Optimized imports

Optimized imports and arranged according to scala style guide @
https://cwiki.apache.org/confluence/display/SPARK/Spark+Code+Style+Guide#SparkCodeStyleGuide-Imports

Author: NirmalReddy <nirmal.reddy@imaginea.com>
Author: NirmalReddy <nirmal_reddy2000@yahoo.com>

Closes #613 from NirmalReddy/opt-imports and squashes the following commits:

578b4f5 [NirmalReddy] imported java.lang.Double as JDouble
a2cbcc5 [NirmalReddy] addressed the comments
776d664 [NirmalReddy] Optimized imports in core

core/src/main/java/org/apache/spark/network/netty/FileClient.java

@@ -17,6 +17,8 @@
 
 package org.apache.spark.network.netty;
 
+import java.util.concurrent.TimeUnit;
+
 import io.netty.bootstrap.Bootstrap;
 import io.netty.channel.Channel;
 import io.netty.channel.ChannelOption;
@@ -27,8 +29,6 @@
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
-import java.util.concurrent.TimeUnit;
-
 class FileClient {
 
   private static final Logger LOG = LoggerFactory.getLogger(FileClient.class.getName());

core/src/main/java/org/apache/spark/network/netty/FileServerHandler.java

@@ -23,11 +23,11 @@
 import io.netty.channel.ChannelHandlerContext;
 import io.netty.channel.SimpleChannelInboundHandler;
 import io.netty.channel.DefaultFileRegion;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
 
 import org.apache.spark.storage.BlockId;
 import org.apache.spark.storage.FileSegment;
-import org.slf4j.Logger;
-import org.slf4j.LoggerFactory;
 
 class FileServerHandler extends SimpleChannelInboundHandler<String> {
 

core/src/main/scala/org/apache/hadoop/mapreduce/SparkHadoopMapReduceUtil.scala

@@ -17,7 +17,8 @@
 
 package org.apache.hadoop.mapreduce
 
-import java.lang.{Integer => JInteger, Boolean => JBoolean}
+import java.lang.{Boolean => JBoolean, Integer => JInteger}
+
 import org.apache.hadoop.conf.Configuration
 
 private[apache]

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

@@ -19,8 +19,9 @@ package org.apache.spark
 
 import java.io.{ObjectInputStream, Serializable}
 
-import scala.collection.mutable.Map
 import scala.collection.generic.Growable
+import scala.collection.mutable.Map
+
 import org.apache.spark.serializer.JavaSerializer
 
 /**

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

@@ -20,12 +20,11 @@ package org.apache.spark
 import scala.collection.mutable.ArrayBuffer
 import scala.collection.mutable.HashMap
 
-import org.apache.spark.executor.{ShuffleReadMetrics, TaskMetrics}
+import org.apache.spark.executor.ShuffleReadMetrics
 import org.apache.spark.serializer.Serializer
 import org.apache.spark.storage.{BlockId, BlockManagerId, ShuffleBlockId}
 import org.apache.spark.util.CompletionIterator
 
-
 private[spark] class BlockStoreShuffleFetcher extends ShuffleFetcher with Logging {
 
   override def fetch[T](

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

@@ -18,9 +18,9 @@
 package org.apache.spark
 
 import scala.collection.mutable.{ArrayBuffer, HashSet}
-import org.apache.spark.storage.{BlockId, BlockManager, StorageLevel, RDDBlockId}
-import org.apache.spark.rdd.RDD
 
+import org.apache.spark.rdd.RDD
+import org.apache.spark.storage.{BlockManager, RDDBlockId, StorageLevel}
 
 /** Spark class responsible for passing RDDs split contents to the BlockManager and making
     sure a node doesn't load two copies of an RDD at once.

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

@@ -21,10 +21,8 @@ import scala.concurrent._
 import scala.concurrent.duration.Duration
 import scala.util.Try
 
-import org.apache.spark.scheduler.{JobSucceeded, JobWaiter}
-import org.apache.spark.scheduler.JobFailed
 import org.apache.spark.rdd.RDD
-
+import org.apache.spark.scheduler.{JobFailed, JobSucceeded, JobWaiter}
 
 /**
  * A future for the result of an action to support cancellation. This is an extension of the

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

@@ -17,8 +17,10 @@
 
 package org.apache.spark
 
-import java.io.{File}
+import java.io.File
+
 import com.google.common.io.Files
+
 import org.apache.spark.util.Utils
 
 private[spark] class HttpFileServer extends Logging {

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

@@ -18,14 +18,14 @@
 package org.apache.spark
 
 import java.io.File
-import java.net.InetAddress
 
 import org.eclipse.jetty.server.Server
 import org.eclipse.jetty.server.bio.SocketConnector
 import org.eclipse.jetty.server.handler.DefaultHandler
 import org.eclipse.jetty.server.handler.HandlerList
 import org.eclipse.jetty.server.handler.ResourceHandler
 import org.eclipse.jetty.util.thread.QueuedThreadPool
+
 import org.apache.spark.util.Utils
 
 /**

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

@@ -22,7 +22,6 @@ import java.util.zip.{GZIPInputStream, GZIPOutputStream}
 
 import scala.collection.mutable.HashSet
 import scala.concurrent.Await
-import scala.concurrent.duration._
 
 import akka.actor._
 import akka.pattern.ask

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

@@ -19,9 +19,9 @@ package org.apache.spark
 
 import java.io._
 
+import org.apache.hadoop.conf.Configuration
 import org.apache.hadoop.io.ObjectWritable
 import org.apache.hadoop.io.Writable
-import org.apache.hadoop.conf.Configuration
 
 class SerializableWritable[T <: Writable](@transient var t: T) extends Serializable {
   def value = t

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

@@ -17,10 +17,8 @@
 
 package org.apache.spark
 
-import org.apache.spark.executor.TaskMetrics
 import org.apache.spark.serializer.Serializer
 
-
 private[spark] abstract class ShuffleFetcher {
 
   /**

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

@@ -20,8 +20,6 @@ package org.apache.spark
 import scala.collection.JavaConverters._
 import scala.collection.mutable.HashMap
 
-import java.io.{ObjectInputStream, ObjectOutputStream, IOException}
-
 /**
  * Configuration for a Spark application. Used to set various Spark parameters as key-value pairs.
  *

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

@@ -19,21 +19,18 @@ package org.apache.spark
 
 import java.io._
 import java.net.URI
-import java.util.{UUID, Properties}
+import java.util.{Properties, UUID}
 import java.util.concurrent.atomic.AtomicInteger
 
 import scala.collection.{Map, Set}
 import scala.collection.generic.Growable
-
 import scala.collection.mutable.{ArrayBuffer, HashMap}
 import scala.reflect.{ClassTag, classTag}
 
 import org.apache.hadoop.conf.Configuration
 import org.apache.hadoop.fs.Path
-import org.apache.hadoop.io.{ArrayWritable, BooleanWritable, BytesWritable, DoubleWritable,
-  FloatWritable, IntWritable, LongWritable, NullWritable, Text, Writable}
-import org.apache.hadoop.mapred.{FileInputFormat, InputFormat, JobConf, SequenceFileInputFormat,
-  TextInputFormat}
+import org.apache.hadoop.io.{ArrayWritable, BooleanWritable, BytesWritable, DoubleWritable, FloatWritable, IntWritable, LongWritable, NullWritable, Text, Writable}
+import org.apache.hadoop.mapred.{FileInputFormat, InputFormat, JobConf, SequenceFileInputFormat, TextInputFormat}
 import org.apache.hadoop.mapreduce.{InputFormat => NewInputFormat, Job => NewHadoopJob}
 import org.apache.hadoop.mapreduce.lib.input.{FileInputFormat => NewFileInputFormat}
 import org.apache.mesos.MesosNativeLibrary
@@ -42,14 +39,12 @@ import org.apache.spark.deploy.{LocalSparkCluster, SparkHadoopUtil}
 import org.apache.spark.partial.{ApproximateEvaluator, PartialResult}
 import org.apache.spark.rdd._
 import org.apache.spark.scheduler._
-import org.apache.spark.scheduler.cluster.{CoarseGrainedSchedulerBackend,
-  SparkDeploySchedulerBackend, SimrSchedulerBackend}
+import org.apache.spark.scheduler.cluster.{CoarseGrainedSchedulerBackend, SparkDeploySchedulerBackend, SimrSchedulerBackend}
 import org.apache.spark.scheduler.cluster.mesos.{CoarseMesosSchedulerBackend, MesosSchedulerBackend}
 import org.apache.spark.scheduler.local.LocalBackend
 import org.apache.spark.storage.{BlockManagerSource, RDDInfo, StorageStatus, StorageUtils}
 import org.apache.spark.ui.SparkUI
-import org.apache.spark.util.{Utils, TimeStampedHashMap, MetadataCleaner, MetadataCleanerType,
-  ClosureCleaner}
+import org.apache.spark.util.{ClosureCleaner, MetadataCleaner, MetadataCleanerType, TimeStampedHashMap, Utils}
 
 /**
  * Main entry point for Spark functionality. A SparkContext represents the connection to a Spark

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

@@ -21,16 +21,15 @@ import scala.collection.mutable
 import scala.concurrent.Await
 
 import akka.actor._
+import com.google.common.collect.MapMaker
 
+import org.apache.spark.api.python.PythonWorkerFactory
 import org.apache.spark.broadcast.BroadcastManager
 import org.apache.spark.metrics.MetricsSystem
-import org.apache.spark.storage.{BlockManagerMasterActor, BlockManager, BlockManagerMaster}
+import org.apache.spark.storage.{BlockManager, BlockManagerMaster, BlockManagerMasterActor}
 import org.apache.spark.network.ConnectionManager
 import org.apache.spark.serializer.{Serializer, SerializerManager}
-import org.apache.spark.util.{Utils, AkkaUtils}
-import org.apache.spark.api.python.PythonWorkerFactory
-
-import com.google.common.collect.MapMaker
+import org.apache.spark.util.{AkkaUtils, Utils}
 
 /**
  * Holds all the runtime environment objects for a running Spark instance (either master or worker),

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

@@ -18,8 +18,8 @@
 package org.apache.hadoop.mapred
 
 import java.io.IOException
-import java.text.SimpleDateFormat
 import java.text.NumberFormat
+import java.text.SimpleDateFormat
 import java.util.Date
 
 import org.apache.hadoop.fs.FileSystem

core/src/main/scala/org/apache/spark/api/java/JavaDoubleRDD.scala

@@ -17,27 +17,25 @@
 
 package org.apache.spark.api.java
 
+import java.lang.{Double => JDouble}
+
 import scala.reflect.ClassTag
 
-import org.apache.spark.rdd.RDD
+import org.apache.spark.Partitioner
 import org.apache.spark.SparkContext.doubleRDDToDoubleRDDFunctions
 import org.apache.spark.api.java.function.{Function => JFunction}
-import org.apache.spark.util.StatCounter
 import org.apache.spark.partial.{BoundedDouble, PartialResult}
+import org.apache.spark.rdd.RDD
 import org.apache.spark.storage.StorageLevel
+import org.apache.spark.util.StatCounter
 
-import java.lang.Double
-import org.apache.spark.Partitioner
-
-import scala.collection.JavaConverters._
-
-class JavaDoubleRDD(val srdd: RDD[scala.Double]) extends JavaRDDLike[Double, JavaDoubleRDD] {
+class JavaDoubleRDD(val srdd: RDD[scala.Double]) extends JavaRDDLike[JDouble, JavaDoubleRDD] {
 
-  override val classTag: ClassTag[Double] = implicitly[ClassTag[Double]]
+  override val classTag: ClassTag[JDouble] = implicitly[ClassTag[JDouble]]
 
-  override val rdd: RDD[Double] = srdd.map(x => Double.valueOf(x))
+  override val rdd: RDD[JDouble] = srdd.map(x => JDouble.valueOf(x))
 
-  override def wrapRDD(rdd: RDD[Double]): JavaDoubleRDD =
+  override def wrapRDD(rdd: RDD[JDouble]): JavaDoubleRDD =
     new JavaDoubleRDD(rdd.map(_.doubleValue))
 
   // Common RDD functions
@@ -67,7 +65,7 @@ class JavaDoubleRDD(val srdd: RDD[scala.Double]) extends JavaRDDLike[Double, Jav
   def unpersist(blocking: Boolean): JavaDoubleRDD = fromRDD(srdd.unpersist(blocking))
 
   // first() has to be overriden here in order for its return type to be Double instead of Object.
-  override def first(): Double = srdd.first()
+  override def first(): JDouble = srdd.first()
 
   // Transformations (return a new RDD)
 
@@ -84,7 +82,7 @@ class JavaDoubleRDD(val srdd: RDD[scala.Double]) extends JavaRDDLike[Double, Jav
   /**
    * Return a new RDD containing only the elements that satisfy a predicate.
    */
-  def filter(f: JFunction[Double, java.lang.Boolean]): JavaDoubleRDD =
+  def filter(f: JFunction[JDouble, java.lang.Boolean]): JavaDoubleRDD =
     fromRDD(srdd.filter(x => f(x).booleanValue()))
 
   /**
@@ -133,7 +131,7 @@ class JavaDoubleRDD(val srdd: RDD[scala.Double]) extends JavaRDDLike[Double, Jav
   /**
    * Return a sampled subset of this RDD.
    */
-  def sample(withReplacement: Boolean, fraction: Double, seed: Int): JavaDoubleRDD =
+  def sample(withReplacement: Boolean, fraction: JDouble, seed: Int): JavaDoubleRDD =
     fromRDD(srdd.sample(withReplacement, fraction, seed))
 
   /**
@@ -145,7 +143,7 @@ class JavaDoubleRDD(val srdd: RDD[scala.Double]) extends JavaRDDLike[Double, Jav
   // Double RDD functions
 
   /** Add up the elements in this RDD. */
-  def sum(): Double = srdd.sum()
+  def sum(): JDouble = srdd.sum()
 
   /**
    * Return a [[org.apache.spark.util.StatCounter]] object that captures the mean, variance and
@@ -154,35 +152,35 @@ class JavaDoubleRDD(val srdd: RDD[scala.Double]) extends JavaRDDLike[Double, Jav
   def stats(): StatCounter = srdd.stats()
 
   /** Compute the mean of this RDD's elements. */
-  def mean(): Double = srdd.mean()
+  def mean(): JDouble = srdd.mean()
 
   /** Compute the variance of this RDD's elements. */
-  def variance(): Double = srdd.variance()
+  def variance(): JDouble = srdd.variance()
 
   /** Compute the standard deviation of this RDD's elements. */
-  def stdev(): Double = srdd.stdev()
+  def stdev(): JDouble = srdd.stdev()
 
   /**
    * Compute the sample standard deviation of this RDD's elements (which corrects for bias in
    * estimating the standard deviation by dividing by N-1 instead of N).
    */
-  def sampleStdev(): Double = srdd.sampleStdev()
+  def sampleStdev(): JDouble = srdd.sampleStdev()
 
   /**
    * Compute the sample variance of this RDD's elements (which corrects for bias in
    * estimating the standard variance by dividing by N-1 instead of N).
    */
-  def sampleVariance(): Double = srdd.sampleVariance()
+  def sampleVariance(): JDouble = srdd.sampleVariance()
 
   /** Return the approximate mean of the elements in this RDD. */
-  def meanApprox(timeout: Long, confidence: Double): PartialResult[BoundedDouble] =
+  def meanApprox(timeout: Long, confidence: JDouble): PartialResult[BoundedDouble] =
     srdd.meanApprox(timeout, confidence)
 
   /** (Experimental) Approximate operation to return the mean within a timeout. */
   def meanApprox(timeout: Long): PartialResult[BoundedDouble] = srdd.meanApprox(timeout)
 
   /** (Experimental) Approximate operation to return the sum within a timeout. */
-  def sumApprox(timeout: Long, confidence: Double): PartialResult[BoundedDouble] =
+  def sumApprox(timeout: Long, confidence: JDouble): PartialResult[BoundedDouble] =
     srdd.sumApprox(timeout, confidence)
 
   /** (Experimental) Approximate operation to return the sum within a timeout. */
@@ -222,7 +220,7 @@ class JavaDoubleRDD(val srdd: RDD[scala.Double]) extends JavaRDDLike[Double, Jav
     srdd.histogram(buckets, false)
   }
 
-  def histogram(buckets: Array[Double], evenBuckets: Boolean): Array[Long] = {
+  def histogram(buckets: Array[JDouble], evenBuckets: Boolean): Array[Long] = {
     srdd.histogram(buckets.map(_.toDouble), evenBuckets)
   }
 

core/src/main/scala/org/apache/spark/api/java/JavaRDD.scala

@@ -20,8 +20,8 @@ package org.apache.spark.api.java
 import scala.reflect.ClassTag
 
 import org.apache.spark._
-import org.apache.spark.rdd.RDD
 import org.apache.spark.api.java.function.{Function => JFunction}
+import org.apache.spark.rdd.RDD
 import org.apache.spark.storage.StorageLevel
 
 class JavaRDD[T](val rdd: RDD[T])(implicit val classTag: ClassTag[T])

core/src/main/scala/org/apache/spark/api/java/function/DoubleFlatMapFunction.java

@@ -17,7 +17,6 @@
 
 package org.apache.spark.api.java.function;
 
-
 import java.io.Serializable;
 
 /**

core/src/main/scala/org/apache/spark/api/java/function/DoubleFunction.java

@@ -17,7 +17,6 @@
 
 package org.apache.spark.api.java.function;
 
-
 import java.io.Serializable;
 
 /**

core/src/main/scala/org/apache/spark/api/java/function/Function.java

@@ -17,11 +17,10 @@
 
 package org.apache.spark.api.java.function;
 
-import scala.reflect.ClassTag;
-import scala.reflect.ClassTag$;
-
 import java.io.Serializable;
 
+import scala.reflect.ClassTag;
+import scala.reflect.ClassTag$;
 
 /**
  * Base class for functions whose return types do not create special RDDs. PairFunction and