Merge branch 'master' of github.com:apache/spark into viz2

R/pkg/NAMESPACE

@@ -71,6 +71,7 @@ exportMethods(
               "unpersist",
               "value",
               "values",
+              "zipPartitions",
               "zipRDD",
               "zipWithIndex",
               "zipWithUniqueId"

R/pkg/R/RDD.R

@@ -66,6 +66,11 @@ setMethod("initialize", "RDD", function(.Object, jrdd, serializedMode,
   .Object
 })
 
+setMethod("show", "RDD",
+          function(.Object) {
+              cat(paste(callJMethod(.Object@jrdd, "toString"), "\n", sep=""))
+          })
+
 setMethod("initialize", "PipelinedRDD", function(.Object, prev, func, jrdd_val) {
   .Object@env <- new.env()
   .Object@env$isCached <- FALSE
@@ -1590,3 +1595,49 @@ setMethod("intersection",
 
             keys(filterRDD(cogroup(rdd1, rdd2, numPartitions = numPartitions), filterFunction))
           })
+
+#' Zips an RDD's partitions with one (or more) RDD(s).
+#' Same as zipPartitions in Spark.
+#' 
+#' @param ... RDDs to be zipped.
+#' @param func A function to transform zipped partitions.
+#' @return A new RDD by applying a function to the zipped partitions. 
+#'         Assumes that all the RDDs have the *same number of partitions*, but 
+#'         does *not* require them to have the same number of elements in each partition.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd1 <- parallelize(sc, 1:2, 2L)  # 1, 2
+#' rdd2 <- parallelize(sc, 1:4, 2L)  # 1:2, 3:4
+#' rdd3 <- parallelize(sc, 1:6, 2L)  # 1:3, 4:6
+#' collect(zipPartitions(rdd1, rdd2, rdd3, 
+#'                       func = function(x, y, z) { list(list(x, y, z))} ))
+#' # list(list(1, c(1,2), c(1,2,3)), list(2, c(3,4), c(4,5,6)))
+#'}
+#' @rdname zipRDD
+#' @aliases zipPartitions,RDD
+setMethod("zipPartitions",
+          "RDD",
+          function(..., func) {
+            rrdds <- list(...)
+            if (length(rrdds) == 1) {
+              return(rrdds[[1]])
+            }
+            nPart <- sapply(rrdds, numPartitions)
+            if (length(unique(nPart)) != 1) {
+              stop("Can only zipPartitions RDDs which have the same number of partitions.")
+            }
+
+            rrdds <- lapply(rrdds, function(rdd) {
+              mapPartitionsWithIndex(rdd, function(partIndex, part) {
+                print(length(part))
+                list(list(partIndex, part))
+              })
+            })
+            union.rdd <- Reduce(unionRDD, rrdds)
+            zipped.rdd <- values(groupByKey(union.rdd, numPartitions = nPart[1]))
+            res <- mapPartitions(zipped.rdd, function(plist) {
+              do.call(func, plist[[1]])
+            })
+            res
+          })

R/pkg/R/generics.R

@@ -217,6 +217,11 @@ setGeneric("unpersist", function(x, ...) { standardGeneric("unpersist") })
 #' @export
 setGeneric("zipRDD", function(x, other) { standardGeneric("zipRDD") })
 
+#' @rdname zipRDD
+#' @export
+setGeneric("zipPartitions", function(..., func) { standardGeneric("zipPartitions") }, 
+           signature = "...")
+
 #' @rdname zipWithIndex
 #' @seealso zipWithUniqueId
 #' @export

R/pkg/inst/tests/test_binary_function.R

@@ -66,3 +66,36 @@ test_that("cogroup on two RDDs", {
   expect_equal(sortKeyValueList(actual),
                sortKeyValueList(expected))
 })
+
+test_that("zipPartitions() on RDDs", {
+  rdd1 <- parallelize(sc, 1:2, 2L)  # 1, 2
+  rdd2 <- parallelize(sc, 1:4, 2L)  # 1:2, 3:4
+  rdd3 <- parallelize(sc, 1:6, 2L)  # 1:3, 4:6
+  actual <- collect(zipPartitions(rdd1, rdd2, rdd3, 
+                                  func = function(x, y, z) { list(list(x, y, z))} ))
+  expect_equal(actual,
+               list(list(1, c(1,2), c(1,2,3)), list(2, c(3,4), c(4,5,6))))
+
+  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(zipPartitions(rdd, rdd, 
+                                  func = function(x, y) { list(paste(x, y, sep = "\n")) }))
+  expected <- list(paste(mockFile, mockFile, sep = "\n"))
+  expect_equal(actual, expected)
+
+  rdd1 <- parallelize(sc, 0:1, 1)
+  actual <- collect(zipPartitions(rdd1, rdd, 
+                                  func = function(x, y) { list(x + nchar(y)) }))
+  expected <- list(0:1 + nchar(mockFile))
+  expect_equal(actual, expected)
+
+  rdd <- map(rdd, function(x) { x })
+  actual <- collect(zipPartitions(rdd, rdd1, 
+                                  func = function(x, y) { list(y + nchar(x)) }))
+  expect_equal(actual, expected)
+
+  unlink(fileName)
+})

R/pkg/inst/tests/test_rdd.R

@@ -759,6 +759,11 @@ test_that("collectAsMap() on a pairwise RDD", {
   expect_equal(vals, list(`1` = "a", `2` = "b"))
 })
 
+test_that("show()", {
+  rdd <- parallelize(sc, list(1:10))    
+  expect_output(show(rdd), "ParallelCollectionRDD\\[\\d+\\] at parallelize at RRDD\\.scala:\\d+")
+})
+
 test_that("sampleByKey() on pairwise RDDs", {
   rdd <- parallelize(sc, 1:2000)
   pairsRDD <- lapply(rdd, function(x) { if (x %% 2 == 0) list("a", x) else list("b", x) })

core/src/main/scala/org/apache/spark/SparkContext.scala

@@ -223,6 +223,7 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli
   private var _listenerBusStarted: Boolean = false
   private var _jars: Seq[String] = _
   private var _files: Seq[String] = _
+  private var _shutdownHookRef: AnyRef = _
 
   /* ------------------------------------------------------------------------------------- *
    | Accessors and public fields. These provide access to the internal state of the        |
@@ -517,6 +518,14 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli
     _taskScheduler.postStartHook()
     _env.metricsSystem.registerSource(new DAGSchedulerSource(dagScheduler))
     _env.metricsSystem.registerSource(new BlockManagerSource(_env.blockManager))
+
+    // Make sure the context is stopped if the user forgets about it. This avoids leaving
+    // unfinished event logs around after the JVM exits cleanly. It doesn't help if the JVM
+    // is killed, though.
+    _shutdownHookRef = Utils.addShutdownHook(Utils.SPARK_CONTEXT_SHUTDOWN_PRIORITY) { () =>
+      logInfo("Invoking stop() from shutdown hook")
+      stop()
+    }
   } catch {
     case NonFatal(e) =>
       logError("Error initializing SparkContext.", e)
@@ -1065,7 +1074,7 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli
   /** Build the union of a list of RDDs. */
   def union[T: ClassTag](rdds: Seq[RDD[T]]): RDD[T] = withRDDScope {
     val partitioners = rdds.flatMap(_.partitioner).toSet
-    if (partitioners.size == 1) {
+    if (rdds.forall(_.partitioner.isDefined) && partitioners.size == 1) {
       new PartitionerAwareUnionRDD(this, rdds)
     } else {
       new UnionRDD(this, rdds)
@@ -1492,6 +1501,9 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli
       logInfo("SparkContext already stopped.")
       return
     }
+    if (_shutdownHookRef != null) {
+      Utils.removeShutdownHook(_shutdownHookRef)
+    }
 
     postApplicationEnd()
     _ui.foreach(_.stop())
@@ -1902,7 +1914,7 @@ object SparkContext extends Logging {
    *
    * Access to this field is guarded by SPARK_CONTEXT_CONSTRUCTOR_LOCK.
    */
-  private val activeContext: AtomicReference[SparkContext] = 
+  private val activeContext: AtomicReference[SparkContext] =
     new AtomicReference[SparkContext](null)
 
   /**
@@ -1955,11 +1967,11 @@ object SparkContext extends Logging {
   }
 
   /**
-   * This function may be used to get or instantiate a SparkContext and register it as a 
-   * singleton object. Because we can only have one active SparkContext per JVM, 
-   * this is useful when applications may wish to share a SparkContext. 
+   * This function may be used to get or instantiate a SparkContext and register it as a
+   * singleton object. Because we can only have one active SparkContext per JVM,
+   * this is useful when applications may wish to share a SparkContext.
    *
-   * Note: This function cannot be used to create multiple SparkContext instances 
+   * Note: This function cannot be used to create multiple SparkContext instances
    * even if multiple contexts are allowed.
    */
   def getOrCreate(config: SparkConf): SparkContext = {
@@ -1972,17 +1984,17 @@ object SparkContext extends Logging {
       activeContext.get()
     }
   }
-  
+
   /**
-   * This function may be used to get or instantiate a SparkContext and register it as a 
-   * singleton object. Because we can only have one active SparkContext per JVM, 
+   * This function may be used to get or instantiate a SparkContext and register it as a
+   * singleton object. Because we can only have one active SparkContext per JVM,
    * this is useful when applications may wish to share a SparkContext.
-   * 
+   *
    * This method allows not passing a SparkConf (useful if just retrieving).
-   * 
-   * Note: This function cannot be used to create multiple SparkContext instances 
-   * even if multiple contexts are allowed. 
-   */ 
+   *
+   * Note: This function cannot be used to create multiple SparkContext instances
+   * even if multiple contexts are allowed.
+   */
   def getOrCreate(): SparkContext = {
     getOrCreate(new SparkConf())
   }

core/src/main/scala/org/apache/spark/rdd/PartitionerAwareUnionRDD.scala

@@ -60,6 +60,7 @@ class PartitionerAwareUnionRDD[T: ClassTag](
     var rdds: Seq[RDD[T]]
   ) extends RDD[T](sc, rdds.map(x => new OneToOneDependency(x))) {
   require(rdds.length > 0)
+  require(rdds.forall(_.partitioner.isDefined))
   require(rdds.flatMap(_.partitioner).toSet.size == 1,
     "Parent RDDs have different partitioners: " + rdds.flatMap(_.partitioner))
 

core/src/main/scala/org/apache/spark/util/SizeEstimator.scala

@@ -179,7 +179,7 @@ private[spark] object SizeEstimator extends Logging {
   }
 
   // Estimate the size of arrays larger than ARRAY_SIZE_FOR_SAMPLING by sampling.
-  private val ARRAY_SIZE_FOR_SAMPLING = 200
+  private val ARRAY_SIZE_FOR_SAMPLING = 400
   private val ARRAY_SAMPLE_SIZE = 100 // should be lower than ARRAY_SIZE_FOR_SAMPLING
 
   private def visitArray(array: AnyRef, arrayClass: Class[_], state: SearchState) {
@@ -204,25 +204,40 @@ private[spark] object SizeEstimator extends Logging {
         }
       } else {
         // Estimate the size of a large array by sampling elements without replacement.
-        var size = 0.0
+        // To exclude the shared objects that the array elements may link, sample twice
+        // and use the min one to caculate array size.
         val rand = new Random(42)
-        val drawn = new OpenHashSet[Int](ARRAY_SAMPLE_SIZE)
-        var numElementsDrawn = 0
-        while (numElementsDrawn < ARRAY_SAMPLE_SIZE) {
-          var index = 0
-          do {
-            index = rand.nextInt(length)
-          } while (drawn.contains(index))
-          drawn.add(index)
-          val elem = ScalaRunTime.array_apply(array, index).asInstanceOf[AnyRef]
-          size += SizeEstimator.estimate(elem, state.visited)
-          numElementsDrawn += 1
-        }
-        state.size += ((length / (ARRAY_SAMPLE_SIZE * 1.0)) * size).toLong
+        val drawn = new OpenHashSet[Int](2 * ARRAY_SAMPLE_SIZE)
+        val s1 = sampleArray(array, state, rand, drawn, length)
+        val s2 = sampleArray(array, state, rand, drawn, length)
+        val size = math.min(s1, s2)
+        state.size += math.max(s1, s2) + 
+          (size * ((length - ARRAY_SAMPLE_SIZE) / (ARRAY_SAMPLE_SIZE))).toLong
       }
     }
   }
 
+  private def sampleArray(
+      array: AnyRef,
+      state: SearchState, 
+      rand: Random,
+      drawn: OpenHashSet[Int],
+      length: Int): Long = {
+    var size = 0L
+    for (i <- 0 until ARRAY_SAMPLE_SIZE) {
+      var index = 0
+      do {
+        index = rand.nextInt(length)
+      } while (drawn.contains(index))
+      drawn.add(index)
+      val obj = ScalaRunTime.array_apply(array, index).asInstanceOf[AnyRef]
+      if (obj != null) {
+        size += SizeEstimator.estimate(obj, state.visited).toLong
+      }
+    }
+    size
+  }
+
   private def primitiveSize(cls: Class[_]): Long = {
     if (cls == classOf[Byte]) {
       BYTE_SIZE

core/src/main/scala/org/apache/spark/util/Utils.scala

@@ -67,6 +67,12 @@ private[spark] object Utils extends Logging {
 
   val DEFAULT_SHUTDOWN_PRIORITY = 100
 
+  /**
+   * The shutdown priority of the SparkContext instance. This is lower than the default
+   * priority, so that by default hooks are run before the context is shut down.
+   */
+  val SPARK_CONTEXT_SHUTDOWN_PRIORITY = 50
+
   private val MAX_DIR_CREATION_ATTEMPTS: Int = 10
   @volatile private var localRootDirs: Array[String] = null
 
@@ -2116,7 +2122,7 @@ private[spark] object Utils extends Logging {
    * @return A handle that can be used to unregister the shutdown hook.
    */
   def addShutdownHook(hook: () => Unit): AnyRef = {
-    addShutdownHook(DEFAULT_SHUTDOWN_PRIORITY, hook)
+    addShutdownHook(DEFAULT_SHUTDOWN_PRIORITY)(hook)
   }
 
   /**
@@ -2126,7 +2132,7 @@ private[spark] object Utils extends Logging {
    * @param hook The code to run during shutdown.
    * @return A handle that can be used to unregister the shutdown hook.
    */
-  def addShutdownHook(priority: Int, hook: () => Unit): AnyRef = {
+  def addShutdownHook(priority: Int)(hook: () => Unit): AnyRef = {
     shutdownHooks.add(priority, hook)
   }
 

core/src/test/scala/org/apache/spark/FileServerSuite.scala

@@ -22,8 +22,7 @@ import java.net.URI
 import java.util.jar.{JarEntry, JarOutputStream}
 import javax.net.ssl.SSLException
 
-import com.google.common.io.ByteStreams
-import org.apache.commons.io.{FileUtils, IOUtils}
+import com.google.common.io.{ByteStreams, Files}
 import org.apache.commons.lang3.RandomUtils
 import org.scalatest.FunSuite
 
@@ -239,7 +238,7 @@ class FileServerSuite extends FunSuite with LocalSparkContext {
   def fileTransferTest(server: HttpFileServer, sm: SecurityManager = null): Unit = {
     val randomContent = RandomUtils.nextBytes(100)
     val file = File.createTempFile("FileServerSuite", "sslTests", tmpDir)
-    FileUtils.writeByteArrayToFile(file, randomContent)
+    Files.write(randomContent, file)
     server.addFile(file)
 
     val uri = new URI(server.serverUri + "/files/" + file.getName)
@@ -254,7 +253,7 @@ class FileServerSuite extends FunSuite with LocalSparkContext {
       Utils.setupSecureURLConnection(connection, sm)
     }
 
-    val buf = IOUtils.toByteArray(connection.getInputStream)
+    val buf = ByteStreams.toByteArray(connection.getInputStream)
     assert(buf === randomContent)
   }
 

core/src/test/scala/org/apache/spark/metrics/InputOutputMetricsSuite.scala

@@ -21,7 +21,7 @@ import java.io.{File, FileWriter, PrintWriter}
 
 import scala.collection.mutable.ArrayBuffer
 
-import org.apache.commons.lang.math.RandomUtils
+import org.apache.commons.lang3.RandomUtils
 import org.apache.hadoop.conf.Configuration
 import org.apache.hadoop.fs.{FileSystem, Path}
 import org.apache.hadoop.io.{LongWritable, Text}
@@ -60,7 +60,7 @@ class InputOutputMetricsSuite extends FunSuite with SharedSparkContext
     tmpFile = new File(testTempDir, getClass.getSimpleName + ".txt")
     val pw = new PrintWriter(new FileWriter(tmpFile))
     for (x <- 1 to numRecords) {
-      pw.println(RandomUtils.nextInt(numBuckets))
+      pw.println(RandomUtils.nextInt(0, numBuckets))
     }
     pw.close()