[SPARK-1112, 2156] (0.9 edition) Use correct akka frame size and overhead amounts.

core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala

@@ -34,7 +34,8 @@ private[spark] class CoarseGrainedExecutorBackend(
     driverUrl: String,
     executorId: String,
     hostPort: String,
-    cores: Int)
+    cores: Int,
+    actorSystem: ActorSystem)
   extends Actor
   with ExecutorBackend
   with Logging {
@@ -93,6 +94,9 @@ private[spark] class CoarseGrainedExecutorBackend(
   override def statusUpdate(taskId: Long, state: TaskState, data: ByteBuffer) {
     driver ! StatusUpdate(executorId, taskId, state, data)
   }
+
+  override def akkaFrameSize() = actorSystem.settings.config.getBytes(
+    "akka.remote.netty.tcp.maximum-frame-size")
 }
 
 private[spark] object CoarseGrainedExecutorBackend {
@@ -110,7 +114,8 @@ private[spark] object CoarseGrainedExecutorBackend {
       // set it
       val sparkHostPort = hostname + ":" + boundPort
       actorSystem.actorOf(
-        Props(classOf[CoarseGrainedExecutorBackend], driverUrl, executorId, sparkHostPort, cores),
+        Props(classOf[CoarseGrainedExecutorBackend], driverUrl, executorId, sparkHostPort, cores,
+          actorSystem),
         name = "Executor")
       workerUrl.foreach {
         url =>

core/src/main/scala/org/apache/spark/executor/Executor.scala

@@ -117,10 +117,6 @@ private[spark] class Executor(
     }
   }
 
-  // Akka's message frame size. If task result is bigger than this, we use the block manager
-  // to send the result back.
-  private val akkaFrameSize = AkkaUtils.maxFrameSizeBytes(conf)
-
   // Start worker thread pool
   val threadPool = Utils.newDaemonCachedThreadPool("Executor task launch worker")
 
@@ -232,8 +228,10 @@ private[spark] class Executor(
         val directResult = new DirectTaskResult(valueBytes, accumUpdates, task.metrics.getOrElse(null))
         val serializedDirectResult = ser.serialize(directResult)
         logInfo("Serialized size of result for " + taskId + " is " + serializedDirectResult.limit)
+
         val serializedResult = {
-          if (serializedDirectResult.limit >= akkaFrameSize - 1024) {
+          if (serializedDirectResult.limit >= execBackend.akkaFrameSize() -
+              AkkaUtils.reservedSizeBytes) {
             logInfo("Storing result for " + taskId + " in local BlockManager")
             val blockId = TaskResultBlockId(taskId)
             env.blockManager.putBytes(

core/src/main/scala/org/apache/spark/executor/ExecutorBackend.scala

@@ -25,4 +25,7 @@ import org.apache.spark.TaskState.TaskState
  */
 private[spark] trait ExecutorBackend {
   def statusUpdate(taskId: Long, state: TaskState, data: ByteBuffer)
+
+  // Exists as a work around for SPARK-1112. This only exists in branch-1.x of Spark.
+  def akkaFrameSize(): Long = Long.MaxValue
 }

core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala

@@ -142,7 +142,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, actorSystem: A
       for (task <- tasks.flatten) {
         val ser = SparkEnv.get.closureSerializer.newInstance()
         val serializedTask = ser.serialize(task)
-        if (serializedTask.limit >= akkaFrameSize - 1024) {
+        if (serializedTask.limit >= akkaFrameSize - AkkaUtils.reservedSizeBytes) {
           val taskSetId = scheduler.taskIdToTaskSetId(task.taskId)
           scheduler.activeTaskSets.get(taskSetId).foreach { taskSet =>
             try {

core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala

@@ -20,11 +20,11 @@ package org.apache.spark.scheduler.local
 import java.nio.ByteBuffer
 
 import akka.actor.{Actor, ActorRef, Props}
-
-import org.apache.spark.{Logging, SparkContext, SparkEnv, TaskState}
+import org.apache.spark.{Logging, SparkEnv, TaskState}
 import org.apache.spark.TaskState.TaskState
 import org.apache.spark.executor.{Executor, ExecutorBackend}
 import org.apache.spark.scheduler.{SchedulerBackend, TaskSchedulerImpl, WorkerOffer}
+import org.apache.spark.util.AkkaUtils
 
 private case class ReviveOffers()
 
@@ -106,4 +106,8 @@ private[spark] class LocalBackend(scheduler: TaskSchedulerImpl, val totalCores:
   override def statusUpdate(taskId: Long, state: TaskState, serializedData: ByteBuffer) {
     localActor ! StatusUpdate(taskId, state, serializedData)
   }
+
+  // This limit is calculated only to preserve expected behavior in tests. In reality, since this
+  // backend sends messages over the existing actor system, there is no need to enforce a limit.
+  override def akkaFrameSize() = AkkaUtils.maxFrameSizeBytes(scheduler.sc.getConf)
 }

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

@@ -115,4 +115,7 @@ private[spark] object AkkaUtils {
   def maxFrameSizeBytes(conf: SparkConf): Int = {
     conf.getInt("spark.akka.frameSize", 10) * 1024 * 1024
   }
+
+  /** Space reserved for extra data in an Akka message besides serialized task or task result. */
+  val reservedSizeBytes = 200 * 1024
 }

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

@@ -161,7 +161,6 @@ class MapOutputTrackerSuite extends FunSuite with LocalSparkContext {
 
   test("remote fetch exceeds akka frame size") {
     val newConf = new SparkConf
-    newConf.set("spark.akka.frameSize", "1")
     newConf.set("spark.akka.askTimeout", "1") // Fail fast
 
     val masterTracker = new MapOutputTrackerMaster(conf)
@@ -170,14 +169,18 @@ class MapOutputTrackerSuite extends FunSuite with LocalSparkContext {
       new MapOutputTrackerMasterActor(masterTracker, newConf))(actorSystem)
     val masterActor = actorRef.underlyingActor
 
-    // Frame size should be ~1.1MB, and MapOutputTrackerMasterActor should throw exception.
-    // Note that the size is hand-selected here because map output statuses are compressed before
-    // being sent.
-    masterTracker.registerShuffle(20, 100)
-    (0 until 100).foreach { i =>
-      masterTracker.registerMapOutput(20, i, new MapStatus(
-        BlockManagerId("999", "mps", 1000, 0), Array.fill[Byte](4000000)(0)))
+    // Frame size should be 2 * the configured frame size, and MapOutputTrackerMasterActor should
+    // throw exception.
+    val shuffleId = 20
+    val numMaps = 2
+    val data = new Array[Byte](AkkaUtils.maxFrameSizeBytes(conf))
+    val random = new java.util.Random(0)
+    random.nextBytes(data) // Make it hard to compress.
+    masterTracker.registerShuffle(shuffleId, numMaps)
+    (0 until numMaps).foreach { i =>
+      masterTracker.registerMapOutput(shuffleId, i, new MapStatus(
+        BlockManagerId("999", "mps", 1000, 0), data))
     }
-    intercept[SparkException] { masterActor.receive(GetMapOutputStatuses(20)) }
+    intercept[SparkException] { masterActor.receive(GetMapOutputStatuses(shuffleId)) }
   }
 }