Merge branch 'master' into stage_distributions

bin/spark-class

@@ -40,35 +40,46 @@ else
   fi
 fi
 
-# Look for the launcher. In non-release mode, add the compiled classes directly to the classpath
-# instead of looking for a jar file.
-SPARK_LAUNCHER_CP=
-if [ -f $SPARK_HOME/RELEASE ]; then
-  LAUNCHER_DIR="$SPARK_HOME/lib"
-  num_jars="$(ls -1 "$LAUNCHER_DIR" | grep "^spark-launcher.*\.jar$" | wc -l)"
-  if [ "$num_jars" -eq "0" -a -z "$SPARK_LAUNCHER_CP" ]; then
-    echo "Failed to find Spark launcher in $LAUNCHER_DIR." 1>&2
-    echo "You need to build Spark before running this program." 1>&2
-    exit 1
-  fi
+# Find assembly jar
+SPARK_ASSEMBLY_JAR=
+if [ -f "$SPARK_HOME/RELEASE" ]; then
+  ASSEMBLY_DIR="$SPARK_HOME/lib"
+else
+  ASSEMBLY_DIR="$SPARK_HOME/assembly/target/scala-$SPARK_SCALA_VERSION"
+fi
 
-  LAUNCHER_JARS="$(ls -1 "$LAUNCHER_DIR" | grep "^spark-launcher.*\.jar$" || true)"
-  if [ "$num_jars" -gt "1" ]; then
-    echo "Found multiple Spark launcher jars in $LAUNCHER_DIR:" 1>&2
-    echo "$LAUNCHER_JARS" 1>&2
-    echo "Please remove all but one jar." 1>&2
-    exit 1
-  fi
+num_jars="$(ls -1 "$ASSEMBLY_DIR" | grep "^spark-assembly.*hadoop.*\.jar$" | wc -l)"
+if [ "$num_jars" -eq "0" -a -z "$SPARK_ASSEMBLY_JAR" ]; then
+  echo "Failed to find Spark assembly in $ASSEMBLY_DIR." 1>&2
+  echo "You need to build Spark before running this program." 1>&2
+  exit 1
+fi
+ASSEMBLY_JARS="$(ls -1 "$ASSEMBLY_DIR" | grep "^spark-assembly.*hadoop.*\.jar$" || true)"
+if [ "$num_jars" -gt "1" ]; then
+  echo "Found multiple Spark assembly jars in $ASSEMBLY_DIR:" 1>&2
+  echo "$ASSEMBLY_JARS" 1>&2
+  echo "Please remove all but one jar." 1>&2
+  exit 1
+fi
 
-  SPARK_LAUNCHER_CP="${LAUNCHER_DIR}/${LAUNCHER_JARS}"
+SPARK_ASSEMBLY_JAR="${ASSEMBLY_DIR}/${ASSEMBLY_JARS}"
+
+# Verify that versions of java used to build the jars and run Spark are compatible
+if [ -n "$JAVA_HOME" ]; then
+  JAR_CMD="$JAVA_HOME/bin/jar"
 else
-  LAUNCHER_DIR="$SPARK_HOME/launcher/target/scala-$SPARK_SCALA_VERSION"
-  if [ ! -d "$LAUNCHER_DIR/classes" ]; then
-    echo "Failed to find Spark launcher classes in $LAUNCHER_DIR." 1>&2
-    echo "You need to build Spark before running this program." 1>&2
+  JAR_CMD="jar"
+fi
+
+if [ $(command -v "$JAR_CMD") ] ; then
+  jar_error_check=$("$JAR_CMD" -tf "$SPARK_ASSEMBLY_JAR" nonexistent/class/path 2>&1)
+  if [[ "$jar_error_check" =~ "invalid CEN header" ]]; then
+    echo "Loading Spark jar with '$JAR_CMD' failed. " 1>&2
+    echo "This is likely because Spark was compiled with Java 7 and run " 1>&2
+    echo "with Java 6. (see SPARK-1703). Please use Java 7 to run Spark " 1>&2
+    echo "or build Spark with Java 6." 1>&2
     exit 1
   fi
-  SPARK_LAUNCHER_CP="$LAUNCHER_DIR/classes"
 fi
 
 # The launcher library will print arguments separated by a NULL character, to allow arguments with
@@ -77,7 +88,7 @@ fi
 CMD=()
 while IFS= read -d '' -r ARG; do
   CMD+=("$ARG")
-done < <("$RUNNER" -cp "$SPARK_LAUNCHER_CP" org.apache.spark.launcher.Main "$@")
+done < <("$RUNNER" -cp "$SPARK_ASSEMBLY_JAR" org.apache.spark.launcher.Main "$@")
 
 if [ "${CMD[0]}" = "usage" ]; then
   "${CMD[@]}"

bin/spark-class2.cmd

@@ -29,31 +29,20 @@ if "x%1"=="x" (
   exit /b 1
 )
 
-set LAUNCHER_CP=0
-if exist %SPARK_HOME%\RELEASE goto find_release_launcher
+rem Find assembly jar
+set SPARK_ASSEMBLY_JAR=0
 
-rem Look for the Spark launcher in both Scala build directories. The launcher doesn't use Scala so
-rem it doesn't really matter which one is picked up. Add the compiled classes directly to the
-rem classpath instead of looking for a jar file, since it's very common for people using sbt to use
-rem the "assembly" target instead of "package".
-set LAUNCHER_CLASSES=%SPARK_HOME%\launcher\target\scala-2.10\classes
-if exist %LAUNCHER_CLASSES% (
-  set LAUNCHER_CP=%LAUNCHER_CLASSES%
+if exist "%SPARK_HOME%\RELEASE" (
+  set ASSEMBLY_DIR=%SPARK_HOME%\lib
+) else (
+  set ASSEMBLY_DIR=%SPARK_HOME%\assembly\target\scala-%SPARK_SCALA_VERSION%
 )
-set LAUNCHER_CLASSES=%SPARK_HOME%\launcher\target\scala-2.11\classes
-if exist %LAUNCHER_CLASSES% (
-  set LAUNCHER_CP=%LAUNCHER_CLASSES%
-)
-goto check_launcher
 
-:find_release_launcher
-for %%d in (%SPARK_HOME%\lib\spark-launcher*.jar) do (
-  set LAUNCHER_CP=%%d
+for %%d in (%ASSEMBLY_DIR%\spark-assembly*hadoop*.jar) do (
+  set SPARK_ASSEMBLY_JAR=%%d
 )
-
-:check_launcher
-if "%LAUNCHER_CP%"=="0" (
-  echo Failed to find Spark launcher JAR.
+if "%SPARK_ASSEMBLY_JAR%"=="0" (
+  echo Failed to find Spark assembly JAR.
   echo You need to build Spark before running this program.
   exit /b 1
 )
@@ -64,7 +53,7 @@ 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 %LAUNCHER_CP% org.apache.spark.launcher.Main %*"') do (
+for /f "tokens=*" %%i in ('cmd /C ""%RUNNER%" -cp %SPARK_ASSEMBLY_JAR% org.apache.spark.launcher.Main %*"') do (
   set SPARK_CMD=%%i
 )
 %SPARK_CMD%

core/src/main/resources/org/apache/spark/ui/static/additional-metrics.js

@@ -30,7 +30,7 @@ $(function() {
 
     stripeSummaryTable();
 
-    $("input:checkbox").click(function() {
+    $('input[type="checkbox"]').click(function() {
         var column = "table ." + $(this).attr("name");
         $(column).toggle();
         stripeSummaryTable();
@@ -39,15 +39,15 @@ $(function() {
     $("#select-all-metrics").click(function() {
        if (this.checked) {
           // Toggle all un-checked options.
-          $('input:checkbox:not(:checked)').trigger('click');
+          $('input[type="checkbox"]:not(:checked)').trigger('click');
        } else {
           // Toggle all checked options.
-          $('input:checkbox:checked').trigger('click');
+          $('input[type="checkbox"]:checked').trigger('click');
        }
     });
 
     // Trigger a click on the checkbox if a user clicks the label next to it.
     $("span.additional-metric-title").click(function() {
-        $(this).parent().find('input:checkbox').trigger('click');
+        $(this).parent().find('input[type="checkbox"]').trigger('click');
     });
 });

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

@@ -49,12 +49,17 @@ private[spark] class HeartbeatReceiver(sc: SparkContext, scheduler: TaskSchedule
 
   // executor ID -> timestamp of when the last heartbeat from this executor was received
   private val executorLastSeen = new mutable.HashMap[String, Long]
-
-  private val executorTimeoutMs = sc.conf.getLong("spark.network.timeout", 
-    sc.conf.getLong("spark.storage.blockManagerSlaveTimeoutMs", 120)) * 1000
-
-  private val checkTimeoutIntervalMs = sc.conf.getLong("spark.network.timeoutInterval",
-    sc.conf.getLong("spark.storage.blockManagerTimeoutIntervalMs", 60)) * 1000
+
+  // "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))
+
+  // "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 var timeoutCheckingTask: Cancellable = null
 
@@ -84,7 +89,7 @@ private[spark] class HeartbeatReceiver(sc: SparkContext, scheduler: TaskSchedule
         logWarning(s"Removing executor $executorId with no recent heartbeats: " +
           s"${now - lastSeenMs} ms exceeds timeout $executorTimeoutMs ms")
         scheduler.executorLost(executorId, SlaveLost("Executor heartbeat " +
-          "timed out after ${now - lastSeenMs} ms"))
+          s"timed out after ${now - lastSeenMs} ms"))
         if (sc.supportDynamicAllocation) {
           sc.killExecutor(executorId)
         }

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

@@ -34,12 +34,14 @@ import org.apache.spark.metrics.MetricsSystem
 import org.apache.spark.network.BlockTransferService
 import org.apache.spark.network.netty.NettyBlockTransferService
 import org.apache.spark.network.nio.NioBlockTransferService
+import org.apache.spark.rpc.{RpcEndpointRef, RpcEndpoint, RpcEnv}
+import org.apache.spark.rpc.akka.AkkaRpcEnv
 import org.apache.spark.scheduler.{OutputCommitCoordinator, LiveListenerBus}
-import org.apache.spark.scheduler.OutputCommitCoordinator.OutputCommitCoordinatorActor
+import org.apache.spark.scheduler.OutputCommitCoordinator.OutputCommitCoordinatorEndpoint
 import org.apache.spark.serializer.Serializer
 import org.apache.spark.shuffle.{ShuffleMemoryManager, ShuffleManager}
 import org.apache.spark.storage._
-import org.apache.spark.util.{AkkaUtils, Utils}
+import org.apache.spark.util.{AkkaUtils, RpcUtils, Utils}
 
 /**
  * :: DeveloperApi ::
@@ -54,7 +56,7 @@ import org.apache.spark.util.{AkkaUtils, Utils}
 @DeveloperApi
 class SparkEnv (
     val executorId: String,
-    val actorSystem: ActorSystem,
+    private[spark] val rpcEnv: RpcEnv,
     val serializer: Serializer,
     val closureSerializer: Serializer,
     val cacheManager: CacheManager,
@@ -71,6 +73,9 @@ class SparkEnv (
     val outputCommitCoordinator: OutputCommitCoordinator,
     val conf: SparkConf) extends Logging {
 
+  // TODO Remove actorSystem
+  val actorSystem = rpcEnv.asInstanceOf[AkkaRpcEnv].actorSystem
+
   private[spark] var isStopped = false
   private val pythonWorkers = mutable.HashMap[(String, Map[String, String]), PythonWorkerFactory]()
 
@@ -91,7 +96,8 @@ class SparkEnv (
     blockManager.master.stop()
     metricsSystem.stop()
     outputCommitCoordinator.stop()
-    actorSystem.shutdown()
+    rpcEnv.shutdown()
+
     // Unfortunately Akka's awaitTermination doesn't actually wait for the Netty server to shut
     // down, but let's call it anyway in case it gets fixed in a later release
     // UPDATE: In Akka 2.1.x, this hangs if there are remote actors, so we can't call it.
@@ -236,16 +242,15 @@ object SparkEnv extends Logging {
     val securityManager = new SecurityManager(conf)
 
     // Create the ActorSystem for Akka and get the port it binds to.
-    val (actorSystem, boundPort) = {
-      val actorSystemName = if (isDriver) driverActorSystemName else executorActorSystemName
-      AkkaUtils.createActorSystem(actorSystemName, hostname, port, conf, securityManager)
-    }
+    val actorSystemName = if (isDriver) driverActorSystemName else executorActorSystemName
+    val rpcEnv = RpcEnv.create(actorSystemName, hostname, port, conf, securityManager)
+    val actorSystem = rpcEnv.asInstanceOf[AkkaRpcEnv].actorSystem
 
     // Figure out which port Akka actually bound to in case the original port is 0 or occupied.
     if (isDriver) {
-      conf.set("spark.driver.port", boundPort.toString)
+      conf.set("spark.driver.port", rpcEnv.address.port.toString)
     } else {
-      conf.set("spark.executor.port", boundPort.toString)
+      conf.set("spark.executor.port", rpcEnv.address.port.toString)
     }
 
     // Create an instance of the class with the given name, possibly initializing it with our conf
@@ -290,6 +295,15 @@ object SparkEnv extends Logging {
       }
     }
 
+    def registerOrLookupEndpoint(name: String, endpointCreator: => RpcEndpoint): RpcEndpointRef = {
+      if (isDriver) {
+        logInfo("Registering " + name)
+        rpcEnv.setupEndpoint(name, endpointCreator)
+      } else {
+        RpcUtils.makeDriverRef(name, conf, rpcEnv)
+      }
+    }
+
     val mapOutputTracker =  if (isDriver) {
       new MapOutputTrackerMaster(conf)
     } else {
@@ -377,13 +391,13 @@ object SparkEnv extends Logging {
     val outputCommitCoordinator = mockOutputCommitCoordinator.getOrElse {
       new OutputCommitCoordinator(conf)
     }
-    val outputCommitCoordinatorActor = registerOrLookup("OutputCommitCoordinator",
-      new OutputCommitCoordinatorActor(outputCommitCoordinator))
-    outputCommitCoordinator.coordinatorActor = Some(outputCommitCoordinatorActor)
+    val outputCommitCoordinatorRef = registerOrLookupEndpoint("OutputCommitCoordinator",
+      new OutputCommitCoordinatorEndpoint(rpcEnv, outputCommitCoordinator))
+    outputCommitCoordinator.coordinatorRef = Some(outputCommitCoordinatorRef)
 
     val envInstance = new SparkEnv(
       executorId,
-      actorSystem,
+      rpcEnv,
       serializer,
       closureSerializer,
       cacheManager,

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

@@ -26,7 +26,6 @@ import org.apache.hadoop.mapred._
 import org.apache.hadoop.fs.FileSystem
 import org.apache.hadoop.fs.Path
 
-import org.apache.spark.executor.CommitDeniedException
 import org.apache.spark.mapred.SparkHadoopMapRedUtil
 import org.apache.spark.rdd.HadoopRDD
 
@@ -104,55 +103,8 @@ class SparkHadoopWriter(@transient jobConf: JobConf)
   }
 
   def commit() {
-    val taCtxt = getTaskContext()
-    val cmtr = getOutputCommitter()
-
-    // Called after we have decided to commit
-    def performCommit(): Unit = {
-      try {
-        cmtr.commitTask(taCtxt)
-        logInfo (s"$taID: Committed")
-      } catch {
-        case e: IOException =>
-          logError("Error committing the output of task: " + taID.value, e)
-          cmtr.abortTask(taCtxt)
-          throw e
-      }
-    }
-
-    // First, check whether the task's output has already been committed by some other attempt
-    if (cmtr.needsTaskCommit(taCtxt)) {
-      // The task output needs to be committed, but we don't know whether some other task attempt
-      // might be racing to commit the same output partition. Therefore, coordinate with the driver
-      // in order to determine whether this attempt can commit (see SPARK-4879).
-      val shouldCoordinateWithDriver: Boolean = {
-        val sparkConf = SparkEnv.get.conf
-        // We only need to coordinate with the driver if there are multiple concurrent task
-        // attempts, which should only occur if speculation is enabled
-        val speculationEnabled = sparkConf.getBoolean("spark.speculation", false)
-        // This (undocumented) setting is an escape-hatch in case the commit code introduces bugs
-        sparkConf.getBoolean("spark.hadoop.outputCommitCoordination.enabled", speculationEnabled)
-      }
-      if (shouldCoordinateWithDriver) {
-        val outputCommitCoordinator = SparkEnv.get.outputCommitCoordinator
-        val canCommit = outputCommitCoordinator.canCommit(jobID, splitID, attemptID)
-        if (canCommit) {
-          performCommit()
-        } else {
-          val msg = s"$taID: Not committed because the driver did not authorize commit"
-          logInfo(msg)
-          // We need to abort the task so that the driver can reschedule new attempts, if necessary
-          cmtr.abortTask(taCtxt)
-          throw new CommitDeniedException(msg, jobID, splitID, attemptID)
-        }
-      } else {
-        // Speculation is disabled or a user has chosen to manually bypass the commit coordination
-        performCommit()
-      }
-    } else {
-      // Some other attempt committed the output, so we do nothing and signal success
-      logInfo(s"No need to commit output of task because needsTaskCommit=false: ${taID.value}")
-    }
+    SparkHadoopMapRedUtil.commitTask(
+      getOutputCommitter(), getTaskContext(), jobID, splitID, attemptID)
   }
 
   def commitJob() {

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

@@ -45,8 +45,7 @@ class SparkStatusTracker private[spark] (sc: SparkContext) {
    */
   def getJobIdsForGroup(jobGroup: String): Array[Int] = {
     jobProgressListener.synchronized {
-      val jobData = jobProgressListener.jobIdToData.valuesIterator
-      jobData.filter(_.jobGroup.orNull == jobGroup).map(_.jobId).toArray
+      jobProgressListener.jobGroupToJobIds.getOrElse(jobGroup, Seq.empty).toArray
     }
   }
 

core/src/main/scala/org/apache/spark/deploy/DeployMessage.scala

@@ -101,6 +101,8 @@ private[deploy] object DeployMessages {
   case class RegisterApplication(appDescription: ApplicationDescription)
     extends DeployMessage
 
+  case class UnregisterApplication(appId: String)
+
   case class MasterChangeAcknowledged(appId: String)
 
   // Master to AppClient

core/src/main/scala/org/apache/spark/deploy/client/AppClient.scala

@@ -157,6 +157,7 @@ private[spark] class AppClient(
 
       case StopAppClient =>
         markDead("Application has been stopped.")
+        master ! UnregisterApplication(appId)
         sender ! true
         context.stop(self)
     }