Merge branch 'master' of git://git.apache.org/spark into SPARK-5188

bin/compute-classpath.sh

@@ -72,22 +72,25 @@ else
   assembly_folder="$ASSEMBLY_DIR"
 fi
 
-num_jars="$(ls "$assembly_folder" | grep "spark-assembly.*hadoop.*\.jar$" | wc -l)"
-if [ "$num_jars" -eq "0" ]; then
-  echo "Failed to find Spark assembly in $assembly_folder"
-  echo "You need to build Spark before running this program."
-  exit 1
-fi
+num_jars=0
+
+for f in ${assembly_folder}/spark-assembly*hadoop*.jar; do
+  if [[ ! -e "$f" ]]; then
+    echo "Failed to find Spark assembly in $assembly_folder" 1>&2
+    echo "You need to build Spark before running this program." 1>&2
+    exit 1
+  fi
+  ASSEMBLY_JAR="$f"
+  num_jars=$((num_jars+1))
+done
+
 if [ "$num_jars" -gt "1" ]; then
-  jars_list=$(ls "$assembly_folder" | grep "spark-assembly.*hadoop.*.jar$")
-  echo "Found multiple Spark assembly jars in $assembly_folder:"
-  echo "$jars_list"
-  echo "Please remove all but one jar."
+  echo "Found multiple Spark assembly jars in $assembly_folder:" 1>&2
+  ls ${assembly_folder}/spark-assembly*hadoop*.jar 1>&2
+  echo "Please remove all but one jar." 1>&2
   exit 1
 fi
 
-ASSEMBLY_JAR="$(ls "$assembly_folder"/spark-assembly*hadoop*.jar 2>/dev/null)"
-
 # Verify that versions of java used to build the jars and run Spark are compatible
 jar_error_check=$("$JAR_CMD" -tf "$ASSEMBLY_JAR" nonexistent/class/path 2>&1)
 if [[ "$jar_error_check" =~ "invalid CEN header" ]]; then

bin/run-example

@@ -35,17 +35,32 @@ else
 fi
 
 if [ -f "$FWDIR/RELEASE" ]; then
-  export SPARK_EXAMPLES_JAR="`ls "$FWDIR"/lib/spark-examples-*hadoop*.jar`"
-elif [ -e "$EXAMPLES_DIR"/target/scala-$SPARK_SCALA_VERSION/spark-examples-*hadoop*.jar ]; then
-  export SPARK_EXAMPLES_JAR="`ls "$EXAMPLES_DIR"/target/scala-$SPARK_SCALA_VERSION/spark-examples-*hadoop*.jar`"
+  JAR_PATH="${FWDIR}/lib"
+else
+  JAR_PATH="${EXAMPLES_DIR}/target/scala-${SPARK_SCALA_VERSION}"
 fi
 
-if [[ -z "$SPARK_EXAMPLES_JAR" ]]; then
-  echo "Failed to find Spark examples assembly in $FWDIR/lib or $FWDIR/examples/target" 1>&2
-  echo "You need to build Spark before running this program" 1>&2
+JAR_COUNT=0
+
+for f in ${JAR_PATH}/spark-examples-*hadoop*.jar; do
+  if [[ ! -e "$f" ]]; then
+    echo "Failed to find Spark examples assembly in $FWDIR/lib or $FWDIR/examples/target" 1>&2
+    echo "You need to build Spark before running this program" 1>&2
+    exit 1
+  fi
+  SPARK_EXAMPLES_JAR="$f"
+  JAR_COUNT=$((JAR_COUNT+1))
+done
+
+if [ "$JAR_COUNT" -gt "1" ]; then
+  echo "Found multiple Spark examples assembly jars in ${JAR_PATH}" 1>&2
+  ls ${JAR_PATH}/spark-examples-*hadoop*.jar 1>&2
+  echo "Please remove all but one jar." 1>&2
   exit 1
 fi
 
+export SPARK_EXAMPLES_JAR
+
 EXAMPLE_MASTER=${MASTER:-"local[*]"}
 
 if [[ ! $EXAMPLE_CLASS == org.apache.spark.examples* ]]; then

bin/spark-class

@@ -71,6 +71,8 @@ case "$1" in
   'org.apache.spark.executor.MesosExecutorBackend')
     OUR_JAVA_OPTS="$SPARK_JAVA_OPTS $SPARK_EXECUTOR_OPTS"
     OUR_JAVA_MEM=${SPARK_EXECUTOR_MEMORY:-$DEFAULT_MEM}
+    export PYTHONPATH="$FWDIR/python:$PYTHONPATH"
+    export PYTHONPATH="$FWDIR/python/lib/py4j-0.8.2.1-src.zip:$PYTHONPATH"
     ;;
 
   # Spark submit uses SPARK_JAVA_OPTS + SPARK_SUBMIT_OPTS +
@@ -148,7 +150,7 @@ fi
 if [[ "$1" =~ org.apache.spark.tools.* ]]; then
   if test -z "$SPARK_TOOLS_JAR"; then
     echo "Failed to find Spark Tools Jar in $FWDIR/tools/target/scala-$SPARK_SCALA_VERSION/" 1>&2
-    echo "You need to build Spark before running $1." 1>&2
+    echo "You need to run \"build/sbt tools/package\" before running $1." 1>&2
     exit 1
   fi
   CLASSPATH="$CLASSPATH:$SPARK_TOOLS_JAR"

bin/spark-submit

@@ -44,7 +44,10 @@ while (($#)); do
   shift
 done
 
-DEFAULT_PROPERTIES_FILE="$SPARK_HOME/conf/spark-defaults.conf"
+if [ -z "$SPARK_CONF_DIR" ]; then
+  export SPARK_CONF_DIR="$SPARK_HOME/conf"
+fi
+DEFAULT_PROPERTIES_FILE="$SPARK_CONF_DIR/spark-defaults.conf"
 if [ "$MASTER" == "yarn-cluster" ]; then
   SPARK_SUBMIT_DEPLOY_MODE=cluster
 fi

bin/spark-submit2.cmd

@@ -24,7 +24,11 @@ set ORIG_ARGS=%*
 
 rem Reset the values of all variables used
 set SPARK_SUBMIT_DEPLOY_MODE=client
-set SPARK_SUBMIT_PROPERTIES_FILE=%SPARK_HOME%\conf\spark-defaults.conf
+
+if not defined %SPARK_CONF_DIR% (
+  set SPARK_CONF_DIR=%SPARK_HOME%\conf
+)
+set SPARK_SUBMIT_PROPERTIES_FILE=%SPARK_CONF_DIR%\spark-defaults.conf
 set SPARK_SUBMIT_DRIVER_MEMORY=
 set SPARK_SUBMIT_LIBRARY_PATH=
 set SPARK_SUBMIT_CLASSPATH=

core/src/main/java/org/apache/spark/JavaSparkListener.java

@@ -0,0 +1,97 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark;
+
+import org.apache.spark.scheduler.SparkListener;
+import org.apache.spark.scheduler.SparkListenerApplicationEnd;
+import org.apache.spark.scheduler.SparkListenerApplicationStart;
+import org.apache.spark.scheduler.SparkListenerBlockManagerAdded;
+import org.apache.spark.scheduler.SparkListenerBlockManagerRemoved;
+import org.apache.spark.scheduler.SparkListenerEnvironmentUpdate;
+import org.apache.spark.scheduler.SparkListenerExecutorAdded;
+import org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate;
+import org.apache.spark.scheduler.SparkListenerExecutorRemoved;
+import org.apache.spark.scheduler.SparkListenerJobEnd;
+import org.apache.spark.scheduler.SparkListenerJobStart;
+import org.apache.spark.scheduler.SparkListenerStageCompleted;
+import org.apache.spark.scheduler.SparkListenerStageSubmitted;
+import org.apache.spark.scheduler.SparkListenerTaskEnd;
+import org.apache.spark.scheduler.SparkListenerTaskGettingResult;
+import org.apache.spark.scheduler.SparkListenerTaskStart;
+import org.apache.spark.scheduler.SparkListenerUnpersistRDD;
+
+/**
+ * Java clients should extend this class instead of implementing
+ * SparkListener directly. This is to prevent java clients
+ * from breaking when new events are added to the SparkListener
+ * trait.
+ *
+ * This is a concrete class instead of abstract to enforce
+ * new events get added to both the SparkListener and this adapter
+ * in lockstep.
+ */
+public class JavaSparkListener implements SparkListener {
+
+  @Override
+  public void onStageCompleted(SparkListenerStageCompleted stageCompleted) { }
+
+  @Override
+  public void onStageSubmitted(SparkListenerStageSubmitted stageSubmitted) { }
+
+  @Override
+  public void onTaskStart(SparkListenerTaskStart taskStart) { }
+
+  @Override
+  public void onTaskGettingResult(SparkListenerTaskGettingResult taskGettingResult) { }
+
+  @Override
+  public void onTaskEnd(SparkListenerTaskEnd taskEnd) { }
+
+  @Override
+  public void onJobStart(SparkListenerJobStart jobStart) { }
+
+  @Override
+  public void onJobEnd(SparkListenerJobEnd jobEnd) { }
+
+  @Override
+  public void onEnvironmentUpdate(SparkListenerEnvironmentUpdate environmentUpdate) { }
+
+  @Override
+  public void onBlockManagerAdded(SparkListenerBlockManagerAdded blockManagerAdded) { }
+
+  @Override
+  public void onBlockManagerRemoved(SparkListenerBlockManagerRemoved blockManagerRemoved) { }
+
+  @Override
+  public void onUnpersistRDD(SparkListenerUnpersistRDD unpersistRDD) { }
+
+  @Override
+  public void onApplicationStart(SparkListenerApplicationStart applicationStart) { }
+
+  @Override
+  public void onApplicationEnd(SparkListenerApplicationEnd applicationEnd) { }
+
+  @Override
+  public void onExecutorMetricsUpdate(SparkListenerExecutorMetricsUpdate executorMetricsUpdate) { }
+
+  @Override
+  public void onExecutorAdded(SparkListenerExecutorAdded executorAdded) { }
+
+  @Override
+  public void onExecutorRemoved(SparkListenerExecutorRemoved executorRemoved) { }
+}

core/src/main/java/org/apache/spark/TaskContext.java

@@ -62,7 +62,7 @@ static void unset() {
    */
   public abstract boolean isInterrupted();
 
-  /** @deprecated: use isRunningLocally() */
+  /** @deprecated use {@link #isRunningLocally()} */
   @Deprecated
   public abstract boolean runningLocally();
 
@@ -87,19 +87,39 @@ static void unset() {
    * is for HadoopRDD to register a callback to close the input stream.
    * Will be called in any situation - success, failure, or cancellation.
    *
-   * @deprecated: use addTaskCompletionListener
+   * @deprecated use {@link #addTaskCompletionListener(scala.Function1)}
    *
    * @param f Callback function.
    */
   @Deprecated
   public abstract void addOnCompleteCallback(final Function0<Unit> f);
 
+  /**
+   * The ID of the stage that this task belong to.
+   */
   public abstract int stageId();
 
+  /**
+   * The ID of the RDD partition that is computed by this task.
+   */
   public abstract int partitionId();
 
+  /**
+   * How many times this task has been attempted.  The first task attempt will be assigned
+   * attemptNumber = 0, and subsequent attempts will have increasing attempt numbers.
+   */
+  public abstract int attemptNumber();
+
+  /** @deprecated use {@link #taskAttemptId()}; it was renamed to avoid ambiguity. */
+  @Deprecated
   public abstract long attemptId();
 
+  /**
+   * An ID that is unique to this task attempt (within the same SparkContext, no two task attempts
+   * will share the same attempt ID).  This is roughly equivalent to Hadoop's TaskAttemptID.
+   */
+  public abstract long taskAttemptId();
+
   /** ::DeveloperApi:: */
   @DeveloperApi
   public abstract TaskMetrics taskMetrics();

core/src/main/resources/org/apache/spark/ui/static/webui.css

@@ -19,6 +19,7 @@
   height: 50px;
   font-size: 15px;
   margin-bottom: 15px;
+  min-width: 1200px
 }
 
 .navbar .navbar-inner {
@@ -39,12 +40,12 @@
 
 .navbar .nav > li a {
   height: 30px;
-  line-height: 30px;
+  line-height: 2;
 }
 
 .navbar-text {
   height: 50px;
-  line-height: 50px;
+  line-height: 3.3;
 }
 
 table.sortable thead {
@@ -170,7 +171,7 @@ span.additional-metric-title {
 }
 
 .version {
-  line-height: 30px;
+  line-height: 2.5;
   vertical-align: bottom;
   font-size: 12px;
   padding: 0;

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

@@ -61,8 +61,8 @@ case class Aggregator[K, V, C] (
       // Update task metrics if context is not null
       // TODO: Make context non optional in a future release
       Option(context).foreach { c =>
-        c.taskMetrics.memoryBytesSpilled += combiners.memoryBytesSpilled
-        c.taskMetrics.diskBytesSpilled += combiners.diskBytesSpilled
+        c.taskMetrics.incMemoryBytesSpilled(combiners.memoryBytesSpilled)
+        c.taskMetrics.incDiskBytesSpilled(combiners.diskBytesSpilled)
       }
       combiners.iterator
     }
@@ -95,8 +95,8 @@ case class Aggregator[K, V, C] (
       // Update task metrics if context is not null
       // TODO: Make context non-optional in a future release
       Option(context).foreach { c =>
-        c.taskMetrics.memoryBytesSpilled += combiners.memoryBytesSpilled
-        c.taskMetrics.diskBytesSpilled += combiners.diskBytesSpilled
+        c.taskMetrics.incMemoryBytesSpilled(combiners.memoryBytesSpilled)
+        c.taskMetrics.incDiskBytesSpilled(combiners.diskBytesSpilled)
       }
       combiners.iterator
     }

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

@@ -44,7 +44,11 @@ private[spark] class CacheManager(blockManager: BlockManager) extends Logging {
     blockManager.get(key) match {
       case Some(blockResult) =>
         // Partition is already materialized, so just return its values
-        context.taskMetrics.inputMetrics = Some(blockResult.inputMetrics)
+        val inputMetrics = blockResult.inputMetrics
+        val existingMetrics = context.taskMetrics
+          .getInputMetricsForReadMethod(inputMetrics.readMethod)
+        existingMetrics.addBytesRead(inputMetrics.bytesRead)
+
         new InterruptibleIterator(context, blockResult.data.asInstanceOf[Iterator[T]])
 
       case None =>