Merge remote-tracking branch 'upstream/master' into serializer2

Conflicts:
	sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala

Author: yhuai

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
 
@@ -279,7 +275,7 @@ setMethod("unpersist",
 #' @examples
 #'\dontrun{
 #' sc <- sparkR.init()
-#' setCheckpointDir(sc, "checkpoints")
+#' setCheckpointDir(sc, "checkpoint")
 #' rdd <- parallelize(sc, 1:10, 2L)
 #' checkpoint(rdd)
 #'}
@@ -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

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)
 #'}

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) {

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", {

bin/spark-class

@@ -82,13 +82,22 @@ if [ $(command -v "$JAR_CMD") ] ; then
   fi
 fi
 
+LAUNCH_CLASSPATH="$SPARK_ASSEMBLY_JAR"
+
+# Add the launcher build dir to the classpath if requested.
+if [ -n "$SPARK_PREPEND_CLASSES" ]; then
+  LAUNCH_CLASSPATH="$SPARK_HOME/launcher/target/scala-$SPARK_SCALA_VERSION/classes:$LAUNCH_CLASSPATH"
+fi
+
+export _SPARK_ASSEMBLY="$SPARK_ASSEMBLY_JAR"
+
 # The launcher library will print arguments separated by a NULL character, to allow arguments with
 # characters that would be otherwise interpreted by the shell. Read that in a while loop, populating
 # an array that will be used to exec the final command.
 CMD=()
 while IFS= read -d '' -r ARG; do
   CMD+=("$ARG")
-done < <("$RUNNER" -cp "$SPARK_ASSEMBLY_JAR" org.apache.spark.launcher.Main "$@")
+done < <("$RUNNER" -cp "$LAUNCH_CLASSPATH" org.apache.spark.launcher.Main "$@")
 
 if [ "${CMD[0]}" = "usage" ]; then
   "${CMD[@]}"

bin/spark-class2.cmd

@@ -46,13 +46,22 @@ if "%SPARK_ASSEMBLY_JAR%"=="0" (
   exit /b 1
 )
 
+set LAUNCH_CLASSPATH=%SPARK_ASSEMBLY_JAR%
+
+rem Add the launcher build dir to the classpath if requested.
+if not "x%SPARK_PREPEND_CLASSES%"=="x" (
+  set LAUNCH_CLASSPATH=%SPARK_HOME%\launcher\target\scala-%SPARK_SCALA_VERSION%\classes;%LAUNCH_CLASSPATH%
+)
+
+set _SPARK_ASSEMBLY=%SPARK_ASSEMBLY_JAR%
+
 rem Figure out where java is.
 set RUNNER=java
 if not "x%JAVA_HOME%"=="x" set RUNNER=%JAVA_HOME%\bin\java
 
 rem The launcher library prints the command to be executed in a single line suitable for being
 rem executed by the batch interpreter. So read all the output of the launcher into a variable.
-for /f "tokens=*" %%i in ('cmd /C ""%RUNNER%" -cp %SPARK_ASSEMBLY_JAR% org.apache.spark.launcher.Main %*"') do (
+for /f "tokens=*" %%i in ('cmd /C ""%RUNNER%" -cp %LAUNCH_CLASSPATH% org.apache.spark.launcher.Main %*"') do (
   set SPARK_CMD=%%i
 )
 %SPARK_CMD%

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

@@ -22,7 +22,7 @@ import java.lang.ref.{ReferenceQueue, WeakReference}
 import scala.collection.mutable.{ArrayBuffer, SynchronizedBuffer}
 
 import org.apache.spark.broadcast.Broadcast
-import org.apache.spark.rdd.RDD
+import org.apache.spark.rdd.{RDDCheckpointData, RDD}
 import org.apache.spark.util.Utils
 
 /**
@@ -33,6 +33,7 @@ private case class CleanRDD(rddId: Int) extends CleanupTask
 private case class CleanShuffle(shuffleId: Int) extends CleanupTask
 private case class CleanBroadcast(broadcastId: Long) extends CleanupTask
 private case class CleanAccum(accId: Long) extends CleanupTask
+private case class CleanCheckpoint(rddId: Int) extends CleanupTask
 
 /**
  * A WeakReference associated with a CleanupTask.
@@ -94,12 +95,12 @@ private[spark] class ContextCleaner(sc: SparkContext) extends Logging {
   @volatile private var stopped = false
 
   /** Attach a listener object to get information of when objects are cleaned. */
-  def attachListener(listener: CleanerListener) {
+  def attachListener(listener: CleanerListener): Unit = {
     listeners += listener
   }
 
   /** Start the cleaner. */
-  def start() {
+  def start(): Unit = {
     cleaningThread.setDaemon(true)
     cleaningThread.setName("Spark Context Cleaner")
     cleaningThread.start()
@@ -108,7 +109,7 @@ private[spark] class ContextCleaner(sc: SparkContext) extends Logging {
   /**
    * Stop the cleaning thread and wait until the thread has finished running its current task.
    */
-  def stop() {
+  def stop(): Unit = {
     stopped = true
     // Interrupt the cleaning thread, but wait until the current task has finished before
     // doing so. This guards against the race condition where a cleaning thread may
@@ -121,7 +122,7 @@ private[spark] class ContextCleaner(sc: SparkContext) extends Logging {
   }
 
   /** Register a RDD for cleanup when it is garbage collected. */
-  def registerRDDForCleanup(rdd: RDD[_]) {
+  def registerRDDForCleanup(rdd: RDD[_]): Unit = {
     registerForCleanup(rdd, CleanRDD(rdd.id))
   }
 
@@ -130,17 +131,22 @@ private[spark] class ContextCleaner(sc: SparkContext) extends Logging {
   }
 
   /** Register a ShuffleDependency for cleanup when it is garbage collected. */
-  def registerShuffleForCleanup(shuffleDependency: ShuffleDependency[_, _, _]) {
+  def registerShuffleForCleanup(shuffleDependency: ShuffleDependency[_, _, _]): Unit = {
     registerForCleanup(shuffleDependency, CleanShuffle(shuffleDependency.shuffleId))
   }
 
   /** Register a Broadcast for cleanup when it is garbage collected. */
-  def registerBroadcastForCleanup[T](broadcast: Broadcast[T]) {
+  def registerBroadcastForCleanup[T](broadcast: Broadcast[T]): Unit = {
     registerForCleanup(broadcast, CleanBroadcast(broadcast.id))
   }
 
+  /** Register a RDDCheckpointData for cleanup when it is garbage collected. */
+  def registerRDDCheckpointDataForCleanup[T](rdd: RDD[_], parentId: Int): Unit = {
+    registerForCleanup(rdd, CleanCheckpoint(parentId))
+  }
+
   /** Register an object for cleanup. */
-  private def registerForCleanup(objectForCleanup: AnyRef, task: CleanupTask) {
+  private def registerForCleanup(objectForCleanup: AnyRef, task: CleanupTask): Unit = {
     referenceBuffer += new CleanupTaskWeakReference(task, objectForCleanup, referenceQueue)
   }
 
@@ -164,6 +170,8 @@ private[spark] class ContextCleaner(sc: SparkContext) extends Logging {
                 doCleanupBroadcast(broadcastId, blocking = blockOnCleanupTasks)
               case CleanAccum(accId) =>
                 doCleanupAccum(accId, blocking = blockOnCleanupTasks)
+              case CleanCheckpoint(rddId) =>
+                doCleanCheckpoint(rddId)
             }
           }
         }
@@ -175,7 +183,7 @@ private[spark] class ContextCleaner(sc: SparkContext) extends Logging {
   }
 
   /** Perform RDD cleanup. */
-  def doCleanupRDD(rddId: Int, blocking: Boolean) {
+  def doCleanupRDD(rddId: Int, blocking: Boolean): Unit = {
     try {
       logDebug("Cleaning RDD " + rddId)
       sc.unpersistRDD(rddId, blocking)
@@ -187,7 +195,7 @@ private[spark] class ContextCleaner(sc: SparkContext) extends Logging {
   }
 
   /** Perform shuffle cleanup, asynchronously. */
-  def doCleanupShuffle(shuffleId: Int, blocking: Boolean) {
+  def doCleanupShuffle(shuffleId: Int, blocking: Boolean): Unit = {
     try {
       logDebug("Cleaning shuffle " + shuffleId)
       mapOutputTrackerMaster.unregisterShuffle(shuffleId)
@@ -200,7 +208,7 @@ private[spark] class ContextCleaner(sc: SparkContext) extends Logging {
   }
 
   /** Perform broadcast cleanup. */
-  def doCleanupBroadcast(broadcastId: Long, blocking: Boolean) {
+  def doCleanupBroadcast(broadcastId: Long, blocking: Boolean): Unit = {
     try {
       logDebug(s"Cleaning broadcast $broadcastId")
       broadcastManager.unbroadcast(broadcastId, true, blocking)
@@ -212,7 +220,7 @@ private[spark] class ContextCleaner(sc: SparkContext) extends Logging {
   }
 
   /** Perform accumulator cleanup. */
-  def doCleanupAccum(accId: Long, blocking: Boolean) {
+  def doCleanupAccum(accId: Long, blocking: Boolean): Unit = {
     try {
       logDebug("Cleaning accumulator " + accId)
       Accumulators.remove(accId)
@@ -223,6 +231,18 @@ private[spark] class ContextCleaner(sc: SparkContext) extends Logging {
     }
   }
 
+  /** Perform checkpoint cleanup. */
+  def doCleanCheckpoint(rddId: Int): Unit = {
+    try {
+      logDebug("Cleaning rdd checkpoint data " + rddId)
+      RDDCheckpointData.clearRDDCheckpointData(sc, rddId)
+      logInfo("Cleaned rdd checkpoint data " + rddId)
+    }
+    catch {
+      case e: Exception => logError("Error cleaning rdd checkpoint data " + rddId, e)
+    }
+  }
+
   private def blockManagerMaster = sc.env.blockManager.master
   private def broadcastManager = sc.env.broadcastManager
   private def mapOutputTrackerMaster = sc.env.mapOutputTracker.asInstanceOf[MapOutputTrackerMaster]

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")

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