+    
+    try {
+      String suffix;
+      long val;
+      Matcher m = Pattern.compile("(-?[0-9]+)([a-z]+)?").matcher(lower);
+      if (m.matches()) {
+        val = Long.parseLong(m.group(1));
+        suffix = m.group(2);
+      } else {
+        throw new NumberFormatException("Failed to parse time string: " + str);
+      }
+      
+      // Check for invalid suffixes
+      if (suffix != null && !timeSuffixes.containsKey(suffix)) {
+        throw new NumberFormatException("Invalid suffix: \"" + suffix + "\"");
+      }
+      
+      // If suffix is valid use that, otherwise none was provided and use the default passed
+      return unit.convert(val, suffix != null ? timeSuffixes.get(suffix) : unit);
+    } catch (NumberFormatException e) {
+      String timeError = "Time must be specified as seconds (s), " +
+              "milliseconds (ms), microseconds (us), minutes (m or min) hour (h), or day (d). " +
+              "E.g. 50s, 100ms, or 250us.";
+      
+      throw new NumberFormatException(timeError + "\n" + e.getMessage());
+    }
+  }
+  
+  /**
+   * Convert a time parameter such as (50s, 100ms, or 250us) to milliseconds for internal use. If
+   * no suffix is provided, the passed number is assumed to be in ms.
+   */
+  public static long timeStringAsMs(String str) {
+    return parseTimeString(str, TimeUnit.MILLISECONDS);
+  }
+
+  /**
+   * Convert a time parameter such as (50s, 100ms, or 250us) to seconds for internal use. If
+   * no suffix is provided, the passed number is assumed to be in seconds.
+   */
+  public static long timeStringAsSec(String str) {
+    return parseTimeString(str, TimeUnit.SECONDS);
+  }
+
 }
diff --git a/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java b/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java
index 2eaf3b71d9a49..0aef7f1987315 100644
--- a/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java
+++ b/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java
@@ -37,8 +37,11 @@ public boolean preferDirectBufs() {
 
   /** Connect timeout in milliseconds. Default 120 secs. */
   public int connectionTimeoutMs() {
-    int defaultTimeout = conf.getInt("spark.network.timeout", 120);
-    return conf.getInt("spark.shuffle.io.connectionTimeout", defaultTimeout) * 1000;
+    long defaultNetworkTimeoutS = JavaUtils.timeStringAsSec(
+      conf.get("spark.network.timeout", "120s"));
+    long defaultTimeoutMs = JavaUtils.timeStringAsSec(
+      conf.get("spark.shuffle.io.connectionTimeout", defaultNetworkTimeoutS + "s")) * 1000;
+    return (int) defaultTimeoutMs;
   }
 
   /** Number of concurrent connections between two nodes for fetching data. */
@@ -68,7 +71,9 @@ public int numConnectionsPerPeer() {
   public int sendBuf() { return conf.getInt("spark.shuffle.io.sendBuffer", -1); }
 
   /** Timeout for a single round trip of SASL token exchange, in milliseconds. */
-  public int saslRTTimeoutMs() { return conf.getInt("spark.shuffle.sasl.timeout", 30) * 1000; }
+  public int saslRTTimeoutMs() {
+    return (int) JavaUtils.timeStringAsSec(conf.get("spark.shuffle.sasl.timeout", "30s")) * 1000;
+  }
 
   /**
    * Max number of times we will try IO exceptions (such as connection timeouts) per request.
@@ -80,7 +85,9 @@ public int numConnectionsPerPeer() {
    * Time (in milliseconds) that we will wait in order to perform a retry after an IOException.
    * Only relevant if maxIORetries &gt; 0.
    */
-  public int ioRetryWaitTimeMs() { return conf.getInt("spark.shuffle.io.retryWait", 5) * 1000; }
+  public int ioRetryWaitTimeMs() {
+    return (int) JavaUtils.timeStringAsSec(conf.get("spark.shuffle.io.retryWait", "5s")) * 1000;
+  }
 
   /**
    * Minimum size of a block that we should start using memory map rather than reading in through
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/receiver/BlockGenerator.scala b/streaming/src/main/scala/org/apache/spark/streaming/receiver/BlockGenerator.scala
index 42514d8b47dcf..f4963a78e1d18 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/receiver/BlockGenerator.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/receiver/BlockGenerator.scala
@@ -24,7 +24,7 @@ import scala.collection.mutable.ArrayBuffer
 import org.apache.spark.{Logging, SparkConf}
 import org.apache.spark.storage.StreamBlockId
 import org.apache.spark.streaming.util.RecurringTimer
-import org.apache.spark.util.SystemClock
+import org.apache.spark.util.{SystemClock, Utils}
 
 /** Listener object for BlockGenerator events */
 private[streaming] trait BlockGeneratorListener {
@@ -79,9 +79,9 @@ private[streaming] class BlockGenerator(
   private case class Block(id: StreamBlockId, buffer: ArrayBuffer[Any])
 
   private val clock = new SystemClock()
-  private val blockInterval = conf.getLong("spark.streaming.blockInterval", 200)
+  private val blockIntervalMs = conf.getTimeAsMs("spark.streaming.blockInterval", "200ms")
   private val blockIntervalTimer =
-    new RecurringTimer(clock, blockInterval, updateCurrentBuffer, "BlockGenerator")
+    new RecurringTimer(clock, blockIntervalMs, updateCurrentBuffer, "BlockGenerator")
   private val blockQueueSize = conf.getInt("spark.streaming.blockQueueSize", 10)
   private val blocksForPushing = new ArrayBlockingQueue[Block](blockQueueSize)
   private val blockPushingThread = new Thread() { override def run() { keepPushingBlocks() } }
@@ -132,7 +132,7 @@ private[streaming] class BlockGenerator(
       val newBlockBuffer = currentBuffer
       currentBuffer = new ArrayBuffer[Any]
       if (newBlockBuffer.size > 0) {
-        val blockId = StreamBlockId(receiverId, time - blockInterval)
+        val blockId = StreamBlockId(receiverId, time - blockIntervalMs)
         val newBlock = new Block(blockId, newBlockBuffer)
         listener.onGenerateBlock(blockId)
         blocksForPushing.put(newBlock)  // put is blocking when queue is full
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala
index 4946806d2ee95..58e56638a2dca 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala
@@ -24,7 +24,7 @@ import akka.actor.{ActorRef, Props, Actor}
 import org.apache.spark.{SparkEnv, Logging}
 import org.apache.spark.streaming.{Checkpoint, CheckpointWriter, Time}
 import org.apache.spark.streaming.util.RecurringTimer
-import org.apache.spark.util.{Clock, ManualClock}
+import org.apache.spark.util.{Clock, ManualClock, Utils}
 
 /** Event classes for JobGenerator */
 private[scheduler] sealed trait JobGeneratorEvent
@@ -104,17 +104,15 @@ class JobGenerator(jobScheduler: JobScheduler) extends Logging {
     if (processReceivedData) {
       logInfo("Stopping JobGenerator gracefully")
       val timeWhenStopStarted = System.currentTimeMillis()
-      val stopTimeout = conf.getLong(
-        "spark.streaming.gracefulStopTimeout",
-        10 * ssc.graph.batchDuration.milliseconds
-      )
+      val stopTimeoutMs = conf.getTimeAsMs(
+        "spark.streaming.gracefulStopTimeout", s"${10 * ssc.graph.batchDuration.milliseconds}ms")
       val pollTime = 100
 
       // To prevent graceful stop to get stuck permanently
       def hasTimedOut: Boolean = {
-        val timedOut = (System.currentTimeMillis() - timeWhenStopStarted) > stopTimeout
+        val timedOut = (System.currentTimeMillis() - timeWhenStopStarted) > stopTimeoutMs
         if (timedOut) {
-          logWarning("Timed out while stopping the job generator (timeout = " + stopTimeout + ")")
+          logWarning("Timed out while stopping the job generator (timeout = " + stopTimeoutMs + ")")
         }
         timedOut
       }
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala
index 10c35cba8dc53..91261a9db7360 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala
@@ -131,11 +131,11 @@ class ReceiverSuite extends TestSuiteBase with Timeouts with Serializable {
 
   test("block generator") {
     val blockGeneratorListener = new FakeBlockGeneratorListener
-    val blockInterval = 200
-    val conf = new SparkConf().set("spark.streaming.blockInterval", blockInterval.toString)
+    val blockIntervalMs = 200
+    val conf = new SparkConf().set("spark.streaming.blockInterval", s"${blockIntervalMs}ms")
     val blockGenerator = new BlockGenerator(blockGeneratorListener, 1, conf)
     val expectedBlocks = 5
-    val waitTime = expectedBlocks * blockInterval + (blockInterval / 2)
+    val waitTime = expectedBlocks * blockIntervalMs + (blockIntervalMs / 2)
     val generatedData = new ArrayBuffer[Int]
 
     // Generate blocks
@@ -157,15 +157,15 @@ class ReceiverSuite extends TestSuiteBase with Timeouts with Serializable {
 
   test("block generator throttling") {
     val blockGeneratorListener = new FakeBlockGeneratorListener
-    val blockInterval = 100
+    val blockIntervalMs = 100
     val maxRate = 100
-    val conf = new SparkConf().set("spark.streaming.blockInterval", blockInterval.toString).
+    val conf = new SparkConf().set("spark.streaming.blockInterval", s"${blockIntervalMs}ms").
       set("spark.streaming.receiver.maxRate", maxRate.toString)
     val blockGenerator = new BlockGenerator(blockGeneratorListener, 1, conf)
     val expectedBlocks = 20
-    val waitTime = expectedBlocks * blockInterval
+    val waitTime = expectedBlocks * blockIntervalMs
     val expectedMessages = maxRate * waitTime / 1000
-    val expectedMessagesPerBlock = maxRate * blockInterval / 1000
+    val expectedMessagesPerBlock = maxRate * blockIntervalMs / 1000
     val generatedData = new ArrayBuffer[Int]
 
     // Generate blocks
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala
index d1bbf39dc7897..58353a5f97c8a 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala
@@ -73,9 +73,9 @@ class StreamingContextSuite extends FunSuite with BeforeAndAfter with Timeouts w
 
   test("from conf with settings") {
     val myConf = SparkContext.updatedConf(new SparkConf(false), master, appName)
-    myConf.set("spark.cleaner.ttl", "10")
+    myConf.set("spark.cleaner.ttl", "10s")
     ssc = new StreamingContext(myConf, batchDuration)
-    assert(ssc.conf.getInt("spark.cleaner.ttl", -1) === 10)
+    assert(ssc.conf.getTimeAsSeconds("spark.cleaner.ttl", "-1") === 10)
   }
 
   test("from existing SparkContext") {
@@ -85,24 +85,26 @@ class StreamingContextSuite extends FunSuite with BeforeAndAfter with Timeouts w
 
   test("from existing SparkContext with settings") {
     val myConf = SparkContext.updatedConf(new SparkConf(false), master, appName)
-    myConf.set("spark.cleaner.ttl", "10")
+    myConf.set("spark.cleaner.ttl", "10s")
     ssc = new StreamingContext(myConf, batchDuration)
-    assert(ssc.conf.getInt("spark.cleaner.ttl", -1) === 10)
+    assert(ssc.conf.getTimeAsSeconds("spark.cleaner.ttl", "-1") === 10)
   }
 
   test("from checkpoint") {
     val myConf = SparkContext.updatedConf(new SparkConf(false), master, appName)
-    myConf.set("spark.cleaner.ttl", "10")
+    myConf.set("spark.cleaner.ttl", "10s")
     val ssc1 = new StreamingContext(myConf, batchDuration)
     addInputStream(ssc1).register()
     ssc1.start()
     val cp = new Checkpoint(ssc1, Time(1000))
-    assert(cp.sparkConfPairs.toMap.getOrElse("spark.cleaner.ttl", "-1") === "10")
+    assert(
+      Utils.timeStringAsSeconds(cp.sparkConfPairs
+          .toMap.getOrElse("spark.cleaner.ttl", "-1")) === 10)
     ssc1.stop()
     val newCp = Utils.deserialize[Checkpoint](Utils.serialize(cp))
-    assert(newCp.createSparkConf().getInt("spark.cleaner.ttl", -1) === 10)
+    assert(newCp.createSparkConf().getTimeAsSeconds("spark.cleaner.ttl", "-1") === 10)
     ssc = new StreamingContext(null, newCp, null)
-    assert(ssc.conf.getInt("spark.cleaner.ttl", -1) === 10)
+    assert(ssc.conf.getTimeAsSeconds("spark.cleaner.ttl", "-1") === 10)
   }
 
   test("start and stop state check") {
@@ -176,7 +178,7 @@ class StreamingContextSuite extends FunSuite with BeforeAndAfter with Timeouts w
 
   test("stop gracefully") {
     val conf = new SparkConf().setMaster(master).setAppName(appName)
-    conf.set("spark.cleaner.ttl", "3600")
+    conf.set("spark.cleaner.ttl", "3600s")
     sc = new SparkContext(conf)
     for (i <- 1 to 4) {
       logInfo("==================================\n\n\n")
@@ -207,7 +209,7 @@ class StreamingContextSuite extends FunSuite with BeforeAndAfter with Timeouts w
 
   test("stop slow receiver gracefully") {
     val conf = new SparkConf().setMaster(master).setAppName(appName)
-    conf.set("spark.streaming.gracefulStopTimeout", "20000")
+    conf.set("spark.streaming.gracefulStopTimeout", "20000s")
     sc = new SparkContext(conf)
     logInfo("==================================\n\n\n")
     ssc = new StreamingContext(sc, Milliseconds(100))
diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
index 26259cee77151..c357b7ae9d4da 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
@@ -296,7 +296,7 @@ private[spark] class ApplicationMaster(
 
     // we want to be reasonably responsive without causing too many requests to RM.
     val schedulerInterval =
-      sparkConf.getLong("spark.yarn.scheduler.heartbeat.interval-ms", 5000)
+      sparkConf.getTimeAsMs("spark.yarn.scheduler.heartbeat.interval-ms", "5s")
 
     // must be <= expiryInterval / 2.
     val interval = math.max(0, math.min(expiryInterval / 2, schedulerInterval))
@@ -379,7 +379,8 @@ private[spark] class ApplicationMaster(
         logWarning(
           "spark.yarn.applicationMaster.waitTries is deprecated, use spark.yarn.am.waitTime")
       }
-      val totalWaitTime = sparkConf.getLong("spark.yarn.am.waitTime", waitTries.getOrElse(100000L))
+      val totalWaitTime = sparkConf.getTimeAsMs("spark.yarn.am.waitTime", 
+        s"${waitTries.getOrElse(100000L)}ms")
       val deadline = System.currentTimeMillis() + totalWaitTime
 
       while (sparkContextRef.get() == null && System.currentTimeMillis < deadline && !finished) {
@@ -404,8 +405,8 @@ private[spark] class ApplicationMaster(
 
     // Spark driver should already be up since it launched us, but we don't want to
     // wait forever, so wait 100 seconds max to match the cluster mode setting.
-    val totalWaitTime = sparkConf.getLong("spark.yarn.am.waitTime", 100000L)
-    val deadline = System.currentTimeMillis + totalWaitTime
+    val totalWaitTimeMs = sparkConf.getTimeAsMs("spark.yarn.am.waitTime", "100s")
+    val deadline = System.currentTimeMillis + totalWaitTimeMs
 
     while (!driverUp && !finished && System.currentTimeMillis < deadline) {
       try {

From d7f2c198678d1f5ffc1c6da3a6fb189b0a4ef070 Mon Sep 17 00:00:00 2001
From: hlin09 <hlin09pu@gmail.com>
Date: Mon, 13 Apr 2015 16:53:50 -0700
Subject: [PATCH 87/95] [SPARK-6881][SparkR] Changes the checkpoint directory
 name.

Author: hlin09 <hlin09pu@gmail.com>

Closes #5493 from hlin09/fixCheckpointDir and squashes the following commits:

e67fc40 [hlin09] Change to temp dir.
1f7ed9e [hlin09] Change the checkpoint dir name.
---
 R/pkg/R/RDD.R               | 2 +-
 R/pkg/R/context.R           | 2 +-
 R/pkg/inst/tests/test_rdd.R | 5 +++--
 3 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/R/pkg/R/RDD.R b/R/pkg/R/RDD.R
index 604ad03c407b9..d6a75007a6ad7 100644
--- a/R/pkg/R/RDD.R
+++ b/R/pkg/R/RDD.R
@@ -279,7 +279,7 @@ setMethod("unpersist",
 #' @examples
 #'\dontrun{
 #' sc <- sparkR.init()
-#' setCheckpointDir(sc, "checkpoints")
+#' setCheckpointDir(sc, "checkpoint")
 #' rdd <- parallelize(sc, 1:10, 2L)
 #' checkpoint(rdd)
 #'}
diff --git a/R/pkg/R/context.R b/R/pkg/R/context.R
index 2fc0bb294bcce..ebbb8fba1052d 100644
--- a/R/pkg/R/context.R
+++ b/R/pkg/R/context.R
@@ -216,7 +216,7 @@ broadcast <- function(sc, object) {
 #' @examples
 #'\dontrun{
 #' sc <- sparkR.init()
-#' setCheckpointDir(sc, "~/checkpoints")
+#' setCheckpointDir(sc, "~/checkpoint")
 #' rdd <- parallelize(sc, 1:2, 2L)
 #' checkpoint(rdd)
 #'}
diff --git a/R/pkg/inst/tests/test_rdd.R b/R/pkg/inst/tests/test_rdd.R
index f75e0817b9406..b76e4db03e715 100644
--- a/R/pkg/inst/tests/test_rdd.R
+++ b/R/pkg/inst/tests/test_rdd.R
@@ -141,7 +141,8 @@ test_that("PipelinedRDD support actions: cache(), persist(), unpersist(), checkp
   unpersist(rdd2)
   expect_false(rdd2@env$isCached)
 
-  setCheckpointDir(sc, "checkpoints")
+  tempDir <- tempfile(pattern = "checkpoint")
+  setCheckpointDir(sc, tempDir)
   checkpoint(rdd2)
   expect_true(rdd2@env$isCheckpointed)
 
@@ -152,7 +153,7 @@ test_that("PipelinedRDD support actions: cache(), persist(), unpersist(), checkp
   # make sure the data is collectable
   collect(rdd2)
 
-  unlink("checkpoints")
+  unlink(tempDir)
 })
 
 test_that("reduce on RDD", {

From 5b8b324f33e857b95de65031334846a7ca26fa60 Mon Sep 17 00:00:00 2001
From: Liang-Chi Hsieh <viirya@gmail.com>
Date: Mon, 13 Apr 2015 18:15:29 -0700
Subject: [PATCH 88/95] [SPARK-6303][SQL] Remove unnecessary Average in
 GeneratedAggregate

Because `Average` is a `PartialAggregate`, we never get a `Average` node when reaching `HashAggregation` to prepare `GeneratedAggregate`.

That is why in SQLQuerySuite there is already a test for `avg` with codegen. And it works.

But we can find a case in `GeneratedAggregate` to deal with `Average`. Based on the above, we actually never execute this case.

So we can remove this case from `GeneratedAggregate`.

Author: Liang-Chi Hsieh <viirya@gmail.com>

Closes #4996 from viirya/add_average_codegened and squashes the following commits:

621c12f [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into add_average_codegened
368cfbc [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into add_average_codegened
74926d1 [Liang-Chi Hsieh] Add Average in canBeCodeGened lists.
---
 .../sql/execution/GeneratedAggregate.scala    | 45 -------------------
 1 file changed, 45 deletions(-)

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
index 95176e425132d..b510cf033c4a4 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
@@ -153,51 +153,6 @@ case class GeneratedAggregate(
 
         AggregateEvaluation(currentSum :: Nil, initialValue :: Nil, updateFunction :: Nil, result)
         
-      case a @ Average(expr) =>
-        val calcType =
-          expr.dataType match {
-            case DecimalType.Fixed(_, _) =>
-              DecimalType.Unlimited
-            case _ =>
-              expr.dataType
-          }
-
-        val currentCount = AttributeReference("currentCount", LongType, nullable = false)()
-        val currentSum = AttributeReference("currentSum", calcType, nullable = false)()
-        val initialCount = Literal(0L)
-        val initialSum = Cast(Literal(0L), calcType)
-
-        // If we're evaluating UnscaledValue(x), we can do Count on x directly, since its
-        // UnscaledValue will be null if and only if x is null; helps with Average on decimals
-        val toCount = expr match {
-          case UnscaledValue(e) => e
-          case _ => expr
-        }
-
-        val updateCount = If(IsNotNull(toCount), Add(currentCount, Literal(1L)), currentCount)
-        val updateSum = Coalesce(Add(Cast(expr, calcType), currentSum) :: currentSum :: Nil)
-
-        val result =
-          expr.dataType match {
-            case DecimalType.Fixed(_, _) =>
-              If(EqualTo(currentCount, Literal(0L)),
-                Literal.create(null, a.dataType),
-                Cast(Divide(
-                  Cast(currentSum, DecimalType.Unlimited),
-                  Cast(currentCount, DecimalType.Unlimited)), a.dataType))
-            case _ =>
-              If(EqualTo(currentCount, Literal(0L)),
-                Literal.create(null, a.dataType),
-                Divide(Cast(currentSum, a.dataType), Cast(currentCount, a.dataType)))
-          }
-
-        AggregateEvaluation(
-          currentCount :: currentSum :: Nil,
-          initialCount :: initialSum :: Nil,
-          updateCount :: updateSum :: Nil,
-          result
-        )
-
       case m @ Max(expr) =>
         val currentMax = AttributeReference("currentMax", expr.dataType, nullable = true)()
         val initialValue = Literal.create(null, expr.dataType)

From 4898dfa464be55772e3f9db10c48adcb3cfc9a3d Mon Sep 17 00:00:00 2001
From: Liang-Chi Hsieh <viirya@gmail.com>
Date: Mon, 13 Apr 2015 18:16:33 -0700
Subject: [PATCH 89/95] [SPARK-6877][SQL] Add code generation support for Min

Currently `min` is not supported in code generation. This pr adds the support for it.

Author: Liang-Chi Hsieh <viirya@gmail.com>

Closes #5487 from viirya/add_min_codegen and squashes the following commits:

0ddec23 [Liang-Chi Hsieh] Add code generation support for Min.
---
 .../sql/catalyst/expressions/arithmetic.scala | 45 +++++++++++++++++++
 .../expressions/codegen/CodeGenerator.scala   | 24 ++++++++++
 .../ExpressionEvaluationSuite.scala           | 10 +++++
 .../sql/execution/GeneratedAggregate.scala    | 13 ++++++
 .../spark/sql/execution/SparkStrategies.scala |  2 +-
 .../org/apache/spark/sql/SQLQuerySuite.scala  | 14 ++++--
 6 files changed, 104 insertions(+), 4 deletions(-)

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala
index 1f6526ef66c56..566b34f7c3a6a 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala
@@ -369,6 +369,51 @@ case class MaxOf(left: Expression, right: Expression) extends Expression {
   override def toString: String = s"MaxOf($left, $right)"
 }
 
+case class MinOf(left: Expression, right: Expression) extends Expression {
+  type EvaluatedType = Any
+
+  override def foldable: Boolean = left.foldable && right.foldable
+
+  override def nullable: Boolean = left.nullable && right.nullable
+
+  override def children: Seq[Expression] = left :: right :: Nil
+
+  override lazy val resolved =
+    left.resolved && right.resolved &&
+    left.dataType == right.dataType
+
+  override def dataType: DataType = {
+    if (!resolved) {
+      throw new UnresolvedException(this,
+        s"datatype. Can not resolve due to differing types ${left.dataType}, ${right.dataType}")
+    }
+    left.dataType
+  }
+
+  lazy val ordering = left.dataType match {
+    case i: NativeType => i.ordering.asInstanceOf[Ordering[Any]]
+    case other => sys.error(s"Type $other does not support ordered operations")
+  }
+
+  override def eval(input: Row): Any = {
+    val evalE1 = left.eval(input)
+    val evalE2 = right.eval(input)
+    if (evalE1 == null) {
+      evalE2
+    } else if (evalE2 == null) {
+      evalE1
+    } else {
+      if (ordering.compare(evalE1, evalE2) < 0) {
+        evalE1
+      } else {
+        evalE2
+      }
+    }
+  }
+
+  override def toString: String = s"MinOf($left, $right)"
+}
+
 /**
  * A function that get the absolute value of the numeric value.
  */
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
index aac56e1568332..d141354a0f427 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
@@ -524,6 +524,30 @@ abstract class CodeGenerator[InType <: AnyRef, OutType <: AnyRef] extends Loggin
           }
         """.children
 
+      case MinOf(e1, e2) =>
+        val eval1 = expressionEvaluator(e1)
+        val eval2 = expressionEvaluator(e2)
+
+        eval1.code ++ eval2.code ++
+        q"""
+          var $nullTerm = false
+          var $primitiveTerm: ${termForType(e1.dataType)} = ${defaultPrimitive(e1.dataType)}
+
+          if (${eval1.nullTerm}) {
+            $nullTerm = ${eval2.nullTerm}
+            $primitiveTerm = ${eval2.primitiveTerm}
+          } else if (${eval2.nullTerm}) {
+            $nullTerm = ${eval1.nullTerm}
+            $primitiveTerm = ${eval1.primitiveTerm}
+          } else {
+            if (${eval1.primitiveTerm} < ${eval2.primitiveTerm}) {
+              $primitiveTerm = ${eval1.primitiveTerm}
+            } else {
+              $primitiveTerm = ${eval2.primitiveTerm}
+            }
+          }
+        """.children
+
       case UnscaledValue(child) =>
         val childEval = expressionEvaluator(child)
 
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala
index d2b1090a0cdd5..d4362a91d992c 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala
@@ -233,6 +233,16 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite {
     checkEvaluation(MaxOf(2, Literal.create(null, IntegerType)), 2)
   }
 
+  test("MinOf") {
+    checkEvaluation(MinOf(1, 2), 1)
+    checkEvaluation(MinOf(2, 1), 1)
+    checkEvaluation(MinOf(1L, 2L), 1L)
+    checkEvaluation(MinOf(2L, 1L), 1L)
+
+    checkEvaluation(MinOf(Literal.create(null, IntegerType), 1), 1)
+    checkEvaluation(MinOf(1, Literal.create(null, IntegerType)), 1)
+  }
+
   test("LIKE literal Regular Expression") {
     checkEvaluation(Literal.create(null, StringType).like("a"), null)
     checkEvaluation(Literal.create("a", StringType).like(Literal.create(null, StringType)), null)
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
index b510cf033c4a4..b1ef6556de1e9 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
@@ -164,6 +164,17 @@ case class GeneratedAggregate(
           updateMax :: Nil,
           currentMax)
 
+      case m @ Min(expr) =>
+        val currentMin = AttributeReference("currentMin", expr.dataType, nullable = true)()
+        val initialValue = Literal.create(null, expr.dataType)
+        val updateMin = MinOf(currentMin, expr)
+
+        AggregateEvaluation(
+          currentMin :: Nil,
+          initialValue :: Nil,
+          updateMin :: Nil,
+          currentMin)
+
       case CollectHashSet(Seq(expr)) =>
         val set =
           AttributeReference("hashSet", new OpenHashSetUDT(expr.dataType), nullable = false)()
@@ -188,6 +199,8 @@ case class GeneratedAggregate(
           initialValue :: Nil,
           collectSets :: Nil,
           CountSet(set))
+
+      case o => sys.error(s"$o can't be codegened.")
     }
 
     val computationSchema = computeFunctions.flatMap(_.schema)
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
index f0d92ffffcda3..5b99e40c2f491 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
@@ -155,7 +155,7 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
     }
 
     def canBeCodeGened(aggs: Seq[AggregateExpression]): Boolean = !aggs.exists {
-      case _: CombineSum | _: Sum | _: Count | _: Max | _: CombineSetsAndCount => false
+      case _: CombineSum | _: Sum | _: Count | _: Max | _: Min |  _: CombineSetsAndCount => false
       // The generated set implementation is pretty limited ATM.
       case CollectHashSet(exprs) if exprs.size == 1  &&
            Seq(IntegerType, LongType).contains(exprs.head.dataType) => false
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
index 5e453e05e2ac7..73fb791c3ead7 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
@@ -172,6 +172,13 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll {
     testCodeGen(
       "SELECT max(key) FROM testData3x",
       Row(100) :: Nil)
+    // MIN
+    testCodeGen(
+      "SELECT value, min(key) FROM testData3x GROUP BY value",
+      (1 to 100).map(i => Row(i.toString, i)))
+    testCodeGen(
+      "SELECT min(key) FROM testData3x",
+      Row(1) :: Nil)
     // Some combinations.
     testCodeGen(
       """
@@ -179,16 +186,17 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll {
         |  value,
         |  sum(key),
         |  max(key),
+        |  min(key),
         |  avg(key),
         |  count(key),
         |  count(distinct key)
         |FROM testData3x
         |GROUP BY value
       """.stripMargin,
-      (1 to 100).map(i => Row(i.toString, i*3, i, i, 3, 1)))
+      (1 to 100).map(i => Row(i.toString, i*3, i, i, i, 3, 1)))
     testCodeGen(
-      "SELECT max(key), avg(key), count(key), count(distinct key) FROM testData3x",
-      Row(100, 50.5, 300, 100) :: Nil)
+      "SELECT max(key), min(key), avg(key), count(key), count(distinct key) FROM testData3x",
+      Row(100, 1, 50.5, 300, 100) :: Nil)
     // Aggregate with Code generation handling all null values
     testCodeGen(
       "SELECT  sum('a'), avg('a'), count(null) FROM testData",

From 435b8779df01a7477addecb1023605957bca4e9b Mon Sep 17 00:00:00 2001
From: Nathan Kronenfeld <nkronenfeld@oculusinfo.com>
Date: Mon, 13 Apr 2015 18:21:16 -0700
Subject: [PATCH 90/95] [Spark-4848] Allow different Worker configurations in
 standalone cluster

This refixes #3699 with the latest code.
This fixes SPARK-4848

I've changed the stand-alone cluster scripts to allow different workers to have different numbers of instances, with both port and web-ui port following allong appropriately.

I did this by moving the loop over instances from start-slaves and stop-slaves (on the master) to start-slave and stop-slave (on the worker).

Wile I was at it, I changed SPARK_WORKER_PORT to work the same way as SPARK_WORKER_WEBUI_PORT, since the new methods work fine for both.

Author: Nathan Kronenfeld <nkronenfeld@oculusinfo.com>

Closes #5140 from nkronenfeld/feature/spark-4848 and squashes the following commits:

cf5f47e [Nathan Kronenfeld] Merge remote branch 'upstream/master' into feature/spark-4848
044ca6f [Nathan Kronenfeld] Documentation and formatting as requested by by andrewor14
d739640 [Nathan Kronenfeld] Move looping through instances from the master to the workers, so that each worker respects its own number of instances and web-ui port
---
 sbin/start-slave.sh  | 59 +++++++++++++++++++++++++++++++++++++++++---
 sbin/start-slaves.sh | 11 +--------
 sbin/stop-slave.sh   | 43 ++++++++++++++++++++++++++++++++
 sbin/stop-slaves.sh  | 12 +++------
 4 files changed, 103 insertions(+), 22 deletions(-)
 create mode 100755 sbin/stop-slave.sh

diff --git a/sbin/start-slave.sh b/sbin/start-slave.sh
index 5a6de11afdd3d..4c919ff76a8f5 100755
--- a/sbin/start-slave.sh
+++ b/sbin/start-slave.sh
@@ -18,15 +18,68 @@
 #
 
 # Starts a slave on the machine this script is executed on.
+#
+# Environment Variables
+#
+#   SPARK_WORKER_INSTANCES  The number of worker instances to run on this 
+#                           slave.  Default is 1.
+#   SPARK_WORKER_PORT       The base port number for the first worker. If set, 
+#                           subsequent workers will increment this number.  If
+#                           unset, Spark will find a valid port number, but
+#                           with no guarantee of a predictable pattern.
+#   SPARK_WORKER_WEBUI_PORT The base port for the web interface of the first
+#                           worker.  Subsequent workers will increment this 
+#                           number.  Default is 8081.
 
-usage="Usage: start-slave.sh <worker#> <spark-master-URL> where <spark-master-URL> is like spark://localhost:7077"
+usage="Usage: start-slave.sh <spark-master-URL> where <spark-master-URL> is like spark://localhost:7077"
 
-if [ $# -lt 2 ]; then
+if [ $# -lt 1 ]; then
   echo $usage
+  echo Called as start-slave.sh $*
   exit 1
 fi
 
 sbin="`dirname "$0"`"
 sbin="`cd "$sbin"; pwd`"
 
-"$sbin"/spark-daemon.sh start org.apache.spark.deploy.worker.Worker "$@"
+. "$sbin/spark-config.sh"
+
+. "$SPARK_PREFIX/bin/load-spark-env.sh"
+
+# First argument should be the master; we need to store it aside because we may
+# need to insert arguments between it and the other arguments
+MASTER=$1
+shift
+
+# Determine desired worker port
+if [ "$SPARK_WORKER_WEBUI_PORT" = "" ]; then
+  SPARK_WORKER_WEBUI_PORT=8081
+fi
+
+# Start up the appropriate number of workers on this machine.
+# quick local function to start a worker
+function start_instance {
+  WORKER_NUM=$1
+  shift
+
+  if [ "$SPARK_WORKER_PORT" = "" ]; then
+    PORT_FLAG=
+    PORT_NUM=
+  else
+    PORT_FLAG="--port"
+    PORT_NUM=$(( $SPARK_WORKER_PORT + $WORKER_NUM - 1 ))
+  fi
+  WEBUI_PORT=$(( $SPARK_WORKER_WEBUI_PORT + $WORKER_NUM - 1 ))
+
+  "$sbin"/spark-daemon.sh start org.apache.spark.deploy.worker.Worker $WORKER_NUM \
+     --webui-port "$WEBUI_PORT" $PORT_FLAG $PORT_NUM $MASTER "$@"
+}
+
+if [ "$SPARK_WORKER_INSTANCES" = "" ]; then
+  start_instance 1 "$@"
+else
+  for ((i=0; i<$SPARK_WORKER_INSTANCES; i++)); do
+    start_instance $(( 1 + $i )) "$@"
+  done
+fi
+
diff --git a/sbin/start-slaves.sh b/sbin/start-slaves.sh
index 4356c03657109..24d6268815ed3 100755
--- a/sbin/start-slaves.sh
+++ b/sbin/start-slaves.sh
@@ -59,13 +59,4 @@ if [ "$START_TACHYON" == "true" ]; then
 fi
 
 # Launch the slaves
-if [ "$SPARK_WORKER_INSTANCES" = "" ]; then
-  exec "$sbin/slaves.sh" cd "$SPARK_HOME" \; "$sbin/start-slave.sh" 1 "spark://$SPARK_MASTER_IP:$SPARK_MASTER_PORT"
-else
-  if [ "$SPARK_WORKER_WEBUI_PORT" = "" ]; then
-    SPARK_WORKER_WEBUI_PORT=8081
-  fi
-  for ((i=0; i<$SPARK_WORKER_INSTANCES; i++)); do
-    "$sbin/slaves.sh" cd "$SPARK_HOME" \; "$sbin/start-slave.sh" $(( $i + 1 )) --webui-port $(( $SPARK_WORKER_WEBUI_PORT + $i )) "spark://$SPARK_MASTER_IP:$SPARK_MASTER_PORT"
-  done
-fi
+"$sbin/slaves.sh" cd "$SPARK_HOME" \; "$sbin/start-slave.sh" "spark://$SPARK_MASTER_IP:$SPARK_MASTER_PORT"
diff --git a/sbin/stop-slave.sh b/sbin/stop-slave.sh
new file mode 100755
index 0000000000000..3d1da5b254f2a
--- /dev/null
+++ b/sbin/stop-slave.sh
@@ -0,0 +1,43 @@
+#!/usr/bin/env bash
+
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# A shell script to stop all workers on a single slave
+#
+# Environment variables
+#
+#   SPARK_WORKER_INSTANCES The number of worker instances that should be 
+#                          running on this slave.  Default is 1.
+
+# Usage: stop-slave.sh
+#   Stops all slaves on this worker machine
+
+sbin="`dirname "$0"`"
+sbin="`cd "$sbin"; pwd`"
+
+. "$sbin/spark-config.sh"
+
+. "$SPARK_PREFIX/bin/load-spark-env.sh"
+
+if [ "$SPARK_WORKER_INSTANCES" = "" ]; then
+  "$sbin"/spark-daemon.sh stop org.apache.spark.deploy.worker.Worker 1
+else
+  for ((i=0; i<$SPARK_WORKER_INSTANCES; i++)); do
+    "$sbin"/spark-daemon.sh stop org.apache.spark.deploy.worker.Worker $(( $i + 1 ))
+  done
+fi
diff --git a/sbin/stop-slaves.sh b/sbin/stop-slaves.sh
index 7c2201100ef97..54c9bd46803a9 100755
--- a/sbin/stop-slaves.sh
+++ b/sbin/stop-slaves.sh
@@ -17,8 +17,8 @@
 # limitations under the License.
 #
 
-sbin=`dirname "$0"`
-sbin=`cd "$sbin"; pwd`
+sbin="`dirname "$0"`"
+sbin="`cd "$sbin"; pwd`"
 
 . "$sbin/spark-config.sh"
 
@@ -29,10 +29,4 @@ if [ -e "$sbin"/../tachyon/bin/tachyon ]; then
   "$sbin/slaves.sh" cd "$SPARK_HOME" \; "$sbin"/../tachyon/bin/tachyon killAll tachyon.worker.Worker
 fi
 
-if [ "$SPARK_WORKER_INSTANCES" = "" ]; then
-  "$sbin"/spark-daemons.sh stop org.apache.spark.deploy.worker.Worker 1
-else
-  for ((i=0; i<$SPARK_WORKER_INSTANCES; i++)); do
-    "$sbin"/spark-daemons.sh stop org.apache.spark.deploy.worker.Worker $(( $i + 1 ))
-  done
-fi
+"$sbin/slaves.sh" cd "$SPARK_HOME" \; "$sbin"/stop-slave.sh

From 3782e1f2bec07b5ffbc8503e40591e96fce67256 Mon Sep 17 00:00:00 2001
From: Fei Wang <wangfei1@huawei.com>
Date: Mon, 13 Apr 2015 18:23:35 -0700
Subject: [PATCH 91/95] [SQL] [Minor] Fix for SqlApp.scala

SqlApp.scala is out of date.

Author: Fei Wang <wangfei1@huawei.com>

Closes #5485 from scwf/patch-1 and squashes the following commits:

6f731c2 [Fei Wang] SqlApp.scala compile error
---
 dev/audit-release/sbt_app_sql/src/main/scala/SqlApp.scala | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/dev/audit-release/sbt_app_sql/src/main/scala/SqlApp.scala b/dev/audit-release/sbt_app_sql/src/main/scala/SqlApp.scala
index d888de929fdda..cc86ef45858c9 100644
--- a/dev/audit-release/sbt_app_sql/src/main/scala/SqlApp.scala
+++ b/dev/audit-release/sbt_app_sql/src/main/scala/SqlApp.scala
@@ -36,8 +36,10 @@ object SparkSqlExample {
     val sc = new SparkContext(conf)
     val sqlContext = new SQLContext(sc)
 
+    import sqlContext.implicits._
     import sqlContext._
-    val people = sc.makeRDD(1 to 100, 10).map(x => Person(s"Name$x", x))
+
+    val people = sc.makeRDD(1 to 100, 10).map(x => Person(s"Name$x", x)).toDF()
     people.registerTempTable("people")
     val teenagers = sql("SELECT name FROM people WHERE age >= 13 AND age <= 19")
     val teenagerNames = teenagers.map(t => "Name: " + t(0)).collect()

From b45059d0d7809a986ba07a447deb71f11ec6afe4 Mon Sep 17 00:00:00 2001
From: Daoyuan Wang <daoyuan.wang@intel.com>
Date: Mon, 13 Apr 2015 18:26:00 -0700
Subject: [PATCH 92/95] [SPARK-5794] [SQL] fix add jar

Author: Daoyuan Wang <daoyuan.wang@intel.com>

Closes #4586 from adrian-wang/addjar and squashes the following commits:

efdd602 [Daoyuan Wang] move jar to another place
6c707e8 [Daoyuan Wang] restrict hive version for test
32c4fb8 [Daoyuan Wang] fix style and add a test
9957d87 [Daoyuan Wang] use sessionstate classloader in makeRDDforTable
0810e71 [Daoyuan Wang] remove variable substitution
1898309 [Daoyuan Wang] fix classnotfound
95a40da [Daoyuan Wang] support env argus in add jar, and set add jar ret to 0
---
 .../hive/thriftserver/SparkSQLCLIDriver.scala  |   5 +++--
 .../apache/spark/sql/hive/TableReader.scala    |   5 ++++-
 .../spark/sql/hive/execution/commands.scala    |   2 +-
 .../resources/hive-hcatalog-core-0.13.1.jar    | Bin 0 -> 468533 bytes
 .../sql/hive/execution/HiveQuerySuite.scala    |  15 +++++++++++++++
 5 files changed, 23 insertions(+), 4 deletions(-)
 create mode 100644 sql/hive/src/test/resources/hive-hcatalog-core-0.13.1.jar

diff --git a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLCLIDriver.scala b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLCLIDriver.scala
index 6272cdedb3e48..62c061bef690a 100644
--- a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLCLIDriver.scala
+++ b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLCLIDriver.scala
@@ -33,7 +33,7 @@ import org.apache.hadoop.hive.common.{HiveInterruptCallback, HiveInterruptUtils,
 import org.apache.hadoop.hive.conf.HiveConf
 import org.apache.hadoop.hive.ql.Driver
 import org.apache.hadoop.hive.ql.exec.Utilities
-import org.apache.hadoop.hive.ql.processors.{SetProcessor, CommandProcessor, CommandProcessorFactory}
+import org.apache.hadoop.hive.ql.processors.{AddResourceProcessor, SetProcessor, CommandProcessor, CommandProcessorFactory}
 import org.apache.hadoop.hive.ql.session.SessionState
 import org.apache.hadoop.hive.shims.ShimLoader
 import org.apache.thrift.transport.TSocket
@@ -264,7 +264,8 @@ private[hive] class SparkSQLCLIDriver extends CliDriver with Logging {
       val proc: CommandProcessor = HiveShim.getCommandProcessor(Array(tokens(0)), hconf)
 
       if (proc != null) {
-        if (proc.isInstanceOf[Driver] || proc.isInstanceOf[SetProcessor]) {
+        if (proc.isInstanceOf[Driver] || proc.isInstanceOf[SetProcessor] ||
+          proc.isInstanceOf[AddResourceProcessor]) {
           val driver = new SparkSQLDriver
 
           driver.init()
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala
index d35291543c9f9..e556c74ffb015 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala
@@ -35,6 +35,7 @@ import org.apache.spark.broadcast.Broadcast
 import org.apache.spark.rdd.{EmptyRDD, HadoopRDD, RDD, UnionRDD}
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.types.DateUtils
+import org.apache.spark.util.Utils
 
 /**
  * A trait for subclasses that handle table scans.
@@ -76,7 +77,9 @@ class HadoopTableReader(
   override def makeRDDForTable(hiveTable: HiveTable): RDD[Row] =
     makeRDDForTable(
       hiveTable,
-      relation.tableDesc.getDeserializerClass.asInstanceOf[Class[Deserializer]],
+      Class.forName(
+        relation.tableDesc.getSerdeClassName, true, sc.sessionState.getConf.getClassLoader)
+        .asInstanceOf[Class[Deserializer]],
       filterOpt = None)
 
   /**
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala
index 99dc58646ddd6..902a12785e3e9 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala
@@ -80,7 +80,7 @@ case class AddJar(path: String) extends RunnableCommand {
     val hiveContext = sqlContext.asInstanceOf[HiveContext]
     hiveContext.runSqlHive(s"ADD JAR $path")
     hiveContext.sparkContext.addJar(path)
-    Seq.empty[Row]
+    Seq(Row(0))
   }
 }
 
diff --git a/sql/hive/src/test/resources/hive-hcatalog-core-0.13.1.jar b/sql/hive/src/test/resources/hive-hcatalog-core-0.13.1.jar
new file mode 100644
index 0000000000000000000000000000000000000000..37af9aafad8a41d3007b63a610b1af37c324544a
GIT binary patch
literal 468533
zcmb5V1DIt`l0IDSvTfV8ZQHkO+qP{RUG74cZQHKuGP>AR|DN5M{l1yq>EG^s&U5kH
zc;iGy<{KFqc~VgZ6bu^ZZ!ex2Q?dW}^7l8W-=A_~szP*9^5P7Ne;0!U;{GkhtKaH6
z|NHN+z(7E#|9>$#A$cirF%?yMIq}ehDXRfS#E@%{?*rWdA##PlTgW0((1C)&bw-KH
z4HdLlTJrO4^%oCcjHT;Xnpg-r#q6!mlR1?yY;T~YwH#VwIvOyd{O_jcY)|(_c59+S
zB4adtsWsgyaDwRcN1a=-Yh;r1CUjifha%kXnU)z$9KEJ+-r|~TYll<54EB*rKrgrB
zE~AmV?7^x<JYc?)QJcIFPqbgkML@%6p5Ry$oVyH3-k?L+mtmS`w>mE-DJYx}BsKlY
z6aa~cRYKg?+8-nwDIXKxiT-T&gr8c&_=gXGfRd{I*;Qb_ePHio{$F1D?-DS7moRcL
z0$7;-K@jnu1uZPy{v?g{KS)~uj9iRt?Ehp9-k)Fq8_Pe~NB>t)6;oRyI~PlUke!i@
zr?aK=A9UgWNtem*R{Q}=@t0T^CnGy&GgGHOD53k`D{*!)a`{tF(EjgLS=u_-{J|))
zztrUXdkES7$vFgnQekiJW%;L;5dH}au(!3fxBG+jlz&1yyVyG!nVVV|*_qh<v19%?
zKrM{^)Te(m-w9x5Y4fMXll;kiTO$W2QxjLfpA`Hp9R4j7{GI6k3o>H<8^oV^Nc9KQ
z|AB)48bJOLJN|-w#Q)~*{{j175bs|{$v@rpzwm#>xqpoT|Ff3Apc~<zn(~)S!~Qqu
zzakmVzrp<_zy5WA{-e$RYij+w;r3@%{X2XAl2HH3<o~kQ6yWM)>Eii^Q1Y+S!#|+^
zoraMAF(Vs|gi$DB00F@;0|8P0i+}$%js6!G|Hdpy5hE878%uhCjghl+iw=~J>e7<H
ziJ94U_80&MlAD@QH~<kj2$~X#SPBwxG>8<Dgb<#EVXW7LyektpQQNw@wMDJdLdVAX
z$9$QZPP9x!*-~q(g*Atc&ZTkf)|1%A`m55*$H_ElW+2pHeNTLTm-|lpNuKvl=PSJT
z*B|lx;-V*25%Ktkq5O5b(!m&5x<>~?K5^-~K6QO3SY3m=rTomEnenjvI};c;P7LA`
zaCK?%*vT5t7Q_aWz1V>@DRa`n40n5g)S9YCC%hG$uJsYPF7b$3v{7y>wydsg2_BE&
zJ~@8qJK^N)qb=fi^<<9mw|(R7L0gEnw+dO0tw|l(tAr;qa`*8!Wlx*bGh1?dju+-+
z_Y9wQshMotr1o6$@FP5?HTG{4hjz){vT?5!VeVL68xqwaPBGqaac_ja{U#G5zFiXh
zxCEYDRQXh%C34#|!q>^|G_u<aNxD=7Uk-1{gX@`Jruf$fHL~B)gX@`IYWdguHQt_W
zeQcQwMpiKHH(v1WJj(m7smm_k?Sk!7p5(}PZ0@{8DX!UGeEIzZc8KG3j&6a8K81n>
z4vQ%XSfAMmE{_o=4oJxTRRh{4MlSoWMnpdeFt~qPUOwiI<<l1bQ&>8HpD12o+`K1V
zU?`vc1wZ&Y)wG4bBkDR?qNgwac8;xa7yF}z_lo1$nZJV`l#8_Z$9GL-lHxBW&GUy}
zhVt>5UyKM4Zj6Gz_&(rwuQ#0^tC9N4`iauMR*Z>2_-{)P95P_OXT-xt9TB8IVSqoA
zCHK(M@*CZ0__$#BFCCIV2w2{!@PA<Y>)|WFyyKAjt8DKijkNi`<M|CAUXPDF$@-~x
z_t@Vd$ok0(V&J^<swk=a&@MAn=|8K3ehlsBb5rA-+sKZfs5Xwgy0Yl%tfHFJ8#vTL
zij`2IX(+PkLnqhpB{pV}vx*wNOmn%G->^iui~-)amktqWpd+H7-q9+cSwfLxo|@Py
zqv*hhcc4V;7gyWUY_`(#rBow`HfGVVr^GhT(r<0C)UdFxphgEFu%-HPu{e4Kn`ItQ
zFa8x3Zm38jOnFYUYcJ~S76mAIH4}bY?yDwcW^;q1@Ahz^B=KDOngB_4#5XRqSTdQB
zGA)t|YqO%rs;OI(j(Uc@k_$-@-kgYldfma7&_ya_J6J9$9t`JY$T7CLjIAWeTB(wQ
zMBSJqq?qAl-ETC9E+UPU;H-lsNf}j`Di#hPd~IuEq!ulu!c;ntVJNqC2ev8YRUR5k
z+%e}&h~Zxk91v`8L2x~?IW8?Mv^G}fdre4L7si<0Wmhey3?bL}=MqV(xH6IP3b6OK
zC6mnxU1&GGVniHcL&5pqpm}nP62~r(W5c}~Hn+@qz8lt8Y@7kIfMP@3Il^C?@1?N{
z%3bbyBu_qZ5<THQ3i||v?L_TFgaKJe%_>FdvGO3z%1VwM(c{DA<1w%EH$7EzN9$8t
zaJMN<{)1mwp`WRj44IspQ!KToO#tI=!j&PEBU@jzca6P_?wAuXD&F40f?LXF?P#20
zHanct@#L3sAhomrH}RQK4X&8esSR>cT7j5$A%!T8o!uNod~1QYbs2ag(Kx0R8t7bZ
z(lt2^L^X`k+C|`y-bp-}AQZFpG7<o!OJaVeJ8~XWr1-2f3>&NpkDTOO0bi4D`mH5X
z9yikHVC3NQpe&mk1wm(0*g}1SG$J~v;L-Vpm~IO8i&(l=#V}>(gSG6apZy@6wk8bv
zaBKa-j<-@3WGuHjuDZCL$(0G9-*3I>x|3yFC|K1L2K%JHe%oEN^k@;Uonx0g<}s{2
z2>Hn&mQ0n)(i|Ce;UPMTE~xETbUP%IR+LrbQ$%QmCVo&kHKxcR+tGEQN@YAKS$n2x
zzztsHR-q9dEgkdvc6*<3xsjeN$1z@pC(l|sl+%HMB>)0$CrTb+<r}2_w2Gul7}}j^
zA<$h=Nl%(522SZhR{bijS*4wfdxW6vgREr(t~rKkW}riS8FDFWp}A(<A=%nw5isl1
zWq7ObB38Ek*?~!X5Lcdr^Ue}&u%EB<fXFwg%I{~2-`1zO9x}bH=_82p4&(VgziXiN
zZv6pglYfGY<=^n!_RcdnfBcgz6$A3)n(iZ5P<mtmMDtzZBYDXGxCirHBii6tBja4Y
z>MJ`=BoP|i%CJbouQ3Z{Yeoc*(o4*D_vp_)2JLqRzomWuTN?DwY=hvZ2X6FF1OiiT
z+Za_y39V#@ejqTq4}>22ctFICAvIDn>TPtGu?&^kAnX0%tvO|S>E?Lwkg^<|DJ6;(
zl4a1EEZ#+!&#hs4@+ls$lz3Z;MrPVwrLl~b6$qt^r2*ZTUJk5ygX+N6mOOFnH_f7*
zzPb<;*~its(dnub)hffr8F-1#A~(^rMSH6XTYE_Iq4Do-xLTE7tPV-`4h^N`RZ_Aj
zZ_MD%pP`ZnmNx=ghk42J>wPix;B2}mGo!p+0hYs3OA!y7pfBDRn1|VQcnp*Th7f~Z
zuFZXyi>ME>07PvZ1#@m9R+6;4>PlJXktH{6-eB`0--bn2HRCz^(>8Pk<pny|Ebc93
zU{{ERD7OkLzfwK{%GPXyH8z2a%e|mIMczC~aQ9;?MyyM@5#_>fxsnusH#*lc?umV_
z7^^Fk1^W4)P0#df14Zd)Xwh-V#Kyx?ItI^90NfXyH(|xri=-E^K4zJz6xv}JCt;3q
z4m0X%g%SYLcZlT(k#Z83L1pDDB*+4j3avEgswOzL4P|Flstyd9DYbiAHUlFkli+vt
zQRSnm7|XlcLbJ+H5Q?wrfJ$h!$Ub%vx<=JhZJSEx#r8Dr_;_ubsD}>}ZzQH?Er;-a
zy@*NrhDBw%&Kc#2)32q|8W@^Z?NzO+vAxl)WElIIDMdchtC>t2O{6)b$O={mH|eG7
z6)<!y%6cZ1YE{dMu4z>o7(s?5G+g>Y)tyPjV13NmnJ))691nGfvaLDV1?gW^gS7#b
zEiRbS+9*NW#C^VVstU9Ct$a>v+@TOj)o?A_$~dYh3!b0hez1>Cc$b=tWWO|9N@SN}
zP_bp#DFqS_Z`nu|#3P#NUP5U&AXkXGR!&#trTDvbDZYdDN%L@e59KvqUKnukJeL`o
zV(<^Cy$M(13)Vr~!Ku4}mH{9GE<sK~1@pDSfUC{xBMvB=?)uTVNuXAhYpse)>6h0#
zY;+pCY^qfn>i46f#xK958MFWeD9hL;74;#>v{br1n?Tq)9=&WJ<fIGrG2O+ok`cD9
zDrVEQh`DN>BQH@&x2IUT0d(Cp`{rB+UPx+^@ltA9t8CNO>kwJewXDKBaK%_O@kCo)
zgW4;*IC2+X$~pE{Nl?6vYVs6$GpNwGIyI?FTA7xD=Wm_M2~!2XJKRZKsv4Ea2%dux
z^AXV|2W7~wc{a__=Q<<|1-}i--I0sP+hOC$r>`xX9v;kS05DQx*I4c^R0x8@SroQC
z9ajq<%`W-mjSY?|IqiLNiKi#$gQYbfW|Q<dty1YIU1$_51dnuCYN0~=V57>*H{|zl
z`m((}7FW2~VB~!@*lK&JS=V5OJqa;3H!r#cBI^X@H*ULrWO!Vi6;US2=Q?y@X4X>D
z_)xbu-&humy5VjahzTvIEmJZU^EeL#+^M%3cDb{r9`w<qj-Y!WGH;$bc<G2Z+sb$Y
ze#Nb)t(Q&9;ILn6uB>+iR$A$1$0LGcB*(Fci)TzOMSp35wvg?F#*#=zm7cq5F1{ap
zme(ro#87t_>lmhk<H4r4tk~JyUR`H)QX%szZ;$-=bWmZWB;W9!FVt*o;EAJEC6JDD
zH4kDvhkATGYjQIs3Q67!KHM|6x0VmHFGC)9G6|gq<=TVzlA8C(nHS!+%IwBB$=XkH
zf})^6srADpe|H-|51c-v{HuZTKza$>m04anIb_j_2g|K!4ZaseJYrnR#ZBuM)#&J>
z93?WA-KDjHW4I%A9jRGN40lpe3-$<Is6ojpF`gg}c7%-;LrFRc5uk*)tvk;2ocHLv
zY+?25t=@#Z*rI90p?-c^{N+A{zS$KnOG~_~61y2Z-kaGJOg8MsDtNh|pggXTp0!?4
zLAPN7&TA44Isr**;n~XpbF$&<S4$Sn1q`zVXiG3)n+c^-Id~A2ai=8+#MR7%FF;-{
zB`6tr;d#!*wDfDn28r_mz(Q^sy8eghuQt0UmjTHt<Slkzl{VyZ0WFQ2W8E1k--L@8
zD4z$0bA-n%P)Rmo1)n7wK?@n}YNI&!^1z;RIO-;;&m+ix0Ik7&;?-WQ!2lYPsB8_&
z4xGXPP*6ohc5{#IfR*b8UwdiJOU|#AxH4JA4H@q_5G*z6JIgtg9ViNuaqiKB0sCNw
za%Jx1O;}x`%#y%RQ8}#d4VS8x&KFJk>@gD4-q{x>1hmBO`p*VPg8X4sVLi+OZ0Hx;
z&?$#|kbUPaw5hmk@ju0U9qEq4<ZLP*_T$#-Osw)K%wLD!^SC>$$?cr@rt{}qn`xe4
z+X*$ANc3Ed?76FL9>>ld4PzjbLmtl;8|4kixQad6F*ailpn_D$o`*qH>6h4wXwu~S
z?_qOn8#G^ee4%Z{nzT9Ouerzg-1R}%mXi|*ICznA28U>l^Qd*f4g4Ub#|g9D5s7V+
z`Zq$}pd13GIQf>sSk$X2G4n?5)BEbiR0CR^zT)Z|u>Z7`I9?>hz~5(=Y#Hd`W-Y$o
z;B<O7Ij21Q0r<-3H<=hj_GQD!?F8<AHi4^aSxf~7k0(-fVU=vHW@(PUL}!%aD@v{$
zy;s5^`y@r%C#EM8e!+kT{C>6c)!2<&I;ayQs95~&*<A0@17)5%L}1wIz1IuIX~U%P
zO8i&>l%~@oVP%}36Pp~_3Sm0|=?o%Pu84`7JlVC;9bVafStvrnBcq%qrzi>!L4g$g
z=ivbBk<pzwuu3@a!t0m~MCuvLm(%9ss4u4vm8h5nED&e1J~?cXEZXlZ)p{S9si3Ss
z*trz~J~A_W1>NA>@XMNhHGQ#w?*&yo&yOzjC&ve6y++EaClteSKv(Sqy%M6nzG1*E
ziGue(BBVRdut88>0;0PbmCr3MpI%bYdr>(#t0eQP;_<ht%+oF_e-$rdboUGY1j)oH
zIl}v};_LA;@r$tH{zdbSf&QX_Ult9<E?V7dVcQa39UDNgOHWYHVO5-8rkV}Rfyypf
zEhdKsJg~zkXboXWC#toA#7O=Gt9T%kh3mlJ6Y(xc1A^WA6R37X8{m`<+XZ|NIR)zx
zuLxwZ@QwpfAyuD|Mg}{`FZ2NJBQe_cm3SAY#0;ntToad)Uw8=ZBTeuYs0F%mKY&XT
z$23=izbn{<iU0L1$x0>yKD!LA3{n$xk=|`Brvb*z&2lr!XEToWii~3a*wG7e8p=L|
z1zm}YO^GJ;=BO*$yHbBl?p3Q<s%K>m-LUt&R^t0WzIKgPteUHdGN@c(3v2jtV82&Y
zAzZ-%h_qaDVpb*IjQqN&-lDjp4_9+0e876kqR`WPX++KCgKgC8wIxUA*dF2KiJA*s
z+rowikKRQ3!iFct7Hr)17*t2#)0~`7!1l<>LhU>KE8>pymlwB=*z1yw7yXW4f+C(5
zrjF?RlFk>N2PnTZ{wao8zIW%2bbpDb`-ulGzf|~JCTvA|?iyNbWtG!=YC(g*=J?9Y
zhi_G-3{?<5^~DU8j}N9xG71%Z4<#K*dCK->^=Gr)2+G+W0`dmplJ+6|_~jImff6vq
z^$AeY_e`(US_MSKBpE`z3&{_t%Tr1lf@eQ8H!6?k79QYA;yF2A$bDh5+!nzsj&urM
z5e4LS3e88SHayvV)4L_`H7(HjWOgV(kp*M~fbyW)^UF>c?}XQR&OBp$5+220iNuE<
zNG?`Il2@=F0Nmo%l2{KY!TN;kr{#4kmeE2C*bgl4?lIk>W@b)cX0tL7zcvdDAYU0M
zCf^WplQTJ`7ap3x6eg-zPBl8=UR|;7j((?wYqXvSC60T({7K3uBq3niy0?(FrreVE
zjH|;BV(Z(=`Y(`r<O6t^x^-V5<30d0c=K0Op031@NQ<nX)Y=e*gOEoV*+L72n>&DI
z3ABeVuOz6Em(9{r@gJi85G?*<#|N+<27wIHROGHHJ`ley*|Z@+7#3)-x;?2zF$GsO
zn)?Z?=%21}3mjyQ028`m6PsjL$Sb)nTBeb2n^p?F2l22;z6oaL!S%w%Gc1yN$lg3G
z4J(@pFn485yHP^t{E~Toq#;7*iMe&I&YulD(_IKUKLUblDo`ANz!y4=t_WfE;Z^Db
z6LE+J++LyjPr%R1@|9xri@+S_zowp=<B38Nqkh8sdJ_7kd;p)&6pfiI2%M=|*i&DI
zOzSUM8WQ}1@lYO_f3WYJ#URo(0F|}Wn<9T=qP^)|uff~($2_{Eq#GKESs8uCxbeN4
zz`PL)wY(su-kgxz<Q1KhM;+Ib6KU>r-ZP3~Gk;XN3=;R^(TSU_37~<gMqL^TUs%rh
z?N$M}Z;awuy2tt+A+Ve(MIiRHmo$z$8kb!7m^Zxe^tzIwL=K2WU;WHkwZFVT(O2!3
z(0fdSSr~G6nV|cWz~(hzBR31GWET|E&5o7MibL*fJ#WWegLR8_$`D@bY8SSshb*~1
z5P0eFyy@db6^)_dEeKS!C#++Ru@sNhn&1wAv{@uZ!-|85--(!{9rr%;(n06-3u>sc
zMomL_#}yVbiVJ~Z<9lLqn_$+w9fo(r2w>!bV&X>H6O{1D1s^UJQId0{ys6y$C~{`1
za|74?VC4=DW(7q2?1z0D7dz8{o%NGNm`w$B+2!Buk~+xY6V-4PKCtJP)i^o$E_M@k
zimm8T{Q$jsY70bnpW*>OKN#R0P<Kfw<ReQ^^drET&#IZn5O#J0VIJAD2Q+ngvMhqd
zw8VKZ&WhoDnFmxqrQrj>0JRVIYb5V{#0v%G8oSQtI_-w}%c(dk|GpT9X%7RI8x>V6
zN4)x=DP;HSZKB6@25Gb6#3b^Jtw~D81YwSIw|fVN$HZkbB*R;n<wN)2-TtPWUEk}%
z9PsA(XD?(a@{BLz{o5Y*Os|*6J*$@j`>(AKXqv4O7$$QkB)NdGnSeeSqwCbK_uM~~
zF?3RPBVEW8%Bnq~^+x<uCy~7b^2G^`7S5F5XHk40@b*}Qyy^J{SWdlplPR1M%5QY@
zhRyF?@}@AHsoL&+w#Q8?*kCyO(QuEXuMWg~0;-<}eB$5(vJ+AW#D;FAw+cHG2}yrt
zNvhJgerNIQh|&DudIW}cVtW3aUmZem^XmHG_`<zMi4yEe?P?2^S@*T8c7wUy-K&DF
zrRr9pBz;Lj4W2;ucu}wV@~F|kEG_fGTJsoJ@(jCtCdn@_58msQtB#GE5RvsskOjEG
z@<COLo8gsCc0Cu^5WIbTtX4I@(ZawhmCDdR7Ji=G&0J$fmoQ6yRpAyTNO^c9Dya`<
zJhVkqIYs{rZ{IxHD*}FnbefTnm;vz{gP<hS*B5X4mUZk9tFFr^B7@=fqB7nz`@Bmi
zYu*pm)UZzR`AVo0<p)Wf1s_3?-Co-7{|4kM8*VwA&JT}JHR>@(xHUJgAlR-_JV{X0
z$sIm-H7)iw2;_Um_z3!PahEfEt5VFl=7-e&yzuNjL%8LQGer~fqv!e={Au^vT)uI)
ziQ<A$@`<2if%(mll}KdwqXE)~KE7A@vrt#f@Dg<3zBXKZ-VeqK<5t>58Ds2oP%ybY
zZoEBj`e13X&)Nc^zLd3IVy7LL&jiIcNoUr#g;<z<-nlFCqc3|;P3PI=>X7WFXAeRY
zmNpmnEU_7{Mq=hiza^pB@m-fqCsSffv8vt8dlXhQ#!Lp>H60F@!t`vo7%m1@d9TRp
zE|*tcjktBY;Cs}>Tp>~}aFCd8;NWTLr4Q(@>4Q*C@=sf}U4P(z?3Dj!UH-m@WwZ<)
z2uOtp2uS3w>hk|>?@GkU^!LuIs*$mcsieKV^?w%ZYqelJaF<*^;#=0&Mphe-FsyrN
z#am6a=GP%`x|kufk`ir*pk$a=fpc!JG_kunn=Ynbm&h$uBysMnkS&;O@rUG=j_20l
zN73y9?!M~0Le8>+A!8#awOUGBKw9De96otS*0epzCi3t1a^JY0a-3&gX1JcBPPV--
z9D!&|%ptQK31b9?(pld#!vcXmc)<uhh(idwYxoW3Zk7<c!+KzgF#Jo+;KLjt!$F@r
zh<!*SB$z7rC0KFcj3DDJInnzK4seWk<0w$4lC3^>D)v;2cw@~MPqg4hM83gNfIM#?
zvhQBA@?r?1egS#*Uit{u_Mr{%R}J=uKFIdacl0C*!ML3P_K_Lrv3Pa^VxVf>nY(d<
zWa=u~>m;Hbc@p+O`>fh~Bhn29wYte#e*$%#CaBu`aehzo_~Hop8RoxoLtu4-Qu^dy
zwXMMRt^pbAK^nqw(*(4wdg&j2>)eGl%y5$u);3@<#K86*Z}q8h`63{8Uri{#pNlBJ
zw?();aE9mwu8RgWnv#$bsgUd>_a0OLuu;gw6JJMFZQU`wU^b>AS-|+==A>R$FSKg_
zFr_uGEvWGtGYhOAlTT_c+8WQm3w>~7St-V>m~!ivv}Jcn!$wee&GDmQ_*S?z{Wug;
zlX%Jj__a*$ha3hdx#-p;HXZ7iYEE>l5d{oOUQX$}XsS%J;>Jr<+g_KT7urm_q(3G8
z09_J$k14S==WBH@H`XFa=K$2=qBU%pAEQ>2^BiP&=Y-ueTU=b7?MmUK$z~}NF4_)(
zJy<R<CGoaZ>rLc^WV+Jw6x&>I2Zm)`c^2$yR%&*px_@IgmGA?pi!$AAa3;s7UG<uf
zCF_(*W?z)AmS(g@9bq4t#3DV`4(Q;KbBpRKulyyRzh-5UM8!fusqmmvS+Xk}r=Lbu
zVi~|5n06yeYtd!FkjS7gl1$pBP$Qpc+FqM;&iV+`uTHMxu)NXUEX3ZS=O7LjOl5rn
zsc2elD9;r1WF~=LJ?vpR)$Z7sCY(J()M;2w#jetcN78U_M)E^i<3*8`LmPB5FvdkL
zC@TaL*&I=nBCN@6n+t`IuO|!$3se;CEp<rJa)NS4mq)A31;h4O$lRNmmS=gHiyPZ#
zEho1WL5Er1j^X=q+E_+=SxVweHDV^8Gz)g+c&ReIJFoeYtT@3+Gqva>-=NTRYc4)X
zPx7X(6iYrLZT6_&!`mtB(j*>rQO;#0J$0VOSc9Y(J$s6B2Uv_WXti}?Z;{(EJ`0jc
zxK`6cjAy5uFt_QYGs5>})AmNqLaC}EDNU4IQ|aW&W}UXBbfz5PIQ5>-mAG%w{3XIR
z6&v)2$j4qXM1bXtM&<g}^VOi*7&^T&DR4ah!Zn?*?>=7$xE?C_s<SVIsWY`MMBij7
zsxZZ~SH$QbQWB*yE=2DKvWtctlw!=@V!N~yd`&y(SxS`CGnr++dL&6{C$Du(Cbo0i
z4cT_+5+lhSpE*^kLa%c-RWU2JSPZ)ry$G{gpWw1+5j@JGy8>ve4vV+U#$`E`s)`|F
zPwBIGv05ZrJJ0pX#*R8BHI(amZG+C8*<^8QPR2A5er>z4i&!Hs9Z72uYO;M4s&<@C
zFnZdtK2`n7Eq3B&DW%ttLQ^TBhp{BKYLfh27O9;;t~6R-G_71bSEhJ8c=OtPsHqV<
zdiUhOcZnQh?%Ql|Y^>`&uRK4^J<x7x8SDHddMRslJqp4%nPt=d0L7ywX?~~VEwN~X
z7v+WgqnP*jMmwiWo1R9Ko>Oa-RF9j@vxRo{5L-`u97IojtR+jge8Q^KQbC8@sJw|P
z8Gg!qDx_sV+T&a)20F3AeCYKQy%SLm<4!&$(<42VwYWG(6$j7OF{{B(*ud6GIcGyW
zeQ%YN-349k+{0brq%7^&0`P=66e+Uc^g4wray+?aW1ljCRQcF382Vy2=b0qs?A$p{
z(NUB5gQCQ(Nubic#koYEhJ%sf+^Luq+AK%TuvWY~-%>5zbsR>nQ8wMoa?bQS_I3$>
z?YNw6lwq);S)_2qgt*uWJ;#svLPHELjY_;1&Gfwo7MvgRRC+bM18814JsPI2?PBaq
zra$KC__7}2BB<#_J8aZ%8GUJ!T-((wdN)dx(&_qXU-<Q|5_s6w$|l~1W=%Tjp`^~c
zo~~v~6+HH`O6h+-LUC9xHW4qIKR3<}&L7dQk$(Fq+6E4K#Ar1bT3bzOiqmrGuhB|5
zd2wqW?HGn}b2K{OJKv;v2{BSVAMWdAxHB1J)p^|>;Nh;0bMGi!!f>jstIWH}n_b9n
za_@Z9SlX^coiEWxu5ra0@fEo9M8wQQ6Rq9|3pLMCrB5SCO=SnjPqPB}-W7M*PFT9{
zjx`TZ#!%<83sYliG9R{ESMooDoPLgJ>|@nDTs637(Qc=!rz>yhk?w6ertwx+Yk*&W
zCA+AQRp;REx^!8e{uV%9x5(DFC)U*1d6c%D7FU+`XnRSwvCiG$<&C)~mYn;Y@5*LK
zEAUEfU1g+cs^&aNqE7X-17X3{JJT#e6~Cw|<@}^u+t*WuPn5nA9|NBV9ISp4YFT!h
zM@L2yM$^3CLjEyno<To$r5v6EA4;_Qrw^99qR-FiOZNtg1g{QH_ddy^@7dzX+04@1
zu`%!B?AB%xCmpwP&R37UzD%pzs6=c+n6RL~w+Y0JFqgL4n&U6@Sg9IP+?Oa(ygkO_
z%T7!CPNNc1ufOJ|xh(H(RL3MOjcrI{OP!UT7u?+^&0{z+pocrJ{7gx2SC`Fj8TK>?
zO+}jKZ7@S^U-LGZA{2Yd=rOfW_j{(yif)^PCm&DRN70R@0;#Uw-CD=yO}OLL&yYPR
zI3-r;i`<Wvel!8m#L{L|guWw7$(Wq5VP;95zCY<&cueHo%_K@-az|K6Y#}Rj2fnsH
zQhn6GxK>k5<j6In&(F;?7?&Jq!{>+&X%`dfpQIvS$os}0JKhYeqUY0r))8GeSQ%Ed
zem?(PNwI^YkF{!30$rxD6A@d&1v^&xlGu>QG9UDVyj-?YvKD6~gq}Ag9#ynz(VWGZ
zq=kDUcV)e`-Bbr)uV8&r)><3OXPb++q0NoG($dCyf6SL>FU?X$u9m#EJ2b|<q3+L%
zvdOMxVvxa1y)ry9qP{JQ>Xg>RVTPLH$20O?95UG9v`pVk@p{VWzfhJooQJNS4Mph1
z&)zKMU=qn&8wtIF`OP3^5veABDj;<UfLuUKwO8j1H`6RHuNkIq13{Qk^g-IIkL9oP
zHI?NWz%Z=7nzn))h-+*PZFjPAEl)p!_kNBKd^O0PKKEvn5S8tFbYnzazOBU_LKPGT
zJQ?v8*Vk6s$h*%2@`=(CJgfdfs!#9eFK4?(2%<pjfm$emM6Xl&q7H8M#q13~4YZ{R
zbX%Jj6AE6KpkK95qhN4rLgDxBVD2Tw8vn%4r`0?&8N6{T$)<!$?KrvCSlpf7*2sfm
z8z~a-)^pWgHcOGvb#V)E1^bb}k@&+89xp~!R|E-}EJ|DvnYVYD8Kv6teQnY>y<;6&
z5{USN7ao+z+;LHo7Ld+h`4XO&eZW2p_{y{-g(MkoqNJQYvyH{yL=zE+gcZX{_J}4?
zE=I(cI#q8->7#!j`68xkOcM;EArO^i;EK3RAn9tg8zO2{4pFzJ!i0ZGZ^9cS*0^5?
zhe)^yfir5jX<m{ZRiZ77SPvdg(0&=nILB`lx5X0C#fN$okN*X_`;rcy-?Pm3$p?((
zas6{`T_gjCN+3>f(BC)%kh`zxouCNB+ED>pf1pQn0SRq-F%n5v5NOTe<O*lx!bdNJ
za$F3qrWs#77p1n^yA=C=ZH6m~fls2{Bb34~7LrFOo=*Z~KzgH3bgC}~QcomB^~(bk
zUEYXdJ6JB#l1fCpjF=(4kPvQ_tag<So}aSwmS`;;VZ!&D1b=Y+=&$E*KJfVoz&_e>
zyG>3Y2&2v(iu!|op5Qo#Y(7HUgBV8|&q*-9>Wv{Dmm6{$eN(uD@8m)#84jmIDQ(%@
z3J|!3zC~tfL8?TLIHt?E6U;OxpFjbMeW0mIkOr-!XL`j2!KWP*EA`Rcs|5iJ5*<{t
zhqi}%vw8PNYN+1^!f7gx=<jGGQoBO7E?yd>^M>#*N^_qQ=Wwqc9^T=`pIBeytlog@
zY=<}Du=zcpRoHw^S&Ja8p6TFvYWD_m5aD_T{F^D{I-{NYsJu*Hx?DGr{4ku^HjDSR
z-De$<Rh}7?+jmK+<%@i@5ebOw30yULc1#`8+5_7ov?0`PmO2ve5Pia}zSl8ug}hRQ
z_}d^(<PF{l)tpxF^gVV6>Eb<!`A`%P46wxnr8*Lvs3TP#NjP5mAr`t$vaK|DIA!%L
zy$`)ub4Ia2_n<lU;6(VLMYxXK0vK2ljV}r9BHq^8Z#m7xC6~U5!NnPF5oV#b9b};2
zYOq&d5o!~66V+hA?vaPpq0fbhxL2OH7j9si(~4s9+FCUWJ+gQ3+2M2k0$FQLKUCzw
zg6G)bc6jx?E(o7<M9qCGToHW_pJR*A8O~$wC)_?n(s1+Esyab5nw459$8sS^pg-eB
zNqaH^?lDmLw9oy@858OOCWHCG2HS1Q8I~F{sm&W}#w!9(F?s;*^g_P(#4GfZ4&-d(
znNz>t{1y+_(9jQSXQ=p@U*F83JCtBI{kc##YQ>byk91{^!U@HXTF)aHyNl@ibEeIJ
zj`2PQ>`dDh;u~q162y&?)p0p0nkE6@+EkSCL<KgvyrCbCHrD6F(^+}?VQ<>;9oCN^
zKP-P!<QX=2{@Uz4v6ngrss_ZB-7-CN@x+f;Fq$?Q{T=utA<Z)F$gUu*Q%H3HOW`9p
z<w(kR7EW^rAmHi26KTou6<ZOBJCug?eU55!@n)o)F*ngAJZvUZ!6-6pX2t<<wVkZ#
z2aRTDJ|s2iDq^kr;L}IfV{mw_u(>@@wOg3<UHu(5|EBtL%U{~Ahw1L~pO?XGShShq
zkU&5Pzn>YD{XZ{*|MtAvKdp_uOr3;{oK638Jv^lOrh&VJ_qn+h8ffZq2s~ES5{8{h
zo4`b_1R6mk2u)=dLCDm=j+ZvZY_zsE2_I4-XX{&nz_z}uS=_p;VJX*aoC@ZxeaT>}
z@L7Vd^VaU3K6N+RXu?Gi-o&!=vi<gJd*)a7)zjVer|(Y=pr`#N!gD75xLQfDJwhsi
za?%;Nr1YwQ@JJ`weHTO(P7;9`_1(8;A@J$F@VncRFamI;Py%ZY=_uaXJuJ8xD^7wz
zuXoW#KkdN$y%X%bg_|x?1IT?4{l%Lk-1pGKcV&LR(mhi+3~(3cew<79Tq*BCC-B!-
zTn@7gDHd)ktm5N{1JYO}?|EkVq1Y6(TnF3h7$Py;6@F{4)?`L6&dtP$%#~$o#dR|Z
zn|i(8ov*%<gtKQcnjlNQZv9cRF$g+W1zflk=DztTYzHD`))UvTEW5GmRDpTm38ZOr
z6=#`_6lS6atxSfo*-$faZlsgXnJKx<Ufgo_!1pyrR~#znd#WR}^?*J<61a^Ow~<uP
zJS;r#RarB3r9>BHeTcALLy^3tq_XVBl)IrDZ(Q@51u2i^l$CY&`5e~R-zsr@-Nvm`
z-Ij{ZgaYG=9$`{C;|}1mDw(i*%x;}PTw#1&$+@oUKg66j?hG5sYAT3UEUaZ^*5LW1
zQXR8W*0ncYC=f65qO_$fjg6@Yz5<{YvK`u&C#>y8i{_*yPVWPaU0olUf)seJG6eN&
z99fJU?vSQ!QkiDdz^-V)V9VbwY(a3G-R6I2)tzxMBl|9=^wyzGvDz2alv1r{Nmy;(
zO(GrVHxPn4m0B-&d~3)^oIsF719?HFuh!*`C%zow5*whw_N$fNs>Y@_ttLC*UQv=r
zNvE$9l0@rh5(X6>R`o=$>TM4j(J-ic)$^W@(_yM^p)`s-+7@=t`0-SbD=F`xjFkM`
zSH$==j~ivXi#^W?Boe1X4n&#>gBE^W9HS6!0#Kld^DG_)9-~G-eyX4xE!fSh()+Wz
zu`hwD!~9<CvZ$alFAX%$n!;EtyWieBWL6n6XnT+p#aXm)8ZORB!HM|z+c`)YAu8qV
zJPsU2W0dktv%l1UHHe!~tJDOlb<}Op@;Qgzj5-g4+jk%u<e4|TYMs<E&RyAWN<RYV
zY`r#Oy-M-sk+@s;<neX}@v!w*ZXx`N585o|8$iS2zB6j7xpqbFSbE5ebb2TZT)WC1
zAaH*~JZagx>JFo!8{!e{is1S8OMtkeD$cr2?g9ckp=px1;R_86PpS~O1HW_lPD0se
z9w#KDzcs~)vsyljju`P0JIq+okfWR*14QUwsp9$Yn!Zur^iG+TEutjHTi-EJI2hVy
zIiUBZzArN6-08A(i0a}ugScZ@$g3xp>LvDyh~eMX^ulb2ySaxhW13m>kCZ9TCxf1G
z*dsMIzj_+&Rd)81nO2r`MVMT1pMTw*X7h7Kp@8(za_th%VLSxmVc*Njw3_n?HeE8Y
zq^9~R$L~R~d#3M}yXcJqHE|h}O$CCwI={fP=-YKL*Ow;}|A7Ak^MVhRYa8!ub!TNO
z^@LT=4-aHRJp!m2kK_A}<DsqCZo`rE1M`MHS;pna{IHya9zfrK?#h1R!p3A-$zhFO
zABRl^3C*iZ)VWqr*w-c}zg~K_a4%V1b$gmL$wi>k)31NOTNC~$0zR%|+LDcMCN<dF
z9S8ke<NEf+vRj*JvmUw122R>fVsI`uM!^1=+5>)@+e*5|TKlGSbH#}I2T<!?BNGuC
z=@ftHOy{%d4c#+6ltE|)(cZw8Pa3ru3-<Hk0?JoBqtb|SSMg^?^NEIz8;YA>D5-na
zH#5XHR6a?!ND}YTI%qq0pPtxmMtD~fbK2>1>ovzwt|pCI#8gW<J~Dmd4uAzUVjG(*
zv9n3yTHC=_#Fk4H?Y1&-W^FQ81h=YG>h=%%{jFR*9jBiO&ID&bTt6Ip);~et*Le_x
zy9O9yed-<IvwBA;JHzf)5Ht4N6$$5A!=c>>0~HP7J9^13(o{=(F)FO6pi(D`Uau?K
zL+GO3LD=X@3+Md{h&NYpsdI-q&gwtdViQt6dGDWLmI>g%>xzEfV;NWUG4Tr7-0{W0
zo#PFN7bUTC3VMU=2(fifBvP`^S$I1HEl2DTim#omaRzakDlam}9Y`uh2P2Vk9iU3+
z#d(aoQD9<!u}np8o-gypq__1*@axIlxoma}nD?`~B4jJ7_*G&feJMggwN7d6&hYyJ
zJjv<yz-*;#)V^O$)Hnptl$c8yjB>6<HfDVmNe{HKK5TvxJa_L07>Lw|1!H%^6&BXZ
z3=F)Bb&G<Z(ESi*Z!a;yeXLTVjlFiZ+Sz+BMDH9m#(-{6P@1RyxDd{MF=@-v+U1of
ziBt4Ica4pSkn?MOOhq~yJ8mW^?SKxuIF`LxuCx^p+ip7Km;1s$&~UFMxI|g5^+lC4
zym3|-bFf%i15%`99%5lP+JaNLZZ<WkJuocc8GmB8vzH3l;Cnv>h`-orMUSN+ybj33
z-lm`nj3d9qHu(I^LM#L0nEvGcW=e1qe{>VR1eTMqQalT96K8l@-wPOkBlcddit4CS
z-RyNm8)SjfmMRk}9Av8L8(pj%;F~XBux)gfPhywMVRwJCU+Uf)ck%&TXnpPh^HThQ
zw-rW<mQTxggRl}gN`E<J<f4MDnrsOYh_!lY|42bocZdQYNcT$~e1PV1Zz&f<UR!;}
z00%Vdjn3hBnO9rv2R!WO?`UweMCcZ~1GHc?yItP}bFP!0fX^ldT|+qqbdkzqlSB6&
zjATpAb08%1m6J32H{OIlzx;E)!oWK#I|~5>#DW9_B>sQSSN^kXFZ%lsm+|i`<^QYP
zw`l6P<1C?l#L;=$cp_5}xe;3kg{F+IIO0MQQb6dqohu%6G$3Qshc>tn%h66nWGW$N
zqt8287h*^jJ}E;Zcv=vgPT7rXmn!f+P&Aw#@vt-^52e{Ks92v(&hfup{JONicE<Yr
zA>jY{B>>3>aX|0ci$WftFCspW>6Q~q6f^=j?d4E)mLEW2;*BilcA&^pPqKI0$Ku5a
zjtrGINmO}N&g9&Q^MM7|96t@kL|0l=jOq(3&T6#EQ;Ee9LFj^it{Aj<EDDpsriVG@
zTHwHtRhZ5qqxx!p9OOC28da9daqPR&cwY=+J3_Z{Hv*=e{M{U!*pfnGsSax*ttoXr
z$c5!tm?`7JWNKe)p=I&9ig6!<R>9DC*zrD0i@gcl6167Urtv}7<xafS0_(ofWW75T
zuWf2S$=p+XJ++L1qI$Os&pc7k*i-`odxG^{zHz!F(>ce<;-$SviCs?td*NNp+*7M#
zTy?#{*K>_vYq9s)$1JTc?x&rWiXh^KB+9R(2RSjX0K0Q1^)%m!2CfFSHo>BwAy^g9
z>T?+ly!oJWHht8`V6DMLOLZv`M=1emaK&htJ4{B+)?UqvNjetr<@CR^fxQwK5WYvU
zMpb>9WRbQIUmsthxVh;%&z(tnezUY-%f45weJdl&#SGH$T+@+z>(HbZT<D{;oC?#~
zJ?^-Crtf0hIXdCp4HBMOW^ioR9{!vYPMRO2B^Gqm1(@Yg&4BIkjWPpAtiFwWZ!jK+
z3d~i2`g_oU_Jos@)3M`--n&1;_-mEbail9iRR~-$R(yQC<b<d0u)wtDlH*XIDD34M
z>fjP<O?EC+v-v=6G|l0uS<|_DyVRMf1RHHr)=6$ub}9v33oCrh4otYJzRPB;H!E-b
zfzESl?~Pj<ZXikakrkZ+$CM}KrD_z{+t>V28G%Ara&ijfw9A*W+|&!wuJe)*t*uFv
zBM?UfsxF384<rp2pD#OToLxhgvI8>Q`olEb$j?b}8n;<t*JscCbq<d|Jn-x-o&)0u
zs0Z8+B)I)zIKb^xzDz1+#1wA!Crp9L59n~$?Ne~$_k9a%bL|SwhlaJQ=FA|%6Bw9r
zeHUiyQJt#4u|9g^z}{ZE)#)lfaQ86SP0Ypj0-<O#H|Dl|ZL6z;!nPiF)AMCzh>opR
z-`&Hb_s&zPDWCQCcjA$dF>v~&<d{sV;*cxT*IN2BP|qbvy_~9g^=B{+T>R)ywn{-_
z&#LpypV4)D$`jO51Ma1)%r>Vt-BZG9K0Dad?lRn5fMnVxTIW66AA`r8N3l4g5Ev|>
zJO{MW^b<TuIDPOCl^z9silZIeVc;EWIun%~4Xoy`-7b}m7NCCKD+bDLD>C1lz0$aS
z5y)}KMPAHaXPmva7!SI><#40~rPhBldrWh&pz)Hep@`gbxL?<d4%58aTK~YGZ=M7B
z)?+!xzJ4i!+;6p-zsWe(5KyWtRpqrcMQ{#X8pL~`{iv1goZIN)D|08_$l>W6=V4S-
zdPdhUC#lR*aw^RRzm&WdW&I*EynaatWIfrwEQW9H39+8W&&QURiEQBpvo;yiLA-QD
z0OB@Ky0{y%6ZvDi3G-NHQO_qI<^4|87-uj23o}{xD$BDfV6Iy&LZERWh@r_ACgkZ3
z^t2EJo&*c?T#TTFQ>#k?aG9ca*%OBzxMsbY9pw`;+U`5&VS;8$fKVgIgMNl%p(pev
zFn7x__z^Wd+F;?{%yY+|hkY6s23pzbu>t+?W0ma28_XX-bebk`-|qkQn&DKp?<xg-
zg<nWRw=<4D&>acy`3Ac~IqME<MZMwVAia2h-CqFnIRO$Fj;VQHi}nDVpG3%nq9Of~
zaU{;^0kRmUPY9Pp4#60aiZ?(>b{EV%_5j3NM)JVZCltNRA+*V$d^$S=DuYV_hFjnl
zX2By&Gj9ZucDHbQl4Xv7TvYhj2_qeTVSUAZ^?2zy-jFYFkA|awt2XBeT#;vh$MvDi
zO>hoUpU4tz2)^<n7F^QmM@85{zEOG@%I7dJ5r1%@(Zx?FX#ug5@`p!<1P3G^&(s37
zRF~`-b$;)Rw(mX!+ZglSItHJ;)IY1KE#SVb<5}d2V;s-L$|5=w=V(P2l%oqF6yq6#
zSzCxmWhLQIk_SU)8())h!Bs)}6Y|)e8^8zCoXU&sCo0UoA$d&?k<f4!WCd46Rv-UV
z+f0o5IaKW5kD-1ugd^z<qCYb?jdD7eJouA!&5vA=SKJaA&%~8`7Q51j;P=%><+P3b
zfIp;R*%JGb-3Jh@`eyfKjIYS36<vm=#{i}%^Nrx2=S-(qHKpd?N4On+ACs2+KhK%}
z(;ENp2h_CTejiXv{mdsC%l7nqAq<Hpq6S71LB<pk<nbXR4FnTGPA0q~V$9@C4m2_I
zxEBtnYFVmk(Wc{#{+VpWwj8gv#+))w=k_D4wsy<Sy_3MLa|6At^Y@RA^A1~eud8gH
z0a<2Q^5I`o4A-0PJ6yj{s$G5NIbVgQ@4OAS0nwJ4tJ)06(Ax|dRL(Ny#5X-#gYT#%
z;{5Q_8hX0%1+TAg*dyz^2L<;p-VK+3mlOm3Q19Dmzj=CY2=Z4{3QEs;mJs@s;{DL#
z)mKxB$*-vSVGz=*fc9QJ`(iKuE;}@H3xjrYlLhk`XHfP2jBxv`(D#exc5mgy1FuKv
zca$sKcYkKU@QdddTKPmb*ipV^-$wMkj#&9rx~<#g3I9~P{qn9f1o@%ByN%*|q84<@
zBT<qRTvm}H(*BYn5#_;&<`ij{8eZswra!MrT_Aj`U82|!#r)2iU#46qOlAWlhms|&
zmL<;uHX}QiMW$^xmqmwfO5YJeZ+d^qjONNJ5s_NWntojA!ZoFF20iB<hhE`Qis?b4
z7BM0`r%|blrbg2&SvVAuv#n^sU?k@}dV2fZ&+lJ<b@u2QE^MS=Z`gCSwsHdX787w*
zc^Q=vHe>I0`m4JD>t+SQ*Y^v;nK;QrJ*n)im~4Ol?UIX2Ye<J{+Ncg1B*Y{et#-o=
z1bazbCzRM!V8J%?>`p08Zg(C36_q9Yi?1)ob4-9odM=llJ)v-g0+s^o;*Y1y?rz2S
zksXYil2vRdQQlbBZYC5%mBp`x6B_*@Xb18|i97Qzh4iSbkD$lnHQyPL{HZ=N+=MSn
z;7CzjGWb8Y<+{JRRIEGn)`w3CQjXe9A%qi~^%Lb11c>~6{`tlWYF03_fE$rPGZchU
z{nJFVN73J((xP6opS9K75<=(Ibzx;{zm;oDn4Sccna4NrJ8#?mTq~kk3Gsy?XIx{e
zQdc!IY#qVuFMOuqs;UfC!og=is&Al(@WwdX`$596P!!xb<O7)RaX??NCc!sv3fnTx
zJY#j*pPiRc=mr8h9R<YX^CvJrJ-B5_5HF0t;?IaJx;*w~1;6r;Yb3={xHFo#+<VDx
z<Xu@e*!Nz*VFikK`TE|cB{V#JdK;7(QXD{-iSW%+ZYafF)y)aYCn0)~n2pZ90D4ts
zNL*fs-JXA3MR}Tg&A%rLWe+&-Pjz$R6mMj(5gy?NzJ$z^O0s5l>;X_h7N#)2(ljYq
z)pz0H9jtq{=j@k~)V#H?rCC_X^%dAHKE4nm<!07lt@w*mqI;Y_M)>>bBE+W>EPffX
zLoL2#XJQCoSRr5)yO}_WVm8lOY%xg`!V$!}P423~#UuG%*!OHK#w>xS(@c_SAUm#a
zlxNBp43J{KijbiQ$uy&&#Z(E+P3#LeyGGmBh`08PVN(mFKDK92Bn53vrXT>M?TbM<
zPBR|^{m@KniOUF4Jv@&CCA$~LgrR1FGRV)YARf*YwGHB8Vqd5kiMt;T4gCUEN3up6
zco=)hR9R>SBE%<$yQ?dLA6lnu5h*N#)}dW!3QebB5h}d0I<(UQ?JG&dpivIZbWcq$
zhNeBmRx#BsUf6QcA2%DYx3cmj1ZDHAs(h$l8m{xJ&Vbx%r4rl{b+ddicNIlVo~Ea|
z`6)k3nvdA(@>e__RI6DB7Oz#3YY8pf)mDCO1sq5XGcD)aZJc-(ehXqd6tk8vv2RCi
zo{T1G5)l1+2}b8z(Q8tRlA5fAQ4)pZvF!7%A(_QZhaG`}25oi@UR$_}2oBGOLgQ1j
z`h2H!D;1gSkrL73wTt9o-TK9D57Fvh_NpS$m9SrDXWC6ijK#ynbDJ{@i|62)#R_rQ
z)}=RC*X4OwJEVBs=ILYIlH-NSlrUbf!m(Xda7g428n4Yly;#pn19mry=k(738CHu7
zUO}kFy;i7YzA@Udutex{qb0zxKks!d65tt=*tjLbF{iP8GwhU3)no07;~87oI&%4|
z=0;B8`|qAo!&p01VDB9}WQse_@I(0v=e`%6B)br-&{#IIUE>QsivBFmc=?6x8->5i
zS3Vcq04zWU!CNzj)X3^3`QRIduYQUY%P*6^aC+Y_U{D}V^e(pDjO`m4NA+MDi(fi|
z`Whu3zkt%^%7!~g6dQIb727SXa4WxjYH3AMll^WP`PJ`EdigeN60-k+E4BC;48;;1
zxwz5%ST3L6C~kf6z)X_fUc%mto{2n<kj2=JwwFseh7KCannFv>9JYdLE<^!wP0diZ
z+EgbW8CvE3@Hsj$>#WJa*vW1NgaFXUg<-<iu|_4#QdlFLRwvXnbAt(bvE;V}@IR~(
zxF^nker8a;nOp2;uq3X@nhcejEb7poCJecYDsv&v44V$V51z`(yE+^(&ksEyYl0Yn
z#A0ePXKQY2YrVFzI<v8`ue9A>ascRw=$NZm!xUO=S_g#SD`CI&8}W^XF^r${Qr{nr
zE4|n1d2^bY9lB=~K3~z+N_x-MR%Qeoo#|DO<-4rOjIq1@#4Z$iLnY^QCfVx_ShYJV
z%l(O}Hy)is9z|b0>T&JTa6jqsCTepldP`!LfvwZFxZ<{4SAA)5I$9JapLlX>*7PXX
zcN4HycZ~yy>E)h{v^tY&5zm=YQ@cxLplc-hgn$WrUqErCr&CE$7`T+)@VX3qPyDJE
zX-c%I{hM>-WVGmh*gD+oO?rGE)MZ>6QH;pZLuyz@68VMEA#loS7lL{Diy{>=ofs5e
zRQtZ4dHVoAUvC-=u1t7otzKe}IqRTk&0m2vR~gi#*-LodH#0vhEbJ<N90t(2`DF>4
zdZOzHY=sIY#*pUf`7%e)j?qVyY{GmSR6S~0*_XA877fYgHdaODCBAH6Oqaq6m!lXv
zNQ*GxFvRp?glZ_oC`-{*uFdG}Qof>wKB71EWs=h{Z4*kahhtqv5(slZ%)*-Cc5_v+
z#_SHh8~4)AvXj>g6jkFO5o0}r{(r>1Q*dulx9z)P+qP{xS;0THZQEF}ZQHhOd&Rbs
z75ikLeeS9H>Q>$Tc;Dun594LjtkFm7t^K<E*`t`|Wkd8um`#^ez!ShSAaR_@RDJ=j
zj^#_r9MHH&fe5^y!+K0HonzGha&5(l$UY?L6NtYQ{m1W9aE<}5eg9L^@vkAy(5U-<
zF1<~Jiqi#r4MNy?{9M8ryTj5Hy=F1#H;Jg9Dl~)ktu*^(7#?0_(1H83p?GXNsgfA-
zRpRr<iWykA4a&gK11c`Z8*z80_g+ypau^zp7kL+M3x7Thk5_`->aeVxWKZb~nl5Cc
z9K(yavUgXY6~+1DYoT%#u1h$(0T}Grx+#5orq+d}(el%}q*l>7wp;jqjGK)p2SXb%
zV|;KLX^<HAS=7#)?&f^C2M>JJ#AUk?%;tPH6M6B3i~Zz^(fcf9kWu`zA(I8JWV*%>
zku!0+$x^VhK|xNk5_i(F@bDL#^<_=Y;RM>`rqxcInO=HPCxx03m82-))Uc{G$nNfr
z>t&r5hXKW+c3fNGacS%hue9WYY7S_(exu7B%j~r_xPU-2CP+s<3z-ARv^MRf`!A&z
z2yq9KM<~vU!Zb%{uAow|jm{7CfgN`Hcf6A51lyzsZb=Twbz+OkqHO8japy+w9pbZ}
z?}^TxMLeWiRONaLwvsNA&rEoR*zq^-WO&A&X=gyMzNtlS0MFQ>+=K@qNd$nW=t3x|
zkLbcEnUC-S1=*)=l&k`&i<Bny8LXt46gNPzwWyJ-TX}&iVJ6YJy$DE%MvlboLh>;C
zkK!vErAn9b%t`y=aJHqCnTssyD}!)k?UAzh2GgNx>6x8CNWdcHs-~hlvY1)g!7Gei
z*OQVpZnYqgzzU=1-vy?n`NgtQlvP27f_U8#mj@QsMTWZY`Gs@)T~BfN7|wt8OCvfS
zuv*A&1<R3t`iNUWlkiptw_fGHBu1qGW-~+sy4Pa{DZpPBA_6psj6NZuvj!Yp(~Hie
zfl2Q%<o!ztjLoFdbWlowf&c#=u?Lb%6}lcdOLBfgi8%eVflwEZD#VybBGM_CE~Jb9
zRCqzMXo2pdXAfPnU}yqQ49@L`^&EnYK%Jt!5k=U%QBPpP0%roa8h~P%>1XGSUdXbC
zYfsTWVz~553HCUqUbWt!w)0kQy*%;k7PQ<aM~;{e|G8lVKpH?hg{i9RCvV3XC2Jv9
zZmvTF+Jp^}ly4bHJ;*lCU$k{8^a~~ieAX0@!Xm8iz5M#d8zRE0<+$5G1$wVY02H=a
zD?KI^&r%e$P#;I!%e$uy!SCY{SMUD~b%3E!bpNB}fa7$sOVY-NKJ65HyP>Sw?4^L}
z)Wvn3WguP28}pCyczxDGL3<|m*vo0FeK1YS1zHVpvt5BUY+uSQhexh$E87hhO@Y>U
zWI}z1EP;t3g1Wy<xg+_YEar~(AGPffa4hn$VgEsuGY<+ce(mBF?g()!OGM?2@H=;k
zXuUI}Z0F!bMbZF$iZrCol}o#haF|zWF=RM=EjET?VsMI=N-K91gy>B~;~36Bwku17
zRoCnFhf-V0E#yGKBhf(Qt!MLjnqhwnbA-w^@IQ3bPMA$xN;UC%@`&c`0U}h7NZCT`
z%Fa_#%h@&<IRiWld9iEa@_Oke>u8tleJQv4tAV%tdjSG&KZ49<LU4kStGoJth3c~#
z27ziMcK+^GxFbuJt)?8WB1%<mg{|^&7cqseP)qGFAxxzUI`+7k>Kt0?m|}o^AIN*^
zt&A;Ow3b#ehwfc-xrYWkJl*MPxPt|${&^4N%x*9T4)j(2F8}nF+g&hrB_UJ}=#l|W
zC4;ClFvMkf9GAS`*FysKA-}ld#pw?dBbcd&w5bPxsYjqQB9fISJdDuU6L6|oaXQOj
zyPdHDSRs(8NAXxOp69)BOK9wq(092i`dZ7O&C0QNO2yoxdEG-*^@D1N3algxmz8C#
zUNr`LU915hF7kLbC7$bI7iaA2f^JGATL2kn0h<DnC1C_58a}bB2U@3`JlQvRoBUJ@
zh|e_J0yPVY?82=FtAF!6ho$#LKNZ><Q?_snGc?bHMQ&jPY-lPtE?d*iykKAqJNNFY
zSm+Rcu@zG&iwO~bM6AP6b0kTGIaQlTOO`u4*@r7kZ!ftPwaxJ-{!lh$!A9HnK^x5Q
zQlv*4&a?fFB|KVgUpHkQw)GGN7dTo2hwDB+@2_Z6`yb)r^#K(Ex4(405w|fY1voza
zjxbi?v`iR@f4Ul2JkuI20y2JVywgGb_;8C87%)U&%NI0je>i?{=!S}Lk3H*BWs>BV
zvUvM@6!yn5bD{x$CgTmHcc_71La+<q9BJeQ#O_YICz-JbZ@I(j?P=im)41cx5$-62
zfWz)dn#W+rSnCZd;S!rDCp&p(RHG<7cBU}}FoVrT<q7vUlC){}=dR73Tz;Kgpmi}$
z+v2BApFw|lgVKZP@x-c7D%uMRDfdf)>6!6W1+mp}PBy^aGZzLZLHFeEvP$%G+>7rv
z6`u%C{?^RfzQa$Ud4bWIZ2euQ+@J2|um*Wd<38`}%M%YbvD)ls0r7V8$B8Gf4~T)w
zUSR0kFGp6~YSRz+Kb4WV!Z5|gANPaE4<PIR6T9~Rz<ER+f0#Xv|1EzMt4I2ws-b<^
zHjGcnl9PfK=n&N@<KwJeg0CB{$>%}UCXs>$DEF-xyCu+GUemIm;1^5iEuf=Ss#?`Q
zs`ytd1^fk#tbPpEY_{}KeZT*nBM8{(&WuB3w=zupFugw5bn3b9GW++ooT>*_2W*F<
z9uwtl%y!7i2|f|OQokeks|E<62Nw?8d<2M#n{oyIjMI9TA9voN*T3*3&ELpfa5T_y
zU^vv7*LoMpd$Z4hmzp3J%N>^j)*CpN^_D6tDOS$Pomj#)cm7TTE|+EQ4+UA_EY1sX
zPC{u<*`5Vnsk66ajX>d^21xWv!{%EAu8+#-%HiP!_m4FK4z3i8TCLQ{!Y^9TqsXCD
zFmGCN4VVq@ENhD`?W%bTPt`7j#syDyVdAoBvneZ<7W~7%iDGVbukF);#*Pf)@<s6N
z7lGttE3>R0Z@T0tN2|t{XX>Oa%y3&Emw%4LsP4rdv|07`FZbA+5~oi(4##@Mm_!D~
zjok1P9SRGtoCD80c8bhq$MWm><g1ocH^&^A?SQyz%6^kW^HiJCmW>`S_rd(4?B_+<
z7_-SuQmiHz^Ksy0<yZ2kq1>rXV5=Rbzs#{AR`mTN2T;P1&#2pcJx7yH%ebV^E}9-k
zz(>O@Q6gy3W?-i7Exq-n8?KGIE94vu_FBdr%-9w|j=dZtbxlL_RaaV6+*~#Gh-o7v
zTPXsBjHP4s{0#IQ#rr<W-a-xu(PvRxPOJA<RiwCiJZjQl1E%y*&nBOoqg%TN$~Qy$
zbp7!V)Jol8$rG1HQBOsQ7bxo5LH?Whtxi5?UqUO`NECDnCMGt+rHqs}sr>Wz3j(lI
z{?KfwVQ3s-n=%;QP4gE${1)@KT_JXsFDW5*R-C1KVCWF0y?^EpU^^tWG!ra%Q#_e0
zkQ2!+*-<Lv^z}aoJc#XAcp|(|cKRcM<2YwnbY-;r++@5F7}8e*;M+fZP((1%)5ri4
zv}fzE<LVV0DTSY`+N^gVU9^l|AN13_4WC`c?%`Ml`=Rb)yD84>H*LPOCSJbWr60)m
zFvXMdxNkaUi~`&WHF+8`T@eKHEeUH@<i1h4a}(sg5xMhA<i0VJO|9X2yQ$>9!7Jg-
z5^d=(Y`%jpTjuj9<#jhf>FIk+ex43w8!$ZWw=tbsJnW<cl^7mY1Cf}p%|;(BPuI<f
zJ>fh1VkmaIZrHwd`v~rfLj-r^Fk{Y*BKnh<1xXi&Fat0R)%-iIgFc&P)iiKiSEH!P
zbSBRlfmp;JC|^?%Oi=hxBlmbKF*{c6Pk&e_jSRrP4EJkaGQ(SM-Bhn7WzbA%hw(V7
zh5%<5TD4k}Ljpxa>@stfJ{Qi)*tPQsRNE%Nd*jgpQi?ox;07gfwYV^}SyJstVX~!v
zq~#k$4<SWMJfR?i$mu?S@4v-|%`_ge6-cIISkXJZN#dU}QzM;`c}$9%eM<C-l-qL;
zBdYi2f4q<8p{qD|im;;VWM<JDHs|DF(la_966<n`EvPR0)6S@el1qRHXYt|YE+@;R
zVe9hZZn(8BKXr@N%zF@3)46Ra#A+q$8L3S<;7KV>-+i&l#S#*xCew`Sz3FI34>aML
ze9Dk|)uN1~1CY9I^;+da%iN#~xGex19~b`)cf=ijFf-qQ)aZqA@1wr#-?YC8S*02D
zEf>0WSqrjVnLPZ@HUMg)Ir(g9<Vrnu7N3~RX3Ubx2zN`l(V@;t_lId};;@>@NsW->
z3I=qrA*`fjA5ul?tIt5ykxW5e>SUrVP8Gid2Q(G!S;q5b-Ui!DS;QC}TUCBM0uyFM
ziQlEcVYJv_#c4_K`bwHcN$4;y^X<6*N^yl<J-xSQG_vg2b;{JaVIBMfnK%2*iZ!*v
zlH=ggiTmE|DRzWi!-59`=&1ets|%dY8Vr(La)zsF0Fal|R@lN~I!BC6_ZazZVxfq<
z!E1ob5Q8dMiGa60#tLpplfNn}D)0s&*ni6m9(dPMg~ZY7Q)oD8Ab~$5=mwc<M%z%1
zq)?9KD_=Ktq&a1Zk`T3^>QLyQ->|6-3ql%~50^ke+#Ki#iDJu0#I5ROB`=4zcy)fq
zOq&mS=B)O8wo~?!=bNvV86<{GBVw;x)#%5Bcu7oeH|fU+N=pX1n_?xOMWHX1Ulmxg
z<c?gL>*yHpGpC`^mFZ?eie8w)aFvDqU9J=|*^_pm%-cpgIuR|~hpiAT`xliJOwF*b
z10|!FJ%B=-uQ$|*;wf=5Ko_o0$r&U+0EyM~?uE=-lpTUq0gXju1L-t&#>(Y1F^_nh
zk_!M$?GEyAxu?+;a#!<EnyvYBSeJJ~Y>PMGB_<&dowwh8ON&klE7sM<>9Cs>;4LLw
ztHm4?23$L*BYaSE%9s-3EGdj4My3cB-$##<j|3efK6d63)PcONjED^_QT~>u{4bT)
z$jsp)jQ;K}iDNhMJ2GAm+gyL=1ATjhSb?Tvn4LAOi<30Qz8ldgRi&rO=ufL5_(6US
z5>qTvJ!U2*K_-^T)#h4&O;jen^8v{!Jj~7Luj}AI1o;VD+#!72K?nz2f)PnY-tgFc
zjfZ_M(mP=5g3}YXp<nTrCbK=U?zqGg`?+I#J7WjX-b^46qIB?)o|_cd4x+T9pN3>H
z5zU<B?7KkqXb4E3g9Q+=VZ1SsBJNq5ywoxKOb*Z#%J^L&8bkBaMLLkkG9-mPnQQh5
zE(SObY6|<>mi2*F7-dQ@kC2LiD65h-&J((P%$A}*>Ntr6u7S(nydv<+1d6bHo$O^3
z^e9tIapp{Q+99Q;as1;cSce2v4RHWRBrN}s!mmov1XaZ+^iGRPm#GpU2Oc_8A*J*e
zaMLe{NVW%Ngj(W?28Ayby+V1VqZ7X1EeAhII4Zc0uZu-<>m_ZHIDIJ1^eqszxiPcK
z5a+>OLeq%KFe>(h(EU8Q5h1+Z-yo@ROnG6)@zc60_RpXH7Z&{A5lBSO6`a?f>Id+H
zC;Xuk{s$rSKhT8#8=xs|;OX&Sy&y#sBRfaq|1N>L)!zTB1p3}4Wy~Cp6QmTPOtJuL
zSfkbOFb}?^gaZ{$EFlMqdYm7>HfAwqZk(AS2dzks_^WDD`8dD+M)|Z?XlXtPj!pMi
z{rK6^^T_cHCO}YqvYozlX(XHx@Kwj-cFp(fHNzKs!*{>$m*a)shyGEB4waQMAMm`q
z_t^#*fOwhO@;=VtUfK<0<_|&uw5bjFAZ;>;jEIwZE0gC#7}NHTzMRtcJRczQBlT05
zu<i?eeF=ghh}}|QAsirK<&KyUzgUCjCf1|H{@sJ+*NYszZ406>t{N<4&Kbfm_D0g%
zuhom$Er;wG819+av1mX?kb1%POOM#C3Mw@jdTrs%iNB@Y@sRxuzqt8vk4(>~?DmYW
zZ+_X5?L5F1+KLBo-Z*QzZepQLw{MdEE%ykIx0r~J!Cew<1*O!u0Oc1GRH3t>zsm4r
zg+<3zK=HdN$;J$sWTY*}-i4yrPI6Uvvu+cX&zfTXhHI_pB+&WDj7w9KLX4(Bht8nG
zlKV1gW^T?#{cU=!o@fheE<{=<Eq7^(<R^mstlwa|Iv<L)u9s|)9b#J|K}M3-;(_?)
zVwT(U?XEcM9%AFb(~UGpw=>ESMam|}a^*}cHY?idYWPn-^!V{ia$|3Tcu<=rJL<tT
z{`;Mej%&TpWXPYg6B9kr?<s>kn-kle@&e1WV8g!M4^u3F3l>0=njyu<nm+Dj;gfzj
zBQ<(sn|g~YV$&Pn!pd+lR}+nPF7kZ$unS}p;i^L4iff?GT9dAUPqV@)6nkzClda|I
zOh*R1`>*;-c2M?`q|`+ty{fl)q7E}9lonZ#2(u;#Yk_$W6TiQfcKCeS)1%Ik2Vkm;
z)-q+!s%gwy9BNR!aROBhxHr-a5O39k-4H?P_>0iSUXrS+mKP-CAZq)937d&gl@eoG
z6a#qS9?YyAVj381Tb&=hbify{(DtmATu+w_k(u|njcmxZi|lrESZH6YgSF!r6l_{3
z1N-aEg%tj=-_>%$>>uV#<}EVtv)_t7UM)9nQqAT7^{&cIq7W4{8V*x9mSU$i3e58`
zkQhbb_eUIxJTUj@;^Wx@pSQXcwr)ks^>kJcKc)BtuR~v+3(`l~K%Dxnq>1&mPw4Hi
zD`?$5B0~f)9zn_tJvKBNcaR#jTbUmtU+Wzn)Q-w6pLgy|FQTofI>*I2{o>MMh9v0)
z8lVbIYiS@VV*zS%PWk{;OxQn~V9wuc+^+V(JTVIh4YyyRhrePs6jR?kXW3=du`xaB
z%H28B)LHzXPmJ3r<*GcxVjaa(>d|_6T$38ftVxXQv$*F7TGyCUgS!&D#!@}Uw%GfZ
zuTy14@f$uIZY4TzrDaV;x!49rc}QuA^_EIIS;}=G>=|{bq04Ih=n`;$3)AME-@=SX
zrv7VY$&908W)K0@3zIMLUMaM1NTDbj5&nZD)l@iaHPOGUrenufstN-zfzevh56ynN
zTdfY6<1$5Rcd*{U8?vq<ec(~F4<NrHYx%@YvJ|fJ7>hz~yfIQbY6iY#Gmo8FSRC)r
z_6okLjsj5SSbA%Y8h8^v7h$!<mR1p!TMAsW(>CB}jMm%PA-HDPa4^L{U=$-06;8d<
z!d-?unzLHyuaI7v)sPhyQ9Y_qrlnMN{8z&wt<K8UvJ&>`@U*7U5o>@x`Zxn!uPCOg
z4*Kf}97>#6gz5{QHd6cJ+2GO{>w@<@shk`5)jx*T{Sfvh7!ApYVaH*hrxYD}nBHFu
zXrT>b(A&kg$7`w>>`bTMf$w}%aP@Ux=B}ptL-iCd*%us9n$*Jr%G9m5%N`YF1=ar;
z9<{7jZk2vwSFPq1kz;?qe`~2SNxHE)+#&VW9@iC#$!)+t8pW^WFPLa_EE-tWR4QHL
zb!-aO&Wa?;WUGOPYj%D4_YC4WC*pTGj)=91ztorW0z4U+B!S^fl#Ic@p<5ISa=VSy
zr83!e-anKk?QS`O5ATXy0Zkh_?F}CXT}lU|#0bj?Kauj@@qwz!mzvS$hpS#RK{i!~
z>tY2oyPBayO?J<}fp@;qUv3K<gJnb-`c{`3b+{EZJ%7%r&o3-JUqC<6hn>`Mdw+%R
z@e(WXvBW{(T<kB((<6h{Ax)Q&h3T-`k}}4vn-sOBFNsO+*=B^#e=xHeAlMSJ6qF6>
zZc30SM#5i$44DgXL*4y~#t1AX!!2s1$0g>nJtgtaug9XriaL@Phz_|v*RguJg;i~;
z39lYEI0K`t966(YI-LBr&L%#?Hc&%BpZ~_EEb0w+))Swlv^Z`l57LZXZVPWxgVOSe
zMAZ(oeTakOh~z+@dH`pqE_>rRC)*tO607k|w6`ayel#MqzY-EYMxSIc$F<hxkFKPL
zF4y^j3Krc4PM~%dhUe`U52bQeVJ$gk5$w*%@wSmftb<YSzg5PvkNu_U-Ty1C2Z;%j
z(}|<JiaPBts-b4Cp!vVz2x%`E+v3Mo=oRL!XkWWg9$^KwkUaPqe@~ny<|RB#XnDJ0
z3c1P<cPseXaf9XSRn3S8Wgty-`&I>X%V2AgJ78~+1PQ1|xH%^2g=S;f3~y~6c`jmN
zGf?Vx^Wx)#cpUl#W$(Bya;~|gScCEsBTP7#wR1$7LZ>!bI>#c+WY1>#rAiTb7N<Pd
zL28j^$-m;+@YHn_?9psPkXBeZBW$roldzT$W_7mq*wiWq&0N~4gH|{z_q}ir;srQZ
z=5ZqTtOXcGcNlYyF=NG#xaiqv+QV>KG9^ItRCjf#8q_N&%H|Z~MH`V5MWy=IvAb*n
z8#_>;QM`ndVcpVNm1J$myy5opoHLxCWhMyFXZgFF8z75j<HjOZU#wY*j$v#qZ+{oR
z6@=&+=0)$7`<-+3wgVw$<AK}?qH{LvJM>$m(-Tfof3k1Ht5K5NhDe!X$g;?pO>>)9
z?rOV_nWy8=Y*U1?>^A4NWF#A!W{bVLS^K)cU9py*Uj=>asLGP=9M_ak)<IKzXzqrA
zx5P}tj--z6TOQWF;94`#6KT_FoI=}FNj(_7sO<x{m@~T=993`smk<5lg%l(@+qp5w
zuU~3E##GAxv5=BCu=qa;Qna#-6N(C|udVC-M2mluB9KC#aH6vXDv*B)rA>KY%Whhe
zl1tVdyG}y21BWg9)G5YjZoXe1!)G3gqN#mIKLhgt!@ochelv~||D|~2ryQpozUQ2i
zuFcPbo6y)_+I>>+9@-Ozu&E{<Jkc~<X>CdUD)B3akKW)gSlSp~x|f#NH(}l!(Kr^g
z)VSB&{*@azvU4szcAtM60zCB$tjC`_@}CCawywD(hXjh_x-P)C<n!w~3UAJ&w7jM#
zva9h*k!EO&t!x(;4H)cEqdc=EDlS;P?X;#`m@u?w;VPk7hUY&EB`iexwg0txX!|Zd
zW^Hscv}Wbiw64c6-r|tfNanf{unwkdsHEvW2AYbwITs!&YhLrw!{ME`>{MARsq!z`
z3UZ&*6Lb*xJeAe*eB+z-_Hn^TCylF+eH&K6+(@6U4D>x_Kqn3_$lEeW-ADu6v>aT2
z*E>gw)dqLm4QE`7&aY9SPrX)@ZWO&N0D;l?4EVknOhRFDCk%-16$ZaGE8IMS)Sdge
z^gq%xn=@|O1;MNxTlzAXbJEl-k<s`c4=oPRs5jW7Dxt?1Ng15KN@IB0dTCKs$kEXr
zlmrt?HCglLYET-f?oEBCt_|Q)XZ<*88oMBvVk{@vi=0aj#(w26#60OY(fKsob57$V
zLmc$$>x#?g@%Pij^^vlbOg<is@&CShiSr3?lc}esDDRaz)RGEh*7N<PlG7b4y4Hhm
zU?vQ%d!V@suAgzCVe9~Zkk(H{T)J;l<VfD(<I#m5jAWCc8SpizdjhUI3a(3Winf?R
zG&10XrpO~YWOl8VMj#;A5VtPU@d1PEH6~AEY_xcq$wlwQ`LOuMiFzCFuIbHl>i&`?
z%wBQfz<2YeO>cV*`2uR;ICgB<pn6bT6WM`)6*SA-rw8EYM0u_yqHq;o<|<GzZ3cXt
zkJen0Gcm(DL(<QXmLT-gj%?h?oL-}l!0v49HMk6w@QA8!PTOyjx$FFMY&#`~Xha~n
ziu8SV!$fp*6~<Xz)NXaDq<2UPq;}LP&Ah^;qr!d)UTP68qiKrFu~zde@d@%zdswV$
zkNJ8R+Oq7vxBvS~-Woo{5XDYZglU{*n=}QJdiYqLY9wCP<ZFPmGVkB{p*}5rT^2FJ
z7s!7Kz6S<^w!2`zevSN)Ul{(!KUK=f&Q{69QPhN#>Hj$1Qnjp6Rd7doS+=e&TQ(FC
ziv?AJl3N0*1pN(x)>^bWoEc2qv?$T+JMcE>HnKZ9>D<5={%qDxOj}74#$(JcRRmF>
zK>gbd3@80(P8`mgAwkUa_1*a(twfdoXZ-2CXJ;z?JKgDcYW!hBU`H325hC|EADhj!
zP2Q^X(4b1GJ}N(Fc(Ng@m<WOYrQM=WmTF9Wv^?Gf3=l>(g=}D9Xkn@`-Vjk7Y{CYh
znVj@c4{X+U&dy$-iE_zeO<_-=1n@-8{G$dy04M-a#gQg_fUM$7vVOz5hcb5=G0nWc
zSlfsIah^}j*hL9f&SreN^>Q8_BOg))y6WL*cr%`M7O~MzHZz~-l$yx1yC?e;l1xu$
zpyFj3M7;czzqXisYY9|*Yc;bD*fu(ztayMT&#|bYMkcI_nBsCFMyG-I9h9ZYZ39vc
zs4Dke-4F~8t95j-gL+ZgZc)P0sxFN_MWd$0x{(({D89LkA3`{ZrdC!=)IF90-F6k3
z(UcoJ_1kZMWWChCrS1Eg1%qge1Ksm8Q>;Jq1`-W2c|=*O`A6r)bSrZ%sKemsZDZxy
zNQdZwBPtT4zlqInv^63=UdZ!p@eyR)AD$hH=4$hmhJhfNb!-06Qx5ttE!=f*wJ_4y
z?N$)myQUi&u614E)zsU^+&p+`lP<0XtsplImj-K-4Y4KylRznfw4v(ojkpF}6OK_w
zoUWDbxquvJefHGNNG13zQ?9{(K$G+-pR^F_@C~?zTvLugN0gIHDF?I!4c2CB{z||{
z4{bVYqgVSUm)P2Q^tyTUT>dj_z=-zlC{TPFC@YFod}Q**GYYOmkV)HSLTCg~OK>(>
z8rEx84UyAq*7fbz^{Z298>PcuugBOE6Iwp8B_NtsPa|<FH_`5ye87*fHC2|R8%9uc
zIUbUyKCLfZdyxJ+TM{Br;=(d)L4QmBaA3;c)%R7*yYOY`=wIr@RAYUTZu_P3ex2*j
zoj5>%s($BgsaI$bKkQcRz3GRQuHb~-YD0iDnW$fQ3vn3O+SHY=pNz|Prp_L!dVyTa
z!!%d9+#fxKt=vF~Z~A(&TUM8jT)4ecvUQ5EJzgW;*c(&xBdNRJv=VmSbYAz|Xf?DL
zzf8qez(%*9=hvu`YzqQRGpr4;OBhfrgi}lcmhqt5Eez2GmLeI?;q;5l=;iMSjp#Cj
z2|yX<Af#j!m~QHSy>9a8_RDJJz}++EdIRZyf^#M1y+9Ds>rA~PPk?<LJq#K`<pdWK
z1-1vNqNogLqu2yhgu4oBfkVWlmZ$sq`^EU8!u}<tC2h*!3}IXuA{JgAst;mE8AU>e
zv-rfkk2^j{4{h?xTC@F!GUY)or$58dp0;N2PxKf#k%9?h8|&b33KKwodo%9K%f|V8
zpcJZ_T$X5x?GEc_q4J-FO8;x2D`WhH4~=7@t5TK?8G4f$mi8#FokK^{(D7L&j5OZB
z_PN9KDI;m$oc6IpjVU9R53sB{BVO{p2t(;X=YNWt-uGiCgVCCf2-ryErL_uG6tPAi
z?1^^$vTqZ03*sXVS%d=Nv-T+;xIF_ahafNb0&#jHvoFCP*uH}|ha9&QU&Os+w8FtE
zt3&QWpOJ=psKtjS1;Vt1ZZNr!2^<ls^(o%jr^s7}Q1z15WIN=pk==*yLr@MGA5okX
z{1gHV;6rYQ7{exaB(EwCG9OaDI-7`oaXYB3Lpz79XqgEJmHYA$$>WD)Qt8Zr-X)6V
z%JB?}=gHt5v$)C&lj;)i4q!-kiDjs->Jm$0jcU>-x}s<n<<j>i|He?`spuEc)1Sti
z6-%6$;l`XbO01Z-;?Dl+BeSO;eugurQ=3>OS!7E?rMHYX$(67$XQ!SONUQyzau#LM
zZ4t<aiIl>nSxhuZ6Xjx}V;>8Biz9|_cf>NpxsfoVc{8X7gH&gbJG{Uc45-?Jw`mB)
z{FJCV(;}=NX3YrL>9Zxi8G3@<##VOuvedcn^#1d(@Zea7RfG8T>*{Bu%a3*Xf6&MN
zU)osOyW5f|>Zsjn%UTNER?8m*??1p#LK^)X)xj-EEp18S0FUsDk~4O)%p}rI#oK5*
z@4|wBfHFdA==1&+u8BMGZ^~FV@-<c-9E5S^E3PY3S9Yh~XQz|xap|wu=Vt*ReYy{A
zkjOnzINE?%(U&xB0U`nlF?EUoDkOfiJr*R{Nc-PGvtpby0~o~KR0C?nStxs5kb05!
zLP2(-FRDQ|pk?RsF3Z=bgnyTKi3P=CnMxq#Q&n9|7*p|7rVK2U2XjK2hyd$h#ubO1
z8yW_3WhuYtEC#2Fil`)W<P}jY@db>>Q&>q7u?MXxdc_;uC>so7nhRxr*MqGtC*>sl
zQ<O@4khUCSSK(Xqg`+`#GQ%?xX<FO9Y^-;2R*bi4(p&VBP%W`uo})veFUS#laJ`?S
zNhTqxWKOP%r<ga#&Lc{SF1G+$&lnI7hRxi)G>9eFP_+-M7*!F&!AWXx)&(eoNu(_?
zjF$bfB7P?lEUuCaMSzjl+eel~DiLfoFpns5%D@sRu}VKx=g;QLI?#$Ea#BlAZNdd_
zWSWZx?ayvWre92AWO{4+b#w81P&Izf7eD0L1trg8sO$8Nu21&bDae$Gxj;o8bB~Wl
z^iLcqK;>YJjnyEHokBwZvl+ljD;GGas75TbdJYmKX#;oKlAti9QAW4Yprw@qf3r?K
zhB!7N=#h|VAu>B9Y>V7zYs(GY<&+3r*M3%!u(?@;wP1Zn-h6RfQrXYLfd|FT0W+`+
z**ZTqUk&mM_s1x$Or3?gi{QNm637~Ii5vivoDL>@b0-Z6L)`_XgAz0sJU-68Lp`}x
zks?)zE)!0~RtRvN85+;Xf{Tv%yMQNuA`MH0I|`g@aF5nT;O=n8@99}lm#T}ja0k-3
zYh8y<ly^b9-T$n?OtQJ4p>A0&VYGXLOTZwOa(0ae)GDC_410epQhC*g$j-VkFFdGd
z(q7|4B|GAToY{e#F(N4LJ}cMHEF&0nnI31KXyBl5hY&XcYczpHfwNYXUus=7sx07&
zC|R+CZV{x!7}HChn;uIp*J9GvHntS_q5XSGrC6ww=bX@N=bS4ib8+r9i%<(fOtmqA
zeRSSQrBJMvaV$LN<Yn`>-3XLo1rC|*iP&h6i#!0S@C$7G!f9f9{;=Km9dr!KOMRL;
zh0esGd}}gws!{q59sF~*OW?M>&!pJ~KBWSS*|DU`T5&w4$o3d++0wD~7r^z<8OM%b
z?!KaUzoi(k0;lDu*Yf!%w#cRpN!8@RLvRHxvFBES7U-=eUWU0{0Z+}uGBW3W%0W`K
z!_lasU~<B7)V32c_3mRKlcR}u>(iEg@j8w!x+23;j)7tIhr=3euLNuxTI}vl<q<97
zYcAWDU8nsAY}gK!QGSZ4YwVAk#1ov;OmdIGwFB)qK2<~qwAL5cFb@`xWh8z!aMN#h
zQ^-2*b!IHzKdpqz=xAv8*-}n&e@g1?0Fj3K)~aCYXs%6-Yqsw@8#<88eO~dj1F^sl
zj^p}BzQ}pGY75YF9zMEIbzj^*<?7&(`b?1aAir4m&?+GX>_+UUx}e>wtzW@{CRfuS
z0Jn`1t}O#}FX{HSf3)`4|3LdI6Fkul_CR-S`}3(gNY6s6k3VdR1$X0r3>k{C?GLGj
z?YaG`FLqf*OLGf%H~>2T9qAN#0B+Nq7YJ-q9l(w&q*)nHd7Ri!!B*v9g5TeRscWTB
zf@G+cw@*E!UhhiXveZ70Qu#P!sl(Jeq}eu_j5)%;Z;DH{UL$xUEoxO3criZ=$Dh?!
ziujDWk1vaR9sG`&_0EJF^EWRtv4~RzwG{eWy#Sv;VPO&A={f$Z0AepcPSi(Yi6Gn@
zPh<%m&mV<UkvM)>GL=aPLBvcV%O<Rm4|&ED+ziASY=4MKHfwlI16-D4#)318FRYOR
zdFD5GDF!>(zOqu5CAyg(7N<{|;GR9{5LR>$OW&^b?<m47><Fd7{isy`#1J|n2Xdqn
zLDDQCa5EZmYs4Av2$tO8`N_UDcpl;Xv@j#F0W3rNkb2wzdt_9K{{6$rJ}iG7A_sVq
znRp4#POL0GbuS^#X4KM@VUH5nET3C*i7X7n6LZomRd6!_-VnZGP8iA=VDyvZG0s>e
z7&(2d0cN+N5s*4V{wkxe$KRy1SfjB*26`f%NyPG_kq*{o1wg$z<hP(L%X59BNH3ok
zpgFL=`2X0zHTd_rpti+;@hgzm#n^z92m|Me?kdIqK}h+P3Dk$)Vlx&@`{T_XPM6R<
zO#kPB3=dWVE{VNKinG~hQU$))W*$7q70P)+vWIJ6pA%3D;&4tS%NOaC51VDSyB5cZ
zfpqdN!8yysIeP$%6|^YmfUTYdFxkZo#t_;6h~VrM8}JD4_rOZsA<X(6u{gH>p#VNp
zd8;Xr)r)vyNt(5Sm1Wd60<lM1#0jI3)k|_Pv@2tIK&L&7*BX29DDvTl@Qri(&XcBp
zQ&Tn4{EX~f*YGCrpGP#8LEy!&pV@@X8vlcV=YO}b{_lP6zi)HHUjH><>+zQBWad!D
zR96BL6cZ7T&|Csi0W|0jq@>^gatbISqJspvfj%>e8M(FPmfKZ<3lPn<VKq!ah^Tg%
zOJ%i7xn^avrcHITN@a63%)ocn`?fUsco696^ZVTMaktYf-}9!^tmn=&%sajh@UM{y
zt*u)y{tT$xJ==D^<AG7W7f}AQ0Y2LgE`BnGUi-bpfB&Lja$N>xUb6gWJBcRGp8yy=
zgnfGLcPlRiIDUZ)?YAapPZ2PBXi+<!w`|^9eH@#+!{S>nJl>0aJDqoQ-dY*oyCZJ5
zv9{hAJ5GbhABlb2ZhH{)AC14h4R=Gqzn0-fcg4ZKrr`>26+i@B4|eVd28JlWea}OP
zKc?V}ZgUqt+HrdO{7m*!U+h4>4+g$F3~+tPZuC0SpE$sMF9x~?_S_sd%yxY_vLyO2
zgXoE`Wg|k#Aqo>0Ww4Cf#>jfpfgL8N2c5_l#WbV?-Y}D{LfT)-A{}2+-#RGOeBay4
zdOwb#nt^D+vCZcQ&#seG`)#p>#oNrwGGmGg509M|8L{bGk(jl6>R1(DxHN4?jR#Vd
z`-BS=Y^jTgE%4~zh8=MZN|3o#b7Gtp)wy+ZM%pcSW$YKBSQT_B+RKy3Cl^sUvL%#$
zBBYrm^UfT}3hkNH<{^l=7IWjas}hZ{70!dE88&mc99d$GI;?6TSrif~%>J+Rn)-9X
z9NK*s6MbUB9hx~msLV)~^hq*&O{vm0^K?kd_S<gZ64wg*PDM;U8F%fYg2iB&Ui&u9
zv`QC+>`Y)~JNZBy+dMXU=nnJhFsE!GqWm3mdG!op{I>KAP{)wS0{Vz?c?X4vT2aGk
z{Fk7=ofaTySWOCqnY=$kqg)r$fw?9@o)_2X-*SXb+;@ez)j~LD^X~a>8FlpMg7MAs
zBVjvML8_g@S#>SvOz>A_QYR<Tz;(|2DNd<9UVDTDZu@4>LT%rWbZq9>@ZB?fX_;qO
zPBjsD#aF_sUXMHxx&%2en}$JpOR9-Y!M9KSQ%@;~t$f?Z#Wpr?seMi6rt#ggZR0np
z={u&yT5+61A+`&6j$BhWTN;zr)X!|+%0sX7bH}fA1F!G<-kp2P&OsbEh*}}QT9ibe
z;)D>qcI_U*HZ>1hCi7G=nz0_rGF=yqY(2Ab7*8bwpD-VsKm{3T2KNM;cn@QTftf(r
z+`h&k+nq?}LlV@>d^gt<+T%k)1f7`!O4*SuZDG}3aln|&t~I|s{Un`uF{#sWqK2`E
z8o5^ypGGqafr36{r<JOn;{-P474c%h2jLP+9aE#!uQCJ+3HCVo3VO$9Z^*0yE?!kH
zV&6sLLlU^Z=<08!Oq1UamfsXGHE|+?%-*aH;!nwg_A-QRis<V`c5rDlE^2i~r^y;O
z9NGZ7)v)p$evj*dHeJlPR?reK14Z~DsSX%mmL&5tI_ajp-tjuD_)$SdX#Ht^E|l`2
ze<nR#l>+wky{Q4s`b)^5;#@4DaeN$@@XBmI4JlD8P>smWzXY25vEWBr;N1IG0kkIy
zeD>t`mGGi8z*FH`Auw+u{nMM@MFH@9pDytdD3KJ}dWtix`XWwC4775x8f9Sf5{c5J
zh?%q>>oB^F<&x;Q>86s;Q%k?GaWpoG%dl{)Kx8u5XN7-@a(1|N)fMemia>%aung0R
zk>CX7PT2c^?gg<bv#E9Ay7<?VIgG$EmzZli+3?QCpB=VbG|2cR(u!c<$rwuQxK07#
zVMJ|QiqYH@Jar#3j%TWisk&q}yXEvsDw!Oxol*t*_UkU>m2xdPf*uXaMx<kmDq-kH
zgcl3&Z!JKOkO2z&+vKx&sZB~!gzw8{+>LbzqjoR0<19gq9EGVC3ute}jr^72#u`WV
z_h?Ss=AxGK$1H;iJ@u2(7-ASn`BY`}3+-cMAO}75C27$LAzY<fC`)9Iy@&G5U_Dcm
zU}U)v-&n;mGDN=I`y7EGG0>c!{P-lR#lPU!K_a4w8GKEB7!fN_bWF?ta)@CrF_@?(
z@45H=+g%fOC?Qnauyqr@fsi?)=;>+U!d}jcaW#sZ%R51AaZXXt)cF36&uk?^%pD#h
z&N5#mpq6_B`MVl0p>U=Rq)Hrh=nF$!pGSE&WnNV8g{?yswf|*0_q%1T0i_n^!@)y;
zM9~=i$Yn#_kOK-N`fUB=^?<jQa`M9?(03ewqJ?3txsSjGz@$G_@Fs?P_7qzA$9@W?
zO3+eC2{G-cdnm|hTkBM2W*Ax`JGuBqqCLC9?SMLk_g$4svpud*>6auhF;a#7DT6G(
zAvPeZG!T>{Cp^w#G+l`@i@HIp5gG$w{kK0Yr-@IFyet%ZCte@BS>}S3wDv7osF(dz
z?5e`g=x5SFxAhzic=tp*N9mR}9p-~ppl&1U_&HB+5AVRiXa?~f_uoXYd3}<L6;C`h
zL|M5)$?j-sJc+a01l0vw^n<KEa;vTd5eoVO+gRcG09HpH#;dRqX!3;0gqiWbWjTRj
zaTrYKd+$+!xRVn|9VKoh#k87wWJ1Tju!mk!Z|(~QGk^z2mxUH3)s8AI%!<XH&Wc6`
zI_{#^GYfN*>0|DwMRz|XB|`01R!qIdIxgf?Q9Dz$U_f2`NGaYQlM~NLD3e<Bxy$oc
z6?AZ6quP)cg0m=5NpxGkNXN@4c}bZ#Kw4X`f;QM+GQ2QW75k`E)+R}1^S?sy*-c?J
z7nQ=obsvOK6T)uAY@9>8Sowk^omKS7Q7pvOA3P+usST7rgDfUj^y^<;{AF5xP_eIM
z_3Sf$mg56nCG*d=lW~JT&>?2t^p(LCqM0ij0<+K>=Uo&%QV`CWbNyjg`l|quBn92Q
zmgxA@@Cl*A2JpK&?SeJb5~q(B*0#Y3X<my^PEz@{7b{fekV|>d+JBt7XCJ$TYMnl3
z(6}k2C0BBpv(LcJx;FYfkchOiZ~I(2%FITf6{D3wuw1;=%r#RJ&UIaE4B-@zcCpE3
zmc*aOTzS~t++@n(*2L;NxfgJ&;ih1v_Le9#Mq`j_q@4{zpx)OO2mJPEYTBq#is@*|
z8N#jSaL7MnwhzlW99+=vhe`PPtjlkv8rzMT&z>Jr^t+<<)swZSiUj6(c#+;+qCi=}
zzv8z|G@5Jo9?X||B~!M8YWHwdqvy%H#r>F1eG>We1aKZO68VdI8=mW+#^VZK6ZZJ`
zu`D{E@@7SY;pumz-!frY%XFR=Q92=53g#u2@?vG)cs>KwPU9l90{NNFl-{O9MVU`?
z$$ez?><0`MdQSm~UoziJdpxV7TnWihuR$Wdi)^COz3C5nhVd8#%GI+Ob1-ZY1^2*<
zE8131KR6Bc6`LcoISz6kfLHKeH%M{P^Qi`zyFa?!6ZT3@S;Hu|92rfqPb>w%O8JKU
zyhhZ;?n1hZ$tW<$G&}WDM<3~r?AXs|6RQ|8Lq3o3$M)HFASW9@disT!x_PoAev8Uj
z>iYYlSwZ&F43$Pfd!ExiG&8(j#kJuZqU|PXlNcwj7Ppv6SPw`SNsdHGxSZWJkW25G
zB6m;I)amvm<(r-X+z;;q+HOrwHM|q7Dk<ki`{SIEmF!9;mAFCb%K=zDZ+SD~J~FP|
zgNd<kO*!hY5QF?$p@%L_a_33Eb1>ZuSPoOxU3&Dp88Dy0jQIUlQ_EbuQ~K4bf&wmp
zdsJY#{wn*N>7Zcj3Zu~2hm<?22m}o)8Wi75s2-gROEh3WHcpv1+ajtSSOMeRes-CD
zwJ|8FVX&z9)zABH852Q@bP%-kDSKG{qB$<J4OxK%K?;dJPmdNN_G9oFJ}w6*iQ-9m
z8y~{fwyq#LhZKQhTaM=p+$src(jTrLPE<vY-k+FL7N^QB4=LZ%Cdsf2n&4QLK>9b&
zIjKBacU}R^HlZ9mVNgNLwyr!}F(ltbIeJ%6Rv%#B#T%`3&_030mabocvLssLc4(4N
zE`>JQiE(5SkuRIHQ(nR?DRUq!p<9w!A)V|bNy>l*DNd2yR!ff@W^ob0#=$1Gx;;T%
zS;C-sjDj%=mgJn)uafjJbEr6>OhIGXp*a1UGe1?fVTu4IsrF7B#dbm2X$UU%tfcd5
zugELhd;r<6Da9+2Z(5A<+=KxuE_v!7QM_las}$7;hg^~7FuumL8Vn~nDN^-V&X6=^
zMRs)13fQ^ntC1DwB;&I1S&u|hndUS*Q_OTpg+gTe1nV+#bCOcq@Se-wSV&z;$x*MA
zPr>(PgRH`&XqnGpi?%Jzp=*UTzj!9dzb-}F(s3I!VFQmM4Q<F;WgF72oWhh^er$_}
z;ijvwd8gl|(MDy9GDm9UCtcrx%u~vhWW-zp(?s;MchXFCn)JHdnYG~<2V{_m@a@dZ
zD%txUD+ht(x*@6e>bN+u^;ym$gtSoh;uzH@c1Wml)!HSNh!+}#f3Yp`FqFPCp$C+S
z^4H6VL-w;;&v(n%$;wia#EA3%^g8X+%$WHbKYqzaIn{H8N@s)EVK11CIo1>58hdWY
zwtB+x1hWQleP;QTvC?!d$qF<1Vm9XDKyefit<g5>`Te|LMZ7HDbqGP)iKe-g1<?>s
zXDyfJcS%y(@xxA}u({6fu`FwZaBnE@B!0Zd9nq3`VlSK!(sC*%jKle}I?sx!JC`|=
zK`Mh<21b9$V^5smk(=;P7Uz5O4}1*fYv<%#f<Xpu=v)^Z+h-l6Buv9g1!a)3;lWDz
zXm8;^jf9rd8`oCRD`GUN>GrQk1zCi4-sx8Wf=-JaJEe7O%V?xsiaR2#T$FtD9E%9b
z2wcmc6IFW4eT#g}D=NwU>5`-gsIFw3bNlNs7}Q?gK9fkh1isABSyq<YCcU`r8(bmS
zH!l;R?LKs)j4*aOpAD~=ihK?!bCi3F*sv^5pQph0uM$Tx7GR(e4V3A^r~Bcq7<Io!
zO>xO}%#La&xNR;9aaM%hU_pu?w2=hNwNARVz>jN&GH_aGUfOX$isQe~s0X<5#RX{u
zT_zoh?;Am&hKu3JJ0qUeNu)fBkDb>&hsSNWWHvo}G+bRGE2EGv8Xc`4k>~`(!t=yV
z`JFgXWi>B>sd8{Q-w)eB1psc$R3Y4-d{De}GpGZ}8wX0?yB16kGzmiE<ow1-eu<aj
z&~K>?M#&RyBI*?)_$xDa)|bdL=J;+Z&@3R0oi$MmM`Z2AYC!Wg=!;>ScH&QCx#<Hg
z9bpZao{t>B?~_pS(!8&eQip!um0gp~Ie<iu<}T4tm8N!*ln7ABaE?)ta>Tt&#F&Kg
zF$bO3<lgXfKQ~pbJsyG&EQ#=nCK*3MzEW@DrF<2*nnUP%a*I0W9msU=B-GKasAki8
zQA0V^T(I4AA9HV|GcFT`@JsgW66}wMY!-DWxB9X3_w352Az@8PXHDy;AEFmAO$(Km
zC^V8|uj%8>8%)nyiPOgh2_tVlS`d(E<6A5s*%%9%)L!mnR@_`Q(L#)COGy|w#snzP
zOstBdRZ%9UWUZV3F%q`q%~GH9%_{YAb8(b|2oQ~D9@J*sn74NC2l6D9#Y$ghTf|td
z%Ftu?`t1>o>t0bI(Zk99LY9Y)zgp{zYSv5tyLOg;sw#`A)lg;m!GlG;VgEKwMwSSA
z!P7}@;x*Pb%YD6&BjgL6yBFU;aCDLEin2zZ)0SXk3@U4Ws@dH{gcBJq>D_1xk5Yp^
z_rlmoSUBJ-E>eE8vTx}txrKAu><whEb3a}bbWHlxt!gqq{csH!4d&E*r8~!UNG@@2
zEgihnql0}O0{Y(F{Gv<7Bou@V+>BJ_Eph?qFz(4ddOmGzI7aS@s#u<lL7Y$<M`BUH
z;e~unpai6wR$7F0VJbZq@bq{Tg-8=yJhzBJm(e2)k6s1Co?L6t{(G48H|`i|!tW%y
z`xe>C)e_}+y>6m05`f9T=RMupQRLh|6nbhsZRMV$f`2^iUEUX~5Y=T(%X+=sRk<h#
zBR4MO-0h39n?f$8rkuE7g9*|dsnWTf?mzsEVW$&KboKNm)J0d_Cz{9}Y1nRBmDVD@
zyCX&BBiBvK`ulVEb$ZA|x{d_V)`J=Jjz%SiVjss)<i2g)i#4Xzuy9PGagTQimf*_t
z@>6X8_;<#J<knUrwXiFdB10|AM6u$IBjTefk$(SrMFfDcI*@-dy-jW)4YIY}dQOte
z*`3lq|5^O;gtecD2<wMRMC)u4p&?G*3u1QBx)~L6zwYbBIXBm4(5R+uapI480xBHe
zXT5sCQG`9gr)(la_qWS*!7y?s{8f_nKoP3=))VKZ$XnLT;M1~86kV@IO0~_Yi)+fY
z#M+)TMK1-QKFZBlPGP!bBWG-lohMJ<!_(=~A}fgON%@P+#(qD4qIrw^5~aAHI$wTb
zG(ybZGlpFpHHm;yyS22j17U;rqVoGT_P7|I0#IoRf-)|Y%4}-DfdoLX1f#c_`;ZMh
zb|X%nrA9NKOHLfC_?%w;;(WJ{T_%M{_ny;p>M(14iW8gL!YFtOc~W>Q)%4_Pv%_93
zhoCFjW*G?JIr>Jsvi)#QUlq$x+Prd&Z_#q$xSg=wZ8S++gW#KzK4ZVn>r|0wjR0}M
ziR;*H#G<Q5@p7(B@RkJktT(Yzdod+cy|CMX$DaR0+#<u#saH&lj%X@_$Tq@7$9hMZ
zH0H{2!!(|t!xkYE;p$tH8MM7Y9qC}WfFN6pqHh8(EuzxFW~mwhq1T*ncuShr?v6c&
zCg(7Qa9&-I;3BrHx*M%<CcA<xr7BA_5LP$%dW;X$CwYb$F=b^Rhqnrm@a;g<2hg`Z
zQ7JZjrC<3y5VKl-z@bNcjzaTUcqjP#>L3`6a9d|@j8Z}@ff@Fj=h1s;%f+y=I}P^D
zcrA=y@n*-bZ!F;<!(1R9m(}>0Kn?D)yZ|G9fnhPK$M6IH8V3>$@u|#x{`ZJ?xj6fd
zbf^~d26PCUKoati1421U@oIa!Av%J>>b6JUC+rP+Dzr69#%K$o4hygDpZ;O2nRfac
z;hQ)kZ8%Lj7&O$2@Cr2f!W@LcpVuVH7N`(T8~XQ&Y0IC^B`)q2l3pxbGnh23e7il{
zG0hg3H(ubijo0amsc8%Up6a;CUv?oQXGVp}HlfmXziA#SkrzI@X9hxvI^q7|dX@og
zM;X4G?5bi~HpA_6>+RTq&)VKHC-=)q0UT&x*FeORxS_jaR59Nmamxu}6zO)Y{0(CJ
z?1{Jn6hf`8kLdKaHT8?YtwS#rjW}={r>rgm0w_Gt3)9^5Q}BgpKG66>3j6bm-LZcz
zdVGLJAn<<fTOmkjLf}zh6zO2fso+O>5FC9p>wsTbVAJ;OSqLY6Hum_uzc3h^BX>R8
zFt`5z(youBUlm^<w86jqX^{4)yO~Rc$@QS$>&Pi>U5wa|{}9m_)~4`24r^-&`JRV<
zdf0&2CvF`8m5uP?_Enw+K06S?15@0;pnJYjfj~Gt14Y$}_Yp<adQG6<_uByaS7()&
zU~w&X<H7O4^z&lBA;u=QW{cLfU~yBdGaCqGuUCzC?K_d+aQFJX$*=WOVhv3G7iaGj
zWm&Xri&omUZQEw0ZQHrhwkmC_(zb2ewkz$-O5NOdpLg!tyS>)#+3#b{HP>gfF-Am>
z5fQ!PgiC0Tht@C-!P;5Utb>T%i}EB?L{~9-VxZpl^TRgc4AUBe(XN4wH1|5F4$(2X
zQsDYgm|TWBOgN5Q2SUk1+h~?KQDgxqVDGqdLwqYC^~~!kAL-LteZF#=2XHOb+lur~
zPTA8co8Y>p+0*g`t^Ji*e{*nl><yagjnJpH2bpq#{?Q;HKii=($f}}Y$z#}QxdF95
zOvyBWwK0b2!W!4WvD$?n?#lJr0ux&9eFSh=kIJ__^8wJ_VVnEA02G@e)@>r^gT&3F
zQka1w20#li{eb0g#dqgqU+O~&bVFgDmoi9+hSKaCM)U*BV*sp90GT^&%@g8k=tx}-
zXCwJ9j9En72}I2=%iT=~Q*eCyT~56r!?(5;<(hMM@W4v0nv-BH5cyRE5~U1UZ@u}a
z5OOY(iTT8k?nFc8#1e_?;6&te_9?xVvm!aoa&$^#`-EFuR*Z3J4;qyuvr(<d8^?|(
z$bAX3dAc}FjZPRj-#EOm(8k_M^wLdeWl%46WAny7T!>M^4nz9P`_9dB^fU&QlN0(l
zimN6@Hza{3!6v|-OQT?P@e+6>)KhPQQbFyib*XM`<DzPzc4sv^r&yoTZF!mXJEQgq
z$$MjDmk5ovE>2Xi#2UqgnTTiB<v!FCjC?<@d+5hV!v#}L*!dor-cf4X3e63SJDcS*
zZSEm8f7J@qV`3%G8HF|4QCSj6P>@6?0);isa~~cjn7oP8Uo3YA>YT#1@nK6&Je{$n
zWoM5j#Tr-k((au;6WdbL9br?)+hI*2$O)`EVDnWVGvpRXoN1z}S{n)GW)q9{nsZIq
zTEv6~0JA(x8{W}ko$N94aQvx@$<>{j29v$BB1{%Fd6y#%M5b4y2br98i0U(Q===kO
z#fNX$$ScXrp6)5cwGjRrJ66qXeiH7rWTlBEAitO1gnfE1US@QtjdSM79>4dRaHf|U
z<b>r729S3YzUq;PUYXj4#S`1~@W9hIB`~rBMi2h_Sg!qk_=icrxSHQwulrE)rs;Ud
z97*zSf2o4Zb(H{P4B85wIp9fH0Hgv>YaNUCiZq2|Y)&sSHA<pQnmv{sMjB6~#eeLe
zhTg?-5_Nl!Z>gT4(mJ3w&C3Lr>|zx87qi-ZQ%nuaOM84x*o$Xm4Fl%T6b6s8D_*Y@
zP-|2T%Zm}Occ{7(q<)KMy6=as&DloZ)B)QsH16gF<Lq5)Eh5Sr9`3%C=6>z~{WU0j
zs}S*k5#?R+_*MSQ_l7vKGeHf+a>c8AZkO0b;l$n%x4_&vXvF}8OW~9N`b$%z^==;5
z%x!3g;a-G}{!FmX%<7v*V0*(p`&AGeZG#0+5-<vL4jVmkcaJR5EUGm1VuN;Wqa0Ji
zcGteOz_xX}sibh@=+5k%o46g6?aRV46^0&ohm%bx33nElNcSiwvbjCU#zwel5{-7B
zFP?3gJmX@e5TCo0sMHf}6$XQHjFk5DQ8D4dMdc)9;R)#1OC!4u6AT?KD^ISKiVdjL
zEikSSF}+yVNX-o*X+7M(L+4K!+m-CCI#3uLopxBy`|vt87vo?Ej8SEo+&BlN0z}eg
znW@RYK7Eut_6zG{S2PdVTzJ1mHza<=806*x?$m2VT4aog-X7Uo6HxZ?^hRQW2h2(|
zhuk1=9KmZsfw*j1K~{ARvOe{Op%#;~thOS2){>tN7}p8#4@Cc<;X>BrVep$!{B@H{
z`ivIYqiHU%cfdT}1<3W@)%iPR5W6l=+%2$9cbOkp=nVC_v32;vxzpMW*S&yzQ(6q)
zw!%>u;N<wn?vZ-qOW%UH?h-i8$gf%Y#Zc^}a^gK3VVN3$nI6D$1DnsgXNe`&CKT`D
zev`F3Gfx++apt1$0du2ad=Jb~1+qD#(-%)TQ0YdN%-XhQT@58KMwHCi>4?eipFN;f
z7h}|>=nZmvVx6DK+WdZIk|fyE`im?gWmquYSIdo@xd`ADi5^U&9%;=8IB$yF7=UMp
zETXuY{K;{@fc!+N>C6??SM+W&-({f1_!6hKN5y@%8M@(s6$TV^;>AvXLV+=316;lP
zBlRbcJA(XB@@_F?XF!R=?%k|JEwZ|UKg*f4#;+2mSlXiBupgTRu}@LWiANL@W8;aS
zeDm@ZrqM!7J57_3AmF8S=ri1i^##qtCxU61J@A{$kg(?@G1w!0i(PTX1_m{STuVFs
zQZq8}-+BGYxmQqkjf49*9ITbj4#zI)s@7Khw3UO&xU^&t_9NfLOAHCeG#ld`8|Twc
zRU!si{Q#1RYhSsiP41fgs6VjN&A`0e{?lCshrThGSi0Ip+Vp9b?G8PqM0UOmQA>$q
zhi@yhCqII{<FaGo;v(|Qi~$^7u~K7%lAoe|)A#4Sc|iv>$Q@dH<)Rnu8!<Ya#f(8U
zYu-~Q6`>3<ataeG*xlH#5jRcYHP>r%mrC7slvW|v*Si}ChfgAH9~KgdS4&xN&HZe5
ze~sI8I|?i$yl4#sb$(AdYWIkAT+O9an4NTq@SGmLt??)|jGog%IQe+(r%ghSw_-!^
zqM+}t)nd*B9J%9H_QU*!X9#4}17_-kW#31u#i|K}xrMl}^99`*vEIe*M7J9`-y_;g
zND%8xm?YLS#9)$yIYVRbhjT@rL#Xcw0fYZcJp&Nx$6Q>Xu94Uc$~Ir@#Fa;DZ#PpY
z4mow?EfQf}qdQdU7!#ydwinKyX_#Q}L1+%OX?qMyw}@17K8t%Op)lVu+iY$a{L~v}
z2Vk7kn)ueMKv!RM!tz9Sm!UP&(M?k=(dkLVucX_ww}ILH^szObnRvao#W34_`fx)%
z*|vk@DqJMe{J>KJ+O%9TfUf|j(Ne2a->b&swZu5t>quByAwHc^?#X7^=~&Hb5y9Vv
zL%AtYh<FwR+lFzv;n&N1^9aHB_w+_&-;?9SAPBsK?Lp9Pb@YUFHN=4kkl4f8gk#t{
z7?Y}u@Uk^aP3p7q!pI3XubaK!HPdrz_MQHOIL(krsBcNEcwzUA#Y6g2;&h|qs!abv
zmlJl<@I>n9BpbvwT&Dg)3AhY`0@t(H6|-^Dv}xtM!AW~%GXZ={R`ezbPtf_n8dI!H
zq%{`q20`a8yo%cyP6N>S!{%Q98cHY`x~#`|Da}6#Wf0BEr$)?Mio+6OluTgUF{bVv
zr6^(5+{-k$doSl+>QL-N&jJfHEzHT=6r@!8fC_v@EQ}vuP6w5rYrI~SA!k!Jx=8VL
zq4=t8f<HrtztJN52cV8HPPhVRzP2aS*m{q#=Io!db(?g4F?+^juge`<3*F+k_LRcm
z6Q=D_PCD5Dsb4K^^rd%*AVhQvi@V1mxgsOHA&UHkJTwgDH4-tX5!Ax0rvZA^AgqG5
zL>VoB^-w14z`9El#5W&p0QLwZl7}`y5WzR=ox!?6t@Hfq-!5AphT~{{BNg|^P|P8k
zy`;OT45^RD$vFr;Y3nPS*w@#Bt1wB!XgyMAo)iw9L>aBYy2}^zHO`Yo-Ia#**7UE@
z=tb(-TPl=(qk|zO`V3jm((`iUNxtFk(i^(rh~uI*1MWeA@0?CbCUG;o%GB)=>V5(b
zN#UTB(Q1`hufODgcJi~Y>SypsYB5P_d8D+xf%tS8x46Es@MIw5!u~9rz2k$Q?o2-<
zh?l+89d`Sv`-$I=&MBYsIrw{$*BHj69BTN9lw^C7@5Z-mBgds|<ovdMV;7|HCE=mD
z9qiMlDBo`lI;fNUWRTz(wkMtICL?8YGi09I&ob|520El)f5@CU<nnEXR;IO*VQ@f7
ztfOc#zWmS4TYvDI^YIxS99^yQT~-;e(;?S}?!Lr6atoORExnX2I>b8AhU;%R^gG+1
zc7M_`dt4Z~G%W5FDf2&9=dYfK)_1Q-GpoJ?Yd0>D_zm}e)@$aAw&g~&lX8gOSd|`p
zqZZmv?BRn*Mkqg!qZj5){~AZR4{di){UEh>Jl-(-ewY{bcl@tj>reWVrR%<u7a;F2
zKk?q4dXNuDr`zi+!>^!*^BGR3&#Zx6j4ZM*9QomzTI`<T<QF*eP%oz79S4KWuuRBX
zCF0INTz3@nnU**lw*&}+JX-H;#~ax{Vb=<N?=Wz^@|J|3k>Go7tZBHc!GGtFSbv4i
zE57ew`VvSCSTINbE^}s0USRr`N+`{MK2xD47Kko(i9#zvwkkG0<K~XBE39*-d2Y`n
zp9OISZkiYMOd+3}P>~{FERs)~Pi2knE;<_*GaVN>qE0m{<;^GpS1!7nvq_eBTExsK
z8CFg%|NUB?fL;pLD7mEEWL1dm0yoeytK<Shr`)no_Qy`E?5b!%1tz;1pQ7h4S(O@t
za@Ai7utmQzAs-QIJb37EKZ(~t0K~%x4JU)^?(M}mSsB0pvc6TSEkQ(%Eh|=i@0lw<
zYGk8L?Um?c6dYAM0DcEZ;PaQd`kuZ4mfir+WI(QC`Moie$HR|-`djYlU2QB^z7a%(
zE?AUXaQuP7bHeemDd*`%2LJEWa(i^mk7YAhz)%mCI!yhRd~>*9$}qZBlTw+DH>Bkz
zF;VX5hd0d%IF=Q$6JaOkl7U<{=_&P55RCJzOKFE8()RG4-cLy>Q6}H^0qFL3=Mqp|
zJS!NKZz7Di-E7+p{Bt{e>4hUf8{2SS*pQK{5FHS|zjTWisauqINnCqfVTP1%c^Frz
zwmC5d^EEn%CJ#$r;HL1{i!FX%1>HdF5U=2$G9>T~1D;<sgiZocDSQv4@m`PFU$MY|
zuHJ*q77We<c$14DXprj`@KMAR9m|f}$!8JrQj>yNER!RYr`Cq<P#L~9i0**9NqDS7
zc)7^Rt~%tk-bDZDvaR^+r;k#uBd>(6>lMQWKMHeI^mHb6EC~V1KQg9H&}d=VY?|6}
z2rSVOoFonNnRD!L{nMz^vUzbYO8fn~V>QO6?O+Cy0xy+dpKWNcBd*I?VFrXCT6_0l
zf-WCA%NQwEcmQBi*#ovAwdi^9uepfBV1_*we_V`CdFk8rC>iQtGOI~e23vo5l{mkd
zU@sN-jOVW(|Jq9RUYIwb4E*CqH|YOGS>b=TQvIK9XL%zlQ)B0!c20orAA3h}!+*Rz
z{-24NDwQ4i1qIa4EB0ku^z>hlzao@;%fBad@)1Wjg$KY#$@y=bE$x?$E_K`O#`O;y
zGBAx{{eJi*-EL0XNC~_97xJBW+s?dp=Qv&SeSF-5_A=`oG6wKynlPmoomK}vvu>&z
zNToxJ^DZ)08K&$-E54nIHESQqiiE-iakO1R4;;lL$qqbn_gjR|B29$y@*=w)f>n`o
zVPW$yHG8&>lFY^JF^TN=8jW_=`!L+(vxOeM_w$RCQ{we8s@wwCZG8eL`?&=k&c*;@
z>zg|#c_lYHVNkc>hV_nvJev<5vy3gKRkj_b@-K2!u%<5whPCJpZ+uj-PNxJ|j%;i2
zwu(<G(dn}DjTAOm+~$KRZS^BysyU>|z#FM_3>GS4hf)#)S)pKfu{RncY^U5gzkd%5
zDu;&Oqn&9e<<imI!-9pnSe35XmX>i_wzJ2!GT;=8Y<Eg#*A4yv-+~54LigFW3P%^|
zX84^sT<gk(4>yA~{<ZuoY=>?MuiL}y<@j}A=3&4&?9H~w!`gT6w<8-U>yvX;_j9v`
z`D$l-2DZxxOe+C{npW4^7GH(cQq>1C-DZR;NwbNIajM~?Qqn8cdMej?39Ue}T1rG*
zA7OPO0kLxgshHp^#OhehCI@MEIn66x+2XW$VY5*hIp=H`cAqnW8Kf1{dm!p<^e#I%
zW2oh1Lawqo=qsAdF54^V-C$~rrn*DW1+i&#Ji)MRy;GM(5k|7-9OPEPXy*a|X6Xw~
z6~Cwj%1C`l36p~7yY)^IEzdhtF5iQ;I`-?|bi9dpyKcw7XD_S2i7fd3gC_ld+qVDg
z2&_`mcG?g{{akjX8&aJ&nD^SEmi@8zlNvHr&j#3XzOh&?W0(vP6Q6y4SW%HQmNYD>
zryu2uaFTI)c3N;JZI6Qq)|_la)@Gn_cGBeeV$JDwy2V`m^Pr}r2RLm=ohxe32aKTf
zg)t13UkSh$hSJIw%%R914$ZH|m^y&SuXtOQb#esI9tzCDK-(NMM3r`It=P>8q!wx3
zcb8)wVKiLCzt^>ECLUq4mcvZ;S{ZT)oeZ>x2~}nrL7}P2mPO*-&!o4!W82xk;zq!2
zyP{;7Yer$-tb7$3IFz-sg>l+gE9%=va{CCiT(H^J-kr;+eed<HebvxVT!P7DeHBVK
zWQ__;L8Ig9Z&H7W`3)%O>cynTulo}&1aBT=>^09j$gze}mQbmC#Wv}Q%BfetD=|m#
zl#W*ww$Z&KGY&0g5UIHki^LfQIk{bKGMU%DaO1uR4LPjG@Cf42>56#Adk=@Sqz`D3
z9O>(gCV55axuY@TL2l5wh!w9g94WgCdRnAAYawsO{FK)NCxchfH8EKHGw}FJdx!qs
z?BrpFpoTALXeKN{`%e@QD(c%?%quL1UVr1fJ#i+X`m=TbSqd)H$(?{+koCOgfMu3p
z>tAApB^R-vj(eekCX&w6=^V0*_yaFkGR=tXLqkfNt=osul`=IxGm#zWcf1cC{6BgV
zE+eL^GnjvBq*$J9@K>RH_y82Cxr4#TU%EdlJaZt?b)cvg0R(Jt6O@!1b2mTOLL0j9
z{5p<Wn;}WNRYMn4?Nd8qw#xc$ZR$$=s`iMM4;4xZUc?7Tyr&I1FN_Ne@$@ZTka1vF
zz7Al90AFm(5-!*u>iXLYxY;}NhAbt~`QB~D)TbUeT-(;pEy5>WNSX2GDIA&o1te)$
zsO|DgdD$8F35p*rwrqDOXai|;_LAt9{j@aY@ZLY_8+oqVA3!mEFklWI#BhS%rAbI|
za{1lNEy*mhi#4faWeNO0P;s&f6nzl_XhwxcJQ5xTVKD$q@CCcb&<1tR>4m6k#PFFH
zXIotk^SWeQAyD(O`*hf*e@Z|}MehGBUSs-(E{gN}_)mU5IAvLo@Tk846@<*sDEJ19
z-;j_Oj<LYn;u59`tc9vs7;_2;3*(fG-nNvT9L^5oylr9ABYG+f!+z713!O%|Ly&C_
z$>=CkjqOxfqS-I-N0J5EC?7gRRu)rkvs$VaN_-A-xrW%70jfj{L)7Z6RDmr>dI(mi
z@68W18XUgKK$<e8L$FSy(mYZ>cOr{4H>1|fA9ze)Ieve@{cCI+Q9hz?`*sjtm_L4q
z{{MFp{}tQ*t9w|((ivq1?Q=MV?aqC5Qf=->AS5+TP{bNC<KRWwFS=rXpwy_MI^Jg5
zG7>08D9y3uLhJeBvy5U}i=PYih0T4edD01?)s_p5Q(PZw3pwwXXSq39^Vd_O36*ty
z^=D<59vhurJ6$^;+dlT*j{>QBU<$F%sFkAXWZFz%6LWMV^xRMg3D8zIP>N})l0>@U
zs-u*g5ynOrt(2Z7S*87at?GTES*TTSCYv=1pFndS3IQ+(W9}NmRA4M~M|~vuzKcO4
z!TBS6?!pfQ>Wm<{s1pKI%f3>>CA=?<fmU_iY%*B6inWNjsyAHTdczCQIep)JIEsD5
zyfobU3Ab5+WH0rU-NfSE)Cbnk-7)r~?s}A03AeIX43hq!O;q?RQ_)Ox$@9v{<02i+
zQl;=@lNO9<*81C6uw?m)TRJ3t7|Z>5o+caObUvy0a%u6pw%MMXTd4A6nq)Fk@^CIz
z5={o=wu6BijVdGXbU*vX%}B6U=CPDh0X<IQK}~5XsOv#^TBPxk;5<<Uo{UAANL~DC
zS3m!Vck&@^PKcx6ScgLXO2;$&o?S(rGYED8h{CK?7O=6{aAXY&I4;OKL6cUhM)#=(
z4Pc$xG46|d;u#~Au2J+gF(DBF5{1QecGA!67N)wiv}IZXQJ0P0SQijKE`HN&8P28-
z*9kX@p_n2}wUU*WNMw=s!A7BH9yg{#l{i5zMR9o|lLpBr28Wjsag$YI7ce0wxr)S!
zxms-nek8(BA~GvkcIR4j5uom7oh|z(^5-~DXVimUcKYD@PGe$gQBQ}i=$jY>ZN*yN
zmI9`JNzg&tI?K=`j|flXAU8#YZlYu?XthRaPdNU1O~#TLZov$j8X53pwk6#kbR=pU
z3BUbyOj??LIz8g^K#LpTSLD@qddk$L9b1CuwIAb9QGGS<g=<xUw`7F1#njnovf`0+
zBTB4_(_d#3qnLq$#Zqa{1lobVNl8bG6s%AOgrmx8P!(Z+z_aOXOxhl?^n0eEg?yf$
zZmCGZ`x0uQrDCl7itCJLutaqz@})ZBdM_#}RmGctq2dL|m-3)8!ilryTSimymZY<P
zfkJ-evAFCJaymhq+H<HA?iA(eNg6WcS7roBtM-tX4zd<F>7uT_(D$U&ypwYZV}pCF
z-6&?=uW3Z;An6zQveqa9X^ovfJjF%c4#Ei*&uf;`6ts7APe%a{XCq+2qLl{X*$h%t
z)ShVOY2?}=bv0$Jfw`p?gIZA5BSX{iAgUC^OVoSKiu>&wtnJaPJBL7@RC=kmp%EOn
zFi<qZNfV}>Mf=pgREBGmM_>YX<nPcuYPUG=YQi6sM`Gv`;a_sUdgvl{4iJ!+qp#nS
zZ(||^z8Tn*aZ{1;l|6*l_IYncT5|lT<lFPsa-I>)43GB(OWnDS6-MHMspU?XJ(K>X
z8Q)D^1~?q+eEqJzpaynvFk)c?x5}a*1fuTlmMZ;qYMV|Od*rX&dp5;Le^1>!vg17|
z877AKuG44FbJ&7+2NU+*Eb>Vl_D;ez*wIh4ZQi_z>rOfvRg1J@w0smFVUAe!SeMqN
z+>E;EYz7a^!K#bgp$Q)!I1x)@nuXXhDVW%6%w4gUrcf<Lyno3^iJt_p{{51ox{1-g
zrNvw}Qf79`2;>CLm#MV!%S)plpSs>aA*p>L5exaP+3*5~Y^emPKnER1RDU?PO&4zf
z89sILD=T4NlBaPY?W5>S4!#`IA=ySQj<IES>N2>`fmEk`?!y{4CmC96yYA7J7yWGT
z(S`z$Iox#aNcjp)U-4A!(3{lCbR_Nk)DBZ!$I-3Oxz=5NY(F_+Cn<i?rP!YZOc0_K
z7ABu86>O9^0^Q5FJiATRn5y|#u8ZRORmICDw^imu!W_eWxCMTsI%cKr3x!@zA97-H
z--$_LU#c(lLb2^PBa_w_*0>haA%QUSC-GkIm(_EsH+f7U_Ps)E@{e&QX>a@5BcvVr
zUA*YaZ+byrV<A629h-ZUup{yqT4TDp>e9=gf1K0wqJC^hz#YAfp>z|4Ax(2#wJ1un
z6F8dWwPVa=o!fLlW%IY7^e!}=CyITRgjiE12s6Qqm`XbUKjQQ`-)c;{*0=qKbd7uQ
z(pBksNPFT?@KQC9jLmI3y-`9izl@%)V)s1XRyLkH5WjuM3fq<slJfWqkiu4M83t1o
z?3;XB(Zb3$j(>$|T}wW~f=Ef7(GM0aaK?rr1cLIXC!-X`FxAJfOZKTYF=z9J)1fT>
zNgr9x`cjPUkI3nH`qYpSa2YcXo^r@LQefWLICkVsINBEEMLe4(<V8#-kF-Y=(Mv3&
zN7|jv5WY?}4sA|55;eC1a5rL54paPtw`@^I8hqmU4y<9k*3^49r!6(Bj>szL0Qw`h
z`s)1Vt`|(Cjgg$#d)u)Ot}zg<F?1>X!^$IopT9U(ShXR&30Bxz<G9*e?CBRyfOVQb
z^BY<1Vo<DhH_H<9`nzD`nbLA^omBVhipOL_0iV9;+coiei(~JMxsXuf2l2Z3g@yjK
z`1+7}xG5hXV#cXSy|xyE;7r0F$Sb2OBU21){x?C>Vta}f)&h68{^e8qTU}ZZ5Ip^v
zm;&s$>svwo<?Xnhyg-VhR0t|^4*EhKo?Z$a?1<3(9^={UxIexjCTmRaTEvaI1ciBy
zAjFx$uE#P%!W{!iOoJpcd?G<8Rc8!rPi4$r&1v5b=Nkd+!CNcB*B}VG>3SQM{4u2y
zsJs~!N?(EIxU*xiY&y!Kwem4D(ekW#c#EZV8eKY#%x@JO7GMxb;WPBSZHl~gXh_rZ
zt=t7K!V<SQg$jjNAYtZp3Y`J(zEaAK0j6>#MybxjryK^4R)7TkZDj*9ETcK~pSQXT
zU~2H%tPbZPu%sic`)_7Uq&WFPAwfEqWkc$08j?a{Z5K!Nz_FSvvn7y3K2E6uIS$WT
zmUk!t`-jheBLTz=y&gk^`SC*s?Z*$=|0^^S{gzHt@c{gnz;lrXjCZCg+Sd+4EW<|v
ze~TRqdP|=_y{R(-)~u`X)OwxOy6^^E%NU8Y2##c8Lh(hOoG7Am#Hd#%`|+kbD0xk#
zu}0|cT~W|QBIr?R(4##NG@$e^r^MnhHJA5`>xqxglkedvzUM5j=?}YSZ|5&Y|1~L1
zPN2-9*O+iR@@{LRif~(UJ0^#U@C}(wJ7Uv)coZDjO-rMW@ay!}iNP)Om=V7DP3yjp
zH(FF8+rAh)bX?5(-9b4R@~aku0eTp8e8j!$j=kYpRs`s_4LF2QSzePp#&^Mtuq}5`
z0p|k=ca@A0nfKLbtBX2?z+4T=p#${s8)cXy_kLk8U$gz6DDs+V;ZyXybl17k_b?c~
zRM%bTR<}{%`swa!ecR2Xhzbh6A^Rb>tAfnmGy!np5CiP(B2;OgPfvnQ#+h;O5pSt3
zY%s3%6-8AQuZ73(M08*hC;Lw^^hBFUFpVwQq^(JKk-(SH?Z%yf4P`#z0>4$=f4aE3
zG@5|Mk{sDvT3=|8tAMD|>TH&}%p9ml<M4=&zLI8UU^F+fg9r1*C&)%)6`)h1x->Pi
zyScJ8=g>xpgK1kAgl?s;rO+;>3=R&a$VIC!3?9eCJi%}9e=1fIAxDyOMOS(LRjMP|
z##5t&6E)gv?(0t86IBP8CS^qk@}fr3!;upUo2NgS*qaFEaU;q<EP}rU<!u9O?GJg`
z^9-0Vqn{UD?{zl@i>+n-TJ`!|)JT`<H1g`X0j@Wl2DYr2=Vi9~9<JZ|Be~O~rLB{$
zf*6<ZVnNm`)JZ2U^ikjt;Hw;Yv%GR~Y!2_A{czo{Neovq;36lD;BQT7;ra_RdG7jt
zjD1WJ(S~c7&CQgUx0>^lYH7X-#_zsZN3f5NP8$woq$<Ht0NQj77HMG;!M+9L$PkqE
zZALtu^f}hFC{b(6dsaGC0p^&73Pg~!i-J%Gk9^&5K-&Ied#sYUiP|)g)^9Q_Incyg
z(XNMZe+x>wESbM1wYCPAv|AB6Nwu`{^oUq-kXVXHQK4;nHd|ww?PMjswD&mh!}`eO
zDDXOSLa}_NQA6zS1k1ms9YPLpyt_Zz_Tkpd+Fki8CQd}ieFwC}YfRnJ{bZRp(<DK$
zY#Ka6{6e-dhoP_hDp>f_AVV<3Oy1CA52u;(w}X-)J#KJwO7a!&xf8=BE5pK>#;wB1
z2Ke@Zg~uov5Ha%R6^HXJc++TS7f}foH4{t52x27$`ZNN_nYsm)&Fy*PagoMe{f{wP
zrSiyo6hJ!;Za-zZek=douUjX@(CSEw3h5GB_nj1yV!0F{uohJ2L_JFcom}Mr*r`}0
zskGs4p`F3pd!L>^69zW$VfIoZ==Itcc_?P27J6uAs26&uX6*dD&w$|ACr9v&UEy;F
z@r$b)LrOiqHVQu`;B!Z@Pj}x4a=W3hLq_<F>T$nO@0{Rc8y0`uwRcx9e(hlWiaX}B
z{G^(CgAR)VFEVCKIi$`|59|LJlguK@YW>Q&MG(*5s+Z-JHaZzpA1eM8S?qoT#GiDm
z4}C=yznXNB^SDcLQLt3W!FjhU<=b~PUZ~hNJV$0XcnxMb-jGj`HTe`<k;5-O$1uLW
zG=yR-?E5iwrKy`gg60f3u(AtqXV-*BO^uq{ynWTlX3x+C1e-dZ2>K2$K$OpM6|6l4
zjIP)62mD-ZwVIn{{^$i3l~BD_&pw)UJv08TJe(ZMDFqX!svj4uHH<da<}MuIzU^S}
z1P-y@Uy-<8e#FXD9DciGtVI?-zoQ7v0wVzaDG_siG{bdDv?ltMR#3mDhp5-3H|8;w
zopyvy+I{5!{`NM&<SRFYNmB?>TmLGWs)7a%__9-H=2vQh@ySsAAb6TpdQ<Ub&+WZ#
zb-2lgf1DfyR{}qd&&id@mGl(C-;!L<m0%#<N|NA6)Ju}c74>w$-xB`2;PGHC32}F-
zHgD_U%yX7_f2u6$b~u+^*l~ACR+xG`SCa5)gWnbPaL4Njb~bY~R}#<97t0^?knZ6e
zw}MPILa|}zXhozNmHXO_r{HE8U+aBleXPhCSw%tOkN<F|OL`(`R@)vh5AH#=Qvg_1
z?q-b=oZ?(<?$>nHi5R6HMLtASp&q5O=p<B*Q;)Nz!KDWh>vx2%2W?aC4%^)pY}AUA
zP-yvWBm@^I1v-VILT%Cgn^}kgni``~P$A^^a8i7JmuuJX1XHvvOPQFCJq&{}&~~Ag
z;@A&0CO{%qD+yNZ8SJVIxD`Bz>d22NWB&}yG%;8i8W2Zj5Jzf|x~u?5<{w+Iy<E=T
zQ85Ih=4@LZ--JNGPu|fienEO&f!m!KpPljBo1%Vp2fsFEOFsCB4wN199c%ih4o6OJ
z-PzHx<OJs04rPSf?nRQ)BvEf?RKNRk3*C3k1};vh#jL|?hB<;A*xum`y{&rO5e}#H
zg*Qxng-(#Ds_a$8bB%!>RRK4D%SAY_&dcpE#3t5~Ccu>5)LdZ!Mayv2@hf6o)S5^)
z?VHH2I0-PsezBuVaXl1AN~1eYj(CUHx^2)(&lE@Sqb>6Ee%>?5kpw%wZP&M3<f(je
zcnKAFJ966NEjZQKpYx@tI-)vB!=QbxMqbz`U_8I@EM<@{NL`Ef&}@)1Epdrg#ciYy
zPy*?UXrih6hP<tqYlv{Eaow^{U01j|pR!*H`*qBV7S3k@BvOv8Jf@k}Y8lDXQ>9Pq
zG~c__ruTd_kVq!|yxiGgK&@Q~Bg1N=+x)?i*TpEQWcsLRQ-zx0uARBJoVL7?eZa5~
z)F$3!Gh`seV+xP6bGj-|`uE7WobkFGZk~er#p59$yv3a&MrGBXUPyxKLfl2Stc5ge
zqO*vHNw-hCSl`IVqsT<v)Z<T&v+agkBzsqIXlmgeijI^{hIsTY^L{;R47!e-PR=lF
zAKD<ACGLRfBK<~4`h=^2+Rz2-u}aZxS%fjvd|C&{2%m<_sae`E`|4#uco)V<z3vcP
zEB1;JUG)G)9oor(oj2IP3-uEt+%q$r{&33;d&{4<Rw)laRe3Ks8`Mf!S*zYuFWevZ
z&BFK9(iFo)Zaj_(!ZUmuMWoIA{Z>`DefB2!mWs%DrPO_R7pyCl6@!j-f3HRK&5Gs&
z{w5g9M@rYy62`)u5xGb3D|G^+)Vv#i!;xAhBm`{LRa=?ifnh`U!L-nksPt81)?Ei<
zrX0rhn?eWj9QNswp@b|i#+;|t)_OKTnJ4blV^zS<Enjc^bA@rN<ND1?5v&ugtO~s#
zM=dA*?n&UoV%eaFez2R_dPw>~G0I|}k~tcTyx@v<1dIdZKRAP~o@dC@bury<+)bzs
z*&IfE@kP`sQJ-(*7gh;>hKfYt*;KQI{Ho)fIhJEl5%Ohj5uLGSh(rqPQP!M=cp}%C
zoAq-VJ{;F`>RuwUhSU#fyP3^zler>m#x=ds=%zK?T&CMA+E5Brsz(kHFwNYaYTii}
z(^^9j_)JSlw!;qiN_{F{?NC<k6qUwgY<5Xzn-EwOxW!Y$&mWxl2yX0V4fetL|M1}&
zT^y`m78pMaChEetcO`EqHghA)Vcp4>ac^`|@7$QZlv{;zoS`&X$;mEd$pY*|u$Tz4
zH^l!42dNs`Pu1GHN1AlWviHc^f3ES86#BN`@X|cPP!2>^Rx;d*dVxvos^*;4e1FA2
zd}TU6X}?E#O4wIY;o1WN>az<!SLQBpTs~@yAvw(CGm+EwD~wu-PU$hoIL=rO&5F}h
z+(WFUzrf7rdj734QHQN+_3(|TU4Z^4^xFTYpk`=f^I!PdG;T_2KoB)##@5LAT;Fys
zTl=RVE}#OE_*X!nfzV1zB2hN8vlR1Lzl75s$cw_htV5m|lix|l$>yG~Z<pVX)_&4H
z%07ocCL(HC!mL6McHO(s<O9{RoMY*N0k%AbhiR^U&W}CWS~*$Ut@*ym6dHJ0Q^=F-
zz)ZW{s<ixeTlb7(-K;Le{q^pjI!R_+hMf1ZMN>g8#IpF;T)a4!6@e$yI?b;AAvID%
z*2^#j=&mH0$Gy|3<#Ea%kBH)5naI<=6o9=CEzKG|8XPU@T*1?^2oq-qT7tnC9TQeb
z(Ji#5uz=36)r~)IoQTnYRx*j5f4#V!Z(yAd`YuY2eHSGq{;%1Iv!kJ%lbNX_gOjtN
zvnhk9shOdRjkEGU{wO%wyIPw3w{(k&w(^1?>SuF{AY@4X(J>riQ;`(vwZCd`UzzeO
zlBxJk^H>7-Mq$Gm^C!?(ggn1{Iu%~}EyPO!uDmd)#I2CWs9U}H%+ZF^^i|8Xem8L1
zfC!$Z%o%6w86tf!KyiQ!?@S?ETu1_mC9l2kfVujizqb-xnS!fmuRPQmHvIQct;S=K
z@f~{0pZ>}Y9#C}k&OM%D*?E-&ufCKxv)`@A$Kt=_i+T>$h3Oeh&~;~2O+!ucTF2tF
zo^1OV6<ql0w(XXKy{E0==3!NRB01RGoCjPgWy;!d7-_$7LeT1lHsBt45*tZWhGKrH
zV8SwtcmJ6nSBEWFvh5a$AH*@O{;C)8{ds3hi4ieEBPu{uxnkXkmMgn+voVicVb_Yu
z6LD`NIo69PXOYGNz~g}39HawjaR@VHB;HiB8}J_H+px!OjdXy!2S=~9*u@{mzQS?$
zCj$u@WunFFh!ALCZ#_wqx7z5>AD{g4)5HvorRNdRU!{xn=8gQrBDeHq9V8B%w`?(<
zacMTB+>hiq<f0=Mlt``8pNB&jBr$K_qBG-x1j)1Mj%H_pA3{P9da>8G+*+=@;z0*5
zIFPUwp?L%oYfKz}7Mg&XKzRu7!UPtYgPt1jEB^$>j~k69t#Bd*?6yE2!AsPQ<LB3+
zLw{l;^H1i4vvl3s*oQ>H97YtX5k?t{3mgN`0#eH)Mtq(PR9Yd&_DIpD#RZ}IqzgjT
zb&<bE^vrk`x(}U~zgu8FK7=la3Lz<=N@k_6MbH-%bM`(o9CA>}0njB>%1Gt__Gyh6
z8-L!n;BL3mogks~zXAoZ%LMRBCgGS0f#MAE@C}?Tepk3+>A#}L{r;`^zOCtV8UMY%
ztG^$?|8$@Ke{68o7#{e3K|~QgB7)z-S-{xh`G-Fw%LK=vLZ@nfqMFW`jqOo#{s<E`
zk=Ehus5_c@egp>$mJ2Ex{2Z+ettY2-eM_jV-dw=pYw1F6R*n0ueqG$G=67m>+&|_q
zafi4-$#Ka#AQ`u<S#5r@Yl?aO$0JJjQ=8CcAN-kFqkEH^jfesfSyYibR}dSeJ{{_g
z;9rk*S;fRx!nc{V-w*fy++1}>OJ`F@5qmplQ+MZoR$){l`JjQBP=hHxZ5E|yc|#Ef
zaeg(Uqc7VZIB`fzk`9~RTA<_iiiB(OKpf*>nr-Kv!1Q7(M+=Ks%b=Q#0Aj_Tmc#q^
zQEd}i;rM^1s=>8X)<V@0ch{GNSZ$bL%3TPHon$2uzio&SfB2vse`MmmMZlYqkgHGV
zn}S@ncRpNP1W8kb1ojhp{nCRjm;@Tu|5r;tk;wvUznvE}?2jKD|8q<K5e@!n?SB`h
z-M*QEKjku9Gn@$(##L2%wdP@hI|Qwetn-R6D2Iq4Psa{P`7WKw<;a12BYJwx@#9o=
zCXNyj_}|PQgx;rrQo=2oQdU-Gb<L#vJRNPMrVD&}eA4(UmloB1vrXz0f71X(?U_w6
zpX_>K>!zLc!A(BzlB0V9VDvLh=lU-3TVICz@I<b$`|R;HodEiTXCXpA4GhSm#<?`(
zw-d(c#*8r49FKq6Wku4j5M!M)j>3@QQwOln&9_evCDuI*I95w$M3P{sNK=n*#W+`z
z2WpJOdT^8lDNzEhs_Y~l2-RYZj61ZDFm0b**;4Ap>Czs>QI}m5#TNI}h*jg`>)XMm
z%^_O;$a?O_mr#SJlm|foXCvTHKbx7SnCc!|)jc^WcM=~kjw8@R7ot0J#W~RBFTR*5
zePL`Iwno`gGekwaGF8+~z^JRc&;p1$ni!)J<TN2k{+wbj1;mViR(EFCoB47Kve3||
zIXUvuGA~a?!7u83lUn6#*YDmJx{*H=_E3`8K1~gnbQV?smu#@v&02^iwn(N4vkhx~
zAg(T0T{s*S^)*!G7erSv1TjyL&kJ#V9gkt6{k;atWsk-}Rc-D%_D&sUboFe=EM%-x
zG7n)4K4r=@r-szv>8?~mV`=J8?cR|}=U@5&_Q`Y!5cF-}u_ft=*7Kt2G-t6eUv<Ov
zf$!$1>NE{rfH9=ITST)hC%!MQj=}K=K(Jd*>sMt%TXa!fxH%$(G+wj$0FJyCuiCYi
z-~B_LUSG!OgAL9#BUmE6-jM2~Y|~##%IDIiwn%-W;wPfGEu{F{D<A)_izgMpHqsMH
zUFfZ{`!luujvgGaK4f>nl;v0l<3s;+;4kRMV=6wVo21}cdnjz2zS^M?aBYMZ&|57#
ze@@IA>)IL99SIGLAwY=C`MNB-lYirBsOgbqIP$41i$dk(=L2Z?t+i>2(5cx7uki=v
znyd!?bpP;8sz^{`S;fAEnUI0<&-U2LS_Pzgl0DSixbwN0K~@yqK2H0hX2KFzH$i21
z2kunB)<aj)j(=NvmnoV&&2*R@bL4zYT_kt;@ba7ukE}%?rWc1l7=0H><=DV`%%3B3
zwFH5u;G@-Vje;S5={52~xdav<2%?)jKD3u#6a)u|$Tf0+G#y}xmqV0?9`ZNKbEp*{
z+#=@`3Vcfl%bD3xmS1^$C6c^*%^*QKEgKTgv*B-&2SA~%Jd21UjN(5guv$WnV)i(f
zjz&AqDJb0M0at}=-VyRqdpxoO>3Qa-jIN0yB=U2wgAv#VU8oSKE67Te3+Y90@FvT6
zqqCB^Y^im>$X*U+Er*{mig<pWM5pV|x}0ETt?lhFv3G{r1+W!@9>-J>(cO@Mk3B%X
zgFhQNn)o@wZA_YV>@lajVe$BS-j+D9z7F<V;_?OBRZnbIG1?LEATs_zOvL3}D80ks
zYL3axBcVuJXL*ULhX`Nr(5da4tbt&$XFBXaKxwAMwzwj)-R!gwN^fbsdldI2KxQbV
zJu_JBJAog@)dBu2P67X;Kih9Q;S=sK&)P;)sQjLL@bx3N<Kfmu9a>+=$cQkcf;Mt2
zV6o?4o#3hMaINt-3U>QOa{qx76ti=-boLN7bowtioUAA-4Z?)zW4Y42y!6fA{)5kb
z7GI|kGH@s;pU@YNx=X&rA+z30nw{>Yffow@9q5zNp<WyD*2LhXOJ=(>-9(^gTi^$-
zVMPS-^0)?raY2-9z<g2jcsJzBik7q!l5)m)(!IDi^&Ify22eEBub&b^8`wn!$^n+r
zTN>L74JM{FnJ9jep<S(iiU;7EIsqoCxSMmcs!gheV==Iiv3|MDpRTW&T*k3V(w3$(
zpb=hgctF?0XFpe@Ej<K0ucYoz$(@WTh=%Z($1f><&OD*XFL%nypw7nicf<a*nj|8X
zc0dN>8}7xPKTBj4`eZ*zlDg8dr655Wr#Z^95|DtflOtf8gu(sX&@lKs$wAl(fUW8s
z>#=op`g8faR{-<og{A<wrI<n^dl%Lla*~<GAO>smA_`_QBZ{77$vwz@iuAFvvDYEf
z7DvP6_=K3&kZYmR!~v~HW&&ZVgR184-`Xa~OuQ-jzt_z3n*{YgST`k8Lz925-9Lj@
zk&3N6iV&i2N{XJgyay5z8d9O8ev&m6p@yi3D(Ia5-dnToc>00VRki46GAS#Y@69*R
zj$-K&E_e{3vSfa{xZ-8uVUfRn&du%lA!AGv!Ecg(I^ql(G%9Y9Y05fa5jsa(pegPY
zb(|lp$DCol4xFiO<7k7<*13EmK2ZMy^g(t*ZMvLHSG^5e4YV;i!V)c6#0{eOh{}A%
zNv4Bzw&z1NM{*#+b?j!w5jan5fxU|?K#;eN0a1qzBUx~!*|H*gTv3lp-(*`!h90A^
zi2*P1IeOr?n?*bD+GV{m^I;t=F7?4IFOhOwPUARPfn>!V*Ssr2lJNz#rcMjr0#DJT
z^zHeAQS`dwyBeLJqQw<>eCcY!9sB3mq9E^Fx%$P6CbuZZ#M3gr>Ni=N#;wf63uWvW
zjj*2eE1ria+&t8Z*OC3Jm3s0oy4~%<clgqD&zbh_qBRpxGoA<{#4Q^2tib%xI=PHg
z<xL1Y1g7ER_!w2**}7q~>?!c=Gxu0oJdsYH(4Tk?GN+QYKaGS5oh~sfUkDj@$frsw
zCDn(#CI9sNScA_Xs-3+BrD|G06fRvwlpeIE78CfCFy~WOK~D||bllS5mIe86F6dFB
zDQn@0Fq3BzC#dwj;V6rgkfD_MRVYX?&^R$Kl}qbPVSUO?G8-~tQqUMUDimcL9CyXD
z2PJ;aPg*MOue@G&4Fex1lTD%^7PoRmE!=6P8tf6Rf+Sn)yQ_xg$ubAYT91-sflS*4
zq_oWl#Sn^`vk;qz@D~bu42!SG{I<h*@FCYwXW0S%<IVI%;bXQ{OXQk4@&mdpbmJ>A
zOe^7lj(G)8!snPz*7p6bCu?iLW45p>1NVsT1i8qTSt6X)s+aJIofr<YAUt?{LxeLd
z=l3X>mN~%Z^!(xW6L1Q*F#8ukfP}n*ybV6!_iu^4xYS5a=r^YG{4SgQ2gl-{8NT6v
zC!ycXhU&@^sGsDZ@IPb370cE$F(USeODvkI@-&J{6-8lFB2xbVn1cfVa-NO}WCBG3
zzbj_=H85POs`;PWdWsR6c4UY%q}1D5>zTb~CUbmVpSD>}Vte%8!FOSOC5;8Di#c_q
z3n0J-bU6m#Ae1eg^WyqsWy}FEELfZ3bFdBYS0=mr+7M2mzUH9U+-YtAc|s(rfCgnl
zl_wL`ztZE{^KkIpQKn?HUSvuPF(wMyD)H(n^{iNf+<Fr*q#ukLsHgTkw9<wekCQPR
zeL|_{@lh_Am>zhvp};3C#xi1y$Q2Y!GZa>;0d-Y5)kDl`+m%@6`L%gv5!}p6lB%YK
zQFZ|gjvzcP<b1D#>Z&N3Q++<*7@E;ti><Uc^A#iQ`)Ec(ry|CjY!wp$QRm=S6PeH-
z`X(#nCORs<n8|ksDywY8Ab7DbGRLlQT^tuXNlWj&xFl(i($4feMIdat`nn2pcx?)M
zQZp*26XRJ?jp;4uiMI*WwgrwE+Y@H!?cUnh!x|j~ptW18T93(nPM7({Q<h@jrsQ1z
zKyFVFeU_%rH#T!AK#E7r%WxfKM#d!+EkD6gXy5|mLJ_N=T0;m8`qWISiqlF(F7JHQ
z##xiEP&ivXrj9vy8ccVeXRZB0PHccLeeV5Nl7hmDZ(XARp6rzp-R=3ZiYEH0OTXeV
z+<P?4q19E1EKW0u_oRgohwGP0V>P^39z!CYz^d&Ms4}4ibadfBW;kZg#4a}m^a8R8
z=%n;@%TpVny_Z&0lH3Fvwi2Uj=YOXHueg<_0_aYmD{8Kjt2-kTUlxaea9KA4BSlVK
z96%+&{x&O_iEf6(CV(6nA&va%ieygFv7m*)T_x?JSDRe!_A9u~4>ZN7fCLq9*}Aud
zwx^?|5kTks$hFdvOuxrjp@k`*(tYaP5Igrrm^|bes{qMpeX3TXnvG{!+NgpZZHU;r
zw)X;SO|pmi2XIp}0G>{$l)b;K%Xk4$fbej=NKN3(X5che?&CzP2y&!zX_hr;a$AWX
zm2IkdPQ7q<^WcKfUm<rLI{2<X+)Pl65oGo{+5k!K3>ZqU!4+ozZ06_p?+tTR-6g5^
zjxv_))a!F_gv#2zApJY))88h)E|h_V>kH4s`2ZVUlI8k4_du`11uHvE5PN4A)qEsl
zf7I|tZI*+qh8?1a3Wv=0mIl{Ua`7IL_3A+k6Ymal7M^zuyfFtC=R0h+d{rsawupm4
z#sOU+qlmd(&z_*`Kmcv@gO-zKq<EmfHcr*cXTCFq<y_h;n(qC~-X^MufT6bq-WKq=
zB$Q09o`lw}1Z><G<U9Pcu;YuQBc9i!NzGn;${X05ukUNgE$i#zz7;QDfL)9mSEl*y
zb6V3I<`4+#4WhEUXb*w*j6eZJ!Q=*I8|nT29`5vpMFh?qD%~&d9>CCXJ5)*DRAR2S
zN(8zFKj|R?$!)@T0(`eKpbyCYkO}2k66UGK!f?|O<Ce`bV-xfY?Q`bNFX@fGCv(QR
z2mrNn;OG}o<{LHkxhU|jNDZCI+1K(r;<tV)*$Dp6)7Af-s{S+NlM1_7+WfbVD@yv`
zp?~B{dmWz-p-h#AKabK%I|+qW6pYEz=T{vfs`9}^*OSc(?uwZ`!a&PBMyM!?fIq=F
zrx#zXEYaMP-sJSu^t-E>d3}$s-xrhtRs}h8YhoWMv=(X;rDdJLZgn{86_y680ZZXZ
z2*V=yfM}kExuhD8Y^q^9xwjk5ri;#N3=h7hW0PEvmkWK!XKeJ(C3K)5MW~P!XR@Hj
z@n>DlM|Z^5#yY+8(Uhr<&N<i1=2eop-3YJjl&!)gwS>1m3H9~sB84j_eW)e@f`Mhs
z$r<6Mop!ppTdZc7CVB7J4g6>Ar<jC(`zo}NgA&upX}E$ibf3R0{hYkNwH9Q}Bd-$@
z=AK@FVUOJT&Xbz$oPJ7(j!toIDL~C^A8t7~v9%9=^G`V2gZII{_HAFdA-pv(pSJVs
z9M_r#`KRN}-L*lJF$MNZ#xYIEa%q`r&_w~yH#96jnGX06J@A>lJ)yhQqswH~1Mody
zShO}*jG!7|C%*i$ij%SMWA&H@<^{l?_o?S3&64b#>_027_Ach)Ff|N+h-hGzz!VJ9
zSDmRB@=B2&pZbgo`dN-=V~ft`3uLNMLzK+}t*R>_r$uB7M)Szd|KT#g<~r@4+1J5+
zPwGTz#4ZZ4mrUx$4atmu1p-SZ5$!%fCutO4K+5*sb6*`qyddhs&;F4aZio>ZMiyou
z583Phe4zx}5k=EjVrc)@unh8>l%@i)(i8ZC+6>C&@)W)4h}+UhQJ6!rBm9-~ggGHT
z_7&s|fz0*Cf&F@yZ|B8%7*=jVZ<XZsFqW26p=^R%N=BCqO?~3OU#IztH>{L?Z{P9n
z=Rde#`Ui0R_xq(7S$H5J)Zp`1>j81vtbk~_LAc;SseY)Obo1gO7kMod2UZve0Oi~T
z?Vk!MvgF0{4|m|Syqa0nQB=?1NnN>)^$d4%){#WEyq5daxQTHMBG{Jxkl+wEMLP%2
zLmHH0{-g}+X_~p@Hu6K<wZBRjV=k~4(-2U9?WHljSJvxk9?krccvTDZO*{3r^Fc?J
zH$Ci&L<m_EGR_#9An6)=pt1+S7a{)j7}M<=K{kKe4*s2V{Rj5{zmM^MDc&SUGuZ(%
zA&T{YgpbuLJwZ|_8G|_lK^CG?ibX62xvjF*+nDgsIIuy(_vR6U&&`^N-}iL0dVamT
z@dBk4EYD&m3qRudB_1W;SI)kZs=H%F(1fkUfGfFcf}b0^=4m^f8CNi=Y78!7ttVct
zJ=h`Esf><HH|`gcLVHY%ZSHMvqy1L!3++7{P@c{zy3sP?4Vm_~b+w7?fB(8TRvkrX
zosvXP7<NY`IQaRXS)D-OB0F{XZz}JYplyOZ-&hTY=*JJq|G87Mv<28O`~$SfyEp?}
zoW<=OZU603P7}&qWeM%mzByG!PlFgyI8H1em=+YVk{l=)aoj*MF4$tTe`1mZOVVtZ
z!(OAYsjAt<R$5mJsi}%?SWA0o9kfu@io+U1+uHis%9=y_(n_7?W5$bRfHa*nk<fe7
zE!Am;>sere&&~aB^awsgtxoo(5TD)h4L<_&jW3orA;Nj>P7uOAx}{z6F*}0YNEoZP
z#`4uoZx9H+OkegqZqhM5oZG}Rz9s*DpTupQ_hw`)%o)X<1LX7n;_MxxD{Ysp;qKVB
zZQHhO+jcrmR&3k0osMmEY}@LjlQ(DY{hhO)=lgLm*7~!?J;wTRkE*(=<~3(c$p!Mt
zXYU(Hp1fUUEWF8q(pyY;shc=JsA!OP5hslj-q?uwZCPmdjO9t{CNLgNFXF0?$_r0Q
ztno`1i~j6Q8@T*V8;d?lAbIg?0*gKxqW;*By6E_F@RTyspGO{^XnTq4%=VWQ@a<vd
z_LmsIwU<Jqx6^IakDugI&htO?DSY#GJz@D(M$4f=fS;^FU`?Y5D=XI^uzTzpJGkpI
zqi5=(a}?B@bGNP5nF8Z+OH_UGQR}7vdAN1YOKevxZrDqT+_TEvs}Rd{cFLm_@UOBV
zW6=S5t0<S3EY)g-jiJmT(S*5k3uYSMF-OQ6FRlbc41GHKfxCBe&Y~Xyn>ft_ir&Jb
zXRJ2j#Fc7<#_*aoX`_N+!SpB_h$l!>;P_I8!v<5&A^U5!I5JwtaNbb{>aLNtpn<y0
z1LkUphI-O@)D|m>kvv{oAUg{vG)Lhv@>#0*P-{neoot)Bi0gH-5hk5OP?vBomKgDw
zm(Xk8wjqt=WH~L-!Ki0)qOhR6HtB`~Ot@Q6$4Rs~Wo(}LZTI2mQKLo6c_My`=5Y6#
zcM2+o9oD4+Wozpjb<5^}O96_}W>3kdd!;f{(Sepzd9pb-09SV(E@8;wDa8)d_QBQe
zlZ>5u8ox#5E__J8q_>3ZIO{&tw4j71r!X8SORzmU?ov25`SbheSOz>ZJhcbXh!NH3
z);?Bg8O_*8w~6Hn;c_w)?Lw&nA3zQ0MQs7S;eC(ih-q!o381&Gl$H{~c?#saHdI;X
zqN1Y}JzCS;V*3QRBuTvq@$v@FB7Lh+Z0#&5i%pcibA+>n<z1SMzVbvmz3M^<#h?~S
zFo>6NkzKnxQ&O0>HC2onUtnk`QdjTss<L5}fQ02gimu!x$MUV%HHUgEr{S-04o^L3
zJ5u0q55$yDv*2?l_?7%l`cbueT*Y`&CT2dmCnY%8<jF45C3v;bM_oNht<6iDUv|jM
z4suXHA?agE8}EFk5epWgT8d)A<r{z=yb#GXEnW!FKYKydo4>WT^bOi(+H-k_`>CGB
zEjD=Wf$4{!=C^nYrMGlT{;oNqf1@7KNEUYzys+)^j$3Q_5*p*Tr;qhfz0d!W8^eAR
z2tei%mOG^qHa(+~HeG;qNe)^@k&}+c#?&UJB1D4+#f3$B$e4FYuDmM)+)+$o@>ZWw
z>BnpWpjnI0D+FZc9eM2(G_uUNZfcg7Ojt#WWS3O)xn$KB7F{~pYRt-rbf;8?piECY
zm<9w#=vbxIN&78ZxOCN>i`dmOJgH*CZGr^h?`PH*re=5~iM!54-+$<4=T9##0Rh#b
zomR-u{!(qP*va0v>KQCqlg4PGp}@(ba#bx(p^%Z%OAXdwX-d&RhkbY<)kVd;s^{iP
zxswk){IN2p+N?!2#iUDH3SQB;2o>U5s&_z1Bb^w25qqu4we=RibasPMRA=%dHBe}X
zqb7jRmr;w(ES@_)Y52!4(>1#kDr}{<w!I>-ni_YgU5c3tG%PbsucT5fB079O+{vy<
z<mzi1Ca-kU(p#B<aXmF35=SWbR4b-X?L9p|Uu@}^@>?HCR==1TCfIV}j`4ZQnoz!A
zGNpLaSDXnNsb#vzg{DY@%n|AF<kHy`tL>cv`}ecRI7!Dm?Y7!wg*Foz$?yp`nB#B`
zoa{We^yLoo2<bI9DswEsKxOL`N$wEj9^I<|?f#NjKIQn2xzRiqj_N|8BJNr2ay!Fy
z45q9oDhxXp3X_yTDrGRM`74sMwIogw)@q@iu!Mc5(Ym;+Jl9QZ7$)}zjQFrI!%Yqp
zO@?4h)J!C4UdW#ZZ`K7D8dz<+oF_-7mT^i$h;&wGEY29IA|+jJM3VL{o|flsce08r
zsPOAW)&<5c%hG)oE@K0^#O+a479NQ_2<WjGto2rveGNh>?_~Y`1%~Ipj;e8Gr>b$c
z$m}cKZ400Gz%q)B4rZ~(i+)jle(5R32dg*LEMiUYTb*JD?K?8U^`&X<EWg!mj{*Nc
zJtO}kx?!t`b#?Tjxw?WzoXwt7R%n=R*v{)K+}i%UzGJjI&%XM#0YSLgj(Gk61Xi&l
z?O9_M6Q(CRliNLm&+&A=VYhL>d?Po?O9-*OE~w-*HZ0|_o_rI;KVJ{;S@gsx^SEnk
z<3ncIzFW2$Ry*?-n;VOc%647x()z~W^UF!=r$KJ!UdPDTMlFIT^L*Gwy>W4D5j6R&
zGRQGYvr`mRlE~iu+$hk<Bc%65W}{(st75<V13ok0BK2Zd;M^oOa=wRjgjBd!FAlDT
z2XsH2o;L)OlIB!ICk7ENQ}E{o-T);4J*mDGeugs>{*Pjc^JN_OP+K07FpuA$l#+^8
z8X87gtZP~5`&{0EI*5q@uy`s#q93QWo+9Tr*R)NUuH@?XSdcm(PL1&Biz(-^ouLwp
z%=<YBwfXfZG9~uLT5_`%ha;dT=DH=sm3}o4wh<7tBy}8dF@7dWw(~k+52XuE6BoOL
zmB8Q?peCbC;v#{Zt)i0SyiMNdJK{*cfc0^FQ8#|4jo2e!r&xm8TMV8{oFjOFZ5>TV
z5YXggafVX}GW>z0r|&Yh6%`lahD(T9ZYT>HijT%#U4AIcMU>+r{AN!1ZSbY+xWbZe
z#A&*${tLMnEF1usyUg>O%&k~YRe0qQqqLJ@nq%ytER4lU#`H_7>6#&-weqYKExA!E
zi(*!uRLQ)~a4~-hk?;XKAwO8cp7^?LApy|RXpn9&)V7s+3;!40h>4Z;%Lh7lg)Ulv
z5o3)IcnflS2t=O%IcsP9XluVX7eA#L@jZyBnFRyuh5!8QQd$0+>j{?UHHj#id+N<L
z-Gc*s{ftL?O~OdBI^^|xA&0P`>g&b#EKG1VxWYU?80a<m{*Jg?Mt@PbCRWV~vd#*Q
zNQ7k*baUy_Ma-0?0~MShqYz*Uvr?U14l1jrJsj1l$HIo|LFpk*A@xH$EvIjIt?HYh
z6ILv$Sw0Yro9V?q6jfuc(alvH%gt(%-n(~3w%^Qo8R_;0M2v8s_SLi=39g0+eNBI4
z{qljD+0l$?#G%%YZntSgJZ4*a6GEA@U!K)Fw<wiungwl=<gT8VjC^Q_p2zaGjCP;>
zV4sC}b0jTx*>}_0A#nVOE+};_h+mE`nub){n^;G&RI<UFgfrya^clGls&3(Un?QXE
z+dX>tli*KrEF((6gU(%*!@KBy%*#gN^u}RUp)B(4GZm?>V5j#DlBwtkr>F<tk*oC$
zg3qWMf@j>kJ8>p?M|Q_WvAu*>+OA0J&5AhQ)mpL+a<2Ec9OSHdoZQX`x@R_6`(=k_
zF%X8*6Oh&;7+q(cdyo<$_Z2AgtR+eExLhyeX9?_1c{`bEStXD*%B$>)pOK8GM~m!6
zniicVZBvY&^5Ycgl+0300bCKNOzlpKD9&kj4dJf9J~BPp$Y1>FHTXrAOs(nx*`l_X
z3|;vM?6ffZqSDQamjNgx8;OI6lp>vaUc=kVwqIjyt4+6^r-_&`&1RAS3xSfL8E=*@
z_IQ#9!Pngm4l1c3h1+Z*s@R<i-!4*E11yh0&1v^_1cN8%C$#Bp(FksjS>U3!L_^Ow
zLw9!|411uo77~LWkpJ<e!-tw2uJ<2{%Z)H*FNk$ULMu+dgr1>19ch=VJ;JaGSJd6D
z@U1$!$nectj%_Bt9+!*}dS*m>tAlvvj_5>G%TQ=o3|Bfd@mO_7);n&E>lU6Q_?#LW
zSg^{c;;nu8{OicH+TU2e@ueg0{E~^P{vU<}NxT1?5&k(wlKd0zHMVy$k#zZ&;cv65
zwlj(-%7+(yx(QP|#%N%k31ZR|9mDtA3<Ox}cvfj8GK?W|?#8LB-iyhVb>uv$p}RhI
zKmX4F@G2!GQq`SC`40kV-p$T2J0YkRDW5dH($1N~w`tDqw>SNtd|(cE)NI4I!wADS
zCDE-nEqYt^H#H%e*uZIx4vP3w+8#6gZ$TP$j8W2TtEsd)Ep-;V!eArP2NgGJptX==
z3RPkaS9fXNu)Ay?v=K(FW5$$L;p93@Q6|;4+!G8<N6W%BNR${?kCz;+vBmi9xl;PK
z(E>?@W|PIg%-k`5XEu50+!9oDvL;+5GpS$pHr@xD8BD|bu+BJ?%<_kyx&mZ4D-eU~
zEAS%@i`oefShI5s3$Q$SG>+$&-=+=4Sl`hGB-p)06?e0wFrYNyJSs^~e(xU}s3(M0
zV+(coGQ+_nN@0*&F(%03su^>)Qv)N)NRB72N1xhtMW1(mXnykJ&K5Uebv4smQ2<;F
ze><OrqgZ8w!$h$~DafhW-^tcAs;bd#--=YdQ;^ubK6&;IbZA2+$1#N`mpx`gRZ(7T
zc8nVfuS79S{T4lwuwcrelX-?;7O)n}>?a^S03YjwHZ<KYxk1sa=JQ$MlT5;ILj@XF
zZ7R*1$yV{El`0}f^Vw`Aeq;NrlG`H)#RNy@FxZU<f|BESfnbIKf1)H3JrmNE6*^=e
znl6rM8g#f=6?Ib>;sgl&G{KN_1@=X1N#KYf0o4h2)ub?hZ`(bTIP^piX%&?%Y(Lw9
znby)U(|C=|g&KI-Dw)&v?XdPv<2xUkefuTcLUJ|FLcZ8sg)Tyy5DLu;>{LxyxPG*G
z5{^{~ttwZ9l7Ge_`-D|Xc^c|!+<sFF?a%Y4DmG{r^tY0ikp$kCD>@2UJZbs>;XHie
z6XqC-WM><w8qJ@;MfoP_eNioONg!4e0)}904kMmu)|fpEgC<I3Uil8;1|O#O#A^=A
z+8vN;u62AA#kbT5e&R=j)AmAsqRjT~Ez|ku%2)=6?k3Q4N%g{qUWo70NO@WDUVb=1
zX0@i+SJog%ZK7}fc`T=FWCZ#Np+yI@4Jsg{j4Tl-u5l4ANVQlN!Utct)RI;o0;Q{j
z+=4sADL>=*2N}6pJUeZ1M96}Pg!8)LvvBC9O6JV0eI5SAM44{C;lLnS)H;mQ(E)YG
zYX-&-VfN>f3+*5ddA4b|X&w0Ka=a`yC23s?Iy0_Wy0})$X<``tT!$8hyTK-Lb6f`Y
z?M#|=S{B3+^stR~Igr$%o(VL3qlZ4cV|uTwMqG~5X^^aub1}W%2{IO5&>#M(2A_X3
z8b(hyS0ni{8s_=J9fbdv<>W6gl;jr*@vm!CRZV9URSaJD7CAF4AVQFSB0`ZYk~p=n
z2m~R9NEkUJAvCtu%=GCZ!+G8(AV@p<o;S1P*x&t;YL>|Yq7^hbf1p!hKOm)soW04I
z6GNCND=V)r-!|W}uYasxZhyQUs(&lJ5k-1qDBrb0LX=@EKvl*nNeoLxXQrIo%h1x3
z-vzU)IIKq58hEpM5f})?;*%<XTwcOV@5gbn;w%R%mpf)n!#ZL`VWEMzxRY5<7}8vL
zq#4N>gMkj40OAJVtlt-3&Wsxw4EtTD+3A1$uCxb5(kr)k#Y1guJ=C=X=}~2ANIA|$
zw#aILYIy)&M&anR>*POg0~Jm&vFl?&Gud*K8ZMw|H{%;k7aOJn{YVnxV;9KNn65tt
zjj=B%bc0FAY=sJ-_HjCT75QnZ{oyabvdJp_NJuUZC965XHWD<%xsaXWEGm`JC>PTs
z<u&OligAxl^V``ln(>@2H0!~1juOLj8gMPOp2@B|phbfkU0E`jN$2@;l#rVrOylNN
zqVF6W=RJRJT(r_$Lt3w+Me5}H=hk*m<~uvuWX0)`%kuF1gFS*BHFdOGU0cMAfH??@
z77mnhGT8%KVzFnXl<sNuDaA2TyTagj*RfU)XTw2e4Q(WlZE~4r3?rla`s6Eefc#p%
z5)X}9!+J#~5MrfrUNM~vCRRevz7zc!NYD6o$<wIKcxpShaRbVcau8`8j^=ne>0xl`
zZj1j_gPqmJbL}yn5@h*vPaBT)Bt7gHm7}0DQ6Wwp=#yOpb(|3t`O$>rqC+T1X;$x4
zdSMDx?=M)@%}N88uBiR0BP|)ajv5`c$HIMxHBheB1Tox^+4B4{V?-Y=8xAZfE<Qlz
zK+ufGDTIUi2ro_jb88A?0P=cxVvOm=^34|pf*Lw=!?}Lt_sC1%&p;<?iB8prcCt=%
zfW;DE{E0ezN7_=)rk*(P!<?*wlzdjNkWD2ihyCiMP|o1^Jmx~joA8F~q3W#(34UG1
zK)+ffbga9kU5m{cH~^r)XiQz^B8F>ISHYsaydmIPT}&%s&jSNwpOUH4JRmx8_S$iC
z=c3d+S7wTKpVO~1Q1?s7o9*<wmQn{{ciH6eD%EK;T8CXhHvhWMJLt7Ib^%B4F#!nN
zEk16aVNaEJO)TIXuBXb@mtA4lZ1)99J#i5w3*L<%aN-*{8a)!mClZzG=u3tt^hOCH
z;r!(ZxDOda{#toeEC{TdbYcqOQV0$qpH&11{Mpah&pEd#tPp|%8=sK>fb#iSDjfXl
zuAEA!K&YoRqJ{)l)g30LcCR@CHOR@8Z0irR5x?3gnb0n_E6P49uxXrfQnr{rDUuIr
zToI6_U{LS#dEE38At|*4Q0+qCih!`Tys-l^7Lfg(jHqWGpOPyhy|`5{S0R1aqP9#W
z(~lI8iQAWe#_`2GqWOD>XkOJ^wYaFfE-A>UY>fcA8`!6N<IrB^3mpDe6xqeq$DP;Q
z<{!9uxI0Xd$GRyxDScSN{KJmlkqIm9*3S3s_@|ZkDf9~X(S=HaR7-+>&?OwNzsnKc
zp~qNZcnwS8mJkd_BlZ+}l<o}@PdiSVQ^{RiX$mse_Mi0b3UBA%LuP2?dQT6p8Ex1o
z(lyVOcO&Y&F;U_1d=`rJ1P%II#xT>YYXWYtB2T$Gcfh1AQY70@x#q;Z#WfE8w2AO_
zt`cK*;HctM$YmLRYdBaHiDtYK6LL>0`dP0XW<H1mmxz?lzR$ysNOm{=H{Ow<iC;YJ
z7k4EA<$uK<|4-oe|JT#~vk*6HSbAeGq59Syco=!^DS#_w01R3+N!B9>1SE)&u}nfK
zDA-1acR;X)?^bd|G8Dy#$@8I2Py4k_#I#ecOwW-hRv3MAQfB@L|Cukn^fo&XZ6TU)
zdlPiO%Hllto^F3$`FwdU^#gW*xW}3n&ASl+QN(D#wibok$C^aL=?#t}XO$U?L=}Xd
zp12YM@kBAHH+3Xh2`YflkLndIN5vcO=h=*qZllq!9bG0jeeD3)TfCS-_k@%Zt%TTH
zduR<X_q!+#G$Oj}6om1TCtZu&=>Cu&cqU#6J!b97+Z7G5C07QdvO33b=RE0v^4hMK
zWR7DOCul0IC{Z2J$`fWdZj1#hvN$Q58I5DOXBib3py)bxWicaLc4|BUf|<)_H>_7v
z++_?qv_><I5}0|2uVu)FUu8UM3{%Nu*yCBF9kE<(X1Xp&7osDQc?Ot~g&X)zxE9b{
zNsNi1WGT%zR9158ZJhITFqk(DjcMeiyobjyUl9kI54weH?n-FHGOQLWR4I;-12ga+
zAxCH-{E@x|EjtM!K!viSbqQHh+RLcFt0`E9D3q7Yc4Dfa{9aCu@?CH2q8^*{G+vWP
z;-${zutfp3q4n-pY%>O4)4&oj@6SkDRIyfD(ag@E9twHbP@P)C?mB|?PGIav;Z4_(
z<rE8{75-IZ>tUM8MQ6kJ0(J={Qf(7iu$xgJy(_`eGA9L*>pqOab>6Z?X&#j&tITOF
zv^#ySt(Bmm*palA(8x=<>b<-Kq`FlinNKEKXAk92pC#f|_vtiE<CS83uRX%lHIL%7
z=`_bYlG<ovymUl|V9WpfvHR2{WD*}@yLRxq?24p9`c+anbC*-;xOGX?dWAxl<I2-4
z|Ae-0!)A2|8FU!mY1Kj36%~a1(5RDtiNV<(R!-<4%-R#ldYrP(#3WUR7*hI}bz+Kt
zD0l8Aq2GrUQS*GUY+kG^G^-(#Szcq_v(pOC34AE5pEr{V6_<V=71!}yV5HJRb^zY>
z9fDtNWqXCSun?P<$WLYW7wekvi2RN6u8;1>%xvZE@fXa>?$Sj$q216Gtq(O&%kr)@
zVt=Cz`*Y#eyQ^?tx2s^67x#J}`1T=|>m!)|`~_N1eMPZw8g*|Ol<XJ<D&|tSXS8;=
zA_o38KJBxzKj$}XfrG^#*ct@uI?{O`F1}%ME;ELSjCn^`XQ-ge9`t9mDGa2uQm7I3
zYPH=bFjtT#;B<>Z+=+=F^GU{m;MOifgm|N4wkZ;?>RRcWXjz74)r#d{$7Z2fXk5q7
zK=4CP6<aeJq@2IjDk!_;DEjs}Gh%4D!@)<UGdT_I$6w>G>{+HYf*d1i3EP9QWq-}1
z;()BOvl*aJ_!+ab{2o5+l|uXMfM{#EPaZ+{Cf`w5(P9c(Q}k&6z@T=wBwl{ElFFv;
z*&4!*f#L#JdpoG4kkt%PG77UEhJ<Q}?#q7Q3?3hRUaXohou6n+WVQauMjwj7C>na0
zTsGcv=6%gYbFE7#D{oiU^vfvQL1C?o%WA@r>PF^>zL~){m2Dot3PrS;T7_zXIx|n<
z=rRSQy;HqZ2OZKe`-{7PI=x7zX}-T4Mf<$s)LnNZSu?|SJ9i4sYz7tvE>{}9D0E?j
z`IPyO57g#z?MAZHiBZKgL3f0YW+se$`!uOvM?8cb+<dbahO)<#UwlgiwQcmnQWnHI
zFnFbX&@t8rwnsPExp$k<LDZ=Ja!Pz_j)~gL$L9~DoV~|pbxt&FL2@_(DF5T`DDw?g
zNBj}N8ps}9ku;RN#>zM5GR)w;MhNvM+0NrS(%_ldcgQCAF_eB=oplPJ4N%<Bxqwbb
z?(GgBQjTEmZ+`CNoJl{qWpd(vatGEbs7>ONicaPpc3LcSba<Q9t40O;5F_dzP-MhE
zz`B6gM1rx*d;0)mUG*_KZBKOfNW4-}j`*Zr6VrzD^yXO&plvU`^Js~6@`;(CRj1q8
zJz&~E<JtBZzp-vOc;Q*OpygtRJ?jX+;kebYn>!R{49FV7nQ)umytW~jIXJ&tnc;Pc
z@%N*5n%BQwtJ3?@z!OH&zsxwd6(gCV?}PX(ou2!8dB*wX3_|jRy^Z-G2}>ltq2%-e
z^FfV-g-&1pd3U5S;JYSQ4|DP!^Ni36efjg<<bYrA<EklEq9<_OKUVQ1chm}F(xT~J
zp_s_+HnrGgMcfkJGH^cK^TP1G)eNlweeh^bQ0o|{2W8k_pmfOm=5T>Gd2`F%VM2iP
zcbka*BU7wT;pD?d<%1V><bj<L(F~u_d=pF}O*wp{iI_%n?9H3;!H*<R7O83Gs81SR
zzaNN+au){g0}me(q#q2PfiJ~&(<*!0Qr+;#j3x1oF$(uen;=Qzl88xe#P9g!+OUOK
zL#m*)euB$C)}hNlS)VZcV&6Jz=lt@rJAE#?FpS$l;QcJ@Ug`gevN*l%kYs)FO9H<}
zqyOz#^cVHVzl}x8+F$Hal#i0u;%1;gl&&Cxr$8E_yg;XV0i}iBporVPP($t{!U?-Z
z?ns{3#3(YVaI&7)y;!Ck&9!-=K{CFJ$#m!G=c(4?tk=i4b@*=!Y4Z8dpuotKA_@}y
zy}Y)vXG1IuraL_WmcZ~BUOu~$cJ`1nsWtZ%P2;^e%sMn3F|}=lEp51AFQM`6tqa$F
zbj*V^%d3VM^qqQ32ds9NP|m69I<01BVUlgQny@@IVRiw8w<26hv`iw6?X-dDn-K;l
zl+xlhAaCpa-eaw{cMr+BktPmE!p9xVC2qwtb&GE4Jb6QV5$kqKRkL<fvD_aqH!|(|
zjZ@1xD*eQ`QaBYzo)RI7s1+DcGiJ`&Qta<w6seamg`W(DA#_x`+_WZ_af2KiW^D<y
z*SElSQp+0~TgWMEFe<bPgcN6B5roceK*Cm+vq-EyA@&9U!b?a!PD4DdDIF)QLBvxA
zm@G^-2I)!qjo!w=j>W_2chwF_SeZijKQPAGNd(b)I#R}P@CzQnBQWxxm98wg`7W8<
zOC277bU4cO6%4V@Vt$<V53zEo%&7uqnA|dowT)+Xo#rbrxnfdMyp~MEn<C6glG5Ta
z%FSk1$_uC|mlEFUIYyWT<I4i`j9}j?b;s|Pvov#!F?pGMRP?KkcZ$ju-7=--VF{oQ
zN3p$k+lZdd!6)d0d?97uwK^$*M~MMIUJL;++4Cb9Fh*f+8S)*MX){H-BYUqiVLmnq
zBtpk3&>UMJ`d@oNJ>naPxw!Q$662t{8-vrKF_}g*UBPTO^Yj<cw+Cq>ENhav)Rmwq
ze~7-bZ1OBw<%iI%7D+3SiicgWtun5OpJESWJBJ~chNp&m9OCRbZd4<aQ?NzQWIGY^
zeg2J=u^NB*Ui}sPV_z*P|Nk5l_%Ay3-?>%R{}K3rZOUTlR8a&}MEkrlTg8?Ql>Q-*
zuHitSl5qUe%h?*umZ=N0Lw(Bv!nr~Gov*M@*QG1AEx1f&HlLaHoaXkPzPRS+_x+wW
zWQ8Qj!(?cr<=MidX=;{~&dOlk-`f=c3LJ}B#XABUya8LZpNt7`#((|Zs(Y1u$<Q(x
zr{Ty$u3>y4S$q$38*L@Y0CR*RZ?p6aE!1-is$O<r72oMehx>>Fx-U3%iy8IUv7ZuL
z6j947KMI@r){}=m(OyBb-ZdPFYN(zC%p{8E(5lrU-Lw{Pkn@wgsGHd1v>lzJZ`Wjy
z$nuDsyzC;ZLHQA5t0ZHow6mYwB)CN-+dN5OhYy!Zk;>-Q$0>mdFMAOJ$_@ipVa{C#
zN!I+B$nde(@lsarTq#+R_#v~a)@ydu6vOhO&+xJh9y(fEJ%eA>*(BP3Ot<vnHjgfx
zP#IUSgS*=97MiyhrW+KsbfJjLp9+H>E#z9>tWlGfJ{wxPwS%&LCYaT|(p3|ML~}D?
zVbL<#ARj*^<hxECLq!*(X%0nWm?I$lQ?1BA#jAY3@ZEck!CqHCz$EX8D$Bjnjpv*t
z8B7hMcgOwSm0KcPQ;om09S(_6&`%6m%0;F*w2SYqT-*fwbgU$KI(Tam(MW$R+%U{W
z2prupz6#Z@m!ZaD7NSOMOy1HxN{yKL5tlcep8T`~u2yM2Lo6zIohbNDj5TFf%UYug
zvPG^gnys!L!mXRNsul7n!Ju}n*G{A^vrY6G#paEMCf|_P+<-ICwk2S5m?NJ|uBRYk
zgYdcrjYV>+`&Wi$;*l*?<3fpyU(qWco=BbNpsV0Lc@#XRTX2uE-pa;%`cVd<bs0Qm
zQ6||w_R8zQ@YtvYA)}1t8$zljE*ZV#JYBqQLGsSu8PwU&bJUGr836pnPvZPPWx{{b
zlLRAx1Ytz|IIDSE`X3N=+H!<=1Dke)g42-)&t%-C6-iZ#cb0TKzQL1<eLW0*pMl>!
zbo;6EeUfoH{+I$KLf;Ptpq_0SQj1^G;Z!bte9fCJ!IsSYYh;=gTdum+ISK`hk0k@n
zMC+HWI}&5k=x?#*JuXnE+t?uAg%V~^im2sjM-8or_(GxA_k7xRF?)A!Hc7)Ldlybb
z2l(3GaeyKipIaE<xqKNy_OtZynZMNp(Hrdc=C8Lf{B`xf_dkCV|0Rtf`FEv7c7pCd
zOF}?#v8!t{fiE?c5Mcl$*)V;7NLhG2lCkWy{JJBzNxH3BDai-5goH%fKeQI+9jt?w
zTPI}q)2ofgoXq#rAMdUoz`e>W=Vg0xu&5i4PBRle^zaoLHGBC2rsCL_ZlGqF=ePj|
z^q15DWyR5J__%J#f21~pnWNR#3X6o*-kv3y9DuVOW8H@>pLGe|4Wb&nAx+cw-YeCt
zj3tH7V3Tl8h*R)5rRFuBJX59<#(F5Joj+hrtw`bZp%;w~d&)FQ#SH4(x480%6Cl$y
zTC$hOjuPUehq+fvg_Du(J3Vn6-_vQnF2nJ;yV9-wyrQz?4#=^7v#xQm9f+lb9}it~
zFG$OoyR}PqXUEvccQ0=xob1tP_izpJSP|mwI)<Ur%Xd{7$?gn&b`aP7nW5ND$ZlJu
zxNkV3i>i7crvnW9q=|w81Dkj!SKZC!#QUL8hm9kd6Eb6$C79*F5F}ld?C1ncXq|?>
z!&GxOxg0c%@*^UBAE-+ciax2oQPiUoMUN&Vi0Hivr6-28hN|CL^u-kNhp~=x;z+fl
z3pV16Yt3zm9^{eV-+<#|0e%>YuV6^~5{wG`&jaEgi@E+KfB);6Qni0d-O-@(EfGaT
zQRpG`@(2{|sH#<Kh?yy(7+ino2vPLKxy;)J;P1@Ls{0I*V`TqB={`eNJlijfRe4}Y
zPww4won`-Qb9esyocm3Tp_C|Q1WHVW#Xw~UV_0>Nfv{8_g-11iC%s8#Tv16-s?Qm4
zlw_GnG&Q@zA7>ag$#D)Qyk205Z4b3>4d@(SrfG1Y;o@p#+F(8GGKmV4WuA%Ca@nXF
zcGlTuX_9S}h@J**&8ljV>n78&J7$Mb&n#ZGvSgZZ-EH%h1pKNZ)SGg+{k3xrn5bL8
zN0IlMT<u5k9vh<7JJ1qLOL@vTP5>4pj0vYq08354g6)&zI*aKxG%I#Vj%RRDlWI-n
zPO$HCvK-IV+L*SY?q|KUxoaYo^`Ap!wsuyGoAdqcT@Q2zNL;L-<QvF#v@yJhI1u9C
z5`F%IN!EYMG<b(bp904ZtZndu#TJ@p=h+t`D5cza!6mAEgmedT?995juh}*7_%h8J
zl4QW{@H<Bw7i!)-<@90}5g%H3=B6Fa@H29rg8VtZ<=eyv6^?eIU1Y{tK|<25^r*w9
zHe!;p>X)3S68pZS%cOJq<pgGeH>wa79is$@DQ%r|qENHW8I<w5ZC%`yJYXJ5Z}1jL
z*-=L<w@HRsW*Mqm1;NyYA3K}{dBg{1Vvc6O<VBuV`0aL8S8JWgg$vI4@nyv<aN^|p
z?rX^`bV}KZ&2P~B$WX#fe2?Xso}UrNPP&O;_pa>}kYx^d#VLKbzqzA?`JmFO;H=gy
zN)%_x?4@x0eF_DE*UD|5qPp88Y&Z1%;dBc4q(mJ;)Fh8hMJzzd_-AkU7(M)leKJ^c
z1Tbz9xc;av>OTr8%!OD#e0X8%YIRt;3`Fjfj5t-I>^Tc1eawkG6B315tkps}{|1pn
zX`S1T7oj}X^P<oHEu{dRBu4zmNWXKH56q$-WXe;A=ckEDqXv{%*x4qIr%1H{Uh1mA
zgR52HI;wUu8yg_NMZ%NPr*uPX5^t@Almjz&HaZl(Y1M~-=S4L8sB|Z<E?%xi{G%#t
zUObLCy`G0GqxEAB|F3h3T<F?wzpqv;_lpP5@juVPe<RTTf6}+F;Y1PPLr&YxQrA{c
zWDuGFbiIHER0QNeX?9Q}98oz}e%+YUY&GFB<>Y6=AYc&O&!2ysqfwU*z?akj@67q;
z!|ZHEc09AK|MUB#F?Rq-4q04(BL{#1o7_ExHj_59nzQ9-WxO%j{DvnI6fKe_CsTu|
z-o{Au8_+N9W!0?~Vr<wYhI%Rkw2ZZKD*0ZGg_@^j(1LUuNrD#LTB-mO#ZIeMPX)Ct
za!t1rlRAxBiBb~YDPIqa`)5~SgL;i;s}`Q5WFOP(b7CaaQ|VH@#>yhw?L@o%$h(V~
zoTnx0<>e1|DkI_rV0v7&p7EuO!v*UqU2>Go){=Ml`9ft~_wD2pIpB1g+e)4Uw}s`H
zKYDmbRB~n6cQrhDmGIdg?nT;-&p+flSpzjdATt)k821Y+6cqxFnrqgf+3{H@?`&g4
z^$f~e34p@8y%s9V*fT<NI&R!kv<(a~;59dz>j3I#zcg*?Rt8f-9Az{-q9ma$(Uj9r
z(tdi8l0gAY=-#a*1=^IktQX1hv!Z#Q2KGu_FBBf=wSfj@w+xp7v{9dD+()?H?Fkc8
ze=+(U>KO#$MWMVfBkqRJoihk+0a<!c&8Bh-9;8J<T*b@8fej-N?@?%~VF$l?AQ)I&
z8Ttd?VQ>$9cVgy8v?Uzws09sbUKQd$_ka$+2PtHbkW&g|@n8lp$mZw9r9vXXwFUto
zSG`0I!xqu#Rnyjb6yBoo&GVyo91ff|MM_LB1X?<XOTQ|Vn|RKdM9&gzdM6`pf;$B6
zmv8qG$X*+<cULsWdA6VrF7yZX;-(Elolb97-=zVXBFwBW!IHeQ#2(yU(gUd8@bAB`
z$`|XXqhtA+Jz^2QePjJ^gZf|FQ~ry^@Xv^@R@ZjM8N%f4?!2=w7q|Aboxm6~h>BLD
z4rkrb2{S<)Lsy8ST_;Mh6*6ez){EAhqG@dGXA72Y6Q&c85JIwZ{FXSFFM&D=QE`_R
z`X0!0%&7YQT|IzvlNs-N3axxR$jhta=g0KvwUgOnZ7ts$xWD#oehjvOHAg-%7<c%T
zhr;wYB~5R95Ort-4qieKd8ic>pA{F{ZQV4o4tKcn-DA^+4@rplEixxh$-W~`{;nkM
zx#7faX|{(HUvA0(Ggr=#Ggr<C^t`Mn9K94Dz2!?fAQ##NO=qMP=O@)HuWP>!%RTEh
z-Erwf1wT<-R=sr0=`xSBf%U?Z#f=_Ywvw;cRj}%f_^^k`QrYFoN16Z+w}S>j{RHjZ
z%^Br-{nIkq5zRH8bIoM(WRf<+M5ydc%Jr^Me{Sp8K?>zE_2E>6W?Jjr{S#4W;Ay65
zYZCok`nD}DyS3?Ojc$qGC{>$Yd|UWM(I7J0C)ul3v;2bLa+Ez9-iEmv$~Su1z?|kC
zIwyKNba|)~Z#lH82>VVs)d6~tUuKyDc{PehGI^!(59Q;edw-@%*TlrVB2sC%wB%c=
z(PTy(*QwAkDej7PJ=!NFOu@C7os}o{Q11|HrMhx1OwL;h8ZD&4+;q|ez?7b88r#$x
zDx}y0@-L6vnZLlHVzjpKRXE{gvqZb`l)~LqAY6FwmKhCO3l}EcdwS3CPF5$~WxGs-
zrG==OF3oIsDXBIjH*1qxAjVVeoYT%68VJjZT~oZfP0a1aY$V&pM?-kE<ZI4=Xj*P$
z)=r(KF2twQUYnN311MLm!{34FsjggwCB(LgIWP%!bQ;m=VJDb56?eTO<Ck+#)D8!q
zeLX&qu64my4W7_;he^E-ZlFJ1Z7aEcA&>gp6IYF5wjQBYb+_1b<)G2FX(q5ZAph2k
zPo*~AxSv#RkcYA9i+1wU7@!8z8>)rb04M?zJ7J7igS8mP2Iv>+57@)JqkZw1>~`E=
zx&izc9>4=&TZ7tQTf^K{^uT_Dn81GhomgAU4hY^Fd+KE*z}NdUwOL7t@Gz5mVE}&Y
z7wC_Q-K>D0k~@wv7#IV%K(C*QV4w}#EHRS{sIt&k{ekBc`w}?xLkYT^oVu+UmY2K%
zE`?0>^;1TQ5qg<GTx3Iy*&NO1NijmJOptXYq81=5lq!jE=Ixc>y9k#w_G%G`x}=AU
z9q|e4+iF{Dh+|DsD6V3VSp|8OmM3m`)jQ4hC34&mM)E;}%aoa7rt9|E56L3TzL4VG
zELPeg&7GdnxoC|_^;rdHOO;?fieQ-+!l>;Tf1p4&3K)PWeIMc4RJqG)K2UEktSgJ+
zel^jIYjAxSmdn2PHKzN0OV)Ga&((fK8(^zC%2MiMoJfWo<OJ?;J|=X^C3bt@*~=xk
zbvNbhWt4@U6%NExyZ;emFXjLigrS6ylrp<r*_8MM9RG9c{v>bUWx8jJStIog1F}9!
zm2r{}7ulTNmoQ)t>O`w*Z$%zlvjeXeOvrYZSsDSdBi#-2VaM!1G8%!fE6es6iyt|w
zR`7yoY7ff}mBcgPCnV^SU79$_&&?m>0|1iwPMByBx@}c;@AdcsYRFaO6)^!YH;O!a
z$DEz}^|PyONFRJipYyY;AVZXWSH-UAQa6IJ`_%69cz4`w)$|VDh&r8Bw8Ja!EX9Ta
ziEYG!;{HsR;TuJlc-6C)OIL<+2(pmuGbAA?I|*J7aIT_8Gj?NF&TEKGkf@#+)(H1e
ziwyUq)(fR5KuUa6E0{Yv?q$rK<o=g`(x~*bTe%42t1eXbH3a6_{40}7fU_*ibwy#h
zcyT+rJHY)%_6$g_a6o8M?+z18K=y6DtdDt}ARWAKL`@yne%16RoBFXYnSI8Rr~i^?
zTsfye7G_9h;WZ3f#aYrbR>T#nh*_e^d^F#?z|s}1AWM&kSQvC08C7ZLD|?6!;r8;0
z_}$b|O57IbN^8^-W3Uc5>8dQ%X>LI$@3JP@ImEsrinU{ukwa3qtNtLX?g%Tk<J28s
z!DOyah-Y?`b#wgDASt`Gf8_|dP|#%=;=&lz1jJ8tR7r!n&hI7n<gBO1-PZ&191nxn
z`<B1^ID;b7g?WSlRRc$Ko@cs;Ry65N;x_^`@wD`2Z{2nw6cv6#?A%jmJd6wB2WevE
z?oA1FMZ(Jf@xgCHjOFl|`W&le=B05D?NJW~7Q%hlbnBElN62NTtgnCH4$AUHnY%U|
z?EO^c-c@MSX|W1fdRGwffhI;*m??{ZERzpj<hJxn;)E(IRW-F}OFf{!X|nl^AHwSB
zzGx&&GTRy4LuzAnwLC=KwCwZZxT5#G|2?Nnz1|Vk8`6;mMxHBh=d#w?ZeRT5aPGt_
z;ej;EB{&hz@xVq-w+FAj7Y00RKR<!g8KkRccOTiGw-16>v($79f(9~Dbe>|A)Ya?5
z`mepEbo5{!*4Kn5`gIil_ZYadv4yFv;XiapVwR>hCd&W#P4Xp6GByA5S^C$Ztg5KI
zpn>v1Cz;6tV){MaZBAF$L0hGw=A=Q?raEtvb}wOEW~5Xak~FQvCWDD<|N2(b!E94g
ze8k)@X`eIo#Gi{#VIkeQC(--rwa3{mp~w646Z@O`jXD%pjb>ZSHf$93%RoN^l+BS+
zn?H6J&&&x~AyFYxp|;I9nHbGot87%dMCK@l27<(<emRY*RkCWonWmUsBQ76e9kt*N
zz*OIj%T9d9tQnW>-btH{ZS%dPRk(zZ__Q_i)%ETbZqt73U6-ovr2V6#a4$Ue5eg`L
zeq5@YE{`_(3YsK)Z9K?Hwl__KRu!Ly1869e*O|n<Xxp^CwV{2h^7QbjgW93%4D_no
z&Uy;g+G(nk8&IIRh2YSzMB7e$-vg83Ne<PWr#bp4!=qx$Ui6bnIQG>@i8qcmb-9P2
zsOPw=H}VKn>}Nq~f_CxdT#2}|B&Qy8oFaRXlvWD*WOUtT1@EdGER7NtaX{&6;bU*-
zPvK9mA{7)b1VV-#k%n6fNxPAI=3^{hp5mYIFqVWTEk|A|Jn}9n3s(SG_c`O5_!*_r
z^qJw<_vx7RwxCWhDj;^Rf@ViBzcr3fecPyAq|8J%rYNSU`LB=Iib76r{XjJIB%bHs
zgBbg}TkocsGdNgBSIZ$AQO4*}VG>#z=L<yTwfwI2^~$ao)X>C(DRxP$NkQ6?@Ao_7
zdifE)0bhoJ<KA?MT@*Rt9rB3jgyV^|pcix>`+VL~i5>F>$>tW(S92A-<C#49%}aa$
z-y=Sfef~Y5M;P0e(E7U65Gc_qdpdw7wGAfP*PqeV_nkDMb9=>(U}7y^nNzvwfTzTm
z)Ue9LDVB;is2=?O6;J7HmT2WCylo(Gm7+39X*tCW{A%2yD?>0u;mN#&TiMhI_$Yb&
z2x)O@Xvw2Cn#^zJjEL9V`GePr?m#_!u9EJ-TXYPCzPuVBWl(++6@y9xigKU{57~IJ
z{;UqU{%o(nV6I0JN_Rbh3tz4v#R4!q!*6`q#*qMw9jYmbNb@^v(F=15<V6|$@{A!!
zu1Dwtdb9=nzpYt=q0_27`x@(>zfw>1zwLnkE%pAHb*e6wHqIonh7NzxI9IFw^8yNh
zmP(h*9p<hWrxctV$u0na1UXnSNCW|&aq4CP-r6~Jg?8BY84L-QJgAQR<#0CHA~Zpo
zzr@DP?0uAV&E1;*=ke_g{##+%ueq=f2$#V{hCIR=;wWF-ptglDLKtfX7nYqGfFi6h
z%$j$7cULw#3^L@%6b8@CR24%5&n1T^F?DP3E+jjx7;J7+QTHx}bj_q>u3OS3kt7)=
zR%@Fof+W+FBOo4%A|#%*eTJ6YxX6;NOJGJLZQpk;7-3pgQv3G;O#VtQl(5INWTNsE
zq-7*}h>ld-1dnNa5$$f;hSqM4$~CFs%8XR3px^YpJk-1tbShzo#d?2sW7{$0T4wdH
z(&e6}t}S7ayL!Ij6d2?B04<`88=BKs7}{{zo}p+UL=4D;Sv_@Am82CV6KHXl(rGy!
z`jBM0dU@o~kB36ayB-%C`2pVXOYl>3_3`tgkqWrVGm)&gUt))&jX!-}DAl})Kj7^j
zij*B>8R=DjbH|jyRa%M61^%Ka;J_C}&cIxQw`Mv2+U$TTHSmW5Zzmrht|;U0A5G<>
z%<?65WS)FCR)M)^CB*5$|JIyCfX#)v;o`(O0_Omq5o_3$f@XHYrrYNuXjty0Zu2J!
zH8y<cGAjN-*V3HK`nsS3zR&TF3akD-jfq7S&%FcAGs7-x`tF;430ugiJY1FX@lebb
z>De8Rci==tG+tRPxPmzRBimx^TIMiAnw2Nk`iX4{3&zycEpHviTOb!}FdulyWq@MX
zFe#IF2t>jO#5Z7Mmx4?)KxCW98q~C~kHBhc?9Ce98FCO!k91lmM13vCGprV_+Vfl;
zTU+QT93@~}LhV%h2~52XFU|!uK#BymEn=c+#Db1XAxWoj=}}3A{p7T7O38%Tq!yv+
zg#Z*~n=?!Te$akw!QE6uD_o*lr2ylPef~2^U5Bv&SwOM;cjZ-cl1peCyM3T3+opL&
zp*6&cd5GbGc>cehV?(BA+_hiHB=D6?GXK|P61KOo`SK04w72_9PBkan{)cVg$Y(3e
zc!wN@e1!aq{|ah8RM@yb2s#=}WRC#j%T-NvVUe}uI-=~4UGaGlQPNxBm;9(>H&<+B
zWK9Oy>-KK=pKtunIo`kjj4a!KJ5o@H>r=skvKya8c`%R?#On~EUBKMvkBZU+{lj3g
zk>VIC=ySSK(`<UR#)`)Tlk)uXo&79+AIp?H3JT_ww)E__3~vPn8+UWUl)nt?NAAK8
z<7Ljg{(~<&wF<*{*8VhW8x&6!t7>HpQk(6Dea^YBV<u(WOaj#>5)FfbJLgZEUgb)k
zvYunPY1u{Q#^zA~aZlo~O4E7Vn$DcN?s^o?wzr16&IH_OzIcu~xM*r<J}%VIXH^~H
z73M3N+y@xh(4UP4BYKQ2i;=pGyFY)xy3NFSqTYK;<VGyqx%|AOm~2Cb8Qh&{Va9(`
zFKnT&C=BxqXjgX@@`%<t)vGTm*Lwc^p?x8TDr_(6fO*u6OpVgnc(@F_K*#yD3Yu$h
zCW1T92!RuossU!8TDl$$<h{8KlL<{_W2hj)QD(HQbdL{@0fT&zC`HqVB72(59oou=
zU9g?MY3d!-?ss#>_0Wdd1|y9NF@Q;EDTWI!%kcVhYjnTQ^~eLQ2uG|uz);1yNIcbB
zbzjmn_Ngb%Pw+P1)okgVtw!j;%70E;QRE3`i3El~G$k-n3sBY~DX9~Mxdh+m@`RY+
z8=R9ZTvYa(FNaCyP=UubeVnwYJ`k~Lo_hAy#A|veGJ2n93SkGe0co{~?+<2o?(B07
z<as1{^^kx4a2^PO6}m(GZ+b;u(I+REY>CAh^4Y47@AD7nqewaDv~@`CHHrJhY#uF;
zGkZ|BFonlhHRN3AiLeT>vp<RJLM7a#Hf`=zWi4m}kjVCL*&W!nC?WSsImBvAMyHGC
z`Tw>bh{z=|E%OV$_aOS8sPF&nl=-&?@1K3$kjB3h=1hs{FtM~CCXh@-(S*>2{-an?
zgkLUOGC~?EH>P(9GHH{8>5>{770oSFXsI2GbS=&Pw)LPD0aCiw#Y?|B(6yJZmO88}
ztCK&DyV<4tgGuvQx7po)e)7I?(#QHb&G>vHqc$;Sv6~UY?Ah<rv57xbvuu%c4rSR+
zKJxz3YiC^IvAK8L0K>D`IPQneU&oo1f_L5!!yoO^aXPo=xp}T!OdqY`!TUyen;6&1
z`0e#~GquYzT&EVoOWfx{!?)im2Y9bU=eFO5VZUv>w1e;8K(phy?lZFcp7z)BPz>(d
z(Ik8<+o`lG(mKeuIi}EDCXFTH@r0CadWhxt{)#@{c!~Zpkn`9I+TL@Y?;?2UrYJ<$
z^%x6D)%6hV)2$haI&v@x3RJ^{!i>Mm!;8jJMAuVwShTfZM*)aLO9;UK!j88fz|m6U
zlozB`!O*~i6E*gtP^$&!h9R%w7Zqd&jWRH9-Wu-YjMRRV+eBX!p6XfCAVILoDc-pY
zU0;h*h@u~yL^q>_6VLGR>b$aN{6QNa$L7mh0zNR+BlgrovApiG4TQw4UuQk_3PKp`
zkmD)lJ-7o}7!UJ`3^R3!ZKXpbG9BZ_qEQJ|io==VDoSC!u#S$2O~V*daSAa6WGm)F
zfMo%JWty+RQ8Gd?SJoef!bsYV2!a?#%5g`QIIf_qVQ9u~^)T$vwn-GxVZ}oBc3|R9
z?jubc&>|4U?fRq}2q%?bnr{kTaJbv@lvl4u*l4gvMODJHA&~)24;LJD7SjSotW=t4
zp=hxpuRUvtn6(}mqap3DBXgeED>>V{mUgADUEI3vq1gzWFHp5eQj+sDZ!<`PIZc_i
zLa&S|P*gOO`iM$9BofRvvFIG0GQ7fjXR@&czLKS3l)JhAr%=UMxUcW}QJ4!nDExvK
z_56=mr)|maT|FKuxOsk$0mh><i*7bt)u<i1_Z-H#5PpTjxwi4p(tK49hv3P}5q?^=
z4|b(Gpis=qeL=?}exq6RLFZSQ@kXe(nCfaAV6fj<*$rc^S(P|k47XhG^=l?pX-+JT
zB;UES6inm8dh&@ZBwWG@VGq1irM58EZ0$thysI<moJbwTFK!ZGoHC(5uE|m%Vo$3j
zka<UD(o{zsCFd&#>Q&C@f1{M6Yi-s$@Vvn_8N2_;L9{hc;tv~Q<^t*yBW8+pC61&y
zV%mR)<Hfi{q)B0E!unXDk!()i1^l`SN$4)$ff><?f+)9`E2LEuGZU*Ku^0?<14&mv
zA<tQJ5FeDkPFzf156YGVs$>|Z<D(MJ22aMPdk+tj=Ee&A{<A;5o3k9nb~kQ@9@Hq0
za)+J%jY^o2c)sW@x*=xRAMp+wnTFu*6CFu!4inBTV^3>ETqgw#Ho$<O#ZU;xIt9?E
zP`Fz=&(c3z2NB7tBB>lrie;r(YM36SHo7KNHGku&BglO&stH9tEKOajk3Qys4P#$M
zjFELHi_+-K@(x>T*@k7U>!CZaeG34v-=+Yl9g_jAAsOyBHGt>3U{9few=c;DS5;~^
zDU|Y?QFQ-~7_2!o^k*FUmT<I?WUWFA11M>H8>$>a=i@N7vAs6ITFJ;eZDJSd`MRa0
zSfRSd8@cS*`Yhso1Wgx<hdn`3mx!qsw2Yxc85xve71}*~q)ia)V}wd4u+@?E`9m2y
zR!-55^zQf`vDIls-+V$X-G;2SP=Bb<i#QgWVKu<np$7VM{>Hv4nZ_1yx{Ae@Qf|bW
zUM$^~J@q~rHZ6zBTxtChyU`7|Y~2RQe(zjbN<3daSuC)kZtV*R%BE#{mgPHy9)jru
zXS-Pz1x~W9ctn8Cr&z{8wsqD2Jp^=Qyf57;^_Pm8>Mzw_>S4du)}s;lFQw*HwY!J)
zLju1RE}7N~#Ff~Q5|HIuaq+SylBqo_O^XD{Dr@^h4opq`P*DOL9Ep5y?4AGB5!jQ;
z_vdYItcproYS}g-c%4Rx?m}Md^7A>Nv8trRhV--`Nn|?Nhi;<5>f9<NdHJy}(!+>1
zShq-aP-WxJ1=Skspb$p+hohH%a_+lP6F*1MI}4}+nryWw*kFI;z<HEJJKkaW{Ksok
z|Awy@lU%RGWJv#M+^5{sNIDMvx3~bQ7MbOv&xneP9LdZ#>B~<7#@0;U#<o@F`1_n@
z?HPTv89MfQwX|nulD^D8t7iNOZ<8Q4>dtC?u0y^OySfUUarK~dBWxT@t<JQ_);2sl
zMp+|jjnhKnz~20Rawafb*+V%fSZpSP02+#o=t&`0cAR;R;;{rV$^C?3TG=PLL=I0X
z{8bzKP+)b32T&LzM#iXiYm%A~jg7F|Hc)ayX(&oiHcBX23$lo=>wTH0EE7s=aiER8
z{pq9$xwi&V?hrH(8#E<C75T8v1p$gCBioFLn4HvWS#Qp?|Hs)owr2uxOS-XbcgMDE
z+qP}nwr$&Xp4hh0v7Jt)_w~+)z30o!Isc++t-GpTnwrl}AeZ#)gehiB<>#h87xnB!
zGQ85J5F6ba^8G`ssLNW>t_K5#h&Z)q$~%b8q&#RVmors}??wz$K1d?{VU+J#%=WQA
z0L?AaXEIT+v{g1yrX=5m(~7N@pG+wF6C&JW2sg3Pe_D{ww#@F6X7(<KkLM1j%p$Km
zqh5uyJ8?msAzTd|ko|SBie3yX4DSh!p(Nb<q!}}=zlZPs@<iQ(l<kYkkcUd&Gxffp
zd!1EN_SDPW^>Gb;S}j#GPb<prhF(ShT5)FdzF)Up(6n}f4X>OwO8=zEAhf4m9^ORM
zV#!cDo4OrvwBi!OigViB)K)YiaoXr}!@brUqx7T70dQNA*s+oKj7WU4w|j>FywExB
znk&2yq>QLUM~9GPp(I&IX$U4`qcYDVj*l3MQH*wjhB$Q%(069Q;?ub}4dj-LFdcJ`
zxD_eQg3(Ty@KwskcYY9_zm1nzgt$@(Dq^r@phZ5hYw?wCUp05EIUO&~q32VbpK5nA
zOg_}<Xan0RZ`R#BxVts;DSuBoTD((}`;^?Xq{eRiJKnGY!KRMJHwJ2yK?te`FVuu(
zY^Q1YkaXBej`x!i{$Ma;nr0QlRzQbyqR4U}K1|!_L`2)nU4=|7+wJPb=uvJbJ?9)I
z?O-u4F-{61AIC~X76%`Lr$!rIaKtDPE7uUyCvrYYOi(3v@gyg~Ih(vsF!cE{b~?B`
zW=P*@W@j<wC1wwk_+AZZL>?Bwz;H{3Si)J+KvW(n4_z>5^HdI`zd-nW5eAH*zKsk6
z>5qn_XCiR0LtouM^CS+0hJ(dH&dxDbmy~jY^VO64Kp&9fhuuthqe|Qmf;qtilK(<k
zC;k~~2)qp#mNSLZS|JtHR_MY!QX4&LUyIr!KaM#oP=FwJQXmS3#zT8df5fKlyA}KX
zJ5i8ETw#TibHU=V?4nYUxucZA0WzJ4W~mm1lAMC1BSv0B7#BjqzC2dpa1g!oryoUq
z<H`Oot7Ac>u)nIqf;vk1oS#z8O)w`hvR9cqd^s&?vooV;QpTzm!!2mDlC2dEf-DwW
z5~tjyTycWm{feP;Qf+s_Td^bQpq8Rs<7q84DMwPNdwf8gN<M9nQc2u#K6HY25=Aw!
zXeAldbfWBy`+}{H_@+A_X(OKDsd39t+KBPKd>h6-ahdybADMg8%<W%Bw$vcaepogQ
zwz`%l&6(<?MMti?i(v-uEQf4|Erd3_B~JGCc^za*#<Qk{!d&c2Bk#Fw%Zq!?ubaZ$
zjGiM@Wix?pS__cSPh41!bDXqi)v=6X5yh+;%~*x7w8E5Ac%fLC#!OQ`fYXWs+zNAj
zVWU$qJBWUvqf@PRWY!A7z2doE?7~xnbC+QyBdPLfyK#DGs1r=D*yXnb-rNc*1BGqo
zwhae31!6_bZ{E8aYSnyyw_d!BA)R-frc7&UdQZVpw<fe*Jzv*rL7bhw7DY6Asy*EY
zj;TYrM}KS=RU0vR5j@(yhYHhvG+K%=%Vr-5Fv-ttofB-dR9Wpa_C~x1x45ZAGeiPa
z!G)+|0IbI$Qwb@GCDt2JDCACiT{6hlmRqnJ^>qQkE{jfkVHWG@2BBXlu~bgY7tzT(
zrmu>eS_9zUnBMV)Upo`6)4JipwoY99V+zsc48HFNWIHxqQpvB9imb-xH-txHEs>G0
zjBnbmLgN_EdfvK-JLL#dHZRN2YFv{&>*6Jy_=KAByI?XeteiR{<NV+;DrYDs>zgX)
zOmrP!`;4glA({{vq$0#L+bTNT-dW3+7lq}ZU8>K=^Z{#ESiZQQ_K)hbdmf|FOn&Qm
zjvo}$#`=Tbmv6*<iTSbihjVXgelPzg(09B#$kF*P>RL+t|IzaNx5L_hEKjQzw2lq{
z|2s_g!N3z(2#PV15L40sm_0#6Hi*K=f+2wNH%9F$WY55;DW*FnD$k*6eU{d(*ONkV
zq`PqoEHbN__U-ECXIpD{@9pYp^WOB9?-kuh1MY>q*~`q=nZN%J=TqtHFMk+;R*uO~
zva4l>c3AAD{xNWJx2^`fZj<J%P;bY4SX{?`Sj7E78?gT>#bWiD0LS+}ekI0vk%|&;
zzQ^jL2`6^)&=`(@ZEldC<)u3lJGn!}$#XHJ%S)Q^ll<EfRxfcn*P#$&uKPySN0!b*
zo_*$g2ckDUDD9!iR&VjvrSgQ^<hc^+<Fgdn>Y+Gn{cxo1^tR=+<Idv44!h@k@c9-9
zOMNHI`9^HH6>s{8y5Zmp?njlKZ|R}?Q23YMy%2)C`3`oYKQUB)@>|{Mxt=tCPa<?L
zWyaq0k$dAykLv<4={R0#i{J9CIjkS5BP%xW2(q`2fSICz{o}7$!>)OVkeP&mnD4+D
zbNBFW0KZhxK|S8Cf_=zV*XOj~upVda=;dpeH8@_WDL%;Thd?}K!rJk3Hf``<U9*Or
zKM#&21(fr)Z(K12>VD#oxd(jo0Q?O!s28so;NTiw-(BZ*7hJ<(%s<ah4X+_75_1_(
z$-{d37P$h7_1Jc>kdWQUtz3;QG_-l7M{wmSLQ<9wVM(Ub#|*w1EL!<>$BhmOCcvK3
zK@j!lmyH!*Z7F09Y+fLNz|sQ!*la=v0`tcuYpCrOx-gR?^r++O(*r8ybPB({o4;%r
zKUA07vCgmv@(*sG85H#V>7k$Kh)voM;WJ{tXMh8%K%t>C2ML-tQOQcvQ}WhPnjC8P
zR&5c+8A4gUWcPa(?}L=gvfJt(K9Yn}g~Z4?=~>p%jg?ZZh#ddAoP05!T`bC=Wb_8^
zCxrP!nE?90*ziU~1M6r}V87>qx&`K)lRoTXeA7obBs*;li$7^j8-&=v8)2MTvPK!B
zXLC#-%JX{KK+8glny8dfNCT})=YKE!Npz5x_L)6>V;R3oYw#Jlw}s0V3~nkd$`<C6
zLLQe-qb_g-OiqMVQX7j#qGxy_*A87Kqg7DK<G-|Cc1T*kku!J9Y+bSs1q(Xurd=&P
zX_TWzWbV|!TUkfQ4}hl6A6FUJQlBq}anOX@;t`~l=>+CUR{Kayc6}UftFVJ>Yp6|o
z<hg>KlBxuS85HPSS*u!^?Sq|g(-IFk%D6@oy=0<dk-QmUoGRrbZt0NgHcc&V5IvGy
zg57&YemLCf@(A+cs8itiI%Utw8;uc$%gfnFgz0;+ttu@-|C+Q~WIfaeS&N~DIk!r^
zN@#I0T5SP`2;MOZR>v3~Dk<R;ike@DVhaqbtOS6J5fJsbeBs)kzaj1}-s$7pAK~Mh
z7swBHbNvgRbMXyqfK)F!Ru3#B)39d;?fThgFgJDy(<8eINo-UvQMq%~4Wwp`|3*DX
zxngo<lx@=HlyqZ)wJ{Sy)#QS3Y^7_Okn12RzmRlF635O~M8JmDWm^)h8z^ctBDK^4
zIgk}(Hu)HSsZ_!AWD=+)(nn=>*(QQ1Arj`|a-<S0h|VlZ=q{x*izL#W#t4V5kzjRq
zWfY%Y0q{6>(49sbr3D`2R7HbN!zIx!JL1Tp-<4#zgUpW*>C#|GmoSoY@x?8<HmcAp
z0h|=8qM5WPw~Hb^ud&cBg9ME$By(-e$g53+1)AB;aCB3mVSp8@qovN9tQ~Xd;*bb*
zYYGgh=0sC%s%XROmK{;;RsmFvT&ZyJ!-_%0HN>`E^LhJxI-UYzJAvQd0s8k1k0Pkz
zWD{~fXtP_ZZ^2~lT_ZS>bI#R`cIKg_rl>n}B!SbHBtLS8$H>pOITWCrDIaS5owx<$
z08$<xg=$89(taeo#cOhJWou(+V{hXzFW@7jx}qbgi!SJ#mBDUdZSTv8=W7t_Map|p
zHHTcacDmXf_4|SocD(7$Wvnuv)9iKr*|O0#w@Xin(=V_5jkyb+G#F|`oUceFy5_pp
z*1BZ#>eDXSmq+>V1Kb$z=?ueIJC^X#QG`o`tm)K0aY+qpeEh8wOyIlHuLnfrQJ&RJ
z9pp{ac57F#5N(rF<xy&$Fqp0wor}=3gPMBXyXd6TW4ax!e8kH}cCgjuQg&f-{T~uE
zK^Wtt;>G3SniLM-Kd(F22CpwN&sYq6mgMfFNmvz+?={Y9!dIqoqF!!6`B%K$2db@v
z_l)O7l%2%*Nz4z)DrJOAF$t}Ww6wgoJ|yH4X_-g%YSTkGwYv`bXzd`FG9RnF1Yyee
zKsn^Cimjw+uLo#3{uX}n3L}ztFQ`1b^B>=VcL^@90|Dped}?wX$-njo$_c<g8ifOb
zu}5dBTNtmMlo?(g_+JdTc(sC!jC7pF&MKo@^`$=NlUxRnGjS0xKm#>PQA;pkCm6$B
z;s%IpL{N|UJCPoWCfaiKsW%>h;$&VKMu@)>1Cuu<e<HwWf>E>Q2lcx|LzM3rUp5}X
zkWCvD6hSnL$N%7k86*0`0*te?l*KNV$YgaTt@6Idl({8yGi7u|FPQJ3l_W3ZUJzcG
zcaUYQjf!J`S9kUpfo*u(3_GDuY_O0<oI_C_VQ5V`kinUn&~?qr0xwaPL6WK4opvM>
z_qxE<52Oh+#y)1|boTOqs6Xl*t6T{kP&~=Gzb|Fbg(Yq^;bPv15{yN2rtk-0Tjxd@
z(8HW^NHQj)mEVdIQeq?;sey?SXV{|Ro1x<OVmeEx2o-fAPb-VqT^>2W5br>pCe!(&
z0dkkkf!Aoa^(o=qDTb{R$K0sV35;0g06sb4C^_=+`T;mL;-GXUS~?<_Ix)=-(3JE5
z)ebmr2TnUc>ZBs*_@K_iqY><uloJmuA6MBZfpzN`oVN`%Op&qrhOtYQ6Vr0NA6KR}
zl3iGS;Y2}C425pOBXhz#-KjMcEtTdsoeTUyhlk1IsJ9#oa8+?<4q%-gXYjDGLi@al
zm@c)sVwLSBGAE2e$*C*<GUqCjTRLm|Q-Nq+rx8&aT$TDT-V{XM*i+im6s)xT>U&?7
ztH&n(kfap7vZf<Vf2|N}ZE1$xfYVN8aR-mKjPHyJ@?_s3?7%1W6di8F4N#m?*b%{{
zYhz7)MrZg-1v}@Sz==ht>LA(PST6@Wozk1$JWg*gK$EXC*?BQ(Wikos&A!uC%5gdc
zChM?_F?B==Onkm%&6teyP^K%i#ts0oJ-WUZhyIphyBI`afv3_j!e+@z{7qS^r@BnC
z1;lGMkW_-CgAcw2l}l{eCl;$K3#R@~H(id5f<1%}z;rFmn(4m(ttb{$Y6ojd%P4eM
zqeL`L){|mDY<LaDLz|iu56)@&Orhq&m4D0>uA{9W`n5oA3a)B0&lYrHSVI!dMU;p~
zwZn!&X}j_-)mXk2W(-!{`7jO@XB8*3h#zbM$WX@3*c`xTd8F&IC7-(9ak=7k*`iy$
z*m1e(rOA0khI&21;SqS{m#7No_+WT3M$8)|_CSx{oYxWR<A!R1bIPdwefB$leZ5kn
zG-&^K{rbAxX}+jCy}C|>JTubgwI)}7OIcN9J%t6#<W$5ggz5|lOFD8^>1}~sD9D*P
z%AqGMVFH|-nkg48cFr*LevjTt*vNE*<K`e^<@Wu}8AGlgFINz2dy#;cJ(_i=e2sCz
zOH5H1e>`PH?7jvHzP1BiHq?cfgO742anJ{p92Tr-AjkxT^CPs{Xn8}J-5&+ddJ^OT
zrTl;NxEPN831jQ{jO_e9nHq!jSyky&3F$UM+SGdenLg+bA5#qcL>fP?xhEmtl*1JM
z3x+B<Y5iC+;9odc*GVu7Q@BwMExy3<m)tZE;g^`FlcZN(o-c6pJ<-w?>EWv>Zhv$p
zUwdU#_E@nHT>py5yBj(pdt)E3R#Mbe=iHXFe#DqtUKl-<4Sh^n3HO_O`G+f}R?3LX
z<aUJFX6E2G$xHUS|1#yzZAQQGeg~%qT$ckL`<eg$d=9QHFyr?@0|A9%{J*fK|Lq6z
zA4BjTFVL$2?X9wc?RQJlnLLpj031YU0V!iF5v2V4H-v}~5VW-w8l3Lc%(SeN;pr}i
zGdY<;39K!p)k+(c!Ag)CT1AkQPyzZ?QSFX<_wBX5MSeKsN1iiza^}SRs)2MKr}OHq
z&#m|FEw{PH<6)*c@buVTuttn8)eY=W@TYVm5Msrf43gg!YAmE^dkwEjSor-0lMg~Z
zCV-fVK=ob&=rfpNEbzAwhep`gJvh2N7$f*6h=-C7Kl%VB;I;6#m4n8#hZdHX7$6<Q
zgDoPH17*M&nCI6qfp{=S*pbm<x@ymFFFmv=xrj~4#w$`qJaoVma1YT{9!e}>qX|dA
z5^xNZ{A|QwO;mkEs6INg9y+UA{;(%{edSwL&;%v1<;DGs7?bJdD!wf>I)ycQh?Xt&
z$)B`l&G>S7{%!v#klHPl!^Sv^`owu<oj$+p-ForGIPCZucI8<V@KSuU_)_lkl0pO7
z!Mnw0w<hwU*K?g;=d7QaBCg``TfB)_{lt`(>`i5=?rQPZ%_i70a%s5jTa-(M#kfy=
z;K@!k&B4hSC$BWF*^WCGkuDsPOBb3+OG{>)V)2P7tHFyOV!Vb(Dl;7QW0}a-QfXOf
z=QPR;rF99RoZ0AaTGttbIV`ls##{@gB=&3FhgX#v_Tm#Aa=RO|E@@`?NT{RN<pcEO
zP!Xs_3V~xaiVUn{OKf8j7je1A8FS~X&_28V_T1L1)}s&=nQY*x?;Q}IVvV6(c)VS?
zXM|g5|1yTvZ(%XH_EZ|`5_=)4L>BZ5pC541B0DPVjLbt3?d{nvVCwK9v3!K=Y*OBE
z?l_m|uFj*Ee%Bqd)C%6%?zk&mL6?`K)JAg1q)U!<sC8)B{DM0nVu9vG#cfctMfZ-%
zx?3Ua@K2_LpGv0)QRCX|;W*TiIMChtA*l>0&0*4bTRS;a_1VsuNK$1I@lB}<3IB?3
zS?yM%TCn32B~R_amm;=Xcau<@2w3%vwsTjHN{qDV=CZrmuoc7jV!f~HY~KxYuuBlz
zmaIw6ZR_(cT$x20hULhMN3E1cCQBOky98;}6@0Zfou)$;%$~C;lYy6wG~0@$HLE;=
zZ(7Q`56x0KJ7=0=OssX}OGgBEvc&rcny>j@;fmad47C$0GA!J(6)mNsC^l-vW7Axw
zS!ya2k2Xm$_saUKKdwFcL;Br<+%mztraR8zR%14`iVWd*O+fIMl%<&}5n&V~3vVqt
zz^Bl4SlRl*S{RcpEC5pQ)r~owBE#<Yykuzbdt-<!Ur78)^DM{*lo`3GD)$`=#beq@
zyyqc?oEtg<o)e@86?6zh+omD4E<AK!e;dQ{1HvDa;rWN<z?bNW=?PM;hm0fuLpV1>
zbDmFzym>57>jvvszkw;?B^%zr|G5L{FR9`B(3#G3@U%jGgGom>!{{TdNIvqbbwhSm
zDfeOU`QbA3*~C1NVuOu0K<MQSWA3icSfnzDH3IXp#Y9l;Av=y=^q%D(z^(WkGrOzh
zAF=o_{s9c-!=kt1Fn;KP8BV^Dn2rN1LtdMWRh>?3c{04#qw^5-8@WyBbG>!fT1}Ks
zb9mo%N*KEumWQPr!WVjj1d-j-*mA<Cj4=H5iEim(yLF!|v{6n{qHY=PMZ$dbQ-oJC
znmPHLY2>5&BOdQM8<j8B!76u>EY+{rxh8k208_0~U(HnS(Du!koC*!9+r@xPaJ5W#
z*W(_36|>>k(E#FW#=sAnjq$mo4Lq*e_2<!Cl~e0iaP&!UhzG9N&9vfdHLG04aikB#
zHOp^Rf$qPD$UT+XKo;H8y<6#J{n63ekfL@GMj1U`G4^Se01dRctCrLTV;&SjVs*~u
zF@CPGeo3onT?IfJVn$|ppFw-=TZ$qAEEJ7VTY|uS$at?nx^89)`nFRj$SBP>k``Q_
z;{Grki!t=2^gHZWaJC{L9e$g(i8uIGk9E_vs!jbYc7G~=6PBWdu`jJZ(RC33B@VCp
zSD2DNM&4|gp@;n7S#Kt-{~3dnoM0;GFjS6^<uFtb4BITeU}g}gL~{`(N4!FF{p2fz
zkh$WnCZi=*@|@~>n1gC_|2KMt>Nm2A2S=|MTs{B|CtHir7AjTM4+DKk6YjvOaWa?h
zk)=wEVK|!BCOzt8g}`RxNHI=l(>v+rqap4DM#gMoWL0Pt1NkDhBTQr^u|jRJB}`;T
zEQ+fUj<>{;UUGd-b<W`lN|H;;YjtUeNohVZc6}f|-<Z)xh`Uy-0rj>Ny#6;7euwUN
z4Nn?jPmssWfEh|>XfKZUb|ZSt&cuh!8{I;Pyl8n;ZB*1NFeZaG;FI2<FbeT2c<h2;
z60-A<&S#t#r3a7;h}*&?$z|rIuEQQ}J;ND4g&34G4x73hS*J+9B?^uWn!KY(U4x<W
zg{N~40*u<I+SdFUqS2?3ZYo%&rmPjEoMLq;gg?2;6bc$5G2?{R6lY>fj<YQhn#XY4
znMP^G=Q6+d6?qGiiZ3Zd%X@&$5FhxHL|$${#^009<Z;$a+5rpYFK_$;JrU_pCh}sR
zn%(&Y!Ia(EgMD=*I_*@e5*+R?&?z9Xz2-?Vl_g}YXj!|Mo9WuC!$tG;Cp7cEI`nR&
zM!}c2)BhF8D%`=hurm+Oxv-{FVN{21-&S)V5zYYl-(&<t`&q&BS>X;{Z#1UhWi^3d
zt^h7oi<v%zZ4e}7&b~3ZaXsacio!bXARhP_tWD`Zg>Gg;=~EGN@q$zs<-5t;RsFjE
zyKV-Z(z52boKZjDnYjoJ<kuiPc54?cBOBQ)Hj^rR!mi-xTX-g#dt$aXc5Sz_Lz}r{
z+mRjRICm*{Dcvp4Tg9Y6|G4SlPfSr?DYiU&2gxy6S1M;@-N$dCSajr~4JR<aTcyl%
zy|HC6P2`<e^xH)JBICRqcT150zC-|1z6{8(vsLf$Q}T$jWQ&pV3;^E@oZBzZ8$YgB
zAmJN9vbgXJVuCcR>_1lciI+^mvL`tUaOgApFAmd!S^GiLR)0IlQ6rWP`Xef*g+XOR
zF&UyGB|1Oy9|RzO^mV3x*mZb@YJZi^#Ut<eIXMRC@W|2S{l=7E>@1IXLh9s@q09T;
za~y1U3X2}jp@|W_z|9NYbI*BSzvbP%!@<ByNqy942#jorG{_QbP#DkM={wTYdEQ3%
zh|}XkOm!E=Hl_-}{Bs_?d?BfFM9Q*nIt{4I3Bj4TU>AzLEn;5Laiss$*_-kxeFMc*
zn1~Jy?rtXJNs|a~uz+I6fVj&fid>G4AJ_Z^7&FoErVv&LDj*r8o)wPli{ouAO*w6E
zXm5Mc|DS@85Gol`<X_O)^B*zx|C<*3uQ1Yo1mgdo#cKZz0}cxy`7V{k#;*8j^v4B-
zt5v}I<)9&ANQV}MTis^6ShkaFB$WXAPbBa55%0t!lPO@LAOXD7*`D0D*KnU-4{u=m
zKwAh88qJM%#=#0aD}{2iQ152e5)E8tB~Yn-2rDZ*4yrE1y7`%2dmf9wCMC+Bxh+Xi
z@lmaM<76OqMZh0?>i#B1L7hx7s3?x5JJxiRuCXs@jAtIxF)qL&<jIuSj~b0o9Lmu0
z#oD1>k9F_G$U}j%%R-0GtlG<JUh8aoTBTW_j<T_J5@dKDSJuhBTKahU`%_^y!NG##
zYKPqXTnSW^^$n#TXy|k+pOA*U#P8-ogP@wV{c1*y`(}!64aW2L^KvS1p^p=-10!a{
zcp(sY-DsU@%t##5IMnd77Kmil2tlu5QZ}45s%a`pJHOB{bIF)01RkU6{XZr%tj00%
zy#F=f?xOy`R8{;p`TpM!CK44-hyT6Y*sA{Oue^r-qbL31on)F|3zv~$5V7O|hK7e4
z7HdsNA83QkyP?6B!6%KVEs~}JFQ(4*XSchQTUIu^gf=3;(juU)MfO$ZRfg*)@FjiT
zxh{|Vru>)j+PBXx=brP}d!F|k@9RY-W?m0O0rF4FU=-rUy<v_jlIk5YH^P4L*E?3b
zPY!?n{v5gO{5>T&V)a`KKEPu{ZglR>d@;^BL*-60Ex)-KEuP9_I&SRV6P*ti&L^<j
zH_@E4z9^m+6YF0wwTVOGASx9I935jvjgT<|U_UDAcQ8Gphmt6Na5Y?CjZwg$GF)9H
z$H+ccFfJ7YwomAwx@riPPwe2DDjee*L~yw(9P=Aluze-R^!^rHo}yz2@i&6<51n>j
zxlsu1p7|Xpx;XY%!eBhwmxjQ`+3P3Qb}z{4{&@-E{@v)2*d*%Gk|i<i{FQXcsE(Hs
zVmxl${U7L$kmncz>6lI;5?#wC`9F1b@p<PlIE@ixj_`9UGR=^^y@dAm3IZ!$+kE*d
zv=7=Xb6cdTLvs0hGhuH2KYaR-@K(2X9+m8wEd~QyTcX=MJ2ybBa2=qYv0|@XpoCVI
z?vR!-w12M8=YwwY__F5lp*kuj7LRVG=Kh5)AV#*Zq)X(e-zW*=Bf+}PLMy~kB2D-f
zTN0zNV(Ui!I1=YXjxI@}M5av9H@f4j$;^q|r;#ZyL|TMFc$?+?&6)OvodFS+e&S*V
z2)(vX&s^#;@4q~|TY%6GPi+o7;LHZAkYz=bZxvhmvY3g0jUd%tLi47bz**MTYUd$V
zlOq?7XkSN<#_nE?R3ySQ{fZLmy8DHCxAqZtN$#R96CdB%B147q%eqcGZHY;rsAde}
zNhQTM6QS18cWA#&J4dmHcEN*XiHe~K3iDQ~RAC3GaXd!cQkNDjRv<EMVHok{kECQG
zRc?^EDacmK9}S&36J?P%forJ``8t6B>2Wo;%Dc{chaT}XoJka3^my#d4dIUdHoFsq
zADk?&#9%*<3BEL!W$81o>)Ext<R5Ef=4DzO{<I8N0BEm?=4m5JOQ;%eY84?e^C3xy
zdckigDL_RYo83Km!`Vyc;*LBl(wyA1^<lHJwz!@2X<LG-E%ey5unay0w$~|%7o@A5
zrr1?2TCc9OiLzla^CZAzCdh7UJstGuOD~e^4)#mQ;MMli`FEr~X9A!e-vfFGL4@IS
zz>(+AfISk120w15cUO>miBe>WfO5ixwCfweWW~jk2N7<xN<7ZWMhkK!pIDiL5fL`C
zoT~i4xw;-;OSfljNTUpgeK@`PeRq&-b6<wiT`<z3M7G1sIAufP2?G2#-tPh79|=2q
zay4*&r~NsPS>Rt|=>XxHcYKdL!(Z0^hS$HXfmcCl{-(0Vw*IyjT>a3zG`9_C1ztsH
zbc<*eT!qktZNxCLjc6rY4b#LmyJoNs*Zjn-_rf5@;}~)XIe@Yj*W`xjAE<giFWtWd
z$)#4dNBa^sxcgC62g`x22l7%6HIC#UXG3q<SpCvT`Qkp+!+rR>-m_lH>n~}sy$Ptp
z<;!jB3uqt1eL|T3tSfp^OW!tMyIzg^lKs7;w)_4VoYnb!iAl&lhJq(gD)#`OnW)i2
z;s;<bE-s`XXL1I)WScj=gNWKwT=pUH>%q3#`3LA#sO9VPx%ukF&hMI%P9~vV_mhfm
zxqZ|+1o*kCwx~WVfJ(e%J`_-bmMzO*vzYc%LdtlKrv#V5Wjc+g443iPOcIyjF`g)<
zQ5;2)lcMtubOuIKO+4%TjN29aQ>h?Dpl%8!{akTIOi^?IPk9P~K!0FNv}s-Bk4Vpa
zb1VF=1)Maj>I)vgYj_F__5f3Ua6RlKh>5i+(-zRn-;-%rEChsogjG?Zt=RX1mFnpP
zWd&c;tgi3_lR|!yNYxc_sGMd9O+3Rc?-1$Mh!Xnp9#`d(-3FlQR*1K|bf)3Ww{TFd
z1-2@;pkU;X_2M0pxwcSwWCo?f{u97Q)TGVol5U8ZS1if8ofB~t4E#iudKu6yGH&-M
z(SIol|I!!t=9?<;4Hw|mm+>}a#OVo3KWO#L>PTWr>J<qgcpTuo%xVq`IdcuFPZ0&L
zga!vk!?hj2dlYlNF&fQPcO1c}z2nqfx3<{Tcwyn<va#JXs%g<1yZ$xhAXike<n<pV
zn%(iap^_3dp+;4v=<hS2Mo>%$UKg3@3VqU&l5^V?u|3g{^}Z%IS6kknNeOvM0hslG
z+mm*&;XJY}(lAx-#<?dP$7+F3!8TBOlp|gKh&Hd^(e-SRd{e|4=fkI+dM;PXTr6cO
zyFdsr`TGqYF}twOUj)pG0skGTAE2nBWWOQmMHn-qP*3>eIU%x|Qf^b6<2f<fwp5}k
zP`o9CH?z~UQz}-KSRLRxtv&4Z(9d%htTcgV)Qn?IS9HXPdd90si*C>jWmRcgO&ac^
ztm%)Cie%St?hrntie$$)btoUnCaI&FG;AKxCh3bVs!M#ci_{k(KPQN^CarT`4DhnF
zNC@-JWihH|u}OwVPY&BAhu<nKT(F!v@Uyf?3d5JHLPC@nma|+xp_w&oXSqrYGb<+!
z$FN+dhOeDX!qcOHw_V(KtD7|3L*v0*po7PsUEy?*5>97v;m+msC^hVFexhVrSX8kh
z)JmYD6`5*~gjJ-`Zb1TfXvZL0ZPkhxw*D>HW=k^OkqZVsFA`*NOCo6Un(#ZyTN0^}
z4Mn6p7cB7)kzn1cH7221yeGXa?OL;vO=-_g*tN^ec1JwSr<+uc7**8kQsBRy-rYd)
zJ0Lnk^1M+xp6Hz?pv_?aV$t<R_3c14NBS9OErRi&BsNB6)ZKVQiFZM#QO-$#IlNaz
z*5w<tm?X~IzfA(w@BgE2XL_A-tOywh=$r-!i247TS@<uxsbu<J4gSieP9pzX%k*l&
z`lzgA{`gOjxM%3-1p<K*6@yJ!Gr>e8{YC)^w1AR88hIt@l!PF2Udn{V+Ee{puBu(Z
zuxiyxtx~-glqga4QQ4{65pUOB>)P7fvF-NN(7t{V6n*iZ?PboCfdCnL5qG-f+~Yjs
z-h1!+dF>$gc^x*-2W61gdl?+vGM*2}_qxv)eWU+s$K-!JIC~4d_=?BuSIO1)ytn@4
z7wiuAwF<eUd0&UwuROB%c}K9Tp2Gij*Z)?G>91t{a|O^xbM#04jzWaPyBmye_kBZx
zga;NE@kt_ouR6Jx3Y3Qd{06<pVH!osCluwIR;0FJ^kq^TZKOWxWfJTq|4^U;h%!l%
z#V4X<7Lmz3O{$1ynnmm-obxf|9UKwL-x>BztHh&H_DmNEpfDVl5G{{SSgqQKQmXo#
zR@_ilv92XBtx&4x!U$8TmQN-Ws8^)|5!UBug`7BLc}+8$^dZW6XuD#dO`NOb)1)v*
z9m{Bz5U_?VV-$*FRF7%q{FaVVAUCfbQxd+2YLHB$q`Vj#chWpKDjp=KHcj<n!EuTs
zJo74@2%j=-MKrX0DU@EtYFec}!)}@lN3c{Z(G073HH^-we`*{g$2|cNX2W(W{M~Ok
zBPHmVjDHJ9T7(bF7M^uAD@UzIO<~ns+`H3w>d>BwBxA9Ow~K@DOh&w*piGi@9KuMO
zIIF?2f!hvNsyQ5;>&Jq33D-(;l&E2TokW;-`RRo=_kkRpf_0GRpq-9>0n@(aCSO6_
zv;sp~<I&AZpK{zJQ8SEC`5bG*!E^M|h9>AR`j1>!>9w6;As3X))>`T-b8TKpvxy<~
zdTTlg5*_BCQq#3PFyXLr58Hf4sI5XIU(>X8<MF2Sl%s+t?{H)?8bg^Pj&!hIw!)+U
zVA92n5KWM_2xz`T1eWjGmE(-DiyEmp+q+kz>(`T6FSUdg;||?NTy%@bH&F}y4UN-i
z!l3TkF5>A!S8vhe)xvX20ZVjXaU#{s(@hh0v~{Z?R+$qoX=W!-o3dh-X=Af{t!UPa
z)ba&m)pnRnygwLBu2mdN*@pAHBYf+8;wz0sZumF6TZWg#*+z<Ox7Eb8U94(0E*b=G
zTKtDv(5t<;4P(b;c15&nzol4D#-dHT#ZL<G=v>KR6wWqEEJ<o&>p6OkN0S&X?ua>!
zV@kWjXk6{FA)!{x5msw1s<aPp8r<ol0{k#x)DgKD&cK;+pk)55n8qdL$q=6(LnQ9+
zI6`$I<S*p+2ktAVoeYb)_-X;Ns<m-Fp#^okbX#m9E+Vy-+$&y1yD9vZZa7%TkRDu=
ztY%}&6Y-=XLEFmVivyyr>Rr;-FddqR?^>4r4k2hZI$JN=nt_iWAa4XDOc#z%+11+`
zQkjYnPc0URydxs4cRV?2JhdRrMw1-IdV|nMHe6#yYQ0~oo#A(s*nI^mbB9em5|oI^
zjO!UKSh=h(58dcV>G<6(Cat24lY3RVW!fhlHt(?==yq#3k7p>Zj-hRz=fh)8`;3@E
znZeDgly)`SaGfIw((s*E9U*ZG*T;EAHaJAGo0Z)0zV?7W5<zMzng!n+4CW$DEX|yq
z#v=^js^NUwJt<bpJv08erW}qYR+}i+M~QZ7LfW|jLtR;#HA|Cb#1+(2sbKMRj+CRc
zm9bl`@hC;6nZV+x==<VI&SKBgG&O{$HjO!zj5#E)Rf+(DteKNtfUROX+jHxB?>$?U
zsA<N8=7~vb(#(i!$L`3Oz;n)gMisecI(U;Au2Uzap=BwAmqrOGh$MG`dp)#{Yb>E{
zSxa=O8ABzGoM1Xbsj`M=tZVm5m79D+3Uj8trlkx{la($H!HsemYhr*@s%n`{Vg=z&
z*~kc6BfO-rm&|*H!n`A$a4W0-a-B+Y<wm(h2gDjvcV?1`wk&Rwux?d>K5~3@!=Ck|
z+J>05Z^<nJs&B_)0=3L}GPSHuXtgFefn0o`iTd`<^%V>pdKOyyW<s@0r<O;W^$C~Y
zMxq}U623T4?2|fZFIhK`{wi){o3^8J-B@;*&vpuK3L5*QtPBq;@Fh&>m&hok9McJE
zPT*xpD&cyH{A4-&dkkfMYBu;vV4DMt!B~-RV2e8hik303ZC;gtwLMeA42;X>L{<Q0
z`#9?t0@s&ix;Fm7t_9QM{PS2L52GV}U)k(Er?Oq@mQ1HEUwxN8!wJGWQ9mxf(_hoc
zT#w-qIv&eO-3L<TzJC<VTi}JAx>gnUX@bR}tIu2te$>{Y@r(<ZTd_V8PgT64pl!iU
z8%khCE}Tu|#ums{*N`MS`sVdOn?w`!zDhrEH}U+x$ehuL*y2UYk?-Uk`=t8Y1Zu@%
zgF;AmCDS|AE|Lsh6zt_u8WljMQ~YLS<J-DyoBWmeGW)^Rb07usq|h*sMAs#wNtuA@
z1oz^;fyZdFxTVfV`QDy`E3~v(x^45A(NhQe4O-YO^Pz;tbaLq-hOk@qT)k<h(1e;d
zss4O9vsIg}`MLs~tX2iPK#Q_JOS+B8O0}KKctx_C3#FJTb?+t-SQ%m^Y;IC7%^VwH
z*K`b9MxNks*!WqMylZ%&LQ8)}V%IhvselpiuKi#Ou?08rkpy=?H}P0@l?(~zIhcZZ
zLOK|7RYITP3#MqfE<}!1+9qA@HK;k3(wONR78rbPZPF_v*mOIm5!0?++ly8~(p=_v
zOS9ZMbgc7AFx}UcX5UEhKGHNj6iPyN*2&osTa$_QL!<^Qyhd1loJ6!{DrLAF<x1B5
z)Qi?{0gJ-BAi?z7cY=9h#6U<*{U{T95Mmt7X^MG*<YrRYwNG&iJa?vb!<;KFmxuyC
zQg%@ipy+1-4@Xbf@l!;+=w#RHjq(9ucA!X5NLaHkCM~P7vekeiIIomeTYU9xfxbIl
ztvr|%?@^zL@eCH_HLm%Aa#6ekNc%M$dr8qc5TVV*RiV^jw?@hY%-l&+9{k2EkQUpB
z&dKQZly>ig_`39)7_S>GIQT+M<y}=i9^IG|m51oojhYp}Z&@y)W>~a4Q;mmZmFHaZ
zi@TIkuT?yk2@wz}Zl~FQ^Y!r@q&g<wL9|vBr$iom$9l2?L*lw%A(q%Sdr`m`HRTjS
z@4p%PJU!w>R6h$JSjx%g=-hCZ!dhkf$gN65VMx9fx~vk%cH9wt*yX@&$XHs#=pKX9
z?52BkG5Q>ftL9K%Hi~h<?C-j>N%I>%osK-AOcBHk;9T2>OeEtT#uifCyOD}G^9PP;
zF1`riEXd-jfkh%iY%$Y)k^$6Y+W=elK&07KRLQ&v)^j%F2JZEug(_8mC-lfm%dGD5
z{3M9kc}EgYP13S#QW?K`&PAKLNR1u!3(8k!VPdlub&jxH1>a?o0z&duHOZPNUe|Nn
zW8KW%eTxwvMpK5Y)vYIXhW7F@>oPKWzcBc2JoU!#@>xH?Oc{`aa?x@<TalWzgCnO=
z$ofIegm?0#Su8^+MI71cNG<3K?Q@(*XH$L*<&If3oMq>Gi8H@mHMmyDOQ>vZ7h3iG
zJMG_(aB|=Dgm$|v)${_%6kEMrJ5plXO5XpYx;jbE>u33@i9Q!+j3T%@bw5YOF?TBW
zA<^FfAZZZ*FNg@ksJl}EG_JgcUGjYKqV{b!^+$hjk58v^OZ~vgV2H)lcJP~Hwi973
z`P=d3w3*xoQ{^g<r?Px+pgi8b0D@roP^?YH9K~*k{Oy~>pSL9C;Z^yqWmu|9l6rsK
zTAr|;!yhS+r$S9ol^+Ju@VK~YeJh@EMis!<XT>w<hju+M64lGVem%IpgVm0TN)-e+
z`eZZ&Lfv@vZYoE+4beP!g)>0eiuyb@05D^*N1(*-+C=RQ`!#OmcYy+%dt?n1HapTs
zy$s3wE#=oM6k8bpF~1yy>||6@Fhe>V+D$8Mj<0QMghBh%m8hv1;>-eQSPbb_3vjF(
zu`cH$;5iU+9kJO8VbkZ4(v|4b50FFdX<H6eTP$hm9G;G>6kGX%=d5P>!m=G<pE+O=
zkDNPFKW72H9kH~Cc4u!QXm|rgp!sL<numX>FPdWRz}NCH(y5ka6gQz%ta{Z|UXDtD
zb8;R-;(DVeVE%|86WtjzXNt9sDC3z~MxN~>_$1<*+4+&*II+hkmz_dV>knMvQ|v@9
z%6c<~SMik={c`?PT#bJ)Vw?I@?1WUEQ@<I$(zRrbKf)EM7VJqwE*1s>TLJ;QC-uq9
z-mO!Y++dJwGY+So$St8XgI5iPf+<w^`#Xqu1e(%O?j*Qb4i#>q74wlzRqcBC3z%j-
zc&S;mC-vI_7efhCY9ydpS!)Es2i)Ddnr*+jBOIl3h;ABbwcIX3LM5&_@Rkv8Lx`JJ
zM^|!V)&ij~3S^_yLBCY68`6B$qe^dZ@+%aa6dd8&kEV)>5^JQ0=Sq0yH&(M1OfX&P
z=pF9&5HL;M{Rb~8xZmyX*~u|k@TSN8Xuml++6b-%p_r3LKB7lItsmf+v0#xcc8@A?
ziqqnZ@Uccb`2y_jh&%GgQ}M`q^QQ^=vh^uPBK5uDf#sNqV@LLx_QagN*|c<uI^sD<
z)|+;VUV(OkA-SqTApC7gNqF=FCnA1HQLsPy@eL;jd~tTUntL*HUNpRyjBDId3I0H+
z@I15mpcDtnFUFQ(ZMhk5V1OL}F~@;b9&BPam2L!$XGCME6OeiRZX~YK$VE6qU(uo<
z$a%K%Qz>1q9nh47etOYb_tOcehM<=$#3@<fVCc3KUk><R4b|;GPhr3fR!~mpBQSS7
zgzfQ=zJZ<lqF#g28X@V8AbW=Uo}q+itX(IUn-tX+0Y-JI5aUM|D%P4^u7+KJC1tZQ
z3ikucEX8s1Is9H-$nT(}O679DfKZ6oyvV&Bw6#HdSWCUQbshj`(27qkwZ(2U8G*NJ
zY<ZIr(u{~nV81}|rhG^pGMrH@NKO940nbTydDSY{0i!mQUi=;wSo9o~kOu3V`NrVs
zZ?<FOquJnkbE9>|1w_v~|I+Zjz)Fu~sCVSz6>X7ye<W&tGo4Rp<4yV2s8z*n=g2MI
zf2v1r410ZwL$@NX02yxQgDvk!5x(fJ=QZF6Yv#2vRsI`u9*N%R6{vYY+6KL3;o{CW
z^D;+sPjb#Hv^hmeI?+GD2wkZVLXY(>>-(Mi8|aroP2la#*bwsmU+=v8f4W4`bGI9>
zxCceOYbPUoMOCYL`3rp6#{p_#s!3?P;m)yX4|O|Sw(>Vq1nkOD5s%HX<Du*Y2gfm_
zG~yW5{%grP7{2|4!IK(9aj7^!qH~Q9YvmU@@kzX948nQVpkW>Mw9^dBMVk>>K0k4q
zpB(!;`29UK*Pr_Hg8sou4@l`dZLuNuKRNxz+aJ6OuLQ|kpVROD27mnX8Smm_%>0Xp
z|7Lo;!}i7heIwnwMFGD(0OA`7XTpFq4XZG4RhUiTsYH(#yGz}6<a4|oSyg_&HN<DG
zH$8N*P;caNw5Tt$q%XH%A{0GBsPq(3hWTsr7xX*v&*P*Se(a+HQTl#9%g3)3f-^^V
zRmSy=%lr*5&K0M3zrEObbK@&Wtg(SFLMhg5)eyS9_#V)VbC*+sHs&Gx@6ek&&{3xa
zWC;Mb>cIBocz31Hkq2w?$+P^yp`XrTymUKprj>phVmiBeZ@`@!SP-E0{jbGV9Hq?5
zfnSS#_`wFW{5MdIZq8C8J~>$QzcUWNd!aS*k?R9_BY4KjN4oBw_HV?+eGQgeD%u3c
zbizGFa-;?csYMcHhe#PQ6|+O^^bjqRcD8zDJKS{_j|)tkN=n~K?4oFnyFZr{X7z(Z
zDFOw*4%K_}OLGDm#4!7|6GckhL;hfm?s-+c0x~I!ROpX=Oc_G9ReG#>l5(4=lV-vo
z;K<2Q=9zeLcc`DcOel4VSiXsK*~DSonbQNix87ZyZi#pR?z(n|TSu8Uw(?&mzzfSm
z6TbmQQwpcDbp?>8aXL&S|EjXz5J&lPS~vzLK4|F0&y`$~Jni$(umAaY6gVwUh=K<K
za>NA!V)(zFeEze&_MfSN|3GND>aafAC$2xgG#^%uHp${nL?kIj=l3ZZWkDQ+Y(OOO
zP=k|OI1rPN1lmlrBWbWTnIvIY6jp1!(YoT?Y-mecC~as-^|Uwa0_Fwu2eb<2l?qIE
zV08C();~&0ew=Sp6Y!XG-p@XHXWeICbG`c>fA)&U^nMP7fz-xl{O|_ufd~eRH+?j-
z>#^RdF!djYgX?iUrV;7mtRFkr<lh>>f2{U#{ZuMDqyVaKWxskolxp)Ij3M(@7uvtp
zL(N^DYJPd&+49#7y1RVj{QCP=7kKtpBLeelJsuPE&(JHJ&t5$9oe+@qeNv$RW3ghq
z#WFF@Jt*kU&6rUtjoO6KS9svB4`ek-4N}7%n|*YCEtSQhB#f`|0soIiAyR6UCJ=tM
zJ5*5qXJhm@?|bHJ|GF9ap10DM{)b}tpOZ2FqZOcU$RF$dwTpRsmj`Y9zjD0ay@C7{
zOZ^L{tw7%qYoHv2^I~w0;Pb@jn;r1?3}#A|3rAC40EUq%hsgLq)PA-UFf2Ak&oC8i
zrI~TbSUEXn6NF&$R<2BI3H)FR!Q5qBrg+DccP{ArCX>K83>=Sq!e}f8PF-BPzigvY
zv-4re5Mh$D%VEi4ViL29Vad(dc%I#CIW%m?c!Azqt92_un|ZwpjTY8SSvWS=GiE52
zgKmN=A1+obxU#10;>n#I1x>_>QYLFqR9R^@<>wzRF^gGwB2;~x?Aw@gHnA_HM_rm-
z{8`%sGbAoIP&*riBNYak@?6a8IQWq-hyd+y6l0r@;tdNX-gO+~JugoloM>}56O;{)
zFuFIU9CxwiPQyV?*|y|J7i!Xln`H^Qt-g|xds<)bqraM3l0ow9_%~DVa3jnhYd5Y>
z1~iG2Ftb#Tzj36?#a;fPu$46g)w@oxa~e#!IA}S4$u@a)Xcg-vMwNNW=qHWEP$A#@
zm}&|ebEZsDCst(_kS{vL5S55Cu}X={Q)^xninidM^~pKx!<cIoVn>-9-(YzCiOVm;
zi!zlk!$vK(*toUz<bGTp*RN){kN!p;STv1nm#)^@+s<T1r)Qa3x_xVB+seX?WkwAX
zm$pHN`P{&97EZVsh};IW>*?pkq;NxbHhnp9$;p)@lUi@G5>M9KLI|r?U(ASozB(FT
zatLRQlO1CR`VW79ze%tO+BiDpnsp`bOHZQuNYho@J3qX@@X7O}&fppJ58lk&s8Ho;
z=Euavjdt2Me4Wg;wfs@ljqJ%riZ)w<VJ?hhPsi7A|6RR`ey-D2p?w37IaV~`G(>So
z$Ffw3f6y>$eDl<hOR^%};CeQ*UwVPt6jEX;kr8+)d&czlzAi-XBu8o0LQxx)eP0Y>
zC#AG$I>pSAu~c=I^iSC%p0EUrjh-y5CLPBk?ZjXTx>FwI*<~7asqFmQDqP`3wTf>m
zC8mUk_;s1fcqo^a@ua9zW8A7$^K8oVVr4PBPcu76BO@2r2vTLfE}7k6ex_5TjS1AA
zf@b!F2%?39Y|~z8&`J3;ahVPougLLFxQNUKNw&E)cdVey2GK1NOFoLfg~}eKhU3MR
z;pEApHWWU3S38>E#8q}4(WO(Qi3~sSpl#*bH}a_$&uW2wHAHD9gmT*?n=RB7Cp_r6
z4%KRc1Z#}h`!$YP(p3WW)1n(r(^Sfi6KV5$3hyFm1zmVZ<Q7Y1-QnMdnL4(6>}_!(
zO5q5~HHqZ}KIIQmF_H|FwQcN#!6q4sqPY}8Y?gOHJQ|YZXQSz}Hv=ByNj+Z2_$z7-
z<65hWtR$1kMf<;Ty^YJMGUAzfl(L5{F)6@R%(=}*-nFN$Vw|PNBd+HzOa!u-Nvi(N
zOlodLDDjkQlxnZmCQ@=&_)_K`hroalLHL>OV=vcC1HBJ2_Pu-p0=aUnXSXQqx_YPJ
z0@E}yIlJnW*yeVpCav0C-Hy%$>twansyn2}W(pd!(z<ODsJT8SD%ft>{!oK-KWNzU
zR7DR#jnTRi|Js%(oSKKYUvk3WJ6ep6yVog3x}7FU{amu$Yv<|~1fR*&;=1?Rn~@$&
zqbwEqjZVdC0E3)QTw^VLJ8T8O&0^5(#G>02_`}9_nY45|t1K*QQEGY`L34RsWwpwj
zmbJT2Q}XiS6-iMxmo)3OXca__#X6<+`Hj+<Tj~W@^#`)GmU`R3Z;b7xq_xcg^_>ga
zmFCqJjRR?GnwoCS9hPh^lhLYnqJO)1xHAQEx1eyYz_2yTS!q3*3#_Of9p0_Rw?M%y
z+@G{~*-5&11v!g!aq#Y$OUGaZ0ko4cH##CIdTNnUigLY^f5s(v00OM+GYOsKk$5-d
z2SpFtIek|%Ww79)x=RyL*GqO~U{ujR_S@7(ZCWQa?!ObGHioh7GYg(Io=H?|cZKX5
zwr`EPJZfQ@)PXf($^p=5t?9mQH2C&K66nvS7o?^ojA-~fczg1;?vodj#ELv!N$#$i
zIXs6a1MiOKvS|M1v)PRZs|xQ=;+e%KWY`o7a1>qmnYwb^I{Rd>3WP|_0@oH`S3z5Z
z!0ZR|=*@GZO~uAqT%u3ik>0%B@f~g~K5b!uv~NX#V<srV#q)JeRF_{__u8-0Gqzk5
zgq6fcGh3yBok~q~hcdNR*`)xp=5LvKt)?AcvX>(upg|D4k?wW<xlGv9iv0|9&MkN4
z#Yw$&?;+F#N9hx!Eh%XaIy)olO_&bsTf^HWuXHUIxB3v=@`Vyc9`N)6<Ad@-{|9e2
z=bB-{l{DHrYHM|YwJ)EWGt~XAY+v|%@%QC>&qVo%IcguZ`*&_W{N*Fgj)cFE>-B~|
zlrNZ#{FC2CFY-<LQ{Sd9j4#sbx90w=zST%P`#WfQY~by%;s+a@HEm8Hqlv|LH#q_J
z&dwZ&{>}t}k{M`fiW>Ni;oE3yA={ogY>}Me9rCpXD9)}b<;4YY7p^R~5%__U(`$+n
z;;?b!$e&ki^7D@Y>`K@Os#*jgRIsq4iZt8UEMyH7hqV@u;J$)Kb|FH$cO-Ia<}miv
z1993uPIHm!Lc2k!w-mGM*iW(rgopJOuwbBqdpl5JUu}R)IxR4Z`{aat`la!7PHGe=
z@HZy&a1hU)+#vv39x9_SS*R=_b37?p7^MzQC5)<K2aQUqICCg1TANsv@CsTUZq=+Y
zXDBrV54{p<RpH&2f-C_wrOlQnT6IT5*Gmu&5$vNy{q_Fucv$j=Q!M*oThmqbh8$a5
zxZN9Zq(Q@$=8l^IF#AU=`v=9{L)1Sb&HszDcMK9Gh}LY|wr$(CZR50U+qP}nwolu(
zZS!<b-?=mK;@%%K@4bl1sNWTlS(RVq-fOM-qtAul7h?Ab!23qg9t<8E8fGmWLS@8l
zFZffNFuq7Y*Crl^Pk^2!$vsV)4j)myFxF#;3oWcsgEz?A3M$ze{SX!(!9|a4x2xTV
zit$BN%Mg&m8_M7f_<8_=A6eiepW63)`J?W~*%y7`gdMH6Oa2*}rbB1U9~)yPrW-hS
zr~k&`>j?0uDguCW`a*ZdS9Fy5xKDed4!qG^5AOTB+fNJY9rvm{E4-^WRI^l7e9HgV
zCK>bT=kpEV8|{zhKThwtjdy|@QaIbNJUsltusZ{gvs=C|-Wz{OyS798ySVbgIxEb@
zxWdd_x}lu6bfU@S@UA-tPpfvc16%LF@-Gsz=PC8i>LH#<zI|np6JDLoppVr%L`?<u
z*)l(-ACSO1>~?i)Z|pa6MH2eo19j(hM^(lss?-I3ZK+4;<clZxyw=2k2pOjRTdFV_
zG-WYEdl#CVVNvu@blH7FbTrNAgGx%m<S=WY1nS=bn5B@8!d75xBh&!lA54VHRxnob
zJEq|Zyax%Bjec*7gvn_*LhmKQ6y(-I18Fuw1K??V(Jfh7W&QGES=>0z@&-N7s8A32
zSsXCz;JnIb&Iv$lTL+3bv5SS&2asVDeIokjm+nQenls{5DHs|myMhdk&KY|KPa@Iw
zW9frr$BD2j_D!tar^C#LQaW4C(s;M&{oE0QlcOoE6c^J*mmsZ*%|1L+@3B0!>4S3U
z)$6r9uJZd6P+qO%aaE=EElsYnc=MD`oK4?6hRWeie<R2ZgQGVlc)*Bu?8iRipTTfs
z4Cd4@4*Z7E;ohO7`MfN2-oq{<Ag@ZKKmVq9a>&c+r#~*WH^QBsLq^;Gwh17?on}Br
zJLcl5*Y5MM2QbdmVdu#)N9{zL=9;+%^gkjvlNq?72e_sqbj3mbfDT?_6g+c$mO)gN
zK^C84e5FAasYB-T9~2!7<tT;4jbpY;W8FJ&Lgyu?fVg5mx)U$<Vdo`Wx68ZkL0FjT
z9K3ZK-+^L|6yppgZv}%N{c~5a9T{@u?j><MXx|DFKl0_F62DW;7+gK#=%tI>XY|0?
zB?!+;M!!q$4!0YZzmNWc*-ho&<1Ws+?F4e)F*y(&eD$gobssOx4f3v%472BXYQ@VN
z;gEc;_g*WEg!*u;62-UW5r<Dv;&D&$?L+?&8tljs_`$gZ3d-G%m`w`qemdtx!+l2y
ziB{Sf%vE|MNjP<=X*?S;nHNtNG0o#r<#~?cS?0Smzpn-lS1d`6k)m`Pzf3Rd?uRn?
zzD;Jv(#LS0>lYSb(;V6B$rnXbS43G|Q9IWg0$MuLgY;^LK&I8`4JJkdhu}xnZSPxn
zCI7FvF7!-rMi=-u)BWNH>Hkl;&d$!$!h~MRz|}zTe}V@8GuEZ3?kjDIA$-HZFbPqj
zAZaZmvrz(Kv-hSpOJXgs{7v5&UR!d^C(F6VIbfI=OQfdEhzB3{D(06doq7WNP{_F%
z&)|?biax~eYV+#)yuS7!|M}eA{Q=Mz!RO)=)*6b8MJ!>K^v)WF#nrUOh4e1_+Lc#0
zl7;0zdqZqXK5c#2Qmo2j*;;0dVa0vDYYP43GEGoBK!=5AIl}mRyIzaCV}>DH;)aRj
zajU>2lVYQ;mfH$ntcMN`=V3aLOPZ~_zd7N1C=)#D+8<Bp<r@_hTOUix-<p?DFG7J+
zH^O@xLi?WTPUfg)?sbDj+7fcjG*yC^mKUGLJ!s>={AAPCg4ROtg@&3FvtBAY=@f^N
zIzt#KJbU@%zsyFzKqU_yxe7f?yRJAE5bDw>ds|^QF00+bzkEwwRS)AG>k&F)V97ky
zhwqAVhl_~EOcDpNM|YaNuf!5qeKt^zwSH<NF1*tZ1_kA~*k4CsNr6dWlx5(v$3i=L
zQfdv&-dvMSot@MV=gvq!=rn`Au&ThQFcKTEtH7*pxG8`ehoJ_R6GL^1yO}H~V3Sz@
zQDSMMK9n1<JO9?N;+cWXhuIt8!(%D|KMfvw{!Ob6pDRIKTy@*E^Jlk1;E@EvB+H<Y
zbO?9%Qi7j{P^s7u0#&^5IKAJUPA+n2C=-TghJmKo(ERmersxiPh`~$|(o<si-q_C~
zSx5cDLmVW4#A$}c`jqNfsW+qQXd>pHP>p7_8a~rqLHZ9`kR10izotsAU{QmrNS2&4
zBPw_Py+CO4bUmWm0sO#7oP%$d!feK~WzC$oF<R!cVNJ89T_$If41Hq#3h!*hovkm;
zPA^p+9v!tMDL27`d>A<I!=oEM;E)CaRGx$f1A?&tmBTGDa=0DtZqrx^U*FStII%ON
zI-~dx^aVRmDW4_@ebR^|^MVm|nSNd2HN8Zv_zb;6Nbx*0fmOg0Nble(N=c$#qFeCO
z3Z@uV83wJ{OuYG2^mKGzsB5G#I&wx|{;XjmbWs$vv3KH`;RVcM%oHV`PfSJ+^OVxX
zNXq;&9o_Xaw}!vi165+Xn8vO?X4KM^OSJ(cX`_mn6R&e*rx;g+OQd$OZCz3dL66Ai
zq~Zt)UgFAlo7Bom(EES)PAE6WaA5qFeTV+XYW+X0R3keZ8#~+o$-4dz)Go>YmV7C1
z+Aazp@MaY|7~)_}&?W;3vQC3)K_lGti&h3w6D6uydJ0|uZ&+^`M;*pklivwS@BkwT
zK|BM$Q4CiXL<9$`ko+Qc?`JZ$bME8vc4Gmzf{YHJ&>qKr{|nD0maf9+tR983nE<oH
zuED%s&uC*t31-DvqrTYi9T@Jd1MetX8sm$-j6sJnMHWL{#hB|3gJ39u%Z6?t?@tQ+
zoyAyK-oO(sE%3w}@|FhMIdNZm9>m>wrfi&33jFlqNzVL%EbVrKk**=;+mD?M>TRmv
zGGbhd&)szzQV5B|gvv>eVsCCE34`m`cU|H@*$G|33PFd(yZyVMx5%Wj0UKOLg!#1j
zhev@IxDBRSqdeboU>Fmcb%}QCFK+0FpL%P3Wm-+aj6#{VgYRx6b38Ir;OLgRk9hgM
z0_e;*+Eo{feto9kUdZo8H36Lw#Z0xeQ#>~uv$9O}%gSN_>6F3Il-9wN_7{x6zk;e>
z)e^K~@pu+nW8?Pk-Rd=Eb8Xw<y!$7~s=S^Y_=X%=fY^Xc>vL1KMn&Q)!m&YSF}>{E
zcqGv_L=2@tfxs_y&8rv^Fs?Tc*N>f__*s(woPNx>m5<<&sX(*PiP;iin(T?V<kSH$
zjWG-<wLz#?sBaMX!D1@OUTw0ei~@;Hxmx5K2W?EP^lTp`M_$2omtgv3Nnu0uBYu#S
z3d9&G!Nha=h-Emk<G(c+R1d51(2@cG02u%P(EWdyW&im(81aJqt?GLI>3Eg>Wi5h3
zMgS6N_X8L-Hc&$b5`sVkgGd4pQ^=4d8QU`<n~~AfE*EZBt66C`wA?Ic)s(vc$zCdH
zSFc#MxVEgU(7CpGRf+!dnf0;zV@j69Q2g@q<2{!1dE@!=Yxhnw+j)N|5@}ZG+7j(U
zt2>Fzi^$_1v6B0Uk^U0;S`dAW(&HSd%Q<lQ{*IyZy(CI=S4Ho0N+9%|9l>vZBWC{@
z7nKiZcfL2%{Srm@bD5_+P%V4I{`uY(1wFvm`7Dcq8tHT2_q#lh&Am^JDvkU(J7|wG
z4R7mkAEn$G(U8O-3!y8CGL@bt#bu&aH<iZC^G9VhtDQ=qqjUUifOE`_N*%k`P&w%+
zmpbV>0^$6V2FlZ-kXF`CK^EmcB|=AbkCf!0-#{ntqDYI7q^#py>b@+R;z)JNN2@NE
z#_TQw8J9b5)8y=-6-$%Sl;aqyJYym;neCXX+^M@nFzF!%`l`-lf=aJ)o%nbRl%@lr
zH6be3fuY(lOqq59Ft_M*jOmC8UpJo6;>d|^b~1PA7y{jr^5ubs?xItDQ1~aU%4I!&
zl9ldZqJ{1v{?d8<tkAY2m!Ivdaa^<uGh*A37=4;<orvARfek&Y!`y_brQ-;#BPGg4
zCwoY=i*D9s{5tykPe)MHqq9e^@{RMj?!pi+F5P)bPUjP+Nm>*g+K>H&ZK-q|-9NdG
zO;Po6=xincF<^pq>L5DIM4#^S5IM}5lGpL@sMvAL&gchmesnLLC&rGnC?B1xQ=lUH
zgLic9W701#%Gu5-N_w-o-O;Anx#JYMcVF~vsDwmtV}&$zL4^|KH1*Sk?FV2T?|3h|
zlLMu)F9i8dhNd&(&hAh@{!Hq+6uDd%Ty%V=iA&w5_U-{u;D^Jh0&JIeNL}B=KK_vr
z*-oCbWcDVSeQvVvv*bKeGGDQ@wzG#O9*-L3or%6S#^Sci2e{C$qAkZ9x?AV@#Rt0Y
zcI~v+_A^b7aDKkB$=R+m4-a}jZ^5+Jjx$jYen0PdN__i?p{Z-|j`kT+{6u)}<Fxd%
zI1Uq;G+;W<kdB{7o`YoZoQKIR*7C`^_A~UU;JOKMm-lo!d~}h(=)d}N=(X_fM2LDK
z@heM>Y6^nN6kEEukj}I_y4xrhH!mSppvTW|uWuK?zIqH=xA!k^AhZfYJU(Bl(>=?)
zf8>{tAzakGgnN1l^q)JAC^bmEI{44xYWw9(9$TRtm%_Ljl>Q{~pIP19Uf+dm^56pI
z0S#P2T0aN>`?6u>D&+MAIOn_Xea<~gE$8=#l^-Iw1-%r;eJ;>nYNOv+Yw6&}cmnTQ
z4HoXH;@N@r9*`3}Hj%XQ<Pt9Ez4#-qx3;=|`>YBtTbJWjOVFUL@D~{*#wx}zFD91{
zIwm_D-W>D`z2Jt<YU6tSu;L}GQoBYCPlbEd8qPg%d%0$wVXvlzywzF%2lJ&{^|PqA
z(|)a~uY`YN6@SD$uPjYGjLS6(Kd^M8h;jWirW6L%znH>cG}Pyhp578ZRG~cdy({u!
z5F|AHm<c?%lOwke<k>VOcC0v&B^k?_$%nl&R!{_ioa6vOhkBIA5Dkk(c<LpzC!ujS
zO@Ed~tB<PI1{D7{7O06!I`Hv}YP=dvS7o2H!hJnu)yKa8ISMd2_7LX<Jd5~~<6v~Z
z=gxG0#_e7T>2s_;`nh!|%!_B1cVb0BSd+~~iPXf0KYB~Z5ut;8&L36Crhg?j;1lXj
zOfc{TdhU+Y0~0+4_mu>r{sMrJfqM(er23+)>u!O18i)BLd;{1|;=`Q`8}sh&qOU%?
zP#UGhRX^pt)x=UDR4SWmbpgQ)o<D#r6)f-KK8bt|X?!ib296npO3YO^sz?>@?@>a^
z#whBo0hiBpd#W%n4T6Xy=pj4XP@x!UUGS1ja;#0(k7BcCf#jskj8&4-!%(Cz1=^$z
zOu1`oYc&;?R(CM(ip7%?=d*bXD)u$z8v)Xk(evplERWlOQ$s8=O;yw2Vyo+Kd2C@x
zC&?2qk`G+Xmyik1BOig(rVg}wiuA(J4t$S^dAB^Iou@CswJo2=Rwp6ETi0oEq?}*^
z2cvRvXY%%3QBnXNchco89k05)!)A**WXp0{KZ<*?i3U9v0OV=udV`3Ed5S+Th{f}R
z$Ol3-MA52hboZsnyM?LSFk8USxJ|vR6CZRv=LS#Yvglhx8>ey^6O=-ovYv#kV4sJw
zHl&2drKkvz2!Q#OEVk8iMJj&ltCwenu@@>~oB4C{*U_V{7o@`W{=2(fOTZ08fPH}?
zb8`&r?Qu}uNaS(!z+%Kn(&Z05Q=hy3p<ibZ+s?s2FO0!x7)QT(7AHz4HP`0a>mpkA
zS;63Vvm$c&V{*fUKOW0nOggo~kTZa9fW;kPf5Rb>jtt&zkT<)D|6KDR&OXo*Fhf*+
z=fR~txH<Sufl$r^34)@r1(=Zzl_PvKhjvm=(!GIx=i-(86^c*-aUs!0BXC(MRy}`w
zdjsz!lWA<+=da4&zpaORyj-=6*CI6(WRH7l+=@zL&%ZR<thQlmC!la19*__jdB7$o
zvN)<h?C;_bD!e#;prDb;RJ2%X?*i3;%?((B-%467@|^I)dHlm}kFEjtD_~gLMQs@_
z=ahAS(2IyJ;A6CtrHIyW>VD@uve8SXgq@J*VE}yYj13pEbw=8H$u<1s2Xp{h%Ebkc
zZ?nrGU&Fi$NhwRo7>+UT4l5StL^p6LG&vfpS5Ab1{|rF%LKR#l@2JVQ+7b3%JAb2Z
zz<hv}38s>_)DsN*YmM-Cg~?S${v1jafv0q0wNVD)Pm(E>cpc<j#gu^)MJL%3{*{aj
zHYV?hJ1YQFE*H4)UvVY>iO9POaPXDcaokoiylf;f3DT;AJZvR(sj8$5gs|<BN7-lX
zZAJ7e>nQHcz!{0GHmq&MjiY;J7cytpHE7BpfGg-Wcs)6Ed_?DOj91B1IyftXO(l>c
zl}Z@1+fsXoSh1y9&dPt7oZ-K3iioXY_U2@kWm39EWsexz2qLGC^pLGP@+%I@F=n9n
ztDpcbMDF>Deq5sT>#@2Q(e5I0n2&y-#io-68ibzD<t34axXqlYSW@y>u!VZ{G`BOR
zN@<ZW`SSz%K-+&mBg@gp4w<WsalP(PT<aiPce(n%;4XSHeYQevMAgr|RZ~`wqWyoZ
zPk(=v4bwFE`V|orUvwjPC@I+JQaT*0+*ybWftHKcxs1<c);D2?^HFE6ar_71;VuLE
z6qORl^T&&UPqGF-c<`eP=Qv9AS=w*3e-^teU=Ezm9^8Fg{^i_V^z<rOv4K2lhr?jK
z1Os`Y@Tz4G8`k9K@B_G2vhd{<{qm0O{CXl~wEiAQMsq~2SBVbJS%{a#2@g4Br?=JB
zB!}P$5-eL<Qcw}+&5=vJw4+wNz<MO)ew)j)7Wd;HO|ttj%!_b&RsUNMH@DbRa`TzJ
zc*yrSox_2utZJVT!6EkqE(o_PKfdzqqsQ{ErpGpti>b)OCNB<b<rJ=sk@#y|-A~uL
zYA^kX#BvopVW7(nYiFSC8AVse1~2pYQX6FlQKQWxD4Vg15Q_(pwb$jkiJb3pB97jr
zhB?KXl0rD%-W;+rs;;4v>bR5ZE_$MtI@@e}ni?}+Z`K+yiLY74g-)l0-hT@8%-hRA
zF5>I~YrcEg(cd<Xd|hGn?EJp+cDS<^VT*Vz&0~gsatAbL)H@F+yi+v&FTfw^c>aih
z@if)>e%c-#CXb4OJ0DDc@p#AIrQ+HW_BpHv%25EJFQoQh9qeDk&fIYu?0dF1UT>Xb
zE|vK_sOq<zuJ33({TMpzyY4%Zo^#k|gOG1tU)Kaa#FG;WCa5<Cac`Wk^HP-_#MoF`
z4}h@mZ2WE-Kf@9HIjr!v#P=FP=w7s4=I5@vRbw5Q`2xgh!Crw6{}i#b_r5)aj<Vrc
z+Oa&$d*oLIp`Iupg|F#Y-sCEXEbjHeDuSpXQQUV({sAJrzehhk>^t?ll|bu8uOA-R
zz-8!H%$E%gIq89=u$<uoR^Q_BE$ln^ySOf&!5IH|8q9m>R})>I=~y4c-AP^dz*my2
zE0GT0I7}7c5801xxUwjx@H4#bH?k*hY80CAxAeERf@W!lzVOlnyT@!B%sak6LEPkO
zy1gB7tjyFq82z0~=BpHPXy&R15pO+4sCQV$SM65?T^uHs#o!!C-E&|mW~T6@P;<`s
zC#?2{GwtS_^K`^C*2{CiWA6-7U1vOnCY-32;z2~}QwR}NrWu<R=UjGVB3-NmGFT+4
zfQ%C(P6rslfTt$5_os9!_6A3PWej^W53SxRnLyFywdSFkO7h!5m!WyU7v;zN8gAr4
zmall<YKxFCw<tAJb3~@{DjDX6al_(VWCw?8mZ7<_pok5YpWLY-7&@sTdG)^t=8`}u
zIb$tQ+KK)I<HS}HkOi6O44tV!Q`lV~%azck2ylRg#bzaq{V65mP`0eHsri!&t&D={
zAO>?=x`~c*0m6?F(oQuCbJZ=S=@D-_GzJ@ae4{@?t7uI1Q7|?QtspAgijhKdSFCtz
z=QD}s<s=9X&Z+4UiAdCxiVMhkZWRSNwK)dnlg(JVRjkd&8yOI5e^E*xGS~Z0%7^h)
zyaw${Z`4EVjl@$5YUb2RAtXLz0AlCl^wP@s^W9xi^JQOh_T%>qyUgR@F+#nhQy-V$
z<cHCR<55*7m+z3C0TrnwziO#8p((}fEzDgusC28?o0qkM3Toz8gfNq)tX2DW4a_f_
z|0>qVI$B$sU$%$|Z~6n}vtw?E)vV8HHOq1Uc=!o(XORl|V`XXbX|=EgGqhsdrK-xr
zQ?<*hdOMlTX+Por+K%_9av4bgVgP4)!4Nd=mSd)WG=;y~f))~03O2~h&&S^G8rE=w
zr^5&hTr4CfR8ULr#bB>--mQeKPLqr`>{X@^=0(J~)i*88H`npU<aupjZNgl0Yjf<(
zxm$EYPYT#Ua?sFYsle(cx<hIon6^}Nz9E!*7U#HF>Im^rfx-R-e5X5B8(-|kxfYiA
zy^q4&7~h%zJS13j6Pug({5pCuv$1LK53=KgBtwCf6%8v<zFb`sq*|+Oj0NfUy(mG}
zP07JIwk(QN4HL?SkMznG;E$;UHoPCq0;QNCMU;wtn%lw=+7aJvm|!k3wbEKw5Y~m{
zxg3xeA&`+ku<wC&6ofBNkW0lM$)9VXLV)<-ukLN%=r%yH2r&4UHc<>IFP7)<7v4@h
z%dKE#l$Yk{mg*fvqGG|?8$VSM`3=9$p&+yRg>_F@5v2Q(bT8SPd8?NWU7e?P6<h4*
zV=F5kaO-ir*6HWmoM}XYwBr$9pVv~@eh&deZ`J^f6l}~tkE8r8(tTG$x<0)I7C}b$
ziG;f}x=1AbWKIzc+)BNvbrH(4eD-6)_1_k01X(dXLZ=H>eC^^O#RALaWz%s~S6!BE
zAh)5JwX#%+4Hnu-fLStEN@pL=H%crTCRpH$t<oU1zITg#6AKetbM4LR-q*-u=o9JC
zz)ua(5}9D;)*77=JvSz=S=jX7ID#A3NdDyrhB{ca-VXZ0_aRV9A(uF&>+n3uaGaml
zN;O{{tAjgq$aMjMzfp}2#RUnu=7%`7%J9lezdSuxxXq<tif-Ju)j_xiyo>3P1QH{I
zRnhn;;K7bO7T(ND8Z&DMX5-$0c5x=JPMq8i>G*a;os0_?OLzlUKR_G!h8Q3cVPbJx
z=V__&V+pPA;K{esO(a`ntJ{5B^Jbh)!gR0Mi%gZdQxaz6Z)1`yhxYN}9zOC;FG99*
z{cBCg)JRS5ly_IJe03+9mNLT;WTq}r5id|oJvmn0zhkc^P#GELQ42PZ^{wKF=D;+{
z6#Q^`vpSwO^2LrfJ%4-byMS5WG==u`Jy7O$PyCvpE6kmx$EId&&Aeh>{Kb@)&i&DA
z-x&fE2%0Izs6t#Uv|yzmpJ6ts!&;0TXNS!^*U9)qD`BQ(uz8eoMxchD@eX8fF?c*l
zo#xiQTxGSc-qhS(Xf`o=oQa94!M@zMScRm*&(Nx{qLiNF$Ry>kLfL@VriHcCR(?n=
zN_bi#>1JEDv9+?cvbNaiC@9!AE{^z?nE8-^$DpNFv8L^p&0ak5+#+Jnz60WF3QJrj
z=N#$A-=kL+dsIfQn+xd4wYLZ9SkIJdYJHJ~g-nbm1C#yvhWk)hT?(Gg)Xu~Pp{26f
zzKrwaj2kiYtLPB<y)4v=oy{W_3P_J!v*kT0qTP3Z={FlX3T#=iux2dEcNaocn_6vb
zkMz*puA2EQ<-Q>!-t7Yu@^~L?M3nyKz~>v>LSQe*wj%M7Ki*W$ed*EDC}|G{w2O2Q
z^_o}FcaPqJYL~@zF0afh1)Sp{Ww>dKGj=}r2j5<6X|7e<y~tp7A@OM);2)FUFM%7T
z`U)#sl9Sk2w#r8KwKFUNK=LMGMh3$O3aS5rN>aX|mOCjy$odXHe;RBz^}G(%bP|Vg
zPifGO%b^JxENca7qC8TR{5c@eqb`X02L*CSmS|Qgc)o>r0;^reR<l@_9XH)u>n~qX
z2&!j0*Ve{}5#bp~6NEhxT9b0FYmB9wgL*C;3}jjIPyWyO*KS7!Zp)rOqTjk*<jz5(
z;#Tj`R4s26+i@UK5@+fIiTQfql&hTQ{-_nn2_+dhXN;u01&yvQ?&|X3{(-X9H+-;)
zXrOkUTm;B+se$81sEYjop2mb#45Y~rKHaf+C@i%^kL~gC!`g+Grke7T&5RbF=5Xoq
zcLPXlD~ntMbJ{tc2QB_JqwEBC35&Tgkp%6yomOK2IgiF8|B3Z8$QzoI<wQ~*3W3u+
z?(<s^qEl{XnC-DUR|c?orR;=xIiuDvdmvqDTXcA!Pj0;jfyR5o(~sVx&T*#c$4ij<
z&6CTMTUMb8Is}Q~*%SC-^H^-XjQHYh1(9sg5XfX^f7v-Cz({en0L7Zkw7{=EjR%Nh
zB+Ylh6P4D@A=l1)1xp}Olj<|gcLOUo^<+Wn-l)nW!EOR@an%xlMnO3`HodmmgEvkA
z7wGJH`F{JWSmo3%W)ym{aW|Uv;Ct_CpNfxu+fPM4iHciskm?wUc8CUbx|sZIRfObR
zr58fPhSzNQURx^g_EYg2Q!na{`Y!7jkKjH(^A0_k?hC0UUU+FyPmy^_@QM9{+t=v~
z|4H5|z;;1JFXWR#5(BrUAF+srt`UCW2x!~V^)CguEW2{5Yu+JW^y(7d;k|To$b>m|
zM+L7z9n=T<KkPoc%7(!h+1<h)0GgdA49=xtu~+3}-8~K-iP{&y2^%buq8@Mmzc$tO
zqvqbC(GL?w$$r6PIAZDsp9DF92BM(IMl6uHN%zP_hB6$_j8_%Fksd1gf^6W}NI79K
zGvaY!59L8*Nol2u<l&b?V{`&rH3Y6kDtHh+**kx^k}QCFgl~aV*rx$pWP#YBC|RKK
zbBb@~Lxhd@hXQVdCiaIrL$=jvuU0za5}?Cn0GC1Rvo~(|gciZfx#BYh+*7SVBAJsM
zvQp669Qw^_V>X=y1W@vIE=1+=QI*q86+ws#^9B22lo{WgbT}CO(A<Aw#{m6JAUSGK
z=@P8=k4R|Mo6Cqy!W~kxw<3EmE3}~J$gZa<Zp3f%J&tcGqMo829_c1uuR00E%4`lp
zgJ*%2a6DhZ1uEX^Y1zt@*e0Ut&q<Tz(*g<8=DnBF7EqzykfNOwLonzck_lELy%_}o
zJ0wuTh5VmNkyzf@I-DIM-J>P|trODC0lh%ZxbC_lEAmj^B9#TBK5$ufd0E9us3*!y
zK}(OlxSoAh+d9g)Tt_xtX%1F&SKDyoALhDdQ{V@9pu3QDK^r=;ir)dkKLs;o@e8Fs
z7?$&|X*$UQ?wChN7%`chEFxk?sG_zwn`QQs{6%Z&A_GPYKjJx5Wd?Zu9&En-qBC)d
z*ROBH!Oi88yo^SQsGCb-iAI~b&80*Wj0|MeJRDXKGrf{0NNl+G02=&C@?9y)$&s2K
zJry3s!l%grwqx?2WT6&NHGH@*4J*?_6~R&>&kex{rh%VG{WXL7Wzm@xjkM@cn&u`;
zOJuUi^h1WNrPrrZInnr%BzmJFG&|F)qL`8q*fatyT6I{%J*>;tNba~%px4V9810<E
zWC9mb*W(*KWEuEv1+l4Pl{)f+1l}oz1M$ixP9CJNFNJS=Q~et&aNG7Sn*{FI&ib$8
zKe+X&ZiD@|O_(d99Z@f^PyzQd3V{%!M{S`vLqQ<YkSJNmH+-C~dZnbD1j?`4EV_kS
zFKDSSL(N$ca_G@CRtz#s>>t4@Dsh=KeS%Nm=K_aXuV>V@^W^JGJPZpoKqRh0mII^2
zHS7&OKyT%>>?1TX8~4ujLvWy}(J0ku@G?;0_b&|u?ja;FfY-tMBZ>7#=26tL8KJ0C
zOAJIyw%N@{)Y4(f0X<s`J3{^-2j|ePzX@tB+|Y$V{^1fRD@(j&+(a-a=1{ICP-;n0
zFetDzD<DIKG~gD^(Fkc`6R&Q?{0DKugo&MqxgC6gDQ*BHFyz>jE3q<8iG){_*)B%D
zF+(13$!-qCD{MB`rtg(o;^{e4dWw030xQ*QMh#o5@KQE_LOk_bd>G!6+8b;3$*hfj
zi85YFn(^}&#280-3`U8T#PHoKbSe&DAueEQ65xwm-~^T6@j{ZIiI3QrEu3s|Wz4Of
z8m8gxi6943M9sRH(5|+bAWs!DtoyH`B8;86N%RbrD^3YlOvsnXiCI$#CM%qcg_<H-
zY`bbCid(p<4*dj|)N>*#$cAE)ZnCPy%R;SGS5>1J{YrzoL+ggY^R)9Z0c$hAh}FS&
zzZM6OC4?{ZN&&^h!D3~DKChdxHZHb|n}L5OUR6ETESD7aHEnFdrcN7Yuk9qnV$^dP
zMc<lYw#_;7^L@Fj_}LW}`A~r+=g5p<dr+2L>Gb`x7V@gqAw105AinndkcE#1_i{U4
zq0LBbk#j5wa{Y@Tx}6_^G>#{^+7(74p)Q9kBwihIbyiU7A|VE=y^;E0gf2LF6K*to
zzr!YU*);&mqgXaO{lKyZ?!`Me2Sdmm2HB8!dJJ+0R@oJkMy4mDtPTvaFKYD|>=V61
z5{2@CD=mmQoGb!1p)DMap^4NM3ztBa2=j)s1EVYwt;RZN)eUOa@H)bb$r2q~QK~Q?
zqxkf6>FPQ33CxB++6zFV#vV<<u~rq5R@qy-IkGmv0`&-71FD)_k;~a;Xr}NwH=E!|
zxzm+m%1gOa|9GID+)P`AfEheoApa}wgt}P03{DyR#lhBLGte=J!Ub*mZ^s?YXFKjj
zgK)MPr#$}vTeX4L7W{n2FS5}uymeRhmln;NeB6FZxB<A%Uw84x1ip=tPAUuXLs})K
z&r^ou$JTM*?3A~d8!kb(%dXr;-Ei}liN2v=T>uA<(5A4Yl)!-;>PyNR!L<R(jg1N$
zX@D#%G4gI$7HAf?7LsWJEmzPj#At=XuY*nHUm@<Sk<PS^`C-@=XdAc*0>Pi_wE)Ux
z$P8c+1Y#}AAsrQ>Zu4DAR7oRbOvx28>u3chfVO5kgH;T-CTrK#70(4e#x9_XO$}C&
zHRPX*@t#EuUv||39G(|OY@KEU(GYotv<)?{StyPx62dY0&yXE~5|Ef40T4&jp>N9i
zTvR%H9~5mU$e)qqg9hVO>wY3xa06DiS3p!R0OZV*I@F(9UmzHts3Yrd1hl`e-Jm3=
zs7|?#PHhOPzg+%+z9cqH6KSHo>q?YrD~%YSR^OTtE_aLq_KAH0HX3VqAHw&?o!dU*
zuXb+zpb#X1qLEUS<R#MQP7OIO(6@nq8w~MF^nNw2kJo~&-7y%JE>Kfqdk@J8_zhO`
zA{sgwzv$~hXal>*hpIJ~Tf%FTItmvRxVew4iUXRZubku3UKUL}2s91F%;8M^hC?U~
zuV8Y?pV;~R@QKe#Wb5Y7zzQq1n0jXDa&~ABd3pG~p%xJFdbr+Vdgp$1QadQwjaqg|
z+t6`e&`Bh>MQ%HEz(fxN{VVZ;4}jQZ{h$kY^oH}EQ$;(B`;>6Kz=7kE+8{u$yiULd
z7>Bhfwtce&5`wyxuaZD_-aismZvV_uOZ9@2deT9iYs+c_Fp*eDZRh&{hZ>5+@(;m#
zLTO`us|K5zuDySZTyrYl<%evpXSJ5}?HjxT_#8Ul<|{TV0oW5QA;+;HTd5MQ@PRrv
zZxycvqlvgkh(RUz{_gk%;|CNF&n9m`dXoCzTE|}wM0+&%2KR`Qdj#Ela!D=@vil6s
zpNay0HSIHr5mf-Z+<)DKX83T5;)c&MV^BfyLxOy22uSf)ZLo{uT8j2P1u5(hKp5ZM
zolK%_y(9nrK8$oUUqGt-3P&U^XkH`3P$K)ipx4|K@s{-gMv=T-6WOxyJr!skCBINx
z`b~6KBgXfb87r3vvSlOq`N~V+W@Hoi*~=(FoPZ&`t~k3tU@64%FSPKDi^ugX?*L;O
zeYbdVWHH<}ZzSW%<^pwg2&PX!J?eJe<-nx>TR3~1zi@MyIx_Im|06~!p05<;P%eDp
zS<3tdg*`mZs86R;a*Kiw&~Ume{H^#6CC{}Px9o`=U<j`g1>C{Vbp61nb;~+J9@D~Z
zkxJKF3q8*xO^ZSsz3uFv$ux*+Q}XO!#R1LA7TC%*42xoAOwRyS4H17ZkXvSjMLl*b
zQ>e2E$=d*oV&({yJ5&SsVt2&T$|Lz$N15(;n|0li=TqYq;vi2r@Sye>dh1m(*ZdKs
z-kWYld5NDtyX+(o^i>UpartS#H$UNmDW|{FuxD?l$T<&$M|!IB0r57>?vzKYDYB{N
zCd-0o^_uV`vwII6a{(OW9tN73eU)a)aU#kIMNK2wDolk|EDXNqlPD_9HX?22;F%!(
z6<{m9rqv#FJqn>O!2TcF;4^n6lApidk2u6?-kJA3*fpwOY1FXZIn+J7^#lEsZxSB5
z-6Hec1bT7)t+ZsF<Ql|zzTX%Pp>ZpRDAoZCr<`@-p=cEig0@L6hxkd9oTfRq&*>pf
zm+}^DfQ~qH%3>O*0|n}<z;q6T40+WK4r3Hr`5*Eg0rf~>1Yum;49cminzw_&Xsk`4
z0?Rz)yfF9UNT(DHtNsgT(iOPQK;MdCt|+|xbfimb(iPj3Hskag(Ws7}9tMV!T6QCP
zr>|-M^pM`jZGP#qIHwy>xxGNQvwX_iH@ED+1^2R<eNqwM=n}`_Bk1E(Sf}A(!$Ya+
zPx+{AbRhuz5ZE4RxHHocVNPzu*-=g%OcCS!?(vCA@{UlPM=F_AW%ELuIjLiqt=!Bh
zWK@-w{Z)gpm#LBTnr354_Ylf+YEDjHJs7hXr;QEMis6no^k7~#xo7m6J5!!+1HxL-
zczh76&k#Q6cfwC&$|_nC4KJm26<o1V0j@Y`;&`Rv6L~x$Gcm{VYCNHId)`Yj6KF7*
zkQ%UtnxfG47eHFozG({?&4InvIan7ODaS{NDaqvM3JE$A%11<*l<3O8R%_{FCM`lM
z^OEWo`Ggb%h(XAqup>_g6f+o2TPw94hs?^Tf#uG(3GE||s;Ih3U{Y+Ds<6uTw}hUM
zYa;6RBxZ<V|0#7PZ!{0Jz^Y6mTV(zmmEHr!`}UDnUX4gjhIOB4=efPAFp4@z1FeCg
zWASsw7(5j#4#D@p;UOh9{~@a}N^DB?T2kTKB1y-dn9_ndmdEL&8lK1$J69nz+z$VJ
z$a~hwuUK#$9ExSQg~KZ<entU3D@Sx5%%beFas<?|qg8`Ljg?>)?$|kYyfUL~DL*Mq
zGVV~nngup#IJj-XQu(=m;1-^oewu6(j3m9gJR+~_hq-(b%!@HzTw=4sXWC(BP+n(E
z#4tW=V!N^PPGRO%yif0lp?vs7x5H;4!Ya1#J`NxPdeQT4Mo$X`Ze{Jzz2HxAghJGB
zy_(=~kn3%xV^HI0^~I=2>tapEoC<^2&5}3yk4GNO^11Tr<2lY{Pjd$Ag0tgto|+$L
zvg@RcCT;1IZc$3>)Kn%4G)V>{3nTioWS)XNkRvX0jvq0og!ILIzvyme?5U<L0pNQ!
z=&g9DEapCgk!ohjQx0;g*dAHrl!8hwxt31%iECHlV4tKTO39sF_I=~@#Lk(-C2v%P
z3g}9}4?*Sk_^YZ<dJo2!v^4T|oA(1u7jjlS=3Y>@5aAZPs8br%k4BT%)Q&K@j%e9k
z_#~M;sKg_{Ov1Xr@vh97c>Mb59hmfn)0A~)q^TVylP}3-6m!?wMI67nMvKYh@iIbS
z^K`H|N0VM)?>`9iS}GeBqHSe(1^71h=wBRS^t&>lU3=u^I7bS6gez=--w-VCSeX?3
zQc1@xt=skh{<j;iA`|1FU4IM@eB`}%H?CwR;ZWfgsI9|%v5M58ebw$BF?v!h6KrMb
zB|;9sPg26)2z5l9Dxhn!N)2C??cHJ%stUIzkpBf9&g=2L<ioal4DS)7unz#>24DYU
z5%{(05zva2zZ;3J8m6={62GLKzXFU$u03XR9QYaTmd_{|5eU`uiJz&%FS6~(lN5)}
zf>r1#g8WeaQ=7J*yPVUQa9h}R>};pz7T+T8qrAyWBF2lK4IgrH{D%Lpg}BMHz^=`|
zWLNXw@;>(eH-%Rgt|r3P7ACgN!Ujg>CM3-NtItw-Qx2OEftSppl_m?xyd6bql5{R!
zipItr_?eW7N@+u?`FNXg<?mR-;x_D0h|2JB0Q_E2WvncMDn3<6iYpIZ9w#3+v)AY6
z2Ux$?(&#-1G@+CR3}ajxvc_N)Kpij*xP}46v2Mz8E9Op%P3Ca-tf=~5T^A{_yKJkh
z;lUTrmEk;!wFRln?qh+j<nFTQ34VsFCGnXZ9z%-Os|MqAYii;?7*E^`-&0)Kg!5KZ
z9sGNhj(-dq&Ptg52)G!;i>W7?WRwdy&ktHj!{`eEgxYRGgLba*P#tw!yvu%b+T>r!
zNfU8m=D)0V?^KUfJaCN|1Vh?E<!J6Ytb)*I0Bppad?{31O;q8LZB#4U#5b!`k;rVz
zdju{V3@7y{cM;plKmYpuDA9#XHETL#dHKCXHaDCR$XCd;c8r4M`|u-6et<B53P{=c
zKQv0mX%yLk>!n6e6Tn=fcMy<kM~|-OcEqvlW(Tm)F}NSonKaWNF?fivJ@|)7O7~9=
zIV*)jb+xuNJMN*ckV2?YF!3aW<af!>X8Xb?gbRU8c^uK4n$gZ*Jpw56MkG4@z5)L0
zM7YH>;}rb$UfUA<Uz`vByUz2!PK5uQ2Gg1zIx4HE-*hnD2JUnOh3z7R!!QKVQ07o7
zLBL?iqM)oKvQtJUkh3t4XH(cCrRP|irJsgr#TK2VWEPq2BE#__O?KOD#o8|{vada|
z8%w^g(?pX5z|V1SpANS^uenY)>$jYThd(`+e*maQE@-MpY8>A}acq-@*pKbIaBkv<
z1kvI4>jR1DjQ8b0#dXL2`Xi6(U<^B;6W%xyf(t|4sM*IsceJmDAai7deA@Tv@DhZ9
zAK%3XhUrrD_h5#9U;b{kc`{>0@7e>&bu>sE`a<j`_qo^K=z7y)ZV$oN-w1t^WAG2j
z9o>}%l<C^<l|lKP4o=tKKz%6<@>08b4hKcu)oOE-7-lE;K|MYSb$W{T)ag|AO*$T}
zK<nD=0ey@1+Ms;P_Fm<_20|>q6bJHj-k84&_v+}D_US<VoCcx@13>>wuNGP90`|<W
z)wG?ZuGnS}Zeue%<&);Kfd+YwVb2X3@K*oAGdqyzJgtjtmtLU+^eudbK00frak;Uw
zT3N5|Ry?q=U0HOxD=ef>V`EEGLvgQRcUo6ITmk1v7^bbjhEma*TP*^@bLmjY<Clpk
zr89w|GJQ<z$~IZLfIGt`|1h83j}yniDhQvs7IBwrCLk2VWn*@>uEV%^HS>9i|2a6n
zw@5`}=sN5#GN!_!HkvNB$d+tiwW1L8blMbMDwE~FS<~#8T(ov|yClS;Or5XFLd4Qn
zQ%S;wb<w`qY;C(Sw|%rtmgs8U&LqzV?c%l3?Q+f&EuPBXv15G)l`1MjoP>z)$frkw
zx|fSH&FBf8RW_5C6_k$KVVy>wYtb*RQ-uBiRykQXTDwmEiw}AB{ft=QOoUbjqM=P>
z;-bY%sQV~=a{_bNGqhvF=A-2=FqxRQ1h*O6L~CK{cBv*FXx-VB9(#P3={vztv<`7m
zldwa_yF@6fUzJhZYC$OMJIaQu7KezY!Kk_U@ZkMt#}e#X{^#5%U~-$d+`@P9DhjD2
z)>VwsK~b3pPlH~Ulty<XY09B|A{PVFqB6M_$)5G;^NDX#e`#LcGA7@krT|dc#06XR
z*f#OkNws5jvjQ|NwziOgS&SZy?xigj2<OyNz6|mZs_80Cf|0C7xE76(&f*%5lFrP=
zKsx-7rQqr%H~g6W73A>9ar7;YWl3V__BsmtCszg2FQ_!m;yU%Dt5Ni_>DVAt{SF@V
zr+B#6A9LjrD1gG=-D!BPrvDGOi1{FBFSF^_O4DS8K&E1HeRB?Vrn%|~(K&(~Z~m(k
z9%y8u8M2+Bq+|r4dB^(DRkpo#E^Mj50jz}#=#SDJm7bsJcY4~Q))d21JpKLHN*?UW
zd*M^`vEYD}_m*bp8tZIdQAZ2ykqL~Z%A4=&dVA-awO4Ar*awi&&KB|{;USM4?7vQW
zqV416-FkDwz$I@!UK~2DUhfWp3@@B3hd*;14^R<X3>Lb}DCAz#iyvuur8<O^b{SB|
z5fkNauqh9rJZ=t+mLzb>qy}7NG`qv7qF;r}4}}wyI>S)?nwQYSJM8LRn2_&J&!IA}
z9!36>r1Df;^@^h8bczk2*Hl{brH0h46>G6ks@=c3rMI|9_<fgvY(|st$e#l!N3N7K
zospEi$yOFR<qi?b*LAbw)|iRsZ$9GYHl39~7zNZajX2~gbvSkCDV%H8YGX2N18PZW
z2+`sSB3%xYgn~$!g7QJiMir0{Y1DP09H4C|Q5oeCXGUQ}X4M2@$1;H;CB!C`1ai|V
zBE2caVI5VJaF3~!%5-`(3c~`b8N{e`4pl{p8PyR(i{hqCBb5dbDo?e<Q?dLBYGxOM
z;<~vlO^Q0IXe@dia}eknJYT7a5N_7ayuR-G3T}x`Us05b1D*yI)YC&tRBrnas;xqe
z5npdDRMJ8f)X8E7lR_O-Jde-fXEjor&TKhqHHhpyLoAgMDMdu|Wd>eZn;{Wh&VnE-
zpHOisJB&o_#EaKp59P7?7tiMK<wL?vF$GgJVh$K*2Vn~1P$-{=4#vRk5XnCjl#5D$
zvm_}6;Zmw95vtw@N;7B53Y@4tH$Q%a7Bwi+N-Ld4)MghB2Os3IoP|h6&nZ&G3`9ss
zakRU8#WvbcoRSZXoG}`^vueR6VoB9pkK028n>7eM`K6Mjj}_fOG>%a-Z#Okj7=V3C
zh1BJ@lHTpx$UJF`5|Q-`6@}dC<!uk=2B>LoEk=qDZS-(bTFlohb*tCKjIGQ{<*8z?
zp^$S*C(cdW$KNz2nV7ncl=e3wP{dc9W@G%O;VyoBvhn30g*Q#(Ea$w`>ke`X9K++y
zO|mTB51oyYgm*9YSLR&?&(-W7E`B|Da~Kh69ZAon*krBJktM&V`HP2$GIk~`B>X0E
z5P55Dw$aR8d^>M!*+(fz&eq!$#`?SH)&k6y`W%GRSoNFOn;s^&$?}rvli2>d%m4sl
z?v0>h(#<r+JPFo!;`lJuAgMSs+vQK%F2x>^e#B<}?9|$j3rbpH6K4mhd|s_^a#G0$
z@r4-yDzXhDo07AOnfP@tuAb-8w;+kdBkhdh8jbE9UDC_#=_I?xnKgV#N#+>)-vhRP
z?a>4=W^dQ7w!uTg3yr}u^?n=(XL;T;ywv~p*}A;2hBi26DnNl0qsV-WFr@y_5|v~y
z6UB$VhC7LMEqYFigED<Ih2y=}KZZ6L{~-NIDwY-^Tp<GYM+RN<kJ10N)Uq@asJo(m
z?HK#n{pDG=w9lc=g7-2V8t}-y;<UziA%=XD?wDmGx%c5TwKv`#!;Rst;)I@AgcHW}
ze<W!H+v}VLyFN&_z-Jp8Rg3`|gwJt8b1lqLNR$9wxNfQ@G<HkH3G%c@36LFvFfITG
zJJtPivM&quyD~BSVzH-}{iCdu$!%l$15k=T6fF$tNcUMERNT5w@>tZ*n0q9Jgw8g;
zLm`<uAV<NoDLiAE3PV_y^r&c@JjD;i7_2jXU!9sLcr?B1hS3Bb-)9Zr1jg`6fg?;2
zKl-Tk$l%vv^xf+{`i)&MwcEC#cz`iH*!Vs}-7a2z$RR$USPW~BAVN_+gEQO#ngOig
zJ(jA>)E9Xb(CUz%sn(9-(L5!@q!U13>417+&zgA$xACO~)tuMGuFu}958WA>SquRw
z_`0@YmP*z`AX8b8nt3&(Z4t?}gCdmv3Q}PMjd*Yqd(IEl7k2k=YdnZ!<dO;H3KeRn
zbdM@b_TTjpiDlfWg#3-Jh9f!7XhX2CrYDXl(5OSMz+~g0zNQcELpz7w9?4dX2`~kp
z{Y46J`n)&Bc}EF|UTUmx>vfv)N@6-2+9FN=s`)~eLUdgb47j^5HKDB-scpg!sG0Pi
z2$)>%@-(-^H1Chct~=X@+d-vn@LSStDdR(|t0ud4hSGxeZpHFf2h!sl(9z2=^*dis
ze0NmPOB9`~=^}Wt;T{4sxZ3h|6QClWTi42`Sc99ZNL`Ax<Iw}b>U|pC+N$JQ1wIJ*
zD09+*=o!n=f25PK1|C-H1ZpT8cpUy$7ceuRnB?WHDXT`JK+&(tWvCW=g2x!eG7-rh
zg;xZq%u(Y;kapTYZM^EtgkvK1j6;8B&e>j<(`OvQw{~S+atKx=OEW*u5MGN=;PpxI
zNT!6#M~BRZiDkIrnC5x@irfd&+C*G~=|X~EMT%;nEl!8sBT8jYgFGp2O8k5AiB&ch
z?@SGhqkL-*l&5$jIWx=igq@(I!G4{RgOyvTAWYFxGIhe9WRYJ;A;q6o;x7>{zo4Py
z4OJa&;L_#V9Y71c$<ms<5q@^DPt6f|hOD(Jyu|9Ljj6Sghbib}ew{WMtv?C28TFnj
zcrNOsDo_n5Yky=pIl#O)(?nrJiM;30eF9b47kzj}0=_;DwnZBZn%!$EW=MncfaNpu
zl6Df(n{G`lv`q&dbp>7RiN%Rc=H%ukbYu;w%{d=_e)FCpMPIvO48svS5!{@YJ6(nn
z+UbWu40#&PW*6p~KSR-BoHAp!FFJ}G(;H4pB;ZyO{$}cBN*#SN=J8E&;CsnzUaIYg
z7&oA4#P}ycDp)E8Pa@<+yI_NdK0UZ0sN)WDE?j;o!yoD*9?uCvuNU$`tN=&4mS;;`
zT^hE^r0D6fKK+u?rr&eD3w3Bii(gHnGu)Bjgj)E6HgXcUmW`d&^K$m}-{?Q+j4xSD
z|IvH)+a>z{C!DhWXDX>t^^;!|!0@%jUP`$jBftU`&9SAHc&8*no{vZfHw+}apDn`C
zmRu#a5x<k~3&Iyc1}uue@0Zs<aAWLMFQpqnz+NqOyZ+>R-Fn>VdEHsX&+7$9A2vkO
zOjb3zm}4w7P#Lw@T2LHLkA<Ph@jk>NW0A2;H)L?_(5~;$MVBA3f?b5^k<Zpubiv&Z
zSx(K-pUfrys+<fG0D*~9E7ogzi+#{`8Ps;k3foFyolK1heX7Qg+~+vw5q8sX3moJa
z5>et~Z9j0AYwxdDm*VL}ewe(3$*9~yf$2aUMV`%yf!*&r!lu*oR4<<1cDdoc=rfrr
zx5w;fNYUtr5zQu)N;6<+q>uvjBopdIlj;jGbyuV!H|38=AX`a$v2H--T7YJmVt86a
z+4N4+rhBzqx%k^!KjZ=1hS_K(H+^WZSZ2SAGm4{`S#X$$G;908C#$bYNyF+<($tBb
z{J^^YWOKi!c)5#@%~!fKcSGyZN)0?(g($3RYnje!5AFmuQ@H9M&>g_HWpY-|1N>Ny
z(H;gm;=9{V3NtS#k&O=X{>H=%lhZx}1OLPSgGsh2`Bs|DEv^Imi((2$Tx?KT>st&f
zxQ$z5t4dLT7nYX|uJT<*=PB-Mi;(WulXotgmF+B!3{J#?P2NEhrgY`mM2l^;ocst;
z8K1P#1`#xH&6YZHexOqSW6B`?!?x+@fji{Pex{P+89#BVx&yqlNSNP6Dr<-TG42)H
zdlDZ>!|7y<KZUa`KEWgM!JDCkk>8r--_M?1wi4d!)b1apFcOE9qY!DDU`uk0{T4k%
z{RpfCepVRkBl1ev?8ex7Yhw*e+dBC~6-)gNKFqy!&@xu2pnC!+H)63N>M~+ptK>yH
zs3%T%VYg>`L|rIC=s#!CsSw2h>@tbRJHZ`(CI4Tu`H}}Ui0!YBu?^|}(k=bJvbm_E
zqn+dbBXCJkTld3ON99AN?`%c&GPO37=W1yhYeXg|v{*E?K=Ht-nn#m#r7=_dyP%P)
zlBrmdfSXpLkgDVgm0WX`+%hL(kvX@3v?4SK{3*AO=zfU5H_EAQr0FUm`DNe7yvuvK
zb(`yTlcM)N`$!Mi|L4sEn`H=mV?XGQ5FJJLZr_yyGH&q>G4q`Q7Qbj85{qw!;O`#t
zwYhI%@BiTJD}yTQwj?PEx5C}s-Q67uxVXE!JB3}`-QC@t!rk57t#B=1=y}}}@pVk}
zOuS#`od0L-l{<5-Oo2hd-ko`4{!#tRUbB(Ew1LnNIV5*?aPmygplN!>jH5d;#=dDn
z@x1_J-{4-<z?%3MHi!}|@2m+sM$Z173}gPu9oj&<xEC9UV@zI=BQgjoh?LPvM$YLS
zn6zo;8BA@mJ1&TMxav5METQyXw-N7bAz&}8v2Tk1)Q%Xlo*`rZj+gP4eyqv053^s7
zesb@R(Z5LF1AAje|AxWpqU$$dM~E4g#Tk_ea>gR+Gn%6{^lJ*qOrP~P4B;YJOfEU9
zx^mha-X(KYqDQDQ)hW#UfSCbAsZzX`bH~HHkQa1glAo5(Ik5R_6zq>UtECCL_hG<A
z79w{W38{cMj5081??j*D@$Jv*_xzD5r5eMO1S2;1=2_viE6G^|%nv&-OvldI$$;8H
z2AqY0;Gko`lPcYak{<C?7Y}*w#^qvH$cYcffPcTK6MS}mm(IX7_+Vl?ka;2Ly;0yq
zgBcL%4)Uu+KbKwJQ=(Wn7#kI3E?*L})zA$oQuvFnwhwAu$*nKyomOmVJDL_HTUw^5
zM=06hOpF`{g)hjNhAjp3$@?XMCKt5d1f?6OKfocZm7=;3+<H}nJv3Y}D@iNVmUZ{=
z@@~l+?E*z%7^gq!!HWwe7HBC6?{w@EVS!>vdjWe}9jbc1S`3(fu8O4pg^1WQ`CG)Z
ztk5JbJ`kgk%Z9TgZFRR*hjoJXF}V^ArakS(>M&mS4z(EUgi)FaudDGCm$|wsq6mlE
zN2_a{yX0`pQ|gyaw*PvBb+v6Fjd`kPYi7<;1hfR~PpmYg9scP_E$r4Rv4h;CB}WuZ
zmz*ik$>L-Qb3Wr#ppWP;e~57~Q26BR9(Av!p3UaLsLHa{L*gTi{TG7nEv*S2u_-GY
zlU<g;mUN(3ja6#M&$fp4D*7gc1T&C~QmeSiuXs(fTt$jJo@RKS#3?Ql5zqwu>N}N5
z$B!AC%xNUqb^MmG!LJFxnNjDZBUeRL4qnOMLSh_$QGJ2O&f{sDj6Z5xccZS$ab#;Z
z6moY#d3S)g2jC~i*)TQ(Gmb+dts-QBZN*LT)rqx;Koh0sj19!^ov2UQwC981MWrcY
zTw1dX#V&jWW{I7yvm+^Y;iKznb*6~{s*Ow~CdsIDDGf&tkvPbSyU}OiWSh+vO#QTp
zHn?V$hPn+emiq_I!7Zgq)F&23Lp@~7$+}9i5$J5v%{b&EG8)+v)ax83JYv32q8Nv{
z>G{<r=!u|LLL4?GTeW6MwCJ<ibCtZg43vv+7eFa#M$G1ktR{~{BPWlD(Ya&`D~PKk
z%VQvEFfR6;m1__U_Mv0zt7g%|1mbBmH)VsSR2`j(rrLG#QK>q>dlh0BP+vvdOaV+y
z%al(b(_)!-Unrp(;8LVZAUZChGkEN@wL*=mHgkXc6_&xuOevr?wf|A2w76VaBL>|;
z8}nt#MD$iLZkf0wyM{WZOG^P<Yw*-@Zz4XXbRQ0Xu(qBVvML(svYYj>==LO+(b)yw
z9dMy`y&SkV!HQW;<w6Vs6<`ieGZoWa0*B5~`>4*+u;>-jX0P`QGLlY{X`Ex=F6u2D
zH%}XE`1ESafEK*=S`x71WofX|rr)*|NOYF}*h&Isjvyp3*y^RH=9sy44<^pJZUDj*
zT~njfCt_Rk-eyIPdHQHJ)V*+AQi@%v9M3)~%<ZFA2}NNx1tu(V2C3UaC^Q%m?(%Km
zMb_9a!t&Gm7+llwceZGD&i)LBMQv8%X*q*^3S{&5xVeI7R^H$62NHT<uuzxV{+^=b
zl4bQ<)!#x#$?DC_vv<3^o$ERJ$<rhuu)q3iWj_$U_pv^MW2SPpLw<ha3;S%g<8II1
zq5>HR3fxDK=X4+Im4Zw_kmqt=>t#X6cDc?Bq=KC0Ddpn4)L-k33~Uc%K`_P3beSOx
zQn{ye8gNS^;a|pu4cdcv1@HOeY95HZLMVv!`xWuDrVF&ssrC$lRi}^P+mXHXq0{+{
zA3i<z#~Twt9p2{5MHd1cNAA~JNg==fHwm{zcznl!9R`r-#J(VM^E@RlNDiGqRl7SC
zdykB2&^z017@Mt!=S|<XWT)?@;GF&iKN_NbK?$7%BU%SB>Phrkr^0ScL<piM<&7y4
zrSH=5F86EqYvIAi<U$@^df~xuZJ`^dBwByNh(>Xdmd}fqQjQPexw)2#!dNcIr!POP
zC_8mph!umJ-#hWdS$+sDIETJ3QsMnnOKE9AJ0)}R>9LnxE*sC~##@}sZKu8HaU}|V
zbHC(c3(ig#{wbF?tSE`j_Oqhk;nKbM&o4LbD#l1jvyD9;^tEi=Suj-{lt#`7=xciS
zMj`vRF@$tGOzmH898jh-YQC)owX2LPP0Y`;5WR5tfltbTYF!f@5UPWEzm5twW=YxJ
zMO^g)7u9kTSac?p<^@dRSdh&Q(92Hs968K9Ip^1@+kA;?b|*BaDxIXN^~TP*8vI#s
z(hgpeI>T5pxEjO;YW2q5?4@@XvWSP?#jp021xlL3F`u<Oa7vn;EJIev+k7d!IN5rr
zYF6mmd>MW?T80961`$RdAU!ZjfLu*l&N9^kV_uw1DF8b}wXgTlH_oOUfLmBr{Q30l
zW+rz}nb!dQ=mW-!t~}ns0+C{(wqMc@r!%OMD-^QPhji~m0KYsQipl5$$Le$$l6;wA
z%fV|0?^xM>CN_#!Vf4A<FTj)2S<nj2gVzCJiEt)NgjM0kH?F?2($+^Y(hTYute@;^
zg5eZe)H5hQn^pB~cu&iFfbQ`s`cAx5#6^UJ%Q3$WT!Wfn;0SkUxPoRB{SCm}z#oY#
zt9yKdreJUdPs)3Q!0JFH5DQ_R5f5M@37yq;IE8<LUrC%)2|^jjf#=`Q5NcO<b<95p
zf$C~w<<wR^Uu*<pxWh3#qu%eMZHD7@!{disUZd)sox6+a1%Gpg&&l@d&z*r2>C;@H
zayLk^#{>pbUZBs_N~8w*^cmT=T$AD=X7~QB$fSAKbtf2p`o#Drbi37|5kCCV*J}Sw
zeeM6aXpDckXrS`V7dlu)z7o<UK9LA2!6bn4luN6O^(#qZRJG^GLU>VoMGozIV^~WM
z27JkDh|9K!WRn4!w_W=MPSZXU57T<vejx5)@C5j_uj>7D1T7B3!#W#xvpqgPe(>@d
zn_F8HY_f|~ZE_iwKGo+Ls-IXD@S~p!u8J^8LTOx?DUnL_o!xrDE$LK#aU)=POk<D8
zamV4YYVQ-`+TQ5Qs=P}i%u1Yb#z-j|>83zG!rByb6YUz(Cid-ENsVy&22${{nns>?
zBPL{CB=WsH2Wq8c^GUz!_ujhr=$)7Ecv!nIGI==1P$6|HhU!Vb*~IKJgx>=zYn8g@
zO#qW&bGnI4tnn@4<Qmm-jV0Qd@O->5j3F-|bi9w(q&<K}K4;L%eT`pav@F)To-hj!
z3u9Q%WKE?sL`7qFsx9j#?jL66!Sm3;m>TLb+VtAVmZNUePi`YwpXBrA#D}gEjI49z
ziRO#U!EiDd#gjWxW8<5j1GQ@iC7TTGjoJ8PCE^TnsY~M}C=@?CfU6I7`g*5~fi%WA
zXsr>ytnI~nRA}RCQc@TZeEAR_e=<1*tWllmk)v+q0IsJ|(cPqW*MjdUzH%J0v%59w
zRBJU~&RZ4ptc)?rN$;Oje5T$Z{`u$BNuBe!f`Ndf!hnEC{u|1y<Ua*E8558HybY^r
zso|)ge#j#;k1`6%$y~x0h1)Ra;aOEI&Kb&J>#r#!f=G8E7)S!iSsa*8sr`mHeD;Jo
zq!l#A4-<ZT5dRtPqA-H8P!B4i8Ra*d;(A-(?#|?UIs8N53w8~Gi^Z@fj*HStwU17|
zAA3_Bx!yV-LuLGYLmxpKVFBI19K}tunP9Is1Y%n|QkQCUBiPp&3C2KijUVx(K`S`|
z3#TkQJ>nH@MNfCa<}Yg7?`~~w(ob*cG2L{r7bMuK+Xz;DfZI}vrBa~4+!SAT#Hmtc
zihfpoXk#hEHlO8?<*CxLjMrl5o@|t0T4~J3&Jx{4Z=V;z{l^k~ZOJsysd7I_dtQBh
z87zn%vCCpLnS&~q+)HEzFb*0Q*<cC-cSyVLtx!{$ewAOR$-XL7qMw)ozr1&>&$O3B
z>$){esa1SwvNGc11Q49HS$AeJDNtoOo!ImtUGXf_cNbr!LXMIitZPDutvePPmEw9U
z)K}$_W`mAEP9B+QKUX%@x+%ZExcclb{cY~)wUjWbT=Np1uD1}y9Bj(Ds>*v;fn(a6
zA<0)r%l&pvy>i=c>#iK=F-^&v&QdPKZb(+3YI($vDXR!Q;!$#iK4B5z_S3oc_e2kj
zcpdHTcW@ea%3Tt0f_)V55_`?Q5*YseW8{+=Y8aTQoyq_wOvP(t-DE)%_J{57BVbcB
zj6!uC3lPg-rEGY5Ra%E^^NaPqJ;muiVZtfvYEi9s;(ocNzFH$@v;Sg_2nWSk29I_D
zYVNfDHs(s_-=^l3X0G91?HCZ>q_H??HnHMLwvnJh8h_*CsU;m!p8+oj551IwJgSdy
zyN$Sm)v#n;aBs{Ws|XfbWL}B@O(I!jvVb!7>=5)KSK9R49{kQ|NmijWe@p5VEu?{n
zc>sHmv!mkZ@pp%3VZoM1E;+s{yGTF2tO(0z%^`!o#@T7{DgLR-aMOnUz}6eVYIhBZ
z0n#LE<>fv8jD8hg*)NU<s92TGuG3jWk5?e`V-)XHIL^O9N=Kkwb)wuPP*wa;K8j|&
zDi054-GLAKS+gFJeY#>a`|c0%RN(ftV9?ga!lHTdj`&f`!ua2~HLNHfC<g}O7Z^Sp
zVp)Qn{Pyp8#W}<ag6=p-4?Oopza?0MY$Po`ahM)9*!Q;QW)XGCJRlU~f5-Q3GX`ys
zju3#oQqb=(M9xl`qoCIiK|iw;6aB?PfhH2Wql}`S3pK(`0hLY&!pc|N3hvC$-W2-e
zpsP?6&t=f!T;)Y;9cCFqd$R|p7a<vK<*k3`f50-#ibWz&vcQLugzb!`@xM(G%5-LX
zXL}{qI?Z7!WzQ`<eL{Qf`}!c9zBJS~31QDBVwV360W_zcRkoDhXN}^puk^=ghN8Vd
zk&OL~=pZRPL^T_Ol-DSxU?-+fBH*VMHU%|!hFukWUHp@s7QWudZr8Kt0pF&MprAt%
zF>Am4=V8#<{Ej~*9EZJQ1qnpI4HG8(1n|0<VLPvpX%R8l0~kN?DPXtTzh3g+O{I*9
z!<0q8h&|!2^X=au_E`UO>O@)VCyEg2M=>30vX~{Hho?f-CZb+DoB<OBKo+lz0tkp}
zId$I9!8IMxW&HSo!tmKQ0Q>wO5yDv0w4{jHl^GYSPA^A1W>cA~+kU<uptX^2`<TNj
zkO<XWt&wd^?kKI%I7_Wu{@k`2m#$cDW9E#J#RiEB7+A^e<Otr~!(x>0jB6A`?qf;N
z-UhC2QI9$C4F$wy^U>f{vwM(n(Q_eimqRlZ8Cq~f(O8neGTXw#JL?vPeYq{QgEH5s
z9m|N}xTcsaGA-)wm>cj_CL4;pQluWLKsjAIz|A1%JSk2yVu@M3`pCn`QCXG{!^O3a
zybAxUa2n}cFH0KGR6%@xkW`bNd`Ht}X^{7d`71x`Al+WK`FPclH!i`Wuihi>(bFKA
zpWUtr1N*Kx(u*E_r$c=}32U5Qb;h+WT!T9?k7G!o?(jAIyk{HEXcQ9eBbIgHd`Nr?
zgFZ+$-qS0Nyl~0<C`x|e{4si)O^DFw%;>N(#=w~HO{0f#^CTN}UdHHbbj@N-Mds~H
z!1OqjU4}#qk*=PzICZ;Vg%IFan_Z+~4cYj?z?p8;+Y~!y>($XV$!PRLlV9nK(&Cml
z!nk~^x1i#1hR!G{oX>d<=3ageck%$$!lu4z*kaP}yVbkku1s`UEG`+`HU6<wd)rlR
zxWzaSYXYCe8fk5)^E+xqkw_%!%qxuRuh~7KG4RgDCAY||YgI+!7ylLhJy3oFgq)v;
z*U?U>RHka$17xqsCqL}Ln>r!Hy~c8W|Fh}#iY@kTgM)xPz=D7%{Tog9e-A|&7+RbB
zNB5O8aW()r+d2N{z|?=WUmF058mccn^eQ5{hr~HfZ@zFTtysBgBi#_lEQlp&chg>d
z8!2pt&W1I}Z1YmuN1$)n`#0a42o@D<o_XIt45#-J&Yn~8z-uKLGcd<LlWkAD#~a6;
z+P<IX$9mu3_AJ0cm<IcsprUu$18|VQ;;KocfFTz6ro^pbT20q}ADz?r>)sa#KivAC
zGrx5!*vA}e;9uQEPgQUYv7s81#HRirQH$Z7fI_b=?NL%dETuy$(n39vp*tCGSG|>$
zVZmLeY^!eMlY7bxurMe2NNnUwOSq~POwiV0)=9&2$r9G)xK$F|K!VB`Y&}FZQ6=2V
zaZhD}?Q|2%WpOyyydAn+m31U$%4kiJk}XaEBs7eUu7(*?C&|v26$*-M)J0_5da<;t
z#DD9q6Fdp9$k?I)t;<f_KVtO>le6^TJLi<q+|o|Ixb0+@r<uzkkbj(l0^65Qw&p07
z)sjz!ahjVvaYC2UREo~iVrjR!eX3_XIh4!at@Xn}XIcrmzi&KlWwuQl0RBpEv^gE3
z>rzj2_H>NkxsceJ;oEd{JW$BnS;3)y8RNHqTHgs<CfpX;8Q7|(%5@*80T53UhpC9r
zdyvnT^c3T5x+~-(LW6mx!Ve}TFGSpTHBojAL|@NR!RU|B%F{_HVUTibUIwSQO?vzs
zSDuJ{05+E3M4-IJPZJdp7A5rFlz`n7Ug^53UL5>w)VXCL{u?8i>qD|iyE$c%@hh>!
z*>bDVWn7ztGvwpMu-#z9u+Ga~UvS5By2B(htxN-NrO^>sB|0ZR%63pX8aCSuUz?+&
z=74^zti6|qAp_dwRgJIep1ViMts**Gw1?S_8rur>bMWm%Rk5!=9E}zhH^=#6pj_h~
z>XLcWDVms5&N`a=s&#>mfnZw3NO6!FU+JowPMezF)NJ~$cIeqbH);o$Y=FL3;aYOg
z$eYTZdbd3q=dd;1m3}N!0#?*0&VrN)Wu8Fp$oe(?Qtdh^yyix<mxEdy>pcrXR{ung
zx?nH9xnga{ul!V|c*qhBrWr9|v}0;ayyRrl2<6sGA!a)~o!x)#2UY5VTgEt7AG~8<
zBdsmJa^M0bj@-JviT|Vc#YO79H&@fpP~`@>np1r|TH)3vKt<JJy2u{>Nww(#^$<zL
zhH$uj?GtX?Gz`umtnuOgl@_(?B@dkL@L=pupDUJPZGK1dcDoyA%3ARDu8p_cB%Nfx
z2u7Ew#L2fxG58dODtd>98SQ>>Q771Cgh@yTTna+_x$Sd*>2uuy^G%6(iXg$Sbx0$h
zbEpAdp=(!tyrvq&aBy9rT_Rks!1n%0e}UWWGaKh~H3hv_b%N&;BEd}2s?dB5=R6VI
zej=oPs@V`gBf+L%$@Y(T$c~(?m-&NlHNcS?Y;VzXLaC{l^mM4Im6`_DyR!C`7^p7s
z{z<t6q;#TJB=mGU;Z06;cEx^|E}oHYJi<UQM^6mIUY|TTW>E?c22@yNqIIOHnaOEY
zq9AIhVMcB7nK9dic${4fv|os@gD=#FYxRzZ7}R4P+;YGfOe+iTsN#%iBx!J6Fui9O
z7>`+5I2LWlG7-|;PzTWg%CkXCY|*)pKZK#4ui66?-MU7rGbQ}ulW5>MH)ImjDc$EG
zV4R3r65}{If)5=8lmxm3Nuq4BB2B9}P~oiDVh~k^*l&Zfi&Y59Sg?YP@dPQ<!0ME?
z(-kPib(V{Qq}wjLa-aDL{wWfN7)NXLOW~S;KPxcX@=^pfJpyD%4Hzb8IY=km8u^^S
zocT{7JNw+juI?Or#$PG?$|#z3zpbw+k-o=KaLeU8BFXg?cW9WSfIGvK2wUMGc_F3v
zyqhP{7=WD(qmrJ5Nu9kNI%?%QUHqikj?Uz|$Bjds_W9j)&k+Cy`C9s+Eq6n$*eU+<
z8oHq&65*~rD0IH$uB*a`UXHrt4#1SsUX6=9WK^XvI!-q397`?CTvO4w5K4Qb`0IfD
z-FI}RK=#was`L%#pY23+Q*;~U>*i1YCEolyIEVRPJ!4Wu3ox(nWp|4zY=j6V+7?Pk
z8LZSdi9<+<7F4%G3CF_E=?N9Wo_fS+A^0N3&r&e*yaPWBsrOfaztn4P4;+(q?0eQ}
z_M|Dpw&~M_@9XOs+b{l&@O-%9Xi87#`~06GzoWq*oJH*w<7BYuty=SUsYS|i>YQx&
z;JT<zi{!fdsv;R#9<h-k-ZtVa=Hpi@ohPM`$?>#WeU+%-<8Ep%*FK>71!)^yhIvIu
zsW8Ar#Kv3)CoEls+?~98iKJAdH8;|Zv#YXU`$7Z8Kp>39T!K@a-RUVL=Lp!{wFvxU
zq@S`!#@MbH?+26$Exz_Yc?^d~VE&>xn-<zJtR5^S+y2_L_lsjB73R_}Rpl%Ro;LG2
zMXP0Eg}7F3Pk8IfhR!+>`hXI<{Il)hL-tw42B!q?`qECfgtZkc<;2Ol(M1%3z;TEq
z-R`|~ytHr8t@IW9)`z$mw<8V*(3@DZNO`NkZ`ue^@Npo$Q|Wr;YMNMXJ+<es+0sx)
zPZqc@=~Qx^!f+mqHkOBbt<-*?WiqJfRcILR)H0DVGTCUtO>5X>^%xlugI|VAG#cn(
z!VJeL>cja$k8mO3Gd-B`5VnR3J)Gp`&A{xRa7i69Lo**KY(|)GpZQD!B8~j;jXCbe
z%-P=YIjg3Ugsg`~fO3-vqwwUSV1el@6_o?^;Vt@N@ttHc$F}Az{56C9&syN4lV%pm
z$MZbeI!Xje_5^zDWzZQQ?+S?EVh?beC`em!O>E9UP}L~&Ol<Z*dLMVlEJPcCpJ|9c
z$-2SN&tgz)L^@GMrX$1K`6iFZ2C6H8CNF$Bu9-<pcewjKi_CdwKZDXYV#Ik_qS2Wj
za$R`zJ?%*+gYt4MAbG_X!iO<_r8=T>l`ugQbXnT8%KXQaBw{@@_G}2)8&dE=Vbd>9
zb<(eR>ts;MNlMjS7zI=}Y!|Sy$iE8(ao#yE-_*OT$g6{&Ay9otl0tz_*qUsO7Mwqd
zcl$8L8u>=J#Tjq4A%g*CxH{ij!P*r?wE4gpL_SIi;qQGiPIx0u-2Pc-GNBX)(O)$N
zME`#zL;u(C@>e#rh@GvIvw^L%)4ysgDb+0#Wf*OEd(O5Eig6f=GcXDs^ZSt3kh}w&
zLnlSm6?&mg9gPkr&!{Qc<taL8Rjg`I#Qy!3*B?H4aNGpWy7>%1)_;7x(B%9z%@A+z
zN8~4HeDnD;nUTg}w>7cF_t|x4OWY3pV38%cKO*uRXY5MaYK~u;TMs$GyLg#Oa>nV3
zc<;>E^;%i?T3vqwp1c!hp`Ip6mZa@G620~yZW7I$Byv}&i*r{Tp~_5Zo@QF7gGL=h
zuMA(_v~N~MW%#b!EImRuQeU$1bZ_35TzW1eolXck@mbQ(LGJb{BP5~HRRv`?371jM
zwDafbQbWu=04&<f(H5k}Y0rSXWdpYSq%-NFDf5SshM~?Sf*FuO?t-~z=_b@-ar_fQ
zZ2Ckv3HHxOTSVuPT%8ddKZ4_4HbHe#%~MClD7n~b@?&CPoNw}}c^e$5AQNJ4zDNCi
z{Bgez8byX)Ufi3jPEE+1o~b7K8YGyKrLuW`oB-QptU{I&*6D4Tmy+Fnd^q2!!K!&^
zugJv8l>(<#I86u-+7LJv$wriMveR$_!>rg^oSc@ebXzZ(gJN!z&y)L8A4Ef^aC$fo
zdX6FsfL0Z{1yjysgr>rN<^|Sn>@OzHb_hKoK-b?TsTZ1s@!ewM7$eTxpR)$_P@i0N
zQ~?|tp`--UgZ47TFq`#WNvM!vSSpqswXIZrFiacucMYM9hny*~lDA53)c1E(I2D-+
za4rl;mV(ssJmbm$Yt%*k-6o|iW>~JKP@xSRw=psL$kS!?+1i;wfYBZ!b9-{saBq;<
zdv3sm5(QhEIx}i(m?nz|isg7>36ZYbogoizrukN;=m45VLp{(@vap5%C74*VNOm-o
zc@O92R)j~<PzQCv88zPyrqM((t6WYKoUf$VO!O7~xZ6ybQGpa8;{MWI*#VV#DbZR!
z>^`e?djifW6kRN;C^a4Fv;$NJ|3sNZ@%XUcAG)5@XGV!NnFY%~C?h$)JYF#4HM2-Y
zeU^8rYNYv><aPvyMxz0Q_{%$IR-y%IxunEC*C>|n4awyXWHX?ydg+HjeIAOO_;RB9
zJBdI0eUWACd))1?!zhgQQ<*REjF?Xttw@x0#DhT8FfJ?J!UyftNT*?XrT9-8AQov4
zoz#|SdZq1w32U25E{(>T2A7BMsKz_HBQ}rekkVbSHu7MO(R@ym(7`<hCEg7-?U8Ju
zp5a{@OL4v&34oa!R-~3HfTcuj)HfIxntOcwL;xU7Bjhh^&zxFIeJpDwylDI#>($D?
zIV4U<VMV@gqYmK0w?euCC|6Y`U)8w9@qf&WG07AMwYf~gP_Y?ezH_7>o<Kz7s|hiB
zuM+H-wpn&+r<3)iqou?eSD0&$s|yDJ4dqWu-zm|E-{o^@rc6>>QR~O6JDw(h&nsFp
zU|QVwuWzl7be3~>CG|cnqPb{qo5knbgfnwl9mU|9$&cj-(WjZ~&W*MO7mX3FZCAB4
zVQO{f^RDYAxX>vtPPP)cH<`;{4it19%*T<_ZNoQ!I-icK#UUEqf?c-ZlDTFAJw5JH
z=e-YUzB9L#`}WK51eZYFS2!|N62QH*XOf`Woz9BNv{e+xh3a})bjDO&^*kJ3>7?rN
z^q1qy<&RkcrF)52K=_cka&Fi0qVAv9us~ED(E^eC6x8>ukGOolIrH$ji(@@Fr-@VW
zKr!5N6wgal+_I}=GIS^gd+N4HjUUi%s(i4S$~Wl^PbLRm5?RFy4pvmuN>aHMA2lOS
zQR)l?4%FR($l8*5uvC$<oQXy*qYtFo^l$s&hx{=R-h^>++7ZcG31d1fR~>R?J4>?L
zR_koZj@AeM%~z``B~ijGguUNEm;3+XapK`AuU~40Jk9%C9ho@`B4gP~4n!7}1Ke<`
zr?H{Do~H`L-?L)KEL&ECmi{!KMK3hsq>kDX!jQtko9UG3Ub4WEhR*7TOhLmHTP!DJ
z*YTkr1q-Ioqe?3_J0o5LqxxNt5=eBpq(|`_rbMaK-Li@qR00+q<r_C1I}bXnJJ+xJ
zYtLNO<$6SyAg+AGM?rx7qg<Eb6hO`O^X9$5vPQghH`3qQF~SYe7;58jtdWX~r>&_`
z3-#;WIJ8m?>#^Kb?c>be`>T)g7mc%J1}D**iKgpQOstZHv&I#huBd+=>dH4R_0O9&
zq*-I>BB&KW3X|2`XzntXv%!IE=h^DcY<tN5*O#0X&D_(krL{>$K%Rbm(LPd4Ys4ga
z$I@?U(@Ib-+!Ki^KFdV@s!w{q2v2_BLM84oaH+R#H9_Fm>=1wd^ijjuAdmO9;LJjB
zZDX}ki`}@3UpHSYGKYP{5k=eg>>jE$#;G-K;GOH8BVcr)BVeBbPOb8tS7O9;U-mVF
zC{>2jx?XxpP<O~>G;QOHqvO?kdgFR&P<!ddGIxi_?enmyk~cq2C`=p`$@f<;r(x4v
zvUM^B_sKeFyeE#is#x-%)#xPsZEK!SyIUC|(Aof94Z?gHb7{AAi`^1o8(t2;#ocVP
z+LahUeD~T>fSPXKvDOb6e@5N1C!DY~6X2ZQ1zdC$E33u_bmQ)nAMC?y+aK*n`N=PH
zo`yuPU)oPwU-^{cDMvyN&d7a4*u1^C7k4!#i`zRX+LzZ9D0*{hk6bY|;&=M*M|}l8
zxf2)-yI*e%oN@#*96cjnqenA<>kZwgUb9EH1Tq}ELq5Yqy9Ky8bmDlE4SV&dIneqK
zb9G~PrtDkwEIWGpU4Q5FC43gb)r0h999|B5a_A)Zix_POB9OR`)5|=Jvg3?83`b#h
z9((AH%sW^I!{2iwWKVyaaD0HRe%$(%L3u-6+k0bKJ9>l7NH6NYZ6W``cx@1E*2Cf8
z&GNj9D**aeGMetXfU~*RB${T2nhSb5z$()h;lj}y%sX+PyS3K=<-%bDlwiLV{>uI$
zumhI>QXqXFWyd3$;CpxQ{&0ZZ;j_ceu+v|#YZNYD<mXXb0r0=d(K!&l+{4o#0tx$O
z{yBVzHOKa^#{oGUxqkd5e&3#h@AHH7;C!J={HUHy?r($i{6A$@Fu+J_fCrkq;Jhh+
z_(l3gdk)y1@rDx6l1wCzmiOq;uxHOt9^Aw4fdfL|>=)bJE{z8Wnx5%jf!2q;<KX~S
zXP&SUi$f}G1l_BaJ$mU$T09MtDOwy2n<-iX4WsO0Sa}G)YyHh?35=k%2IM9)us35A
zM|U1aedsPG%(aXYyWSnJ_NWh8zb=OhzkkBJ3#(mm)i0`e{7VXB`Tt?%zTlmhyOD{#
zvxS}Qzu;Yy%BB;F3hL)3`z87MB?ld)FBq!i-E7mdh9ITfcR4wL?3^%?wcWf;d%W?!
z>37a(yJ&{PSq!tkDDEH<00~p?gWlhx4!loS>{OG)%EQJ-SF29bFYi;!U2nsBzuysd
zXl2o0Ob6qYZ(xpuNsEMA11eyS&<a&(cTmu}Mkv*l^N4W<;@x!tqbC5O!-04VcJMqc
z^l@p#Wt9#4MUOlUG+Yie?;%EI4(o&zHMkC2&Beoe-0xcYCqFe8+xsh~U>G<e@mmFk
z5Sgvl>tXd4;ehHx^)lQwH+#)_b{TFKRE{AjRq?uw)MypuC6AHQEcd#M6~#_*2F#97
zzr)agf^%!6?Y)s2Z1quNKm&|t@ibNvtP06Gr?FpKd?r1s?B{T=uu?|}8&aDL*lZ!p
zB_IhQVKjH(zsDb#Ym)E#nr${wHkenkiR~7sBAN7HfoXoD@ov@)n(?UV4%>Av`HD4n
z@s+|MX#KZ-1s=AZMo6EjiDSB)iUbkIeeiay6Su{Yg-O#(pGfU`QJ~Sd`$l+P4N+Be
z{p1lJo&6DR=pJ%Y=vl%*{)TK8T(>W>iUftDjEJmXs%ct`nAxE;Vb;;@IFoT6PH5OM
z(0~*923~Jc3%<i#o9R%|-87vdxDAMsx^SZFp(Y8y-V#;srGsxlGR1uQnVv7O(586Z
z24vGlM&<6Gl~+EiF^ITyk*4#euk<$(=?C|wEzAc-^ko<U0*MOgWC6AbyM>$*#x=Qx
zyCkw!D??;J#Zi4tPtP(mu>Jv=<&4*?vBP9Xt5a*Dq;cJ;$|74*z%tBf5v>l><#mFI
zZi$s>-j=b)pbad%HABr}<XN$K{j|_^8fhB8%XyRJYfke%1N1Tc(azRLqun<SMvbOq
z$Ax2B1&7g9mb_-l`?7EC*VOMZfuKotHAbQnu%kYOJpKud-C}kuP&4$1kwcj4;9j&<
z+r=tLuk%4}5G9h>ZkLiy;=a5A$T3olp&`wJ=9~DM8<3ZH!Wr@A2Fumo<s?x;<C}V-
zT=s_E^E1geoEQe8NOpJSzeeZmzu)7MZw%C&NMGdhV84O;v-kc2lT})+HiWv1Cq3hC
zk_2jz_Tz`eiehiZ%Ril%b{SU8=FFhn$&kh%!n}=DHFGLc>-Nz+C5EKjjP32cp#4SP
z-P}@3mFFdD1OE|LF(_uLV@&6`;SsR4s7NUX=7uyzo-L@eDYhNDB<j}~=1&fhfoW;@
z{MuWE<ms+eSHk%*;ab@xkz63KWBiwD%RCJ?@6sK`$fiORWj}^8(>86*0tT&Bq>2h~
zf;Q2cKja<e!bzDY#Pf8G*S)n|j@L<HrYGsZaEZro`ORCT$UUc4fY1g?$InowH>6}F
z)RwAd&dlU+5ac6L5JiHZ`D}ycVOyGc5{I>AC{p~k^SH+AgRk#%_S-S!Tc(%hlylx|
z!Vg^1&#jcq>Rp6e@@PEL&)F1jaZR0%|Hk(4-zbf9e~AZDUu(2X|DVUy*Dci9#NGM7
zv;ix%FKuAch&Ulgh%yw7fUSv&R0yl7NHdRe5NZ~YR<Uwz*%-5L#~6Z~Me)`51Ikb6
z_p7<$`Xc@BHdQ~R^+nfhsTo2CXqEa@o~JFRM=rA*r|B$#kC#I?5Q%FMR0Crp&cFud
z$I+3&nLw$Vk%+7^sHwqg{9+@@9d8<XeQ{p;vDSrfcI{*bvVb3k=EEVvdn9$wb?$GZ
z5b%Rgu7jcZu%#MUz#vI>Jx+mif^kXCRHu#jayrY`&b+A%6@KT*dD@b~Gx@fQm9v4=
zqbROsGwmlJX^_iscEU`DxLk%yrkKh_X<{aeOm~Gxu@OL5ej@US-WUcMqS|^+Sw^M7
zyMTE2OWD`hyiR2q7hHELwmEoroVA~}5{sa51mPY;6i;XauPQG~HceRwI8Jx9plp(2
z$>Ne&uEd&T1NYn%U0E6fu4q9{rvl~H@5M<k%nkW6(({@*?3j<tdudnGk2^$R$OeJh
zOhG1|zC>+Ij~qCYs{M}}CedkYrN%bv_QSMQN=Ozb)gBjK#YOU#5n+PimRb`*L6`6u
z8q>Lu(KK^*ILnsuf7E3bZ}+HmL?-n^mKz#;O@biSV6uz#igbUG2PPlPQ7hJv0l37=
zlW|Lou_}Zxn!@ws>0rWHBM{AU=-4`$`hrE`3^vQZlIsJ<vDO)W*ijRJ(yH2ft8vI@
z1e8VtH^2GQ8ay@Hd6}+`tf@2@#{W`WckS#+3y<_zTIc$0p4J|8LyiPSzd(0RJbsi}
z203P#th&J^$07c%F<<LKqWB#<zODz8MP<00860`)?@#UGDs#=^mQ3|QY^CdPbKf^q
z?O?JzKNMps$=pi9;Kl&Hm2p!R8`_s*tBD~Dwv^#G)qS4_&5MYX_izjf#hZMj7N2qK
zSOXgST1q1+e^^J3lAgetTo{=lHfSBWaOGZ?UGw3DV5zm>n(xl0SUJ?sa5*&3pveIY
zH%XB-Xx@Q#=UZ2Ow$STKOVD1!ul=O^JkV(v@uFDUGO6y09!9@s=!Q-GZI6XKaYvOM
zdS}G6u&k|Jgg7i5lL0?7(ay-S9Vw^VAf~q}v6Q(wP)TNLj_??!Wu-Zjwg2?LCKX4M
zvpbGxyqofo<wulc&pjPANoNORvHls~lZPU=u__OB=~H!C(yvGwPnT%OA7}4K4n@qT
z{Igk{qM8svE_{RKu&CHT%=(sY&fdEx*6;^wGB$C#O<rS0=X@tnj&fUaAJ3!P(lpR#
z3Y*^}HAj^1FBojr1rkM^otEe)2)ApP>3|1pe(1i6<jVA_Z}c96E6yBDGq2zYxml+<
zs8n5v62JfQ`EB3;N=20pRLLKM^Y1}+5aQTqo-fLlh9@G-D`s{(06|=dPyy+}x2Fv;
z8O>L$+bRi6rsy66!>-j|1-SxHM}mZIu~$E4<agpx$u(2YW!|&myh3$lKfzvz3{QRc
zitWNzVGI)>uL@N9;3MzE;;un#UIL%$<T{(&Tq}2qa3miDG&O{dMecdC?}{qA>)wa`
z)Xr8|u@N%m=WX;cnZ;}2DQ1EbPKG)-gP42|vxT8c>V7$}AA}K>vOXZ}Qhsjd-gz;N
z>O%(hq@4MOx3sj9D3*&0%Y9%TZXZeW^lkcyBs=_NF#d##XBLIDgd^CMtwl%b-4=OD
zz)H8(XRimYx^WT^{cbWQfOiLX{S3b@n!?NLaDPE?1^VsNI^*!bx)E-AD$_L$;O(Zg
zOE+O}K;IG$DLN`9jM!&F9rV1yDZcvP+J?oKAj?09k0ylOY@Pf!ya?^4$uIatyVHIp
zhl~7A2eH$aI%{BNVs2n-Y;EGmAnIac<01J49)(<-%@rK&TrG@E9RGDR532Smp$H*f
zN`cZqAtNd(qM|X0njngap~3{BYf_2TwYodhV{wSsxb_>P4^qE_`Sl0l-y0`E3iNzl
zlXR*-%CZv){*o(_M(9Yp%zo1Sy)`=V@%pw;0V3PyOfj(A4$eWFTE9c?|Jc!oVwo(+
z%hoJR7<Y4*Dfm;>{jZe5gu_d~p?2iGiBCowjV#PNE(A(B;TYIaeYZ0u4O2&tg;3@G
zq-l6tx5)Td%ET`C(V-6gsjvdAEv;#4`VVCTsn>Jj=|i}0<Ga-RUNz8#N=8~M>RV4T
z3q!bzC_yNa#X)~86xv|0WyJb1Lz?{~#Z{zEJ`hj5ua}O<@MyH`BLtCYmdIO6z|tSc
z{9k}Y8NQWmjT4uGFik=jObQ{QL+#?E<2>enIGC5=DqJ@wo8zaNv@JqR?~B|+&Ubvy
zOi;V2`xIu$sFs4q@%ZPF)jMRQr*5ZTGzm$k&r$uo=;Dx1d;(G2`AWcBpuJZgOi<el
zJ)4|lVcLJ43k;9Zd0MqG)p<vQ*wh<?<~(XTVkZr^Em(s>TGz^{xaK?G2S9sA8{36R
zkxh`>*P^44(FXOnJF%fWZw|;<NAq-yEn&eY+FPh5E`EC&uJ_@f^mIocYrzoL*FUdo
zQY^>UAz44#s^aaKa5|}v?{hLWeV}il#f>QwBtDq_v^4M6L}(t(8uul%`A|67f@kL)
z8g`l0nSr=$eQUlK`eo<X@a?Bl#m3OXXR8I|;(i7C>OoHEwI^$*>j_F~G{|bcYJVT&
zz;y-e=jb!ED<*?A62As#{<DlT={w#C2kyWQ;?}yHJu3J0mP#5(7KHS58xNQsbT8Ab
z3l6hRNaSLyL@tG>d>ZFPVj%>lf)r4YPg=MJ>0BgyWee5qv5+%-AME3C-v!R>@+*-e
zFJa%_P=F#$XN(g%Q2YWl6CrD27tK!eW<mi@E#3uH#D3@iI&)BQ!rgLs+c&c!Y&v)#
zCUO~Kpa#yNJ-(8J{|AQf9+8N4Qs|#p%+;TL+hTjf)#c{MDUS)ywGpB)L&VaBOr~ju
zF1(4M%TnH~$PG!xA{d&L#12?$ik;*crK8Qgi)%1*4MQzx!ckSw6FMvfqyMcy+b4d)
z-+e9h%_4ry0R2w|YHr}jAZg(E)5Y1|<%_Ymv9WM=HgQz2b8`MFPa_j2C%gZw&my%q
zFVsaWUy9WWS@HsZGC~^5<nZ=31T>gdA!=Y@C0KI(w{`_=ijD+heK%7c9vsj$OFK<V
zt3Mc*T}@3*&B3Z1=E|N;Rb6@?fgcMWKdOADCrmZszwOT-ukt<pdE5HqIo0{NjiL9=
zp5mk05NE@+6CMrie7CIBQ1$S>(fmj`vsVNB2c>)M_doq_CcK6D->W%!Ds~LO2^8wS
z5uip8C|w)OPQ&06C|-vKNDLlHm}H{74};AbG4ogNpcsC9?UhnLCr19PkOZR@DA;MB
z<`0>UcxRw|&R=<nkEBp0y(tW5*r#FcF5j^do?2G9-(^DE?%^=;mg#Ll<1O0Zp=RIj
zV9rjy;e)<ZH5p(hk1!PqaF!KzE-}&CqKB>;%_c!6?w9XPoZ&KEJ@U7-m~$Q;G=Q#S
zqOe1a!K@}bdKe7lFj67Cz;@cO*rddH!2;yenXVqdPg8Qwzeet!dBJl49>!GcR;ZF_
zr&%@w<p+6AxIG$_95#sb*z-!!=B@N2NMoRR>sQqok0&~VRu9nnA_MjlAL12VCxzMU
z&Yrju`lBz?oVFB3xCpdH?<2#HTgf@--g9?7lg+qXS6<3sp1RVA2&DLTXbc9S%r9?=
zy`VF;X$hgj3BTNzty>{@(`}9E?UKP&#D<=rlU)g#f+Fr28{xZ#<gpuox~vx#eCKV+
zd~&*us}0}N>S`~iED~b1=O4uzdh6)xklp8LLm8p((J(nt3gR8cj8P>=DmT2wMH%#N
zHVrdMq*%yy9}$=CR}<-*t4_<U7OK{m2U9mOZP5)HFVe!zlHKi%YWc4+nQiLoO4mdA
zGT8WH5HZ_Xglia^c!#M}G5;FYuTR3NsRcQwDAE?al(;RiQ!U!(Nrnc9RXfHx#IcPd
zb4UIX(!UPfl?Mc~4fp?b(ph4;EqTN-5s)z9?SJj_Bryti5gYoU&ZEwR$*fUwb~H&S
z&E6#xjQ}HreI+d2?|LzFP3ud!FM;hFd54WaSg^|&J<^)HOYux~qnQ-OZ5-F0twk1p
z%*q>+9)y#e-`!$~21}0iWhTHb^$X~sy>JbxOL|ENUup2|Sfhed_LN($#L69-K_*m>
zt(mPeKnC<?nzT}rS|Na4A;hhRG7Z}|T5pEsdt>8*j8!FREbCw7-|_bQTbo|YX@MyF
zX+9*7<l^&2Bq&B{yPNx`6W_3YFI`jn7VNgPN(kp89S2fmjrQ^m%My=MszOlEt=mtV
zKjY~d;nvV52HE~jxq*cD8_2<gBl0IT;CoNEm#aBjGbJ);uihuWt-OXd*c4#FX8jB9
zm&9nl2%2ri%h}xRwsM{R>>34DsXdQq5sPRT-JqK#DcdG51y_Uuy0cAs@z?JPNaLN7
z#%poZC8k0r@zX4wFgTU2vR3lMH*g?j=7=jqC!#*#0n{QR+xJ-^eYJ>fx~%q?R$N()
zxiKA~yDfkEFZ>xzfBcYsa*ghR)<b3fR3|!@?;z+M5F)XbgsXW$U1VI%Gnqk=ZkZMX
zUJ-s{Oi5mi;kUu7c$DL6W7_?9BHm=c0zgljr+X{E(<QV%r5W}}+f<qtY>uzd*{g_K
zqb$QyhdB!Yt(#qzoFUA7wy^}<il24PKP=-t3xQ^vNKIlI<|^_?6JSPA#5tdB5?Vb%
z+K294m^8M91$vYr*@s7S2g!D+QAW+%;qW3QP&lMvgP>xwUNd5w#MDL>X|;c$Fv3SV
z;SFFOkV(PAr%M&X210vOQH(L&Fkf^vf9$hVJ85pXD#PNuNN*3N@cuz^P^nYlJenMI
z4Q;?Pzj<2N@<4xEI-Yg(Z$Q65wYu=vLh7|?#n~gi{b`7?b>*}X?RBQ@{AgHH^~BZ4
zyRMJ;fRP|KU<1Fm+1euC8Br3PYyJm_c=KL}b<I@?E5FDUI?K2V+v~;H$JaYfv;y^Z
z)$Nb1X%%{3Z`ToO?g#HE8`kt2qzO%e0k#dl>cee{+Par+<qY-=UY!-p#R&D!^{$%{
z!yJF4?M8@CA>KY`U)THJyS<wJ)PwY$40S;XTYODD_~pUs7?-8ma^PYeW(M}s#UFv+
zqN|q!_9-z$NHZLar1r75q*pBpQ#`BeGW-j%yt3TAWewBIzboh;>T`Q2+`crh2BN|S
z`oc7q=HA!dcBQg*r3d=v<h6w&a8J5f*5)hAv#a7yV8((RTWsN(q^Nr|gJO#gZ#Aea
zoz6l@AkXKOUeU6Be>HgJ^h3**wum=AM=^0lK7)}+HJdAd9pm&jm!m*|;Dw2kO`TSK
zo4Fo4#c+EA7a4wDV0~FLIBDtJkTNTNn1q$PjCAy-CsKxzw6+JDjzbY}Jv#_JX2=#}
zp9ej5VzA)uM5<|ceIKr2%jQh;0os`%m!ZWRe@weewaVYW)f7K4Wv?D&Rl*y!oWKV=
z127A2ZJX&wGYy-*lI5?XHrx#Mh!Wqd+b)O`dE0i2EMTkUqZMt)wk{HTTH(^TM0r&*
z4c7_lA)EV)Sk~7b<Azb16A~weMJBt~;+9i}-pLy)yZ86?uRkFT6Z3HLdz57be{n{3
zF}Z%$^2rNaCuDznwav`Mn7R>p<=apk&5L1%SDHcbt?wa_ix<9?5E>bKE{Q2i;`|gc
zemj{}<Q4M<Ox#*zZv>8<gRRpWi3107NcRgP0nFjd(wW~sdsVTT@41_z>G>cY<v-DG
zv>uJFx<0@ElOx`QZs*d600Bw<f)qmk6Qpo7GPSTaVNeng|9Z$7*ejVByBL`$nHbqQ
z8Y`I?{2#<$q^1EtRYU!_qGg4n!&D%-3dhD=a2?J6B}y7g7&<}-!8B`n#LNn}Y2@}J
z+>~QB)rY8TOvz(1qRvp|7pZE|ZRU1@S%Q<NW~zT2+^)fu@9(?KKiN*NQ+hxAKEL-E
zc;ofDYSZ?!clHfdASv%6x6nJ~IWbL$Wl|s`Nk)p6W*l5mV(5-5Fro{Q4UNb31%c88
zuvTA3PWB^U(7Um~kdv&0M!-~y*Fs}pU0`DXV5(_ai4YlO{p0z|C<^IvUDJyj*Ol7$
zB_;IrT1+U|_^O5_irC93XlbgVuoILz;^*LG&aKWFl^oq%oe~6B99-7X5KF)U=47FQ
z$Z56adcd(UQvje%;E2#=>&ywqHvNksfOvoM2W8-66Yo?v$z>4lm;IWuY2Sj)<v}7%
z7C+aV<@&2Kf`U|o0k$oyMok3)A-9ccfIdwJJmAro99XnD4GUi0Ue%h7J!2F2_Mtz5
z$0ixH??JlqYOd|}keIY^@eBpMb8fHs^J!F+oc_&tqaNk1+<Ig<TUwycP7mJR$xjXN
zDF}eAK>MkIuq(D!Gib8LMmw)~o!*mP=)BI{Oefb8(X<Uv(+hfq(WMARZ$>b#*%R%Z
zq-l?I1ifskDx||3?ubL!!*qIh=FFN|7G*nRGd<TT5<B1~!be@vQUmkRCD@hWxKDJ*
zA_T%*rq9ebQ<N=P6tmdUW-)IRn=C(^Pq|l|kA*d^o2JntSsKQ`@N}x=nv;M^^LFU%
z>`2qai^L4nL;RrY;4p!+g1}i^@yFLdC~|RA)_3x+B8gs-N$3nciHcnTN56>_*A|a7
z9$H$R9nl&>?abSeW60?&+OhF>IiNOrEvznbW+}_U!cTB$)<tKDFTOJ6B>KC#v8X;^
zf`F>o2%1BaD1a_H23tbBQW*~`g&3xR#Y6uh59UgXvI(g!fcEAfI0z^O)O~NF&OWr|
z%csV!{W++6p;(s@;bsr$?V#T3r$e)G7aFwbtl2}bg)yhOM?oXl5own|BiJ<p&w&z+
z_=JjODE%@DW_p-b@%GQ4?mjTY)`PzI`!fnWU5%tZ+!R;M0WJzuu0paJb$XCHTCnN(
z+&OlN<qle1e_a^NS?PMsmHcu{bSfZy7$UFd%Fr;zu(36h#9rUTW9a8%vXSwn0(von
z=U`u$yccaC%3oKgWfy1nH1FMnSu-6pbGk%iHAIF?9hy_3y`e%@BY<h<v%;;hVfI56
zxPT<Ahc(^Z=yFB%PBN%Q)E1T4v-jhK?v5;1VUD0#9t%c~AKV={r6D1#!6Ad@(O<D!
z!YG+jxVnpus>t-sIobM7q7c%O@+;+c5ZAc~2Od6s8N?k~(JBxM{F<%v<;3F7^xFhA
zKzKekXs<@3bd+a_x%RcWGXgR8S0FS0LjdPV6`VpFEKwhqC>>izJpQCasV}$P0aiJ9
ziO5=iD}!Rpv2?+2Le7X8!vzurD1&cJ&d`=+F|WAq!mN&ozKP=Ae^m(tWS@6)j(cS~
zdkeUFcFB5narKk`P^Oz_&MAL8i65L9{)BXf&3?+O`La&{tD32Ce$@&Z|5K(BH|8$7
z<-tnvC-pb6<1`OHN+}_6kJR;3A?PKSD0VWU#dTQb^+`mySfnO2`S{48MY&ahqN*dp
z;Q{CZjCbIdR)swg01a_9#Zs1!eL}8Pq8NqmIM~2tZJAPAHfh#C7bEveAcj992P(Cz
zAnh`awYOt}dWA89jlb$5mjdGsQ2e_;-FzmeGvlWd!&oV=L^iu%l~Cm{xOFe$=Xe2B
zt7suTN`gVmE3i^0hr5N-Qgn(a-3b9nyw-Yih<DjqLgEq8@K>~|FiQ*0hp5T)heo9h
z+~phmPbgMk!4CyCb(C`G>HPExuF4FeIEz`&SDP8LT>JH>kW+&Clpc`=cjmJn(+bLU
zf$qnj_|hj5LA=oT`ujV$mZm+f?21lzaMD-P=MJgzpqK-`aEF*B6*99_6qJ^9`8nbY
zxJtuCOQg0t)V6WI>)Gj6_b05Ja2PyqCadHb0)tMw=EV?@NH>;8s60mu*@&`;ChVhu
zEl#Wph~A;P;AUv|RH5)xC!Zmk0hZv$CsRiyh`CI0=d4y*r`%HvVapoU8n`tbs@OGP
zK9z*`ODZDsS1G+=?y<OW=R|!Y<OkHLiF4y0;Qwr2L?$2b`d^fl(bp8)|43Q=-`m%}
zF393`jy49)|CPMnrTVpLAcg2l?oT^P*OzDL(VZs_M^yjIts6;kq8E<>_kVHrPQju@
zOPA(3XWO=I+qP}nwr$(CZQHhO+r6u9b#(pR5f#<-x}MjZGjrrOawv(q>2$&jT*p#c
zIxnxO1@i3w)QZ=gb8Eh>;TWwogoPSC@)w=UC#`Ltot5NVpJlJT;C#QK^iqD062$0C
z+E)1fvqsT9h(^0sZ#B`Y=1ngT`anKLtJK0qG|H#qG#vdZ@}xox=)w%<U;2kVf^S?}
zDXQe+I=B^Vi@upaZ;$?6ZJP}eO_TMs9*+~MKj9j!>o^b-u>kqfQ_BDhm12QC+Fr0p
zRd1G2eQ&De8b+}Uk45AzR!+PETzVeTO`Od4`_LWC=D3c}sw8CVqN?8s+?mX8BAN%-
z05dYw<7;7a9*wiyT#a!fPy?W1KlazN3c$Ve&{Co{OJK1gs0hrvR*e}CCdGB5X;LPV
z7-Ojbi!mIIyEWDbby7DYC+>gb*v{KFaOmgg<y*uECX^H7r9X7BnV^2r=Y7nT6grc)
zMO&61x%HD#Ubo@TcS9OLKtR5ccyk@H%K<K3vZnx7yf{90_(hK0Oi6oZaLS)8b6{|8
ztIeu25@;plA$zndd88ks6~|au?7<B@&5twh97*>Mv^O-j{ZjYeHO7${liQ7CCpC`3
z3<J0K9oH*C6iF-Qspmf_n~nuJqk?Vyj&K93F6(CFfx=v!sOeX?1MlUtP-kkTYp+NV
z%)xgBQ8=`Q27nUG-UBzx!*zmUm-M*7<}`b&uV5#qk(Xzqx};7Wa>&VO<6Aj_kR%J|
zxo<~J1JC-cuWiQ3WsiyC_*9()5XbJJq0E)kk8<mfGtoODS}HV3ip_@acq0X(f!G5{
zKde;q*KO-U=ybv_mVVZUlee{H48GZlj*JT;KX93a7zc=AE^&Ox*#bvnEV@VI7>46E
zab8A}cIm^IRDjI1;ssgb0>5J^S{3LeSTu~(o(<Z!dkaHykW+>~YlykL<hy9Vrg4AK
zET}94P|rB23wzyuT|DYs&Zpz2)CrD6M^bqOsqh`b_pH?khM7EtEC&X?tUSCwCihf3
z*p#7*FQyh-c{hI(Y3GJ#;;zZZ2Otoa4Kd#6?3gS;CK7I9D>?(5eEp`|%z~I)LAgS~
ztqb4zB;yj<&IA3;fcACSy{2bN62R_=y@$gb1Lza|K@2Upi{^Jk{_6q$6cvmD`K>?S
zVE&Kl&;R)V|3`7|Qd#>Q2BQ9K!J>i&=*r^l3l|~7kF_qY6N?(fF{AhW<F8ZakR;YK
z{BN1|;9D<VUX>@0btN@g(|;>Y8o8ezeacIAx)7Mb$V@jlH{04KTE4trKCZtWzO#1z
zU=Fb0HR=^Y!)eCe@`Ea&mJOML8lb|=?FxY*;4SLcW7Fu92THh-1x~c~XQWuvh19f-
zXQ&XCesW;>2S);G@lyw8rN-$7&iY%x8w=3JrRdW6@=2>DUqhyrUz}45IDp)+X6tEO
z=kAp+6ld${rl6X;Lr&bfqm{FF5Tp77I18JYN@65)Yfj2sOtb1t!b)$Xn@g8Q_x+>*
z2W&_3&C3*7k(87IDP_zhp&bA-rJt7-XDMJ(S){hpv(pOZJecb#&LA>*6`mr6Z^vF8
zD$$6oYi?oGPU&yoE71#btb{5uG;7H+Zj6%yETXpM7uf5>lj$+!=(0ApQ9(Mb$5Vsz
zh3Dx_Dm1ClS05@FNWTa>O*zviMDN)-P^U1E)F5N-MbTHcH+W^2oIo4~ADua9*H`QZ
zFU^nT#tQST0IEW6EUYYIl<Su(OT!6>VVlhN+8S0UgX%oE4IpSgDsEb%FN9Os%CRbQ
z3j#=Vv?YCC0xf0enNko?T#$RlCj-|Xih8^eX}+#@N;un(uyUZ53;h}AFkKDQ&#rXT
z;-9~Pjm|7V7c0fD2py6T#iAzQqrGn*BYNY!RE_?uZmP_tp``N|2_StG^hj`2Ct8IE
zcl<+!ZF0=mg&Un1cmXf!v6ULvpjdM{`-t;{XEKf_wtXjN%?*=qev94WUJxqFJ$gEV
z_(NM7J<oG<c3ql%<$&qrEv8tXlCQW?kXA%__qEJ+i1YBXb~u}=<;dtII(xwz^oVf6
zI>GAejP_BRljj8V+Fg|CHf(3<-;#v^$8y=4v$WrhWhX&c#X7?TuZe~oPH(+SEU>=^
zlNrf2DdDO#Y~h-vN^$_zDYlq!hrFG92W_)G<UzkZ0+L8Wk(0s4Re>xelZl3gvrhnq
zGw}+TLqFK!yie$<th^y?5-IZRP!1a-i_0EukEcURh{G2eNMqy~RD&kXP3VV)k5SAS
z{Ph!iQ3?p5E$1muFcB7@w*$T*p9q9mqI&x{Sq_AiL1v!#rz|l3&$ww;1^r6u399mR
zO}t*YIgIVE!r7BqxU3T8F3(}c(cqo>?3}#OBhNZsTNlp+DaGdPq>2zeUC%zg4Tx^~
zVjd}<(dlftJD5JNTrh)HE#hRW!<HvO?Q%z<>dkDxS`8z2R(c=%HfC`FTSdZqlxu@R
z_c+rAgDX&3zufTrNRKxfu)MShZ*N)Rm?dVTKHKggqmq^}oA=Zoo~<YEG@0H$+}9@R
zBWBZ8v?HljU80T-bf<a3u9hL>ZnQJ{$Ry7vjJYZJZP42A_qsy0p6xdYN5xn?@W9{T
zgcUL$+xkg<s3E9r`L$~Mti>MU;2a%?H{@Pb*aZrI%pR&(qFu#th~o%;{fuf+n1*tB
zalC^0$^Y>*4`2Gq;87-zrYk@eOAGKLjQuZWVY4u#bAEvOnvU;?U1+zHtN-xVl*(Be
za_-G_4qR){aPy6<4~mjP1n4(5lu8R#Zm>ipJbcR>iYvTcCT>DDe7wtB$6OF8t~(tj
z@!FO?3WNfSG_tat5hYX@wr}s0spa2!uElJgPT%&u>(v@iI?7ybxJbYb6x<ztQAc#*
zg1XygAV%VHwR~b{45=M`nM$+`8-mPO{P><b=JXpqk^Ez7XK5k-Z`DF}<TACv>Oe;n
zDuubw#?WOPp;PGak#b2Z9HIQ2PISVG5Ytb#`#s8N0;%q-5i-byQ&3`B@t7&Qy(^=2
zy5F3-J~{g!OfsRwm*_d^cBFxP(5&22%K$!m>G+EdJ0O_@w0W;gM<Ub8-)O*CL6|(l
z{A@=qiF@gk*n6hOInWq=h<`6|NwYM1y#2d6p<&Z#>cf1{v1>B~M7lf@b6hQx5eWYr
zaW^AJ|2gmYBYytvE7yTlm5I0Ji{TwG+t(CRP1o=38CabNlC1&ywjrrM724YQudmD)
zQOf4jZ<%QGOTzK~|5rK0tbfNS|EUuH^T<poYdCBOB7QI1<qslvwVJiIG^Q>~^CQZS
z6EXi~K{+36)5S=6wxX)R0@9eTT**4l!U3d#@<R(Y$$mxoLV+|PIv`(!l1|mTjdUq0
zXxMq1R(ijR$?^VM8z=&%In4hL89Cwgj|A{FA?yf0JkGxLKb*Y-Lhinj1XXGLkWRmu
zVYtu89R$_BllNB?U~u4TI>|$<6*&q>gEY%1yzX-*z=5IogYYcv5^BSwl?_6%B+iT$
z3r+U-Zkosnuab#a8n=2QyPS=W{&g4Z1$~F14eg0|=LIu}iq3Yv4d$1L{J939xhD_v
zfds5-dq@V7JeaSZ-IZ@3>+bfXie-C>z?}M`UGc=At1)4<+u&Hp9V2Pqhv1Vp<&Y2h
zKlT3#!*`q&uNAw<Z@e{R#T`AH&fCN}<=QUGK=LU=H(XUVbWziw0`x+HQITiFqwwm!
z2a&t&Ia@4rmwM3$6o<^(G@l5CKG%M5$=~qOqfL@HTb_8?#Z!i9FZjG1gDgXdCZ5;3
zq9=-+Ze+u()fge<?+5zKv=9}j;N1D2Iy~D~GPJ+iP(VKETHMFYG>A$n2-ux>mww26
z-~fY%+p3@<CT9<010s)Fl0`xdty1UJ^xeoyniX0wrzYmT(5+^E2*<+0R}z|Mo6)L!
zJXI-ASu;fU!u^~OFka_-y%2;f=?|w_1M-V3bteSDHh`TaFZE}7Rfxw+XC>FEFOybQ
znj<)py5#HB$+*>7WSQ=mOhI+P=eLioC(23BTB!hFBs~K{h^_aSmoDB$@CUXWjw1HN
zdBg1$H?byRgDqytkjqSqF5ko%@xkGAoG(E7i3`P!f~@HzP2QQX?UL`CZJYP_w>FEc
zl^F+1Gir>r0~c$WH42=t<cjBbS)@vq5;!066VRA@Okr875Yh*~o+rwkcg`HEz^jO8
zJb|=uIbHyusECdq1gZq3MH<KCjTN=XTl~nRTtZv`!DvkK0fNheXm!}|a?gZ8$Q<Wl
zgUu$5bP(wZMZn;@`bo9gm(I3$2-Pyy(5-jjy^2nEP*bfX)l1H*c{vKaJfA@?Lw4_!
z)JgvBNlnh02ZOsJ)y#drgN<P{GIWNuoMr}F;0vqpntNZ9>5rgB?3oPWVC#K;{B`zs
z^rgIN`1{SV7slP){kv)E9|W0ZNl9Jkl;X~Dl&?V~YIg*q*2pb3SBdfUgYDUel!n+0
zmVy7C2<k{GVNXePT<D$(VTm61P|#W%f#xSigHXLUi7qpOK4fZ99Nso%KMB?z0?F7E
zcZS+~h>Alh%=60+;D5a;n$<dDbAJH{XTm>!xc*mHg_WMI{eRa$Y5p7fz^~_E^#3hJ
zr_{ha6^GD%Wa6hbEU`iNLiutdK&aV5@k0sWAjM*JMH#_nclmUjb>c%hK9;#;FUy2H
zHkPxMJ=Ox0t&l7nL@8DQG(1|Go1SZ{x-=|q0`$*(j<2kpS!i1GMruCm86J+k9=vuw
zdn}IcPI+)VL3_#ThC-@Z8{mJZsa~i3AchZoIMM^&INX6S6C)jjV_Wu)F_|BsFgQb9
z_jlY-AdH(jVKIAuak!)9pbUP^O0B_QILCUM5g=Zyp)#hghCtZ;csS*Ds?<KJ10{@}
z>hy1sh|g+km~m4CNve@EV&^j!u8ScIwk0S!v0o@g4@5NGmqRLtw-xalD}-+=6n9XZ
z#40`t^gqeLHWI)w68<-${v?c^D<MnvIT3eV;+{A>u~P}?-lQqtqS8OA0}9-YyCn5*
zWtrb<MBdRiV<S4F$0_x1Ns0FsP(5*?oL2%M-V{RI1SLKs89NilFzDZ<dourysFWAQ
zt5HayDp#pxmyJUt{S?|OOV_f(A=B@?4QMCR%BeX_16wfcB)CgRCgKT{`E|8YuyCvy
z^@VK*Eivn!Yr)XP2rOY(gd<fqA&dNt5004$+U7)4xylSFlQs=U2!!j^bf0U}6gS^n
zS@l6Ru}2S#11&j{2aF@QR*gjxj-AGikrpDL>TD!Qqs40nGWQ#E8&q>m>Hc*`U-%nS
znyt+R2J<|$Z4qJ_rQ!MgWf4xKUlauvShgj%9!(-CvPwH7sO@A0+uXADsAXU`gs3DR
zCX6O)X0>SbgboW(;b`!pV-Q_fMzV>zLjUHU$>Va6qMY@K2c{yVbj%c-kH#1{HYPv^
z&#?1rqOMq)t^s2ao-E9h-JT5V?hG<ys-Q6gtl2gnOe84p{i)y;%3;D}iZ5fu`pW+4
z$5z)QrRuN~*%TLNTE7&X44sgZxOzW6vBf@P>N1{<4oP2;2q}VVHq_h;{}JSsx?$|z
zQUm_S@$;pdsx1#h^h9)^?5J8?ur-WbKxZi!f|1o`TrBQK)Yq8ln0-cJ8-JYNXA4*u
zuiRQUAujrZ42$fO<#<24T?$v{pMrjONOY_{JeJ9C4?pKACSmQ;0VkaXmZn4!c4}34
z7o4U<1ok#Rg?xBPp5c)Ga1@88Ml~rj;$e`M=xOYSPo>}&k6ll!gM>of;)MP^oL;(j
zgC1QU2=<ssnOSWv7CJEGkXZ+T)JrooHQiFk8|GBp`-wR|T_{%4WR!gymns+y^q8l}
zN|`byS+<AsujPA2k!D`gJOGS=tjW>@xUq1%tXE7l$L!3WuYD0*i-eX&WJcPbt`fc$
zd7@V*TNDRink#LedQBFa!F^Kt5pv9{WzBxUVbS4Z`}9yTX+SR|3A0WC9A7%y=^x8f
zDaF7pncv3G3+r_6CCj%?VjedK5=?pqWm>BFCbTa_(K~zl+`wY~0c!SA9hAyxC~omV
z4r?{tY#=NVJ3p-xDr(|Qemg0WQTpv^zNRUAJgVUrO+RMFCE!3?EomcSLwv^Ql4fvy
zpMZU)36PenP!O?adnqD&mMQz`gY8N65TzfK(5N*_NTed`8F@AljYKQGB~*3dg_Tg-
zeEtlb+J*jaOk1v=x)>h^d|kn~`&xNH7+ZTPMR{TRgCm^|B`m8+G4#x10*=hQBAFH?
z;!-=S(&DLp9IF&c#1Om|C6dy=rJ(ChI-?)~`;;&%xwF9U!mF8NS08q_kA|dVicbOO
z%^YrwcM(j4l@9`C|56~4&j90l^@Ygyf^++WmJni;kC#&Rs}>NX#=HrqJI=k7DSE$k
zimyYbd?UMu^h6;<Y7?p+d6W_dkHKrmu<x|Wly+7L%9Wutd|uc=@M8WH^_mEEkb8Em
z#fV_Yxc(X@Y?fzo*dg(`(eQ!@2f+a9X{3tOU2wky{h5U!^E%;NyI?aBl#>O@Mg1yj
zYS;_LxxxtJIeazk(ugPh0BY*^aiDNk+X{m)YV{%Ev05pVt9${J48n^DqXxC?l5jAs
zmdCwve~<JD-m%5ywS*xJT{Cb0m=Og!?F)O*<;=w@|CHwa>3^JcNDlhOViOcVl{yMB
zq>cdCpAgGH|EyKuS1t;&+afsXI@o0w>9o*^JIdQyDdSp(-#}-j@s*Di3CGzzx5ETw
zG=5Ctq8J0vTvoF+Hi3y#7*SXk9o6hH<WN#GkW(z4G{QUoOv%!)ARxQ6Wa-%A*g#-_
z{o{<8m2~e;w{(6|JJRhsmR*GuA3B<D>!df=-awNgj53Wa`ik#G)E?3XAX#~Wye<YM
zm*e<NiTuIvWmmHISmdC6!fez(PwWjpskav4v>rKf3Qwtv-rmmM*4pCw>R|8S_~6j!
zV0UqDgjoEI1?4ABY`q5@86-Qj7fHfn(7RVhX|86;@i0+aEDz3d@ZJt`upS;~Q<)Zr
zcQ&%gdiaHXsN(;!xiO3{DxXwqB#kh6ZBR*&dPx9Kq|T(U&pJ8VkeFU|P+MJHk@#|L
zb-Z>~6~v5q5+E}a;9-l0*K58b^3p{BWRbXENv)^R0HRC*x}p%7h6BCz*Q=(?g8)&3
zN_w$44R5J}p%^FuX<AEFyNv7O|L~*)-`CK}mkFUgI6vQ<U)-Eob+sC-94}u#S4V66
zH75*q`4C#`P)PX0=c$E7i&D0!xGhSfFOM&`2Dx3QIB=~9M+&x(ml??|9dWoIe;rW=
zJG3;wfs4`D;+2RaMaD@bqd}KBo<FyhewsVj<V?!E*^QPRce+=b8ft2rlTeaS&v-|-
zrgn1J*cDN>yOv`aQkc4JMy`6Gj$BCV4k6UVZdBL7Q@0st@Ox9e7)PVhGe~PJ6&g$s
zbdIGYI|LTmM=cEdV{|PRri(a4oTsY^(f>@ql95+qN;7bWwHA)Bff;RW+Q2{1E4bwl
zNsAetI|(l>G0+MvgBwlE235uWkmDT!Wn2|`nj6xrdYF&kLfgvvPpl?aj3J#GRd4{F
z3h;b@Ymc@RC{k%>X<t@k@rL!Xir-M|){=(=z;N7pJ_CFv*%^~itAL9|tJo$TuJ*mb
zKR1|<$So_efX|SQlcc>bPC%4Rx(~VL2}DxZCCSf4Xu1AXlMIKw$KXqU6MiNV*P>s3
zeZVH&-4ruwKD2!<V#$)*-qW0R;eaa)gq>tW%-L5!`>=94C|y-Axh+*W{}`5An^NoA
z)0=FEl7QBK<{bcZ1*nlIU_PNej?O#p4oE$DH|_?^RV-@@?dMD49JItkQWp$LmP<4K
zhr3kmlsH=6MOD=tA}($!-f9jIOe^V45Y50DVGNZVyv0_kRb>l?5CxjQfYwntyGr0T
z++0HE3|QC5)qhASr>(Bhq>BjAagN=08BmJdic=DucMMCX;fPuyW!)`qMGXc;M&2Ew
zv6f*_QDjClD;s42TO!%UM>9xAxfnY-H%P$)TjZoVp?$6)M*(ec$C`}TKFA%vlh{xf
zPKJ?iDGx15G!f<qwBxz**UX}8J*^?m+N2uq0!hjUlg8@4)=OK#Z42)5V05Q&?tLPa
znQ5sDLkgO>1ZNNpz<{;kyi$(RMO4_%S;<$%O#ZFaKc+yJb_I)^Yp0_(!`q2Oy5?@t
z6rvNMl!i~MJ%{&q-TUQ3_}2)IO=+Gog~j+e#_(J#PDIC9^-@dUhArw+2qx6D73x5_
z07$DD6wIDprobOU*{;-?XQ<4sqyiQ_wrzj+&ZNE{=gb(FT%Z<)k4?XngRa6>1eXRL
zUk}<~k1><P%xi;B%-$0_p6*DHTfiOB-Vjs&3^@@A9f??tTYgQE2#Z9!6#HX&arX}U
zWBTz9q?LqzfwG#R2-6??drl;pVF^)@fWj$a5gH<twvds;k;Gl2%%_C$I9q@n)=g_d
zmXPn@Miwo|E7q31rCWQb55~<y!RX+OGri2e(Q|_$avq4;2abXBlz4%`DwqM&&!kx`
zw2RtcZ)BHB(I{bmJfa>{=tSN+FrsN)BzHOeHfT8xia+L@VJpsHEKY?GSaov86b{mQ
z)y16JF|}}QQ7_WR&F0hZ!5GCHSW<LHz7J#;mlKP)w&-^4j~a50oMUK5vHRfD_1Un6
zIJ$c|?}d(IY2eChNDC~BjjvJzR477K>V-RleLX~bkZTBP=>==VP2Ab+;p;KC_+2GL
z*>WdU(}T9u+yvZ@r~<hJoCMe<vcPBP6yZd78d3{xJ-_4tqshxXF?V<|f3bSDIahR#
zwg!>~Stk=bj?m=4{vLa%%Pel^B(;37SrMT6ZG+-|t>V%1xaLkw>!j)+>7637Te1gE
zv6XkFXHf;F8$O?N>vD}d!4s=*SRRt~=4ru8^<v6K)siqcf+M_D;;0$Jwsuh_m>DjM
z^b(Hqfd#Ab6amliVgl@Ouc!q_8L1ICv?SbN%AcW0KO>auGIhw`iA)zPfEQ-yS7^dB
zH>eRkCW7C7cCRG*w<_uHH?Qo``*xoJn9*bfIx?y)v^CveHpDl|=~q;YJ;SS-C6hYS
zCq`#2HAZmu+t+*=?^IH`n19V5l{=-{1``r#wE81#5D3rU9ngMmWThJu)%Kj{-RiCP
zXLnMIdI%(ZK+cLX77IREmF5*?yA^<rxSvMuF8r88<m@3G*tUD+n&VYWvVPNV*a}<@
zxXOKQdj4Noeg?;7v*o{j$#c*@e<c3*TfhIAfg$|wQqg~c1nl(;EdFl}zDn8320;YY
zn>p-Y;tdo21ZtiUlj!fpUk)H}KUvcUU@<Jygg;U{EGJQ3VGb74Cxtn$e?`A!k;254
z-e5#y6Y-N`ls>BDA7s>(yx^`bvk*Y`g-gqeGPbg^JdBUi)---zA2)9PWcH><dv})U
z73!UqMEx#sM77|@8D^3Ug#A2Ee2$;jR@RpfE2G_>kDY@Xazs^O)LfeLH-oaFSmIze
zro|Y}jFtxSmWo<QYR%izf_gB2*9N>f0D!_N9}+?5R=$v7yro6%uSIn%>7*y1JTsPn
zv<%M+Lp-Ra&{AiCU`m_l$WKfOqC|^~>kGfKL}Scu!P@BPjSV#^%#e7%Z@I_MI#DBw
zFq2@9IFo~SuD-ONNuIXdXBQYKodgf|Lfe2-8K;2g&pLnrnjfT}-w(RjY+7p1x4gY)
zb~Dd%3^$s2;W)9kP-}%8E<6BrY3!9C;v-JU2J6!%(zA;}F{JM5kEk9^ri$z49Ph&2
zLF;SizuE}mkmOc6gcSK*c8)*iTxkV=aX>ysEN@lU$dj$MU%{!hD@`qBInI=nJ|i@`
ze*|x|Cb!^^CyA80hpi@P!Ub-VjzZCS+E9O~uHUa55q+{CPR0r_LOW<HI~QB8lwAgt
zE!EboHNHV^fvN`ZF9H}|lpeFxN?M5}R$#mLPc%Afz96OuT6;y@Od{5dHrzpudVXoC
z-f0#tc#(<wd}EeU8|5Uq(%qmCQr^_8a?t9X^<#R&<tWq0V@K>>EKj<HoA{a|nbgKu
zns=r#tbte`RZyK}t}jw>HTh-bN&J)O8nvO)$z#ll@BTD{sqv;SK$&119|O_Vs89l)
zesW>ks1}3WG@~toHR|Eo0KA-)dbQ$~sd^GJoSH+%>7P2u5mG%}B_eLbLcu7)=kW^v
zc7SlbPaiYq;AC<!6_n(_Bf7^f(G3J5wmm6C!V;F>QqQ&b=~htR|2@T$etv9;IZb>P
zq@-Xtm>qo#{oRL4gyaVR!!fwkC``W0#@04Ak1P9j#-ps()toFVt}XM2%Jgt3-!}C2
zplN@zsJs!iYZW19-9qERFc+Nj#=m%+69>vGb-DF|^t7%kSHN4PuaKfJr#czf{j~Lc
zMY5BAUhHM$uaB0@3>_wjz%M`s$DdU%X6;J^qVH7q?!@T%42!4E*i6tFT^ur-K!`7n
z`m*#D#5iWn82=fh`5mtO8La&oJ@6W^`5nf$eg^4#M=q_@?+R5iMr8{ufb?QA)-^8}
z{{RC!$L3bXKI`RM!uWj!fbMt3ysMT8p}Pv%S31dp6q%<Rc?j?mw%HbPY9M%GFom)D
zVz}$kWS$n&WIYQd_>p%^(<9tqGs|4-_e`>rdqBs2!ZM4r(Gv{-Zj7~6m*VdxIOSp5
z9i0M#o!5drzT3RsMnyuw{luZ8$6nogvpt}SRExaar;Du~g2sWk%iT}mbW6Z~DdM<8
zla7DL_=WJNB4GM_Zj7HcEtq>b5Rt()SctA)eYc)@Q(x=V|7rxL5`(7!JBM?D=JS}@
zEdzDfE&m4Dde_N3mR%Fq3ITo6bVKL0GaC`*OT5!B!JFz-f$xV;n)d_bzp7zfx_*gq
zzZ*wEe@C?cOTOa&QNyI1EFI1MXDN*EcZagFo~4t~f3))=1u2DJOORKB)F?;<uI?>_
zkdWBF`fyjd!FpLza#D~|*IP!*;{M(GjP=R<%ugzBMYmi0<iunUA77sFdJ`7}urT>?
zJ(G5wm(FW%hL3}jmYYAuwj3dd#0{eQ;xsD@weziU!&1NpZL3D8nrr(UoA#|54azLd
zfmPS^hAW0sN94CaMO7(aVpp~#pk3f@Tn_U|=Gl7rvu>RTzdU+8gm%*OOO2=sCs;E}
zV9zuQW*)|^<+WlfO%qOlSQ8lrWLo`dm0-}6(Qjg_{{RLQU)%>pwoZd<)<#DEdLl>T
zs;1pYh1y2vb%ePt#D(21X&ZW}doD7UPe#QZG0s%1O-+Y}&9XK-_7mor5dM?}8bn;x
z$xRuU(y~7cO86F`3{rUBEZTU4$a1VQ$5Vew_-CA|<(V2xSzf8TsI{vf{;{=Q@Mb|u
zb1B7HTNI=5=nGH{wfLT**oY^`N&QBlq-cs>sYLAFn&zAI31|}as%OfIovfzzQ)hdz
zk2r$)lT(L<_U?wh+<C{S%PD6Sn$+W7au_2$v3s1DLGs>qopqGnu5ATmfzMUap;>uD
z=lXmqbwTb^##fFrt?-X2_@jDkZ*F$XCFR#B*x~36*KUTMHjZ@cmdq%{I@J1ygifz`
z!iQ*L@w46~oT0AoGG9KhM--t)0HsF+!X=h8JU22{!7CYVV}AYmJP^WYi&0c#y?qsB
zLVbR-G=ej*$w4u8Y>9(>(Tu34Wz&2C-!nI*jWC$qn<qxTgizxND929HGOOgr9*(I9
zSch)}-IaVO+|V}OxD1{VH+XZPKH)f#x=%tw>L<OI*nRaZOLT?EoX;1)7n39=pUt2H
zqAcVKe6ZQdOZ*^XaO}tbizuS03tIa6U1R!<{lBgM3jg|QjO_p0%F<s`oalc{asT6A
zR|WILG(!6E$&fN;NMn{tFI00cDza)eiw}~oCWI;$vryP5wBpYt4IH~BOml8%xSU1~
z-}lS)|A$X13k{Jk1X#qI&?v+^i0iuRwd?odx9^u9D(bbv(vYz>7HB<QvzGSKb+fhO
zapSRIqRsP3>bq1aH+<D9AdJCHW`OmKgy2ZxvpIy56K}`Djn!)+UW@Z0`dS(3amNPs
zGA3)=6FGAL@s|^}_pkJe?jM*jSJanL)=;@`)C0o<dPB^3TUBAE=-Uwj_-;}I?q{G|
zQXigSoEX4cR+67zbIq+0G}jo8&R#mnKUeX76{AIc9F_ORNR!(pcu%Yy(ms|uN*~V%
znjWeHj#p}xSFY(#uj(t1%v8e9Sc&(zNSp(<>meD!PsRS3f3Izk40oM@I-{n2G;J$A
z@wXOeCVDx6JEE^t0X+JHAZW^#%<%$xOnJh=O}Dk^Op$`AH-Q^xc`!u@<z*Om#=&Y`
z7cG`oH>aE1J4?+*Tmo;$S?AVFm<k61d)N$RBO$DCc14m**3V^ijmW(>sDxg%T*bxm
zkVeqZe)z%r*j}X7>1Tz*vxnO@YDapTq3NRLbG9a&am*~JV{l8B)<k^qadHcs2y|O!
z3@Xu?^YK{eROgeOf>0M7O|*4FO-p;&(^P;+O{aESmPB}YWpU#m4fQe5Wm}>0hT<$2
zc2yKy^tnVHOMa=t1vY|<syXS4Z|lPEQ+iseSB-HPESPdqOvaFF+9d?)t^slMO@=XM
zgiCl<1?Vxujf5@gIG6GwqRMf407Lx@5Xmb#@N@8-c=GVxGq&oc<8jy+eP89{Og=LB
z2mO9z@DDQnEOyr;UelXtZ35|MwS&`HZFx!9Z`<@p90`;)xJti{RV@n>VkhzW8T>k~
z=uVqyg>0AOl-Ne9^fGJ4NG(W`gi143kx)`0w9+7!dHMl<_+!D#;{q#s;B}##b7(1&
zqkL6XKIdQ|U?<Zu(TB(Ejs3woqzp9R;P%fTg^IN_I`gwSCc4QPb^_@H=4Rrkz+^@z
zsv!h@VDB&nu?%<0P9Z5!6632$B$e}gJys@^g?O2Zy%JX2&ETUl|BN173=9eqt-drX
zP)Zx*&NEuX>*E)2r}oxU5pFNEr9c4>k|)L_`f{~R8#;Kpk-82wnY7LkFg&sgT#kbP
z;DK{bb>n5h>4BQ?!1TraW921GVzoK0yC`$>)Rx&&AlmxcdHEWQz3FSq2f}S5>IP1I
zV(^9$MS>2}V*KU(^Y4H_p7~mShloHF!q2d3Pm^dceihV;Ev<pj4Du~fvEa}ZGLNRP
zq&Jb#qQFgA$Pr)xt88|%a>F(ybG#YmeYP^uGROsSnj216SMqz@rlKi5f-)WQTExCB
z_e78~i+5z<rr3G>vqI}@unKAGxp~ebCW%)DBAJ*tY2ijF_MRty?G`(N8Bj19@>huO
za$St+lb9Z|(?Mb&jn@K<3{pJAPb?Zb%E@d214$gy!x4j^F1ZrVqDr}2n9l_A{wy<i
zZRJ~<&y2moG-W@3m0KLJ8uC{f?E*b}b%av(ML4c`QKS+PGM$nZrt)1M*DSo+@6GL}
zjgEC@3087BaJpena0*@TAf$b!ASAke;1cW!UGhnac>SS&;1tKkQw|=T)Kw#cWA7gv
z&W>b~#zcj+JtbZq8a5xoL1eB{`VEN88A;@p&@0NpDTvC`O8(W)W9wED#7kVAzDUd|
zN}`qWdP<hqO2z%<YO&)AdL*_9Ck;U08l%W!mUaE+tMEZoN2dsD^wy+Kb@UYYQE9Gc
zVnI|U6okqZwXhmxwd~F01#B%Dw3OM8H4MlL!HcL(PznyRfGnknrgP{ErFr|Mb%~3F
zm#j+*Oo=n2qWGK?nG>e6v(eDORt(gM&{nciBa>zqL3@t}nI>q{soUt>o`PbM!aW&H
zwK+bww2Q64dDH=$G9v}ir@{AKq;FnVon&Xh6J5ZjwK?u-ZRhsrEUurJ%t`H&#m%gy
zgjICjZ6hdQE4Avd`%!k#Ou{Qc^2up1SPsH}<K#eW!>_Sd%Y-H|=a|Ql8ZsH8PzeY+
zeVQwd*9fzZ$4Z46imQhoC74oxVGbJ55$Qz*x7+tu0`J@VTh}R79K5OMLPo$-Ri&q?
zkk|m84o~Rijx`tA?6NlZ5_(XwrS;{{*#|<+$jK50Jr|^2bgt<1jT&xsp;UEqm~`gG
za!kCe8cWRhan5SjUz`VW8K}d}?(n!DV3kT*;BRWye9crT;`4~%)ibUAgAGzs7iu%O
zEbE7BY_mrOJyMgDjKrvn2AwUEX(hyUOphIMD`2M|I8DFB7}KDRK3A34`MNI~LgakJ
z3tu!(v^(G=Vg}6~5?REx<-W=KV@mr+u>Ugm$jNr9RR(V6TGWx+AQrZ8lHgsvvE`az
zC@4*L8@wk6FDa%thmDCi-HliITE-!l%8C1n*HrU?sd7l|G-wDO(~ij+32qhLwW?uR
zOO0AJdtA9m#%HVZ#M8da`W0n@D4!)2Ce8vSf;f)3s^*xWOp;i6z^ezQ>vW{=lgx|$
zb<iI*xljF<bI!!slQ#|BM*rxlu=%9JIuxC)i8Ahe{P^qW{^<<ReEHq+;=*dCX=(QY
zw$Irk^Ii*Rr3&(ktudwxfvWpHt@2j1z+Vmszt3GtUbKWg8NXZERd$@NT&da&{gPaI
z9DQ7YY&hQUAc;#==pYp(Isjk8yBxTq9%p0=7^cIRjr*4V=aj&YdzieuC*T3BjRCkh
zzS9Jye{4urWjt<R#b;WQyd$?Yg@v|I!OxYk0(+{zaltRpq4Ps8s9@bIM$KX$yzM(v
zHFKn*XNbxYm=z7JN^1jp@vggNcsK9<Y4X}aby1a1sg+k#E-9}!^)JYDpzt?cK`w+V
zpe%Di{s64`B7z+f>xJsWtp=;|1B0U6A<Ca3&vRA9lI}6e;0amdbuECS5pKc;pN$1A
zZt#0fQt5>V_|GKw<{Fetxh1nA_G8)7Jwpgnv{QPZLw3L-d_WR}B7g+=1zt@sm(>0X
zsXe6&(h4L5Ys0mm7%2obaI=_a&yqW+DN&uocQjohExhl=L;Sd9J+w>Ygf6PkLu?SH
z>lmYPmSE_R3ex8y>7WKjmfq#(PfkjS(XWP;r3)X|sPz|Al+va1iPGQ3D&_P)$KvDB
ziNRwHM@aufJ_bF$K^^eF4=PYaq%0gEMK&RQHgKbsgCZdxC)#JOysP)4(4qG;|AuFt
zwATH$qqK^DHsDl!MO5~%qawUVAdwx?@t4?xJ!$iQu>GtTP@S$tv3~=Pj=|!iQbREZ
zH}ut~@TCxua{+yXTOkBF63C6I*04nnK~DwM0ZT!m91B(e1AZ-^3vuut;v4dR#>v8U
zykqT`l9x^Am6Amt67v|NqG04310N)n-i~Qwwuh{sQe0lI6e_tK$b7$N+AI@bZTfSv
z$a1@mF=F;~^w->`L}T@f^ore|!6lJ}DKhV^4uG@3bE*4{H6R^gX1t;<F`Gk9Osq5X
zx5=@uNTRRALQ$~N40qYrS`BeI0PDn|*(dMxuUHFfO<p=+Z$@5efZptF-W6UB$yhU5
zov7}sx+LBlz8<`~wBGEy9?80-z1E-Ew|?fl)}uMl&VhOP5Wn@UL5E2of_X>Y#nYh@
z7Bbotv3fEpkKS4YBx<IIXfn#PD9zH6jOBk%-h=lSUxi)Phf$+Qph5x90Ek>!HUdN{
zm{;M&?hGNM)UVm^8r%~h@c4T}Pzqah$)+hS3%AxjG0%sb6x*Y6Oa2r@uOuF;RRk!d
zOtw^C^)z0&Od(bwG(_<NAn3$qj6(!3)(=ADDcY|DU!8obcLAf?e7LA^j8)V?dPf|4
z3wP%NbxW=ujqmGAk_X#d=y)clSb!_>mw0a-UIe7=dNu0&Hp5!6SH!MsOLHY2)BD$`
z!#5GFWT1L+Jskt)q=YP|tVO3)z!DnmO~7p(VXuu)WlbmJu89Dd(<{a7Kq2RVB=jk4
z?X>eFgD}GYEf8KGj2PAzNYR~Ez5~8xKKJnV9K}Sg$2DRj*#xT@&{8Z-O^@cw8tJj+
z3+KOf($dPM7oopgN$W3H!uEeAF8&YpOx?{>amDF7nsGkCI9m-6RM3*Zk~bib(Q=qs
z7n2gtgBR4_5EC-&3zcgybgpx6D#0p~**a^hs^R8iKDilBI*bZ0ZJ2m!e^9KUMXa63
zEVEc_VR0*CndxoXqhK!5I97Pk2l4B;yCc)#dhMF+WE)3@=jRpS53_hP_Q#znDhO?P
z7oF9#8AJ7yAZpBkXKEME@?J^Piy)xPK0g*W!f?)RgPtdJ4$Ey2ZFWCO(_6e>$$)8Z
z3ep}$`)3LJ*Ai`aaLvUn2An6tZ>aIcD}&an!`40roF~f8LQoIr0nMEX@VENhkFZI1
zO)AgqaR~T(3$VB0E*bz2G(q?r`)8K75B%`XLCN}u8Y<N*$k2Bi^ABnt&8>`+E3?1P
zaL?(k4%BCc_s>?Z59y%K`EF0*k&f_e<PY;L&$}0O<khPVz|6(CkO1tkXB@4wc+zt@
z0epOV=wf)DR2JS7I~KHrpkz=xKK_Ftx7ox$b17u=1>Mp7TFPXiU`BA{;e|9fo0JQ7
z>mCat>DB7q$dZNTjkNlDH4ci>>ou2(+`JJx5QDYFx+#G=Y!lmA=N7nmYW~ipkUDzh
z{Z=fF?9LFW{`<;A22_k@`f4uP_*#P&C-v>W9DA(*AeI)r&MHZ^y#0HFp%?3BHZfk}
zwauZGOuMXUs`Fu6d&FE9rsLO+!3@b2Tt}oKuCwA%tNus~1@L-$(0buid>2JWsJkt^
zfbgoei{tA-|G?D8FVRVHl|e-h-@6ZW*YAZj@7?R^E3c3&43O7cY=7L;X6&l?KA0)E
zV&#`>XaWu`b`8myEj^TRc}U*FVU->LoR^&wl*!$C;MHBo_yN&tS%%xebHln$v6)nx
zSMK)DsITYF3Qyf1Jc27dDpx~OB!`~W(fYMiI2*W7iz^>>D`y-M&ibs17|2V{B3&ID
zxa}D%!I&rY_bOpdFxYwJau$=s{xxkRoE5eRz{Y474;P0uKj-2uo<XjXJJDOcL_^{<
zZFx5(`n<v`pXUk%*=1%xx{V~LEsYvsvWG9IN<JtW$5%h}iz?=sDPGr})87L1?b&b0
zi0z9+bW4(-B|Y4bwR%%{=$D+V4WQL5h<QAFW%npaDa!#N+2Dt|5+)Vksq(C7xs5L2
zdi8Z<C8=B3zfin$0t=llv_#`clvQiJ5M4&5IL@mHB+tcztu%9fB*(Kp3OZVMXjN~W
zn1_T96wn=F5-rp9F{KQzVfB_4#hbTSk6<;Io-?HghspH8RpHI*sK|Y~zx*g{&4mnQ
zUyBs&HO)A8Tz2MI8g%iipf`3+`**G*XGs`m@dRZ_R9_VD&BT)u5Z3NE0c&woC<!@Q
zwdjh$!nc}u>fp7^(CU|v(Y#Gs3BPiXwHNf+l1E;0up5$mG8|*MWO)SqX)gSe>tnC3
z7fp1v$Xml?iGnaTgwLmBpQLNYhZ^D0Y%!;+iSQmcTTu?YxwasZ;x&mb<|ec+5#Pfa
zK_if^I#-v<V8}+nJX|O^J_d|G-yTu6ME~zMG{Zk!qsja0{ZFwZn{o?R+;~wDh_PcO
zN^W-Q+-kbrfY)?rMr}tzw^%VrE;Q2I;1#Q>KB|c%<X&J{A~P6dD(aw}fVSayl6_Jb
z$Q?O?%bqnt%?Ji$+j=6>Jf-P0#A2K{_LZzPyFcR&+@Xzta=Lw#ro||^g7O49pJlXJ
z&fRh%a#(u3a=yP7ji{GISkclTmTMWARsD3L^BFCn@h`EWJ1)FtIBKj=oj?_=X)_LG
zUqGf|ltH#}L@eN(YTwYgnwZt@89|mcKjhzZuRakNWl($>Z>-RMq^w}AaJFBcapFde
z7eu6yRzRW3{-wD^A20c~W@^+Tq=RZYP2xe#jDj3>Xd3f~TECL0y=F4*&8)a2A&J?a
zMXVj1f??k~sBx>@xAaCOR^ujqGF4sUDDW<MMpC{REmMnIGdm>3R=TS)1!}!d8=Yz&
zGV2*~+WuI{Q9@R;*x+9IAtPmHHm=8(U*BaZA2rlBo|rPB)!=R+mPmJGU6*(%rvOi{
z3krsnz&DJh5Pgt!s8*ywyTwl|umD>SpPhtITxhr&+X#(`fV0x@M%=kJIN(~KyI_R*
zM}WRKbMY0eijjD#aGHKB<(igAAv0{=NrXO|OLjMTPTT-RLBQ-YXACh&iJ)&m`P@05
zUWd4{a^(h*_H8~qVjAt<{EfWMz}g5fi?@NTqWEwZln7E$u^CeomQ)#V>`Gbb-$>xF
zlxm2Ogu~Uk{n^VrvpDO(fb@C_tE_b)uJvTM0C(6lfq*v_ms`{ZqXn44HF0T>qDr5U
ztrgoqvRr2I3(??|Qsq`PLne#p%;Yp&?xZreOj5u3&R6mUk<)?eJL*O8s${+NRiSD)
zFTRz-ADCuB0LnXhW|rlWf}n&Z$v!A=xBjtAa{mh#XPM-;jDm$-lN6;S_bnr&oyac3
zwq5F79yhz@(ti&mV=u$tF@~MD(DkVpvXKDKymOC`E}Na2M3j@dFZ&;nV^UA_sSq4g
zMl()$$A*Y$D4K!Lt7s!niaaedmx&Ht8$gB=BQf$~{uCm1>aH7*;T4BQy5b!T4Qg*p
zN(X*ASVx$qQe^ozvmloSWWe~@qEY&Qk%d<t2WOQgMF@}v9{EJfHMG@<5l+I?{UG1F
zB3-+g*432Ir8FmXkI9;-a>N8W2a6L@cTaAg@iC%D+dt$84%eD9Y|R$5Wli*G98>(c
zUHOAa6*f=7oKx<8Q2rmrcU9Cm_vf4>rwze04H|0^mG`af_$!8z+1?U}f!9r%$H(ux
zl^-yF<8pI4%tGe9`OU+U-IdNFwZ{j>9PxiM;?bOvO-|~k%cqebT`}oDO{ba~EO*Hr
z@kd0&r1J-h<8b%B?d3mrLd(A|$m)HH3I-?gQy3LUFIGr8S4Y@Fhn=JYgkBB>0Ov5m
z?G0t<FGTkD(b&c5b;6mE@en!XP)DjPYiu}v%7(^>1L!M_ka?EdnOu2W3o>D*-yoA1
zY@L)P`i4zABO%J<!|T5r!>!?~F}I2qusS#73FgW!$^yi4bhOabCOC6*(LU_{@B&Ue
z8TogScNGcz+<~9_xV=2|bVj{j{N5>`ls!I(Q19-0FK!dhJpruQIx_bxfe79_M?N*X
z>$LNj9GGA1Jxia=P1yoU6_NSs8L}1|q~_`?QTfl5C>3#f9hgm)FSvo!iv}pic_0zB
zC=;_037TfmpnXEiCM{zolAqc2ia;@53_JyuK$6k6*VvmG24@(hd)SB_R+z#z78V{C
z2Bm5)&`t%VGcf&C7sRl66d4As`j`*Yy50BRsO35Qg-u?N5RRia{7J{0=+Hp7C$*-C
z5ha1@0&<EAOpEvU=WpcZE(A^P1Zg{B#RrSqS&JFqtLU{!D7UoN17tdx1FbkUxF1Z7
zyESqpORhvF7q~NeC4L~c7??};T|hl!&wQQaB<CKYa!KuZUYHWi!Ry1btieT6d3KZ*
z;BkAz#!Qqu>I;ekMJP-`pw35t)!=(Eo?T^sptu##;@QT!BajyB={pE;GfkWWW>R0d
znk15T6q+l*)`C?Im<k*H8MPx;<Y0~11YeQ)yRmIX={~Whmu@`-mwcEWl4=(1DqDSz
z<thumRqXfBm+!hsSAcVr4phC+t26|D_oJM0=7&t{SqWUAuK&X~P-Q6wy^_jvICZ_J
zbg?3|$uP_0pYZ@P!P)(^XuZd6mJJITs~B%j<Fx8C=M3DrZ?Yq#d5Y^?6uFnj8564_
zrk6cJd%a=;+7IXEI2??!D;#A)q+~97Q1`iy`rh{ASvhp3WNbVo5Juy_C_!*PsSMoq
zZ>d+}C!??CrzFUG2eX9boPQt_9T;u~vn&@rgv$}<dh`KML}48bVSUgOPK%KZ!+ChI
zAj|^&!S3Ji%rt7t(m}gz+UVV2`+>GUiI835-G;2@s%UowUug!$v_#hIbt(uw8rE?1
z{35lU&GWx^8344dEN+Mqi@7{<y+ds-uK<+TD4+Gf-herq(`NI_c#OS1Ws6$he(ti8
z(aXl4<<s_j-zS+dIKksOFlar(WcR3O3G|m+0d)R_TP1TfS{JCVw#q9vo12np^NQE$
z277#mpNaCCiG7SAJ4R|x7?B;q57vv<!5$Uo&|W&(2}@|QEv#^c-e=R!85a3j2rS@P
zP8it*Ljb4cF>?ClImM-7^f1!8!$9_oIi*i!3UFj#PZ$Q><8M(+TV~*293oM3N*=u8
z)PLZ=E`JFl`n(?hnuCg0ybTl7Z*PB_y^~jF@4f@)d6!l9d5hkTTWfn-L61(58>1Ua
z<~=W0o~kGA;C-0gfW}#=%rDr7z}N(t`TZNBM*+vrnB9Uw*VMl+2CrB<1ld%zFUX56
znueVf%(orD-ZQ;spc&<EGX_C^J0?Fc*#pJ^KCQbcrER6xe7*2AU#!!In_t119U%ZY
zs}!smFK@LsJv$|mJfycDwthPwC$@dk*f}zZm^pNh(mdQ3CfwYFkG5+3AIIXQ&@r+l
zeQcfcA^0_%p5h|mr;BvFIb(d<2?3Ba{oi(-hjOE9X15q-X}ECNMIvV}a_bsS{h!0{
zxiC&W|Nd)x2mbzJO8RR;m-~%Uk^J9l@BY7o(*OSDKRAhsz1i<f=|3G`mnwuSq6*UY
zP4~62v%aXfC<>@0-Mkd88ajRz7*GNtArauZpuRX9aYw>b?9?<n2gG2D|7)pC`LceM
zmDg?sDH3y`oVZS7QB||~5_gl*NA7Zq^4I5}gNe%kH5xzv+h={7!^yV84A%?K58KNn
z_Q%at$lt{S9eC<t=;$nX%vHHSqSx3!t=C#p?*2PDFieil*Hl++g7lb=TQE;~NuTi$
znF9vx%Vb+B?up;gQqgOtX?4OakS0w!7yoSpCX47Rymg|iAI--vhj82)bU=ZrlSB)l
zgD|y1q^Mt$`UyP3()F5*vXe|JLt5GELO3~GmA^)E`Be@3kqz@<mjSag@^=pNQ1nAK
z#7i48;^a5L6c3N9->yRt1mo!S?+6T<xJOc<dlC9_lxRy{T6vryso74x<?jhshzMFH
z4I>WDm!?8jnM};1f7Osyn=2oY5{jq*4%kF4F|m*oBUX}6q*QEVd_Y&&pOY;yGrcoa
z=&%+P5a$PbsmSxTqF~Y+Qq*^6WGp3wWQqr`$YUx?Evu4B3rlR1X8}fPIB!H|q#`ij
zl4xo*rZ!N;q?D}@bmWRFX^{|vX3QvNPo)j|=hU&L*p=P4R4$_U_aE7%DAaSgaLPPJ
zL0r8vSLNU`MKJMpLx51b(W()8mUr@$v)9-x`_Lsx1EyEt=x<s#MN{fJTOy%`sI0Pn
zdi-SiV6AC+2yTHr`aA0J1|`gbq^P9DTw-2oIyOq}*_uIOlnVk{(FvPxo-u#HeU^~L
zRx(>)r9P?><cU@7MlX`W0pr*@C|MLcb%Ra;Q&IBEL)KL7`K2m@G{V*R09$ICQK9Zt
zBtH)fk$rb{#$#T}@**fPvP-(St8c0eSuOuH?FbU$Ii?G(C`EI~QlKx-m|ft3w7+>q
zZDihBbbC5Bd@zKTlu0VGpfhx-0HnhVu9%0ll0Mn`LerSK?ufqnY*JpbiGuQahdP#e
z&KWfihtDBm>@qwBgwu&pyweFggY5nU(K^QI<X&nv;lh^rCgbVsHBy?1o8EAFeehWC
zncIO?p$eT7Uk)C}-H$~2L2JZbzwWlOg-1)NUW3_Z=&rxPM}B|r^mJHS1ZuP7=%pt{
zayPSfcxf#AQzD$Q&~$+=hRY?pUSXtBYewEaVP|4A$l@qD(V7hJL@S`peyhlE7c2Pz
z_hwGQlt33z(Gb4B#Dh9iQoSZ8I&EbFU?ncYKd*MU+Wc-h+=IWE33s^I`>v|PF}DV2
zF}rf%Drh`?GGs7DyQLF_eeI#fvY->MXxIf9ca3H`m;sDmm_56%MUf+SfsrIa4~W^u
zr>rfNyRO2+HMbUZXAPJ$W3N!&78Y8}nP}8rQhpP(SBjHHpU^WCu77F3DYW7LV3B}i
zB3eWYEtbMtFz1)?g?H6Kj@o*EWBXa9ujSZD`&vix@^Brrqn#=(x$=eyE{3w6PtbeE
zs2G0oF_Ldn9mKpMjN};oUyQv|aAyIx?c1?!chIqI+qRQ`)Uj>bwr$(CZQJPR=BsmW
z?Q{0Sx%++9dRn#Ss4>U<jUP%}5oFvQ+lS6D-!1f6ZJ2U<j1~n#rXN<#eh#Ce`m{U;
zVOtQC<6bp4TMCMhZ9Rho+rpwGXmI%$Dj3J?X{6QP2W}R!nXJMYdPOLus6(j4D7j=u
zJTMU=3w9hwa#QlX+H`5vCAxfW=d(eltt0mvbskeKi^D`3^zmYd3L2|1b-jUP`40Rj
z%^*K936e$Ez&uuVU6H5OJj?35AYG*ySb*||CEwNJ)#>@tz8B{fud@e|*^$Ch<3qkV
zG2c<V%lXj}Gvf(rK4^fmyXA#6Sygepqhf71cKD!N@(8Sz^K{GF=ybLc)m57*A|ZC^
zMpL1L$R2KomBWzNlL`q3JAaDcJxK>PXh%D#+)|nHB1&;^|0o6F2Xw;FlG3*(^Vz+x
z<pz7*Kj5>5H*Zz#*wHXKNA+MSQZ?u`6@Fd8Qotx`Q4f`RS6)yz-<)^{c1-%G>Uw?+
z33qE=QI(7(-;N2fRuhbs(0*gBo7v1#{uk{eHkhi3jZTe9qjNYt<rI{b>#V#I5Px!{
z8qP!?6ZGH%w1zB(Wk{0JY3HDc+NOIPV_fza>ys&aY*Y_oFS0hQ?=`4G{ai!bHf}2_
z?K$0m{drGXv0e}a;}mWs7I+0#P=P7tbbu`lJLpS#5MEPAN^7Rn=FzqN3QcQs^QO+u
zDF^5bIs2H~MEHE{2foGpZ4|$A?@eCNP}Js(*e&P!!o^E+QXxZC-Kd@;>QVvu)g1<0
zL8ZdIl(!A`3Cq6^UOt+fZiqEqx0W1&{z%cX<6qj|>*e_&#%|ar?{D-U#HnY(FS2YK
z9z@MKur7IN>q+EA1Gs(>TVcq~7{v`83Io@DlFoFTs|t<{?{#TBzmo8T{CPqNpAnsF
zL+s!@Ks(k7R>kfiR*lREb+{BFK~3_|QUv-Dfm;0^-)H@%TwzrG3NpUdZ8<uB_<u`g
zVo1(Ltjn_*f!Oo4$-~^KemHgTYQ14;s{vGV63eRloQ?`JH2fo45-6418{$lMh-?KR
zs_eFCQRB?<a~*z<x-!HSyW9el+_*R#+tYPnypcd;^pIt?u|^F~#qwg1pnJF|zh$}}
zZ}PnQLuYA~`2kRb34qMwf9SY<mC-?B^c{07;p5rs%*X6yX<U)~1snHK9-tWPwxDQH
z_&q1Q%29^8a?w~d7?ZY2N~%eDBlO$0A-Ut8JycOJA}G=Yny$0vZnpS&P|xg}mr$>(
z38ltzdC5Fc?$5BCYYm5OC)78U<LYd|+64KhB`BfUqC605HTp2%;x#e05ro!x+a_;=
zQJT=;Ssxd5x0xW${+WF=#@hy7rI~V?t7!-Fl1KgEBN83AxkSF0gyjaHFqq5KxP5}b
z7j@~JO_8-_7o~Utp&I0E_e7>hd4fzBVQJ$Zzw7~o<#I-M+bAtrg|E_#pqFlwMs%^~
z7<JKIfl-(2bN>J^so)p35tRdNkkh1=L(Ys1fv1Zi%+8PwBl=49ffIAo#NV><7`3mv
zuLzRt+fO$8Hu&HR=^{-zL;5UGTxS~ELdxd9i<t}WhCfx4&6|^Bl~zjuTEB_en>`q|
z170*`sfOQ6Pso3*r%kEcj6hVLK-4V~g~Fh%ia3YwD7YB#49eAYfZi#DWYkV6J@WmZ
ziY(1)pVIFqwwCcjwqyODDYE|@aw`9)hFHSd#O8l#uPW8|{}iBnSvQOopZ!pa{q9x8
ztQL}QDWSnYwPFRO`UIOq0<GGuKqQ(;GQvwk^I!QB=M+qF@kStWiTOh3`$r=WUO_m&
zaK`!e*!Nv-NX-+9S98-Yw>)}yPBtB;Kd09|uWksuL2I#3K-9x|`Tj{M1cBJQO2R`N
z-8SOFkL}t1A_WJAG?EWN<HrgH#vBd}BnJAqxNnO*50xOHh2Y}vQZWBi{{=+?VtZJt
z3{R?P&p}EMId+ulNnd<`g*O65nV?E!DC$uq%xF0B;?f8cngx7h<;;DSYFDxnSxim0
znS)3VE;E8lpRjDrWCEq^g3mBADZdzr5aOOGOv1ZKDK8mjrkN`}-m*5QOr4FYzGO}o
zEOcCog<mH~9LE4}z#FqZKuCchi5!!bhi6s1P*B{c%3(p887g#BZ_;T2;#Z98aGYxu
z)2?ciY($F3WpHOe(kLgnpvW%}7X2DagP6XSl**A_3$A1kK?p!Cz23kK6U&?e_F0sR
zY5%2YS^8Zd*asOdp(<44yKI8MIOf1fZ1>lNl2!lDbDMe1b>l!`q{O~$7C4J3Nq>O`
z4^D|OtRzj=+CBaVEWs6{7@D}rg{$fa6yD64Yc@WtmaGT-)$uYLDp9sTpI5?Wh4=-)
zts&TA2&FdI<XQSapJOhY!c)_UY=eouobjMWy0npYcZMIB>Yn<Gs^^J8qjF0KIOHON
z^Rk13Nss!<#J0F9T4c$ZvIYyo%i3QfVk0`FN&(A3aRkOwA5SVx;ke1!!p;c+x2|9I
zuMl5HeAb55d<^5(Fc0W=Xd14a`9+z{Y3^EJlC%h3xdYN^ol;nB6HmT)Cdw?d`6@po
zS=z9`-_gQ&zxO*|KZqmw7;um%Gsf9SG;n{j-%N0wp-P;(jJJ%eP>VCH2=+M(oVpCR
zl+&25a5WdM1HBpSfAy)RAuFk$xnVnlWWZS`2m_PAr}wPTWBs;HO=!m6xxn3PV=^b?
z2rDE6khm5Lw!z|1uKQGv)i5(m;+BYKwUuRJWg1RssF)61#axnQ&kxtSI_r5Mz*r}n
z!wWHvYnQD541|r6V;nBGcPt$Kjp>j>cPeeQznnTylwI$4rZyQ-iGJaVBgctz+LTD$
zvm8d4Ze4ry@62#kzit+CRu3V716E1X&CKT_WW8JFx--6C<l0}1$xvVmFPBDDYPI!D
zHqY?3cY{aUNs~INFzWS+8cp6rXGw@`B0cFU=v~f_X(4#Ib+DoUO%@mtq(0Hy)%Dg(
z+T~TAs2*@@vgAIW-Y&TAd(5&DAFD^X(;bfZBL`E#{+`fE8@J06s((OttCphezswFV
zS8I-|S?h+ot)FFs+pVAFg6m!@ixct<t-}2w2)1?Wun7j2wOJ1Hu*QjAknxJoS)ZcC
z8_klqx@R5GWTuc4OnB5R&vfP*mM*cvV?mm=vMAktrNV?2ig3YhBQ$2E%)fFM8y&Lb
z)Ai40b`DzLm9@ykReQgG)06neu0Y(^;XHuT4LZ?EqQ%OR^Yfwv9zYWp`)&L{om+WC
zl>wGS(3cE6zU_Gw=Rd9mL;3!Ybmc!D!|1k<^yGO|=Rbb6mZ~*B4p4rU$#n$w^F$#l
zP9>kf|6sMGtL>rFdvo;r{B(`vrc@Xwu>YemXAc7KBB_~MbHzK-5oqtP*ylXHB$aOy
z=<qA&C0gpVNI!2h8K2JDw9IC-$1ieC@pO+_dg8sf0BL&DbO~_$Otio3mE}|x=)Wf7
zks|LBpIZ>hT4x4uQB)|DM_}v}TUQc^m`hx0^$kbdTBP9E<on|<vEH};syVSgkSjfp
z|LJvXyI&ss3;e*_pD6{&Op&P=pH=M}l4=V4&;Xnr>AQn=i}E1Xv^xWNTJ0+<ozv@I
z>6?vo+XmcC>eT3@0i-9&?*PVZxUNjV{3lmu+Bw9D{N$D4?>7o{Z;879jJjh^gL8MU
zfM=Lct8YSUs8Z`7nckkMXVlJJl;pQPn}NpurlHu{gd=TV%_Rkmbm=8%ghGW{Xisgb
z$Q8<i!*}8_oAf`(WhEi!GzV+si2zDJn6)cz9I6x=Y`cT_+T>saQ`?$|2Y&RUU2lw+
zlLKB1(|h!j-S!Bk3n^{SIpgx=a&R{=me=UW_iPn+Gzj`=5>i|A6=lieHlRW!#R2Gz
z7~NnplsSX~i-=Yk{PC~h*&s{5>rUa&?eE${c)8MWxBLILMV>&sC0PObnPxwIIlTX~
zq4vM~3ID0hF)+9O|BQtu<ry1f0n{&WbVOmTs^(_Rg^b#&>a#IO!ZMO#i2Xj+)W_%5
ztX_3})&c&<bDx7M8D>)a50H<7^zJnps6o}Txq<0-2Al1dE;gH!lON38FXy{fP=pH+
z<2r@j0bqP6Y8Nw-opJe$(<}v5Y(Fv@t9GCv)Mw+_0`UuWOnFOV)JgDV&~S)yE)p(Q
zMg98KvVRLw`-$+Iv`+u(%ODuAN|ruFuMqm0z!OGSmgLuhdlil(p%3K2Lzp?Y8&u&9
zHx`Ac_*U2bgH$(wb(O@lj})cgjxz3YiKp_6e%rPb37xl$k(=tV^K2*)`=vPivgnr*
zPyW}=HSiaG9En)ec8VsDLdx%CrAkWQDSK(eb^P+d$6~&xTW#ebsk*Vo8*9d*sQuR0
z`=3>v!$*zK_xax_b?|qYdh=^zeklldOTjnIwl5oP_pO=jg}`xg!-h!QdtkaRXIoIp
zh-B*6D&>uBbUp}tJ_PP@_zZww6|D8`NDsRtwM~7=0OLgcp-;fAOE;0jxGFk8*M^LX
z_hjuDg{yUFSrvQALyAA2<^bN*F@0c+9{=@m@!(eR5bb$uz)Kg;x_5r)@PlqNlLQE!
zF^Am+rIcCX8rUM;1nqB_r!D;dse>>m!qcOEG|&gl|4(Vae?|EJgZTa56a4@Ev(bR@
z)CMGd=Qz%DWo>rPV^Dx8of6N;?(k!86iY}h6ibNDi%Ax3PHvL4WK9OTHG+E1QikV_
z4nUwHAvHmkqS8y?<f^zBU~D?6y>wN)J30Y0G+b6xfG)l}Tue9<wk61r&SJQBKCj=V
zId<GWX5P9x?=u$YfYoVs?)&<4-eyDi==xu7z39FK2lW2ks=fXt_yYI27}_b@>3P{B
zxCMdZd(4CUJ{{oO%UPQ2LEY24v*G=K{I1>`(fufdY`7!f{Xngu=>J~4Z4dswH{kUy
z-h-q2+6Y1Z&>r}Ht%dx)82Wy@h56`7|0q)2Q?q#d`{cS1(sJvJ<Q?F^3#3bh-1kDE
z0KI4wPKtm2JBU|#RJj^eM#h6BtvGBZBuTL_Y<h`NXKH5Fm=tWBnqYa%vZ+{|=NNTN
zJ57uS&}~@9A4RJWgPcR1D8-_|EJK?x;k8PAqxe|Ft3j>ydMK%}pHNgU?WI#Kk%q8Q
zsEwpts!*g>z9_|_x5&ym5l(bB!7b7?PgT)buNhZ$H?AqO{8p<qo`io9aY)&w$x}U7
zI2>}3^ocME-qfs`;8Jmf(^Wr4m4W7#rPgewcoRSYcRp7-rYcj7CSBFkuj*Nln_tO+
zeD#C_BAPq%_=43ZZrr<L11mh0+rxrHAU@b4n*S;4DfDLTSHg?T491jERl62{dc#_f
zCF&B&G&B|Gi?nVfO!JhT`8fDqnW}G;{Of|A0EpN+kf=+7Bh2?~$0BG_+U_aNb~88e
z6kI@{P^^|)js@(Y!3hgj{LF!!54~xL)=_n^hs<IKt>B;dw=a@P!FqTU&QEf}fS4tH
z+2AQS%9Tj+5BNjl3s+T;{m!H=)3!A@(Om97eNnJ?hrb1#^X7x_OG5`H-@aFf4<^BV
ztuTyjR5Kzm^!=puhS+R?-~%}Hq>e>^f!ySd$>2LGAa@2DY$<{thJ77MRo0Qu{|th7
zOJ*-yT#VZy$U}vifEga=D;DYciOYdxK3>>==`FC~VC-rdyU3CnKP(*{#D^D_6V;2k
z%{^Gt>M?yI(w4q((>ZB^)=HKw=;PC56EZ%>2ZxNa9z9;gU^22CH9M<r>|ZQW1cl9z
zzkgAi`UZ^JJJ+OHfW*F$n@5u~kzeKp>vZ;clriW=nA6m%&Z6pZQMV>n7qK-c{1r2}
zrDLs~9S%@plT-q!O!MFRfF{WV6Th0fV_y!$7NWgWQZBHWPyB}C7qco25*S>2!3LvV
zSi}sfksT-y_AZe95Vf&g&^=cTS}rCOkIPvlM^sAK=BBn#mCE(BzL;bmvYq+l<M|1u
zl%e;0Rk_WbG>P2!d4-ek&D`@#fwK4)T@8E?!U%d2bsxK>C6lCc=keu@3s$rFe2I!J
z)6?`uBxT61=%cefZz}788$TEJ=wZlQ^p!f?=e4n&SWHNbNcaYtIlOv9&?$`j=8-`p
z8++9Wh^0$Qr*bS5LhCa5RjWW`(gL?+5Qwl=w0kx!h9hyF*wAwSc~MP8>4t<+3T!Z*
zO!Z4$BW1362F!x1u>p*_m*ZR)gH3bN&2mk60GQM;xvGaj*qXRa6U;G#?0Wrk(J2_$
zW@eI*ZZLg6j?po21uDL3Ce|^7{RP`FdQ&D=`x2v2AG}9YImR+_-zMy}3@m5B;Ky;(
zANkI6^oFOr)d7i+s)?^dLv$A*C$ssnXEodR!m0R@%DQ2PC)^41$;g{9;e_4u!Iktd
z)0b<<S`KPYyf|TI{c<xB+~dnQHS#P++(AOTntd*6<MvBrMy=gYt-V`qyHQ+iBzZu*
z-Hj$d6FE=5e7^SUtX}NdV!mjCw@uepL-P%du)-q<*pI|0qAYL1+bxEa?bM#%+L)MC
zVRCjT)>;O*9du~1NX%U$(CG|CDj}d9H$HZEoIAWDm&9Ymxt8O7xk#@L<^nkmNXHu4
z-_|O-Bw>;$>nFTYlo>?k0F*`C=q@oGoXnoJ_z!Y`yvTjFUXAfvicWP0Rmb0y7A!m+
zcljuEv+@|+sZGRs>8R_TS7*Cs^X=zt2?go63wFZ1rDGxLm5yyXyp<DThw#Z`o=lP{
zG2>a1!#bSZ(IrlAsh*kgjCY!JsYa$~#I<ECJQeIaH0sQ{D7goOZ-KNgqh0<oD4Zt6
z6~^l+oZ0d3iL>ucZ-v56Z;77i@&yy7hd?^`KV`1jBQWjUBpyz0mG#CIv<MR?pi3No
zAjtn9H{;YbPN#F{Pn;Yn{5k)5h}6a6UPPyxL~r>pkT!;DT5s+M%1tq)<WRxnPJMJO
zes^pHs=Vg>o~3AJ<;eV5lge^v@k2r;d+tc1$+P^bQZe7#JO_zNrE#WiHnDiZl){cs
zRb?F~ETx#+;6O)**#eewcHszzQFwF-puPqWmW>*_@q`YhElJ9M2P6i$Uq(B+>6V?Z
z8Ne$-=$RLmEP@kSy!&^Gdrrxo<#OULM}|~`lJ^K*9y<W?nA$UwY>sojt4FC?Ic+jK
z^v}Y>l0xqGC$Dx#?>Wnqh^U@Zm6E7PTM6{ki>K+V^S9^B41ZgLGueA-c<YeGz$KUy
zDIr->&8}fY;oALc%H+b_VCeu)mNIJ*=0x`EUcL@6`JG+YfwlJe!|H)~Cno*1!5y@&
zYU9uJ++WYwa=gte3s5L`Ku~MJ{M=mHthaC32><g&k1TDlLZq&nEJs!7o<PwR?wtnH
zRe=t8>)oft7L`Y3))=56Hr_JS)%G`XT-s71#M#Pp)#Dlt<WLk2lc`yc)vJha5~a`b
zXJWEa@s4k>b}}JzGd9`YvgRp}f|Zs})iOSE(KEJDZc>r>otl7VTb4nblGqH=y>$sS
zr?jZvmNpU5e;ikAOKlwpQtVZVH9^&L)d4P4S5S^3+*jDGc67EuBT5akrx7@6?QuST
zL-bOZ_Ck`-hEH8*_=A)y*nuvb@s51cVPG09q@vm(TV<PWvRg(wH=f3Q*u0N=IC2v$
zkjYT$svBB>D%UZ%C=NW!U2V2wO=<5QLvc`Tuanfl?zpjsZ)%(UJgT<6{K9}}%6VV|
z_b>LmN**~1V9V}KeLg|ba2|uhA%svh1<fx;I++9fMsAYYsCKy>9?LQ8Fz8g0Z&o3g
z*vpQjkt0RbUS54&K#zJ9ol>7{V;W})aJ8R7VXl8s9V8dm@r2g&4#BkT63@yu%&~N^
z9(8+)>tZbNy}Q}RbSv8*mtA7P(oWA`3`*fEvA2GtggJo_j7xR%4p{j^&4iDQs+|Bq
z)dELeoMH^D)sEH3XXW*C=-iEpAPf$Um(wC!>>d+Qu7V+!_ps81A#<ax)_!2GVu7kr
zSN!!Qe1GnsdW`o+&XT%e2teBsnVq^dRp-mXvD9XD8FY17379_0{YMM{S*Xg0y-W;o
zOgZU94;kg1lAMZLXmVqzGjh7LoonYdy(jBf9yVh}R`F3a*|N5@v9aQtt*xkPE9<Uq
zxZ~H-@i0{~Rr(u|%jiN(pF9ViWPtKpjW(?~GG2Nn{KG*;zI2`B8I9%b*s-3>lHSO#
zlx0`@raEU+5`tuD=Ohax^gG{jUL(u$x7TH2r5P~{YM#MDp*{N&TxqjK_Cas*axzF1
z*9K<?yyLQ!xpkuvtNB5&HQ9MFHVBAGs&mEk#cM)meqI@?++f2s-uPoB?jF*{TzeV7
zMaMyD;4PP{_eCcP&tC)}b5M5JG!HTNrh%1e=U4NDRfqnLc@4F}w<b2_xT1p^!z>n^
zI_F+|k(!_tKkT$tG>z`e>g34Wq@7V0gcqg5+=B!gZ7!uW`FuoPb%t+){8<An>Ev;v
zJ*az}j!E%FE<!+E`pq2L?jQyv==t}+2FRyGRT*AL)}9&c)AQfu8aQe`l0oz_mvX3n
z?=d498=<5uL$uQuCzD+?GA_n0y_lFSQ=5WhAFd?L{s&GHF?lI>5XGR-3@$3X!8u~%
zVW11-g0pH=uM4^e&63b;2z}S^fhYA{q`s((fy5rgBnhN6P1^ZnjQ+C5WVJ*cIqjUR
zLG<r27f^=~`Wt~syrB<TjtH>LgFh_WD5p3g5^DBSg5h|>MJx-8+E6(W@p{2_8h1y;
zt}FDCe?7y6h7i$Hq#bzS_rj^ik#`WQ3w!^R)HePAc#&@wHXBBoPedmV9k_Nh>0?y&
zBApWpP%7$RGHM|<YE!<S<DS9St8iR?htBj5QatWEY3jV~qHF$h)^v;|rt8rS(Yn)>
zCZ5vlj3Lgcw_O*q+5LR|)m4kRGi1dsnUi<`z#V`XGhopj3>lpeS|htN@C@|c4j!R+
zDtJ85<@V*W!|-}`*G#{6pxD8EBRGf@`nH?z$<FS`P@Yh*jV9>C=FQu~hkLPTl^giP
z<}KS(!sdnR49X3jkq?DV2d*3p7|Z35bt2dwzMM_edUc{aiJ7aMaF&Fz>e6=WtQ;=r
z&+9CzFLy^p(@}9Qojr`qIzLCMWcT~SlC4mANqGlrw3Jq9mq$cS!95`I5M981HgMF8
z@RxghKyjZVh(!t0p2F|1+`K$?c`dm2y9)|jske)K2g|DYH>Y_6TEko9LMD_Vt^kA5
zE;4pWc(9(tLQP)5@*G3PX*y>+0OEwpeDUHeFu-xZfOD5zre<?XHUQm-5P$fD+y`&#
z9g=rOA&bX7u^>R*mu{CK+N`MYASUh`!+cC|T=AMVm$YSH>Xp$+8NMAj=%h4s#CaBK
zgDXae*%J^FO!oSnuw72Q1DV~gmSAhQnGHs%LKI`DqXys{W9IPV(BNPQd>UvyKVwL>
zM_B4&15u(}2v;K|R;6f@6qy4?WmgEK&~@#UJo1=kh*NCHeyj|x0i0bb`K(I}&wVxq
z4%^5fD^>Ht&q#dfIzY1sc64{lM+dx@zjYXZHnC(=MlW6tBgdFRX5dcNnVUu$I;=32
z;tVG<k=gEkAcNr^YVZXH6Eag$@8v^txk92qS4u*Q)jqLP;=!*(8)~i4r?;BCBRZq9
zJ@nnle!=DeFsn>uqx+&v+x$*2;e}GA26V?$wZj!EP0?+JTQG%v_?6wl+}@$>K2?G@
zb7t>+!pUxVHm2XhkfiD&)4pKas>!~%Clm<JHWC~{Fk@$s1fbiTS-SIXm9Qq^NmdIC
zz~fhm(Zs=?%>qZ6{zSn>2QHXHl`J4HZf-Sy^K7%#746Cdzk^J3WgV3aDqLT=b?z#|
zv;|NlecaH;udk97Z$3eu<ALa=FzefK$*AtBSGNveaTN-kQg07Ig@EkD2jdM{({45_
z5N=MCYkNUcZz1f9!mAg}?7J^#BDZ^gBW^oDv!U9a``VvQs2_><F#Ord^(8rq-oJh*
zCjqFGjY6U7&xHL<`K%gHG*;Pf-?C33%@eV~4}yhrK7;x1M8Z#OuYXMYk2sG<GgdcN
zg*4ZKG$%3ZU*<zt<%b4dr+sW^pA_SY&2;)P-BV_W_EGx?XB)s9e6q!5HgrWjS;v|8
z<ASc+!tWcYReJz9pGVeq<_`vg_ms+2gjG$LuESrCRF4Z4hX=lWR*{lJE>1y85&@Nk
zQ%Q6N68Bzv<dd`=^Nc1`!E;Q3x~dYY#}8hjb#S^p`ha&dlf9M6_ZG%lgQh6R@&WbX
zRNnMKaJoa9%KUJwe^3WH=C4~j|1E|i6ssq0|FiVbMEUhg<bURm2?I<Fevk$KH=9iD
z>_7d|-(9t^Bm+dsmQ6&<l!OBQrA|;HNFoZLXoD72S4ND1eiEdzq`uA#@76C~J96(+
z4$y)gvKJ>`3RX86P=s-yWEOlR56K-L+c(=TC(}FMA75m?@E?amqM7%GkON6({pJLs
zw!;x(w#yL?u8R>5uF{s;h(tdT8_-sa0(lbQ!Fo#Jk<L&<ZD|&U^jLZdfg1kF2=~FR
zM(fb0Km-f}_qotQ1V(BG85MoW{>DHoLT8D70F)e~G8xUlp~4enjF{t+@#>OI>Kvk+
zEkGMC>LJvCMDSoe5xc!K#ISsbcym9GxRE}w0MmqAs{B|W$-sdSrjbB_OHfEK@~{ZX
zsF9A>gx>Mc406scX!BH*8TH_2<6nr%!kk)<OmR_KAaq_I%TYubjD>Y+wCVy=Gkh9Y
zuCB?QmK$Oa41VRdv!4l@>|$Xzb#BOhGGp`?YLs41)>$hVTS}crbW_o^(pKOt7UVYa
z2S%+h0V!l2gG3l_@vo_sGd4V`{Ft6#$-Jm~N4}M}Uq)tfAtKV-%KDX?xu6tEifP|5
zR`IX46r*E@!BZ~huu^*xoDyz03TIzfAv>9|8C^0;@VY{_asv$$bBA$w9$`wfRG5fl
z@n+iTX1bUxlc1p*<~f5Qly$g*X)cu~%$_X<VL5hvE2CQ`ndR?iFn7uR1xE<1POPs4
z<ZOdd-1&Sv>mq63kBRR@S(o=fBCZM4Epg=ID-omSrV=pv;5g59x40mflTsx!cl4Xq
zt6XEnuEE*;bxwiwefRL+V4GZqW;DU-!41_hREH5<b`3o~{&IJ*(+6{oQ_ysJNb%We
z&I-cGS7BLJiFrbz<I0P=GMjl(R66gh27;o$1fXWdTm4UrEd`hW9g!z@{(%^P&cKvE
zokRyJouqqCST?&dSP1$FkuA0={TqzieI3Z#33t4_`m2Ze{$s9)8351F7!ptF0~Aln
zff#hGoIM9<2?mzfyzOE?!&$b}ruOEPg*#%I<T(<_u3@LE`t`(T{9X*k?m;!i?qN2^
z8USu@3uE`d3!`^$3?qC#-w0@%td{LI4JvhtdGD@E25A2kp?k-c0fp)6Rlgw6QuDqf
zkkhZ~a}1#a#ro&Ca`R&3Wb85MRcDM`Fg015*}tg_ve#V-PIYqn>^=5>h})#WI<jaB
zlRe}77--TN+d$TDX4G;|ML5yN<4CTa4S5tdgy63*Vwtw~T)?zq6X)#D*u_G0eGb(h
zJ<HD~TiPBv3z2mxuF!rsf&0xf3(3Vym69D3*D^K75deI{h`}T}?Q6~LC&~4ibKx_S
zUV)b}F*MH;t3GitQPev8EV8n@ijq<4EozUrT5An!9uet<B-{lNQ_DfHyTa>;iiJfC
zE$(XhBF<wylL;L}&HJu!3rLG}%K2!!IrGX`(dW2?=E5xOXyi4hw$NG~#eHp;d-E*A
z@=c=a$wb4g#Sf;**9dS0`oGYgwuevBVj5kKl#)ybo}xNqDO?jh1=rhAqcm1Tgdl5m
zWFMN`>06$#F&V>+Tc%KZ?$B3$KR;QiZNt=_qZ(&HM@bpX;wsPfS6atErqLR9XwVxv
z$S9_iB}`5ii9AjbYUACEpPGs!4uE11efozdbC+ik_Xt)t>6|;6Rmfaar~H?Eg{;%O
zOEMPA=LAl2E&niY_&;V~tJvu&^XEhSwNIStzu6IHs3n2>z!Kv(ZOGGv)^Nv92&eM>
zovA<?)$4xIsW5Aq;CJK1nkt~#7FL`nFhyvlE7M@5jg;poFx^6&&n#~>JaMXiJ4NYd
z{t^rHO){hsFbjzJA`s+o&cp72`oIV7{K0n8OYln9ze}{kP(Bm-S;s@*6(%0@2F}Vt
z<QwVZaQ^aW#N!$b!Mq}=z^{iMO-tHptPdH6yZw+dks`TFLQI~8BHc3}cmpE5%gye*
zDya+MX6&CAA|`_GdVHL1;G_=$-v>+qUq9`p(@@ABG`V;v1P!pxgNtzn)Nn@8Z6Kh)
zWustzgfnu{3mD`;v1*;z67c-RsBH#?QCIVaEqXB}2V2f#5HbhB0*YQ(htkCB1&2ij
zkTES<jpoy)`k|AohFEC{;0ox$I~m@PM}ayab7Mf;I#o7nJ&u}JN5_He<x?Vd`aM;#
z&9aBUNhv37BxhJD%S7vgOQGcv)V@?ezW*{mM0W0Pw!i;xNro$FrUrPVU%$-gfBj<l
zpA9t$>!0+fwSlFIqq*h(8zR+&@Wfq8`{p$-(ufkJjn9Bx#Uai}qBh^MA^~a!z)U0?
z<Fx6A8#Hpo4{Ki0HV|WE3L=Z!3X1>!xp#~gv=xK~N7fL8`V%!Mac%#{Wo*lC<cM~q
zb(>Di_UmRUdClYo`uje?`FJYh#;dEV#pAjPLzg69<%2j0e(nPLvq%!~=+5%#|5cv;
zmF}$}<0IrlMe9>CyAyHdgZRs)^fBg9j`EY~Ga~g}E$FK%-DI{WV#0^~F=zkDCv3t8
zCiVMn{=1wx<4Z12&+Y76C0)*j^6_sH`uqiDm&i#)+Gz@OgJeXj^pX8@r~+7Vn_`iH
zs`9hF3R+Zc`MgE7s>T6!kZCD*f++>JRuO46S_&r+yVzbEWz#+P9lhQj7-iL=dk{wW
zJ3zNv`-sXlu9X^n)NAPjURN<_E(w~gbWyg(!;Rv)6P9zYLiyRDASGjP(%#Oz`WW51
z>i8F(f*V-P<2_}P+5<Lu@QS-zmaF>B5u9%K`h=CPwOU(1jUVu<CXjtrKaR@zi43&O
zvwcZQOKE3PM_}zrMQ2n;SEtUVi)))$?8TFPPKpa<r_>)j()}$;ur`H1bUVM%pI~4*
z^KS8zUha8=UZ^~YAIA!v#E62Iu$B+(h^Lje8y?(?*RxAmP(wo?R&b#og+qd2E3(S!
z2O?9Sn|$xsu8r;;MTNi@Ch?gJAETn+F_-bZep`+X3Gj5vwMgG(rarC?kj~a5hCZd@
z<FWz|92;o+w^xM}2>B`Sm|*4A<szL%uLh&d4R}~F!L~O<6*Lz?TzPX@V5zzo(~mnY
z=J<&th!ikD?35Z@*a3y5nDAH5g+$Vba+{?wa5ui-&Ldp-G33HOp4UAO8)8Z-fpZ-Z
z4>J%J4x%g*3%OdQ#SwN=GU22iw~{*wA?nBj%0thRdBfkAL#=@NHl;<e4;y=t5E!gd
zs~x2+Cc}qeCs>16On-Q~%tE0p6JU%pVDZ^D7<7!2uGGoQ01w`2F8ilAE(e;~>M3oV
z$M$q@Ere+OphI8^@jZ}O=Zm>qq=qRo(0t{m3?ZZ~{D$7cgOpK$@WUEMwsvYWtahtk
z1M0Ke9JZs7>sxWIuq~xY2Rm4hLah+{sRT<P8=OuZdhiYEwotfim9ce{h)K+oBvJgj
z<5xtA2IrUJQzB%!(xJ$R*>SPv#k+MA%>9HRWW`QH5qp{t%9@Uo(NSv>+!&)cV2eQ3
z;9$dvX11{!v>VT<c3OcEpyvx>fY!kxS#9T4_provt_XXvFxLi#@KCeSzO)erv~H*|
zi_uXhh6?>a)JEGf+T@B5%Cc*o`2h>VWDbjU^&9RMw22wom-fI53P>i1sdU4+M@}ka
zNao+R=B5r|`M?_0job8-`?gKZ>ecSZQplD|kf^lXoKlBUxf1|sC)_OqE3dlBrxNr(
zsY*)AkucMe4tLrw$lL9RS(xDkr_9nkmfPl+j`zL>RzMXlI+Lb<v_0^1^_dwlPX~u^
zv4tc=`^@M_0bGkMVi36BVjD_GF6tVZsAS?L{)`Lt`>y`P1ooi}Rg_r*K{ld$vQ!9w
zsoG3JPt$$Fb%y{w!9U@Z)D_K#b&vhvRe$qfCDNske!8wA)XYd5PTdc}kd+CsD_Rqz
z-@&k4Fq}SspZ?8L<jYqK@8&8F6M<`mM-5Dhj_P=eIHm19lCfddl>%V0Zl+Fn%-5bz
z@8V>dts;jlT|=X?d2HHj(Lv+Qf(9V)Y>Ux~kokw;1p|2$$_mw2LE~}gCQV#~jZuI!
zwP%w1sWo3)h4RgyS7F&THvwYKm?O_;dki2!{^o`HB-=>I&T;s^b^hq#9y9FF;!Xc1
zu4gDY(Nk%M;8))`d(H?yLG>s|#T&C3fvJbR;h}Z}xmhwaSJ{h`@oY!y4m$JO$(|11
zPITq+-y1Aezlw?05Ga^HmCU%>?r#n+!X7$>e--M640grd8HYgYmO0qa7?~D50D`x`
zHT<2CB%^sCFbqhQ2|_UE?l%Y$V~Ms^KENa}E}v)+Sa^kJWo`x?PL5}#!k&+)x=U@v
zHPLDwvtMxBsKtj0f`h5Qiz88C!am*p31~9VTu1jdn~a_?Kk|}Qy$RD95&?n+_Y1Io
zmetgssiWG^0T*0vt(OKX(x$|DcU)Lz+eLRBZ#>vLe}rA>dgKboP8Xni^bR`S@T2&8
z2^L><zhe7e%s-I23Epqcob#c5ln-L=Kp@-aJLIDX4rBg){1ClJa*Q>3qOuhZLI(eZ
zyrHH~o3l7$^Y!N#LMN_vn}3w5tM;%lB8TCJy&CgKrfcz2eWVV@JfL9vr1KTbwVZK5
z`=}nw+$CU(Kt8#7Hy7C8GYt?bcv!S2(7>5^Vf$p~%)c`G2<*{GRuJubib;E{rtp5m
z%FF%z__Oy*Z~62OZ~5&{Rc-n3%q^CNbH7mm66j6?Hs8q1-w&2APVzs+T3{n~Q6q0|
zqluTK#xo1pSTG@45CzMn@cn?6N5V=bp!gftqJC4B>|Kc{y<Li^p1z&QdJDf(A$!dF
zNLOwRGLgj2(C(7N@E~m3o9?-~)+-!(PwAy@puk;yM{4AIijVkVx(B-`y}fs|ujJvK
z;{)jpMUA<WL*pE*yCFpf6VM}0cpoOB<^p>SGEYJy`R1%SaR)=ugB!>J<=0@R5zHMC
zMq2}HhUlRTof%-*G1_Di{9>7sU@Lb|b@W-ZB30(79x{KQSiPzHOQPxDXkXpKe7g=<
zWvgq-3{})f8UvDzv2A35^r|Ks$$(2>99Xsdsxk3@<Yhl>FhaqB8(N!Gi<w`^^twz#
zBb~6eD^SJ2Fi&HmRhv7Zk(XhkAsiB}DVoAm^dz^m4=3Fd2+`}lof#0F;-DABE}J3I
z#A`ET&N^TICAb=;fnO*Yfy?u%{NKOZrEno}W^K4PL}fRQS%kNekIO(`;q5LjhxngG
zZ!us2HET(utZBjGc#<=yA$;}Eq(B$AVGB?dBe?qWpF@s3Lo>!UN`tJ{*7(?l-L}HV
zJJ1X&0>RaT(Iu=xZeamDc?JsUxRe^7LP$r_gOs)_WV4}Vv{anuqHQcW%nR(SD*Qs3
z{6x@?^5jxd5;<bMR&H7)HahLC{UM(HAFP^eThM6i-qHUW(9%D(|Cv94L573O2YV|g
z<c?m$^=|I!TiepJK~BQK9|u!U!fCW(?~)A1qBdS0TPJdhXJp?Ohit$=xZ6R?C|Iby
zhDhtAfMabES_DZe!=#xK_I=GGmdL6sY?%|vsZ-a>Bb#x-W*$Jspn8dCdXQ_CyDvoA
zV24iFe9#VNyc!~24(P>VCNR%w>nxVP5!Fujkud$mUO}toALH2paJn!YX<u@GSkdNK
z!yfZgWJ4H;7~8<%6p(Y9(@@)+6V8}3E_m6f!7U^af3H0Y-gZ#nIwQ-d-TP{e`aAOS
z6(|=vr$fClrTpne)l?7;NU?*yXhbb@;7!E$nG=(_P8f0AlSS{cJfXezsHKWHB~Dv>
zEMr)3dXrASd2G=ys#!E*Aoe$0j&Bi1Up;H$!i)Z30nTSE$csx5q|s2)Ah~}G<si8<
zs}GzR|H=YUQo0kHkpA*Nh7=VOD?l=bnv-Nd8Loy4TR5N_qiA%~OcUg~b97mYh~uu6
zaHJt}a2k)QbTpi6HTI<0kPo#qxlqSri|;{WPhQHzu>87bJu&w_OcCMuKt(aa+S_|{
zxz-D;q^2EZ><&oLX}v)8@$1<|^7zw_cqYJ{vDWi@jSRTqu;I>Y=o(w`-LB+JCOgu7
zpHcA>%=R!dtbZkoCnNw?gy~vRS@zwnt><0PPRUBlBVP=*LMi44J$N<!_u_4hFv)@q
z^nHw6>wE_4YS@#Hv;EjA3H^SK9*^jbt0ZVY5~{$$)6fyZggR37V7gU}IqQ!%dH`ei
z0i}1B=%Oq>rvR&HI*725Bc=--US5GRE#fV{BE6iWMff;;X3_ojQNp1?dLeXicd|se
zF{cPGENXGe*v7GW^$T^)i?pH&R#Za!_v712`f!<hW}`&;nC?ofHk(j&Mq%1&>@I5r
z%3mK|kp={PFB)Da_-u}ezbBHHxyzo($5}uQ_!NuC^s<h4)i`5v8D>0I#jNM~8)xpF
zJK%H9;sz}OBz#kaMvi2v(|G{L%xx$;n-WfUj4lWVp2ft}fL%w7t`za;ZLyn>{LaT;
zTQV>FK?J>*+?!cR1cQ<g=eqn^y{^1&-ZBoT|6&CRzR+mA5=<rph_}eng6ZbO3T3V#
z=40kZ=#e?~;QNzO*)nvC(kaq?a-I7$%6-hk(fff@o=C2{W=D<^9D}5CDiZ!_FCLe@
zL@w+@-8ZQ)N9=KtnoD3^>FMe*2&i!$ES$`+(B<R?cPBT(YZZMz9+)Fc<$lIqi)sq9
zDL`z&%4|!r%?f;MiE@4glc&y`V$k@i;s;hZ_QDgC$o&e)sg^aLE0mj;D68^z55*5Y
zjnI!$!b}2^!{QOl0oGQ`fnO}3C>^0Ed(@CRV%pAk55iCRmOlbdp;WOu&ywH6=_Ms`
zJLAxV=ApqUsnE<Bepp~s71un6_N?wVCFXrk*Cq8qXq<BeFDTwVw(B2AYGpZK6`+wv
z)@|f;hZ}7}vqF19Gjs-M0lbdbt1Og|i_IUFspc82RGw6zHmK2w%`=y*EV^2Bo!0hP
z>O5t-FoqGSro}UA&{*ZLOt=EcKs$0oON06wp#{3}4Ys3NxOUe&kQyNN<~dP$K}{oj
z<6?T9<oezCAW}S`Y2R^CKc0jKcfwNnBv>A?FlE3pQ9xCCKYx3nQ(>;&6p@`h$eXd<
z@`;q>&2RO-gZ(3N<%E=!TS(ErC2So{IitE=h1~W*BURyd%V2K6VE$WZR}sii7$HAC
z3ID-F@hS%7BgmPzU!zI?!d+QI=_m@GBREq$DI2KIiSTWFVzmwi+I515k=vDuQmwYq
zh-;!9GV>2=onAsMMah}S^VhhSeEHA`bzY5t0*TmxqpG_!p3HBLq@vKSUxrGLQJ{5V
zwX%g{(Z}eB<`3LrR!WQTdZ(pbCYjYiFuH8AI1J@mff2WPQwNJ25?bS>62%i$*3}k8
zKG}h@2z|2%#0oj_n^ksZvutM~V>)8t9q{BY017FHF8`z>^^WB3AnGGKyUK97KghUp
zK%(+%>5`Y?WGIVEE7~4B#;dHdTkjcvTa12;`RB!F&VcUqEc;)1&QS~3cI|l@>Uo<<
zfdm6jcIiRBov`@Lu)3(e5LUh?j{T;A<TCJfW2|FyE`817)hpu76SeL%UI_hM<^sy(
zrpGFitx>mL{{+fclcWI3G78^7sGU5fir7_&blG-j9h976e2Fgvb1^8K9Mp07^sHTi
z9&&LQbzN%UM)S$<`kkEX8T3bAuoL~+VWCdU3_|V5hWOeRwu#JV&j0ZK>1@i0t1mO+
zzLGt9gw6lem+i|SGf2bn$RIoWmHuMaE&-p77%au)+%Pas<6otfRR_W*3-Q-xK-l5@
z?3uYnsnF<&U+;}Grh&hZnxsj1+yb3At=``%iH1llXn4#l8^#5XI>1=ysPWqxA&2)H
zMGef{KLx3?5*R!S!2!>=ma`CApxWaU0qKwr?7=6H<e@?NsTE>tg6i?TRuNScHB9{V
zE#VQumyF{dg(|&CPA*?Ei%<yhC+t!yt}EO8%$XcNPns%j>4>8I3$SFVJ8e>r1VpUh
zc77Z5C&dJCJ!J{{H&*1WX1Sjx5lyhLg4h6xF|VA}%s6tqb2)tFn?u_@of+y&&~G+>
zX_<!3TR*+o4yp?E1B8dLsHYyF|1%<~R9bt`{FADc`hmay4^y@Omw05Al7Jk_Ppa0W
z!^*rW-&dtCfNeu$D-b1527#FnA6p_2wI*gO4{zR?b-)s(`in@0o)q^L=!^Uy!-`><
zUmY$a>!z#4ru$|p!;Q~dR~Klte}dAJyCT>31kg!tq|>`V23+H@4l5{0jy-NGUbig4
zUOYI;zA0xFzs_SdY^(*G1j3RUD-(s9dc3jZ?IDyszZa*F94%H~F#?5U+7uvr5q+o{
z5<%XyB)k^QKRc@7+CaDK;xws3_p&JLEj}_bkIO0Qmy{iCwn$cx$%pXIxpW%T869*n
zF(s5b>QTQsLDXKLyn-xQz0Wr5No4=wF#Utubn9h{b0v7mud&0C^m`G>j5WP&r}spQ
z>DyZLU2nXnYk|S&wOi`BAhI#6flZ!gwk+&0+x}C#=MH>3Yd+DURKFmYND_GC+am=y
zs#6S|oH^a=8*L_ahG_)kxDjjO(oKCorUX)D7y|cg@RUI{;0Cepn9WshjVgEef>`vo
zezwf^9XP^T#Z3L%4r8na)ANYs3Z`jX(T=;^s%9T$jVz6^BgfD#@OBDyA5>EPt|}=#
zF~u}kC&v_awu$=pf1?1$54fbUK>YfZi}pW09{OKjgrtq(e;p4sscP7ws-W^@0Z64e
zNzwuXLD96+q+<!GvC)v=DE;_}{K#ARP3NVtO^Zja@kz+T-@9*G-wRX~{wSvj7KO`I
z)l2p~P4M}AF4Em?ukc9qbV`7gO9OO!UjA)4%xrC6<$Qnc;rcec5`~W#&fdDh^003Q
zlA+J-OW<ek@12onhvh+yxZP1B%-r32qS6h{`ePWmLeV`;Q*n2W5B%lsoF2g8?i?G?
z;_lpvbh))gy%D+V249~Id2n068pp2w+uoST$Za%lJC!9my@*J_VT{YFs6m_~5#<q`
zG_zS~fRr@~4zaGiP#1X_c-ESnwZqgY63{FoG!dKS!b5x`gSnQ!2Kg;VH3olzu#UYP
zy(&uzK#hECOiOQuUx+2W(%?!M#{wJ4q%59VTqYdY(1|BJYS(#$7O}}Rwhs>WTgSAN
z7)Lt+4W|=Cl+nnTM%013I?KOUYolRuBQ`B^S!*V{iNe}$3|{u%b48zk3>a0Y>NX9}
zPLjEzhrUd<qe@`w%onm=L-g*jtHwFGwj_#7_P>h8$0Y^`IVU$Zs_aFoSBr^NCpVYZ
zg*;@ZG2j6$k>-wuLu*#<u7V}N8i2Hy+YXPvldPsOMJGlfR2Dz1*9KoxnCH0Ku$i7-
zsXWw{*UROwX6hUZ9SY235>0wx6Pb@NbKh%_)*;eKSl?)g!$*ZDu9?Vzb1c#u%cbE8
zQrTQnACt<68Do}k0Yshqa}$f5YS+-VGbs{vJMEDIF;by00IJ3XNiCf+*wr26a<Z{T
zo#qod`Ud0cTEjfVpT7yAZf2v<haeO(XKi=BPf7PTlNq||Y?lU6yc{k}jxwh-lNJ;N
zVbKt_9P6{A11p1}{v7Hw;q$KVl{23e`nVjWYv-uTvyNf_sPZC%ug9GpfR;LGv~;jc
zz4rYLR#!uDM%hpr;_lHlHNvG@$Cx{oLXydUOq-PXvb^()cA|QF0rQdHSy)hmHy{qp
zpQ?x_sbgEev*nc+^!M`<II|VV%@F{#JC4;UFX)>Vj%<kloMR}9DiWjOOcO1^9oVDC
zrxY4XNtGQ9Y(w00?upQO_=C_Ss$*2RQbLAF=nkg+*nNJle4Evom8v}2h1gX!Lu_vW
z;6-0|YBg|Tf-AcpcfyZC_aBeVk!KJ-w5g2=e(K-juGDfObext5+4ar=<SI(X?`jhu
zxWBZI+sh1rG~Ax0gq#3;=5P(Uk)l@V5qo^qJxxkbl~%{f5pcY}^tncO;HBo;rPmeU
z>UUxao|Qk#vGM~8?E<4e$ejPwUE)K$@v8@(IIRa|IKdeZhfFznM-1BIsC2QjxQ&au
zkX0sRqatP$FG_dHHjI4~HG_XBBK?Dc6~8zCsas2cMP1)g+d<hcH{s<kv6U!9D#IL}
zUd-QGit*FH=M=W8UthKPvjt3?Idp}1cbSP~1_<XY+C`)Ac+?4Y_V^z=wZ?lN$}o_H
zgq!BDtBqKr&3x@j5R$en8D{4bh%|QUO7%F+r}xtyqoUs7R=WFue3HvD>jjIfhGv*|
zg{i*eBRxG@^1@iz)cY)9EoS8dc&zgn1owMESr=OS`Oq;(m{{ddm`F84w9KnhTvBUm
z{;~d3poM_;A<P7KCyh6i&$;}DlDYel@w0pp!-wS>!tpE9MCsfS#a*VgX6SVbj?DtK
zXMcEmKO5bBGdl>j*nOq+V{yp91`1;$Hta(5QxUaU7>uf&42QKZDq2ZFSKK!x9)K3J
zMhuyS>sZ1K?t0*`tEQR4X05Y&prtou%f)Jm=@~?NVYgC0(5FfU{leKwz|{0yjCz+K
z)+BxxNFwTh*PVc24d?)k0%_K*-F-Eftx4hQec)*(99|qR9Q~$4_w!1fjn2c1fjXqs
zE596fjrBllxtm_McfKOxIRI1{JsQ73{+*{vH#B^~GW@ViN*33UA{jjmN8c`6&NpCt
zo+alhm2sY(fQB$n9CM)x+yLygB=*1P+x+e<Tkn2e0GRJ|qmVopz`Z{!wAbx>*yZ?(
zYm?r$#gBd_enS)4rH!hQJUGD-c?ke6OHl9X*j@Acu_^+j>KcGgPe$25UBi3jLTCe#
z%^F&JKJIT2#;4@h*9bS<L=DJF%T@Zb>TfxUY_XNfEhER*UWvy(lm{ffKDDx<DnQZr
zaAeZ)ghdsq71H)=SSFm(MPWje?<^Az-f+ggbOR_`P)Tod=S`y+^Y{|Ol2o9@jQ9AG
z`Z*5K`WZA{>56Kj`f)L+Glr1Yz<d%W`B=1jbz;!?K*a=%$0Wi=-Tok9WQU8V2nV_g
z7Az|VK(=V8Y7ZKK#nFa^E|-(s+iJL){@xVo-{Mm=pFi-RUOLSWvp=ci3zP3zZm;;|
z0o=<4=Bo2zGR&FZUDi>wKAW5nM`eM@!G2PVUuYAlXf-)|Sz4duBn6eHqtU>MpSM$B
z=p6ZvJ0agjC=dVpzezLRLaGj|A6XU#`|B6m|7`d5pDSJ&16xIa@qcZ<iqx!JP()C@
zNhLZ+*7%F^@_ifSCF7H=>$-ibAW03C1S8<86!mQ5r4wkztf#NRKd<R-5ngc?5#~oZ
zaCsjJxVP7$SZ~(&XU--sCmnJ;PSUts*lNDs-obod6e4zEttnqg!dWWC5PM7P9jW|h
zY`OfoUb!PN=aB~E!ggUcqxPjNh2w^b{XObuM$@!WU+QQxXrQ)|VK$)g$zQ__>~+{2
zPtb+v<2H>Ti>BiB*^?IF>Xu5;0-s_r%9$NFP0`()Vzk;lt!08U!>ySrkEJUr?>OmH
z16Aj86qOF)YtjK#!xzcqEa8G1;tnUgH8-L2)dgxRnA7MqeR%oxIh%I43Kd-D3$}wZ
z@B;_J5X5w8CS6hGE5<Y&v$+K60u)~-e*xNRusx43F^~w%{kW$`!9#dk%*!8)rc6Tn
z1ehY??#Al37%)QoKj`sjB$NT0fEj@eW|;YbT^Z-Pr#=>Pq(+EjjpjhBiAd~sOuDG(
z7=uyLcDBmpjeLXFeJZoyvux#Q6U_U8hE!mZocFcLn+6x5Om-43&anyJQK+g7$1}`T
zULB{9(n5-f|A(<}2of#ql6+;`wr$(C?W$L{ZQHhO+qPfXwyU}p6VuT>F%kdf?!L{9
z69;)R^Ds)g6L?a(vl)0Ack$Y2Vf{_J*9n5|?UAU!xp|dotRgBA|7WExVy~9kPQR_u
zmjd^uRAUHg%QO`eq1_)7!Hp~VSrftIRlSRa5?fchtA(<&=ZV6%TOR?XE`M7H850mt
z5P>)WN$KDdV_=h)iKD<qBc@L2L`}i2d<U$8Qu!LT_rBJgo*-l+Tj@|(WsL?a5}#n?
z-t{hwZL;T-gfAH?%y;yGT3IxUNVTJ}ptQQ&xw5*rE0z2RW6Hjl=03U*%_x+$g)Mb7
zjkp=m>mg*D545<k&oWW-Bup3IYj`?>x3MvO6tW!jqZHJq<|$xfxQ5bgYU%#hk(3T1
za*vpzbC2+ly8A5k{d~i8J0#_0hc1PHQbz%ELhSuJZZO7~#S(o$Qmx$@O6&ZHFYb+&
z5%O~6VneY7W52Y<2;1#nwn~g*DC^k@g-3JLn0#%PK@9KO4F5NUe#3^mXG#w9ImQ!G
zxtYH29KN4xS+*0I*&S_j1y~<PRw=JE%VBrQ9ccjWH3wj<q6{!b4uNnWL`W~aJMfWQ
z7Q5i<3+=y2>#oK&@gLk9?MODEE`amW7<dc9i8xIwL70Ny8S{S1O<kK%x2@1!JKuS{
zZO(8@AdKDrmEmAPYAAyp<J_S8xM9Y_&9M8tVI-VouV!@IHiCLUeMm9VH}w%h0gvc=
zsr>;hgPmnwsB0gwlpDWY!zJ9v36$#E1A6t$h-WwE*aDdtt@1VRXx~NZ5@W$NVvhun
z*)6g^`PHelc9}KYOne_sC%il^7SXsvEiMxXMB^Hs*e_OR5{o^LSI|=9eHov0@aKQg
z$3#osXsUj*jrZ>XkpIx6SKh(a%)!LbQPITC*5UtJHWjOGDq@KtUur<m;2T7>K^Pj+
z!lELI_Kd{zqYL)!85%){u*WDhqiP8XXj)gR(!K_M3ikN5Dk~<li{L8GNa5ZqNO*__
zHfc-aQ$(z<r!#GPd(2Fo&-VI!!Su;^ZAYn2vFrijjvqTBJtzd#<7bK>#U4FKAWync
zdQvHH4@xotshKpI?ze~k-Yf?+Z8>~>j-j*jEI&MAOtCa+y_`yE)}U-pFF5jeHYKq%
zTdBH#?mAHYJc^igDe3sDjeqTEy76*V;7Lzu_oY`4TZ=DiOn7tnCE>3%{y>YXfd)RC
z#A@xoQru<4SB|W=`7h(Cqc8qdk-`#Xg@%r9=ShEUXCf8k8ryK9*C4Ukt5SXf1U%QH
zILj<`a@MN#@U2Cxnx?WRdE3XT9a6UaEtp?v{h4D=Eo>`Y`+da2$OJMaakA=N_un{0
zdVB+H7+x-#`OLa>#XuGJwRAOFrYrVlCWZP@!*nrRz*?hhF+1<Q?kFQ>k(Y?;7@|uR
zAy1ndvPj-Vom%I$zuuLYA(>+0K^5b1SH>*I)R@uSl7bH7xz~cKY~2+w(QNQ~+=C>F
z8h(argYNWVj1ejA*cXKLX6F`3CHVpHPyqjnghl!8Vfs?V@0DMftpOfYFpFiHLkW8p
zcS+7Cehr*PE{)Bn2a-~&eGnwV1p#|ScL!tHym=VdIJY}rPD(lcZ7HLZ4l5h*Egmrh
z+!1qK8kMdpp48OfW%oy?Xo)3s&O7=L)*&NvvCzKh2R#`EZBbunp)`iO;=ZwTDbbpA
z#yiH4+FQyH3GTzQlt7~fjAM`|JX#q4B?}7W+Gvm4KF{S9qmda`sfLAftmiEXHEocl
z_REbNlE?~Gozi){G!lBJknQ6ye7J0#rXvGLGI!*;SvYwrx39ikyw<cGCZTJ_T!k3d
zf=Fw&ogNj0KD%?Yu%uUv5G%p69fWUKG{rMla7Qb+=yK*zUt?o%h!(s7W3I8Ae<sWn
zJp={12Da#U1mU<dE-LZ!k#K*OEeiqtr7o4$cc59NAJc(}V&a;MRIJTa?v~`}zxgA*
zieBdR^J;bhbNk4hwTWy<`_O9{Mi}^`RYu^2u{x`0K_wCbNYBa>nk*B-{9Wl^;8FSb
z&l9u}Xn}1&*ggJY^R!KPX?$LeDraF!Sg0b2vO)34<U2ssP=FY5%48N8BX+BR;7InL
z@?r`JK;-)cc}fcUI;+SC(k<dCKXe!2633RvlK=fy?t{sGq)iQZlg5_n@WqoMII?Bm
zy#X4Kb~sY@V^<)Oy;W0GL?Anzv36L}iE}LPc-h|Y=aQTm-2jMHf_dTr=cJckMB2KU
zEi+5GiA~B$njmRI0~3ARtzi^=E^3(bj{z>d*+a4(CEqb_%g<s3l%=B#_)8f=+7|ma
zKjy(VU?pr2ef}m^zbea*;LxO0t!IJiqhh^vVw5)n<Qd+GuPL?+oE=_my=KuLCg%uk
z>eR$9PYy|2kudssBy#aSVOhDcV`)m+<B`TttnmuUs#c?Maj2<faj0}b7KEda;O621
zNuqeC;K+FB+#q}jo=7+e#K?}w<dd2XDleUgG{w!E`3vZOVqxV1J}uL~SQyW58dUqw
z8m|A>$WG9}@&5>jg>0>@Eu4Py;{VbRS1VatF7d<rxFmMEF+3ktJXN1V__XO($M3U=
z%moJ6X%-dlvb{J+*=!PHCCJ>FHR~gM?!w)Qg*Ub<ZFnfl8XK6pxa7DW2Y-DZT(JGo
zayu>b-=t}4GaA-`d*R+PQ(sCRr&?UKsECRO89e4kvnO{zh&EwIC8~a)M{y?*Qz0JA
ze%PDE=n^**^<jjTqZ7FfzrRH>SjgIC3Fw<fqf|O3863UVZhBy>zF}(f=1Ew(<2Sk2
zNrpA4Ckuga-vGi1H`YU*_*W{s8l^H`_pF(857;R~Ne%%+<(3$KO;$inB65>cDTNas
z7K9KUGn@3%A{muYw6!8aIaN5xZZ0lW&&+x_l`wGqo@IGYA@Q?X(((<M+fL=HrY1t%
znv64hj;F)T0WU`A7YhcEaSNy|Fewze_vM=l5j~U;96q*hXXb`abUuEzLBjWe#^`h^
z#eAA;*JOQV+-&_;gd=~@Cdrt$2^L`|PWRm7_rxmO?-?t%m$fu!$udQv)ORG*<Q4?N
zI{^5`g@m5XDzEi>i6ez%-?(=7J&BaqdIz(6c6YQlk*zv$)OkQ3kzQuZ4ycl;Z${*H
z51M{-TJzrkqebpN?J5I^Z@K>&LH%)59TvaQ^Yz=ZGyG=}ByZs0^xv@Aw5pUNmI(a!
z%F1BED&5{%{dnf?m?f7KE@=q5P@NI+L1-9usF^;s%%O9&%kbZ1%H1&p8*Gkyusq0M
zNHCv2X5SEOu*f`(R9c$RN-c7y^o!ezdUCxb&A#6sA9#Ok4C$hwR}|6vKMXa{CPUO&
zhZ{&_p)9=ozyfHVjj-TAnu*H90^a52@gUBP>b(+%N+rBfhKyhaov$^f{_W{*J7kBx
zp}=fpg!r4RmVZp$xu$LJ+5_{+49Z8l_Z%hK)HjV*N)JXmuU4j2jfAniRFyU*rTvyY
z!xRg)3&q(f8YVu!tz~-M7oAuYw-^qSOwUQy%2hUvWXrMNrnq#fDP4&nvd4@AMG>z#
zOLI`qxtsD~(`mL1MvnxqC~cxk2cMhL%_chWrmMz)x~+ImtHqtXH1pjmRhgpWS=<B`
zoMkCwL!U)a4y8I`@H0d#b;>n|)&*>VMuQLw=;PX^)0QIlYJ>ZR+n!~Mo3m9#^}(%O
zVV|*alLi_?np!jFh|c1b%5#6g>5uxlvn9Z_)Mk}Ku7q+7@NmpK1)&lddqQ8L7+ZHC
zLCa-Ids)cQ?X;+Ks^`7-BP`17KZB*Yq0oV}UNZ&NlNd)ee@a|Z`?^LUmMspGzru~q
zZBHuIM;m-U5AWEG!E$QD(!n3Wr_}Aq*}TKd>BLIIg`gAU>B><__5+8>N=MY$R^?!m
zVQu7$TC~m3&K`5$1+y*Mr#Wn2LAreC9O)ifvYJX{iP2q{@!i3f<&w+EuPY=(IJBUH
zSF*}3m+`F9YE{m%EZM@Fp@CP=k&xbx=2B?eA!_@TDQ>(#)h8Z0?D>OzC!D18<p+>6
zXKg`~oHctDG1Mi_UH~aWH8F^&PF+!s5=qW>@Yh{)K7?hF0Ttlq0eQOpDlklBX;{c_
z2D~jUFYe=|ph<+2ERpxQEAO0cpWPY?QM{6oR-`a=&de3aibFyO@gc+l0V|n&%k+7f
z$lY>h&>5b=p`T^vIJ=DAe8&8&bFmUp`_S`7j}~)*_6bVQ;WJ^M6JK6!df+dSd$P^(
zA1LE5VbY1&Y9u@&7tP>uC`Bq{>HZiA(}*u@R}veMBeru<>7*V}?W7*j;p#{XMuh)_
zx6;I!<9~N61aHvZGDT7AC*qcI(!KhRaTxGZ`eV>vf~KAfVi(SkNNus`s__G!=)y4p
zGfHWe$U~eQjs7532_vYudHnDAFlVUJU8KDk5sWk$MK*IM+Ob8#r`-vN<6#n#K{%;N
z;Ozcd26O%E$k`wi?J^DSU9y$pK@y#F;aI%|CuZgN+H&H1L}!Zn#JC;8a+z7zprr-7
zqms8+l6JnxQ^~t*$-DXFYpMY^l>I;ob~+HcLt2n_)R5nz5W0&0wy;2aD}j5XT?cY#
z=4dB!;lDV&)=VuZzGCQiq@axaR|KF)2GAVV-~}0-Z$+;Wo@i4BwKjCHV>(^~2ZsB`
zAjhw%qK67aeZ2DHRXoVI$0dcMKZ~SQW&a-i{IALf1n`#g@0VXY=KmjSNB-L=<NsIZ
zmb)Oll7=zZKc}WT-PtnPTmh-^YqUeKf#DU<fQ4Ye1ra3#|Ma&JXBrzMMt5StR;yA~
zYsPvM?5fPVwL~=d@2kLdZT@YpZq}UD)Y6RAjnMBoNq2vdWHkufdHMMM$vxgqcQ^Yj
zgy|<a?(S!sdfWhi8k_v0W%d@Gbj^WgA{Ez(b){nwJ)~Rj6nO_n%<eUmd17!I7xUuq
z<g6X7K7oA-qH~9`9}R0}P824`S;zJts=WZdatselya;$EEX0FhY>tzcIwwM6MOb^%
z)HYuceJY~qjwZ{Lg<>^56vT=bPwTTdSCz{BM_5bx0eT3d+3u1pyioLHVi%ozL{BWO
z<%eeT#2TY>$FZEQ7v4CrrgmvKZAmV-Sks0#!BbtZZgz14x^i%_PJ>hXTs7U*FkkL$
z{&Gx?d~x&R1gQQqI>34(4d_abTbG{JI<;qg;vAjm6%(2%o^WUV_V(#X*5gl{eDmSI
zp)DF!&HkAKb?zFQ@D=Vw(|8*OenYIVD#qnoc`IgBACC+RNmV#=pwtm4&OQB<tk4#D
z)w2#{dSzMis-CHB6o7)=+kAbp_yp}yJlVAN0_%;ZWK+Of|1c$dqEYTn#^r0i->mv{
z*+}C8zs%<BjYPF$tFBxH1@M9E?o6$CS%3Zd^k@FY|Ixtw;qVRHz$NWjmxvWRy(5>Y
zj~qj5xaZZJv!U8CI_j;v?^gDV(&dpw;ueS{v;L&`mh#}10m`kvGkbI7+%XHxos-Nt
zp<8>6{48evW~4buW^POA{d>^6uT}nNxgWT*_G<a*47hE2)LWdw=JZW!e{^HM-Ah*I
zi$BmMvdp*fy7?)m`W=(pYkB0`a{p5G>0R*3qxua{{Xk9i6PNOYVDM6({4+ekSAXAo
z{<*09&Gzj|wPSnqQ`ay1El2e;HNjVEqo@9ss`^bw`JFlPJv#AYdGynGUt9HQsd)o{
z^%H_e{3o>PQ!Arphm@bba#xk0tZZ*<Krj~B<5bmPm?T`evQ9%JL*+NK*q~sj#)nrC
zH~e0`%ar7J9BYo?t{fYE8z$F@YU$@vj2lMJQdp}ttWt@RLOB>#cudnr5!(zB!VWA#
zMN&u`Cf<@_z#x&8t`9HYSEoeDJB+j#gDZfSpolnCkX}YS5AfKdP>_UEgf%4PG2NRO
zwtq~M$-GUVjVayPQTpK!{>hB{-UmLnBjk~7fFxTGof^hLcrX_r(;D^~aPwEm67-%7
z;~{xK+KCKas{ggS3(X>+gh-{#R1d-;L)8*#rcHs5DHD^0mpZGD>R8>C4cDwJD@>Oy
zOgU0jkn4r%FmH-LS^8HLnXFnbiB@U7?^G{}W{FY6rc7IDSyQI_Pg|*_DnVdo;i)FN
zMzOZCvb%}*^u?)pc3AePr-pxS8AW^V{<*Ebr^!XZdn&IgLWKor*LXRVj?R)?58I+4
zg2_%_Lr2F%M#RzENJZsI5)=?%K8x4a)1q&a)zkY-QO~n;GuAQ2W_#i2{IO}N{Zl}0
z?%+aD858JQ71W9)u<P2+F>e6L{Lb3x<1D$mm<;~WS+y)*%A1DvydWf6hS_*8g;T9A
zP@qK9<@Y6x&hh!ko6-f(l}?R*EZ%A-<M&lpKeJ?mkkzEuCtT|K{sm+Q8yHxj)A^nO
z;=1;BO$w~5MQG*n$p!6|lQU6R4yx-J;!cMHh~`Y<s^GTfMIdi)<#zYl^76U!2S!%h
zAJI^=!p=u(TZ>Yz)4$FjI>nLo1U~qH%$(ZaoV~TfIN-1FbD!+|!1+MoH}~%w2vxmK
z^^<y=NSD_TDIc6%JpFl_dM8l8L<b1Erml6C?XzgmwwOTP-L^W;YMHV9Rr&s6XjQv(
z3P$kyHr__=?j|N8CL)e1PYaTXbT|#oJv|ln77qy<!PCvrFwW612~w%aG<?kt9Dzyh
zIka+iyn!PD#uVJfy$b-9Ib7BtK-F8T=cG9gPVJT+oU83$Fg4D)t;j*Bsjk73H~Agw
zWguMK0H7x0b9oa7&Twh*@=klg!baQ1te_IL&?YX~RJ$>LM)GN&h8XGre-Xk#VfLBY
z^)u>uPyep_anoVR>%>nIWz1h0>Q`=U?O&%TMlqgio;-kIY5T)K$6)zLER{pYpI^d;
zq>5@W7!?J=2cov~vRIm?Zf;}dHE2E|?D@Y>VcLOtcEn#pM<o2i(&VqeE{m&|bkGOW
zX^VRlAI4AkS9U$HP506P2*9>rb>wRHw-K-Z20}VzQCu5+CIzpsgitG3S<3S4?qhQB
za+D`gfn=Dx?XNMKnmi>S!fh)(daC|&3qM7<=w)JX7`1DwXuJu%iFr$ukr_|hOeHe4
zt&jtDq8lz^(K`*m7TLz#6T^c#U_=!O5n(K?osy=V-k1Vf^=aV+p#Nb@XP~4xCHJ=p
z?GLE(1#}6?1|jlxi{enh^y0sRR7^$27||=}5>ht6Hxc{VLuN~?8pZj6<3#nch<_!j
za$VQXogLC6S$<<FQXiQ0<9CpoTJ#P)*@u!y?j)?tr`I*~GbL~QscHS_Lr&n>u{7w=
z6`TZa$Njy3K`=%S)V0*)%yjB5l-c4*OM|@#edVN_NJo6Uj0cjjixX}sK;0OG<OrXv
z|7>#2ccpd)JT<Uiz8WMy8x)gM+<=5Sb$(^%@c${-&_pSVRE`4*=?jJz$a(C%D=uYj
zKr3?C;I^@?)Witn7)L6k<b>^4AGcMOP6>&?pO7rK&Y?|Js}GUQj$;6QrxYUm<r%m6
z&)5WW!3&@MB@Fai<Q|#`197Q|+$}QI^~bg#$AG1CI}UTj)4>BiJ{MN^=<MwrSq`V1
z5abG=Srlv06VD0j&0d?rHGNS$yxtqqV32NKLc+)4rTiziv4HcO9K%P*mnAUl$8j9(
zg>*8z{8rpyzWAmS^>zJ2&J#zB(NoyMo}lqvyGX%Nb8T~zBI2Vb=c=J*nT;6zfOPfz
zM>+J_R5avam!+0;b@JD7=#f3-#ljd(JM8%WV;(Hi&4baq`<nKWN|VQ@p##BKo}&qg
zM1JMV=J5tloGY8B3hL2-G#{dd@JpQ`%k;yCZ~|r+c6_5HADApZx%VQB;dMrlg^>Fp
zJ_k9_XjhtYBl??hzi&6G$cvVR5!FMwWH3NB36CbVSn=z4^d*ftQ-Vk;o*$JQXD<o*
zm=q90s&B*jVw<MFJy1)&I^qDM$$Qj<)EZ)BsMDF&c4?soQ*bI78E*zns>rGUKt|Km
zjTIvucy7A|4zRs$^uRjVz*(?e0yUY~f`NNrooAaIW8yl5C&n@~skltASbKr7YP_2A
z#Ut(|W{H^Cs6d<zlMzhe`r+A0aRI+rWQKE&NE%a1QYAQ9!|kYr_J!0DP)DA#ezA34
zMxZ^xD$9BC2aI*!u2xlQQUA`Vxr6P%Rtl^EuHtTnzw>^^js>M?VX>pT2Gun*HVsOr
zcg1h~R+R&=Q{rPE4tNp;I64aE49GVUySBAJHnliO^(W<s=Mc-2lgo2zORnTG(b5P|
zn#c-U`Dx;Z&zy<db8?P7EQX|}Me4oZ;;1>A1tvL(RGWgyf=7oD$Mgx`$9SpEtnyO=
zPL#E0K32duB%y}ZwXVtDouydz%Z3iKFPiarC0GpYV!qLwg{cogN`lr~D^~4q-n)&f
zlrTw}&EHi}*9$|nJRu8v9TJL-xe`2Dqy^SgWoW|;3?vu)kNqI`?3!sH8dg@VZeF!Y
z450B-qP2W_!EThxKFWjwDNXPre`<8d`J$)WBmrFaCM_1l99W1k)+o`5x9zJnq8tan
zLKl=yswRwIk<~P=1MkKKI`P@w>g&0uCT9{&gp8Sq%S+XR2O!Smw%L>0;e24SXewNK
zRD7L@sZss<?374+DoUjyAWTn#YCvdNA_>$G)*)l>PV+EyAp23iVsTP5zMSkvJpnhV
zY$k}Eq2>feXyeMx)11*>e6W^+Se75PjBv8MSXd%0>*+vcq^yq9*+6NeO}1WXBnfm3
zp-Rny?%o`qY&}@4xH}2nJ@G_HzG`bijY1Vq#qjd-{<CUZ_q9uKu5F;!-&lMUyJQt!
zU$VgUafS3t9qLNCFdWp&ThEPvVwic@4)Z0Dzrq*XO_k?c!pLKBMgLY0Z0*$~wCtzs
z$dDE-q@Y!2DCKE;Cm9e2c9mdQW3#R5-Y(SxY4l4^_o;<mK{k$5g@8q3`%UZ8K{JEl
z>J_XQhfM21Ubf-QA|0LXc!aX3W|-0v_a>kcw%LTd^s-_TBcbA8ld0w<my&2$hTw*R
zJJ$Y&;YHwK>=R~bYE#oP48;x?gL1_j_eyKmL{dTDA=wwx)-bL?t`tR9!q~%DGOkg2
zRGF4y?Q7a+_pj77gK`CK^yDcrSu(7JU%CldA+28Qg9=%paXHN!hGAJ0WDZT2g(gf2
z(A#0p=+AA~Fbq}imv)$&#%1D<;@LdCN>*ADRWskRGHVNMXbNq`F!$@aqVLPvhtpm&
z4s8qPMPjh(jm3F&@8br_m=#0Eh&f?f(;64AoW+3tpoU7z6+&})bl^CZ>_2qYp&TeH
zukuo7`^>akmR{`Z3T=^Hvkd|53p6!{yr#dl_s5!AVoZg>8*^%SB@0+WFs(kyruquy
zl?Jy#(J*ML8yCWaxQTOH)jil@vCrvdP0uh4$=-q6_%ynAiBowj!FLLaqj`s{O_wsV
zx91OD@sFI{HgguZJBO0(nmZFAj-6bqhE`TCBb?qoxoP3(^yC?3Z_e-EFL=Pziy@q&
zg{)E08qj-$-TwKCJO1tMLfoXeW4PgU@>UydI3*G_51kgD<wjN9<(YHf(J=QV?vMk|
zh?GV`UP<hq7MlWR<<B(i!8lhX02t(w=e_^ld3MwrhMmYK4DsG^(>#F)b&>0WJF0e-
ztPV?sxM_41KsB{B#uB$yMykQwQQcVzeg2B@!d8baLSC!g2H|agq5S<9^rIx!%op^P
zrkeB~eHlvxAo?M^A+3<tLN|~%vm$pvp)ML+hBY8)vri<23!IH*?@M=`F3T{!$QP%(
z9s*u?yt92Hp-&Mn!#W=5*3Vkv<=lu~jQtzKUV?9drSH;HffIc@(TP2$xoh8$&(pYd
zt<t~<Ml~UkK?I4_vYcG3eJH@!;@4DyZ<_DINEe~cRMXE~w~3_5TIjoGc0c0q>)^A+
z{BGtUw*5R>Sd4wG`C3c(RucrYfw{Ccjn%e%2>Zr-iwu!fMQ9l`v;toj#)dpolQ@>R
zY8V=oMhs0%N|0&zT6{h8vyha0lY)NMCTg0@7@&he8tuYs^M?;ki)K`@Ik8>}SZLX$
zd!l{_73*n)Y5(lZcnd(#k1%g5a}MH#XVCPzzpic@*z7RL;!5l|r9@-R;F*wxtDLM7
z>DKm7z+14Xg_}1*x8_b#A&1fnj6JmDNeIs6mhB-arAI_VkeA1H?q4=)7pS35+CZ>!
zX#1Yh^@Yu)n->J$d-U7#<y0Ns{(fL)*|Nl#!7<wn>`wONlvLJDtRemLDvIHV&()`_
z_<41fm-wN$og0NbVQsL*%w>PgU97A6|LNNjQe++oj$%8GgaMMi|78Y$bNa&{oSYwx
z<a)Z{Cd37)p_9ok#g|`iDU@oflzO?JhY!7s?>`Kq`bVA$F>1vybo1r~Aramu#HH!D
z&u(HaW}dX*n99{zqC>y#47}hRMoh;cToz2n(k?41t(em|E7D~DMGD$FfpvYZ#9Zmj
zp1Ol+y2dmKvD(kSk-H$Bp-ja3>h$bBYx%&XNwhH|BEXurcWAy`HUF5xMSrYnV%Q;!
z+Due%4^RSmi|q4&<N?MSb0SZ*3<X1z!J$W$kk*90rQO~BDPrO{Vxpp9q!?z}*<=!{
z0;|H(GGm^xQBWw8_8X}MHV}wDa9XrffQm$rt$dOURxfjq88pV6T7RJn1S9S;0ZU_P
z8`G{SEr*=dpezjf{K=Y7A_9ZrC?7pNc?9$jE4j`otHzQE=8E0AB_C%tu3<zofwDu;
zA5?br7<~g`BRs?<;h4FpeS=$wOCvM(UwjMysw_hjqcy?1pk{l%ig|K~sz{SY5e;k8
zU+eJv><Su|CKJu*{N)AQ6^l}g4Try#tC-Nw=$>2pYIV8#PPnCM(A5fB2Iey0k+COY
z7?&u|l$f={CX?f|RET-PiJkt~#LgiHS&le3HGc}aDN?jgvLZ>}d991{s~1$UHqH$B
z0^fi`(?AR;EO{B-HZV6zf+y!<@WF_<J~|A+WfI_1eBtUn)W-9yi{9q?5^Y4*`2y3*
zeyNrH+7GahHbzm5;ry_HDv82N#e!>d+QNIznvpflBmNP9{Dp_tf^S<(d!kzkJVRYV
z^QTTAIGNf-rDDIZg+Q$59{2t0*4&n6W`1*`J4vkY#T<7L(rTfU9<32c?UG`=-#7sf
z2}NTOd7OSzsyRY4%%O!0_CjdFK?xYQc~RHl(-fwAP%y8sHjacSWTA;UcRU>@3pSfi
zTN^Zu+@QEVqxvn*P3l?3>|954V;oTe?>#!S$ot&HktDhwNsmQ|C3~GYFq#9pwB&vV
zyk=9sS`sL`_c-?1kcc!4j!!WohVf9Tz#J{!F+Hq`q$0NJcJutvQ`3q|r^*C=2u;+Q
z@nId)#34xF`1m0)Xxr{M>0)A`iS`I3fnZ>x<)FK6IBXO;a_k{?O254XVGVk|WCg1e
z>pVs{{cy&i?K{pmh<Ya(J$*7(yATcJ>AgDY_G!e<NI-ya_+60NIC&&qBTXYz!hnPR
zI|GkHU3uS>G_3U2ouL4utP4>DMhM-pQ+;Y)t@wS<c33Qa?4wOHi?jyx2-39}U_6{&
z4vow{Jncp<qO*mQ*36BNESw=QGfO{6dl1>e`g}_;FWwOo{rQGC9{5rVNsk#C)Cjhq
zRg)~rv@O&<VJkGzl$69wS3r<>k=wS;)gvwjX7f5Zb{D+&48XB}SwdKpPzF&DH<N^}
zE~#w+<uPVq*HOQ#7Y1|er{?Y4C_BUr37q9OD1z}Rw<V!v?UGtl{0wYcpbYO%$eL0&
zb@RLWgNA1irp@U^Cq=^G9DEE#7|%Z4i+lGeAmwmUYMD;<QaY-a^44zJ<S3`dJ`19A
zwbb{}L$*7G0kE2rLXQJss+ZBJ9yhcQ>Fx+a{XX&?KJjZ+T|?ME=_xs4uaY7$PZZKx
zvLtoUDe!H->X)o5)eWu{jWXF3S_$pWnF88+J&?T;x1wnAB5lwc#A^0oZ`IgHSk?n^
z#Ot~Y*(#H7Ae{WY8s(~z8sko)3>#%YWaC=o<Vpj219rb9$B{8w`>`W(1S5GC>RW;^
zEjbR7VJ+~*D?&oNOk=eUzTGDfL<)0fswa9+#71z-xzfLFxF}==jVVdX;kteZVZedP
z!$}MA+?4tJB65%Aw!@sxrOCV*;HgBqQ5rBqDi+Ft6o9A>IPhv_4W#b!E}1rhBo;Yf
zvB|C+fRMop2>${VpvoC-myU-l_#Wsv-jF*0B~alEOoH}8$Taz;WUBXQHOV9vUp*HG
zM8u9f`mA;J#%R#n=nFJ`s;(1kLLypZdG0quA;86@n+KR>&j2_IB|Rk~;IQSuihNq9
za#Gyqo!J>U?j#O@Okk9!$<?y4ey1?^*i9VetSr<=nkVZ4@l6rIEdI-*0U(^58GZ{M
z-qd$(#!@M)F7@ZUl|K0tDpM!v8v|GcuqTyc2}X2P3}Z!x>#r_^DQ@>Z^P$5bBAiIg
zekA-w<?ZISf{L8}fEy=+a3|jiGWm6pD3R6jt;{pZ>5-dzgO$2gl8`}@V2h1qgpN*@
zb6jF*;sR1q0HP8Q!|h0DXuj<Wj}4*=Y6;_j(D}OqC{?(ZjRna$8I4GYsZ>}?RWTQV
ztfHmJeVmyd=;pf!(($e07JQY%Yz~U1Lsq!z$pau5K%<d5AJ@JUm>o$4c~$K3R<%1$
z3V`P6*R3d6p1`l`(@eKsE|(yce{?luf!R20=$XeOB!?!s$XW6}5{WEvTFUxXBjJE(
zjQrNH?&0kDP<%;{%u1jJ4vEo1M3?6&txrj`*&gV!F;fhhC3|y5l~`^@O^(DZW<#yI
zU|M7}_+QT5JXVxf^`sP}UI{j&87daZA(ugv)YC^I2P;;(_f>KeKGDo9@db~xBU+)8
zx5^6w`hi__={oIR?pOE6Ce2ionUxb2sj8~_cHGP`V1Q{{pT+M2+o88h^Hj-Q4hv(;
z3PX~@1(kO9FXCO_>{mpyQedZ9K_BoEOBsy%i5`^=jhPO@E+TsoBOS%dM<y`I^GxFJ
z`<rC8-KN1JJRUd8ra66*vRU%*KOXWo%yb2cGOno<xkV_-N&#dnbB(n6pm1*>;e1=z
zD)QN{!>__X1)wBK9-KZM3umHOF{qOvB_w}Kpbnk?z8kmBpp{uy%Iob>SYSq1Pa^7O
zH#d6@iorpTPz<mvt+3KjRceU5I8CIeq_VBDEG=CWSn@A;lx;m5dsNxQ`<g|gj;8ey
zde&E2ktAP$`PA8~*EyOH&ep!Z+-d}nM)h%e@f@m}I(M+PotfGt@2r+PnT+$VzR>?0
zV<=&ZB;|Ks{2iV?pQJ1<doD)#g@Q^<J#bk@k_L^TP1xSeNI{Q2&7H;#L`R*)$kA{m
zAU)jjB#7W;YDf+u=8i0lVQL*j7?;jdJ3GC7(pNdBdea#ixXsY13tX1x?1)-764z>h
zbq2mAxja+=OxzQuL~v2sp%G@1hH|OgVy6oE5O-uuU%36xPu0*E(;~1#mc2r|v<E6L
z&J1pkIsRb?y))erC4xU7`8p;3!^Kk^?Myhw3bQII-dRR;&1rfIL!uq@=}VrfN47{5
zIR}ym_m+-hG%B-Np4(A6fu1k~PMWTW{<!>T+nbpU`Ml+l8?S#~g(0?kbKVOfdQwab
zlLWKPjS;AKpqG`T?9XIB%JiSHbaagZk&Q#HP)$;5AFS{|5&UJ!wAa}0Eu6m(FSA4%
zZf5|@hz<?PS;v}sN3G!`>`;>)Ai@n<AL5ZHMU-?<9Vc<H^$2`#(g}yIp^S;%dw?>}
zzW^tlMnk?>@Zh@6b((;yu|n(>>kv37$)?+EQ;gzwqZkdLJ7n7#9}2Rye}Zp6y*eTf
z)Dc_<hJOa(spgTjjf?1Up}@x4aX-!j!7){6--i_K=iR=IBn1d?6}=kt@x`!`lvmR3
z>L;!t{}~IZx1!`iMW^b+4E?C%r78LT6J-$0@N}e37qOzj@Jtu({zFwIXI88}lV3|=
zoU3uq7RqZC_q2ZLcF8A}BG=c8WOPnuz(<xDX_6PqV!Y`UB-abIM)7KCX2S45Bj|-X
zvLpw<l`^RT@?0y7?u^er$kvL6it++LwFTv+f)}Qfhti;<pD!k9FmE$=)_SWT4&m>N
zR;0+_40ftXXTG+ss@?>)V5esSMg)A;NnnI#d>ve+65n#kJ64`=ziD79A!`GE?;_*_
zE@~YbUNL*>O+P{%tUpB)r&@Le=t-vzWe@o=7*?#W@|p#7_Ua@ASvB;f0aK_C6BWps
z27E=2!%dI3B1B}>mw{FTg0}^1)^823A8DtYuSugdRS_Pdt~nqJLMkP-&R8VRHD$t5
zg?dskxPp=Q6o?cwBfGfnki85vXvnvRXuYp)47Mko&0=1KurtqcjUj%5QYA5u!Ep47
z$6rIJEouNhLZ~qstncMyfYFBWCzC&PIu6K8DoCu{03pZ`VJ{gxBMzz0VgFbQCH+R)
zv1k5o4|di?*=ZJ1f#b1wKvt+@4xEJ@z>KTGR97L<LrhGrtMXP?<@(uiSLL+(!*W;p
zJV&e#KR3O8G1^`gnh>ovCX<nm@yO>ZhU0;$_TWke6Kf_@OmX>hFc~b;8bW{(DB>&S
zXE)~2ZbzEMsAvgJB|9N^HIK~(Q^ML@IMB&v%;XS_U#4hJ{&bbd^k^<1R8c`6Dg{IX
zD(X`|v8H~s=1UoRKq_*mz5`vAqE70;Y!VNBaz8G6ioa5$rDvWWfhL)v1!iDr-kilc
zlt|?zD#eJm-yg|KR4>_^U}>`n-L(3NoCPqZ+{-K9lqLY@+~DnEeY{n$#%zke4Z*KQ
zI{=BN&IH|j|1Oho0yw<w0G&mO8K%ATjAvX6)^l(`J-e*xEGvY-WgX7B`qP<G>2t{X
zYStBGvbunvJ8f2*;HPW}1E^1fol1$P0Xv_@L*sL(6u!Uw-czCtV7)lkgx^_SN}--W
z^K9n!T<CXYmq=X)=jWhA?BJ#XJnbL9*uM#aZkfObW)-AyMG@SQf2~cn{M5H2%64En
z4e&05UH2f?Vv9a8pBbRIXBqcESV477#rmn(4<@VNb(24OQJU4@t*VkKU|5rz33@g3
z38?k2s(@O*F@|OaSB%cC#3`_rXF!jKQLaJ_8?Ol4B+tE|_8oXHhFXxbzRXvKz1j$k
zlj&m(%C#&wsI!MZ#}tRGv-Q!z3<72V!3>gS0=~pclj>A2`c16{87;b^!SJvC+}h>?
zI<-icWs1EVFh0J{WG++r`4H<1^F05dURY0ALhosrchwu)CKhW9JG)!eOmmC?7gz^c
zNSZ$`8hd6Vo`+rz^^VP!y2z&+lLm4@7?AF7>5llBDAFEs{A@5x+#y2?UGENQ>n09a
zmlCY2YyGLtcM|9Dug0IzD`9tFQ??0(++Q&qu3{lkP!;JBaZ}k$Mo&7VJ`Wt0g}SF^
zbXkTKS1Ue;r;e|}Tt<_Um-_RG;Cf@Necx$5{T=0X$E!RLDi4R(k8ump)K@wO;46gt
z&Q)>wWryJfy4rs-Hmpb3`VGeMfd2^yE73p$Ml~>&h$(|#izW$su*MeajrTSj03Ty^
zVkCi|WpN33h|LJ*Nwi^6JI;Y4Pv<UU4~rQcNDsSy@JAZU5ngq7WVE~*Pq^v9D@gi%
zMwF8HWQkY(-S`uf3AGT#I^Ny71T{wR=ux6@oZ0q39ZG{^i+u87PPyn&9_E{N6HIJA
z_7UHK<g0uGjD?`AI{v9!K9qOHf@4xhUN37AK0uT@NFU_c{%^3$5^3|{JN{`XAs3T?
zWD-cbUZ}LG$nQ#=DGgv!12k)<;Skf5NH)DL=?ngg#=l9<gfGD%!cBC=xul3Nk;Kqc
zWR`gs%phcjmeUUwvJ{SeI+!=w&pcmNv2wG209TQUHZK?%VKbaVvxoKDWsE<@vSPiW
z{@*tploTS3K}8duds~o~ur;)Cef=qQOkj9fLCo+Dq6;(Q;Lw=jNa4a8Lnktte(0S8
zh4EBYd@=jF$)Wnh!qJ)>4GC1!l2BZrhaZk#6_7ZqtX?cWY#Z(!tPOSp`^S^6dbnrZ
zgvA<6Ckt?;kX;95HAKH=XFb}Cx=8aeeAYTx4Sdxm6b*aca=L89PB+-bT!P6Olk_-m
zhNNQCW_J3sljpI`=^79&tW5XU&00L$%I2a_oqtK4mP;TTaJKr2&|EQi<z<YhC|M!e
zwc5R&P3uT|`DlFEO`zd>{3T1gB)gtz3|%P~uo*`qaT+y}bmbwd27)7_1&2?tYYNZg
zP-m1R;*B2@7oVdg=_ahvW%+XyJa8stxxQTErZC<kvLS-?=?J`4gVwt~lk8kC+m<7n
z)q3DJp}aR-7SY`HSVYu{d6ROC6qLo=>51=bdN|G4>4^=P!%;I~5vU-iTtWoqp&%o|
z3%nN}@JXSLit<!aGPO!SLbG}+){t?AaRbhnY2PtXAPxWQF*18Za=)}{47DPFWgH0i
z+T<kaplA!QPhZLa$t80eqV*KbspyRm-ziE9q|dDCAlRvb&(unvS(!wSa4Qv@PX67c
zG;4bMn)FHlf;3g7AeZ{!N~5zmhWG1^=#mOro_A-`+xioApNrw7(O9Tl1I;ChON{Yl
z;MkNUezwkdji5%gAeI0o1CWg{Xg8(?H;}Hs!X>8hrSvP$`GaMB5(r+<PQhzZ!^Ilw
zBXUphu!9xq`8Fs8dHN+_6i!X5QT#B`%FF5=I*^oN=)?kyqLjP^R|>PnhJSpHNQ#Xy
zTfD~L!t`3nB%%n3ss<rcE~QlKu6ic*_JmJ_2XXS1Q7gl}X;#<?&ZR8#Vs5`D>9Z>V
zC#>TN&ZUiGO=f*j=9hh8G5Rd%fmYeVIuB>3+W8v=Q?Gx8tpPLyD=T)82509D)fg2!
zI8^bz<dLYdR_6Tq*Xzq4&pGC0OFNM;D(%pmE!;N0S6^Dx!Sh$Jq8K4NgBexoB>BBi
zb$n;-+y^4B!@}t<@a0F`wlpCHhUYfood%qWNV~b%Y>MY3vg1?37?z!k+8x-@b*202
z#;o$^C3x))oO{T~GA9iP&Pa0DHp#{q{uWIIvmQj2f#8HZwB6&MKNIV*d6?c&m@W)f
z{MFd{d?D4BjBS7ytAt1hQq2ZGF!bSHQD4|>#R%JNp=*O}OUvR5*<+}jRl!JcDzwGZ
zgLy<%e6@+2W5#C)Te!4RvHPr$8XLuHfKmjkNGg2RkvP;l{BN!Ls~UKNagG%;E<|U&
z1FQ8Z4sajA5)T|<;0|!w)G#56Wdv>79;*{7xq8U+QmFSo#kv{7BuaF}$dtC3%5n@A
zxG*>*79@C-@y{+^5^MjC$yqcBVXh5JO;sa@ZQ1~_%*BP3$Q_+%{)S)BA9nzdfT197
z0yK}kMPI54pR%3`#1JFWjj&9KI0`4E0xC)Kg+Lz+BRJ?%9|evhjw7U!B(V7tn8qgk
zk&*O6ICFMgGRFy^SO_FZ9dT$H@AbU9`TgH#lU>%B2j|_lNQY}wsRTzgkp0V^yO^LX
zB&25%QqmJT7fTTo+U+q}1J=qNx+%|nFaehfmct5$Q3(ZZa2{<h2fJW-fWf8+4$5n&
za)I`j5YNaqcDz#wkz}~#G1NU7UkN<XlMRCD%IMm(Nm-OE_ZZma|AJGq06yUlFD^CO
z57UnWatC{VadXFh*8_6RTWrMn{q4GLIF~rbOh=*!BP8of+_vxoMcWbACF1lbbs+EZ
zVTD<tWArtmGELm!G9R=B3S<oo!PqK8SWf`9@bLxbu`lfub0(0AdW%buXT>elnRqR7
z=`FpHUbVGK((Bv|`~LD_lFmI;l*fOPA55{_;rn&OpG|N!L_MXet%aTXJ@`LfKolv<
zudSji|L*LJJCoR6xjPi;2-SLk6YcNMF4f3ydqYSrS=!s)*uRXM=z0Zlq$jyq8m5#K
zPQFEHca_H*wNrG3deFdI1G-~~n#MpW(YwKgx-W)ZoBUPz-}C~`H6(jrQn>=ZQe^Z;
z@d18eYDz}+f1?T*ZE$E}&Ne1dGu=#8jyI4OTb(l5o(8hE>L<rrLd8kwSCw1g$kwuu
zusv)iJ@8w-KqKS#Kn+<GlaX~@I8C8Y3R;`ZpGmxKbLB`XzAf47;;yx`a_cjEkp-%V
zfg7`fWjw;@XUZPxZ)X#K<dv3PzHfEc+W(SqBjP@r7roTfso{Ar-a&f@nyvBJg^)Vb
zMnsginSs^zu}ZRD`h^3Pe2Jh3aTpnkKl{aaf;mI?8yOd_-6Rn-GB#<hc+U|Zuiaa_
zTp+a$Dt5B$utH6%B(04Ovr=Sm8D^r6mpH8-N?!#pRkJoZa9x#u==)nB$<=9PvvyvE
zb66P0#M>U0Zo`hQS-*`?n{jGRI+@Ts&@@@c+OpU^c6L`W?=%4MDsBFh6~!)+CU?=C
zKrFmkh`3-WT5+L^JTs&0i(2Tx3w@9cHu*-J8Yn%2KcH%oRBne*+pcDV{w|{>2PF3D
zd!w){%j##Gf^6h=faDzMC2ZtUfm=!;Cg7d|d=H^Q-p2Cn62`6QfuK6~(sAsnGWORE
z+H2769daBsWvm=>3R}uD??|SEaPDzCFm47JpV1x(`20zq+1NwBaC%0+!*lLV>`*=c
zTk7fdM4$26GQZG#275wU>1#NL-qVwTGKX1MW3|*#<P4m(&3JPrTI{eo{mtsQ+)z7X
z%^JbnVK>Je*J*P`aZlbZd%d8!hOV$**>eWSZnb@&>GqJ`ygqe?O7Dw5)pch}AC|p9
zZBLlo*>a~_Z#lfE`22S!PwsiVaD78^r}+91KHdPoS?G|W=#VjMk&)bz$%l84-V_xk
zErtEq!lJ!`*)!R~BVQ@Y(Rzaz%mHPMdWAyAMx^9@zj1L&op>>U<Q=lCytpyJ9kLc)
z=jlZ_WkG-bh&J-&Nr<0R=BIWCn+}X@8i0Ker7XPSJ`V4UBoL4W?Lk<g=ZM1%B54@7
zUGg%M`VO?JKI3C{xsEv_nHBmMa8wo14Q^mcm1Kq#yC(mB_$uwtrEbd6@uY4NGfAcJ
z^eI4S_r5NLyeg%<w}B6O{7uRe>4D3|<O<!My8>(txZmwh2kLG0#{ufZUogKqYV{d0
zPtq6g*0nQKLuLc{XKVYOX^KSNy<lXw4%J6*h@R`y>Aukl0wQv&g(cQcqy@HnVzb&#
zvO9Q&Yj$9QfgTs241jJ6D0E1XkkopGXK*Iv|7BU>YqTcNx(Ta}&(37v2Be-89hGi_
zyLkTPmHeS1w=NHmtWAJiaO}u#vASF32w?@=wyjJeH}m0S-G*&MwnM^NkbmOnC2R~d
ze6w7DlPt4asXil5pB*#c3tk6Oz00io>qgU+wL1806-N;k&EtcG`y%SLm5IP5J_Boj
zH81aSA>=}HzFif_Ab#T_zK0Vx%|jnj8w%2elwyZhb-X<{H5<T+`v(tBFz%(V-HYfm
z%{GMU)!h!}hu7-hM2N2Uk56E4?}65y&bLs?IGvHv+mRJVZvxA`Wzp`IpTSZ4Sb=Xm
zfgaY@ByYbWrMCa1f;I1JIdUa)8>q^dUiiELmX$%SAqCDsyzSaf91ca0HU@;OTF5$<
z6sf1tc;OnBl&{)lbTJ&UXKCG$72gL~gDb1n(04e=@ISPGCwS_)b+cDrK577=V_!Zs
z?y7*1*~1_8_ORoNQHYSMpdX`FA@E$9(@-P==dqbTJADH{W3TlEw<7Fd6cg}QR@wuk
z%rq@HQ*?`MNr!znKRVz(v3$N|{i9lrO=&^2?!og(HjwT?A7RVRojDJqS*;Y?g;FKU
z<&7xCknV?aGs?(Su5qRRwn2PjP)pa8a@PPTx^LZkMr?zF)u&glfyuJ%Hjv?Z(T;~-
z!mr{Ve6k+^Qd|Z?V+X{DVe!OhB6*zi2s-<jjgO;dpiM*@e^rxpS0TNRf-O9S>MQiH
zn=rZhv3#MGNvs8B!ZfcG<ONlzs^1fS4i=Q1O<=smLoYingFCK+J`;v0n@lc)eB_(B
z07=DvBtF(@Q_-9=XGKRbUZe9KG8Kw<APe8D>2r2qk>0Z9CvF1VKXJ?UUj{5b0n`Wa
zfZ2XHoE}1VvA@Bsjym`LDnG71==DW@V!X!jL4CYA-qQ8N0{Hry+@`Jze?wC3)i!8;
zb6W2Anqa*$T~hzfLt{IMh>w37`h8w`KN7y67}X)B%zi`%Gs0<K-Q2+wLGTRKU-cOA
zZYj6Qr@*>m>;swcZb`R_rob@co=hptxV5IgLt#7p!mIqfNgj%e$uaaMAK$r;lkSrN
zRjfd{{1ht&F<Dc*iH_!`8`cG~0s;4A5W=^NOL_(Y{03g(|2nd)wjR$jW2X45LAKlq
zOp-=`6q$R`7K1@~6JwwlB-(>R&aa$S@pa=RuNaIx9dNdt2e1!=qkau~OV(LI#mN>j
zjIo>cr5nG-6@|?FL=uJm?0NBPqXHIJ2}7ijKEVGTH_P*5q73yQ(4hXDB`lleo98Nw
zaQ{p#;QsX%Ojjx`AKOt(-&cnI<R#)*hsiBm%2-^uLF?R;GRx4Jcr;21fbH+iV(fpj
zH4}AnE0F}8tur%x738tR82Ewv{%W1eSpoYgtP11V&Y1_(OD{KNPc{Av=OxqNAfsK-
zN|JEey^>BNfV$CWV)Liaj8aFg7|2szObD;z7~&rco8!+j{f5S~bn?`ANxZ|gg>r&p
zt<&*Zqq&l}+I-5Iqsw4FJhmWsuS(`?thnK;P{1RN^{AF)I(1TLOKd=}3rVI6$Vr_R
zdEv8L5owud@YuJp<;0h4DR0L13fNb$(_g8JGb2A$_Ed(A6c%x!5thExbOO?h%k)#$
zTgZY`O~e9A+TTodoZukSgzS10qTg*;4WIb-$(_X__l_APog-M{+sgAXE}*WyUpJOC
z<p$Ns&j^^Q&ziTP%77y^Zql(dl5Pmseh?(>LVZ%<r0xPtWJVkRN6lb%d7uj0BAn3`
zmS%uhH)cp}YFtRWQHVMjm(`;vIBjpL_2edymBX$x9ECe`(s;{gw$xn%w8unzh8hDt
z$I8%VBSSkyW+r+aDYBhf?2YF*uC9On`0y!UIX$-b&3%)A$tE)I?Z^5%48&FrXKc37
z@C^e@g7QSTjQU7@qDlJc`L|?Y2|dn|xGG;!h%S*XF?(h}JgHNr%b%(GvkcvzF+d6+
zG>Z|fcCANhQco8V7*33ETeN;5y4Zv&cV1Dfy%}#&ose@hdLxT^Q=rRKA6w=tH-*Ix
zkx`?yShSkE3YE7geJF3j6)U$!3DS7Bnm~V1CXNfvg_AxAF{k6@kAFgOrsd`ZzNwM#
z<`%SnVkzH#nbY$9a^z3UDSQ1I-%{-ee%LZ5fBHo}soJmugRDQX+QRXIxaiB)hClWo
z9xro{pmh-d{~=?3N~o(>h?^A?24>TV)<Xqn>yVB#d<?TcH=)nwAT_Re8nS)}W6yrm
z$nI<FuMr&I*Bj#I5+6U58v^7Kpx(O|U>o&7M!itJ{f+uriJ<&Pjr#B)%+jktz1O|3
z{2ix0f``DuO^o@vSP<V!pnB^ng7l-FHN%Hy`Py2bQ54QJjJ}7sIK;_-cGfK26hXQ-
zvLajcHiSA)GlOInjt9}(rurE6F(i7&+u}t`i<}$wFkHG1X4tz%*#pmqtY=g!w2ufg
zRGdLeyLdlzv>|LC%qsLL>=;4S>|o!lN>Vd_KIFV1SudkSWV0}Xz-Gx7q1B`%EZ!;f
zXyF>U+2lENwIOTY`kZmP{7rbh%!|Ue_#FB1+roi0*$xSz65zHJMTk)s3Xko>caCrC
zs|f*Q0VowSRW~X|xl;sZPG8pPW@FcX%!3$Sx{MjD_Cv3yOn*mT14WOCl2N2OQXd)Q
z(MLjErbZHslsD+X+J=z2hZ1X9`NL=rw!ZBvIl*YQgGgE27GuZLjP#8n>c*sj+KRjK
zsx|e&<^)`O<)onH$Z&ySI|#=dha@7?+9i&(&s3iRUm@mBAUk6I7h~_(oLShd?S>uO
zwr$($*tTtUY}>Zev2EM9W83Jwd1~#dz1MncSFJB|{(x&%U1N?h&f{>J_2xy>B?a|7
zrStrk9Gm^v!TV=I(9bJja}IAp6n+9=x#drL#Wt1}54SY8NOs72m4`WAM)GXA!8b>?
zYDgkMd<kYKm6Ktr{a04PI+{#1Hyws@t|!$~8SdDUVA7iby?kzm39lxq36HtAa`0%Q
znK#J1u&7zC6BYD`he(xMHH1>ziNk}vR?%q6nHck=5Qp-^Seu$l%Z3cs`f*UaUYw6S
zx2!R=em3}S6xb=fMObYgpI85+=#(%fZsiU0EJ(N5nWtqgz@&7l&l_H-WoC53>5QX3
zwam-4<qomk5~tw~M<W;*{$E^(eLoq(F(o87*l59x+bl;t>Mq^V8)pr{-7G#8J|_#}
zWe6|Z6(Jp~BvP8K2jjgFLScHD0xu95Oha<OPKo1MflXfu;qULzVo$SX^q1J!i59rq
z(n5^Y-*GxRo$Nj+be9a{ofZp-Xv#%SIj3rt1U~YfNn#deW7f%L<JFQ?OPhbPa3#BC
z2HY189e;5nSc)C<HCk|zAV3c%F{<){Q$*+s7kOZ>M40zc<bwCEL1+&@IJA2J*P<|t
z-x|Ylzf<(%QrT0@K^nh-Ex<CORhF35@6FV(-1q~|Nlw5wi6KHZiGSX*nro3A2VssB
z+Q`^WE!>P#zZ~P&kljaJ5y_R-aAh8gNM6c25HWMo9wp_+dctDFBm|t+&l<5^N(J=Q
zaE%TuaGv`ypUBf<5QGl+CF#iX0OdxO7Urvxm=bB1hVa0Z(*+ykBQ03JVbCto|HhSz
z9Sd<~5&p?qW4d<-C02oVy>ErmI=cDQ6plkYo`yX(yk8Yh?gxIh&%vnG1%EJ1U{L4*
za~v+v&wEFdP0SzYbVsieE+B%pf>Xakx)YSL?`tva1+l`hXRqLc%VmoTr(AqISP%a)
zP84TE!+2?ZG&=UP#GXls0PrIISTa7Zb~%m5mc(m13OXX35}B!6cq{hGk*}3lX&t!?
zOpymDPk->E9I+c)q)d`unI#bbQ#9a2wIhUW&K|ki>-DXSBVqF>XOHWYtpT(+`*LNa
zjs#8+A`z68hCOUU*)LE({%3#;pd2cH{Nrh8rUwGz{@(>(|F7uuf5{q}wP1Wyeq;?j
zQ>5<4Gi1R)0RU5fAR>9l@Juk$U_udm$Or?$fUJy369Z<J8Cj2}bG3$=6?N^Znwu32
z+nR~NP%vtv=9cCSH}}nLH}{K<&h6$+wN8Z2tM|fh=j)vDsY4K=7J+-77v7!+-`%&J
z6WBT*k55vh<vRq`^Zak8qBr~b4}$s6I%$|wycFU`Z-g&`FQKU~#ggwbcU7;rotHU?
z#{vz`D?_6Z>J!g3p+ACyznRkN90H_=t0^y)ERj3;s{cwD%9T((#zu_-CPNCbZUDr&
zgbJuZl=5I&xyAP;^okyl(v6;#19~aP_pA-fx<^>N$^cDh{d|WCX&BFzs1tv-T$)T~
zgxQ0)Le2bJVFbE;=n$IWR%u%GDozKunTck6`V+B2O<If9h-ES(!-_D5LsR;mv0)6D
zfAmP&^hn)aAvh{p;O!114C<cX`saX@Ez%XW2)&F`woZ@cC~ciCahon#Kr{7+N6tje
zR;fd$G|nkr2#?A+s*?sox$gBbT$f^a&El{weUET`^Y{;B+ovR|bNC#6-bVF}x@Ti}
zQ)Op{N2j{8O~O!MF<RAYKw~#A`iUZ|$k(^PWFeeGf<%fBm1$o#lOfRFSwo&Q8f>xn
z`JV%GGH9)X|2WO94eRH;hk-M1a*RpfR!aNWp%vS+{lef^=)kYVHrIK4n>8%x=h0y+
zq0RS6dh7Kul`Zrb2x}BTj*R<qi&&5l$xdH!OWp3y(y{fq%^50U=Odq&twtP}HBZu=
z0x4v;qhPA!c|tKMuvG;f{m!_`T33(p^z%yU^;MPjhR>C(n3IvR@+KNx1(p26`}1?@
zl0~3CbJ}TS?XL0AK>?5hdPeX^Qh|f5He~{srn@;M=6n(-sIuma(}5(vx`B)#wsR*E
zg3<14wC|M{EFp&3>>A-;3Eer&$lyepblf8t4koUwBH#!D>9f<D3#NVD9~fgi^YaBj
z&Wo3HWTlv89Vc)gP3rA}X?xdt={fW{|L#JH4;OCb`K+N0>GTDs8B4r@9Q$T5gfjBe
zQA8d)LmDpCoM;hr-hvhsMmFCNkUo}Ts)-QJ<0j^vZkCsX3rl7}I=wArte;4wU`Mj;
zoZrBH!uSVWu+)bScY#Q6IFH!p_d2Y-+vN0q-|ei*?hrH9=-C2FXVzYtZ-a>!zh}=V
zcElm>XybZc)9GjH;SCyaV8v|g0U+avuM_sqg59wWsxQ)-9Ce^3MUXqE8_q{#P(%nK
z?G;nd*h0fzC=Lh<Bcm=i`@wH;>3r((=cTWP<W}wut&nwhTVd~Y36e!fl|B-X@QuH-
z_Ctw8LrNh*&@aqa_BJ&HR7G;^&NMct7KQj#k&*TNy_?xL(O7=3@<-*{;)HXBSP*8F
zoEJOU9>+@ucg&>`+E)uPEH<L`;U;pPL@rk1G3^b7!jfJ(=1MO&;tpx=DyLFImTgXM
z6J6(*VSM&!(?jt1_^&X9_Dun>V%Ecjob@?UCiE~!Xd?JrArOnt0xYv!V1jPanbj4H
zdDS$Zx9zp_n>%lqnUrD2CYTx3-Q0yhr*U8l@au$8Ynrm^|G?YoqyLhgoXQa|hf_Pe
zomy^mM5QvynwY_}@C(oI5xl%SMnKcVQ$s0|Xy}&d-zV%MON}Iek(;k-n>u0J$WNrd
z^m9L&sAz;Q<T37Fi1q`J`5t5+Y%x((tdw0N>6^p1`MwGq1lRt$2cxQG$oN~;8(Sua
z<PQ+(<f86`Y(@`sI<_+9NUdZ6_s5Zix|++kn`diUlpPFM@S?(siMD_^VaD(nUCO<n
zh|8wk2QisgkR|B;bHg4WI{x`mSLUHfdeOmIrYc2l1{01qamQ12<M1I}#N>_yw~87i
zaYCSZ4iFQ2c7;pM{dyB5lj-!DAjb{!Y|x`h?L2CJSC{;f88T3M6W)x918-F6Ys3CB
ztm;#D3mp(ILo(iA^P>1ZCDOc#ejfcA$&9BIk`_-!WfKm?#w!wvF>;9!r#SPB`8^MV
zy)DRLwI$KohyNdWLy`X61*1xg@xFJ=h@<#)!ctq_i&a<L3(Y4}jKIvQ)#L1A=)kI_
z58rpnNZuX}VjRCxKd9ZScw63;XD1>rSRZhR{lY0eFy|4hT_lZuBYvp#k7_(b`fSFc
zOGWMcsRa8^qCm-A*_&C2{roG7k6_W}sas5Le$bC!qLs?0bHx2NN7j18rS_-T>Hjv*
z@G%}uO+p7Bn6>=$?2!R5Som=427OFgT*X#A>Ws&n1sWpibJ~DCF+vv?Cxjy6`XpFt
zWs1t>?V&vB#@LztC=rHUtb7P|<HpMFKtJ<G5bg${|6qw_%P}s$(tI)+N!B{C`2`cK
zyefL>9*n*^#?(@zZ=;+#Mk81~qP$m(=pWTtJ~F+x4d}1FO8Mdb<Fm)l4E^;ZT9CK=
zWEDta#=Q_C{JRNRy^PWwZUIfO@XAP__*y<Pd(VM16$}g;E`q=45g%rdW6o^}cdr(c
z(tAAJsiwd?^|Jq$8Qqq~N9O=#fVsEi&e?}qMn&$ftw+Dhgi#JN7tP!sk;#0&hROOe
zQ;@Ru?%}g-pp5k&dvE!j%x4a54AJ+><1aVz$^_OIOvfR=+J#rsfAqrIe;LSyGuw!Y
zI%P1b@E;%B^l^V}eB}zh`T8jW)LH)l3xr3bEGBicolO<qR$=#w*Rf1DaiV~I4eXH`
zK&xh!WxGcG3uW@0UME=Q9*KT{MX;&jf3JdCTw=-4n1Duv_q|}rc2NsWDx8QM{V<jy
zS&W(#PhwV#j;5`OZ<kPC1Dq$T;=!Jbi4jXgCK85edA92k*=T2R1%dzq6XujgB6bw?
z3tLcZwN=vYdJ%7}$%4~EwkmBbO)qEs?doF+p6eZc2~}#!M-oMn&rfUF^CC=`a&`7c
zO!}Zd)R<+OM^VXO^enGA-D!;fG<jH>GwVBz)+jAet8+#hb*A5R$>lyK(lPEU`NO*Y
z_6a#xdV26&Lj1!O9xLStmFNOLD)Mwk3Ar)pw8D9CJ^9`Xg4T)~j+PXJbYW%tywx2~
ziOy6u!?IPr#5hV_8Os4KDig5iaA4tNAs&y%54BZWt7I{J{XhzSSvBipU;9PJBk9;C
zm`{bvKM0yi=SDO}cJjRypj&XMTjV!H08=ByW&i7Mp9sjfQgC(?Mq2a%PE3yB8mjCE
zG^|+D;I`u{prqLctX5HP=2FkS%*^QGJVxSW;v<GLI&v^wJZa1^C>d*m-@Z-wj8-j?
z`z2f=NRMxx=xR%`#{njZg&1P}SJttkj#@wT1F&(;ez(?;<;64oG5fjqJX7sinmGIV
zh$A>%+-@~4GV-tw4<!#dE>s4b#FHdpv3mN~2S&QwJb0WT39{_-#Nr1dET*AI*ZVB(
z%iGNHrZdaqrGzP33@I}(o%6W-&;Su)mx)W)26Y2v*=@@2EJg(8I-d(H)6_TT{8nD$
zS}yFCXf5h~&1)24CyIA(WVI&h20q@~=vgNBbcAHv9tYX+7*lH(0a@5cS5R`aoy%Pz
z8$C>1NLg7r<LM*Qw9z6alH4tO<}y=+Q8o^?I@|S~_3fSG3ybNm5~C>>?5WXv8!hcC
z;UkUsO{<{*ps+-9myG$Dj331XtF4XR#U`oW$a6Z1wU4clir<L8t(I?%fu;sepbDko
zy<RKn$9soBz^RQ|WCiHF&3Qh!=wYGdzSOU7OVlzjCbIe2BI)Q4mJx5poh&B3*t?$S
zyPqF_^XOKCXm7@m)rmV-%!7e!{6B%@g?~V|!=Hi7QuiibkJWLDJ_nHx$(yKu#@6vH
z_B6i8eA8fs^7CbPu8Y$eEJ#bGNU%!%1+0M}T%M%X59X(8?QiTI+Z#SCTw@V83ll_2
z@#hfZY=YO%LP}v{L0h!u^H#DVtTRG*s>@DR@z7OamS{4#vx-DH#ZKH}u8)Dm+J^h3
zJcI;^-8^TF`8tvhXU^%9piSa=quHQ3+hY3l0IM!K^#fCF(zZ+kN4A~ZDs`bNwz)T?
zw)Z=%_KwZas!lTXmpP0(G#x&F-?!HpPNCuL6xC4+qwdCcFuC*4V{-2t5tV(y0>Q9i
zy>NzkoWp`Y1!s?SiT6s*e=_f3-;uXzTv>vyMHu9tuZuq#Rz*+*?}X-jAR9}Nv;6;X
z!hM_eWhv+bFOevncs^3{nQ3ku`1=IH7eZWnk~6k3?rL*M#y(dj(cn&IC*`mZ6kJ!1
z&vd+hk|etambwrWRSfR{XC6;Wum~=OS%~9%J~UXG`3AHa#JB0)QSSr-XM%(4_(SRw
z3V^CWQv&aGjgLdf6QCwKNJ~wHp+@`*DxJ%!f7Vw7{i3KT)K7}@li7YmKhuC&xG4^1
z4;=k<iO8-9R1R}m^~k1F@1B#a#sBYVZuLwmdqQmU4CgU9d0F+5)l0apJ2fgi*U}b2
z6W_qd``21<OmtBf!g$e~;jzHN3hf=!)^T~s<IyX0bDR9!<@JOyE5+)dAHy3xQ@}#g
zcB)*=(nMqW7x@rbbKof;nP(Y=wY3xEb<*jsH!VP4?m*r4wrW3Tec%IV4IQ1O%qaZ0
zKZv$0=T9Vh6JD|76@`T%2W{K_+k{Bsgs1{#>!T`hb+TfE6Mss5P-%UVbi3d^(WL|Q
zZw}E>G70D6=;42NO3H%^?B=;bH}Toyo5gbxFXJ_Ht+Z0S5V7(L52>>ZgVB4UES_|=
zxcQa1n)R7T)2vZ{sdE?Qa6Q>L10bC3vmC1inNPjUQ*aR!Tzz{u{)Ag$&balSE;F|<
zAgA()Mv3*pAIJPdZoH{{rUq?l+PQM=l|AUPW7wYyd6{39u*guyDvY}KFO!wkM!`6V
zunlsN>W<9ObM-$*P`X00LX3(5*&sO%DA~C{EiXf3z?eBk?nbj<C*ZB|&H;6)z^w6!
zJ_e=bgB`mDVzaG9CsK?q1zoH!a}_)vSVYSWS@Qt?ts*_?$^Pa6Z@bst6f{{LcQOy0
zE8lt#((!{W_S2J$b0Wh#(ejGLn5XGV-`V5#ib|9Ifke-P-ZtA0eyFq!x`qouy~ZQ7
zKkz^5GzADh5_{QcMHfFJcf;Dsg_-ip?WWvaU%7O7XZ29<DLn><odC~fJ^FfqtEr0C
zEg~S+<XFNmH+2892{SQK;4eOd{!%C)pn5!5Y|2y#`KMLToA76)N%#*9#V~>5Q}JT`
zabSXh=#7#d-OR&J8DYu8*?_WzsH+cLOM{S;ugaKn9D5#FDWt_GNhi`o9>=b(ZUz?;
zpeo41xRSzi?~YqE8IK%lL8lyAFfEOvg$FxLWpvU+t-M<2odaL7L|w20e2*u6@fTzZ
zNniALPdap4E_8c<nG=cXos-r$jRlUrbf*W|<2vb66Z)2Y&{ptoXvWO6)bFQ9_tek2
zvfi|m$kQ)bvku|Ymy<_?_;2Z<LYucN>+kSp5#}szX#QgIkbmQ-fKHWP@PB}7GX8Da
zyw!1}h^+v^(FSU@r)3i_rs%L{E}LaV(FANYA?-mQeq#+pZvHCo-fl25TOOCNa57z<
z>Zr_^!E<H&%EI-8kpDL0Jj*PYgn-Zp^U6;tJ>bdOT(sPkQ%;D@V-_ireJ1s0=m&Ew
ziI31KMyE0HB^+2b^h+y6Z9m;rG7SB}p;xLvT07v+@MBi9qfr41_cn!7KHj8W(Tus*
z`{w(w;C(SiaZ1=hw~<waf0RIauYJ-KD>^^Gwu1}`!DD!HIWrLci5U|}gpCV??fT%T
zkWOg@h#Fm;pi~(9uOKWONr+9?18?kjBxC<ppzzX_u*BNey+adef`SjUtF+<~&I&u7
z;FYGMrMafxVHVZKJKn3D>R-+Xvc(EAG}$C$-Ymh>lnE-{mAT%htAUt*hE42MC4^If
zMPaP|SC3aCq$x(3%C;s6C9F!7XiFyDzYOVzv$wFhXV$4$dL>fW4FmtcDqU}mbRSCs
zmnS^`L_JZPNAy*q^uo0FRl^#rTrb#2F?3VV^>X_9k<2iVGB^=sPsAO0bED9Yc#h9;
zC2E2&z;(Qj6A14H=)^I0OoKYmj<zR=_;%P4QtV?8*7^P&fHU##|AHF+{VDr7Abpbu
z^xv^*LUmd_hCkZscb5M(d-Ok~<NvRS;{RzL@j&^YF2C(^bdKAQCjkld9l@eIKyjgR
zu?n#U1I@<|k>>9OByCGE*Gp`zgBPk+t$bMVU8vS+Emf-ak%gnlH?=HVU1-i~RjF!U
zXv!e{+kG)}Z|s~3m3#dDNZ`2X_Ppt=dolBLdl88P>XW6C4*>d94S3nJ-|DLCvwH0W
zA?OR+`V<L>+cUP~2LJ@nUNL;MAiqOrp#jdXfmsZuuaRZFYI_2=F|gls{yDb-7?(;0
zU_MoSc56k1gw&J;gCW2Dj*%dz+zX~a(_mn9$|*I%D+9$ess)+g4*(83oPqVmQbe&s
zK7r96?GDM&MQFE-%LD*Szs5gA9RL=rQFLMO*n_Wwc8-8uxkIzW=n`n$0d2Pf6D$M;
z1NeXbyRwE#rA{p4A&Z#%0rZb;4jqA}oP!}p^woqb4T<h*R33=<Q-c}M_<@ZcZ#H(v
z@oNrtz-(dnw~Y8|5A~s84<4fc<{5LhIE8%hIF)*I42Qbk{UI84d&D|Z&N6M53b&NJ
znOWj?srS$1SXmk0=*TqqgSXo4mItNVA(I}{PWZT0dyZ{^St;Niyt(;%5gv)rRj9mJ
zY~&Rp;tYXB4W3NGQpS{9s;2Ke<~6leu&%CW0PNr|kd60{ZXr4Y5A7z0p>WKCe5p(e
zL50p{hblj56%LY)xKcIZ!&#O<aT9)_M_K*Yy=s^@mteyfaRvLxU)+xlohyJ<aO%2a
z{n`*X{85UW1iPQT0(27#zRXtbx^wmwrGsVSOo1g;v^lSV4u<pPs?;URgky_h3T#bO
zXox0AMJ<E#JF4KLTvozN2Gnz@bzhb8B618`bWW{p#7o#^Mv2(v0{GzZkKkAZRO#(#
zM(0~dq~!M}y>5vy9r46FE;k=fk^Y%VZmZ~83yp)Hm60mhZ5%k9gq=$6ff5Lk&|{7;
z%3xlS)5TSi<js5}1rRS$7LtPc-wZL8zx1Y|kvB7&{2Be1H?(Rd>cBfIH;4^M*2G{)
zjiIr!pUAP9K2_n6axkGA@Q#tj0eW65+Vagrm`j7Me$%Y3%$bT*ovBuQ%0tw@)-BB<
z`Dt>ZV7G6qi`al;++y!cHTdQ|ns#LNLd*87SY-{pbHvx85!->mGT7<or|g)4?UVB%
zw3;CAkVGA7mOmA9#*EV>i_!!Svp`sCj21L<AQ%54(W~^3_QaN;H0YGmZiXs<25J&m
zwo12YD-lcqkB^gHaI<o7H7m+rEMT0Ma@ag-oR4$(pwET`Cbn=gK$vqd3Plb#-X0h4
zp#@Occ*?2Lqi>{c_4%zPDQM`9$!}1z(>bMC2<7P`kW5XBiPLVjG{t~v#k#yoWegp0
z;$Y^Oq4gHKmQ%nfVR|e?oaHQLsW!6v$=*LcchUsrd~9;FTMk`tSOhbg?`oOar7cK8
z{{4MP0$H>e<YF&RtgyPqwb|AElO)P`19OuO{aCX(G;Lf=IE3vfrz`Yaor4#uj()6D
z9-+tTG-Wl>p*z6F`eOc7u9Cn+X)HN{KT*b<YjhMJd`163&qW&L>inp~m5iB7<KXE^
zygPOYp;mpiKvL7ef%=Rm<2FF=Fwj@sY<--m6{#7J3z>jAzbau>iqJ-c#{Chox)I_q
zXK*(rd5G48r7J{-43|`6`|l5_Ywol(iOMj;y4$%ha3aymamw^=8n*@lx{YB7nQnwp
za6VXcIO0d;O-33lSauWSmC|OQZ3muRmJV|cbZ3_x%~w5uR;udGDO9*Q-x^<xunJpc
zLwLSkUEjpv5i>=zQ}r)_vaD^4(k=8UTz_+@W&DzLP``p`6o!C_>>J%Ye6P^a`TnIS
z7)XIZN?H|2(c*37w921&2X3}HJ)9>+i-&V%T0s*V>xilMW}<JcNPI{MI3#+pZ1_QW
zA`fX0wHRom@QJqH!%u5f`xPFU&}IEx%>NXI7w=%vW`_tARg~^%d9{a~+uoRRWrU=M
zA8vgj6{+?7F_iL^?uffIhGlM*sCk(|b0gCLN6i03hx7J_A<;DDSZ9D__%otSx`c;m
z?x=&wkzQnC3`kWfQ=m5)bj?LOWSR{s&`Y30U!PJVtqPi0aG{f1Fm-X0=vZjkrj(Ra
zDzL83phCuF!`-_wiEAQP_nMji$qrxKdO^2Q@ARpxlo^stK*FOr_AHp}&p<)#gmYB9
zI{#1%u!sB@1H)p=-DB{np3ZV?qPawRvFwF8?FjoyHKbr)ivsot0ZGji+ieT>E-HUZ
zt3gFd07b<m`*a>v(XAC8JpY7;d2Z9F?fQ6ByI^kA?$kXHO6bvUOs}S;J3K4O8K#vQ
zC0-IUkR5Xh7>VH3NTtf!Jt{a01-hM%#G5KT2>xjef7}6MaS%s0N!?T14alf&O+CL8
zz8JNM4fA*L*m~M>RzEpesXNj{-R1YE?o#s)VYUDUssH^V5T`83&wq<i!O;|H_7Ete
z<`3MgsGgu+_F&VOdYdP_^L|xz`b$wVQr8semWiU;868*oipd|#xU*`hrX{9os<G;m
zV#aZ{U>)487*wdNN3pD1+)8mPg_dUoex-0{=_5Y8yWhzCLtuOLM*H@kt$5}Arx=n3
zKtmfasC)(KDIdt&o27p2qoV!?^<BL$^U55^W1Uj5PeV%N)TD0eBR9Ny$3Wc^U_bGi
z8fkyP!`xG~ukU%!_n8%WbFgdrDL9O9M?md2ba!a{DLVXTzZcm{rcPP)6SdCh^ji%;
z<)Jk^d+UtW+sA-JZqlkv&7<-O-K%yd@EQ~StqRb5&4Fg<i(<Z3am4VGK}(P9bVL{+
z68Q;~AeSRcCqfJ5gP7aJ5~5p_=0cPAGn>AL9+OV0q#Y}zBt#sk1(<92(wkd59TljY
zw<O=>B>hmx`EV8rsJcbVyv%MyxN>Mi-E@kv`RJPFsO;lQt_3S*t~Julj;^)=bKFtW
z5nqkO8DT|ysM#MZ#fSMWPu)w{e-A}9?tN1*Ad{XQSqqE;B3oe>pFA$lr8bStnQneJ
zA2V-uYtH26>Od!$7W;AUI>ltL&X?lOin}$f=|!WG^^NKt73;vP72s#Ko9RhTxhX6)
z)OI|RjIZmsRWvDhWHnEuU=nAirHlk5oHz;3Or&jtD>mf$^b$E*N{BPACc(tEoO$cV
zw?~^SVP0j}{TZfkw>C@SWasAf@pt$&OsMNOjaTJb=PwCjU4KpF%ay<eX}GqlpL*1j
zIYBe1Q|_)LIqzHJC9!n-aAv7*r$_)FHsCWa3|!UI+}!S}s_gtx*<wmZH(hh}1cPK|
zA`oI0NEjIR2y4_H<B__km_5yGmzL5()F%!G^)W7I;CSj8ToDtjl0$>uX)U?Tc##MJ
zJ^6tV{=VA*LwmQDUTTy6<Z^i3Y@~>@?6P765ktAXxt3ZZfblX*hvpvqW=MAm10Kwl
zbZ(-U&7mBRbEIhj({IQ;0P4(awleJ}YVh~@r0R_QKt(s-x}Kgeks&S085qkH`+KGP
zL3DBsJ2Q2aot;)^S!r`)XKrV1t0{71@_Z9A(Gs*`C<!<m$|-{9o&A^?4@GXd*wnXy
zJWrDJ@7oOL5~fyJ*afATRxI5dBF(<>OhIn<*Pk1#O+o-`h-9d_bmWqdvf3ft;U@Jo
zWM*KhBKsI8CKoFK){;h|*zu9{eP^Gfe5qrD!rxW)GgE5)SPiO%@c1RN9^7~$x|YUp
zBHuQuLVxU)u5s$~q3R5?8y803xtE00?}Tj0Db%CsEfb=N-2CHK6DDFIM`^lN{;*FA
z0zzh6w>bg~afjfs*Ib8n_nz5iu~g;KmM__a$^M{a(nqU^$3tAP4teFVzyOiPiZY{Y
zK0&*QU%_%78uv8z1L5XyK$iYlPQQ}<+Rq-V4>1m89mA}^3W2k{Rm#c&FywAWTyX@n
z%&>>ixI9y1-g^YJH#Wbxdha;!E?5~S=o{xNoi=5{@cD2VPd$X$28kQVxC9m2_Lg~?
z%kyqNY?IudukJAW8|rFSQS;<+dIpjF5ubu88~Dgd=%o7b=ZO`SZhUwyBN)6v3s65G
z#IYoZ0*xwxnsf30-25%cY$u<5GXZ*o)7ql{d(ByE9QMyRFo2R6B{M;$Jc<C1uF(cE
z6DcNkGMR+8J>=;18C%hcLi|Yx9{q4~czYo4J%Km*p=`1LV+AqJnhQ!lxOiUg&)Cw(
zY{RH19N#`gEj-S?VnP6XD|Bzm`?Kow<c4-?GszO%U0-~c5|Td`F=<_s)7M5u(gMpL
zd}Uk)ISgd)U#pk%*?%X1HYUlu*Hn7IOYzAMkcQ1Pd26wWn3b&AbJ=XI{uz$n1V>Dc
zKl}Q*;ZKeBAJ!Gw(0^a9nr+pXb`oU_OgqI?ajXAnHIW+pK>)6B`z>)S(_0*hSgW$*
zG(%_@Yt98Kg#YpOXJl!m$@=%DQyVw_NwrB#O)T;`SOAg$<_T?RWd)7eOBM;kb|B&K
z(7TC8IDoW!cZ@(jXax!64?1#x#qostPlGVmkZ~C0EsLbt+EPVKzSvxE9lZ~toTQ)I
z>S5RfuDVRE8C{SeTY46R6V6Yv%EOtjAmLO~1sycvA1=##-#UUQ5(5U3|1ij$g*8()
zyg5+#PR1<>h#&e>&LgijkiaNN?l(0OQ#2+QaMr{-Vco`=+q00LvY02V$-DEDkdUjM
z6YKsIACp4m!}gnY0b+rc+oZOTSR4GYQynBgk+Rl}Y_(ID2~$mXk3PKr_QLR$9kaoR
zBsn>H3*^IgxBi66T@O}#*no8~qCfrOUHx*F#$%xylsx=I4Kpep#8}5@`1LjNE`x^r
zHu7&`1XFrb;l>jy>a&m~fo!eYJT8ixAnq4JZCFsm8WoQLuRzPd5-Q`OG`tDp(Pm$x
z5sYk{(E6{(A&6!0l@_v<7A#2Zg6!hLwv;v%>UN4^B}Ls+dIt=<5NV<!OqIJm!X2l2
z(Ae$z6E2t)OqdnfU@+I#{t;UTNI;fq4d)5!{iBV{d!=^FLB=p&fcbA%Bmh-pzm9MN
z8hlE4N`hU<pJT>|2EGIO`gla&WtTlk!p`=*8|?m8?TG%azlnn(h|7LNm8>UfQsJg#
z4`+CWbQ{3IZCwbll;*x^DJi&`N;Jh=5HMrE_B)QvbqQ#z)sS`88(FDhN`(6b1K&9&
zx1<S{)T@p_tO#f$`;7uzp|b1;$vG>1NN~}Diagiapi&ncEMYUZtgw*Qy5O|bNKYgB
znY8npJHo4br>E&xX3A5C4Lo6EuYwNV4a8v85-pX?#XZF`{Jnj|2(s$~X#Ka2m@pmj
z9It&)#cf(m+!Ht3!PRW*=#N#e_pcD@L3yb08UdnrHe`RYt}IR{JW1aee+T_KXCTSb
z0jAf08g}4~4ok`h`5h`gw+D6#MBqU+aEhwRJ>J*};APyCz8%a#jleHHeW3034ax78
zP~0<yCe~K~T8Aq;faFA>7~s-?$Jn!JLp<phTLZ>8z;b}f1y4JOaUk0PRtMxbu<^sJ
z?%_Dl`GKqg${d1JfH<Uz0O*#yTjZX5ZfAsTBHXCg$+5wm#a?aN+}PJiu>mm)&}*bQ
zuvsOHHVMCj_|M4KsJGz|q+SLF7lP__y<qWEazjUpPXLZ*rXIpxFuBP)VR#D^x6z<`
zVx#|V6OEa>F3W>k@mK(OiAz<n?YEf+kRIEL2=+hVGdEm>8z-MZD#n0ACTKs{6D3mX
z;0n@+2PrFO1AZMKj6m6~n6RilCFXMRbh=~I{Y#)WSbB=64O!r{6P5k<v|E%{s_t$S
zyD%C`I}B-MLu{!hABBif;kHOGF;1M(!DR<HR78C-2Rf02nKD-p=r-KNJ#&-#-<UU)
zME0ElfgT~C0P(<V1arxkLAhJ!cmQ4nl%1Khl+tWJodZoj%;2B{4nR%PDr*m;sVM$%
z8AdikI<X=cu6UO?ahS6W=9(NAwF02-fB@lkz76x@xRH-P>Jd?GP4<a>P2qj;$p~}5
z|94IDZ++Xg=$6)}4f&a-i(TL+=RdijhoGhhN6gMJu=AgI!5});yU7~$pa`=~62K74
z4^*KWrC66yF;s$Feg~YybdA69R6Ct?u;|f?VhXzxXJk&RcwR?~+ZLnEa+-tDjpFc%
zs0P&(_zSWo5x|6nFK@5`rTl{EJhKFsd}HEagaKRRhHyssMMmVikdk_n8;EyjqBW_s
z4>mcTjC?kp5%CDhT!NsCY$?Q?fF6HtKP_1--@oYCcak_K#m5*6648=e<e~fq3k`&4
zN~Rad#UB}r5FTlm1C%3ib+Y6qWYHT8xJ6S%)`w{_MNbb-tuQZ`F4CQaq<i?@d8Jz~
zDlw(Ut<IQcU6jYYfAPyS+&>;|SDP>!5-jVT`B;oXbSbT`9*RP|{=)x<XwH?llOvb<
z(Y5v_k?9Mp7tPX(@mVYTO5*&ZK(S}ocU|Q5x`!`gwcp}9ixlRN)W`%`hGIy-2+R+*
zW=fryL`9;LWU)+zp~V2dy~f0RF`45aD}i(#CTibXHUW3{_Yi557&zzGXoUKt^_HbN
zfTz&xCC~4H{}ZA7hR(NJ(klZ7MxhdqOFzTl&oLLwQHIvHi5cQvdiM>^h4k%S{PF!i
z`gR8(oF`^K!VDNtARwXt-PYHC_3Zxtkl`hXv%d!f5l4DMgiF-!7|#2HgRsko$n_Kv
z5<M72<y5X^)&=2Av;LCtr;=l%An^Mmm}b*ipa%7OtmkBWJ#*|feY`(^f*26spu<)l
z#*b7+1V*rhW>W<9sY{E({?-+@O$*z)fNUMqRtmN28<cF?de8`IsPwg{f?WsgJ*grI
zy;vBsZlKswUaua{MQ*L+=IhxqV6^&6hI#MWOEI&bPgO{>bE#xnLC?2idpoxJR&G%q
zyKBz*xiUyFx9>RI`S)vhL4(6KP8o$S<qWQyS(Xn?q=0UT=_ZPaK1iGTTl(!ywMGU@
zBA4^-Nj57f`g;2oxYf{TTl|-1=(#|t+1gi-M5s%}7GvaND6E(ABS#Zxq!MaYdI6in
zI{1<0#!p6Ss)Co;HP3=p>m(_OuA^6O18+)64Y$(J7+$i_^Dv@>WP0@xoHq89{_36f
zfS1tq1!{(TSQ?}$ED%XybE)#k{l7O~fi~zEHo<{_$bZ)N#Qt}OC~9hE=xX!d`mg`P
zanh{rt&Spr`VChXGf9jJCZ=80Vno=tp;d)GbibqllA1Pb<+x63$Tn`rfs@>GIoU(-
z{Po(ZpWng<JjwM1^rgVp&C)pnCZgeWI?l!8Zg#!3>pR_@)cgJRzyKtFV2%}c&=rhf
zqGG@rj7c!+W*{(Ps?!(c!>t%4B|Dxz5*;1oAyvAq36=Kx`Zsve=OZ%OtBcqeUfsID
zP){7s1<J9<X3Szlm=3vZ;04_@y=|mK|0Iv}yO^|?Oas={c(EY>5Ye7+7oqWuI+#0e
zy^&bjF(RjqH(7cNXFlYll({*muxMQ>*BVzq!fV9^rP|2mJFkGz+-ACNCEbWeQX6Zo
z%X9H=zG048`KzX_UqQgC6i$9GnLV#KWkgYCHIXIL_`bbY<A^>JEA$^RkaGlo$FY?Z
z4dB4URRoV2y~$>QP87Fkp;lZFzCzoOju98CoJvHdfqU}VH)YF!*h{89Bh_o3NtfPy
zPI^6auwo~+C-=UK&$oCsR*EHIWvg0*dJFRO_G&pmqK@A16&`<4saVRHbK}}nQb~ql
zNotj85vrCB%1v&yX#tj28c^zt5^BfgNI&O*NpEihig28q+P-tsAwGdFRQz~h$>5!@
zz)eMXwnG(Kq&-|vEdz6aEu%?}u)748rJb5!Amfn&i2I&T{>C3D)J85-<l`uR6GFsV
zPLCs#lFF!soZMpH{0r}IfD<m?dtD>H5&C<TM+yJ2i!BeL2p4v0DqjP<H6U?6bFG-$
z!Ques5K1F|Q3lvvb5+f#392z%wp?BQy}6lrN-mY6rn(4+gq%STViK*xF841qJOC<m
z`(n|Z(3<=pbg*@nS>=IeqohwrydM}hd5?O`NU9%hE4jXUkFARy00(ZrPY2bC+7;uD
zTFyD)K<>duKlS6rg5DYShJ|2{3JiR4%)0mp2u48j363N4Dcr;4KZ?p@g0*R8I#g~D
zOj~@-j`|QDNQ0i)iw&+r^@*`Z^@+Mc^@$@u{S41*F>xC|Wz2>pGz=<|BhF5ynZNUa
zGg|v598;9`9v$DPMPe{0pSRhR9L4GwKv-=Ii)zgy=>ko?{v>tmr^p;Ukx~1OxAtTm
ztaXrzy{<vSs>D{QhF&QW*~+~yDGSeG+yrG&{=NrrZleQ90O4+AN7>;?#f}UQm-eiQ
zHUiTbM`J8kJTr%1>{4wpeU_$2R2O+7A*AvChI166+dt%|Qk9i)xc^DjOX?;BTGDY{
zWlDwSbQoLIG8wL=l5|Wyvb$kC^=L33I1t)1eJcG(P>b#dxZAUd4wYu}U1I<MA9_b}
z8F&Q-PPG9hW-P_ENiC&ExArDe25{8rqP2EUJ2bZoIbyXr+aQ@Et0wTI3C6#8L@2YN
zaEs~`)74EL_@16P3v}M=-jvZ0U4;F0igXM>XVFz9u2#q1H>;yc-}P?hupHtD0V?dn
z3~B=op;N(U3sDu3JKLmHxtKHDYAdC**)y1qJ&qN=p&f62@7hrDK0E6Xl|-5N;E(qA
zQklB>4S{uTqH2BD$f^;8k150FOe#NsWTfSNM*!r2fBwe2P$ID?4XYPTj;Je=Zh+l>
z(F^c2*92oF*lZ7*%2aLs-v;Wi^Ie6;7dLq11g>B|v{CpEXb=jpY6>rc+(Ln|t#ISw
z-zA8iphSiK2MOM5{qaHBB3IPOYuM*zBzRnxCf4P7CELG3(RdfIG{p}1SXCEIRzVqO
zXNXwiV{vc&DOl}K9N+n5`rw9qK`0_Vk`)?2W(!7Jo70}<i)LReWG_K#tSxe5P|xB;
zCZXNxT3tH&`fEJ*)Ck%TV{`F5cEZ|4BGu;CM&x4N7`?%!G$<}Q!d9eRJY}lZJ_zgS
zP?Zc~d(`K_VtjbyFFNK529wfP3u0VODVD6Hvw=5i@=@e4N!?YCL2s_$>YQaENjNVc
zzLV==E%b(ab`?bo5sq#t;ZnGG-PD6qXjUluNJtBDT$6b^MW3@#W+MN={P){qIA{1k
z?xzG01OWo#{omal%BIGyPL?j7q_T!yo|5)9CZ<mRHNDGG)Rh4dLghPHt-Z)J(>$~0
zdla%26^jQW5*si=h@3lUgXjKxJ<&$9)|-eQ9Ox$~K;6-)$+ro+#qzS{J<G>PkXLsD
zG^4;4FQhq`8UQw-S=>-#C?OIeWY4O7wQ2Sh3s`$r-Q737h7D$mSB8d1XuEi+K_Z};
zhru&!4o0EInySTOW;+|-3ngm*GiNBd{FQ4!xwe2Z?XZMaIo(OmM7HVPwh53He@m1F
z2jwzkwE4&DeY>5j0Bbh*5M0^m!;GZT`O|*f$wSm!w2tj$HE;S<;M&&{*M1PVq7dOf
zBLB;X8LOsYEF3iB@FrjmJ8V&R<Wy(R=N2{q<sjXgP@r#AF1qn3Jx69dbV%6<iDmfi
z0L&gYNj@wqn@b`;|7q8Uy#nQ$>=))<!Nc9oL7Iy$*+a+{=l&(7qcAB>+ZjP@$eLMN
z?SGE(-;YU+F~=$z5(sGY=aT>Nya3rdnKKwV7#drcGFVu;{XC2fT?}pP%^7SB9h^)}
zT#Zc`{xf0ykL2b5HObbfTe_pHV)>0|i6=sUnxPSi+6awcf=g01P(d+~Q#Qo(!vJTs
z8C%jKB$y3NjTyjFX>PD;w>HTY$ZQnXbe6zL(Fj{4)i%jx`Pm3OKW6(~Ay_Eq&*mhU
zLebz#ddK>@p3HRe-#qlFd%a9(+k>t}3rN%>wL`+D8#WOV^ebvGUqXWHG>{Y_3Q6)t
zAEax<O3Z~rIl2k+{*D|?68@*chd(@Onhg(Nx;u8fJBGSDmNGm;d3q(yO}<ls%tPLg
z54)9xoQ=G4MiRa2QuuDt;3qj~M5-QmFnY_@$VDmTXK-T>y#@DCq}4|j*M|j65+AcL
z&rG~V2ESDVUZuC=FJm3_7HNhCTbv-d>d2wu@@3UGMZ57TdM%R^wf%T(&BMU-yDS9*
zd$(n+k&oTZLsxXiVl341xD$`0jLR~V8bK>dqD~eHcCi+1p|ZH;Xp$5jtgK{ZqR$R=
zlq!qNre%rCj_K%hB`qWPt|}X~XRW@X1N~04Gi}XAo1dN9kbmuS7+Ki&k7Hy*OeGXE
zS+%GZuaq2b!n1ioXfBVDdf~}%FuR~jWvmO&oT@q7k+YGW^F;u&Y3GOg3^mdlK1@r9
zx}QN6Ni=6eK-d7Ax(4$~X=a{Ve29^C4V8!xk3f?iW}nX$saCn^?$98)<o@2+?mM#(
z3OU4I#=ls`ofvyN6Fk36_}d<Nctdl#-ehfu|A4hR9k^{+oFuNrGt-xdjIOTkM=YTG
z)mh21$&a(TPQi0(zI`cZeF{C!)g7DZ72Kj5cS(z-Z|XepiruLs+@?N@S*cu)IW_*B
z!NY<1$2PQP$|6?V$#&o<zI(HY*9ztlcbiqmOI;Z-D6Vs+#cC_L)W%U)5}v+xK9DC-
z9O*d6CRZW8pget6Q8}1&hY&LIO%uY^a;y>?_;JAYx!c5Gs5z0a&O%vFfBAFyt7s}O
zmS)IDZx}JgHe?&h7yJ=;+uaj0viKc1TUbK7=(43=u!NZvrVVd{rGL`@tkS|NPttAH
zFKuab*Z`ZdXkS!cW`M#z=^@q6aVrN7wMBGb3f_4OU1I(e7HALHL{9Y)eE3U;>I0z+
z-4k^~^~&#;zZd4A+8=jo3|<EXadOMODc+Cs3U$}E5*utfIOv@SiZ|HF?RIl{bBS}k
z-rmcwp0>5g$6LKuHejVldoq0gqviCF8K}f!8MjfJEML!2D~(@-Ej#d#p7gGsea0#D
zG>*lR$rvfmHS8SW^)MzQ9{F2>zm6Dn<g%IL+kiC9Rca|d<zQcs&ZU(~ugrT4XUk(2
z%Sp{p{g^NLQ5Z}YW?Y%jL!>Ihqcta$E5v+MAD9PK%?>z$-WlP6_6yK=GV>!;M*Yti
z<rXL4)7~)xRpFNBQ?H*OIK%x;f_gM;1y+uI7=i%*FN#Q#NLgqoJO{^c*l#wfSCpNk
z__p!R#!4@5iC7CN^GwV}1}JtlRdpE!>Ty~?Y}OSO6b#E^O^3Bv>@BCBGviET^=FNV
zjA>MBT!k8gOaT^EP0bm%yPmP-T!-qTI2{i84(mngQ{1`u#+TOMB%1-xl4D-F%Nl+3
z8rcp*EJYF<C_?317ddUy5~f%qn_2C=;0QB}sFz|_3&3mik~Pj!t<%bx`E|)fYs^hg
zdx;&XHEvzHt$Ss2T>{k|6yA)DghYD3^$EqL;Rn!PLQOQP;Gv4tF+zRH?W(<IS<atO
z-=#*+LKTMV>=jE}8G=4qABUP)Un5S=k**#8%gwBjc;DKJZVCdoad%-IXYouW+IstX
z>?j9nW%~gBBq>;%%A*^H(8yAArq~gqAMMVnsL{7A75rG{%DTh&_@BP|#qTPp)NE#F
z&zJo+_%|z`oKfk2q3dG=?6e(iN^LL>vss}R==@}_R1u3$Cqy|1rSR@fa2;VZ4jAgg
zD1B-^!Fh%@gWJi4PTPc^<z-hRPhv~1z3}=!%PeZ&VqoyO67_6zK2S~%s3twB+Cdmd
z`;Kj@&$e)4Ut*#&dm1Wsnuq*L7zL<ICw=!U={PAxe)w$RC*=Zr*T*fPMFAFV;hqqM
z{T8nv$E%L$94+F72{IP>;-ZrB1^m<;^yRFmv^dm8fR(wW<uddT%;UnehCWyNXR=+z
z4y`GTG@U*rC<en#F;RrnLOUICDE0hsZS1s%0$NIVyCWeanwf(Z_d;flIwY#zs6)y>
zW59Alby#q;Bgm=7bn}~Ity$qW+oDgvMjJ6|xC8JOZ4g{rVNyGvW%B{%jskl5Ls6$g
zG^YU79)!BWIK2<Y2<$(@`Ne{+G%4n6tmjRIF|L^=j;+oZNN58RmN?hf_**p86WhPv
zD?|h{gWM+G<_O=;nu8J;`ajm>W`RfE<u41w<B`5WrNoI@u6qxJMo@$?<VMQR)~`x+
z<(=&{8?!R`=;w*m9kQZ*nV%<5ZPVu6!JXSCPSf_&hFf!d_wBEH5%u2rgD@S&J^Ukh
zgM;t^xA-D3w~aYE*5oIW973IN^jBIs(!<hAS{*%NjH3s$;6px~jIK}i7ZqgseG}Z-
zH0l;uBw)-#cCavxU{wjGeD_1g<x%H3xiUt+b%OCc0VRjmzaq5p*jf$4i9X8n`V2Ap
zYn@IYr|tZn+bCSq8s<U_zR#5+5m<%|eWt7>)%s3G9_GZVxyMR%wudiQT<qI|;kK&j
z_MaOyj*hxk<Tj^YXaf)VXIEV1bibnJ5E;THvvny+Gr`=mA~hK9pW8j{%~<<5y9r2G
z;*7b-5l5lmBc#NgBDwe`E`KMH#Wh^VHKNM5d0Y~K?x#!4MDSu!iBm$jpAey#eQhQf
z*})ykWM)6kPar=BipP*1BiqK5LyMvhxMRUFkC>c(_hawh+ixH=z%P<ml|&I!$QwUo
zt=<0eIoa}LXDL;4^c@Oe{?PyL<&EP-cjU#-0vQ)O5RmZyuDtnAX`^InZ0}^E{!@(p
zUy{~gZ72_w<)`nQw4>>JVPPOsFqdE;DaeSxNb+z|^ax>LsWmYlDg5z16Y?opjcRS%
zW(!@b8rLcqRhezA)?m@|1*>JNZEb6`nij1W-zxv<@9dWyS+m46M&RC??>onnosXIJ
zldZ;GZ$QNN_6v|d)dVBL%!nPw%mBV+&(q$Y(_{R88PP}x#fe)5a#K&rES0yt`@}3>
z{QJaGrPwK0q;egEqj?3aV;TE&=|NR&Kp`kE=5Gk-A<4JXq#dD!=tO|USxmxCKQ-Py
zaW4eKVgWNg%`~SabTJmgG?*oMrOIi)C^a(k@P80idYQ5%delXO#auciRC>t^DsOJV
zX|cshDY5rP&~ix`MXKE5zmBL?Js4w3Wt^+S)N>0K9Pw2Y64K0|f0sb8oO&S4<ZI$*
z$~l{O)zUf!vOa97h*4C!Btke>jEOxQxd*T=(^on!3cu&FM(L=~BsrUyyW(rf$^@?{
zA<&7mVn{4FS)yXpAhy@4oS7ih6e@!`G>82r+m?AkmknZ#x$k$F$4<#qu|mHC=PfU5
z#y@TPotY1N;!z$V97vF=R~5C=Nx5G@Ieh4x#rnf}7RNEA$x_*<Ua+M0)o1ta2%E`g
zDREE5;BsjhyN96X4wDP=D_@9H;Z}EZ$dwjQvxG5}WJQlXl^fyZTf$@|4z_$4OekgU
zR<*ZapU8X~acFC<=Bn?f)Fz;{W-{_B!e5*`z7w^DHUcN2u@W`I3BLQP>D$GLp)zd-
z8M$o-yf=%BR8ync9_2AE^4l?_qYD$pDySuO0M&UK9302*AX{jZOBe-c5aL1yXQE5Q
zh=bG+9<E*}8n=Kqup)<JB~Ugp{i*2@Vz7<^4>W~&RMQ*M#j$`sYiNPAKdxM=TdXlu
zKwwK*9wF}X3IUy^^RgbYpw%{E4JL^}FE~rW+XDeGzg4b6#ApIi)%b|J&xTp3pFwn(
zg1!;&6I+z6$NhGC>NnN7{=SD7FK2Y73Qi@i27bj$%4t_O)1_)m7bk6EmLWxAWf{pD
z0{j%p7mF^aJ+D$%(!2AeNbNAXX+tBHZ|a7g&60)vJhHpmzflICR14S)2lo5t(F>>H
zF8}m9Bz5n${3@a~RZP->&qB5rz^s9pWe>EWlyW(SC~SasTv)0w*-)izE!Er5w5S{N
zww&jfzCJSLoxVdo-*}xVh0S#ox36av=d9KThsh0!g<4+(EfBQ%WhiFog}>g5^dwSb
z0Y&7j);1rXjs%IdY)khfUi=$3QDpMdAqZcmPy&Rxg(BiRwe-NjnVk)@hFEe((yW@R
z?>;*r7VP9#p!j`muxgHGlENv{cXKHe%3?AUz<(*m#xBO*Z17t?-`Kh~<_zv)O+Z$B
zYKTp&<e^<0AV*G$p?U@~Kxaw)-FfV!Z)0hZgj98v;u}XryYce5i3ls9si^#s)(^B*
z{)A(ztq1~sc_ejL5LxC*)9Zz^L7brJ$l;nO^X-_<C@cF{9UjvnC6{nMiP<AhoDzL~
zs@J(%zlM4UU4W)sqUaaTO!!j1mVq!+CXG>3C<*znBPdn`_z-0CZ<s6d4&^fnYTdD}
ztO0Ub$Ay$4JotEM+NAW7QCb*|<uhAIh>L-gni}!&s60dX`JAG3N@dg(g>r4POC{n>
zm6a`E<FMxbc7S9Q{X5-neN-J!Xgc_RQ2W1Ki(<Ax$&avPg5?a{{MooBfX(HaYzpwL
z(Z@oM1?v@mxiuu?f~)~2Ic*~It&y)JO*>OyWs&8-D6-11QT8*%{&2RJA8U>Hj+^Mj
z(kdWWV9cwNTys7*H32qcIKfprPIwA0m+<6oqA`k$f`zRwWI`<_jCXU~66s;FQ7Rqj
zvnD?2hoF##o*U1!7qBzM2*>vZa`_RH_a4)mG#+ZOxUY%P<?ei>lVvg4TBr?x`t_wt
z8cPXRNFEfJq#g}+wRv}O!W6l%lFX_vxgOk^V+|a;C{|1*>U!9Z8cb<${Xw-3(ZRR|
zvB9Ud9~Y*T3)PqGU~^lna;<pU{485XwqL;l8n&*KdWB1KD13+bAc8}zbnnusmeJS+
zTSq{PQ@&i$^Zc#Ir(}`-d<^w=@%;3oHQdQQ@Bd-!oq{Wk+I7+H*tTukwr$(Cx?|h6
z?HSwZ*tRp1bll0#I%}_swX06mU*G+A_0$;See}k*%{#6!K&tXPf1fq|5Sr@AY`iXY
zvzrc&V}k(<D1VLi*oGVzcVybF+-SGU_F?oY=dazuCHhkLmsvjWw=4H?K9Z8v`pP!?
znd$LZV%a0jOx33e*<;cw1XpTgIlmwN^ghOkf=GYE2bl$VEAP+{UcuS9lhWQWA>iXQ
zJ~8}r_v4!ebfcZ#91%ESdP8+-u69fJN%RW#{j3=hPgJZKl22Tmq}f`=_D;^{EoRMv
zJlZ9m|Mbwb+Aaxis$VQsMBf~4mCPd~4&0sx#En}otKjgQ|BNLl30Hd))dR28RxK7>
z_=m$U7mq{%Uu5y;OmR@Mj|u@iNFsj06o)^KA@);FvE)t_JMt`h<dVx_1UxwhmE9)^
zeb(+%{Ci8BPgdUinYNEY@oA}d;EmdOJ<h*agYOo9$9DeSSk+ju!qSzFenNx8_MwnI
zc4vkARb04B#|SK+m{iAx0j$`XIWIF?vs}mfW{)9Uaw!Vqx}~$*$0W8dql;>pwIuV@
z3h3fyYo>`*nx3Nh>c=dJuVLC87>!p@+Ye$2W8A4rnx4Y>zO!8%fq`<Gp2~UMN5Vm2
zY6KKnXJnu3I^1!zBznzKPd1<Qoy9Z%H=$BQ_O}QDjdRpkfzmm)x13(23&VTrArXdc
zthgFl_-xt~4jB<fLaF5eA^%KpyF9-)wWQvF=%2B@CgwUfO{u*rXMK;cGF@yN^1f_u
zX`hrjw<kmCP&q%;1IrSMm|BtwsWWBL%FJl1$^dAb#v(qAd2@}y{NSi@+x43e@<1vB
z^?5H|nYc2zeW|h|8gHDu{&Z@alVdx2U0Rz-CBI2+%9*Q~bC&Hb`j&h$x!wFjy8Sb@
zKkvfy_*>Qy$!0c25n>xU>)Odd?}fhn0!|_~z5xeWob0cz>KnW<a9+RW=YaGx%{@yn
zs*6abw{FAaVEJmO5I!y&r3%VlfAzo8g}mi#)9?}8Ww%1(!c8JG&8ZVqK3Lkk<&A(o
zV#Ydr<8i23=;s~wFbKqB0@Jw2wtikdDZWZH5H6J^IHt_Fi2Ej#<Xlo_34B-Y$3uzl
zAy!lJ_c7i9r*<<gmq2LOra|VtEQOYFEz}ezEQClctZiHt4i~1F^FoL?WlHoXZCd_D
zbZ+&<j_E4%S`BJSPI^$P^(~jB5H@s6Vjz#X_1SO?FEPKBwQq_#qf>~LZNy)0M+X`_
zHq?I?9r<*JQrbIEK2_klEGw1Ic9aiS@6&hN>rOUkiBg(+XHKe%tg5ScjWTqoT0yge
zPAwMlbL^f0TS&={GyZ{Ax7D}9psEta^Du3@FEVhe&1->tUH!m~oW?4xID}~!!w>h!
zt(1(5+X?z;$X`S0E3ujiGUp28J4U-vF>=Tdw-Zl1-WyI?lmL*(5>Fu*mj&~pjT*`7
znV4*BmS16*JUlxgKN;QaZ^V@t9xNJG_DaLbkd7;tt}~g|YtSF+D2t`TQ1KMD;ywUa
zev$61$+RQxOP!+0EN=M@hU<2G@D!bXt#)TG0`2PJaoT@gQFhUxM!4~mwT=Oi-8-%^
z=&)na32O3WH+?LRqoW2ZIG9T?53}=hoke9zti^cf8P`4Jt=x%HTqL(}c&8_HI%>^U
z?)vgG7vQPOQ<`%I2KpTZHY*pQ?#r!yFjs;|j|MV3!EWz2u1(2~e>0on9b>q7)Qu|h
z)yex-^@UXISWVN(xFZe07wG1XBj=YF@vR-LjgN~ut2(Q)zW+H@GPg;4$!NyINc-6=
ze2O<e7?jN|1an4;d#dE>mBo$-873}KoSH776F5;BX7EoxjB0Ew#M+w0&+lNSP?MWB
zi3|<yNP{CKq(kh!U88Xd{cA^wJCTejS)qy?RQcLhGtUy5=hZ6nGxpHn*%G#eNk43@
zs92(=Hnp*oOVQSwnK^v3U*NX}gMy0Jvfae-Ikx1oU6-6L7Br`Lj1`*^fjT8mQMNY`
zf|Vh_uzhu=M*4P_fQiyN5wB+6*W2}8$d-KFhSKA3j_~~+ifW1xUUEfSk-`-3c;%s6
zB|+hJRGO4#-Tk2dua*j#OZKRF>EIBAl9ZrtMuJB7Exyn~r%e<j5_bz70{BY%di%vp
zuwYX;DJ*3fK6sK+M=@Wh?tZg}Yl=6KTB*0k)pvcC?D}k)PTAHPVz9K8^@|oyd`<9u
znE|*8gl)2un~x)%!m+ByuobkU(YB>aN5e2sh6;(H+5r~gFx@f)827mZTQgWCOB*b_
zh<c^VBQhMh`tLnm+SfbEOktFaq3rrlzkabx6zoj5sXxBiiQ~84(G)B4^ZoJ6*atu6
zDX^YIQQ_ppPw&T|;&cbBx1aLDiwS{Y65A(rJfl3$SIk&CdF-#*UyO=4UqO9_fwZWH
z)n0z?lUj*m1kJzb>sWu)kHLRr&oJo%Y0dT|^5`TezJ8{nrORy~(9Bw$b|iV2p{2W#
zG~;WJkn4}1w74@i@f3LUFGG9s@{REAp9iHc_PzF?ZitRsk0qGEvb3XmUt>)M6Z6Bm
zk^I7SsrEE_x&J^;Za@4DX@3T~$-Hp$7V@*&SBY0*eS7{IYp5qNK1-HH)0pck#s`j@
z*Xi#5L$qz^t6<tNHps+gtZ*SF)gp)OWXsE%!fq(%06zoZ#|r~aH;=!$h`+i>e|8>s
zd#(V8CI^7YYegH=b!BUnSsoxcTxzwU-<dGqzr0J)iDIXj5@_6=nS~k7U{yCDlpBFw
ztoz`s(coxDL)aEWZ_dXEekWu|L&}jxAFM`p8wq%k2XG?}^jr2}N3TXD?u}4m`z`Jd
z*|I_womo{e<?Bo@`bIfc=xx#Z2I%=1dvu*~AL#fSe}cC^v{=k-Mezcjb@RBf*0-lk
z!lHI70jl7)sw3Mw+ZpG10Nhl-SPKF8kaNAg`E|_tKu+=+%59pNd>eLKEU*0UY`b94
zuE`naqVXne)aG*&Dv2`skLvp^_+%dCmVTA{&=1x&*pXqSWPn)4Rw#<e;*+x_%RX^R
zn&lhIdhaBf-DN;>;h6hAQ=kAJw2ua!kBm1(Fxm@C7nAz$I3=(9@q4;VE}0)?sh00e
z{&o(MhT!qbycW98{+kJ^TY)aov-;D;rH{o4L)REPGq2tCuwL(&COEv_+`P{;9yd_D
ze>1O^bk{N&jUjt;a-V!WloN+0oLIYIpBqhBn4@MaAp_=YqK)8g#z4DIGO?l{Gt2D^
zY+-OmN#Qg{e$jEIsp|D?p_ZZ?>IDn#E9>?^-qnlmBaF7Jc*Xb@oy{xtjZmS-SHC<k
z;B`Za0-AAMJ%p9FsBI{`?;1qJS14BIlr%1?)$;5wB(=Lh(XUV!r__O?40y6sp09ds
zTa;3BXdf{y?TYlk4qhicNDGgGCfG4rt<KtaaYD(INtg69?E*_`Kvv%AJl3&Kj*<1R
zHf-L}tq|*jOHb2TglY34%A>hUp;W)~{>WEK=P!rpK1^6Zvf+$8q)nS?p;%~)f?xfX
z{*^0iqqu-4rOgby*8bG#jfg&9K&r1FL8jL9!@5Naj?NAH&@xK?YK$hu#)4Xl`LTiT
zTHx_<mXelo-r=GjH@?>S)cN29#s|&iDVnhE3`rx@aegQ0+dY1T;my>I(2xh)+t#MB
zn~^+Z7SEsQ%Z5D=3L(5=P+ROezX)#b;nP{ebiymKDUXmzSAT;{=AXPsZP*XT_a=i{
z%9uLMN_m#jTj{Hzf3dYDi$%SUq+>>bQnE2HUPlTsqwjkB%mU2313C0a^jQJu`;Unq
z^LcSuMTFT{=^DB%*TxFoY2pI}W0S1y`$WWJURS{&{KFyGHarhfQ)g=VHn`hV=j#%u
zG{6qIWZTV^f1^hVc6a8fZbrp`_cFMruNiD4@anQ4#fQqGy{@%8&jWtH2xFP9`;vP%
zl2O6f$}I=>+<_qlz8KPL<nDexkKtslC<YTvfmD4*RNk#?x;Kxw=;!7#LgV!9iJs?-
za>VskL5udC*l=sCydu#%IQf28Hf+W}&|Z-uUZERzH2S|+&v?2O;`i)*2yXvedZh~t
z`nEvc(!Rb3Q4ftxI=_fjj+ReSzsN!FyPEU&Dsddh9=rLK<^<QL(yx_n1#M4muNAkT
zQY)&I-Lp|oHm4L`mC!+pro;w&Ar1jCXSp2WzLIC|4onExS>wIt70Q9LgnRY8l^AnQ
zrH6&aY&dfV+)sI;RPmk<d~8`l4&A@|NW#7Quzw9jV-4~GQdrlb$B+GMhGgmT`O+?A
zK7xY_qQobyx??o=4)kM8p|``}b|fJTj%jF;J=x*vnOo_0f^omhKJ_Nev25?lY34RQ
zDpBGN0uy}eUCYRtpBX>0gV)dhT&K1>X|!nwK+@KxdOw+WPqZp~kQnJ~^_bVc^L(0G
zj<OcGH+yYaSorCV@bZ-(=%e2{?}2#~njtEv0|PiM1~0)Ld!rE5H2TPvavZHLI4iC!
zqHI7`<N$=sP^Le8_n1W=3a7w!h=Bpq60gt#tt70NSW%g%O_a{_PyQ21*kuzwUIa%X
z7_^d2al1h>W^s12c=?&w+_?G8DoHS)t|#<)9b?m;!!7iahDYj?pxvph>vycv?5<Ii
z{2`071cTW4Tn}{ym0#mz2i(vH+%GVO*}JZHhBwsIn`(El9g_@vb}I`oWlp6JV|K6k
za*T_!nZ5sSli3<|3AE0)m|YL{;|JG&MkW5Yr%lGuMB2f^k&OAj#q3lyeZ?gqH2y_;
zH|pA&--a)tos$95n8TC_RvcM$3?f1M{%yQh2x%UR3iB_%G2M3u!5J?`eovCvw<)nj
zHHg_377n+$uCuwDo3Fr!OU@rtUTlHRTkXdCf$*rX7&08*lNdA@RTwsKhgFoxCb`BP
z=p*{^&mFs{28sj=N3J8m6_@yT0dzc-jNP?re^pzNTeJ5KT4c`Hv1M9k?*ME(-Q810
z97S<P88#D2-7<(9Bmpy<KfTLz6X$~U31t5XIA!r@Lojj8Frhh<?n#r3H?uVPI7cqD
zf1DM}nVK-9>%4y?`2IxfGGJ9JqCHq9u5(FN3K|PUV;-7Lz=t#asmXJ3Lv_=)e)LcH
z3D%OmZR34Vv-*@@XTVEy6`c!nF_Anh5`P`OL&p6;@pCMb2HPw4%1=)mxRIc?8u@1@
za$yaV(M;p9Po|{;`O!WvJOGKD<;nqOIhqH9fJZCj)Ci<4Sb7Pc&Ny@bfEygL86Z~6
z{x)Vz_2J79wr&h*S`ja!coeC$sod1sK4ZEZ0b)~_xsch}YF5<rIi32LlU}%SEKI{9
ziTdz}s=XBI-5?^I9{AaY7c0$m<UXMjD2!;NS(QIPV`$`8#0iRNMNrP)uPZlyW!4r8
zVo~s(b-`|Q_Qzp{Ta#b7PT~-h?hwkM^$A(y2CB?Er}ER-FQ0ifzX&2`qcet9+Ydo=
zg5}$cdsKF>sJ)L(JqwR!h@xV;E%TRm8YdPt1|L!WU2XUu{lNi`gPAiX=LE}HTSqFf
z<Dx;&&Vas-{FW&4;(Frw(|E%R`2VK9+n}}01>k=CxFP+I@ha_L?PhIkXYFGy?cn6@
z_TPA&(T4WIQ^)`M=h`!4wm>Ss$dHnhw&0LNp(`^dPhDcYQ6it*at_}j$FXR(F>}+@
zMGYTCWb{*5OdOmW>}NFO28e@d(Qi$4G)1uyT*YoiG~|k}{|ZlM+a*a0yga@)Iqr17
z?ykP~rI#D{UOE4WwyqDe*s9(a1t^N5-mKpJ5TFYub@5U{AWR&R)PKnUdjW)n-$BFY
z4=Z!?QrtE4lj2b9E5CkHa}R^Z*=A5oJROFFjWH2P`|0!sltINGLc=Q_G&A@yV7k2!
zM1FV&GNK(sb5Y-s!yf}yLm8(|HIMF6@OrC^IeIA?^BD$Lf$-dZs(ZR1yDLhew^E~X
zRu#jZ$9FX;e|>R!;|Z;-`dv|O!%>bTaRTUs-+(p!ifnZ0DgwXrCmjWozk}Oe217I*
zA4mbj;f5IdnlJ9i0m0?q0knn&2|xN!UwXm>_u^5$6qBa%!9R=k>tA$<S--ma1)(}-
zYA>P5X9}g#IdRt7&HCE8mzK>XY@orbYYNbHXPEM$u0y)tl**+uw(P)X(suF?Seus5
zpfX_A9l_dgk!5=+F&<2|HBuVHkU0j!`ZgaubRoU(aG6PwF7BVO_9NEUFFAYUr$<>p
zR*o%HnYM6ESL!OTRb2-;6d|CCS<zt1_Z^_zmv{~bmaqWS07f<1<%w;=3!-W4WG-Wy
zn#~rHb1<mWm~2X6TdpI{A!b^%7?^IUwOo1DUsQlO-MQf9Wn5;myWyp&<PfNb+(x1^
zjj({^E))c*+O1a!>CNt4E-NokiH507f@rOQx{WAktahTwe*SN9`uwPTHSB?71-H?I
zJ#`<0gM?Xk#)h(c6J;+Z3pWlNI=X31g7`UunG^?BT<+6~nvd4_4$qdLa7m+=(*nF(
zo;g__D=9Ob@p%6#GwG>gJ!*0qiGP$>I!s6&4y(Dj)`jdd9U=uv#x*r_VOiRqTzatN
zM|nM(O)k0-vY7zl1Jvd!VZ$_0Fe9$+vP8i4u;cZ8t--!Dscgj?a<R(15^yQww`oq(
z^uhwBLRvbzC|$EnH-gs8(i~yxxK?jETGXa#*jGOVY0WUoOZkTVC;1%;rb*y0*lxNz
z!az-~;%U*wi2eB1Qju%+Ie_SLX4=AyM0&?c%p0kOR+w5=5uF_eOTFwiw&M*R(>oV(
zQEmu2>T=8!O?dNwkp&rzXStmGYx7{-8pShDVgr9@|5-AbkS-Y-2e->~1>A%%LhvOD
ziw*3m6&NolOMDuyv<&vuHFg9`jhCa$X$PBXwfYdM+sovIPM{{Z0V)?cz;4f5n2ai1
zY0beMJXXtbm@MnL4@Nkg<|7}h$`)NyunTixL$n9EZ=yA+TIoDtwp603;Cm%gkc<0d
zu^;|sWB62{0yvqQ%S53P0uK6li7NB{BidBf?`36D@=D{cRjp}VNyv{NigUKiGAHAC
zYns$EwpbbHhnyv)K@-R-nP(dCl~59Xi5T{RbDq?BxLk{*Y$p3Zp6-be^OVu#nw+@`
z#f#uG3+HfIwTqc*b&GgeQ{sx{%~k~IqPeqWuOZqpm1-eNcLW#;8V3~$u;W9xw-GLH
zqWt`Y1t=`b!q8QJDwC?9Si{0*vJ7bdP(L_&&<%r423Kj)BVN-I9%(y>Yp;Z=(TC&Y
zc3+`r_#`Tv{xPXr<H?nkb<>fVf?_}1)P{n^FY$-bYtpY<gwd%?j<<2w5kEcWin#=<
zT{-vb6e{P@DOTmLO;v&qT5*=-Ig6Jd-I#eTS@f}4>L6b$Sd_3i`7^Ci>b4<9&(o@c
zs|lXVv4|mjy=4K%UZ|jJovpBG4OwV|S2=hrQJ%}v?K$sIxgI)u;3$Oy-6>TbZ5<yc
zZ#98b-)h=-9#0OcLSHHpgoulJF4sh{a7QxaJH}NFH*nZOeK<qfjJi)@=Vh8v__T5(
zb;g40X*ST5?sT(Hp)qtknqn|4DZ62}N$qHcx`CV=rAzFnYMa$Jhj(~2S~xV8LG1A8
zMU#^kc|>eQAH8HOHiO~7%vFuW{jKG(7PyqatB==DSafEbp6k9&lZEcXiv<dr;4qK&
zEgYJ8;#r$h?MLR6eVeR+92Ucq5;GCGU4C%VP_uD1iZxZNk{ZRw_t^Oj{fTw=V!Fd=
zcv~wvcm$Ho+`N~{#ccWsZ@-aaY3fF#>mp4WDRFn{z$A}&PnfB{6^0?wdz{<|(&)I;
zVJc7`Tak*an%Cq~Ke9wjZaX2gZheYjVbVXgZB5yX&PGAP7I7l{!Rc~46`8ZX=T!7S
zDKWExah2qaWzH=BoJ(@-jy$gZQ*rgGBOjWV4+D(75i|`qdBY|<Hu(my7R!CDf*Thu
zkEtdk`y>;!nA98iL@6qg_}v^zc-^)ZhxN^d=H5c%>m7M_-pz|PyJHSxvugNKVsVy1
zW7hH0-U~Vs_<D@Uv^Zo-?<|S;tEkW`@<H(87v~JIb=tTond@$I>^ixwD&%d6meBa8
z$>Of{9^t=99m;F=u%d>1CR~V$UBDfy3Y%1bnUuq07-@ht8-<g1+T8x~Y~3R_J={71
zaKz)OWEQB(dS#z~l*?`uL&yg5w4-KoTVc<fnXqXtudF{6$hiPJG|UiLh7Lg<LIW?l
zx0Kp4KjD#cgH6EA(lm<7iwZO?eGr-Yl+ld(n|Xq*<5?nN{wYLdgW!;#?Mu&!aYkB`
zvo}i-sUSb<rDNzlzR$sYGLun^Pj(n&RR#A&e0?!ff2i+`!z$_Pu>xCqZoT??zHOCX
zoG~fl0;0(v`cSm@dwrEbw|`piv~(jTI4o%5I_dDkt}?N9_N3|;e(gBOO~P+Gj%?KD
z1M7c1`1Z1Vs5WeQ-v1ajNAKf?iU+J#2jg(_u|>b!0ddK!Xy?tF626g69%)ZLFM{~W
zaTIKzL^%|QUwpKChO`@A=B#twA7lY1ngo#ehtddbR74#BtZTjtjvs9%xPq{a_`Fy$
zB&$GH$vXAXMAhZ^En$$Xx4mH4)+nh=_=wy!@QQT@z3~vn18)LBMvahXGN@ZikB*NV
zO>{|uulrZce!+Rf)w0Q?!O74i#9Bge=d)lwO6r^$Dsvf2X2OZ~t+L=AfEX}0eNQ)v
zn#n6InIe#a5z-#o#lQ@jqH&!=754R>Mp2~xO0tph7K#GVXrazJ!w*l@&-<o3K+e8W
zA!<Dy#qje-*)>m`ilJ~SuVCEyKdNZcu$)=GpPc(1d^)*x8VY#juOYnkM~_L`&N+?K
z#~75(b-Gl0=XLLmMn9T8`D0iim1f;eQ>J4NYlcs`PDY%coTq<@FwpJg75>rp0wI_%
zFV0a%$`dP9#1&d*@a)y)jSKx(@r2$Hy`_W4?sBKmbc*rn*3R(r%~=62dK=u~AK2{7
zKpbg#9R2_cr)^tED4I+$SK8z$3-0`}2fPutY}=rO+j@lhO%Ruc#;cgSpr3>Dl4cFX
zh+;$FLuDM!Iv}=1SYZ8Q!5?}00EqJG&;b00hm=b-ATTY#*)?-u1?R*B-bg?kHzGS9
zI)!zLR3}Urw+E9mtb0dSHwX*BVZ6Vf)|2Jtl6wW@xoru#I+HH%QRoC_TeCY9@^tHl
zj@xHUd!bLyh#{M%GtV)^y(Mc+<j^BT7t`$q;2A}BIzh_LgAU|48f%L<F<*zmXfi?K
zu7-}Ng)vQK#Ou&ltPx~-v~XjG@v*95O=_btXG$(b8Q>i`&6HcLTp{U}GA43ytWITC
z%U{dOUC(^f!q;gklQ@O;>qaT;`=G(-Q9Gsf>t2foR)g2=3!Xf}=z*;EhRkqBD>jb4
ziV6vXI8I504FTdx_sxis*=Y_K3u)r=bg=iU*LF`|VXDlHYBT}|BAvd|)^}hGL^(qG
z5>&JDp$9nmqr^q@Znl(4`9r|2G}5b%pKMoEZm_dq?kvBzyq#+V<3@`s|71*o{Ej7Z
z!aTj+&WQA7hI}@rzd2R%`VG4fJeg{Y;Yu&6H%GCoG^EhFJz7MIDLmuQzo{+_`@PA&
z<U&P?n?iG@#PmKxm2)RBdp%I~Ws`S(9emmya%V)CG{X~iX9!T25^ZPGen0)`LHjG2
zp-OC)8bb`#tG@poY$u=X-5#VJ)=#Kb54Ialaq`7;PeFb0#stT+oaV0{IjiQ1wbjK~
zm}CPmqv|sF*ateEP%Y#6<Nt9RYr&zmMSjoF%ipo0?@Fit#BHqV=ICPX@?Qh=e~%-j
zs+$grLP-4CTne@*Dn8Kgt1gOL(S`J!fs>-uBFcrSD))nn6zgTW9Uf-9{(HPHNC^=M
zUVES~RKr&r)-o3YL?q@G9v-u^na!7meZM}y8e-I8O&i7%$GTZyC+TRKOJb78hWH4M
z8>g9&ql8@AiG!5hcEW4nA)e9-0XM$J!#x!P+j--}pUe=|xG(z1Vk#kU$Je3()42v@
z`j*dRUqQsTxAk3oB}o&2;bVibO3A=S9vfYRHhP;~j0qE(n2+C{!?-uC`p9J352cT0
zEu;O_mUD0U(^S_w!2?>)n?Z#w^!&hH&n2`00>@5~nf-Pt3I&sS9%-EUK(eseHbOVN
zo#R^2eY|l~7J35b)mtvfZrliudh&`^!U&_O&1dN!)uctWfe?$!I$2U=GYu9L<{l%O
z_${ndGz&!mGILEj<<eC!o{HOtSHB0=v+2TqrE653Mq4ibGx&p&tzxZ;gV0@q1fJ5U
z(vL;~3n-axVPTz2VH#+7QN&po!oO%-<U^~C2w9>&=XL*Ac3l3F*0ihx+J3ejA83q6
zQP)2R9tHbY!b-J}k9C$2VJ(>Yay~p~Rexu$N5LywJ(t2cF}J=uaP=y{@+3m2?c0br
zREOn%bR|=V_)slSDDnj1{6oXYDAkK^RGhC+LDBja+u?v42(og(>WsenNXc2=!Gurk
zfsIdXpp8#$5f--u$6eK};BOL!;2k=>zMJssA~Lizq1mZV%pkSFT*RFId$mG`o%OHP
z5HVfuHrceTzX*3753wCZ2)1;d1R1Z)kv>i0W~GrST6a23Z!*kmY>;4C(CvW%%o-jz
zr|Q5nkVsz8RZUPjW61SU6|)jYlfCQ-@_$d;cUe?yD&NSC`DTYW|1)GuJAAv#9E|P$
z%SZn|<WQ}ez2c%0TEGp*iaiE)1XM(ninnTI!Tm_O)CmSIhY-gdXg<UBj1FDTlz#YI
z^hXWFDAo|-o+S3%^>i48A5%ihDWBq|Yo6~McROWY03N8;Kr#r0Gk-i^*?owEmCs^7
zy?j|~N9_zgC@X{o_Kw!yXW^?i_MN5@8=dYEeM2pQ=Mp>Z04K7VHl;kR#-q<br$Zu}
z_Hk)*dy1`dAWFQrYE?X3C4V^a^E7-gRfHi^$tk7>HVgSVbXcJcQe^Dxey<XIFX2LR
zVwIaWU`oB<H9wph7-(GO(;pAOzpt=%9QPUfOB)E))1;!pZ;n+nw&gELt7u{s4;R{b
zMWv|*l54saX;Mf+a5F3nC{a!H<8~2UM<}w8AMSmGo5t2+az=cX*9)>f_?afR<~7db
z-PRdt{%<{sBfep{L2jhEYoytI*>3lk8PR-E;E0~QJC62hajG#5yWfaMnM{rP=(^2{
z741E0`<`X(D|4;iG;H#`pd@vB&4Kp%myUJ*_M{%6MZDMAe6(J^;aasp%nx?vzSird
zoUmqH3on0XYxv6U-!e&Zgt4ZbZEfPLTJ9I{8!|nOJ*p&kA9_9`);#9mJnl7Ib(WH(
zM@$h@N8u5<MDkD-evrJM+AmQ{nEs`G#L4R)A=5r0&0>&mOGH`Mi+IYUh53oZJ<57R
zKSr5@weMZuhLa6Pa10U^i=}+l#g@mI*2SZ6C<TLP%}#x+TEi##*<_xvTpZ!`#IGGi
zGsn*Cqn6y;;3&p-<VjRpXiP@%{%M{xzPKE4{%@GNUWc3z!+%4R=*JJ{{|u)8lgjxY
zHpu(CNDu$(bDW|%6HaWfBgHhb0Gb;Ej4uf*L`aSajQnRb+UA6X6a)vavj@gV-p2cP
zb>2$eQ%ktL@TO1+K`H%H@9leUO^;%A>+Z8h^A&}x)S2MFyNT)S=YYQ5_wBL!^{=gO
z-y`gi4(g^e08jHEBG7jbu+rZ{Ap=APC1hs~Du#&5q#COTe4m_;Jv8>K0eL?B35pm7
zObCq6&WJ^Y5HQ|LHujqw*2`f7G6~db<SSRtRW0u`36$^TYw{Xa^kV``Vf?TSEBiHp
z?0;W6106$vGcan0x)8ni-@7O8yC`Jt`2W821`=jyg$_Xke7DbsFQ3HI+?jq1lNk!C
z=L@m|T|Wkg8G*E*eH@Jn!v7%pYWqoF^uY;6Zsk9I{(?JHj2e^%f3ZaUHDEaOqKoy5
z6Nvb+INW!aQS{;{eg%Z#3;e1GrhKJl5*uU*hDksX6`^QTaieB0m4g!<3`@Z^fthA_
z9~H$nDB1;rYgn?Jzt}_brn;yECDmQ0!&ZIoo*_z;xzcSHTsek^;|gdls2P#(6sG;|
z_wa-ku{Y==t+;YYR`B$xm;?G=_l6WF9(tIhUw2*bc45On=qEY;3Ar}r6*wD)*bep^
zzV27>0&OJrUGscfbf#Q69A50j#XHDF2UYl!DF^PsqCnD^wPAfQ=b>t9sGAg(95D0A
z4uXwBcd_9}*kTIJ%Z>Dq>kmyyFx<vHP_U|~wjVn6@T0RQ&&`j?wfi^>z={VjNOB?<
zt^7&;NIjm{@0kobBeN0t$eRpVNf5ee`<}v(ujWqRXGyXTw-y--1SHEGgU(z*U%dp{
zKQ*k-{mZLU_$sR@S-He_O5(o}T0mG30Jo~oj2dh!58iicSiZcJyLrg6jgC~gAOrnE
z+SO&b^~Nr6+oLc!G7sIM*n;y6HFDT7w%mL1*rSHbIzQee1sJ_`&%^ptrYe91je~J;
zmg*lb!c_FtZxR%J90#hXSlA<M1~g15l%(csV%#g{yoNgXT6s;oXGceFuqaETdg@4f
z_!B>&0W)ed%;74ThEb+*T9W@kTTUl~Kci<Y-#mBkYti`P*%n_|F{~<-WR=$+kfg95
zB%rQQ<19qF-z7U6Jy+DXg-mrt8ISZF^=jb~-Uw~1672fL%HXBGH#=NZ{JzTw)=;F7
zFEBC%$5N|KBqzyGL-!sR%R-NVjZb>~O{>L<9hyr$*0=S%FeJnMnUEVhxGqC^I7~Hn
z&Fnm)h`kTTcaj}lhr0@cuIJ?uW>lpfg_*<2p4<QexABQ^$`dADuu#mz&9lfRCA*D=
z%+p%(t|w6m6W60E#>@NGc{IajmPVW!mNNt~n6MtE#*BW1Vl$b*9X5@=r8_NAZW1yN
z{KAqYfA0}cFPk0ibdgdQMb&<8iI(>Ds6p2g!vH-EE6@hEu@Q1%J#PC8*KqbFVFTgZ
zfG<=s={s4G`~8lVY&b0O^zlSngB25Olos*nPlpO!)hf@^jVbFDE;XUKYvvPvSH`r=
zGYOj3wCQE;?Pe1o+Ef|Ml#IU|Z#U<>3J%5Tw8<2Wv$)*bCLU1Ya$C%p^BA-|!bS&0
z5PiTeN5LXGE3Fn_iz*-Q8ctc2iv7cjs>-7X+&<8di*|agBoZV<)3ln@(x5NO=6^N(
zvudww{j}N>*M>%&hwf38xBq##juHA#YVU}-S9KeYUzL(n%PH%P{x=DV`JPUbUKKsJ
zriNCNN>yeK4n4P`eJ&$=O<da2B#r0=U1d5%nv5(C&`s8)DJzUxrB#~9VgkqAZ}w%=
z+oO^kbNrjNqam?1$FF|2E+V^}&BiCs(y%b5j*uI6?a^Y?UrYMyLi~_GjyW-cfr8a^
zgi>h{)l?#V#zUW`N8@&6pBy?2*jmj$JanVOZW>6MGAky|rn63_4{OnN>2SkZu%6K9
z2x=^9(suiWv`j{So@76rm*zI*Q5D9Zo7>gPy#K^bb0;UdTEUE?dh?^XhFo(}J?yHX
zMAC<TE9O+UNp*sAE=k{|m0U5^Le@i8t--75qrWEYHjc(qTrrY+^oV_Ol_jk#fVcg$
zus&C$?Z&D(SZ>r|HPB(4KsJxU7n^%AgB2!+IvGT(w_Mmr{8Nadx!;jnTkfh<d#ij!
zv7t4~Va8;ZJA0Byi#fH5+$zVwlDVV88w!tdcD$Ycs_J!i_92P8oG!gx_h{DSI3l#X
zxvSjM)N>QV<Ck1nCK&^u#==B3-;mPnCpA_JMNB@dqUR{ayg7nk|GkIw%<zV43Er~8
zmI?m#)DkH_(tPk3;>Q)K{xw2%)Ob?+BJY{+YV}2d?PoVhf9Gkr3&$ex?Mlr9CtFw5
zZI-S%JUo{y)Q(ERIw^5ZW%0Jsm=Vv*)Ve2%Qq$$pHPwFXq;K7H^;G`1G5_Hc*T9RZ
z13M;ISr~Lzhf|K>k37zMoM4YCU0)fhO2bf-(;8(7f_kS6=|Md+d6wv@wwBvu+T}#1
z;@J0BQ=4R&*R?s26d&WC`Su1Puj&vrB&DPbxU#-c?q=&SD|$J@CEe(=#uu9SBle?e
zlLCiT7^F@zCzQ2WixdC=C);pPh0BM+{bclbx1*|rzHJkxyW-7GM|C;f)@!-6Xr-_x
z75e3V^Hj5YnI^=|A0(UflS)RLJ-#cxGhmS-MD{#DCFISFt;&4Bdy37$fEgh>N6)Vf
zaFsH?jzC$O{bcX4U~#d&wtL&Gj%LSj5-KiHSYt|tzr4dE9FHlu2c}IkLZ8&Utpz>n
zHGU<Ks@McRE_gQjkYwk4F|x#gL3!mwg*PS6*mLvyP|@kWmwNJ9@YQtf=5}spRlr(J
zF|mk%SC!^xo?z=A;*TcQrA51@DMvjG`MfKbUu>1r{~j|lVYTPbdIo2U%cw?*1S3=6
zs9sOZH)f$NXx;q`&HsTP+FEqg>ZFNg=J0ArXs)19f1m~!jM=!E^8OegVSjT*KOuzF
zxY3(g*6HQOE_7Q~9!F-d*sJu*@&jcKX+Y>Iq@aWkv26&yb>V~eZ3e@*L?v=Vw7^@z
zr2b&(@rC~4dNd<4C$CJc$mOQ0gh}0sUqDWAUykGhGX>iZR}uhuxT*6sQlF{89jQUt
z3T@R_Keanl@V7YRvbe3Q=Z&g@RBShNY40^<PAd@UyHu{+%^t92ca+Z<v81&y0WD-0
zQn3@GZ$oiG#rY$VYELnZA+Y({jfely4w{?t3R4@6fHlkyIrm$BBJDm;V7Nmkw&N^Z
zbcWsN=kt?uJ!yNp_$|Cuk6!ljA<=iQ)`o5WHAlmj4JagrQ}mFohB+hU)TDtY!PwTe
z`a_(_XIm#S-I)Vd<o#P1GF^98eqxytnHx&<CHfy_x+)(SL=s{Fi3Tp%=8{S_6(5u?
zlG0)=8Z7YB?6M}Qbt*2V?LduI9R@F`WqAqz<qnu?0h1V$&<)*6!Rpzm>%9EUp34cy
z3-4$aKPg&IRCG{1amWqfd7p|$1F<vvDXKXb5j~mtO)5Xg<;()q(u$bua}vf<o?W5P
z-pC6TnH}K{R5odpA+=|Qs#~5HH`)u5YQ9z(;({`{tvEIWm5EdU`l{+SdG{^FR=;{g
z`}GL%mei>~h4Tq2jp(y>NjA4H$6N|^8qp&d2}GXhUPt_)o<M%T2<RNE)1v7kL`7xt
z*(6gu^2ot#q-jM5C?cMyz3RGiP0`zBR!oF5-d{Zqu}O(PTv1xkS%ZmpLjZsD)Yi^Q
zJ;EC70r13oQ>{(3JWU@+o;Xu{=M~OO<OeJUyb*CalR{-ZKF~2IX@b%ysgWTqweq?O
z8=j~WDJfOnury@7s`lo9gdQ_v_3HcZ`xrs05T>7`g;nr2w@swni>((@(kc@K{%<@!
zH^QSM@K(dHjRcJ4&;}D!-srJ!HZ-5?d>!!ZdoyOY3VwLEOBP+o7no%j-M_gg3Na4F
zy_hR&$7t_RvWjyqk#XM5yUiH{q^cN8ux+g0G?5fK-Xe3n74LdA&%L+{;rT`D9rmxu
zecWliq0X0Wft@wp#e7p+zi_9o;M<QK0J)r0qU}bb$z*0YUOj=FSb(8^T=;HjxbF3S
zUAXSlGRVAPoRnBd;-^iw061k#PZr*8{r3@GmH^?IRBOswy^(@Vtz9JO8Pl{)Hi5>S
z8MH^?+J+T4FNHH1ntOenv&o!4soaIMt|FQip?TxeUBEm#R>A$=q8%B74YgT7MF3j%
zdV>SjKw5G|tto_cAM8}Nh&sM}>2z75%CU1UO}@i+tw7vC6l8otHaOc6%fcMlp9d?6
zJ%hhr$9#pV$N|`KCfxeQ<gQaVTVq^(f|R>5bW73=DM-<oV7Ch>EhlCU%lDB6J(#zo
z&!u$ux2w)I)9A`4I$;TI;I(%@%?WTWZ^(5%SV*XVLu%(*+SRif<gN&vamJfH4RJBm
z^50%!V*4~i*7e`VjbNHhS_UKP?7dL+HF)s{$m@C<pZ`z(jAUy~@b#M#fcX~U|HF8_
zs*}0tw+Jt4>}u}%e<?2wT}@O?v`++RY^+gOsJ8PFA4j2?h=Wov<!JGFDLUnvjZI^g
zkbw!goJ^%g%+0#b$X<`yi{@%u<?CR<g6h7?r)=rpAth{S>8{(pzrMfxsr+AGK$L#y
zkBTBfOf<c#!EhQ1C+QK%jH>~2J!R(5YJNaiP0;23PD>P?L&XagD-8k>AqS^upsq1%
z^<G<)qEk6;51@K4PlztNi>`t5(nnlBt+dhTB21U2Bd&haq0x$4oc|Jo6(o{*sxipf
zrUb$g`~cNq0BtR?70<O(C5yEu+hz7d#&CtbgrAn5HfI&%a3JUy7H)NjPD|Df4qFQ3
zoLu{9T4aRjuirWwowcIW?qg(jTByjs1^DxcB<zg5UyC#9K`!Kgi`nhFt)_GEH0cE0
z%Bv#1Bp>nyyMLW@mK#6yo7s-1yE3bO>ax5*>%Ik0!~m-060A+and@MWK;y~GZQk8X
zv<EEFCcGuk{CaFRQVuf=%vf^rZ13bS^xE~@?*eOe>u!9)6ljyv><R4JB!&Tx-N7J-
z&uuni9QYf^sv!6nkTwl82jSQbW~xS;CZzk5CaD~OsP&5M%iG?hW?}{Hk)DCuvBxcX
z2K1Gxu>rB{<t5(cIS|=NydEXs{_38#y$YQM(h!MHZGJ?t@59mEN_QPWjA(w9MC5;R
z+oR&(Xb5`V+5h%!ZTeL9O0X#_$76e3>s5QVA7EQ(QOJq^OOy@A!rAH126-zh<zPjw
zT0Mlif_+|0%YKUSb|`~itxL&iLDk2};eI$$3Lee@5f%Me;%*>{3=2aC9}Q5<Vqc?z
z#&azHbGgsX<%FKX&iA{#e-){q$Qatt+AG2wKK`yX%<=9zY<vTdjpkRr&)mDp^m`kG
zcNH};TbC_XXaKRMjXr1ku4H-jPuSfiH6p<-{NI7pB5bwL`xezC5K7hHF9R>|r%poY
z3rz|$dFp0t!&-GOp$I<fOpic=M`Tz2&YELLwvHa>P|jpWewJd&a8K1+A1YM^BMkX?
zIB<tqBAdTp&~PPX5W4!a%we=n9I4wGrE(9GMh__U4sQg<<uaG!7Aduqq%i^Vw2KBH
zxNcq|nt`uq4nJzEDSIOp5cTGc%1R~gLvU>jv(!+m{yCFx!(&$&{EH;F)*PJdPQcl^
zs9r=psO7KxSDEI0x&IGIY6@7NIc4mjYj(-dEUO9<u6x}!d0aRn$eX-C#2F&{hwgO$
zr}ZcD$8$XOGK1jS*sYe}mk)?zXgahcbDZ~Xle|k=Gv*a<ctE(<s4ygWpjb=Ap?#Z<
z`j6W^{ip4<;Abjv^L>(8?gl?MOrAWWIVHoZahL<zGrz!)epf2SKj=f(<p9yh8_JCR
zw$7kDbgRX=Mtiorm_EL3Y~EZfDLA*!pyY`cp@ZRyBsGl&|CURwrb}=Sw>`^8MDpt9
zT>Ofx4{GAP-Zxq|E&^^ou+(esJI3gLfDmE55vZ?HZZqcSOFz)EedkXkR%NC91)z3V
zOFEpp^2Lu<1l4!Y4KG4!9sDt>S~%vrXs%#VJaQ}Gw>J=r+w6~&Ylv0Jp_kYKOW14m
zO}}*9vq}|>U=xL)N;2UnwM_2G3)R89VWNuo05-Vgxeyx`I-BPQ`hck|Zpy3}G*0o@
z=?V)#Py}L0|I9zGcemkEn|`<28n0~DtHhfiTtvE#fCv<lk?iZ||K_gXwbqE=zJ&u-
zq#r+|{xk0CfAx|5|8~o1T7Ms}SOE-R6d}Sy3=ys9^fXQ4v>P;0GDv|<RM{H3KnoXW
z&}6x+On}?&v;RNne+!Ilr%G4hPuYZT**-pRJG{gpOalesL%F=HxBhvj`Zv6sUmwq>
z-&4TQ9P!nN7?iIQcL;3;oH5LzOGe^Qjh~15Y~92@Ik#T=DCg0YIrmn@2rU465YJ&E
zFdQiuS&R=X(AzsXAs&-0gT2LpIigfYOUgzn)QGfpUp;JcK2jELUzs;Kf@{TZ&ctj<
zflRC{z3?q2lVw{VER*AJR(VGw5eY1x!{)hEQaLM09=n*?aGdyc3hhm25BW6-sy1h?
zd$9+Lbtl6BVWv5h*fqeYf{<O+gfBZLa+)n(TV#S6z&^!V);-4$2Y@XbVrqyR>Xr{4
z(05pm1d#?c$+M(yk5H>R8Ya(Ogi~Y@U7uxM8Uc{rJHcHazfU1`daWW^uePYhLFniW
znR<-op3I^Q0cXUeiebT$<+`d(%s%2A+>s-hQb^)k1<1v=5?vKfP0s<dNNyq7@~S0R
zJd<%{ZUqwbkHcW<T;oEZ(3M#(9kSA^;i@V16(jhPO852r-sC4&WC1JI>TEKyR?K}F
zXZZ2Gwz5n|377`xQ3=M-d6OgLRJ5skr`QOuMpZmzQ91E&$5&8tp4a4wSuU)>9u(A^
zBP4w@q!^0iB#(dO$j8GH$8*6M@7XDy>y0x>#CLM&Ml#SCJoR`<(XO$!<tMr-bSN)#
zKUmVfC31UVcx@YU9EW6HOQ=m-gj9PPA5{+y(+FYJo23;=yFQ0X%`t(NGeB?`&ds?O
ze7&ugs3c{lo7j;P+L&8+WV@S9>X`fExFw~NjAVW{fAk^F&I%A=XZbEK?im;uhX_QD
zTmmu+7;_~ks<oSscABR*q!u`!uR4s$S-q%@S-$9vVZNx0X})9`cPTQt^Tk?XJt4Z>
zGwvL0&_gI<586b+%8~)ttd$FJdgp=ky{2cs?iot=eenhNB*S)C`eh1he9Sfy_anQ%
zeQZTDouLO7XWls^I+%0kp)vkrwkKUEgV*I2Iwe`e3m#^R{OyhP1hk}FqRKZa*osjv
zF}6BzU9mAl<s46}VI8&Y{R@UacL}<!*EqpS29kMH{^U|jIyRM-*1k93(;&t#Deai~
zvY@WVRQbLIyjjSxH@l~aEo!i+H#u%lr&2PCwu-T(+-4pI5WFkBPy?^O^YV8cG(G2%
zd(BN`1I0Sl{KyLRm#4f`4g&Z+t$31^*C+(Xwf3YTj28;^#_&h)sS6@=|9*T|N3+mv
zBHJQ&Cb5UwZkuwcvnXXt3I%bX5we^sd4^j`Np!`>DCdtB8f8TpLv#qsk=2C-HAVR~
zAgSOJxlGXV923x0Ll=cA{P8_sn>~{u1kDPyQpjggGZNf}FHZXWQQK4efY|WPR@?v6
zTtoO!S?v%juT(qQGE4&xZ0QOK0W~G3bstK*eUVQ{k>@O5Ae=ksXQvEVk3Tj#K5d1b
zL_x+en2oba<JG<0107GJ8>#`ZhZ*ZtmC4m&$hIyAhkv*0+9{`r=2zBOokm_hEpB=o
z2sxYW6cmOn0nrSmtO+5*;LSQ60sF|>Pzb+Dn*$HvsG<HChP=C~%N4uuDb9SUj@eEX
z<1mCRP(qKPBHJmCTn-y}K_TbOt*XXp`QVH*^|}DSpxjP($imAK2DO0Av6)_EKRJVu
ze$$ZF;w4sF%<f=M;^9~U{@BFQP!il}4GLp+X#u(waNi-x?_@i9VQ&%^l{IrW#Ng-B
zuD!xO#eRjA-QCndTGfR-O9|?eQ_iUW+NHeUxo^uqnz)2hep1aja);1dZdK`63irXO
z7yT5eD<&L}2Z(Q`FLq%a4;Hk-s<~6tVnmqaF<~%CKeM{^M2e#a3Aj{7f;h$5XcciB
zf~-T1_ojV9s{J{+|Cu$Vu7<y_H%tV6k_4l>XZUD?g|o!OS7}V9g)~59FibULmW5EE
zrs8ZrmWR&wmpALC+M&5kdIQQu?${2G@#t+%n#=3c@8Roz-!ISCE|FmnKYkp4-!K2+
zTmApD$^Kt|_kX|DYc(!4(af>F;OXFMf-%L=*u+^!z_-M%Ny4aYOrXf15<RdzAhGl;
zR@SxAx-vYPTbizH{3{vr7R&i0`;T%I2rt&ozs_x+e0MYTEz(Cw(Zc;td-&#VJG$q-
zw~$=sclCi-jXu+$7*k=P2BVMqteH!txjIY0#eD~vx0oi4qs4XL4o$dlM`3bQnUP0X
zax{URQJjMn!`UWZ^vrrlLz~7m1LElEYTc+3@H^<X+}-5|{^*1ifEpw3Nhdk}c}p(p
z#WsZ&LbU=sb)|U=U24ttEdl;S4w=1w)G#f8n~Pwd$+M*~IPg^b;x_<+{Mm|A%b2^I
zEkInDn;fP0H>YEJ*tbCyzl{}dIoZc<I3h0N5YI$Rc5P^$ng1LM=r$ceV7<7#6N4}y
z6Fwbc%LOwiz3nWYZcujCX32S-6=@Zo=@Pn3;JUW3-6C53ejoQN5OeHsAX{8ZKbU1o
z36H~ORm<~ZHFq0xb_7q<)A~;2-<BBPhl0ReTex%kwoKV}@l!#5xl%TMIq4LS+|-#|
zJUmX^bP<4rcNBKTdq(d)`-J45evIXQFoYtN#W4C3o}z9Yx5Z;7b#mTSJKg5;KiOJ@
zwd`eN>m6I2vdyZ3%P)CX!o`!g47MIqWM}n9fX~$<Ge5Pfj6n5ELd-Ef9PZ5kUY6Rj
zBdr)(Y*0_L-UI`G=T+6O3cFKO3EAU<t2#rj2q`)4T<$B?`k;rKAMZ4*`(Ur_zh+Mc
zwKWqb*;|?fcH^9CdD@F8lQOFW5*T}x5Wza(ID|ggxt)*y{F=}nbBnDTP$nI<-QCmW
zysl_pPW8}c>b4gpO#U;{Cg1Olh*GSyg;litd*;C+$q!2=0UiN7jlw_tJ=A?38!<N;
zTRM{kozPjn#A~$r@2kNC&8)KwlF>D22?#|z>bjGfUSTQ$@AWX;3KVM}$$0EFNK}Hr
z@@6fN+e{PK2-3RAJZApBv_U`Rw1MJ7L#~qNYwxqwmOP)q#TGuD0Y-$0{gyz$`c!^c
zW;_xzBcK%>rHGz_kJFBNXqFkY0{%O3KG<T=jgrIi5!=r#uvU18pv7t}(1N*Zl*_x=
zhiBi$3r?5K4qX&XcMSt(IW>%mU{xvJ9tY=7#Xf7GvOWMWBy<jaY1U8~h67y#9tJw&
z(&R-%6tQ>d4!zF$MF*=cvz-CWZd%;p4uzYDl&Npt31+t`!lh#({l!jpTFq8{R44v}
zj(N^^*dTA0Zykpv=~{pNUQ>yama4jP(F1YQnl=wz*;#ZTZzMfE>Q*cNtF&kw;4{!A
z(?|0b%ulAa%P{K!CWU*2@W2jUsLC22$EAzz=jhXR6d+A!Tn^^%Zx{!OGnS>@{gIaV
z&hr3#@o&Ftp;_yQ&@&+w3|@U`|4Cz`Ou3r<5~vd*`ARI8=4?P6LGdg_{u(p>mwbR`
zl5?Wx`XkXXNApfLJLh;pq0UD+3MqdBE+tS()O3+8Dj*G~iz`h9=4{X*4q0)woyKCY
zj>K}%BryjXcVuA@)ei<Xyi#-85_>+Cmugn>mv+&rH;eXT6P-_H{AbD5ugO(kouY=H
zug)Lx{=nBAyi5tI1t&!FRB}#an+!4Q5@!^f66+*_rI4FK6NqEbMW|gdX?ZIYSqJ56
ztv6L!Ga`jw@D}b^)yzTeOxRNukIw0qKYf8QkEPl^)#K|Lf}k@Cn<m_-9Z-d-4*?-J
zrqnWOSE@j}lV5^p4qK<MIl&~3hberTC%lwD5DI1#g;Nyw<)n`|WFDIRBqR#FK?1;F
z5HQp<9#Sb`Xb2CMXVq8kQyDRoAo7Ng4Led7NL)*i4bnVltMSviG%H-yNz{B*v_n+1
zZwH-x2dF0R@jDEdqKdupR9+|1Une<XsC=g{_PpS71*ANgvZB^E?u%XnI|XM^W5-tN
zYS0^-`KNXrW)1p*AkGXEo`1_h>M(%rtCw9~>*ao?LuhHUM(h3e_ttcR9Kq<ItQB}x
zRym`S)@tq?k$iH->WgSqmh~f~6ZRx>O-1EvSvL(YzY3c@LG6o}akWSl3gUa|%t<fD
zqQ%zxG1&ThOuC03kmeLzp3!gvPj{($Fu<yce^pyHgc&TuvB?#C;Mm5C<CHhtaPl2c
zu0B+%Y<%P%5>^cI>%6f3QM+jBUD`+Qmhn}ep0&+EmqwI%<%7;`3Pxcb#n{tdgUT;|
z#ZBXgTKhkoy;H1cQIu_awr%@t+qP}nwr$(CZQHhO+t%54*Q?6St9z4|%1hSQ`dI5{
zW{x>WAH8+d8Ur&)cFh4&^lgQIwEw-ZL17|<AtV0zLqzjGMsfZJ<5A$Z1NHwDI1yV1
zYyJQ227z+ZT=xF?rXE*~rQ|&%VkH_1f<F?qdgudY4<doZm%%>Gh6hZ-dLNM|kQ7Mx
zC9^;kCAB1pYED!(^^G(%dj`dDh%f%J<WyUS>ZqwQ#-ZHq0K3#Nrj!)i+HF@&Al7U-
z_PXpjj=bf5&3g3Zot>{V?R^3C8-7T_<GgD@<9#{2y?gbs8kPNe1N$lr@qIYVy^r~L
zLu-Cf<o$>8Q?kDc^ajV=jq_8!Z;H9|T!{Hoyx;p>HoWOmH82b02KR&1XZ|I?J!9sk
ztIvKp3Jr}U*B2i~g5oo!@;CW_Agk^BAYS6R-26b<HaFuQNe%EKAB>1h8B(xW)nY7Z
z2^2n#L;B*|EZMw>62>Q;hH>dss(D^6Ry`x@bQCeY`fO(Y$cvW)yTg&$T<I2SX`;(d
zi|ldvkl<NuFFCRsvA}JiNW2j*RWj0}sbW+>xKcXNrB{m}va3NYk=Un-P(__0^`lsj
zMzPR1D{*o;r%silyFtsF_Hh#Bt(=6Csa=7N8dDb5WJSnuB}2%fZ^~(S%1J|RvvHTp
ztYvh{&9{?#nf%T=`ek%_N^b&Di{8WAT~d}{dDn(ydW@&iJ9j-*jA#>V%4p&OD@yHp
zn*}9P;1u$pLJK!ql#vp+Ms5+-zmsxav}&1qzHOP4t!`Apn(=jrO>s3bEUg~LgrcIS
zG4W=qhs<3|MTp)bE;cNk-Z1<h;DBZ4)D#7yH3|ctz_*IYp<alhCIpurq)V{G9iI5m
zYm4hW!Zn^$db%0G&N>s%JWtQ&A`4GuRba-_7G$g*zdJH8N_bO(m(ZXlW4T#ZE@gi;
z2BU*sV0sfX|7|{_uCwHj1cex&a;fNKb9a&!;e~qY+9JDgc+#-eCz2;Hnp8v<G=&qp
z3u<=YN6EYzvU}vRs-95)%{{SVQnCW)sGI%b8{IH2gRR3+K*kxk6pLNX_p*I+*HDdF
zfww6|hWyT4GP+m>IrBx9TOp1g4~4TO1L}0#>0J?zKnvpvH3ox4BTriR$cATuc`=zj
z9}BWrlB;Nq`-@1mT5evUS7og{y!)c6(COko5TQ;+)Ip+ng|Wp5?|$J#ve^^`;rw(7
zgw25M<C|D@`<qmo5S(mpMT+<)h4ixGfhs>j4-!^O6RMTuF#BJxtkZ%5z3#%U#YdG>
z(&Cg4d*j<Ho$WDCK$A5|#nT4PZYDex73sS*LDYuKm$JFV^i}Ih#(hs(GNP7B03+6{
zbo~nerQt@1`eb;uu%E=rcMM+Q;J5oKeA2ZL;PwhaDYiO^7-S)Z7^)CToRbPYv!QlF
zi<qi~0$q1o9Ja(s#CY*=ixv;dbxgKA05Yy{tCCa9!OlGuh}UsYU!uCBaH)1TZ{E1X
zGLU#9NhQ<yf)TSPj&zN|W6?OKbd5=8(Y}oI3gpKO`$#E~nl_PfI)-H=ig?jSi<(KU
zL-QcgA`Kt?evh@uN8g0h2&R~ch+8&zUR>nNICc}+3lPS_gy##fqH*N;GL45!fCXi%
z?6`a_uh|G_wUceYiOzJkjKTZAA0X-+LkP^w`{XuQgH3CbdQABV9Fr=si++IRB_aVu
z8_W`98EM0Y_SqWE?vp={fjMLsrCsAx=#9AqIhn4DCP&ZvKbks|Gb+kTb=h~n>ggPJ
z^f;KJ?Rt|KjmuXh^#PIJFi+na1Ny8GSQXB^Q&Lw|)F=`L<7S5pt)3UK$aAa_w=Ts$
zw2dcw$%xqHDS3?Q8IcX09V3&MdNrBq%1H{H=W!H-07<l;g0Hnqnr+5g>DEfZwG}~g
z(2|QsTTCWHc@O<u!QJd8-P2@HWlwOXP9;;uhO6j$K#JpErM>xF72G?%U+HRYq-a<?
zx1j$~I6?*LX>{#AO$v#;W~@2OUL{#8slTx2?WLF+<?agJjX=!wjcKGze_4;|glO;G
zkU|ndclizzt}%dff?M`qg+qd`r2!pEeUdgXqhuE0Ch{wX%OMB9VNP?4nv-m%z}5*-
z3=1ibTBUPK!lhG|fKcLd$I}=n|0lAcWTK8X%LIuw%Ot9H%LI#b%VmS0i$eEtQ-&3m
zlNZviK{EM#<Ecq`?@jc(`UKhPQHs@NwN&wx;6zZzRf6TZ&sl?JjUimY<g-H{4PFu!
z2(_Y^RYzKbXlmHgxf@398JBWhZ<fj#?LCl6u5`lI(`AEfLB`eUvEPsrh8#`DlNKyS
z$58N6BIKlW!U8e%(mbX%=y6_5CSPh#UyDf#ukGY(iuHZJKT9dp^07&~@F+h!ky*Ax
zy=uc&#boFai?q$^G3<LC4PHE_^A*3)s46{?ngU7B07LcMPVwY6q9G$!!C<qA2VP_d
zO=xn5g$P(K4PLUR(|g*LF<kj%w?pQ`TI}Tm#5<9rECihCfK}v%yE|cMv_+X$)P%W_
ziS1S<dep0Zi+xc>6ElSlR3KTZnV>WabmmjqvTJd|UQhTyp%d!rJ<fX)&Fdsk2NxOK
z`Gfg8G>+@*no!}msk6Hp52>Ht2phX(qNtO*67J%Wy>?FA?BxRyP7>}Th;|RzWg3QN
zxoBuI%cs=h3L5c}1+M$-wT*<GeY$z9>Er{X+xQS&i&29p+02a9$!Jbz`Z)<@&_$cp
zTH#%ovka*;ZlmaSBKQnm`gw_6`I26Ov;hByL%n*Qi2!kgefek8T$@S+5hy64{ie_+
zIXKi`B){QBLn@C-X7=D{&lgRE<;mIXA+aaC&R6ONAu^>3Vp@0AGfKS*_DST%*OjX(
z?N^D28wpBjZ7qSAg=i@V+eYfH;SH?9vLlgmac#e$>del=^C*nixYFl*`c~~@7dzr6
z_D1;47Vq+*=@`EwS}|suiDMIIUrY*n_2cN1Z#R#5kN)n2mRYIS4f{h#W_sC<!<W$}
zIq?|GtQ)2K9+G7Au~DsA_LtSeEhbR064KpXl*a^C^XNgzeQ9NDv#awG9wrTX315$!
zpgpDyNkQZ0ISQT!xgqayCH<^I@p*UKaiOA7Zig}`>CPG?!Qyly$w{EmV@0+YlpQXL
z;3YH;rJQ#4c%cWm_=HyChj3eSv!n)6*6ISK${PdG<DSn6t~06oC$}0`9|??YLz>RZ
z$S=BAPWj?))$R6VF`8}ZZ5M?!CHigYW1XcPM*nz8vV5wl)0fP!b<tc)@aSnIirA#p
z$ugu=3`YqW=OHQ67UGBPg1wA}Tfd2zoh(#K$nEX$sh0-_zJ6*)SMq-o_jU62g-z<J
zV{$he1Zj~D&g_XU4+kYe92ZB!3d>b<g2^7A*1j|XJ%c?qgbdD>`XYzt&nx-z#5|^>
z3dDWF#ZW29YdRzWAqrNvb(e5~#S9IzQq@Etu4SF&lFDEG+~-%!!%uRquHy=M#)vN%
z($9#Ul6CS1GIX|Ch_`yvDX!c3-PHSAQdE%1W;K!_H)GO4^fv}GeeIQT_FNVVP`L}O
z6vQ6&1=K}6dbo8gr#CuQg)y{aY($Q$)agPu4Ceak*Joqg;WovDCJPQF+h}^6E_^tO
z6m>|ecioY?C~c?!F|LOkJhi7%oV#4peT!bu4_V#Epgfe<<HT=&b2}OVSO<<aYh}{6
ziv3<6wEJJDPC6p++dMRM{9E7IwnQ~!1|JbAVjZT94=V#RXOrjZBA}h}K~>k=N;&V&
z0*6~eG!CvvyS=|21ZMI?1d%`Ak58<az1aNJQa&&bROXbY1?Mg(#1=V$cf+84Je`pO
z))e?EA%VhxUda53>SOd;V{e8k>U86ir&k5Szi9F8oRS<|kpDg-m~V(&2#&10fGddJ
z24dq4O~X2@VhzzpkDObx18CRfKeGjNi^}1+<O)6040=N|)8+_W*BF*Tb)v!M^IXw$
z)#feO;W2ZO(n-U=VD2E9!E=%DFlW%XK`;*RSm>LmS+Xz<vH~BXo0Px0>;H%=-Ef4j
z53!x1&%l9&Io-fxhT8cD%CI_t;XpGt%uhpsMf)LO4+M*b_+I^)qQ&dG!`iUdDq>@g
z0oj)*d;q3t0bmy7jgezp(^x&i6mS$xMqp|RsX#Kb$Jeq}3bl;NK;y8`#&L#mhH0LK
z7nK&=KCtWNzizr=@Dk}pU<(N*ofFyR(IWl*zTMH)Y#G*tS|LKExkjsXIVat!i(>Sz
ziF0eYNs)Tm7Z-**x5TDodBZ$&_zj-rkVRzT+Ub__%mJ?-e=E4ujx}bFt|!Rzj)Nzp
zcc9x1DYtL44eoZ2zbi8IjwdHhf{XmwO#=16Tz&XegNyPKqMYjp8hYXB5Y@m5sW3!S
zoLY=3y2y?5-GiIgm4Q`M3g+l=uq+irO~~d(D0)hS(!B$#nE_3D%awJIBBFI{S2X+w
z{$G|B35L$CLFRQZhr6b1&8=`8cFn*jguE~hE%7yHdF1pPJCC@ySJJVF7v$?Ar7PkG
zfQ7JN>C#%4TXL>RpzbgKZfdDf%NooY#9cdB_K@-E>U|+<_CQ}^o$B$PJ%-CIh%Z{p
z@y#pAi=z{F^424(Q>o1t$zPx0c;PN6WY*FRv0xv{6n^e*_?2FJQ1Q!GrM__gT>pt6
zZFd}Jh9Na)zam6;@$M2c=NO$Wy4?lWJtI*6B<G{v4%5dF`UnB0R~*(S@+bJ7CkoyR
zi4X8r9^>=+NsgbrCkf_@R#Ck-de<IMccyR+V8&K2tL2rUga)EhQ`v6Qoev~@UuC`k
z0~cjXXRx|pRW$dtLal-;M%ZG|0A)_ng+AeHw9biWnnkg<Z?$Ybk?7HRq@R4MFS4nR
z)sCKdE5vsGgO(AY*W%M;L7&7_JLabEc4OTd$Olezya&wk9=k{23&11p0hP60$K2CD
zw2jk>wu~q^xCP9-sIl+mFKzjBv-hH?2Zzt@%YtYF`=YuhQ*Q~EVbw#<>6I$|5s??Y
zSZBf`m_~@*c}U`!9!qCc>bh@wV!~DkXJ*1md3<&P4V<S2%q;vstsZ?pM{-H3s@-H&
za0n@@y)cN3UN97A?B6l-aUW=3<6oUDnsS-uZ)KmZ+}SOI+)o0a7hLK-Se2n|L)yPM
z@e|wgBi@GPjsU9`eT<m;6nC|4mQDX6iah}A(gpok8M*X<=WZso1Oia;Q=;UfhUB7(
z8pcO5QzgHtfKMuujUI70?+@q>H7wad*NnQDjvg6Y*?kZN1r#gumZr~4>r(}1cO?kV
z(!8F}a}v0FZiP0ThWD?)s~g+3;cKOumr19a2QoARcjy=7)KnPi;pJji{S_KU)Dz0!
zPUUwNs9{-+2+GN!Oij_O?fNluhkGd0#n<xN#-%Sh6$UNp@;(52d>R|gk!GhU<0Qdi
zbyme6>`eliP3P?P>34P%R2klb{A48yq=ViWnHm(rlr-B@Khx_jhEM2<Y<~ZLUl(YJ
zR<#a)H!G*iYdRS=$w8FMYd`zwtGwpTQ&plZQj1d5TW|r=MZBk|&R9;4HjB^S1`k}y
z^V_s5<ai_5sFb`i9h)I7FX1~>+BmjqU}Gx_8CFfqYG7>xU1u2E%A5VYmo8v+18*lM
z0Bq{o0WIOuxcH3$9^YI!e`wgRQbHz1?bAC8AHY#@T;N#S@I(~_j}6mq6%<c@ed}`?
zSX_{o$}-b7cOAA@ci1lt4!nA`)8n)l8JEa3y#CB6Okc~R^(<G_m$08Q1~~0ncrREx
zc75PobNQVd0Wkfb-xySkfH3{T`xJ!{F-wIXV1*XoSRr$hJOi~GxzQri_Era;rrRfV
zw{~$xy5{AZ25+Ht&fuFllcR6dY`KsbV6j@@w2_K@GzR@zei(=Xg-rNE3(JJnYhw>x
z(i?WwRQ=Bl$lng+phQtgP6ssVF`n%|J}JYb#>_Dj%5FL<d&rpqtVLM1;~ZUsCwpiO
z0D}!GTn*wDMvc}xsdBRvj)ecfcS~$%4G?^ji8m(~*28#5a_91H=a7DqNNW4Bw%$#t
z-j$=~maX7*3<G@9!_}F=IrdXGVFcz}3bpQQnvojU3RlB}&$XSrLO->VR!6T~S}SC&
zP<tlhLmN8N&U;4D)BD*x13|P6<>}TzyG3epN;SQ6)s$4$Mx@?MSh_2{4z7MIZ&Yj6
zp>FAh?I%bhjg{VFhZU7vo5TW~OX(x+xuWPQL~ei4raoqGSg=YsK5*H>us23Mt!duN
zpQ63M|GnEpm2OEm|0|>5{$jWPhn$@M=r;Xdou+10Ygepc6d#h5?u4$Ea(eNp$_0*a
zDlAGi|E@7+7#9KH7^FIToxDB^<`h=->xktE{GzU=<8ELL$fTScA8T3J-Z{s<aev1R
zpNr6cY5#&+W~)?aQ-ley9Ia-jX13Blxn6hLUB7OBe7;@(B))OQeAc0lGO9%g4z`oc
zjM@XB6}qVmI$BuJkDQd+UyVFkJPBaa4$Q?Z>W$3Dc4@>{sH;fhN1!Zg%4<a&GF-7m
z*fF)qCoO$R+Pjfej;zWdgr(IqQq|ecJVTln8l_P(bQ>ILw<f7jo@216<R4)49CKg*
zY&%Gx{6Mg#I;Uv+hpt>Vs;sAl*sj^&YcomYOsPtx&#+kUBXBFG7``t8YLCzVIsoh+
z74-CG9FDw-(-L<I;v3l+*-kS;x{cgYK43`+|3xUHvMq)0C^ClNo$;J|2oIKCn5nCn
z0@o04%Gq2IZ%u6x8!n4&hA4{BzU3SvZ%jqmz=*99vy#@Gw!oWJd)e%efu5}8Y5hH+
zY*Yd{Ak|?p7Jm;1?daitYKgX+Z7}{^K>BTv)Uo8ha2ve4Vc}b0k@3UrEIVmzr)y!U
zsngQTweDe^950HHx1nOHFl*`e=xOLl(T&N5tnegnvH0Dqj|)poboJdWqKvjiIE+(h
z0^4obYwdyy+L|U#jNs<XiRzhhw-RyhCLm`)^(%W#%CMrgK-Vofz0ACbLT#!41rOAP
zypFO|jevX%h7~+OoqM=iG@e0={<9@Or{u~cmcHz@E_>aGTtyi}+lDfm^n~`!yCh&C
zU=QC$%H*=5zO82iqw3y1qvFtF%)n`iBkIA}B2Pm}_^XF2M6NU#gMOxGVvtUTkjJV%
zq&P{jD{xa5?qfb4hbyn@7|(%A*&a}Vn$9#(|6GV!`-+Uh-4nv_F5Xk<EYe2^0z%04
zDAk|M2JNFz2%o=&e@~ozBB`+ND_Lm{UUKa8&4RqNAXJz3baeF{oe+wSe!KCF(%wnp
zKwQn=l?1$^5*AMzS50f!aCnyRRE~95AL4XX9&#^t#p>3VwDfO*&vTgJ;O%L1w8PpB
zv^XF^z5+)M1r4|Df3Mi%;90zhjn>{{`9G0N*7PYj?$?~-$}T|~7!2<vU6R&F@Wv-D
zh}XSr4Bd2w|Atv14JFiJ`;fyCPb4dhw;1^djQ;L<A+k<cL!}%IZ%TXdu-SKM@+p@M
z8)Brca(gi=NhQB(Ord6sGfXd1+6T=(^<AHJ1-1O+MJv2Gi72PHYjm0oy|&$U05!QB
z6{2j+iJ?tm(yXTb&9ZxpyZg@bY2c+@5&L)UxOPHG?m8P|hkXS5@DtHvOW&ongxD#g
z=EOBM+=vW~bBe6QWL>qY(OXaFntA*#74Eai_O?~xFv@IqfrES<6TFGrarQ;06&d@+
z&3TEUUH!esC1n+DOs8chOG=$uzWiP%n@NSa=E)|Rv=8MbUD;B%R|qDE$72IkcZIZV
zZ9Xomv&M3hBiXt=bM5T`IT%Z)=-ys6leeXP&X(6oUIq0L<kdc}?d!d756+kVFoZ}I
z>y;sV1xEwUzG_Cd-fngWz<n#9742q@o&)bo{c<JXmjvjhXnaA^MwT$J_LZli<r+N;
zjZML2WC|fHs3=i|0s0^td=&1GP~DCsFw&O2-yyi^2M`EcFeEA)nmL(UU335*7^H%7
zy(XDlp?FM(h7u06ayE3kkm7YX*NzYoW`<I<g-3yPI5wp058U<YpwBP5ygmHJ@i36P
z;uCZu7%L1n5?WM27oP<iUz8%&S9oMFo_5|7=_8lkuIdx(Nf-U5$KT%<TC`{HyzuCO
z?jy{^wvT7#1zX!E$Ai`YEvNV~w{Qt6X;S_{7(2xOa14y9B>b4}l`Bd#EVAsv%jEL+
zamj?aZi%!E#Q;LU-oNTzyXVE7tKKgQF>Kz24hkvXA)y5KFv~DB4(655Y|u5i(q&7K
zh~LG$DRbdPuY3u_|D;8bTz-4aR(Tpl`Aj0{4V95u9p9DR@RLL#uBmdkrckYgADCo|
zuyk(4$rD7@7bZsnZN!uY4MHJ?;e2~bk6_OCWrF_@M+X^QhvEuJpR4qRc>mRRcgnZc
z1<E&IqMiB7gW^av$-0MMtZTgbnq%8Mvg<$aOWueo<vG@b%sXVvGjKWQ^NyP3BIuX!
z;2^T#9)PmbF}o~bIBgA9dFwrGtnAe4F*FCaE!#@%5k7z#dP%2v^}v0h^{%RJ;DE~D
zfY^j-!<;`FGUr`wD|s*@LvROlIhR(0Ndu5_hOj@`L`?&w0JHXY|Mto<GMu~)-y!St
zFMb;Q{2zv4LQbJ=Bd|Yz^nQc482)F|Z2wUv7459d|4WKVR{iwcT*B}{nM^UPY$cMW
z*WP5RiZ*0rp0mL*U*%U^C@B&b705?kL)NrM#-1FLSY((mwz3MWug5aPp&K!_3KWni
zN7~arH2qh?y}9E^#Mx3<G=3-~%JHw}_S1VezW3kl=?|bCDXQUFzZ2!lp1nPJ*rXJ6
zrd(7ZQcFm}nmYj`X$*r_J$vQ80JLKp`XDh^`MxN<Rlg!8P2}@AdQN{MW)9M2EHf9L
zC?fCtogxhFP+XrAGB48Q?C>!fy_uW*pya>;ZSZue;aOj8P`)nIuqx9RNyzSjE2dBF
zJ{+XLU?C}T6U?Rzk0Ol}Zq^L+uPfplTcs}Fh^^*W!^OUg&7ATqQ9xvTOeQ^@{1T8>
zeUKT_g@@5F37e5MlbO-9jBu#D*L;91vow0)+r*|ysZI;T6O#&^eUs+BB0b;0d?ndn
zDXMcss2{s<DJp+2Ci(lM&16D>#?hhAjvGZI46+@dldW9O)=$x#c(Rs})SLZ6C`L_q
zl3PM5q1zOt49I212z5|p9y>idoi5uRAsLv`5_twQhB)V2dO5pc0`jF6gb<@V_X29%
zIlqJC&uVn4n5*NC(<~EWj`&MWqC>VwOuTdMZ4L<#C1a0&#He}u#Jm5pR_)k_hz3S2
zZMKRHbmnjuC$TzrF(1CFW@u?Nl*mW}qhR5y&Qu0*d;_?_6mvstqd_r@OGRp2o~Bsb
zPWAZCV~#^V*$JazjUme8QWSehJXX_`K#V~4c!qa;!jz%_Hf5w07^FzLg67557`6N>
z)p*0@l!^AHd|jo?06i&`$;vb|6$Ew-F#+)f5`^YJX~2sgU)$!~st#;H1<-><W?2Hc
zAU3@TxNh53eP?lvWTgrRmgk{D`39aVbEzj$cgX_V1er_~>`(@^{foI<@}P>$?5VgI
z3=<+^jw4lSyp3g%t<y^N16uuYcR<Wv2tWnFOa6?9haD7ntmg_q10|eaWNAMVR-<Wl
z6}uV4baXR)y{_A${U0#rqIy|TyqC+dJr^9`p>2*BeZMNurKT92A~6Z;!bu93<tYm{
z>Cs#};ZbpD`#(&NwfnOiI-^*aJ4^RyUB!R9W6bjoYuz#r8^c|2erIuEZqMJac5Ll9
zIOwGfoWF2><m@&v(U<KZUzL$;uK*g>vZm|RE8`f~RWeiN(wwf+X>fjqz&Ln@lmYHh
zV!EASadGhW4RIdZN)C~<R`1K{jP(Tid!DmEF>TJu^!!CvB-WwciT@y9sWrE$#ZP|Z
za%=ORRR%gZKEBT)S<l#k8&R}-(Jfs^$+Ev>RT<6WZ&!{y`dOk({Hv>ijmqiM$6$&~
zpfpHtHZ{2_09I(*!=6qzP9!YT;}(a10X34l?Wg4Om?N<s#j^LbDNw*!%RX3RXaot|
zf?k@v0UCdt9P+f~n02k9=mV;->UcG3G-<bTr^Oi$1-ZB{U}qJgFHB<wDL73fMN6|C
zB1@h!h_Q8H6>rTC92#@592F5|h^t!R_)?Taj(zXc=?5ksIYzG0xP{3Y2Ixl&CTqW&
zU3oErSH}e5@@QpN{mjGv({t2I_Xaa32doU4+D&T6s(b1=H;{TM6J%eB-u{I@M?li7
z#a?wh;ZD8E`9=s3CWru(y=r@Z{zo;~lCAmAaR%}yOD%oPUUr1w*Pjm3pxZr~ngPCE
z+dMw;WXn*xIEh_8NsC>WAO&yMJeqYRfPm59h(ojCzbps98|>e~*GZ+fo2ae?0Kz-r
z$Qno4Vgy6mgKP($GfM(L$kdO_stE1unCLIA_Dp>2OI2Tbc@M94t+igIwb&>*l;EtF
zKY22|8jHQ9CAzm-)+#e#9H-)%KwL!l?ZQI;FbE)PV0{D3G%Y_EhXl;JDVR0!ed2<P
zwpk$T!Z~H*yhDxJ7DP#}hu+y^Jd0<jds_KvQxq}96^0P5JzKnIH@Ro+K^~uT1a$>+
zb^G6qZ@8pYXXnlx{byQ#|HCfH&Y^l@CW@4@5V>Z@(QJ!=)jL3vlIezft~qq_&yHXU
zy+vtm1y5XP333Ao!Ny6c?wQi*r4l09-^P-kBELakSJc(_4a)4ahwoqu(8hXGr=RuX
zO}9Tr$PIw=hnng&R585nsaX=0N!L4k%zH>8`5fo?)^bmn;Te(T(Aeh_Qqdj7^Byzu
z4RZ6y+2Iw`d8c3{lWqDn-MmYhWv5@!O;z9?9AI-s0q>+$-@?T(=oxE&5q7{)q-Ew<
z!&7VI)t>hd{E%RTPR6ap021zwM#vV3Z8AmP+!tulElUCJUC$GDW|@mi3J&lp+w2`r
zP?0%n^)4(#^c_ri(D0{UCc5}baH8y~^gg#16&J@XwleH8&dgufDO)Bne%o9g1I0<z
z4l8$PPz;a$hlJj=Sg}f1nzZdkCj)x>3Vshrhu2{25&99c!!A3pdLTwOZ>j+JJnysy
zbP(St-cU^5B@s*zt)+j6NWU$+KjLV)W3SMv>SFFP1!a_cHHJHK%@b$dvSB<Wqb_un
z9Ha2r_rG6lC!$Z9z<z7C`Tu+ZUHUf;+x$N{u>UzmLG(K=_?wAsVs7gE%eDEhp+VJm
zSFB}}e>qg<MD7V|5r=!otTF}xR_rNAQj&*yVbTIdS8YRkLsr*n9%F}5%mSDoSY&ez
zf@}EjE)yCZamWOtZ6H2}S^vbjxsyC|kLr=7ky2m4y4`PQyj|aKSUyHyb-iKq;CjOO
z1UUlOib6UG&HSK|hzBR5Lezb{wE|K2(H*;tu=EK>J3ZaTe=nFBh52RsLcsE4@HfY&
zUf@t)U9<rvTeDJdOb4uPbqH|#`Z_+9`>s@b@ghx!^WeCHhh3fmgNgWD#rx;rQe1-s
zG9q=^sbo1Y`|aR4qfnSS$YyEHr64WQ8}CvBV;JQa>1p%}E!mP&80}qBXo?K<2C{JA
zRgIA{HD}P9>z&h5{Cb0DRrUj7$T*7<Q5ft8;Ie7yRr|<~3VR_Nt)CO3lVc``NHRN9
zCZIIs4sk-Duj%TG7|3T)+6ldu3Vpm*rNo;iCdc~+TTN5D22z?r;V~QJgBeT@B)ODA
zy^Mwlq?czd>(mU~w0WeB>gjkbQ3Cv^YsnVVClDG6A%<!$B@=%21;=TJkokcwJ~MV4
zmO%}a<y}nJ3mNKxls|aM@k+_6SW!+L8Jc@?Q-l<i$RK@~;8C7^by9_WbgSaXW-XOV
z6`VqqNQCelG-wpHgrv}wWRzgO6EoD{O)DXG_^pT|{ZPi&k-EtH7RX8|%}WqxCJsk^
zUJ@tRi!-Q9T|{<2n0FtyN}lJ>1@uGxQBERlYPBzPg_hJHT>I$dhe}b9EEnQR^)>-=
zq+#WJ6IF?%bwFSfv(nAZTjgU!Q>HE*ZRM%rq9-t;Cryh=40h*D%jz6TOw~;iGS)3w
z)qtGbQKo~4l;c)*&}S22sr0-x&2pv7cMTz`WK$v(#8AOAJv}@RmN_Y7LE2NLNBoJ6
zmCZFX9_slq09T9VfY=CYT^6X!Ifo41V`Nit{v00hbMt}Pm^vuvAG?tmC_2P-&xo)W
zY{9E(ug)-~&Rzbj&RxN+&Rv6(on2j_uOKb80;x?@>GW0K?^5<L4t>(!D7P1eWOnM!
z`8cl`Gg6_D-k~wOhd}<(IE+qX8#1F!N$0Q@d<@lxf?h)<-c^T4UKRUr96W<~<cJ*q
zf_N|Apm<6%as5~9K~0^%P;xEb1V&TYN(+akq|q?R{(6vA(*PjmUyQknjuOmVstu@e
zq};RmQ`4y4Vv7cLsM-=2k{dgH;pncOVdv%~lba5kEXoj#R?b~&N!lnLR@D;u|HDh9
zGs1F?fEpS#(7_pK9P8*BNdzNxjdW(#FTfR00oPL8&YL)cUQ+D15MPpqT)?Q!MWv>n
zEnmEH*gcYoiKek`un1y;CrU!V4ROyvU~*tjmxj7}xN81sFAv7{BnHtmc#ayXAD1L}
zM^uP*4VbplX)pI9Uf_dSh#)oUP+!m()Y%R#|A18tsoe3wnx3!XSi(H{=*npfNr<?j
zgNdZOe3?oQkV1JZX^bm7FdjW`0o-c5>7t>ZIDhhq9Fg0iJmx~Fh8Bo;wK&|Fj@I;m
zIc;|KV}2yRPMI>v!U#4`h%q-8|5srdOPq-IyEy=cUQa~&3beiZSwHpS%ly!JJq^n|
z3SOI~@#V>0yAp~~!T=RKAswrHobDH%mfQ%xb)?SIHG}`K19u#r!gE#DXh~Zl`|x20
z>uyEB9H46qA^V6ttvnciVS55J8x{l8%eF^E>_<e57@H{;kuYKM9zw?4QQCtI9L!Mo
zN26>GI(4K7DH@Lats&&6y5sZ!J#Y8K*e}1KMWDiO2pj1J*Z@1Q_9s4rVcS4GBiGl~
z)Ki7H+yu1#hsaXL3nOujiu#v|DV)72lF9`fOPe5+$3B+9u&%1_*^;$p)Q2I!Rq!ZY
z_S#0S=l<r;^_LmJ8(hLZz?Rrj%tR+Xw!?cOjc>x6sM#%PIjeF2qr@jYcFmqk!VbM_
zuY)CoG>=#0o!YGHT7A?>xv>zr3RWRCu~oz(?S_OTL?)X3IxDxSmh5D_C;a8GU|2+G
zy(m`!7nSDft;d?~y&bm;1)di=sRj6f?pon~>eGn{Hn}EA2qgfUa=m^NVi0|c6NGg@
z$pNbWU}wr5lK)~_-t=)mmF?~&ZR5YD>E57fDaghAAXpyT!^f9yY=IY3FluDso;?TG
zoKckAug^v{_O8TV^yFhr(As>C8Jaa~>YTSq{zT8K0s()PkQkR_yiZJzpH5$x8$#j%
zu~ek0JaQ==t<E6hf%C@<$F+zLq9zI^07W9clwAB<ID_z0A!M^6%F-DgeGEdj2r2HU
zbz8RF;n<}R`EFOB4MWWIop)?C=FO5_YKZPP(rAXjTeBtsMDl)K11DU)1~xxQ1mOft
z_tc+4g{4Ic>3uYc5grOpq*b~8rp4ZG&47KpKmWbhZX}dQDgP!@v!ng_Bl|zQAphUR
z_W$+ff7`$Qv*tFdzWXALqWsL9ttEGjfT6?Fhu`yC8xqoupkp|$`Rm=q55@Fj2RAp3
zSx#yQYsjA^H%V_6nJy5LpJ$giZ<L5G=-HW>XYPEr`||%pcrBFNWF|N1j1P>Fc=6CR
zdOV&?fA+lg*pB>s?QXULIPKx_H0iCxstggM`?SHMB?RHg5|D=^0WZQ~*khQ}>!J>d
zPS}B{4nK$v-_i5(#K?-h72zqnRY1!gDjK{wVekZ+PTZ+`$w23(-c?1N4o#p19iR>0
z5!*kd8hZ&(>7ooiGU&iRt{Qo1PwmFtOVjs~9TL;~N)9kX&@w7vnlr|;d`7RUZ!<L;
zMdTaUX>?bCE|%az!Ip>Pg6@{#Mpv3}l+!Q0l#^Q%`6~7zuqt!c5Mw0yvrT`~Gbb;M
ztsHx4f-&$KT5w@vGbeg*Z7`Y<74kFZhm<z$CHbU>)LB&g;+eCQk;JJJU@iOeou-x;
zO>r3$8Y|Y@5|FsT#*J&)i%T(G>7A<2|LE`g;jT^xLVG-JNF7}(5QfCtmBp5qrxPB%
zSPdY@SgQU~O6);hdlBY^Ai>A%JX{ncW6Bfh6O`aE^_f{}NSyCEDV3JeYDyYDF<h!&
zghC#~A&YPXLS9g$k%h8eJgMM<JSPz)^_Gkp;`P7R3nJ;MWg@No{4byOQ6UW1_QDDW
zYZEOg6AebrtjM#V(v99}DVn{Olm;1<3RSGAJ-jprT#2v^?(n)1R}f2VhQh~olkd1e
z*^AT9hae0S^hF;d_z7`LLns}B8p#<w@W}Z5o#<@+R+JXu4St%gVFkxyB;R<P0iYVl
z2t&9jZMy}XQ`3oBWoyGMHHer^!h!vm)wu`jWY+96^i9je6$pu&^d*z-+ZnE+5|0C9
zvzZdsjde}dCCaVF&lLyY%E!u?qzX3A6AqnOx%GeZ+MBL4;_r(XM60HH2eN_fmc&R0
zH|VvS0;4A*j7rM@Ksx91_26{$*P4`&mkdmr#_XAyg@tSNz&6SbP`<!xDc<OP5*D57
zT4<|B2?`7{KN2%65{hUPr<`4Wy{;JJ9FdCo93YNv(*3gcj1au4cN{+Xd#P{90lJ4U
z5VjO=FgpfrS3tBr0M8vk?jWpoiv55)DRz?mw)dPAh9Ir?o*=$`c;$Z~0T!-TYDWwJ
z)nazu{dW3uk-so}<?mF#r27lqqVz3yP~|1xJ!K39`qi@x-RMf&m6G2pC`hnht~RDr
zAy3KIg)?iB5ptGK)HO;9^&|B6fG#VSz*X&C>6~hgjY6_3FX5fO)znv__xi%NN6676
z+wuMm8!=?lHHQi2d$@ll-Mx1DQT-(gtW>YttPL5|pjck3kHjVFF4jd8rk%;E=N?!K
zIYFJ&pl~U7<X|%sDpYxVtq2c7jg{jy*Rd%uPA8MJ+91mmiGdt&ia(@;iY=_vjMZg8
zw}{9VKC>*yP^Y3dLHJgF{aNO9ceuYqzQ>~E#vtyBx@t9aEbmY<Mb0+fYODK*v`dC-
zjik(#YtyH0^>*J`%x&XC#puXZ$4k#z8F133No=A*lUJTKQx#=ykWZ$Ro@5L6c#vsy
zGUA@p=s<g1!imK<mym|hY!>4xP7UI;`5vqF`gBuOTHDqc`YE_bF4{@`>40UaWs&w_
zFhD9fq}hy2@l+K5hTJ^6T~_%pOexgh0^zG3{AjLhP~gHl(<E8PbxN?J?ThJy;uZe|
zD%j&xJ%hSkQn!)V^m*gtv}E4FwuWv2yk679R!(XjR^N98C<3@fw-OR<2RT78lz&uw
zKaxR-F--}o^RbKa6?9(;IPmp^NBD8YPQ=wdQ@a5+6<ZMOL5;D>b^ATjWO<BCo}lV_
z271}$M~<lM!=>&WGO*a;0dB>@>V)Xm=w+oECaCUFjOQFIuZez~?hUeG&P9I*StDk`
z3&4$Y+=0X9p&?qF*Kmgk+9^8mL=Cb5!eO3M+y?T=uFc05`aL^GRmFXVE!+qm&D$r~
zfan&%Bm@CKkP>Aj(TV+_1MLiBK*vX<vcMPy2}s(8OPSr%ZrtR*cm3({gNe$aV}=&A
zhFTl5gNdCRB@vNLn;wjj10{>NjuDHPzJ^*G5U-agGQfok%Xh)mJViZCJ!lcu+sBfh
zWzA2u9r+8V7hv1Z{?8AkRK~#s{@4w>5INi<A^faOj{naGorp|gr3=x_Aw&d4<6Wx%
z4;l)hOt&Z~um&qN^rEi^;x^I>nB?e(96}Ww!V1SgM|9l^(hBInMjJ_$DcPlKzXWYB
z)r#*T)r85^a%QYc8+T+&DR(H#QA@>+b>PENPt-F&?4Of*zh&*fqnyCaWzN<&nd?gs
z_{@HHs0=sCmj@j5ea?F}I1PBXg%6ztM0jp9f(`I68zp&ps4$xSd>DHwsQAQx?gRj>
zeKsMd-b(ZWpFA((ZGZO*F6lf|UpV3`+o>4ws>PZNw(uvBB-LqBCgMgVOvbS8fV)s1
zNPfG$lw=`M3g24?m6GneGF_mzMP0YUHao#KJ#e9Jte|f`LT=!UUw;m|Rw3u?9h_O8
z1EgS_6lamV`vt3P3Tf(d2UKGLI%#Ouob}iE8L^$~VQZwczraj)3As)E242MiLl(^E
z)Pg`o$*{eJ0(}bl2ZaI)g#ry<BSGUmt!$->4YzfGFChjz66#<PSMUcoq|`)jR6PrM
ztE?tEsU|92|9**s?c?b264eO10%({rs#ySAKbqxedNsn|l3~7~C%+*LecNZ9mfFSV
zw!HHS7^m<10-?Bu{GcS|VgD#&)n*J+_BctIzTfiwD+6L5je0f-!#86;C@6U#a#`r!
z5_lXea)jXJd$Qa6KMaKw3#1au0Du0F{sKUh{{Nm}{=<dw{}D%B{a-j-OHO+F5^?~@
zV@x7k1x0<Odr*M@vE(>`ND1X3AUG`3WGnlw6%Xxu^}q7?_kCb@+*(Aq6eihz3gD>(
zM&>3iT&G#<7@yz$o34LW?3nprCSlyzY^Oo+QoXcHz?;RAaJl9ez^CD#lW<44PRGTD
z2zlfvVn?}F4dh4&b~4Jlr}s!H7!QK=+uk+TSZH&08AYNT7qkC@YxNQ`n%^*RU4C_+
z$Q!G;pm)_^f`^#Mniv#fzXtD|d?ztf=SaA93^q5NnlCUCs?$;Jo(88Sw?t*3n~CfP
zMtQLw3*(nP&F7aK;id;+<y7oT*}_dOjZH5c6|1XyOiefILe5!b2<o@MUK=+zIwVa4
z3(bAEWHs~Zoz{@LRY_!rIh%(zJSl#%y1e7UA?!(naeTp#&fU$MtiAOP>ZvtJ*iSU-
zcdhTDKxmI$uXXQypb<BnAJ)#}?dKU|m6jQMlHLZ`L?0Rna&Q+zrg|}Y0HJE{h9Xtp
z40<c`%PP^q>EZ3w$C}m2s_Es{^S!?Si^xKi5l{|Rj6t#^=MJ2gOG)kYR0`MbcYVp|
zw2HqJ6F`%KC<=rys$~GV_yXfi0dTTut~;`c^W?eW(ikB0tN!<cFk@i#D-i1MGNS$S
zhxq?kMuz%M`c}54w1!sZwErOw30j%|=kc~!9Y#-a`I+~WdE8SPPfh_66&Mg%Lqak>
zwxIa0^?OBA@Vo$Z7-q&QOB@M4Er37!X^4%ZV(U4JeWv5g`ZPUjc8UQjYpEgL&1Cy@
zdFH3fZf54D6YTL1=PR)_B*fCsTifl9<1F`U&aI<u&-2G%Ed0Ddb-(2612pZdQSVHn
zQ%?0GcD7{q(Mh|G!+n<*&EbRB(}Z&lZ6IVInp?RaC5Re+9L2fvdDmPde{+>a(k$AY
zL3XN}J2@?q0kh7-okKS5(}L3aEkO;lTd>z9v<~^M@`4uCVkJxsYg_-GNZ=~^Q&7L9
zu}yaW<#A{K9!WMWy<1`bG-#_^d4#6(&QbBOfIDNa_$jr{2UDwidv>ct<MbXZ`(rWS
z4U=0Zws|OjsnG)iz)jMLgL%!|yF@mSj>aG(^bYYZ4K1_7oSr1;HpeUa)@5-t_LD=H
zE7~0{ESepjXi@k@SF2x(otCL)4@6)h=<TBd=Pm0S1ufoQ-~x8S$#ld1GDq*QWa=X`
zNAI$v>O=EF*YsX1)Lk7kY~)=H(zy<;(~kZfCyY<3lkMF5whm;VE%XlIbTmWP_$2G2
zCyY<-%x!9OWS7w+^}<%sW3|o(E!4{+SkZgl4Bo>6KA1!1)4;o$0)98)LM6kSOML<y
z))xY;Z_@4DyP-};PGHV5Yc0vU;axUCdMuV#>P+t4LbO-wOzzXdG(o@T(I#!5EXJ2P
z`$0FT?}()6TUmeZ@;gr;@9FXE<M#sB-#c3LuRJfj1e3nWQMb9@Qth_3hmYYqzekJl
z73P;0Lwos!LL#e8hA2^GFhQBy8$G^^4x=H3lp%;v$-Le=8PN*n5)5$9EZPaUZ|(0U
zHbS09IgizlZo(}3JILU#mRGr2adQnx1h{V|>#WMA)SXWsX9gXr@~4>=K7vk~W_P}e
zvyN5{2Uf_VViWORuE;dlYU(d*GyBG3&|(na{#-vF0djOzcg19cc<8uQgiw{6A)DSN
z>WdY2v*};-=#dIf!OyCT8Z%v8CIuJ;O{Dxf?Tkzk8Rl7bDKd?2W&={gdNVG4kX4b6
z0{$#Yq<ShxPE#mN`!;s?)@rG#^g*K4-~km&rh1x;C}2kVh*0_r7UKbJe>XTb$_WB|
zlIam8W0?|r#Ig422J1NsNnpej_^Sw!j^OdEf(R#7TfSNZoV`nVXJo6R+2I=!FrcxV
zG&@|hkXe$9wz=yIs0e=g<dXqwAzpZSHMPCwnuZSSmEnhmu)#Cbeb5iSMV!V1Z#G9A
zS*{T#*eTa*bBLj&a0$B-+VZz9x!^M>XCI~0T7o6~xw5!m9Fh$c0iil}T##xZv8&62
zhkEg8b}hsb748Nt^(IeiA_QK#Dx2T{$7G5+GbW`8CUV0Da{XbT@G`L}93bi}0|%D}
z2KoscxS<7_c7jbCXAFX^Cd*%Qv6?-J(K2K<o*_lwigq2LsQ&P=`c^Z<MyyEHNKYQa
z2HTrma5Xs37Lj%{1Fa3Q&~uDIelWtq0XpBB<*fk)d!UaX12QZ{=Y2#%tD1ja+Io?^
z&oSRH^kMn?W5_91!uGbx)^FTe9BCXuT&9x`Hd81!?7?#hY!RD2yn2e{x#yrcl67+s
zLr}(f$9uRO9#h?@K;8lKUbQ3{4F?qSrv388qSlHvDWLsWG_CyA=(UiilKeC9p&AD7
zbnpy#izV_3B(aZY)AjP`p+C?xK4(5b;DSsJN<aOnsbB@C;;q5oVzHnxuQ6i@k9;wM
zN}Mx)7Fr5k)iLyy*%Bjy6e+(llrzPg0%1|9?<e=Ekr&gEsp$rDQLZF8E7WU2EjR&}
zOax#7iKM*c#7*}`;0e})v(i%PYAkwFeN@P87iX(CvE|FF_(%STSAI9^d84jL2d#do
z<MH4Iu#*+F`Zkbd4gN$PK~d*_8RMjHmr~C^jthnr=$&SI)`sygM0X?5I9m6tMeiju
zyA1CT|5%vVCHiAtr2oPCqRG@ZduuNT2mEj+_R_{J)E8MN<{sgteIftIo#Lf`G5rLY
z8`GScH|}kP%c*)3!Sm>aS{+Ll`u(<tN@vr)sC>7NPTxvNEWa2_FicrJvvXPBPrsnv
zvWS=yeaCwT-i>X2DOf%{|5k+ca^hZNfr>*jzps8#Ci)KcGQWfT!y$8`v?QO=vicNM
ztJu5AabtpT)T-$DcVo7dd)EBbue}U04&%dV;vC!|s3MobWTURR+p}UD$?;JI9>9Mc
z*1chCS3ll+%1aj=%T9jLC*fv{c=}U#$4zRk=`%|91z8jJn<0osC(T=ljsWl3?^}xk
z>YJDx{ATPo=%<#;U|%20o9{HvZ{|&Oj!abcN9rHrPq6t-ngvH9lskb1XyVU=FXOxL
zKTbt$P9sGX<K%Z?bz|ji<9|xmN4Jnd1oJ_@swHDra=Hvz;6hbq3$S=}?|5Gc<B9H&
zTG~$Sa^zD-uJ^ps|ImJZyFKUZi9V9FX-}*k00Zon;^R!jqOikKioo?s7-70G%hZ%;
zACuBP>ALjqyogF}J>#_!rDT%Y6G}Vi(jkEs%t<KzW1-{`1jIiEqH{~{y(GCut4==K
zM~ayFS#-=ROp23>S{)}cwsajV^vtm*1{7S`Ac~71GHkn$ii}NOPBe?mwdE*gCFRkJ
zBbgh()pJEZ5kX$2s9*+gwEY?lsUT^~BpDg95PyUs&&tZB7b2vs8(4;yW{})=j9&no
z%3!6dg(!_W{<@|~DkILfMaw0uW#Oi8C|PHeXV*%zHe+l^X+LIeP+4P^fp%WkBWf*L
z$HEV_n=(%GxFY1S02?-F%BMivS~xZ-C}v8E;ukpsj8UKM;z>MxR5#t&uefVq94S^>
z9+$A_R_bXy{E)@P?QO{8y(207UH;Jb#5}TivxYJ!GRwvN%s!%tQi+k_OXukT*y)vN
z_Yt`Il0ZR%d#|MWx$5W^r}WWVw))BZR^CRBC?5d~*Ws&qxxG_;{!_vQ>z54}29QUC
zVBVLp?u@WStx{d32q4*4qEbxF)NDaqJxSY0IpI1)`Kqd;tls=MC#*UP_NPIMNMwLt
zv6D{|I@4(mRhfF%-7GvXfN~3q9EHy+zJ{8<xp;#?v2s2oQjR9*C6l1y=03JcQZ$nW
z1q$EjnxJ}RNyThVJG;Dk$!^&8ZuJ8p>hRx`*luc*a??fRNcDcWx15UY-vd_$@e!I5
zmwJ`RO;)mO9#>ce`J%)(Glj}#j}l4#3uuCF0IEc<bSbq$6TxkYy}x6huaW6d8PG$F
zfxqyUlA2J)*?SRs3Sf5Cf-QA($BP@z&#l#UCo4?nVad#{jjC=|-0j<~os;P5o<U|+
z9qXchfM(}5TQL)-rky0R6J0&!tw_qvGkAx`Dt3%Oj{sQjIyN=&^0nykQx4p;8B$sD
zwQ#d4DW<fKt){fKk5z73$};$KPRXngQn&Utmt#_T9#OJb%7*=v$)K(lW2@-rGB%o<
z3cDLSOK!s6mfnu1FU^`YYjx&}A|)5});v<krD=8<4A>@FrqFN;&~s@nriw8H<VgbD
z<82Q2_1c;uF0(Xy+U(T$t2oT1V~)BOj>C4PEm$?mT-^YjJUfmdI*v2|=YZpCYDZ&r
zESr|YYU0xH3YJuzl(-Vc)NnTA7pP2~UH8~VM=*ckp-U>4KODD0W}PYMQMVC7sc$xz
zOlZ6YhFQinti?Ra^%A9NOa&a?@-(@h=$&&OLvpXpU9I4J4);M}QJkIJT`i_C=N|Br
zn&Pzk)?wMpO~dSnMh#Ke$gq$;1Js$kVy0UABC1T14~=J#!iJX`C6sTJ*L6GVT%oW<
zxl7T*%|5;z6<VVG^u?dINM_lPCK+Xc;LD=1K>m1`u{}%S2It&gkfE+xXeZ0@g7P)g
zgkeU_P?xU`$aChUfgQ5_h(M{b7m5<3D->?V1QR=%F7|y@-EKKHtVx23P<;Ep=WPQ>
z;x#%1XV>hI&9K`_c_7#aU4inw9MMt9QDKgol#hzg69`fulRkHL4#?kUcj3<WA8fr-
zxZY*0B}a|sTbAc(3hdW??EyY(5%l&9366~fuk0B8wPJl1l5=4OHR6<Ai+BpN^IHQh
ztxxQ{N@7Nlq#7Tv(&2)Dv*1+yGwm%d&i-^KY#eDkn#ZNDfBYl#Cmv%#GB#_sv;mb)
z-Jz&#@Um(IWD9pbjY0Dnox&q1gG#*HpuK!Zi)rF4d*QsvGPSYt&>(%}+|dZ<Vx|jV
zdN%3GZa8)OZiZIZv4u}Qp)dr|<WZS!D{n{qfY2>HwnW<SKGiY!ql8MSrP691M`ojr
z3x}1FDg{w=JD(+A#}d8JIs5q9NeO0o1uMDLK^Fd1tUjXs^uek>Rm@V76s2H~z&b&4
z<LK#7?~kVZ`l>6tM&;B+eQEA&zf5ucvjeq6ZEoW8!mnEFa0?&F&nLrc(ApQs3b&h?
z#?g@O9<x0fLylUDShF>@K$@M(GpKR8vJ5X_6{E=lD67~y)FN$f%tKM#?VoLi>YZ`p
z>~lksGHTV7J6xuL>vHF;icQ#qhZB7xcq!kf@qw+e$e%ZxICZ)R^aNsBZwYg*<VXAn
zDt>uJs`?1u&JjActuB;fScFGd=-v;M^aJmX1})Ej3S`vbbr>`M7HTE{DVGK+bwye@
z%q%7h1!|@sc?_haC6oweHt{#RRWDA0BgD+&ls;ocgIVm<^{oVMAqsYPivPhCStF3i
z($B<|jnQ#QsyyTTH#1mudP<RzyU=7}Nvb^~yx4Rrkg0c26<;y1DQ{4<ykxbgG_<T@
zv2{*0`&82@iUxiTo_Yi#b*ZCmMf;$l0zI#|`Nk(h?Xq0s?yod<5vG3akhU4j+{6DO
z?wx`(iKA`LuIjRFSC?(uwr$()vcIxz+qP}vE2GOscTJsp?v0sqW9CMjr-{gie8`uK
z_($g6Yp?xV+KAjciwg_q`1!DL^I!v6Ke~Ab9<uY#$=;#s<3@U;A<CawnVGcglCda=
zb|z6w;?;kwllFfmexj->o>$RK5ay?(klF85f^>SutHUk?q0AAjz(VUmyc4k*&MTy?
zdWZf)ssX{Y@w<eu^o#WP&AxwWBg`V0whu=is>6lT#ud8dOm2UYaT5+dU}?zW#W*Ie
zEx}KJgu<VfdKdgjDIgzv@j+q-7N!X#Gzt{0YA8jnx-jarv7%m`DTHrM&-`IGdWNDM
zhmKp3!hU!ozbV{Rp5v|piC;Q(j?icsKlu2w@%+X$LeG^guBgqCSZ|8VmCrqZXD)w;
zH?H;&#+!nn0Jj~mJ9K#_ZeNn+3ELCLQ1sFy*5*jKGwE~A&MztPiqn}>SH|;d{*JXL
z?Qt)0W`AAg^Gf;j5d4VEFE8<?<c*}eGe&Xd@(KCQ`vrc8dG7xYk}n^939}i6yL6^d
z$c`RgBi9{Q?nj&`B1$&0ZpVDE4bYd|du-yTwAmS-tp0rbE|S;C*ID!<S#?%r#v_y;
zwhhNa+&Rr7Ww#ecKtiu{oDxCY&%U^&wQ=wYg;LZ<H|OB3v@_gCImO!G=DyHegloVe
z>KXR_mB^#r<NY~Les3&!_1bxtYm|Co>C%hqJAZ?`LZ^Jeq0<lUzk+3DuI~l%0*MoZ
zaXzt=uHHCb=Gnzkui3@M%_`FnIsT0jWfqeI15J;*)Ob6vGhMfO0LFRmY<8v=RRTy3
z*N~Hf2XY7v9c`LQfJ&C@*1|?5H{;_!6@|SzI9XW>UMS>YX8fRvKt<7R^z<zGB;wXQ
zqg9!dN8Z19B!lkKn#JCI`347!ebV6kkY8*4n8;}H?up&pe^1o3e}MLtU}n2KFvl+h
z)(h0lw$+pjt}zLwwW{+eA5K;|VRl99c`O{Oja-j7`oz__#J3U_Y*5`)pq&QFTqB*H
zJ7$-a<ekK2$_F9`)AI=D`g6VzT_xurbai|!kCow%tOBN%=Q*1TU&r?C<B|xYYJXR*
z3C+kU-pW(5Lg{<wH!<=_DeeC{ry|RPHylvNI`c3_+UFPT3xB*XN1}g(Ob?Ha+Si^d
zq5yQ~{R88b!jgJtF)Zhzln(%rRcXwWyH?TsG31$<0{)qjAR)iV3|HDG{Z7;WGI>M&
z{hs6vNfC~O94=Exdb^P^uHej*DLJqJrF=57IBm>dja5xgU^BE%C5CDwowcspT6+rt
z7jGz-?-4F+*WeVA;Y{E(cO%MG>we9vF5LCQ4`$hep-A7LU(n@}UVtd>cdp%1`WG}~
zZm4fwu-s>i`Jnrx5uJ@8ehp(N-M%UAuU7m<7{l%0JA#-ZtZ3J?puG;&vf|Y675GOI
z&_t{c{$o#)39!FE5h9tP5<e;a(vVHy7v~Lvwk00)xp`wddx!3amtZrlc!`1WCIr?h
z?Lu)MedVd#8vB8X=HC%o>8sHXMdazfL60?@cEkP%CceWDUf$uA<a?5|=)tA&C0=*i
zHGZ_wBctED2HA88DMeJmvOcRqDv<bA<j+Bby*GW(IGsXSY$E>1OY%C!Bo^I0L+>J8
zL55bvbMCC4{Sai!HJ(GpF*qQ|55^z4jVmPP2FvD<8Khl+Ji8!mR_%32z)OcgUMem#
z7WJ{?XP#qA{9*H<@K+gWZ!_Qm_phs8O<<(WQpKg+f&S=^9{iFp%?03cJDHtwqGlbg
zlogv}?`T7Ur-VF8R0U4ax(m<wh&X)urB<#0*IvLSelrr`Wti0C?3oyNM%MQ4r&Dye
z`7Xa3>{8V~Trg~VK@p$7n!_0s3NKZFH{_YY&tftE05SI{u5SvavjIcK`lV`&N$`sP
z9JXZAbxT6+$85JVmzpBiE~Inkk4o%kMzdvO>oOGWKboV@rH*FGJbC|N+>6qmNLf-e
z#qEXY^C$rEeF+RAeF=^pxQ3UwMp<5w=8g~_Xpetz5K{`k(ePF<Pwqe=q4>jt<*898
zVUJ5M`oQ;yK#A534Z;pXIPp6nV(!Vu)hAa$1jMt={(Mn+V`P5k7_dmL+L$5W+z_Hy
z1DW_K52Fc5!F?lWmw=c)K&*<ZUp+&JaEG7{;tS-V21&15qRx@S%r5!EmRUsVl>1BM
z^p2uJG4!7ncj6iggG%r$Dm}jxDx=<^uymNFvK1|;MdGIlw<w47YbP}D(wy?XCk6Ff
zeea`v@EF();w@l2M@K5wrceknSK^CC%AyoA4Fs2V^bb#!KD;kO6J{8ce`AF&WEi!s
z`;5ww7MuGWHLnG6&_lPaect8vn?HYhxuFDcFo+tT2B#RY<r!7cUWL+3#I=|u*4>AE
zGaT}abnL81Fjp->>1~H8D2e_R;>_eV;FQSk(>*f{e$8X;9QJznOCj5AV8`MQqhubh
zuu8VyJnkvdt0_I`OAJYU|5_duO!Z$?Z~x=JLq>hy`HG&z*2UKAbKt7u(G{Riizxci
z__`uKUR-1y7%PV`ov<rQd~jRG(Lmy=gj<|5gKmsTEyz5}gOYBi_8$q_Le{Lxd{jJ|
zPq~VbDyN~EN{Q4Qqe=dW)ULVOTz(6M=S@mOa;PSO0dg8)j6`gNjt`#Xd|)o?gG}!g
z6oh4N4{;i4pM?KaMK&s_WLib|@gs!z#}EGhgNm$TW@lvYYGoqyolNHCV&%dh;%sK*
zYNl#rY-=Xz;9&DV9gEtqzN#x3Uje4f9?UMpNcsrW034!_cn~ydR4@?~St9a4UbM=^
zscEtfW)_d^j-je8zvh-LH;)hP9Soh1`PvPBcg%8#LN#5T0-KkGO?RD|)@$vp>mfIr
zD_Es>ffsoqRC40wcav)`zf+#Qx7n{Rztf{r6$k!Ltl#K~2!)7<A&e1yE4N(md5HV4
zLa(<YMAWw)7Y{Eu|A-@kIaLGo@znVYV1PorX#Mdhyvl(^Sn7G<Y`iGLX?NveV?mr@
zV<N8-yalGcg(m@OY<X}%PWke=HP%lRq_q8tAH4*_;-5`n0nj8tkf5&`YX7oud|7`x
zl#g<Vc;f6SYxm+0d)(fD_-YKju=1kzH%VW;u<?H59_MUcg^;H1hKTh011w+Xh-ycF
zR^An6zL2)erKvuQT|A&Zy;&iBg?_Ex3RK?pO<t#|U45~3qll6M!0x_YwSLr9-k%b8
zhZ%(2%6u<VXb?9atl{_<O(t2-UP_;+f`4Pag|abJBgT`7yh~z=4qzp{6h8~CQ09w+
zh5!wuR_<6-DvB%qSq)ne<gu;+&07=N=l>uA17cIYCn7<OnInFn21z;jmS$Zk>^%1s
z_~xw=REkMg?FoNa8dI$?x&3B;r=SjRUfBjLk7M0|uy7-B;E`IrNE}MhY}%E^G@Fdz
zE{QuE%ub4BHI@QBmvroWFyW!h8%ue*^I&djsg%ur+47*`*SlveY$YwkB+O(isJBKf
zUvqqSR!KST(>?M-Ug)guFRqSB@X-`>R7jhx#-MM>=UC9!TP?L_4%^e5sX6M`ZhsXB
z<zBM$JgQBbcP6>;vKm=90@X{HPuI1Qg4JDv&B#%AlBKY%OV#Mo*`!UfOw8e7TxbQi
za>#k4c9xcXi}q~U79)!@(38g?t4)O+iFFucPE}k5vjn4k=rLG(k5vlwuK_$#f6~{p
zN#>ljxn`_zkV2|m$!~1yo2Y`VU3qR|tkr+j=#gTj*adNo?C+#uV^<TnP}|IwjBC?x
z`U2L$2{V;hzQKqGUG|L3*B8`i((`22-!b36)<oA#si~YGgm{M)M`yV#pcWr|h{myq
zs5dpxNlWNzX3fQ<w9DX7*c0Mh3do1f=`+XpW}laJ+?#7$Sdo1*s&jyMEyX#1_z5(1
zxb4id62<Au)|q^gl^zvZXiDU_?q)08nW3C|D%Xv!$-o+0uO6{F^p>w>(mUD>H$-a>
z6XFo$XR-^%kN!xyFWhFsM2e9+*B2x&kRhq!sOTk)pw+OvWZso;es7OhY;W12%t+bv
zb)C1=PNs}N$StDDm0BrJ92HNvzSnGBDB#NT%hc^X`9N;z>=uLC)NjpN9G*bP5Sy%~
z$0*m8Dwl5jl8w|#0@8PrDSRlK=cP1JuBOXxeb*~%*-G?WJY_;->b9gzZW+XCA+w=j
z{sZ?99rnX^MJLtvjSmx|-U+DZ961rnSXTOk4dddZ_#9f1M=(hw;>1Pb%s<6vtIK+r
zRnoMWb<(()HR>%Bk@b_JU7@GG+r<NNJ^EA`)(+LQH)fsr)eI%8&{DCp21)w7iFGaS
zGX4WDzJo><<0FzC^Tik*<jf+l*l~LTZ4%=+S&x}6*`x^iv?{gQez~Ab7rIAdndb0u
zD<0fkwhrYqYb_#8wtuCn{pSiS_x8*$6>m93D4;{t^sr{ghgI}!uE;f7)iO1-3nlWY
z%qJJh3`%;b6Zdy>-rMW7-C~EITxm+3)$vteE@RAgez_GIWI&y<r%IS|>QV7OuFiYo
zKNQlTcbtz8-I?>GPf4C<BZhuq+^JW`Ic9}6VCng`RGZcsS@7pL9;=>GYvoUDxps(S
zoHc42XR@9(ife5yr2@7pWEYPDPngZOH?2na9@=9_w1yvy{Y<NJ;)?INC<Zlqx1`e(
zl)_apv9IpDh5m+Ew3J9$+2iI66(yz5YbBqU?C|C2XlIhf?wG()AjnN&Gd2}ZXY_37
z)5t{eJay{QbU)JbDsWoc+iM_8rMWrpge=<s%YTe@PhE^{%vDlLBe%ks=EMcniQWG3
zvx%PW0*!rKty7nwhMPgd)?PJF?jn6Nr5`>hgG{-C9$&gvrPFnz+7Od}tvsj0G7SjF
zn0whM)|t@-bME)?JFU#^JV77APw)LmT+SXxtCBP2yix7W=w0*IWw$cj+VRz5_0)`W
zG<n;_JpvQ!MuChjN@jZJAG9d=h>|J0#%LvNJ;IAa`{i;A`5J`>u|g^3wB$#a+BdyD
z#O^40?@Av%?4-(77I%3pn&`qV!yTRJ@a`l`3Q_%@*`5&v$y{X)^u?aD?*-1a#TPRD
z%M6?D9lDB+_$*JmnUI(0+`#Idv6(Gu3x#76xr@62xHR|eHF5*Azyy7v;?kOW&rK=w
zA}t0JiJWRHai3RUkVf9z+Xd?wci!tUNspEH#CSUN4VmxN8w0zAK_nT$%;YtJPufJX
zpVM~`!j2HkEWX9~L#KDd?X}Ke+@u*BS%O`evis%;GjYi^I06Hc+74Zoj}CXHHhXhR
zo2|p;*~JxcNi;W)kI(k*WRp!to5LK+99@&O^mVIr#s$C0+Kq`Wv7}Xi8&%bu-{HG+
zs&}idDhoYx5X?_~ebnlV&jDMS2JL?Cp?og3Xqmn^w%s&tU22qIU)=Xa`y$Vq93Fd<
z)ci-+hv)8uX)ldvat`feUIyxW+>DqE^5itYO{UAu&uh}5=gx>yXe`D47@MmYUy%8o
ztSyNX`t0RK-J3}z`sdqZT)G9B@H@&N_1YnKZDs86xfbTyYWH3BMX5>pl-Ff026{h_
z7fVej9iBw}d2J@6ZtPPj3}t!F2kI;(*Xi9ZTL`kwvCm_XZ*i=~l74rQN2)$?YK#j*
z4OBf~x2u%Rljzu=H&fQ6=<Gy!0&tKuk#Y*Gy>Hm>Rkmbk_-DH7lyt83*~NSIg#7H2
zg;+ep7dqU~`fHzlzn~VN{MT&M=Tr4Wwk%`F!sjIIUIFNQI0`^2qa;e#a%+qxmzOLO
zw&_=W$+8bUH~!I3RX~~1$?U&5VG)Y?@)2XY`-p;roWKYxn4O7hg{wt6LNjv|Lp3s2
za@amE7AD;bga19B8jFzp4v#r)X?<$3b@+2-b+x_NTGLQg(`4c!BXRitjG-@DbeJP&
zHPT${&5X+HUfpK*1j#-imjwP4id{rvYwK%!JnhME!}U=pzKdPo6vJ(uV5zaXIb$Ir
zfH=L^TvF0d7RqG~8j-62@2AYfESj?_dTtH3y*F7&swsf`QfWOJ!bhfj&_3(N8_dOK
zgzdcmDaa_+^QlF1=s?rjaC%iOrUf%~zeyS|QY||$^ZC9ro6;U?u!GuPvwltO4GAah
z)L4hdFKf1TDHFydHqR7+&9p~)Yga>!_yOn-sJ4gNq|O_jBs;0Ap}`g2cT&X@yCn{p
zRJZC?3)~3Y=>0hQ*SP`WK&y^iixtElQxU`<Naq15Ae8w;mP%;&_G{{;iFYQEJ$Xgh
z9Av7+Hj5T_Lw~F>@~ViIiqtFBTH`0}3gEsrb_tMwzn(9OVB%f<$td@NI60kBjx#u|
z`6fH9OxCrpQv!c*w73b0j5GL0lM#;>FzM)s<pP!`>a{Z<#ES__odVoPp60`-rL=AS
zLrJfEFa(9VT;OPl^#BH0FSSCC!3&Tv_SPgEEKz$1ciiBMpeBnWYJ7sCuj@31(x@D;
zPE~`2iIvepFe<QlI~NI#@QH>uNpNgqvrZ_|oF=<Kpq8*cele=-+R$b*i*fX7ALQt~
zA_RNsE3W_I_V~JiAK%a7m|MLb*mit#0vr5?3LYzyGTIp&0-AppF?ma}i!=zxSDf{a
zSqEKps?I1{Ll%#1hgvh?-&Bl^ZHKwi3`GFA8l$ow5_#V;CcIHv2ng-x5bfuZEa#3Q
z@J55>N(kuhBlkx9(iev*Gdz?#YCpJA4y%?OA?N`6C<gf`LBBzRyh-KrjQcb8aU|bu
zz#qhOOz$gsJrZt)<S~Wpt17?$n>SQpe5qX{S1i2y_s221ueyKmT*v$uiTS*J4#sdt
zRoaF$lBrNFrt3$Lt{t2EB6AMWw(uowh~<b$`%Fp~s@}TTYG}O_zhsw6dB1gSZs`?>
zST<;dDqZjv`hw<^vONr|7d#i|<EgI~f!FLU&{?}9>wQv*Zf}HO^;45f!I<HBVeX^C
z62ZdTy*KI7C-oDg#t(DsozbHxOn^7E0_WcuD@pnM?HJBK(V?ylVw~NffJX|wt}H)v
zmB-3^uS+h{M~D+^&$=)keTgwCSzw>z3Oa?77s~Mx^)3I!^Md=+he~48G}(!;wpPKo
z#wqhL!7IXwmzsew){_d<*BMeOAK+L-bD`l8Y%C1{Seef7hX>>@vaTFPb<Ep(Ta+Z7
zKvWz459H3|h7%le1^0)x%s#9Dc!>saU>oy^N937?sIE62gI7W%icNSu{fWhK=VAJH
z*MF$K!Wr}=VyV0dFwtH&SgEcQv4s8zYY<|Lxs=kQt41&H5?#@~XdN97Wt><l)y7q`
zOVT+!8d%yZ&U{Y9xgakBhT%dg1PpDR8M)$#or0XT7=0PJ!W%uT>xD@j(B(R+wPBWc
zBOpWM@V=wfj&v2vbk5D+%j*u@5EIM<hm0U$#J@-1nJuGGPdUageL+`~y=C69S-*0-
z`G#xvioN<}5q%H@KGOaJ-5WCia&5;E?mxT|6Od5l4aD72>kl&Ansi_ZB&57n=mw`9
zdv}xQy>ijLW;`CKZ2%0SA`KF9``oFXL1Yhc`tuf;1vHd~-(6O7h0-s5<5}Ne)Z2#_
z%RO?}D30L>?FqLGM#686UMu(_;^LG2IS%5GXad4Cy*6zZ8DK5v^xCrsw8-gRZG4k+
ztx}Kam8SGiRvO22zD#tdbe>G;jZy$Vmw_|CO7)D{@|ith(yU%zsiv22BURGn$#)8Y
zyYp1EtG5%_^rzRHk;i3<=j!U&!@6nOMe7e#9Dn^YTjttZKF$oE_AFqb-yFKpBB%i^
z2W+1u27kXm%FI68fP0|-wPTLO3KdZJUO>RY`SC;Iztb`Qk3IeWXB+Kp=KLQvzW;2U
zM>M`P@K(^jx_3eY&0Z53;%&8U=F3e3V<H=HBCtS<;}621P*82o>t$1+r)JIFQw6nK
zYH+qHm2~=8D^^#_o8>-*tA3qXwe&Uf{rx8FU!C@RQ#sT66KA-L5FM_!U#@%dJZ}76
zcHUmT_&;!e>%H<uc>kJgK$l07%1#cZ@v0#5(g$BmryQe_g<uL@x_=5se?`tM?@#iS
zMi5xNO(LrN-qcr+Nw8q$tpdh`od#*f<w>p1(cHrF)&arc8Km!Rkr;qx@O9%82GX;2
zN4J$>YpmV$`B_#D&2w(#e~_op&#v6I(~Zby&dSYVGD!hRtm0SDQ=Hfw%Id6Fo4d)x
zVt8x(cHXT?jGbINxpNt7tJI2}Yx3**S-<;?KJo?ghp-#KDt)d((52!Kb*_JN;Za!l
z)uFN-2AA4Qz0k7k$8J&u0>I-7OD#ro(vf4g#QWIn$$5D;a~Tg+sCdj=J<@kUPpqbP
z97<_PDgavgA3-(ZIIVl@GwRPi=B|H;Su#cp5?qz_F~a%<hhSC{OS2l2??-OC@GYu`
zq&!!P*EW3yvl(NXEyiN?d5&A8)2tV!iv@ia-oYpJ#_k}dm$ClpH?3z2?hG=@k)4XH
zv{_#5qStFCsV~Q~KeL+`+lD6;Pjc!>+tt{8LW6aY7pW_ErfW`qTxkwIF4Eiecn{%g
zv1(&O`SB}N&(7+T-%yR=qiQ1CY|CQl`i9Wxm~}2i_2Y;B20G{U$QhdK%6s!pvGGZm
z7tUp(wOgoh%ydznT1B<i60zBPoj}dyHSB{O$*h^*I+`$%<`KqIgQ;^navd{!qFK?<
zQ{wE--`c1h&suTj(Iih_ehT6%DS2N(6ss2S(6ADl%BP&>!|*QLu5V7M<=H5#JJFc8
zV35%^{GoOYe{(|Ij5OU$it>ygq=fl-S&{U7(sCDsDyhq2i=r51F>p|9=Zdmf-whG<
z6zE{8*{@loWFC;H4W>@b0&d$!od&m2=;K{dt(WYo5ogwSx*4gtP<y*YK-`QLluyAl
z5X@DmcuFDBLBWOWqRaL}1_>tFGb1((wxMwOVZE;q$N}mu)H^Ybb{TaSWc!p+Yf+Vh
zX~WPTHT>Z}wpo48_{?L)VU1s3qTtY>Ue_!F5fsf+Q*6_))hO<2JA}_|KXmmUTmKmT
zRfl%0=j$LMV+2^V4cz|Wdp4dDV?Le+L(Kqz{kZS#!D!lEZhGKPbrXET15$iK6Y>3L
z(8?}=z##*u2ZlP68=i1p|18^{H>gkT$1Li4{d6n^-*Y5DoYm?(jK_$V*6~Gqib7%S
zi6V-Xdx}SK%uE-#{mVP9Vi`4QC>xL8Bu&eeWmdRdJ7P0jCD%qgEn*5*W4{)ZZ=$lX
znFqzQe!MC-#nb3xoW5>edq|~ASyqJ#d-&gUk^ySt@cSEZaLXelE~O;#KKR$iOc6c&
zweBGghg0_NG_^5>$ipyQ!?DHMj2fJoHO49o84amGJLi255Qn$Ms^Z-wNlkl+ZCT{}
z{?zN-f!cy+35ZTazHOIkzx-20({h@{-oCafmrxxyFCMVg8YB=5W_$0x!|^(dK#4S(
zl_^`FSi@GrDNc?gw^*7{Yo|ON^Hb&~K+x3l!)AF#RQd9u2df=8%7xkCr?;9P0(@S5
z;XREU$;4wz)+r|Kb=<LP?pc5NWwtWvy+4=dVQ&;TeNBr*SBIWGwqF`wg&n+%Pht=#
zPrTdRBaU}`);B=a=8vI0x%RRN%@;`PVIu`G`mY&`(8C;GmRB_2)DQ-d>G)e9J)k72
z<0m}c(=@29geKL2SPnY>^onyW{U@~Vm#En*%x4pnFHD}P?=*JbqWTDhBO>dcQSR-u
zvKIQP7Ofie%W=~@QRT|E*W{oS;ArWT==wTq^kRmXHX+ff-|}j0v;7Q|X^ZrQ{U6m-
z>V{}2Ur|N}9p`JZ)2-s4N7WR}9bX@Btri3!?fo3FzI9FrnTBy{?%>C#$mu{IMWRL4
za2R&NKt)4@&i-%0ooY#cTDdh9bjoz$`%O7lI9=2y3L9NX!D2xEcRVB>b<RlVdEFOV
zY<%(;36C$}NkSxWs{F5U7?!moTpVhaFM>(1_h@}Wc`+iweBQn<TNo!xkR0bM-^f{l
z5?;s*`3)GrFq@e`gRFhBAoZ6<?h$nwjq+zn$_;>p4PlXn&ay<|#;o&CiHD3M&ED26
z5gh{Z9KScWpqJDYg_(*qA-Cj$1XrKW_odb6Q21BgRmr|Bs*Aw}_=C<=eL{1bcRjK(
z^Q%yL$b<De{*3Uo_awwXBrYr%rx&)MpiN~+<TK7U6sA^(J>-vr)CBK^Qj=!po<gNx
zI7<@OAChoA%3*#nsk&E}Fm@NyqD(f&FcxJAO5W&Bar0qvfl?*xgaq4JFy+cB!%6#D
za)+GF=cS_@;uma)Tdi5Xw4bW6&Ydj=B`%bZbRi(Tg|4BDlGKNc@VyaXq{lFNR2jHu
zP?0waw7pHbBzG$`z9hFAA%OR+_tSc^dc0Y9(Ke)0*rOiNcd@WLTEvYhuI#LP$JJBE
z)x+;}LCOmz-y7=L0W(K_z>S4duN+&6@9JdIzu44%R%sn+^T7ha2U`0H!=-fly=mjE
zLX1B7T`%Xo{RaNAN57=-L%Ptq*oXUaL?EO!W(${Z3w6D)5;<asf)Ywa-ex6|Sr8<e
zIX*vm&J(&X4&u1leg;^?F`jPb>Au%j6qj$6AY`A&u1_(;e8J7)z)jtSA#{TvB%wKz
zCirO$_(8YiZg?>R@*3pu+d?I$oqB$d<2zF+z#{ut`d?4<w4NJ`N_#!S<Nrn|cxhZ|
z-2H~{aePySg#J4<%YUl;qThCM<L^r4{}%dNG;K6+*U)z`e?bhduLB0u7s)FRhYz^e
z0ap-k&``SBNW#G}m#b1Nl52}tR^l1h8)3~>i@ck^{J3vks%+jwK8XE<cB)q%Rrnt%
z%u3??ECgHOP&^YdOL&TW=J+h~{AT%1C%@k3_P#*!3Hzdf2)v6?*u`wwi;P<_OH87-
zJy_a~;_!QGx4~Gm2MZY6fU)IiM4da%X{?iYD=`e^i98i*=b7;_LtwWuH=ziK7`!_i
zg0!`#FnldeHx~DPTYd~IlXXuyFfj}qgwN*vB>Q}Vs)-WZT`re{Azgf+*=025M%&$9
zG5@^XOy^&{ph=^PI#Hr?Bbr@Svn`hz{j3y+-7I?0jQl9=bY^WyZ=J08XZJBQoE*3P
zETfD$IYX>(m^iHb>^K^&i8zMbRvR;EtCr?1?VM!C;^Xl;OfB?S21S_WL`vW=iCb@K
z^`f~sewpb}4eX+4p<%M@TGA+3pPH3^a;<WTv#o*tJtT)JBXd%2VP0@fRw^3O@T!4C
zFQuQ#9ezG;UvdK3p0lmJ?euIy5kB#o*&a1kQtGJ-apr_hXm$TgzGd^2m@yYszL~HC
zxOl59)>9?{8=L9r#ZZN_a)%&iMYo`Yn>%f?I*aKSygi{oR`Aerlier>%L8IYiJ^|8
zD~6Y1Iu1Jdgptj}-KTV6abK8d2Qm2tSaUnzuuRS&7ouz}zs^ocKM`Bxif0%9x)HBb
z0GdiOdXnnBg4Zsi!MXK3P0#!GV(oe$6@(hXJ>5*;rhT;#4>ybVs{P^XMno$|?TMDj
zAqHI$M71cjUithDK+|D~UG)_9DY48<i21YcqSLL1Dey#Av(r-;!J)aTb23(nfu$TM
zW&RMO;?8m(QUVywZE2}j7zs5tNkmU@Q#E({Gn9klUwk;`DZRfxvq~5!f(vfXX1R9N
z!Eu}ntM&0aZ(K^C0F8W995waotu!aWSIUzn3*|)GOd<K+wNL^0Hxf{G7X!#U&<gyS
zRc(ipyL88^KcCRw=K2XIuy$JrNV|oT2?V6w!NT_~-_ewK68hI1a=g~`(^YOgh9;a(
z%|30|y5i7ZdV<$ov=frz=r7%I?;@S`RLB~&|Btl4?wT-<<y-n)mDcZ*{2%dt34pk}
z$o_qdOv31wQV)e<*{{)`?9zO0T(y%??-TX@2Qb@hBS~}WBeXDA9uy9xU9Mzn?$MX#
zi(YFTSgQ1DFs%!c(rl_HwO5cY*zOZ2D_Vh~_eW7qTMX@CGE`NR@OvqXk}mlJKJ3nF
zcYZ}xwCSwQljK_FQszTltMjAa51VABIW`%CIqoN9h=+C)Plk}uXxl0#RHk}v#)0m=
zHKWV8dg<(b2A#?4eF%LyHaApTRTi4Od@^kNJrkJ&imllHT&n9Y#j`!qT*6T5oz2#C
zJ1DRAV(@-mN*Qx13UH|R5T|x=XdH-SuJZhlxFENy2_j5HG9S7=>J$Qi)1pT!A78rr
zE45J`A5pDU0ydj3lZ!8P64MfMCN52ec~IHpY@=eeS<uCzY6CZGy_r?q=>i5cdx*dc
zW3ARY`vIv%MRFAqqY{gUpilH9xD`rm#gpiw{k2}n)~s(e>DSpKLjOWKgZoav1pbKO
zk$%?0yO;~?!SSzXH``zz#Q9qF>)~YuO~`N0C?SG7{+JL{qUfX?nK=-lwmI28zOJ%F
zO79HH`I#_>#MMND6GvNg{*X&%DM6~o7b|1=k3#!j*t)?24i}DHT&o2C=tl0dWjo_M
znuB(bKl&D!f873_BUC4F&iDHI>K#@)t=>;C+QuNCu2xShtN$b7+1DG~?q_Br_F8Jg
z;lpX+!DN8I`CBp+2s{(({mU6i?g0ymr#mPQ7s1J<QthtD4Zx7$noKVEYy=6ga8H?a
zb%-_O6=M>}lRNx#nQ<VxU+Vdm*!?p6r}?Z>@NA#`qvD5`^|crwo4|}0Tba@l7!|)H
zKcey>@xO8ab+3B6szZ3B5SW7m<x)Q%1L_9TK@UEE?+iY2A#4$nHdg+$A=2;(BrDz*
z%oZ!$UtFJ%SD3IcppFFB2bp$Xam`22@96y@Sg@AL{4HPh`;CG2tD`!g9&t~btJ@2$
zN!w)5=<lklz-6jtBaACf{MT$K4|U$Na?g1ohmW%X>P<)TkqjHk(I7b7(=BLUifNM1
zz(1@NUyf&b!XJXa2;M+*@(K=Rc^gCctk<i;+HvglM(uts)OtQDypE#udcj*s^j~US
zc%jvJ#;l`lxquuP&5|z&t5bkh{DXP^zWl|XHRD<S#ykZtZw|l89T1bK>2d@g5iByQ
z-IXLPB0}!U9(GA@eEo040W|fd`Nsc1`+VmliTrndp8szR|No>6{I5BA(%8)Qwv;eb
z95IOkaacdp{RLQHJQxa;lw_f#pd)h!`Ok@IM+;%7npJIsmfk3hnrAT^Ce<tYMmNe4
z^fkS~)mpu-t{sW4D!VoJwk`Xb+PaqNXC9APS@XmRQ{!y||Bk(mQ~y1WUYFS~pX{XW
z*MXPZpY=h#HHG-6SL>m~=s5I8hjn*;;0%@Hk?voDBYXQ~-~y^fV_pLfZ7}-kw?(|4
zIWUm_^alji?@T_6f&!G4VjjF+Erh<rc>PHT1k{v50@SqD`k(_f(7LHz|Is1}Xxzbm
zc15k-%JBGyeks1)<sIDF4E!}X7;?D3)A?+R+5@_w_l@DYcSn998|<MN?5W=&=wtfb
zM6JE3e%9^#z~5B8{-m#b74Rh@Aao`aB17@3OOPv}om8g^cYcs6;JvG-DUQ1KB?x0h
zw|6dA6%0LSku0F1mcEnbM^~v8R@wMLjhtCp!J1<Zm77s`j8>yns76hYwr<6)H+iyv
zhrYt95iz4;#ZRYbMXXo4NV4#PL#JLL3)dY@j~VB@&?Z^}qg^@A9I6}g=UQ<8hmoI1
z|CzH_5P?J6^~JL*1gMZk+fDp6_xiU5Fed)G@&YOpK8|C%^2PhpD6ehu<{X=|5Z8^?
zKx+IxWH4lEOk-(t73*wSi^L;m?gqBbVxe)W&Pb%PBTI38|KT#$uLr+#;pF@bn0pZR
zdu_=jcI-CNV<Q9q`Z*K|H*xgAdoVXwFl}n<(1k1m`#x0HZ6#N!wF%vNe*TySIMC>H
zRd?8?Dx-*h8~!u|oQ%OVB#|lcEZT%tOJa}Tw}kiUhHUi-a;96^9Mb2*dItaOE_@ph
zq{K6bZ;dk&diFu^()BYkh^rdFgwcrVAy?PS^}Yn{=>h3$(Q>L<KSH;fK3f^emB(nK
zl|pO84HRsjLFMjWqQ<d;F!E-ug$QD@WsBR_OEY);TYv2q$+SurDg6ct$EUt=$V1Ys
zR(nc_V2YQyp093@wugGn;)(QNVz42VMde-^fey>imRh*5G?hwE9Ub-P`KedCS`U2i
zVDgl3LuTFWHq4*f!%m@*A4yswWaRb|D7}_{Y8hX`yhgz4CH0n*8=C#?wEwk5mQ<g#
z>an4i#yY7@sbc{-z?K>^j|&3{mm~15%f>4lPGJh(GYdGokd;XfAhB%nlK*o$#mv;1
zq2;GMd!i#rDfL^_Pm_b!Hc0c)5pDfAgR;ea7bb@3s$0+NpoFd5r(*-p!TQO+&tCP#
zQ<yj>V>PDBUz`ZX#riSc!$=k}F6CzJBa|a*VO?%;Xn*SNeTd}R3|8#?LFQh+QL+y_
zzxh>aTMZ$m;94-iwn_NB2tc-(InF?CcEvc?7&g$rn{*r@H5Qs-PEL!J6#5|ix3|7c
zC&GZM_E>4v6udIMuSKYUbzMH&H(4tRb997jAml@HY%<18l&qM<#{!P>9N&nweE1hH
zAJFrP@%mTg!Sr22hB>c$3<o)_y5K%{@&tzDZh4#(JT3*&vdS>XESqbn@D#ds!F&o#
zjjCmea22|C(Y$um(MO1|eQ3Iznq`i#h7(BTymu`x-7Gwe-4U5B{3Eu$Uy}lD5Q`eH
zSypo*hK)N-;ZK`)S(snD{*c>xl@hw0a=CU9P9<6OOuKLuyX&fHO&Qc4j=M>ma2DJ4
zZ+hWlu&3dAyNW_ORSC^(qmhwo4gw3?dCxQQX<L}6h^ecNe}bO&<qTMGSl!H1o>t|#
zKb1<K0Kz(Ko8s^x*rYB;rThj8W%iEFJ)3oeC;Jocr(r)KUHg1$#kVSycr#h8OYx1D
zF=DkBXteD@XvnpNt<HoPEK>R4vea<&<klD+SvRHDsGDVq+&60$2s-79dJY=mYS+d^
z@Zp$ZyO$>@m)mEz20WL}ATE^4bw~-XFtfXf`Ie`MR>m2;LD5XxtzF~cMyth%i7{5o
z;}EQt=UfVgSo=9w&!GGg2dWp!&cs9Q7tfYlSx9w?=H}^e{8H`7s^2B0B#X9&8QYfd
zadxEgRL<yQ`5C;gOMTk4r4p((JfP4~@8p>teAqhUt}Wu0&R`cn;-WwZ=f{g7*}Nqm
z`DEiLAIrrJ3K?u3(Hr;;O1z0b+1#~a0SjyB?_uI`3moX&wF`%=<A5ro9}=wGLVJs6
z(B6rEHH*qDA%T@rIq|Q<OjK`je*&!v(zxTCk8%y~rv;5gM`dr0E0TU0org4%q&1W3
zrB6jgQj9c9;=<bi5Q|`i_~{fH6XkJ*l8mA9aG0w)#Y0A1*{BMLxHtfP*b^Ik!D6!0
zr`Y=@st~6n)iQ`}k-udr>5`5s1-4DvWBBz~^moksj${Q)VibHgF{xiUt#@J^4>UP4
zsxr#OR(7&Epj@UdR5H-mT?w)YZC9IB%lP<jXl0Xntl>!wMd@<2wiXwc8|!)-YFbMg
zDvb=TT2@+S?4IOeV<KE3|Fy#?f%yap?aZCf&zv1mxfmZq{VN6h%_dm7KMnoKlt)V?
z<5gTkJ2ic_Y*R``VBz&`X0f?s2mQOMB;$Az62!+3G^jAozAx7u?8+put)-RmsbgI&
zFykFV;>Txj7=~BYTbj+RY^{`2t7)mhMw^tn=iQ}k?cF8(1KV~6`QaP3yJ7o^;MB1}
zCQpDn={ada19!g5KZHr(IHJC$d=X`1_*7EeTfx8^=I`UH1I3XlXI(A@9UYrDnF^3M
z(*X2EQz68W*oy|=BsSlZB2I=5LR3(DU(70;5v!KD4n^+zwhO#V-)Z%hmVDE1fJcTv
z!UuXoxGI6v9eg!+)5fkMg_n++7WkGG-7y8!+`K|&t(3saGVUkLNy)|41=8U0`{^Lb
zMc^KNDfLZjYKcy(qGYv-O>z{B#1R+9Nhjr1eZ?=YZR3QUcQ}z33Zhn1Pw7au<qPO(
znseboL2s(dXzNZA7D%~n+<8rjKg|O|mg2NP&12aVBTtB<p2uaho$M;#yKhA>(Q=S4
zZ}AG6P1_9z6XEI)oBt&lSKCB478@lnlY`+|+EN~PiwXr&VUPNNYChLs_<3B#hsQds
z<r{sy2A}8QlD9{L>HH*-bW}aU9ue1&Eg-jvMz_ZfZ~GkSoG_n$J?S_+JxZ&H^0hdh
zl`sg@$({(q2QDlua)hnH@p>=IrBf$b#&u8cB_RLWqzH+$lH#m=2<dF|34+c&h{nME
zpy<X=<u9ON@j<Cu2rc6v*B3vHP=mV9M5v1^e_ao*BJV7Pl_)RAbK=aa2Mu#o`-!;;
zFSnw$fa5b%Os7m2`yuKyrjNTg^qm})H7+iTGDwosJW^{krhj(SjsH{K>tuTY-u_A!
zH!1O0yW{x0adqw%yePq=I-M0zJWYGB%#|?Be6ZR<q(3)Fg+F0gR2XoNbG4GR-9eJ!
zQ)6>GO_QXW2DD}+i-ZdCS`T&q!TxU}mQVeX`;S@XPZW>2&&S)WXsXEF`=$Icx>f}L
z6YU(E{o^tWGeHX1(qFY{8PTD3FT~LShBVZ5o)E23P>r)hS+~W8K5>LoZ(A7leM8Oi
zi#3V%Nv>VRv5D+bo1>3fr5aN&If?o-R$awiWILqi`cgfK?$VVq-tp%|OYyz}zpMn7
ziewR|Ube`3L>76-dNdY4$oQzwe<t!%o|7gLq&+%GDM-EtQ_d*=nn`LFT|7^mjdv|A
zmY1@S;?`N@N}Nq|O)2IVnwlfAShG6f|5@_MqnLWDew=e8&*Sm^O+w#5J`zBrYfV$J
zof(T)Nhs_)#=^4zuB+)f;)I^2A0FM}-uR`47OgnmHbpHoMFNai_#){Z;aV3T*2NhL
z6a2%--@!An>FC&TH*GgO$5W#v=(cBKjb#qxn>&H1nn$U>8{t1XcnBv6&orebVz@*(
z`|&rX5BB#69veYHmdZR|ZS}+2yfRxw<DK`0pc&c7WaXe$R0fxm|9`xNY<Q)Oa?cq|
zZlW}|l&7PQG|b#?fhv_?JY+S`rNLBmLogOE65L)~N_VqwC(GvrqYFEe$u-aZtzVd?
zWV(=-pFBWR-w{NL>zM8IM&k|FR|@+|*Av2#@!;`D+C7`ySC)4G?+x#;;Bd>{6Y4>y
zTPunX&^8qJqcL5iIS91s(H*X8J5lp^RS3&ggc3ulCbwSn1`W2S72FNx{Q@1Y5tH1o
zeGg_V{LSNsglYHgtb-QlvrLqQgyZ>hR5d!qp^{F^iFL5B))2uk0ZGllD#aa@dhzX#
zZ%f|E>}Z*j3v1@-_K1TDm};6h<5<qsG{NBVy-GUn0PiK2KoIz+RRPaf21|%cYW9E`
zn1wu8G>PV)SvrrCTwyJ+G!}&pp0x~~=_K3%l!2mTo)nexh<jQ$8hNvHiAckY{RtY6
zlMyf7YhH_8q*U$)lJ*18<{M)#FdB#i3%B;GW99YPM5h9p9rrRlD5smrU&ISQbrWIh
z!g=bp3)OJPyfZyNkdEN?6>IVO(VUxUf#8-92_&={1*F{Ytr|5^blBEOsMQYqBl>bj
z?rc2Lx+p_GFx+kMU`kiaT(NU{3!s&1jtfRMP!P(aph?l17M)JUq@}BTTg#NrXl6fL
zfbjFyp1n#Pjz1*J#N=3_K7-FFT8Fevq<aP4NIF!dDf6>{f3s^vk7&GA#nKaRMScwF
zB$)@ltUkxBDHI%;b#xDssc*YN>x$gS#|4ZBOhTqR?aI>4M&1spX$o9o%S!jkeK>W&
zs0PS3-JAsJp(zW1szsLtXDSV%Tv{TkEVf&Yh+Tx<8&HGW@I6Wl^L5ToE;S@TH$j#g
zv8En?$PCoZoS+(tbk785m<fxc56wH-C(n%Lu>`p;2<4Pc143)ZSXAIK%%kY$!*oke
zt@~*J^|WK7o5RqwC8DkPYD(a3#n88uL}HsGGb=JTtytjaF*-vp&e$u<c&vDKrVI%4
z$+_j}T!XaFf3+;QG$+k25qM|R77;G#dxzGR86<}95;62BbjlUr+KQpo%a!HVBqMBM
zBpB(4`L#-On{G+|ZMAb<UzL{#@mbWK27+0QSvbOC>RvUL)SHOwczJ@3ywY}6<JV25
zO3(Z`@!yUT#@YY3<;W8?9{tw-)5CdB8-SEIr01we)_U-O=MCej_IzN!4H>)Ex_2;D
zc8F&ImM2cZsR~Vpz#V7To;OBWPbW;=+fN61+GknSKWWsU+Knq=M!g#gX&6;MR0Da3
z1evWn8;W=s-QD+KYcKv<l<j9@w{%D5n_+QY#Bqo2n_}UG_!r4wh$;6N_7SQV;BafZ
zTO!XJ=5SAYGa|zY7)zK-Y{43awrrI~u-rRfa~ck+$UaQ6&4DW28+(kVRJ&akqgA}M
zyL_WqeNd?Rm&68>n`_OcFmb{P9^j7b4!-w>bg5Xrj}49tUWV?Q_Ee9u+J8Vh#XLO~
z12aqcnj6$a1U`3SAeu|Yhp0`y*#A-Q_gf9--}d7Dwpg{I<29eIH!>_buLIu~NiLYQ
zmykjI!H2;?T{YHhWKMx$aF)p@AJW$vZ%%Lf!kff@^+4QEAb*W~dmv=de*B>PKS(0~
zp@4`wTe<%)qH&34bb!h+wtp}A6&Dv@Ny+>S9Bd%;uXu8B^b)cD-Tci|X)J{GD^@N$
zP$_xN)8r{MCvK-g=C%&5jO&x%9R-6Y+T=?exLez<nC>o^UvXDshI1Z^i=bAv7D;<t
zd&fPzH%}jn9Q3{SIKNX~)56flCnWR(OY-vv!gr``;r%&rbm68J2;gVdX(T?5HvQ4_
zmK_nV)tm%}{5Z>j{=U*9Kb;3hAk}=eheSAwfkwXK`~(Y*SaIJ$^l>(vL35L1s4)DP
z`OR}xuR%c+Y^(>-%JXTgyrB#-wPomdYIo@9bK_4I=)P(qU<OG#25ChO<*%jLyk!SE
zFaRn}dc_v<q`7t*a9`lKI!HiQ3NyI153^U311E>!rcO*Ct;U5<b#cOu^*S~eq0VF1
zc?_weNSqnsNNiAoY}TFYqGN0|8=8VS%U$eM*p`vSbGkbX+xn1KplG{AS;JU_MeL^{
zFK{#CQ_<!K21I<a5$2Ay<DjeQF365dZmhwUV%PrIS)6}Gpto_u6-IrRiAo1)X2z^I
zrr|lm+`8#}^W&T1GZU26aDP-&pM*9~m;WnTb#c>%5hb9}5VqQ9PLl@jy}Ba?D;zHb
zLji3Mdd-o{03LEeuSa~~p%=3sRaS@rxsQ%<ifN}-w9o1^yBFSFXn*up)=l&bERQE1
zT~j@b&7xC0N(kV?2_;J`(+4aCKS?pfbv<xa!Qq!2!b~MUpER8r_8((&No1UHtj$IU
ziPcTVn+lT(>>?Sh015m)OQE97swEIn<Z9_O>1R?j0+jW|AwN2XEKea>M21?KO69$a
z=f*Q~vk&??ewh?vnEIwGgQn~%5~*(zJ9DVSD5Wh0cr8}$dx7sM-Rgl;pm*o*i#>y5
z^!`q*54$R+;+ufUrR+&}g>K`S4zg?Ho=KincP|30SQ@2%5{i*JZuwAy;xhn~fBXV0
z$?D_p4ZXN^#}J;iqw+a>iH=duLQN<9{gv7*cK|4XF!thB89;RF4r&5*p}1K*HQAbz
z2^28)I`c%YgVs%(K&Rb`Es-6YIqD%A**1n<;)NDzWz)sV^K>eRbNj@qTUt<FS8)AA
z6DXQ;`^4+Z-*d|zVmSB3?;EW91}E<!*+gzH-RX2sm|inurK*m%2-7aji#q1Cmu*37
zz0Id?ZFzI+2-{%r*oZ`DV7sB-v%~*kO{xX7IZBV++<x;I=kFx4*X}5?EjTi)DxkKx
z0x8XOLJRK;?M>#{uI7neHeM%1X4{z%D-)R^V}Z2D|F8p$KGH$szz*9}?M83dZCUK#
zr*t(V`!2qt5?1d#K7;Lir8Pp+Wt^rEye>+f0j*QJi+2j=5%3yXD+}zXN#r`sXFGGO
zf%D7$gcKEB@4t*j=Bnu)e&@(<AxF#>CqU8Wm@h(wl=)ymftB(80K@2(IkoU{t#P85
zftQfR9|StSv`mrNqv@E9vFWMnx9e`@9hBFQU3xZA??!m?9RSY|J!B?e+O~R7iFsRG
z8H5)D5*u4gk?Kl{NF)mNwGUENHz#$<B(x^eq({%E(YOERx@~donV5#p$bl`e&&X(J
zxJVm%Y0Vk<?N>gYYa-O-0MYL@VWG{wg~f(nVUaXa@Kh8Oh8`6>Dv_lAFclix#@1L9
z6Hluu($Ad98C)6=`X#S&J`as!%_%9oJI+jYANSzYCL<pmht7Mf#Y{N(D^ny)VMitA
z^NlVLORjE_l2>OP@9We#elF6K#%D0jsU=-F(q<q|5T+)CQ_0jWFZBs-wIl><lgR*C
zj$AZdIaHo>@t<KL3s)>sgOM&Xl%@xV!lO77ug&QRWKH?m@%PZxG7d3I#>4?0wZA_f
zgvMnE@;IC@PP1O<ROxX;IcJ2x?N6E}b#$ZD;ysw+ezfhY_l9=kVPt^URet`+61{0W
zE-F9c3*_>%0Pd+Tum(-OS1M7K%?e&c1Be{aT+-NLg>{b8z~KKWslFsi*VR?j;SA6^
zXkNk>l~MMBQddT<oDOJ7Aqgf|G1b=X%V*Qfq)YH%#2Z5oup#f#S&HGV=40CMo!MAL
z0JLjs3yR4t+hc9~p}nT@xU|Eca!2*I<*#9+ZN+)G#}_94UIM#*6;Pfj*9#4ZLxJzK
zU@|HU;1{2?G@l^^OfNy)O*`W(;nHQQtVt}H3&eITyuTm#+A>mTv-Z@E5Z2_;9OW}>
z@9o1^M)9%<^}W<S=AaEs9+qPaR318GRC5Qvv`{8qQ05}hU0`?jiNROuw%3v&!Nm}*
z7lO0B|NTj4stgc9REKQIXAbg8c8y8oI<^E``;c!1OYMt!dxE7l5VOpxqiUF8AfuJd
z9w<ciRRmixf%0s0;0z3<%arIYW^MQ?hI}gz(eHBwGeYbRzosSGDlF2(P$h%bLran5
zivV*6K(!beG7HNykgD>P$cdE*^(|M*TbB4zvABaqkJ?5mly-v>7C9V>{hPKN&hpIi
z7#b;*e~j*$r-U)iYY)F1$>up-k>Nq@Ms1o8g|O}S6%T+e+MO=1GvD5t5AT|f0}~(|
z3pd;!k~HC={ga;>XUxDK7QD?hoI{G$pCoypmF|fU>=~HMU_>Erf|+pSNZ@tQ5Ly1)
zqaODwFc@~7#@wi{e5j`o1X2|2CGwk+p$_zKKtPO;=cQx^5*G^mLh;l@yNy^6AF~`W
za{3V$Rphx{6}-k2&Y773^n*f@3(?v`eCsO;9q!9G|BLXz8%U?iBe$h(CG%So!Gz{I
zOnS#=R2(_P%0vKk82R3l&DwgHeL@IshoFwS%CLKoGjV0uoH)18!M)zxJd*Sks%kde
zJfS3Sm4&)WEOA#`A)qbt>T$zcT}694L}A_|N+Z(2=sBQ4bl}J3ElHt1+oZz`8TCrf
zdv{Sg&v}+=ymEh@e=tng@6B&Y7o`YI6^|bXGXEBuDb5!>la8+FG%Bf?C(3fgFV8<|
zXZy_Div$b4??z>7jvmA`e;)<@YbgZSAbtRc{<edD^Qh_mKT09fZ~p{?tdY0Zf7C<&
zNp1YkIZ)3xZF+eW{R?0>uZ_W;ZU_^Y|LgbKr3r4n+<+hvdl(tJyxmW?MVVdvI`GEk
zgl6_{7ey^QUsChAP?COeGJ%y%V*RKS?%7W1%g!Ue|3%;YT$$XS<mOYY207Bwzxt|$
zERMaGlOB#eFK?j093P?~>OZAePJ-lx5RcV;Jx|HOuFxYs;rm@2RiGd9ZXBYdr{*9j
zGB35rC?uJ$Bzei0DeXY`$Qg0NGbsu`&cK-I@?o)O0Bum5#BF;F#Vs^;-f$Vot1DPu
zLIZZ0_3bZyo!F(<><|{_RbX<=+#xJ;Zv;c++V>;QU<Sz62Ix1xsz;@ulMaq;!4zaX
z#l@pFSA#6bvQcSVm`fe?+Xd)=Tw#;fyFGAEJE=JUp3&P>(mQ*aoD+ARp+qO0DO1l%
zk25HRPT}(i_R<mfng5HkcM8%ph}Jc$OI@~Y+qP}nwr$(CZQFKLmu=TyMpsSmefG@6
z-Vx`-#N2#&kr8>7-^!J1J@1<`<Gz@bs$6Mv4ddGNrY*-1@$nXv(^DhjPmFl(9l3|u
zhiT<?*>YicX}EXpH#SSpf=Hf~0@BV*Eks!sP|d2VhNT?By6tuVkc~w`J9rCW@Yij5
zt1-gawNY<^8mzW=2H{U?r&{SVu_zfPU@LFT5I;M20PlDb&(UQX<(G@NOL$?WiLR0}
z>#)?g@>7hv^*H&9tA!oDyjEKSGA0_hrLqZ=VBwv6>+vEU?a@srRJ0*us9C$=f?2Vk
zLsOmINVltaNSGp0#%x22PgNlc2XdxQz}o!cjvn4)?hTR|M%CwYOJ%2Kwwmofztt`|
zm9Pm@VHQQc9hV5h#SAkO(JY+59K2M;vMu%-r&?3dy~JrB)UMRKl7iCz9>(Zz5n{(o
z3ztC>AcT(#sZUIG)OLsTGo@6sUz-h9)zWl&%xbU<>$6CFRKe`Zw9DtOhKm$y?U1nP
zXSac;J+k8evq?eEtNe>E*vQ-Tz?h*$CsK4XA&-mf;0oq1v<n}PeY7o~Rcz$QB4z1o
zRY_{5L4?>@I9-)XqtURbWm4%)S7kRhCV0_Foz6jJo;0f-Cgf?CX`p~eHBw%>gW!-T
z*I3=j?<^{+O_a1PDDwzI)s2~2%^eBHU+!UrVR0XZRoXupY-03+B&5HLE2Yt-$??~k
z!nCKjx01yWOt}J4P&)UfHYImUp_iwnJ*#9rWT|p_gi)(Hc}n+P*Q@ri*X4N%4X`1c
zuBcD7!Rkk6q52~2Dc{)oh!47<`oiy)%j!Y`FxO_q*bOmwYB5F1?Hb3l>?5@jDk$YN
zy3EeUDKVjFz5?9%rJcKNwX+d)%J&iAqTh?5^ag-T&DYihmnY4b(qtVkW*xMV2SnM7
z%TB7Y3^k5;O1sjm%w<z4m^Mq2{w@hXgYcVhC{n4qim%G1XH((}=*(A{Rr!eo4^)Lt
zRAm)gSuFz8RNYroMsZa=jGXXIBdUX3Rt>kXRH0Qi#~kK=Cc6wQf>7<VxTgDTk^D;b
z$KN7D@~Pf1;h0;(L>A188wi+K!q1`GvgnUrml)OVoxh}p>QTSI`%Arz^Ma+!^#<?m
zi$eCOF~%AH(}f#rr350<Ql_GKQ&A3^X(EbhuJAIs3*Vebkl!HA3bs1V{a=};&a7M%
zcdF}>Lwz}|TUPa+9LM;)18OJr{(gQ0aaAQUT^<n%MnQhbBQrN9s6T)%zn|(2`@7Bn
zT5s6l$TR_6*w#`$k>A&aklZU8PLTzM#xgcetL(RWNterQ?qGwlpichlWH1d=%h26S
zR76cYyz-BdJb<W>!WP{2z+KZZ9Bb2{hGclxWdq!8zEisHt1p`z%o%X8NKMKrU$yNV
z9{2-q2WWs88PdwvoE(U-jg8(~y#s1hk@9g#p+{_f#7}FAo9yqjZ^zl8j~Qc_AW{rE
zU-?<lQX?y=&Rl;<*dvD4Xc}5hldV-VajPJaN#4Q@JLSlsvilKQ?&gD+<#W}=CAmEM
z`27LrwxHX2cgcy4h={mVCak$+;VGn4kxfj*J~Cb-nQ7;n*^=UB;`cQA?;6_J9+q-n
zswUmCso&{z%kGv=)+UNrMTV<S(pNv!L;cA!{`>^lk10T^2ANl?7;2H<L(XdYR0D>L
zi}}~SynS3zv}@pWz1e_MMTa|f3Q9*rH6CHXUQrq@TDy#pF-P2_$s8PD;43?gk^&9-
z%SME_3exCz>=h)8i3?_?4T-TLQ%f=lV-meEh}|Ha6LA#Q^;j(nQS-R~`F`w6K{Uea
zk_V%P))1eUv;qGGq<B6APVB6~qybI%CgsOr{dS`mjJ%=fW7c{WPMVytCMjNpfw|s?
z`6G#?x~Ctj0pj1gAR#yG2>|R<Op@+Fwp2x{M(oyvSLj*wU1HGHLM$HOAmDWjSkivK
zI4H`$SZ(O$S|8=|kN2<J;!Zyp(83+@i6LW8@aN#?>2ilzFnR0ne&G*!6dr<FA(CSP
zBqNsuC3Qh#D|(QX><h}%G*HOwF{rTeQy~2N091WOATtjT@L+>ml4Mk{KUhLKSFZ?I
zKD9)DZU=H%e#GcoVC;+bvLDhER#FKo+-HJ6)GVA8+6^fLdjFAgHJ4gh&K|08)ox>J
zN@e8G3r)Yv6;a_(t72E6?_DK`PBQC3#u+TtlesOU98Cw0Bhoo}88*b3Rnup5x+at!
z!~ki>14?}1rD<{d78Vm~;TlY*keZv-iAE|`lR}F1u!6nTcq?`p&I+_9z$=yepf4k3
z4Ph9Dw8P6Cw=8V41zrx|SK#FZOO`!+;n+?cjefmvTLS(iU5SC<oGfyLUW98-h_Yu9
zI$86Ei<<G(A;#5{tOKOPnlz&riKCEQ7VgQ?_S9TtykO?uJbK2v=XC4G$9nNW>(VVP
zN<qYfsSwbiH!+LxS%7_lT$r|IRtMiS88((PcVY_Ca1Gz)JKn$eFB2!CNGx(_I<N01
zdLj<^oDTe(=bd2iXxnL(N`S8>)^!0;c0=It=nauHhoJS6NE7$vvcDC3V)Bi3cHp$f
z%GU18oEvLA+TX3aba-R~;^#H|S}E&YL6ng8<GiGivHQ5k4fv6;dMJ^UX~cQM)$>PX
z<_#A$;+V~-%Ti{yk1@OPzj>bZy-<f8u;dTXyVd@p|Mz_A!?eoZ4g?5D`yZ}K{C~=)
z6bvo@>zyoL6<vF5RRrEY-QP9H?Q#|t(iZO)#@t&pDM(UAIuc6)ib_=1AwWWhW4oK!
zGj*EviThv=%=_^7Nxu^;r~*UwL#4io_zH$Hb(1?>D{6b0o!xG8nep9!yxykmf$H{e
zaG*41jDYJWooHkKI5RY63?@yOdg{*Z$HG_{sgL&Mjb#(<Ng0#Is)i=}k~_G%Z$W<4
z-P!KwC@b7i$<%!4@vrE0)OLfAN4}M#B)M-F;8UTnzdWUH-dfe$_P2MRu?(Ar+U(eR
zbK!u-1ua@2NIvJ5-L;NvBQ;-o*=Z<eP{-cki%)GqomTA~I)=jjakhiy+j9*H+r8l$
z8n935AoJZ6UV!1Y(?9qM!*8+OS)PqEcF*Ek(e1Zwr?}bLgq;xCIS`&-j?V+A-t{M+
z=J|-EUNDwsndnBj8fHWO^}^`T(>Cl<!JDKIyU4vb_amR1q)4@IT6tDr=igfCrC|6R
zX5!R`aY?_<<0_LmiC+ifzvlQQEUxrM(W7rm6YFh{8@&2m|59iFr`XY<AC1l=yZSS@
z;G(8mDX9ij3qih5!`UlvxQU~dCvQ*-ubeS?TyutEh9~c3YT%|Vr2c~=9$RC+IE0Bd
zdY;@<g`u9|bHwSa5h#24gTpcHo#Rx|b|Wt3_8AAWf4cNRFQ(mm!Wnb^fe&@SgCS#y
z5~Wi90hokAHa64Am#b-Bft%YX|43GuW`gF~Jkm$lQUQ(XwSel;J+VT=-SA6fV!*Rb
z)DDQwsW*h?lwopHhro$&SBz?2+`T>ky@;WxSAuqsw^%P7u6GW{E4Nr(#ySqedQMg1
z1`#noRNv6g1Afxz66j)TUIK?exHcnJ*4W~-1809EK0HTx(T@8tGhQAG(DMdCl#|lp
zj`6B}o9>=A(iPwG4&vmv{xzwL8|eXx1uW;vw^QEFiS&Fap<+!_#TsMvkQwA@q-$H{
zZ(@#>p1A)iJxKt2!GrN)X8z5WH1_?4pYg`0<TpNICgZqN^rkG}%zsKA;TS?v6Y+EG
zo{{vbCX%DJw9Ot@QSXoxK>ALVEEBuznhUFSz*5^N$(}L7we<{FX`gULmfRC6x;@6q
z^0qg`#)p9!l{;LxJ}AAYFu_TWEFF_#WL|=jEK$znZ=9v70LD74eAw6#q)z0CT0iCZ
z^FP#Zg&#et#9%-`6EHwPRR5>nRm$1kPTAB+#FT{bzZkgmEoWp?jIsQB*)B;90s<*c
z3J63_33Y@j2(Tr#QfYQc$t5AmbDQMWji%W(SuG0M!(XY(vFLFOP8TpU6S3z8;)&Ge
zCOvLq-$3TaOVH-WQxCrEF6_Z7l!r0^o_YJ%t-FT3Y+1lj{@yld1Lhg=dYJmKM(~ZH
z6gP%8$+gM)Xj3-n+!B@`_GYIgkxXT9W9TwonjBiHDZMm$^jMOKWMc{O`550V0diT2
zsm(!(@rB`q>BhWMKxzC5fi(X#VcIZFy`+ckP{2T)#!H3fBzp3P#Ecub@kc}+JyxTU
zUj2C*F9vnO_>_x<M!aj=MJn8K1Jnl9*_b#?V3(gN0lzT2*I=8tk*M=bL@I2#flb^7
zh_G0nQQ8!-NgMK&+l*ne5bV+|<ntZ5g^KZl+ZfmjFM#6J{q_}eGqHUpNppizq2Eon
zUZ7x>ZlUSa+H6uH77iXmP7c4}d_rh;?n<rxHe==$ZVhuBG|gK0Bco2k%ThsdV`I^0
zu~+t=*;eiiuyZpiuYU;Hjh^r*A;RQlvE1%CLub6F_p}?OHOGw@@~f~hxs>NLU3TeU
zi6Z4D7^Ej;Sd1Wwsm%ZvCRvyXP9SN6%W0u0jB_(m^ej^lAtc<Za$;lNC+28IOfk*4
z#+YVYvrL0bQ;vaW^a;rrNzZV4Ke;ijK3|+N)2{h@z=?30Vj5(cWEwIJxu#rmiiS-N
z(mt+A6?cV9diKysnMXTun<Nl$lNJ@GTy|;tw3sHrWqn6iEpYXBFFm9=D3{e%r)sgo
zD#dD*;%zn734YaBJgjjS>(t|=R(GAgHxG!yVn{c$mC|fwFJ$1{_@7!6Zm{MOZM)Xx
z-|PjI8#sbYyRy=gr%b%IA%l4-S#pvb)D8x2!t<v`J^R1L;pV@|_`VW)zSmr|q(_v2
zfB(!I0@wO-Zgv>7G3Op^RhK#W)Gt@^x-<w&k3(W_F7wuE6?tu`@*&SvPKvOh%LDXU
zswzFo<cBx|X_?d9pC@a0-X?J>Hrqb!FNR+Pt}Ogkpi6VIE}hkJr^t@7PQ|pA@z_C+
zGG%(?3r_e~pKJK%nQaRLn5Ip|)R)@tAD^HL_%<ivg#vv3^6m}D&DSF64Tu5A2pkZe
z_ro{bl@ZwOMfyZ`Sp8P@#R(GnVg%BoVM7G*Nr%Akg+r3!4Tln<l_NTQ=Q_ve-?>iZ
zUL`r=8P1P<{!JJEn}&uE=A$EtS!?kN>MVOFI?Z~KXA1ZAi{f;$kBi>nWYatPlXRuQ
z#VbB!`ft&6WVW|AmcrvB<`6=Bbp$bMt$LF>%WoQI*-zCO!+dpSai2KG`G<E-vyBt_
z1{gz{AtTVmh*cF}L8_qHb*bGLj?GEruj!aChNven+z?Uy`teEfb7}z0yQWVJ^fCGa
zCS9`rp!!>u57ge#Z-Dk2B!BYW82wx77o6WXJ_Hn@31dDFRa&I^gnGoY5wU0TI+<HS
zdxYGgXk8>oQT|r~1r(OP#$iSVK|V_PC@0|YFz7AiE2)EskG!9%Y^0q<ju(Y$)AJYs
zpOBnyQ1>egJ+i3fQjDuTQVpv8yt;Bj8j}8`$HdceNZP#DWl>tahvlSHTd(V;lv}Th
zJJ-T&*)lXet7qkqbXGdN=Xh3L#_OUdozC;3D&5Y5*&}k-e4$5w2#o}vpqDvUVwR-2
ze+YfEsg|XXYcnBz62v1^rTmp@$~vQn@Z(c)0J}SVp+ACMk?d}4%ftOOssDd)$ZPNH
zTL%9^?fF09G3Ea$)c(&ZQ*FAg^OguoSiI4=lMc6|6~$g@sqB?c3tgxXAz{mV5vASI
z7@+`2N^A`WRFeq_r|psubV{aP3MSpY|A1`9LC`@K{-}c+=`=uVM&f0TWXX%P_s(-}
zW3}%4{dK+{XrG8@Zh%4qb0U~FSa@F6Yd!fO3C7*DgM7FT<~P%J`avMf-o$+^47{la
z$*?<<551t37&D8xT9AmNk8sd&kESXq2Bmda*HVpr<r>$<QsbG$hDt=AAWiJ|3s>@7
zoS8I(8e6SaBuhk7ahe;-A;L~gYLy3_ZZ`QpOe;gp6^quYig-|~u}AtvLXuppR>hHK
zwnFx&KOk1uRlR&DYxyW}T)o{*byV<T=8#v^mLtp30MAc=I$KNiqvg`Ah*L__YG=Fn
zZPYZ4dDP}wT7gDP3dC0k5&ch(oDDY*x$st2mAbk_ZfgCsLQu`9kdr8BMig=oXmFGq
z92^P8O%(WaU}_$-tS+h8k1E8FXVJ<KoJLKww8eDbnx#Yhx$KM{AxjWV=(hVxb((0y
zxAR{kySc)$okGsN^3zkCQH+AACiGfRcF{EuR7TXM9i)EJ1|*g2vHUwW8Dd$}@s^x#
z++Yrwq^YewpZ@x4I#($ctV7AOnWlpZ)>R~Ka~?(exi>W6GnwhYB2=M&`5Se%nC$g=
zan$a)^C(yxU)gLt-+V$`AL$NBkT`zwlUP1Ey~9)I<=45jCmi8Y(1yu$*97Y3Y6-a8
zmcV}3^@Vaxabeq&=pfFB(|a_<i4`WqF(9u@2Tw@ZF=RHctoWj|$*g%wy(LR9rz|v7
z5o~&1#?4;FY)jHu!syf{n}WeSIAffPz2P%<jm(Y4XlBdk2&TPou-Tn-m(T{)!dq^p
zO)p)hAHhp^W@v$Ms%<vHHJF7&163k4XxZp7B#IfC2A*;Yx?@jrd{jD_acNWmB396V
zR;y@*Pnj`0t%%Oj1vsXqUv6%B>j4n7IbaWRSg}fjvY$!Q13`b#wb%+>hAwA*z|liB
z=x{~`>)OdH7aq_L3(0d@cMv$<Bg!z}|A)Ivi+=B5&X8QNE?7568If<ED`iKMa&Q9z
zzUwZ@XgxPdvpyTV`_GS*Y~D!ylj49VH2+cj5oUADxcP%R<UCT|Z}M-T3wIls0Y;uO
zjWbIRxOmN1a1T5^APK1!uJuQz7t)6>s22m#jyz<Cq$^KYIWX`0h*1%CtPv`bd-ebx
zMow1<kbXx)9Rov|j`j}2hBb^F!#}1R(4sy;ZDS98A_HPUk{JLSzL7rAJZB5#fDuBH
zpD<AS7cyq<gWdD&6QAZBbF>zY-)FqhuGhteWs8T~gfMN)S%$y##t`-(_e*@kTkaBG
z9G5impmFA|92Ot79vlEL<f9HsZ{x_bpb>yR{oU8;aD?7K&j>LWu*kYGqOK9dUNHM`
zGzl{irugP{;Xpd$rQ!n`;<;xHjyorg<&1lV9F}3pM-FP<{hr^=h>mLr<w($HzHnzy
zYV0uP5eG029N4`3GlM=NIa?9Un9$~d!<r$b3OO*tllL6%UIXtyb)qAR2<2GN=9$Bt
zaTtai;uv#?c;#y#a+r1^Bkxd-PZ}K5ICE6nFr$-9IW+OcF9FWbXCf>(*p4|G9H?;S
zxO`BflZ-hy@y_kPb70>%h~|7pJQ1MJV8S0EeWG}GIEG=&GsZnpu+P|(*GFE=?>o&~
zaf4DJ40y$A@Qn?91LyYw*ZRU<d^UbviU~IKqQbvP#t%TXRVN1K6Wz=E0#_3bY^~P~
z%2C`yfZ!bj`rjgI48PFz(G~sr2^#1h177P6xFQ??|IV&i4XCf&{vTRP9K-@KkAH58
z9diGBHsU`U0{>4&{9nBQZ%6}`)#q2vv)N-=GJ2XoAP^`-ViUp<uwqaXNnosy08j;i
zQNqlSMH8~zOoEP8UG3_&+e59|vQ;faQj#K}Y9sZlB`fRd+Re31BlK6W;~(z3*)$U&
zpikccZ|A$t*F5K2-mBi%hevvR|EP#KmQ#<5b{}1~-jP37SK#n_8N=)kvv_@@)9nE8
z+U?VWtyZV-@Vlp_RiE@pcW=r+m@m5Ud&L9Zy<fb2@`SJ6ox%Ng2l(gfzj?k2fc-Ou
z;UD5<{MMz5-?`}RkHuwnOK9W0-WhjmO6BP759sLKACL63Mzm31Lc;T(?v<go%>Zu6
z{@0~O-;tB@-jyl!%<q`={L|bixo0xpmFZJ&=6YN?{&lnc_W=5L^^Gr{pUq=*p0A>G
zsyEWw{%f$?y^Jqy`2HfBzN-4Y%r9^H+2cPg<M=#Z;<(>kNq)oA{)hb8UuAIK)5G>x
zcls`y{?GS&Ef2V&_wF~Jb#qVnWIxKE*DF)rdjIjL!|=}o!2jLX*LVK}{+-y@w<efh
zQ7Hd1hkv?E{oR>f{(wFuQg^dKTVLPHGaf-|NDq;*<rom9-PB_gC0@Ou_aGIQMpJ)0
zMGy}I4u^S|Soo3s`-=(YYr-M^IGbrm8c_mxAn^mM6vTI5Q_TDk1v8oW_vD~~+!)n~
zqg0E)1@2+ugA_oaRIMTej@dLQo$mCChY7J?sifY>H#I})vXt61NqmZjNmKBo499K?
z5sH^7ye_dg<q#zv=Oz(~rVytX$p^BUVEl9enrW3f^(&Ne8HI^A+%EN~he?=_+4&qU
z^CWSjOyy)@N2zw*S|&4D_;pH0Ic~o2^B7dw%DF=L)bc2@Y-Yajw@IMdrHp2VF#IG@
zZH~#*A<ibnvz{iAw5(>DaQxI{S<YeNiQeW6eP$C;c$Z0OpWO3=B_8KaiYn(*Nlqbs
zf1jH1r~&;FK`bXy0+}ysb`x26UMhi#=-kR5%?~R@jcPf56Df{xKT6w=kE}kTG7(-R
z=F%N%>l2&$n&juQ9OJ3ZvYc@d88ur9ln9mfx8g;Cl*x?#dylf7_X7!M&z4flsmznd
z;n~^136`>)Fb8RG>x#L(D%|iH{^kBP{arlhwv>5zG2`<DU3?q3cjKExAZ5e)(+j!Y
zQG6@9`gqZx!c$9TC64qOd*z%}UvNt7Z#MtoEP;0{e`AhqwLY>AHU&Ib5iAh#v~dO+
z3@fPgt2ZqaoSek_4M?D6#?L4aomTddq>PNFB8;U=^Q;vR(O~{ldr0<l_QUq=3nf3H
zR(>^m^wjUnMF)$zenPak8gndrcsmGo@U^$C;uG@^>^ULl_Z}5|m`Qtu?O15_d`ydo
z)vzMlU$%x>OZ=v!og51YaZh+)F2hi&S&9D)tfJOHi@#TC1I5Vn0y$;j!-5(y6Py(v
zn8?&w-;A($_%WbXTHEX3MA9tGwSQrK(N2FQ7OWi!sN2XgR2AK%Q|7Ar5-1@9A?uZ*
zJhg+)4=!YiVvZ~zz_F&PAEDaV#lNL)Sz1ChP$1bYbAlEvr>KIbCB>v*57pLcDC#C~
zUSR>-vJp8{pJ$R?V;j~;*tkM3N6g?Dh$?O3hu8lxy)0gx%&U^D%<Ft+l<*7epVgCg
z)$YNyPBFo_%38(<SU{q7Qz=7*4x5&b12v8^(sIPI6$ca8!iCO9g<wQ|s&|!c`Q3%~
zx@Vfmj|5v%Z`vmeeQb^XqH(lJd$1~V1a5%36wMerxos_Jkn1#OD-#YgkaWo=t|GzP
zf((uOXQ9_K_YG?{BaFg+>b*<{sNQ1g4`LhQTqbyH=+>t8S7U&&sth{XvzsFb?Pb9A
zT|BX3DZ7yEFH|!tG}jwi+UTJ{1sViNbWmacrtF}=G%-~Lh_Xsr7=%AV9jOaCwpH<;
z&BQN}u`Ps`TiBb#h}bL2S4Y)WQ=w%#At_-OVY}05iV#10=}UibB65NH^{b`P0qrW}
zvzV8<D*vGMB>3SB(E|$wbWb~y?aiOJzT)V{CpCuMjSDsoMcw0g%U?33w5lWvI2!7B
z_DYFuW>)(9@rH7UG;gD2I>74iSCIs9D#AR03B)YQbfMrCnhZONPyL#cEVdLXGoQRx
zn^7@v)7@)(OL!WG9<+MVXEYSrExxWonxtNFVMg2>)x(1R>!JL>>;^3#TPz->YY^Y4
z9J9^9SGgPNIP2T{(Y9?!JTOpVws1$$FjH*k;;$t+g7eH>__F<U%qLFDbqps`+`)gt
zDEC5E5>B(7Qj6W?enMqe4HshCLWN@&szehFs9PLu2QqgnF`sS+%yJajHY^V)lu``c
zyyt6%-0BU8=qc}V%TeHQSc5b!EimplKP9InPe07W(uyTszF4<LIe;GIq`S=gMm;O%
z>f|=<vTUk0gK1;k5UQ_kh@{~y{9agWQnLbj5oHWpl`_=(8|DZnRyNgzk#xTPiCHwU
z$n07wN95M!Z6sH3yK}^%iE4J`L%QmG9b@f&dB{l@pt^07@3@7xqV_urG0yHhdSiJM
z!m5>n{YKUo(}1LkJejkD$zQ>X+c0$>5F{EDDm$>uusYcP3&(z2W*`EIRm(M8^*4u5
z<C1&Ohhr2O<mz+AmSlf=rSjR*G1Qjds)ZV!^>cD~3Bkx%pALhYUeRaR%i1f_ZqX+b
z&CM%vhpi@EU6rEkdVRuZFUGfta&L$agIkw`NRmI3Eq6mS6KDDxvw^5io}*vP+Zkpo
zYN@vbR^(6drx3H2bC>zD<tZ1574SO7NPzEBfK9oVafi8=u(S{LSuK3KI2N#TaMmw)
zDZ4>3YITcR$QDsx2+%;WXtyPAw7;>tjpwW%Ab|7D5j0pV?F1alsns+c;y*^Xn+<`H
zXd^>lZ1AaIXGHejZKQjNS1seu5v_A(<W`fgPQ+%Y^>S;rtO4wkvl<;K0_NgG-_KRQ
z(f%gth3CmM9iw%wrog6cleKF<nS1S|aMN@u-v;qV8!LAu-&4$XGm2w-0&5s7@<TX2
z0!#N*uZWeFFmg9S=OIUi5SMKmPxb<MC$0nHKxw?9ciB$(q;J#VqQB+tvH-r)egyCY
z&#lLT?}eoBlkqek(0@@eLy+yDQ)E}Jw|T7o(0FRFF`?dE>7jKs!bc@u!%<EXud~3o
zTmw;GyYrh(kxApFj-&iBD+@;I?yq`o44@s_RM7T@nMS^E*IJ^~ZZS?L-2rg4sioPZ
zk~a`H980>9kL)?$Mbu)ka3WDRyjFu1I@A<UZsS?ea9~f`77#SZ$u6#Gbgm_puiHLQ
zyfDgckMmM5duX46QP1=Kv;?uWREAv*$_T<dHV-D#ZjiZG%NdgEE!l6XAX@<1+eehn
zXs1@<Y2PDx*||Z{LlXANGt$aWFs1WSaVH*WJmpfIu6NxX(9#(WUlU!UPf=LFZdB?E
zX!{-phD4xjo*l`MVNgd@rK{1<9UDpcQ}Y>VSN}>18YL_4W5f?*&y2*c${xamG(<>&
z!A9}7ku4PW;|tx7Lk-2oG92bl)6=|{(yi8;6jOaX%A9;=nrZo<sA~YMJqJ_JX+0yO
z6WwcpCyP?U(`9*UTQIP(r1jGFGyvM3VA|NydZ~Mw0Pox#YaOde{9{PzZ;E<tK-kx0
z694pUS`XxCLVL?o+ZPyRE8s(2`kU;IpmS|%kJeNDJCH@2+5w6C`IT4toAgI)tv2;X
z1EBAT|K6^~XONZP5)2l5Ah4n~YvHY}jWMOAs?F~G004f5PxGk&;9pocc2o|qMYG_(
zNoamz+zRj|${(aA;pSQ-Uqj+tATqhA6+D3YyTB6VljdL8@T=qK3lw`W{?TrVu5J)-
zFlqOx#JOAegVzJIgnmV-Tf$plx|m)_uO1|^$AXZhk87unI>v)NRM_f}0VcbCg(h-i
zclnu!x9&{W0MnjWO25p+1AuXA`VmyK!`!%p(<NL710L#(+M8x6VIP)JhUXA(i@_Og
ziqYv?5(?V{V!EG1#)V(Rfw1ITTjpP<-Y00;8F8D&0Ig*P#}<|)j<>x1A?s|7F^qEU
zU>sr*GtzGG*VsbRn64f=NDJt9$15xQs3gn$PNPr?Mux}W?(x%K8KX!=@d5amX;bz*
zTN|igBE*|zxfgI)f0jH)InJnO{QYvM-~^cpc6s^jAG$Gb3;D_Xz@>&5Z>;4|5Me!Z
zBf-RM(022hP#>_tIKs!pv&*r<0!4eoFbjl^O93DqToYh9wZG{tZ;XK)6S3J=`ZjR%
zrU;v}9Q0dRTF@-K-zW?s;o34(MKj>OPj!z?Qv~fdM8PJ#$EJSB8DqJszFnayR!Njw
zQqN@EV40#layWvpv7<SX0OdQPFqVp+;p~)ciYbnzOj8VuFu*D1jb|;>5-S}ltCX+%
zxWwj|&Zt}S&0!p7GOKdtyQQ|RNQfajHV#KLVd(V|pd5$ysWicArZH~&nq#S=Dc-EO
zKqSG5kqN&Qu8X;LHn0j6XNbk#zee#+%-hl~3x4f-7AEU>4ZiC&E%JqH^FD^-or`B~
z8Ih06EW??ABwSut(YnI)aJG73lL-cOv$0gv?)8qRyOi{HY1B1<r{wB`{+z&zijTF}
zJ3@}R@|BF$_=BObv%5VX`NdRrkZJeYkli+KbqQi%W?{r{?+y%+eG{2Er}>GKPx+10
z%P67uAv-Z5S{5BvlO|BX**4afRy#^lWJ^1!Vb(QD%}j`~WE~yLY5HCqCx)li!UWRn
zTYp!6z2o$u(?&n4v49y%NiLw+OS&jUWJ-PO59XEkJK%f8SL<Zv>NaY#d<FHBGxS)^
zqattYY5j(I^|klsN)`Wnr0nh$vNvhnw|i0E$unWs@cGX)-!*T8J#N%zKg;@-IrwMG
zZx<g49d)N8WQmS?)z6uSzWb~TW0+#iSg$C(`<tIqb3G;MOJ#JW<mi`Vu-vEZkyRQr
z!g`9}hgd1~Z&GWbgXUamzjHUgDreV@Qc>dCzr6vNRdDSaw^t2Co4!pB`dwn>4jU>w
z`%1nX3!PC>>S}|~sI@gqX@sze0sLqZ@m}L-rF;+)xuCMx=gGjTS=R_J>JJL+eHQe@
zNPCnT&(db}dQDb_t38~n(oe~eU0Eihu5J3px|6%S;`1jsYvVPjm$};9=6<tPT^rD+
z2Bxc}fwCjfMKRx8<Tpkg`0TmhQQ^|Ot*~K6FN8d5toN;M*V9(n!UqxsoA@_(Se{_(
zjr7FmY>ctzo{G6b*Kp^0Xw}&Ztrq#(H^;4ch_LI8rT)1W8~qLV$gTZFi^SztpTgNb
z32t<w*52D**{}y|Y@aq=HUS0;pWxdzvL!U)rSUa-NAWAh&%lLY0$~r4*ns1=3S70u
zxZ6{S4&2EQ@p+JEBK*k+rkm}{G1sM-aAsA&-xtittE0@&XY=2J+R1JO6fO!VWC|!$
zQ9{2(4Nq;P)rjC34%~tXd#zsRvU&Y4a#UTV&*t4*>e(tK)V3XtRApMFQhTU$(>C)u
zoEKVXR@?Pld-}qYtivtg^k&zUe9tI%JuiG)eYN6O82peJ8x%*l$-ausf+(e&Q>!~K
zc5dL#c_4CgNf=kV#aw&IdfS(UVOJgTn$hX=dU4hY`-t__Tw9yt-%JgLda=L9#`MZE
z7~)Xj>Y=Zp+dP!6SJI!~v<OO-<G@T-={0*)c2a+-XFBD9n6P5XIu?k!9{a2dc$({s
zfD}eYyNfJF%_Lz*$O&11oD51jn!ays0vC?;c16XYUz%nfx2AvRX>cSKZAL9DCAn#J
za4dl4J1QtX?=qA)fq2Wn(qv8ktoA2K^l!{pfDj|o^~ry`EAi`%lWA3mK;ssL_C}z+
z2&qD(qgb>l%RRGJW|6DrysFk~CX1BaygFL_T(jZaBR#o`WLrrnV%psSJ_5qc0&=_d
zrd#e}3=ZVp{X@I)(KSll5)X_!Q*=#m)c)Cmx8c9>kTTo%PtL3wI=^~r#KKi?Y&9TW
z0OyC>MJ|^?ejdA*J$K#QoM}+?Nj3p5g8N%R^K#|79pX?5{)EIly~;`7c_5qDTH<Tt
z);##p<Bw-NyyzJg|LlxanABVcTf1njUoU5zurT3r0pXrm_qP-ieFBXm%itlzo;NN_
zecq1g9L29~K=x6m5YEegXqke2ZKYccs>MKyowc-GEXt{YG%ajI0i7z`*yJxEHFZ|X
zJED#w`8O|<euLczSS6bnXzbDJ6!FF_9PX9HSipz`Ckhw?qJRIDE5U^&_Rdcvg-33>
z`I_ToyF#4ErPq%7{6<IM3ehXtLt3UjE?oS8ghY(=oA|Yk?e;G3@tvdQk36sa)Ta9l
z{de{IFLtl-&v))FDHfAd|E_>9!q|1m>-{&n)p$|v!xim@kj_xHBwpkAm$u;>sg?kp
zme`Nrq?6Z@|Ap_;&m!QLZv@`J&|RTCnqRmr5%K)0tQ{e(sq7_5b2bmS?9}uviTzGV
z56+iL*A&;}rhu??o6;?Smc@b@_O^hK)YMa$%hCe<r0~}H`If0BxCSY|Iy$VlX8mzm
z3a@x@hh@kV8T-PykdH<Wzcmml#|*!%mJKJgo5Gwr7QByfOR7Z`yX(B*#^v4&t2&`k
zm&J}*jB8XlMh<IFGTg3AsMG<YAoRthg-y^pmt_&$Wno|HRgFsT*4e%=$#%aBMTKl*
zdh!X!S4v+25%Z-fPmcIOFEo@VSWJ;PwirmZgq0;Th$VNfNDFFNawQB8QDE!BMoU_K
zfy*mku8{nk$DljFPhLOVfgW^MI^dmXQx?5hGTjkR*Dl%$e54T@g|8@nvNk9ZT2?yW
z0A;Im{@fYD0cYe5>;~8!xe%jU(P=ULoGWT(hh?XP_s#soyRTp)e}M=&6RH}kBcM1V
zBQ&-HsRu$z0r-+`N6r*l#ZK~<1G?<4&`By4;f7Q=eYg=$V`$uUN%3U?v@+Y`;;Z7V
zT9rng`wSYFTlP?zdKdfR%BMxjd~a}=Ab_tOs>cCZ)$Q7|IaqGRjo7|xp0_ePuGuxf
z_tq}UP(cdebIF`~R_E5)wontBF_95Lf?2lNzrF}cMp=|CJ?zjIm&^l1%Py$GF6?Am
zNYw?Kwvc<F9i;d+2<R@Xp$|H6J9zPRY4wSBQ{eUB?(Y-B-vP8)qjeYBSVQ#gKzfOz
z3*tGU3#)FEs*Vb7Lb^*ccyr^*ohJ-$&fhq4W!3A4IuX_|JCnitAUZr8cDZaJ;Ui!i
z(cAh;sguI8bIhLWgx(CBwg89Z$6q7?5wduT27n1(7YnU_Rw6{QkXld81PdyHdvJD5
zi%vHsvMk($?NuGyRn$9FRdQ7qC7h_5xGKt)X%>IqqG(b_A^BRi#4erFkIh|`Y{_T0
z1c+O2MDn@$tD{fdmw{Qbw*bw@c22xSeFb#<)!ArJw&kJ&>SKJ%>q6wJUQ&<EK6!Rp
zHVczhmc)$lkO=Bs>v%-Tej!U@EqqZgw&xERHIB@<a=8sDv@H2u=PX`0FK?i%i^&Kl
zZtGj|hT8mv*5{VmHnI(6L|K!?o-p@@07*n$Yv{n6Bq-JEBw`|3Tu}FG;2T#T2AgSE
zI4uvF_~6=_;zXT+aG*U>lLrsJ6dp;%O%Fn;Hc?HPx<YRY4$}=LEHkG<+Tvk@EUID1
zZp*4~A306QOjVA=KyslNQ5~GuSLKIln67ab#lK@E)$>i1w+-f8Ll+4-`CF%GVl{hm
zql-F$d~{!Nv)W6d(&#c&HzlT4ljQaRcRz-hpl(v=v_FJi9DMd6wQKXibM=hf=oT2g
z67Nq<vh^c_DJAS_<c7Hj^Oh*-4<-st6!FvV4*N^36NJ063d_VYd`OSnQPeoUkNNP0
z8+@E7)w>>b+mpcR)KrAPniVsYGF97xdG;Mof@EE&a270+@f$8Cow&0unyP0Ja)ZiY
z=Tkjy#~yL=_z&JecNW6M_bo>sGvTp(KmIb5zyX3rs4DDAyM=Xn_sv}r@f~(Ip!>R_
zu~5FV_3p>$peVi~SvoYU%1l3Ia8s_ByDKEQx5qyE8vop%(rFdnKY9-a>$;Q;f%q-}
zcTBJyHm^h+&2F#(j9b@|7yxRv@!}@yc{ip197f{dUOc6wFsrfGG9c}}l-OG#bGIAM
z;`!ha7W<bMm$J2_KfdZYEr<oMYiGcdG)mF$+(cC~lSzUN6jXyYwesDeb9F7>6J%<(
zMXqkevlOQKaJGn#-4+PCPn)d!Z1PX0Z_1v-08OLmwJX?O_f0MI^aOqs_u6hA;$Kx0
ztCDADWQXeoE_q>TZ{Y7uQod=pncuhApz!Cr7TSa=`MnWHpy&n!2HpwLu%dWuNbi3z
z&TW3d7{IQ4`y4Bw6KU*4IQT*jJqkn2Vk4&HhZ26FNc~{Ve90>;x@%gHgV37~u4cSt
z&;BN)iwW-L4085_f<MLNNjY=E`vYLen}6>K5x>8<-<`ca!r1=9is6WhKf`Xcg6qKV
z{z&LUk3R+PL}-5s`Gq2XY`)K!cV_erBJ+)#H*)8UxisQ5c|dGRf=^oP85MI<e1gCy
z7WJ-?Iig&eQ$ESaqigmE!<lC;#XFz2szYj6m-grxr!zvne%gmS_OI0NhS4!aqtP@t
zKJ;(`;CA7V7oAMP;Sk0q8&@V(H@cyzET80owWCm1Tjt1v3+Il|JA&hbqc$<JEA|Bc
z*B6e;JI&;QF7ge_JKoR{)$_~4JF)86z<Gv+WCx)yq|3TVLjOBLSINzGtpwX-ijKMO
z4d>ywEMXb@SVPwZM9W6*uo#T<K|y*xFY2SB{wz<mCkjzMez$b46@hd4meWa=zrW;O
z`!~<LU*6?JC7Z_|9X3$>CubW<+n{}gleX@9yRf^E-{BjXuee4>Bv{d8V-d*Fpl~v}
z0A@TGyl`3)E~J4?e0`+X!(S};Wk4_sbNrv|3M;2E7Ujgy#vHWx)xedhxB(>o_bjSJ
ze$;*jy0b42Gm8u1qL-@tIP|JJPCXg2^7Vd6Cbc4K9`dzH<hcn?xz(D^rs$c?$d!(7
zZh8G9d)ldPz;$7CU)?J7v+Ls6QY@u<S!t~c<JT0aXS&;xDS@9Sxo)BC<N}N4bI{qc
zOI`7XMoVW;hTJh}OGNr26kn*?1C-UVa%H4^IUC>b+5xaR*JOe#YS0&*H<kLR>xDFT
zo=182J^9v2P;S{F(=b{3Sh^WGi}Z4&`;pC>?53Q$S{KX7dl*^$`gn|N*<x1L%l2pr
zpLnOK=ibPQ+-*Vh6rgS?Nii|BX5zvdp7qpxM{>7`Fypgbjt-k?_ggV#GUn0>H^l-|
z$@1q-r!*^O)LUm+@=uw1_r+FB&INb6nd5j~_P<4(F))-bmRN4RWbf@F%Gc@0N9nZn
z%;>*ju^U10j#cN$lCMxpem%=z$WzNuioD~LLD>ag_{UmtKpBn@M7Tj1(S|g{X?gPM
zPMj^E`q1ePpDmiT*q_ud%fB&srO}t2y&-vJ(wF{u2bc`$hAU2A=U5{kT_h8#p#$Q>
zJvej1uz&f5<a$}-0qm42?f_62d|Rcd3P8W|*xy+y0uyJJY;by@I8^qJCLT#uGkn4(
z{W7F)={gD%^Oun@XqN61iI)ME^?rC)=K-FKVemm*eI1c@LwqM@Vp?9&#>8Uo+afH!
zTqvU$d4Klv-3n}3T~5}xR0ESbpfL7!MX;y3F4#mJy|-sPEO5fpUHb2i+073*;pbT&
zaLkeO%<p@G>&!OXx{6z}Z&9ioQZ2|%Cc6uQw>{lCMWmz`4(wds>H=nX1Kv=a=n3|u
z1!O|Ee^2~%jPNN*fD`DePrwHPv<cw>9SeqjAta!q0uTuJl_rJ*Y^WWdl(5-~4iE!(
zZI$>AVR4<jwbI2GPZ)8%J*)oqxcE14Uchq&k~FHsDX%xdLT{@6HegpSt%m8qLtnDU
zYa3BgOKNYePet8SQ#;hqlw4AK>KSTGQkMecH6Y&0DR?SX@|Y@Ll-a(yQn%g|q@7Gl
z6_0I6;bgn1X7Ck!F&f*yAwRvI*PU6GX<v}h@`5P1^?6d8VxyXgCn4&;xOufLVdp!U
z#?g<T-IU>8-<Q5Gqvk&4Bwu{FfSkP3l<4qdGkw!B>Ea$UQ8_(2+pF5l0b93E%iaER
z+7^v0`rFAxQE;=qtb+6kA#*wBVtoJaF5Ol1&rbzX|75P6J>-Ro?WB8IjZttl^-hj6
zPrsrkX-R&8o?7;<bhm1}prhSM7>=F9qgd?zWg72Pn0&O8O40IbYH=GS(#}f{0`S4A
z+`}t(07f8RG^<KF?X9?ak!XVC!TJ914X2cIbz#x>tGgAuGRwY<`dzInkbS||2irIQ
zu7uVHop<haVg60;gLF^cUm)%qoL}JXA@~XZ8}a5KT+;(tsYl$C!ySOJ8^o)`j?_P%
zn8OoEa!jc=u!U&g2Sfh~^ZCx%2T{3w@?}lpM-Q0&LfV_7fBgHU?H8ecK>nus^o9GA
zqAz@b>X-X7;eWuM@YFlW{Z9Lxuy?BarSAB+H!^)U;ozq}cF&*i^;g*pAXj<tYJ&Hp
zEqC}cMfuhD_6|bggFof<Em3zCe}eWca(g&`?DwsMcT8`Be3xeTt>ku(_nw*1LqJ3y
zt?fsy2?)yoq<NT>dz^qwGK$a)r|1|bz_0;KBNVBGV~I)UGpL4RR4w2qAc{rBFby${
zM~(@Mb8&2RXpUm+B?29bag4U<j$+A67Cf}bFt|(BJp`q0Jns3J%CRjt*f$|}7bTKF
zwn6jz5~p%73YUbW+QA#FEjWK4eCj5w5{*!ZKy!u)MWE3hqw<4wpgs_YuPp<M)agp7
z)Rz|{^nXW+xRMd6U=vBS$rN$FS>q7K$CS!OSp0|xwI=Tha_z!l;S;s$TQ9GR)&n*u
zI!9&aAGt~zH35vFwsj3+5inStFrLAE#^QA8h{dBlc#R7S_lDzSP10vviO{8wEKVB_
zRV0kieEgiz&<xPwYkvf%$D%DxqsZ%#;rB!(9_hY<tX|I1cH?X&Ug&^hp0^KTc)eIw
zk!iG6N!Y9_{+fSvT+dr>r>j^1M&0ra9~wBml&5xulUZ_Q;`&GYj`k!)x-Cg0bh@J9
z#H`oSS%#0NakiTqlsa?Dc|4im##UYls#%g^qij=<Q;$~CeZ@9juIYYqs=Uq2)$dc~
zOv;>iUlz`zeJTt7SVqc7a-+oOr#*3C{ss4Ejx%$@iM7T^eI8?Cg^i}p^XB-?uKsJh
z{q6ECa=L^A?qC<gtjsWh100@(-El<Uv>hQ9Q;gnqX&U>m@2?^jm;n0UQ$?naym$E0
z&^DwFNhfp0mM5+3m-d6<r};ZuU#I2jC!|FLc=<p*T;6H%`6)pkHMKUCCFrpPO}<RQ
zcC7bipP%3VU4G!+8X=_w3<T5y`oDL|{!e=2|Ap-2jjT+KT_o+C9sUjWPGW}t@%8+_
zG3QzpTlr-L6u(=xHCwdI2o40)(w?g7f+UO-i7_-RwgKD2-+a28*{vGh>2<>IqJC<~
z#xV!K?~7y3(3&YB85NUWIL|D-=bXLfJ715-+l_&wJ(7kw>`W3zMbdh*qjr}Zv=b%4
z+)=hy8A=Vq4oVk2&P3a^k8Fj*XoK53Z=i-x;!<pfpW#9m5etdaU^@K?t|y?mY?+u?
z+Kla<JtD=6NQa5TM)F1zJk37!_C>2<COhAC!&D@>f($Dz!HlXu-Sk6b`|g&L52{)^
z`=^EFAN1jo4|#`0o&)fmmd^yIx07P)Zq#@VxK9{T4xok&h!0<|t9arH{Y@rVP1svR
zN0m9t*elAq8cfe~DBFfm@laL0s48*R`>s6%tI3Gexv<PwXRbQJKe^}x|2zPR;*#Mp
z#pLTJ#)&>}Bn636Fx4ysWtBr)b+N^F&})|oul=hpj1hrgxKKlgXaGFRiMe3j`(7+D
zhL`=*7Va|&0p1?lPRgy@Jhq*lWhbZawDV6pPlT`CRok<j@4c6!5DLx9v1Wf&D<>Nq
z9XVOGaOwB`c#2q>H*&jFo3qyJGRIo2SS4sRwYLmCzV(ydB{yR^H*;z96&_1?Oc)}j
zO~NB`2_*3p-l5#ScwaFi<u9fD1gTp8{;HhKD2s%9suW|{DaS0*lHn&3^&;+w`-Q>~
zirLhBX+qE)!&;LpOC;}gq2Y?E4uMWlCE$jk4r%Va>oiaO+Jo37p6FS7fMw+mY>HRf
z4ymNRp@c!46Gx1!g4*a4HkZ#y(}VE|`QJC}E;yO)`aiu)(?2^Fj{k2|=>OQT{|i5=
zRl8Hh7RB&OE9oTWr4W<yFXJt+5-Lz{T-_8&5wbJ}DJ@ZJJPIdm52+sCncV@a{E5o{
zf_E5$H0D<RoW=Yh8-Li5l^~3i!_0>7zU%({_SiMw+nLVy=l6#+K$Bm>7<GkZck#&?
z1L9kBV2(wmfIHMpkvn9bv3%o+74#`I)|+cTX(%vOoO5TPDP;`mcIqfEtT~VlQ<;3o
z@rW~IQumy4?^un%{ZqxEsB^vc7>}6*-A9Wdr-~zA!_vks@)lv=(UMg8#(K+lT1fo-
zV#KuTL=<*~%3q_+v)@W<XuIk$quXz{!J_?&=FvlD<!8aa?m=bcxDgGU_0=%JfHZ1Y
zj7HBn)T;j0Rv<yVlYv2p({vdn2xlyA$O{cupnDOeVs%0Hda1?=hg+|gQ+y8ZJp-3M
zWV;7nLu)RskqBYSX#EZq=o~O`Stm7yQ^VyNKOUQ4aP8K-i$1RXn=qb98Qt-j)jiq;
z2ZqO;!hgEnW5y=j2<@?Vv4Ywrm1@~uelNw(+9>(p=h$>Xr2s$#Ld^`LYOMF^m-+i<
zncuzTMFNc<U(&9U`9mS$?uPr6dD{nMS*bqK=AT;BK7_ULSb`({`x#3ob<U)hB1mCj
z7O^dG8N)ck1Gn|Mt7vZLy<vA9P0z=?oh)emfj5j&Gad7u0;%o7!|Xa+rK7TfkzLq-
z>nl*a?2p5aBjyXA@N-9w^ZaSy&S4YuXX=T0lrC3HoJk6=d<b-12nuF}!Nveo6BZtZ
z#wgQp=Iu-Wj)RVN2-2Q#*s`g8cz4`R-Qa^wqctC6Ls%6K-eRYZ`98IRzkJ_dvGKmO
zkFf#n9@7loPoh!B588XtrBiRazTPTJ?&gvpKe?0V<#`HGfL_Nz@r~FYY9~LGsTdw*
z9*7X}k@+X+o#qv??2kvIx-b1Luj}?S3^C{4Fq1@rnWiGAJ$3@o?#DXmdV#t#JHwnl
z^Wubl(4?lF3uE^%7D2BdGutYLUig=2CJyQ1FDzhW2}7ha2_|hbj(BLQn6T)HAj%6Q
zNsta1Kn5V`-x+3~vqmO?S0M3(vd@cUdU*y)BKc@_01wkUFyKYj7=OI`M4e+n#G3vW
zl6a$1zwj@3?t!_CR5Ch-&Yn1za}y--)`)^xMhKZ);?Z5G`tiaDw|6eq9J1Fw$W+oW
z15}7zRtx6#D68tS3blWEnQD*xr;H@$G2{b=U7~8>q3m*1+{nE?$248?EKFS+B~2n(
z^%`ja8IyOFS|)#~(T+l=*35aX4i`;o_2>-i)O}%+*+b%Hf9YJnqJN^I57ZI<e~%VR
zY5~>5|02a51`rVc|F3BAU&q`33L2vt)*dM8n119N*EV5<0v(+i28Gae9kn6a(1GAX
zv@V^j6Rnn+*K%ygY}{KrkO&knV)W}(wY6(rwW`r*)jBp1pxQNUs6E!TTKN7S=ga+k
z-wzkWedcD(-5Zhw+55&xob8<d+^g^Y?mp%+cYfqY*Mn4y>Z8zz7A4iffkh{#7)HrW
zg@2-~5YR@=P-vXjj4<J-I6#DtYNS)dO>l5Qy&h!*QTZsf;3Yg12)&1koEd`Q@emz#
z#E7HHhz*60i~Q|?mxmA~_jyY>&sSi8l#e>eN3!<U8Z-BKs|m7d^kHRU%2Q*&o~L-j
z$xD663HlFHgFJNxbbXXubQ2%RL0}(E6n#Wu{nQ6mF#YjpranRxa+4mCqiiGsL0cKJ
zXBT0iX_Kdz5WvJ5EK(J*85iChi57Z$II$T|UAejhgh;DJHs02Hfu{R~A~WvR=2D$_
z?U)JK=#-4Imrsc<cSR^SEivM5h3O`nH6@f98|FianQNIVr1&=T<@IPw$^xF<vQb$k
zR6FMHX9qF)@u$s()zqa}lWNS}K`~-%>JLZ}R%z*s2ZtC}4}~MOnj*qv9QbWFey`<P
zC+LiqDzUw)e|-Ma8m8p1)+j@Wm7CN(O9rD68<`QwGi@#|t(RB$TGGPJn@H=39Ib7H
zpWA|QE9R3a$9c^kkquF3yU44xf@KnykT59e<kZ_3ElvlkFl1)Pq``7UA=R>cF39OH
z%W%-r)dl26TCMPc&-I`I@tBy=SJjtKzF%{h7VsUCN6k)aDVZ(K5BEAbEBt9InX%>#
z6K!1O`3p&o2dRlMTRD~vvec>n7iI4homseTi&kvgwr$(CZQB*w72CG|*tX4zom5=O
z$=YkTv+r8>wsY5cm=E)5w%NY%jnPLR=<ULjPslB>q0>cKv~=D-ea77*I)1H7kF;S1
zxrG;bPcToB8fD9kI2kjSc35S6>sS*hAY}Li*Vno-VB+x=c$`X2wxC>NHk_Y>c&Eu+
zg#>FCs(8RL(5}1T<M8^8EdVTuvs8bPH?iO?ui^yhHQE1yMTZntw5-XMzA$aVS7`u;
zqdu=!9&Wp94B1$Ksx#&~eP4nrMVn)Wc+|{amW60#-&meE3H0;LRLdUnQ0od(VeTnA
zQ1dkyMsU;~!9ufek{?F6%Z#$`8bP5@*jzqqULk9jiL2mbIIa<jXZ#Zs;u!f-(T?%1
zrYl-E=PWhQbwOjfuxRrKw}woXey7TYJ62TIf-<Ft4ESC31F}v=a~qel*bG=o*tiuu
zTNVQm9qbt5UJ(3o5LlR4ozX;}P@am~8>B3q>RUrNP3;5Ip|X5b8j40@XrUj3O+mC$
zYrsxq$W3SCl##Y)9OMI~i|!B)O<)iWN+v92#!Of3&gDaRppa++#{Wp}h0MR?VD&`~
zDW#5tp;1fzqfPk3qws}qC&lr-9zh=~K=BU$lhP>rf_OlLdX`KgJN%<Q4VwN4X;onL
z0nm>-C5sz{S~moHj-A99wb&7ZU&e2q?(3pr8G^;JRz}kq)u)ZSEE`jR{roCn8^utG
zOl|BfW0AcN*#Wk-1G~rUpuZU`7Y<89eT(26nt!M`=R`?~3(fuQ1aP6@j}aN5-aQkw
z0$lbI30Vfjm1WjE#He#co7E|hXFfFz9EUTuAauV-r7la`MWOBaa$}rCb-$BC;P}XD
zaAV;P^ytVoko<OyftrGY3pFQ$(<keSU%ADZuOOgPc#pQkdPMYwr7WtZLV1*KX=U6}
zmz&`A4iTz(f-%k=RS14q0mt%ga5C+krk^LjP$f1>az-wx<vc1ChV!dTU4lZ+LhbE|
zVQYi;4r1*MNN%fD=kDWb?Dvf%DQYcv0(E!__0mMB6dl#v++$(LA4YyL%&%Y2w-2np
z2;Xs^6lV4^FaU_Kw%f#^7NLDnt@ZHv)u@r8<nZZ#fM|;NjLz$upYi;u?K(NkX~;RC
z&LPOr-ox4j;C6B=kA5n&xBC&%CP&W><3`ee88k}#t{xb&{6e6#5$g^3JLYLHaQ(G>
z&G0IVE6Zk{k1hlB%OvV$!f=v;U!BkhZPTnh`0rcLr?uzWF$dga3$E6Xwy_@532!mW
z(=Rt#v=u=(3Wq`OR#gjRc0-a2X;xzt3&p@k{F5<UpJ&>MW7nb&X5Pe(o4u>1^71EV
z!Q;cupVA1u#;Ef*BjsRahF`cpY`YIK7%d*U?8|jDWAv}j#Fp`UPk=`xKgzK>y9#|P
zJPJ8@ZjpgMp?fU~pMghG_L(bv7(ao@e;KVh)w$kpym#MTX57?q#z!V5Yc51f`FJyV
z&3gG3Z|ufW4dALT6S!@#o}ka?OcdfQ&X~O63?z1JLtbY3WV(CV@~#-tPX5Leix@?m
z!3t^0?X`hC1y9X_vShiFbbKPIR&adeDtzQ^-Gjb92=xk&Jrp-?$!p(<gzWm|lbxg!
zaRkmAQ!@m}{`=mLLx=E(jItxP97T`S3BUal&H4=#X>(lv=L6oj9@qFb*Erv=tx2uu
z{lAERn4k0pUB{TO%@^sjas&#$971Z1SSPa6`h*Ft8~iLP&6;1ePUlLh<4jU~AL^RY
z_eFh5Bc67}zDY&FgxTsKO9-)M1E)eiDjX|>Jh0Y3eNOxgQynqu+b^03!mw*im&;qU
z)Cu5x=^`~W6)8+PqtBDw{tgJoE{sF{VB3(<LhDumy3Kz6>o*tu!txaf!~=`Q+|2{C
z&J2SM@vfHSc-KaP&n&QXxUoo#Ic78)NTW!Y#UecVrhl119;jurNBlxaf;o)#>2QxE
zmW@7ASiZuFULfN3L3n=#91vwO*KEa%I{)gxP%x)L88p$FXg=(xHH#xmDVZV@uAawc
zaC=8GlR1ViqFNq^>HCqS2#_mBkStFH7UuHy`2Bc2b9P0t#H{Kc5fQU8zsjh>NIml;
z7*mNFgUry;Z6VE1zm+P(TXhKwB8wBhfltdF9;HuvOt0q*Z`QFA!@_O>dZfk*nJ$y_
zz=Ut~1k0n-vZ)2yo->OYM{goLq)7lj-+Z(5ey8#Q<*@wz1@o`?h$LH$zW#fg6CLu8
z9~A#5d?fn4(n;0J@xR48OEhd;b=A;5XS%LUkB^sKqg2XTHKmiG5ErZiN$E^CnnlaL
zr<pA)A{NK(n9aD8<?Zupc(u#BQaCiJnnO0iV~C~8=tA$26$MpA5yd_Z89v7l(tsPw
zcllW|rdXA<qP09`{yy=)Uv|!VJgq-(r3rW)aQ*~)sX~xzm&@FQ+cMgd2l2pa-|XW9
zzh-mH3%tQuv)Y3Ix4+w`-C~%gC+PC*3y0=C4TkCTb2N!Zz~?;*4rC(8_FRJ?c#671
z_<L)T$NDbDyB8km2M+(n2qTbmj3m(b(m){4U$pSC)Mw&9H9QOZvDJ6TpB=Z^#Yy^{
z%^Kd#N&H;IKQ)K~9*5<r+`rtyjjg7L6gp9IwiJOUv;Mc?sQmX4Yf2E(*>#+I^S2sq
zsh6poLAW78CwJ!?x4P?N#Hotov;NxlB1KT1`}}n+T2R$`1MkLmEl(+pXR2FWoM=ll
zVaZNU?o8J{*DvB6y(>N&QEL^)T3Z7$M?!~I?+W)s<lUTZY=_dDxZK=p{1d28%av3~
zvP&{t?cF(r&XO}AnF8)iNiDr1oK>xio;3g|+hXCFC+#}HB&jGprQVaGv8a(fYYvue
z6x`^6i29-;ulZ=wS$`?ePF8Be*(S4X3$^Deg)&GG8t|WaxQ0m+xp7VF`U;<Ia2oqI
z_5`_<R0z3q<FPwa+Y9y3jii~9@wG9?ck^EoBM_*CS^kYqI-XEhG(K0FAB`yuMt0_V
zRJGE)-A<gT`{}PLqU>VTInZ&gO{_4e*!;`slA_{X2RPvw)Y;TvDft7^>lt*@jnu%X
zQ!}a)6Q`bZ&NyQ}*exjI<RiYBt=4!1qh(c`t1~;22ySGhepr)*URBpcDJ1i{q@p;k
z8|vidWh^xd6yOI1fDfYuir^d)oh&yRcd3C)<W5UtQT4Gz)WPCmT^IPZX+TM-TjlL0
zKb%3M>WN(Ld>OvaJZiGtJM4VKEa3jmZvS>%+el<VcC~@Rjf%%|k8=`Mi^f#TG}^Ak
zf|-fFRjHS~QJo^pgzjN?H4A@wsOC46)b7Mxw@Yff#R;<wr-_q?76>_D&hEg9SELT5
z;b|j7)H<QlRCqa~u||ldNRh1|x^%eQTeyKY<GTSnH?>6K4?6W7s#ICBI<4BVl)3V8
zg$HF$!>C+Th$FpOSB7S+KS~<0{ec!Q#q`6%hj1oFv6oV2TJdWMYcI1Ciaq-svp&-u
zwLhInFB`s|l{+L;UB(NXzs;Tpx&G*lR8J(wEd+|g0bT7fDwN?t`~sVcF*aWj6;H$b
z`5JCp*p+BzGXHPWRFa~|qo0U2weotYJ;ZFI$I{bGckG{}(|KqgF31&Jp=2C)@Snu}
z-Bpg~Uv#NvGKmU(%&Bfph9%kAd)1A>sd}e%RSxNey6ULH=O#5dO4=RJFxAmIdRh<~
zS~inYFd1y?x(hNkWog!KaaL|xce4~5rhd6c<MysWRxLK94a*C4bkOoM+PtppvO56M
z%Fki|xdV3{eSSA{t$Q}5ouHbH)`&HZL!snd4D&;hur=(kIG}pEHSXLvEPY|%@r|k|
zDP^Gy9Q|SKwm#)R=6$MyGrgGl2;VPc!ot_NZB;&gHRPTUy7mj^>~F1#m#6iCRROe6
zcC0yN?#>SgbmdRw$PcrLXz3#t$~+z7Jc*7HQTviDbz+9nu3}OCyn8S*XP)1ZkzK#;
z8<9JL@9&Ylz<$HX9LY}@P$l+Cb7>RT9T_Q0F`0EnWs>itWN!?F7vL|FV~qF9(O49P
z*JN-AGQ4@#B`Bv7RHH9$2yL(2$~bm5?&IRlk8pE7_p7+br;d@0QH;@*YbQv|xeA5l
z=M&!Ww|4_mi~dGBLOGfZ%L@&lm^T+H%?A=n3EF6kqs_ZsKyv7l<swk#PMdGL7wiIE
zlyvy{7$$jPyWq`zW=oi3kvtMw+z|RmNA5Q%x#_&nn&etTtY<(1NGBbZT>Qb7b_Ye}
z%p?uZ?(#V>5%V!+_3p+sMI6h9TU6iLr>Xw{S140n5q$QFsRrJo)t{%439UR{sIM6g
z34#%>wm))<q{?<50J^-MjBaW-UQ~sd%d0)dO<eMK_~BD`c5#;#K9?Y~Wt55KF(P~M
zt3o9Bsac4DDq*R|OFH$C>x<{n^ryv<>de=bGvP@<8t(9`K)w_>e%c|&SKY*V7QGG(
z|Bjpa;B4RKSO7d*5KRP)b2-{2vHNdEx%#ZN9FZJDga(T6vmiKQlJK8~6b&rlSV4Y6
zJ-G5ny5m($0X#vokt4grJ%8!0^DoMMS!nM;d4<}-I+fIhK(tPXNen@GP0A4fz#~di
zu7s!bKS^Fbh#mSSx1c?ncwk$;hIG8S&7(ohT0MiCVdlNW=CUAq1jYI|z}rY@4C^j~
zOwwD(EpbOMv_G)D!7_yc;G5!&<Ai0*=4cNp4Sy?TSJtEW1@)9mer%<l8>%6#f>y;J
zu!b7O_DDsv1ZqPyu)hlcp7J>NOer5$a0kz9;7vZ8-*B;oxkAd=kdGWkjIv){EmtsM
zNB!G%QQl9vuHhLIw`8Y{$koBoYex|6kLlafIt^j7Ua+hVp>zW=GQR2#sXyR0Z}D3X
z{dA)doN}B^!Ylj#Sd-f;PPZ%34alAIPMmz}vBzyLLvIzRAILAqcP^E*>(q?$SwlWo
zvR<oXIrajOJD1=*1-C;XmhCUqAsQs`21L%aVk$Up>%DP&mU-67KI8tL6L98#hDt0+
zj8(?prIUn+cqeyF-He(0OCm7(*HsQ;X)2h`DS!scep!3#3~|{B!uieo7Oz*F{D#ot
zGYhjP@y-xshRji*8EYZZBhFB-Ya!G#dx+v=LH%C5(lS}Ir=$G3@(gI%iy)?>2Vvd{
zbbGC9!uGow76~<UM}I`vFm}!BBw9~i$jK)hjD<8B4S84rQDYT06W;!OCnmiB%=hIO
zK7u>8;fOja@va)oyH?|&&1fVC3Xa#)S~_tLx}s!jH$L-EoWTi$mu3GTagfzJ;z4+}
z8<KW`pWOY<=N$FHX-QGWdpupB-U@rNstWUFd)|KAeK0SecHs6$CH#BGJpCP=<Rep0
z`h5sLxIi(WkC5&O^B(ACh6`@*m_kHiN1so>H#8ZUSnlI{J{5(fr|pErUBW|f+-Aj&
z4vs!gfV)Y@@wmk?%$eO{VtFPFKTs{*4ib-TqZ>cX4nCyEW4z>Yj-(yZ9KEXbDCsY9
zv4tPvWoMZt{n|sX-Jt`3wmJT>r&@ZW#uQd5*&Qu*_2D{J*Bj}LzOmX2p>K)evM?S~
zx%)R#Y`xgG>+d(%3kLfCS>gFVH6J5m+y91sW(l*>gMx@7y;jC17rh&m9Cewxy0_X$
z(qgcvpfKJ$<T3!Wv#{xr;P~Tyh}(i8soVVHdY-0Uhn@^G{@xvdAG(L615P1MAy7n=
zzbLXttQyzGG^k>>&<~tilrr*=->PR~h++;2x}P>8LTj<z>X(Mq-!`ZQ#LD(cH*Ztr
zgqC4>qZezlc~J(Wd!0H7<&_5<t!&aNeC#mg@Q)V+Dy9IswJ`weOI_zO=`!XsHTm}D
zTExa*>)MfQELOHe&T$8IX^d|I*^Zx^v@SL>1vQ>d8yu<pfpdo_x6p$L0#SJKo?;Q{
z*UVQ&eK$l;+CA~Xsd%l=NaDD6aQ_OP#jGG&qP}ZqgWt6?;r|nOc6BzgcQH3}W^i#e
zay4TRH8VGIvvpPZ$BUw~gS(aK|K1m`qN9K!g!)<97HUR?N=LXOXiul6t|$t60Txt2
zWhpB4Xb0f2#n{|7=OOz9`ifHE_mq+*i4^D~Fyn2iHbg}UM(~-L$#9u@&YARm|NKq!
z)2sSi(nNO@l>B?B)>vCaUP3t|dF&!xNGRi5qBCsW9+QzxcU3ChCVi1{7SV<s6MfQu
zFTJb3rt(`tJFV-Or&Mm^7tnJi4>4m_l8li()hp}mv#t*4By0uRs*717QSPJz3#q!F
z4&!5ro`P-bIT{l0NeZ?W_(adJ%_gtoG8Z$s>9QR&>KB%u+~uvh+^0P88KhRD2s|11
zAWY!u-~1V}K}WB&8zu5P@yx8=Ek)hz1I$$CSCzC~8Sslg;0~f_XFC2g^+SLv_!Id;
zo~pHk!%R!ip!^U!!ygu`Ta1n<FyQt^^L=)-OpoD1Itw)!v+Wk|ZXh0vg+||W{WUh_
zL2lSPIR0KipuZ`m`e#|90Fcd=%M?Y5o{^FZy8JR$SbuWX%v_QAZ>1OurD*Z;=K#D}
zMU^o)?K<x&{rh4^(fVWV+TvKLBWdf+x3PVty*BLHlP*hW9lb7Pj7*6$$}l27-39P8
zwM?!$Q7B6_Wges|+iNFLQrGPypb}E(3=<vEz=Ep&;8MsY3zq=!-!hm*5UJpIMG6|p
z1<%-J0hui0O|HyREDPfqe)aK>C?ct*)U5h_gi?odKq8pra+@KElxwA?ObaM@LldF3
z><6KqIFSQDNes`4)*=`A7j`(?c&9h<&Ip7B#**@dI4Yu!+(THrQ)v67j8P9mKZ)X_
z+fj+oMF<Ed`3p|)yb%l$m2WH_=UxYqL^C6Rn&!%TV2>SN>#t$;;=|-k+6xyx{%sY@
z)=RQ`*0+UseLp<^7nc72Vd83Wa?k^Uu%Ww4pOzX2RIVn1x8TICC37f4?D9I&WwN9A
zGocW-iU%<~O`cF*UIbnNxePxbj<8a()S)BMHI|^GuWA*?WFG2MvN!cn*-K0)G;EGr
z(K~NE%>$g0=B0nb5pZKyMM~6S7mVDrb7WfYj%(qUc4}q<2Y*UJU-T8`Ldd1*P^8G9
zp%RBEHw1t;<Pnn!$R&au{#$B%-lJTe`+d7LzE{w&{YU?-;cVq<<}Bi1?`r1h`p<$v
z%70yGOuog<1psgmYF98}E0~s`5SYkMV5rhS2(-gsgu!dY)M}pT>uO|z4=Hh!6j792
z-#ZDc-gSLTDA6s`lly6p8IR+ssT+aa0O0gtV|cxER!4?#Q1T{5#uABC`%<_m%yc%#
z-9C`89Ys+3XLnIVz(PPn$4Fl;vo5WSfa;b8&sMbP+u_*9#X3T7DwcBV<1^+64Rg76
z*T|Kh(UptDL}rNw?Z8#XGUZ;>DLNLjg6^)G4D7hDQ}~|Q8Dv;))J1g7>2xh*?t@-D
zu^*aMGOWC@<ql-&QV$OElq+ge$3bqjHvFGd=yrnZ$UbkZc4<&my+{!;x7bR>-<sA1
zioA82B(_0Op$|rnxy<gk#EUytNEhLxLnruyDZ;;h_Wn+#skzz)F{-+fTqZ^fPGVMu
zeO*MsbiN30Ek8pp2;>51LEPdp$LAjJI^&2$shwqXJZ}v2GWI7g>O;q|zw{2bQ^6L+
zvMEG|Y}Dc;f18_SbjN3qeLP5t4EHoWU_!^N{^Df=#57pPzb}V<i)eNv9v^Q%|LJ6U
zV~}(DZu;-(*mnM9^wKWBerVKAwj37YTSiBQmq#|Z*RW_q+I<D;@+QfyyU*n+_K;&W
zeb@)t-A(W9rghrpfreoiL=WA)017yxn6%6;#l(`kGRv$XmLkb-a|Km@3mmE<A?+pp
z!zB)<xG9Gv2t_5E50N~!I8|-J7(sM?cCXaJohR0<FO$|o_@_cFDKdD`ZqF6Q7j6}2
zk8DEz^m0KoJVX~ahh)lkDxuDT4fF97+)fUoCsL=mv_l<RSBuW{0B3>X41KI>m>pmn
zO&@J^pR~^&tFjcoAP~l5foLI*%z$z?fi-m4zDYPUw?PTLgl^&+d0BG9@UP))o;6mO
z@jH~QeDguf|B=D}10Vd;=>KW$C2BevC>p4r@|c*C;z1GRHFnF&uozejnl%Lt=mmrr
zLbT{t!-Gc&uwfal%tEhJf5H5Y`x`A+&(Bo|-nIl5`Ir1pKm#oS>diDXCznmLJMWuq
zO(*dI{-0=lW-n5>!&mV1C{nH_$|?q@W)mZ>$ad+n`|#$<>BG9v5A9WHU^vlKob47S
zQa8^ndui;ccD#u7U5uJ2r+IKiK{S&KG}LXB4@R2qe`0xNh8a{zu-=Ul&?I@)fbDad
zDNMAWVeE4|aU___t1HI*5MLWIA&mug3NwF0*c9}Yn4^&#jGSv#Bhi=z+Q?C=8)MOU
zNY%k8wV$1+iMo~HRy4-^Vxn;*W4T4=C#A^ss;pK~Y`9AiyjaX^LCIKm>!8}UzD(P)
zsvP5tX#|-B#*^_UN^oK;RIN>1S_|l8VxvFwnSd$sWw(fF@!B5=BY=r9-&ymj*`?MP
zj5xP5@!uQe3e=I?T(8<I_;GByj@dFY$Qvv(`xcm4XJ1`;+M`RCxX6d&-PlY^VvzTo
zuCDt?156^fcYbTbWGZ(G0AiExh5_#W!}+acps8^oHflYZ1Pgr`H--SczRJagP5aSX
z%^F$c^31uo<>ND1yNbA-0nR4FyKc%c_ih=@V8RW#MnR@kL795&+3lN`xNtLjgK}!M
zbOO9C&MkNH4%z*bt2nzfEnAER&y0frR%@}t-7#KLkL_i>u-cu#e_Dz}H+!)eMG`o!
z>ILz){a}yNo9)k7Khq;8XQ&70TV@5qU$<Mfo`$=c;G5g@T%H6?w>=^T$7&&GTuQ&?
zKb1G|D}n*gl+duf<2V&fZXRxWUcRRp;^>cvP#{GBff>yZZi;n|It=Z6vLcktT31k+
zs2>ts;s~JQ6DwNG%vYa1{th`W1>lX*jm)!5W`vsVG>qZ7Y4_oU3xoOj2Ux=^b`%Y?
zGHU4UC4~($7MW-9fo2!9y{X$D>DnI+8)3$Or~QE`rf0zS>~(-|4p>2VSabuQ$6tR~
zByjHS(N=)Y+#QQNb`!rV@rBz6%&2gS#Eo```dB-9LKr)qav^W>wi^DlDeLf#Q0Em+
zf@2?B%*f;nV}!+&?xcft10rEPNpgSU!WggM@)-YNa2yM+zYZdgaGfu9s2w~wI}flE
zW%J}1ZV5oYKQ(M~Z)8EhmAv6eAeW2}l*x)AdpUI3h`wQvZgVzRV(iVgGlO{An!6c;
zyDHQ(#J~f7z;I7QeE|X?RR-?u?=XVPYjk%KCE#XDVP8@>eY+dZ+fcIEELP$1hQHE{
z=6#Lv!PBE;I){@b>VxeW1tvaxp~UMLTZlWrHdA0xSiOscGItV47fTkI5tU7EEjMdQ
z^O1W9lbR?Try0dROP1`)XPO*Ik5#ZcvfTpxEKSi~5g-|$6Y-043ch3dk_vW$(Aebu
z1p8P2<6UMuVf~$w_<RT5|IGi0*}Gb~dI=l3{C94WqBQxPo1pS7j`YN|t~|r&w%>|@
zM9~a~G9XsbQ*ZB<ns6gim@%V$&}sz12=v7x-;jbKX@DoWIN$J{Y{~vtdU9#f9Y&lw
zsYzwh62lg_5ZXG?1Now%E#rc&k~#6~LR_4B9(ekRgii%AIW8!UO<F<%SWTu|b7vv>
zXxyKH;xhr(r{Nqh3I9izvymF!-ttrx56!BPWN<LNw{tW=<x^dLt;n^yxsd{RxaO+%
zr$_2z$)vLOPF$|{!dB<>)`pa%Q(BDk&0(PhL==Zj3knJtYq29?u#jZx0V(ubOdwnF
zB7{}Yho(GL3a<7ADGADi%x~FqftpmE#LW|DOVanTo_KC-V4p82M9UA~bG;j-F!jAX
z0r)JgKkSNoyD*-<X-a{el_u4(PRRVArRivl)3Ej?BUt7TF}2JM58!v1v8*gsfq6K#
zozYt6{`?_aQ!MBW33BwtR4|lg(EPTwa-Jy;|9WzKJ_{3L->0So@t>ZYvYC<TKTq$U
zkt0X-JMmFM{A{J$Zmo4jx(mWcDC`z&+Y&<rgN9Z$?z{Ehz@Nx8+q|@o{h*PuwD!G)
zcqxiu*$f4@GTuzfaG1$(IG!?le$LD5{V_#MFi2=_f;pgzN|GL*#5HRfI1l{Y3L71h
zib*#N*=^iB)x1ipu36paS!66X%!7sloiDiAKx^fYIp9=WWULYhP-2-%YCgMOW7M-E
z0JIvVpuzs`ji?jm2vu9jvY>$;s0uS{w}B3dJW33jGcO@Udpv=Yxn7lrS@@)dE;V&7
zp`0Qy!m)i1Cwd-oL^Zuf>#UBhq|BB4TTH2Iq(0#t*?he*;2c*{Lm;WN(WpDfS5!P1
zS&Qk^TZragpxsXE(9lMxs;33mT-9dDmTa|w=kZ5opO1}d@enP6*XLf*9b6KKqV^IS
zr_or$C|g2`tzXS99oK+pl(hvDj~DY8&AiJ*eMvQADk9vZ(-XR^S8j?<;vUMH157#Y
zyXGXT=_r$GE!;vL(u%Vk-6{^EN86#_+zAcByR-2cK7i?4OByPRB#A*MLze=)GNSmv
zT)r$=yE#Hg4&@|i{Gph)TZH?489<6cS_SSM#|@&(H#eYayzPqK94=L4QKJ`}4%TVm
zoZ40uO1Aku=I+$L807=<iEb6h`$R}li9`oWlSfUb6H5aS-<07%XP`iDLrh~>5hWtR
zK7S>wxDK$yc=0zg`~PHVT=U2TDPF*UTtPD4){sbV(Uu5tYmU>T{tMD}KBpa-D@>M=
zFG?kyG{RU)dC6KbgSgOrL^2KP?<_vcwBOAWC-sH(riO<x*JBWh;1k}&VS}l8;?^T%
zzxUL8G~aq8nl%NtbrzFtD|3AllWi@7e;NXtsk1?GGR8BuQ{f6S;idDWxp-K4XM{Z-
z;z3YKWZDG@7@aa6d1!~2K^oH2=7ANpbPaBgr>xo2sSYO&0Q%Q^F`^r87x;~+)S&;<
zd+|@k#pr(s0d+eS6$w;-c2Ig!3}Pf-D;u#AOnuVfG;26zTHyj<>w2Yn?X)bi4(#jc
ztu4-bl{b(Le>#>HShv!v6aVYFv+xZI4oJ{N`R3&D>-FuX6R(-c+@tv3fLF9WFHfdN
z!_weE45mk8br~1$mxY08%ne4IQC{=|&7m4j`@=Z=M)cH!dZ*O^4euGNVITDCHWRKe
z`)W;3!+o1T$$U`plfU^1sb*)WYJk%*#ncaB?pZE8@P(@C3c?&UW`V0v`}Rbn2=1OX
zaz;fDg=4?o>=lYLDtP+>?6J8&d^I=THa&fs$(+>rfr@+xUTn%#FuL{!#$>+=q#4fc
z-1h`rtU^~0e+#CV<u_{u!c_Eo<RfPJUzaz!ml*F8bwkB8kgz_9@+Y5JpQbLj6cl#$
zj9h9u!{owNaW}7GQ^$VsM6Xj}nWr2=yiS4IwZwMj;>bhFmhR9?y(?mva<Qb7+)xQ9
zNJo0DszfjUQA68GsUo{3J@J!Bb!K+_<88r$jlM1I(xP-oYlGzAB74s!&j%)6jc@VY
zNOz&!eeP+em82gC1*cn=;N>DAVR01zRw9Lo2N<n5mi~)(p(;YE0;i1b^(LF2av2N<
z<TLZ2nf4C^WnS8*-@9vhhH>}=^T<j+EnCDR7v7m%om19jv0$z}M#4@6vkR#!)$QU~
z69io*D<XyGnfEoXY%Jr?=C~A7bwSaf5m<yBGRlE!z|WF@&kpX`KZ1n2ykLSe>bNxm
z!AUf?3yYc4Ow?fA-;g+p1+Wn@nidBV3mk+awjNxT2#4pkJ%oy4&n+Z%biQ${RaFMl
zVrFaDw84z!t9#p$&N~VBGu40!t`upbgm`46wTrRtT>%r{IWAdg=xlilNsU+=3p%W;
zd(Z6v#Oqq*Y|`#>T*&2<l{|dIF4<I6Ai%{2Q5&;cYK(kmr_V0+!~}6xeM9p=?oo!=
ztPRck*u~5sH=yE0af9l}v|?hyvcfXiLS<UD=y+pO(1j6$Z+Lf8{}Wf@)rbfy(#-Vu
z`L-uRODTJ^5SZYA6!dMXwvXyMdjw1L$$d_NDk#1kyH87+supjCF8fe~L<do1kO6W1
zs1Ym}w{vQqRND!U$v2Lu_Rabna|F_mR89`_3|HKWUT%G7`!$`1ZI21WH<tq2(+h%=
zsW}uq76%X8D{w`wsIos<72?ZOwBaZG=j`b~jUOm-Cnz!~m;D|xIX062%ai-Zd-O(4
zb`$n7*+y!cAzj4&4I@)mtb3rHD<p01rnu~$4y<wn%m@6twd;|mD^8C0d`U@2qW?$%
zf&Sl$3~>%QUADzV%WnbTb9}ts*#PcIS9dTMPr*+FCy031hiFsg5m@~pv-4cT{MtR0
zLpk@=tZFFYO?q?LTAO`d<AE{<eKw`>%)Z7ZW&W@+8tiCo%r?jAfsoMI=G`J5qrBoB
zH}X34C)zvL>bR(aJjB2FISljN*|PTgw+`NiqaYn=u68LEiX(yA>haeJ)0ldRM~r3(
z_J$iTw@|%Ihl9NIEp8tm|LV}5)FG!#zXN^Xw^+e{#smFVdic*sPb%zYW&1y#?U$Vc
zvJm3v*W_ZqS4%|Hp9<|7=*Ruyr+u(uYa5)FwQ|fD1`JN4Ki&yu^N%`bFpHun0zU~R
zIDK?!LXbgrqSrgtGj?Y#WuI1WZUlg;4Yx&spOGU-ip12Tv(aI|(dCBfO%2z7P9xGl
zE0oKHIg;xbMcB5T!w<SjdCvGh=bw*pbe$)WsaY?#>+CC^e)VB0$;}%vwgLufc#`_P
zkG<ly+`Y;U=SIXU$Z*&l9<&!5ve;_dH?7y)wC%_`R=sW{-)m4O*6)5PhCcw6^%?r3
zSH5moMWl|_r&0Os<+Wcq*BPaypz0ST<Y3|@1F^HomOwxDD?qCJ#;auf-c<eoqKv$O
z|I4nta<fU^>OzM843glLb*#B6#HM%e>PvFb62-l4VSXCZl(`rp%V~|@erzM(#;JY4
zXp$TV#cckz{ao7EGb55PSp&PqI)x|?E4kpLc<X#3vx&y_&v;L_SxzAsiUqB%=*B<{
z`g6;eNve@mbuz1EO07pBG8Xz5-YU%ceK>uAD~At?c}sj*w0VCYHV7uaIeFJ5)8IYW
zU-C5*aHBZ<OwdP+BGU>mQo6S$tCA0-X}mx`GP010J}A$hO{6usAf<^xwU4~?p#2Er
zJfc;JIxk_0*OOB1XIZOMmV*+-KK4MuHcJ6tM>1uD10wan{ZS-_EI^m{XZ2%<mq`8i
z@jvyT3^kl$pI9%|1Zd9(2mI>sg0A9z>W$JC*k^AQwr-KyeT&7TTeUF}9CbxS+?ad{
zUh2i+^}l4f*AdLVzZrp-g*c9;c{s(bpjtWI%PTi&Sc)-!{@bX_8?Of!+&7um@g0r-
zGeYklDD~e7J#`%w6bnrM9$ZaHbtO?$1hoX~A8yOqHb_Wt%0>J6xYbWb5{)6t^;y?K
z{rFvHemC5UlTRa6GtDe&;oOUNfPjL<$xo=V8owSnN#J6Y>?!|~XRo|xzdQ$y-oFo%
zbwA|ym4G`LEB3vCkz`x*K{!}t$q*S7N|!CkBek|<5B#>2i#DZve<G+oB!<Pa`6da{
zm@oD7NJ&mroE2MNmoIX`dBK&2dBK4N+U1^UH*(qla(}O}WFP@KsTs;_H1HX0d{)zf
zn}0lCp9N3u`u@!kOxB>*?vWV0)bldH4s<|^t^WOb0;*kF9YpuHj|~ib#SXz7ug!2Q
zX^Jj=Bxs69eq8ex+3FMo*W%b(Nnf7w*hv^9>Lk}wSKmH3yY(nxhgTJ1`vQeUt^;<n
z?IZzmM5(uhRj&Je@myw$tqZSaHp{jZm&TE_&dNBG`gjCa9qq^mSoB@C?jbFOpO!1M
zcy9N8=fcym+-kegMAz9urvrV(&o=K;gCh9^yox_sO1|7H06qE|0Dtf2i;bxiP#fx0
z<wdLN%}5liy{2ysx8;yRc!?yEW%BS`ms-)z(y^^7rCf(&<b=<jc8{0WIES7NIv6(%
zS0k>8@pWy+0|js%sYsD0rFi3}ts*c|l|+6wJrx#rQqQ3?!#QYArMgIfDf{oqt!^eQ
z=&CX!AwnlFDvMNA#9VM0L63?A?C0%^j&N1s^KQ7`>Lh+-bXD14iDKeTZD8)~A*hlY
z{Rcz7T5#CcNt?e=+PPeopi_Fq0i$T33Nh)f61(R5qgkA?e^>6E=iPocD#yfua8k}S
zWhkF>hT!8pD=yWS4~7*L6d$UzbMwATWyJk>cH`|szIi^bBzH7T?pSDu3CHGNyyL>f
zGuV>>I%KP3+qE@9j#{8sRhE^jKK5;CT^YQG<9`g$qU!ZvpRi+F9h#C=RU>t*Kjzi@
zmCJGcQY3G9auGK)h(laoRa%QQqT<2OTHF2LJL<I}!s5%PEPfUHNH>Q&U~cQio1(-x
zt)5~#nu#H`oimSK%z<ATyVquA9iIHO{NQGFbQS_2C`#3u@_}}N``XxEn-|=FEVdQ#
zR?3)tATDP2KJAXB_b2nX+w8!}i7-Y8@FA*?Cs>7idMHTex`95~_NCN}W2?Obujd<B
zchiP`@_Ek{dgPNhT452*Bm6Fg50+BQ`9lLK+ioJ7*wpj&J6uX}^M>lzo|-{E7UXsJ
zDd84{2IZL&80{{tDkz4c!X+Z_pKpFR=0PEGPn1zZTC0)=bVb#w1FH5hadQZR8!^~a
zEDrnxNS;hm>{Z%d?D2*@hlQ|?P*-;b&ZNoDg_{2miogkizUEb6A}o(;r8PKbTW!RA
zNMzsCQ%>AzA=61bfcT`G7>N~sQDwfXY0_9CX$lbs-P2Mry1Rk_`r6i}`_Th2*0}vI
z!L+TKuI{P?Y}R)~1p3feNksZ}&Bj(4BWURjX-$_U0?Imge!4WD4&ZF@5isM`GUJ)Y
zV2rt>ACeLW6vzw?r!B3M(GRsJ9<u~ZrV!>f#y1J*KpFddL2tZp5OOyM>^`4*#i>`?
zj0#q>j7+<uDN_V*VD(Se6&`$l)cUAX3bwu9J*qIv9NL01RLlB>9E@=qbO$<^Q!W64
zavmrqY1W<kgD(tM4YyJ#+YGoi$%2Ni)`<f-Y>@bG?3HjA>2XOtC6aiu84o(TGcL-+
zi^0EwgM%N6U`^k=@yGY`pZVASCph?Tm6ViNCV3DhM6s{Fuuw8&pAb~5{veus!V*C$
z%5sXG{)-edlFi7WWlHCtxYWkP*xKfgCl@jX4sm5SAU`Rlbeie7g`ZR1*C(P8gim*y
z>Kdb#SL?zfpJm&1#Bh}F=DVfw7UvF94VB%)1lHq>#V1oloXr(E*j#7{lBNk3?h}6u
z_~I2Eo%EGR&Kp?tK;h=B+fp>7IDRqM_9~u&`Ja4O{II8%aCFbQmE1N8T+ZtP{;gDY
zOSV-W2=hHmN$}%`$bZD5TiH3<GW;X)Q*d*2baNGVaJKtbTD?XK%JU!HmJY3Hvifb!
ztayM$y6FY0KxoqK1=bdo1y?D`U&4cvQ#Q<Y%q(4Ai(sHi=tyEPc4~s_s8tcdNXe<x
zg!U0IQIxfmQ8?1uU}!a8UJm9-8L~-Igs;xKdNX{J0W*9jJ5Og{d~cXPS(cFzupN_G
zZ>ajMyH<m<?)a^C7^Z;`?E7o5;U_kT5Tcycf*W3bvJ(6{7QwbpzPVc1+V2m)OH|&9
z><oFlR^AHsDS0ig_MZxVzjcC>VD&8o%^UiQ?|DZBhhX{A46ztG?CL8H%BL9>?zl9#
zGl<Pk1B-uW2+vOe>m8!zKoz&&&Khscx!-?s2WEwj5;R)kC7j6+^@}3<jtuG1Z2uE&
z|Bss1yEatrz-q~}D^t&YKgV5-v9Hb`3;xpnld-Qv&u+@GmQ@c0>a5jEPZ$9uDjiIy
z$P;wvTU2Sp@;*zUc>dy}8#wIdX_V_r(8rtYB;=@jX6lVFjcHb_5s&Fjoy~^XC6lic
z&(iNrL(vO#do@bS2vE6DC%J<9b=(_!jvDo%?r0V>xx}CIEz9-7%<{76YdHn!0~5GM
zVSpmN9yhqKZYFz)!|x`BWxKUFX7wE59ewAASVg}~{D=^bFmBOZR~1z9vWrfE%q1@?
z?lWeOHM0;NU%FN_XpbehY%QTMGP;7edZSUg`%_O7$rDPI4<{`EDG6qzsGo65T|X0_
zJ(fEqa_yv0Ub@{Hc}LT>sn}CUkf^@s)T|tE4r(-YHjA_rwD%HoQJ5KbJ7u<71EU5a
zowae+yX~DYDHacObkp?>J0%4sLOMuc>?Rsm-mx)W)XN7B&NJAQ<v^F#U*Ekl-pMEl
zJC?OP(M>d~=Wq{kRO_(Bs|mfEBo_;Q59+BIV7Fa-<>W?2#Mb9|09lcs1uPT7rFjTf
z!!>EdNe=30wYy?}a${(Ct7F|o_<fXr{}~0(U|f4(qC*Bys8{d>(GLeE5F{GPc_aD)
zA6kpkHo8!$^_L`i)MA2<jO$6zqUDII+BUl;9_!}^f5L@ryo2hLv%sk<`cF71=W(>S
z?k!EOBk|Q-RpZJ@<DtfE#KdeTwVA?HvjWqQiNf}zu-j8f2d&>xMDRYDzHkDjd`q_^
zZ~`m0D4}TUx;a&B$Vg)JpU@U3**{d~soq<D@)$m1T_Hv9GBGWhC&j%ECfR8!QGW=Z
zT15`k{On*S#qzO!YHX0SB|5`S{;3SYQf>l=U1Bxw#GlFfp*lKy8x)r(^8nK|c9?&d
z_L4F%WdvUsmo`UT?O$`q@lq4FyZ_9sKSF?t9!q-xnJjSb2}Z&8AvKzJhXEI`e8=&j
zGFs&+H`wd?f%7$g$NgD#7{Dp!a0bm;!N??2s9ZiqZh(sd#WSE%oT&_$P<dSvM5CO-
z<nC_xjGHR~P@{U%_o>UFok^<<bJvc-LBqK4u6?orsFm>N>r~5XO<dX3V@=l1t-CVw
ztC-o8jO5|>$4^%pbmSJ6tp-dRsaKa#&%8>w^nSD8)UaX7_G|g@yk?Mf{1j6sRajnT
z?JBK0vkt2@Uy!kGtvxR90A!XOH)*$LGBj2^5$6h}x<G7z0V)+?&_<pN(w5Y7wZ=6@
zMf8NEcz=i4xa({he>Q8)gyZR{RZ?43x~UCHszv`&FnYxSs8FdQ^cu91k5`E+&U)hD
zrb~QJ+26kMiX1ay@seDJPn1-{kpOZUYF*QxGM~(gvewO!Z^%ICO}e@hhAJxQmpS1%
z$cpwqYO2dnlHT9+grk8|tt1oe>c)Ogq<Ik#?Bf*??iJ64a_M7{&89N`1=ympTWqHJ
z^I#<k4+PjEx1igfnYZq6S0|`;V|EP;;hM|80DLcWWs-#1V;7Qy(s?`zpshw-i0e1m
zn#iodPoFBc;E034K&*H~d}Ix(S(fk~TI%hhFy$K&k5;%)nPr5Qv7Ubeb-pXDn(@)C
zTcJsd{YsxCBGCa@T>u1d%@=N%jhT`M%}5kY?ZH{7*>e{bfD-}cztjJ~IbU0nHDv<A
znQA^6)l5_PBs&U$RlpskN}6mW9@KHP^=ANowi740lOzBJ*S0v^(oKxm+V_1IZcMWV
zya0WDE|>83d{%Asp`=w#8k@sZI-Is<HV0d~2ab20zklRDqj6SEdn6z>4Ni0|TnaDK
zEOmHl#`MP}uH9IV!wLr$l=!T@V#(G%^ONyk3g_RAMTBkq;R}8bsSe-n5akGD)E_Ek
zBw{>9<N%gybkCOWlQ_6InR6Aj%aCl`;USd(>1NcIunQNLBTstff&(5x!+q<4EXI;X
z`83GM%DC*)hO*7Jl3nuRK(K%A+v9OCHjz*K4xY-|1J51o?Y0(lcb8T?l|&9p)xSo}
zd&t6TFR=Dk5@Fl!?DHSdAVSx&5_yXs;nP^()QXpaGhH&Zd8a~SM3MjAt?8a1&H+U_
z%x`!HBxi3G<Q-wXlUZ;Q@^Bp%W>20*m_lB<xb&x}-<sa(6*F>0E95k3n2Hveb5gRI
z5Dxdrm>ldV@RZ#t@eDaP;5n6f3YUwHU|~MCQc_P(LcvarShEWHvr>AIk|5Y{ZN&M0
zI=41f0x-@gJ6}C%bP%9^HYtUaXpZjCrosAGE7b45XI2-t0ZkY0jP>MZt`B8QU!E96
zlhlXSKt7g1P4S#3JVNoN0ng%y?twRxuRZijS%<<nCEA2T7yj(+E0~Z-*bN4LRyp;L
ziW9Qo4m_~KO?@0_Dgc~gN>^3I3kifVQ82peFpRLRsy-X~PBY1J#xd)+dNVSu3&cq+
zWT(dC%N`5ABFQ@N1KqTSJ9*17l=A1Ya|WIraSZNrG(fP};1|Z}r=Jd?p5Tl&gO1TK
z#$7qjteD{QsY(&#NYz`P<)t)Fk`CpFl8B-n3>hH^1yDG(NB-QE?gJ}x8!AFqTMLUG
zXA{M+9VNTGa`H~&ro@-dKOIh43uGteKtR$356;{cJ=#Pf)Js5Jx<nN_wqj(v3|W|)
zFD`g+JH__8Ar=Gj@Of>+(c2Qae9$kQm2P)Vx}D*UTleiym%kXsk}^zYgnpx7w9p}_
zcJX5NW||FbZ53QbU-5*2bh0aGQ{;Zg*$>(%tUN4NY=_f#e>w06PHD+(lk{rASH<J{
zlhh`8TDdL9*4BUcgpSu=(vo?Pz7uYB9diRYVI8e!LHC5-xpQw%qjRwA?R0!dLd-8s
zs($zbexb@^Pk(E)E+&sKOkp33chV{F@OKqc@)g*S7tLQkq6w@PnzNea#~JT86BfS4
z*d5C<0l@mmS*+jV$mZFX$08JjBUp*+0VAIygi|kuk@Up?lCnS$C7FI4g^^OFT!#-8
zSKP_z7e)g?-P|EEnFb>^KxwL%@$fg~$lO=jSU?_=GpRo7wd4%n*_7S{*Bh(br@ZpQ
z@5fFE1|{{FM3uM`6s0y~1Z9U!p(7ya-C*Hb+*0~?Oq?W4a-K3B&r1pfk1Oa}si|#*
zSt@xe`6<2e1fQ(1DpuVZB%mouf#Djl3>$gV+yPKj1kL@RChjLx=_ZFuTw4>1-I2?U
zM;;)1=gzRd9=Ec9^+&MUaj(r>$iJq=8h`extH+B40=eUw%$%v3Cc{L9D^km4aB$sz
z>c*+TGQ8SLk|krs4c6{&b+&ucsZ6-(cIQ?cfODUTQ@~PJ82S;59XSolA$iFYNpgGh
zJcC=NwwuG=8w^*9BF`<(e7R9o8OUmOn>?xu#I!x`W#hsc48w8_zuHeQewfeT9h?Il
z&+4>$)9|?_jNr**^^lvr9Q%jeNMiMnEZ&CEhMkNHIFegy{d5^H4m53TbSZn<<1N$h
z0d@m5)>^;Euim?yz^^_R@-wKxx!7}~m|f6IkMG2T+eT?5ESUyA`E@5O=rPfQlL2#d
zLhwOz_=11^<)Z|ZtK77NRn_(HD^t=*r*2lhH&7&h&y_3w-ywV{`~MB_|H&<p{!fdo
zl<R-XyVj`cxS)!metI)xT$(yFC4dQy8!NJR4uB5X2%~Bc%dktS1u6M9vTR<$PtC-1
z^Xbwm<@r89ybyTyQIn}DlkvYFAv7*6c4u9Zi&|G58NFp+^QYbLoIHNqJ=gUDamKUZ
zpm?%`J9U{I+I1DBdC+xP810N8qSNXwNkpUXwB7bI(ywFohqJG1(CW6<o9>%{kIEbY
zZdbtSV8#_I#TxhT(|zRj*}eFpjN67ysLmrPbeUsJyG?jz6E<&gh%_QmVGZCe+Z}(F
z5Om~88{E|hsurqGm8={;V|we}5n8vqC0(aLYviOqM1z`I_9OVUj5(Haa(=GMg~^gt
zqP*N?5=1Q*w~!sN<zyH&qI>bK9WAWBUmJ<D{be7tWbjc_n$EVyg#ONoI_XXUPrLOg
zM@H{q3AMXXAR>j>BazxsrZN&s_3~Fx@>|MD%16%w9T+!)00GYZ6MYXo!K(4is)Jf%
zNel~tGI_}YcCWrZ%R$IJ)hqJeX}7}jjo+QQ5h(<rqE&NT2%c+>RRze(<PFGw{FCS5
zhP!oWc-eKQrxqLyiupsx56=!R1tsAs)m?Qk6F}b>xt<#9?6y&JiK|k|5O^pe??Kw6
zF*~B3Qtq@=tQ<rmABU3aaNI8Y?DLlI@Q#>H43WcWb)6K4V}h&FO*mZz&nT4<etRQR
z_ma6YxD}g)q0G|P1Y^%IO~LjBM{Py_ky?{K;7mfbp<5Zw*Ys-_S0_>16GGfZa)UD+
z?#Ie*sh@EC^V$s=7Wr4NaP`eK3o|O1AJ)6yJ3n=pFLNuzJLOMMx!k>Fg9C9bo0;n<
zF9M(NAzT4<<S$}Xy|N1bLpZX(^+vQ9p9mhPryhJjVHl?}XGla|>Hc3-vP3e>@g&6r
zWLGRnR7vhuIMu43U=?|mX(Q3iafzVkV}gX?IGpCZv21aNpoYy>DBXepkwzEhmaH36
zt2)Cl^_(k(sPey)C3%V7A&&!h1c}qUr<crU5G|va0R5e?KgDHA-iE(^SU@T6NOlWE
z8a1spf;_VULv0oM2`Xy4;-DljjEgAWvujZYC1GNdMRCiDaffQaHRF2au`9Nyvx-jW
zB{e<b3B57IGz5%AY8}bRbXf1ZF&A51HNF>2+5-kDo_Q|AA(+p9ISw&4KpnydcX7RD
z+FzptJDeWtaKFzG(kH|=MYHUNy8sZ%Vwao|GNU`_n_-UZG9NHWRw;7qV)&V^=C#77
zrk}|t<zeK8B4tFcbvc4$ly}W!;u)VD^Byq#X4dJmT|Izj4&g``_RLT+^?~>YWa_{E
zt=GkR-<)mryND8i@}IVj|8JJy|K&se*+J2w@#=x9hW@F~T`XCq2@1x6h`CgpTnai&
z7>UIMHMa&TC(H;mEbT$2H>bC(t}*)aA|`ILnw$Hb|9TR4^pKR9OCsQz;2vW(X1C^?
zHs_aIQ@YFjThFG)-)p~{p3n1uufM>3_#ZTJI!r4uIh<5WRB-WQ$Mc-nPTJ+82aHVg
zGURbt31}0@*206PxHbvVgCiN}*<$*?py?d<q6C$C{B+S3M5KauW0*@1)?z4FWo<Yq
zgt_2O4%dRR%lW9X%MLuTXDvP1<M2G?2jf{kG>xYB^%n`6nQPPJUUP$TopC2Grn5?t
z)RZ;VsE_Ro3fQi^lf$%FS-2+0GPG9du)&&6wbq?Sn3d%lE)gP4(}Y#puGakH2PWNU
z#Kz2YEe1}18!M#pEw<^EX;YiLneXJVHh!@B&bmsYq+0y)U2KaX(js`=qT;df(z7Fh
zj_tNzQPxar#k0xR#cb;`a^Y2&32V+`dLSvanCuy_eRN@Wxv3Z|(4#zt3uGKS&c8qd
zl~egZj+9009kBaDRz9alP3@|0UI_i%vQj|3|A(jND(^x%kEu+y=yKERuv`l^u`vfq
z!)Ubx3)!;Dj>@(&>`B)Nf2Vu7aC@KKfje1ttSM)_HYFP$+ZMl(0&kJQr<ut~EMw(N
z`PR~?6J2f=SqIvqwRQO{&0@^W*G5}j^fHF0w!Zt=it`{&rI9JEfdVx~k|KIw5<4!c
ziaAbT+6C~=JfJf40ALK*WK$k}D`Qb_SV-7R-AgJAI!TG{NztQj4AV>Jl2Hx52j^I5
z7WNeip{SULncEb7M88NVWLxwoakwdmny%O4_UU`B5uP`I1&q5#LBLG4_aD}zlv@#Y
z?V!i~eg%Yfl8{2pL(M*st?IY+tsqv8Y&U!MHWmfxJZFcUpk2p;7In&tfO?M6`Cwh-
z(@C6<jL}%8t(BSP4If!fPMk~bf#KCyqFC1r&|#cO;R*EPC;BOk%A79UHpXe(R>tK`
z+_QY>jxvP2k@*j|b`R~Kbk<pU>W$Xjg@tjreSr5a-uZk84HCG0Kn1MaVSK2K?%sOf
zef32{<B)9pTBMqA8lgkgrTA$lq&g_z))m?|{J;aPW5dxVe4jK^Agq()mwmo?N58Xp
z$Ioxbar%NtK!w|p<ki$<ogfoLK;vo<DHa+RT@|h`a<}3=n=)Xc<PcoN`!I|vqg+Oz
zWR)<lEU^$B9I9fqaQ{96F$Jtvmm{z!a{{@miV8(Ps%Y&t4&ASwUinuvsX%eIJPKdB
z<#?DoY^W-jk08?!zr-s}*x_RN7Rd%p*1;gda3;4gMtO$*R}4|D6~|>{OU#)gA(3ue
zY@FGmd*~DLS?$<Ubn0(a3=LS#R#1_#%9~Dx{)ZW}jTlqDX$?1w|Haum21y!aYolE@
zx@@z{wz_QFwrzA(mTlX%tIM`++s0S-oH=o3=EryE-pI&|_jkr#?|#-=5B`KVV7x%C
zyS8SXu=k0dX`ZK#qL$0GWyGV+gp_twmB5x6p$*k%gl$_-<vi*(j2t~A$@Dj9BMDj_
zA&hl2Mpljm6^u0~gtYWdV%6tt-D%0{<au4+Bfx(fiSXE2Jv&(tuw-z?$V5Io(fF46
zCi8-vh5Gnc#b`Oi0UWd5gs!z>VyY1=8*iQSuiqC+)E8P>#V&}l)v$Yil+#_JSM7^x
zO9wX+Ydr$O$84q6#@CM2$Ktnir79HbnjXr!S4C<v|6bUFb(<4iQ7c3iAe$Yn_H0o0
z4+Gr`i8`SDn)$?Meoub`CuyxZXztcw-mz)OL2hr647{bcgFuusPz9T}InOPUbKRvq
z4J+>44=Ijc4`-p7*<=V$VGjk9+4Udw;XHxHv4R;u!!dK(#AKg7*26Eng3=mye2kw%
z4P2Mr>^z3TEwilo1-XzZxM#M@RFNjE*p?Z{`e$KB^zJAmSZNIQKHpJ|i8H(rWF%^;
z_7ZrJs$psy%NYpUAf;yzQ!5>15VlIvCoZe+a7NbN`;FS>xy}N)fGJ{c8O1AVZ%`r+
zst9_0Xc_^rRtK;d3}J^T$S!o!hanI)D;h(n>UT^?!s*Ue0Iv%#b^7D7_+g{MoX**B
zetJe0CXDkpE;PSA)if@=p2aiP5KF-<77d?V>6gi8v3&v>Xi4Qhl$@bsOX$m1M%I)L
ze|jI<ZIezn4FfEs2iypz71yeKZqwgz8j!^E_&Dzc6L>BW^>ci$-V)V%V$RS|ug9P9
zgQO|2ah@5SoV{J#Jy){wxB5vQ32}zwXC!#N#4ssVLn4QK-N#SLx6$@+cgc&G<@<lr
zT%vz6B*kVxm>bqQ|DGh^2$-D+`N*clW`;GVPA%JhfOCqpr^!QWT7m4$fGi2d%zfXO
z{DND*(lfR(6oH@IZI+(c`nU9Ty8NxqvTy!D<Tuff^FM;#|4TIdSNcI_g0<ot|2O?W
zRYFh@QAoI-TyDOJfD*C<geYJeG6ZrMmah6@W)RApTwJ*;aq^fxpULM3U&7udDffH>
z6RYhbYx>&Or>$-Lmaoq{Fny4zdBKfba1_)@>g;}DYJ!PGA2BXg5zDw)iZMMr^&0wR
z)Rl%zYOe1d$k(uRI+rn1$OJ>dA<fV&ItC}>3J+l4p^*f`gN<6$Y7qgZcjEv|b9mn(
zcFl9Wao-U`>J@d&a60KUNgIh)+3SM6SG%e82+D(@UEX<&top`4I3<zjsa2aMom4}5
z>mbUNK+93{dNyoN^K-^5gi!gFe5~3kyiVB}W06sQXQgF70b2o1eV3FJrA1U!JP|tm
zJtm_eBKT<TJpfn8)5s~jT}W}I`nR<6R^0?!2byk-3i0V{7J2$+h!KXF)vNqP!3|TS
z=21Rem<SqV%4Y2-{L>jN13XhLK`lbrrIWHWiJ+;#Am(lA<F|EVxbTj9{)?B+ga|dq
zipkdRU8bK8nHC!~(BCNcPyIYps$LE@z#mVGo}QwU&>T<l4zv$;?;<1?r;HQ#=*O4x
zFEMq6yUfRfeb7Fuc^UB3LzzBq5R8hHOe;D|2boV}vemI3$d3&tu|z0$pnd09*=GKx
z<SZ$T6U5_jT;iL=4A9r%A|*R`^bxEc@cX?mV7P6Il=lo5a<c^o!>yUvH;1&U@@pc}
zPPq_&J<X7q&759FElYSw5j`qUO=}=*X#J)1K2G8qmVnA;zYR!zHv8~R@#XfrnuGx7
zj6a>E%PKI-*09JH`wiiY4#6Gm64Mm!PidAWKPTFi4!y$}H*yc(+z@+<VwJ!ivZo&%
z&oQ)3JGLF3rnIZ@YF^u71Xvj{x4J*2Z89P<km9;i>h@ZsEcx8c<6J_|6*Ztf(f@VH
zc99(<RQrAMU%tQ0|6eQMe|BsU(iXr1h(Wrd@iX=Wj)Bx#qs$&)@^(LgN1%T39K26E
zNxD+Gv7qC13yNFV?Qkk9@oethY+NQ&`JslvsspqLzix)~+}6}p+`df8*l3+kv>u#@
z#91fR@VS<}94x#u^^4?Qrp-8G%+;F#Na|b18cN0dw3i&m<Yrw;e!puSqxx1AB5+Vg
zfvRa*MSMRVt>Suj`Q~p0Q|R2r#n5&K-B5A&q(7BtlcTV-I9~pZgp^Sr8D00y6L0?R
z!8!h;zu<p);w1k<I*!w}oufwq=-R5cC-LWCV{gGOi?U5q!vP^lwd?r>9+L^lU&(65
zdyHm`+Q&Xt0|J>tVZPr27P~E!X=08bv0h#dx4c7-XYZU}H^|-aY0gUa?EvV@XS=0f
zPu}%vgTgQf;6!cfhBf3AYa18PfRBc1(7YtpQ#+@1<wquG<SJ$j^XNEu^@}a?fo?db
zL7q*l;*C)L=S>XbC*)Dafd|vd`N25AJT?W#acn+Gq;a<C33clEw}3%ZSFuRt?mm&9
zM&&X-%-I4IEj_)G_*H_D5P7Vrezl((N}X}DpAfe^!)<QjF61uSs1=><d3wiN>ut_(
z--!sp?0CuSY&iy7olFPi@0AQ4hxW=I?Sl(v9nXV|CtF^4y_KhPi2M9+?*4qla^8xU
znkYE`;xGM(?s(taXN~jzK9STvEUx;xg?u-(IG@H^N;NcUJG#ZtU*k91d;UDzQn%Dz
z&S$W@*yKzt{k4p=yduL4<6tcj-x#SdhXKrYXxtoVlQsxlVrPY@LlK%TsaN2qj}El%
z5K?*AwboA`bzr(^7B;ta9MfjR8!gjFwg(CNFYJG<h4%`=ESv8`Fbw;jveEv_#pWMk
z+<!6ln@~|#M3zMP<fIk^^lPu9vIXWu<h6jw8Oft0Bf&gOn9K$?#if>tBaDVuzg~K`
z@b$gf4b1-X_2V18y*Gj-DRLUrOLRXz*uQt}x^vFHe7SwtGyT!mVn`IO4{{`3VAs<R
zNt-sj9harUYBvz*U%nd0#t_E9gUe<&(d`VFls^$;nVeqatLdKRJwXHQTjV$i@f2{E
ze~x}O2&Lva)JjiAYoUAKW^5`qR@ZM~K6(`n_gvROTdbQvrE3)~=kF}^x>QOEw3VJY
zmuF7hX>#~j;1+D6n6DJC!h_a9<P~h?15a?ta!F7se`!7P3exnCBR!*ix&>iSsSeJ6
zrp&IxkU)!PuGcmdM{AUNxWV)|HP(3Ol4Mc1;?&4YYEf)BOr*;+_!J#u2P!%;p4s^|
zEwt5CATu5l%HpLw6^5?0R6n|YCrnrq#B%25pY|l7aFG6NPFgu4H`#q8(I(>njEfpM
ziI@%{sLTBe_RH46fx)4iq6+i^q7lK%Rrr)79{)THy_z;%ShIR;s7tAhHj|y4&dH{d
zzWj#y3*Bk6GEe~X(>(HsELn^O8!tUcc1Soh`ImbH{F*#nDfA>M{J^!XgOBes!O|?_
z(MEUkK*W6V@g`aIaLgvbZ90-t0w@JErd5v$U`AIo&bS%{0CVOx_%OC5DP|~z(GuH3
zQpC6%xwpzVL7(*F!6(O}W+9MySPI-5gVB!Zk7mk3(%L=u`y$L}jrE7yrmh#Q73Ys7
zO)o)o198=jb;{cQKXGMihOY@ZYkzhmd^09&e7-tfB&)P%4e}Psqv<OG7Y6iV0y)7v
z7O;%oM+_e-QZ3R;!J}qHjnH0A{Z1J3U9cypPca{GTUlzp%wl?7EVu;s#LshB6`i|f
z&hvPsNf!ilJZ?Z5<{;_$2p^c)S^!P1%$93@^hiYaN}V+jo`TS1kNSKczBzy@8VGYI
z3L`uA2nUipc99SdZ%(#npbPxzn=1dqdjNs?y+ReF=$l={=aSqIaf!M_e&p-rubnx|
zV=GWkq<{yN4GX=EpDB2m1lkIqYr%?qr+R^$PAsPcXHLgM{M5J(`UyQD@AT>ovZ}NR
zgd4+N#(g%<JIs@TMAMO|mDwR`CW1*<`baaEA~8$YAtuC#JhS3+dooADZ`lJJ)}P@2
zTE;2T=j=h>pw9Dq9>Vk=z0d!NH}XI7kqen`-8|1+lD3AbCZfCmSb-j&UoJtOA4Opr
z1{H(B^-}}x*lC@0lV-jxX((JMpVtrkQMW6X7kcK{S^THXRE{GbSKqIf7np7&2`CbV
zY<_4M`w0HQ6N(iLBg@!IU`?>5q-70*YsT>4Z|Mj(W39z*Xs9y~q*}F>s^?miMWfSL
zKfq7jYE4Gk6L=7CvHDrW&m6yj9AeF8p+TVDq}@5kTVi(AS;p?fq-CR&SYOPYKDA>!
zzSXP=T(^FGs=%V`tULBmcAGd?GKOV-;yG&VJ)iZyz0&2g^V;+k8K*IJFDf4VQso$B
za=`wwAnB0{e75Ra&fV6CeR;<7%YY)D##cc%!RoDvc&mggcQ^2tvdcWs0;j|KB}Fr>
ztM`=48E7pel2d-T!6275c`<M{ou*NC!|&<D;U!@-F#q3MUjF?y`4`F$lIcTfoOf;A
zEOVaXY&_CkP7}Qpmvt@XJCv+6+=e$9188ArWDLeTyhStx>f?GEdR^5KQdTh3U)i(5
z=*p7C?PQgAwS;fy{@tU60Aa#TyUo7N$G(!FH{>VT=6;LMdXEvuaJD7co0PmMe&~0m
zpF2I%zMp8BN#b)5KR{ZEh2Td*wpm9&&8Gtmm~$BFDrh11T9Eb3I&%Mja5A_6aQAQd
z5HAP@J#s+)G_LdzoVh`S&iyc?7n@Y@gV^U5)GecKos@6!LbPi*V}>1G<dNbpXmWGy
zoxYX2RPD-cVGS6&xpPNOb*X|_X~W>yi1&Ih*iX&+j$bBpWHS+T2%VM}Il2`^4CYyh
z*X|d;f<3(vy0(!kuJ;et>K-?w<<~+WLmEJ|hEn*$97$qBAd`!4NW=R4Z$J%=@8X#4
zyG^k~{PBbS|8}bX;Rf-)i-3P<X;su6aTYLnTut^D?;8ehmy;Oc{xG0nMUsGz<Bfoi
zBnb#?lGM~rET)-D(ui#AW#JKX`3KTakp#wo*2U<d)noiFL&6Ly<31$(>t~8rx{J^f
z#(uPE(`bs^0<C=Vc;Wf?z-#T~<?8G6!S)B&H5=}dfll8Zr$LIW0hNS9b4&n;Dy?yA
zMnX7wa+uaTN*R0M9u)QI{Pv1@Mr`#~ax<UUjyN}IGXClF&#cAkh^WYv<gxk-HyPgS
z<gsYycTm2Co9_ut8V6;vt{69+nVWnc9oQ;N)t+XQ?$6_l3^v)+monSr+jy4&d^9nc
zwfd+NRUSz_&%Ot-YaPbSm3RMC_wsFotGv;)pKG-r+Q2tfU;5uCv{~$+F}}(0qMCMG
zZS&($DwI4`yjd>^K0S+OtFJGR&lGuNyWni%aH38<rT*3tY>rLx(yD9N)F;}xw<77?
z(>47wLD{a8NSmw<c{Z`;g|BBR%p1_eS>#=R{mffmVa23la908LgmSg(VlU5+uS>0F
zyycP^2GE77m|`{I7na+V$tlOXI=O{D>=LO=3XM(Ltw)2iCRsIsQrQi(P7E9WX|G_{
zpkxqN_c0;d+I3==sL)R}tE=jg_oC6mVJv}OSySU8RdA_pVqYz!9BTqBur_g}Pe_*G
zz(S8)k6TnVKsu2?E!rmuY%S~7H1!?E&E}AETCEn^u57R|eVRu5%QPjMqn;7nDc-Jd
z?IN~AqCe2qz39rLj<BEvpsP6ITKrw@CY0%w(w=r@R#V>*rEQqytA%+7aE=Y2MRgNt
z<;`Y6qA(^pO~(zZ@XZyjj3v#jdJE`;zfIiAdO)ysxlktXz>5Bo9xi@MDYHsP1!!6h
z=73kuPsuDrl%$Kvr#*#dtvbw`Pf;s6n=-1aiemo?{LY`pD<4Nm?NVm8<9S^UN^aMm
zzZ;)(V1>2nbH4Qv>l*|2`J)QE9`O^T&jEA57H&Pn9^|iJHed_e4RsGohv^#PUA`|H
z_8n6YTxUoZ_8rx>rWiJ3ART<OcMWTk!47iI>P)$9sGFl>Y&zcIF3X?TO|I_^oVVK@
z4j=1Tj1zAl#b3KclEC$#g4}KcwIB}6f>hZK9ZgGgL>RUujyr0z-#=|m>dp_U;Or!L
z&Jry=ZbgH6f?*`45~E~6ssU9ZNgU!VZCQvv-imq0ZmHekSP`YRgE-F0jFghaOhCax
zSMt>&h;U9yVE?DE-e`MOQ|`)VQsAP8%jyM%zqT`qPM;Q5s^#CtV=8EqQ=}-5(xWO!
z3)4MJK3tPlD-P;GxpIRF2}ihFLS3)S_tS~heo|mcpK16uRIcOFE?c_+X3hH1k+vei
zRFNS*YV{C4!=_t&g3vL-BS)?+gW~~>%MnPedTva?46Ym|S0JJ%N&`_kf=^kJ&#HpA
z)*?!vQ__;gBoB@*On-QA`Vy}gf#05ViZY{5qK|EKIg#LdT%K)H27;IPVj;#Ap*zEl
z4EC3^$+PlW9Bo*Z1w?TB2`AFbU6E7NHgYn}3bcP{yAGhFCBQEaE=97S*84v=`)TE=
ztMr2jhQr?r$;B)Lm13VCuPGDZpb9)OvHZUm!K$uYF?j%|71UvoDA@HpoQ+ZMfT=a5
z^XA|td|2zVUyuIu;Wug2n-Z04F$IIhXC6k{L%3xMt|FL8<el;tU1PYZ9OL)exy?!#
z;-0YhqW%@~r+q9o3bE-ZE@cFPMvI6Z*YFMEhLI+hRi*BlW@P+MY*WKCgn1wl@**p_
zh;X#Tn6@&P>~I&6r{X)1s-hv1moDYMp<Z5~BDau;<_m9(kAaV{^?a(qi|`r`b=Hvw
zpMPaT@j`&WQ2P5DV*qpQwKv^o43N2VUqf;BUPjb&{WUwE{6oD-=yHV8?wD4XnwJfc
zu!Uo7TBGh<9AQZxW{LP@5Fo}mBN$QVY71R=gUa|@t6y23Yh&n3{2b<{>o*sYEo*b&
z{iJ`EaYZCyKPN$tjlA#|Xl7+Co^fpy1O8Ag9zrZ^l%pGdWKEG}jR|pu`nf6QORYXJ
zUd2$F&7cQG+2onN&0T0LLHil#V=V|HaJ4{FuZRDK;Fo~t5zB_7pycxP@^GtUwrjSn
zpH@yP(VS5&hYaE&&e38N!4u*=3O4a%PL=WNl`32!LeCJz8@~_;Ziw%|t_6F?LEb6J
zXBT9x56YqQxuO-xnzJ-3@g>|(gg_#p4ob%bBv!f|iz?Ac?N=+mwP@mJ?Qx9lJX~Xk
zMe(SzA)6|p>1GB;pnKSzDt>&J+-Aj33QJUe+49M0yNqo*1x@%5L4DbE^vGobASb$9
zQz%WWBWL@>8xM@=z`X|wynGRw@W@_RZ5)`n_$V#<*DL0zoA`!XC6p}C&Rufc7x7@9
zeH#%l-Lu+m2?#t<K{Cn1<Lk7xXxZ&^Oq1gkELusC$vCS-WamJfzKYo_!@cXPuYZM>
z+n%+6rEh2n`VB4F{%@DCqoJ9xwf=vxa25aSQQ67d%JF|PO&XOfzcWoRd?qo@0D|Co
zT0+95S{=%Ah+wgBtm-(}xgf&KH`A<|wGEP*a(`2YMfqY%{`O2+7(_6<|L{$?;Tf=k
z*@Zw7Upl(YlH79KtiQWkdeZ(uoMPR}aX)B>b7WXR3%N!vfOeSY=K}-+3=Reh)k3me
z=SPK9CDAgOGja+uw={a!LBwSveu!F?2-iC9JXAVt>^K&~)3*@$b46W~jd`n~6FPQp
z6sD?G|8+hWk=f|WCS|8f-eFx8Hg|zq&`F_QYVE!l0}DJj3A2|e%7(sSUutdG)}{i}
zCbn7~#e9qdt2wFF68eiAgHea^et+==O_kavIiVxp#^NBtT+L(E8P_!+SN);&F=G)a
zBKJbiOd(TRm5H$^CEq*BLBZS~+iQf4<|-{El2L3e?ZB-_JB{tVE?*KO$&NTmK4Ku2
z-x8;p9&gBcUH|yg71&-X#3mm25;_IRPPV(jufPvw5EEctp4eHbGK%%odXRvUsdf{v
zpWy92+6Su_Vrso+XG(qP4j76lDXdck0Y8XAmQ2xiQ{tnb=pcfwK1bDAQFS|@53=PU
zKwH^eEE@hg*`EH^!*od(3rL_sw>mLST|bNQ?X|R-J5sSPI!*SKCK{wAacHVZ9EdTS
zI0PBRYSg>;+EvB;l@)NVsu5$&Lqo48LKHW?8yP?ajDLx<%t*Ql!fc>Y&rnX*$c5y=
zk%z2}bO?h`Zuha(Y~V}lBEC}l!0G;kN9QGaC#d;Z7s)~u8#!;4P@z=MP&boiO_W}8
z<}LNyc4@zJ_R0o>5A#mme{3!afi)A#dykAT-N+`vE#h0CzRQf3gM@wqi&Yy1&251H
zz0z{S=5iBV_ls{B7pqyu%^>pn?dXc+3d%00Y^a=ARc4@kqI{sb;G*1FT}JDH+Q5@A
z9r*%6@J&sRD>hey<Y5=Y8C=mrlI#4fB<c`Kp}j`j!m;u2Z_^a}+)YP>?`aDBH)!Sk
z4{Jrl+}O(KzYB)so4{^t`W*!H5BRG5-!VY67mHOWx<6v2y&yIaD{TpCLdT&vaV?HX
z)Zd*jjg{J?5+?imxAsg2gd#-tOuvgIV~jaxP-r>MGi%QC(mm_W>7vW~>lv(DnOjU?
zC@=^+g_+(+Z}m6+Z3l`1MxXR%mcCQ?40S$H{#r+Z)V(IkRSE`kENd(SJ$Z~rhnfzB
z>X>BUL|jCt2$ct=UUJ`bxP<@u@--`H5mjZ$&akt(?p;P>TZHkn1v?c=CS2Qm!XytT
z*Og~aSo!TvcI7Q_=<cpTEm;l?3O)?U#_4Xnf^s*8&M%d$@mAoM;y3ebFTy{p;T@?H
z7v-@!7L{(m5L7<LJXUPUoh84LLD~!`0HWo<2=$4kw?R(8n5;N#QSUXeQy0PY&9h}=
zdg3Cyiq6mXa;!X?Z-2szXr6QNryyb9g(Wzeg^KrBve(60eTWn6x$<N*lGw%<N){@*
zw4Pwc6)}nZDc-hjU$#Gs77Yh@YS}FO@z|0cj$j-*4O7%hAaFH*acQN(tWET8I!_|T
zA2hAXZ=^q^7JW6(N=g~;Veo|uvR>|H`PX&t>tI@c8(d=_*=-II(B3)BivZ*S@@d~6
zJ~}0GJH4kC;H9TsN}hs;9Ms#0m34Rsd>X#HQ-+uAcT-jWo6Ntm4@4th7b`0?e0-ik
zI`ZE4O_Jk9?h<~xdgMi141G6pfXE|>0y`XX0=u|6CX^RL>)#!sOR8qJ6v*ttmI@cz
zd9UB0A7?`|g;g$30{9<({i?@aIhITQ^$n|Q#u$SktK?7S2WYA}GwAdpbg<ThFOT>`
za7OA}4rL|@30gTH)}->HBg16Q9&m=phw0J<O}WA~p4h9Po@)6;Vlr}yczxZVrS1MY
zQU*U1jYgOw)t3c$fgzF;by%g(ny6Fms~J~!e1#|PieI5TDxdtCg8p1h=f?@QNk}E)
z$dvS}h}$ZVCf%emMh3RBWCpf3f<if4iYr`p{c(Fc!-GX+5feiYABjo0E7<0A&vE8%
z6~P>`F9U^}6D}*V3%q>A7znRF`8NYbv1hc&{qJk(?7P(X|HD%I=W9t?-|k<uw2jJd
z|4-)D=Ort}8Tel1HgakkgaUrZC?ZC<(4HK!j=}tXRk>!ZWpb0?P4(|T>Ip)=PtlB7
zYc%wFWY~i=?a}pj-bY?f8JnN4A0H5YYs16GB8(yQWc_x6y#*0J;*b&uh*~J~k(+<-
zyNUKDz+$?RuE*PD3wTstR9q&oKrz7r)fzzZF-T8LVyxRU2kUcMu7Cw4w`$BM<c(_E
zsDY8n*6+rY_9qTuUecbV#p>QX$_vCBKw3NI=Pg*lBGb&wcR;Okl&80G4Q)pcEKxQ_
zBo@yTsc+0@DNArn=p1nTq5e>pJQ(C`cCM|)2C<PZ9zQVF(Wy8V(W%EYSqu4lcnUz~
z5mMyE<)}4Ei5OTzxt(Ni8Zthfu(`3WQVP)=i3|F~=1t?q)zs!cOtG~bVVfsl5xu|7
zk1kVjaUOFbndZF}a1B3;6kZ8yBrd`|kdC4!>E)|@!2YwQag6N!5G_7Tr81z>NUDu<
zx6QC5Zhxu|tIr;RcOT5)Cjjv8(<rb`zcT7{_+@Q^KUkrM(<=z&s6TG#PdL+t;x8qs
zW|YFw=>u?T-|qVW64gasn>V)@L9_%{tW+3b<mndxnd7O+@aef`Qt@PjwLwcjU0R&@
zed^?Wk1zi)bYN7pOLoTbY7|eORqSb8BENjMo>cTLpr^9vTE4LqjA@wnf-~;N=tOHf
z(ca0&cV_JmPD>yBkz)4EsF|jf#)~)<%Y#nR)7?S-^HmSQbLRiST=mlmM4+P|@}ido
zQp7&X1OU?_wi$4V+}06;{03>IG7~F(neQ0y?Vqqre9H5zj;g(dc&~4We``_~Hck8T
zhHcPE7R81!q)E4E7g>#04kNGCYaGU*GL>)A`n&w5t%c&FYF9&hn|lZBPl8xnRsW?w
z{R-33G*Ba9j1mHg%5DdScQx^1#JFof1;5e2-<VJ$`no|LDPV8r=(tVD&N5GQ5wS7m
z$r&iuxpxA@e;1<9E&-~_zbokL8`z2d|EM5ATPv&Y^g44}n}02&M9c53FbZIcCTN-&
zY*hLNfZoqc@l&Y-#a;qJq%eOnhyB@lt-?BmSw9ZtLH8sgY&7EAeDlDKwZBP;S8ia0
z#I(NsXvEWHD(n6E<$}x4eP6kNAu}M13fc*kCq*UpPp-n06qc&JbWcT?PYQGuRf^%X
z&RTEnA{C4L5m29;dH9uG{m<1X^}0XwQ!yIN<+KRcU3wHQuyje>e=TmUWj;+Rdj&7u
zl;?;n!GF$rsqODroFTuE5<SwaR^iez+#k2X0gPtqLwMBcv~LRJ>0rJ%=(y&Yv~GW`
zuWWbGZ0$`Nsnv^{H63$Al>{~&(Xv?$A@L5}4m$_wI=LZ+@Q3k)wRmgOQRL~JB9Mh%
z93`QGbzh6{@$V-cS*Npjil#V!8{FP|3H)hV!Lz+o6DnA93DxiN#DqN^T?<=ITITP8
z1K@U^b#i5?)yY#c&z7|RB~CljfDyD+C&Dy&uyGnmRC~hm5w2Ke%oO1wnHmLMq7SS9
zhr<NKstlrgW&e#guih>KXsS)q`-_7$v#j@MgYO+P?xSBapnSRud<D#S*fQ1y-=75A
zQ|WYGw*IV3m4!7)MmjcA6<)3_gx&p{S^X!K$*v|u9ygC^lD_Cll`Xhk`Oe%ue32vD
zQy4SH6>VT0oR&XH!*52~{kMys1{5rjc+zaJ2cWc3ghg!<lgXtA_7Muo5P>JXT}<Il
zaG&w_)Xs1v{}hCnK4w0}EX_<TlQwyNwDdNLyV$jN9aJ5q;USC%U;dRh@*+A%rHJ3n
zhd2X&lgu7$WOkuT+<7Y`CuX^JXfEa+F%pw*F3I(*ng4>>H3L}JBKQ>Z4rWGikiL_4
zf1%pZ?~Wg<c&}`vF6gB)rBka03kDjJdccY^?_=ygE0ut6vsq<w3q~f%761O5>ad;u
zY0>uEw~y&N=j#8ez5J&}=bymae`B^zRZlym1<bEZBeo}#)}2}s?r`n-!5D~ea4>&`
z-$*3<F=RX1jcg;*bqp(!?btfr;Ux`^2byInYrsu;;DJ9B1Zsn1iZ7gsF7Bg0*Cy{j
ze58X*KfI4Ny-BPf#c>(quQEI*U%KwzHckJ2ZLv)Pw}7ET%STS382r3M*j71DoPr2E
zN50L82@d3@HuCk`um8<UjuQ<k#;Y4b`uzKcZhx}T-q`I+$vH3CzCDO6h8v?F(mBgb
zLWC@g`(Qs1vM$3-Md*>y&dZOm8)am=6t|iFC0H*WKkREbWEMs|W_imz8CrHDgG6c`
z+ufS=*SJvIwCAMIWN93zZPX5nZ5B)jSR59+@$NHdlgdmdPQ#lGXca-`(|$|ObD>^w
z4ECyR%ax5I3Mm=(n~;tAkx+7?+T%e0Cs?CMZV4-zG|7dTL;S|v)$`6LWl(Qa$lP4l
z<|V1Eopy6)AN<qu%%q(oBVMQrtup<pL1(87^9Xj_D`0JLU^i30eahy{p;z15W%e@E
z8L-9yK-M~K>?;p-OboGJ++u@flwe$&y-to$7m;utrIfmFZYzgQR3#nekzVAl-e_K2
zxk&p(@Y>>`U`8U3eRgqX??SnsJh3L?Y-xDG&0?-ia$0e9W$nC6<6;@js#p<;)?{w#
z;~Cy%q)L)&cc+F*T#|QKu;F5xzi|}$OARelByNl)O4^CPINk|}jy9c5XH7OIM(Um#
zJ2;0L0+NW$AdHeibR2ZQNojdq+2tknrqsR_r&cz{M>Tye*{EUe^KGkrY!Fec)sMj!
zE<?`(3!`8Ji84NMpP$0wInU#5y-|6aM^#gw$Wcl)RVfM_^PBi%E6Hk#<oc-$(BqVp
zpeQ86Yj$0FVn<S=6cE<39UncVynI3g9Z(?K;|#~jOJ!bGb%~@-pUhlGt1mz-oIIA`
z;{kE=rcRCIu%BRn`OSnWi8@MDjZ@flhg1p8M5kzF>|5}?UZ*o&GZJ>ZJZttu>I?Xq
zT(l{sX;reY_Ni#}H2b<?MSZU|N=7zKV;g$ivz{yqNf_SMH#>qMo|@<IwijKMY7bIw
z>FX6Iq**r01*f8!hb|TD3|cU&sSz=;G^Pnl31UY=lYtsC@6g|YJxy&#>xyKfY3PgP
z$>O7enB0aBs?%akbioX_a4dpB#^ns~MmY>)5G-B9IE^InxG>UOdYAjC;??LjM^I-E
zZVv2_h7+v(7>VhZ45@+?&cl@Ppj0Yq=P0(w3L<F=zhqWDDRFf}Dh|x6-KQ^2>T)Q~
zgd{b%L+w?UXm2Ca>eSGV?4_wC#DWgI3;4u^`B<hclv@fgM(ZNZ4vVbnPU_bgBpP1r
z5m2sk(s-^q4<5p3L31%g*b?Xy3>C;vCaSfo_aPE~Y`Ji`abptH-*Hp0hip<pOVstI
z+1E4{R1`E6l<X_=Fp)8w0Qcx3#yfKk8X8h3_^d|v|65dAYC<(r!#+)I3}=`mLI^fN
zBaLmTNrLnGnqk)dTe(Vy!=Mz?g;!ap%8u8R!=QC7qa5lehI>%yx-F&LPMWAaOh#;Q
zalqwP*p?h;`~V?PvnQEVYP^@xE9UONtLkV+uz=d=^+x9`lG@b6sB?~(Djjd>_<_6B
z7N=NYkdryC>PVGm33X`XU??|=@Cq^Fz3=)Z%8mx#H4g3ggVTzjalQVTK8>CAZY#PY
zluGTbu)%|9FKf8&Hh!2+m3$j{7hQos2#O&v<u`P+g`I;kCA9ceK=cn7D0`v<>4Qnw
z(X2l-EqH5o$d@Al3Woyn%YhS{ANo;sN5vA~>cE{UJY4nhPv$!`tBIZp0F$UAqix?K
z&Un|(IF|#XF9~_QFZ*3q#yCxba+V3Ntm#YtgR1$RL|fY~3h)7{LxX~hz3`-REX`gl
z={-=5D@rss|Mgo9BEqf<cOa@;ihiRmF|Dh-dx$ZaK>2-z3`F)giQk<)+Y#?2s^!F`
zJ&R&J`)Kui6oZ)yG%~vyPThSucMy@Rz@K(x1brkL>wN@+IL?vh?2|iY*FGP(fP(0#
zycffi=%Lg+*=Yq?M#^l1Qy%Fk(-a(tlD>Mo>x`!U->Tsaq@1%!$6}g!g2h%{S)tNi
zoC7BOos#lCAowhL*k&x#gHW!FXk+oFq3B{`FQl{34Y!!O;P<C6{Wp0c%o99`B1+ww
zs;2~20>!4@@n+C1OU@6A%_LQ2fc_;0DSP7aTO7S__aDKFD|{sPst;YfflpBk_iDYL
zI>z>1k*wGRTk=_)gNoI2B15GkP?Z-Bs?iNi+U9Srg%?|elEz(G&NIloJjk-o!9u2>
z8#<c{*A2rdzZwrQ0^*+YSW&StOr8~$cAQkOWFK;jV7gpMdK9Y(o~5CAxx%*bRE9DF
zDkJn9Tej~|-X|#nJVk$7X#?E|Lw|0ff<f%#UPAeVTH06}f>&3Uv4<R(%5^-zN;GBl
zH*DVvjF({ak8e}Uj2bhh$Nx(0h>n-|ggA<U-EE6^`)ZW}Ks3(dPdD@Jd-LTT`EnPS
z7_XKxD<xLxC`4OK4>fvaW|Pg6zWCd1A-=yu?d<plS|TaJfcY944-hJu>>(8DO-WNa
zd<>iU_O|;<obc`SZ69G-4<}}dv`-73nVLWjcEApv=3*qi(_UK)vQD|fOl|`z$G^K5
ze8exfJZ87}d*alDp9kEj36i$^Mu@0=Z}W6@9c=^~#jlD_C5;`TMBB{5C^~w$+w|M&
z2Dp|0F%$i&7>qnhR{TL;w(=INGRQC{wy`3HkY79qlgT^umoAR|JZN|~%S3GS?iFQ3
zEd<Wv3FW^6*rK~tWU95;LNuFdyWt9OXN8b~{|5T&%J1mjow2pR|22MokCJ)jN!mqV
z{=zp8<dgs4%SZLqm-|9(zh+yH{#!5b`RC#w+Y0roSKvLp@SIQG_@%+L!{G9wTPCeq
z9edGMyB7zfT|%<Fbr7FDOCM&0)PGug^7-~HN=Yk_?@Mf8t%Ns++%~sO9;JH!OF;eS
zlTP4(?G{)<%U0s*0SrqpyXGTD%Ug!h=?}Z7dYzCe(#@c39X2IAvJx*8O1>~<prYEK
zak4fARQ}XDL>1u{Y3Y6g7R>T_lnNE<(=v>7C8%#x>SH;k>4BnbsEbRdk;}oMYx`5K
z^k$y`OB*xU0Q2Vw$&}tt_E2A=*Mg`~*`2wx3ztkD_j9BLwGIO^E@zgcs+1SLe;rkS
zy|nR$!~ggZK>42|xPO`n`~$&hz__6-Ie$jG42YEjK>-mlg2N80Rm7lyE`u9_iHi|<
zHtLBFqdmtaGK+<)wvS#yN8rXUhvK&|U$r&9*=4lE6xf6>82u~?6<6Sj%nZJ>Ln=0p
zFA~RXHcwa8t&P9uV|tsFz^JUD>S|?jylOpizIvHzt>=DAC+CC9k;l8%`yq?%Hu#6A
z({~euE$cA{%C~$1o!bp<%6&ST&f}WYs}*JF8Wm*9a!Qql{)Xk^rOn^gYzn5Z1z~Ic
z($@T`8Ls2FhsaBG=u>8>t9--Pb{n6&1#)Zd@NM-Yn)3hx{8QZcefrPAvpgmE%@nxK
ztsbh+dC%B$vcfx+&#wNRE#5oVr(k+E*0Va4&!s>5Upd~t^M`zr*Sa2Gw$`7b>0b+n
zs;eD&6XmP#8kmanw%3{#<kKRf1!7vpyGaJthZqLaR0?_0r4XpQH`|={m<mO7MJ`hd
z?su@1bp8ji(5Y8F@TK#UU`_?p^Cq#Z8C$=USE*U|rS}C*B^x0&+}ea_ceRreh6g-!
z%j%OUvk#oYwelvQtyL`Q!^(+RBpgaD+E-(~;}cknB7Xqa6C>3cRPN|;+YFd1nc6iN
zQ={ND7zDgj&e$zui3R4xDrFPuxLjGmk+nepDr5BkPLqprBnf6nEf!1n(Cd{m0+Mo<
z2*MTJ%VK{~&!8TIR}@d8;X(U4d(_0X6f-aT?Lz97-tub+b?unN7Q1%*^@uQ{;9tPq
zp9ZYWyDGMMLgm<f5_2quC7j3&3_)I?8yBi56SOB#94Yk(!JY+gydGherBx3eSSNm)
zE$$?!h&M@0<JI;4flur%%j{=n$B2x21qedWY=tC34kFK_4D`g%na(OR%@Ml-a?JS9
zb8GF?17<&7u^^+Csk{i>=#OC_hy{78q$n7Lfb01%nmyp7HE?4;X5JGge<C#-{87oL
z6BtFL^gf|9+A(jp?#5ae2*p+)XIJA=mg})H-7C7?c?U~d8Juub_p0FI@wEm@7vW(*
z!s%S(tPsJdOWMho4H$!2$P+n=-O}=Ws4F)t%NDbM6E+NnGe=A)*aGF6+S@bx0)opG
z^Gawo8*d)-xf1)kRKQWXeko+Pt#av$4NeiF9&p@?xQq)E8HlvsHpf8YGzsbUp~89*
zDcq*a1YPj55|x!6HhJH6k*=?Yh7zA@oP{hKT1qDtmKTGJY1ogRZJ?SPH}-gRd6_2%
zr%xYjEZQ3eMycYwj*p<|mqVmm(0wf1XK;2F(61b?2!T$P$h&%LWLrsv)0b9dAYd30
z?Z1MH6$XlI$lwrl<mup20ps))0A!GnIp@H()>_Z+1IzwW(=9d(R3rorRh3dG)<a{f
z)Ndkh$3DcNNk@H=M8c@AL#xI}Ilg8%^K)TFoFTw^Za?$4vh4mf6K>eOrMgqZPGXZK
zp0azTh8|g~$%GZ7M{8XcNvl`gFKSd3nLkX5a@{Ny%EH2UTrRD>oYQIedSK~GLWFC&
z@ncdz{EJXgGNI4v6bV-V_0m4;SzO$3IJFBxu+|`V>=psx7?XAutoo897PDQIK(Gn)
zh{gb#`e-u6Mag_h?1Gt?$Rew_F=?D$ZGe{kXky(;0*za9w`z`}bO%0uj=w`9rDkGJ
zkvdR(X!Ne(=uXLP+iC*YL8CsP!-<k9V}GJ<qW_QEdV)z^JlerLyP%B5oe@T3T&&en
z(ZEc(bPW*<g9JuM9ZB7;3P~(wfV6pWws>b>Lgp-CivyspIDxfDi`YjHxad4?1E6Ip
zk?fQ{OY8}I!gAoz+LOS$LRFIb%RklPZ*`)ynOOu2&;wB_t=S)16Odp8janf=UuLYP
zfLMS~10jn3NAa3b_PW`q^l4kVeS%(G=D_KVouC&920WE>9|aKmX^K~P++X4J9M+Fj
zSTm-Q$e?_{Ih(x(z{wbo^(V*_^qCZ95~5=}CB%G^=0cKlkVpZgJ|+Vx(f!hQSYk|4
zHkeeXeSJK&4H1w*y6d65kyvj614jvr$8bLee40Z#4(owSYhOaMxzGkBTMhFtu%sh3
z8uxi~c=f<bnGx`c-DyZ=5l(C~Ou<Nk>v5Ai@LpSqYpO#tmQnCISEGA!ed#4bY(J&q
zW#XF&Mg@l%{Ro@P#}t!7ZcLpInjGsyaOmoZ8?2D1NZwCR53(FkY*R-A`h6dPw=+kw
z-5qy}#0erj2iBc3MpUlgi=al!A}$*$e@BN^H9gcMjqXzvkc&||ztu_29~0;NS5$V;
zmc$l`4+|`fNAVin>J3h=s-mW%vZ8c7Pepg$>M1wo4p^cOx6|_*bB)D~<eF9;@Bz>z
ze8sAx7gxuZ_Fcs%WR@_R#8PbPTej@g&BdB~yN6X(hrDQ>nG@}q`QE07Ye9W%4}_I$
z7<gkZ{P*);)ux+2e3J@^hC>yvoF4c0pLf*mWAIEaN<mmQf`5nl>$eFj+C=7yM(*8W
zIlF)VrggyS#E)FOaPct3z-8xo<4!J3m=7Mx&bb=)?65jot9jOgw(LY2$nr-Ff(yp#
zEr0S#x2tB8Q`HoRt2O_$kmLm3;F<7O>FvEIuP%*OcrI6t)kEzRLE4gI=0s_loqr7-
zX&#f|>Y+bL&JGTIMhPqa#lHrsLQgw7Ec+vh{QkJR2d((nKuWg$<#Cmo6ByP#-*}1E
zSJTl?mIv3Lx7~K~QQK4Fow==L<8Qe-mj<WHGBN2!=7i5*K_Q$o$nzQqkO^(ryEb56
zC5Dv+8AlyzDC1k5g@T)mYMDVhdc2zCAzXVEN_KX$p_=V!?8n-7udU*+i!1E_K!6XZ
z*au(+2cAnb@$o*{$z*3B9w&zKne5|yhWBOdq6g-KmtOOX>K3K&)iJ=nSf{nYWourV
zb7GY)<yAl+HbIX)V-zz$s0W-g#K)iS8xA75#7SIjf-or>Ey`q(Y)+Km?hGOftci#q
z2QM_|=c@#^SNg14oZ~<MzbUFRYY$sjT%=4~;U}(Suh;SEk4qP}GuuW-`VkYe>RJ0-
zoV!lqX?vp!YSxsvq`?V+w!a2IcL%^cITqqn@biJ^_#PmB!1uWX+G4w*Z-#dk6UbiY
zLjG)e9pjLLV0$DOC7&bgrPv(xEX~qXgr%*e^p9hrIOPIc5<iY^8a0gKDfXWa#Z+XA
zOEVoSowrdyKT_0{ITdV)RFc>jY7c(`+ax)BUco@7IH}O&@}G^z>^oc`F=Rd<ICOCM
zPSlX?(_gp2=0I@Wwnm{(Hn{BnIqAjqwsGzbf$IqA$^m@fO)mz7Q!Uv$#}QT6I8=KL
zJI-sn0eUz}IS!N24YEgJ`c>CfUy{=OPGgg<hm*Kqqd-kCaLtYuX8=ZtMk>$ZKY*FX
zW*nk1Bri>bA4)4>0QF*P&oza97PvbfSh#R`Y9OONNQr7%(-B>!-TQ<pyHJjx)r6oS
z*YgOk;X#i62$?k7g|(_8JJz&o)3BF$+}n=W&$CYXG`st@?8wI(lK<?@?KfmM{<wCL
z;r-Knb3z{7G}&>I=YDQcN>{arF6D$v$o(lUKHc{2V#dHhCVDo#=}DiDhyNm_`I^E9
z;;Lu~fA3(rGkEV#{{2@HmfKZW+MudFmfKcAkOv>{_BnCu$|Z;n-jKwVdWA$DS*Rp7
zZ`JRt`lp0T^9}EA>5j`I=ZGawckh@b{Oebo>Zxc$XQX6O`8UL*!tAAtpys;C#QxP_
zInJn8<P@eTK>QKO!$E8n@rj2{WXGwyb;`?pB*{kq*=>B=e3Y^3a(Slu8F<19z$%~1
zrjQU}SN58oxBs#4{RzX{3rBZg&ke}eAKjjjd|9{XMAS`HmQHwpYPqRxp!=%FT>D*;
zZ^jkD!H`{kIR!WY34A*dc{u})hunlOl{haDny25>Wg%g%Pf44@JL7J>gUPS?xwBZn
z=t|2IOEbu^?Afkyn>r2H`9Zwn<rVp_cc`ZKns|D=MEPzLkj&kMICUSU&Gp|w<L3mL
zjj>JR`6GnZAZ@4VfoJ0P+DI15lN3=ayhf+l{P~kUOl#+JV#?rg!I^4#lW(_T-&ZQ?
zk=pGR>no_szu)&GWj6OHL!(i=wK&p*c!QCYdJ=14Vv(EqxC^ifk~Q;*r+K^<2bnjZ
zf;aqNJ?7yVyP|InGd`&}W=uH9l99|hkN9g`#nyYYAOgr_)lb=7^4bl0C#%pAWk)Ax
z7LV^|)g^n<ETk~@O%Z=oo5I8-^0o{$c~7AZ#3``(?*Q%2UNyiqFA*M8I@vT{3A!!T
zlU4bYo@n-)V#eWYYa$m^!2L+mXr|FLkAIY63jk*oGI+mcGu^+>k1ZT<38mFu*wU7Q
z{IPIJ!Wj?gRP<ve9lXC$eMskzM3ZigXLkNsSIELMQs$d++a=ZYp8Gwc(BrNpyI(aj
zpsPpw4cN7p?I!sdjo07Sky59h=^0-1Z#vMR^8UvWXfu(6x>a9Bc*m@_XYGs*Ec#2~
z8*i`BH})dh3Zh(o2L-wpgq<)L6`Ql?5VP->QJz}srby6A!19jH9EFT1hl*&d&T-F&
zizFwnyhg^zMyirZy4Ut;@$pq?`Am!)kAIR#n`3w^b)eZarBBw`Ozgi5mMcAT2VY|F
zcC|l&RNC-5FI|rpq6_t)sy2=9heJNTqYAl{Hqdp^|8-IGLg;!H9U?%d&*Wourg$Kh
z=c$xEF~1kjyt%S6Z?M@R&PitfOIeP2#@GU?-YNbv5ZnFxa33nRkZ#>(@2hnoB9C*X
zk;ov+;CN<B^(Y#Swt0nU#6?-g+w=H0XNc55!k*&KAN-k@Jz2@tC-s?>eu5FXr(^or
z8F%A4IQh+z+@AfpAx7cZuY*7bbP<aprffXOn~CZ9i*0obE~7F3BMwE(8{oxf$>$v<
zmgoECZmqA(G;Hw`m2^G_U$CJq<Vk;1umj)j?2Coj{;SCXC*I?o_KHrjSgXDA_3PjE
z6Yz1Oh6LaH32v1C7dG@i?I-@byZuLFs}}BxvVi+(f}c8J!m8(|_v0i0g$+T=-;Y^{
zgoFSHxM@c3{Ev(adAk2bY7195)O?vRm5TLQIkbvZV;Go{87bi`^kZ(N_h0L;xJMlL
z`*v5d^o@yG=%a?6^NqLnjjgARt*ds|m+M`wD_}K$-@saM2qkV500M%lA!%3HZY+HO
zI{_AiaB~HZ#-Hk)S}g7;a-kb%)GfK23B)Yed^FjhpFMLdZs1d8&ng)8b_9V({ZDs<
zI7nN;eQE*d{Sme>f^=o<NWGH!)ZMPXpKT!Nf?J2E^t}+O!^Epg*?)QHppSLYSq$~p
z?d7=%qmci06I}LIWZp!QlmXcN3dDz$^`QuBR{plO9_o*<mp6RElqzu(9Z&~jauivd
zpYs-BHC<iI+|Y(jpn)dJY)W)=8atVrb0>y;l9kVaOB3N-NylJh^oSa3zF2%Zz3DJ4
z+FKjXs8<niu1>9UBF|<)aY}+~wym!(ZQ-qO^!B32<?>jS8Hj(6Iw}}>K9t#5VQw5)
zb#7o+ymW8RWWs%2&PSk1kvB@g&1h(ADBiFxa;8GPa<2Ohd(oVqv*r*P9hNxLH}`JO
zVhAxEVGb@%{b^aYDm~`3NST64MV?bDE08lMgVifO$Jlhl1S0YX?@cg~)n@GyV02cH
zVO?F{w(XZfZ_NiLz#-6cOJySKKc$tY=Mo#g5f!_D%QaT($7F=$I5xznS#!)5PYfGp
z1NKm8CK62kQ`iHSr#85lU@d|ll~3WuFqQi1*Rqn#>Ox@9cB=$F9xFBD99Fvlj6tWb
zS<G`EwkXnI4I~X~nIeEI@}W&_@BVs|z4Gofpbda64QL3!Hkd=`s{P$PYg&b@qm<@*
zu=6uD@ND2~7W(*?3BP5<o5dpx96AAn!y)fr7~kTsT-hiVrf2mqrhbVTTrzu8JKY}p
zqFd_w@S#|k1KS=CTTYJtY6YA-QznV;yfK&~<Z9z)EV4Y8dDmzQd3EtfZ-#-3E9^Nd
z(zqqo(;7&-q~knx0YVd#k<rOTOcu7o9N)U-Q9YDlJf(ucpc4EBMUrF77{(-)kR=I=
z)gVXM2+AGqN(Jw)V|2kImi4d)=&Dq#t#R!XT`bO-LVe^#ratD5;B5K{=64jnxogLc
zY671i(E>et`RT$r5eZpWBgK~peU2dJ9f4uenLr!$CS+XtJQdzdv?`yR9rWSS=RyEN
zt!~fy7!D{M(o*0+i=+t4d2h9tf|9H$91jN;i%1AhF(C}v-$7gEceKBA*Pi-JDo~2O
zlSWpOy_C0(%E5aWsruxn%krvJ1;sOr^YU|HXqnNVd3qc70|#f9ESb3q*--KZ7U7I|
z<|6@>y9ijHA$;Z-z1iflwe00AutbGBbTtDB4HTbcJGQ`<nz0Dt#MbO0O3@lkjZ!v)
zf}v#RPP~S~5cMu1ZRpP0mhl-r1^O6o!ab3RXg;glGGFk6?sG%vK5$U<GT-=xRIBf!
z#+@$t2na;bCDo-vm6vMV`!YyQvy5^)_XJ%bv~wh(fK#p*JB%(uCS5-j@ra6r+X!uO
zDLF)SM!1-fvKgB=s$qy5{(Is5i#$jvOHo|2HC|%H&h|uXMDdSCRt=3PTjjcnp;AxX
zSKdKkm{7at0Jh~&&W~wt%o+U2xh)n{qtXC5<=*|J_ztooB?I}6-CLDGnY2H*c&-R$
zH}}C4_w9D(q?r{B-oy7gaRD2bql#o4)WkIbD-OT|q^yN|YW<?$L6^@cz$wA36~>*J
z)vEY50-16OO<YEvAZsYozdec9(!&OA_dqmqF`VkVf~L0K%xc4khtdagnKOf`|GMLR
z&Otug>QgQAMU~CT9dxt*E|%Zm_OA)J7$cL*-$uNxFoT{Xo<%c*^zs{4pMPAMz!(~L
zg!5<6nnSblz_t*y19s+>(Io;*8K6Z@RHZWkUI7H*ZLQRUc9m)eGP-u)aL6e~Lo!X}
z1Gg`{=U&6bIGs+{C>wBkRAX={Be!HtN%c(ua;m$W4MYHC5`7l^&4{U(1|NkaB6A4w
zr8~8uEu!XK3ULk*g{GNaPKD{{i{l;g;Y9KC?u!PjAs??awD$ml`(5~#_?;F}H{6@`
zP+p|g_)aX(^;)=!je%DKP}&(Ge&N4i?Wm~PV6=L*VN=@OzfiNk$fFl{66ov(XuW25
zki7ac2ckUFNHbwx&#JJ8dL1W>>P2hjcJ19eG1B*Mk&SAE<uEe~9CC9Qr_UM5)vPF$
z7Ltk>sG&(<NMIyB;${m=Ojd-^S#OWFtltTnFy%$YJdhd_K_6oCHVQ<i(VRD^5$hp1
z&G!mrp93Va3v#i#R$<g+x-nwNi?5q=i5iyr+5>2Mw8fr1!NX-GWCEF#>;B5x9NuEz
zvO2mmEf0AD4$v^+ct1fbz<%#`Z4T9FDcD#iH>g}qQn%<(;iCD#_T0ap5^yt6&CUy5
z@^JtP4O?>8wep6w3iN1qQ>nl^+JCTL0{tJ(-toD!AW+wxnb@{}v2EM7ZQIGjwr$%^
zCbn(cc5-vh-nZ`AyXx!@w^sFEuvS<1>VDqmMJ<!pwxLrFWKr{XiFu&W{%x)I1#Ixg
zx^QDHdpvhCR(Tir+F@F!;#f&-C4;ZPAIZ4+0x;c|O&#=nW3+)wpj0OtgXSvDgFV!@
zhff^!_|cd+bj(0YrrtFRrHpWX^-sxYDuLrLcAX2!E3k}bY+zHg<O$91g8c7AFE<0`
zbv$aK+Nl0b@6K-bi18jT5Tc*U^dxSIpFz?&g+kkF2!eT81k%`40r=Z`(L`6wDs?@e
zUGvN)UN_&cEz{LpK#xcLU%fw*KP@aCE`Aam;<W0FKTu+2NZEZ1-8$@Cn<zO?j65@L
z2_F{$ee>KRdfd4}wu$3ZAr~>%22V7*QD}_4#G1~=x$&+RFs%WLu-Q+(@pnY2z*y6F
zd<py8_nyI^@6MjM%_p+APx?zX0ortY#PP@=frEYOR2N?%ZF~gb!Cuif4w@IVhgRpr
zXrEeV*()<J5GmOZ|99BYbM0MiW#;f0Zn+s{Z=;M}QmC^Fm<+NVv;B{|24YXSwA04o
zhQsg~ott|~%^T?cmL&ZaHF;MlE`12<7Hc@g4lgTh8b#M6=iC$KIzjK`&zXCL-OZQ4
zmrU6Sx=PIM(cJ}3MQ%ReL+BO1KgRd_za=V7v^-sTeiHI}KZMl(A3ExPWzqg)_w`@s
zs3Li3$)D<H@A=}Ws6`*Oo@oD&vpgtVWnh?afmy+(XX*Av&G^mu!oBS~BDeol&@~{A
z4DzV3(chWYa=$fITVp#-`wO=AGB1)D?VN@Me9_R_$wh$7^*I=LxP?&I?4e11`JPQ~
zv<ezvvgVC7W=4jTwVYF!Anhb!rv1i%6^Mi~-q02;LP4-l6Dc2tH_D{EvG;7vfa*Zf
zCMhM5HaZeL7%E>FB<JP1Vay@n>g$e+K*67l=&{)a@}YK;#T#gmY;LK5mZ1fA!3D7x
zG}UtQ;nvQY^jr@MhJvOUIPWVfV|J7bh&Q3K@h^j96nLgxpBbuS4%%NH0Iu5so`RM5
z7=9)9yAx(pX+w-0P+Rr=!;QL3Gi<?+YY=AmS@4_rr@vgKc1$XOJ)~|lTqV!aFm2Yb
zIuMqt<O%k_UiTR9tBKhD(AJkf0Nej)GWkC?#Qz7dL!{(x_n)PASxT1*>niZveSPuP
z2*@L%1mb=Rf310x)`FRsi@=BfBI%PR6UZlg!HX~(1ZL8^6np#e@aN>p&X6%mm!!Ge
zb=WTOW?kr5GR&B8C`vLOpImHqxIS-nz1?4LfBm|F=oaT6+GHAAQK-$=BaJdwLcc0Y
z6`$YneyUZPV7M+%HLNaAHLWfiq34y0GxaIW|EHx|_s^<A&B&%y&0tHhZlbfMPtT`t
zr!G*aXe}0>wcGbde1<~*#96}6)8i~lLak{nD|wg4F+()le!;23X2u31WMGIqO-9SG
z<iMrHi<Yf1Xv!fqAGk=qi~~?>ah;w_%#)CjWPO`wwPc~PS}B3PRc}E8w^?;*tzrCD
zi}fhsoFOvdvFSwCrG3x8-KlyuT$=7&Pr2$nzec%^Xv2%aG=AX7dSajD>hS6pFjDkH
zaJf->7^2hU>agRCdBx9%DlAmvO}VQx#o?0EA+i%p-GAlsQL8)w*S?jyXw%-?y?*PS
z=0?r#B+G^SzRaO?n2z_h=?tN|l^{agBiqm+%5y0&_N1A&e(6l602l^3(_joGz0OS2
zg!Lq~3^?qOfhf9kshNLh_L};b<K0Mh$AH1R_g0(T*|7wXCGuh!vA|ThRT4z7q@TdA
z&`;Kn*3Tvwjx{BtqoSi?prWT@L?4l8wd?jdn=zSzZS&Xqn%G)^jqWl@DQEgJ9YVCp
z;>NQFi?}||xOYcpRXL%Mo&Pp6GW3T64mCB*j&SEW(wcZpg`%e&=tRF)m>8$Wns_6^
zgQ_AT6!xu=<sTL}BcbO#1)rlu_Xrr6E-c0FD@4x#d@FB6f7<GcsWI-yLiHHDz!+uI
zIob3b2Wo7?xZVVzmk<&iz*CCNK#>Ino!7*A-Qvxoc#XChYQK1apkM_8kVXq7US7|c
zjZCG)JN@4f$qDA_;V}pr^$A1*TVs(8l)$wS_VVEk%i;G0wC3J@Qi9qMIdxFZfV!^P
z2^I>o5zo@)mLD7CSOeeWroowuEPE1Ugq*~2*ae1Mf(av6WElENFUb&S)}k@>H(Z<;
zv`GN#$^Zr#_#%K7VLoF!e_|M&aZljG-X?#QL7-i_9cY46;r&Z!GZ|EZMwx{5Ln77i
z0?)Sm`3Il%Jz>*?Y~yU0o1wH7B+V?B1xPrBAr>nu$<}`p5|z!Sy;LCl`c*~s>le-c
z#G(Fw@m@t^2ciF*x?LJjdP<9FUtbeaS9EQ=2;lm1Mv1@Nr5I4*iSZE;0kcH-{P12f
z46LL7jBGd<fA4ErZa1!}Sm&u|Rw-1dc)=r@qg2(nT=KMUHZ5&lu5Df#uAenGt)mJ*
zasFi5rAUB)^(jZYjz5kwzdw$@d%o>uKfc~&d4cr&I!^+^SV?msc<=Xk!*6n4XlZ?}
z`e|<@7hjXmzN<KTp7vOIK2UAV-PXZ2b#8feK4cJlulw<CqVqpyL%s)dI$s(z-qC1b
zDfT*q-QYr)I<EupY~SqEa>ML|AieewTP)l=6;6<(JB{#>m~PD#3d64YwVL`84RWLs
z#V^K;YNX_^5%I>1E#jmS<{%if#})z+YbNB7dq^0W*#||3O5WT?)On~9=NAlFf>M5g
z#LqLc7l1o6h)z<dCbor7b1i1oXrQDkmCGcZDOn;aWnoHNbRjDI$vjPhL&=jzEgcq+
zMtz;}XH`C~1gJ|rj;=b$#8Jg@JgSwC)&m;H+s^7Tkq$Zm3*(TFrOQUf2rS|O@%i@t
zmGLBac*pNXO-vQTAn97A;t{GE-mMaAUf|=HcpgSoBxvr&StOS{PNN>ekY)~baGJ&e
zbHgGzT7V3u)ymPLKdR&D_aMa7Ci$F+k<Qd>h!*r69Z>@c{PHCj=hsm!L7q{CdJf~s
zH_djXyeLsY8u_Ehq*7)vF2nt0Ux5T<(-=A?&xX5huBF^bp+g-hG<dshKDn~DR_G04
zVF*`Hu21NB*>(d=?*iPj)*@u)M1UcGx$yD)TN=i~CDsQ0d#Tj*dEnmF{X_n;H%>(i
z8UHz%CX)JM!-&~5i)hmK7X~DM;Q}_7V8z|kRh;k}9F0wQnJPw(Nueu>`V0+R8HZ`5
zg-BAYf>ArsiBNE(hFm*!CR}Oik~>NYR`3lNlR(VO1;i*U>(4G65reLDEA=8q>~(k<
zA?0m?c13Ra@@fk%fhMdlk%0Uc741#)2le>c0+yIy!&%Fb%g%7FvoofB?L1JP{LRm>
zT8(C=aXCvQlN^rZI4ukD8WX6as2I5E%(GC4;$zbh#+biTd2nRHk-rs9iWzoBCib3`
zS{*GdTc_ueNm3vLP()Rf;|p~(4KG#Zc@*GI{daCF384u=C$m&8`n<xU((|Ii%p}5^
z8yU`}SlmYXt6HH<exmx?w3Zb@gK8?nc7Nv6QKSo)6C<|93?X*_5wpRg*aF9L$?uu2
z{`E7A3?WV4KMU(E;d<o|u9sAzqjQ@48#VovL}@N@`SOI0!mR3#MhpX~Jzs=M;OPpz
z<q$SGA@a`m&t}+f>o)s_Hz4uZ!sbSSliB>1f~`X-l@urgU+PKP3I%`ZiPSAb6}=DN
zzua)4+}ck*^Odesh|<FL+=Q6@li~=GUeU!Uu#~-#ZWO&@$LhvCk4J7BVoU={^#ooL
zqO@c!Cid$5jhP{%m{u|vk)x<jT3wK%l(JeH^=sv7ZO!U5^A+(L)gKyt;G$GfulHf?
zm1Fhq>IK7hJM?%0X-<wy<TjOaOl<-Ql+0~sg@MtA>!a+#_MiajWJTAUm#y$wH-8l=
z_1s+|I#VGADig>1;ZS+l3Rv$(ck{(kcg-)3vD$qx^&vz{q*<LM-t~*WeVFO$mFpwM
zgrzkjDZnwb_T)pCr%{B-F^KsntG|Z<6#rt1j-t+1)mQveyMzf94cUaRdJV(588XJZ
z#yJdS=+7)!-;uJEBF5<E9l}R6h_Q~DFufrHieeFF?Fnt>ZuR9<OIS)IC6Z12GK<m!
zolj$B$_rwgH5g(UfRf3a{VZ#iiSi=|v@Jwf0|K<?iJed7&6`(Fm&)_GM=fMhsOys`
zu<7l+0SLHqE=zHNV;THeWeutctu)0Crz_EkBzQ~21PfC_A$e=*ycVj}v(!)Km_IEF
zQqJuU6;&pY=tVr*Q#BGqO0X-%<1TIK#qWH0*c_mCQ6xa^T7=7It*Fa&W?bpGKxNs1
ztJ|AM=w%$_HdQ3crw&~kx#Lj|33^j(JW!$W_IyP5lYG~s)IF+CqJ{{BdE=9A+6kIY
zuc3%LDz9Wna@zk|HQf0a&VQAh-_cL~i<%pis~jIbOi1^VNRb_f<+sjd#D+_~UE#yu
zFY+ras{CvGV^AyLMOm={Zl6@r=1Z9#f%*8wvB!@URc+@>mE^q@oFJEX(u$_5Ec#MO
z(=vM5?j^%h)2=&n2-~JudjOQ8*S-<7>~zt)-|i*fT{teYnzt`n-XTd|`W0A^AFX-|
zq}^TFTE#YNRANXA3WBo#`3r>#Mo5YfBQ&Gz-%@KEcWoDGrh-1c0cf+RBKPl(Czw=i
zzpvJGc(_vdd215T#5UWcj@Mo!a1A}Vz#2JC2RI!hDGUhUbEII30jD<AZi~aWnp20I
zjp@vq@#Vwc+PI0E1pv|FgPB9Ddd-xOh5d}XTAG-d+Pl)dZ6~kxv4do-sL_@KdgFEO
z^qErGk%V?GVozp_1>>CfOITvfSGVrmdDG@h`y%t9NILVwv0qIRuT5I@QTpZ0{kRp<
zX-%_iNoAeRV!_Vt8rH44-IIG%<5iv$z=XRPgkElyerrayY^aLomKg1xlk|U>O4xlx
ze^Q2%@mBc8CwG<DGl%T%d<n<SuhpISshJsfj)0$f+S$?|7jOyN6!8atM_Dpm#?8n-
zVE2nF7HR$mTZwhZG3Yp-$fZmj`Sw@j3*LQ=UamM3T`I)eHgb35D67U$;!>0M_jXvC
z^yFW{mA^%*`Hl_~0NWrE`V*n9B_5TQWIod#@!oZ26yM!RDMyBM?4&UFQbD_g))8$e
zDMtt{R(b6wY_=aXM;cd*38FFy@zMjuXN7+9?nW??)flbc@%HBIJzJaN=U>LR_PBZE
zl{+Gm((+B~rTKg_I&l>R8((#29d#*%>}}>=tf?5}vPFranZzfPuCvV9P|IU*E>#`}
zoxDd1(YR$yR!!##tKexWam$1s>ZM~Ki{+iU96pL}Z6Wu>u_(Sc;Y0k+k7d|pHPfLD
zPGuM=oSYzOdpQjAfQr_c9U=wTNG4jgS=)>|rkbMREW((9Fi{)bo~ym!NB>1q*;c@C
zezQVJv^~w?5G2uKotg@N^VCT`y#&SG0HyDcX;s>&2%u&w%>B^4+w8v9PL-*`T6>e?
zE~P%<`l~FmK-#@JyOjo;fT~!P=@?D|X{q{$*woqX)JJi(Ft;h;(XM*5bo|St(ca0I
z&JU3aO3MT~6iPRby9OWqc%00^RKPtl-~;Wv^2|S2aEGgpIa#=NS^ypEtY7pPm|#7$
zNKWZ&eZ;=6V%n%`s#FHNM{c#;V06^p?L)&xx{Wd*pOmOy&b8S5Mpe>8Ve-IG5HmaM
zM9Ik+v<q^ONaJ;c(~qClC2=o(P<MO?6_jOSTZ7S(j}JARScGotsQLc()(k2D_{I|)
zqH%~`(fhPFg+&=B&$F4oh{iZw#n~-H&@l7{1RG}ZzN0IKPMSGb_lYS;{=sWAJzG9?
z_unva{sBP@aT?6mseYoZFVjm&ilOB_&cw>(87z*%#+)seddwUG>Z6MYgc#E3aTBCn
z?Qo|h(<z54u4znc{AsJ?FGnU3mfJf@(VtKhGNMRQ;BRuFX=la2e17f4_*L5$w)@vl
zm0yb=IRBVc-Ziwqq_Xp>30HDP*je{T=4?%D2|W8+N-XdW>@DA@z206xll!8KU%)ln
zxglEi3cP$Hdu$ZOUf=D#`b>zs3f<Z6#*oO!>|y$~e=XhtgUPc&PX_6Qxxyo@`4jVW
zpKUM)kgWxgE5GO2u7&J%rM6-vR9Hxmz!==Y7uR099?Oug!gP&Y<Mt^vqdc24E6eKd
z(MfDBnaqFMJV|EytkM8q>|#hgqh>{U$~WTq+-1C4C1EN939=pjlG%(<4`;9hFS#7F
zDuPKVib_hIIJU4T!eE^7Uo{)_suZTC$@f_k-yB&YZbi(P4WKj&r7TOSxRG|+Sw9&V
z4^`99GWtoa=396p=F~I2L-Iu7EbLox1y1iYY`F4t2d}R<?7KwE`W?e3o4;WDJ}6vw
zlupz49piXnYL!c|s+tqZS)X>5d%%~#?M8NzHePBAsN`M<ul(U{jyJC%zIDn_7ujoj
z`E#`syqd8c){!}hRQPkmv^cH*;{m=FeJ%b>l~kUtz#RDCSAx#351bt1SGpFwSv><v
zZ6GZ;3iAq3TMS)*1UL!(O^^J=`~v76khX165g#NIcQHsI9L*{uH<9kuUjWaOd;euI
z6pEy<mpKY%>MceGSoWb>QNrQ+8ziXK2xod2?uPZb>q1pbk{J5ivm`Q9`i0@DxpFPA
zW(QZ|0K9`uQZ1()2q4cs1=>w&XGD3~*xHm{pS7uS&%jkLy31qc=Yls?<_M<S_gX!e
ztq>#K0VnBSl&w!i{_pn!OaOgFb?s2zg1OJ6E?c0nvrbRP!u~Vtz80Fz<H%M2^!uhK
z75_pQYC-Dsd+5Zw`6n111RSC@+^rIv;)H1Jub4ap&za!iushPw6VcFwuBB1hf|V$?
zD6y^(zcQHlkz<>5TSE5D>Esl$>fz;4<z1hOA~dxsu(}M3n_Q@Ey%~y~kBU~)@Nn=Q
zfj8;!Iqr*-rR+yBlcj<*^%#yVdB|k~so5LqFKhww90z#H`bO*Ffnl;MT-<(GRVeJx
z4dqKdqt}2)>P11e8fR7;aU@H;fx>bNEQmr|@p)CYhc|*sB5&>VtsmAVq&EDaooYf_
zI02~b{<Rhj+Q3=7VG|4F-wyaec__-vKaT8u{v1=97n-ge5USn?wV)JqH=Uuw7u?<#
zpmDMa^S_AI%AjOBXHJ&J#ZBz<d#B_L)`=ZAM3ZC(iaU{8HXuH-=IZLJo@$l5W%4hZ
zlJ?dg%?U?`p`(gg_-2Ra0{rVfjW;V*&R1vU`i%&2xIM!HO*!D&gy=&WAZok`{la6e
z(@Is&eFe=(oi;rz(8-zn0&2{(CYz&2bS$m4_RqVj4fIwOCpqpn%O`ofA{agbft|f(
zkF-KNJqVP%!pPsz=sqT8W;lagv8|gSC2dDknNgpS^Fe3esQ&s*-2tX<N>OIMOLu!=
z;EK(jZYK;wZ^vektgh;UKXUcR;#rG(Z@=>kby^dXt^sw4qC-2JVznTp(%=;4PJ>Uc
z7~X%LWJ@=n0cu>Joxc5y-4aNe6tr#`hKZ_(5-nIzGnkD`l9Rdulgp9#9>y}@7$`hb
zHyxI+dWsyO(1r~jS{i?&R5IPNII1yj15iW_QEocstt_l;M-3iCPzz9o2gTZ!5zv{j
z(FhM?*dwD)(wPgi8c2qj8B5oL)xEwl)!slh4^jq(Yff`}@&dk4P4}p&hSwtlZD-ki
zhg%;#^RMBk2DkL5z6k}tIV1gi4Vc~;aZYIm#`!<sulH2FdZGj~KY6}!k_}W$OF~Ef
zbWbCsP@%*G?O3+%3+!!0SDD^z3#v?X`i0FGYmc7|6nACjb;TBs9xzFVGv0?5Grg_8
zX@20$9w$+&FwyXpX+`(6%zW1#+S{0_q6A!aefd?P%~6M3!)1Yc<A!hd3xOUz%iHv7
z3!jVykg)}-yO@5-a~f{!;+?|s8c?B8ZsHZIQ6yiNdO)yp`;CLzzv5S~gekRqAO6-_
z)Of`1<3s>Yc4`HkZ9|%`fW_wu9g#7++O+Ek*1Oovtj=O%R-3b)CSQ%omd;#e4n5(q
zlHb?7kFv!Pl8Rz{ur060HYf6*R$SF4F{qd7qe}DFAQ$eEGOf%AtIhNeoEVy9AXSu_
zFlZ}<6hz5!HQKv}CFP-XmhnI4R)+nWhqRyM87Y@X|I~4`$dM~9^o4AAHj?NR5Kf$-
zAA7~ycMg%R>L21>te&lJqZ-@Wb7@_1d4({yrMp;jf#BeRBuWv~Mh*EB5`gwSRz9uM
zHi!9JrcSHDHN`NWR9>VHeor<Z|Jm};YKdBs>d{S3uG3%F4EobzOcvv9(YIeEPxG&f
zih*Fz*>^`4Nsij?_kV-+znq+{Xn#r`TYqo{%Kz!u=RaCr{<p92KigfRR3Y4y7E!*Y
zt!$IgRvG;C<7&zD@r7#tkk~_^!vGosh50HHCL|fyCI&{K|5#|EST9m&6qPzt(zN>J
zGKd2w(X3f$Hd$y|F0L(UG%cxEYBr(1<vf!R2=4u8%{`|%pEo?89Iw4Swh3c?rxGyw
ztNBY4c%fx9b?9_pL2sN4Kl|V8kpQuR?GBS%+RR=p;ak{c_+5j^=bs=7r|3z-5AV8Y
zdyB$5+LZ{ng2=~IL2lv*0bM~D@LVlUzx%8GeTT7vGC*zyt3!tiqyyrFzJNBMY7UVL
z1B2l*+S$b?(M!PVaGJ1OJ{3)g-sF!QCgi^u%7(`sGz7(6Huikn2ZQ{Sd;W~`!#iK{
zZ1MyIlHMl3`-GP?danJO7D$cCv3!OCnl3e&E{|Ss@|^ldt6X-h+=bRicqFWRr8>61
z4C+(x)>Vkt!+cX;{=)g`Hu$fi{LB*6rzX6+dW5%>`MY!`2U-nui|)qM&vbO}ZPh>T
zUUhJ3pgg`#$x_*nB|)rd30&f+P!VTUjiQ4oc|!e<t~DTO1eelIRZ3^9$Z^iz0BlmW
zuo9$gQCh{szLMPh)a3L?&B2^1VdnbJT!OWv6FAAFtf@wY!DZbMOGSAVdvX-<e3i0&
zv~onH+Qt~wI8nVy@CFcu&vcZrV?|qeUmR^*HGpI()?(V&lH@tgU4NdUf_+>$Ue7YO
zQo1b}m6Fh|s*>=YIZR1~E-%!bDqE)IJXsP;LEX5*-vR16-H2n6BJ~Ah;hudxWFxCl
z!Dt?tFe7@vqnx5*k)qkI%?hCIY*CrzR2}_TC`Q6THnPLha33~%3hau(@;BY0-TAVe
z8ikyah58oc9#?syrn$%Z%`m!3o;ZRSLoY8riOIxp($vu~Bg>B!V=>Z||7M_RQpJ;{
zS8R8<?X1&(ngs3LN}r};?O|I-aMZG>KFt|h)=8v+AgP|gF}^MuHsU=vA}Pa6QNDbR
z=LJ+mnkr*y1cB!ExSrbiyuN)cYs%QuJfdj#AYHAV?ZZ=$oB@7$%}nW%{z9+evA-M%
zdu<m;tn2~ws}Gs!1{G#Gb;>xs>MgL{L2O$nwb)XeZrNg5O$v?D#(-UA28d*9h?C?i
z+*SGm=9<0~Rz`m<VO5)5Q}sie?#eM>dw}<*I}FZg+;>l~_howe7x8yW{P+5R?@gQl
zUd9XXxAKW1(sw^k&{IQ!uJAxnY=#AH?bv8tG|O6qL-_E3dT81n3f`sr--AFYl4cod
z>u`dvY;wr?+FI5>=4S!Yaw(ET`x>Bqk_t;}E*wkYDV9y-%b66c#Q6M|0*NJ^#95Mq
z<49$9(NvbxXXeGJ3i$#!1|#^2pyTlE6N!0y2-pf2zDVMj(!pgPcw%K?HM{2%>G^ha
z#8k$?(5%LRLMJYYB6BPZ5+Z2kYgiV=k#V!d*yZ<vuw){>>QyR3iFIRjT0@WEhSTMi
zQW!Nf>NH4dA+S=5r1SLYwty_6kkMV?-;AtTin?P&Z_*S-4hX~TP8{Zg3dKUoTjUH)
zp#>&s<VkKNq3VX39D*kECpKmI$_L<SGUm)OaPI=7d~t3vGEd-(EnEz)@5jz?^<;-?
zNDo5t_LoSJiwkl>0ol+WHe}fBk8MT@lJbLN9MsbN>`%Pd&Ln1vq?JaQ!o^nqkiwO&
zR3hH7EFZwNSMmd4yy2?-SuL#)j_BbjjvljAT%R(7n!l~uJ(3&3-@2Wiw50h-hSOLM
zwM2XdH@Xw2h{Oe(nX#AG8Yz`pQM}Ee8Z=fZ&caE|25{@FWY@8n%GIL0PcPWHdrKSF
z`kp2)!f74YVBFd}3~yU4n0~PrJrAy}S0O`CP=em5@hau9*saeF^02$D<w!pxFU*C1
z1u}z)FOUiid7G44#!@xMIQvQhP+b50Mls9;y>MI%)9Qg)=f|Q!?O2xZd1ta-XvLZ%
ztjU5DT0~YR&KSx$nT)Lm-0_H(&!V2I=~WRoks8Ad2A>#T8aCz_(0hLXLoSQ>=0Ag;
zHU%vgVxBOmM1VY8Dd#@Xp)pNsFttLl9f!+{fxspF1<q^5nFk4vb%Y>4_!}}Si`Xy<
zarh_d6upu3g&W%Qa8n5C`Q~(HhT1>_+-b4Wu7M0|<dX87Yv1i!w{JK~k0{vyV|f1M
z&>zmGkE?sNhNw8a!0thWlYrAYetz}c>VPP-cgqR<MmckoJ~xE0taXJO2X{)KI?Sb?
zxD>}3?|~G;6Xn9$cFnT4B=`!FYZ}$)okTPA5~Z2ninT7Oo_hjSe?DcEs+mZWdR^1X
z-loj6`j9Px%RTV=HU~3n4JIbS7XSLLOwc=v&gCN5*PZka6h(nMFy%eCb1zYS;D}&3
zHv-&j03e$S)Kz~3_KHzyCP*JLi2_-rR4Q+m6MM3qP9QH-fY5aWHso2#cBNxj_cB7n
zs~H$UcRH{Rs~|ZfN+z=Uslybs&#$%)BrcS9Er@=t-M$oSoCVnE{EL<FD_hxb6TO2A
z`$Wjyd4`)288!$=6FwR^3uRwR3t=zZ6~Iry=<{kLl`DW0f}1?NTX2`k)acKLo4|?S
zohfp+65W{zCv-z#riWRd8V&UVyz!T?4uP>Q4YWIKx|{RmU|oceH_)&aZ1~=r4Q%>W
z`I!OF(e?)B85i|Vr5PMA58=I5%}WjNJCj7vtvhB2k{z4Um}FQZlVEt4iXDPpJ&=SQ
zXL4?c9z=4AKLbY!ORi6|ADt-=<F~qiDkX9sh=Rnk26W|QXIoQll6`yB#(Hcn3EnPf
zB_J#1qh@fm@ILOH6&-t$j!Y1?BF;Z2^O(T;x-&Fp$tANOk7OA?0QQdMz+nyl2L$P_
zVc=L&cc)S1c(4@jiFPc}A1N6b8=2ev{W%)?2~KFH*TweRW`|24NAJN0^1|Up!r&=>
zMd)~4i0}=5_UjBo$1+W<GnYN=z#d6dT$`}ONq>yKfH~@*A4r_&nnRq(^k=LJAbw7Z
z1I~;|<09?i#iE_!#V|98;@5vhNhVSL@Fh`S`N>YxX6jjAVppk_+-j6Lw4f~0#i>XV
zlnu;HZ3sPj6|`rEePF~cuXli|p`EFdU8m_`q=hY0-zy==6Gu=_;f=h%MGncZR2~o|
zays!!#Ok65lY!H|*<{Hni<)(S=5x<TRKU|v`oKmfNz9rIc7GywvSI+FA~A=v7Vfa?
z9<a=!efdImI3h1;Oxq^gEQkSN*UB50%-PVWjlpNvNHEut^FDIM!g54b&T!ciSY4jZ
zg+CXn%l`PlUB9NaP-I>=SGU4t3~crxyzocNDk%O;lrXG5;dcelY;O}tJRh9+KY}n1
zY#A`qhm+~CljV#0R1>bods;zW7rOHL*1$S1VnR>G{a2UhXS(?7!B@A~2JOfuQgmzD
z9f8j9h!?94bUX&M=Y2%`T?PAn28dk;i~!05IjzCSEwTptChRE7LtrgZs9JH<JrDI@
zETU+v!M@4(0qT0#mN5^jxCpxrs{tGb=H{`-R?VvcZU?lhl=nJm7yS;daIgdMi&)cI
z#q7cUJ4Bb!^O5oOlf>s)Vm!STuSo7Y2;7#60S}R{#h|sFqDJG1#|ZU)n%IoXN*Bc|
zX_sQp*7ngUA6gx~FIIU<yw_s07~_c-?MjrC`q$BhscP)slZ?2$+jB(3P8gO%H6Ycs
z+E`jH)}ao%A?GMvT0PR$ur-vP?%IP^3m){M=fWKq{c6%4<@9@o)Zi#|&{j-lVyJkT
zraPE=Yd&)wp0k9a!Tm+Mc7tvOvgUUCoKNCj)YT1=qrxuj_iJN&-g&e)zW<e)pd_Fg
zHTj_?n0~}r6#tifx2>&*xiPJTzKcHp{}%lG2SA*peCaSRg3Nu+7FSRzozA!RKxj<>
zGW^>%Bhd#wmn}K~2b;4Ax(o<sT4Za*z-Uy=pMXnjyWn$|ZW0=9Cd8nXlCkyg1h9K2
z-tkt)@zrL-oG<N{H>@6t@7W771`H(!VtG$u-yw262V3`Y+yES;Zq@*%&w`!su<VOE
zK@Zu1Dsy|ezV<M5^=WG~7N*ZUeMqE*jm3!hie74~Nr#JDfId~1R|-MevqrpryH!X1
zU8yJjXFHo6cp9~5vfUNrw#vP#9>c}T@BX0r<CeA)hzdgYVZ=PUPL}7+lIDZ;y}A+g
zyvw%pgKd=Nak`vtRUbY!*TD57laqBDPi_M=pNyr92>OKCyN&*qQK9jBk4{70WUVy!
zI1zWu*d84>gVAgQSf&GW8;=+-Nt;!Q`%`@#^+Dky>D7B;Vp>g5p8h}mbLOGws9VmQ
z&@a{CoX};01|4JUrfgV?gp{C}7Eu=o)dl+Ve7`lr?~?rh5}3^}7rA|Q+|}jDhK`CZ
zL0D@lQz%pNdSIQYXuDWDil>&Pm@9+VpcZs63-a`KU`huQrPi}!?!zp`@N&T>Vo7r9
zm*y}1d_eEl<RkbF^Ce-nJGfUphny0K(2V^7)wo=-Dq<zPfjT)mSkXuF@MARnN}9nP
z-OC9+ZbI#1!)8C{muQCA`-g1A8dd4gfK@uGV#CDevqHk>@sio`c#9LvxCzDnJb4H0
z(_<V2;P~Qu6Ma(EvXr|?En-!h3p9&KgC>s*zZ{8=8g{dm`Ti{7aYi$x=J1ob=&3?O
zC?<rF*nA9@eU}fO_7?`43*<BQ2AwLDbk_-i2A#^J<}+zV)8x}7gyrC4c7*M<kh{x@
z!xULGl%jZ?-Pf7jUcTp#?>AF)IDy>+GB}a=NO0my?;ota>ev&N|LjnbHj<4$<%as`
zv?4bfIMqX5{+)f2?J@H0c7lFoJMI<Af)sFr<t1K4Z}(4Ct<VQi7b!c`{~N%>|M>)g
z7-bllq$(3@H4!~6!xi8Xsf3q6`OTNpuY@Ophc|n$Z-h5bnrdE&y`Ny3y2;s#9h5y9
zS@mS^Vw>6vV6sSw?Q<P){*87z95=*~EH6MZX65rwCWBMd8xo6679kSAx6R(ZfnGq?
zWRRY}pjg}^lg!*_v#sR@@n2`_PGDdN+7E)}^)qAtZ-2>#w$|3RHve0^`oEN`|F3a1
zNpaogr=E#BqtM;}8*_|0@ejX!22>*|{?2cuGRWxA^hSkwC<VNkA^UymXx93yJ}`n?
zXfbet1-P98_=aGTPJEQnY<5$Z<49N2kNx8o#b0pxr>%a2Tn?>iq>Y6q)G#e5Z3R;5
z{n{`j{e%tADg)8WhlYy5f(bEg`)$R;U<%Qb1tZuUyJA9dv3{%JESagl1kY+GV?D24
z0PwdQg6%5XrXx&;|BO?wL;r22N50v#j=%E=qjJpce(}Hs?fLqXKjZW(9H-{kjUV^U
zti^YQ?KcIU!(GrN?lJ}o&>l@;y)_es!2Zj9J|J@1NS4D4N|DCB9_-UqWKddz#nu%8
zpu23YBmlvTW2!(a$us8e`}=WVf?n<N^zZdhVyP*wFU{zw6>HY{Y=<ARa~*YKYeZv5
z8R=yyv*OYH?KK1Q!(#Eq6}B0W%S2hZ!t0QkkYf)){}F3wixXBBjHEO7r85IO`#!@c
znl&o$T&6NaSuHPCuxNGGYc7tqswZb&a<rs_fe`F?PdQ=yv(0cW8j}<VZcWDq87B3z
zP2y1`%YQ@45AgYY2pe3-kpOdjLb|+Ze@8BmJ{I=iC#-(`oiGt-5IQzdB21S)5tW$U
zhpaY)C042x=$7F9XLx5mkzl7X+Te@~kwUHl@P&Xfs!)6|3a23@^URGiakU`3q@XUe
zi-P=}CR8X;lbso?M*j@;U%xM=c~J&3!e75~G=Kg2u_pYobugvXx6}Xe_tKgf>O1LM
z*_zV+x9{se(<GcfnuNv0<BioxD;6M#UcNuS|A2yLpaBbs!3W0j;X{c1K`-1RNh5+9
zx7padsclw~tXf-JT3S-AK*lqtwwAX97YVY6SX8O1T3k}q)U0T>@NR6@i2cswY-os)
z(o0y&x!%8;$a0+KzV@8zVvX^3+79?7msjcBZ+l|~%Hz-LxLZKuwiFe!JH0s*(POu}
zPvhmkouhP{Vq>>2kCNjM5ZtqOw7kJJx!Gec$jei(*Ff>5GPvEg%fxlocl`3~&T6y|
z_3@C8HMA!g`SMKh<tO?v3-kI?AMWeWkNm;NTGM(%OVNE6Jbz2ZT4R3?i1}HSd)o8B
zzmJAkZziF=puVSSL|;!Yp}oMi50AJ}zVr5YH*0@wA7gwS2D87|vikhJu6QAU`-}-6
z-nilBnxezAcl4J7$LI4ahqqCa(t;d>F=d2k2nsMkn}UubQ3|%Fcj9<%Q;v(HVWJ-+
z7U>WosUxe`GKiEk>d-GjA19RAzh<YQk4A`cjnIlaMn$?o+u)uhzSA~9?1~trp(oZx
z4lUb|k_<5&IJNPhI9NX2nAkBPVHGY<ErN`p2;ZEck=U3akx-UD3Z{{tqHR#7ABI^^
zeX!2=&uFuum(A>*^s<>cF!?<yLgf@8AwM_?u$kI3siR149bBDwps7pDFfK232|Kir
zC$xAShip+JKU1n3BUb6yHSp>sK2yhpDK~QpW43A4s&o!>6k8UGRU=K`$XBmC7H4f8
z5MkA#m~!q15>OU~>ap58;$qbzWO2NQu$giVqn6qM`IxK-S4lB*?2j_y%-3cr6EKbN
z(nP_*s8w}xm_J110o@uC*iI(+_;Ba+3;V^|>(sYY75;-tJA~C@!G?!oJta{0`pg!D
z<IvP4Snrt!uOA|IFb)XsC6u?Sq2w6sAf~)9ee3iod5fT=Fo3PMlIDhwZ`cWWCF?$w
z?m61HscB8o=BN&$*sxJlAEZ<$-GZ=kQFQ-!j5-EVwD!g;dur^E>>?}&RJHdksfH}I
z_s(r@VeGRgs#OPJ!2jkhg8cC)UAu+}d8G4K=rI8iaPg*FP{)08omkh<!MnIv5L5<F
z)9%LcXxc6T11xSe)8OO@`MY<#R&`cPV%@$4WF1=fUaklD-6e(11nLdlrLPs8pJ%jG
zR<6r66nU6Gj-^vGA6HjtF4q^eRp*&VDoQ`54;@N_tA)^&bD)EZcKVHg*7S&~lBHh=
zh-n@`y#OM@Ci2y>;IS8bT>yj)TWB*_p3N<1c_y|Mx+xDW?w?ql1b96eS<zxCF>IMW
z3i%aXagPW&Ii=iL-7VIdC|1M*fVXNf?cw%pzJF*Zl`tSJwD--{^FWv2gTfFeotM3O
zuCFe(u41;==JVr*{S_wGfT3nUA=h7{8RR^7%+5^`uv7gkw!3$ld{bHZPnBy}+csLY
zEu$v}xkaji^=lZXWL9ATA=@NoJ88;E-a*V3D_0?1Oh|Xvn$s|+XCZKnXB*QKy>pd)
z5Q1(0;$9C;A_(NL_{>%eOP8k8O$1#!zU@SOS=Om+Dad1R8>q~O_}S{=I@SU+I=tIT
zjD;Dh1h580v`|ue14OVe-6T7rfhPmPMriICk*7hkuugm7W9o(^>NohzD$rOqTMP{H
zJgud9zgSN2%y!O^6f=bQ50c!L-IO|gtj`)1d4g0K?mkeB^ZCz9X(OKXuE%aW;Jo4!
zF029rSL*F*(av2ly25!;UH6TVQYO!lwQ&rX1_2>eXgs90WL9Jfp;XR43}&^ua5H+l
z1te7gym4G}0v@fyvYo~-B#v77uGd%59&XNv7XVFF+mh|O+RQF4@l53iaaKbmdqQ^p
zgc`=3sE0uC>*^T6ZbAZ3eGPerZx#<u>go!b{E$u|cxPH(au9NQ{yTV90<AQu!B9DG
zE<_CBI{E|a2y|`m<24W^@$n!Z@o1qHE6`yjlSZm}4El?)gg0pL48?rYDpus%Q9gF5
z^tp}#LWHqkR-{4paQuM$;Y|GsKLBh0VtTg+<hhu19Vu%xGBtFsFn0Rv&K&^?f?%(>
z1W*_AZAM&`5)ABsi{vaF6`)EQAd<?<;14e7X<6XPY5Hpp@T!iotu)x8WX~v|lV~ak
zi{%|x-4w^?JTpzH07hFCx3Zj9-%J1<eTEZQ$K+=$64+wONxKrw!ruRa(`Ynrw&@=#
zv%m~JjSVZ!f-pnA3{x*TYF>5AFy?@wLl_Uk9gRK4x%L=-2hRWc2dCEow5A}Wy!2nx
zZQAB2_K=6lc?Y@dz7~@Rma`f<v~?laLzaAvdJcHo$k2rda<y$91<G#5w`@ILUPg2T
zrZf<L<)Yxa_by$Oz>1lut7vQIdSD)Q7fWZO^iabB0sAuv5`=wg1Jscq^uAVfJk!*@
zsSrf<YEjFh(1UUJh=zpx2zMFHOxLBQ0G41kIK3PPH0Y19+i!v($15`a`v_hYHSe%p
z_xeF%9!4S0Z^j}dS?rvw#38SLc@^mnlR=zZ2|<-x=<4bY+>kcKQAs=oRt}Plu&In}
z<tg?U-A{aV?MRdiyS_OtNSY~Af1n#0)4x)-_@^x+qHc`BT&RP1_l`(^xd|zW2a=4y
zy!`oVn)tgXk8^z@A-zMOJ37={B#Om&$k&)5-K)sHsTV#eq9AHn?aWKQoPmsoSr7YM
zQnNq4Eg?ehdU)*eJ8*#h;Hh)Tlk+iYi?2hs#KK9o9Mu%9#W0vqF*H_d_`-1ly%hQe
zLdh-~tr?z3bTZ*5bGbU)|BDovkd(Li4GSB&hy$yy8=>Q4#6x6Y+Z?BtZqZ|Oi18Y^
z)xuiDJ_|!MX#?5{TErrN+wbWG2d8TMZ^|#Dj!{E!BPX^nT+>ul#xZ{H&g(w;KFL{K
zs4?%t6H9A`Vj^8haiYu*B`n;gPG|GnF7|W^!ilC$X-tMo_4CI%siDRe4Yop0q-n!x
ztVr>}2n3B_-XQHU*3yswA=o;imMSv@Z7fKIA^6+dV)+{-7Hh&H#mG<@!#8aQh73dN
z;>D`4mdNlpwc4YI46D+1Bk(ykdw_Ug6^w|ukrbQCUY8bJOID}<HHke|8ePA`!Ad&W
z5u;32*?OroN=kXYFiM3|o$BB=!0Yo{Rg+wExsZji^mKM|QwXkmucyef@OB%2*uWM@
zxq*W?Z7Q9QsByi1kgO-DK4TFr5>FK4wYHeQw7x&1o{6;jJnzw)b1{a~OCJwoagGlk
zJ?<k|xektB8|&`!#-U6v<+;iJq2M8RQVekR2f327)B0^L+eIRK{XxKyDQ($0@$d2l
z_?zp@0(eA-Uu76q|8YrW5gkW%!fUhM^Oc4AuS$&3H*O+iN*Rcd5h$EX4pqGZH@tNY
z904}p5e;R7gxm+ZhvM<FW?3!;<qm_<^cK=NWf_$nsGHklT6nxME$t((r=VCE?K`GR
z7v+mwy@eyV;74@F<A;}r(40u;U2xU{H8%`-ckz5oMWw0OISHcd#y-Eqxvs0$SXT)=
zx@ld|XS<yaH58noa${^$=bN}R_sSr-oVU2u(Q)wruV)p@U+gKjbG;DKkcOnSlcZGT
zlfBCF(D&i-$vujOM%L`kgk07XnDSgQ)`%^%oeDmcsg!VntO)0v5Ae3MrT%Ah%lRxl
z?n-AikWYbY4;pyaVbS5ZcFDI35B6;`t>io>mzW<2Ix2%W=_e@Lc|udEO_7m~nrSuK
zDBFtzS$m%8E41Cyre%4!0x64^=T!HvpWIq!LZQEdUw>1RlX4pnwZVCpiW!CCS?v97
zl|*vwA5U);{SXU40#Ec@&14kuL}Ek?ybXxi^7?YonR2Lf6bq)B5zNyot>;5}4(E}^
zM*d7^6M~Vq&mjRF_ym6?<<wh{6Gju{{Ts`Az)uLoRT|d62QJ^d!Er2=``16@)1DyV
z$xxb$2sfI6Qd&ZxPtz{)gS7mmj3hc-RLQ=8#D}E2CQNkDu)I|qiFdd^{RL#2%d=I}
z8JS&i8*^b`e-8qNIdcG*yDVH6kO+5=&G#c=(v>euK3ggZF4|k>+MG{+ftjSqMtE*$
z%`Unl^T}bTm9}Mt<s2GlSM})EK1fM_p{D$F&DTX~G23Im?Ih9B({c?*W4?`l@kZok
zVFjh?P#nZ#x)r@;m{e@2$gtwGr8P@<KLm*wDMCeaBLvy(t*w+O8vP9ODlN<nfU08S
z)0*J=OcQq#M)KA7np%9j@)u5bOB(f(MyiSEDc`eAcMITcFR#igKutkDnJt6(lAe{_
zE^A;!Cs!*BZ(+K1)v5?<X>%9ttO$EnGy2|H_I0@DVg2rFLgtt4N(qs(E4K@hb2+=P
zm)2q)sr=5!fEy_QH6(quD3+W4_4DF*_t2^5%PzOg_SoQF#WLkkW{`=hDE+a5u)vsC
z{MMBR%gD_)3LN(LNV0;|=s(&ulsAM*;`7MU8N!X6%Mr2kJ*ranoILr7)OO%J)}bOX
zd;U?CL$&9-iCRh&#}|<sCR!<DRFIdDvx|RaNu)>9H3bLA`qAQ-6vQTQDPs_CW{fi#
zXEJ2>y@`*jYxu7{!rI2<Bo!P0Dw|*{3`oQoh1;F>C>y)<5a6sIgCBqSQPF4;^+Fv$
zr781&c&hh8*6WrRG7-zB<x(Iq6YHiG{wQO~4=f>W8z-(U7Zd*&pNa2_8O)ZD&nK3p
zJ8&=ydE^yKshXILNfm|Oxl8_yY>ix{DIh9{gbQbKL)w~4R1XK!myl|6_Sw3<S4^H9
z21&Ll8FaE#)&dy?Rg9$bH7j>dI)|1kEH?Y6Q%j<cW?U&fRZLF27h0U?@R7rmic+A&
zkSafh98;V~*`RC;8&q^KD5gk}*p|)^vt;CktCRa-Mg(yQFB$%sMelG)CWKKy!w9P|
zzV>2>v6@KR*bx~)EzK^NCcBGhOIlQteojbL2K)4~4#Y?ZV%;bqI&uPrq@|$O3QpXR
zxr1D(D?hxX`A-xN^8+@!U__74?ra(!^&5nw4J3GKt>|!kv0F-cY9SG1k0-ECsop7Y
zUa_@NgoLFq80Hp%LR!64YIX<cg-$;za{C$`$#g7H)fKTog18D%BB`Ei_q<+jrp6N}
z-2wFweayfZqRPIm=8>Nzy&<V6y<VzJWF*qNyvPh`Ht|p*s(68dQbwc|ddFBFFR3+w
z7%AD!FekDf)MZn?yk0@^j7=wIZG*$pQGIY@(%5(~gB(z~m!!41p}~)XtE^r{{wN{n
zpM_<P1+t55q|HV;R^f~s9?SiL2`gYMp{{CJTUJsvo{K*vaK8^KdcZH^?znLro@mz~
zJPd=G1WyudC-%-wqHNx1Otz>ErK}!Md(yL7DpvaEXZ7#R8Zw5<!2VZVNaUSBNQyj$
zOdoy$DZP#)i)D)gEsBC6?O%&OxKElP8D#zz#I4g!AFIgJI&frht@KPtE#+S4nGfO0
zdN|Z4!_yF*-gT*@H8aKy(=CkHNP%DeE8^gBfXUXir4w8;9g*JzWyqK_tdt)v#Qe5^
zPsvEKgA$P`+i+PsB(}&HB7Tpl2lph>X>_bL8hxiCV<8I*N%(_UPF*(S1$rA<2*A7~
zJs&2#=mI^8mE|>BGLEHzso%RWS<d3aQmFPDV-PMRsn%YUvW!Y#MsbA))9bhW%X2%j
zE$8XnVMG3MYyOM%Ve5F1MGET%8TS|hU9(Q1p*U=~mCZ>cj#pgVfFeUClohf)(sd0?
zyd;HGacu<KOY~VgLJrY-ZuAxurL26}WU{{Lpzc6EcC4*_(4qIKJ0bi4sG#`}0*1S*
zw_OQt`BQxj<pHkvZ>td;UQJW+7z>G^S`N)rD#8(r)i`?FXl>-xL}b^5WTP~14A#aw
z%cUyK1{+DmpZ~ewBF*yUg&JG4jXAmHh1$k8592$ZD><{!`VXP-1Vh!NpH5PO`dwo|
zg%h4MXi_4(2A9+Jqo0R4N>gRI5j~wT6_)}I?@T2F!}LxHcw_Lr;R8FWnYn~(LhABK
z>y<8q=ze3PzL`YE7lULpcyLY0_362CBr|1cIiZ57+PsoKRdc0r9?g8e3y-Bj07y8`
zFTa*h3tdniU65d^AV~-&xK!*(q4-iwwZVzqc_C9%v8y|+mV>prVqcflcg3Jv3HBS{
zXCFJ|!r*=4eHYlJr<t>=M@1BH6}PxT!2GNf?09WjdAkf{#da?ERl3>Q?@=fYcX`tk
z=R=a?R1PC(Rk5l~PXF~lP^ZLljen!AfTWr5I%O`bExIwDeli}JFpb*v#ZO|!o1*Vz
zh<L>KHY6Hz93{YYB}sz>uUatdJtn2l#s$D!y+nxK*C(v_sc}EMg^x;SH@YMTTBS%I
zg+}eXkzhCv&}oavPKhNP^xj+eduA9g+F+%&#x&5%|59$%;E~2#InVjg?j)7a9r?Gr
zLFTIqU32R!pTAXso3R0+f69(E37?31op-iwT+_6;*(M&e@nq4u|6wdbp$*aqCbuj+
z<hPB7WTs|PrbBn2r#2UtPXRtF!K`Gfm;T$~U8!y~juox)(BPfXbl%7Ml;uG=r&z@k
z&gg-VVoBjSqhUCxuH7gk+@En79xx*(q$+BzjtKS$8JBmC)9x^sJ4G^Q>AlZjroBi9
z{(W1#16@glKM77Hgkd}>Tm@Ep0A_jc1?8k#L45thTAskqby31{bZ6U<+{)<ZkBhJN
zs%Xgusw1YaYbkTPj;*zMb26*4?Hs;lT6kkRYA=O_3yrFwt3>v{DI|_PV?Hw^xQSPA
zpd6D3N?g?p0Lp8lRX7deh+){Rsqm<BVhQuaje~kTmGOS7Db>OeR`lc6U<Y>yM$S-F
z2T=bb-gdEM&8n6tF6WjwH&J1B@7m#s`uB024C_M0%M&?FW`Aq!RLIX8tY30^f3CCU
z<|($Mink$d0G+_#Jtd~UeeuN(fXpqvg}5F4;Qs#3%ntbLDjv(LcwVgg*YTg<_%4da
z95nt5RHsDG=?!M54dA4Z{8cmT7#{r2oOpc}OvYx;=I@5p;)Tm2KZo-sxQua+VGmK_
zF$T;B*vPQ}g4G{5tLTgh;4etuf^AkJDi5<c)?I2q1SvNpEPL(LJ$RupCoJ^ejzfH-
z1-QRU3SK{v-$b`JJtuKIBh+Vp72Zg8zMP?E=zr$G$qC%ma6|JUT5qQTT$pq}w_Ih2
zC=K}Qg;t=_;C8>I4~l3nV<9*W1i+*K(Io<C{BNOqRq+OJ{KoOQ->|kw*;?p8*Z(?%
z%E5~NdEUT{%Hn(=ZLz+}^Ox$Ne1Uuyqk-Z5n>WJy7ee9+m%34PgAKw;&k$D_JYeV(
zQG!Q;6F53Bfqc}E>!+5PKC;fFxg~<Y%SgRNf&}u5f8?*t8)7imiJy6G0KQ8+w2L~|
zVVutw?04Snyx8;gKYBndS#$}C9X1bxyMtf6AN8nIR;(}NwA7}6Bcq}+kR1nthFVQ#
z(zUxC-UP+d!L%~%*w}|t^0R-<Q}0962Euc@sNQv$X;={k7*#{sFY^VTaFQ<I`W?o?
zSV?^r?&%Qj_?JKaj)D*Xbsj7S6i6kaILBE(8Nexw`Om(pRavSZE)RX~wa-u7ins1O
zciWiCyX4y^r7$`Bxz|e82X8`4EA#q6cI>XXqNCdU>41|a^vODVybDchzEd=G3rQAv
z*eqM50Z5Bqpe<g=5e4EIiVmk6yvUAONnv~S=8&ydcF@UbegvAWf6pL|{K`p<>@{p3
zAUFuUXMn2}h8dl2KQXxfFz!%}{x=_WIsi;xrK=?Gpm%W0OElVWjwe+ue!sNT3H6x$
z-EX5&?cWeLEaDSoyhTW%2e$a19gY8ovUlLNwB3>gbKACU+qP}nwr$(CZQHi(-1g3m
zo9CXY?*3|w8a>W$So3*jtcaKqiKi~ctZPUvYYD}6iOIC2zmo)p7Sbi;F_8^XV+kag
zB0j7OH3)*TqKz&hOf&+@7Sv#AMACzfemQhs{1%m~otSfnCo|7i8sSDElb8BTl96fr
zZAl_~%pUSy%m_o4G0iK9^vDcFPAqOmK}bbaLDnmYfGG(pfH4R&{6Ii1#tzto6(vPe
z>m}EXJ=S=D<8^VpHN0PQ4AhpevL{>c0LxgfD<vTkPoSZOABK(_l@t-Uu+NZgBpH6-
zVElblf?l-eSYxLoJx2g-F=o(g+`2E+xMM6@hFG+8=gh=O%?xCF`fJ*PAglU3tOLwo
z7l6vOY+~-uk)Z`C>Y=kgx?zO<C_MOFy_h>bz=1Tiq#%2gGJ$Ae<hvq@8Ej3Y*G0@K
z?8D@OefY31UWK8*vV&hDB{!LZNJ9)|srsH{n0!cuKcZnB@|5(;<-|HidNi&-2u-db
z<Ny?$ph;spZX+OqfZ<;|e7u~~c!&b8%6w8hVexu|lLKz9z~giqvJYL13BxKeWoIsK
z73=_EszJj&Hr?trG1P5PQz0%69#<S<9bZrcG7)M&60%oru%-KC;u)a*LB?WpSreF)
z2O>c!hRL9}wm+1NAI{9ZS!ZO5qH)sU5TEJ@!%;W`)32xr!c=eT>27}F9`WgJ;ozU#
z^mibJ#|Qd!jbub7vjan-)$lZPRkn<!6(D<7hQ{WB!tRFUVsA~0<OfMH30xDQsgHcl
zIS24mD(mC9CSEL=xpHUn#~cn>%|pv#@|Oc{-&qITK+OSI!Ci%n)FWz^-a(L()v}Eg
z%UsFv$Hil4D%;>GP<@lB9eK1FFjWOYe1UT|FBTRKS>2k;CagE1%=dx?aWvS$%pnp}
zvu6TzD;Wo5ZqQw)LiaTo25vbY;Km1R4~tShAu1u3XCbGOsEc^H3y)fENwBp&@F|#P
ztU`0P(ITESJ@DEPJ=XiEDes6Z`#2;oz7L69B2<=Hu$M=-@tWPD<}*Bd(h}X2<aBBR
zm)c_Lst`mBzW04uO^ug%PEQ)neT(IN6>JzgebNl@5DV<MB?mwbTVC2>3iTL}b}-)I
zD*IICY97WC%pj@pdhBLx6p10lazC0}86V2jAy4hdsqr_|K}*cO=v5oOgA)XcWKq8<
z{~|l7W5`?MAjX))yi}<o=Yz9)P^$^!G<~AleDc!yPWd3JiwS}wj4*Vd%Gtn7Ljf6r
z%k}!G0T=8>6>Sn2uT!yjlAvv1Zcw%I_78OGQrBrP`|mK}aFb`#&nmJjyM9q74$pv6
z1GvqD4y@U(9L3*V29MYK56F7}vSZ&}2S~<SXK6bWM?0dYBA!&gjws81R+#mtuJ=px
zpl*JxEI`4U_*Ktg?VZVlDjBu}X=B$XmTLoZ9A`n@S(lSB=<%~i1q;7KV*HL!)DE&D
z;o-W&_GI+_VjjniS`wu&Q}VQC8NT4OX5`S3E6Vubjw`l}9>Wj!)x52zGB($Ttqr?x
zXRxiA9x~;4$5JdO45O6Lj>DR6Hi6p!92>C!niq9w=ow)`eF~a)fak=L1kI0H^47z%
zwxQ;UXI>)<zkjrdc+d=pt=|{rR%7IZ(K;4nN?pB_amQs)<d58zE<&cdW%QgSvsMT(
z%Yxh!WY*<Rhrx8qd>$VLSQnMOOj}ubVZQ_<VK{8efZvuR?SK(2$XkaSt_enJP${kd
zTqcEZM!=FztsiIf+&o$xWwOsTiQ-IH4ahldR1{mC#GJjCABJB1vHkEP_=0;DVz-bO
zl^e|vjwPwU{w;{-69@N<GweSDjPS81^y4=Flf#PS?HUfznt+{1wr(rU?|PMNmEQM8
zZv5BVuj5m%wK~fLrmrStky~_(udRGB?UXppmvP1|e{pO{_eaS?mi9Ul=j-mmw_O<U
zX~-<Lzl2nnIbV0wU}*y^kA<+5A^H@Th-xtE02(sF<;f~oHcorZwzR)BZFSNod2tVt
z>7F$`q)mz7fd`U~&!3Z<U*L*%;>r}#GASbO7idJBMseS3eO7L&KNj6EJWoyO;q*BX
zE=|T8gY~I^Z}d2Kc%J9EM1maG`GkQ+aDWZj0X-z{So$;N4d#llOrWyckx1#pu63nN
z2$`20o_B5Uo4}Z^>^iO8#CP`@zP3aDo4}ba`Vh{Dq)0<i;Ge@0SCWV+Bpu^g&g^vi
zeSyf^FXP=Xe6(940T}t3cmC`LwejOvsIR8`B=-gk`$YllAZ-*r7FYS;FJ=Wl2;b4>
zh$iVQeWPzdJnsg$T3hmoZ^VU16AK)@4fbDa_L6TZA3rRN@m5$;fA+89`p*@ah%SQc
z(&bWMzmt7*9Qd^DjPY_6XT@yKLl~?n*jkPEhDGmZhPs0Zm*ZvI;+bK*%JD6LzLOWP
zijF7Z<TpRbr~g*s!g*vfmXldT{P~-pwl{$44ch%iZ9R5Yvp7#xbD&u9ZVP>6qWHM;
zrlBdG0I8LOS~GP*D?#InTZa#@#?PQDk-$~zQFKP>gpdV0>7ZVGh^G8`2(g<ae{YG>
zXY4$`393Bk=aEdYSQjr|H&BO3h*E}tq3zcvd-2f*oxqy98R<;Dtu2XI<6NICUYg+%
zn=UUw&{kiUp`pvbH^FRYXObCw)_t}G{@Daaka@#{q7teEXtJk?xCDA4d7RtEP`c$Y
zi~}A_HIqFsBzFpJ>5xm=fES?ayGfS!vCq{*<~y<}&D4@Hy4f97>;}ONHK)<3Ez*E-
zM^`+hCXrT`K>H&p^1i3f&<l`tCj)+@)y&%qleXV=hvJP_I|jG!`x&oT^wZzu4wze{
zeE`A@TbB^h6x$^cmIc1Fc6U{LeG(j{gin@Y($Oea;^`6lTdF8~pdO_4a*amIU1t<1
zS#GcYN?ZlwF0mOhr24SF84}E)K}9oUNzyG^qmImaRC{en8+2L4G&&vj(m~c@oj$f9
zM}Cp%j6GQlDSu<CxMcg6V--@LL|{h<5Ay3_+sw!hZPRC_9On-$#wd-d3L}wb%I}g&
z;>!3%U>|NTG~(a+;Arf^oX1dX%Hh!LLguTLIdDhC?Z}aEB&r^ac&`}+j=X;r*+%U_
z|GwP)j0Naeii<?D-NDY7!{!Ei9&6Q#shdzPJOEAg-ZjOac<)&Z|1X-{-?wH9ijP4-
zcSBzLvxi|`11s{M_7ety__}cDUXdGaSbxGGWw?V1x#oWm-?c=qM!hKrt*oS^gP9ZH
zGSh)K3>lFlE96Nb4SLgI%_1>W?YWc0ec^87HT6P!-f);$2&s5LLnwXSIwIYC!DCS<
zY1n>JrK<7=(}(`}e)d*m;V?5uQLH&3D;K`z>W)|UVfiNe*xeJHEA7)p?20IvjE&hS
z2x^jpq@}}P6h@2Fgxwp)ie!!!XJ}=0m`>Q*+H|H?+|@xB9)P_GF%?FW?l{cqvit($
zu)5*{54+^qczqW5Afivj9k&G?pV`2bN5}g(_$Iphb-T$+j<Z9FrbpY-y*;2pn6VgF
z@Cur)J#AMy#brq9+K%?3WiMvyU*T#m_OU<ab0<%yZ5hDJ4SYW2bC<;XW<h6N&mRX1
z;Moj^dl8iPEZ6|@aSk8My9pNeJTT`aC;epn6S&SNIU@LSG|F@j-?p$M4hhPTr>qFU
zQ3zQYMRH6&RSsAaDi?lIFSXo%CQP$UsX7Rt045i{a@SoR1}6+u8X=lZIXfV@5M5%(
zLyJtKSn?>&V|75m%|CnMFLIZuQK-`2<({VPA?{%+TA0wefof!H8r{96?NKWD!LW<g
ze#Rc1q)@Vtu3Yg(6gMWcvJBSUJ4{CSYM5tHK_w$Kli1P24aEU2w~RKXDCV(DsA<rA
z9zKQNNItfI6t}=!nD+o(i+NMTJ!F6LXL`MP9!ZN?5mru)G?*--F3N^p<c)&bCJcm7
zKctib+43f>Kq3lC2FipP^qp9usdWYV?aE|ZgS?1gI5621n8L}$*Z<7}9xh99(-2h?
z>Ej@+if2Rad7#b~cqZw~%CkM7YO=j?4xe2(7dzB}5U`_gtg;nbxF6w4T<}z@xE9X|
z<160fm_<fbB#<ocI;`wA0Iz|W-uAXO!ZJ3DB!jPDJM8C6HP)%0X<n|=VL&$_bgi`H
zDCTg>eJR@cGqoMXE;r%(f0!=^3bG5X|CK8C*UrWG|6{kYa5WLKwlJ}E7W$VRhnVTV
zOql<Vt4rcCoi(_4dw~BJS<PkS3rujZHhc;+qU6eJOw+m+YgY=Lh&L+YD;TeToZxh(
zxQGv7DtB&14u{jr?~k=xJU#&K!BtAl_M7||EZEvZQ>-@5c9=O(H_i5~L7q_4gh}uA
zp?Z`IYKS+8I3<K)2D)}e3HYq{?eqN-Zj^#VL9_xLKWQJi;?xnP(0;vA2j}5=@EK|P
zYB9yAwG(g3Mj>96<O>nf)5~zP#nC9^Aw=U}L0<VS<ANiP+VZAe5gkK1h1zqHGOKOa
z*%1^?>fQ0K!av&2FARJq!gn39DHA2Kx)FpdO{k%?ob9)UD6!9=w7B~O3=k>%nU~!U
z!%`4aQB?GFt>(GQyTmk6K99Oy6%4nUcRJDZt_=|Y5Pj3E=$)zB`R%fSL(E9tqx9c?
zz>7<K<-q$6)DPb6T|#DiuVN|b9iClo*uta|!lHpLb7$zPriPlN&_H~gM+_8<o8B(1
zSgH*7(iMG7k8CB#As@fuY7Mh&Nv{5N%fE7d-CyF=!@r9=!g>_V#upURSNPIUsX??=
zjHw^$(rA0ab$*yAB7_$NGRUj4)w0XB>=kpXUSaSF@f#}BOx&tGNv51{L}c6#-V17&
zleO}4s$Fmo^owH6d`8x|Iq32o=$~G#9SxLkEXZHKo-zLS0O0@jYW;I~{yjP~>K@wI
zD>y%}Yw;Tk#QwwPi}{Ay`1Qf@qo9~1P?*zzGWcMv3^=Y~I})K7oLpJ(Tb6WQ=2te%
zFT6@xF~@}XH4&RjyRSa$Tf1RA%_~oTOw(onp#tO{!anbJw_bf;Z~yq-vT?r;62$?Q
zCq10$gY1%oYK_=uq1&Pj;XvLD>oDG^;veCHK)y`2tBv|Vdasx5`*wT5?gqU^uKXFk
z^JVbnulJQ74MRqTs)RctGJGqC!yEF&<BbLLego#c7z%P1hXym|uGU8YHNmDHCcuL|
z3eV@Ml%I_c1jR<GG7w-Q3>6!`C|CE994$jp-dAXF(jJ8XnYv4l9y8%4IARKUs}98U
zmK{Aq@dnUKzAp|;c}t9@qf!s)K|}><v6o)+l=jJKkg{9Ssaa~l;W5YTJdu>wqLFe7
zEJcmGa=_3_kS9J*9K*fx^!eMVn2v<>$53oAQGWdfO4x?W@)Cgdk2MuMsu)0Ae!y~$
z=<?!ru+Sw~X_+nbhAeabvlmxG{i$Us4o*>)zVy5C5vJ)7uMR!t>io^N{Mbr#02!0*
z%jzw7@NaWvH+SML(L7r+bmj^bL5F&Z_F5A!HL0c1(^#78Eg_tN=Rk+BRw=0TOcWUB
zr{D8Kv=~s-KK(W^;^mULq}oHp0jlf=?8{j5+Ff(tV42+&D~`{_y@G6~=bFOwwBztw
zC)c6B>rE5QHC~cNqpukv26^<9-MSVHoxV_>i0RD5(n~rBh8DMwe0VySNC=Nb0t#8J
zVhMc9SRc335zsu%a9t1rMTZ!-S&U!XRIN)H#crG2EKJA4yEp;J3k)UWt+C}KEu;oZ
zYc(Ril{`6(AlM9VTN8U@=7b#MtV@o*HkSBKmku&6eH8>+n5{P*dM22YyzXHjgxqF$
zbTu&!MGh?Je6KW`L<D0MXbXsewrgr{;8$=XU6gK-P9@0aV1M*IH%gzAgbYPzr^fZB
z_|<RSV73l70x-he6-X|!W!0c=i&b!!jlESy*WMuOGmGh`o$qBO+h_S?>rfl6zx~NO
z2IqE*4QVkcO9`)vUfSnz$8(DZ)g^<2OPG{Ia_v7r+7F?NCL=MjtkL#pF!av4hR_zh
z-1`UwB*?gPsnv00<Js0psBK^J3Q$nY5S|mcaLcNhUTg(+@hde{vs<Ch4}$N0BbUAx
zFPYF_uO8h$Y;I~otb9|nm${RTrl&!jQkfwYghpD=sm$_UQxs4I&m;PYw1PQAo0jB5
zOv^It<qVG2XLzC{%W@qAKUYC3#7L3CuYqGpELFd9ah_Zvpv;&nG@uHgs2y0MT+LS=
zVpgZ!%b<|<k{Em!zsilYEz}l5Z4pmrowMRKYy2vb4S$b~zO8)2?WH>cqx22Ot9WDZ
zEi`2Etvob)>xg7&H*|GW8+Vr+`5R$|(l=OV@+mrEch7|igCckI%J`js825%m6&}fV
zL`V5e$=&loO`tilCu|<sgscle6;!C1Lh>>7dzaB6ZfbBstZce|avR+ba>AqslL@_o
z!YW2H87tx54dthwiSj$bhH_K*^C!fwsvWmZ<sOf_>X74L%<rBLWe)1PDMGbpd=QFo
zkBmf{b?8s&!>*)}E~aaK3(?S2=TfR_%^rAoy9xb!NO=H%b|&`F4$?fLEj51=jMO&r
z&?J6O`-p>e88vlfhJnabBeL+p5)&e&87`Q{q(X@{MVyG)sEUyJ26LA=UE19PQ)Q3y
z&yyV+SKEXRFjrVcx7tyC7VT*Df(F;IvC5R<Hzdr|PIU%^&niodjM{s%9;X#jC<ekz
zt>H!265r={h1Z@m>t-vv6>!&^PGdw!vW$qCRDDrThmv=JjFhCt<5Pg|&_b3c#tDru
z?U&A3-zl>-Q>$~3-{{w8w8`mfcu8=SELwf2!?T~!AfldaG^ba@Q{3aI315rMXon^-
z;|oi}Y^xjO<OCiP;aXH#OTek61KfgCndclCYcEI_@bC4fY`$0`^DNSW3~PU>#%rkg
z(p$+3_S0xt?O2O@SKkOvJn*##rRfJ><j&4h<|Qpb!$Tsu!kx^aq{(S?=T6uvHKEm2
zF<{b-P20jN%Q~aioX)%kjF<MBCd;Kp)-0nQiJo&A!6r+rGMhiaejuXVMS5n+$U}yc
z(cx=Zu|X1*nc$b+w@fmDELDb%r9QMMZN?1dkocCR8PmF}f#X(4%ZP(vAV;(^rbAu&
zgwC~#gV0!2-`I_D1s99bN!@;&EXEhq3ZW?SzmW6AnHBW4rt~<>2SExijylDi{dcFo
z;~qf@L7q%q11vt^y|Fi3?aP9=s@SEn=Qx5t36Qh>xq}D6cox;%FNY1FSnZXQg4e@k
z!+(75d!!*efZxZDwzWN=ohZc$oSk?hw<n?E1TjPEvi?|VozTyA+?5KkyMa5U!5Hkq
zpW=xukVlR<Nc^Fnt-=+&5SW~JcGim)jJ=}pAUR#UL(J?!-+>kej#-x|lbNfXEWSzB
zF(d&TFbtkr_pmJ>i%D)y$?j-pJrR5Oox%;I8)8GjmrEED?_zR-fE=R_P$#hhKAT1#
z7=pN&8nX`w@kf4eBm_}bUxAB8xBKUK=??>&GdPEcl(=qcRFH15rNxC5`E4?tL+QK-
z2x9ptZSF0>i0!hGKSa;&V@Ym8HU6B-x~!Ju-<cIEN`Xu*1T&bdF#{x;=Ydfx^~Qaq
zlvtTkN#+_E_rfh<G-Ql6Yp}10#^J@imhSTMpnR2F+=(K_mL}7^7ku=b9)Q7^P+Oc}
zTM&bkOjxx~?O0P9Vb<l2mf9?Kg`B?D&3Sb{X*43YtHT{FfqKkchugdKo`rghW3raI
z9eZHLcxEb1JMjnmmXHPstk`#d#s^ZG&a#JS(E;pZt0M((bKI4zYb`Bk!aQ^A&RE?W
zwBM1e-KvLgW4d<Bhjc51bxSz41w6ssP3-B0d0lM!gZ}#u6aGq4s4^V&`XOE~umYd1
zP@E5N>JbUW<;4`2gwun`u*n@1FM(0o^s*!)Xl{@<;#4U&5jem7F`+-EAfcEyI5E)_
zTm|4<Y<#%f3OQvbRaI<(Bd|&bpm&f>x5&!%N?d^{9%PkV{we!fz%eKOYRiPn^}WKf
zGa5}DZ)oR{F0NFAKPick%Ed~`*R}`v+0iefC;CYSadg~bo-p@!*hfGdgAxqMF;j*b
zADo2*saVg!dr&x<0_X0(?#4v=?6__kM%%wX1jnLT9^JJg%*gUA)iBoGC^9jc$0>kE
zSUlS~z_l_8VzS*}mQr#6vil=QI4Bu%^(OT6=@HE!CF5Rjo2+V5lFZE3-3zs4afAy)
z6z0cs>=Q^=Aa7(J$%r~b^vBRR#>nK&wvqdV!EuZs%GB{mSb`tD%|HjP5ROA@<VkHp
zpY4nCZlIfIpsH6HNV6Y^u4pCbY)m#){3n&{Oz(2{Bo@>U+&_V43LWW-^WUb4YQ+Ej
zMC`wSrii1Xo#X!-q#L7Z;f1A!!iz-L*_z^RYHg-h>WZqNksaJ=Y!yx@XV|hyI1zh7
zJ*kd4l_bejX?i?tVnLxbB^%I~lGBKqNiKt=sX3@=e&Dh028kD7_X&VI+krXNNEG>X
z&}+8qHQRB^^SVvd_nCL53+(@O_Xukq0_Qvkb|8dH?zP__%MOB9dO*bdsDO!Ec3{Np
zoh=YJK*qW7N$lenDG)h;WbB(cfF3j#|E>Xg1kEdUdWMm0dI!STH?AKzkT&j}D3Cdj
zHt`7=Bmt^N@@NG;OaI21v8QjJI-q3in>4@yx<~kE0eXg^P4Gw=1RX?~v4*a#e+Qkh
zhG7n!OY#UBL;=b+@yQxQ9dtJCohuMK;5P0Z5HPzh!q_*ZpE*Fo*f)khxBtiZ+kXH$
z2ru!S2oy93FX=rI%$KlVk|iOWgpp{Bslc3^r2nN}WfsnYgodjKZpN5Jj7t5zpjw4m
z^E6(QR_kP0TY`_8-;PE;2fXr9oD?xV91IbCPp2r!5)x^2EdHW`q2Syd9~*O`7;tQ;
z^4DRYo;CFd&RU1!=;47peY_%5GD9-tNFm_U%4uPPxoFI=(#1Qo3-8Etn0<tVi?ILm
zV^pYOhB0L-c(yWAQNX#ly38`!k<r*t!Ld2HXQM+&Ol|#sIVOa0V8fj{ab`qtVgf%U
zyJnnA*_A_v*UHo4gfeF>tFW!Ec36n~C$3TwpmjNizOZ9Lsiy5jPE1Ty22y~0y6c5#
zu^|Juzd0vUVk{_Ofj((&B<U4GH|T-7esC)-O$C$#4-|`Z?8s4raHM0`85TI`iZS99
zybOuqLFc17Gjc@ON;u}ptkv04>9R00{HYE?-Aa>CSt*1jht4koV*fNhG3Tw-2l0u6
zsLg6t<@xDP`9%sWQ(P~pRY{VaX^@u4nl+vf34l&$u7aX8Ru%ryCYN4ku373fn=P{z
zL6J5P^d}fvuJRVrJ}&EY&t}E!#VHCkfH~AG)cyF|ml$YTwm$6EMok0lDx2w<9ZO4*
z;1{A$3wAMyyKAaoK^aw?F?F-iejZoinC=RW6vk7H>pytC-zKLy#AhrsjdvM2Q!+z6
zYpgRvW!)Y-3TU3CBW&S1OFVL`TLo)u>(wsvIDdk1CQ!E<2?8YGnBOW*OWch;#GH_s
zTuEyrIjZvL&*fED&R*mNvvC%rOmL9SIq0_K`nXK!K9O}%^{*UN?*>WSN1*J2^E?KC
zr=UnMX$O6D$@vxh0d6Yhb)jqYx&5=09n-BOn_NalHPKTg4(uKT0q+R0IaL;>oFp~c
zs6fOP=*(Pr%FdDtT{p;8BO@oW)EY`t5>;L4%S<*SRms)U#C;<ftt)EGuVRIwFia~B
z_t|YyqB4inu!!1bx}{LMip^pyfYQb_I&0EVX)M=c(MBhvG_t2F+1pIGWPHJn9v$Un
zG}auQAXQgZWyCs+*_kB&21L(*%uM=xWGi-!>!#-ea}}j_bn(VHV$<63YOFHi%=Gst
zUU$cr#uF6@%tSbdkhNpi_Uc;jv_(0uVJBnEsA5ZHETVLmgHWy#>$OhYug9v4!j8Z*
zsm)s~x-v6GiTQ*IZX>NYayaU)Bbw4(#)>YSd#0MfWwc8Wg*`x}5Z>%HTJ?$=(O6s8
z6WU&4hd_^^t&mq`G*cw==*dF6m_CKxX^PA$-NlkzajfUhtWCyy{dE5s^uCrx?Hq(c
z8+TIsd`UW5p-rjL2*O0h5~NTmg$(660*P6p2vk~TTGB3LtT_M~X04hRQ9H-QST|8R
z?&R8M_iQ+phiP)(kBvo5Rbo0z-p1xF5^XKm>xnPPmywC3wLMM=EID!R9_m<gJS+>A
z^$bc<S)A%Fd!PL+Sz(;=UPUh>tEf$f2IH%jl5P92d2C_06%m<HLO*@GAE7d7!d*6)
zt;i5#Sdou*AC+x3?ok)X);WyU(74S~rky!3C{NP#gq_cSY2^)YGnUj3iGkc^d4EO5
zuhr_mW_&?~nblcthU5JhiiP*6FVJ*7G~>IAYQ`hY$0*|q3_2EfJ@msSci?w{6<1T_
z2KkHO<S;$zh&I>NVQ{25Dv37N;l4WROq=`GaC8KU){<7XBi)7JtnlWrIm!dgOq&_p
z0EA}}`(EcXe2(SsRc?DOuHWZPFl_w*008CNN}RY~jtYEk2ufT238XIseUuSbo>tg*
z+J55|U-WzU^<{wSkBoU2NR8SXVGMv1yQh`yoj(<*AAo%^GHEkER?23d(-DmMYnv`u
zT;B;N{ZHxD{DEHBUXI!o$C{C<KYi>NLlz{Va6VjNJ%FJ%4oH&$tveGPpoVfNrdWu1
zNZXw@oFfce2PUp4+~n2|Cg!J)%{VRj1~e|V92<ECKZ%7hBZS+2K@uikt(ZuT+LE5y
z(rqO{6m03t%Cl<im4VvY(YaLB+jkwUpB~pD)a6IOLAsTESy88ja+;V6Q$5gDF!Jt%
z)om5k(+bMRC8STSU}L$*rcRCB5R(sA_mE8pfiUM0>krfX{c<8HISaEuR#*D3+h8{q
zh#T!qfwU~pwEYCq0qcuNI2IVzEKsjhP`*Xt^ns$g8_m1OH21as$m7TP%+xN;;#9x!
zU99>C%<4mFx2oj_IgR7!VT=wL%lEYHp$y&GrxvMPz40oJrcfp;p2V}X2hQ2*vuRLL
z4_^|y<7v`aYgC5cYY(Wh6xp3Z!|i+HU)h-Z%c=-KepGfx%dWE5@La@mx5jv7pd2S?
zTqJY1Cpp=hBNaP_X~*wD-C;^X*_%|JBy)HtKG~ad6>AYxBy)MkTpTRZ6<xzBiDz>U
zR~#<>N?;?l6OU-`@MW-0m*M1+xqXvvPM73myZDlcXDaXLWq{e7w0|XiJI8n>qHM(x
z+=)lGci=KvM@!}3DV?^H1hP9r6<#B}7X4&l94H6M%GxwA(31?ZBO@$y_#28LDih9D
zD8<H|HIO|M&R!_1#7nu9f3GJrP*_Qp2o)g#9f82bZN<*Z2k`-W6T9F$E9ryxYX*IT
zQ&iAJ)m1`(z;{&Gqw!S_$ODx_eg$fWAOz=9W(%L!4Dx{csD$HJ*9vlbzyw!4ySYKG
zKAcH~%G9H@_UpKJh#CCK%cyY|X**DA#land`Xbhy%c2Lb+i!ZL{2lB!L|cI33T34q
zw;x7uV7pE=Y>*cp@-;{e4HY*CZ~(zh&K)D?9OYHA2XuS##_P_<^5O^ZPwZAVPp5YD
zmtijW&lzThe=^Kl#ST`{o&+?>e@OTdC2`>Gk|Qbo>ygies(S5Mqk2+$qE@fG(Yli(
z|1ZNFy@M~A8D==ab+y4^W;z?|_x<q=)bC{dac93X25S4(9-+l+dlVZ7dgIxCcEBrS
zq-Am9if(y5OCZ!^Cz@zrk>C8OZY*R0_eM`Lci9h~i|bf5c^lDmgP6kPPY~Xm+M4&k
zop!u|iH;Ta$%GaGjWmEGCxZ={WFi`NyQ2Q0MACAVc2;9X2cf50FbQlSFl==_yB{9s
zk?x2Smf*^mnmU;I^Y$7lrpWF{cT=VAq^2Hdn+w4%UVU6t`EZTl%?14YDq|4hT{h{P
zsZ?T<g06T}gIY0>63Zu^mYxs>27p?Ro*xp1iwoi&-5MtAPn!#@K0ujr&j%<!#1v(E
zuA3d|c_28>ZTIZS6I$k1OqneSQ7B?SGZMO;Asu1g#^_gat<9be98t2hQX~#V#ROSZ
zN@l3eQN|F&MqB56i!|iPmFZG-zQFBCo`=~}Of{1v*A-6<gLc}r*WbHn3Y%tbqdcny
zZVn?0WREdrd{y#<bQcA&&Nr~lU`bZ)mtpAc6FR_WqV6jMtu|Z2H~Pu!?)qVh(h~YS
zsXNj#*(GqLm=f&URyh~4_s@}uTR~Ov0RHtW_%F9C^q+|m;{W8CrA$2jJwqj`T25QS
z$lu0XsWs#h4s`Qa#qgS1vQ&~#A*B*@qY}%UFvAY`C!G$gsft>RjoTLA&~|spVCT%R
z@fe|Gv>_O{?gtN(xBBc<5yK8S5nMQNbGX;Jk2zPk7YluRzF_+*?2x%5C&Z)nA_MHC
ziSqU;11#FNV=%|VM_Pf$AQ{OFHS?C>C0UHN6zKgX0+4~z;Er0O)q%<DvIjN-y9maz
zq6&ljF<#Z@9JF*Z7%&hOgOpukPn1nmo(oPiU5umzo7L)wvuN0Dg-x7PS=wwHjYrGR
zpmc0HQ(8+>FgLOtvQ2-VXRMY{?#X&_27Qee_t`oXqO6+&TA61??DK`Z?74gC)J9_i
zwE!dWaGiSViH!LCVh;g&1_(q$cGENoGzxXrp6zOCJJ(!lr8e++vW81QN2)t4n^CSs
z#J*2-<%kU(S@ibd-(3Eo){d;IM$w?8=@lK><czUO*%0pX6>P2Bc{~s7xI?9f*Qst=
z#N~Jfx*}m#RqZm?o*c@iGx5C5jBm(SSLm{(4BaZ^vpiOf6hue%omIvrsjBYZF(x<i
z*V#Ke$hhwlrnoM;3q~hhOx3un_y&!k7|Jx6v+@Tig-gy;-iwH3VVvE3Wd179MgpT<
zl&B73qkkxQ`@<-6hZHdWl8ESe<M;(6$tu`G4k%>yiX)Hi0-!8wZ%QY!>%1j_L5r@f
zFciPcff?vnYAzYwp1bp^um+MMA*BVVQL5Uh1oq^7IH#qt_*LRFA+gekvCpR)gM+?P
zPtHewyLKt~jNE+XXia72Rw%8f)}R5~AeCTJ|BkhuvqeV;wnb(UG7Q5>pP195o1L3I
zv1ptxUhulCwxPC6PS8azN2&;s5E86yvuZLTT(Viu*#Igs&}<3SCDyb@R}mP@Z|CX_
zUN4Ckd+p^7aLr=YkbI?-njlvCd!n)E5R{JA6>=#?F<bNZK9AI%&F>{^L-Y1E5K=bw
zy(vMHb|+WPPiY!LwazK4R;ywv`<#&jQqDPTyg#JbfV)F=(DHZ)Kr~18h;q*+`WkA>
zfeGTxuoKJ<S51lg>_;X$&^-%?!Bc99nuwNUG_7wD_)!hhu=$06a1?$4?ZN^^;RC>|
zSw>v*1%Qx7m<@iZS5)r>YnW)=zuJT?eqPoZ{~aYl^bT>sC>-f40s3$2!Kbt+F2Xq-
zdyF1~AlVQAwXP`U9mhfFvD07zIOFh`#Y(&gVi7x5C$m60f@TU0dDP~;%#&Y-4a*JD
z=cyJuqIk#wgzUa#mpw^#kgW24q>A~g1zf^;@aImLGEl(01w`GxcloDAI+@UvZ$R(5
z=L;CLB~7`;hhJ>(x#x=)Ig=K;`gU<pSa{50UkHJriQ$RA3}Tk`0YB7SHIn+W8@|Xr
zpdbHeo^od&d1l`hqq()&d_G(c)bXsu<ci2<)IQ7JMmaY*pchV>pq|}gLb#DT6ouni
z{%Mz^_~Q;dREK?g2+<V|$6FZ<*igX+`0m|BmNM&sW$+@mhzROl=HEQ8&4vG2naQ&H
z`ltSHdItaBtegK(Ze{-Whpa~BT6UQqnWw2szD-#JV1b<clClc~Ls&jRu1SC-|Fb{-
z&53--R>DnklXhX4>`p}bvn0ZQVHoVLAlhxRGD{E~hWSF;>$c;}cRD9SudnY1m_GEK
z`+@vwfYrcoyuUu;vE9rNo`}?OpY%c$W}A)PbRQt7g{ZrbC_7U-@fJFo$+^eg&3MGA
zB$85wV*oWJQD6kgfLtiF!-TKgv7zR<`!rnK-8Y5Hx95f`x1J97G|SLD&eB#L+XP)!
zpyaw#=R~v#x-xn6F8Mxn4c!sNPl(Z(wo9_ta(T_<PP5vJ_(Jmq=b$E{f8|HUK=y3x
zS7-ur?-<1hc7q4BPlIri#k>?o#L75arg><IA_vU9gYof_w)@ri_4u=jxqe_l*m~P=
z?0&AiN^fH?NsjqszfkCBrIrezC2;cbpP_Uh2_i?HNMVi`e0;EOK@5wtB{S5AYFN(|
zJK$LF)62kD;%PBw{AO*a$@|ZF6&1tscPvm`4fkjXD6|EW0l@)5wp@B{zM^qzX@ku{
zXj7K^>=3K-GFrJMAm|Wd9gL4S8tS3x3eIeU>J?q<w{O-ugy=Pj9{Dmc$+RoupB6}=
z*B^GR;+F{_gY)u9bCPmkMd7Dcf|*)g$Fkgm((%-%-Zg;H(B4gBa*|dZsS<My)_1*P
zTe$;vM(8M{BIoIQ<uMhHgi3YJjG~bTOwe;>wu|Zu{!;mQ8JKx#9N9L()Lq-B_!mSU
z8A2o}&g%jldM|f03@^M5I^xOvv{6?;Ks<*GQL68oVHE8U-pTS5h!Ts_3)+RwUA*z0
zhCafkFxJd<w&vTRw`~1C%Y&<1#$B>?r|k;vlHEWuy0VBdmQAnrv=U30%36V^q%m!V
zpEk%x@31$cf6I8tLEt&1)DG}z`S;?$;#OY>e!%{@*@sNI&QC#p{W^g9^-JbI+wA|>
zbYNg;ZSt=bFJt0tpyX`l_+N&E|9Tp#J4#4u$Ui&8#zN}HSQVNgB2Wd0mCc$8TG0S#
zK;;6TmQhot5~yrl4sJl^ebr1~a36|)z}^m{m{hE}mU>_5E}jbT=yEK~E}yccFaZ^(
zg7|NGI9_x2I9}a&Y592nym<WzbD)dWNk2UB#;!XI42*IRj;|q`V1`R`PmefatX&rP
z{`3wKQF~u!!L1#;!v*TD+Xu=u^JpL7;;cJGUz3lI8XES7eg{R?A8GK<g0uz^3FvIJ
z^X%pKGZoNVPCDstObWe1H<@F~!LI<bU0_Tka$L;rpU&E?=WpuJZscZSyX+WAwndf(
zaFD?_eW%!Zp2_Cd&TZ$hLGiHD)|dO3^te7;*|4x7<jLw~%*ma$R7z^vJpLV=I$^HC
zSpvaasyznhOqRZI-H36D1tlz}9*dHVDE?%sO_#SUWzDED?^LTLiCQg^q?0R`TY_>i
z2WREO1elPVMYJV@F~vYOHNvr!wR&cq*lemT)Mn;9cX*3pKuoSKJVfh(h03rVjB&ov
z|2&;+gMbBCdCFdz*66awcG28Aiz5W*yfu?VH&S?2?Md`ZY&sVeAF&9oC$PW2YD=CE
zEL@{ST6TD0GDHo6%23u{fV0!CQhE*^?3DpN!epcLdf}C22YPWvC{{-9sxXyDnNdtD
z-rThsmA|j?DB##>8CuO|3bfPCQIJOLlkAf$0UDO;NJQ^)8{Ktm{+O2CC>^@qM;H*h
z!rkOTmZuF=j9jAhm|C>8iWBH`5l35!6?*Z9CkzY>gt3P%#+sC*nY-OoKOAPb$##Qj
zS|Mtwzz1mmmsiapd29vyj1ZnAppRB9hH86>A=^v&`KT_+pL#Wb2p?d|mm)C{j3~;~
zdUAXHMVG~?R6O`ijLtJ`kXu9qj!RE7nH^Zjia?8P<%a03<OaIP<jA&-jU(=DgHPl-
zQTu2|gCutHH~A5<H}!q_%}4FJEFnvdciY+i8^VQirWj&VL(tBaZXrD<AV^+?dx{&%
zH|Y`bqPU)7bqMG$F&^a}3EN87H@}sq#1!L}%j-1<MxDFul9ko@wvk$*EZMr>JTq4O
z8(YX?md!LNPy4a#1{<tySe4wD(K4w<?xqPZqS@Q&7~&kygQeLW0=1_zmV)t~a&|Hd
zCO~n7EZb^JV@%0{%2fy4SEQ}D2`z){gCPsMTVxP-*Y5=(#-lT8yZ$kZonMJJ9E~!3
zXKJQMmSJr2EG%vMm;f(}Q_qw<t}fsX1M`>6YtS<Uv{;#19fsz+0YL2F0c*#)bjq5q
z1OivSiQ6Q=o&xmo=XwI{_c(-VLsaEn(dLAo=#X#?!%EAymJmP6Z`yWcT701&;)Xr6
z3q{P|0_1&#AbkZ$eMV&8!vvoqc=2+GIlg=GagV=xF2u%xbYT+o2)ZS%z$JDISz2H<
z8}!61PL-Y`>JWSaN2jbvkC=h{h(gU4gF8Lz4GD)=x;e&MWAFn%D!^?33EQ!h`9sf%
zZ$*$02#tvZaV~|MK?yWP*24}U1se}VaXJvZ)Iq`<<(JpU*Hn^;*cDW0=Pi2elnPre
zATsIr_?eM>(LKmfkRJ*|&`sNA6~oNK2wRD0Ip^^?7sxw_y~zZa=g){`C3;FD3*3lB
z&9w)*yeASaOX{ZLf9XV^H1nnaSL%6-yx#%a5JNJ+w3xmU6225j{1(ePA8>WZKULLX
z86AYTIUc*HEPz6><x~?|_Ql&WFY%_3ajDMO81*2AEf9gu7lK~xcdHG%%`cWyIk-&-
z-?%cpyhS>P)F@;h#hw4*mRnf)ko;j=M;Il7Sczt}u0!9J8Ro|(;fzB_8C#&1UEB#>
zpq15+V^=9@$qDC)U{dVs8cjhTgfW6#gc&Aw`6JmuGtco-7Gozi``g>!J@o7w4|gI4
zd?0|gGTVv*mnf2Da?Qa}OsI-oZAf72!#!7t9<>H_b>kGBIhrpmI)#3fn8;TnE&2>S
zDVZsYGKz+L={p#kjDcJ#G}rKhjw|BB?|*cVGkDvI!T)6zcESH+K*jj)tudpbp@bv=
z{|$<oS{;Q?IY|(hAB;^+s0(}_j-Lz=ho2fZ#7J6|m9uOr@GiouRl@(CpIQ$0O^mmk
zOQOqPq4mID$+)z&G`6<Hvy<1`?Fplg&Sq%tZ-O66093|MeH0zQEDCMTUX|*^IeXQf
z|M%p_N8XvzM+mwi`w0q_&Z&#Mx^M>QW-`!ZN>RddHMxnpv6iSCziO7LnC;YEmVQ=$
zq=+1Ln#o+FgB(56F_z3UO%iG_?+A+4LDO;Z^oIKt=UK<Z5)vN>ecECU$#?Z6B@%yD
zAGptF2$+Mkr>l@Stz(KFc`l(?CBAV#@>bH-ypocM3h1mr$Q0)yq+aG04OWOV5g;^3
zB#@a1Fc+>^Z)9{HV^AqU_S%^nhh&s5gYZ{P-`<U+$785V^x}+NgNsr%eYHr0JvHRw
z^)6!<>N$JJW;$H^mwRYh6@p@m**Quu3!i96yc;AgT&g!^omv8<0h~yM<b%)+g5GKB
zR8OFb)j>ji(DYv61V;-0JkzF70zJA%$MKfoq5|CaJnFLm3Q<cG#GI?i$UUTS0XdqB
zHseCL1JWOT%1cI)jlamnq`g6EUs_veb=XCll_5aFGEqSjR_Jl{Zy>~vkuN&!ms%it
zBEn_n=8{~wlZYPghIMa*-xz-mCvQz;BWvwyXdw7$M^`Z-Cf>SkS+cY3R-xhr7mx7L
znPf9XV^U8L3W78@4Og#v_LE5k<YiZy!3hc4$W-2xt3K||-(YR#H0b(MQ<V^AAFK1d
z@ULMTLd)P@lreE)y+D#x`A6<#i_(@{V}A|o{1s>mAR2aPmJ3aX;Ns+v*XFf_T<O}v
z7n<gbWw9q>UH_V*n}Oe5%aoT&SMy6)bNbPi7cs2YGfs*YB=$YUt5M(fYl3My^A<fa
z^|$d;UBoG3T&LlFa1h&Y1<pmP9aVw~%L>g1#h{H#v9gUmzrplfR%Mjo7I4bnB?&WQ
zkvKhFo-WuSN{^P!BAfZ5Ic4ctD*znJUWgS5+L=Ke!pmJ9cl~Gb4qfNJTo-(?8|?lG
z*x<V*%GmxYuhA&~dl%w=Tm1eO%nI4rIyoEIIy?RQZKb3~<SnftjEU9Pn_3C3@BG3N
z7au1D5Il}&w$U`ltf9Guw4M-uNtM~GY^-^X98Ya90qnW`(|gO+Lx&GzvswI_l6&E^
z_xgqQw6wQ$Vs>jQ^zL2%l#{_`$82|cVR8F2$McG?@ceYkfLYcSySO!ae*F{+)10x(
zA$e=K=4O}Ab;0xdtOt5;>}GfFhL>IvPkJFt@#z5BCm4d4QxXrWWC>7amg2Fo!t7B}
zfHkE%gGM}*VBY;8-DPmHU9~EK;WKv05*yy!Xw}Nar|M)*%XUt7A*0|xlbKt@>|h{1
zPT81+DlB(Jv4nbl*k8UX8R#Olqgt6&YO>lQnMEfv#fZ%fqM2d=g_(lvisGZ4pDQ%D
zoj>2a(qjAsd1vMjvoZcjgPnVf%Q%T4EN_2C$iVnpB7jzsS=#vYI8afUevAiDr?C)n
zty`I*|5(X8KVffxpO0o<*|4CT5_&QPk+DcpghS*N()qpe@|*jW<~336SdjMNA>%~%
z<FYqx?!i={`C*~4x=N7%f=eV%2m{zO>;%L~l#zbm><GoU&|XG{h>HxZ1ldO*e<tE4
zo;B##gJxtedKoEsp0z;23Zp3%#Ydoqs`|2CBv@(*2DiiS+bQyDe(mHbMfehp1(bl%
z!FiLOaFaih(@mYK6eZ_X_kd<D8kAF}9;NUnr&i<=x=C3P$gfb%Hs-mBwdEQm#3+Zt
zC&oexC)pZ_PmPGwm6{Zpq80hc2*Ybf5*^jS?;oR(n5n663+e3BQKhFx?CJH@IH?L8
zlhu?dRGrXl3+ATg{5F`2+`~w1HOoB*L8vhr$6Be%Om$OYicd4g0tMl!_-YG9E8nW!
z&GWO$>&PS|SS9CMfY;gzW#vt#5>(_HA;>;qPJ3*W7wf-bOV0z=eQX0_f(ok}DHR+k
zK5F^ZKsiUmmqjlA{+~1)$7MB1NfDLBKUi&9N2jn2DlZN@{m|7$e&CLz5pl)NNIpuV
zU-ad3D77j%xx^!;Ni%oMq#V1%gKT!m-w(u$P3DVaOX+|1zZ?V9;g*j@TrSU0|4Cv$
z)jzL)DRa<4F&WbDI`6K=8en`$T!~}$kfD=AcMRiSt3PCbT8!4F2eT=rzVsbXjw}&O
z9La-lzNiEuEaMY%8ndcTY(oA5q%o#OZ{)O_mEedeAt1lrubJPo@{K?QC#8~1=Tn=Q
z96${`KECUZRHmQC5J_=f-lzl4gk=gUuJ`S4D%xYFA$M^OElfSpXx;kJ%=bAn!bnTt
z@A^135z(QKDO4t>XEGL{vNWjfLomM$+Ir5>MObacw1whON^8o@Wtwv8w4SzD&sn&m
z_^9Dm<4ZR<R2+}ne(LY2xsS5gfM+&6e|EcvZ7r18%NyLZjN!k6<D?nu)5ve>dYy)1
zPJF&R&y@iwGpXt^UAalFskCYm3Q}v@_NY3dj}0dJPFxakgw!odX!zTZIx$PVLcQnM
zBU*aOlBG+<l-Bb3X1y??n!>5>R75cbUAI=T;X#(J-!E^Rg-z|~+GR9Uq$9Ufb-n_q
zGbU%U!c&)Hp;=#H2K~o<&Nk#GS+(oztVed~LG0qy;sfZ5K}Lz0V*dLPv+ntGSRj+O
zbVA|7Df3&@Pi~3NoKXhx&pX+W(DX&fkQU=A#nWchM&XsRNGb}QJtb$22wX^8rSAlX
zK@>|}%UfTx_pNIeiEEB%rt@Hi?dyAOKYzXEbGptW2qJ?fv{;mZ;vji!SK(0vI{<8{
za{jaj^uAMg;jw6QPN@1dN9}F%aN-iZcbyT7`bxt%P|cNwOIJ{jsrcWr-`Fs*wgYEJ
zbsHB<on1M!+Kjvj0tw@G76c~LtJW)KoIDu#m-{5KAW*VA$z|CpkeWTKuGaO&O!veF
zeq`}fELzT1Ej)T?;_-#M;1>ztrN(Vz)8>hXMELW@6F~;bWLm^sVKN)Nf#Y<wn9BRg
zcGJR3C!DU6s22T}-$^!QPLfYJsJEy3`E#3m4m_x#Hg1_a=$JTlYq3kZSL^2b3w50f
zLUMP9o-B!>a(ZoDu!qQ7s$*_}#%-Q54O^}_s$E;ER^jUwO<Vj=tt*IVTrUpL;>8O_
z%U(I;Nm_;~Eo&ltEjgOV<FhCz=avoE9kSQRXDxOC^{6>X?iDqt24BcdibfJ{^{Ye&
zlQ!7w1>nvD`x(H214`li7T?<guH(nW0fTs)TKzx$7Jzhb#syifZBeyIXf>FT*U9J1
zTeavd!}$Ws18fgGeCETBPSsH@oW|ys4A^OKUyVw0m1F(^lO`+SndL<f*i+Y$DrF`O
z_e%yk`hu-gx%^rYDsxb)>#y>Cy*v6iT~&6WJ}1fRHk!3l%j%eQ7a>--v^7Jmj1876
zBHdcuvN}&`oUU#YMm+2-jUcIb7uUDh8f%w@xMEnXb)X_l9bR(}LGR>WQu$VCeGckL
zChMqq8ACWPry~|GL2Xptr5|k;A=j`2+N}0Q4+DX>gw`J!gFh#jbbAX(s$|p;IA3vj
zLyf#dSD6ETAToJzW}9+Z7T9Ou7~NWA=7?oaQR@|ft^RF}-7wK@bT?(|Q_StQXHQ)H
zY4+X}?qp+W0d!~XXm60QWdmxC-Y9RDv2H=H_T6aSFk^rE*Bq$>nXvW1cIWP&_p#W0
z$=^g{@j!jq$Jhe!2JVRlz}R`geUZo5g79YUY4j;3x1h=90-dm@_PNKJ_Bmov?h3}|
z3}khGp>e1VV2)u8ki^pc!aHzBLLZCox64RU>wm=N1NBZm0=cWf-UIce9*YCw%QZs!
z1a3sE4YbPcg>B`~1!iN{1?0lU1KOKyfU<Sm2K2&i8yMrb@$bU^vyVGQ*6(KTjp!YD
zL>8Dge4jKRckouRU*_=Xe8<G@OZujP&4=}wUGT}Bw!{bb`AP5v#r_2~Kv#%H_KA2W
z#ql-OPgkZ!{3-dVH#B<^-wm3GWshR7)AouDQ3jN>cIXDJCRh-g&#xEO<!mloSH`xV
zS;$5TYgupb11mkB*=2F9ftiu-GBESO#O#SyGP@Yc#EiPlZT!`ftgFt|yP%Ga(buo8
z&el7@E`^p0`>okux)VqN{$~{QH`-D8*LC^4MfIzurxN^T)&<Rgu^)^e^118>($`69
z#Sh>=A=p(z_nqEfHLUut8uq`{QU8A+n25WPiM_Lho$Y_~#XCw^D*qzI>L(h#fgx*F
z<C<I19|VB;v?yC(Du9Lh;ms>rpAb{)Z4&<m=c1TBDd?f&`P>cs^oL!V+y9P^^SQHg
z#GdQvB2Kopa^9Za=JC4W=-YemWb^xc-n#u|>Yx`A*sPAK-0d$NUW`TH9WDZ*0U|}o
zD<~_%mx^+%QmzhRsM5`+I#G^a%+i1yGSfM46MkX}-==KMd09BWjf$N|{+4V|T%ZM7
zXML_ZL~nJq0Rq}OOrOqb1(UV*8%EdS(#IZm6n>FrsyQ-m%_Vdq+ag7&dsfQJ)3R>Z
zMwel#B2l9zvqkxI+%~r0CsKjww?}A&xgD(%7IZ*!hY;})M^Win){4#FO37<T3sEQ2
z2*OijHlMCZ{~j}Dbi=tJJ!vPdCcVWg))GmBnOAg~8(zP0B@|t%vPiGg_YD1Hf|nHc
zCV}IlTvTYMpIrT!)@V(QLaUEnn|qU<g?*C@*EE!&OFvV0Q^g~NTl?fo1!4xcD6_$k
zwk%N-G0{cYke@jPFBMY#DGZ*a7Pp>`t|~2KhIZ4(#UK;iG$LWKXoG%pWaljmYEVDt
zOV*Zx>aC2~d9fm;o>-r)r3~XhqR4z3P6ztzNKet)+6<Yh;ywD~dOnusrNL}!)Tho8
zq^91Y1ME_kPVQag#pqBq1O<DsAsu0K((a@(YEK?g$X4d<A(en!L-rjQ@tqZ#2AP0&
zqBJ7RR)s}-kXxt-z-+YLt$CK;kQLEV$pg;BG_$Z9RO?H3xU?4Z_9+I^jOeD6U5l`R
z2ZD4YWwvIJAt{5Zta{VP4{MHE8Cn<9fBUc#%e;z_JUR!loYlyebGhp{a|$G`&z?JV
zw+zHRbAH8fBxWcL=|-C7wdI^6%;HQP6jfYgdy~;?)VDfL9}&yzOl+_e#F9VJ0lwW4
ze$55~rs&ZbDN93402OnEJvRT9oAB`Y{|{yF7+hHxtqrDQqhoh$+qP|W?BwLcwr!go
z+jcs(ZJV7;?%eslntN;ROik6UI)C@BI_rJcde(yuK}HPo3*-w4OK*R5wKD^XPD=U&
z*4-7O1Ylf3ukla1vjRGljBPO)x4cQ@wMx-QP8U53;SAxZN(j47T#jAzL(~53cZm(~
z1p2GS$O#w@!E44{a^GMEcW7VQPdHHg03w)HK~tSU==ucGBhDtNe%pjv8Di4-5QDj5
z-S%_4y2TZRlSof8Wl`w!k@2c#F4az<QTaA=-Oel>45;ZpJFd{zS9SfseV8#SH%VPe
zMCSYWrqSCSrZ<j}yhdbRQOaB|c;|a$utIIPz&eZ&Z7e&ZqTrj!M4iG1K+B$j!&CXC
zn|UnlNcX_&AZq6vJD1pcIL0uK`WOZ|ffA=r`Wk64tZEsX8f=&NWVwnHZF^k?aF%xv
z>|)>A%dt`o%1vgfJMO358kF6d$V-CsExS>V$QrVj?_N%TD?<W`o}yi`x#{5$$Y+!w
zT&b_ca+|?fPl8DXkA-|RcJyJ^c`o4Jd(c-Q>eM!#)0H*Pyxy4{KQQ4#M*-08-!ZDg
z>6Gx{i3A|jgZtejjw&<#-xl|x{a;r}-|&77JO~Kw{|CJPpVK1H)D8H*(0kkeK<|B0
zz}aCUm653pWvo=7VG@3O(@3F2D8*q>3em2$Odcgv+PMsvaY%3LtgpQl?@Ra!j?{EF
zmR&YFpFx?wC0;xnZph{Rm}62;Oz-l%<~!y(<~`nUdVcQl`GDxv*L~`b4nm@cLz|`f
zJse8^_ihB&%X}*E+h~yUbO2PIZC{S|Zp0GBo~;nVKGJO@(A9e-=D9WKFXsG*+$|B<
zkx)ylVhX3Kx~ROLIdyslp@RG%1UPC)dh{rS)>xgSd_0{NOFhca=rIBxGZ&E#YKUDO
zoVu!?4$}kK4{u!7gD4|3VlN8e1R1L(c2gNPU;-u>+<tiCZIYiq%cG7Z^;pJa1ZaQX
zh?0{67B;z|r|_cI+*D~g7egtVHVS?xHh>pHHY-^MAe#7SLu#5{krR!$V4qKCL|Nbb
zE0Y?kI<Lc-Yx-pi!z6;V<g9{?I<FyQx7;6Mt{Ffrb|zP@rPpke7^f@LO@x8nA}c=)
zd0zO=1Zrv0ZdyHq#SlA}RL$ZfoERxK<teeMwXWPW3e$${P$XF;gaEyw)Wl`V#B7(w
zyU5LB@YLc&B103*R#MPpXsi>y+RiKusjZw+nMJ|}B^N}!R~hDH!qqXn5ZUJsK7>1l
zBd%_2onLxL9QhZGQ=(p6a6UFAVsV7ibplnTQ941Q0x$O5g<suXm@|gKbfu&}rXs6+
zsbZ4|QTkm%v(E&)pBdES$YxXd-bR|CTrBwnYuR}KkVPFas<Jz|W+|rzj`s&eN}jGN
zwCX17k4(iLr9{bSQ5z|Z&Bj!jtcGSDJQ})@V&!c@eljHyXv~*_uJmv1MOACE+7R^Q
z8{TWTuAi`)B}dAHmOnum$>4vH8e!(3GO~`O*e;r2`wFq2N+t;T`W92Z|8wuKcnv4<
z&3JXznGX>~Bh#!EOCrr0fv6ydp>Z?lhtkBj&G&o4S)|@2xiUUKf+ZVns}VW)JMtph
zU-}~3f2^6}fMO8#qTH|1s(Rau%Lm$QOPh=k$8y>rTUS<W!)IZw&jq;Wn&&j&hc|!=
z6G#?~d=c+Gm>;Ke#u8%zR-E7iPuL|S)p~l`8MyzI4xbXP0IMY#ZU~{=QewjL%~g*{
z6%7iZlboamq?N}Z@L=s8jn1XzB)}e7!MTafJPNp%iMQscoB&Kx=oi4Z`43P>ays1c
zXxNCgHP*r-+9T7*zjxib=WoQ|nBjAM<?d~Zt;xKk-MuxUbF_fTPn-<4+7tCNZ_$0y
z@l;uo=~MdWkAG~GHKkIq{90^qoF74KyzH{u(s~cJM>ywu5-D3aZiPRzJKP5f+)+Dk
z_938G<Qg_v?{crngVb0z0?)Z8Pm}?quUm{`P&dkAJ_5V9i$^Z4BCa!TNLS}E@m9h7
z9@3^v4<siSDyaDsp;-QrpQI?T*X_|IaW`OtxaU~>IQ|;Y=Yr@lLA9uV^GI4kHwcA`
zE)p2!EaVz}$Tp7Jz^=<@o{<TAF=0{dPPlV}djcm%hERKMjnKOfayl$99MEAr;=wmW
zCc-)<yfN2b-k+M6)OelH19yE>)n}hT_|)J&s=Df%_Sd#KAg>Jq?TZ|5d^GlJ(AN*F
z{4&nO09VBHT!rf}cOc#;poPdxA+}f&Jo*w)dr75*MUGMG6#0e`8E>r4N8t4Hm`^Qf
zj?geD!&n7w>5>3cBBvDzt=%B~^0>imMC25|Ky=WFyHLqbHSN=om0JpKv8b@HPyYiE
zRy-6G&oFY1v2JmnWYnfqvn($pic3Upb_$O=YM~qi7;f2nCTW#6GsFbF&+}K9tD$E3
zWm{fPIG#;``M=JnJSr`}HZ&R90iVw(LIW0+z0s(AURk{;P?Y-d-)S6cj!965#MvxZ
zc6UF&ov0q&!v*n2-aG$0dBGB!f=cEaYiC0M0pb52PIss8rL2*;sfCf9iH#|MLDbpS
z)?M=Zs26euS||eST`WyZ|F6u<A@xn=c|kP(bqs1~Wn?8KH1vGG`mllzO85XoZhX_;
z-QhpB^(7NUQmb}~S&m-dgadG0Gc@L%H$S|P2>WqI8rB=pDC5?!+a&9`Jiigc?J@Gq
zT;J|55I>kS%V5q8seY56SLC|{{zvcqs8%t8ynLPVzv@obvjio?-9EJ9rU9=3rg~98
zQ?JOjb6Hq#LP%6<iU@Es=58P*4I|Bn<<#$pwr-Kg@zlS&Tt}<)sX(gH<Cav+bZux=
zJFz#N{v$w&;M}g&?6W?KWND}?3e);C+(JKB1!@qgWJ%DqrD7dCj=aPGmQ#v9yttaw
z$r7@K_rvfW1U?P9QG_5Y%@TQQDR{;snSXFb@$n!=X(l}#fF@4ZcHR_Tl_<Wh0;PP9
ze=W4>@8Up(UQ5Gf(LI93S^>5<)z;omw^SeO;F>5#RiIb|-7X+>njL)UN;!eWGua+e
z7@(to;x>a!<v+EY*87Jmkx_2v-XDo%8h!px_I^>GOzUSu<w{;l2rg<v1Gq&t8S0DM
zO2RxPu2Z@DSL~``BDHsrcmbyDjtZ$KjV!ehKj?@xlTxoRbkw2-i@$+0@8DZ23$9J%
ztRPIPnWz%JlW#)GHKaRIOWwj(KlH=JR$VjPp`Nv&!qvaIt_j}IYAPyTa~FBv!=<2o
zCUnW5k52=HDy@lI_BQ89q@p20xXq5OjP;i^dK{KiHzB|Ved{Kq+>ET@nSn3-P52e-
zp1Vt+&I<u=)w+~B?jKQ?mk|<Pa)cV2Pw)~FL6>s1+8HFKkK29@oUeZQJ^#(V4$>G(
z{qUG5FR(jwC?-z-V>48|01V!i<ezzqf-qYxp*y%loZ{UVLNV$@#^?uBC(!YU<cRNN
zBM7yntk|HBln~kCm2gzQLsk9~NIT+;z;wFoJ3=<Z0GJKt$Fw+IlM;);#yOF?#4kW~
z;j{nlqtuAiSy8^pB&wl#JB<BBZH+2SyIqJ{w)?v{s3E*ZF>H<S+bm2%I#F#<V^>>p
z!#r%_=dJfoFbOF%#JE<(Koqi&m;^UpKT(_z66q*IS(z7d0_nj&r2JUnZF44anA(-3
zOc8&+3sp|lBy-2i6ymh9jxSiz*cvZZ$BgwyOVg;qf1MZib^0>DzWGIq$RHqm|3jHt
z7y%e0jQ|SHKnLe<(B9V85(qQ}DB3##zl+q^)XB;I|Ekh#jaOeZb9^82)eBkndB_yO
z)j9S^V!3*vKt4|Pu$j2glwNUmJh<Q7tKNz57gILo=3oyq9*q%89)wjb>VKN7W?jId
zA*L%Hmp-9Bi@pMvjyG3nWte9cyb@fu?%%z0t{=PIAA1<|Kpmj;BMsrkFI#c-!L60T
z4KYed@N(iOSD^`d191rEZXBStLZAP*kp>_p9d6Cz@aOFYqErrq9vp<S@lyAc7DtV+
zdWjB59PV+U6DDrQPKd<*c?k-kICx3K;V<5ur{+f$+Q59(LdcEWxqk`J{VE7y7)z#5
z<3$%j>c;ESxKTqln7?r@KgLBNy>SEI9&Azd(ixb?`5vq~P;7=-sJlz|-eK3O?rLr2
zF+}zK0kT4Fp{6=p@(@*gU7_efAz7V@Gh9}ydxFKBR2z<MT0+2uvGm}966-NXZ{~wZ
zO;d<<34GTzMj10ZaV!?Dc^0^-MkeF-Vf}eIjZWnuTtI}_#C;IYQBoJv@>n=v)e*|t
zDx6puLmy1N>^Lo`AYwR(lLP>3=2<;we1u<Wf;O2zbC;aOc;!qUinoqx-r48p&9YR<
z7}3u%k+Tm=uRWZ0`mG`1a+&!oXI}0~@54#RV$kTTN12%^hPZ`g@6i&3Wp&pjR;<0^
zzOiWEW#LjvC>^KHA=6y*9!%I`3YcMci_T#+mn$?}n-?E;qVvqCUq~>2=PneQ$es^~
z(>3xW!S>Zj&ARQPx?>jh>i+&q*K4pUz=-<?Jlu7)h(6AxXME>NW|)_t*}x;q<;r0L
zRx_$w%{D9ORN$8%`^@6SC$i`~3r3^Q|GhdMC)FPIgSHrXvXk(}B4f3)BxoShO*_Jx
zLiXTYxH!!%nwD>xqR~)&&hq@plw{MTL?yOYs?avnH4&8(3O$9pK_Fn>v{cq~<{cH_
zFyUo!wd&ETC@zg4tZl4aC`<b-rF4ro0T~G)LcXuMk#$pOGJtz<;-@;u;t8%NMiSN;
zb18YY5@E~zf6CD7VvZg4M}8DJ<MkV%3(VfCbPC?6yBEY59Mv7GL!XP`tNo>FwPXtR
zq*f<l80}t^v{3}X$8=B{kx4sV{h_ThGVPGV7P(nuG!qjNlj<lXbdlj-z0d4JkMbql
z7cm5jev)~1gP10kzn}VozS$UVrtxNxaVVM`W3bNwYq!<msld(0&Xlvo;br)nl#QF0
zDT82*FGreC@iro6d(V~ICsq%3FFKEq^Hdh`V8vWq%PgOl(Q>uKQ+?#m3s|6syCYfK
zKc%5u;0Ly^kqNkHazGOhuz~)~x)$T7*Ijnp=Td)bZM-tT#^L@9>0wC=gmsT`++7*o
zBAU1Uxyp7S;}}dePejj#XTHgek_*T#xS*yWZT6*HdGpmr(r~Bcb5}m-ga}A6E}E0G
z0F6Rd)j<RH2wl-w+-HeYi*52f;#k5>a{?KMz~?hZ4$ipX92XW*H5H+@bT`dm-^o(?
zB#jwoHRwmH+|>IFttMD|tO8br!Khc3SlU-K17*xTQsv`QXrv)jFu+?nHRqaW9FVtb
zwWwh-%e$!rhv!fqgHkyZqFX8*@ayl2FFH9Ba}w<RRT=0u^{Zu5&P(*?6Qv=j4e*N+
zpG8}LU070O*heSX@0t0Q22i{8Ue0zzSr@kTFARm2%da%R&zh!-t_3JGeoF;pdc82H
zTD{#rf6Z?lD(`MR%D65GTV=5w84fjDJFiqRl3&9otgY~1IiO3iY|o+Y6w@Fg9gF#g
z7zyiNCj(^p5#Ot)eZ7XA<tN}`8*6jyALzVB?w{f?(R8A{w=`^^xYj~a*0hW4W5~K6
z#Tv7Y%OH3T@Opa1gI*eapbj2Y*2A;i%;omfFDhi1UXrbCy&3Wj+d}*tY?)_)tyPY0
z99QLpTVtEbO0D*Kejb75?8~H;x2}t1qg%+kGDDt>f7z%eh*pq$HpAuA8r4zG_FFDN
z`~RtxDbcO@pv0@=wf)DEp}q^3#-ezARFeAaUW^sZ*%<t~qVIb6Tj9;v?#S?TdqMe5
zRDF3&So6*uB{e10cIyr_InJY~XeIJ6ZfuA^SF4N?UsbKM^8LDx93>Aol0XpI5ZLZT
z9>IE~(zVaeac!_&@~X{u4?8X@ni7rn)zCXf7wcAVVbf}C$S-QBF46*)5WVGdmz!j(
z{zKK1V|TXYuMv|iw5}F&Mf%4vC(5xZm{3U)zsuDfX4m1R{F<iSK3W<`^L1rlr0O_7
z<z6}Y)Uu^5W`oE<Awtv7V64~7<{?9ld)C7SBrFuHHm$dvU1wf(AWl>(+)S^;fSVOc
zH(BT1D{AD&jtTy~OTCq#T4>+phag2)(iKphrarWu6F>kb!7=`Md4DoC-0yTE*F3Uj
z4ByaA7rz)!G0PV#>e9!%&<1cWf`#0x;DXnUDgS8_@KUzGc?Zu<F>t@KvGV0|m1<t#
z`r@L8-8J8my8v81yl?D-roY=w&6_Nulc-I&Br0nh$HCj>l*m1FL{mxYWra->3QoU;
zmgWq7zXjLjo%mW~*fWxLM@~Ii^}RK4Jq?9QE49ojN-Au;P)Zx!!y;3t<&zh%NUF!b
z?t}5z#k;@j(hXM>27Pw4*Yqezp)GqPcNZ>y{D@P#RrsCx>x#`S8v1#*ki-oqKyp1y
zRb2GMIlxwfsjz>qreLoqLWLTZIsy;ut51*G=FqtwkzotcC;PKR(~`&>+vz!x#rN~S
zu{Q-97gB5?K|nITI}6_bp|b!On_1eJGAN6PfB(oCIVhW&I2)TPn;P2#Oq5NH{&)Ld
ztf8fXrh)c(Mav3bg{8RP4Nl5gRz;2jAuO5{miIGcM_AIvj9z47hR@|Wuh5KzeDDHJ
zidyE7jbS)K?MH%U^0<?aLXO<jsbxAg)?}XQ<mR<&&;6#8yuoMp^GGhp(_SVtyKyUQ
z<_$GwjhJHO{l;7y)-LhXw|ABac%h_t8PBj@AY6^JP@fw(o1~gCXh{GN9MkANYG8mK
z6Z=Y@x)rSt2cD)Cua6s^MKdLm2DX~Il^mH-)<43hoT7*>&n2^@kw>L{UsA$QqQ;bh
zjjw8Cq=>zQf|jN#8aq+BBW(^|=KT7CS-GC5rA_VEMQi&dY}h`ikR>^|Flq{&<qjS~
z)I_DAH;kz8S<~MG%XNpx_#~4&DZb=<?@J`^?RXdAtHnKaY8IojW*5$L=~9CjmzCxm
zI*<wr7TE#Y()rA0q@UUHG(xp(T_IEoX5`{Ue7$fGR-RR@IXDZpf$yJ&qxdY6L11E}
zd+mQpD~rrVB*t6}0#H5L4ak`tR~hzGvePh4oSAIcy$RoDNPagXJTxN0H#awk-zFU*
zs~(&jw#s&dm~zAFV``=(*_jVF7oR@W?yYAur{=c>a7d<pEcI<b;8C}^OKB*|<#{(J
zHx}=^J<o{Y8CMe!Qown0sjBFkHGh^jhT)M927*S*na&(PqI6q{C}3+q|1MjohT*gI
zOt9KC<K7>hqZ+XFK5754iGA&$#})6wLpM(*Ty-H~6xsrt<Q?YsbNUi<rE39oELy_2
z4eXg0Xg`iM3(v1=4At%npseaJ20fRt!FO)t&o~ehwNDzPuM0D0-D9>QWoe#@5#M62
z-jRc_ch@?wg;<7APxzxdL*YzUoGEp=FbaWvJpbpn_}s!Ke5t?hnuqpy>)$@*$dnzY
z;(BrYq5=o%z)52O5ezXCjqwQCc6e_}sOU5OQtT38yl6^7fNa@HxE^(mcwz)ynMPf1
z$2yAIY!p5<PMw?>80Pg(NPw$aXDAhVHfO<}_lD~24?AcJ86XZi;T}o5DmvjlDnu@<
z=)@OdoN?I;d@jo)gQ{0JE_F%U3#<X0%|C-ah&2KUM|4{^{UM=7=nLOQQW;0RYA~1u
zcYXzSU~Y!OAZX@Y{EVEC&3ZcPrdeM=6B4|*e+b}r-0yE!KayH&%hzFr)fD4{seBvR
z?fXObNO?EfK-3QaG>5aZJ2v0f=}8Mc3@}MLS|$v4s-Eou-qBb&qplL0f<H+#J<auP
zIDxRli(jYDE8@|Lx~*8$rBFi}`zohlH8Q<Y<P8RxTHgl#36^%8ALdURtk!u#^prXl
z$XZQ``@2m;2c6BcINiiu1W`&}ZT|K$a7FrhX!60UO3*J6xd}AOsk42yhDyYpt(d%~
z<U-ULJOC9d8Rs!(zIA8z1W%NeHLw@|45Dsb2RpC+2hmzjsJ4|I8DDyC{@ZFnytgXc
zR8V86W2{o_F?C@NF=ynA@PfCZg)>1D0L7{}_6_f!Fe|{%CrQZb1CdZb_GQ=LsE?+z
zF9mexhIq%}2jhe*NENF*b_F<aNcaSk;75D5%V8eFJLM#J)l3cGjVI`j{U5IQ3OCWM
zZ>^DiMh_8Soh28BmV&q!h5L-M$$<9PTxXbMgTg_agaNHVZy8vqw>Z6miXLHfeS%XN
zIcA>vjt;H4dSxGNn&Hk8Z=!aEe<E;+Y9T*Xmr1?1#0Mqw?KgX7#0vP!#7V<zy5B0#
z+6!+2xm%<bM5cM&-_m5<hlAff;}6f87zl5PEfJRN1rg)(2bSh#Y(Z*n5V(x8z-blm
z6H%+6G*aHPKTgMQ3vEM6B(PByG>pVihKu8DV%6?wdR!!fztYu(SX3r`^N$Xuv??uN
zE?@8!pc{h<U6njtY%OfvFr0NKjSk_%Wh2#R?VI?)g4eqRWWUlnzzH&j5|w=2LJA`A
z2OGYiDD!iX??_uC+02h?T_C-txUH&lg@&@-`JNKUdO7P9{J&(X0;SZo(Lyo9yX7#`
ziIU0V$pyM1X!&%i-PRh9|E4dSMPyy4m5!mccftQ0c7Di9rEkGmb_mcV5j~-AlOUWt
zWXqzSQ53l$cth(f$}<qMk?ia3xxi4RantJC`9K3@C5O#66NAzlITgF*jzoalZ!#*s
zm7al;5w`cTvG{oi&xw*d#8pE;9D2}G8YeT+1jN=+dL;a>1M*_JjG@LijwSugYx|#Y
ztpDe0>_6vaaeIKR5%7Pd+IFd1E1(LY@y!dTE{P$d@8dREQ7uAj$3_@Jh$;Q_@>WVT
z;%SUr&vtgf*o}P=kVQikz!G>bjB;&8XHut&TPbRAJ$9UGbG^!5t=Z=HhIBxDt{>ei
zu%thX8#u(X(Pf%cgIlK6ot~9k?f?E@_$B7&d*&q!axCWQq|)HuwdMhWWf9YblA`d%
zTIE)VNNqZp^4S{2@Y(Gxv{}pD`%>oJ%$Kjk+qz!ahQQ6pyFz#kAFX4+q_>t+QitTc
z&L4ss2YppzjlV<OQICzP2-OJUt8lz>pw_`v0XE_fH!3035tXnZ-C7LDNc+P9im|T&
z3VdJ<bBCWQ)x7sxXBW)!%znFT7!XGzqtjO$;vfUc`O&%wmJitd5jH`(*ypi6V!~=e
zTqDUo8_=x)yDBS`$;ct8;+Hd|tikyQn!0hu4JMMYBGz!JqnD>qY)IeeL#r2(oJ&Au
zRR+K@%K@N5Qw`lj5jfgUD)JPs0oNLXF2u$iQ{1=a!`Y!{AU^2Xjc*?qO1<iF%oM9H
zXGMpTUp*=qiM}bzBli!!FjLQZ7h~YG|Kg{?QOtB;21`pVsqXmuwg<eNmFa@XoxQP{
zN!0G8!Rc`@jariy&EXg3hDjmem}XnQD$2l&!T4#VWAwNyHRJj&L=%+ovgxAm(6FuS
z>d6Q_F3*g)F~~go)lPM^N?OS;mlI?Wcb=;iPQO4PrQKtrAtkU~0>ca|B0JX?z9Vrk
z?=!vaar`&u9gChB<#|$s2wep(x$as9OQRfHJ_og#TleePDW^GA>>Pv&1U5kkaTzn-
z*9dm}!ryR2;xM9ic_-j)$=kb}%a4a5)xsS5HzY$2JrvK;_6W4OhYOk*FA$m({$FYz
zVGleFXrAShGom{%kmXIN9Z2uBghw&?fAfbRkHp}}b-ZF#EfMq}e`SLlSd7Y^^i6=9
zlyTKT{H_$?%mOiY1edV<c2ZBq<`G}I73FA)@glw;T`hIUpcUa4vJWX7iL1$fFMT0z
z@e3Xb@~q{u&+dSNfN!~BVRZo=`ji4#7X^FeHsUmO4aGBzCUy5}izvLWux_5|g<grl
zm?zxoXOYn~#Rp|sa_<?ky2s37COF>m(i@uB3sJ%L$!S}6rzLE={@0RCq>2(l{q8(p
zkpBO6p8xlf{m(^Xm&U5fx;WNX6%%w6^dRYvP+eA52p&zYjKYvPKmTEvAFwb<thUr9
ztCXV&Bx5iS-Pi9`>8Hk}HGF2j<jmH1UET!P=Iu3(V22?}st8;(I^H*X{&jB(5N^FA
z^ul<d3d4z8BlkJ|92PF?wO|_-X^o;G%E*di#1>}DsTo464!HrX4!$AQ-<y22y4d&B
zKZ>R{%6Qg>wmkXC{L@T$1wo`g8aacJrVpM7N+w_u1d_{Ct38obZFx~IWSE`bfp?&J
z!)HLPRE}@5x0+ei88>D3kx{kLRhAJv(M8+5jF6euyEQIzDSN_;MZ|4%N!3Z%8UE8C
z3*LhT(oulNghxwk^3PgS^<RsM(hL`M$Hpk5vvEy8T)T{wkE{YFt9Q}PA>3Bp<$-EV
zBzRkUYU8Bv)Lk)?==!pQ%6xOS2J8AbrIb~aO`lR5wjNbJy@4TTJ=f0=99t<2t=!*b
zxX-G#DM>Uqs=13@OnMF34@Jgqy4lvn3uEQ(5}Jj&>YJ<j)ALU5%ma51Ts40RY5T0M
ziWDVDe65M);dw&s%34&1RI4h9OWIo_r9cPjs;r1?CJ*5iG-vfvHdss0bq2+D>+VF7
zbPJBO-~JR<a16{S2WSkdy%5_Xn2g3P&FOI7-@2zh9E3Om8C7ASlGtZzsUo=M=A5Y#
zKK=Gai7HS+Vdo-1I?>7t$vFRFwEz!G#<*TNZFHVKa+>^drWyP_mJ5|mVxEArLdkKd
z4vA9)uf~S*^Y?qKQVyhXV{H54OUhjVB6y!KNK7i!2`2ak2WL(k<%ooiRUCKF#Q}{z
z!na6)XO!OeIae{K>G~r|$Eljmk8!CL9c&G0zq+@%Lq3c@1^(dSw7|ubAi=ufQz!cD
z@lG}N7*LQ<TAx~Cht5#%gCH`q*5u{6Qn?~>#>h!pAL0xl@LZL)w$`X_{KTf6LX8Di
z5dYC)vN4P&^83A1VVGAx{-z>o`G#9aaTwPv(SdTGu9I#bf2%X{*`zZTiPAkqK=hx7
zI9*x}ryw)`pu|u9lv@~n(=hwX7pa%ZqQ+=MyyuH!RjOtU%C#7$HwG+u`&j+{ROasf
zWq9-EaHEjX5UtqV9f2Yq>RwQ}gXD!#z?C6qZ9p9w8R!Vr0Zi~8_D0*1Y9+)XYH4`N
z@}?ST{rwzcO|2fqkn&o-0NRlAFF=mA0jHJJMbYKoH@mfM{Rp38m!w`pE?X>|`j4mD
zVf0Hf)1*%L1(e4#tYUWe`<31>w#6#xTo&EfvwnYN*;Lu99n9Jdn>7br0ns6_alNDC
znyOF>K9F%9@6wxm-}ZkX%!A`HU4{w_U;(ri`q6ZKBQ6mf8ToQ7+OChMl#bZk^*LI7
zEV9&b*ec6z4%IUZV^vKL>r@kusxl-L`Zfk5)(!Fc`MBxbLd25c1DT^9@XzdF@6<^)
z@}bOqG<BpKOlK=v1dvKUTRdv^R*5^*U+FeZS^!Y{31@^b@Wr)_S2#hjhXpbkz?z*1
zsByK%Ig+yA9QDfl^i)e6h|?w!wam4V6NUU70>QE<`hb6;fgp$~I%MQLGvZYj_PzU@
z!rlluf}Zg&++EY43)la!{dvmlUlE(0m6)2scCKd~Oea7qI7eXn9HAb2se&9cRJlnw
zuW!qx<k64|v0{E+%L@(lvqmL`pzC7c28c2U?6|NtgPi`TV8GWCoOCe1&<Mi9P|SoD
z56Fg#yZ%KA>6|#L={5p-hMG*Pgx(PuVqeFw6qfCZA}@(DM$s8L47HM6)*id55}zl4
zSso=;fl)_6v?(#K%1TUE@G7y}KCqWet+FnWBblHER`l4w>YHQJ8kX29`h>7=8D)rE
znAXcFtBbOvPZA--x`P#yNM#~9Tj&K0pgfg_hf_$11sz=e#cw|P(Dl&B7g;L#B=tZd
z<dobv7fBCPNs?Vis5B4TZu?#21=Gbk(6tiOD<VqvASEe%@&(7lgq3H@JNiTUAFnd;
z1?Ff6W~!s3G&nvq2XVb$m+LPGU%}cvOz@?^B9&eeMb{VtDls#W1E?*eM8cPr+=hZL
z@|SHpli9$Gp8w`p5?<s*sQ29;QhfJ^JpaF74k^3ub;^IXhyQukOscN~P$iK0j3@L-
zB4vUubU{#|F;_w9n09~4Ffl=vf<RQ5q?UCSSvBH}8LRW?G&G=1Iq_4v_lcG5fw}E5
z++k9AxCGM$GS(9+Ukpsi+CQJN@NM$FzxDX)|418Q(83d^ij-;P4QJMc(x@NJV-3G%
z67c_HEJ<)Ihas?&q1Ju16B3vSzpsWZ*)Yneon^~tlA<QVh*vcx$Q#umm%r>bPa)M^
z!h6Nhn&PsFYWBB13d?RG>8h3YV5{9>na{4ZhP(P{Z4T4U+dVkMz+DrwY6bN<fRUX>
z+O@5mQTAGV6Mma$n;Xl-`BKQVN=b|Kq_Y%)qkx{bSjV|fN0{Y9Ya@6<M>^OpHI(}Y
z0JUgwCbgu#bPFdohZdWpJzq=RA7xtB)I}lC2V>Bdww@m=#B5;4t(+u;=Dm10uIv3T
zYJNO*7~aQ;q5tko#Rd4rU`D{dYjfn}GZ4A*jSN`s*d|tX8c278RE1z%n9ZN})ukV;
zxDJ<FTdc$tkxvOrUQX+4<U{!}lCHv99ktKZ*ME+t=-FRXu7<_m?BvAR3kq>7Ud!*#
zMGP(QSJv}J;d$}aei<)9!HJ00Gf7$s)NLdtGGtaacIxVs{yTi_!2`Ic4XvRraSWWs
zazxfgvy^Y6h-PU=SsXfmOW>;l%JwLrBDpsDr{R}Fuf_gRT^dq_u4|g5NgJzNjpt=0
z`EVupLPNO%S|gM3ruKM3tf9`_u2&Jf(cniCSqpErJsUR(u*`mzPX{6vr=Vz$5J8kE
z?5@Q07aoP&KwI{gsTG>e7*V2mo@P=ODRU>>eZE1WTZsl+l?f>2%cBbfHM%Ya@4`k<
zsw~bI(DBrLOS>b6gsQ?lY}Pl6r8cG!3MCLSu+~LOWNbmU-y0CJgktRU-=hLnWecB~
zwCQF?E$}keLEm{^KOnkBP<OcwPP1jcW4R!3N?oK%EKOd18pLM@TN?+N34SV{a*693
z0>K&LUv1%xeQk}+rJyMLKAAN?>{TKOy0g8b?SFoUaP&&eZQZ6{zw#zK;Pt`FC-Pai
zgmkM=Kf8U%`~F&z$$tRd2NLo?$nr|KR5u2XJ*WRw;jAW?Em6s|C5MRUb?@K2H8{D?
zB^r~Reuog2HOEwv9oG7*71r`!Tf`vVybPXil@cNM|J))vnHoC-EP?I}k|t(O|3OKx
z2UvO-{Rdh0zj6~MwPAF17Z(N0)6zNM8At^snYB=uh>)?OBjN`se<b9Af2%-e2Y(PS
za{t|-C0E+lKUZ$Dn+47;A)IH32Gd$KHibJ|o-Zvfb!l5`q^d_Bz30B0h5Ud79cDN1
zNq?T|xTgPV$n_+g_G;UAB+jsua-MU~+ABh^SzIZpE2$fhQkQqGPn^$6>i3}5kBPH8
ziN7jhC7_}!WSyGfoR=cuqDh`Qo|T_EVv;AA*jKjX?Koi8r$=SYIoXkt|8}xu%h@}?
z;}>0;KtEH2I_7$1%%Q%Q|0WgfpURIz5VK-HtDWp%0~i2vM7kFy9E9|#BqkB*%x98q
zc*VD~^3umYDbVjt++Cv-wS*@DcXhgF2dlgzV<We^>2Ge9JVGlps8%_DmFQK26KQ54
z29DsG1nJ=p>!j%^V2=_H0G+(*6Q=RQZ2h_^!%a90OD`r+%Uq|Vy*nQIdpqAI`ok07
z`P8^`Ze%qH6IA_^<?{NI)(1nD%<&RyIN2M6lXt>$cB92&2b*U*>`<QgUhRR?$o?;Q
z8#%*1h?2*M(bEf@Cq?QgeV|%AgGOzl;FnsKohi%T#?Fn|bi|w^W5;)p6s*9U#OY(W
zgInP?-GiM-e6R4pp4}Z8e4u~tml=-1aH_Re@UVu}2OatExj!F1B$`+ELBir;WA)9^
zmg3I8R?eP)ZW(Lvu9>A=$R`dh?$gX0m*Oj^uuuUZo^2EsjS$2{#_aQ>L(WY!I7_ru
zHI+IlD$QjHR1I&yX)S`5>3w_W<<LNVUz+x4N~9MNqga8?zx$C`vegmwWTyAyXEe*S
z41fOUYDV5#pQTRa8Z-rr@sFH8ha58(A1D|Mo6sS#8V`<I)ohoAH*(<gk>!Zz62U=a
z@OGQ#<Z0v-MlU&JVpje=8xl*TxVVMT-Xtod`uPyD+=0p75;RV{+blTa*-UYP@PY{i
zX6~LD{VPv?T7lTV#II)vfk3;nDn1W~NyjMBrKDU0*Z;F0JFx+vmpDsg>sJvR<<OQf
z{JYYa+v@A?8R)hdd4rZK2Chr^#F||<I-h?4GHoVp&DMV}Vk$Qmc)Dj|QyxD3@CZGe
zNckP&lJ`toGi||UMuENl6Tt8kv~H%L@L4?o-RvnsluiyQ3_jyem41W=jgbxk$0COX
zjvmG1?;Y00=ey`D2Qt1xVpKD&cN*KcjBC_)0t0!U7Q>UL#uPn$V~kTB;O-{0BI@^>
zEeFe3ODdIcew}N{brA31<#RL9(ij9`D!b}d4QF#WN&DLN(X&7P*U`p9Pts-Wj4(1|
zAZ+0f>TNI$G9(Tkk#Su;fveA#Ae$eZ1l{=7hUUH{R1b;Clz4pYsm>zUo4S2z^pBNk
zZbSnwGZ`n6I7BCx=o)p$PaF#>a;Lm42SaV{yuP2b5)cRqPT7uTgSf02n149q>M#nU
zwrrOSe<6$G_W`#ZhCCcz&+%ycVfV~-fHWMuqms5pEEs6;_>A*31BUjLe3+gAMm2!>
zKpJ?`#9siw?F}Q#CJ(9mhwtuP_E*N!Phwyb2O9sVmzCTPgCf1Vy|V7!w7WOf$<y2)
zq^4ePJqc=ak4V)YcJjlXv~2jg782y?zxZn_%g3OD6(vFge;E8W(#<pJtbYD!cLCYy
zbD*Y+%JZGAbql$n*2H(YLXg2Df`z_h$8GG`x#X8kN4V!>gxp46z7w>YB>5-xG^}q$
zABQ;rF2G+>BDseQ*(UaqMHzV>`AEce>uKhfk$#segDTyluuNaLH~z4;Hsej)LE5nh
z#pAh%Q6YZ8YxD53mDji8GYTwupf-Xpes%4~1;>y38?@PNF%7bE+&X~OpA(^t3@Sdf
z(=h7cN~|inPmGO{!AqH&1@QiRFce>>0*Df~jHvGQWfL1Di)$AJ;6SSEIoQ>NIE8~g
zI(uG)-$n3c1jVWesS%E@kqjZhhU^RxvDu-;6XcMs@ED7&fgv9OIkP2#xPk<0xBfmZ
zYq!!qm28XeWII7h9l|O-bFEg{wJ~C`2%oW}N6K8%N~mR}+Xe3c=1ogT3b;qgZ*JN#
zj8c2`tnP%<m4DAN85Jg#4gAP3?AXLkC1YR&m1q+V57ms^0gx^n;tletvxnT9f-5DJ
zST0tYVarmO8KKdFIh|qy?T-!<;N13prb!3Ix$cNgd&{AavUlRq_H(ahTck+av#%W=
zd~U}x3ag@u%O^k-y}ztZFQFo``<|*An75%_m*OAAf^XeZEjLv-UxLSkceXg&)%W;b
zrBkl6@7%8Ahjt!>;><zPrK#{gkxghHb9a#{ACG~9%<Z%vBqbmD9$CX0r(Q_gf9A;p
z;IH@JmCo5R-#so|zXNFq7u;FwjQ|KI_czJi>bwklkKs9PGy+BU10T@+a*j@gQ+jTY
z!*(`>&RgUREiw~<jatX}K_l58l=HhH$Pri)vAwTM>1I%THS_8olKUghTSE#KA4O9F
zN4XXsNmByJi!S#B*|`{J<{wd0)3A?t0yX#3?vcYiaa4>4shwiSm@i`PUecvHFw$P(
z21~E#pULtJ^E73IA$n{=bRt#hao7o}va)S_fa*J;Z2|+WTDCd6mjRe;AlLB3Z3y54
zC0AkJ;QRyklWu+#@pkEVxYdwPkW92M#nrth8V+~QxUb-3{ypI<TeiV52hb;RTlio8
z{rX4Dl<%Hv@Fj<{kHX-CdG_{k&&dO}clA8xL-7>hjY0fUk<Iv6u=&9eYlc4y1>UHV
zREK0SuX}oePFCQ-Qep%^JCHztSOZbID(mD`$5OsKZE{<YN$&fyyXO81{3^fic@Zg*
z3MBU|NvKIVhzEE63=>#-MP-Wcz4whncK%d_KVtdRJ?@(O_=bvA%kNV=6<Xqg*&@YS
ziZm<Rhsfz%wlD=m!BdT$KKvbGw7F^V3Y4gzP;?w=#(M`$f}ZyX{PKU3F}s%+L9%JF
zPVV&z@8x#A;J#t=s!T3tA}T6)vyr+>`~p7Gpw_~j;EJV1gg7fFv)+&~jHPc3RDLO$
zU6s<}G=^5Jq?y5&N*a$}7ziMC{go=CTNt5K<B-GsZIS$@m;|`<>v+;X<vU%qo(os9
z%6>=Z&w#gz5aDJ}jQleI@7^RH<EP;>$>~8&>cB-`_n|X~0bi*mfg6xVUE@>5v9ZuR
zI!`pDk`w-GS~QLV`flpsa0vO}Q8*5ByL;jo3Vc*ejWN8&2O7j(aQ2Akw)3NJp|vL+
z9O)&;(~t#3;n&K=qo>!I3R#-dl3I#drIx-%Q_;_k>yu6DXxY^<eh$HY7vEm{g>i|&
zk59X}hk5yk(zdo~ucqiyTsbp3fpJcjz1!dl?SIhRhu_w_dLG3Wn$b6R&Fz99TP#%N
zf}Y({MZsW;{!QXDS&l%Tx$N-G`B|fvAJvqnEy+Ku7*_E^!0H4&UJRiW$HdYQ`F|4{
zr$Ba<WT)X)#orZ|ESnRSHok})4OI4F;OhQjo+dUiS2+JQ+qvzYPxU~i)b3_TbCu2U
z+x+Hzn{Ci@0K{~El~&0u?9W0VC=a@L8P&-pqXJ060;LGHrH}X3t8j_CNb)8A?&G*h
zL5T*+zl@ZWJd%<-BA*o83!b>wTaEBOUE)uR3hze;0a}D-nS5APt8!9H;LiOnf#+p>
z76~N269Ue|n|Ey;iG0#4a+dBZjAIe6pT`F8AhH;=veR;AF7T<ycbHMpiaipON~Z#h
zKy57C`ia^Ma+he;(j)=j(^u5{_p#rtS##DlBtop0qYY9}bn#hH10W2trH4i1m9i5k
zwD=)7lVm;+H|-YEvqb4=dr(~4$syOtyb1`MPW%8$ecBM`D_3%ZuzTbV^$|xqZz*D_
zGrG^TcFc*Q2r$4&!Di+>fHSLcX(PXnYpPX8b<$!zR3e4L1^oqE9k|mVlS=*9gIuh-
zOm8?YCAy4eVLzfS(cH80+B^>F=8_A)?Acv}ZFjfBQXzm~1p^<qluA}crkykW4>tYJ
zvVWy)nr1H{zv2(Zo3=`l64JOWw^;#l0i|k~&@t^y3RUCEK=w)>=W{(V(R8-bD!p^e
z?Z(U@*@ZU4fw~?uX##Ob-mRt1OMLzsEah1cfDF4lJQGLy7I-ytU9llbBKHoGQLIKc
z<RJx1<3X~vhpZP<Nl`xg#?ruH<&SC8XWWxH&rEiFVcZj5Vrim3S)>6t3aK+3VW-M7
z7!^bJ9H=>^$`~gTCji|V!HM`*maFCfyFI#!iR4ypM+$8}Da^SR!BaDe_K0e7WmH|%
zY{PE?yg{j~qT-5JN{-gtkH{0!zshpujgphB!x#A3Qf2n@O|XN`Y4Zg~l@y_8Z25*1
z#jHEOZ7Kf}>u{{L#4pLkNKiI0EF|`s>-B@8?!n21(L3;2&|D3@Y$AvHQmug>Bn9-_
z-P9(|;Rv3@&V<S1)LBqO+oa9P6}s38x#F76SPac4OaFDzP0e?PSku^*12dhM&X6so
z#Ns+hMX0tfiiVv@;>@E`66Ek-8m$*C%vACJjp|JiamojeF8f)P^uyoGMM?dZ&&^J;
z05c{$X82n3BW9omzDN3_;zp;)M5s~q&Axaxvqkv{q=)IOC2^SDB<7ranch^aUz@3T
z*8?Y8Fj`e;lF=W7vNjrH{<Ja3%Wwth8#5ybYl-LV5X3W|Q`j!PrfT$g<KF~D*(ieV
zf91-K`}q!4ZC^|%n*6E3%jLi@S#Y~<AuP8`P>*g)PutX98JoJIEPb*1WV3F|I%_)F
zJWab80js+fMW3-EmY8Dj`*_OR9^F<Q2Lq8@q*l~?--F(5RgmNaRP!^K74=!`21!Ua
zbg`tr7NS(VkTTatvc<@Y9bdX-9$)c-)4`d7QVD38)u7xC_fJ!a+#IK~Eb%G?+y~7W
zz2T6c5qeoGsXkTQ0(hNzuyDeE^wkS_r2+W?;)67IR0ciOSMZyLEI2)}!(yCVn#L_n
z9H@lY2$U2_+LCHR*aT9-lhi~aPGm*MV9K4Bd`vn*Wcav3R9;K39I3(BDg87r3~DZ`
zbx6b+!gl<U9C4=MLkn)?vx>B<<nW%2;wy@b9ax6rfFpR_#g3p{gSV%$13A1Z8E`FM
zWTwQNHzk%le7em%?>&9&bp_k98(hyMdXR%P|B=!%OX`7jLTj<OPjC=p>^e`ffIh?@
zL+eSUQh4Rfnm~(VJMWjitI~z%19ch24E&Q}fVYKaE+?c!BuF?bMIuwx??167$C5no
z4K!VVeYj{&;#*t~X7cPlxb`hwsrSbAHx}+@f-bL(>=H(6|3&kFPl9lYDjqT7De*or
zDF@r>N-CM9hggr{A37oF%?$(X`31|18)LLdtj$@!puJN+MG5*w=eQZGlzk;}3?*pW
zcYyR`X}~co?H3{~&v)bsfm(0S&oC;i)QZ3BI1R`;0wxL>qnd-X^;%VNj^*epF=qvZ
z9c3mQrjNY9S*A=2z=DnPEdQU#n4zl1NV8OJ9<_NqBJq^9ByyXAZ~~0@xOltom?Nfd
zm+8uGu&B%ab&6BQH<-O8h1qNKlQyWaW6QyQ^HWt1`EWz}xE!>_1ZZPtU93N+BUlp=
z5irKis#u8NZv;kB#2vN_a{l$h>qkP4mj6iaRaMP3#GO-kj5)ZBOh+#B9|HP`Q=1}>
zTmnSrZ_lWN{L{xh^ug^Jgwktz-F>q2IyX4Cz8~G24xQaewNVwc$FvBufMsziOL=pF
zIM0G#|4x3%m<=MF2MNc!X&K1Y?7cw&eGq=S@m*CG2}gxfi4Yly4Vk2&B=7o}J+Nj#
zj6llLnI)+!at@d}uX+$MHhgrn_FyiPv=3{@N6L`U(MPkc^s-3fSi(lDDFqB;#4ecC
zn9tInq+n;|s@&wnYQLV9(Obir35wp6G7tg%&I;}h3kD+Oh`Z@4Xn|TSvmf#q<UdR+
zVJYEUAB#OfqZye|3UvL-IOH}D+rW=#rpc(Q6pGw|1s*9K=?BtrOJV#$jy~W>Us&G!
zLa_>#I4owbS!Of(53isw*D_IS66ib4A#}F~$AX**jizD>j$yfh8O3D=eie!f49PQA
z`@gHz?0O?2s9M=8cG4s#-LJ!OwpjyeWQFh6LsQk!b6tsG_IgB5G3Dn@#6I-TE=A5z
zOD!?H5Q^xX`^3|Z!?J<OB4*AUbZbq~R#vdg)*TkNcH@lUw!nH(q^>eUo<*&)1=!^^
z`Nuq);F*a8<&Fu&V7g7wLZQD7tD@Eu&9is%8PQMZ9jBCS$yW5X9MP_;dKqUn5@eL5
z`oJqsjf`)tV7}(0BXMUCXLMzy3O9+<uTuFP*^H?|OY+!!F5Z}NcV4x7aPDLZWfp~!
zd3RU{&d{ZMA|O4Xbn2aId;EQJguD<)4lMQu?5Dlhp_*im|4DK6Y8kAgvZ^dTZZb7p
zuLI1#6rWH>7NyK|<KsNqe|&T0(c?<mJ+Oq$6f0li#k39lJV|(`o|c{Bz8f-#(faQJ
zuyI;!9^MS6GdkjD=Fr_tV%g9WtoVlr#kCxA!CF&&36x4)6Q-MT6N8vI(zbD5<F<{`
zsyp?zg(~c`Sye!*#*{JLXyOvdigdQt)(hcma!e%pu=wb7IkV)3><qdh;Up!i^P&so
z_Y~!KdF`2B#%t|k9WwpHr<xEgEYih-56RrRF_#NdWeoHfu<tb#7G9QC@eeRSr4jP+
zgkAG?<&JLy)U9XG{@CVd;aQH|9FEO9yi@n9q#<M7EV3OHh%0TyVByM0<`QaFhOEti
zGk1iuGYn^rGBztdx`Tkx7*bq9F>XS+Rb63~7cA|mkvUj?|D_vHs{>|DIWBBnp(@_o
zeqFKSn{XhC#ynkT*wrr1*^%~IpYsFS@;qE;kp9u(17uBJi#wV5UHN!@b;wU=)dzbb
z?zOm^iBnt6Q2eL<2gH9csx-nA9bt_wni^@JveyF`41s{_qMk4YKuSHavg!h;P&x)>
zlBP~X0l%X2KOD4QzJ)!;O-_nw{{lb5(-{H~zTp0`nno(;WTfRJQ~oiF)H3~1>?2Q8
z!TN^0`c&AJR6RRlpqwI}OS%8?tj{f6_|+=zBP|9q-1f^VE4Lp@K!h{u(p4pCu@u9k
zdYZQ*a%xq!F1kps&QZJHhXWnuK|9&2TM(YD!Bh^|b51Fm#I+p2h#{kN^l}trwVn?y
z6Y&Ppe+1r=m|`xJ{_9yOf;AyHoz7}7nEF!t#Opu|=dc&&xGuZ$zx#b^QKHLdep|Dl
z;(~xk{ST{@{|(CihoR@Uc1+aN#?<`(1ZDqU5ZWP47+2I~^v@hxPZM_=<8)+HX&TDN
zPQze9j9Q{0_CfG{EIbU6dB&9CIYam1DDmN`IdaPkpiDc%Y4<$4C7jfEdR7oH-?sfL
z>@)1?p|R_EQgg{nBF1}scJ^;3$Mfd3&-2#vmiPUWuf8W(FaC>X9DPiHEHXdm;z~Ho
zRhwp@m98pd`Hm7qECfpLzK|CdA&hVzD(w?#B;U|)h1-1z>l;>nj6s%fhWkjM#UMq%
zN{|BNEtOZsHecz^>n|7|^04VWCm}Ba1H~IL2m{!i2_c(74bYd008Gt+<p7KRWvxe!
zmpeIvCptTCp0Mkkj*T}0gYKFgD51uFn4QocA7MlE5I4pU0!lY3{_Q4Sq~5>wN$J+z
zL|Y)<-e`GH7KfWOm1D`9T1}%R5{H8by5b^A9yN#Av&zek5N7ZOm<zie-URKY{cPp1
z95=6!%S>lqj~fNOx7}@pBhBzg(D^E&6Gb2M;u+Z}jL$(`k9sbFgen>7VTjz#M&#TP
zo==G}74ieDS^q%M<Bt+SKkaC$SyGJ7{-xI$ZTcwU$}1_9O-ERkCuZ2*G%TOGCO~Sr
zFvhycIyELGYv%EuXf~(Jcs?ZM#F1heR~9*!t}{!3XONJ2VHavB`Ph>(H{-1n$;FHj
zt&igh-N|bHa&urViFG1m(i9oBNw(vLT(wtX?T}7aM4NgA@c?srt+izi`F8!%%a`|W
zYR+Mti?Jgd9YgfLj0b>Dk+YR-Iy_jJ@fNRdQqg4}-C)4Lu^yP^QD`R4;4>s7fh5Xs
zS<1RLa*~Otn#oAqpUETT@>A7vjo4Tk_8j8XGn?_^>LyeIH*9RFw$;anip~lBJ0`G)
zQxK21Qp|7i3Wvlk*`<qN^^;^qWEz!c=S1gSb7)te+zu}8HdzdDQ6YncuQg{4ry|&z
ztA}FGF_}ZEMqZP9yV0qNFWMwQJ*wp)1W?^9XOoP~0f4iIxv-}=ozSKS*tV(_rtX(o
zL0~#LoUZopU~3z=0qw-xk4YDJu3Wq7rcXy^(L8T=cDN5?>|4#8t1R!9Sd6303qmrp
zVrFB23=ONSq24C}KO28ftUXm6of4lz)y?!*Dyq!hw(bZdw=q?XGAyDtHcts5^NMrT
zp&G}fY*@(C$$qnZW;=mK9hB$y0a_0{o1|j8e<)uG-lXRD0|PD9us66YShR-gDUKPV
zS}Opoof*wPjDuv~Sx*p`)gSE{*^#+^onem<ytf4ylzkImK5ptGG;S&)L|PSwvRh^P
z)X?YC^7+(<Xpg|{7!EhTBVdrH2Oli#TaFH{*QoUe*wA|h&tbO|Z^^4!)^u32VOf-i
zYHq9{dX#Q;HWY7o(0fJ*!TYaO<Iu30MET-bOf*`|GEz|4|27sXX-UGM#hA0u({3In
zIV`WMW_f}S5DeUenTDE*HM&}J+Y}8{YOwGvGV$3&2Sxr%IQD}InLcNd7$RKd@$Ju5
z;|)T(B`ewc0q<Zf+Gn8pf$qB>3T`l^B38>d;n@UCfF)VRzWjbIJ@du}mbJvr_~vJT
zFot$Lk82p_g6{u8**iv85{F&B-LY-kwr$%<$JR;5wr$(!*v^TaoERP3=p^0I&EUOv
z-kCLb?)_SyYOShO^?&xW_iz7|Og`}^KwbNbWG2sgV-yC86Zt%!RpYzst!dIAQM<-t
zYN$Y15P<)w=I)dw-7y4b^s8-i>QHJ-i!T9&K;PABQa?UjAmos?eEYhw2`O+2MpxIT
z7$Sq8x8FOnW{$naeryPA&MLKM4(f334&m=Z{?<V$|2BWLPj*bVb+Wn$oVufOsr?u>
zVR1Iv^+L~5s-D_aH;+0L%oP6#msEBPn|fhiVNALtQE^tftn?p^el986PA(_wCyw5_
zP-S^<71`+ksHjv5o%<T8sH+Ygr9#Jilhsta%M~<YBsta{t=b<{GXOsdNz0Ub^v7{x
z7=`zJ6DMX=9yHoT&Et$bwfxSq)J6_%4O7Yth75H~2Y^{N&`X;k!2OKI9Jt(;3$~(2
z=(KE4&%C+Khnv%Y?(yw*aE_C()tnJLsN3R3@R6ZItJDtq&!seEYak~hI|}3KE`GM?
zh~`VZ%$ZWxeT5c@+&_2If+gxBo5NmLYy%GOu75I%)NZY_g-u7AFZw4cN5J4;d}83b
zYO?N2DVViRdHkcGu{tK#6saJh#mkgzXw*bC{BbdhNT#5o6)BCc&h40N+)8a#ed}AH
zEh#$eZ(Qczxjer?S6x-SO8rxx(T<kLlP>Pdl)z3pr9u;oNjx1fS=5<v3$Eyl7;Q}b
z$3|ZuE)J=LsV5kSM=-TenJg$>CWZOFR7_64D)CEy*qg>2l4XN0ZhoN+pJ(+63-5=B
z;-(vilG&Aom~GA|BS?okLf@|=zWjrbyP?wp@4`djfU9rL6j&u+xpUDU9w%P(JiF`X
zG^w@r$;XALnRq-C((Ebx+|16D0;@{49`=lqr}S6TsO$ok?GR%@P;n_@KD61ojE*rn
zLe@RAbPm-ojwW{ANds+5k=#4-iIsp_txh5mw#iPq*^!`ZTv#SDjpH0b3GGUKsT=nr
zphR}??6VlxA5t7{c0NU{P;3y|?jub9Az1#XG(-Bmv;b8DceRbzzDmRdW)TBSS`WwF
zqIsoq_&9gkKdmE|+(xRZ_*H6uoQD<JDzf3-wcZWjK5bId4|9sD_D~673kYi#X^j-m
z5NSnQq}E5!RfXW)7tOyTxzM9A-=sKxGM%QDnM>i#bkm*Yn_J$>9;?-dVBa$lIyB*8
zu{0-Y>%@7&os72nX^h|0fG9JR*np_J7A|Q#r%ntMQtZ`qMV?VNy!r8iHzJ)bN<S&&
zmEi1a^?2<eZ4MCE?IN`aQf`w<N@hit)qiUmY11%e=)P}E)iuuRZqsX#i?h;R@l&I2
z_`uV%QFZWvv=ieOyK0UMcg$#~clmpnN{4HUjq68@>zi3VhYHp~lD3hWn7BSvYRz8(
z%MJPYKZoXt$%$o7zli_YUs#m?o!R*RJ^}r2*V6xCHZIe!QwFKv_#@$8a78FcNRId%
z?T0}@N~o6FbD~X3>0qJ@j~6lOH?}oj93Q1beSAaz`<=@6t(IyO2Z($tjl09%k|Wh8
zvnZ4SdhYR?<8^v{A6r%YhMlN<z@t<;AD2R_RuP&;nTus9GEf*u`W*;13&TUdn;ZB5
zCPhJm#>6r`Q6{Zqt%c>O`4rMLU9(lY<`Smg_alv737AgY<ub!{5ri(3<Rw`967-N7
z5q~og69jTL=(fjKuI3US+vW{F)C9Q+Q0H1kA|mcsMxOY_5V>E(TVbCgYh4ZO)-c6A
zp7u>_ZwfevesZpv2wR@6u6l*gGd)kr4Kgp!Od^iCGcv-w8Alh@V7NR8X>R3;(_4Kd
zQM`>exCxRDP8IFy%G<QNa9$9{nnF;MGHe$FK!5DwwT&8RCzG93hjgG0GRKXPz1ccK
zClHtp;DAL}@)O2#p@x{wiUTcy7hskUm0*^Thb$8;vadDvSM_SFUgL)SwQs+5EjF`{
zRH0bRj|JwCT$t*YFY(0NG_?S3+g#$|QJ+(DEZahjUboRao<~KS*&kzr^Z|sv#e>^j
zm2})3zS=vwTzos3)fWit{K^!6gN{769NNhKSn4e!I-D69acYEb>syMlFVzJ}ILfLc
z#_@6WYZ#cH=F%Uw@|*uLb<8Kq;4qxREq-^z%E*zmTt*9%Z-;vb+jk-L$rYMl@GEB6
zr0$ZTp=iYJ9ey466^q5Vy@p>qZhxe9^~KP>{8GX9eTGkRxJ28UEhw9!(iM}_^tdFs
z)|+ga*4s`EhuXueLY-o6(1e!nyTg>Z-=RyBiWiX!(fxSBzVD0vdyPd`R<S#Y;$$e6
zus4RJY7C>Z9VX4+<Gq9L8K&Py>>0)1$9V$Xqt7Vn6ipA{^_C@cAVb4KlXIfdGO9_H
z*2;t>d81av$@Io8k#>#EcQfp<V10ZKy9%_uuIMD>2`(815Rem;@hjGxVlm~s!Tx7!
zhv8i_zv35k;+5>%H=h5^6yadv?DAiuX3YNuHz8*7)8c=1{(cP&o*K)TA5LxDSpsdL
zj4(VjLy2Lk5(^N6i4riQ5-BJW^p6(DlwK@Z*j7{`5)O4OZVoleS}n`AH61Hu4kX3F
z_)K*h8(kW8?x3!vl`hvJoqs#8mQ-025LB(LzK6e`ulb)DK6#&WeU2vrwqL&mdKHhx
z@fqj`UfdFLr|)_5Ztadz_^!s?>`DFgPN7(*D{xG=YwrNiJEqjPcLSjNZbrY3N5Jj-
zBO+}7-BIK_azwwsYvEUp7)3uEJG6mFh|d!a&+<>m<0cgZ?wH1GM5#;2HlAy7A%Hsg
zgz>+syqE5Ktk^^u3Cc2#%5wL_*t^u8a@YQPYynb0Wy+8O*<dTmufOfvP#mz#BIVBD
zd;S=_i>E4(`Di8M@O}!<2ylS&CWll%d9(_5YbQYcBY-?&XL8R&ZSsb*hshxT7)SRe
z8ttpj)K3}FesmijE^O<mP2yC9*;E_@(bW4>57MRjDv*|?{5M<{qM)IJWygp$yh~Zb
z?<f30Epq#b=QUHM7Em<IbbULJP^e_{)+4)5sUMXy*gc|t>J%v_h^YTeU&}!v0|&La
zk$PhrU2qV|19w3#Xo1jDgVpx9k4e06IcInrX3hPXglp=m&6Xd7lUs`Zq%;j@_cDgY
zQm!1Bk<8KGtW07C3wFH`=ikh4yIvF-E_~NJN<nCm^*t!vHI}AqTN>(0OImp?kzcyn
zI^LX=g`WMZ3A=7v3){9GauRtL9QySLiPs~ZGA|&nd1K4r-`VKm^q$l5t(6okA<tR`
za3DDdS{+uMoD!`SC>7B;4Fef$sbg#eg}R#C5@B$kQx~6zdIihw(*A*rVVD`d*yKkK
z)Y6dhYTaIT2t5J~B}=9O$HJC+CmuKVM2^UC!y&x9wx;NX_h4~_h_>v|eIT`bi%*G+
zWQ4*vq=8zM;#8@vquxMl4lzO@t2l^~FSmNYwyae9B)oz@80d{Psqt|k7Y!~AS9~Al
zGD=VMM=xfQDgz0_$1-awcrR(m)O~?{XbE+8uK=Q%`h={+rzE3|R}JbVD><7o5{jzb
zVn^_FN^+<#t`$0zZq_(;+Qj{MY%LWP_1f=i&*Z$U;_;!Pfe9X7I^8r5jk6~k&jd{+
z;17*XpC3SI21T&APufbGv=k8!^H~4|Yg%xBDhJ<s8kp{iLeO0Z%|$U4_*y#eprR=n
zFVp;{Pq1jGB9#OpF`U6a8|%EHny<D9b~?;j){<~aO`{XStX))%5{`LG{h&B7$&i+s
zl0SrW-L~6+o(Hl<ZzHZDI!0a<43J1Wp^be;xYp+4WaD{nIX6dx#;LQ8jU@jSQ5Y;X
z@}@G!C}$e$XY_zY0hTlQ?KSV`jT*@QIrRM)HeG>#<jm3GXW21d`hf%$5+U(kJ)hEG
z72k%**$e*1uRUVEr`-ZRA$YX>pyhl0i1^+Y9bmuf<pHZWOih-(E2%^}Rg+s1xyxD4
zUaWGH0k)TznWoGx8@F}qOq%6-wCz`tnYG|-i1OZRN8YM?=lZ-!eDa@!(n_d4Hl$bu
zz%-RfDu%TOC5}YQlPkqcS<mLev=*l#MohId=FT*ji7HyQE0e)BNVZC}p>zxm%3Lz0
z7Djf}tGJC?^;Mv;^jJ2P<odQ{(?t2w_VCOV&NQoHDjJ14prT?X){$i<k-GHyj;Pzu
zxY??g&X}k>&WpkvN@-QHF_SDJ1VV21HgWZ%Eo_F}hoRV+FJ=q3D^u<PW|Jf8uWLGr
zApwIxS0*VEDa^i#Wh{rJ3N|}o3o>Ygft6pW^tJ{rBF+f1_%@n%dbo=Qwb@OTZZZ==
zEhxow%8ga~rPAm4L<2hlM6R(5V>pd2ZEM=c6ptn??+EV-h~?43##CdzneVu4S;^^R
z59wnnHyJTVvo+L+4oltxbm>rFUF>^KbjcyfOK>vRk>4aQ$|)D1?SErKT;ils!OG0f
z1q1HoJG!%kz*t&n?Rlb394gT`zsS@dPe04zrcC%**Ol*hp(>#s{VDIxtGG&i^lUyO
z&?<Nq@zAcaG8I4io+66Y3EEsqj2x-1pdVi3@W2TIY5`RbNdRm>q_HM&TLF=os|X^J
zyE>8%ume*uD1Nh_;TfOPtrHOEq}v-WsmD!x))J9ss3tg()~z~OT;ZCJ99dVQAm-(?
zCl?>l@huhXXo<MQ0?uoR8x*4~E+Oz&yv-Fgh_uYyYF6a<>0iUHe{P@04~@8+<LSbL
zEv(eJOm2~S^`>Q4t!B2AU6;av?mADzmqxZZ*?2iC92{-6Rd$tjRW;T1{B><qf1acE
zp44Y^AKPn5Q}3VDQCP^Sx(f>3(!Gq;(JHasd9?RS`|J$_<e=OvAt`E=IjjzPZGy7M
z=B`9OQR-Wi<aIKKIae@_B~ts=fAiXtSMUcebGD#WXLC|(bGD+ijfQjj{!rbV?rvPz
zb_fRpJHqXxbEhuMtoq&c?&mIf<!NS^MS5&=2!cmXKB6$5wOoTGI3WDza4P35EV=kn
zHJ?*H)v+t0{lM{ezdyMtx&BQpjTR8F(pqcdXk%Zkr`K(%t0}JN=a4c`oCLnTh}*_J
zPFK`nr&Zck!@p5ee8R!EAcxT%C0oQ*X|l{0Clf+9#!Jdc3GD)Qt!pEY_PbGvgk(EE
zJeTh1K_J&SYcNo*_sm~(Lf`6%Yw9q?_qanNOJfZ)P9TJO6LpF=q#4;63MzYQqa`(K
zNxjUsxbiq`hRH`T;o|MFZ*%ACmKrf-QwX&r4wZ*~y&#%dHxj$rrD{ugS#bYdaJi04
zyXRv=^RAkpFdAX3wxhy``i%a~%TQ0sy@J}>YU8rA7U^=btJO=>m%3D!5H&1sW+4B=
z5=q9mfE|2F1^RFOH!=4@f{VY$2MjzX>GmNVImo&^QD*si43gl|+oU4oO2@f#@vX4y
zwhwP>mL9UgO%QG5ufH&m9-slvCAf^a+PBOR^mRH_7|8_6M@$oq=@+`W(rNb6N`5xP
zF0YB)150&6Oyz82^rPs6rnN&ha+26eV^-s)BB6<juCag7W_9HZ*;Zaoy7<E$qBP3=
zQLH?sPdo0BP6YhzM)2f}Gl)X=eP?;m<`%EUg{w67RLhq<oTNp;wg24T3&qmKk#c%t
zk3O1Q2HJ$#zQW-x$n8~_!o?*=r}EgNN57axAKu4saK$W*SceqAA!HJ&_$p?D;^X&v
z(o)VD$tU#lfSxskS_tzbyz-gl85r?j#xTD#Gn`&<$(rlI7l+J-6e;DcFj+OZCldVb
z!p2VKK*bqg$Ur{P&ysLiofx-N+`}ArQ)VjLEzZIy`40#*kjZzeDkuM_wXlgz)!cK?
zPZ|Gf65xFV4%PZPl8i1pjJ;65z)hg5T2|9EYiUufz}`YMfsk_5_>rfIq|uq9{V`|>
zF76|5RHCBlj8B8dSz#wAMB5>x!dZ$K2_W;&*?Lc*Z$#$k!o>FqSnH74%l>M;3ZZ=o
zLZp~v{K9qp+nW)yvA-V6wXfZ}MALun)iF}2lZ*a2IoV#~N?*>EDjZqN=$v*VwxA>(
za)0lT+5O<SQ3JT}qba#UE1`-#@g&t|J_b={2GtvL^+mfFgp=R84f#N(@5_;Sax#r@
zc0@f~b)Y`)THbf2<T?(%cVH&$atQ?S-x6G_>9nK2KV*t@0jTZ_0~KA}Le)lp)+21%
z%XP_xIUpSw#?yF5`tow>D6gI*otWDXNG&d4vnEVb7`Y^I36um=!dn5B#p$GnsQdvP
zd5Vrm@8voqjA3mFmK_|qC3^;l1)y6m#1oqru#gz~0V8i;<gdr#L2O3CFA7t%_trbl
zdu_5+p5HWcPTk4O_no3Am-AP>rGF8*`@_~Vkh%e~<N&n`bD7_n=U@*;N>%t6R^t%s
z<mo_0)-BREo4EmATJvzBY{cuGN3Y9A6idr-`x$MU0N!ORs9B>!NaUx-z3<f!hrn=a
zgsON(%dTqv#<oIG0(}KTi6tja3^Q%yi78TFEPTgLtiA5Ufk{v&UwYY5N{Ye}NYYgq
zi&mSK+mhPY!`(6Zswc8xtcvTdCe)A3<+(Ufq)T{IC+uXzXP0tR-1%#}W;A*G6KP*G
zx6Gn`q|jDIqz!zmmaJpUQCw2eQCC<;_O&sQ<XE;ABl6);9YLb5MdtztsG&3HX07U3
zJ0j7|tx3oJV{*6Rr=0${_rk~%2GSTK2Cv0J0@{v#tI2Iq@VF9Lu0~5^Nw*hw16;c=
z)iRi*SC+xQI*UaKw8%pfoaGKzc<SYk^7IV2zK~VlqV@MGL>ig6_@{~VDy{a4R{lOb
z^MYSJaLDiW$Q1ld33UT_e)Ys6c0P$H{gB~(XBhvHOMRyh5Z6<4+BP*Vey}c})hV1%
z;Ujf<LCHWjyZWax-meT^gG5Boa5k4@34}>UVX*WlhlzGj`OK|>qBs`vLUrbXZn8gL
zkXP7GCmMixW|5gn>O`!$xKy-NjC9m_{)v^9<-9~>el@})#C)t?42Mk_d}8b3n*VFC
zed*1i!uTEkKaXf16RLJ)Uy$m}uVs(a|ECe{e?)>%{MX=&q>GD_i-wDdncaUd0?V`<
zl<}oe{IOVsX05=EIa8@JpwKocxD-L5p&YVac7;?nL5YjcM?GuM$1A)AMFscZWPik$
zW$H9IKS|ZV6v;V>Yo7GW?v?d4{Zu#B`9ox#znD>7>v`*)R+jmBy?+vv``(cTXlpM{
z$1d=s@WTB!E*Dv&8>t>m41f|agY`<fJ1Q&matd^;n4>v(Y<$I;NC(y7c6@p)b$g5!
z-uhz*mcUHVLe)Th4ZtW0AMf`<Lt*)i)Gg8P)!QI7p{3iTMd6hJpbi4ibUyF?Jhq`U
zhmo~`Hk^trw)>Z>tP_?kTZV@uEi=5X3l4dN=H|M)b&oNBn@18U>YNOB#<8U1ktE+-
zvl<pC-8Fr&gyPa*{V1O?Z*N#Y99TIG7Y>fQiK;zS6El=|5ChpX%(l26=5@UxSC50=
z)1#QAN1bQ7{%|ncxuu876vBGOGepREt0tQ`HLgypvvmNOC0~DEOy6W7Us@mQ!c5~P
zbzAHF`Xqv+&XdLgY&@ZlcxfiIi|GH?QC%OUunFNd#y;g6R{_5@Q5GfB`K$Wg21d8X
zpcstb)|(|X>J9fgN!oR#<gwhVQ7lS`e(Dz`m3^73fWDU8ATCc3X*e)CJhkpzf$`pc
z^3S{4@2B|iBu<hBbCMtm;NZq}%N~@=I6lq*0DLSp@_<KNne!p5>0rIa^bK7e1CtXW
zf+|w%EGwVG!AkKLOtYM(06^Bln!QDn)V&wK_qvwHWt;UK%A99E;n+K0j?0h^<nB^l
zP=R}>qvkwiQj0@loK{o=$A8gzD5%y3ue;3ge!yAS@qm$y%e^Z?r)oa0AWQEuVIG-D
zX~P6qRmkN=+zQ2ql6-1V(8x)r*Cfx@DwC90*&^i=VF1C(;pnJ`AwyECl1IItR~KFf
zn|8bfyyg~_P0qEBSeSg(RL+6!hNYA|(IF?!;%2vJ2<HU^k}?ZdC<|g;U0Myx(H^tT
zDjN%xB%8wDe<Y}!_oIqZN9d>1r2T_}hQ{4Efc;F(fRnGt0O4j${rwRrWyAm%VJ)Of
zKO$HzXSNX2dsp?I&Z!JlPI6CVy^(6wTr{`9=RpW5*hcI+enXk*YV`;*TogejRQoiF
z(w5@e`QX{T`1AOc#6bz;=#D};PgQn7XW&JtiCK0k+yg<wBrUGR-$G>*i6|#W(wJ<i
zV`D8+_{_`PW5fNW*So_<+Vdb7A;x%8Mp%@y`WBl3=t>@~;So0pYR0J!6_(yhqf9pF
zNQj)JmE#P&1{Wy0b0VIHG4S{{x99r}XbB^w*;i(a0BJ^X^QwF}YbZfX+J$2GdpKwe
ze22cyf^?-zRvW1<BD?<$Z>CRtbAW1tI3Ofm`qW@eLc7)n92#>P%G;C~;vq8odC?b~
z8A)Kc$eSi&)Apz>w|02x#y9M&1MG93X|y`9wE+qGVIFFFE$Q1csZn)E!GfxAiO)wl
zt=R1RGO`wQ-f~Gwm@yloUo9-H<t{^vX=v+!g+s?k*DdeGC~_^daI;Z?0BGl>j_|&X
zB^F*{hjDAbZi&RLLuQ4FBXgmx|5jHJm+3D*0Jr|dNAw5mKM(+JL-;>`2%nC8;S#>|
z-pBtJz4!mosubPqU2XnHp^D<Gv0BT--p%5_<p=Xp4F3yUB7Enp?J?v?d|)3tI(iYy
z9Fvn(Mh0UrvDiT5JWLztt_GE{ZOI?wawL35emBHVnUv|d_h01Rxl2d-GEFdSe)f~R
z<~iPn+3WfpVSlj9k#_>M%t^8+8^J9(pxl8wo(E2>wrPTiwOh`O%haCZjNaxJR-5;D
zqG1MSM$G_rYMUw*W$RQPNh}@4pJ{pRYRK>jv6G8DxyGSHgU9N}kAZ5}kq2Wd^%s0!
z5Ng-=xnrfUSGBRmObz{}!9?1aUOA051AyTkGhfdFN(+1Y`CrbM)y`hZTE-muYfnzQ
zh*dvTM0*oKcmm2*Fiqs8rjr|I&IJk8*S}B6K7TCN$12KaQ{>HOg1PEZ>i$&u*ovjK
z&X9+ha+j!wnOZxA-|vUm%KGGbU&%|}S=%>0)>1F2Xb6Vl8x=-wIpmPGKaOI#Q3|#v
zjWUe%?Jir;=F)X$I9dJbP&60oLI4_a;Tp|mobV;6oE0;={{4c1PS)gWufAZriaGQ+
zdThh{>NCjuA^t@wu;N&dAimC)AvY_=&f>Uc72vrFV?`jkN;bLdcSvSeG}Btqds-C4
zXmMMC<samEPoSOW4u%MStg_B4E8q$u80n2LWuLwf7p{Yr@se*AeGob0*ReVO7Pa{J
zJ=QN70b!9x!n(mjrs;XS3Hj8D7!dw=cgndT3?EukS!;9_412iQB&Dz0sg*9PtEzt@
z!=C^TP*0#)<gHrdrs!+aJ6j-o#YpEa3GMLhQ(Pz`yOdmHavQ;uZY)p^BqYCL`!&2)
zQ6v@lPCm{|%0}$a7Heugsrdy?)kWx+Qcf<ucvRRO1-yg=>^hm=<Mf~wlmwdcWUz=e
z_hnF6vczuvPaGAVxDGY?uOipCFLTHLS(cUhf{R+X{CAIs%zxtp|F@UCOdHl1;|TNP
z!`#ElgDo);Uh6w}aA@cy9hog!LnaDrI0P)zpl$A@QgYDDY!`owY0aPWves6;P17p9
znzD#iQ%cfNy55G?XOo-m*4BzT!B#EbPvPd2^_gLN26L<50X;XppN5|~6-NG#fNwRr
zd9m*u>Z9JiBBQ)KC}ig$ZvgCoEye>PUz$jtsaumR>OFs4;z3bZ;<Tb&Gd7`kWr(}L
zP-Qt!l~Dl#n0@uPca#8vWYwUEzXvE0e_c@$#(832&0|eth2x!50k~{LM@tac_c|yA
zNw*!bWjq6S1&IKR0!HA;?O!(E?>`O`%zR%;W107+a&Kt+!e07@{`TVyuf80v{ypS=
z867kCMc>(v4$vR+pz!66tgxsZd8Y9FF}nWpUHBB4@=ZpH9!ch<F|>f?#Z<~AaW9pL
zTo6N3-PT?w2B`)Bl#%=^*AhqcPlc;4yDQ1wq|$n4z1Qy`z3%-gZ}VR_xBdFK%6hB*
zc8wIetqaYDUHP9wl&c)^SX_0*Y(HDFnuU%)*+uA0G+Qbl%iIW4c_jZ*4Kk%Bdk)p?
z@z9?YDP#-jB@Mk8Y5tU|+I5psX^mzJ!SAwCN(xi<#@<bqLh-o^i&xo*Ztkioz<)-J
za`pfRx0Z~b@P#5Z`Aai@Ak>7H?MJ3-FUc!faRE&VUK#mIUCrd+dfwf9iSr%wv6<PY
z>L5Pi%@m=ZI@EQmhi5qIikv10>(H~KE!Gi9tgWu~Hl@p?4k_8O)GZv^I>eV+(lAuU
zYZ5X9lf_4I+M_KP330KZ1#Go-1^Y8u)GtZ451cz0lQsd?aHe-3pTY(o*@n}|>YSxn
zOp2EcRn<SvP|xest*p>@mnkOex)|-YFI6grUkQS*+`@e2lRSTm{*bcP=TP4^$ML~Y
zBCoaKk+xP3CsT=WEH;S`Ls5!dcauSfTC+#6SH!1fbU4=w-*o01m_lE`s3O1|T>52U
z+Gf^Vo*(I`sy<{$%HBRXuOfh^Yva*JbOgDJV0Adxf|atjWeQ&ZS3)v+_r&NFXZb!L
zNb>~GG@Y7C*%|87s3!e2ne18q(E=lY=`2q}SmWL(rb7!2LUm8?YLT6)o*FE4g@Vn<
z%4OczI=hICcjNA=2d84GC7q+a`j};K_?eQs3bz>NOv4OzDbCs|K|MRtLN|zvNDIwm
z$F90j&|K2Qu<Nr56NUR|j^fQ=h?(Lo`C2O+GECQsLNP5GkiDnIJm*!mK3S|}7^uug
z7j741BAK*5u2$-r({Xhn$Ugtjm%+wco@NC7u)CKua@9;~hlFqQPRA+_Xw^>m`Rb}%
z@Q$&8%b2csaoksVevGv|fL<>-R8KRVD^gC<*m9Mn2&QN!im#L#HC7YW>uL!Fw`fG3
z6K_Mv*FQXDlwlVdLE>P)8kzQ1KSKGYH|TU58|-+wpRhxBI^YGz^&pKsTOy)y%P%n1
zFb<n4BSsu~`_i~iR;-?^(n9wl_#skG8~YPBK;xGBEvpECrCYJf?5Q;L1M>}Wj-8=E
ziI1{`uXv2ioL*4rB;U4jP+>`K>u*?gUd}Q)nS}5Ak~!TA|3}eofoDGc{tvj1xK9=c
zZle~zgSKl#Lo}nr+v4EQeM-nr;1pauNQn+i!GzLN%cLw;b>#fSf!eS)Wxby?PwV*(
zt&oNIL7t(IB?^+Z9TUrxjk05C5+>gGn8u!oK0_yL=(tfXOtaDUT&pfc+TLvJPs@<4
z4kHka$N+UaveYc(@Bs#M;8KPy8RJSf6uNTgn7w}pE0F_BYYp~NB8<^I#%1GZl_5NZ
z>I#%4V=ZnQ9Gz0t=^o0jk&IE#9>+Ji$R}Ucg`u0FFp9;V%PT%6y_K&S-ds?+>$W!F
zJXo93YKX7V4Eu8<*Fs0|RVj6EN!w~;sXRN3!3~m8zFm}hhU$O`e+65g^2On%&+5#7
zx?ipGHQyT(t1^!{(1Rbq7fIv9ls5^#RKCG(U0U}QlO3}P(bm`1o3qn`T;2=T_cQvH
z^3#pBtR=4R`}Vvbcz0`N7PNyhYwqPyR3<Ci5Itw-o|ss9IrA@7^2!?6ce=W7TjEa8
z2Be0e3w6Iq^n^iz6O?=ijO^*HJy+>r!_G}JRkIgvdCVJu*>X0rbhe7@1eEpJsAlsV
zwX|KeG5<~v@(&O@HXY#ax41fogunM3Pb{Q#oZv}`sh?RVTlaZG^>PA;hb;Gya2sS^
z#q+`JGL{#V^%xT8lf`?=L8jD4-&YMOIbUoGwy*!Pks(!Y**O$TEt;C+F~?kv&o4#V
zQg)EYR)z0-=(k<Yw@TzzpvcxtH<xW^K)F#{*gdQm8rE^tT6VS4EB*$H(e|(8VKt~8
zrB$-+xsS4MH_eVVwnC|&6bO+~wUF2@0odtw_LujmTn#l^?WS97^;O@w2tXRp8iFHO
zd7T=VYtndl@8@od^LC#|n^`R`g?oDCo8bwvrtH{hxi2kwcoUHvR+A(CQHt2Ho4ddK
zBjg3Fsn~qlYXO9fY*TY#uXj9~z^)t+eEZJgFOSxWa#9>8btREe7(I$_ctH7BA{9TH
zGu)BlpJRCNaJG7c=QK!A+`S<FsFmFbA@mP<+Rj=4tS#DK@eyBqg0%4+%zN??idIuJ
z+Mc|6&{TxE4LrC@g=V-)s8|l7HKbC_K%ymK#T~Aw+rFrMA;(OEJGQ8$=#Iq~u?7ja
zGw+J?ovB@8ye_ODpRnaYAXMhP)3t++Z>tn(IUZ@b4V7mk;RhLw|E-#Vf-7NfonhYW
zuZKKCed}emxeJ>=Xa=?yxMiq2S5BS~eGvp95X0u}DiV!cYtcF+?;IXk)RFxtr5<`H
zX~$3kqF`Yp*oyFIC7nDR-Y$unTr#lq5*@=~DyHNt2&Us$0YT1iGm740rm^r+Q(e<{
zP(T*f#@PmZADBZ^==?bf>rpl5(9wz9%tedRJ~92+QB|3=K|rXSGsZn?Dq+~-Hb*pX
zN#^Dydd*SivSq+p0KyctN+bJa&OlF|S!Hc4o}}BFa)RnoY>_+01LS7#<SmU7N+NZ<
z>7G9W*}UYK%G8e%9baq=B~ECh{n3U`S=N9>o^zb*P=n6UIclngREgXzhNH;Bvb82v
z2I4VVgqb2|YXW+lCo{&1^DGthV;z%q)ouocyM;-#OBiUN1(w_G3u`tKk*N63!U;Y#
z9%DjdjJSBN_+icGLQ_o(bZu{fB(+N&P294<suCUtf*RcT-N!B8L^Pi`PM*m7YuMUt
zT`x-z&aC%7iU-1l6*y1GVl=-8w-U-6p3A(ciwXp8E>a5GJ6+Fr?E@);5PoMyq+Rc=
z1pHf)-_aF!?gAk>w*-!(@Se~{LyXf2`s==1v)RtjcBB4nh|oI1*QBx@jX2kqvRm|E
zr|&dlZWt0!m~r3M8Kniq&$7s>W9KvWT#C&Fg4|?Mgh-QpanDl2B<?+onN>xX8fH4c
zw9$r4+rGa>0wZAf;~pJD3Le)jNK+o!_$KhZcG<|WJ0#YF<d@8M?{C}84X?(#vdwk7
zJz0K;cZZ{R<6_Hsri9v^F|&R0qz4PV{z`G~4aLue4DL{U>&5j%ts8@t$?l4A8qPk@
z2~x8{RT$Er%$@#@`|jXwTThPZ#R;#tdzlw!X3aEx8!|N8x<W;*Dt_3UBca)mB`{i^
znw>6|2`wOp2xRoEnCZ!P|B3qDXjvcbCQ*F&p+P<=utY}0!2K(u;ap?rss+lKf>kO^
zLvt`JVlrbg4CYe1?(^b)cLZLwX`OUTW#I3h#vWY=Vw}9m++gP3l*p6?)c;TA*PJSo
z5usnc2waM9-#Gq%i*Em&P^0VRYoP7+5zn!hVrkSf-e%7WARCL3N-jf<M@QQPn96IB
z>8Hn)((oWr%#~Pq9WL}t<Wx`~F}A?kSucVyrq-n{t~jt3Q6({qP_kOULdX@(FA`c8
zxfXG3%jb;xp7btQbIF(dcmcooa#bJY{+x54<9+`3HzVI4YQX*O8~~wif?%rWbJCi%
zV5yZ;0qh9efp316{W1siT9J1|DlhLn17A3V&_}KAc){nw?!0_Ob50O_S!1DmWl=vw
zGWu&l0XU;y{C>g@Rh%EdRp5)+TNIP8c>4<o<^v(%7kmKf=#Tw+gtyk>0ClUrvdo>8
zV<(J9Cq&<|0T0ACLmX9w)jgko@2@N$-#;sR1K>&^ceF19R*s=j-{6fZf&EgqPA?vW
zZxKPCOE&?yFHT`E#Ds4ux*t0**>?d@MoTxJ5smoFxE;foL8NG-E>&=5^%{1}7)f|l
zagn5M8%y|TD`zq~3Y}s_>5}H1wImL@vURc{Tr~)~gz21%*5i7ElYJWAi<>uH@%)#1
zcj|5QEU#*`n^#JDS+RMj8qdUiiu3a~9cGOR_rvjbI{oZimfhVjHrOQB4<@xOn8G$=
zN~4T(a(rfuu=H0OB`E-Ycc1nn#0|h0Az@3M>gKjV6R%D9LCP<?ik^@s8&SLOl6Fgg
z#l}$dZjhqq%3bO9l|m__w$G#j7GPLTX(QMUONw%6l3_?dKbX-%66c6J!Ds&$kE6w<
zuPy|m1s8&O!Vx%Hr#}sAdQ*>VhW&4C+?DHS%*MzypN`L_*prTxOuz0lJVm;TO?s9s
zmGANAK1;J}jze-(L~3}OllH!BfPO;q`O03wl@w^jOU>t+EH?1?)r|AK@NK2!zP6r#
zt*)JDMeiu{%fvLQtv_Mx-61B6a&aT!0^CV>o0@zjY}vD=(kFOi+~``Y9+2)cFC;;+
z{@Qse+Q-gz9@J{EP6>t7U9N(duuFVoFmC)MZIjtD>)<KqV-6lViU$Ra9ccuOl~nP~
zDWo^%!P#ee`|HIhabbr_6(=(B{r0?c93gV}T1SxX*aR^~E8A{AgozN!Qef+I@#lbu
z`dR8ef^+#YKHEx@&BTvyb+&BLbd{dyqQm4>3~{EE+70w`P1Q~`YwfLQt(M$<rsHPA
zC3Jo{I8E`{8=uBoN<OgEX{@DDPchwXN9(V0WHaiR>-8FOX}I21(e*r+xCgTU(>xRd
zAFo{S@3GlbMd9aeTd*-*+umNOeO^4poDg~!v@l8upAt5)zvu)I@?s>WNjI+=e+o6m
za6)fePCs=$pqcx)($c#86>#U0Z<Cnfcd!|aL3xh6i0yQjiV3#1t2b73KJ7Hz+4Gg^
zpL)qDt~6)uM&7$AUW$k6{3`-@dFdd0R!;I*bR&W(24xEb?seLP@g_B-lz^{<8p=@M
zJ3weg%>*xd1y#>A8^*NlXV1fiI%;t0C0D~qTsJD~q{!BbxX9kFjx|jr{;3_&3CDGz
zv}1(I^<12QSX?NtshVPI3aj(X<=fm^Ud9|qr7b;oA4^%Mc$g2qel)9uWwJ7z$=)Ni
zT8!K5h223J;Vn}yBUedKbe9<=;siiTDJbmLMgel!l9s5Dm}2)zNwu?@M1OJJu@JEW
zkgqxKw0dR|?G$X%<ARTKjq@gk@02X+*vB{XM76jM_0+j0EXCV0n>6(x9MVnzP@3w+
zi?(t(EpU#0og=hIsqW|=`^)9_DM;#kl$J6XwDpNs<p$LJ2%W!E@ek9&x2z`>n?R|C
zO`EAX773*7nJzV#oE8O49yyETuQ8#z9p-E%2cfjRO$(`;hwkeCG#bEN60dtwS%xNS
zrn4|>8HH3{snBJGH|;N5PmxMyIt6A&j^8%w*T29}=Hr315l4}<^`_#Qh}k^R-3mQW
z^_=G8!~C~OgUg+avh`j@Co{k5UB$x{J3}hjf)iNzzDPdhTUERGSP<NRFI>&NEwAmQ
zp{ve6P-8J8+*{R-_vxcRNck3Hy=tQof5qU?H;YL@mm9HbT{K;V#={P^*c>)GhVRzD
zS@()M7gHgAD=KN0V~)79S{Nv?qMdchWV4adiW3l)D*9^7?aduvD+q*-Wf`X*--T~k
zeUV?gr0EewGZubi^~izd<QK;zPP<ZUq!I<Nw=_gkO;4HQZZcGT{3oQxQ`34vbf$v=
z^aqIiUbTpt2CPhF!xsj6h9dfQ-j;VMI60*TeM-d^4?ejfjbJj4?VV^m$8?TEE_8a?
zqWV*m%S}>I{OIUPlh|A;HWbW63`znSco|99{U3SVwr)%s@u}UFHiAnj9@=({RugRJ
zi@v?#9qTU5t8P>-mZv|~@WE0?Y<K?hY1MfTyYz-SZe{Qd;#FR;na(;D!@$YE)uo9-
z;RE!sY;1Bi&o*Z!JCiAHq<V#}OO>$)5c#2x=^h9d$X-S$H8kBBTdgfoDBHc#x<9vu
z*MspU3n-=tV^VIW`Wb4e9N2`d6R;GRonNPA)tg?yxR`o8Gq*HuY}Yf@40JP0XGfwe
z2IDN|mH2;ERCk)0KpUJ>GLYyCiKWV+ZK1)1yme!#7*KjVd0jEhS{^;i3cmUSQvT%C
zl|}a9BX3YA$8rn!;nl+6$gU$lma*lhMYHP>#-^|J4B@CTmEx}B5WR#DZv}&J^&h8e
z@J~=4sd9*Uj=>BL-hRsMVLnH>aCKdR8(5$*MeUVAIL6_&YVkQ#WG?X2O-inNYdAGZ
z9>b*)86d#l7<V#go$!kOFuMtM(thApIs(W`_KnZ$`&OWb5;Yi<Z~ohLe$DtJGe2h(
zB~B~6*&-poUHQeno7<D1BeIuIs;9TQevA0s^t*})6XEpJ#=pgLL!V3Ss5}0kgyLAm
zRFXo*vm+OSIid2rKcDPXn?<gN$y=8_jLm<0(9V+>dO;`;bUM%fY%1~?9;~reF#b~1
z?)=r1G`^e~2MOcl1Uo8A&%V1k8-NaAiz;lg)g4Y~g+u)H8gk_8OgmPQ>rlh4x5g>;
zI_a5kUP4ljjcN1K`RMc)<I|Oq{FQjXuZowS*L`Ii(dk}iBJA<TC?XISf6fAX>3UVf
zKkwR31H2R;`g?f(T|Dm^!7%g(5Fq~R*?smRed;&k$<kN8<&IbP7d{K9-`#*vBj6`^
z=jdO4<7&;5*33~T(#uiNf5oufXj3eDBEYUmvg{^mwMQlkC0a5QPA?*^afZ2I34HBX
zBtQv{iJfyynag|;w5Wn3di`n!(uL2=J=}WtB$-;&Rs{;uxW6LA2DP=tw^gV#UkRL-
zs}$geZnn*ki7|6k07ekf4ToKh-f1<2BV_c)IJ8a^chcx)AUOyScjwHOF|_93Thodw
z%k3(UG?yNrY(4l}z0tFF<jY?xd%G*SF&h|->8W>F1tLLxJY%;gM$%7q)`JDbN;P-h
zvn!%T!$#mv19Q$AQ-84D7&asBWVDu^6N~9MS6D+h`Ngk5*14k_<?{$DoMCN>B{onO
z9xEKn&U=&PC_%rnN5WD3S68!}c6OUnsghpTJSO^1n!Bh;a?Ci7n<@R3>(q{(Q_pP0
z+V<l-(P<q>;<yhOF~o6^Q2W9XokliY(qRFJI5y-?+8!@(d4rtT3j$$rOYc%jKk#81
zX<zK~2h-UjuMrGIrWW8Mi3Af?!rN?G=!0w;C=I05PX+i21jpXBO27>{<od>X<C~p!
z-*P(cS>hgGkSBBeXgv~huGT`O@7#YNlk<8>yWGbg9uiJW)|9iVq;cK;%z1#o^dldK
z!#j{kvZK+kH`;9dI6V0H9Ynlp?lH~Xa2g|yD`q$n`n#8=$YVFpK20S#wg%-wrqUm)
z-q;WH2`dA9deSw}jvGf8O7lJqXwg3D9F5?4sEK7FmLeD0zgd;xL;Vnp_V~+l(Zt^`
zw0jX4^yBc2If?&AXf@QmrSlc!^2pD%B`oI#ac9(3WzuxQox%fcr9CM^I+_6P+5K|c
z9&FG*qS3o^n@bID*mQSIlU*=(;$`w)02cSf-WDhTsui3tVxs`aCRrG=<$b(3#%z3}
zD!2(+^B~#=U*--CR-I#bf`1I1F4pb<`Co09*KYMSr?V85Z`eHgA;l5eiCrmvOmiS9
z9PHxO9%GEPDz-MC)`Ok=#z|(+m~D4cD57_5`^V5aKNXohz^EG+4<Zfvxim`MfTgSk
z0<B4wI~|jDKq{mEOTigsAO4Hcm{0j8xp4&=en%i5u{!fDs95P25%$T~=#x2R-lKnE
z>zjGv7ckfXuHO3j5(*D+`^s-C`XGVgZw8rDLI4{Fy`IEAC(eYw6OiZiZmeKFNc_XF
zy0V&yP5n_^?g4slexd%U@t-Ddc&tQbh3_!_+s~2M_m_U)=lV>nvzquXh~WJ;y9l9*
z%S{>1aX~w#pY1<}k-+<#_aiDhORq%-(3sz8W-YhhM{BzyzzcXNcrqUTHr({@lq&2@
zKD;{T@4TKkj~EdZB%~1(*dSmK7yJrKK!z36N}t~=L#qa&FWERF)!!G5(<2uwCV}y}
zA<S4cC$3tO0&ASjq3XTSTz<j$^HU<B?eco3`WFnV3(Ypv<63fSL5o+uqW<R%BK4A^
zE6EpnlmhG9H|hW5RQJDb5dZ6y|K_gH{(>F;hnJ#N2i{j*8~3xIN6GuAosIMv7zSG{
z17nK`<hlZG^OZ<f`p}Bp70!@@OO8?Y@n}wts2_b~!e8@qg4xa)=)Q0^(y|)xHr};)
z#k{Tx$Mbxp6a9*hx2T;?SvfK0vhCygv(A(JhrFA+PofifrMKrN;5WQGW>{=f=rJW&
zq)VDX7hjPfCSMf<;{BHfh<HLHUkQPFRG_rq3yu&|oA4fx`i_>_UA_aW;P@pr)Wuf|
zVO92p;1@QKNc6=k9-qSZJGWfr5Vl_jEcef?p}Vg}dHKwc`pCT+wCYA}d;hqD3nO1(
zjFX%W369pDKHBlV7V9PYKY#s1zp;q-j+uy?{XiTf7js|h0U>6o;Rh|ibz&jWQHLQJ
zaFnNS3;-?eRgkP!uR`91dd142&Z&lAL8zZrlcut<v|rRJ*A!J$Dj!3M!R}Cr@R1Hu
zYB`5hUqGuKBx$ESUB}Z_qfNu1jK-}S?;A~%U|6!i(<571D#C9}Ox7R+x3wlI&XhAq
z2n$awEs_GEa<*_0a<{tKuxD{;UyLT2uH>qEg5(xK&0_M_$8zCigJiRE8mlRgzTIg{
z#?3a>;<D;2D(yLnt@t<wb>147Pw2qeN0kCwS9(8yUe)P5xtwo^sr9~KyH2rwv|)A9
z-cS4CKNVsZm_GxTTprPJPS#UuSN3gJougez#dM?W<mf8UfXQcgqH;&PkL(OByhKHL
ziEAsSHsY+Df~3ZvpOzX5k0`Wd*gSznj%sCad6HJ!>3pHJrZ}7kC-yDqyU{hU8|Dt7
zsZ!_}yoC!{E>o{zvzFF*?gI+OVqjhr2`uf8=#6|eYa_sko*evg`<v)4KGe{%FW&=h
zsb@QmPLzA*fs34TJUPN*^%W{7ZK5)O;HV=-WrK>t%(^W`PZ1e*1hT%o***rx9jO|K
z@GvJP%T}+oZ<BnsVNciqZ_GEJ7e_aDOwihHNccN3FTCO^`c2nV$1*K1KX`HBgDxG6
z&gE~hH@Gfd)CH~DS{;=_h=N=Fq!4{fje1<GLe~s~juUxbbX80t>(%(@4rSZ{Q}{y&
zq}s|K2TgKI&@kqn@7NRNh-~gAIzKjxeI7?DyqnJ5B$#Sx&{A1NTqNB&zQrm;Gk$0?
zo7TQ#c(wYt+8LoniCyZ_Hxq^fvYw!WSGMaxR@^awQ-0gG+w>N!glHJOdD}{j1+>OM
z6J4~1rb(E`3#kFQ2WOE{KOWKp=oiwlcQ&Gd1oJl>;Ub8%I}(36PHK2*@wP)w3C<7~
zt<kyLpItArI{RU`!)K%d(|3`v(s!A$V<WflZ^=bhn(#33)aC+FKVZH3k6+?qD{for
zOgon>I!=$MXo0byr1U$4{IolQd~CQkt$};6LI3DlMj~x9xt{gNvIv^>QFuaNXBZpU
zCdW^bi{x+HutDFwsa)CTE2^Uc(c-FAO^$BN--wteUqWy+deldW@2KO2r(WPc<h)1^
zoL;(P19m0%O;WO558BlB3n+<<hJ-Cj0kGnKN=X?t3h7(_V*U_D7_6cq-4+COf8yGf
zyBwU{kv(jzVDi`)1yM&8n3SfJ<1vy{X6oRa4Z%iFqGwaFXb`8$NGO)s;$^7Jba~$U
zU$ON%^(Z$xkls(H!&$P2v|_bu^aQN0s6-IO=(hJs%Tg^%q!tPBBuQR{mKhipg&3*N
zF<IztMiv0Nc)GM(CHj>zV)Gb=YS_xN-H|vPPAj%2mHHiWMbC4w$Oj7vi8ntMWGkw+
zbJ1#xMak~f9hfm?_)j)rnm{LyNZud1GBgNFS9+7B@lN@9YrY^OA4*ju#6`$NK1{<Y
z30F5|L5&I!t+F0wG<!wtE&VTaZN<-v*;M`Siw>Z}%b3a^v(LX4i|-ZhBt{pPIa}Mt
zer?{Ni7^7pPcIAyH{uu{dn2{@mL#SL8tAb6mUjo^7#$qM-o)@l+w8G7%ZG7I9ulYB
z7Ywkq<H#6)dep6+D|SoZrJY1E3RqWF!H~p^*2HD(=t>?!zSC9MwSuZ?&6y>e=}mfN
z))nToaz>kR%nz6$8VIn#3NJ)jtR4|SIpEkp$%nL#&||04tBl<s1%BwSSMq#x_mnW`
zfy5vNX|UHFVD-Lt#B}1~QP#ca2LG$B-jzFCFk%-MoSM%`QWh$CM_e4LPjwvWMbNc@
zWBT0}qn<R&sK33KAq001EntFmDZZ#@^#@yUbi-lB+i!$f*w;59VZwq==uTaWgaYEB
z+6E1eZ%o2b)#qOXufa}#A+S#xOa6ss(9BbQ><#sZp>;Wcb8;e+f7diZbu`|Xia(mq
zom#88dw$|t3b`9ve~q>Bk|+7n2%-74AtY~r^V0v)64{t|f!G+iILz}(f;KrbM9TmU
z76`FRw|^r}-L|W!10GNG&kksDyC_G!u@HoIIciW_#trK>Y(iM)#RAW5D##Rp-rNYS
zT^Q3+H|lm;o~0ic&y7y4)7*|?6)n0IYs9xVkk&#6l1sml+V{b%s||XfXuNf{-}j^+
zv;4;bl{<`5x-S{exRN7=E{YQRGdGau&q9C1p#%yg?Go1!m>AUz&($AhzG&XOm;_VD
zHO}z!-~SMfd2KR<gGJUH{*DSpKM?RlS2v8^@WyAeGMvsxkJ?F^ci2=`PK1xa7<ov9
zPKx!@hdhj+Oc!c-&f9o7e=mZ4LfN`Bd08W`v`i?@7Yvtr;^|sLKkTGtys4eA<&HNH
zHpL-<A66*I3VGCSzzi8)mF^fxYEW@%_T85fqzqB|_@m=F3(hY)yNku<)GV~rU%_xW
z4NFt@U=xBJ*?n6`7Kl@(0;IuWtu+*g9zj?w$)oxc+hB8AODq|wOVbI*W(8X$#*ZDD
zcRmE+aztV~ZG84Sr9BVsZoL#{O<iXopK4{!SkMP6XYD7(%AEcHLvyUYDeegwPmVKZ
zTS~SChSE01C{ocikG&kz?!8HRSpfe6ypFH)8?*(%%?tO4(|0KLY{`TIU}0Wl-XlX@
ziHfdNQWHbS>P>sKLbF?F?hul07i3fD!J_;fQ_rT09_?>&c4^f4*{`1_^KUD`odis+
zzz&r#!_tZu8&_;Dk+-fcc?cmqXY@8Nx&OK9F4o)3Kjy1&#OSN)j`ja|2>UOQLk$yC
zdka}dOQ-)ZwY>gB*Tnc}TQ>)}>i^r-oRr6HRn%L7)+h=zhF7};x33bASSy$BPBa&9
zDuU^gybGH=9gk(_>-*;RF9cZ+CksFjATqY|4o~m_JBHft!!5hX5hlgA-u>+FGuwHR
z`<mChDg5z%X7vqu-vDN+kva1HsB#cw%0m)vHSDZ{5HV~V&Jt-2Bi_J4fK&tqB#j-w
zx=lifC!<OSAi@Umn977#dMM~9hb4yNi%B6&jj%)>nDWvQ#YP`hda_jSg@#*UYE;yv
zI*dZqYHYZpb@TIM(C}kuwDCu^*imhLXHRc@yZyj`{Fiu^9b&n0&U%m@yzz_t7yydQ
ziZUsgQ(TYQ<AOX&jkJKI3-#?rpBhHDft)c^vRz|IvHW6_N)`KJ{0v7VH7$i5Q8e@E
zK6{#=MbxC8Nww>CWpEl~cEHwSiy)x3iCr6GBzNqz+;CIFBHobdPb@D>3{}gE0>%eB
zt1|CfvRNQn6k~x;OsKIp3@WW%Q$YrB&BnIEsEGx7Fz7EGsiA>53Pl_|!ZYW+4Bdy$
zCx)TxH2O34H<+m9EHe+GS9Mj~r0t2srySl;^X230vFKk7*u7ge7331PmYvmrw1{&y
zp7}Y*`i^59rZZ0VbW)6Y!S5-T)syE(XN}pml&ZDySnjjNx|9ojw6Qk%BbN-hRkL2S
zY%~b;Fvo>iLch~{HUO%jUnRkpP7G(R@&ctI0v9HpZHDn9hf-`gyf<J*db(!%$`W;@
zFx+)}kU|ad7SlM*oyN9Dk4Qv~#g6(QAuc>CZ}17BNlp~zKZB_3g8QmVt7}WL&9wA+
zQJoqmWJ@RJYN~cQjIjKSh08-Mlza@MQ@eHl7h~_(ooU#$30CZ+V%xTD+qP||V%xTD
z+x8vXwkt_Zdi6|qzddXEnJ?Eb*z4T;I!K5Mu4lp(Ry{;Ud)5x|deJTq8)LDEDA*K>
zR=t8KhU{5!NZMV!kBVDoR1`ScK_+_TtTklKr8kC&YriK8XMgU2eS5YR$P7(HnjIC}
zv{r7MgaNx%cc|Mv_7js6q=%N!-d9(I@Kvm9NTn%;)QDRo-|G3d*u5VRQZmAv=e>?n
ze4sX>VDP#UY|47Fb$vCHB$><oH(7uAC_eDnnHGOPgww`V<J@9W&PmX$<(pr&cdY%d
z2`hF9fUrkjmBv_+9M2tzsi{ksd$iX$$3fYQCGV8C>4v!pN!rFIMeooU+x7iMT_MT3
z9n;IGUb$^%Fk-^^Mn-|vaFl1)+NoEb^YaPkk>#-*+K2K-G8@%4nEx93+qaF^tQ6C5
zyIDOFbW@6N(ziWoS8J-k0E~rZK&lpXYbLIUsamMUf--wGvX<!9hUNipc4ytVm}V39
z7PVVrx%uvw`5)v}P^4a9Qk-|VfsICK1>(cIkgTzSQ0>uugjI-9M99^@V+A3X07uZi
zvdFl+w0vyASY3sMnHsNp$R3TzoMHEc1o943e7wS8H+$^r0j+mkbBQ)oPUP6Mi42Er
za`Qn?)!E=pKThNT(D_ME?n%2s=*-Zcs%xS@mq+$Jp==bv_DWW%W2Si1GwcS&YzW}D
zgP4Ebn0$68Tq4eZk+#T*=XnEcKqD>UM3VtR#{-3vaYoLFrhf_=byYm26^{)HoEpm?
zjAeFYOluT8o6DWV`A%9ikD;j`$Q1Yj6bd4gm1R_p5d5fHQP=qu%6&S=zXf^Z@KPj?
zA9bMAs(V5sdr0bbP&*<gZy0p<Rb5dZy&zTU)awe&=o7T`Tz|TaU`$Wt?OGMEIKzJa
z{P=vwFFwMbUG?mGM>h$y`Hyk98-n0f6YAyTb4`<fqFbL7%>`2%b(2*o0W(pz()4Pi
z!j^(p*!$z6Z-9nzSCxe#Fho7{z1J8~KS9~H{C?MI^fog+WQ{k*6J4Ql&4Xm5t0z#O
zVIO3TWc0gZ(7;@Qcnycj5Cb`ZM^F}{4N$aGu;y%meq>0NsiK-W7*HqRO7eUp<+6`_
zDIiyxU0f~2iF@Rg?=p?(xq4Xr`m<h>Yo8F1cK@LEaCC<Vd|v%SXP+Sbd)n{8beVrr
z^oE`XTL$XuBQA79w^!8G843$fsYU^6C7(ehG#CDj79VkopHdTe16)?&bj~Z%My48M
z4p3b=_QKDRp@{T!KvkM=3h=Mq90<jRSa?r&282H?Y-IN5EIN-4X1*C=>@uZR9X9d&
z`SARSj%k`Dhih?A-!Q%*d5-F)QfOX4Cdx`-Noz4cp{rC`$$Cwi9g=vF-=p)W3&1^|
z8HKQ01BqRHq|{~zFOf-a2>%scXxiC9-v#>h3-m{z%=sTT+y9Cq2;1Aa7+Tu>4?sah
z+8&wl_jmR-i7e!kC`_`tJ;}K-B5IjP0s*9BILADd#1>hXnvujo%Av|}Kf(bxQaMuC
zxBoZAum^hz5+Z@9gT~y@;d?LU+{fqNHs)V(4t<dL+F%~-Ib%6IH_+8C79{!;3R!0@
zifUK^5VW?PKqDwGCi6uSmmC-hHYO-C5G$b2VU^q@+-ypF9u3ORJ)DkG5O!%?zU#|D
z>CsCU0I_R?ffn$jaR5MJJ+wdTfu1s27!zmVY#Z77n4ndbxA|ds1&yY85$!IE>wqdv
z+loRz76R8Y76&AtB^AD6m#iq8*YTsZObj^A{FhMU^6ECF)DlH3vZK@Ls!uu+iigK~
zA}E_VR8Jhegzu;P*ZZpa#YWFg%FDTYk|w1(TJ8)&AFW&HKhv|ho`rDJyFy7e*{o>O
z`yVcgB9D6Yqo#ws=U-}U1aY2Z=}3o(iV)DN)Ho5j!yS4Pv4UQ+6;Pdy<=@RujJHpY
zI|6QvRL@o>jf1#94k(&>hVo%0V~rZTA>}uIq9@GScv9VZ(r#`Xb98xYL#nN<OBOrY
z;7GP$RoM%c@Z>`tdrRneVQEBlO}AWZ9<J>`(&$Mweu5{;NP7g%5sw4`Qb{J{3Ogh-
zWOgJEWOkgN|C`qLv$)li0`b?cW4d3zc>m+n{I~Ak|5ergzfX=9l!rDT<vWh}@5F<&
z1P;>gDiFe`YYk1vDBMJFZbCVmu{F8CA*9?AbnOTlOj;=T5}J_I)EgLSt<==kb1_01
zr$A{TN@?i=m>joK<|R4v^JZl;i!$b=0x+q6-g(6mlSwtjEW76Cy?<vpU$>e*Pq(VN
z@5;#Gfi$S-|1w19ef%Dnv$~Ui>p=f!v#0O#rv90Q(AVGReJ}m|MUDRr(#LieiNN|M
zkN*u*SDCT<cBlQ>hR`?k593Xr{<{vG`OX{v8^4ZnkRRi%C}7n$J%$~&`+OwN=kAbJ
zcyGv(NU!2<0_EO8iK-${r6Qq#ubZy|O+RKi{5+|`qeiTB|5Qg&P62-jE<+HvcqPm$
zqk=<TWvK}^!**Pfk0vz<?w<NadHJ&<G`kdyXFKfJDfED|N$kP|UNyN1<#pYPMcp_1
zFv*i?Hy#YosBqz{K?)byyFeaQJV6emd6h)kxJ*4&IpJRGrBN#}$9&|2zcK|D`60w=
z^&%DJrBQ&_Eww1h+Ng9waiOZ`8K$mQ#g6V>0*GhBr%QrKR<gD-snIFqTftns8A_Q%
zNUc`y#)dstxXRHxf0z^#-MLPYhC9DERPX|b=MiT4tP!GPG_J?f0z*!}SS-i3iB*dX
z%0ZSQga{LIce3F$yr(rE26EyyyczUkH3SN~8H_`Z7!e0tM+mf~;5bQWfvQpuE;u-q
z<ogA{JlC@#wFw8rR2)fAb+Dn~w<gm5<ka%iG{n<#6cFRIbSVvixOLBAg*%kC5~DQ}
zWz~3S@S2nHP82Y(cGnvO<fk+fH4IE6RpjF;RG!u?V?~kC(&aB#hufl0(<=)PTnVv?
zi8oeWQOOTSiqg64YZyrLWUB;f84nSw>BOil*V$wQx0{l(R^GrNh}D=-$&rdpu{>|q
zggk6P1-Uhj!H*sgJ`0IXpq8{K>YX<sajTOjz1)Snh5OPH8wiE^oKHI6Z^PCa@0XvH
zURgBK${fql;tobKaiGKoF9-EQa&17N;a~cJD!UJZZxn4B_e^+jaFq{wgtbgTi&UQ(
z^k)z!BoHFeWRfJ}lGnPAr{qSM(AaTzKPTP2P%V0dI%XO*gI~L<v7ji<YH>lmcB)aY
zYxfINra*DmF1m{C)Uw!7ypjk7I_uD|q3oDKupBN5)ZyAUN&5J%+vzycBwTiu{qB2q
z!)f4(prhI8j|^>OQSVmvPEvC)FJmoC5I8(D1=U;O6aIi(w;DgLb`8}TplUtY$mdOj
z9V>(qu0`Q_QlF0Ri!CTkB5GfP8rnhRmUyyF_dteS$$kiis$(J|5AS@G%1DQ5<E^I?
z9uo~AbhD#8Fyyv8r`elw$WM~zBu;vc_Gvv*;OXYYJo^#Lb)1$vt65&TyyUA;de_nT
z4@jh25Odf&0RUzx7hK}ntol)e>X?nPZ4`dOwPbF;4RNQIJcss+!Pjl=ogq<a1!!s1
zdI)nKY%3BZ(iaTf%fN~DK^yJ`)?YZt47mA%QVu%F3Nc+dE^%BhP>1+2)fDU3Ba2;%
z4*dnFFk?Zv2BD6HnbRYy5*K8(lvGF)tDAAMT|2zr6>`MtN)`92k!L80P&biDH_2vL
zGV_zhkD@H4IpXy)Try$WsML+D13N@FH5^?gG$q^MA<Y=`J7KEx&%m&^y0wgYx<?=b
zU~7wPG&-au)kce&4XfIhlVy%u47rgm06dl1!Kcu2(@8tCXU!7R?s`4IY3eb?1$;Vg
z>Z3hVF!~+oBijms!a_DRU~PD9nv*(JYaX?^#x1gI6SNH;;2}A0T5eYi^_=K7v5>dW
zz^O}(@|yX(FQZEL`Boq2J<L*U3$jv@N^R>pvIWB9A~;aU{DX0t(6WW>3(q9t8D!=o
zr8zGa$_l7jW+B!&7gC}`>slkwR+IU#m`H4<VOJ>Gxtm(bBs}xQzetHWriU3xiH1T&
zWFw%A3->Yd$C9l{>?8)0i;HE}NxL)$WINQv;MR>NT_5BI)=gc&f&c7>x}tDtvmJYp
z-sqNY5wK@EC2i4g{CPl@@pGKR%%fGCs7#p?NE`2}P?;!ABgj+qU>ByYa;2!|v`1W)
zRl`BuuHi|f)L=d0E$vpfQ+B>(KK^p*qQs9!$b29?9!AJ|KzuJJ#AkL4^4W@)uV2h~
zkn9*r=02udS#xTdPVO?T(>hcp8+GVUmY?DcPBXSg0cCbAWxUy7KQT)=@&+rDT^3CD
z5V&DJ_Ir=c@7PkdsO>!2vN&LTuhzN+QsyJiBR@-j09!YoL_d}$%N=?w_0bHKd5>(|
zWmE2@LO@%m?9z*GG*;YhJx*phvM%KzL8t<I$$ALCVm(q+#!DK5lgwf&4PNwuIEH%B
zdL|Qdh@m`ua8=Gt4$J5qp>T1G3?s%>ev6<COEwBSrhH(tgaa_`G8|bd_g1V`HP>Be
zKwgAai{upghPIT^ssFiz1dkZ)9MEW_yM%-bs5*4CR@u*|oSSqOF;vb?%aVOh_4%oe
zHm)Ho?aoJu8F$w>k8(GejFM8F1NTnmdb=>%ykvP$*i1X>3f>wtfv-R|c@*)NR)OXi
zw)0a*`^cr-O~b!CbIf)}cTP(V!K&@9Mn5(<P}GqfQ!|zdF5gUO9xph~=GVN6g14=m
z-}mD(667A-lCwR$Uxt)c$0M1hu4_78IP&NO*c4lXeS{t~Y|B-tJ3)-(bXfoDEEZ6&
zW=F-@;HV#hCwp{buc-&@ogbX7L`Dq4D+YLbFpOZ%v>OC$0tw--LsJ0OBe!%{7~EYC
z0z>T3@tvm-huwnV;tak6ojNH1?J}4uPmelhx-A^uNI2UfS&&vjY%o4+k-@KPNignL
zHFCd~MM3hBj{}G<J0QGb3rrVpO8j*gQl^g0RS%0VQFUNu#_Lbb*J<r)N}~Fv^viIN
zaa>o6-AlEqWGd%qAS<qFlB5?e;%^$-#Ls?TRCG(eWd4xmypxYQEEbo@@(tAwY}Xf$
zTH>nYYC@R4X>z@%Q8gk!dQC`*iyv3Vd#MlfTCw+73;1%)F=93Q4h-%%CIa?SYlOaN
zYgB7o12awow3qid!e$+$$fxM3n4X!f#a<(-^H3$S3wNxPn}TJo$ToD|&&p(}G;YW#
zJ?d_|$1+yV&8O&{gVlfIkgWK{=@3D$k2h+f|3ca`xx4G~J1U%0VYLv!>&U^3+UA0J
zUnOYhs8`9_ABw6HP`8>EKFSve;#2HrbZ_IyqqN^y^q<F$fgidN?QgNCWblaMrgBT6
z*j0u0>Zf%nU4Ovv+<HB8u~PFbHS4H8z!%3i9RVZj?=$W+J}0(1$O5IIk$XR)QdDGP
z_e}Pz4@l4$;;-+ORMh80M>kT_3ny=aC(kE6?$fMpoU2>!#u6;Ao(-&xmmfaHj49`l
z4=)~+8WyrOn=Ve%xkB+2sFaL8eO^lDPHTu*qqplYcp-I?8W&i(TiLtc&)h@<vz_WG
zeCe%^f?^XqahVdVR&vI*AV$tbC^;v)NNUPjG{pAMY0bG#J;|(gkm1FR0OF=-W~{xu
z*j{X`H<z~;b~-!lXIgInyuR1I*VtW=e*`E=i;l~Mv=Wsxd$cqOlLDTP%aG$<D=!U)
z=5_2g%(S}MxDlhn#Ivim9%JK{1_YlsyPb_VoD*q~Rn}J*5uVO4kyUK~A8+8q4FNmT
zBmV%%E3XsZ>cfLher)N-9^KZ)tF5d#+rD3$A8Ptr4Wo`SoBqgIsw?B+xFrqfDX!xa
zI%^6Z(isVRJC!oD5=0xbiY-0Xj~B5ot;7W#F>_ffPtbDO^Lz<xI}SI+oLvN>k94mw
zgwzWqbL+X~-&8!(Cz&^yCe_5Po3U+7c~P_Gm{{tq$~m+yt*<Yw?z)L>A#m0o5tM2a
zD$99hA-1%Nw&akZlGui*!xv_|9r3)|tO<<|ieZqU1>ZxnlozA1#Pnm1Bnkl}d7baN
z1GkkQp^W2xv84nf@_D(saZ)z@bg^dKDr+&;K)hHZcv79Q#!0)g)7+e$xrfl*QAOAe
z#3ha?k(dk$L+|R?@cD)N1f{<@c$pP5#8k1w%m%Z>T+I)G-g1RxR|{FDSxVWwv(x<M
zfMl#|pOOxPPpJN+Fnj-6${UP6srJ|EbNtN=hFJmOV1(6lGa7N2zD+N`PjYj2WOmC3
z8#A<<x6c_86}!KDV#RuTdTN=$Zp_j15)H!P4C^|>M_Rxa!})D>YKmo!s_@}!nLPt`
ziZ{%e;;?e>{nLWYyOBxl7}(kZ;hP>ZlO8lx|698OCCwPMc34YiWWA~ZnQ#$dpLZ>w
z#|NwER&PK0p&xJKeY^QowmpMyD@yv^1*THcna=KbyzDCLajq))Uhl&IUT@IW1E06?
z_uRo(dk#|S!R6a8J_%d3eL^2d{L-}5gQz!1J}G*;QQaT1TQ06AQCrrtBUXO)BX2KS
z_@CrrUt(5QkjkUtJzCleR{K)FF8B>w{c3+1tj|V2FZd1Ej=*@oZ@Ye&3>exWb4L6-
z4Z!zTo-?rW%bhLiseP&DsjC#aEwBEMG`dL~Y-q4HbX4@P{MLRsKq!gX35}M^zts1~
zqJTMe;MZpkD-DkxO^q7R_rQ>0c0Do}jc{s>&*q&RHgd}uZmNvounso2Eia5|G0X(|
z^h$-L;A@}nHZ@<-ms6}6g}I@a!je9q3t)niGs9w81dBQkHf7m!>a;?|ZOv5M=zr(y
zJaXzZhQMu%s%?*uQ@FV)5VX!{&KpB-|90wh$Cte!%)|1HD8l7{(jQglC`@sR?aOfL
zlaf|*@;$zRwsOM78(u9ha+=pH_lb)1Xb!?#-0{RPGWZ7$5_fm2Xm1=~4;r_B536wn
zXc7pLI&`GDwI3(VApFbFL_ogCVGn!CuM<q+uCUGh_`8I#%tM&WC?!!^1tljKnmm$W
z1SU?s!e>=mrueFwoZXs%@X__90^f_t@##11{&APENHPrkfsi4r-g5rezda&9c6<Tp
zrm}=0)X%Q*+xy}MB|_Oyw+#-pXZ}F<Xv61y-!<o8Q6O+ry=*aSEL&*dah1BD(7SvA
zsRBS|SHp^a$v{b?8|}amqE6yyr`eD_PA58C?A?oF^)3Doc;ux-QB!LaK92p7I@Y#v
z`_tVw5rt>ALHwwUsX0#o8BYX^17wXyB;y-PzzHYlJrB^o&FE2d3{`q2Red7B)W*}M
zWx*070>s26;VVtFvx;OVnb1&Dbh;gI+#{PrI@fS|O>wgv&IvRXHNrVX5T0+4BAHil
zVYN_P?kM~D3ylqjHE)vkC8m_Knu7D>J|O*pON&~s%<J`1<9<E?h-{<DWyg6dvX<Bh
z8x!zA&ot?^=4qzug|CGx{bEL=xhcL0;3liyK8nU&WMNyi+YcrVkjI3HJ7i*dF^5#$
z)^qut26HnCz|kSxdP}Jm^9vnQwY1?5ucGEKr7Yu*Bb~hfSqB8^5D2epVsjNrnbnA)
z>biloUU^^UjuNXD>KVVuXT0zmfBXv!{YUD2sLpa*7tvBTU)@(g>L(rcE!X8pYU{|Y
zwx=DODy3vs+@+si{Tufax6>!GG1(35>5SATEp}t_;va8kt5Db2gwXTN-wyXV2RY7T
z6c0V|xvX@<JqU0;KjbfPKM9FHF)g2dH7)bf@E-r*zMhCbIY3a@nSztIN}lCXwr8m}
z7w&LQ%yQ*1#|-*v2dA?>7-35g&A?0ne2W3gRtA50LB0^uWBHMgcgBZeO0Z~EZW$5&
zOnq^;5A2-4(G)~_et6!yzd?yh)itrwD=^36x-8F%J5Km*<CL&?l~d@A9RJg^KgYj|
z%j75pQ3`Ln$a|gpufU!9lfkI-4<+@6^y`<ve}rH}Ow9~`!Ug_M_?`N>I<h*-zn*$n
zk|83M4J*-VRUu%|hA1qZ-y({^RONuyjWH8QkO>*Cj9*r-8@{`*zW2?$JY@vUr_Fvh
z_<)z*jQ9}}63c6d^tP>I_dmD2f9<|MFIRVgo(?LpwHa<kLFE92aAmw4L19}QQO<Te
z(c)VkD5oQ%V1y6p*f>dc6p)e%BM-^H;kp>%WM#~UE!2cWgqp!Sv1b^zn(>e?<Gc-s
zZp5f*5KKshU24G}k<dtVP>j+@bW-m?g?+b}WboAD9C%R_WkYumhhQN*qN$gx47B#q
z;xP6FlE-9NlNFZx6M*bu%+EnFD-S9;%b9GZluihT!of;gI9Ub$61K22&<#uIWipb5
zJyQl1RE2jn1fxo8h~qjgCWlN*sxnT`uQ3dL6T!z!V5&B-@ZuH48G?^qz29AA!>YYn
zcA8xqbDYi?Q^T1Aj+y_Zm5v#$1`=*t2BX$c;M@DfV{C=Cu;iFo;M5O^$PY)HSsP1M
zm{iF*Ku+Ae$YMmn<CK||nNE(5`Q@4>bX))?8l#z6piGdm(u`()MlE!f&ozRKNR3<&
z9)`>y7*@<N!1$Cb4Iz9;5?7Uxin$?85>Y^!6%o~-%61~fys(-gF2@XPq>h2bP{?Q(
zshDT4Umxz^fKOP7-PX?Jojqnl@Dk&xG^p%yj<H2~afp;_R*t(m$km2K2K0UYXR=ru
zw?JZ=iqvQr>T$M_adYDl7-J~HXTviA?6K55yw}ataj?Z!eYz4IlS_(C#^S_-Btba@
z`rY7+CQL3gA~6W%fpl#B1~+5hndkSu7l&qEU<b9(V#_=+wAgI!+PWYmryYrmDDL8L
z$$H}o?=2dcgrP#oBdLv*L@0tE)ZDlS+T6ritlOk3=G<XqFuF;1cp6DJ%^_+x)jlg`
z-60&NyKz-C`+aI~n`w8DJ83uhp|4MWeM|5n=^>s?(mf$x;$1_u{9OesJ(r13=-dyj
zMCk`R!$$6cHe`%hg&oS_h-lRm&8B$Binl;lVJmsd=R<fX?L&HK{o@wW8Wr@RKIHbH
zKZN+CF#b)fNjC1f82DH|Kar9S&yJ`>fEhd{4D0>v`(CQu-RcBXbMs)wr(2&mi7IT(
zr5Yv)U_oY_Y>7s`(8I1H7_<Bp3d=k>(ZpR{%l6~nT&dM0Nvl*fb;FD~3Uw)Kb{IT@
zSE*yyrz~7`qKYS#-1uh7RumWRy@D9c0Ph~@hgMU99@#dHSSk{`5&2h|IosV--q-9>
zFF-~u#$t8WTBe*TR(IH0oHRZ9Al17xIi!DXAw@`4rn+5B(o-?ZxdpqV@1>+Dc|(aV
z`0z^v4lDeQgVkon<=45l5k1oMbq4{G2(4~?MfjNooGydx1)gqBncvDmr%=dAI{TQK
zWwrZ}w;C3tRU+wP>|)Y_E`j!y7Ft_KcK$VC#$AnUye^sxp5vlfkx}InR*bfpP=lQn
z0P|qSN$0ey#`=qC{4yC>BhQa3QH6uwmF{#ZX=|6OjpVdxDruZs|AZ6SMHa!F4Gwv!
zl+oT@RH!{8_TE6wd?%qT|M+(1GAD?$Via~sjZf9Dt38!@tXkslpxcrWQK?mA1-}sI
zQnQ!u)g@!$i0HveDV{Yrv;LpwT|ZVdOR1nIkggcNE07cmBwM7IOpz|*KNW3_ealyC
zNHWcO<pSjWD@)ypYH)ddk6h_<eXy%UR6gIRDv4Y4<r+c&q{=ix+QLvbYu{##CeSwG
z2G}{c@u>1g&c^2{3k?xs*^5Q8)P@@>EU`brkL#tIowdea_^Xh^6m$lO2C9Wozg&id
z|J{nS;tBA&AwF$`x+B07NF;hozWkEB4GR34Uyy&uXP~mY5&XrA0uL5|dj@v3Ah#vW
zH+;s|ctKR<pRKhnO5J6-1-!az(ke8F2PFvQYk>6PHI4uo0W))S{VPWIC_%B0O@O!%
zPWZ`np>3xv7|rPT1$AqGkX2hr<gnE}Od)KDZ4phJE2NGuf_@1B`8wU1<_%NzrQt2a
zmu&4yXE5i<R%aj-y4t`POeuLMr4VH;d<CV1)&!J8&KhCyf`ZLBnu0r_(9Rj$^&5qS
ze}K<s^WhLOw5c4~TilYQJZX<h-@nQ@=BqG6*2y&*2NK<t?;o7aMR&josg0bns;#zN
zn_>%RASI1!u;21d9r0CBal-kus3R0Lxq}kqKal^r(A?1&x8;5~1>GNk1;c+_Xp(k6
zQdT=d8&wxeoBuAc=+T1mL0--H$EW==e#jU$V~Qj|8Vaecu`d;VP2xW=U;rBt1JyCM
zxP})`N*F^J&vu^BESrgEnN(Ul16W)vww02gw#n`i*YYZPHFIwgZ|&Ny+Wvb{YWVLq
zCUzl&)Zj13T({?A&u#Axc8=HIBN&n9#6Ja#dS1!}eM%L9JJlun3;L^zyYqF{=l18f
z!^gL%9}tXRalm`*R9~szk|lpi{~$X5tDNrxEV6vKJH8`?d@FZ<(>uP~13mKFedI_n
zpZ`Jinv(5Px1{T-nYT<iS<0e9cBWOIuS2a>u_WwLsXee_RAQL1OOdHn)I8q6f^H~X
zw5nD1#FAI{2$j;yt#IOHr{Iw;LCdA3a|V6V2|2AeIu*NT(BFqqf%GgGgc<fN$U?8U
z+IJ71G7{V`)UrDuWyPRXeKShoI+JDhc04szfMu`R8suZAM`x}%IH)_8_7J75J0hj3
zI{?_}6+M*rU^Wj~Z~Jt3SU5X(WpQu$gk;sJyi@5x(B63gH45&_rF?i64Q6d^9iLRG
z?o4kB9nezQALFsxBfsjg+oK=3wZCJr>sLACNd?s-zgD4`<Vo4>P@=&>GJlHg>r&~D
zb)oj^?PI5hOJ2f<#b}sI#Er#pD4Wi`RApRv6EztA;bCd^it8h1;;|Xt$f)F=uD8^M
z!nkb&B2zafv0#wBWgHT_T|3K1yj+D44%NY#7Y6Z~Mwy$COk*_y?vW>2De^KHzKa8O
zkwy>={VMWeF#{a~4(;Q%!EC6<+px?ajL){*G8=jF2bhZ*iB)s+pcqDaH#wXQNRV9M
zGrnSfD-JCl0wdAO_GuI$U}ML45SWSG&+jye@7Dbt^WW%`jccXP3QU7lbWrM8<)9Er
zq7d@(z^F4e`}t5!la*@1A8p4AqJw5s7JA9xkN7IDMFI_6+2Ca!HTNSTFxBvC52P<!
z&>*oIrBd2(@QN#xS_*aJ!pC#M$4~ooc_jSox`kw*O&G_Wgu1xT4C(+k*_VsNRlu{R
zmjS(+1YNu@N-yG~T_>%92rV;GC<UwUiGxPlsFA_Lo##Ug(mVB35FO+&>^4)q2aSO(
z{+2Ol^^F5hq&7+FDS%Q(aO=xaCg$RMCZ`iX9>y7rYcv|8F|TnRC-Gzk-P1>~;D(sO
zz_1iaIS)mFtn?PbPco80=W)dpqcDF$i7w3ug(K}R8WpX%z(^fZ=-@?B2ztjr5?=xq
z$UN<^)-V>WO~gW?P{&6lOiahRukcy=SUhR%MB$zs!H!;Z_g%`94VJC2pB0}T8sn1}
zi5e4H=tjHR@bIia4A`dss-(kW7MF#&ygqGJdSBnyNps-<b2Kf|)TPR_eTgIihJ(b}
zSXU@57f7YA;RbD5)2X3MsmeV{B++&S4hgE8WqL<Cd%#q-6>rn*s#aO~Sd2=XuCTNo
z1v5YH@aXl1ve)(3g9%Z1LMp{$LcrX-Mll#>3j}PIJ!nF$>iwel4TbQN^~D%Arr@WD
zvr#57$F@(KAh`Lwu%t3#OP88F4Ej(;FxlM9;<h*BZDS-eHFY4npQV_|OeMU}Wc2bI
z@9{~6%Q-L)9}vMpBi(3HSG@?vYCS;n?R#90P?AMz$&e-5Tz7AhP=VB=v^AUI8yMKc
zxS`$-pNBpX^{fNi31FIMSkthIH+5&3ZKRSKW9iy#UkMj8N>zB66_QIttkRFW)wS0g
zwO9@$);Q~eSpoJA;15x2cj*T=?=02<rWgYXpT|#-iVT$@IOk^0+BQs}0zFHfQOByV
z7&>HoNlYjzXhUrug0^Rchd(P|1OfB6v|rHJL{B737)^s$qF991unU9dk7sP7sk7JD
z?7b(fHg&(6DRGYcl3j*IXWPfr3_ZL-?+iG!T8OT^8z=kjMC}bZ|K`u0mD<s0=LRk~
za#OpGiXH(LOQTF?Tj~I@MU@7sU+|CWABxTw`wKb1Ql&s5tQKQ$s=F^31A;TGCTbiM
z#)5Z(*j(D-W1+Bs7xU^Qv9B02grmq&dCwPXIS!e>sbDZx(lA1d6$cf)qvVc{b$bee
zwM#|^@$PREbPRr$ipYxti^&*15~c(?6W-_T?G-lCT+R)Poh2BzUFCf>eS+8%8c|K^
zGT3JB*u{sogb;aDa>vc;hrUbbt@0;h6C~#L2n4!M`|$P7o7FFG@0+eyyJ+kjDrC3r
z9^x$sYj^0?>XY!heh?q<X6(b?x?sL(V)g0hr?4+?_4)e`^nkiwTE)GgpT?nl)Rg%f
zVyUY60<zU-xyC;X{@BuoYAp7cyuG;-itgYSnZvmV(-`g{@1X<`!#EmAN@p00kT{D^
z&+oud@%Jb!-=yA>yCf|B5&cC9q48K}XJ4P8bWG^T2j$fqD?NtGg}13s)R?@JIw~KT
zOtgekP6I9C+-bqkU@x)5!$Fu_z!_<;?tUHRr)vzdkC0mK{F()ZBYW*VXx_3%Vjf7z
zkxSJcNA3Ni4-!)e7v%bObLf~*!AgOIjf%Kpd3ysoVh&uq*BCX5pWq?-J86vmi8{+S
z_@AVT=jnj3WCom{VhNQL6rcy%(kSU_b&8#b8%*3N?Oeg3A(cx^kv%xk(Luqu!QGWN
z)n4Jl+q*C5KkA3dJ`hVME^<$6nCr%&ybDj+m|{7xLsQZ9rqo($Q1bH_iMFOBSJJZ<
zpS*^#RCD2WS$lsafZ%1ke@YJW4mJG=yF{JGhw?Lm>ow!z#veQ-JDz0@@x$BM-@_;@
zO7d{2K8a)W5An@QbiLDp{hC~OWU1%LPx7t?MAmh+;1`Lw!NrworY5f`iWIE#fOwdD
zW)njzUT6%U4%wD`rYC^ivw5iMrR%PysCuSq#aD4s5t@|l;A6rc_-XFwo=^IyVPm=c
zMYMl)|I~BmZZqO`Myo8@*%zsKMdfN7<s*H_-+*dOX#;%)oxwZCTMP8v>tL_fWN!XG
z*32x!+S49!Y`_LtM;Op&Nd7WaXKFIRCh|?^(Zx9$=gI=MsVAK!DZ_J)mwZiKJWu9J
z>Y_&6Y+eVm2!9WB)bLmuQUQ7CO7zb9py?r<I}LUc1#5(2sG)1JieLb{870AD1fWJm
zb1B+Uk&J6*ds5{S!XqL6@?uCY%1`bhUSZ2!BGgKwt98JStM3khmyH99!oe2r?tq^0
zrTbU@1`9gEX|9YvDK1d_NM>Ny$jH8)o&|bBhV85je^QF0BkO=<tO2d%D9mn!Q#>Qn
z!8}AeV%*IVQcBrE{fS&!`xpd!^E(1e76m%Ph;V==flNu(6k29KkI?W)mU&yFRl|~`
zgXY*UEXOS+jN4a9J6URj7M*is3)p_@aWY96S0X3K<d}+<c<p1L{WINzY-faBJRIUw
z3|L;2Z{v;9R+U1RWi8zVY<y2^FZ|+@*|b#on2KIK*jdM~6{=|O{S60_dU3uqo-q<Q
zV_{Gz3=KNlfO*@!)`~-$6FRSK4x;b!N0LD8Rsuf~LQ~G`+;pMk^_rE;@2&YDtRjs$
z*5|gG#OE?RI;%aopZ0jiyrfoq;be`7Bg)^Zt0ELMRcr=dkx@%!G9(l>BdQ&5#f!x{
zNYOF{lX^$AIpfy#oXBq_fMMpU<)mamVont%5^%yA7mO;&ioxvkhc01>B<Ed*TfB`@
z8kDH0D50Ju@XYZF#CmLHe8-(;_VO3>lg5Y~Fca=ATl7(YVq*@HW~H)Sami3*EY+p4
zy)t9t`n8Simc-Z1p22KrfrYS^!%+ObxL@?-p?RdoWF$n_smpiiFuSRMsqbXkU!XDZ
zAkUpb^S=N{PLf{>e^0(YO$3%x8WD~mq_+Et=RmITcwFf&Bd6w{&;}CRiC|7!-TB#=
zl1JK!@z=NSLUwML!K7+X&m(XcjB>oTe#<($3&PCJ#1yy;5w6LH0FdnUXy~b*j7z9z
zD?BJZol7sjfBMN9wdak>CxpqaN$;6!-w%Gl7ioQ77h#wkVAKreIM!M534X$Yqnhkf
z`4xz}kanE$VGT(%1z7Oo_HWC!EeKYkK(^<hOe5pw7DsNAmpf@sfp(;ml}A>%zk{kW
z<B}nOLoZ1m**U*s>C(p3LRD7egI09K=K2+J3bsHkl9kiB>ndAqvvk-6mKtM+ZNkdc
z`uZlC-Hd*CeX_23n6)g=rLGCixCfr#fH>1pE*mk(H3O~6JuHfK{-6Tbu1ht|V1+gz
z4n0b1GruRKm(G80$EGw{Q1&G4fH~TifOiJ%#B|_U$;}Encp>zpNyP4my9+AXb>`ia
zz6yun_g~>`U8mp=OJQH&32aB*>o|Sono&LxhTQzcrS*(5n;c;Js5il)lgCeBd#8x^
zgSDV8p4Ap;$9gn-tWsf@bar2z;}(pems|AF*bB@(^2L5~+y|v~ICEB&%7fX|iKzvp
z#Uhv2PLYS*WfY8}wosQg25{(_#Kq<E9b03TmF^s4;<ift!|Y$8%M@D`?!>kr+!n!g
zVRjXqwU!*S_`OO1x1^wzr^^z@Czt16<<bw2Fdx*vS2DGv#d4nX6u+#7?+cw>_%BEl
zZ?qiPgX(PQ3A4ZC$x@g%G1LpiSt##Wh4b3hO68349luiNQlW&Z7l!1gZ_NNXvD+y-
zRX|=E*~Rfv+2cDh8Z|Lh%fHX;)AhjK{Zabp+EQ}9(b0-8G%VG&7xX=!dMoviO|E7h
zS?|pjphtA7)~w2^7O|dU3y1+gX#q+}YL-syREixptgx&TPc%uy7Wt|+m&M$RE*M6z
zjovfG*sloHaFWdWRML5EvuNY<eqZZBFFA?)#gf<vW#?UNLQvx8(Fz+4av{GCz`qUJ
z#S3J|3tjaC!uw0|^w;(6#DnP!f$$1J8P^xhO&Q31Oc2h2Um~xFcwQOX=i^aBo6r)c
zgkGrXEB~8>7cAH1^DmMwCfly?s$i4+kmc(F>yxU1s=sejb2B!}WwEbyFmG|1!p0)o
zX9LS8v45ZXN5KK$WQGq8LIKrFY&1`3Y$=soh$kmBs_~2M5X{aiwb#rW=z2K&t~c}q
zE&ZP9vj(?pioCog(aCuqMBye#i5AZrYE4d}5zYme%9!&<b>c6Fm<8H!diGAz5Y`}P
zG6|3WdHle(>S&c$4F5KW`m9cNM&+^J30gB&?gv6Q7{-O%>=?+Vs?ao@t}9o2ku)I!
zw3DKs|0CgV*S1~CM?Vvt&=t?@f`0={DW$@fzY{tX^^5ifh#WgPR7b|KNyd@`5trLY
zow}JMJ9c)is`p_sxsY2-(dmDw!Fpfqw|?k(*Z25^;RuvlBe~cHe)tfDsc=2q9k%lc
zGVkf4_ot-}x_{nfwcMr2c}%89^GfP8$~ryS*3&**q9$HLSL+Ga2|>A;{T7|feTO&8
z7JH-1ky`DNs)){%yx5J&Y<twuDgr!=IEwdF72Gbo9)CeR4He71NEeG-&(JUZ>PBzi
zB?w|Pozi8{1A!xv_0&x@HJmdU-pEWR(>>?JIPi@3SrF{Z@e`@r_p1vwrJV}+Bf~GL
zrVru_y@L~A>Sq5aJO8|<PI3m$=^=wbH?$VRM$Hb@YS%i(rW0sa(T9rM`;?Ts@0tkS
zz%{S!Suv$YpoEsF#bo+EEKyo*p#AKWP!tUc_ii?%8%F&bo;aoXk`5i8_bam~oMmVV
z(yTJD;AD`ai!ecsU)1OWb8()2f8r15iGG;%r(~!9Rt)$FYQG9`Lrr3Y#M?V!^;?Ha
zEb$XewaGMJD4@{h%%ONSVS_5b9rugTp<~f<B-D!q&J`g)xYAttSi2dU^2j!`W<Ia6
znvnW&@*bOEFt5bBd}Pr`0tL<_b}84q;tNw#lu6DNb^c$6&O7>38WJ1LY6nH|q&V}|
zU9kQ_4uF*>hJWz2#`;M9PX0Z>HRgXW?v*R1i0b)K3CsUvy8maD@c%*US)(j#za;S6
z_mV>r8ThNP042UXp&dU}%TX#BL{Jq0Q33_5R@qy!RjP5tO}8TKyNpOt^`IYNPrP83
z3kVS<SP<umojKR{)>G~AdGnP1*UNn|G=3H;%3XbQ4HF)e$45|qQ!ZOjJW^yR6OK}~
zD^e^aBNM!S8JpyF0h@6nZNOv$mdtpm7<Be2H(*D1zRcxqmO`4GcpY#U938bGSoR!t
zq828bykS*nBTis(#Ikb*^QMd2ba|YcIj(;GCX(3}t7uSDMvV15L6J5W*^67r9B}Fk
zjHroqJ|IIBbCfNmE>FYQVHox7IU9AveJd(A_0QYN4)_wpQhz?<Q&T*D-QuM8durG1
zn=ATdcTJz;D4mh#BGH$a*!JM+q-u<dHGxOPE?FBUtj}HQbU25ebkm3qb5&vB5G#@b
z3g>gk6`JMYyG5X2;p(rv=aA11haNrol*Y;Q5E6g4a5>Y?{-n29Tm#mY0O;oG9iNk$
zK+NtdMu6?f`aW`3`;?~d#>{SN08M6Nor8{Xwpyy+S&dV3sH-1$OZ>t!N|5|rZ6i3j
z%FhLn(Vtw*flM)Nabrw8#D&KJ(EhJ@ohJyH+t3dIwTt}!#}oD6XF|%}=zn^mTGX^1
zkX13h*<_R0ws#h>QRq2<WtXIXO^FUfwh{y^szHwc6K%R=(UGjzcMYJS-uk0=A8eEB
z<KW_z8$%>u>btmvV&eNeEAIL%v*Qo{%ib<tzm~MjXjsbTJ-zz(=ijUT?4Os>zFl7g
z17be-gNolIGGX(98PM4k#Uo2L9-(k^;Ers;(9`uJ&Nd#oaP*+}Mvwpx%HXtn=uOVC
z&_|p0{!sPxJ1lIyx<TxAjNvT7Zqfj@BM-77EMLkI7S*Iw<j9g}>Qb)qVpXX90OUza
z(o`j;iM4Q3i;N>Ss1%X}C(sKSz<ly@xm9{*E+@uq8o_mf!giUtjP!&?(U0*ub?7_k
zq4R#an6AKDfIX3sw2Gv3c}*n{w(QA-rp5%$l_*WYxa%*<rGQ@c)uh+#<ViImk~}pM
zSI9;5pXnnaoc>g@>&Rp|CJ`keTQx?Sm>Eu9r>>P3W^>DmH9pd*Y@CHe%#lgVqa(7{
z&1;yTMu)OAhRUW+P8Lp?(T^t-%?j#4%z2q8krl7j$c95qY1vBfu*yS)FXjx-W`&jc
zCMwQB91FTZOuDNiBV(-$GFH+W($Gh}q;8b7d8Yk!@*QsgrdO94qMGRUgmPqqKCdWZ
z^D@*R4-H{FgUU!@dW?7~5~=*!roAGfaQCmDCSf_zx4%zNDW>vM<v|@!?N)bQhOW{R
zaxqjYS<P;2S=(96>z`3DZ3C_mqV+m)z?&`6X3tV<KHB%#CFvT<nVy$J$E-TMMwAgr
zpo7LjwiMxQK_23R3;!57MB3;ow1#eskz$+ac_?gQ*rah&LU{@=n-z*4HY~$EW*CGJ
zZ)?}!k!=}7Q%xHG81zn!5VchT+2>V}`V*>GUDEyB+3SEzy>JZ^PRQvl|MPM+#Jm8Z
zN1JK#L0?Lhj1eK(z(T`xLo`PFM>ug%({5I$O;S`j=;-CHi?N$~?QU=Bo2$n2$$KwH
z2kDaZ1QW>{_wAOD&W1F=bW|aH-=OFU;7}bg%XhLlb+!boW(PllIfz!0j^sB*RP)$%
z;`;T)>G$|PkMb*wQodTB5_69MN^THYk_9Qlfb?HCOYN)R4yN@?9Z<9FLfirh%>qPT
zbCP9UtUgSgn7S;=c#%G-jKXHd8{8?2Y$m)xc(!h8LXHACs*Yq*W7L~?M{;Z;i!x+l
zsjTSdHG(2!T_&Tm!q6VrCTli^tXnWg$<e=W0;4?|#KyEM6Bfp1><4_9Sq-9M2%Uj%
z3Zvrr%9`x>xdr#gR)dqyOHXT%|6-SB*Vv76*yB~=YLf<|3|yd6exhL0rIvVpvreNd
zI9x0*!x=62=2Ih}P#2$X$~L$J2?N?mDIqdDm~&dp91wgrTIcP-e9^)*h0Y$Cr=5i6
z)V4yp&bO^H|4J;54UV0n2!7ifI`O6QB}P4XLVQtZhq$tT8RfE;B+pTPf37P({jl{E
zq%8UYQZ^%B&3^uB;tH`$UTV5wENItf-O#(JTB(NEF+fTX@P^zmRkn;{m~6&35<a8h
zA9n;Z$Aj?1Hd!|%_<#!IJM_W(C1#|a$VQ8?xpK(Aeg1vM@W%_YoS=oe&X8htMMhUt
zRHwf)Nj3S+m!y3Bjhnp^13j~WtA7VMLaPTdM{l%yV8l6uBF?HFFpmPp%%iO}5mzBk
zwL<wa?fq}bto9HJ`NMNQ|Dcm-ZJUtjbn$r~x4%(j?8LMm8b$kKx_CZetLW|nKQ1hD
zsBgM;3<1E`g$cYv2pZ8zx+unfy>R}Jh$CC@?mFVn7^2-L+RI{;E2>Q)B&&DBa>yH+
z%ZHq?TQ=6HLYQt=_Ix%rWnBuoK_=$q2CnJ3GW`8C6OXAvKCd{8eEKG&3iU`1R9-vK
zo0P3Yh%d%0ULY!`aPy*q{v=mp;Q}2yRX&pCKEEJvk9UmzU6{jcwEoFUoHZx?#4bUe
zg~cB{1ST@1PnZi48FkPQA-N)bAU*d{4V1`oW{TY_r?3>XUo?ZdyhPG)%c7FQ;#Pbw
z<`rx*b}>R%bDh7uX-QP|%@zxZ?d-qis@vp`zlkF)Z<L#YBniH!e?{sfjQ$s_z`3XT
zty*4fq?C{IK=qGIMb5}d5K?WXU;sOCSMoFtiO?Vogt>Y@*k5AE6d{2>L`05=lxXpc
z^a1_+Q#TN@D<*xPg$bA_Mvv$pWW*WRv7opoDJA<?F!)P*s2Nlq!8l!d<CKH0bz&W)
zLkY;**nlrBH-?(p)_f+9xiEBrP9@d8$y{LQim<xlw@r3o2I1A4Y;It@l~gWV(zu3C
z>X4;fYl?D_Jz4MIpZ~fMs{wos-#=GU5y-D!{Qr@``u}vr{6Fo!Isf;qw8`PfKo>kO
zB%M#IKwv2hr}G>7fVxnrq*xT1N{Qa$fF>g9uw@0?5B85g3_6|Ye><1h35Pw9p;Q&%
zd9QA+uCmze#hUp2eE-7l0Rbb>sqs`B)kI(7+3lHOUeeihv|k^@3Y<G8i=0FV6zr^_
zJ8W1HfX%uWirmPJ`c~*G^P9=H6bVJXN{YYxp14d?Oo9^Z-I7EsU#B<9G?oDry)YD{
z_9eiJ;$cUuFrp~|P7F|{^|&KW_C|{l>uO#yr8P*x*-CZ0_6=mv!WmcrDIbh@SQIJX
zw~c$K8H!bo1O!R}8-EyR7z-Lw{z%|cgi~UI^A;7EjN3o*3h)1=D`~|+cLk~|BjZZ$
z;FJ4PI9-z+v-!jXWt_sOt)7{H)o$^|0Wvod8Yj!5xu;$F?1-*y^XTPr(F>{aom{`l
zpG?SZ@jSekF(KhgW1-d7KcsB+TZ4}=$DcddZ1u&fVCPM}t!Fx(Z9R)ZoPOnBC=0v;
z0%@*#029J34*d=3?rbCK-9%F8!KivT{mc4kk4cU^<6IX%*d7iYLEZ!v-E1Ig5sZ)C
zCeNTwn<g#Jz<an<lU8%+rB9&p+q8cm>9ftvsm${rQk`s&`EW;zzi26)5mcH(#)9-x
zd0u&khTmu&lzR0rR_(*N1E@j+My}nI;y2uX9j%&_@5-j1<2&@HVBtS!yDB)@n>(30
zJ1dzw*gO4?$e$8bTjd{xkKYZM2_Y20KCOZ!5bC24R3Sj^cL5@bh(e%7&4%VsPJH6k
zjSU;_8^jmP7nsjwGjk36*L;KiM*)B3b%(osA}Ims(!|ltw)Y(GoO7=8>~`Px_qF>k
z<~OovyRBORbi8mw(J?DfK^~N$%vjg^t?)g@-0*cXP)?iB2?uFdc~_fDkJ3YGa9;Zi
zx?OinyJ}52LgO_tzch2V7~H8wX44_JH#ychW^FN3`;q3V8!<o$<7G~!X?RC-(^+S?
z&8iw^>A$7bd*mZ>7Il`W8=j$Ok*ctyP1u3zmLbf})kre^y3}0<^C=JI!j!el6n3f2
zP-T=`E5@@MH0l|a$589!>Oh3c24hqly$TzrO(&h3-!rq>)<>^+n5|DFAwIM7iu-i7
z?W#^2c^ZFL-e$*>VVmM7I^-5;Bti=!nZk3n%puV^MwCnZaipYt(R3MQZ%m}cN(Rr*
zaQkjao3wIe{S>OBos>GN$%2tsVwghy6s*Gx^*d(3UuCNF$hJCHylYZ1L~^Rrq@yGV
zi^0rv2di2y=VlXaQVO*mHP!5CsAdr=u{_G@F7+Z4)kc1TzPtgMPEf#bgSSpHcxY)X
zayZhpE+%uy0J$s0nj#!uDJ2lplFdSv8B$alTk_A@wpnDL;?h$PJg8918RbgQF*k31
zg8}=!@uQ;R&d)1t=AjL-hHBHI>^tJ`XREqC_;gS}SM_ytl?JObb&j2ruoCY^6ym!V
zoe9!J>OC<|H~Wc--b0BMwFg(n)?p@|*5W&w364!s=<U0rJhn^M(4mzLGYl{QHjW44
zxuSa9eOaQ%_#~PQnE@N3lBlZ^TgpvJEhR-ca9P};6t!L{Ibixr5&MgrjdHKS7JPaq
zg%yENR#4H4?B&=laDqknrfGbZnGy`V#LYW#Kv)px*WQ*uGQ~RqC2Mu_!@ni|1?(Z5
zNtNspOIU|l$d_2Yn>WG|$Q_Q&TXqZO^*XvJw01HG>eV4RC8{l96mA2}F^AqG5}5N2
z`|lIYM6C0hRG(ukOklnn7Dl5~nMbP9Ji|2eFHqv06E|C0Fq{>V#}nc$9l4K&VN?;1
zGKhWh4FA$Vkgcd6m+((U8IOlptP&8y+7ad#iT?r}kTwW8BXC#>V^kT#C@e>A&MWp*
z*@#F<76KH&DaDjAQYzn7m@t$K9*IbSGF~yBCBc%#&EwrEL%vZ=OF<XyRB(kDCK~G8
zARs?+>{Fbz2baz<)K=spoLR)@-Xjaf;S~@QJi~oF=@PI<xiDS+MB@e=7JCZ;k2&J9
zLlzYTu1T{t<EudXkezS+ST~vhE8_wB0S#REe|m3`^B|sjsoslCXufrpgE0naDTC9Y
z%mT3DIBfsK(kJ62J&{ebRy3a|d+7pu6j(s-v2_dOl>EcFDaW|rBjRU!U*j5qKz_~U
zdY8(<xi7p$iz5#H$>b~X+=E0sQ6?ZO@|A<`&e!vkMC^G1il*?7N-SR4^fOf4s)M$Y
zOv%iZlJ6C5=G;)!_j>NkCVI}z=ITXpl1kG&erUbOQ=s}n%PI4I$|O~J#UP3+GyrZV
zzfP;CS*@Grm$~G^+h^kX2K%p%Ai?Xe#EGB%O84^+D*ea(`u~nX`=2%7!uGbdmM%Xp
z<Nszwtx?vsUKT*%WuCCx!r1Hte5ksD;kQ<?E~<;phXmHQBBTb=Z*;92va?PEn-G1|
zfJN;E@%Q7adXaZYX{SvFf}ZSj{I@WUflsdQd*psJyf=$IH5fX(&BNHRF1#Bkn#;+f
zl=DlLm>9*7{u2T8!+57iGOFx(iAx?CO8VvUNR@VPwyz9-^z-TRIkCO-ka1or{$3NA
zOy+JehW2-!S))gxz5K5Dt3oO4zrc3-aVYLQ;mj?{CBmv#3k>@b-uc8*FBRd}zGyBp
zBy?aa`id2^71~NhNO)>@T*jO7<us_~x7iicM8Xkxd6iePDd`@Qtu;}}(?d~bo_y5C
zrZ$rmU%}fkVC+ZClK);4Tfc$wy2$?3)J96!j=3>e|8c!Pisw`Oh5rh|vJciCoEjF}
z{|6UBe&`|?%Jk5|-J_hyZtQ#m5DIgVKV+XjfFN9GOKnzX8)bIszd2&c2h!Vf2pe|o
zbjvMryMSnNdykl1$ND4%=e+KVpzbFijb|W<l*+M_G5BT;(qe8Za;-@?@l91bV<Oc0
zqF?k1_b`S3PzpDxD2pM3Y!(c>+Q0^Jl?@?(;!kR~d@B2YF?LSTnFdk14mwUcwr$(C
zZQHhOb&@}}-LY-kwr%$0taCAI&RMf&uD_e_Vy~)QyXt)&9n*^ke)J2CK!1?`S~%JO
z(|Nt0q8Wq*0;2gJ3rE4w$>l$%6jN%_&e);|-)i#GdfLqnm#c@e4kkm-VFJAf#*j?I
zPA1xsID#H#B(jIDk{uOGKlJDQQA9f&PN#4xlnM@qgMR(|R~QuD25M=oc*<yGu1TMT
zg_|?GD}4Wd@7Mtw3`r6PKgMo~2vc<$Z=*GIX~j)GiG4z;eUF4e;$$!{{XF<zUNp1e
zAigAk_=8uHIQfHDnE{ndZZhlSwgooZ3q?QW;O0U@B6DrqR86~dRxTdsn^H@OrnG|$
zx;sEcc;^@k4Z2OK-CwlA21gB3I_p)}La~lH0L`#lTpQktE}XONikn8ZJ#*#qu3Syu
z`W5f;A=Z2-@iQkg)?@`X=?Y^tSKUmSTIGS=np{#FXy?ggTxEg05(g`v1Ogr^ZpYA=
z?e;Rmh2~kS*}&<-*u2I7nHsbWg9Ij@WHES=n`ZPXGHHVyW6ME8BKJVc1vx0E<Qf4k
zvbdY+Y)i-l6<khB&N`M_vZZZ3V8A+?DpivAv@WS;wcRrPIxK95xsYcRvnn|ZPX;lH
zt1vJo7G+vVQ<%hjrFFE^@~%s+p&!?i{yYS)LeWg6#pO8?@nyCMw!-)(lX8CG9V!!t
zP6Vz+d?u8ll+e7};tA*d!T$}`oMtK!pIZ0Cj*$aXjaj;IDhzC1iOZJfrw1GgNFz?~
zbP~%d&GdarOG66-N!pi^pZg0D{N>qw(m!^_C^sK^0Q|=ezNnC0cs^Y~I%2Te^m_p`
zd(?Ag^f4iNyUdGLg8LyLg9w>>fLV%sUeI3#v$XT>ESO5Oo?9-(KD|Ji%nPoK>T=<T
zjGR-c-<qr5qreyshO1^TD2}?d;sCtnV$?tqLYOqJA`WZWh37}=<$x=%IOnM7umaXj
zGn+4v`pXM=g_S19R!HIYEBR7A&SR+<E16`0P3m5M;dB1t$w91h1jAHpIVtQU%t{rB
z@?IsNh)|A5?`aFm6(|8w^hjB(YkvFi+f!@_tW_!(*fQaFj4?1XhqwpedrvrxnCmFZ
zLCZw-8vX0*PmlhyyBA`ce$q+8DE*nI;=ZVs{jcdqyT)^oiG8v;z}X}EmE*d5Lyy43
z_9aoW?io>5cDxJX*tB>@gxQI)?qL1I41#}H9UT$~87U6BLaKvMuOyT*e_}s_nuTsL
zP~Zzf9~;uBF%mb*wJ-Evf$N(@><<rA(aizS0v-}Sgi;qsaJ#XY9NlyT*@DzlZyJ(B
zNG_U031JZ;L<bcjL@QYOk3BE<XqOYx1Jr^o!j24?K*5gPNHc%2Q}HnZop{N8<Fh}d
zB<CF>w6UzA4n!26B9x!)N*+8EI_l6p`6zN=p|r)fy2ZC53ay1GdLx<8dlCw-)Wx@9
z^G+NTpG``yw4GP#)`@O+pNxv-%3n;<Qs?X>57mnd7mm283X?aneu9wW`;P9L#E-w7
zx>E$vOM~eAN*(5u>m?iAQ=|$6Nq7EL{-L!>OB#y;OZm)GKq|OKw9a{t@%#7x7#t?n
z?ujaX7N|Cx|IM5J|2#ncciY*L4}^=((9*wbOiBADFDd}-hPCptE`W3b47LipK8kkZ
zPb`UgR3~70ex16yv%@KHHVB!3Bw2vK4I~5!HlKa1zws9XtpE~1NCtw^uCxTCqy)pz
z&ds#<Mv*G>3HQGTezBXWOm^p+Z0?pG&76<>eDO#NfY*rRKcpVk!J90Sp^o&&x>sKP
z?Sl#Yto`_XdAU3DJ3fBD-qe3%L@lo{FJDWPd?^0TQ9aS|uS5J<tv;71|4{xpMfpd|
zXYKRv_iVl=(}%wfnQy*l(d*yt(zm%{IFp*rRVtZCQmO)ElFod_7>W!f!jp!_WV$)B
znWS;piY!NM$YlYXVUu8(Oz<Y7hH~lj;h<$WdqqN;y{U<?p2@;-(|_nVhbc$K3q5-0
zetX6!<56z~kdFlZ(wXJWp-1*u6ba87d?0@qKq;k3R>rN5P_+8H@Tz1pibS3g?VkM@
zlNAS`Ia-Fbn_@Yn@k^Ux!96Lm^5k)!VLXJAs~AG@Ea0J(_9|jJ)G5s(KY17c!7CJ}
z|8;UW_Ng(PD*9V<dY3AzUP<lFv@WTeF4aN5i7=IEYa**rknZFf%dg6H9M#Dbz$3bB
zI_9<3>s$G^$B9*c`PP)ySZjn@XC_rS`<}&<OMiM7JvMA}w+Lb3JOw+uUXsmR5+Avf
zGP-#Jt<)xEX!HJI*p}@OtrT{Yjoeojjl+a{C-}2uAVK>rA47>qxO0*rI6eTrJ_)~t
z^T@3&n6rJ8(ET1{+GVsMZM&9H)BIsM8x(S1H=HMxF#9Cog!^!%?H`En^?345!j8)*
z4DLM<xh^ri+o(O~At}$(hR<7^u-<t>s^fzbxL2sK-wI)^%V;Iey*KQERd{Duo&OG{
z`vmXrH_-4;LiSqIvGzDjSKb!C!BlLVd$I7&$jHug!td3D77oi?HLSK&%C;p!dt)O1
z{e%|taqh!xpSB6Y8@F-q!!89JPyCyauUW9S0A)Ukj@Bl4EwUHv`b_sn!sA8YZl1~b
z_}emZPkp?Di36Dt`L}y!y=i10&p()3HlwAlc*l1T>0K~sUGfhB<~aA7dKb=<7bl*w
z{O+UZ7(>xjT=aKG=roo+hrm7ip`DYHK0}21M?VzJ>lK`P_A1uehXL#`p9R95{ZxDG
zd))BPYC`{$<eTvw?0a6pHMkU3YHaF?3oPpiD=M%f`kl+IV_G<m4Q;6lVnToK2_0A}
z_~vlp?dMS|`@DtllOt-h6>=FRkK^(_1!+r;zh|ve#S_7_wA~0LaaP-F*R~Jr)sJCB
z-x2()zauL9yUhfRy7CZl=dK+>`8QEEk74dA8Oz(zuXN608==RWC@y1OL5o?pfA5Y~
zy|grX6K4}9G_$>3b#6~!9tI5NfW3wnvw&?7cjG2*lh9&gkTnc%?Acm9r8IkG2KU9y
zv)MxkxUjuRrGm2qwDVYV5M_C)+W3%QJ+*zLJFljI^(AJjNHAo#BiIpaBm?S;HnAmh
zKsC%N*&CTqZ0<t`1baCsNnv9sb@$<_Ph(tM#KwbdZNDW3(X}vP#f_AKsalBV_0VC(
z01%Au+Qg%)IGY+<-INq%CP3>nv(nXj0j!;Vs-B*vrlO{z#;Q;EQra<_?JeEiR!jH8
z#nfo5H5yBQom7JX4H@<ArYWvLOvi5<Ux{ErYN)>f#lCUWS9QB>%IYvu)bMN{8l#_A
z-RslMvE2&6?#8{P#T{eV8dq>{Z)?{w(T(o|LC0`^KdJnCS3oh9Pr!a3R~f<p@&xIj
zxmxG2pND#(sIWe{7~A;vZP!5*mo5SXXTLw-gR)Y%GkkEh9`e+;WBU|}`mnc&EZqJT
z-Q_U>*<VD6NSfG9W1N#H%od$B{ylE~@R>5S(_X|!#Qn=0_m_Tt4fq=>gUtf(0fgyE
zBpM^!3<4bEUOs5PuOCvRx5{pW4gk@)_ZOZ=`(x>79&hB9djOdgOEwy)Iq25{(gu|S
zZDlz#3RQem;-h>BrX+*Z(yE)iNM#*#c*d_-*+5_A*5oP7;lscLE`8@L4Z);$v|5t7
z<jmd>$MXCJti>BxV|R~Sc5(rEc<o6VOeAI4H*?|c_^sK%V~7YwxHo<VI@<0C(tFfz
zg;@4RFmR38MHOt&p$!#iDz-OmF5&eGOGn8AKfxpjc2Fgwu_^%l2wBy<6U=m8Nxv5Z
zn`Wgs6#Q%FRWnB%cpc+TnvGs5%JVbvlCtuf`QC^=tHUbUx)m@|9>)gvhML%V>Klfu
zA2Rp7g1ItIDZ-UFSv{!cTOg0UmBmzRYS`S;aT8C5-81(RQR`CAlzKa>!uoNv2P=Z@
zx>BqRU{LVQO6Ke~bp3OWfkRCTRS(lUjk}3nD=mS+WjZ|ddmf`lQ<MG8H_*)5G|23C
z6ujykWx(z(&=`Q)&dA*x9MV_m53Hrl%xhIYdfe-VEg}mh$AqFv1;&aM<R8mOHy5}e
z;WcRw$KJbUU>UE$`@-@pb$o1SDlH-0rfoJE=@VJtv@_uiCJGyxUYV;x@YP<}u0VmT
zRD#rrFGIEf;-3g}Htw9p-YYRQ518s>FQfhGMki27{a}K>Ab1psd_?&7j>RWIs?VX@
zo&>_Dzd7%H7cOpKcC>KcbX@)OaS8xDE7eNeJ7K+L1RravYo#-10J+r7VV(a4ANZ6|
zLn4D6MJS8ud$BJD?sc6}jr9ZZoa-RD54@3qJa3*5-zbm4!#v_I;Xf)15FKk&8O^)`
zeq{BeC}-bD;d*qbv*-bFSo?(eOeAaI<?%86c{a9czCrH*3JbeEAS@f%`E%|jb))QS
z>-dme&3Wo-Z^8SB$o9;ue88ffq(slEfHsvyq>M(LV?!+^Q;R$NMnmZ@&v+ll;O6ea
zBw{jq1JlWenhW6*niMRGcgf<nJ4l{N;;2~0F$N-0b^3&8uCG9|?3wHjRSC?-%_s5O
zztg`Vn~yFE6#GnlD}*-NY5R=favs%EAU+dXiJN9XTcMj3OXAqag9E48<Q$kYScC+f
z<6;!(qC{e)T;`_TcHFQ73Hb*jns?do$rAvzzm{$PK{R{isjmx_er#m=ay!^th3@ud
zG>2+eX+TDo8%$&@A>OjRX$8}$MKC>abS@6_qQoU@Kg_SrH!O!|Jkk_mf~&SLWe9U$
za53_^BV%u)LcPUfHVrQuj~5+OR@eCh%Ni4bnTi`}*HMKuQjQ=!x#<_VsOqw+PYQJd
z=?t)C4`ANgJG4%@_0b;-Z~$#DV$L?_bq}ndD9dq6Snupx>+Qp}XsIp!Wzr={K7f!a
zV0Q$cGC3v-IZ7ZSz?nPVnp;TB-#~=)%A^ID8UAjei82r*s`dyWw^%`2cbbIxAaa>S
zb5yGJVBxF6QY2pST@(0+n+5Zx#Xywq3|(HHlBZ<?(@F_Jt?ijB*`g+z?MYuZ!l+G*
z4T^(LLS@)WsIj~``KDNuJ>|!-W}Xr%w4LpiMc207%RocL)MSdG!<rN;CG6ty2N4pK
z8~yJL#%Po8lGbAZu{89)BMGQxP891yTmqS}pUJ45@b^FhKK6ZX*k>x?Kig5{1VmQP
zjZB|FX#L)mg5a94U9{Zgd`NbnLMjX^WS7m|<z6w4x<^-;{YDAv(H=^rbp(8aQT899
zvWO90OqVLRS}2!ZHN0C`hL7qxAoikGggYBO1`3r=0%)*r#U{!ok@z%(xT@sgkzF>C
z5LTJv6j|8>x|EQg@yP$sAMP!Xl0PL}<~@dw{R~Fu&>Sh1{xH>`ni8IxDVZTfWgNwl
zXiLSCYD)pLgeiGIA-#k{3&)tEw7h<hvBcrQGz-I?O4&5iC@9S$N^;YkyM-*8NLhl*
zrUEC$x{OB|PWdg&XGdi~FbFFjIxjJJ0u`(cqTWuU1<SHR(W;S-4PIVxBIfx$xOj=$
zsEcO~jC!LqkbMb*by-Ecyb#VcraVs7PFW?on8!Y=e7F*d%vUP>*VHf4Ygs)Tw+9z@
z&Xqlap6lt~?5Q!qg!UGt*p%Q#lLT6&Ij+xV3vjG+DoKkb7%a-NilHSQq6En4h{k;`
z&tYnuMU?Fu3mcvJw0qNJ+jbn#96-N7@zbp;Ksu<??%?l^Occ#3EGsbP*DU-$45FlE
zSanmdtisC8qS(Qv>@A+!@_$wLnYnkmoj!+eO)*BgcyDBG?JXOa=dEqw#k8`&Z^~{1
z(J!bpEZQjJmJUN_@Uc)ERve^PI;Vw`J6wpc{_dO43s}u9NU&xN{lxWPSdu)qQ1)EZ
z(L3N#o>G4(=*YGSf^F(mfms?0`;7isqtr%V!E)%7j!G&NQc5b6qGg*zR5Pt8TL9%p
z25v{|VdL%V^*<jKo5HjVD^ku;lz*^~E5a@+!CaWyJd0e>l<T6iDwS!<m5zw$k<oBX
z!z$KGT*B4tOXcS-!r6uuVoiN0=8?7O;}aC@6=ce+)VbwsjHTKrgKM>H#F4B^Xm|*_
za5w|l95mB(8}<XU85KW3edsdoMK$5jKdo5K{3XzpAi|<DOXbiqO|rJ=EEVy|{R-SN
zP0CCC+%xP;>E|@czOvc06tyQF%Grg}tV^DgjSov>oelczOJG*$IDzHe`Q1<rYZwc(
z%DQD#i2iIw@B<~SnxCsG=;cPrx-|KjHQ?E)Ev;Xfn~)i8LlsAkx#J{0FoKh3*Alb7
zRHJ-bUAod<NiEEm&fZ(N`2?GendNkbz_c=?OjVhEZnU(F4Mt`5ndjW+N&;2A3@z*k
z_nw*V?Y`Uup@uCzTW~W9mv+~ekgu8(o4DE7px+La%YWkxI4&WU&pJ;h5Wp5m=3>hC
zU6ggFCpv_D)o1He*Dr68GWMW>WefKxaViWusriDEz*|gJUguQQD=K9in_9v38W<@h
zW?JTkCjk%%^Bzb>xp+Xd^D<Ao$MaB?>n)8CEiD&%?k48p@M6J)gaXaSy<xYF$3`vm
zDA4zA%#tPTTDrl#t13I{9ecRrT~`_S5jR_i7!?+uRq98M59U%YJ_t!?%V)oS`ay+6
zUYd1&1%8&LrUV?<?EXB)*jVWbb#*p16}6OVt?k*?`l_1z_Ixi<TVvu^O_Pd?rFa?F
z;B}mot?j@nN&R~Mj>Hz%*e9qJ+|9#gP%C#HwT9G<5MFc8^I(<NjDc&ikAvUs2u{Le
zAbnRjm!y-6AfCt*hKwO0z#&i8mACtRO9}{=UFT}bTVlBeBXZ`6$MWe6BVq56<#y`s
zY3FjTspZ#dFMkiZR}@~-&;6c&I?f<umx`aC5)Qua4FJ7gCFg4J>E{7nt19tj;<8U^
zUYjcXrgHyecnvGa+ioabXHiZfoMr2jvVv?V#^ln@EuUh_bB4Mjq`^eIrvKD)xiO;^
z=2<ypTt>T8UGiPnxL2~rxZ28_oNJoPoBO|ImFKAQvoFCw&n<z34KRUd0GzRiI?<P;
zOWwigMLY8K>pMTCx@;=c7mGVz)xl(GR}{?zE<i3)QLWouW6riwU@iAT$d?cMCciVT
z&R$!w;a}P1%&iSAw_JGby;gVnOKO)@YU`#avAjZ{`Tsm#Zf}pjFDJ{`64ephvY)#O
zia(*R5J_8NK+6c`5c3xrl(EY^m3UQ#-`rey3)llunsPp!{Sxk?wOB{s1BJ<8h>%}k
zNbcefe-U8meTgj!Xv$|bNe2_;94p75`2u>fp%~0NENl18WZ$*do7-#XW+AufPS<EU
zMK7eIfXd)VlV2O{i!1ugMu44!be!DyIDPx!a8MrA5fl}E4_qjYk(HrieZt9j1Rab#
zO-lx54elRg5;0Ps^X)K$B!Ah8^Jn=9vR6PNo|c+MM)g(7Q!dcj0qR3RivuB$ml}7i
zZU&ZZ2O=av<t~>&z@QnLD+FUj?2pH*?FxasJ?v3%FCtDUHq<;?-`dMx%`VL~WeP9+
zzKnE^tl}PcEUQOFoM`64YK`I-LUO@aVSe-_cSfe8zA8UkC;G4=n%JUyHb4}qN0gzV
zzKJYDBWaySmN_lYTvjcI5bfp1snReT-xl-*Pdme%wW242rAtz^AhFUDapB_#&-iH3
z7!*V;>@W7FjK@YdUu;E=rkB!cLL3z>xLh>u^W@(594XFT&EC1lkr*R8+29$F*H_OX
z6EEXjJY2;>kd6!_XXqI;-f=~i*SX$Y50$7H=B1CBN6P_7c#VYpzbN#C+Wu}4AARS2
zPVNZetM^_x?!(LPO}a9!E|o8O%)Xdvbdc!VI}nLaHXmzHw9w#fK!Zkrb7mefQ;o68
zJmYuJQDSr0tHS(}<#}O2)i02nVE3mi6KxR4G(P$VhjD`Nd-X~I2H3@P0LE$S!D%uG
z`oGhIh+nkl)t0E()y~2`70l~#Zz3OzS&yR)ST=9c<~_gUFMsB~FI0h3S5Ja|kj_u&
zoqt7z6sayU-aAU0!l*uamHhs=*7JwLRt%a68uR~R;8aXd#OYql-T&YoVv`^v!&g_<
z`|eCCx>Pg`62Ugi{c5uDFq|=E`hZ5FjrgVwM*U0wF>Wq^v^F;1wC+Z_W*9q11#9vB
zl4YN{mXc4<zceZ*n53*(uM+02(MfNH275K2W+P=Agw(gH%t5tj!Fq-7Zt~0Ligx|%
zxv|CPaT>i2g_s&i2X8YDWoCjaT_~FMqrdvQ*};;xW+GTmx5j8pvq0RzzLnlSg@N1f
zakJZ+sB2iuX6a9~xM16+j2FK>WE%N%8l03I&wSf%EB|C%QM<3CsA^YUsQ#G%5R6|5
zzs}n9{+RxWFZb(*{kSrCFmJ^6P3ge5g{EzX<%M)=Ehipt^79R&(x|%{2jlx}MsmUc
zE&e-j5Fh;B-AXS|GJ8hOOA{elbuecwAWlXOKX#UDa6K7U-O2xkfccw@b5tg4Z??4V
z+?PRP;15}$wVe{JeEb-YkS`raZE1C*5u5fFst!#EXQ-&Gp|SE%rSDmH_6nnRfgb4e
z<VHTcnuZw3z{cF3b@(IzcKmo~hPxb1Z|_jWjsP{X&;=JPaAG{C)Kx3o=q=o7wX8*3
z0_MVD$s+QdLf!D3Mi@ft*4Z>rfIm3zNpl;hQ>xH6tiAhRTEopjx$p2v2Exv=9KCX;
z;Tp{)k;q0%T?46^gB18`SWaf@_T++ha-f$ADAijqD1J^@mHP5hb(wXQW?g%IT}73b
zr>W?SFp=-n6|UVAXMMawi>-7+?v@*PzbtJXIqqH^>2{3<6%s87o+NCxiOHimCZ8z&
zqIvp#ff}J-#+apl>|BAnjN$!-UZHc7^Y10Y8D9tPRc-PryUhlab7PawkBpSQ+bCI7
zpKS^+K1&oYYb88I5V-f~6u=2G1ZgqlS6~AvLiHy!mbIklz)!H1)wJmXi+Xtpu%wd8
zUSm@hD$ZNMFa&Q}fMhZ1FJu9s9Go?px}*mH67S?(A4dIPQ&nyTZ1ie#l?_NU{&jZk
zMXMLF-qrDdtIt_BAcxTLwB4rV<2zMFg>KdyZY(ml;0(xhTV<6kTPOmqQ1`<4XVakm
z6=|Ld%fM~Pk*DK8($x7K_&X!Oqlw%U8Z~!-eC;nIaOEw)n6`6z1rhcPYXXR$A6Ki5
z78*@OcaD8?6|qmyMm36X&Y^%bq<50(Cb%jZ7x#k*OLjELx`FmzY7d#DRI<`=!dE+e
zHt1kC#iC#6zWg|I#G2ymvwH&bI|+m5F@e+0;z?|S_MeBbLxEW?doI|j-=3L&pr3sI
zQ5ojd3-^pHLzKNVL~7c6@dzX5Aau{1Ryr-b#5do2o8A~sm{v=?(`wBS9R~D>VH;Am
zJP}L6ssD2^nn(-_3zo?Dvd;*F{k?2d`kN74ky}Prc2aP4bv1F<TX|8ig0@7Hw6VgA
znj5n`+S*Z(uXy1m`j^`?;w`L@N;;O<fGZE*Po}$cNQ!uB)OMd=xEL86z2{lyH%KL;
z8qHs)rGlfSC+P}n^pW`3$EbR6WMDG%K2KCQNeERKB|HmJpT?~T^Xlk#eF>&VMPBPs
zRXyLRk$u(1DjrJ2qVMXq>ImL%d+a3er>(5bN5-${h<Z!duS`Bd!GC>8MbfvQJ0T}G
zyKl-|A#QxRVoSdIt1t9t3{Zlb!?O2;^Q#R7K78rp@IIreFPuQBH|hP69nvPGyXn$}
zq3O3iII$pAHi^M^ZKs~`DBp<HbQx-$@gj4;e=eRAy%Of527{BQQ)3D&KgM>w=RlL^
zMB^YRlQPr2M<q6Xw(d)sjAdEPReavw%Yw_V<OhPIZJ1H1!#%EaCP&+!i?l++MFC<<
z*4Sb=mcUMy><kNF)&;8jNJEUHW(uS?BaT|+YQ%zo5W85ELV-7n#?n7LGI&a14wyzU
zgu{OX9vF;c+$C8;IiRyGffz8Q`G1aD^uDyKgpT-j)ug3m(f5Dn4Rw?8OS#1t_Q`|U
zj7vc>x)YZhF?<IEcj|zqR49eqiTK=McfhfCC}8yY9N^*)a1ck*<HtmBdoc@Wph5M`
zLADhcI}88Z#mV$@%f+<Z)wJB9X?QpvaKKzExIb!~$r<n_g)OW>VZaz+!2DtSE#J=}
zDAUNuwvI8vP!X&+s0bc^S)j;^=>vS-F)E5qmWPWh%sq@0K%u3Mv@RLEIy=XEryFGI
zhaJ=Ha*EBRiK6*>=p{uCvHcl*cSR;X*XVn=54NmzftTKU`)8jHt08q+Q~1IGdqY+n
z>b#^7%yVAnr=g0;+j1dli9>zlXyZMDu-N2MZ(pwRW$BJ4Yn=x++t(X^GQr6kyU@Y>
zuoyS?hUXuHK9_7UkmnExy@=8|(`8AaR}kBUFjcrgf`4?y=vk?C4X2(`+M>(29&3%4
zdN5}IV@7Rb(y_GEWwC~%w|>?ef5vD(V#4b{*U^*~j5r~o`G@<CT;pHx^0c*okIBF+
zq8>D%o+zm<eAFX9V&u7C0Y6oMZ}8ld=1)xU8A0R%nk~#e_d~bSmGC}OYEQW?*f=w6
zPs$O!P;JNNxDG9EhsU@sjz9J5vc^@2gXA1yQG{)%2arW0Nl0?h7K9qLQw)V|{kAfT
zNVkA1L?5JK#CGAAIk@VEv5aL)KkHQ@h(jI$g=S+W1N(>IY}4=n?-;}}$HvX)l##o@
z7{+ntjAaQqV@OpTQ`VOrZTFZzHEgj>IL;+<4?{&JJjoB6J8QfP;({FWvDiA6F@cP3
zMkbM!G*d5pt<i5@$FYA+G0rdNI(O%8(J=!%Gy4T^Ih?kPQ74hykh!aT2N;a%07~*5
zW(JfcTSm$PhBAz_k;u`+!Ri1<e@O&krQ0p0w+CupinquaR*^NytZCNP<;kx~paC65
z(wA1!`$7;<zj)$lTS?!XU*>q^+o@wk7aPLstCv6Nv=ER7VWkn62_mXm;pd54`Gn%n
zI!FUtSwL2DjhgsD`E!EeIU)Nz!l=$TD@soY^XU68K7+K*QV|OD=R6;oVEb#&ydSX!
z?_49MwF5rrctv_37TwP*z2qO7e`E1yi&+F0?e;}AmPt-x5>gSWodvjbmI+A%Z>!W{
z7^Q&Iuxc%)t(zNxJjak4XjO?R44<%|)jLO&#C^x8(O(mS3DHERuYd(iC1lxv-lJa^
zCgEQYLio!uSWjc{mD-9OD3Jd9GXSXe21+@IN?)CMEG<uPH^#b2$w*R5a9fN`4z{JL
z+)5#P#`|uCyb{I1H@M_wEWs}fy`XRPlkj|GUww$5ePPdt$SX_xu8!pTEfKcBP$xqJ
zf#{jgfi*=#5QoU6ym+1vs!h!>J>RLLq(AFm5z8Us86F^VFR7ge{&db#g|j=90#Swo
zEE7sTk#fY;UREDn@#Czc)7l^B5?H!;wX{U1-4LJXC_4sPGU|tpA2VvM&y)+~opv+b
z&~l(@X~bIebkZrIHs@b*R}L;>^@i`c8b2>krPEklis?^j&Ruqy(`rQg1uXsjPRHfS
zpS>(v+Q23F2tPmPb5X!tQ@989zB{%pU21u^0&gYvdtucAG3jEwDUvf%J0lG)r!y!^
zm(z&-2(=BT#wK+krTjUu1#+sBZhci$wx-c{5w<rxcU8XIPAF~~w4+?K4}8SD_>RUF
z4uE=x^{iM)4uQ+?^}RLdsJG5iMbQz>c5&ns{!GA0&=lS5q6kD~=}08bf2awcRtGs#
zLj#Csp~XMxg+S0sPx$4botC+`x(9L}k?4X2!p;B83AE7$NA&L6`V>9%>pe0Jwn0ro
zKC1kYMdt>>2<y_3(HClH0=YOsFb-LH@UAt7<QN)0*@4c)EQdpN5`DvfYbF@8Qy@8d
z;x6n5SVNV!K%u=D=`{$VdW%)nyY|;cibVja;S4l`NG)<HVJh{^<ckgcyhlgcCa$cg
z%?PfDIXsk>s?K7KkV>n$ps)$;Ala@uI7NP;`e|Q9jk!@ySU=1zn{L`*N-(-BLAV8r
zkzKik4U(R-ufaYtwg8H6hIl#BY%f^T`;T6|1zP6l?@Y{8i#o^bFtsq=?i877(FV#3
z=?bQh9fZuLw)98LB_GK`&Dz^fPE<^z34hCw4`(W7kzE8+DP}vyOPV4$|0^O3?-U$@
zy~#p5Ek=@pY64$&Rrz3(7H=jU%=l@>MI7<K!rs<IS+_uA0Qo}7nrPn^OMwMe3zrmv
zg#a|6*fVp$rBm<ZCl6k8?23)180KmSjiPWU10wSvG*vK|M%an+U(?R6OaVzkSp-}o
z>ebYE1p<=(JbRQ?ggzZm&lRZE#Un1K%INegt|_m4?QDbc#cErFuKDV#)i{=|^*|b0
z-3BL;VqeMIHSW;YEHdnU8HS4<k5mi&86^FN>SyiK10dsawkiPFc|o;}Vd;<yFCJuE
zG*}Qe!dl8-N26*nlog$hm)lGm|AQ!2rRYVk!?4nM8^~oMM=sSUW)^WYpbMMvC8BIO
z@nB~)hhI`gmHHK;3a4n%6~9j877L0SEz;-Q5hx}wP8@Wc8-E)T2rJvPabWxZ3?r^k
zdn~<^&p}awBH>mHvJ>gfFT;YAZ6mv8_mRA_H+U_FI!|$N&@T^{)7zJ1%_-ShdT6fO
zc4Hx(d>raC%RoYC(W)8YnNx;^9(v+T(PnA747P{QSA!}Ik=+axe?uZ%<S$N`gj-I1
zf}5SYkHOF}46;83nXkiiBl!P}@vgvjf;2mKIU!E1FQQ%+);>;gw&y>cJ5D=UBb*VG
zvgzv<YY%YUEfpR57WD%1$gjm+K_E#d(5@n6f>-O~R>y&Oo1-}YLNPxrPa;+l<SDgy
zfTCWmsyIfzvc012^m2NErpSJ{-@2E#PL_OuYV)L`re2on0tozqU(E5iNB7G*{haZ2
zBTi|u_4R+zTl5&*=}d9yNA?V<oeaGUH%mi+@B4)Gq4z%B6hs=_x;P@b+#5+Okuq{-
zL&7+7HYcaH(KJt*?nB?{b_JMf$ran_LTRc8XcN}-$26{jYcXg64|uIaxpxNs4g%1H
zE-k#D4LXrW-w-OiLBh6b=@{1$`ZAS`9wUJ)-&TK0x1Vl!TU6Qki?=wtdeg0UP+n~p
z>?1v=rFt=WT%}&2o!NZ)NEEi8IhpA}WzfKWoJM`#7>zKVkAGIq?jr1sf8OMWPTiDL
zlFA;?&DeRa0k@lN`96M~Hg46;c~{MSoI=DG58n=KW7J$l=2u16Xfs!*Wv<*L9?XqM
zZsTF?fL_HH5ZJ`bQSRUHf^W}S8=!BEKI`%rZ~{}r44C2+v0BNQ36@NFJc?;uGyMqP
z`W8phdARE)_M5ottZS~vmv!+*^u{++px_;ICma)wJ8;%>ac-DaTX?ue%8yM@O;9=P
zMP31#39J*w{R?S;Qc8&(arUe6{>_~$)Hbj)?^9dq&o)ixk)-nA%*oG8PB=%aaF;DR
zrqZ@7H6)}HA48B6f1IOF+R0d%Xl%5F=(oFfUKb^o%WV~7Ud@2x@$(XG(luB&Q%kq@
ztf+?Du13eQi9*a~nYrY?(M3J1ME}f@zv0I_!@iCXpWsu0(EkuBylG{TR+P(M5pmAo
zSmZY$C%lnuQCoWTZi+7kuUs-)e>7Jwvm5(*MMN)zdL8(6>%m4br$Wik2uSmw5hZwN
zP5X$7^mwS1L&gqj@zK_U@<Xos=KJ7xMXS^~Xz&pygVFn*cWl@GNc53C5&9AFL)81q
zch>2IdP!~jaGYA5q~sATM@V<tn&f`uEm7`An)@&JM0XILZLfu$N}rnBl-sHB2j9uB
zl|G6-6#QuT6aLZuWAZ~is$sA3Z2UK~5*(w-gD;3!CQ;~n4DQ4s3`2eyCBhLhcaX5)
z;Rtef93Zg23F{Blut=YK@696R&#>-5H4bFb1$U76MJ6b3VuTV`MDj=R#qvil3Ke>z
zyY{s@S$h*R`vR*E6LS0CnN5UOm~E9K0JtT2u3e}lc~8XD!9o|{x@)`3u{b3P<)5*w
zP`;S!ztk4WB2V?eTXcOkJNxO+D1OmLXb+k<J|YxfP$2Y8`djk&Y{^`0q9@aRCTHm@
zsa;N$s?a?AG0Msuink@d=gu=BugA;zCU-b#t#|L(8b7hmFTiv15LZFH7BSY^4ExL7
zCT%X+u2o!^+p#JNc$8ox%>u}j8XCM?Sk4Na6%{i@FOOfQ$pf=8%Gc{L%bqU7a*u1%
z+s$20<bm4^RJUuW(Ao)4MBU4{eZs)qA%C)SS#Gt6GdsQES7kQLh@~N&;MM7^@Np>j
z?_XaRcsq2oprw8s7m=Fz-WEa)vFjbm|CNgmT)g}KglIn%To%(H4u;^?!L&JP=Skn)
z=lg5_FL)8xJ}%UBRT$Izj2+App<2{~Mxx^fu5JnMlpnD6t&n^L(R&4QIWh1SpXZ9t
z`wsNuY5YELG~OM5<j|cKKQSriGz-*Ba3zKfYv|278f#`G!k*s4sWs;RLZQA|w*6IH
zgF~&?fcDH0d+>=0&oBI)jy)yPaRyZb&D)lnvn~(8>sixjG+mW@tfT^~kOO9s3T5n8
zqbJ6b2Z_iggqA=kF4&>NA{AF$c&LalV@&WcGS9=AQ*ro<OH{68;SlA1tbCC$`jkdf
zsN<04y(UX`W%S@wlQVZa3FfrciO`ow9!*Y@4Em7BF-V67t-oY(;>{>qhi*EdNh|NV
zm+fDQ)*$Y_++h${qrfKVbr>L5K>Y077_UnlcOTEffvrnmXPN7!NPjL=>!jgSb-mbi
zJH)iSfqAGfA%8m>L2S<Bu=?e!U4oKn<HMEHG6%zcg{*SW;x3>WvJ?u+nhTjQHl8n3
z7Vbi(ju8;cwjP>eAz`A}3C~y+YR#__A^Kq=#V^w_ib=~ieR3*M>C3LfzqKm)h^adG
z^bcg(xR@0<4QXjFzl;mxN@IuO^bCL(dS}7=_Zf(HK&rRt%=fWsgo>hw^jM?{n-ri`
zban|@cZ&CH?0Cf(m4`Tss@@(nbI?quzC+D})0vJZ-dLX$8S%`CcJlSelRPmz@REB|
ziq4}+SM9~_CF52=?^XZy{D+*Ji+6>}0nqLgy*tV1gxLEJ#J`8e2>pvXtr=FGZADnG
znOYddEcUcSU1L7+;%~sl+BBEl+SxP%T-_+E%n8pZbgL^_i{4d<zH?m@$Myn#_W--7
z<<tQ*BKe;IkCI`I6m2ZyHu9a6kt%cU{uuY8o6?o`Q}%${`X*KSAu4`(#-f$<Gl)ls
zPzZ|bbiSDM-@7#~gI(-Hc$c^sX1)x&Tu2KY@!Pxf(DqD~=nwrnQpBATR|PFAtxmk@
z-e)WcCdxdUteYjRLE3CX#5RY3h?vs?Re+Dn9Jh=da01#X!pI>&tmoy{Po1wIz4-^1
z!It>jy6XXxTjYW(gLhGtjBe2Ml6+9xTzHhp)?=b==wf`oOs>`%y5-U}JuObxBbC0#
zJkYx~`Wt9oe@pr;hh{?W-`vrrxWCur(I=&DLnf2%^vGGp$R9mVF{{a%M99VYA@X~T
zv@S`Pd>?&3k)*>DtL6-2-by%zRQ&Q-pB9<2v>1ngLrR8xSB8AJ+x*I1VRhwv9ngn1
z0M(&a+RVZktS7i_Vk}A`c9}BU-0wA+6AAph=2>?WYF*MVm*`C)_X!}^F*Yv|@Uy(j
zJahycUn=(~<D+z=Bp&_OBRa%CI|%Bd_EFkLq5E#0bsQA*i1ZWEh|RiTe=nV?b~}{D
zsgE2yQ*fwz!k={LM<yzdMBaQg>D(t`o#J6f@kix6t2YU2lg!7k4>|A2-e^6Uz5Hoz
z5?V&>+SKuqTgFq5Z0~73J3c|Zc2ea>;g6E;i9J(4HMVK_Q(r3U?txi_-OAVQ12TwT
z%8^Z5Dw5;Nu-?ilQsXP(?xC7635h?RL=TVUwYba}2J0X_+FBW8Oy<FLbw-iZcdvlw
zMBeskGV(vd#$s7;1g~YN5{_74^6ijg13olMc7CTKTgHC7q|ob?XtN#~)?*Xq+XXh1
z5;6F}P9LDPNuX2L_wFSjkPv76$~8X&F=T7yl|_ei?tQp}%=L8;BdmiHd_+zz9aah)
zwytnF+=yY9&W`B4m)xEDgRk6C(mPhdg=S<|C!Id9=(QmjtM>G+{ii@kwTAhYC8Jbo
zNO@gQwT!Ykc%ATHIkPM1{aro>MNU|7yTXrt5VV4+iJ2<sQghQA&AO4ok526F!6A3~
z^@IWMx0FnQ;<2F>DRH0h*CqnJ2456^wyuCD<qqb)sBmYIbyg3<AU)!tRs1vcBZAPb
zj_#1<XHXdCzUdYnugnI8f7##1OR#t29rR1_6X0d@##aPF8NfX=*B8U{)Ed7^!I0NG
zr1d)?m1c;V+_Rz0qkyuvA5HRS&uslfeWt5|bYqI`PHxAUuO!j4;B}i8$Iywj0WSZp
z){G#QY1i1lT)OuO!EqWh?Y9*p+hwyQrjVW#mxUcvP2G|68h;YE^c)wv)_KEdCV}?w
z@l)X+=6?KR7uaC3Vr)12EV!>dVNbU<qc5!>_z|;2Tu!L0SB}^?x<!>w`tX?gDaRX@
z=OK5az&Bw0@S;(oTaeX*4{QeRURH~ArvT2wZrB;-8u#9v>*s#P6DP7UrAcy*!zohT
zmDU{*z%BcU<y+};!KzENi8X=RyzXW2M_#%~6`UsTab_$Su8e8W{v7s>>l=*=$*q@g
z8^L}(cX9YaC3uuGi*H;0UuUiqXAmkB{yD&C&;HD6b7LPDw?lU6VSW(hO<d8VKDv3K
za{n_%Mw4D%v2@Qbyj^q4ss6$r_`l{g!kpn&pMFrV;Xisg*8efD@&5&V{x1)<NejkD
zMLqprce>=Y$uSavfI&bq5L8GfI7qQAQUU@9tfztm7M4X|X1X*JLwfqOjE9A`tzfmU
zmUX4ChPAd}bu*8ZL`1QwwW^IPetTud#`$&ohA#e=u6xHuHR@-s^Noxd8M=hh7veSV
z3HQ!h_l?hu_aEnznJm%*tnb9=_0yjF+t+N2uNIHb_-M3+4LazBf9+@gPH}-h{L#Cl
zd)()|A0gPYOJOt&oR}NnDs9{wg17sEoqy4&8xDzrU8-=*h%T%hnXy+w%R9}<cx{Zm
zc|4fhrR^V=>kvrDfGX$EjZQl_63(c20HTi@#P`<dv__o=$92%r?@*y<lv_3S-srUY
zVX`_A3LGOnlG{BI>CxhuLMOHwlc`Z^P;RK|bgudXyEv%nT_2G2$naQ$UYzRMg=lon
zj#GS6l4{-VS%tc_>WbB3&QWUI=d?~k)$gp({R387+X7djn#35XPzzn<?40hs$n6oZ
z*{Lp_@5t=j9Dh7mo5uyTkIns=x{Gv=4%NHOr133I9SYjvNwv;Sr3luUNww}ysYxx-
zOSt=v!O`}I*>c-Q`&(6<Z5v~Lp`bF(D^`xa&i+K}xfU^xPhiMUyvrC+<c$Uz@r>o&
z4BN4Uw0J8AG7H)t!jT4O?fqOy;<IZNAH;RN%^D0zqbhCGzKLUNRru$NLSOCu-f3jE
zQ7*;<IR^6nGF8XTHrs#mEvc0SrAd|#V#A-SRxfNLA0JQaxX9Emj&<Q^yThJK+yd*=
zH)=hFwOU6uaw5P6cze@+8Qq1T$w{E?0yg&!@k&02r))3WS=n8$v{n}PtxYqCfV1If
zS6E2}uZO3qtKr7hRC-Y8wh`Al_2Y+vfM>Ie7_Q}i32y@ocz~NduljQS0(vpir0M||
z;uCFH+V{%I+D{tr&$4nGD;1)FPNrmoK?$s9o9_l3X&O@|^xE@dhZZrvNPIDht9xp-
z<6SMb2zAd_YeTu3G!!Of^N8oLL;6xBzpNFfb}GHSzqEv4M7=tFwOC3Z-oM(}r|_4>
zjeIj^`%(O5R*<~fc{?VUPAvi@NHWC0mTR?{^yEk}f5KVMU5R!jZ>dMWUQXwbhp$8Y
z82V5s8fMQ-N7FJJ4!eI5DaWBfTPalR%QJOXX^F9&j7{zLMvNb><}rbeoXzfkU?If%
z&WS+hVBFM+A-7H5(XcVl;{F3<ffCU&JZVbufUIqHslSj{5u_fR!VK8|@toknH0tk`
z=TA--k_kev>`CNOlL=u9f=?C<EO*=V%btwMQ%b|k2rn4BZFFaWiN84=biNAVTnvVm
zh%ni+;yPU^j3l@(>F<JuNdLXWz7n@AQwnC&6uJgGkNg9nu(`cq-n~-XiZ3h2aQ+Jk
zVnuS*D|3{(nVHgyqeY|E&te;{YUvpA$bhysVgh5Nz-u=CbaW)NkhG4R;g65h#!@Ua
zLqJX(z&vpPm&$k93d)+zW#Vx;BhkGL!i;ejCF*EEohqS^Mnx6CSDyh}qU&#z-hdHs
zHHo4<V8FK~{EBFYYy8r6$B|)?g;vCwe%Y{2Byb83p#-c+j=k(Dv+@tKh#|Y4;o=mo
zpf@7UereTHD=Zpo1<pw9Xnse$7+3za<3ofURifGd6m~Lyfc|LI5}Mpd;)|KdyAla1
zY;|E_m(L>{5CI9V_<rDJlVri1Wn_|NnHXvi6wSVtZ80CUy0wK53l>7}EoNz0UH7Ys
zi#l<5^^vj@9bXFiW*{}XpU`InqmRUUA|PQzWuQbFeLY$Tps~imj|B7lYoI_OkRywX
zz6xI=_P|Re={=aaNRu>Y?Y#Mdhycw@h{oG2^g{vPYkspr_F^CrO%rEKNv8!3(nSRJ
zKw!)GK>{WinjhJfX~q7Jlciq|UVJKzc00<@UY-vPa(qT&6ILA{iv~UE%v73&-$^D5
z6=X#720neNvz{Dde&dN^VY?3E?L&U7=2^mjvbGjJ>blTDMOu;81+vPO>$MPU4wNdp
zL@=emB}vNsOf*HWz`nu-d#lDNjSu)lg|lBVMX!{7w~1<pWScSNAWNZD|LDs{;Yj#X
zFqFUOe#$3WioaB!!l!Z^|2V$P2YYAQ<w*n^AF@9jF${2WEr5gwDUR}8CIt^Qn2rvm
z?sLp)MVMAn%F$s+xs4o&I>Fb~tZ@{7H=^1d?0C(s+8rHV=EA;JIIqZ6a=+yh-~UqK
zgYW;R+^|y|>&cc@q$k&MD+JOMRaEdonTo$RSM60W1%H2LH`BCAZ$!nXZGM=={?`yX
z^ck-f<dve3ydfkM-vkTyP(i!=XykQ`7PD3IIQ#=K75{iV;Z6A`r=QNz%mXsCKQL{U
zD3$7)q#p<-$wm<s|B!syCrelUJ^EXjRLgw0Dqk4l&Y-^1*~lYuO3$Re;#u$ygfLg}
zt<nc&PFE{RTsM1M|G-?;FD{;ZYv}V4{$>FbyUBz8KE0n@g>S4B#ZT|3_5nyKo#DgM
zaa1rR{1w*c-iW+fY^j2+Qr+@wD(FDcFJz2cPMDgf>YhD>x;yV)(~nVD8m=zQO+rVV
zK^8X<`YxZp_Xl7s=B$egNo1hEUkL55d}RMHLFFH=KgNItZSQJtAm0hS<kW*FJbxmU
z(lfCmEGPXaDoTfpKZtR?G+2R6OnZC-ca0wQ)lJ|Tr?2)3LDe%JU$`jJBx3JcQAF{X
zG0tDao)#rD_Di_umNhbsB;^mK_0}Q(HGG-0e#RS_&^3{}dFA#>HRM87ber=0rG!WK
zlqImIsFpxMZq(3w;pnj?B&jiFoCUWSyF%HVvGv|<V)7hBjLJZ90anz0?of5rWW`a_
zW&b5_(C+@+YQJ*l-L`@L=0=>kv`7*rAO0&gX;^@eeF~s+-mTPdMe|tNTF0ZuV5y9B
z5alWn!>np0KG<1u*-m1grKZd0B29{x(sZ@IrG~DuKQ3JN9E)MA!m%<Q3WhjVu+dSc
zLpA=UVeYn;rFB+)$@DQL@OMr_%z(Bc|7WR!5LpkD&O9w0_C!~Pg`>H~(^9}n%s(rL
zu6nfC^SuCtQ;qhg#9AVABBOwqu(g8f+&^0)g>vAJ*WY-=A=rfJcyhm*5PTXo=d&EQ
zcH%$1M>E5;&C?sJ7>4#h0>czeiPTjAi=jlR@&AkpmA5tHU#$FyY)Z^^VMqCXHxUnj
zBUw~aruVm;dkZ;`dpx<OMTvyN4<>G;9M>y04!?q#xjJ%FXKRVu(>MwE4Mq&KI$#Xw
z?`t9^JPJ&3!<sXw_ChC};JGr-Rt{|xMQ=<1Y|NcPjz|{Nm6_zmPo?)b5vnwGM59q`
z{R&`K)vkcR-(|n%d(1Qjt9Fl`vA=|L{%Dwlnv#a_(!uQg=#4_2@0tDc!3>jp2#qD+
zUr4-;&V19r9~0>49;3&7x}`&(`dPR?=A=aX?_5L{be;C+6cAu*F*B<GVp)Hd4#z!W
zu^}jFHyjmzvhRK~$^dZdm=Kv#fS5z_TgadL{jV)YW<^vjJUkaN^EU2Hh+(!GMl-Y0
zx~B|$I`DyGVDj{}Dtd038pO*{Nf}vW+5^&+VIoCd0EY==shJ!(D;tZQ&HB>z()zx&
zwb?qu-Ze?Ee6}NT&X{$$Dj*BeQ9AnPmBQ>*Of`iTm~wZ1R9JN^wr}?S%e)=v-|ZD5
zGni_proCG|!fFSX!%~Aygbp*$V~F#74y1-Te6ks#hw@l7<isSiXl=9@Gv%25!Q|dm
zG1Rn|(y13?KLXos=!am-hov-psZ9G39R2pR9h#FCgE;y9#ZO`uxPy&THy(J<dK~*<
z?$S?|qpSo9@mrTYSr>9no0SD|MkP3scMM;g8=m%HK0~D25=dC3>pPS{9Vnihx;MFY
zX}j*sYex1RK{uz}t^%V76qHv%r{4;C7X)o#qp?vm`5qNA!YpHQwkfJeED~?3#GTM2
zv4-QN_6nF?0<11-_q6O53thADV{^Wbk`B|QqAvUfYzCE&l)aY;=fLlcp(;tV#ThiY
z${{MsvgKsj(oa9{ZXoz-g(_C)sFs4!lz1tMy(0L6TN2J0FDLrEuNhEXR8?|HESusg
z3^TUDCZ=vV!pdgl`UBj?c=7EER>oxQXK~)!4m<l-bN6{t`J~~cHzte48S4MfA5c8E
zTT*fO{pP`kXw*<be$AEN;|KNuy@2WUQd-{>lb>5CDfLB66F<WcOUQ{9=!5dGA0k-O
zrk<&3u63DoK;f0tO<~4iZQ>*!W0PU-kXxt%nE{%5KHOy#a1OJmiRIy3RZ+>j7{ev0
zQRRsucMqru06r#cI~iXALIss3;E3aRT@5uBLjGMIDLP9u$G;%+PTKjUUl#YBvOJ%8
zSm<9$_l|0*ago0x0cRT;<GM=dLxisJa4P+1s`S@AX;JI<x9fuXDQ4EVWXEacBWrmj
z_Nit}h_3e(0wVFi1|B<cZ{9Ob85DlHNb|#?+Uc(c?nYu^Um5bVWXnfY5158SxP{M}
zsD(xX?tVY=BRZA@rOpSLTrAs^6W}kdMbhe^%e@3{-GRoxl{k;m^=CavVmm1XH}!cp
zNa`bGTO$O`w`pKU!YWaaOu=q*(v7W07_wHlC8WByyZ7kSanf`Pz4?=k>iLiJ4=k~^
zDiK5JlPZ&Ll;O7n=^R@K*@;NB30!C&<kHfy78?OP;d72qb*@w_pLj=<qljT-dI5t!
zdpz^8ItUSoBAg}+6?hqwG<sE$Df80dB@+7~IGi@C+%EVfEwO!5`fuHfvg8Ngii)Yb
zLs&&t;#E9UVtV5brM)%bMwuAv-E9nd_Tg!&cqRdAs|Oy>+F26$90<?Taq-jPq{jI|
z*f~|USxQ6$WQQhM8|)%$E8W#IM>vHm#`~Nit~w3+zgr-`shaS@33xjUQXtt%F{+1+
zH|k(AMi>R~5gJ(K7l`tTOMp3X^1^IYiAbZ?a1^j28`&(fJ=mtXAle-1<Wxi|U!m{s
zc-H%e8Z%Fn@#*shIuow<k=j$G&lL4U<Q*}y_oTc6D^GFM7wA`|dyY(%HWV!$8H}#9
zBlyt!_s|aWIE+Ta*WVz;<kp1*-`T`G8(~GyOufLCGeBp20NvEQXVog*-qGFU#7Z$D
zAsYfGvL>g_w-uD5N&Nr8*gFPC8a7(HGqE$VZQGhmY}@MCNyo{=?AV;xwr$(C?PTU;
z*RHSX?Dy2E{r&0xPv1{fcdfPV>-w1tEZ`sc^MqSMkdh|Mqu`AGmitRc`GkpahS!Pa
zAqDO;>4T*g?z0ghf+(--6l-U)HGej2iy{N-_?6{z;D(^;yE&w{9Yg2>#&D=5gKlwc
zWm$()>=L5#{Ey1!*`~6Hs8WX-CrzlSHh|mI)qKNu3ZpPi)<T{&3>t}Y|9l?Nt4ux1
zl{dtgenyZs%>>`iu6-JvWD(vyjDsCInw081@2>QS7u>P~ZS8*7hJ<rVrs@Cz4H-V$
zpa;HOE~5n932BwL?xep%3;!w~n(I_h@^i+dQ;^^PM*T&4GYHg8EcG+Fysic6s;hWi
zc~~i)5Fuc6$xy`JxN1&@ZHu${3XIa$!Aj6$`EJ^%#$OofXJAec&Wq{pHLFqfwv%*-
z6x9SIf48!2tY$3Ze<z<TDWNYbrFXih@;@i4U60m#d6b+@Dveww`^Nc)XhqWbCVM(V
z*-R(~Fe@|`Polj1S)`5GGdbm74%YlhrKLTQ_y`?WC4bY-?i_(8HYUrqU`nY`sOuiM
zFM8BFV@AP7p{RI|KnX{iv-=KrM&wOIzAbCk{XjXDtp|2BVX@~+Ge^kz4{xlv)}u<-
zfB#QNWM^g<R%-XJBcjQW;U1{j&vVn_F+NAq+NXNU1<s!t(5GuEdFCr%*7gEouKf$q
zO2ahT;oce!n?GDhe=^GgZK*8Rf9TogAM}j{R0Uj$H1yla+DYbYqzbO4apI6P$)MKj
zu4UD-ORn`NYSeVTVrOp#9@t}wf*+D0xH$9gNu1BB!y=>G8j|478#nl4SU@b3yxIy&
zUW=w)ievzP1V4Rex17#n@FGN9#VP1aQH(GUyMI(+HyEAs!FBN?BiN;I|HFcM=9X~z
z>~bV9hH^S)v^2O)$`|qMH{&N=|FrjyvgL~K3&<2S@~b1TW<bB=*@&^r;+H$t&Zfkk
z!pJ%`*hgVUP**}m=$TJ8@<D`<IpFUS?ljSV<Vc#@-TDY$e!N1a{~KzSq==Er{~KNV
ze_|vLL-fbaf8Jcf7xE!=x_aLc;ZlQQi3jO&RV4#NMNktQJa$dlq@Xz49nG=AD@!Vs
ztF_A;2^Y01F_HPdX$5G`YBN<ttf^NvR=OE%pP!$5O`FS9KD=kGZklo>n2NmrT}gZW
zJbHiMTE6CL|93x}{jKKrUpX->-`u?vcM(SWGUl7)2!mbQ)(`DLz88?LFJ1q3sXNv+
z#*UA-;&0^JI9);Y8?Q8gs9#Sv-3v0&->`oVdkVCaJKd@uIR7g5{BF8w1$+N_+?H<q
zBc=X(HYkkqF&Q}xv3LFJ=pGEe&j1IqSEe9VVvwb8i!ZU?p1S$>-HrdRS4e6~u|dtd
zu>^&!QYRWkNfjkVnZL3o=(y#3+_+TsLu_*C#3^7*7;r=3`soF8rs;Wes&4_r_v1G(
z$%#dyZ>O}Af5^<-6Q#x2RWJz{QcN^u*vE%cR#`L2`c2F<>HAT&l*(pwlcUE}Gv)79
zX^Y`J(yQkj8-5lt&HYN_(`TeAaUsnjPf0jbrWr3s*Cy9~LA8#<g#XJleu&;me><n_
zUz#iol5T8}Wh{QP;8`qn!Of~t?3AV}5!SR)EeVfR*><PRtr5gOt*8kgfM3>F2<77g
zNn#i&H+Pj5aTT~__)`j?a^wTJO;Jjs|G1vU0ro#qjl@8}Y~F;}?h%Bv*}<sV7E=t8
zX5J0EA47{7B>5yun*dSm$EH6<32-O9YMuj$j>fE9Yi6uxubg<EF@z_qv~6IXs>mUH
zbZw8>VY7tr*cjvGj}|8MYiN;-@Dgp0)NH5qQ3L3^QF{%Ko?hG=Y=)1PyG>;%Fx;uw
zHH-@=Rj52pOQGv9Y!aff*l2_;sm%7O4KP-hMZafF=(KX#U@|rfV1q;mFc!U8_)Jjr
zewXY1p(pzhnL4`_VO3-nlvhO9AkO5Ojbp{di87{3?UIHEim)Rq)0uS`*hvA1W&Mm4
zyD&raY_`34d=u{^EeYkN)6PR-TNwRD=#0sia!-lL5s2Zc6lew;Ieo~|9H-y4%<ERk
zh|Ws7D7;yR0E`_4SFfD$0<0<q)CC$ajzmwJ6`|PJ8>QN1X~^47-#8rIy5y(Kf{1>W
zZ#CGMpEHxGC$3&nQg=AC+POLku9ZNWK-H67We*WCjW*jzBT!U?9l|(=7%wzk-9cnp
zkevldoGQXkA+Pl{)^pHZC`z9ia05Cu@w2GRic>Is=lDRl{cxfagv0odoZt+wU(cvF
zLU|==32h<WSO((T6BRjyxmu17NK!nL($43_H&uyh#NSFj&wcuXGRofQm1iNP)32Fi
zp;IFjQ#V-DYEjT%7Mp?~AwD*1Gb}eq(LIicU@4q3V+slNMi#q+Ia^gb=8FcC&QF@j
zT=zI&qJA^7WYpLh%_1wM(9kI`YN~UHDH;hSaki5-7zI=p*KDCjui2juHwF31%BUjS
z>|k)#!*S3p<SCZ_qQlTGoUsaCqHa*nWy9c&#6t+4Qa{133Wv)&M-MEh=Oh5IVE1KF
zkW}$!MrA_koB7lMsP|svDNot+CdG;IEe$5ONCf?!ZonGPmO?0$<mCjEjwr2cBGi)*
z+6{?;;nBbAY3t$4g(Y%bE8a2d*$N~~P@ZZ+{}E~F9e`Pe&>a-I%euB?xKb-bN@F3L
zz_R!UE&<#7rcCjAVcI53DsNr?8MCm$NIn|X(do8VpmMD-isc2h*LE-#SA|W}D_Bp|
z4fP>rx}g-~7YD28^wmoCXac0$QZrXwlVo;S6+yiLwaOqMqR|7jOSU*~qa`|V_G;K9
z91gClVzIcMsnZYZhHOp?^h6o1VD2IgI5Z~R{MlFZ-Ik@1yb^JiwUI|IHX#d_@3zV%
z8u{?yn++?IP2bh+xJ`AqlA18yBE$^}BViDMA@r;wvkr0krtdPdkbs7ANo0)ET8q?R
zHgGZEC;eGiP<v$hg#4&}^k;-@IW>ATrdDlsw!;8QhUUm3uAXcPwM(hEL4LKf)!YfI
zQ4J>u*Lldj1!T!2t=3!-Hgnh@mTwO;#5TwLlwWIR5ednOJ(~y27pX|)c%rj_H=1+^
zW5A1tgc)iR$sh8g&?}r>bU{3}26fS>Yo^}aleRn8MN|-y83I#f3&`+|AaXruFx?qv
zA>>Y&sOQ{R<Um!0_LeRLK03MQuxNT?Ujl;}aZnc-qgy_|Pm0~#380M@(OZf<?^&8<
z{sdEL_+yqc9(R)#y-T9m(uHqRoVpCY*5>G^j{Qzmoq;l_OTq02ptw%NW5$LKO9<G6
z65iC1DHFIlWu}-<G?N9lSvZS)Y6rT?C9-Ttx>`IDY%|D*7VTbV_lzZ+J2CPU&AkMx
z7s=0hC=qX`uG+=GpP2#0ino_4^iSW!hakdOHG~q*TQCX8-ypAIT0WRy#(sXn20vLo
zkP8&fDx6pb`<BhJJyiUfwtVQ2?fUu7;Th*!G$VuCDO+vf@{{yU%~LLa`Se(-v6xF8
z_cMSI^`d*>1|oam1kqC^zxhNX2uFmbWaA*Bbaws08nl(WP5q#QsIXs*`?N0>>|6X*
zlL$5=;QIU|LLHN6u2nrD0|^#wTQk>YuTRElFfB5e5Qh}}(M><YRS9r<Pn3i1MFapr
zq()cNKv#Uv(0Q3QR)Ll<Q`3W8AkD^XF;|@KZ)khy)@OkZ5WHKQW$AA>qE$Cj5p>Mv
zEa`N%W}sLf7Iz=Ps*ujGk1#pv`K~H=4{S7UF5BVWa3Oy`MMUIg8~n1~u%?#4jEuD2
zGE(g$Hz265Eq-x~56_ZQxyXK`jss}Y?|RNh87{aRa12-<#lHeded&HMn?T^JJRPY6
z(#||xGuSgv#?WIK_^3??qx&}l^{aS@G%4#SJuAe+s(N?WA(wu}j-2e;(ojSm?vtwQ
z@-&Q&LJdl7F6F&jya(tqRB3p1(5G+KHahkYHc=HdykBz>0lFsfT!d$|(z%P=)=B0{
z-2A}6B@27bHDf@H0NFn?QBhlR)aa3`^m<`iXJ?c9wveGER|dL_bleObYirhNxDf40
z8+8nG=+ivpEz!3DWVC3_E8HtaRw@EYK17O|W0pe9C26xJ)eZS%_W3e-*8%w!rbax?
z<ALIul|d|w`Le@F_38v~?Ur7b-&D8Miz;KgdXXNvMtmk&_4P8Hx@ONAHV5nvQ&O98
z(T``i>I|jT<yy-P1+9%$ja9Wq1Th**P0W<zkSa!wP^7iN%YuV8EO}{(?q#%<ysONw
z6QuPF!?wF`H<025>CUle)SNh&gM!<FrS1;=h}n*aZMx&?qc5^wcPc%`Mol4|!2V>A
zj31fR!Lz_#;df?Tx<Z_jIxna5@?>ddTJpV<cdD3X?W5jRSpseTZNR<HFbd^`uJvy=
z>G4#cdtJ}0kYp~k7?0Ej?bK==VjDRim{*1oN<MzK4v{?$bhaC{nDWMVGw-Zj<B8N3
zd7%1a@ZS^*dibN_K}G(GKNF^@l}PxkIN`EAn>jBZ%RIrI-g%M3L+)J2hALAP+DY~>
zSU1#^ncr1kr@HMhL<rV;z&nmDY18GEO=Q*Ca@4Y*QB~lq-a>|Rl&IuTkb`uHnM1==
zr1eCSxJqyi<Ov&Ns6zXL;~(^h+MX#}Zx9Dk#8H1s;U3$$R#(P9xLCK$plYYU521D5
zJb%KDvzxDTHydOvr{N$jnIps{@T8}vDyT}bKRFB!OSx}I)*t`tt@^CMJ|SB|q?U9J
zBt<m+_E<s)s#U^jS5ol(juTzb>FXX3iwcauEBV=3OtsSP6l`aUotHr*?w7CLoZ`bP
zZ2h?FCqWRMuZEN1l7gPRqR&I9g;kg5No|O*6@}PYH)bc1kiQmt01>@js|Wn{xWAqB
z7+R<VId60YsGDob@+g7`Fd9GEKFUI216jmE^1d>=DF?W8%nvs%G*wyauC6uIxyH7e
z&ubMo-E+!^|6L%FZp!f&uX8#g`Zh%QHjaxqme>XCm*n~4M1d54=%%aZn2D}PTnN^(
z$FWZ`zvr=Klz21xEVV2&CmhUboQG|1iQo5<KN=vX+*7z|_I21G!2?Fkk{A(FoB!21
zcx;xfQA{p6mD_68HRy9XVrXRv7W`1>VXSBW5`onOL9S-$KUAm4ds!X%IVC&JV<r2E
zy<EUisRXTppJ#kZga;|l|D6m>W1fK|hL#vfqZBH2db8ecN2$9e&vAV56pW#Lk@uda
z+eBQOLM9Y_Nw-(XhKQ_A2meiN?EP#+#%M^br8{oQ?@gqF8yf1z<NO}G9wXXlpw1S6
zi#Ll7jh!(AzoLM(M;G-`{*gKU9BFfqL2&S@H!+}zY0Alw_(W38x}38f`Vrz`=1Bc<
z|J19ImVztS@}h`uW!5F+hYaUFUG|bBFay)PBkF-G;*M%U*Gc2v%@ysKB-qUqecNpO
zp)af14jvqg=4LY2RT-LndpyX(6HOC96<yl=AmS}dY&!Rk9<cH(z#YK+ZMcDa-~nRb
zK{gDBGe~4_M8^@I&1IoJm9bfX8uuG-{f)(UhV@93rK_O|Zh(E^Xt;3UvR2cE7H4P;
z^l;q)y~?jUCyzP`rYhA>{q8nsiYCH6>ZD#>E#>6EMIGeMi=FhdopcFFCpWCCl}M)|
z4W-j@0pX<6*XR)V4@g*E_`}g6XWhafmj-T3=5T?Ryil>Uljp~2`UjZC<4^rin0q(=
z-460vzPCfc-ejE#XJgA<DaXu?rn(&-^oQI!WVIwn{$r*v6Q#5j$0ng_WP`E?N)YAq
zpwEj_A=79Z-&ZAfTe+r7spVa~aDCoSlLTqTxg<y*Zc-{&sr^v{pt2eV{^5)^W94_H
z$}oaX9#%SLqGmYnxAby+TO${8T(};JkOpnG^j14&vcr`YaZiQiw<0t6Sb$6@-m!%y
z7&0`h_VqZbV_tuTzkI5sI>3AX-JoJI%E|xJ_;+KI+u7g{+y5?RwONmJ_P+GkxgySM
ziaok_+8HpCB@!7Jr%Hc#3_z+<yD{bnUBZ<e)=CX^R*Z3W<Xp-nICeZ~bS!}8MnJR?
zhPK;bcVeQ7*UJ=qat8AVB-t{F$|05}w8^_|3Hw-)6>CXN-bJ<QFErg@ZG+I5Not9&
z>Q#IAQB_3ch)B@W_`qA0FSO^$8-~Y&w{bA*P;ZWE_bfY{m7VX{TnzE-Ugl6;4E5~6
z>(D*i2c8XbpQ*=*aj)tFPP?w`w&L&!xa}xSt6$vl2W@8St?YYzSMb^ztj`wO;h8Sx
z-g(8-H?!@C1;3cS-5boTbq{ZJBsRy?PcR+uRxnAU+Beqivn(d8cckeWO6U0=dF!eR
z6<nAWJ?;ppnjW)%$wMUL#9lR^b|J)-KbB2rNMql#*b=g>A9#Kvw-k4FYeZUQ<_&p3
zMbtHTub&J+=wh%IkW1aKI9wIl_0-RaJk4&tCD<780A`yDb&bE=)vnG*W;n2+FO7{~
z)HJhtV-OBMJK%X&<Yu*G?W!)xF?Gf8DfVbn4<kEJu_t@sUiBg4uoWwAfV{}}@8)A_
z)b4nMr0yPj5}Xm%p9P<C-f;{`?ogeCdYt&;ZB0h;X$Va}xi@S@d;|V+%HJd3jtSfl
z86SFJ@K@}hK(1q4DAuU-=EDJL!oZWDcV7`CXjcTB0jH_m`_zy=AA7`@gtt6JtmwBV
zqEPAgI3I9NACP0h2L#5*iy=STbb3wTo+x4Q2QEZxCO7<NdRQT2{6ZYP1qPC+KPgl`
zYPl-^^85RQ?=^`gl0hm&;9)h@v%;@uRDhbH&^ZmtYF<~SngQrdRNRx?VNB+F^=izZ
z``%SL@_o+4$wO|z;)WYtd4hB9O50{S_W|*&;pOMox9<s`KlX1?G@fE?>k5(53mjiZ
zNiv4Zv+F=~e!YKT`EpEjX%40)0{Q2s@kgQ6vQdsOsS4C(j)xox|2;^srUxiMg;h|d
zgL!yDO;d_a9lK%e^6=YNd;6O|?+*su1l}~8?G$fR+?L-t^34v@@3mKqJkqB(F>ESk
zzVWjgeOuB+D#EkDj@iTuSJ&_LhbV&Nr*rb;L5AM5*iP=<KKL#d$K^j7si8u!IQxWG
zB!D7L#0$(*sgMF^*Bov0og8}O^|kBw4fG4<XB;B28BO`;m?M6jz4xC|q+biU*^Xa0
zV)QTEKmY%_Qu^;?>Hm+^m=!-R-TxCk<e%mI(2!N<5<JXiiERgjZkVE@(O@t-#==$c
z=#2Q9yd>402@Q1sJW)?5>U4oxgL0`IV2bB{+U;+`#QFL?{BHt!9cJbnVN?$^cuGth
z)+(E3pF+_QLk+VP2lt-MB8T*i1XhPNewg6nuhuwB^-x3yAbI^xU_ijEixH|Hsk@sw
z;wc79Y*9O$y)DEIREo<s98vp><_4{~qUhgwM$)pWo!+T~Lc6Bk#Y8wh8T+@I2^lpy
zDDVt65ZLFYxNjeS7OmHhGT;3~cnwhu?Vy8dL6EO~pgTN<Ze%n?Z`)g0-mgGlYx9}3
z=MIm7h_evfH8V1%iA0}6X#bayZM2W9j}t$rJV`yn#(JVPi#$6?Bdus-9JPdCcAQ9M
z*?d98>~)V4{;p{<%Zrm!G55(aS7nk}_e%jpPx+fWT{K#gcg|Zbr_UwlYNl#h`3W4=
zEoa9?cO$}oHTw^;Y^+@8l(GE$_J0J0MRx3#hmhaCp?r<be*UjVDQX5Va<%y%S>b<h
zq#HFnoae>S|5ZAVP)jFJlK+@fjz;w+4@;iIM4gL=m)#FK`f^_>ny#X(B-6_L^fY)7
zJn{KlMV|Tk26Mm0xhJ7#50wSjeAp7F1^YPH>zmEj&s$yAkIzDWe<61qKj`;R_^Awa
zMPWvnDPOo-5!)Tr2kuk%=1(an4Alqlr^4O8-;-WuW8IJvF~PWp+Z&+I2FQ>yidgo6
zsiI6u!p^)nX^TR$%4rUWbrnap1eEJ~CjUEpG0^`_(qn3oohpX}lGnq{$dt~`G+N>D
z6>BXTX#(~qQ)O-h06;kE^0n_cxX=$BcF3#)r28RBaTqE}SR5WoQaB+r$LRBO%6A1O
z8PS(H;a~Tyknw0hxn{c4*4aHcW+XCnw)-JvrpM?q$IgDWTlx#|2;dms%8co>$o56J
z%P3<kEC)x|4h{Rox71<!N##Vu({~MjQsD5?acHqFH`E4(W0&+5;ob4bG`D6Nk(twC
z7DE{ael~i%Lrdk@&U;c;uSAQ{>LR-@>y(4L={k$wGr9j7jiV%p6J3Chu85x=nQtmQ
zX4BO{wK;FHJHXKl;FmitVqdIL*8Kxu(QWBQ+(=`S-aV6AUvers7meunYcUCaI4AX8
z_)(q(e~TUoQg@4^sxsYd?*vhet<?<jI}<#yiti_p-0L-?u1qXC=<d{Lu-lI-bxqoi
z{5#JkP{7GDa#9oeXHDfmvHs&yv7B6CLG&_|fC+tK5A_Ea8=IuK7O5h?t|M0|#6`Q`
zl{?s+%bRu&#QA!Z7pEam0F6+w-dC(L(jj5cvcFc<R`$5j+`bamElh%r0DD$a;jSw=
zz6SXn2Uvl;Pa-j0#2#s%V{Eb0x<-}zO{b6W0%J$ACFC5{&QPj{4po298caXs25Jla
zCON42HW~sa6ek**cJ%POp0Y+?yL*h$wD?x61KPE-n$VA%+@P47+TRM~_`Sv6w`?J3
z85Zz`7W69n5Q4|?T|XRT`q*BSdo)nHhPY6>2HjA*hLKTy2NZ-sm1lS%WR1w%$Exk;
zym0XYrlnWR7hUHw5QFVzJd_^oQMpPiatt}fCy^UE{Z|YtzWg^;8lAHV0}To;qEo7s
zFGlM(79p2$W%!|-8hRzVib=FO3Q-PTR?C@iz`iIbKvDK#zhfKKw`lkpdlSYn=J-s>
zRvfv`nk;~bv~WfRwc;#p*!ec)hq1fW3C^%Ge~d&KVKHTDG9CA8mTGyP8n?$|_+qp+
z*V~;maA~O?0l6eu+{|2>4RQREx?X2R>42lwwAcS9*5Hi{$A^pX(V&ZG>CcfxeS!1z
z-p*Xz!zd9f;+)2)s6q@lJC<rosX>*)k0N`TKNeR#TcG~34iWpE+BzgWU0RKNs#MjG
z+DZo;i46k=CpG1<k@jj5Ce!{hBSw$wfYINUDEuDj?rX>JP4OC~Zr9r75sQNPKy-FK
zDIcNZ19y2dc5Bh;6HbBHv(sR?I_<FCL^Ezm$Q>JDnOo5PEYI0;`{_Cg@oR@0+M*<T
zqtBbEcOt;t65)1H(;Mf4Q^}S4=fAx6HwfIXc3RZcQ<pmoW=C0RKvFr=B3#_QFr`E=
zPlQ|4`vL3^j|7fb=lFbQ#LNfl+1gp8#R~zb-42uFhnDCI*YnDE1K}M@tR=Kf(C`Ue
zDxPDIYMHZ`zC<eZj>QL36AL;C=4=BPO>4x_t9wNl^a`!^k!5p|5f1Xxkj4xU`Vx_S
z)fa1`-Wk0T+xh#m`!5+FVc~WH#D?^SLYy)QzOx#_F87;{4z$HT2&hjyxwiJ7%e1^l
z`xw0Fv#n7C=L}hN?K@Sd4k^gGNW&+uw-w0Fk?57hwV@g54@ST?X0*<VYoxZbnPY}Z
z!>?op7%$^L{!slVOYosRcg}Nck>p5<{&Yr!H<Nq;3NDjm4RJOch+q<ATFJAuj;H6w
zV$?RJ(sduxn*5!B?&L2x=-|l#1$kCcW1zoTui0sEP4`A0l_Won)SQn;AZY%|jKU#A
z<^}72ZkDr$&3$FQ{teKBef!4szy5@%n3=dbS-N<T%NlulNZQ+&nmPS<-IS!HCj%yo
zF0j8`b)F8;I<-bw5?LP>5k?I{hm91V{uQ&&eKOWYw{K_oPulYb+}rohl9MaIs}&ow
z`Bm%jmRIWQhv)k@hv+hYgfUzo0=eQ8DM$~|3zrtbvwrbvqY2jyfn!|*JW`<rTiTl1
zy+_Z_5cDcK>Pua)m`tiF&)g0eSs<8(wZo2Y%x4rS+kK`G=>_ty!VL?Q@^&1fs?_=P
zZZc}fqce@FGP@KZgiIO$kh|7XB6@8+vsDpO6pG`Wu&lLtG#`mIJoQ>+48+%wlVYFc
z*_r>*3E|wD+mXTt?mBeBQnH^QnE!j~SBxssVtj^LGO;HY`>o>nitq^|LSZG-3}IU*
zA{$K_8H-XBgJpQnZ9A71J}Pr?%I*iT(nFaWJ!fz$Sel>YC9!Aee?X^v@4i$vh#}Rq
z*R)QJDqd(A0r%xS{h#Oa*K&FK<V#gp^ED_J_+QWGzu4N!W+wJdrW#+z^#Ach4C=tU
zqc1-G%NjL#Vj&^<Q%BnJ>-Ude0WUw%M9GlDe+7{L{u7pPL9VrOF|>(@Txp@xC}>^T
zs9uq$CevsoCP%EC)TFLczNBsKvnWyixcTPmf9N+gaRG2+lj7WY{_OsAI^N<t-f*6N
z-{8Ah`FG{_qsPUp0Q%Ud8Si+{+VbylFCo}-SVw_kG&IZDqaxv<mn20>hlAIMh(5BV
z>Yq90G#d00Qe?zpW1Q&NEy<)O6-z%Xf}LJTT#6rp9v*)l#ATdg5r!r0D;|*4N3Zil
z__1a7P5JfHQ7tJY*_6_y<`T=;R|BO~DNT#qOEZf+O9N;-*+EE2fHvt+4<+Hy@piHf
z7jm^S_WsCIm&6JDO64SkGPU&6UIbq8bS*;tSIwm8`#<Sp9jav9!(Pmh051om$=ey-
zbgFr(5!Cy_QrG!#mw0J-{!|GwMs4b8UduDRh7mccd1Fgl-397|`=ELXLT%~spd}hY
zZTXu$7;O@{=ty~t*6gA=Y2+;Va)=uQ<kN+NLI6A^F^GgoTX&&MIYU|)W!nll-2w#7
z8(d(SvdfPgOhfuYFvmA9ri3-fk6tYA(W##9s-OAmJU9uFHmh)MmDWclRbW^I?^O3R
z>sai&kB;dp0hW)3?7nvrqvGkW-5oDly@I*HAfsA$^0H>!`$q?2Q&HG?EYZBmB+t;T
z4S;GB$GM{bx@D!!GGCtfpZe93Od*{Zu7X`vv^!&QmuTVC*pLcn(zxicrXB74_-*K@
z(<DT&p_|~iqOU<@2PgjdjzrKXAs<Xp@DEvH)um#l9&5rMD?gUj11BRNEcmgJ#rt|4
z&f`;2h-ct_IVKRY9clg;&+BbL0o`(9RxB-_C1u?jmN?~Z^+vYf1ymXdY~h#zs^t9m
z=5a$F9IVYm_{YjM_%2paRS%8xc~B8Gg8=fbzv0Dc4=cCOSpgDjd=DiLfaJ+CLWmYm
z%zrRqG#BiebvfN!>zC#DT0Y&0iym&5y)6{g!SBRzZ&U6P=KQVcQpL=%e^8?F&i7@F
zW(5^37EG+I+%KP^TRQ(pksD#*VD=BBKdBi9;uOXbr4ifT`570Ka&DmFu;%-GGTRCy
zD1X;MaVCu55I@2uX^KNfg%7B8Z+tO-Q>9(i#?-P7F~(e_W5v6Cd*i`D8k$#?QPiMH
zP3J8TU<1?_QuQ_XF4DRqrBfVCBZLIrY6W2wuD%-mE1E|Jjmp5b){}h~Ar)h`S#WLQ
z!kHC!6hWefC!O@PC?!N3TgfK>TRt*0c~oW3$txN%A!*maFp|gb`D1qyJ|s#NXqv)%
zEp415fxnbaDLbZ&AM`ozu`(04V{-XV!PErLF6?~LdWB>Hlqz+`oW!{68I&dq$51p^
z7_?ru@Xpma-pP``TPZHSM2@e|>rw4w>r9PmLO`%2^bT$#YO8IY5spf4)GQAR)5u?`
z)4H&}fdiV7=Ppi=e2ZxfLNNy6-1`1e^Ar)W_cRm)Iq<jn=QvjutK$JoatP*3SOPb{
zb|K%ijeoJE(^<KQ=1~sbg0F@`4!|JF!(W<MshqMVF&=kj^igJB6wpbaxgfoN_f20i
zTx~3svUet5z%D&KVeZr2k8%h*z;6<b$;&Tb++;P;KzJ?6K0?H1q2D?Z%e!nVX`=U{
zaj>On;9jE&=SvFZ1Tv+n8qp&x{mmq%b8G;Ym#J`yBeX{wIchSbCI)Y(ly>z7wkPs8
zsUo{Z>>k{2NDV=S@A$Y(C?iTq%I?IlOFX6xmJMe%6`rs@8Ui*lIqI$sDqJU_>ePWr
zG--bqrsNHk<<(Irzz>`=D8kDQMPPp~k@WH_c^eecz4Q!Hi3#fcz^!jG)}pc&Askox
zDN~bVeI+WKfkIsl9qmF>l%RDxa;HUBoFZVuXhZ+#C9|f4R+lAJNMlbwUUtPt7CZK4
zc`9zzoxl}Zhr%h!`z8EHgrx8HEf0k2H9z5jvQJ+$gkawg6`Hvb&@C`xvr|2l2Kh>A
zShf&yIaDp4NVqhL3l&+bzJ-e~&rv2-&CkdQE#BCAOB9}SwE1(EyX1>=%}#Sq0F<sR
zUKppAzxq3|LLH7b9@|-m?~Ds4ST1<$$BML+(XK_3D>qi>DgcSec`c~#e*AmKeTvAC
z)2ttyml-EOkgt@RMGMr#T$W3Ucz66RCC-+d4u@`NPF*Q?nhl#ogX9YP8oHJLT8j_>
z`;x`4LoUUx!@qXzac=al;RI3iz~@DAU6$kuQ%R{~Lti(wsYAtG^SL#GUliiDcEM&?
zvlv)_{jU1R)b*?b596#uExU%Kb0NEilrsn8F7~pu`~9OPUNN(9yGH(diA<p#sA(3M
z<jLNa19VWHJ6Z1g3;sYXkyUX<g}8o70s_w2tG?O(dOJN;&flI5#1)Y3rjo_^Rr_a_
ztS-h^37-}mL|7<f@gTu05i^@J_oRXbI>Q@y=XRlhNJvNF@XU0bT=)J}NX7BS_EjSq
zoP1p~q@84IP%G@Ve4zi#QUIl0d3jS&;f9NkSD5@3n%isc5AG)OAid+lK{&UM#@(~@
z4MZG*sS!j&VeH{GxHi8OUy{m{?d4a?KR)rW)Hgh%8($4GOG<^!ueW3#RZ;Vl%1=4P
z0O=1#W+JM;1v30)PN)GLawPpNo$WqxMI_o0N!pq@*?yqh?P1>zEB1iy6w82S4OSgj
zJGK34CEYkYW41I-g>XMp1Qkz3K!SNO9B)B_7-u=RqkX@sG_k^~O2bm=R3XT-G!P5U
z6l+T7z&I87e554}x(k1c=hU+@xV46N&78=*Nf+wjUKUkzyb)a*RnqO$C&OfZQzMa6
zO2iLQcjBN>7+pqJbF_@mx&1*2z`AEcaErZX+)edqlbb=W&MTGncVLxOf#dO|5gYp=
zV(reeBi=hT1yo{i6k-!O?Txa!nL|AIvNp$>9cR?0n5zqRAw;brs}IgZ^Jiku2mWMV
zTkVZbLmffJd5G$fYPlu}FJFHMntn6~j9}kb<>jzxC!4#KBGW=88v>SgaepJ{N}1>;
zyPC1B&~V(V7l(~bG=XQ^!L~Lmlu{>`Xr@8YU@)3wg!)-$Bxw=EC%`NQzM0~3=k^Gu
z;wf3{3Q~9KpPc#XQWP3%_8kdxZ%Zv9ZI~-~RNEmHAz}<;#uUKbZ%mFR56)X39ho+o
zbg+LK*UqBG$6~@p;$v^(aV|Ojj6B~3M6*#PJ!#SL@yG#bBj7#ClWDY*u=yl~+So<3
zCLrokIoqAu2sD2JzQLZ8$du++l22D{t>Rxhi$*0O1vezPAtd7BhmQ^V*aMrzjIxxb
zfvi1UZvVE!l8QpXVO7lvk(y~b*+8~R<+!Z=6rS`E17|v(*V&P1;whd<m+(WZ*I%S0
zZzpN0YC|2liUEhtNP?bvc!KLXobqI`lNzm6tZqG84cwwRFO~lI-0eOyS30#=bu+ZP
z<+Ww3{JEfB{#8QC9Nf$!*eXL-^UIu&OsC!ArqfzpHlw4E$>9-Y391b4oviXsFO<ab
zj!tW4_tITUQ4iWI0W`{-Mq~Z4gN8AOynd2ZM<GTi11r5;bZG+oddBtw<Bf7WWllVW
z`fx^j20Y%b>Bc$JVV5KC;VZZhG`@}MhNZahya}G62nkdU(KgC>EHxfa;#i|fSm8=$
zCg{m@8UP#z*U)!=Mb@8n>3AUVygSI>;OiTMk>^;|Ru$C-jWtDfuVp;r=T?|YQ~Hf1
zwN?IV`zL?X%154YHoMX@&kmG)iZ1Rk$Osb|iyoHCSOYXJs8Z8<tpuOR4U;76Ra20C
zs<y7EGcv?DBJr&8tk2IemoiCxjw<T9u}?cH+$XiO?uFZDk0Z(qYPpA#MN}MvjfGaz
z$a;;*3=4CV)XAO7JT!a~SVnI{{N8qw25v{~zu_DfkHpwI5@Xfnk{3`Uv^7TPg}gwE
z92Ue4$nyLIsJjK~8e(a&$_w0@`H^r_`!&(a)NlS+cbo`w12Q+ME@&|@Egd=tEkn<Y
zwbQg!Ws!OC@wJy^nWPv*=EW_QphQAWnjDZzxUd~jeY@1T!Gkg@qG-SVf{9j0A}wxp
zPGox1HKJN&%>&W4$)Aq$GwHkOQT0rGhOzglo44!<DSQl`D(AR`2gnoTaa*3GVSm}p
zw^TH6*?tRt=<gq>$n$m`N)lG*`WgO>G&GK4cPB0DsnBhGMqzn%q|b6b8ceEeLn*sX
zXVttv1pC@wG2@V=hUoB_(Tq>WQ_9I%2v1gcyl=Sf^@NAqevCTANi!oTzwRAkPnGsi
z0`xSZz2w7)1uH{fZyyjh);6U`?N}?8x^tp{W4Ne}sEr1fmTkEG2PIG5YqQx8gMH*#
zcxyEEz^B$HVw^jPPxN<JFx&?>*70|0(OU18UHw|`V3r)LonOARcPJzH22nCUTNX0g
zqlQz8qq?W}>6C|rc5ahs_KEIZ$`Ws5Uarr+K3_jMUZkA78Dh8!K^U(e#!uD5h)2$B
zb_eEy{To3!B+y*<rZi5k(6n@PIdvc+9zDgevG!OM^)7-|y%9RPYhl6S%J<l1#74ZT
zO9!`Jl_9ijJNL@w_1sHQVXTlOEr;NBrG?;Ke(a^lE`mWFMa^b#vJ|XqE?2xKzmX8Z
zKk)e%RSF|Io8axtYgdE|!7Lkik72C^P7LCACJ*`4EB>|Pk;q$6|3p~3VJXZOf<+2&
zs3zSlCt6|WWH$m@&G?utUpW)uH0$`Pn)$k#b>`NyX4bP>k`9+)z-_U6<J*HN+EAdK
z+k+_h(DdoWP?C+%lk-vOn30QFAEZNs0$JoGew6=^VAE0h-Dp`OucJw4d$PxcOcEvW
zqc>;9zu1BDZwR&iPlRgbp$yH)m>MJl6M@zmfAJl9+{k)M)~Vh~+0LkERMRt|Vaz3Z
zI@InSTYjd_^;?;(`iB89^o`#6bOC3+tAi~)em2ZkFLyE?THnGwJB*3q2(ONIhfJ?I
z#)TdIc_4b!fKL<1l?A}HVl@z-suRz#YP`aF#rfT?b`tS|w3#xDbb2d2RSsE%g;j4r
zA?esIvyLDEOIx}tifG?cQ5=CI7(S>}fSQWahRCf56_}StyPPuqr1qsy$X>?r^hPd%
zeaNMmsYjccFL%Nz7)V(U?1wmU2&RfD8A}K!gESOZ>tfm-J_0T@-e`8_H(#{+!NZNU
zDVfc#j(IgC`jW%7bf&hp2EDc=u6E<ItyGq;RBF`mNvvjZ)!`Wo*m*;izghv8Cp(DZ
z`Yj#UI^dt{jh$H1C(WUKC#@ol5eRz%JC4K=%$-+8=XAnPUl0iaE!uyz9O#RKJX@)x
zDTZ2+y3Oxv7utn{7~tGkiyDXWH_*h0AReuw)Ni3N{664J+)S|DfJRpuis)|X=~7)1
zn*O9rQ*Ss^(mvT`cXFT9419`{f-LpY81@&vEJ3s>(`Ms7c@MI^(`8QY3r;!hc*DT`
z7Q2Oq9e2p_rVEdy;oE|uF$z!2lT|p**#v&ve48QI<fr4*T9XNeRFW=V<fE$|eoD_@
zw;y&3V;Odtn%=0-*S!JnHL-kyt{X1-zId2Ysw1n>3FRARg3Uj4E}ZQp0!M#CFy*vE
zgThbL4sSh7jbVFJ?1##B)%4jk86G_*EzC$6WW;z2X=}x~k~J*r-XhAta*pUuhDy5v
z2s4KwS$d?;9ozm?8ary5Moh1K_jyHPXLvqz%lE(o6MW{x-n2Lsx8_=NC&1L6fsizG
zG2!S}Lu8{0ecc$eju2U&?Lyow`<0^sknOP(y#T$!d9bXm91yx3<d%)ZH&vHFn;#kC
z#31d)QSsnTlQHnn?#A))r0+OC4m}@Sh&nfkvRk~VCZb84$$0SsB7Ah6bd}6!n?fPg
zJTM`>@T<o*1Hgmv_iO*bJ}{#JT24pu=>t`K%4{9-3(fH|%Quc$Co7%5-nSyVVQm9_
z53Z%~^6F`$?d@1_rE06PXZjr4v&}K_e_&gE?bx|CYJ_TpGDFW)j@ZrdEcX7PWEU{v
zf|&#kg6%s}7k!bdhf{_UI@4FK(8K+VOLyS1hep69td*>7<72Os%~zkT^%VD1xLb12
zkP17Jg7b%O2w>ks8<cV)+aZg!hp`s4Y(ce^M|I2D8RT|C&>>^6BVdNTrBSp4UWiLX
zOSMO41}UhnzK>Q&kVDJjT~slAJSOg)n;D}wR=HBS5nP>ASwJ15oPCFVNFAe6b%%c_
z1GD$^^T>#ta2O3gYRI?@M_ac;Vse5+{|ixg^dao~4we-q<P6%+{ly!`HgB*~IIB8<
zFMtRdio^38WTW2c+#cgO*FrEssv6jC)fn-v=yj&gCrv(M<)6lgh!`BBP9BeRV8PnI
zMeUw65_GyjuF7#rD@SopD?MaEwwv-%VBWyMHosC(BW!*ymZp}55Web+SSD|ExXyXO
zg06d<xlEcqp0KIxh;y!OWt|p`TyCWuQ-G4OcC%kO?~3qS*Sf{G@Y3YBW25UTtz+zE
zwl8-N4Wzum7<1c4z_`BZrFYNzy`^@WJ!YI_s(nL2@J3<v#4N@EYfZWSj~T|~Tl+3c
z{~bv&OozzaCllTw^vg`dn64o;KyW0d?{IB3KFdiq;qiuFlf~nJg)MqJKpFt@p28(c
zTjeGqs#jKy0CPS<%x+zta2;r17|TIl95HvKGpXM_PPN8Nlv@qAPr4r9*<5MiAiE?=
z`_(}#)$uK7*ZJP(d)H2O{15=?J*?sm1DH0`&1P*0IbVw3J(=?F=L6~IKKJ&&|7Zyj
zaS=GwzT(~FFO?|U{~96wci}5-Z~R{_(f{LgPg2!U_!7+iEz+S*R9El8+fr0|g3_De
zinZWOuVDNYu<O&rcY!HmJ}-|L?l(LF&m<TYjyz=Umv}o-b361_V+lBV$oxW0WS*XS
z|GPb;`^~|hIlz6@?r_r+45EOhNZ~hw#(-9X<_K|IjI0~v?RSzX+Wh_Ov4SSdbPzFI
z_vKpirRDXY4!G2PbbkERlrh?+OSL1OC~B3EtB(t-wPjL+S4W0jq@zTte;8^T*L8H6
z%Fo7tbLSpY9Op~KZJR|3j@<!>4{JcVr$;-06-Uw6EiA}VBz*FaE;v*^|J{8kJdt2G
zBb#^<;o=ikzCoV2V~HQ0XapQV3aL${BY1SfK;E{w{Y!jXD8$jU4o#|hek`Ef%UgE7
zH$CWLnq=g}bw;Us$a_2dZ+}7!9U4)ENP~3~JN}FkrLCP+LFAU7_4socrP2bzC)r#I
zdz@anP3PC6>2PmdC<X)}<*sMyug!kiC2YoQl^f<znFSd#AFPnQZVHwO#PaZ5UNE*>
zz^}^@8!x}m;xZDGv$WMYqT<B}Rx{i>#kqUY#1a9*<38?m%|CvFxlI}0=rCPxA5<_b
zWP8b~6_&^}AHLZYzQI=9;Vemb);stgIj(`@8>IuLR~REwgY8Ut3%`qm0<EWB&uHK{
zaIbeYhi}RoksaWMYcA39-!g8qjC8q05V0FwaWrJT2{lIR943k3=Ft>1Z)s?zkkJiL
zl}$dSAMq}5K`K#M2y*YT1OF)Y_Id46TVgUywOmR!SVz_yG^*VkQq=LDYr=3;SU1t3
zB6I#{&>g3gE-&^ax+Nz2zj;fg>?~a@jchDE&7|xcTwVUVgc#I@byr=)_^Z&w=iy-l
zOTrw1jY&dI9vB9L_I2S!mYCeXrtLRVg2bI6t9@n~aqXgZVacMlwQYH$_Ib!=MF|1w
ze3@QBrR`-^<>vF+q+Qce*~7*=fRZf%mM!;jKBo1$>wOA%{W|^CSiC%(#|R)9(&$y>
zBDz_(KtEeq4Eo?+4U??$6KBMX9hua<w!r7aLgXym5DOOWlHezIhC&jexU2S)duw+|
zm^q6YO7^qU0I_2%v3t!6!luWThh_e2U3|miy%o%K5Qwxzk=9LpqskJ!Cj(}%q!`|=
z_Y&bP$dFMzc4UnU*gubdPeb(v-%gxthUj9rAwcAKsZ#wAKwNZJ=bV<(>8{>|cGnkS
z^QC_EC71H8*rkd$#h!-!Q0>>68+*THd%Zl4|BD6Iy-*{KBot;adbCXOg6OLgu)T}p
zk99D9P0>pP@wa4G;idk-Ps!>vvd4hq1JREOaQN?sdwA^jk|SYm#U#?BXW!q=@hA7S
zi!FUNRRwBoGsub&tD;ivh9t!qi|5p!QCsyM8={kIPLT|dU3Y1!Pl#VRO5K5%O%3s!
zc`z&?#R?2=m*D*TF&k;f_SNG9UT^Fw+YXyRWkoOR$C4Sqnwa~CQDs#Pj*`zWb2Yf;
zS(Ei%@-0`On~(Y}eb}isc>AR%PxyxbkjqG3y)~#bPH-NM0-l&YJB&AAsbkw5iY%D`
z2L2<VhGO2^8)(>E9EVr#Mr<m%2dhx_bBvgNM2=UuSsB35%GI<N9+$EGO=SHE`yC->
z8|J~Yjg*9LMyK1txLgYz(B^Bx&-8FJzaQ(ajSG@YIg|bg2~r$L(@?_%WwA&fjUkJJ
z1ySHE<xa1ed%jJEp+v8cBnW9oOh+)-Wpm^xUQGarjb8;SQ4&(dlTp;D<#tO_;~!cl
z;bc}KeNDR2MgFK$MsX{t3S|G4`51%Xu*7hjtGo@Djti3VMUt^x&>o+r9N{L|2h&%}
z*=7Zo?c#q|)p>CR?{*z+79XTq)==h%j{Hd>VpL2aKFp6%N@K!|t$=4erw&*YC8$X+
z^opT7;I>PdDAYsgZ*~hrQN@J)kg+9Zg8#^HF7KfO`-kGLw!?vh@9alz`a+ro`@1t0
z$7tV>t+{n{k<)XMlI;RsOBlAG;IuX?ZQ!F?$_&i0ZW-TnCe#atPToZ@lLn^^Dj_Ym
zX2VGNcsK{cZA5GTjDE<K!XnK%p8N!1RXE|haR|kocyLU#%vg<yMkLC~?YM(hx>$^p
zDO`*w@-@@w*_3S7cv&q8H_+6zv*#Ra7{VNqbn6oG5O$0T-A$|WI~nT_*6^ZkSjq9(
zH!h5rDz(g+%sR32I_O`53G+l$$#)IX`SQ3^>~fUwM&W>%Xe1Xn+L_YW2p5|{`Dl+U
zh*lTcWDsQr>YOWWp;S-;+S~bux?2`|d32|Nc`XTV+b$ZrRxu5GQhn%Gfh||;lrEo|
zBNI)&0FcN@AJOJpuoqo%FPpK1np_x_qe3YHc~+62vqG5>9$Xa8kFv|m(C|(cseDl#
zcz7oZJu(+u(iMsw+vY95GmuXx-%IV}M>iK6@{fkNmgR|cWC2)b&7YswzndB4eW0jT
zsvt5@PDl=qr+**cChNBa4gkI<eOJ>`Uu&n6SX9&AmCmv%mFFbPO0FSu?<ziTNSxX+
zt(a%!RVhAn!OXQYeuvaR<GHATbt(l0%hQdPs|Zxio!V$u?h{v`xJ1hzD+kJ3mnaoe
zS|zJmLpnMNxGrEYh_}RmOBG{UEm{&(E|-EhnR(eLD6-Z{MT+IuM$&#3%Pmk?uwfye
z%9PAwu9eMmu1)bd*!lOZiWL)}P9M)hIw@lTAa%7rVA>>$vl?WEp&E*@7iT+%AH?=x
zR7GHke<Wu~CdIK>3>~3w;W;VLTHXlg+YV-kSPAzwF08yUnhj;V|9UE{#btcvpHy23
zr?6_hB{x5FG-jKp92L6~eQte`WmunIi#u3Xsn0CKru1Hrbk<T^%+sA_xcf6V@Z^eT
zRG&2t8I1>+Qd~HbE#W^_#JIQafMGoJy@L{9V>Gf6Q#^oA>tOl8SUzU9k7rM=cLNb4
za9>Bh%0Qo8jLj(`@4~ucd{pPvW}JT(6zf=e_u3+-nL3Yfs8t`dZ10j_HGTUhb#xF1
z8R~E}g#8WVplQhfvIZ3fW~Ds<esEW9RfMK<2f#oNFS>e@@Km0NPPw5DWtfOBnnk4}
zl#)*ACJ2mRlqR4K2=)sZ0&7B<MvR{FJ?o74#6SoOHE9(<sU~nw+U~DLhdTVyqmyTZ
zL@yb2uJ+zlSaVR^cac<3U*pAtxfes94SO1?k_!7&4~HGI)EWcIS_~?;axUt1820i=
zaRg~JkY!l(zDSNB1IS@-Z)0b-)|hMLW!_&jc^Z0oyHZFZ&TIko@>@NlH?~%aL_LmW
zzoKku-v=mWV;-iMv+8IPHJYiSt8NTmDS4|mw-|oH)_3W>rOwEo^NFL#REqaiax*`Q
z?dJh)4CNj|gb(vqMuoa;4N?=j$Z^ox`)Ez6U2DNRTg82f*np*IG~p&s3yFn5q&2N`
zDgYw3ulY2M+tct=SX6r@t5M0A$u(Z<lL<W|Jk?+~>o2q4?7Xgz)(<zR^3}MJSmDK&
zXf>VzTjf&%{&gww$Neg4>PgvJ2fDQ0zI-;(S7CV2^lW=X<Q4qAlhSZmxX`Z3w%AiF
zpXQwfV@+%Y8*8#j?h14~$RB=J1qlxaby}d-oi8w*R<^FhTC0to<s2mtGCukvuk*+-
zg?>vJJT3H0B^o?}vRk7Gp4DGS<?n=spPyEoKflEHI$4{@O(CkqeWVh8HMB~!Y~I`T
zstx`)lS|)@jAh-jB%D(}fX?_WAQUQVZwiMrGdUNA@Ew|0H4nq~8w}N`2={Zu%d)>b
z;p&J0vQT(V@S?=e(AI=dxd=%lMlr1BHj&?xD}B?(HiMi+@e_z26A31ZN(YMwBz~&D
ziv-<we|4fN@BT361AZ%W6J#{(#d7NYor6Ww%V!esT+`<5J5?Q?_uDV{gKjSeJHT4R
zRm<_w7&m}3D4zO3DJubeT0F77z@tLqtkUJc5Q|aW^LY3n*#r*Z>X1U~&nP_4a6m`O
zN`O>{4PI$h2jrqet_E`Mf{p`Bf&{bWFuSZ^0L>PdTknsersbhY{9kF!4iNJ|eBsvS
zk|90p!3PpmQ5F%PIa0q|3u4R?r2-vOL_$ZOo+8j`wSrn+>&huIpSzy{{nll<Q<FPj
zm5*?!l&r+G)p_hloQ3I$C*oBp69@sH9SaWcanA(ALe7`A(qi(8gi**_D+m1ngtpIA
z67=qoEO^RnP}ng<@UFU-tvbtewCSWkh;R!;6kd@w3r4Zs)m+Zh_J`JNOtR?=iNkT^
zQ%@yMA0p+CU*h&^*{s5a&K@!^wM6D=YVBh*irlmfifkz_()a{mwZ!6<1Y<P^FO5<$
zb-NhA)PF@f-FO`@f>5H!V>Nj7v%_}v*dSjhm2bzr0DAoZecdtscSjB=N0^j->Z+dl
z7F4Dk+Kz$zVTa#$4zX~K45uy8M|+-S{fG@<Tys_%qKGY8!UyWIfG)9$Nl{p5jhZQa
z@lT}+(@D&Of0Q-hB&{h7XM>kEVnPtsUE#L1yT+@L7}bV|NY(H%rC`EMwLczJ#~MCa
zFDy*(LpIpZ5zLsP!lKB|dcHle=)#wR%$ssF%$PB`qnE}t%gHVo=r1cjD$%Nz6)7EB
zdoU=59T*}Yw<sM7d)Bjr{mUV$j{GW4)mk8sI-)=xGBLMN@bi+wVAqncA%QI+mAi(-
z3FfMO1{b*E3Z0@av`^2gTY1{BQHyZc_%O%rdXb@yj7HdqG>VxSzxQyfhkndrwl^BF
zAF=pmU>i-x{PB=z)Nx?1Nc!f4CF;0^(!ihidq|h_TL%o7o5RLdc-jlh(GDT|u6{_L
zPi8EkViiJNnw+d715;@TFR*N%lT)u1rp%3Ct5i81bnX~9Ce!33+jS;2j9ybD*a6Q~
z2VQ*B>{eeNsd>)X5h_fk>BhG;-cc14iEr8LF#QUI_e)?b6W?Ot6h(8->G^*cd&eeC
zqbN%|ot3s#X+3GX(zb2e&Z@L+JZamuZJU+0J=N1Q5pQ?I8$F-yKd{d^_geefYrjMC
zBkMnDL)xLe<l=IHbOw|U?(f7Pm1Vg>PqebcmmSk&ay7^apCd2x1w4kT>JiDVOr#wT
zMBLNs5q(|v{8v>n*U4lN|4%z_|D$aGr8<JxJDD>WIv5&Tm@-%x8@d?U*qbxh8ag<c
znz$O9GAO&)JDEEDhj9K+K~ki=VYl!LnJ<%5&KgzA3kG4uL4GqbZ_{!KT8mgov{C72
zC$Vj!ZF{n{c=G`GPT#*}5<!FDM7`p~W-D^aO6o!+N@ix}#}`>#9bb>{Bk~{>9yW$x
zk%^<mlIf<VYDtbsZ8;->ylVFzql^R*znogg0~Fr2JKiwCH_WK)-t@2?8LS*z7@Wd>
zNA;aS`pHAYqZ134IgScAl@Lj;tnp3PFdcq=%BF^@Fr%fmZk}^bQN`)0+fM8?i(c}O
zXikR26WvsMOm)T329Q}-OUsMl!FPJSRep~}EmSvQN6Gg5liaxTX!dX7-XtCq&pLU3
zZ#Kx#DC;bMWYH(TP=!18pmjr^J>GwDLfaBLu3U4AcVdOf_0W}85QXJlUB0t+EMX}6
za(?MFr4%ETF_)*y<7g|YLSMp1Ml@Pv$JG}uTUwR(Z=tETGMYHNp+@fQ6dj$dwQI`u
z5H$|bmYJmEB6Q{>H+GRrz$=Nlz*6lgf;Oa4?*=eCk5AIF1Y3rj^;k*TyBAJOZ|7Nv
zla<Oz?pU6g(+Lb=C08wLwF=7r27^yzbcDg2R@BK=2MWf2E$WO6O1`fR&XD`*c?UD>
zk*q;#`4)Fdb{qYMZoq;bU6lqmxjX`e@34W7YnW&Qove8aVqUWz1oZ#|mk%Fd$r^D!
zdkA=1b|5$(gj)@p88p?I)7KSsHsn^iVCGiptmjsmgeNG&aZ>S2ej9`*xPwh^=pnv8
zN((7VWN_^e(ur#{7AZ*h!%?cm#`0)UKnws@p_ystC`44mz+}Q0iY1hwjK!d>$&x#<
zVAw<j?vw=B7X>&U>>`!zZnP$Xv5)kTVEAA?&p)t?JUYWTyM*|ik>HqC;3@}J&Ho1Z
zuf>gsTmDPwUvUTgGlrP|$KsZ>`v;WS8QQ42SlawwU#Ln&S03#j_P3B?r;SA&_9HB!
z{*JspU_6p2ev#eI0@Sh(Iy+=b(%o>)vRHdj|F9tg+ZbNp50PnSLmH;6gv`&iuIH?^
zbnmOlt_I2;KYVbF;RUc^N0wM#in|~?ORtSy0$GZtwu&h}aAl}soNcYgXTgg%w(a^t
zE3M8UU40Gy=RzAzKL@hPW`%5x=ELo7hl8J1Eu)gAwq%>9cc`(V%H^@}WxAon&zlH=
zRAKteh33a@*v#aoFd_a{$l;IEd)W#I-B|OZ3aahAn|m~~A2SA0J_c!}SNEiLp}bb>
z=k?o;pHe@CYATadX0YGRncR`6?oALb<MR|!363J9a*g4+6#*)P1DBjXuw1DU7{u+U
zHUt+d!&g(Y{c*sZDF_Yv1~Jko2#w}~qQ&74jw>=X<`+_$JflQIAh~(pA8u@R{yCba
z3;c(4<ef3J7Y*qe((ne1Kq}O7^gB20Mw|$~x`jm3wD0dUsBA`+>1labi*vB`63E7H
z>RewxP-nh0zI{XS;}&+F7VR#4P#Rr7=ZP{d1oM)~o4<GcxJsU&1d{X4i$SOBXB4h_
zOJy7uw2#BfZsEO=aHklQr*;@8)ph%&SJ=^U!UEL^L_ggESc!A*2rgdC_h^;$9}>Sp
zWXulGn5|)^P%qCF11*}xokgO9{KP^YLL9+;v4_x$$7W8v<@_KkJY@N!Nls1CmcZc?
zfF-I0hoKJ97cy8?E{biDA*Td_S3v*s(ob8eyC1%?@$E4web{U7W8>(iqLpa{J!62s
z`q7_I|FuH38#Qf){#ED(6bK0W|5%~_k%aOeSFoYEsf3}OiOv6oQ-LbB|Ed%@+ZIlo
zb~JK4GB?1!F&AL;Vif<6PR)R|l11xDv$;+=PdLA9Ygq~FkrIfv*hjh%$2oqIqAoHz
zO6X`y2YUYX{r&m%g$A;`Yl#SDuofWBCDCULrv}KytVG4$MDCu=gqVL7O8!+$Mj&U<
z2=M8~VzbieGG{{~M>Dl#sTofSdre_1I42>iRZAH!0vNaf7uu&-?+c~z01BJoHgfLL
zGU|;glSdts?!46z5N5WgL_au`K8lD$-jXZ36q$FW;9}zNURly6<C$|^=MEnd#ld4=
z7lUf2ggZ3&O=QJL>3H8VAcr`kZA4r77k<d)x>=S+2Z>^&sx_i^Yx6R!u_7L?uU&}0
z`EW1LuV}|tOOtmq(iO&r%I-Oc8ZhX${_Kw1h(~=3tCzEGj~wB<t*vdt%CRLJ?4J#w
z1O~Hvx{0PNQI4T$ob@O`h#}5^MY}cm_a3grbHU0Dn|&&o4o^07#h_1Px&N5#jP#+y
z?W7U%FV*g5XrdOy_U3OAXcB~gdspapLLPkvc<az;SuIWE4vFoBE9R|GJ=TU(lGu4N
z!|^DwX+-7X*kLq(7&D}q=vtIW*4@MoorTAuAWg)8gGKtb55TIM6xwu??z77RcQ%q+
zs|O7Fkp0cEMw+LPG!7r>1*2-k3?6^iAb=T{L~qp)IN>#Df4|SNx0)gDXZW6mXk9K;
zcgeN>Td`A}q4@`1ug#-x|C1+Zk$DH;gibBUUF!mWi1$_aGjvCgv=d4Fh9`^aCjsav
zaw}{B6%I@L!Kl2;?aD6q9Y@^EPhgN^nox9<<1^+CYxl5f`+(|HYlb``n)+XRT(e0o
z|4hb6#J}sHLkZecZMLl1S9@}Bj@v=)AnpiVp=E<J;2x{v?_6F|#8Y2?7DJDWC4OIy
zcUgjE$Rw?Uni`_qd1MC!%;`&Q{&!Emxg`3T5&;AR?dLyq`+qzb{}<c-&%cr>O?Lyl
zBaH7Zji<3Ya*An{Q3cG^TLp>%_K?Bwy1>g{7Z5@}9sv3m(k4JIppp=!i@X#yI`?T|
zAejIDAcRn^t;K1sH$(e#c4N|4w|qUxSj0i$_XE;-xA%_swfB41^~d3FLT)gFCLOeX
zOnj=5qSl>Wa6uj0-2>vJeL-+iV*Ej3@B-qb17h&diMi;|K#xK&@tacr0zqE0-CN}1
z12iap%Uxwbd^kgj>>qmzFHu^2WokL972twCa(n_cKlMv{m0ye?yMq|icWGbB-(EBP
zYoKqVVF7&{2tKr7_7z9&LR5Y3OEb^#J_11)oCdql#EW}>z`kn1<PXG&#~+O!-x87i
zB65OnoIm<|8H6<|YW;%s)pt2wY$5$ZcS3KVKbXP<s1fC<1_eTIus+zrdLVC~k-z+Z
zhupw_6>)xPGkG_IefK$UBHySE#!(AW=Yf(LNLc>JENf2+{(*$6WG68i2b=GvwQ_Cm
ze(>2$$;g8Wvtb>rJyr-rPjazq(@<DC^#Y$W@p)e7o0D@l=zYq7FrAX?zts*?)@{&5
zws3v76*MhLtnE-1_HACVejKuu#c$Z(pqo*=#xdw6avAN`VrdSkTFoUOh|=uFaEHzp
zUamENE-`Xz9EmC79od;Vpn<aKA&q~i5{Y`CEw`qS=iZWx>9Un7y?<|-Rfjc^V61VD
zZJLP~t{VKc*x){LnMQP3|0&p#Q`p~tdHmC*gRgAWz{`8VmC1Y6eG}qVDkK41YUv=2
zultw`s#R4#=(o5LQFOkAH(hMRQN30|;0{Xc2DqA!FTjj4u}wnR+lRKfWde8k$)u5`
z7iVcPdDCmF%PoHdM?%AIya4Q6-s~?O^>5B2d$)IP)Q+v<3?r?ib(o!vnd9OIXEj{v
zBc5BTA&ug`!OVRC+T`Tg#f|OEoh}BG^46wvlBt|1KrG9gQrS@-nUHcXB&lFuo%r$D
zRa<zmeN(+yvPO6y<=DPupBiH!`87Y$%*`+Ciii+yq1Z@^J+@`WLjrECdZHwojDQx6
zHiEdASQ&Bws!HVdCSjz0U*PL><D0HKXU3$BxV9y?*LdCjSg~@w9ZGTFG(Qiw$-7#@
zRYSq0kLj*9-&qyg)lHg_3KK^i&-yr#`Ol+MWczldrO<J{^wvgIs8#?QEv3?+dg~l7
ztk&WvBXuP{B?ZMCYtK(2DJAe2gC!CCW^&tWqZwHQ+5-<^HHyn(+D!CP#q8iZiJ_Q{
zZ!+e;UJ;6T3s4wY&R#JFqN*WSS!`UXwX;ZC+iLGxW<fP)d9}FfB`0xz*CkP1EM(nz
zWE7IIIw&OFygppbGtDH5h|RH?fzAQMsv(mG7^7;lg~Tif>Ex{?X|XZKKN=3c0nt)V
zt-j^tKp88H$a2+TmUv4H<%b8637#;Lw<lM>!~|PI`g(yAu8vO&d%G28Bg>2ZGQ}i@
zf2q>l-7CW)tS0QCxPrCmFo}c$LVR}Pk!!XwG^@%Zu%?0Km7ALuiPT+Y&zY+sm&KEP
za)J-&%KFJQHbu(=@zl=bfV4W6k|6ujje$-BkZG19ne-VaM<4sZ^I=<B!*MVjQVo}c
z@O}{_FG%Z=#&FItiT+2@vBjI(bH#Ltov$$5Jd$@C2FZZ14xR+H!oIlRVn9Mz?h`r`
z(lmiBrtB)w?beS>LtbV(i}LC*G+vfW2jtsJ{Jxg5L{dsTLkMTN*?vd`8B7*`SxpjY
zSxt%wSuW|6dI`2Pr)Dr!X#~7NYTCl(IBw;$U@Lhx@(61gP3nr1G?M5{`26BZwGDIh
z?CCBz8BNj(8J()M%4AoYT}p{`85{e?WUKYGS2|+e>}kh>t|)Wm>3C<&SQ#$)X%3W;
zIO^#7q@wX83QP7RWICt3T<iP~s#5<?O)fdI1Y)f8dOddRd8=_TOO`_;<@KV0xT#_t
z5}*ve>N<({N0^zVRH{ouL`J<ReUT-0y>$Hu#~`p9Dma_)7?)L4cpk@~iS3Aa%}OGc
zx~qO_Fxn%XdL!AdLAFh&n$a|rHS>Zk67rss1{2`ewpR+PdDxm^EOez(m-57Vxlu<R
z+G)67zO`-jdOE&U?7SIQA+tuV-rz5Hr4^4QbUJt}!Nj$0+J;qK=IKAqGx##s_Nx>P
z303A**+Q+7p=1FSVuE6!8dk^Q&eF(;&iMyKg*;6Q+eN8#Rx%n2OUyehwASIIk#875
zNkK=6yRZ8>g`5u{>okC_wbbhaK4$~XrD3!~DZ0aWns1J9L@4ypi{X9!b?M+;CVp9&
zg>VpRJ@tz3?Q5Wwu5-fK&BcYYk}6*svCw_iIj4r(-|nd);^#S6&hXl3?|DN)`ozlQ
zSw6=&v$e;noWj_fQ5Hq(Uiw*t_lF(U!&cqDsY0N%=Yn&R{YbU<!br?a+YRKSZS%+z
zTnmiV_=IFMnoE5;Cl3<ev6D5t)|eduwSSP`VFmC}49B!{(CqVvQ@rCCE4{XIws_g%
z1F?qkji<3wOX6K!hd@(yCZ%}=p1NbQScSw{)WqTZv{8Y^zfB|<=1h4uukH+wOJb6l
zZpnA@f}uuGa^s(eO^q71k!`}l7vAOB_62FYfll6-OAB=5&SKAl@jyP;c`u-E0BjPz
zOGv^T;g?%`O7-=4%O$R`;Awh$e)m+~bl+derNkjwJZ&7IE@qS^X8WF3bU8h>U$T<Z
zJi1zlB1twCz{NnX)Z|(X*X8GD@2nq?c#)6>@#pds6sXM^Mz%d8(U(o1@TvQRV{dkq
zx5cC;UO6=6>DvdF&PH61O`Ok0W_Z#lh|DT6!2DFjmX)XBA@?1!$M>9lCX2^s^J(i$
z#yrX~MSZr!@+Tl)+amE-{=ZDpe;pkHby$G|xtHid=66dLUn~<^<&V42n6rHRNIy_&
z9EG<jDf!fcO*Jd;Y?>Em*bURnqT=MwQzxEf!Blmu)7Jz33}f>4I><i;+3kCd7>7jH
zML{~#OSt@=phBk+fpOqEGJO~y2)8hmVj#yx(2J0gq<c~qhYk4ZhUy`GK3(7tS0hR9
z4}uZhGQyd!BOS81$|;H3;Q^DsBvo?{QIcYED;v}fsiIIIV)K0<@;Z2~Lp9l&+|U=K
z9I%#M)PQrM61un!*bDB9ON1gz1(X4)n^iMuv5=*+Gu$d?$6_}cblRlFx9)t!M&NZ?
zb#dNoCnSF<77L;&I?^~VgWQno(<`KFF@TG0+8g-<P?j^j_Xdg$!Mr6%Ox0>e6mNzL
zPLFBAt9JeC4Yjhk?75dtuEQ~b9~B}7sh}krz1b587eHa;YYUvjt{4*9-&>y8Ebb~(
z++l0FO{8fHy1(I%Tpvl(yt(uTqWv9qvHz}67Y3%OyHarUgMLLB_(7Qq8e6tLU^j<K
zi`OYIMu-Ls*E_6HdE~T#(^(DS%_{;dS<lK-Xv*7bnIcSKn{|5BfXTtxz~Jr2&3NwY
ze0-wW;jLc-e;hH5qEwm3%@kr8r<%iP7z*aG7#*}M|G0&SW>Lt@hjGj^*5tw1my~VG
zp;43C7i~MXlldEFc=JrT)A5F2*v2zuYmx5>e;%K*7uLp#RS!;i@K5RX-`n-N>Ogv|
z(_f4{!f#{6nX%W+`{+w_pLSt6%C{MTg3XZF><&Tc-Pr?<t{c*<cZ;CxJVNF`T-(Un
zoF-Ywm|#3Vkjt-o<AqBt0X$I{tiNpwP}mU*VkX`k)_&lMq0k8$GvfPzwN&NSsj;V=
zN2`)*5YP(*u|@Z37P;qsGA<{W=^9hva|bz#Inrlp7@!}^_7P|043v@R+(P_aDkm++
zMarkfpWQ^v^Mt^%aG*eB4xOyBQoL2jj)4|MCNttxaLo(Qb@_STjtQh*nI9!IUN=9y
zGS}+_LGWN(-ivnW%S=PyXo%Vr8rYG#-;T+=v5R=-=M6!!YSBe{Brd~Y7@<8$A-lgy
z_P}VX8aN*tGCL~m{Q>;c%4S9*8aNL#ze(C?`=%i{i#6YR=iKg97OhDtC^=b@P0AOk
zu^Y~$ZqwQdXffHu+tYjd&_)^0a<G01+VJSlt(I2KCM}5bZ^3Qd>Lq~MHru^4+Wq&n
z+|_mAyTMn>t3(c7yk34}`lY=&CUr|lfORc90;zLW6wv4dnP}&$>&wX)scI)|XxNoX
ze!_2Co5Jd)b}EH?|EYC4UOAtvSw!0)rEZo)$S?_g64A&gk5=8<qL8Ad$}(MrHzbBw
zi4|k8z_hqnAJDiJJQVF;{xqzlw%||}(Tb=l&vC850PQ$d08KT8&+UZrS^{^X=|Xxk
z{4W7&n(8^m;h7jfvE{@o)4<oyE0D2d&-M3=L_;d-b@H*J5sFR|sNLw7uTIn-O6^NM
zJtFQxNb4S)+<{4)>nq6MqtX^S-R|wL))NIG_4%`lZ+SVzq+Q7ZiW@2K95f9Y)@wnF
zxktR?NN=;mvE|O5FfX-!T7P&6l^3$562E7_-b7jR_4j{+sQiWHr4jzQ5K71(Aj1En
z;QB973;%!N8Aa-v>gfMgHNZl7VdMHc3Py#OmX5OHhT%nw{|qox)MOo&@bZet%PaAo
zUpPqc-Ff~bIwWVHI7XfnzWXcerz|IDr^+$F_^_KBD(vd|Sat39T%p}!_4Rr^(*wdA
znM1l7J%Mu3pZufRh&g~-Celodb!BkXb<SIml|$q{pRt?Tiy{248J(RWdq8SlI0cG-
zj0rYx09WDQL?<>oI$&|ObBJ+LtI&|TmUMI%0}@gA=wwhd<fQbn&`8s{+MSr)szhn?
z)VP%2RwHC%hH;BRz#2z3=eW+3&T=DNLu-PQH+{kLA^{k-kuq`J?n{1YgvP~@=zQSD
zZQDxUN0e>&W9X91yp)Iyz@IHm*~(HxE<=BMlEGEL72@#>Eqv7(Z_3#*99rF$VOavZ
z3V+8%XWlOQ1tA!{8P<xvWjvwarUUN^LpO2n0DpNDI*#1tpni<AQd?CC7Lg|=y&A()
zWQv93#ZEySHH{|2eNY{TGEcB}K}M1%Etb9F6?t!>_Q01NJ9Gdg%sH{86Ov?fLZvN>
z@+&&)BpybZYxI|3OrF*Jl8%<W>tOz4M5Y$|gk;0He0ESbuy@8(y9jTLygn{R=Bgq4
zy;`<U;a7I2Qbd@Y)6|_S%nV)&wR0s`NFZq1zI7C{6FvLI21?r5dgNw?3y^q2GV-%F
zcWc?G*sREi)k1^1-cZEJyD!uyCcLU56RL$O!?=jIxUIrecVln<61z(_qNO#9@(#E^
zk2TU5wdo6Mr;MTK5ZccryQ-&KYLj>-yUrzkEF7|0SQWeKw-vxJg>zU)W~-O2QU^^(
zbG4rxpsv~(vVzf>myf1PW0cPoP(ZUis7;eRNr=&9bitLSGRL4dlPli0L9^Z00lTey
z%g?WHOUzF)Ov67+3IBdqv22SQZl}m>Gghq~u?b{Tg5_7e#o<@Kh3r<j#ppI$#m%jZ
zD7l3n*d~q+kZo>ti>%h<=Fm>qJfxOQYm`uc+$nv*++oV{%(p7q^~Mm`71tV#c9a6G
z95h_5ix2m~hxN<<Y!Cl1JMqop)hgIu>@?oFm3oaqcZV*`#;h|7Ya-Zo*r;Nt5{H|D
z%mZ-@ImnPs_erKK(H$^ZE#t`w(9)mBHsjETlqQ1kH}w!+TY;J1RqRqx$fX#sX(%eI
z;@Ut=2^F`o*b)h5R^k#j;~~iNr=>Vw!<BYw5TFVcU23Fj6WQKhOo-j{8Nx?`We4F4
z6EQHY()NEwdr*rD{F6>jz*`=-oH$U%w&a5+iK#H7Jpq#xLBBVb&{P%rLuBhpwY1O2
zKS9TW_s5^|SH!Kx1|QWtTCTv3zkDHy<iYD2prGptJ{^S{n*>wDxR;=;V&GOGL6$Tj
zIP)%dB8OHINf?LV!EtwQy9|1Bk59ieACc%>T(@PPUB%?fzZN4Ea;5<)1`J)%xd~q&
zMO_8=NVV^aRlWR{YQ#0KODBDPXH6bv7DJ%Fo)Gtu1;h355EET_9)(%w1;1UsUJ;>A
zspA%($W>eb1x_$|Mhqj0k!bT1h%@ZhqT~!)LF!=y8$UYAvENw@bExq$<*bR`H@z;-
z^zT=fnD6dQ59ZhO0~+ds9GH%Y_kHTfp7Ka8wxb_PsfYctYsDx2%5q>3y|?F3&0%Z<
zrNbKC0eNmq1DKYM>2cM$@qXV`e`Q&($s?5gwngT|D;n7Crw?6m?~N^WmLw5eID|oU
zg~3sD5XzaZtLNO+PYQnz!B|rUS-mlLoE64IyYlv8hL|qKy3-XHMuFM#Vpt*ai6lOg
z<LdS=hnAk&AkrCXA2T<92k;&A<WaXboP%c2?je+wl#7(Kon5~lw#VcX{Pf!AlBI`c
zq|aFp(c`5xmG~?zd7=nrl}^FUh|9gKSZE=uf-Gr+<BSx|01DyX2i5)JW<c!+`%Ggm
zg7`#NLW6Ngani_TSI$O64&=-mrWOyfXz=tm`;00l&4Nqv#7OcKYM$*mQD)>VG&n2|
zklq7>97qx=SVWs>l&2>rUs1cz8dmNpIPI=vugDa!;H6lx!AF~a3epdb=^MIrp8Ec8
zQ~wWmQy{<py*6$CUK_^$@wNHi2;~1EcK_4jt5Vz0MmNR&MgYK929l6OWaOvs*SAKv
zq2|N0G0BA+6%vGOfkLIG+qz*UPrKF6*Vh;5E(K$49o`3N-|_NoB`tj~*gm~?r|X)f
ziVp1?_Pioqzk4I?ynCB}y&b<XfUMs{N0?y4QVbac*Acp5C@tx9QbCEsTVmK@FVzl_
zkcLn*Wx*PA$yIQo4KvGBct{RS7%uK%)P0v@>!A&t8&(eE(M*?nutbS<k}o@XXb<tw
zY^yrT3EHkZ$nbHQa9S=j$GBZ9=i)0VESPFrs<&(s^QAM<?0!<iHU?dtk$SD4EKnjq
zy7HmDB@s%WEo<1!y2@Br>I$-vCv^YexNa7+g{<OhX2D!g_VU>biynbVY8)|2^crVE
zO>afvSuN@iciJB;!)HsZ-lO_a;xfXf%biv{l06n>O<~MuwvGV>J;fyL&Vq<=Ma_NH
z8a)RpB<&5n?2j`pfnR5~C?)>G8n=VxH$))pZfV`_>G$H^tqk9J$)4?|T^8j%N_g9V
zc2<w}V5k{uiQ}6-hB6S}hURWG;#t6booxM^#WA&-e!lF6Kadig1r-(-$sDkf#Tqi%
zC`tLGm2!FZMaK>yGj$qv=$4jp>PB<&{X3CoFski<LRK6LOKB>%VnqJwj5=L%UTw&m
zjDkhLto0psRbi*I3Y~}*mN30Q#P76@WZ9<!AM0L78VlsYLNBR%RD?~Jb2qUf<lY~o
z=gdhE0%w`Y-dVA;ToP+tV@}6L$YV)Cqt#rgZQr+0!v|#;vKF4H_hJch4&A|fjC#Z+
z`YRrWbeeX17mxiitz{|4Q4_yYQ#dDS_NZC5*R=(;K%pPIXz9<CCCgAfk!<}50W3iF
z6_E&SS#)IMH@97(NwZ4l3|l-ZSIsh(H#u!{FSX*awLLKgqi5P^NWnh17EU9J+@^sk
z<LN{o?<#%nk5iWRjf{*DOAIXZQt%iqa_@p=Tg{M#<i!Qc_`80*1+->h#L!S4m(?&i
zi08<x_+x7wM<OEvt)0zN-@2+#VXoD85-^LT0NsTiEb4-QDY4kw%vmm{PyDJA++sD*
z4S{Fw-<T>634`(snJ&V!VPr^^QJ4YTntpj9>tL<0FiW$gg`mp72v|X$3;7SY94d_l
z2PW!O6)iR@G6Q~$0dj=E7ny<M*3vyV!&b+>1cll<<n%u2!#`2IA4&r-K0|NRCS*Gk
z&OiqB(nl`qz&p}`tfvzl?M>1(WT%9!&)0GFSyoCaxUv~Hq*WZ+cr3+Rww)JueNCEw
zF`eJiOz}2T0Zy)ds`zltu?o&DoEtd1*0oH4MWi6P12FD=8`GPqleL6*jN3vW=H#O<
z7yb!O#qmu<hv=U6#E9~2^GhSmsw-C8pqSrc^|3v;N~K_;j{W|z8P3&_Ii2RPC-7&+
zCTa2^3(1N(WChg@&2#g;c(<e8z_poE3S~ztcYsvT%c5Bxytr0=m1ffCPc}E_%0hI;
zKkr;(yj(lwX)qlTSul~NP82pt(r`#O)ByZkJ+2&85p_QyPo_6#)UL6_u>$p@xeA{L
z=%X*;?(G58V1&`w1N*bc*xP0a%shz+1eGOK9l=slsO0z)_(h3xcs>jGtzT1s^3aAK
z`hudy7EsdFN)<Y94I!g{1b>UCFF95QguA9004R%MJNV#EdP(O~*-xuT%(Xw^8zt>0
zj${r=g5;)SiCxg774!BLF=CIto`v>?WwU2^sP5V2Mx9OboWXV-U0$ifZmF}%!al;r
z_W?Z2U{h!}qzbh)h4osMyt+!B0yS>k^=g$q%|XmJ5QuN%z$DD{im03V#tP5N+D$%r
zARKC5U*b5a%D5L+NQbnTqUyzHQGz0Ve_|4iS~ay=w~o-7u^Q5d-oxup@IDKxzg82G
zf3?s2T7Iz-YQNvB4NgDt{)XoCh7FY-Y%5${x|VL$8eZ8#*%@-?KPsSGsdd4e2(hkc
zD7^#@-R)^EBD9D!XvB;9>Q{^ouvOZ0g@m+O-%2nGLs*ecEI+VBescqX2#w(u{Iygu
zMq%9mQ&OIglJI(eI*T;#Bae_{;%tKBD;VDMcMicCNdJtJopQ~}V)f_&I?c*4BU^hi
zFNAZyAwEARzMQkdsU6O*7_SdOxZhA2Qp($@6zrMDmNnUHp8gHYr-I};BYDc+A|%6~
zYKb>BwplZYAJLN1rZ&jOOzlM(Q+vWPHf3M`En=t|(M59RUqT%^-TzC((0?>>g$$kl
zlj|3=cd|A7KXm_;CY*=%lJEB?-I#hTtv~@82l9SU+-U47*&nn+WQnXGPR{883StN<
zj=Sgrk(4MhXdzGZA9TSf;`*IZ&^7?=4)K%HL{@~_YFg`-db<MSKqiY0SM9Y1JUj%@
zXZNdQld%-zbl<HOpWCkEuNkiI=W~4D=fD~PB!hIHvDizGiAbWiThfo!SlU~6zYjjY
z{5_(N7x9n8x0kXE?~T~s!#x%+D<EI8{xyR=)-Om10`~>D-(`C}AEiUuewBSZpdTDx
zlz-fBogX=i_V|L28i^Wiy4PR)aiguk1g6!rX+&G)X+HK*TizZll*+a<0zBF@ea`lt
zrGL2?#pSA(k0z-=Bgf&&T76o?bI&Jx^-RXay=9eQPAkQ(Wnla1{B)L3pPoOo5m+Z^
zcV^=f?>a6^5BW2h3VG&O?FD!k_teuAxizVyFchFq5qq>yiZv6h5KScavrJ~M$*LJs
z5@1KI03^bFIOXXSid_bcIW?IDtJ6P8iTJj>7lGSb*DEDTL$DZy=j~0tX>4lc$RK2-
zPq(Ja!C7@Yr$bLRx29uTGzb!a>D$}<G&BoQPT5Vky{FCWNG$VbcOH$pYFdBF_#8V_
z*vREds(%YDP}5G89V(u!i)f`$A4aX4r17WSY}MVpl6gY2c6A3BKEfkiH7oi4z2YQx
z-5M*!*|94&I^%(JF@G8!J%AKNFEAU9qJ)OEusdO8v7T&HmB?g;s+|102QS#Q$zcKe
z)=#bxOM&LS&ixvO0ADgG14uuy07%y4TsJpHj~Aa9kQ28E5o@RrIthw0R~-^8Sld%z
zNW(i&tY$J5ymO=rH-9|fv|qJn<}b&skI62b-jdi-lh3D_u~WFa%ZOu}lB{$e+Vy=<
z-zIPb(~n3_JS4FPF6ZTLRDOX~z_`iM$C8w*tTFW&<5BJ?U!cMji_w>cM_-OXjj{Cb
zR;#6GU`RJ#N(?cNLvtqv3Y$qqb5D29BC-=Duk)bCnvOb~NX`7*z&S65$7#|enjYM@
z-KuL;N@9Ewf<!$6#yMy6G0|=_XlSMMtyBzoR;UkR&Obmtv@>HKkfbYlEJQf>c`Bbw
zVJZXz)1^>0@^z1@W3^$bQ|X6sbbX|0xJ-(enWTqQLB(C9=$9uwI$3azb$+Uy<P-&T
z7FH}hXrE&D$vAOEzPPi9AMppUT2mCOtS7G~q6d|XI%>D-RFR#PvtpPbYT!-&Ynn;H
zq$I}^c}G4`!8~)tNOwOS`5N*Pncv|0+gXSF6c3n(G0-s`tyT*r1}=$Ai9A=(DaC-n
znqgvv1q!#3I4aiNs>#Vzq7l<*kQ|((L<~A^@>H`v{$)wCR}IyTQ@3;~v$7_u95c<R
zTsA@2z>?)&L$a(_OLV>X!@8L_<|X(Yig;u>rh+A_X*RrWCYo6GWt*~A<8wZnZi$u4
zdC<<!()HVw!WaS3bl8J$Aw-CtyVz+WpA*SMg7$jmSU#1`OtGVqYpm3TmXW@(KIj}N
z?beWXE3vR>#i=M!K=1W;ZZDFiNrY2-!eXB#&jfx7E^O;o6c!9GZ|NI)g$sLTAr2LX
z3ofOJWsYuy*Q8)ED4*scwr6PlM%oVg7XGFzY5c(Z7Xv4N2SZgc-Hm<1vCS73MWCu#
zI`S{rK+iG>w_UBq#HY#6oY8N0+q*)Toe}1PQ5oa9_@<JUwDhikqlNRD`V8eME77El
zqQu`!eixFdb~?|68;gA<&juNwg>M&lAyXbv(+k(L?nrAj4N~^1)~%-(O3}lsjU3Z&
zg%ADn!*a&Ih#y2lm2U$xLjhpE5m4{%=&nTAVGW>6IMdYAqf0@Y4N~;uyNdcg@AE0J
zGAVY=N2l;P!w_thI59&&{5A)nJBB?QT)n?2N)EM~%9{+t?l0c|Bynkx3`v^q{=;%P
z_DUVx$`9N-ou*;q4sDEmHOfV80%&vcr6Z@c+yk=w442b-#cE{MWFo8#m-Bi_FPAld
zw#ypL2J7ikk$iQb(!}Yr#*FI+fA<)!LcaO5U|Cc3lqc0t;$<84hFOI&^?fdL7Cp})
z%@bt%MN-8Y{z<)b_1uwGTMUAQXPHE5?C4{ATD|s2%S~vzNU$M)!K@(adzD`%E>4}x
z8Yy_j#S)JAyUQAbI?Q_U+Riy@s-P|^te{eeOPiq5g{g}qT=*tP`?b%8&)RY;+s;uF
zMF_Mu&`%-NkSq7#&nA_Ij@hLu>Sp1DV4G%Q?3q*KX8DAzQ%B5J*x3uN7(|tF0SzDx
z_F%-NP57w}hd_B9ilr;nQ#X|-+0SY?G?m_cj9B+7#gE;o-ABhxE#?(Q_bOhVxg*KJ
zq<C;S4d}w*yqX&_o>Q6-BEq~-OUadWLfL2t*lS^@(t|T5Pn8;oej;QabFBDQBJb-;
z6cIc{uR3^l%AwCmkUw|o;mw^0yhHwUUKs@BkD0r?R{F?+^i@itCQ#(89KqeyQpBFz
zmGTx(9Jq+Jk7Buc3b8X@HYo%n(pEi5<~Iop>sou%XFa*jaO!gjbK_wNCaNzd<O$Tl
z)_Y)?>psn)#kR;8D`RlF($LuuuC~iPtBeF*v`YWz<1&t;A5WG-K&sovI;6mo7Dz^=
zSJao*RRn5Blvy}AFs9dXwI^IOWHAlWWiRg6Wmc8N+i!QxM3f_XZKD_G4XoOl$A1m%
zDMdSsWpe0)D$8mXrzLwgD0D<5C#@%|NonZ_#mw7E!VooFwok32m6RTeol0)elU3q%
zpq@shhb5HI_M_RwkJ}DOSvb29H+OfH9Y)9eIb@Jvvl}zjcg4e@cZ4~NKI(EeoAc=_
zif&$!d0w5{hvle`b)>wA#o0^156)s&zU}5u#-9||dJeU5r)=wki<5Eh#-sg9Za<G3
zn%ZxjyM8lBD(36aX_WN!pfhmgGHJW#G#&nmAhN+5eKh@=d-7+A8>Ub4-OrW9BGt;S
znl*GazMi19wo_PP4<j43yL;C24lor?5sHXO-N=wGZ;KT&LhWY7LL=35#_y~X(a|uu
zAo*(EjO6H9tTM~Cm(kiiy5Q9F@8Y#yLQo5Tm|I#k4gE|yJFx;hXWysP*Pu=aabD&i
zP5QN~QSmZ;srseW6Df+5uw1FcpOvOhKak)1X6LqCOeCG^Y%Zd6H=;SpDvP=F1z)U}
zvFi1Q4i5#+>*x~WwPpS>pm$iJ6JH;*)lN7~OWcrBEfgYBdBd;eYyR=-_MRUxx@h|c
zN4l`47BPl)fh#jv>VV!#vo?S5ju|CLs;+CRnixKG{6vqXDFc0TuX<QcwJFrS<R34~
zGN7wVzR;E;xqeK!gmgjECkB&d&_`yv-j_i)*Dl<_aJq>BKuA3alZHB8-TK3HYBJs1
zHUT5J658%d?K`8GpF^W1bQbv6&)WKmeUSa^FhE9#*&Q@N@^7_!O45>S%$ClH8n+dq
zCgLg|k-8Dj;#xi!j|0XI&#S6`1<I}mR`uS!meBgkUlfS!;(|EyOY)UlO-pcwe({$@
zAY>~c#g3or&qJCfPoy0TpBcOI3T*$1j#qMz%$Ppk!dGlwhWxu9$2#oY+^w${K_N{h
z1_V|PZPDJv4Md-{FUtzjS>S~&srq`OmWvi)hD1G^L23h`pJC=@HI#Nu9p#n~TDp*y
zUgEoWiGB7ncEZTMkd5VxVGstf3D_jdOczg}nHm^R()IPP8PxILq7X4r%G0Wl622lC
z&GBz>bxnLBi*xUcBhU^7ft!zf`)Ps)E*wOm^s9?b@O{|>r7^AYxn3oE{1F*g|5(3c
z#YNFgX)y(&TkPyq1<Tf0?CgUy;xG?{YsVmn*oa~=7DxsowLx*Z$ruaS5VIFC1N<TU
zM}FFU0snCzr2{+DG+%@>2`CAWBOnB2(tY+c<SI8XPmH}CGCmiDF@Tiw`Q{`RhyXXS
zWAK7-i9M~Hg+GulQKZNfFtk~W^TrfJ+LzKUw(=umy&@_%FStCWU@cgpNs*w8$tv5v
z#<giB_)Mrt9!*%b)K0T-JJ(Lj4VS-Q`v?9|!huDRIZ=7yKtT<`*Diro2=1~)zZLGX
z?Zzp{-@CTd*&y3>E8NZ$3W3OGEeRgBIU3u>G3L#Ps@7;nCm!Itu}dqDBXZ~s+0}6B
zEzAebRo{6lmOy{W4LjlB%nkDPz`_17no=ZX5sv(rsZY%a%Y5)avwl{HpqAgJh>V@l
zyaNlrlzJx?LTm7Yi_uh{+@ZlBItfurfu4|tl-$*?=t)7i*EYB&W~^u(cdS6_5RTEE
zt-;^OI|C!s%71ho*Sbp*TWCig`F<n}u)UDEtHjSlO1vYU8PIO``6dmDYgP}GI12bW
zLc0t6s<JqVqshdoxtq2bt(Xf;N`Fgsbt_eiTba1Q@k#mWROo-f=a;9>Gy(1IjfX~Z
zRt7)D=O-f0nJyQ<uOK|2!8rW=r<W?-$<jk-0E>+mbnd2T;fKXb@-vh2K;p-@zmfQW
za>0opV^0EYmZcoulqNz?`Q8dE?*Nkn?ES^XEjo08M)X_wJL|_=5HOVO1B&ZK_6tkw
zm8$;+Xh?ZOpIkR12aAz(FtO(F4V(O^{bEbGc?5_c`00aI&`=c`@8UPOl`pg&<A;G8
zqCFI5=ArW9h0qeAN#wg#K~j2$ol*`tp@OYnn}~8K5CJ!mV2$<&=L5v$6J*}W{mvN#
zbpC?#L5nQgQ}c;j{$@|U(cRz(#W!<WK00ClhygCJ@3}h$U3k}m&g@qV66Hcu+dHD2
z7d2yfgmr8^1xP7r7<tEuaYx!9-6gE^ZgBV(mK;3WF!*w2QUlw>@0`b3C}^&^gnB|y
zD5oL?*OP;;?FsutGv#uDTsEFa&R?*UC~XMt>?pP>q&z6P__vMN*(f4<{mgdf3K@Eu
zedNw5*xC5I39$GhG+1u<VsQpzeo=m|V<<eHv`h3P6}|cjC+gUx0=Xc+!;d_oF)mzF
zW;ryfw(}FeXVuPW>enJLILBfC8p>{1K_`@ZzdJ@rh4OLBnZh1F&l(7$Gf8k$mXf7b
zk*Qh}jFJYGf~12#L#NrkQ}8{MEu5H$@<Q%VU%4(mBHVeP&X}Js2d@QO+1CT5RSz74
z&r2Xxx8ylI!>;R`9*vr#fRn18il>VOn<2rBtGYT8>}*&o@!8~>+LKxdH85A0M>7Bz
z0ZaO7VspJs=D)kgvweSZ5+juXnI&Zh&!@i%YN><*49gGKdf8~H@}$b_il5t>pLClu
zxofLD(_leM4sK>iXrf_m^^7U!Bbcff8V^2kctW#$ahIlZf2sRDdW$yWt>s*b{bgU$
z&A1E>C{J6_bwjVvcfieOJHRC=S4+f&NCOH_z8HTFZu$tbCf;f<A_qs{<-<Ns1Purc
zx&NpjUtUi^ajAA{>d?I;RQEQmj-S=J+>Ud<T4>E9AC$AS?O-^3k6?asWmh)<D$?PW
z0t`UE?T&U{LpM>&ec&gyE|Wv+9^$-N5B=by^Tx&NW{Z9umue2oY6%ery8@L{h4r2v
zFSCX9)Q+Jq+S*>Jg`I(eLnC$F0Z=_3*z6*muDU2YFg9eV>LMQ@9H@+7GcD)UPX<)j
z^Etz?q{y)Jkt#T<F1dC~q}ZyYtE>TpPq2PVyEg1rF@|tEJZH^fKA{0*?@G>F>;nP;
z+b9ownX$*2r_ynrHxl5T%sJ)yz55>YW@DZfaiTvaj9jEi*`?9mG-7H}?j5TDLw^7R
zxd3q~wOzS3>}QA1PbX@;KTDh>);C!$`(%*^6*geoNfWotHoe~UC<XO$y!Db+g(K|O
zk)`IMZP{Zl<io4@m=^*@o=^L-#q-yUeCiEUGrdF$hio3nwBJETT@iZCDO0@@GQ&G&
zsA^Mxrk7|h&3=}`XEQ7|xuIfuKa>pitI+>TU2~-$KQ~@*Of45x3KuvY6<*Vww5wqh
zGh=G@>)o%a14)~7Vo0nwK2fVdjU0#aeWCquWlyfy+^hT@eV%On)XO8~n58t<kB#<a
zoQJ*yLzir@MLo#{IYUKKirXVLaQ-oS!+~F#@lMYTi@%vX<z&BWfBBp#7xD)AUqS!j
zVqiM(-;C7&;{Qwf!+&^0|GVk&|MiEO)NR$#)RFz@AyNiK0kFYVY|UYDe`s?b$zf@_
z^RN|=r7kzjH2aO}@i_2&u2Z`|6Q3S3`NZRuXDoXjg?|hGmfkqFOCbx&60W@@_CCJa
zY-72foCJ1!+^#V6fME}-qqyvuK_s?f^x2V-ru8@C+fA(SII)wOH#oVePyf|oB<dT{
zu;`<Ny^>s>Vhoip8Z>u$@`TX;S+*+;=><U`(bTI@ONGpg?=6|@KJU1Yk-ZRYs;s??
zML=0HhGCl(m`vZ=ZqDT<^sDJYr>|qLkm7<|+`wRgU-<bUDsj2qYnlxUE~HFWMZ($r
zo@=7HQ_+98`-=;g$Q@JGzgcpEJu%p3+{OG+B_!)fa%7gpx!ro~`47%rN>%5d=IF8W
zgZAUhuCrFnt%9YLPR+v~GS5pOTHDg{Xgq>sf~?h?)cyk-XBc5Ro+fErI1>F~I_zyy
zpA-$Vz9k0UYRg#-cbIj0jkY5T;C<6$7{012%<aJCaqrSAJ30VcLbLL(3fIBXi}|Qy
zEw^^4lHVhqR(dkzkCi!Jbn6iP*?_?O-UY9`Zw5bDuUW;s(j>L&COUgeEDPYR%fS~N
z-*IXk*jI{&gePWrc(UixxJNN9<MwmTpaZqSiqz6Vbs~%I46~-#3fLp$%(%r-a0?^K
zm}==|WmU2gi(DU@OuljBld2^b1qaLp(zsv0-j>n}Y)ZIUd)&AN)W&p>ZRVAS*vxU!
zl1SCVgsAlx^T#K^I>b<tV=^*WbfOWVp`?^H&mfp?Z@fHF(=-fH%sn@<OhyxD!h5r!
zP9SgJ7hlCeUld9cgAZH5pu!<e`SuqgAGXro_?o5yH<J92XDzgt?!922QCdNJCcTO5
zMkHY}n-8niQGpwAqN0LAT|_9DxK&t6jIgAhfrEIP%3Sob3U9wL#=GOMJ~aO>wsEgO
zYp(S{m2g^rfukwKfhH$^l^6ELF8kDn&bHHwhehXc$R`yde8?Gy=}y;ZDi3;xtDU6a
z-aK0`sxG-qJ&d^S?k_KfeT`3Dpl*0Ey)wlR2o}!?zgGF2i7M=L%DWAx?v;Gi=@ded
zweY}l!;UehCfz0HX_Vw~gXXZ5R&kspAX3etq3mI+HOHm1Q2%EME#9t*)evjvpqkvb
z8s>Y@UPdPdWcH#({-d+oI$lM$T{D+2+Q&oPL)7CSJik~w4G^g71`K7s`y$}&ykEz_
z_Kb`eGV~*GyX|Q3|7`>P6*cuo#Xqhq`hd9GvM`{L`U!X6TpuuAw`NY5hx>~Tb{E`7
z0@v)ACm^opHNPgia}^hN|J(vV8}<T+tL3n%KCg)`!Vm-YCF3<v(B~P}2>!`0fQcOo
zT?_@L++gv*h95Sxg1o=b7-NQNia<xU$0qW(qADjpx&dPu2_inO;jI$MDW}m7xQth%
zM|1)r+fxd=1i2&ENTn)-)5j#x@8p)%5CR*i^sSKlEg#Yn?gCiuwkA0H_~l(eW?$>Q
z$F`mjSf{?qf=z^ML~z|H<ZW|9zP?iTEZzu2=n@<eazA0?{*C7&IMl_;73Aweb_O2d
zAj5pB3<%qRA0!aU$y>xf!ldGgMfr+!Bz*P(p*$J>@eJ<_FBvLDj7KYo1DET<Y(c4k
z7R@PX$ASA*+#VMYi=K7&yM!1$YfaT(b992a_XAvZ%z}Ks=fDLZCL&`K&pH&zir?!S
z&R2&pSk*$d3mVQraZ6|xZb9A&9geP%-^Qw5uQTDeR6K$>ebc@zG4B|nZ<J&j|AR(*
zdioVx{%xeNFYkFzcKbd6sq>rq#*cOTt6D}C;}41AzAMN{-q;=u$P6d{@%W0)drZa7
z?2`TI<}*16DF%p`G>BMw7Mv-F9mXGI`AWcsv|w8-wD=M3DFVOxYvcVVbAfvi$7FpA
z;~d@>^nbnW6P5<iY@q+GANto7_}3KpAEs*m_gI&MjphI810<`z{$BV?;D^2uZyZSr
zlSdCOguTlN;U1jA#<-3O3*j^yG7o0UA*zNCIdW%`o`kp@xn;dl)xo{oq`P7aO^42y
z=i~LU*<+d0H1jT{W+NU42-SOCdiLqwxh`1I|GZw90o{zugs~YqWw#L%)G-?@O6!GP
zm2}A~+z&Mx2`|VBii}w0EihvDH+N+BKfWQwI7Zb7zNhg6EFYtJfHIVONLDgbw8n|x
z3Mk$xV+ct93|?^j(5dV}PSvN#-B+jaqXTr2*mP(7qVyw$@1j8eU9s;D(;2f<@e&vz
zKobTZOQ15#Z^QFy)5h55%*|tSd|%w4-B+J*)tX|xHk7wtSoM=G_#wegCVh=s*!?j8
zI5T}hJ~F8a&*Gi5FO*PDOYu<8m7hw;;(SmPa744ZnOk{m({Wf~78+3$K|55M?(!HO
zz$I6PqubZ4kjhoPR*ybLh`XpOpD}(*eICVSfkla719MB6ZHB-<O?Y=yy3jsCqjjZ6
z5`V>4{gd0`ScZbp24iY&d@|@19}QG848F@j#~pCHwiDH^tfnb=O)@(A^Alo*4riF0
z_~{#j>`ptKW2+$Ab*d06vZuNp_wl)|)laj9{dBv#cA~U3C&jvG%MY)nh3?7;ms4#A
z-*yw5J<`)%3iG-aESOxAkGCpkt|0|Tfa`szIRFS33I29e=a6flEJBFMON}fok2Anf
zFY%W59Ea>mn~CX&QJqv~*-P`f`eTaegnlLk{UplHEDB?j4?raVoR~^gl{b*Kh?qCr
zk5?-*>1-(0=E?OlQNk7PnL!^zx<Q9agujUxrQDR|l9C}`vBOuT23l;#b*@udxh4_E
zoUsHks6D}Ul-nU%tF_~b@7k2HLm{!2bd=aj>ei(y;&-wjOE-%cDc@2umlY1f0VF_h
z;ZQSO0jcrTmVh0Np{k{trIcq_?g6qN5`UJ_SdWgnh{@Q`mLMQVFPUKZd&q__BaG9a
z0eNk_xj~oxcsW-b>1f__la{OgK-{-lSz&=@>(PBegx|x$xKD<0<cO9I2wkJKLVaQ_
zsuzepr5?fq`VNW%#PIRp8JU7Z`fQ!yJ!Kx!0~;Qp4{fYMvp4RY(#<wBJt4n$`7o}n
zUqFc1U+^;1%>3Ct(7u&wEn$+E9I(Z$xHzW4D%P?_yCYOb)A4IC?tjT}KgqO&{5}xC
zrQaj<zY<N@o^KN$7-_BCgXN!dz*u3`!BTUPiTg?!eWxkMwKJ%OS$)e2{_t6cUEZo|
zT8)J(&Oy_azhcYKS^Ka$wzgJtj|h0dnitxduA?5wPWA=-EjW(3<-O7hu9r_{YhT5c
zN;Z^fq=pw8$WE_|L=`p!LS(Q^P_&g8@Qr-51VQNAZ=SQ_s#DsI95hcwmM*5XOLvyb
z6y!Dl0v`*zNPVsRJ+AXby02oud{~lYpA82XCrl@JR0`!`dlN;S-NKB#<`^N<N-!y~
zGVCk#XwrwW0=`7&ZLx9sRPAoMPh>)u%c>B+Cw*K;K6Pu<`_U5<{H&L~g(W%3H1d(n
z={{1e#JMXqXdpZPEn>BM0B;9*sr;>U<K2@7V@0mx@HQkyINy>VEdG~%(4i$)o$y*4
zf_5T#5TNeVpwlx@AP^TsGMc&a{$dHO9&8P81|P?ub`z+9sqO_2GXm-GDDf0}p@05~
z0RI97n-t}Ai4Mi=yE2!s=0*@N^X)2fd>IbnFHYr&Y>VCRq+|viBe8)azw_?|iGW3P
zqER=F^2Cb-b#&B?JZB;NQ^Y9~{uOF%uNoGsI|JLuM-mNpV+u#mw{bN-H8uEH*%e`I
z=kklEBjBH*;GbT{b7n`U3dcSbP=Cb9$lSw6?ekUpiuUA@?d{Jy!bKo#Qwz=T23IP>
z8aL=c>77SRA87%@l@D{GJd$5m=7vGjy4@|{dVo+>Olg!F<DG^}Z@qI*Iht0TYpy$-
z#)%fkFEDq#!iv<B2cgpYro8D_qau7DZ9`+h-P&t67XWX}CUfA9p)TN(f<N|Y#_;GD
z0K*u*qTGVWLbge);zXj!sh}ZZNk8BEXGR3`EF0ZuVgAJ|(ku&d2jt@*U7_4&@7ASt
z#fzH2cZEi3#8&ScL(q}G1_ef9H~VPF-}KZld}1}l^ld#qYbZU#BE2E0&f$_8mSm1v
zNUXI%dncJ~qs#5$>5fG&Xj0y2nFGG08~*=A+EsvMv3z~HySqE3ySuwv8tE311`(w}
z1OZV>8l+P~q+0|eq*J6MCB8-PRq-O?|J%pcSA5v>o6~2`&d&61Et95shWQnk=OOP{
zKTHz9X~hx2Y2s~mQIF_7H0JM}Q*q~td~m$TA7L6~$&t0my+QVwGjxt1k!GE_1%2Yd
zj0~}DU(5Z*78x%T<07f95d_BE*|@N5b^ab98oJa&=687qf<D5DG$%R7Oa9ID&}>%G
zPU~poH|~9k7SuE|eY*UR&MSBHwbE>hl@QArCyQmank~uugxMOWR9r7^(nhH|Lz8wb
z+(i!8blID=9rw@TSSu-{fio+C%?gZ3+M;HYsgOhL^ZoD3G&>>(Vs=Qa1w@h)M;S(b
z<bJ6S&Dm$trSZC`o%9KDGs3z;2M*(-2SOiy*)PDq1vCi~NZT6MS_7>BoHb|tZ8ynp
z(=-ZTi5hU=oQ1We8?Z~pKRaY-9eUscTlS?gSX11N84a78#z3cL5vd^Pl4%*_#zBik
z!Q~6#=H{NnkwL!wu|!fj-55O$gN89E)7Dz2wz%At)cQWb9M%#3(k8VNcVoTMwsu(7
zeShM`o;&-K9tj&v4vRZQf~OFTMBaG*A@UGT(un&K{SdfRvXAarBeK;A<TZtnJmevA
z?kSF58av^~@T6hw8BiW{qzj-igF)WBBNznfBZMPDugEqe*5ip2$v%he8F$af#`7U0
z|I|Z8e$=L-O^QCBf*CGS{>+&b82Mxq)IRazlzTL(h%?nNscjA%btL`lrr8h`;qQZO
zo7?eMtP>w|vR0%hb>kiebjJ;{vfRvuf_yhdNp0jDvOaOwqJpN_#PtogIfZP5HRYR!
z{7ymC-L}1svXHcndMBSwI|o^v$6g1i-EbLeqR%BDi*7ox=yeT&s4>-=-$=yRL>|ZO
zs7U0wUB;de6Feu`Nha(1RuTVQhRTiG29!rB*0KCLQrYzO(JPRk0*PH6&Bf*z4`M1D
za)y#Q30hv3a@4fRJ~EA<cSITw=4n|ejBPW_fFE>}HnBl8^med|b`597e<+{zNN-xY
zn;a_-V_^>u=AnCIv3z>_G^aF%Rr#&AxoqOMP{>h|;^Bwa+i6?qI#!#XR_wrot?&Bl
zwHHA+EUW5#nM;7I#Da|1vqJ>)N+jT6fBNWlTbYXlA~RgFA-LfO#qtD0W;`*1ZduD9
zxzAq6Y+mnFE6^jNQ!~-ji&dzf^SYr2tqNs<(Yh%5HzE<_)^QDMIaHFx-gr8;KAXiE
z8^M4R(PN#RV>TVIVpaUvxTB1fj;B0PwgT?s=NqYra`_acO)P2T<c4p&D?>z2G+N~F
z46|<Fuaq%h)j~r-wHMvSBSUx3iF$NTp|@}^gm=v{m=~(VD7(Q|-gqZh=dHbk`C_O_
zG8MSnXYyz1$hGWsWR5%gxt8yC#rzAjHWk`*jw5dS7R_i77R|U3I!r4NI&5u16P<<%
z!P**0Fk0)d-qMDK8yh4D{?K!T*@o9b?Wj@k%mDduuWLe>S3-o)oSlET!BAQIn4*?!
zr#$v9QR2WB(v<no)X<jT>GPQ)Uctr>G%&oU5x&a@)PfnYL@e)|ke1wz;fZYyDkCBt
zMWhlF^_V!6g+HrE8h}!W4oB}qL`dkrEeVQrW0(^H)6*|J<%xjeC_J@cRjXJ&U>3|7
z;z>=4wzh1w7*eEYyVbvDD5tB|XUjn5|GKgpll8$-3uTNcOHsqLj;?^=el#@oeyE!p
z>hoR^O_&Mw@kexx2%M^3crtIL!Ul02>d4>UO!ZL6>$-dIju8+CVmYv-&_zT$rcEAa
z<BE_!O{jj@$kd1Q<xEefy+rF}5#zgdX@Vzp6fw-C!}ipp-S6UK;k3yR-;ox0ie^0_
zS$F$bKA8ZwK|@)&x=g*Y*PSC#Z&KK|#&e4%ryXgi7^c*)FPXN}HOH72{yv_ed$J;Z
zqkvrR8cKR{2SM@j_We7V$=T22*CJ=@-xqqg)IKuQ+I}DA+v6=;OX;FxscVvyVJ@i~
zBQ(cr+A+Vtnx4~cQu}F}7|CAH82^O)^@>BYl+lvwtrxfkq$oJbJCiVj()%DPduR*x
zM_ro(chok>yz9HHl5~U4z`*La;9*j=qzbcH;DksbT9_kD0;}-tZlZCa)Ym)XaNQ(M
zv&fGlS*$I{y;+s}{5I};j2zhTH+|Is<aLx;C|K0DAUL(`kcU<+&=dr4#j1iKN*eo?
z2{ZOTnFnQi35gazY$r?FhqNLJ^?-Pk#x)}@l~(l7jnLn~Jbwem^`L9C@sypmTu<BY
z#sHZ`KdnWHnD#QN3l0j8`5R>k|FseOi7;?8h(4qkDM5}}g~K<cV(dHV!P7$WA<&L|
zDz&+Hpq*YXDAgRx%o0DVews0*g4j#b)8<$fHqKVoHgP9jPtIy<#up}X_ihMbmsN_c
zWZcbimiL-(vbY5X-0?a`>q7Gc*ZG#bbnj1C=VK$2(h<EO+Iq2Fd~?!pq@`X1dBik(
zyXl_O^AM7T*F=aOgS`gankDiGTHuZqHZ4{hFs8OEXuJ>xp?VMzpLCm%Aq-m~6biA-
z?k)-X2Ja>zouO5*0`Ic0)_B&3kBsj-!Hhj6WLL&G^y`|ui#pP9whQg#>`Be0pD?3?
zTY`RffGEkHDSf|AH2&^Jws?Ri9O)Lj#1X>XWBv!ITLe_CJJR>DRnVAC4C@}U&0-$a
z@UBVvpy^@afzrhWK29UsLN^avrpB<b%zH8Lf%y|DuR)3@8ugZ`XgGNhdZzO>wQG!%
zZSV%Y?eL}=qR`Oh4zr_@9L#<VWsEW|5?$>Bl)P3{v*$Qk?kkv3IK$5sb6CQOb8x=A
z_^2=;4ml*_yVn*t<M2zCMGYDIqyPgP>WU2lBKyb5@qe@IPyh4%&7*J0wj7u_qmQ7T
zHDsG=ZQ~J-`l*T`jK1dNY=%yFXjhEhXlxrm7|H{8%Q|}GQMssYW<S04lPQlU=@}kL
z@2sB?$pkh%%e3>_Upj?6q2HEyQnRBu=tT)n4tnTq?7`t+G39N!$hUF$^z6<WrytXC
z%RSBR!-0@0h!$jQU{<<0#~L#m9b<e%O3p;iI0bB$bdSyvQmb|QUh5pWk2eN!?52~D
z&8914Y7_PAxme5tjMRe0>@D1_gZ!Yrj)OYw!vN*u=bqj&wkPJeMyMM_VQnL3-UfBA
zNavo+o+Lk9YW)I<%N({}NueLRi6&Ma&53U9(*F3#kb;_A7EZ3D#oO$+#_!*nHqF^Q
zPiW#Ql$y&;RJ1`r478EO@8ZH^oz2Q^E2ju#CCJ`amRHDR-*)5qFml@6_ZTk{s;wu3
zC~_|Xr^8BF;l+$KBR8R@0*8fopo<Mzj>Mn|qbENh+ith}y@&J3Hk<_&z79eXYaH3T
z>O+blz0P;x=T5xzxxV0%F`DZw;l4m^k>-9&{r2rg5jb}ylQ73}dJBg&TB!Xf)B*8c
z+T(%G6LF7{m9uYB<Pfqn+kA{mdfU2@udHHPlhpa1?IVMSR7fYS?9&wPkO&O}jQPZm
z0-6wHb(rxKH*8qPUKj7#4zxbT%9h~lZge|xe89@`mS=l8bWM5eu1Ytu9euFNSWJGu
zgqCK+6C2M*M+35X62T5~2N6M_P-muE&AQER!?~mPYJo#hNwV45Qn+p8S!^A2IE*sp
z80<A7^f?72iEV4ujtC&|vp9y?gGPl+rJ9wUyU`ky%qsiC7EP87CqE+z7?{LNOx4pB
zT1USPqC^Av)Uk#e!qFT#gvcjW8nsCI3{mg7eD|=4WokZ(_i9{pH`5o^E=>+|ImM@F
zKGFpW1}117sSG?u9z*CzLpfAkMe(>wbfvAU`SfKJeshw%xbKiwZo=g24N&ljBhxI4
zCj{8nbr<_o(^?gG+eDMw*d!epG`W|lmC_%e8merX9#dqmO|Kg3MoNg6aw1c53{%LM
zW<}z!cXJxD#)M;~h=#*0Zsi6%owY>sDV*jw7HwkQqKAC-W({phc@w{`V^jExVOkxN
ziAWRTgnDskCB=m5rrvP`uXdB&v0)SOrqpV%sI99HVou59#yD~}!AF%_)R4Y!j4+Nd
zebpSnBH3)a*--7`9Cj$EFq2z(LKJv<7DBqUG+0(PEi26%RJoNpK8<*1hKA;o_6@-i
zA`T%$3Wkcv#uhyUc5TpJ%tGMn#D{h5)Gi+mpWb{d@G=Li3zL|t)r>XeMtP{%GxvqM
zxXu0AX?kOdz&wfmv7(R`UAp17<+1kocQc6*CHmTuOYLX!3p0neAB7pLCc;MG47}i2
zueTw4)=JJUtgBgLWkA}=nuuUN)Q&1##q{#7+l;%b=-QSXl-S*pdYHR+)!80kzF~N7
zwAaXdW)a(E6xseke5I9U2F&aOlAi2vreONV{Iu5KZKVd*4NGjT56}9i4I}nD>*xiX
z{P|fwx@q3EwULA$I;;{MtWgy=5Xdti9BG$QDCA&VqFC)2?-`8VWw^CM(yit(;gey_
z!C|vYwiQ>1^r>o>{MF9-x`E1!hhFr-gIulHBjZy_-ceQi#N+wbRPrMR-4816xXA3l
zJz3f4=R6{hPuEO7NgFUZd9P!@_zC_qV{AUY0L3_Dao}dN(xB!03M1%SwV+e(@P!@t
zjz;&gPpInB2}wN~@7}3wD<9X}DA=!iI0WiZUrA3f8RQDjnsa1x0{;R=`m?s*%TU<}
zKk<rNqRzq%_jCQ~{8poi))hR#%v9NMHzDWoUl_dB#a0wrGvARbYEWdUDt?k`M@IB1
zB=U}OTRn^;tbzU;n*AA!ebX@dD%qFWw=wskPI;mT^h&V5z>H(OBM&l+ahtiZmyV2v
zw;Z(I1~L(sf;<a?)Er2~+XzkCkM52z!_s)fD{e^RE#BefN5(5U7(Oj$Mk0gr$WgtS
z1(y7CB+E2ma+8zlR?Gm+8=7+0!1fHRGcp(C`abyS2QN%ropLO>ry4@t5Jnsy3%+Bk
zsj|g!%U~7O`RHh-isQjBOR5;g@f-vGz|WJN!FcX?u-SQv2u=Gy*LKEjd2SbHX6;7D
z$Q;23<At1i0k|TRiZ_#4OM=bF_?XmD{Y2!I`!RA;?(cX8yzFE+#+*Krhz}athynM1
zrvRV+`6-j=ez2R`iZ(G*K)HXhJw^T#n6;Lm^5|mw2I_pv7popkvitQ6?|g^!%6fwG
zn2Fb|q_FH9q>${|?cD0ep%$z?VQ+yGfp(jM-l~J@5J0ZXbMRSN4;g_Y;SAidvs#Qa
z#&&4J`4ACXHyJRhv{oxEC;T}r(Tbd;Mnz14k)%dEi1YP*264rsrTY*QV6~vB`^qga
z>vu-UX99vA6oP*weCbA}<)UFBs2gq7S|t`wosg%WA4eLg(H+G#4eQA`-xFams^5=*
zo5=|1mto{C{uW+c?CMmo;#7Ej9W=N%cF3W<_yJM(_TA8(sQ5H;3>)g60D0t(nTgbk
z0r#{g71eGMXF9-#tT$8{?+2Su_c(rT#j9eyyG5LQH{o+KEZhfb#EM6Xfmvki%h|37
zD2PbFA2dX$`%q#V*ob8NJX1+>Z8Zfj?^=R(VN3|A@}*$cSekjaeZskpTspJrx}Mj0
zK{pe-piF`8p*k_t!1wdsYuYBUG7|1O9>fp!R5GUbP1Zf8aPlQsI)q@_rnWteRME3I
zcom<-*K$TjryOyX8?Mzei)qAb@$%S%L}*61m*v(Z?oAk7|0=5&`freU6ZBS2Xjb%_
zkx>Lt4umdt^b_*8mWP02gmHka1eN}WqUC(W{}l(<7N{BAI^Soow6-H@{ry|*yxlz7
zgQ&vR_y%1FM2xTjQASMSqZ?xg9q)R2S^4Ns8G^Bzpnd($vgi&-LOnQhGVp}JUf$U6
zO}W!s?XvOlp2Nlz_-JG9J-A1=936)lM)W5fono7`$YOH$<y&=WLej`JgywN0p~wg}
zQ{!~F=M&ND$<Ss#iGLD+;)=<^Dq?S$6l&h{Je~D_ck}Ve9*oHJszvgfBf%DtwGSMY
z@jBy{j_+Sm<E*A|V=9H2XuS}aQlJ@JZV#pYqTgyEgv9HGvV_oue4B|X6Oo)6YBl;*
zN{k&fe;;I~Ag`MGYYrtd-{<*l63^#SL@k4-Vr<%X3qClj>8;*<=F#`itiGJHOPQa{
z>S?d}9P?;SEO17NsKiZr&J*pU%wxWL$CUdsCaqGKg^?~Vs;yXU&ng9PFyKVrn6Va`
zSRo1v{dBXko4o~BqCaEA@R?DgXiJ=&VT-!_JE%!am$IX>JBqlRV_utB3{`g#=(UAH
zPO^ehnN5%y6{m|MUz8|4wtUK>w6zE$X#`FqK;9zT2ct7@^m<mCisDu;T@z~lh){bT
zReM8R&?$|He7hs8oLb{v-*k~$BNkJ_8m2zU+CXC9nzr9Q;Sc-a%Qu%OE1M0mLk0mc
z1U54Rx=SDm66zw1GK!MS@-ku)ifR&*x_U0-Z!mrKi$<NZ)U2VhQrNBWm+qI$hZKle
zi&xuI#onVVCaHufZf7D1JJ}UTsQ1q>^ElE}$l{RsI99r}owAYK3cpqTN`kp71#QDE
zhd0}he`j7O&h5SH?Aqa)=&^!(dKvWA?%K!){%R{Ogp(&)MSEXP^anXzOe>4<raJ4r
z{NXo>Hhgp+w64n5)dTruBY`Wg+|$E_S}?x|-pS+c9S@h?8Acz2el@MG-IK}fd&mcf
zum?6wh3W--0)Ec+r_Hz6cBqqJD`OSNbt(B+8fBo(^{CCX?hm?R7NM1w+;q)F(cFEf
zZhGGc+Ym!g&zeiS9(U^wY03*nIgR^0BKaB}q77h&?;eh)94J1<6SVT|jWf-wnbBr8
zRl=ZG@GbVL#Sa?u=!8>-#af*qndkoaaQH0iq%PToJ|u+z!nURy4a;56t9_hQP1w$y
zyin%zeKga1&=l+OQIs;Ux_-FRI?Qhx!3{+U2pkZh2=lGsNDJVI@l<OXho&n{wVGZI
zmKChjQJkfXu9>tsd$v@2S~9E*L{@O2uyo`O%rr@{F`G+DIn9b1ZL5}QRe<d4Y@*RU
z<2&^rg(8=QRcu?T!#KUqU@Sq;SFN$kKQRI<nx)qaJy9IkYWh-EL@`!vzK53%o1t&j
zA2c!NULz$_Uf7gW|B^DS;b3ofgV~x7e9@!@T4Zh-s+ji(WWp>S9!+Fk(#<$XHISZq
zkWC=A%a?ObUcXWII3dMg(eU0`KNWHfp2{Q4+uoj_tEgqeNSL7Ydg}y`{H?gupw$Z$
zZ{HQ`!P3I43=>J|I%pK+2QPfSrGRx7q*s<T=*TXkgGrEI`x3VUBP!@QTcDL|o|DIB
zI@@k>+op3FDR(B=+Pw*K5kmwa<)GuDUH7ujd{vn$xZV@Cr;yJab89{#9TQfW+R_Nw
z+|oTLndm?&LxKfU8Q}3&4e@*KfOl4crCNMjTAxKAEy2lEUiyilsVJ^$FR=@JG>D~N
z5jAx00KDQ+<MO&P(vp219b>EG@{Xx5``!>N&BqzJ!N-m;<cyhqpPE^2f)%eEm+0z%
zM)6Bewkx1-3$<i|4Pby5#|g%ny$<%XH-_@$ZpPPxBYJ11$%CM+*Dfle$2<#$ltyGe
z-qKr)l1A8^j6ECsph2s6hnzyqbT6R;POEbjx_CAa%?gE!F9Kv@t`6~drJkZfMA@61
zkhdsZJ>L=ep-(8$8@h?GiQwwu4=c_I{-E5q{O~{$t%n1tv~FSqT6?F$Kw@!ndV`@(
z_1xyXZKAyp7bs1-CO6v69*0pZ@8AYqn|ySP5ecq19Q&F1b;)7f?v14S4e7cfJk4^|
zwqy1BG7MTPY+lK{d>f=F=t*kU38?3ga~ZJ(H3*6$AmSB|C^7Go<wXy?pq72+7MBw{
z@_{Vw3!d-0xi%gYHO_Hnynbr^7nv%^7@S+Mt&R(c(otrkoMmu6zOsj8a$%q<9~$2&
z_}OvUgYfZtLQIJaNF>F231V82H*cZqqSnbTd>XTfM#mI4e@`@bH@)#O$KzS+?QQd6
z!|vHc3q!1tFECxj(i~BK??7;{mxIG?X(INpM%=^&-}LGk8Dq^$YIP`EWjAG-k$$P2
z9aF_9q5lAWD#r^-whD#KB}^-#tND@)(;1rU#k&O*Bn}UCZBg0W=u=pCAx%LG`siB=
zlFY0)iQ*y_c4hdE6V9&c3)XFqHV22=BZEA1*mK&9gI09J_?uPqi@F9LBE?k3@1cu6
zRrpAw%(U>ig8bt>WpUzYlRinZfMHw6y+>qy!-pT)gCh^z_}$wZ`&3gW{6Ztw2eNKL
zciLjSMpu@UkVcYS`jSE6x>|`ko84q52fnxH93I3aCj|ApXlb@cI?r*ua_hif=l*Vc
z>u}rZm<5$wDM37@x=b{#G)a&j@P1M#HV99U8d%HPFvug=8R-5I^*iDE>1>m7+jW8H
zb8QKYULUdWsa>La96fdPAfK|M)IzI~MLkt_`EWK9@@zZ+Gs;xp%@*t+CHF=fVm>6j
zXxd(QkZ|M&zg~SC!n<?#C8jDD*oAJgL@&e=_Qkn0W4ZSevq4YFLQI~4Z|FC&4kJG{
z?srD;C-V=8z<(|`u%pAa0crqk!grV!x&RscB9hZBoF6&N&j!Q?*xg0tA>k+sDm1^!
zUVfA@RWgD?qaa*uXM;oWBs(E@O8&#q1r2)qoTjN`TX*haGT4p+e5caDk8X;(3S&BY
z!cY4LXb5eLQV*~{p}jXAqBTMVJ@tzg*Hr3?zzza;y0@0c_@a-(AvgKM&B#KSa(kvn
z97jTXqDWD2ro6o7{d$@r_LQgcBun`F57djvDl6VpCz##fm$a6gS31V!XO<w}w|@&x
zRIZ}O1ZG^4<~<7`_2Ph_QANSHHN~MkHkp-Y2_*vacmPcel108XD;kGJ%}VlaR*)q5
z!ei#!{u)khjTjOe!P?PGC>3xG2u;`p@Poxl`8aS5i4XYVl|mNF+~|>E$0Af<9F?K%
z*_zTVwTY@BtjTRT!P->_NYnk#xJt;B#x0m;lt^@<bxB#J;R-Zq_nhtUmhV?JK!5Z?
zU;P+dHy;~;Vy*WUdw9+Vd?I%y6h@b4H++)xG=)H2^)B}(iiT`fyuAstJKNJ#D%Ky<
zi+z`#MYN&>?1^~bP)`Wd*xm`M!WpDN*V|{r6)Q<z={2t?)c~i^M)h=g*R19Nf=5Wq
zG|p}R80>i?g4}S)=70eSgC^W<wdiPAxB=44Cqnp<B)!Wn2ssA{kMYwjqeMD2LSPux
zarvo|V%d6;avZm06y<i`S`AYMXnua>aNIv!I^1)zy}pYOv*AQ?$MpT7K$NrPm-(@H
zk;X)Mo)U&bdUQ-(C0M~Y%-zSd%Wri`$!KJfcPwu5zd&W(6j_F8O&H}scbRIoT$gQv
zV#T8*tWZ0Qn_`w3gL@6bc^Ca{oJgD5n%OfM^=eDE13~B=nW%-^0))b_2Gq$-G1Ur~
zo9YcEtvT`L(_Uk7UHed$`Rc^xaHufLAY(ct{hG{MQTLXgAT7D{-yknhMoa4dLg--<
zYLso!d#o_;ueZWIA4o*TQPi%SwR$i?_L^7TVyDEmJ-69c@1w_dXm<w0aD8wC1v*?s
z1Gv<@<#QjnHhhiD8XH@1yA*MG5UfvU0eq1x;RpmFIL0BR9pXcD%ZZPnN4L07M{g)i
z>LqiitkQ*63>K%tHV#bFyFkKiEwyXBiB6V$$7@n;iQ|p8o>I+vlV!{xI;YP{Eu$<a
zM~9z(AZ&i9`mrnpa%FGUZ5jXA@mv|qh<tp@4)IKu2rARW(HsIdF!X!gay=2RV5bc^
zN`$$viFsc<k4VlUGD%l8{UV1}3LnG$ft#ST-S%;Ocu6XO0cBPs9}%+i<5j!ul^x%q
zq}xdnHWr{QWRGh!XZE5;in{$C%&sF2Cxp*rAq=_8trI>%RqY8^MoP}bFoH0_Gh^Dq
zXQ`bArPXGs5Z7B?q1i+h6njCg7Ma^klIq8W_d2(r%)7{S;?6;>pAaYp6xb{Z78{WP
zu4u16t%o~#P{=;Ejl5AaM~JPHJr*vaVtw4*#>9p*7~Vsi#d~7?P~l=38JxqpA0*cu
zB8$`bHenyRI@4nK49)Jc+kk6AO{p}4*3;h{@{fHVduZF9HO*y&*c%5@@%HJ`tSp~R
z%I07N7O}r?fB_N<?DO0w;9SLTZ<{`dH}<QO?vYCh!0a#)+&56&1#@eC*5vdcNho}-
z>%I%KQz2xOkY0YPvjDmf!@DlG8=u-1P9nL8Kee{CPEOu*dsS!n;7RSV?&)HRcD@gm
zuTf#4-zTdEP@mT;FXX5Pg6K6ksT6R<T~u)$S3wk*62tJw?!c88cYj$p`LYI<-{4iP
zUtg<Nc<OaBw7c4XB4qHP{sgs5|G3!uRoz*l=<?*Yk6ZoX2sD=AoAp^Fg1woOS;YyT
zs@i%TBbV}p@n$FoEa5XE&SBRzVJ@}_OvM&ReoF-hjzJe*N5p~PNabV7*FB4w{C2KL
z+^9rcjpgn^AA93?D>@KXPgCQwN)9E~tl7Fs_7ix#k*HcFHp(ZKLzwy!v~NT9KeZ<j
z(1!9J?k`4n4N~O8FAsXc0Fy>ajO%JMZe?tgS;H`E=fQ%z@TQ~Ba_%JHK3MN({CZMR
zsZKj5BGe7W=11TS{?p6u$KF0Syc9d3k<0_S@D%XB+y|-FtN>mfnVDPNloj^kY21a|
zcvm`ZDNRFC;T`V>5n@^6NxBpa74#+%e>r^4rpsedyVbPdjo#dxWI{fV<U`y;{K?yv
z7Qj}|2u!K<=*YS=CHO6%wH#UR*QlNn`UE_;Ju;k)L*Z!(4I5GAN?)*{c;fXDt@;_6
z=b{2i9c1Hl&w3L+J+yzIQz*oVC(4rfYm=IMB6fqAcc;6E?H~?8o6dpQeYl&G`V6x9
zuvWo-byYiLn5zu5f}f&ll!kT>UT%)9RWyorrLgcrX38whzf7?xY#g_d@B~wq!s{$l
z_YO^MOCvf#!tlsl-yDu%M=>qs6!9?O41X$$>To-_IIugRNOzk5F>}MKK~NFXz^(K#
zQ|i|RX6!g)Z0O0oQVwOV3hwx5Je9Aoo{<)w;rX*S(X7bHQ%^pp5Lb$Q&VX<%k8_90
zfKAY}*`*=YZq@3E>~MeKCY<q`;lzRJGDcDrl97Qh+7zi<Lw1Qz3Bakuv?6-wkX0TG
zRc|d$cS!Q~gEB_h;&mJgK6vwxQ__IjuSiQvTdS`gO6nD}y~9lOg3yOFcxzpdP_NA*
z=J}#eGY%P@f>V@DA5O5DXpV1T3|Wh&4MV+rBZ@B=lp`6<d#Ib2<qQS~LBSVz3gtkH
zDZcnI!N?Nzz>0MyZ;})O{aNnD(Mv@yCZ<C9{d)%u!jIBL4mOw|-PYb_@up#;zzT1r
z6E*O)ce=ZCJ*b{V@>`1BB8yA%(gbk?!{S6@esN$eM2$$J*ylVU97k%pQ1QUZf;h~n
zN_X<b=T5lEC@2L2reuF-_9{t)RFi_oQ{G1jM#>5>{Dd2G^$X4Qw+Q+&Nbi*`AUWjo
z;0&72GD9DH(Kr_M3QU!%%zrgFCn%kpZ<!RL6#WW?j%m~Xpm$+mpN8x+IShn;!|?%s
zzvm=yuyY!Vq<RK7ncInl*bplZ?pUz!BQco$zIx{)qN*=8cTdpNvnY+4`=8Ddou;s1
z#D>3B{NUIu7kKQSjdO4&{R(`Gs<a?J=><wavK8WM1cHL`2oy(Q*fa*$Hix}KYnj=#
zPoMR7uz%ia{CsMTht0BZ2bhxQ0v}+8{$pycsH6@|&hK`!z=5%#2oLxuvSf1J4~tKM
zF#9qIkI?ZL;!#SJJg4U!iQ@93p1GDdk2f9BgLJ4V>QK}R8ZPo-2}6frayRR+x1V-z
zzZHq!BE1Wrp~LA%xe$^myKKnf;Ir<JUqOsmw?h{U9@Bh=O%!8Ot;6@`#%FU$n=&bI
z5QmE`1g$r)3!T9012`HWAecXoQ(Qt>LQz~oQA|ccZ9!khWt<z$r?057MN>haFN0yM
z*PrX~p}{swbgaU<92^<xeK;9M8Rd%7^0T}6*s#iIjKF$|Qoi_S9g^T5iv~by{Ihro
z=j#t%ait*D^vLLn^Czic3_i>vRR|2l3JphnDhb)?%$W{)PgHS-Le@I;4Ub$}RM;wP
z;t+<pu<>C~#()wHvA|>KX7Wcz0UOvbUlwCgwuew>C@j!jUppTy_B>HTflB`%9oG3-
zs`HcT(&Vdpk#@0@IAp<e{1|L@DNFWDo*4!yhwNm_s-f!I+8vqBxruwZDTEXoB{jX$
z5qD1SoC&Z8^^?F^=_)@&y4SV{T3|)3*?JmBy%m8rcLWv99U+a^pNnRa`0Nmpe#bB3
z8RxEAr$|f<%J{x$ZsDu7PFJ;v>6GQiloYbj-gDM*A@>$CHZ3F?D(@)QyCQr>?SJ9`
zu?Z@73~L(u_y`m}$3eTqM)Z|e-`R4*vAe8_5IN{E?n{<e<UAa~uhNUynbX*m`##uN
z$-OHc)^LSdlA_jXK}UXk*QYOjwO5vv8Ye}j$!tVyEj@X@SzW~26?8#kNOcoVe6WKT
zUFE|A1<c)#e(@Ojg=pl<BO7)Y^YZPUPhY3AhKVIrHd;Hb+CPa7!jehcfqpfwf?%-t
zQbxb_v;kfg+=~S%7!(S(8jQzzSSHH{YF<4mQ$;~Wr`?_IC0Jv2ezN=_VV5t4k4DHE
z9|zt(RvVdD9%W8BEFu*HV;w4Gjykk1#f(JQ%Z>dTRc7?fg-Fkeg-<}JWO#DYh6plH
zRi9U4pA4nIW%gGZ#pSGKCI_20!pmT;Kd5zr4neQqx0I+L|MF#uTBCNfM&qWdL57s7
zuB-eKyM>OZ8j_1fXheFz(!h(jmx($n>jPU`#?U>r8eCW;GZa)3ED>Qj#Dmq$3z#i}
zv1(FM>Zq9cJaQd4na+sXc2Oi{W-A}LIUMIeZ`iqt-=C_bP<eR7wG>GwGNJ6%@4v!U
z=okvkz?>_!XC(5pk&ZKxc3&Eclrf9SBu^Uo5x9Aqv7_8UFyT#ujKkXUN%{}MIF!aO
z*sI?6^04U6xk(_*cP5z+iKVK6rM?!gprzVyNB}3t>DKfi#dU1zxJ!v+)p)D>jir{+
z=bJ=N%9RRWkqgV^2M0OgWw7MXoxW@xZEqjJ5kB=6z}5etpQ=Ck{B)RwSCDwhM^Nb4
z`3_R>`#17Jcwatpt`EJSf@#q<%<rwm@k7?Q#Tt^`>Sh#E($FdMCH>6Fx4^mx840Dz
zNxD4eD4GrHEVSyan-Hmx$l^>Y`PRejo00Gw>uKtv!OJGr5idcW2<bkW6mo&Bt|FBw
zNP9@(!=h<}8q-vtX5yy9DJOVWQH9yMO7uZeeGMeDvuADOo(XXHumDn^K#F6M8Ox0N
z3Mx}4;cI27FuFCyz31u@#yl|viWxLwcQ#M^%sbPAm^_5mN4oM7=-p{y)O}4&V+KFi
ztULwjW*k=7Pa@oQeVDs%pM9IXP>Ya>m=S+4=7pt3SW_#0<evNfjUb9H`CTPLM?<RW
zhVh7HA>1z_q+s3AjQSF-yD3q~4DAez*l{~A{5-n6;(fV>%=9N8cCtUTu16sdqwvsx
zVqt`Lb@FCR2xMTQMyVf#5jB>>)GOe75L$4j#L%-eN+avQKApD=mFILL)(JwnmPqMI
zIRt*|(p*c|%#O+Y3=J(E!IN;@S0^qktn&-VqJz@!8qRVEaCtVQF={YAoays5TkxQ}
z_Z1%)-BzwWg`Qjf{EEjXcGGGC#0nbreL&vMHs!iZ5?D4o)l%mjR^arO=N`|Owa-)p
zn}9v9ZZA;XcT`r-D|AdJ``m34rBIq;<B@&;B(6#QIj3iCNJ}*0XktX9wV+p&g#Z~z
zmkcke;A6)jr5IF1F}&tu7tf%G9V`3RN&5%Sti+8{4)tP+YdTK@KLz^s2)=#!Idwov
zNu}lCF$oX#gPH?~1t}*AusAG3LKF`ODU#~p#ejz~x5x}dRnxtj+zpmC@1IVqMb#qO
z7^yPTchzEG!J(J5bC8=2ljtMP^AK8%&H5?qS!%$uJn>^xOxA=D%U;_T-r6S0yH)Ph
z>{UFbQSdbDVO|O{>gr=oDt1fjxEr<4$kIhr;yp8R4+(92urqu6bCRNV9rXm})*L)-
z>Z;bkmp`cqi#5WldW=Zj(i%mRpZrXX#`;Ky(2%=#S{=)Dw{10}*|yuRZJbkesR?6o
zLo=GAYb~mBeuz`&*?~rTjz^WIT<*I7Ez-5@xgnDW8AFbB1q~x;6ck<7+E8!R^0Hh%
z>rohXzA}J8rcfF-oR!T%?4n0u_w4p!EMyG5MUbqf>X_tPOYruzTRY};2#vJmUTGjP
z*<c|d_u<Fa7<}P3^h=CSwBAQb!IeHeacZ&D$3AhGT6)H<kt#L&P)^dSWsQE5MUBZ@
z?KEm2Vfsn*m%35@s^F9rP{!3Ei(7%ZPazO`?V<Sg_-a4#wY83VkyeH7=9!lI8bGcs
z$CxFmEOseSL>Jf%NH<WHXuGjGGD)fsY(a}}R4WHMO8cO;f0;geE!~Zf-rGCr*umQ}
z)K<we$6(CD%g|<;%cb-Y#Aa)m8C^qiVU$OKOWf9;AJrleCu@nAJ$sbiOKSuDmFFvA
zlM}*}Z2wnqC5jBnxR92V?BJ1_7ENOC7Q535;sp^kyqmlJ*$gZ*^A<al`r6dHn_K<L
zDJKQ+MMPePP^ww_pnIQDXIZCx450bC@kfGLLX{|Bopm=q=qf95L{2dcD0NcI>)*sF
zuFgp*3HDSNb#5Y_P0-zDXzzGj%b9Pbx~hXJzuU}<kY%S&B_*y}lD3>uTlngOUR-@S
z?UGfuv{%!tn7f0Wc!}rhPixWc?W$g`fj0~V+imuGVYmb3yXZT#qq~nw)_nbtPQ6*V
zSCEw+*$;L<t&&UcO{JqT8hnwng9dnI%=8QMBDm<f)+4&e<D@71yva7*yYziAS~~Jk
zt&>^tMlX}o#kN5<q#v*@7L!%cpc&&tLw7yPAkfrWjy*Mt8M@DXf{yI;&`ke%*g6(X
z5UI|y%0BU&8n4%H_g$OQp0#;7OsdD3y}H?k`9yu>&KaR!(!P7`?1wLzcgK^-LEe-i
zC#UQw#fA11ZfSZ%6d+bhbqA<s_+bzxwNBO5=0Uj>ShMU8dNYQvcD#GRW@3UH`1z$W
zu=RZwg~?q=%7#Fe$vgW(*|p622LWU=8@Q`#;?c9^sva*t`zrZcI9CzDN*o79Owjtv
zY!ecWwNbUm?H|No$ONL&kf~Kj1L22p?MPc|_)#19I-=)d@iQCXSQ`Ago)z+0PXg`y
ztk<TKikZR55Ojg;riU@$5L8`^k)BYi*~m6evSi0p#p&JhEe6-}r9oBIZ87nTo<&2D
z4c?z;a;fjpUkGCCg8sty8uCN!huWj%!TWUfPy((aB2rw`eYbj`1oCd?WAz7EQ!eYM
zEU}(S2xGs)m;}=+DS#*pJG<GRS=0~`pG{U?vOHRjg)xKAX<M53_)GlS-1D<_l)Dw^
zL>p3WlX$tK$@mi1p^$;tlsfs9D0fa%N8~ZwM6h0AEvP-oGYMM;UNLgMwII*#3>ThO
zbmtK*3?%nT4xeVTML~d9U**VzrgiHpx}9A}UhSd|8<T@MuVrX850(RLdT(?iMCj}<
z*s3}SgXk`$^Rrv0`BSbjk=lj@`4Ri4{&~?|JLB04QWU5j>92K*n|8-egGbh%i7mrN
z>(yp?ZrfImf7uadKQh3YXXa}iA!@vN8sJ1rQh_TKtI9ZKH+;Icfe=F5ahshAR0!GR
zb%c8J>^L&tS;-(CSgk}|a_;AyW0(B}mYo_|9r?HYPhJfKg^2~YvGR)c+ydpIs1sIp
z6gnoW5`7!n1T0AyMT>khT4RtDU0y<@oup63B_$^anau|mCxGN8%co6CtpbNumW9;b
zw}gcTBONUv5`Wmg5~gjE!Vgwyn8Nb%@T6iXr<`T5)q~4uK7mj1#!IsoT2D8$-wka?
zN3K8c9o_7;<p@XY9Y+zdwd_-N3R=HId1QfXzIw=&A(FQo(3EI6gIlX~WSYbX8fuF7
z;^QMt9Ly)+S<h$9%P?s-@dMoDtp*!tLSkAB!6`twi1PT~))!23zp`&ZVUarxHCfX<
zOdT)D11*^-q`cXtY!AysRI*d7F{43t^U1LelA_U6j<_a=t$0|#lRm0UJH86n1p+t5
zv|KP=T2_9OFH;|h?MTyeo^HRP((g<uA9ROJllNX!BeZr<m<6R(tLl47#-aTxx6FKN
zi6^f$<emoc$52)VX8Pw@;f!W7kA`NWHRQLd!nnrscj2<CH1EzI)mZdnkp!4J(5JsM
zuA=aMA42NC?T!$T-dt>gu}#hSn%j`y7WICqyV&el;J}(Os<^FeH|S1Qt!O~;$y(;~
zK;n8)*Etgh1y?uG38wma9mup^iwUd{A=xCMc2I*DSi3gS4gCAt9B3+K8UzV(u>s><
zo2oGPP4xWJ=|0dsChcjF^1}!)hlJ6oumjnl@gxW^)<wK&k3?1hWr{}`DW4x~tOF?$
zR}ThK>*L^oh><$2=Qm4_fmopxU{l4E4{Tx+QUpFal~lF&F0gzbPPw2|o6cX0A@M=G
zVbgX_F`~8d;@Tm2#r%!7`(C%mhmZBZyRil3Q=pK9Ny1=)Gs$Wtd|~FEyKonK=L^YB
z?%(NwQE17DtibYJ7ju%HNnUuR!M^3x8pKcc#0kQXY)lKUl;q{$&SH{rm()UbZ%Xo;
zxKN}U{Dvb!j_D|B0eSdaY{-*{_bO&#0vB0{!f)Qf_AjL%>6H`>bb+SDnn;u5AU=S;
zp<@RwJ#`TND4v_$6g}i5oe^Ksgm{5qrHE$Y^UA6me7tii8)s306B+T7SMH4;l~^(0
zHGOk2`cuzhT;3(5)x}tcaM76-ha`1A)F@eDaAI;~G7(4JSwPp+x{F5b!)`tz6t0R^
ziFlN7>=)DIqO=qGI$%J+Hg5&5_XefTUh#n(ZfvMhSG0VPnj3HMd>pa!a_Zag95CB>
zJ*i0iWZ~DoXW!qS2i~FtCh5R@_xp8Wl5S_>Zf?)~?@al>zf1$%_Wfb|w_gU%IA!{F
z#wnAPwYxdf_k&J<PlfL<sGQSe{Ff%9DR5%y_u;{SnAKE>$9lSuBLI5=P~(Gui2nZw
zJ381gdD_{oYs<NebD}h?Y1wiJP_R+aj`LLKTBx@X-CC8#RkKb~gCZk^gM%#wdC_Ke
z^r03+<o>&s$cOslDTcNtC6NxV3>ZWze7EbM8aW=&Xt6^v3M<jLx}eRxQhvCbEDe|N
ze41rI-qCXik@*7{Qw~HEEgn2<qHw0PBjebMei~`Hd%|ck){@nlg2K`{yHmsncb2ek
zSmdxoCeroXI8I)H&AkEXLi(x+M<ANpg6f8hzY~TT7Swy0Both>RO4xHS{>E_lEq|M
z4ig?p{3QP7F1RqdlbW>0OR5-5;ks`kLdg%nPaeA}9b?srK$cn8^em1W<vU3}Y77n$
z9VmB5dl0&aS3;K0poBXU&ElR|Kt|HY+<OnlI$-tnBIr$hE%4{~R){wSc!l5t4!u92
z!w+M#!sbo{+@dHWHuQuUS@xZ!)qtZt$}>j0O~~j!4?{&p9`rb-nl`B*oRLTJshn9N
zwUkwUZte(usYR}62<!-E6#dQ4!H*&R@J}}NxIP9;ZB}#D;d$dVFMaA!s1*8W5Okx;
ze@Eo(uEQw)XD2t<$y03h<N6U_UkHrb&BCtHa<QPzW+4)IBS+by#_!V^!aJ>BzhP*8
z>!}(QBuZwX?mR@u6OXHw^%xHI%_uVNP{n-=UHgRvF8-n+t1=hbEcU_TcGW^3JKj?^
z*7Q0<|Hwe(Ccak-l}Q!ynMY%yCGq!Z$By69JuTC1YkEptC|1@R+Ez7~B|xXv+8Z}n
zjTH@f;8$F%)B;yGR$Ek1#OV8M)}oDFk`J9l!NA2M|DL;}oJE{-zTgNUd|ryQ%6xrQ
zpd$SlI<OH)XmkddHFUgWj#7q&DVj9~j(|gf);O((C6h&$kl=3Qc#~~7s0XD&bTICT
z^yiGZFCt8=#4C2tm7EAuX<!po<PF#}QSTxAb0j}V2izS@M6)K)kSpzwk>t}_hA8Zn
zqjt1U8AZfL9EZS{XUiq9=~9Sj_h$5_4dU#-`-;%kA+G-x(nFFgp4Qa)f%lZXRxchj
z5h%v=cBq<g(YqXNLeP`0^TcI6+iI-MCGhWgob<4%Y_F5D#Yv$qw@*tiPr6IB_!T54
z-K)SaH0I;xMVO~c8%%W@6uu6eBE_&v#RuY#U{9ZuTBxIEdX#;7AS#2+&dV)4lA$h`
zD^rr?Lna=hN=yvN=1lFG?L_UE=fZ7Bo?L;hO5+<=Dw+7H7X0bZ7OS^6IkI@>zMmTu
za<HCW5fw^|ojvRDXQwU=h7d~X5|rwD=uZk*Y>^8EY(K8Euem*lDDa^V+(=ra-{l}y
z{E~tBDc#Hi^C?Cx7MX?;;#4w`!thZ)znv`3iZSl9`^{Z9*5eGjKHQ_%?B!%;9Jkg<
zxichE(6U%^n@CRQ1ZK*KNGWxPA1z`-bfNqR^{(SlfFfmd^zBFWng?GtSc^dT1wU*G
zl!tzdM=jcpB-~)8O_1UDStUApHfGNxnLB-o5!k;_KNe?``rP@^;Jxm>!D-y3BbQX{
zvQX9M82D^-c0Qxv935Tr(@_OSytt!y{IOza+W|YtVJe4fXRf~NlUk#n<jATCR}NTL
zZk$yvA8>8#m4Bw9zSp@o#pO5LTwfRo_ehgieWy$s$H-uRvIff$+H@ho)UrCTme*xL
zYJoP|Fz3~iHx-9?>Z4lzdh+?N-Eu%FrE~4OlHU$4jxm?I-yUZgWwnLoyZJWgmPG(B
z$FOYtF|Q=!z+$Od_7?KLK^z7oHrHI@3(qN;D-dJ-fRD`oKh`=rJ2;v<yIPyOaD<h>
zHQzuH-v1I7*o!EW3lrQsn+5~dYw48*+7ZtNb$n-TdV6}yuyUzeHrTSxcT+l^&9%~k
zI>)MVd2)H3`{Sl}_47)5@c7+$3Z-{dP28b$8@o4@o)7fPnwXSkyhnM_53C+|^f^uW
z{SN$z&}Wgj8F*zmP%sQ|IDichkn_&<*MI!;7wq>RP(ap2&VTrx^?uw21Hud3#&1~R
zHVFJeF|eKy<NIwOAQ}GDKi{Sxq9`LNp{CBHAo+s=2uKVd)t_zx0Tx95bDaaz12oUi
z5WngU_<wHzR>G}|DExEBKc|jgb>sQMxo_9`jqVq3JWsn<!s7mW^H<o6OYZ(RX<tc(
z@B*3ftH_wzT3<=({J`~Z*Ev5}z&XG_AHROi&-W3XlTtIcGqHEIHWdL5slM%E?Q$h;
zqJK$$<@V-Pw9SBX-mj!}ZWiCJ^KqvBk(R5oiM@-3x$~7o&-canL3Hl=L|t4>T(8#j
z`GK)NNHc+7A=j_Ge;=>4ouloQgQonK@K>pN{*khasTH8KD@hVxAX$4ANe2fn>#I2@
zxj^jTDq^M%c6JWumGh67@~dl~*UsOrbG>r{p8i|=boq8Hwbi#{sjsAZ(Sf|LqH1Mw
zwGEN{JHD^#sJx1lv#Eu(?bX5~zd&vGDr$Bnj?U(0Zl+fg{1IHg$`2^{f0myq;C8kS
zSBFZR3q!K{4TV3&8QKd}Qm>%$S0UzNKwbC^**``XvJ0al08WLuOiC9W_4-z;e=T}{
zjwu&o;PY!y{bM*Gxxo6;RYb25N$@UEqXafGxJ;0L4kEy`^q=e8Yz=-x=Nj?jqC-9U
z4WYjX9T(kU<TnKW6g4jLhX}lidYPQA5il-BGRfZ%axph`bGCN9ePvL*n6CYQL+Y}y
z1M{^aGieK<Rt8?Eg=Yl;q5D^Tz;}j!{V%lsQ&yaBKP6^s{p}UnACC2n?#?T=_AFr0
zfg0(zV*&pqo#C%Ra#3#oq5Gd$BIaxkWNvkno3`fC4i2|22jswINIaJ$GGNW}|Dt_m
zM4$O@0l#jn^>fkWW$t|bBF^Q=%>4cG{eTOy0h@M7UO-0R{#)d4tcn8>{w9F;dv2Y>
zHB`!gvepqO1*I=w3Jd)$=4ISo&S_M7sA?%7V=*8>{V2oEjYU`a52)uL;?97s|JmQ<
zS9?M68o@sVNCT%bfdHoX{mSsy*13Z8*XS;9;&uC+{<rs}E+0A!7RRa?P}XPxilX^W
z{e0-pZvKhBvWfL?Mm=XDY(EX;uQ!0D16KC^%J7%7_!CuG7YBPab7ygL3YN=<e4Fb%
zf))^})~P{2epLMDL-w@&6Y)QZgU2Lr4TKT|q#O|LMNQ(n{)zVYfnPrC<BVrrYCu)q
z0MtPj-N7R9Po#egTj{2axhb%hsf#1<<=`x7a{l-2--(KpzkaI|&~71MK?2{ka4sss
z<o_A-a`xKP7MQ95m@^=!h+lvbP5Ymr{$cNOM4XU~4isSSs}C&R`Y}T}XU-t!Pl)G{
zME$noZz5L-o`%h5fCo2VGJ4VJD$D*v`G=~`<MQPrA1q}b3<OM}126@t3$prB{wMn1
z=T_fJtbY!URXd-<DLXs3TbunZl1%B`U5^I93W1OC1<<*wzXZJoT25ZqSqy+u419Pm
zpbb`E8%+yH^XAUL7ErF{p8ss-_-lMTMWYNT2E+)5@a?Rqf1xt`>uRozbFQ;*SeNT-
z+3roTDPRj8fX=x7MF74t{F`1~8$<$VHMrjXeY&JH^QLYF0K9<Eb`j)u)3rfV%}va{
z0bS0Cq-<Mi2p}#mz;7;sM7_Q?$Tt%=`K_g4vAFtJ1DsR=IYsz_xNdb^8|14#zOh0f
z>Sk^GTQon((vcScN+<BSXlbn7*G4;++aD~AarP!m1%Lqs7{V_&J=ezhnXBKVHyns+
z;a7lq@Jatu!t`Dn=j%-ATu(pmr*@Tzk2RN;OaPgp76{?Mdf4w*hQImyzeoLPukCM=
zrT7sRWn6z#G+-xMYEl4213$pL*!KaPds*4k-wok{Hf4Yw)aA}#V&)so2zXlzP_|tR
z!#wkU2YAlie|Wwe)cMOaMKa(V0RX2Lx$Ii|JJ4_H{3km8p3AZ5_2U8numj)}sDZy<
z8UF2`t_}Dju3YVmDf<KTr2qst;3PcXq0V(Uxb?q){l-TmHu0;=0f;w%#R^`4nb^KI
z%#VOfaaG7%5*9+B0dO7z8AkX5);drl{5;dWFk`#eU-?>Z{L{s~vZztK_x{Ki(AHBR
zb^^1c?^lMu%fYqLeu^@e8=+)PF%vsr50SuBiQ_xQxtgTE{0ZfsisOevUk)J`{<;Yd
z5Ss)5bJ5QGz(D^Xwtspv=Ma+C=C)>PU%S2(z>nsZK(%{0AOe$a-YOuueE?A60#C9)
z$i7-nKLLKj(r~r5b)ir&alA71w3@H-6#<aK0Hpi{$OPE`5mL;-))uJjtsU&IL?&~M
zef$J4NKdj~lTk6kUm*V^-OGhK|E`I<8i>c4<iFyi<NgKCPeQ#MXJmklumO1F7L4_)
zL6%YeHO}P_q%g72;y}!}4JhoQvRaw{8seLMoEzvj)~-~RO*=Nh9U!kxq5m3zU0D7C
z`6p#j{C@7zJxbg59O$^LFnl{0<6pA`rrx}N0{h|9Unk&~%TahSJ1Ptj1jGqw``!4L
zI`Ez0FDU;ffNzQUsyZZOS)|th2pcy5m%7+Fz|y^f`nM*mtckmc$XDmNeCTRr;oLZY
z`a{kEE)2cV;0ogZbY{<`bFTN_O}6u2Yw|M!y#p|lU;7eN#@DBQ`N-q?z}?FL<Fx`t
zez9(U8hj1fKxP6ulIHfVVkST+rC_@pWP`|(M+68e_9VYL;fs5J4RSdIHp||V(sK;}
z>b=MZf81X~P;guh^7b}8ggp>UD$#zmA@PJigGe|#J2?N|zqSqNMHc`~6#qvPXK8;X
zF8zxpepBC+$gJ_X1Jks}z}f`q3x>**{`VlifXbQwCWD%h-B%X}lp_itUsMj}i@!%@
zzg#&@62na&fZBH#$SSHASS!r^dyud8{IvlN2v)(|)kF<why7#gm*b01ihn={bjJi3
z$VDbkfb|={EffBY0l(;v^>ProQ0n;z03ZZNXKWXkGzYx+k03yx0m^!y!DH|0ayh`q
zTQicHfSS4h1Gxww-f%qt2~SgV$MZVlasa_C)h=E@O)@|{V7b7-TJ!Y)u58=DdguxY
z16p7J5{cLa@~-VykpJb;mbjap-PaDch?}d`)!na}ZY9JWAm|JL6|d+8K+Ntd0M8$N
zNt-x-n?;KOPx!4}fsT~2gNrKwXKL=^;_#cv>?CXrk1<fgKLYSXF5p?cy#nu_hh(Z^
zlEA}tp!`(*`cV8^1OHp{yj)$R=BJ3pfILkBqq`_iYG6gpZw>BpxSx9lze{$<(&FLJ
z0Dp(bzw);{_5T9AoWBmrgoz%2KL^0xg)fLx5eUYA$=^>i^~=#JbZVp00Lyfz__b|*
zd*uqWA5Rm{ONH}J-_Me~9LjVtr#}~P<W-<Pl)J!~>;AQ&ezp&auiSl0V$LR}w|>_S
zt~d6Niw1%{44}k|7IW|TTEIVT8~o39{Xk;TG_iI2P1BpXBzX7)2>PeMquGnkB5t2u
z3s4g9I&<gq0B>SxF8ys`%;iE=)O@iP3h1v2(BH)_!~i_l@2%yc{(ctf<uGtZXI3<T
z!>IsK{^E?H824H*{}tia|M`Y|Rh67*H%sRaDDDXmT{tgTjVSrGkk1YD>w{w%dkcrl
zx$8pNq!<AT9S|T3T<o!6(_IVWXEx50fr+*K?~D<fHY_O|;N_U{*XS(Ea4oF!aQU;d
z{Q*xb%1GK7ke@CvBa^rwKQ4i5;r-JD`3n};<=IM+fO(nKjbDpv1fb^nZ3O#alQO_l
z5NBYe;`tQha*e6ID4weTG$seclZzU&)3_GIUq~>f#Uqge$fs$*!?%kT=&SV?SilJ%
zzqdfa4EkDJfS3C~4RWzmgE6`m#<`V$OQOFQnq<}?V?F?K7YI!kV}-lvwLpMEz|tA0
z1XRr(9h?CbU9OuP5ub`4KsN#al-31{yKQwXnE%F#9|`7rVe$vFZ;GO?u?7Zk@}Huv
z*5+D+P&RP}`rN;Z7~r6XsZ&5ZvEBbyuX1s?7Wp4ud|i%a)IyXN0k0|t76M#+C{vbs
zEy(|f^>X!z6zMjY0Kwu2D7G(J$#&(naL!HfXZN}sW)6&d$pWwvc%ak~xnL!^UDty7
z260{KfxKsA9tXlZ6(GTjVbG!HT5$h_!JirXg9)~#w9cKcP!|SD5B>`r77SerQthAB
zUld<gw>bR%xuE8a6q|=YRn-PCcd^H<K71{tbCsQ2<nLpL(^`Gl8ekPXKm@!vsbHJB
z7Q{LEzsMn@v>C9vfZ&P%AHMi-z-Rkfc;6KDPtg5cX<q@WV=f3ph)?9dqA=}V3q{7>
z+SS^`*4oSbYb|=YscR#kSKJ4983ybRaH{WDhJQ0CuvHK6%ELb|FnoOv;rqJ%ANla>
zOyBwU(P%S?hFui^cnApVV)jUexE8?A3HNuha#;^rBn2u>E|OoT$zssg0{PdRFBcNo
z#Hi3AF#hw^4Hs>=6ytj2fn`E~D#U=f$Zt9ch}xs1M}Q90fb#2NtLY5)S`Zgvz;z?f
z{<`!15TF2C08lS7W<+u=)UTFxW%U4$hZ>3jbO0%U)NnD<a8q9k;@tnwbL=0diwudk
z$Oiysh=5RV(Jixhu8s6Z6mmZCNi(40G6v!q>vwlK@4NQ^os?@h%sD@5KaNHHbtO$_
z_+l9}K;Qa5hTt!KE&BgSrI(%G_ABc9m@Ih>AWHLKf7=KCU&b>0KPml>s6UP4yE$I&
zUUY-hvco_!q6S<{{a<9@JHx+N`+o#KH<-VO=xl)n``}o>2!LlDlov*@uX}L>rvJR%
zaQ<$>xh8+R!q_A;m*pK22uKj=ud@IFr{9zO-xe2#;{*#S0oudC`*j6{gWq3ZeYMPM
zuPfevIs9@8a5pZ%5iS-<<oEvq^twxmF*Hm2U!MB}5JxUHN{pla0`4*%FSp7KYSgn<
zK&bM-vJ{#NHsSK@_kid0uUbePF-E!r2{bEk07nC6+25}Wf1ljTsa|^x@sWA1uRTz)
z>H$gtYKHGuhJWw>m3BQqRaI#mOWmy%id8Y978Mg*HFXyT64q4|6cJDyLNm>Vz=cq2
zVbcVwXN0-pkeY^QB-2w1DgS`3)~j8`DBX5T63|S{v|`r9YKH`sV1I|_d-s0#oqNu?
zbZ6c$I&;6@`Tm~oocp`?R0%|z(}&BiJ5qu$Cw+uz@3(GoEH797O(4)sz%`q#8?J?)
zT?o0&2-gurZnHxmmzma?(|m{B<GVd}IkN3gqS0Z+M+IWt!{tj|cHqV7tbeISaiU?K
za7iFl8>}^|a8uvm^H0Nx`w@9`66^e?CvbeF>K=S<cMTA}yUX|}eAMNhpa{7%LEBR9
z-;0nRjV>UVxO+yc08GpcK4Z^!`~+do_cG?uq)vfQ%`N7%;F!!`9QZ3dUIULulku+U
z5{T|GBlwH<jZbX_jsw3)f|qkkZ_-h?CLc;_ax#z=$iV-3Klu&zmTM|<k9K>DZdCyy
zOgDaDoeW(UJr;IrfWK*XG^ei$1oMw*$92W7>=RjVc^=fD@=xEcB3~n$@yGv%yt)$~
zLG~<kU{wBwek$@cf*xOf?Zc}V+hCs*JV2rHEACK{?~Gq_&hOO+fBEra7(d&Urm>Va
zKt+DH?VUyvGYqdsEqlNlada4p&{&EXqypr8ipF*+OgZIWdClxog?#A1k3y8(qXMDV
z#pD71_xFAAh7CK8lkm1OZ7Ry{Re`X~?=2bj@pla<?;BBkXOdihZiFR3-8#i-N)>8v
z)`g6)MnuN5SRq9d^kbuc9y&kT$Gm?2y$VF*I%E^w7Q7Lvf~RGZI2c=Adtu5x=yMIf
zP@>mQ;TCaB0%e;$zIZ?C4*DL$#-rB*DhOKL5t3XxDu<M@7LIjXG<|Q2RDn_Ex0WRQ
zH{u0&CJ)g-w|zdHpaP`JExzmh{@BtS4!1v!mVGR7$<9dv07X{omwEdN8!`Oe7(U%p
z8W|^$Zo)4$@%fYGO*wbK89q>hKF3L&p$4L-3Swdtux6*V`~CY86uJzoiNst-lhm+u
z+)gQBwyv@8?cG4@g88NrwBEC=qbYJ_-yPf5uoP{<@6mJ8ay|eQ8vVuzX>)Ww)0vYW
zbY0ipnXndX?p0V-P>6;{)F5<L<U`>6<+Q=jA_}WQ8rRiJtU&OkXFQy@Yy!&6LO6#y
zX6SM&(%D{lPWO!9R7l8+O}{uNb}8b#1<^pO^aoF?f$AJ1pv1m;a!dPeY!<vV%1F#C
zS}DNMT6O^&wlnuH*<&z~AA(y(l8Ao3SRmUub&49!kwZou&wz0lO`ooTZ<O){t8rkz
zEGSq#2wu*IY&zgK%lLBBoF6t}=3wqMTU>{JHuZNQL3ndvo^f$~Te*^8eq<gg-&Wqj
zA`|1KjqCDbVzCCQo(bvo+}wek0q7-v^f%_!fm$o_`J>-7X86@yWNqcIjb8lCNuhKJ
z3w6(@V^S}|D%cP*SmpE2g>nsCP%~#1*ZZX)2fYelnaL!qz0X;aZ@@F<o`yBF-Pnt;
zWUo?CH-CG<5}*m~v?e36`5P=7E+AJEh(h09vLt^pV^CXSoQ}(1GWAaQsR^w&RW0JO
zC1?|}>79<aUEzqaqJhTpR&qrw9~q5>kcek`d7tBZ%wS%Xhy(0@x-Yvepj|3kLNT3k
zwCl>taLFF@oT$w1%WkXfkjfS=;4=M#N5sS8VR$k}8z}oNeYi7z&xxfM=N;MFg`llR
zze#Cr@qPJNJ?4~7tUk4QG3LrrK+z{!JAC+1e14~MFVi^%@yk~ImiUFKFyM5A6*XY?
zKr2XkVt`qx**Kyora!c52a}X)73kknEWTE2?D>K0-I8EvMHe|mfmV=oOJF`wLDcrr
zNMvImx*DodG`6*Q9jE)7Hq#!<$YE^erGL&`@hGEbi)qbsLk1>pMP2D1;QSn;D~as3
z#s~@0O(Nx#^z8IS-AEQ-1A_vmHKSUWB7JFmoS7tnHC50oKIZ>W6`6oUzA@CeF@0|g
zA4}s1u%1PuNjYh%e3x||pY`|-6uPr8W~|GK_-nWQBUuGSpHr$7+^b*b-(CzWwt86c
zICe^TVWMfKd&sH8zKvLSD0w92z77Nm-QKT$NQR|OybYUqVs!z0<v+~09}<=!L($r8
zQDq7~wIr7<gNEUuDP5@iDp!W!X|wMC(Lb)`2S?G0v}e|$L@hw!9Y=!WrIj*Jrj~?h
zTh-Jw=scRa-iQNAF3T#AiPsNaLcQv+A50IyGU#he<aDOmUMPdnn0d}<lR%}mF09RA
zH63m5L}IX@5*d_rYV9(=apw}D*nIegE{$99Z9Z`x=}A6(=i^wPweP_@*bXsx=cT<e
z>H7IkVzQ@i9sX1eOm-eyq%_9t`_*8CY?#XW3Hv&s#p{^==vM#^9+rtWb-r22err=_
zMHS3dh=N16MSUGIFf}^u;5M%f$Dz*sKuIP6=66Jf;8_N=DZ)({k$7v~=JdJ+z&_^D
zyC&7h@WmwBf1df@&<eD}hqH~T)ApfEvgRmNJqmNYPydM2S&f=NH?F!cD~VIb!;bv?
zne))!7xY6N*a3<Q4Th<Bfk+I&il;t@_z2Ob%FCWaFn|(gXt#Fw%MhH>Rn4_?NoXef
zE~hU{M(f%W0Wu`QlT)gqWgjkjCLVg>6$ry-bJY+Tnu}K`rO9??Hh$8KnzI+~r?bNB
zAQ^~7`l|Qc{lf4fg4bpw4&D3T94>=$`bolET|cWdF$NhqILHVPHC_gwL|Q%R822ak
z(o_>-fG&sYVr2j_zN*jN6%!fXV->7Jw+Z&d$z<ziF|(pPuX=9w2atajlMMLE?#phQ
zHA5z!<>Afsg7C$wgS*zX1*8A#KiIgW&q|VExFVLH<F?63@!lADGFq_7?y<A}{4Bmm
zE3P6W^Hfv4HQ--f&jRo;0BKVZmnH-3ULXpm<F|cs<32$V88F(I+J0Fw>C72QywuvA
zuWor2ky_(pOo#FLDj?Ez?uPnf{j;(65d}@4i2JhJLRP5&2-v8$nqH-SAUegv-{;rJ
zM0-q3DnwM@!ZTMAu=w)@KW@5P6Bb}G>#YOohTsl3eqg^+`9t$(DDrn9?UM-Z^)1$M
zEznQdfd|#qUllIKzRLnM95A%|vfIXQ>#H4jFayW-CeDu0b9Z?M{km?q+v<1g?oRAJ
z_Sbl`@$_Bo=9QJYoAqb$Y9bJF7`^Kj_7_Uryx2FESG=ne;X2Vs`!2ij<`CDt-Jd<*
z<#{vei`fZB=2EpSCN`uN3sTuD4<08Txq$d*9=SBI+hQFax|<H419bBQB+b_Rb3Zh^
f{YQQ_-V^RqKxW4GLCwY0%d6LhG!QtBvVZ;`@8iXe

literal 0
HcmV?d00001

diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
index 1222fbabd8b33..300b1f7920473 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
@@ -813,6 +813,21 @@ class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter {
     sql("DROP TABLE alter1")
   }
 
+  test("ADD JAR command 2") {
+    // this is a test case from mapjoin_addjar.q
+    val testJar = TestHive.getHiveFile("hive-hcatalog-core-0.13.1.jar").getCanonicalPath
+    val testData = TestHive.getHiveFile("data/files/sample.json").getCanonicalPath
+    if (HiveShim.version == "0.13.1") {
+      sql(s"ADD JAR $testJar")
+      sql(
+        """CREATE TABLE t1(a string, b string)
+        |ROW FORMAT SERDE 'org.apache.hive.hcatalog.data.JsonSerDe'""".stripMargin)
+      sql(s"""LOAD DATA LOCAL INPATH "$testData" INTO TABLE t1""")
+      sql("select * from src join t1 on src.key = t1.a")
+      sql("DROP TABLE t1")
+    }
+  }
+
   test("ADD FILE command") {
     val testFile = TestHive.getHiveFile("data/files/v1.txt").getCanonicalFile
     sql(s"ADD FILE $testFile")

From 0ba3fdd5992cf09bd38303ebff34d2ed19e5e09b Mon Sep 17 00:00:00 2001
From: hlin09 <hlin09pu@gmail.com>
Date: Mon, 13 Apr 2015 20:43:24 -0700
Subject: [PATCH 93/95] [Minor][SparkR] Minor refactor and removes redundancy
 related to cleanClosure.

1. Only use `cleanClosure` in creation of RRDDs. Normally, user and developer do not need to call `cleanClosure` in their function definition.
2. Removes redundant code (e.g. unnecessary wrapper functions) related to `cleanClosure`.

Author: hlin09 <hlin09pu@gmail.com>

Closes #5495 from hlin09/cleanClosureFix and squashes the following commits:

74ec303 [hlin09] Minor refactor and removes redundancy.
---
 R/pkg/R/RDD.R     | 16 ++++------------
 R/pkg/R/pairRDD.R |  4 ----
 2 files changed, 4 insertions(+), 16 deletions(-)

diff --git a/R/pkg/R/RDD.R b/R/pkg/R/RDD.R
index d6a75007a6ad7..820027ef67e3b 100644
--- a/R/pkg/R/RDD.R
+++ b/R/pkg/R/RDD.R
@@ -85,7 +85,7 @@ setMethod("initialize", "PipelinedRDD", function(.Object, prev, func, jrdd_val)
 
   if (!inherits(prev, "PipelinedRDD") || !isPipelinable(prev)) {
     # This transformation is the first in its stage:
-    .Object@func <- func
+    .Object@func <- cleanClosure(func)
     .Object@prev_jrdd <- getJRDD(prev)
     .Object@env$prev_serializedMode <- prev@env$serializedMode
     # NOTE: We use prev_serializedMode to track the serialization mode of prev_JRDD
@@ -94,7 +94,7 @@ setMethod("initialize", "PipelinedRDD", function(.Object, prev, func, jrdd_val)
     pipelinedFunc <- function(split, iterator) {
       func(split, prev@func(split, iterator))
     }
-    .Object@func <- pipelinedFunc
+    .Object@func <- cleanClosure(pipelinedFunc)
     .Object@prev_jrdd <- prev@prev_jrdd # maintain the pipeline
     # Get the serialization mode of the parent RDD
     .Object@env$prev_serializedMode <- prev@env$prev_serializedMode
@@ -144,17 +144,13 @@ setMethod("getJRDD", signature(rdd = "PipelinedRDD"),
               return(rdd@env$jrdd_val)
             }
 
-            computeFunc <- function(split, part) {
-              rdd@func(split, part)
-            }
-
             packageNamesArr <- serialize(.sparkREnv[[".packages"]],
                                          connection = NULL)
 
             broadcastArr <- lapply(ls(.broadcastNames),
                                    function(name) { get(name, .broadcastNames) })
 
-            serializedFuncArr <- serialize(computeFunc, connection = NULL)
+            serializedFuncArr <- serialize(rdd@func, connection = NULL)
 
             prev_jrdd <- rdd@prev_jrdd
 
@@ -551,11 +547,7 @@ setMethod("mapPartitions",
 setMethod("lapplyPartitionsWithIndex",
           signature(X = "RDD", FUN = "function"),
           function(X, FUN) {
-            FUN <- cleanClosure(FUN)
-            closureCapturingFunc <- function(split, part) {
-              FUN(split, part)
-            }
-            PipelinedRDD(X, closureCapturingFunc)
+            PipelinedRDD(X, FUN)
           })
 
 #' @rdname lapplyPartitionsWithIndex
diff --git a/R/pkg/R/pairRDD.R b/R/pkg/R/pairRDD.R
index c2396c32a7548..739d399f0820f 100644
--- a/R/pkg/R/pairRDD.R
+++ b/R/pkg/R/pairRDD.R
@@ -694,10 +694,6 @@ setMethod("cogroup",
             for (i in 1:rddsLen) {
               rdds[[i]] <- lapply(rdds[[i]], 
                                   function(x) { list(x[[1]], list(i, x[[2]])) })
-              # TODO(hao): As issue [SparkR-142] mentions, the right value of i
-              # will not be captured into UDF if getJRDD is not invoked.
-              # It should be resolved together with that issue.
-              getJRDD(rdds[[i]])  # Capture the closure.
             }
             union.rdd <- Reduce(unionRDD, rdds)
             group.func <- function(vlist) {

From 971b95b0c9002bd541bcbe0da54a9967ba22588f Mon Sep 17 00:00:00 2001
From: Xiangrui Meng <meng@databricks.com>
Date: Mon, 13 Apr 2015 21:18:05 -0700
Subject: [PATCH 94/95] [SPARK-5957][ML] better handling of parameters

The design doc was posted on the JIRA page. Python changes will be in a follow-up PR. jkbradley

1. Use codegen for shared params.
1. Move shared params to package `ml.param.shared`.
1. Set default values in `Params` instead of in `Param`.
1. Add a few methods to `Params` and `ParamMap`.
1. Move schema handling to `SchemaUtils` from `Params`.

- [x] check visibility of the methods added

Author: Xiangrui Meng <meng@databricks.com>

Closes #5431 from mengxr/SPARK-5957 and squashes the following commits:

d19236d [Xiangrui Meng] fix test
26ae2d7 [Xiangrui Meng] re-gen code and mark clear protected
38b78c7 [Xiangrui Meng] update Param.toString and remove Params.explain()
409e2d5 [Xiangrui Meng] address comments
2d637bd [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-5957
eec2264 [Xiangrui Meng] make get* public in Params
4090d95 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-5957
4fee9e7 [Xiangrui Meng] re-gen shared params
2737c2d [Xiangrui Meng] rename SharedParamCodeGen to SharedParamsCodeGen
e938f81 [Xiangrui Meng] update code to set default parameter values
28ed322 [Xiangrui Meng] merge master
55be1f3 [Xiangrui Meng] merge master
d63b5cc [Xiangrui Meng] fix examples
29b004c [Xiangrui Meng] update ParamsSuite
94fd98e [Xiangrui Meng] fix explain params
48d0e84 [Xiangrui Meng] add remove and update explainParams
4ac6348 [Xiangrui Meng] move schema utils to SchemaUtils add a few methods to Params
0d9594e [Xiangrui Meng] add getOrElse to ParamMap
eeeffe8 [Xiangrui Meng] map ++ paramMap => extractValues
0d3fc5b [Xiangrui Meng] setDefault after param
a9dbf59 [Xiangrui Meng] minor updates
d9302b8 [Xiangrui Meng] generate default values
1c72579 [Xiangrui Meng] pass test compile
abb7a3b [Xiangrui Meng] update default values handling
dcab97a [Xiangrui Meng] add codegen for shared params
---
 .../examples/ml/JavaDeveloperApiExample.java  |   4 +-
 .../examples/ml/DeveloperApiExample.scala     |   6 +-
 .../scala/org/apache/spark/ml/Estimator.scala |   2 +-
 .../scala/org/apache/spark/ml/Pipeline.scala  |  10 +-
 .../org/apache/spark/ml/Transformer.scala     |   5 +-
 .../spark/ml/classification/Classifier.scala  |  17 +-
 .../classification/LogisticRegression.scala   |  18 +-
 .../ProbabilisticClassifier.scala             |  11 +-
 .../BinaryClassificationEvaluator.scala       |  15 +-
 .../apache/spark/ml/feature/HashingTF.scala   |   6 +-
 .../apache/spark/ml/feature/Normalizer.scala  |   7 +-
 .../spark/ml/feature/StandardScaler.scala     |   9 +-
 .../spark/ml/feature/StringIndexer.scala      |  10 +-
 .../apache/spark/ml/feature/Tokenizer.scala   |  16 +-
 .../spark/ml/feature/VectorAssembler.scala    |   7 +-
 .../spark/ml/feature/VectorIndexer.scala      |  25 +-
 .../spark/ml/impl/estimator/Predictor.scala   |  16 +-
 .../org/apache/spark/ml/param/params.scala    | 236 ++++++++++------
 .../ml/param/shared/SharedParamsCodeGen.scala | 169 ++++++++++++
 .../spark/ml/param/shared/sharedParams.scala  | 259 ++++++++++++++++++
 .../apache/spark/ml/param/sharedParams.scala  | 173 ------------
 .../apache/spark/ml/recommendation/ALS.scala  |  49 ++--
 .../ml/regression/LinearRegression.scala      |   8 +-
 .../spark/ml/tuning/CrossValidator.scala      |  18 +-
 .../apache/spark/ml/util/SchemaUtils.scala    |  61 +++++
 .../apache/spark/ml/param/ParamsSuite.scala   |  47 +++-
 .../apache/spark/ml/param/TestParams.scala    |  12 +-
 27 files changed, 820 insertions(+), 396 deletions(-)
 create mode 100644 mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala
 create mode 100644 mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala
 delete mode 100644 mllib/src/main/scala/org/apache/spark/ml/param/sharedParams.scala
 create mode 100644 mllib/src/main/scala/org/apache/spark/ml/util/SchemaUtils.scala

diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
index 19d0eb216848e..eaf00d09f550d 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
@@ -116,7 +116,7 @@ class MyJavaLogisticRegression
    */
   IntParam maxIter = new IntParam(this, "maxIter", "max number of iterations");
 
-  int getMaxIter() { return (Integer) get(maxIter); }
+  int getMaxIter() { return (Integer) getOrDefault(maxIter); }
 
   public MyJavaLogisticRegression() {
     setMaxIter(100);
@@ -211,7 +211,7 @@ public Vector predictRaw(Vector features) {
   public MyJavaLogisticRegressionModel copy() {
     MyJavaLogisticRegressionModel m =
         new MyJavaLogisticRegressionModel(parent_, fittingParamMap_, weights_);
-    Params$.MODULE$.inheritValues(this.paramMap(), this, m);
+    Params$.MODULE$.inheritValues(this.extractParamMap(), this, m);
     return m;
   }
 }
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala
index df26798e41b7b..2245fa429fda3 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala
@@ -99,7 +99,7 @@ private trait MyLogisticRegressionParams extends ClassifierParams {
    * class since the maxIter parameter is only used during training (not in the Model).
    */
   val maxIter: IntParam = new IntParam(this, "maxIter", "max number of iterations")
-  def getMaxIter: Int = get(maxIter)
+  def getMaxIter: Int = getOrDefault(maxIter)
 }
 
 /**
@@ -174,11 +174,11 @@ private class MyLogisticRegressionModel(
    * Create a copy of the model.
    * The copy is shallow, except for the embedded paramMap, which gets a deep copy.
    *
-   * This is used for the defaul implementation of [[transform()]].
+   * This is used for the default implementation of [[transform()]].
    */
   override protected def copy(): MyLogisticRegressionModel = {
     val m = new MyLogisticRegressionModel(parent, fittingParamMap, weights)
-    Params.inheritValues(this.paramMap, this, m)
+    Params.inheritValues(extractParamMap(), this, m)
     m
   }
 }
diff --git a/mllib/src/main/scala/org/apache/spark/ml/Estimator.scala b/mllib/src/main/scala/org/apache/spark/ml/Estimator.scala
index eff7ef925dfbd..d6b3503ebdd9a 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/Estimator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/Estimator.scala
@@ -40,7 +40,7 @@ abstract class Estimator[M <: Model[M]] extends PipelineStage with Params {
    */
   @varargs
   def fit(dataset: DataFrame, paramPairs: ParamPair[_]*): M = {
-    val map = new ParamMap().put(paramPairs: _*)
+    val map = ParamMap(paramPairs: _*)
     fit(dataset, map)
   }
 
diff --git a/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala b/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala
index a455341a1f723..8eddf79cdfe28 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala
@@ -84,7 +84,7 @@ class Pipeline extends Estimator[PipelineModel] {
   /** param for pipeline stages */
   val stages: Param[Array[PipelineStage]] = new Param(this, "stages", "stages of the pipeline")
   def setStages(value: Array[PipelineStage]): this.type = { set(stages, value); this }
-  def getStages: Array[PipelineStage] = get(stages)
+  def getStages: Array[PipelineStage] = getOrDefault(stages)
 
   /**
    * Fits the pipeline to the input dataset with additional parameters. If a stage is an
@@ -101,7 +101,7 @@ class Pipeline extends Estimator[PipelineModel] {
    */
   override def fit(dataset: DataFrame, paramMap: ParamMap): PipelineModel = {
     transformSchema(dataset.schema, paramMap, logging = true)
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val theStages = map(stages)
     // Search for the last estimator.
     var indexOfLastEstimator = -1
@@ -138,7 +138,7 @@ class Pipeline extends Estimator[PipelineModel] {
   }
 
   override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val theStages = map(stages)
     require(theStages.toSet.size == theStages.size,
       "Cannot have duplicate components in a pipeline.")
@@ -177,14 +177,14 @@ class PipelineModel private[ml] (
 
   override def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame = {
     // Precedence of ParamMaps: paramMap > this.paramMap > fittingParamMap
-    val map = (fittingParamMap ++ this.paramMap) ++ paramMap
+    val map = fittingParamMap ++ extractParamMap(paramMap)
     transformSchema(dataset.schema, map, logging = true)
     stages.foldLeft(dataset)((cur, transformer) => transformer.transform(cur, map))
   }
 
   override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = {
     // Precedence of ParamMaps: paramMap > this.paramMap > fittingParamMap
-    val map = (fittingParamMap ++ this.paramMap) ++ paramMap
+    val map = fittingParamMap ++ extractParamMap(paramMap)
     stages.foldLeft(schema)((cur, transformer) => transformer.transformSchema(cur, map))
   }
 }
diff --git a/mllib/src/main/scala/org/apache/spark/ml/Transformer.scala b/mllib/src/main/scala/org/apache/spark/ml/Transformer.scala
index 9a5848684b179..7fb87fe452ee6 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/Transformer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/Transformer.scala
@@ -22,6 +22,7 @@ import scala.annotation.varargs
 import org.apache.spark.Logging
 import org.apache.spark.annotation.AlphaComponent
 import org.apache.spark.ml.param._
+import org.apache.spark.ml.param.shared._
 import org.apache.spark.sql.DataFrame
 import org.apache.spark.sql.functions._
 import org.apache.spark.sql.types._
@@ -86,7 +87,7 @@ private[ml] abstract class UnaryTransformer[IN, OUT, T <: UnaryTransformer[IN, O
   protected def validateInputType(inputType: DataType): Unit = {}
 
   override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val inputType = schema(map(inputCol)).dataType
     validateInputType(inputType)
     if (schema.fieldNames.contains(map(outputCol))) {
@@ -99,7 +100,7 @@ private[ml] abstract class UnaryTransformer[IN, OUT, T <: UnaryTransformer[IN, O
 
   override def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame = {
     transformSchema(dataset.schema, paramMap, logging = true)
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     dataset.withColumn(map(outputCol),
       callUDF(this.createTransformFunc(map), outputDataType, dataset(map(inputCol))))
   }
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/Classifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/Classifier.scala
index c5fc89f935432..29339c98f51cf 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/Classifier.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/Classifier.scala
@@ -17,12 +17,14 @@
 
 package org.apache.spark.ml.classification
 
-import org.apache.spark.annotation.{DeveloperApi, AlphaComponent}
+import org.apache.spark.annotation.{AlphaComponent, DeveloperApi}
 import org.apache.spark.ml.impl.estimator.{PredictionModel, Predictor, PredictorParams}
-import org.apache.spark.ml.param.{Params, ParamMap, HasRawPredictionCol}
+import org.apache.spark.ml.param.{ParamMap, Params}
+import org.apache.spark.ml.param.shared.HasRawPredictionCol
+import org.apache.spark.ml.util.SchemaUtils
 import org.apache.spark.mllib.linalg.{Vector, VectorUDT}
-import org.apache.spark.sql.functions._
 import org.apache.spark.sql.DataFrame
+import org.apache.spark.sql.functions._
 import org.apache.spark.sql.types.{DataType, DoubleType, StructType}
 
 
@@ -42,8 +44,8 @@ private[spark] trait ClassifierParams extends PredictorParams
       fitting: Boolean,
       featuresDataType: DataType): StructType = {
     val parentSchema = super.validateAndTransformSchema(schema, paramMap, fitting, featuresDataType)
-    val map = this.paramMap ++ paramMap
-    addOutputColumn(parentSchema, map(rawPredictionCol), new VectorUDT)
+    val map = extractParamMap(paramMap)
+    SchemaUtils.appendColumn(parentSchema, map(rawPredictionCol), new VectorUDT)
   }
 }
 
@@ -67,8 +69,7 @@ private[spark] abstract class Classifier[
   with ClassifierParams {
 
   /** @group setParam */
-  def setRawPredictionCol(value: String): E =
-    set(rawPredictionCol, value).asInstanceOf[E]
+  def setRawPredictionCol(value: String): E = set(rawPredictionCol, value).asInstanceOf[E]
 
   // TODO: defaultEvaluator (follow-up PR)
 }
@@ -109,7 +110,7 @@ abstract class ClassificationModel[FeaturesType, M <: ClassificationModel[Featur
 
     // Check schema
     transformSchema(dataset.schema, paramMap, logging = true)
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
 
     // Prepare model
     val tmpModel = if (paramMap.size != 0) {
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
index 34625745dd0a8..cc8b0721cf2b6 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
@@ -19,11 +19,11 @@ package org.apache.spark.ml.classification
 
 import org.apache.spark.annotation.AlphaComponent
 import org.apache.spark.ml.param._
+import org.apache.spark.ml.param.shared._
 import org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
 import org.apache.spark.mllib.linalg.{VectorUDT, BLAS, Vector, Vectors}
 import org.apache.spark.sql.DataFrame
 import org.apache.spark.sql.functions._
-import org.apache.spark.sql.types.DoubleType
 import org.apache.spark.storage.StorageLevel
 
 
@@ -31,8 +31,10 @@ import org.apache.spark.storage.StorageLevel
  * Params for logistic regression.
  */
 private[classification] trait LogisticRegressionParams extends ProbabilisticClassifierParams
-  with HasRegParam with HasMaxIter with HasFitIntercept with HasThreshold
+  with HasRegParam with HasMaxIter with HasFitIntercept with HasThreshold {
 
+  setDefault(regParam -> 0.1, maxIter -> 100, threshold -> 0.5)
+}
 
 /**
  * :: AlphaComponent ::
@@ -45,10 +47,6 @@ class LogisticRegression
   extends ProbabilisticClassifier[Vector, LogisticRegression, LogisticRegressionModel]
   with LogisticRegressionParams {
 
-  setRegParam(0.1)
-  setMaxIter(100)
-  setThreshold(0.5)
-
   /** @group setParam */
   def setRegParam(value: Double): this.type = set(regParam, value)
 
@@ -100,8 +98,6 @@ class LogisticRegressionModel private[ml] (
   extends ProbabilisticClassificationModel[Vector, LogisticRegressionModel]
   with LogisticRegressionParams {
 
-  setThreshold(0.5)
-
   /** @group setParam */
   def setThreshold(value: Double): this.type = set(threshold, value)
 
@@ -123,7 +119,7 @@ class LogisticRegressionModel private[ml] (
     // Check schema
     transformSchema(dataset.schema, paramMap, logging = true)
 
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
 
     // Output selected columns only.
     // This is a bit complicated since it tries to avoid repeated computation.
@@ -184,7 +180,7 @@ class LogisticRegressionModel private[ml] (
    * The behavior of this can be adjusted using [[threshold]].
    */
   override protected def predict(features: Vector): Double = {
-    if (score(features) > paramMap(threshold)) 1 else 0
+    if (score(features) > getThreshold) 1 else 0
   }
 
   override protected def predictProbabilities(features: Vector): Vector = {
@@ -199,7 +195,7 @@ class LogisticRegressionModel private[ml] (
 
   override protected def copy(): LogisticRegressionModel = {
     val m = new LogisticRegressionModel(parent, fittingParamMap, weights, intercept)
-    Params.inheritValues(this.paramMap, this, m)
+    Params.inheritValues(this.extractParamMap(), this, m)
     m
   }
 }
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/ProbabilisticClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/ProbabilisticClassifier.scala
index bd8caac855981..10404548ccfde 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/ProbabilisticClassifier.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/ProbabilisticClassifier.scala
@@ -18,13 +18,14 @@
 package org.apache.spark.ml.classification
 
 import org.apache.spark.annotation.{AlphaComponent, DeveloperApi}
-import org.apache.spark.ml.param.{HasProbabilityCol, ParamMap, Params}
+import org.apache.spark.ml.param.{ParamMap, Params}
+import org.apache.spark.ml.param.shared._
+import org.apache.spark.ml.util.SchemaUtils
 import org.apache.spark.mllib.linalg.{Vector, VectorUDT}
 import org.apache.spark.sql.DataFrame
 import org.apache.spark.sql.functions._
 import org.apache.spark.sql.types.{DataType, StructType}
 
-
 /**
  * Params for probabilistic classification.
  */
@@ -37,8 +38,8 @@ private[classification] trait ProbabilisticClassifierParams
       fitting: Boolean,
       featuresDataType: DataType): StructType = {
     val parentSchema = super.validateAndTransformSchema(schema, paramMap, fitting, featuresDataType)
-    val map = this.paramMap ++ paramMap
-    addOutputColumn(parentSchema, map(probabilityCol), new VectorUDT)
+    val map = extractParamMap(paramMap)
+    SchemaUtils.appendColumn(parentSchema, map(probabilityCol), new VectorUDT)
   }
 }
 
@@ -102,7 +103,7 @@ private[spark] abstract class ProbabilisticClassificationModel[
 
     // Check schema
     transformSchema(dataset.schema, paramMap, logging = true)
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
 
     // Prepare model
     val tmpModel = if (paramMap.size != 0) {
diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala
index 2360f4479f1c2..c865eb9fe092d 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala
@@ -20,12 +20,13 @@ package org.apache.spark.ml.evaluation
 import org.apache.spark.annotation.AlphaComponent
 import org.apache.spark.ml.Evaluator
 import org.apache.spark.ml.param._
+import org.apache.spark.ml.param.shared._
+import org.apache.spark.ml.util.SchemaUtils
 import org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
 import org.apache.spark.mllib.linalg.{Vector, VectorUDT}
 import org.apache.spark.sql.{DataFrame, Row}
 import org.apache.spark.sql.types.DoubleType
 
-
 /**
  * :: AlphaComponent ::
  *
@@ -40,10 +41,10 @@ class BinaryClassificationEvaluator extends Evaluator with Params
    * @group param
    */
   val metricName: Param[String] = new Param(this, "metricName",
-    "metric name in evaluation (areaUnderROC|areaUnderPR)", Some("areaUnderROC"))
+    "metric name in evaluation (areaUnderROC|areaUnderPR)")
 
   /** @group getParam */
-  def getMetricName: String = get(metricName)
+  def getMetricName: String = getOrDefault(metricName)
 
   /** @group setParam */
   def setMetricName(value: String): this.type = set(metricName, value)
@@ -54,12 +55,14 @@ class BinaryClassificationEvaluator extends Evaluator with Params
   /** @group setParam */
   def setLabelCol(value: String): this.type = set(labelCol, value)
 
+  setDefault(metricName -> "areaUnderROC")
+
   override def evaluate(dataset: DataFrame, paramMap: ParamMap): Double = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
 
     val schema = dataset.schema
-    checkInputColumn(schema, map(rawPredictionCol), new VectorUDT)
-    checkInputColumn(schema, map(labelCol), DoubleType)
+    SchemaUtils.checkColumnType(schema, map(rawPredictionCol), new VectorUDT)
+    SchemaUtils.checkColumnType(schema, map(labelCol), DoubleType)
 
     // TODO: When dataset metadata has been implemented, check rawPredictionCol vector length = 2.
     val scoreAndLabels = dataset.select(map(rawPredictionCol), map(labelCol))
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala
index fc4e12773c46d..b20f2fc49a8f6 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala
@@ -35,14 +35,16 @@ class HashingTF extends UnaryTransformer[Iterable[_], Vector, HashingTF] {
    * number of features
    * @group param
    */
-  val numFeatures = new IntParam(this, "numFeatures", "number of features", Some(1 << 18))
+  val numFeatures = new IntParam(this, "numFeatures", "number of features")
 
   /** @group getParam */
-  def getNumFeatures: Int = get(numFeatures)
+  def getNumFeatures: Int = getOrDefault(numFeatures)
 
   /** @group setParam */
   def setNumFeatures(value: Int): this.type = set(numFeatures, value)
 
+  setDefault(numFeatures -> (1 << 18))
+
   override protected def createTransformFunc(paramMap: ParamMap): Iterable[_] => Vector = {
     val hashingTF = new feature.HashingTF(paramMap(numFeatures))
     hashingTF.transform
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Normalizer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/Normalizer.scala
index 05f91dc9105fe..decaeb0da6246 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/Normalizer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Normalizer.scala
@@ -35,14 +35,16 @@ class Normalizer extends UnaryTransformer[Vector, Vector, Normalizer] {
    * Normalization in L^p^ space, p = 2 by default.
    * @group param
    */
-  val p = new DoubleParam(this, "p", "the p norm value", Some(2))
+  val p = new DoubleParam(this, "p", "the p norm value")
 
   /** @group getParam */
-  def getP: Double = get(p)
+  def getP: Double = getOrDefault(p)
 
   /** @group setParam */
   def setP(value: Double): this.type = set(p, value)
 
+  setDefault(p -> 2.0)
+
   override protected def createTransformFunc(paramMap: ParamMap): Vector => Vector = {
     val normalizer = new feature.Normalizer(paramMap(p))
     normalizer.transform
@@ -50,4 +52,3 @@ class Normalizer extends UnaryTransformer[Vector, Vector, Normalizer] {
 
   override protected def outputDataType: DataType = new VectorUDT()
 }
-
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala
index 1142aa4f8e73d..1b102619b3524 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala
@@ -20,6 +20,7 @@ package org.apache.spark.ml.feature
 import org.apache.spark.annotation.AlphaComponent
 import org.apache.spark.ml._
 import org.apache.spark.ml.param._
+import org.apache.spark.ml.param.shared._
 import org.apache.spark.mllib.feature
 import org.apache.spark.mllib.linalg.{Vector, VectorUDT}
 import org.apache.spark.sql._
@@ -47,7 +48,7 @@ class StandardScaler extends Estimator[StandardScalerModel] with StandardScalerP
 
   override def fit(dataset: DataFrame, paramMap: ParamMap): StandardScalerModel = {
     transformSchema(dataset.schema, paramMap, logging = true)
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val input = dataset.select(map(inputCol)).map { case Row(v: Vector) => v }
     val scaler = new feature.StandardScaler().fit(input)
     val model = new StandardScalerModel(this, map, scaler)
@@ -56,7 +57,7 @@ class StandardScaler extends Estimator[StandardScalerModel] with StandardScalerP
   }
 
   override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val inputType = schema(map(inputCol)).dataType
     require(inputType.isInstanceOf[VectorUDT],
       s"Input column ${map(inputCol)} must be a vector column")
@@ -86,13 +87,13 @@ class StandardScalerModel private[ml] (
 
   override def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame = {
     transformSchema(dataset.schema, paramMap, logging = true)
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val scale = udf((v: Vector) => { scaler.transform(v) } : Vector)
     dataset.withColumn(map(outputCol), scale(col(map(inputCol))))
   }
 
   override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val inputType = schema(map(inputCol)).dataType
     require(inputType.isInstanceOf[VectorUDT],
       s"Input column ${map(inputCol)} must be a vector column")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
index 61e6742e880d8..4d960df357fe9 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
@@ -22,6 +22,8 @@ import org.apache.spark.annotation.AlphaComponent
 import org.apache.spark.ml.{Estimator, Model}
 import org.apache.spark.ml.attribute.NominalAttribute
 import org.apache.spark.ml.param._
+import org.apache.spark.ml.param.shared._
+import org.apache.spark.ml.util.SchemaUtils
 import org.apache.spark.sql.DataFrame
 import org.apache.spark.sql.functions._
 import org.apache.spark.sql.types.{StringType, StructType}
@@ -34,8 +36,8 @@ private[feature] trait StringIndexerBase extends Params with HasInputCol with Ha
 
   /** Validates and transforms the input schema. */
   protected def validateAndTransformSchema(schema: StructType, paramMap: ParamMap): StructType = {
-    val map = this.paramMap ++ paramMap
-    checkInputColumn(schema, map(inputCol), StringType)
+    val map = extractParamMap(paramMap)
+    SchemaUtils.checkColumnType(schema, map(inputCol), StringType)
     val inputFields = schema.fields
     val outputColName = map(outputCol)
     require(inputFields.forall(_.name != outputColName),
@@ -64,7 +66,7 @@ class StringIndexer extends Estimator[StringIndexerModel] with StringIndexerBase
   // TODO: handle unseen labels
 
   override def fit(dataset: DataFrame, paramMap: ParamMap): StringIndexerModel = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val counts = dataset.select(map(inputCol)).map(_.getString(0)).countByValue()
     val labels = counts.toSeq.sortBy(-_._2).map(_._1).toArray
     val model = new StringIndexerModel(this, map, labels)
@@ -105,7 +107,7 @@ class StringIndexerModel private[ml] (
   def setOutputCol(value: String): this.type = set(outputCol, value)
 
   override def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val indexer = udf { label: String =>
       if (labelToIndex.contains(label)) {
         labelToIndex(label)
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Tokenizer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/Tokenizer.scala
index 68401e36950bd..376a004858b4c 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/Tokenizer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Tokenizer.scala
@@ -56,39 +56,39 @@ class RegexTokenizer extends UnaryTransformer[String, Seq[String], RegexTokenize
    * param for minimum token length, default is one to avoid returning empty strings
    * @group param
    */
-  val minTokenLength: IntParam = new IntParam(this, "minLength", "minimum token length", Some(1))
+  val minTokenLength: IntParam = new IntParam(this, "minLength", "minimum token length")
 
   /** @group setParam */
   def setMinTokenLength(value: Int): this.type = set(minTokenLength, value)
 
   /** @group getParam */
-  def getMinTokenLength: Int = get(minTokenLength)
+  def getMinTokenLength: Int = getOrDefault(minTokenLength)
 
   /**
    * param sets regex as splitting on gaps (true) or matching tokens (false)
    * @group param
    */
-  val gaps: BooleanParam = new BooleanParam(
-    this, "gaps", "Set regex to match gaps or tokens", Some(false))
+  val gaps: BooleanParam = new BooleanParam(this, "gaps", "Set regex to match gaps or tokens")
 
   /** @group setParam */
   def setGaps(value: Boolean): this.type = set(gaps, value)
 
   /** @group getParam */
-  def getGaps: Boolean = get(gaps)
+  def getGaps: Boolean = getOrDefault(gaps)
 
   /**
    * param sets regex pattern used by tokenizer 
    * @group param
    */
-  val pattern: Param[String] = new Param(
-    this, "pattern", "regex pattern used for tokenizing", Some("\\p{L}+|[^\\p{L}\\s]+"))
+  val pattern: Param[String] = new Param(this, "pattern", "regex pattern used for tokenizing")
 
   /** @group setParam */
   def setPattern(value: String): this.type = set(pattern, value)
 
   /** @group getParam */
-  def getPattern: String = get(pattern)
+  def getPattern: String = getOrDefault(pattern)
+
+  setDefault(minTokenLength -> 1, gaps -> false, pattern -> "\\p{L}+|[^\\p{L}\\s]+")
 
   override protected def createTransformFunc(paramMap: ParamMap): String => Seq[String] = { str =>
     val re = paramMap(pattern).r
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala
index d1b8f7e6e9295..e567e069e7c0b 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala
@@ -22,7 +22,8 @@ import scala.collection.mutable.ArrayBuilder
 import org.apache.spark.SparkException
 import org.apache.spark.annotation.AlphaComponent
 import org.apache.spark.ml.Transformer
-import org.apache.spark.ml.param.{HasInputCols, HasOutputCol, ParamMap}
+import org.apache.spark.ml.param.ParamMap
+import org.apache.spark.ml.param.shared._
 import org.apache.spark.mllib.linalg.{Vector, VectorUDT, Vectors}
 import org.apache.spark.sql.{Column, DataFrame, Row}
 import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute
@@ -44,7 +45,7 @@ class VectorAssembler extends Transformer with HasInputCols with HasOutputCol {
   def setOutputCol(value: String): this.type = set(outputCol, value)
 
   override def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val assembleFunc = udf { r: Row =>
       VectorAssembler.assemble(r.toSeq: _*)
     }
@@ -61,7 +62,7 @@ class VectorAssembler extends Transformer with HasInputCols with HasOutputCol {
   }
 
   override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val inputColNames = map(inputCols)
     val outputColName = map(outputCol)
     val inputDataTypes = inputColNames.map(name => schema(name).dataType)
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala
index 8760960e19272..452faa06e2021 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala
@@ -18,10 +18,12 @@
 package org.apache.spark.ml.feature
 
 import org.apache.spark.annotation.AlphaComponent
+import org.apache.spark.ml.util.SchemaUtils
 import org.apache.spark.ml.{Estimator, Model}
 import org.apache.spark.ml.attribute.{BinaryAttribute, NumericAttribute, NominalAttribute,
   Attribute, AttributeGroup}
-import org.apache.spark.ml.param.{HasInputCol, HasOutputCol, IntParam, ParamMap, Params}
+import org.apache.spark.ml.param.{IntParam, ParamMap, Params}
+import org.apache.spark.ml.param.shared._
 import org.apache.spark.mllib.linalg.{SparseVector, DenseVector, Vector, VectorUDT}
 import org.apache.spark.sql.{Row, DataFrame}
 import org.apache.spark.sql.functions.callUDF
@@ -40,11 +42,12 @@ private[ml] trait VectorIndexerParams extends Params with HasInputCol with HasOu
    */
   val maxCategories = new IntParam(this, "maxCategories",
     "Threshold for the number of values a categorical feature can take." +
-      " If a feature is found to have > maxCategories values, then it is declared continuous.",
-    Some(20))
+      " If a feature is found to have > maxCategories values, then it is declared continuous.")
 
   /** @group getParam */
-  def getMaxCategories: Int = get(maxCategories)
+  def getMaxCategories: Int = getOrDefault(maxCategories)
+
+  setDefault(maxCategories -> 20)
 }
 
 /**
@@ -101,7 +104,7 @@ class VectorIndexer extends Estimator[VectorIndexerModel] with VectorIndexerPara
 
   override def fit(dataset: DataFrame, paramMap: ParamMap): VectorIndexerModel = {
     transformSchema(dataset.schema, paramMap, logging = true)
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val firstRow = dataset.select(map(inputCol)).take(1)
     require(firstRow.length == 1, s"VectorIndexer cannot be fit on an empty dataset.")
     val numFeatures = firstRow(0).getAs[Vector](0).size
@@ -120,12 +123,12 @@ class VectorIndexer extends Estimator[VectorIndexerModel] with VectorIndexerPara
   override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = {
     // We do not transfer feature metadata since we do not know what types of features we will
     // produce in transform().
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val dataType = new VectorUDT
     require(map.contains(inputCol), s"VectorIndexer requires input column parameter: $inputCol")
     require(map.contains(outputCol), s"VectorIndexer requires output column parameter: $outputCol")
-    checkInputColumn(schema, map(inputCol), dataType)
-    addOutputColumn(schema, map(outputCol), dataType)
+    SchemaUtils.checkColumnType(schema, map(inputCol), dataType)
+    SchemaUtils.appendColumn(schema, map(outputCol), dataType)
   }
 }
 
@@ -320,7 +323,7 @@ class VectorIndexerModel private[ml] (
 
   override def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame = {
     transformSchema(dataset.schema, paramMap, logging = true)
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val newField = prepOutputField(dataset.schema, map)
     val newCol = callUDF(transformFunc, new VectorUDT, dataset(map(inputCol)))
     // For now, just check the first row of inputCol for vector length.
@@ -334,13 +337,13 @@ class VectorIndexerModel private[ml] (
   }
 
   override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val dataType = new VectorUDT
     require(map.contains(inputCol),
       s"VectorIndexerModel requires input column parameter: $inputCol")
     require(map.contains(outputCol),
       s"VectorIndexerModel requires output column parameter: $outputCol")
-    checkInputColumn(schema, map(inputCol), dataType)
+    SchemaUtils.checkColumnType(schema, map(inputCol), dataType)
 
     val origAttrGroup = AttributeGroup.fromStructField(schema(map(inputCol)))
     val origNumFeatures: Option[Int] = if (origAttrGroup.attributes.nonEmpty) {
diff --git a/mllib/src/main/scala/org/apache/spark/ml/impl/estimator/Predictor.scala b/mllib/src/main/scala/org/apache/spark/ml/impl/estimator/Predictor.scala
index dfb89cc8d4af3..195333a5cc47f 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/impl/estimator/Predictor.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/impl/estimator/Predictor.scala
@@ -18,8 +18,10 @@
 package org.apache.spark.ml.impl.estimator
 
 import org.apache.spark.annotation.{AlphaComponent, DeveloperApi}
+import org.apache.spark.ml.util.SchemaUtils
 import org.apache.spark.ml.{Estimator, Model}
 import org.apache.spark.ml.param._
+import org.apache.spark.ml.param.shared._
 import org.apache.spark.mllib.linalg.{VectorUDT, Vector}
 import org.apache.spark.mllib.regression.LabeledPoint
 import org.apache.spark.rdd.RDD
@@ -53,14 +55,14 @@ private[spark] trait PredictorParams extends Params
       paramMap: ParamMap,
       fitting: Boolean,
       featuresDataType: DataType): StructType = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     // TODO: Support casting Array[Double] and Array[Float] to Vector when FeaturesType = Vector
-    checkInputColumn(schema, map(featuresCol), featuresDataType)
+    SchemaUtils.checkColumnType(schema, map(featuresCol), featuresDataType)
     if (fitting) {
       // TODO: Allow other numeric types
-      checkInputColumn(schema, map(labelCol), DoubleType)
+      SchemaUtils.checkColumnType(schema, map(labelCol), DoubleType)
     }
-    addOutputColumn(schema, map(predictionCol), DoubleType)
+    SchemaUtils.appendColumn(schema, map(predictionCol), DoubleType)
   }
 }
 
@@ -98,7 +100,7 @@ private[spark] abstract class Predictor[
     // This handles a few items such as schema validation.
     // Developers only need to implement train().
     transformSchema(dataset.schema, paramMap, logging = true)
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val model = train(dataset, map)
     Params.inheritValues(map, this, model) // copy params to model
     model
@@ -141,7 +143,7 @@ private[spark] abstract class Predictor[
    * and put it in an RDD with strong types.
    */
   protected def extractLabeledPoints(dataset: DataFrame, paramMap: ParamMap): RDD[LabeledPoint] = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     dataset.select(map(labelCol), map(featuresCol))
       .map { case Row(label: Double, features: Vector) =>
       LabeledPoint(label, features)
@@ -201,7 +203,7 @@ private[spark] abstract class PredictionModel[FeaturesType, M <: PredictionModel
 
     // Check schema
     transformSchema(dataset.schema, paramMap, logging = true)
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
 
     // Prepare model
     val tmpModel = if (paramMap.size != 0) {
diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/params.scala b/mllib/src/main/scala/org/apache/spark/ml/param/params.scala
index 7d5178d0abb2d..849c60433c777 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/param/params.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/param/params.scala
@@ -17,15 +17,14 @@
 
 package org.apache.spark.ml.param
 
+import java.lang.reflect.Modifier
+import java.util.NoSuchElementException
+
 import scala.annotation.varargs
 import scala.collection.mutable
 
-import java.lang.reflect.Modifier
-
 import org.apache.spark.annotation.{AlphaComponent, DeveloperApi}
 import org.apache.spark.ml.Identifiable
-import org.apache.spark.sql.types.{DataType, StructField, StructType}
-
 
 /**
  * :: AlphaComponent ::
@@ -38,12 +37,7 @@ import org.apache.spark.sql.types.{DataType, StructField, StructType}
  * @tparam T param value type
  */
 @AlphaComponent
-class Param[T] (
-    val parent: Params,
-    val name: String,
-    val doc: String,
-    val defaultValue: Option[T] = None)
-  extends Serializable {
+class Param[T] (val parent: Params, val name: String, val doc: String) extends Serializable {
 
   /**
    * Creates a param pair with the given value (for Java).
@@ -55,58 +49,55 @@ class Param[T] (
    */
   def ->(value: T): ParamPair[T] = ParamPair(this, value)
 
+  /**
+   * Converts this param's name, doc, and optionally its default value and the user-supplied
+   * value in its parent to string.
+   */
   override def toString: String = {
-    if (defaultValue.isDefined) {
-      s"$name: $doc (default: ${defaultValue.get})"
+    val valueStr = if (parent.isDefined(this)) {
+      val defaultValueStr = parent.getDefault(this).map("default: " + _)
+      val currentValueStr = parent.get(this).map("current: " + _)
+      (defaultValueStr ++ currentValueStr).mkString("(", ", ", ")")
     } else {
-      s"$name: $doc"
+      "(undefined)"
     }
+    s"$name: $doc $valueStr"
   }
 }
 
 // specialize primitive-typed params because Java doesn't recognize scala.Double, scala.Int, ...
 
 /** Specialized version of [[Param[Double]]] for Java. */
-class DoubleParam(parent: Params, name: String, doc: String, defaultValue: Option[Double])
-  extends Param[Double](parent, name, doc, defaultValue) {
-
-  def this(parent: Params, name: String, doc: String) = this(parent, name, doc, None)
+class DoubleParam(parent: Params, name: String, doc: String)
+  extends Param[Double](parent, name, doc) {
 
   override def w(value: Double): ParamPair[Double] = super.w(value)
 }
 
 /** Specialized version of [[Param[Int]]] for Java. */
-class IntParam(parent: Params, name: String, doc: String, defaultValue: Option[Int])
-  extends Param[Int](parent, name, doc, defaultValue) {
-
-  def this(parent: Params, name: String, doc: String) = this(parent, name, doc, None)
+class IntParam(parent: Params, name: String, doc: String)
+  extends Param[Int](parent, name, doc) {
 
   override def w(value: Int): ParamPair[Int] = super.w(value)
 }
 
 /** Specialized version of [[Param[Float]]] for Java. */
-class FloatParam(parent: Params, name: String, doc: String, defaultValue: Option[Float])
-  extends Param[Float](parent, name, doc, defaultValue) {
-
-  def this(parent: Params, name: String, doc: String) = this(parent, name, doc, None)
+class FloatParam(parent: Params, name: String, doc: String)
+  extends Param[Float](parent, name, doc) {
 
   override def w(value: Float): ParamPair[Float] = super.w(value)
 }
 
 /** Specialized version of [[Param[Long]]] for Java. */
-class LongParam(parent: Params, name: String, doc: String, defaultValue: Option[Long])
-  extends Param[Long](parent, name, doc, defaultValue) {
-
-  def this(parent: Params, name: String, doc: String) = this(parent, name, doc, None)
+class LongParam(parent: Params, name: String, doc: String)
+  extends Param[Long](parent, name, doc) {
 
   override def w(value: Long): ParamPair[Long] = super.w(value)
 }
 
 /** Specialized version of [[Param[Boolean]]] for Java. */
-class BooleanParam(parent: Params, name: String, doc: String, defaultValue: Option[Boolean])
-  extends Param[Boolean](parent, name, doc, defaultValue) {
-
-  def this(parent: Params, name: String, doc: String) = this(parent, name, doc, None)
+class BooleanParam(parent: Params, name: String, doc: String)
+  extends Param[Boolean](parent, name, doc) {
 
   override def w(value: Boolean): ParamPair[Boolean] = super.w(value)
 }
@@ -124,8 +115,11 @@ case class ParamPair[T](param: Param[T], value: T)
 @AlphaComponent
 trait Params extends Identifiable with Serializable {
 
-  /** Returns all params. */
-  def params: Array[Param[_]] = {
+  /**
+   * Returns all params sorted by their names. The default implementation uses Java reflection to
+   * list all public methods that have no arguments and return [[Param]].
+   */
+  lazy val params: Array[Param[_]] = {
     val methods = this.getClass.getMethods
     methods.filter { m =>
         Modifier.isPublic(m.getModifiers) &&
@@ -153,25 +147,29 @@ trait Params extends Identifiable with Serializable {
   def explainParams(): String = params.mkString("\n")
 
   /** Checks whether a param is explicitly set. */
-  def isSet(param: Param[_]): Boolean = {
-    require(param.parent.eq(this))
+  final def isSet(param: Param[_]): Boolean = {
+    shouldOwn(param)
     paramMap.contains(param)
   }
 
+  /** Checks whether a param is explicitly set or has a default value. */
+  final def isDefined(param: Param[_]): Boolean = {
+    shouldOwn(param)
+    defaultParamMap.contains(param) || paramMap.contains(param)
+  }
+
   /** Gets a param by its name. */
-  private[ml] def getParam(paramName: String): Param[Any] = {
-    val m = this.getClass.getMethod(paramName)
-    assert(Modifier.isPublic(m.getModifiers) &&
-      classOf[Param[_]].isAssignableFrom(m.getReturnType) &&
-      m.getParameterTypes.isEmpty)
-    m.invoke(this).asInstanceOf[Param[Any]]
+  def getParam(paramName: String): Param[Any] = {
+    params.find(_.name == paramName).getOrElse {
+      throw new NoSuchElementException(s"Param $paramName does not exist.")
+    }.asInstanceOf[Param[Any]]
   }
 
   /**
    * Sets a parameter in the embedded param map.
    */
-  protected def set[T](param: Param[T], value: T): this.type = {
-    require(param.parent.eq(this))
+  protected final def set[T](param: Param[T], value: T): this.type = {
+    shouldOwn(param)
     paramMap.put(param.asInstanceOf[Param[Any]], value)
     this
   }
@@ -179,52 +177,102 @@ trait Params extends Identifiable with Serializable {
   /**
    * Sets a parameter (by name) in the embedded param map.
    */
-  private[ml] def set(param: String, value: Any): this.type = {
+  protected final def set(param: String, value: Any): this.type = {
     set(getParam(param), value)
   }
 
   /**
-   * Gets the value of a parameter in the embedded param map.
+   * Optionally returns the user-supplied value of a param.
+   */
+  final def get[T](param: Param[T]): Option[T] = {
+    shouldOwn(param)
+    paramMap.get(param)
+  }
+
+  /**
+   * Clears the user-supplied value for the input param.
+   */
+  protected final def clear(param: Param[_]): this.type = {
+    shouldOwn(param)
+    paramMap.remove(param)
+    this
+  }
+
+  /**
+   * Gets the value of a param in the embedded param map or its default value. Throws an exception
+   * if neither is set.
+   */
+  final def getOrDefault[T](param: Param[T]): T = {
+    shouldOwn(param)
+    get(param).orElse(getDefault(param)).get
+  }
+
+  /**
+   * Sets a default value for a param.
+   * @param param  param to set the default value. Make sure that this param is initialized before
+   *               this method gets called.
+   * @param value  the default value
    */
-  protected def get[T](param: Param[T]): T = {
-    require(param.parent.eq(this))
-    paramMap(param)
+  protected final def setDefault[T](param: Param[T], value: T): this.type = {
+    shouldOwn(param)
+    defaultParamMap.put(param, value)
+    this
   }
 
   /**
-   * Internal param map.
+   * Sets default values for a list of params.
+   * @param paramPairs  a list of param pairs that specify params and their default values to set
+   *                    respectively. Make sure that the params are initialized before this method
+   *                    gets called.
    */
-  protected val paramMap: ParamMap = ParamMap.empty
+  protected final def setDefault(paramPairs: ParamPair[_]*): this.type = {
+    paramPairs.foreach { p =>
+      setDefault(p.param.asInstanceOf[Param[Any]], p.value)
+    }
+    this
+  }
 
   /**
-   * Check whether the given schema contains an input column.
-   * @param colName  Input column name
-   * @param dataType  Input column DataType
+   * Gets the default value of a parameter.
    */
-  protected def checkInputColumn(schema: StructType, colName: String, dataType: DataType): Unit = {
-    val actualDataType = schema(colName).dataType
-    require(actualDataType.equals(dataType), s"Input column $colName must be of type $dataType" +
-      s" but was actually $actualDataType.  Column param description: ${getParam(colName)}")
+  final def getDefault[T](param: Param[T]): Option[T] = {
+    shouldOwn(param)
+    defaultParamMap.get(param)
   }
 
   /**
-   * Add an output column to the given schema.
-   * This fails if the given output column already exists.
-   * @param schema  Initial schema (not modified)
-   * @param colName  Output column name.  If this column name is an empy String "", this method
-   *                 returns the initial schema, unchanged.  This allows users to disable output
-   *                 columns.
-   * @param dataType  Output column DataType
-   */
-  protected def addOutputColumn(
-      schema: StructType,
-      colName: String,
-      dataType: DataType): StructType = {
-    if (colName.length == 0) return schema
-    val fieldNames = schema.fieldNames
-    require(!fieldNames.contains(colName), s"Output column $colName already exists.")
-    val outputFields = schema.fields ++ Seq(StructField(colName, dataType, nullable = false))
-    StructType(outputFields)
+   * Tests whether the input param has a default value set.
+   */
+  final def hasDefault[T](param: Param[T]): Boolean = {
+    shouldOwn(param)
+    defaultParamMap.contains(param)
+  }
+
+  /**
+   * Extracts the embedded default param values and user-supplied values, and then merges them with
+   * extra values from input into a flat param map, where the latter value is used if there exist
+   * conflicts, i.e., with ordering: default param values < user-supplied values < extraParamMap.
+   */
+  protected final def extractParamMap(extraParamMap: ParamMap): ParamMap = {
+    defaultParamMap ++ paramMap ++ extraParamMap
+  }
+
+  /**
+   * [[extractParamMap]] with no extra values.
+   */
+  protected final def extractParamMap(): ParamMap = {
+    extractParamMap(ParamMap.empty)
+  }
+
+  /** Internal param map for user-supplied values. */
+  private val paramMap: ParamMap = ParamMap.empty
+
+  /** Internal param map for default values. */
+  private val defaultParamMap: ParamMap = ParamMap.empty
+
+  /** Validates that the input param belongs to this instance. */
+  private def shouldOwn(param: Param[_]): Unit = {
+    require(param.parent.eq(this), s"Param $param does not belong to $this.")
   }
 }
 
@@ -261,12 +309,13 @@ private[spark] object Params {
  * A param to value map.
  */
 @AlphaComponent
-class ParamMap private[ml] (private val map: mutable.Map[Param[Any], Any]) extends Serializable {
+final class ParamMap private[ml] (private val map: mutable.Map[Param[Any], Any])
+  extends Serializable {
 
   /**
    * Creates an empty param map.
    */
-  def this() = this(mutable.Map.empty[Param[Any], Any])
+  def this() = this(mutable.Map.empty)
 
   /**
    * Puts a (param, value) pair (overwrites if the input param exists).
@@ -288,12 +337,17 @@ class ParamMap private[ml] (private val map: mutable.Map[Param[Any], Any]) exten
   }
 
   /**
-   * Optionally returns the value associated with a param or its default.
+   * Optionally returns the value associated with a param.
    */
   def get[T](param: Param[T]): Option[T] = {
-    map.get(param.asInstanceOf[Param[Any]])
-      .orElse(param.defaultValue)
-      .asInstanceOf[Option[T]]
+    map.get(param.asInstanceOf[Param[Any]]).asInstanceOf[Option[T]]
+  }
+
+  /**
+   * Returns the value associated with a param or a default value.
+   */
+  def getOrElse[T](param: Param[T], default: T): T = {
+    get(param).getOrElse(default)
   }
 
   /**
@@ -301,10 +355,7 @@ class ParamMap private[ml] (private val map: mutable.Map[Param[Any], Any]) exten
    * Raises a NoSuchElementException if there is no value associated with the input param.
    */
   def apply[T](param: Param[T]): T = {
-    val value = get(param)
-    if (value.isDefined) {
-      value.get
-    } else {
+    get(param).getOrElse {
       throw new NoSuchElementException(s"Cannot find param ${param.name}.")
     }
   }
@@ -316,6 +367,13 @@ class ParamMap private[ml] (private val map: mutable.Map[Param[Any], Any]) exten
     map.contains(param.asInstanceOf[Param[Any]])
   }
 
+  /**
+   * Removes a key from this map and returns its value associated previously as an option.
+   */
+  def remove[T](param: Param[T]): Option[T] = {
+    map.remove(param.asInstanceOf[Param[Any]]).asInstanceOf[Option[T]]
+  }
+
   /**
    * Filters this param map for the given parent.
    */
@@ -325,7 +383,7 @@ class ParamMap private[ml] (private val map: mutable.Map[Param[Any], Any]) exten
   }
 
   /**
-   * Make a copy of this param map.
+   * Creates a copy of this param map.
    */
   def copy: ParamMap = new ParamMap(map.clone())
 
@@ -337,7 +395,7 @@ class ParamMap private[ml] (private val map: mutable.Map[Param[Any], Any]) exten
 
   /**
    * Returns a new param map that contains parameters in this map and the given map,
-   * where the latter overwrites this if there exists conflicts.
+   * where the latter overwrites this if there exist conflicts.
    */
   def ++(other: ParamMap): ParamMap = {
     // TODO: Provide a better method name for Java users.
@@ -363,7 +421,7 @@ class ParamMap private[ml] (private val map: mutable.Map[Param[Any], Any]) exten
   }
 
   /**
-   * Number of param pairs in this set.
+   * Number of param pairs in this map.
    */
   def size: Int = map.size
 }
diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala b/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala
new file mode 100644
index 0000000000000..95d7e64790c79
--- /dev/null
+++ b/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala
@@ -0,0 +1,169 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.param.shared
+
+import java.io.PrintWriter
+
+import scala.reflect.ClassTag
+
+/**
+ * Code generator for shared params (sharedParams.scala). Run under the Spark folder with
+ * {{{
+ *   build/sbt "mllib/runMain org.apache.spark.ml.param.shared.SharedParamsCodeGen"
+ * }}}
+ */
+private[shared] object SharedParamsCodeGen {
+
+  def main(args: Array[String]): Unit = {
+    val params = Seq(
+      ParamDesc[Double]("regParam", "regularization parameter"),
+      ParamDesc[Int]("maxIter", "max number of iterations"),
+      ParamDesc[String]("featuresCol", "features column name", Some("\"features\"")),
+      ParamDesc[String]("labelCol", "label column name", Some("\"label\"")),
+      ParamDesc[String]("predictionCol", "prediction column name", Some("\"prediction\"")),
+      ParamDesc[String]("rawPredictionCol", "raw prediction (a.k.a. confidence) column name",
+        Some("\"rawPrediction\"")),
+      ParamDesc[String]("probabilityCol",
+        "column name for predicted class conditional probabilities", Some("\"probability\"")),
+      ParamDesc[Double]("threshold", "threshold in binary classification prediction"),
+      ParamDesc[String]("inputCol", "input column name"),
+      ParamDesc[Array[String]]("inputCols", "input column names"),
+      ParamDesc[String]("outputCol", "output column name"),
+      ParamDesc[Int]("checkpointInterval", "checkpoint interval"),
+      ParamDesc[Boolean]("fitIntercept", "whether to fit an intercept term", Some("true")))
+
+    val code = genSharedParams(params)
+    val file = "src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala"
+    val writer = new PrintWriter(file)
+    writer.write(code)
+    writer.close()
+  }
+
+  /** Description of a param. */
+  private case class ParamDesc[T: ClassTag](
+      name: String,
+      doc: String,
+      defaultValueStr: Option[String] = None) {
+
+    require(name.matches("[a-z][a-zA-Z0-9]*"), s"Param name $name is invalid.")
+    require(doc.nonEmpty) // TODO: more rigorous on doc
+
+    def paramTypeName: String = {
+      val c = implicitly[ClassTag[T]].runtimeClass
+      c match {
+        case _ if c == classOf[Int] => "IntParam"
+        case _ if c == classOf[Long] => "LongParam"
+        case _ if c == classOf[Float] => "FloatParam"
+        case _ if c == classOf[Double] => "DoubleParam"
+        case _ if c == classOf[Boolean] => "BooleanParam"
+        case _ => s"Param[${getTypeString(c)}]"
+      }
+    }
+
+    def valueTypeName: String = {
+      val c = implicitly[ClassTag[T]].runtimeClass
+      getTypeString(c)
+    }
+
+    private def getTypeString(c: Class[_]): String = {
+      c match {
+        case _ if c == classOf[Int] => "Int"
+        case _ if c == classOf[Long] => "Long"
+        case _ if c == classOf[Float] => "Float"
+        case _ if c == classOf[Double] => "Double"
+        case _ if c == classOf[Boolean] => "Boolean"
+        case _ if c == classOf[String] => "String"
+        case _ if c.isArray => s"Array[${getTypeString(c.getComponentType)}]"
+      }
+    }
+  }
+
+  /** Generates the HasParam trait code for the input param. */
+  private def genHasParamTrait(param: ParamDesc[_]): String = {
+    val name = param.name
+    val Name = name(0).toUpper +: name.substring(1)
+    val Param = param.paramTypeName
+    val T = param.valueTypeName
+    val doc = param.doc
+    val defaultValue = param.defaultValueStr
+    val defaultValueDoc = defaultValue.map { v =>
+      s" (default: $v)"
+    }.getOrElse("")
+    val setDefault = defaultValue.map { v =>
+      s"""
+         |  setDefault($name, $v)
+         |""".stripMargin
+    }.getOrElse("")
+
+    s"""
+      |/**
+      | * :: DeveloperApi ::
+      | * Trait for shared param $name$defaultValueDoc.
+      | */
+      |@DeveloperApi
+      |trait Has$Name extends Params {
+      |
+      |  /**
+      |   * Param for $doc.
+      |   * @group param
+      |   */
+      |  final val $name: $Param = new $Param(this, "$name", "$doc")
+      |$setDefault
+      |  /** @group getParam */
+      |  final def get$Name: $T = getOrDefault($name)
+      |}
+      |""".stripMargin
+  }
+
+  /** Generates Scala source code for the input params with header. */
+  private def genSharedParams(params: Seq[ParamDesc[_]]): String = {
+    val header =
+      """/*
+        | * Licensed to the Apache Software Foundation (ASF) under one or more
+        | * contributor license agreements.  See the NOTICE file distributed with
+        | * this work for additional information regarding copyright ownership.
+        | * The ASF licenses this file to You under the Apache License, Version 2.0
+        | * (the "License"); you may not use this file except in compliance with
+        | * the License.  You may obtain a copy of the License at
+        | *
+        | *    http://www.apache.org/licenses/LICENSE-2.0
+        | *
+        | * Unless required by applicable law or agreed to in writing, software
+        | * distributed under the License is distributed on an "AS IS" BASIS,
+        | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+        | * See the License for the specific language governing permissions and
+        | * limitations under the License.
+        | */
+        |
+        |package org.apache.spark.ml.param.shared
+        |
+        |import org.apache.spark.annotation.DeveloperApi
+        |import org.apache.spark.ml.param._
+        |
+        |// DO NOT MODIFY THIS FILE! It was generated by SharedParamsCodeGen.
+        |
+        |// scalastyle:off
+        |""".stripMargin
+
+    val footer = "// scalastyle:on\n"
+
+    val traits = params.map(genHasParamTrait).mkString
+
+    header + traits + footer
+  }
+}
diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala b/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala
new file mode 100644
index 0000000000000..72b08bf276483
--- /dev/null
+++ b/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala
@@ -0,0 +1,259 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.param.shared
+
+import org.apache.spark.annotation.DeveloperApi
+import org.apache.spark.ml.param._
+
+// DO NOT MODIFY THIS FILE! It was generated by SharedParamsCodeGen.
+
+// scalastyle:off
+
+/**
+ * :: DeveloperApi ::
+ * Trait for shared param regParam.
+ */
+@DeveloperApi
+trait HasRegParam extends Params {
+
+  /**
+   * Param for regularization parameter.
+   * @group param
+   */
+  final val regParam: DoubleParam = new DoubleParam(this, "regParam", "regularization parameter")
+
+  /** @group getParam */
+  final def getRegParam: Double = getOrDefault(regParam)
+}
+
+/**
+ * :: DeveloperApi ::
+ * Trait for shared param maxIter.
+ */
+@DeveloperApi
+trait HasMaxIter extends Params {
+
+  /**
+   * Param for max number of iterations.
+   * @group param
+   */
+  final val maxIter: IntParam = new IntParam(this, "maxIter", "max number of iterations")
+
+  /** @group getParam */
+  final def getMaxIter: Int = getOrDefault(maxIter)
+}
+
+/**
+ * :: DeveloperApi ::
+ * Trait for shared param featuresCol (default: "features").
+ */
+@DeveloperApi
+trait HasFeaturesCol extends Params {
+
+  /**
+   * Param for features column name.
+   * @group param
+   */
+  final val featuresCol: Param[String] = new Param[String](this, "featuresCol", "features column name")
+
+  setDefault(featuresCol, "features")
+
+  /** @group getParam */
+  final def getFeaturesCol: String = getOrDefault(featuresCol)
+}
+
+/**
+ * :: DeveloperApi ::
+ * Trait for shared param labelCol (default: "label").
+ */
+@DeveloperApi
+trait HasLabelCol extends Params {
+
+  /**
+   * Param for label column name.
+   * @group param
+   */
+  final val labelCol: Param[String] = new Param[String](this, "labelCol", "label column name")
+
+  setDefault(labelCol, "label")
+
+  /** @group getParam */
+  final def getLabelCol: String = getOrDefault(labelCol)
+}
+
+/**
+ * :: DeveloperApi ::
+ * Trait for shared param predictionCol (default: "prediction").
+ */
+@DeveloperApi
+trait HasPredictionCol extends Params {
+
+  /**
+   * Param for prediction column name.
+   * @group param
+   */
+  final val predictionCol: Param[String] = new Param[String](this, "predictionCol", "prediction column name")
+
+  setDefault(predictionCol, "prediction")
+
+  /** @group getParam */
+  final def getPredictionCol: String = getOrDefault(predictionCol)
+}
+
+/**
+ * :: DeveloperApi ::
+ * Trait for shared param rawPredictionCol (default: "rawPrediction").
+ */
+@DeveloperApi
+trait HasRawPredictionCol extends Params {
+
+  /**
+   * Param for raw prediction (a.k.a. confidence) column name.
+   * @group param
+   */
+  final val rawPredictionCol: Param[String] = new Param[String](this, "rawPredictionCol", "raw prediction (a.k.a. confidence) column name")
+
+  setDefault(rawPredictionCol, "rawPrediction")
+
+  /** @group getParam */
+  final def getRawPredictionCol: String = getOrDefault(rawPredictionCol)
+}
+
+/**
+ * :: DeveloperApi ::
+ * Trait for shared param probabilityCol (default: "probability").
+ */
+@DeveloperApi
+trait HasProbabilityCol extends Params {
+
+  /**
+   * Param for column name for predicted class conditional probabilities.
+   * @group param
+   */
+  final val probabilityCol: Param[String] = new Param[String](this, "probabilityCol", "column name for predicted class conditional probabilities")
+
+  setDefault(probabilityCol, "probability")
+
+  /** @group getParam */
+  final def getProbabilityCol: String = getOrDefault(probabilityCol)
+}
+
+/**
+ * :: DeveloperApi ::
+ * Trait for shared param threshold.
+ */
+@DeveloperApi
+trait HasThreshold extends Params {
+
+  /**
+   * Param for threshold in binary classification prediction.
+   * @group param
+   */
+  final val threshold: DoubleParam = new DoubleParam(this, "threshold", "threshold in binary classification prediction")
+
+  /** @group getParam */
+  final def getThreshold: Double = getOrDefault(threshold)
+}
+
+/**
+ * :: DeveloperApi ::
+ * Trait for shared param inputCol.
+ */
+@DeveloperApi
+trait HasInputCol extends Params {
+
+  /**
+   * Param for input column name.
+   * @group param
+   */
+  final val inputCol: Param[String] = new Param[String](this, "inputCol", "input column name")
+
+  /** @group getParam */
+  final def getInputCol: String = getOrDefault(inputCol)
+}
+
+/**
+ * :: DeveloperApi ::
+ * Trait for shared param inputCols.
+ */
+@DeveloperApi
+trait HasInputCols extends Params {
+
+  /**
+   * Param for input column names.
+   * @group param
+   */
+  final val inputCols: Param[Array[String]] = new Param[Array[String]](this, "inputCols", "input column names")
+
+  /** @group getParam */
+  final def getInputCols: Array[String] = getOrDefault(inputCols)
+}
+
+/**
+ * :: DeveloperApi ::
+ * Trait for shared param outputCol.
+ */
+@DeveloperApi
+trait HasOutputCol extends Params {
+
+  /**
+   * Param for output column name.
+   * @group param
+   */
+  final val outputCol: Param[String] = new Param[String](this, "outputCol", "output column name")
+
+  /** @group getParam */
+  final def getOutputCol: String = getOrDefault(outputCol)
+}
+
+/**
+ * :: DeveloperApi ::
+ * Trait for shared param checkpointInterval.
+ */
+@DeveloperApi
+trait HasCheckpointInterval extends Params {
+
+  /**
+   * Param for checkpoint interval.
+   * @group param
+   */
+  final val checkpointInterval: IntParam = new IntParam(this, "checkpointInterval", "checkpoint interval")
+
+  /** @group getParam */
+  final def getCheckpointInterval: Int = getOrDefault(checkpointInterval)
+}
+
+/**
+ * :: DeveloperApi ::
+ * Trait for shared param fitIntercept (default: true).
+ */
+@DeveloperApi
+trait HasFitIntercept extends Params {
+
+  /**
+   * Param for whether to fit an intercept term.
+   * @group param
+   */
+  final val fitIntercept: BooleanParam = new BooleanParam(this, "fitIntercept", "whether to fit an intercept term")
+
+  setDefault(fitIntercept, true)
+
+  /** @group getParam */
+  final def getFitIntercept: Boolean = getOrDefault(fitIntercept)
+}
+// scalastyle:on
diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/sharedParams.scala b/mllib/src/main/scala/org/apache/spark/ml/param/sharedParams.scala
deleted file mode 100644
index 07e6eb417763d..0000000000000
--- a/mllib/src/main/scala/org/apache/spark/ml/param/sharedParams.scala
+++ /dev/null
@@ -1,173 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License.  You may obtain a copy of the License at
- *
- *    http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package org.apache.spark.ml.param
-
-/* NOTE TO DEVELOPERS:
- * If you mix these parameter traits into your algorithm, please add a setter method as well
- * so that users may use a builder pattern:
- *  val myLearner = new MyLearner().setParam1(x).setParam2(y)...
- */
-
-private[ml] trait HasRegParam extends Params {
-  /**
-   * param for regularization parameter
-   * @group param
-   */
-  val regParam: DoubleParam = new DoubleParam(this, "regParam", "regularization parameter")
-
-  /** @group getParam */
-  def getRegParam: Double = get(regParam)
-}
-
-private[ml] trait HasMaxIter extends Params {
-  /**
-   * param for max number of iterations
-   * @group param
-   */
-  val maxIter: IntParam = new IntParam(this, "maxIter", "max number of iterations")
-
-  /** @group getParam */
-  def getMaxIter: Int = get(maxIter)
-}
-
-private[ml] trait HasFeaturesCol extends Params {
-  /**
-   * param for features column name
-   * @group param
-   */
-  val featuresCol: Param[String] =
-    new Param(this, "featuresCol", "features column name", Some("features"))
-
-  /** @group getParam */
-  def getFeaturesCol: String = get(featuresCol)
-}
-
-private[ml] trait HasLabelCol extends Params {
-  /**
-   * param for label column name
-   * @group param
-   */
-  val labelCol: Param[String] = new Param(this, "labelCol", "label column name", Some("label"))
-
-  /** @group getParam */
-  def getLabelCol: String = get(labelCol)
-}
-
-private[ml] trait HasPredictionCol extends Params {
-  /**
-   * param for prediction column name
-   * @group param
-   */
-  val predictionCol: Param[String] =
-    new Param(this, "predictionCol", "prediction column name", Some("prediction"))
-
-  /** @group getParam */
-  def getPredictionCol: String = get(predictionCol)
-}
-
-private[ml] trait HasRawPredictionCol extends Params {
-  /**
-   * param for raw prediction column name
-   * @group param
-   */
-  val rawPredictionCol: Param[String] =
-    new Param(this, "rawPredictionCol", "raw prediction (a.k.a. confidence) column name",
-      Some("rawPrediction"))
-
-  /** @group getParam */
-  def getRawPredictionCol: String = get(rawPredictionCol)
-}
-
-private[ml] trait HasProbabilityCol extends Params {
-  /**
-   * param for predicted class conditional probabilities column name
-   * @group param
-   */
-  val probabilityCol: Param[String] =
-    new Param(this, "probabilityCol", "column name for predicted class conditional probabilities",
-      Some("probability"))
-
-  /** @group getParam */
-  def getProbabilityCol: String = get(probabilityCol)
-}
-
-private[ml] trait HasFitIntercept extends Params {
-  /**
-   * param for fitting the intercept term, defaults to true
-   * @group param
-   */
-  val fitIntercept: BooleanParam =
-    new BooleanParam(this, "fitIntercept", "indicates whether to fit an intercept term", Some(true))
-
-  /** @group getParam */
-  def getFitIntercept: Boolean = get(fitIntercept)
-}
-
-private[ml] trait HasThreshold extends Params {
-  /**
-   * param for threshold in (binary) prediction
-   * @group param
-   */
-  val threshold: DoubleParam = new DoubleParam(this, "threshold", "threshold in prediction")
-
-  /** @group getParam */
-  def getThreshold: Double = get(threshold)
-}
-
-private[ml] trait HasInputCol extends Params {
-  /**
-   * param for input column name
-   * @group param
-   */
-  val inputCol: Param[String] = new Param(this, "inputCol", "input column name")
-
-  /** @group getParam */
-  def getInputCol: String = get(inputCol)
-}
-
-private[ml] trait HasInputCols extends Params {
-  /**
-   * Param for input column names.
-   */
-  val inputCols: Param[Array[String]] = new Param(this, "inputCols", "input column names")
-
-  /** @group getParam */
-  def getInputCols: Array[String] = get(inputCols)
-}
-
-private[ml] trait HasOutputCol extends Params {
-  /**
-   * param for output column name
-   * @group param
-   */
-  val outputCol: Param[String] = new Param(this, "outputCol", "output column name")
-
-  /** @group getParam */
-  def getOutputCol: String = get(outputCol)
-}
-
-private[ml] trait HasCheckpointInterval extends Params {
-  /**
-   * param for checkpoint interval
-   * @group param
-   */
-  val checkpointInterval: IntParam = new IntParam(this, "checkpointInterval", "checkpoint interval")
-
-  /** @group getParam */
-  def getCheckpointInterval: Int = get(checkpointInterval)
-}
diff --git a/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala b/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
index 52c9e95d6012f..bd793beba35b6 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
@@ -34,6 +34,7 @@ import org.apache.spark.{Logging, Partitioner}
 import org.apache.spark.annotation.DeveloperApi
 import org.apache.spark.ml.{Estimator, Model}
 import org.apache.spark.ml.param._
+import org.apache.spark.ml.param.shared._
 import org.apache.spark.mllib.optimization.NNLS
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.DataFrame
@@ -54,86 +55,88 @@ private[recommendation] trait ALSParams extends Params with HasMaxIter with HasR
    * Param for rank of the matrix factorization.
    * @group param
    */
-  val rank = new IntParam(this, "rank", "rank of the factorization", Some(10))
+  val rank = new IntParam(this, "rank", "rank of the factorization")
 
   /** @group getParam */
-  def getRank: Int = get(rank)
+  def getRank: Int = getOrDefault(rank)
 
   /**
    * Param for number of user blocks.
    * @group param
    */
-  val numUserBlocks = new IntParam(this, "numUserBlocks", "number of user blocks", Some(10))
+  val numUserBlocks = new IntParam(this, "numUserBlocks", "number of user blocks")
 
   /** @group getParam */
-  def getNumUserBlocks: Int = get(numUserBlocks)
+  def getNumUserBlocks: Int = getOrDefault(numUserBlocks)
 
   /**
    * Param for number of item blocks.
    * @group param
    */
   val numItemBlocks =
-    new IntParam(this, "numItemBlocks", "number of item blocks", Some(10))
+    new IntParam(this, "numItemBlocks", "number of item blocks")
 
   /** @group getParam */
-  def getNumItemBlocks: Int = get(numItemBlocks)
+  def getNumItemBlocks: Int = getOrDefault(numItemBlocks)
 
   /**
    * Param to decide whether to use implicit preference.
    * @group param
    */
-  val implicitPrefs =
-    new BooleanParam(this, "implicitPrefs", "whether to use implicit preference", Some(false))
+  val implicitPrefs = new BooleanParam(this, "implicitPrefs", "whether to use implicit preference")
 
   /** @group getParam */
-  def getImplicitPrefs: Boolean = get(implicitPrefs)
+  def getImplicitPrefs: Boolean = getOrDefault(implicitPrefs)
 
   /**
    * Param for the alpha parameter in the implicit preference formulation.
    * @group param
    */
-  val alpha = new DoubleParam(this, "alpha", "alpha for implicit preference", Some(1.0))
+  val alpha = new DoubleParam(this, "alpha", "alpha for implicit preference")
 
   /** @group getParam */
-  def getAlpha: Double = get(alpha)
+  def getAlpha: Double = getOrDefault(alpha)
 
   /**
    * Param for the column name for user ids.
    * @group param
    */
-  val userCol = new Param[String](this, "userCol", "column name for user ids", Some("user"))
+  val userCol = new Param[String](this, "userCol", "column name for user ids")
 
   /** @group getParam */
-  def getUserCol: String = get(userCol)
+  def getUserCol: String = getOrDefault(userCol)
 
   /**
    * Param for the column name for item ids.
    * @group param
    */
-  val itemCol =
-    new Param[String](this, "itemCol", "column name for item ids", Some("item"))
+  val itemCol = new Param[String](this, "itemCol", "column name for item ids")
 
   /** @group getParam */
-  def getItemCol: String = get(itemCol)
+  def getItemCol: String = getOrDefault(itemCol)
 
   /**
    * Param for the column name for ratings.
    * @group param
    */
-  val ratingCol = new Param[String](this, "ratingCol", "column name for ratings", Some("rating"))
+  val ratingCol = new Param[String](this, "ratingCol", "column name for ratings")
 
   /** @group getParam */
-  def getRatingCol: String = get(ratingCol)
+  def getRatingCol: String = getOrDefault(ratingCol)
 
   /**
    * Param for whether to apply nonnegativity constraints.
    * @group param
    */
   val nonnegative = new BooleanParam(
-    this, "nonnegative", "whether to use nonnegative constraint for least squares", Some(false))
+    this, "nonnegative", "whether to use nonnegative constraint for least squares")
 
   /** @group getParam */
-  val getNonnegative: Boolean = get(nonnegative)
+  def getNonnegative: Boolean = getOrDefault(nonnegative)
+
+  setDefault(rank -> 10, maxIter -> 10, regParam -> 0.1, numUserBlocks -> 10, numItemBlocks -> 10,
+    implicitPrefs -> false, alpha -> 1.0, userCol -> "user", itemCol -> "item",
+    ratingCol -> "rating", nonnegative -> false)
 
   /**
    * Validates and transforms the input schema.
@@ -142,7 +145,7 @@ private[recommendation] trait ALSParams extends Params with HasMaxIter with HasR
    * @return output schema
    */
   protected def validateAndTransformSchema(schema: StructType, paramMap: ParamMap): StructType = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     assert(schema(map(userCol)).dataType == IntegerType)
     assert(schema(map(itemCol)).dataType== IntegerType)
     val ratingType = schema(map(ratingCol)).dataType
@@ -171,7 +174,7 @@ class ALSModel private[ml] (
 
   override def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame = {
     import dataset.sqlContext.implicits._
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val users = userFactors.toDF("id", "features")
     val items = itemFactors.toDF("id", "features")
 
@@ -283,7 +286,7 @@ class ALS extends Estimator[ALSModel] with ALSParams {
   setCheckpointInterval(10)
 
   override def fit(dataset: DataFrame, paramMap: ParamMap): ALSModel = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val ratings = dataset
       .select(col(map(userCol)), col(map(itemCol)), col(map(ratingCol)).cast(FloatType))
       .map { row =>
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
index 65f6627a0c351..26ca7459c4fdf 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
@@ -18,7 +18,8 @@
 package org.apache.spark.ml.regression
 
 import org.apache.spark.annotation.AlphaComponent
-import org.apache.spark.ml.param.{Params, ParamMap, HasMaxIter, HasRegParam}
+import org.apache.spark.ml.param.{Params, ParamMap}
+import org.apache.spark.ml.param.shared._
 import org.apache.spark.mllib.linalg.{BLAS, Vector}
 import org.apache.spark.mllib.regression.LinearRegressionWithSGD
 import org.apache.spark.sql.DataFrame
@@ -41,8 +42,7 @@ private[regression] trait LinearRegressionParams extends RegressorParams
 class LinearRegression extends Regressor[Vector, LinearRegression, LinearRegressionModel]
   with LinearRegressionParams {
 
-  setRegParam(0.1)
-  setMaxIter(100)
+  setDefault(regParam -> 0.1, maxIter -> 100)
 
   /** @group setParam */
   def setRegParam(value: Double): this.type = set(regParam, value)
@@ -93,7 +93,7 @@ class LinearRegressionModel private[ml] (
 
   override protected def copy(): LinearRegressionModel = {
     val m = new LinearRegressionModel(parent, fittingParamMap, weights, intercept)
-    Params.inheritValues(this.paramMap, this, m)
+    Params.inheritValues(extractParamMap(), this, m)
     m
   }
 }
diff --git a/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala b/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala
index 2eb1dac56f1e9..4bb4ed813c006 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala
@@ -31,6 +31,7 @@ import org.apache.spark.sql.types.StructType
  * Params for [[CrossValidator]] and [[CrossValidatorModel]].
  */
 private[ml] trait CrossValidatorParams extends Params {
+
   /**
    * param for the estimator to be cross-validated
    * @group param
@@ -38,7 +39,7 @@ private[ml] trait CrossValidatorParams extends Params {
   val estimator: Param[Estimator[_]] = new Param(this, "estimator", "estimator for selection")
 
   /** @group getParam */
-  def getEstimator: Estimator[_] = get(estimator)
+  def getEstimator: Estimator[_] = getOrDefault(estimator)
 
   /**
    * param for estimator param maps
@@ -48,7 +49,7 @@ private[ml] trait CrossValidatorParams extends Params {
     new Param(this, "estimatorParamMaps", "param maps for the estimator")
 
   /** @group getParam */
-  def getEstimatorParamMaps: Array[ParamMap] = get(estimatorParamMaps)
+  def getEstimatorParamMaps: Array[ParamMap] = getOrDefault(estimatorParamMaps)
 
   /**
    * param for the evaluator for selection
@@ -57,17 +58,18 @@ private[ml] trait CrossValidatorParams extends Params {
   val evaluator: Param[Evaluator] = new Param(this, "evaluator", "evaluator for selection")
 
   /** @group getParam */
-  def getEvaluator: Evaluator = get(evaluator)
+  def getEvaluator: Evaluator = getOrDefault(evaluator)
 
   /**
    * param for number of folds for cross validation
    * @group param
    */
-  val numFolds: IntParam =
-    new IntParam(this, "numFolds", "number of folds for cross validation", Some(3))
+  val numFolds: IntParam = new IntParam(this, "numFolds", "number of folds for cross validation")
 
   /** @group getParam */
-  def getNumFolds: Int = get(numFolds)
+  def getNumFolds: Int = getOrDefault(numFolds)
+
+  setDefault(numFolds -> 3)
 }
 
 /**
@@ -92,7 +94,7 @@ class CrossValidator extends Estimator[CrossValidatorModel] with CrossValidatorP
   def setNumFolds(value: Int): this.type = set(numFolds, value)
 
   override def fit(dataset: DataFrame, paramMap: ParamMap): CrossValidatorModel = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     val schema = dataset.schema
     transformSchema(dataset.schema, paramMap, logging = true)
     val sqlCtx = dataset.sqlContext
@@ -130,7 +132,7 @@ class CrossValidator extends Estimator[CrossValidatorModel] with CrossValidatorP
   }
 
   override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
     map(estimator).transformSchema(schema, paramMap)
   }
 }
diff --git a/mllib/src/main/scala/org/apache/spark/ml/util/SchemaUtils.scala b/mllib/src/main/scala/org/apache/spark/ml/util/SchemaUtils.scala
new file mode 100644
index 0000000000000..0383bf0b382b7
--- /dev/null
+++ b/mllib/src/main/scala/org/apache/spark/ml/util/SchemaUtils.scala
@@ -0,0 +1,61 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.util
+
+import org.apache.spark.annotation.DeveloperApi
+import org.apache.spark.sql.types.{DataType, StructField, StructType}
+
+/**
+ * :: DeveloperApi ::
+ * Utils for handling schemas.
+ */
+@DeveloperApi
+object SchemaUtils {
+
+  // TODO: Move the utility methods to SQL.
+
+  /**
+   * Check whether the given schema contains a column of the required data type.
+   * @param colName  column name
+   * @param dataType  required column data type
+   */
+  def checkColumnType(schema: StructType, colName: String, dataType: DataType): Unit = {
+    val actualDataType = schema(colName).dataType
+    require(actualDataType.equals(dataType),
+      s"Column $colName must be of type $dataType but was actually $actualDataType.")
+  }
+
+  /**
+   * Appends a new column to the input schema. This fails if the given output column already exists.
+   * @param schema input schema
+   * @param colName new column name. If this column name is an empty string "", this method returns
+   *                the input schema unchanged. This allows users to disable output columns.
+   * @param dataType new column data type
+   * @return new schema with the input column appended
+   */
+  def appendColumn(
+      schema: StructType,
+      colName: String,
+      dataType: DataType): StructType = {
+    if (colName.isEmpty) return schema
+    val fieldNames = schema.fieldNames
+    require(!fieldNames.contains(colName), s"Column $colName already exists.")
+    val outputFields = schema.fields :+ StructField(colName, dataType, nullable = false)
+    StructType(outputFields)
+  }
+}
diff --git a/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala
index 1ce2987612378..88ea679eeaad5 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala
@@ -21,19 +21,25 @@ import org.scalatest.FunSuite
 
 class ParamsSuite extends FunSuite {
 
-  val solver = new TestParams()
-  import solver.{inputCol, maxIter}
-
   test("param") {
+    val solver = new TestParams()
+    import solver.{maxIter, inputCol}
+
     assert(maxIter.name === "maxIter")
     assert(maxIter.doc === "max number of iterations")
-    assert(maxIter.defaultValue.get === 100)
     assert(maxIter.parent.eq(solver))
-    assert(maxIter.toString === "maxIter: max number of iterations (default: 100)")
-    assert(inputCol.defaultValue === None)
+    assert(maxIter.toString === "maxIter: max number of iterations (default: 10)")
+
+    solver.setMaxIter(5)
+    assert(maxIter.toString === "maxIter: max number of iterations (default: 10, current: 5)")
+
+    assert(inputCol.toString === "inputCol: input column name (undefined)")
   }
 
   test("param pair") {
+    val solver = new TestParams()
+    import solver.maxIter
+
     val pair0 = maxIter -> 5
     val pair1 = maxIter.w(5)
     val pair2 = ParamPair(maxIter, 5)
@@ -44,10 +50,12 @@ class ParamsSuite extends FunSuite {
   }
 
   test("param map") {
+    val solver = new TestParams()
+    import solver.{maxIter, inputCol}
+
     val map0 = ParamMap.empty
 
     assert(!map0.contains(maxIter))
-    assert(map0(maxIter) === maxIter.defaultValue.get)
     map0.put(maxIter, 10)
     assert(map0.contains(maxIter))
     assert(map0(maxIter) === 10)
@@ -78,23 +86,39 @@ class ParamsSuite extends FunSuite {
   }
 
   test("params") {
+    val solver = new TestParams()
+    import solver.{maxIter, inputCol}
+
     val params = solver.params
-    assert(params.size === 2)
+    assert(params.length === 2)
     assert(params(0).eq(inputCol), "params must be ordered by name")
     assert(params(1).eq(maxIter))
+
+    assert(!solver.isSet(maxIter))
+    assert(solver.isDefined(maxIter))
+    assert(solver.getMaxIter === 10)
+    solver.setMaxIter(100)
+    assert(solver.isSet(maxIter))
+    assert(solver.getMaxIter === 100)
+    assert(!solver.isSet(inputCol))
+    assert(!solver.isDefined(inputCol))
+    intercept[NoSuchElementException](solver.getInputCol)
+
     assert(solver.explainParams() === Seq(inputCol, maxIter).mkString("\n"))
+
     assert(solver.getParam("inputCol").eq(inputCol))
     assert(solver.getParam("maxIter").eq(maxIter))
-    intercept[NoSuchMethodException] {
+    intercept[NoSuchElementException] {
       solver.getParam("abc")
     }
-    assert(!solver.isSet(inputCol))
+
     intercept[IllegalArgumentException] {
       solver.validate()
     }
     solver.validate(ParamMap(inputCol -> "input"))
     solver.setInputCol("input")
     assert(solver.isSet(inputCol))
+    assert(solver.isDefined(inputCol))
     assert(solver.getInputCol === "input")
     solver.validate()
     intercept[IllegalArgumentException] {
@@ -104,5 +128,8 @@ class ParamsSuite extends FunSuite {
     intercept[IllegalArgumentException] {
       solver.validate()
     }
+
+    solver.clearMaxIter()
+    assert(!solver.isSet(maxIter))
   }
 }
diff --git a/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala b/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala
index ce52f2f230085..8f9ab687c05cb 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala
@@ -20,17 +20,21 @@ package org.apache.spark.ml.param
 /** A subclass of Params for testing. */
 class TestParams extends Params {
 
-  val maxIter = new IntParam(this, "maxIter", "max number of iterations", Some(100))
+  val maxIter = new IntParam(this, "maxIter", "max number of iterations")
   def setMaxIter(value: Int): this.type = { set(maxIter, value); this }
-  def getMaxIter: Int = get(maxIter)
+  def getMaxIter: Int = getOrDefault(maxIter)
 
   val inputCol = new Param[String](this, "inputCol", "input column name")
   def setInputCol(value: String): this.type = { set(inputCol, value); this }
-  def getInputCol: String = get(inputCol)
+  def getInputCol: String = getOrDefault(inputCol)
+
+  setDefault(maxIter -> 10)
 
   override def validate(paramMap: ParamMap): Unit = {
-    val m = this.paramMap ++ paramMap
+    val m = extractParamMap(paramMap)
     require(m(maxIter) >= 0)
     require(m.contains(inputCol))
   }
+
+  def clearMaxIter(): this.type = clear(maxIter)
 }

From 77eeb10fd1f5beb558d6278d9443d267fc6c2f62 Mon Sep 17 00:00:00 2001
From: Brennon York <brennon.york@capitalone.com>
Date: Mon, 13 Apr 2015 22:31:44 -0700
Subject: [PATCH 95/95] [WIP][HOTFIX][SPARK-4123]: Fix bug in PR dependency
 (all deps. removed issue)

We're seeing a bug sporadically in the new PR dependency comparison test whereby it notes that *all* dependencies are removed. This happens when the current PR is built, but the final, sorted, dependency file is left blank. I believe this is an error either in the way the `git checkout` calls have been or an error within the `mvn` build for that PR (again, likely related to the `git checkout`). As such I've set the checkouts to now force (with `-f` flag) which is more in line with what Jenkins currently does on the initial checkout.

Setting this as a WIP for now to trigger the build process myriad times to see if the issue still arises.

Author: Brennon York <brennon.york@capitalone.com>

Closes #5443 from brennonyork/HOTFIX2-SPARK-4123 and squashes the following commits:

f2186be [Brennon York] added output for the various git commit refs
3f073d6 [Brennon York] removed the git checkouts piping to dev null
07765a6 [Brennon York] updated the diff logic to reference the filenames rather than hardlink
e3f63c7 [Brennon York] added '-f' to the checkout flags for git
710c8d1 [Brennon York] added 30 minutes to the test benchmark
---
 dev/run-tests-jenkins            | 4 ++++
 dev/tests/pr_new_dependencies.sh | 8 ++++----
 2 files changed, 8 insertions(+), 4 deletions(-)

diff --git a/dev/run-tests-jenkins b/dev/run-tests-jenkins
index f6372835a6dbf..3c1c91a111357 100755
--- a/dev/run-tests-jenkins
+++ b/dev/run-tests-jenkins
@@ -161,6 +161,10 @@ pr_message=""
 # Ensure we save off the current HEAD to revert to
 current_pr_head="`git rev-parse HEAD`"
 
+echo "HEAD:  `git rev-parse HEAD`"
+echo "GHPRB: $ghprbActualCommit"
+echo "SHA1:  $sha1"
+
 # Run pull request tests
 for t in "${PR_TESTS[@]}"; do
   this_test="${FWDIR}/dev/tests/${t}.sh"
diff --git a/dev/tests/pr_new_dependencies.sh b/dev/tests/pr_new_dependencies.sh
index 370c7cc737bbd..fdfb3c62aff58 100755
--- a/dev/tests/pr_new_dependencies.sh
+++ b/dev/tests/pr_new_dependencies.sh
@@ -39,12 +39,12 @@ CURR_CP_FILE="my-classpath.txt"
 MASTER_CP_FILE="master-classpath.txt"
 
 # First switch over to the master branch
-git checkout master &>/dev/null
+git checkout -f master
 # Find and copy all pom.xml files into a *.gate file that we can check
 # against through various `git` changes
 find -name "pom.xml" -exec cp {} {}.gate \;
 # Switch back to the current PR
-git checkout "${current_pr_head}" &>/dev/null
+git checkout -f "${current_pr_head}"
 
 # Check if any *.pom files from the current branch are different from the master
 difference_q=""
@@ -71,7 +71,7 @@ else
     sort > ${CURR_CP_FILE}
 
   # Checkout the master branch to compare against
-  git checkout master &>/dev/null
+  git checkout -f master
 
   ${MVN_BIN} clean package dependency:build-classpath -DskipTests 2>/dev/null | \
     sed -n -e '/Building Spark Project Assembly/,$p' | \
@@ -84,7 +84,7 @@ else
     rev | \
     sort > ${MASTER_CP_FILE}
 
-  DIFF_RESULTS="`diff my-classpath.txt master-classpath.txt`"
+  DIFF_RESULTS="`diff ${CURR_CP_FILE} ${MASTER_CP_FILE}`"
 
   if [ -z "${DIFF_RESULTS}" ]; then
     echo " * This patch does not change any dependencies."