Merge remote-tracking branch 'apache-github/master' into doc-fix

Conflicts:
	docs/streaming-programming-guide.md

Author: tdas

.gitignore

@@ -49,3 +49,9 @@ unit-tests.log
 /lib/
 rat-results.txt
 scalastyle.txt
+
+# For Hive
+metastore_db/
+metastore/
+warehouse/
+TempStatsStore/

bin/compute-classpath.sh

@@ -32,6 +32,12 @@ CLASSPATH="$SPARK_CLASSPATH:$SPARK_SUBMIT_CLASSPATH:$FWDIR/conf"
 
 ASSEMBLY_DIR="$FWDIR/assembly/target/scala-$SCALA_VERSION"
 
+if [ -n "${JAVA_HOME}" ]; then
+  JAR_CMD="${JAVA_HOME}/bin/jar"
+else
+  JAR_CMD="jar"
+fi
+
 # First check if we have a dependencies jar. If so, include binary classes with the deps jar
 if [ -f "$ASSEMBLY_DIR"/spark-assembly*hadoop*-deps.jar ]; then
   CLASSPATH="$CLASSPATH:$FWDIR/core/target/scala-$SCALA_VERSION/classes"
@@ -44,6 +50,7 @@ if [ -f "$ASSEMBLY_DIR"/spark-assembly*hadoop*-deps.jar ]; then
   CLASSPATH="$CLASSPATH:$FWDIR/sql/catalyst/target/scala-$SCALA_VERSION/classes"
   CLASSPATH="$CLASSPATH:$FWDIR/sql/core/target/scala-$SCALA_VERSION/classes"
   CLASSPATH="$CLASSPATH:$FWDIR/sql/hive/target/scala-$SCALA_VERSION/classes"
+  CLASSPATH="$CLASSPATH:$FWDIR/yarn/stable/target/scala-$SCALA_VERSION/classes"
 
   DEPS_ASSEMBLY_JAR=`ls "$ASSEMBLY_DIR"/spark-assembly*hadoop*-deps.jar`
   CLASSPATH="$CLASSPATH:$DEPS_ASSEMBLY_JAR"
@@ -54,6 +61,14 @@ else
   else
     ASSEMBLY_JAR=`ls "$ASSEMBLY_DIR"/spark-assembly*hadoop*.jar`
   fi
+  jar_error_check=$($JAR_CMD -tf $ASSEMBLY_JAR org/apache/spark/SparkContext 2>&1)
+  if [[ "$jar_error_check" =~ "invalid CEN header" ]]; then
+    echo "Loading Spark jar with '$JAR_CMD' failed. "
+    echo "This is likely because Spark was compiled with Java 7 and run "
+    echo "with Java 6. (see SPARK-1703). Please use Java 7 to run Spark "
+    echo "or build Spark with Java 6."
+    exit 1
+  fi
   CLASSPATH="$CLASSPATH:$ASSEMBLY_JAR"
 fi
 

bin/pyspark

@@ -46,6 +46,7 @@ export PYSPARK_PYTHON
 
 # Add the PySpark classes to the Python path:
 export PYTHONPATH=$SPARK_HOME/python/:$PYTHONPATH
+export PYTHONPATH=$SPARK_HOME/python/lib/py4j-0.8.1-src.zip:$PYTHONPATH
 
 # Load the PySpark shell.py script when ./pyspark is used interactively:
 export OLD_PYTHONSTARTUP=$PYTHONSTARTUP

bin/pyspark2.cmd

@@ -45,6 +45,7 @@ rem Figure out which Python to use.
 if "x%PYSPARK_PYTHON%"=="x" set PYSPARK_PYTHON=python
 
 set PYTHONPATH=%FWDIR%python;%PYTHONPATH%
+set PYTHONPATH=%FWDIR%python\lib\py4j-0.8.1-src.zip;%PYTHONPATH%
 
 set OLD_PYTHONSTARTUP=%PYTHONSTARTUP%
 set PYTHONSTARTUP=%FWDIR%python\pyspark\shell.py

bin/spark-class

@@ -138,7 +138,14 @@ if [ -e "$TOOLS_DIR"/target/spark-tools*[0-9Tg].jar ]; then
 fi
 
 # Compute classpath using external script
-CLASSPATH=`$FWDIR/bin/compute-classpath.sh`
+classpath_output=$($FWDIR/bin/compute-classpath.sh)
+if [[ "$?" != "0" ]]; then
+  echo "$classpath_output"
+  exit 1
+else
+  CLASSPATH=$classpath_output
+fi
+
 if [[ "$1" =~ org.apache.spark.tools.* ]]; then
   CLASSPATH="$CLASSPATH:$SPARK_TOOLS_JAR"
 fi

bin/spark-submit

@@ -18,7 +18,7 @@
 #
 
 export SPARK_HOME="$(cd `dirname $0`/..; pwd)"
-ORIG_ARGS=$@
+ORIG_ARGS=("$@")
 
 while (($#)); do
   if [ "$1" = "--deploy-mode" ]; then
@@ -39,5 +39,5 @@ if [ ! -z $DRIVER_MEMORY ] && [ ! -z $DEPLOY_MODE ] && [ $DEPLOY_MODE = "client"
   export SPARK_MEM=$DRIVER_MEMORY
 fi
 
-$SPARK_HOME/bin/spark-class org.apache.spark.deploy.SparkSubmit $ORIG_ARGS
+$SPARK_HOME/bin/spark-class org.apache.spark.deploy.SparkSubmit "${ORIG_ARGS[@]}"
 

core/pom.xml

@@ -38,12 +38,6 @@
     <dependency>
       <groupId>net.java.dev.jets3t</groupId>
       <artifactId>jets3t</artifactId>
-      <exclusions>
-        <exclusion>
-          <groupId>commons-logging</groupId>
-          <artifactId>commons-logging</artifactId>
-        </exclusion>
-      </exclusions>
     </dependency>
     <dependency>
       <groupId>org.apache.curator</groupId>
@@ -69,6 +63,10 @@
       <groupId>com.google.guava</groupId>
       <artifactId>guava</artifactId>
     </dependency>
+    <dependency>
+      <groupId>org.apache.commons</groupId>
+      <artifactId>commons-lang3</artifactId>
+    </dependency>
     <dependency>
       <groupId>com.google.code.findbugs</groupId>
       <artifactId>jsr305</artifactId>
@@ -294,6 +292,48 @@
           </environmentVariables>
         </configuration>
       </plugin>
+      <!-- Unzip py4j so we can include its files in the jar -->
+      <plugin>
+        <groupId>org.codehaus.mojo</groupId>
+        <artifactId>exec-maven-plugin</artifactId>
+        <version>1.2.1</version>
+        <executions>
+          <execution>
+            <phase>generate-resources</phase>
+            <goals>
+              <goal>exec</goal>
+            </goals>
+          </execution>
+        </executions>
+        <configuration>
+          <executable>unzip</executable>
+          <workingDirectory>../python</workingDirectory>
+          <arguments>
+            <argument>-o</argument>
+            <argument>lib/py4j*.zip</argument>
+            <argument>-d</argument>
+            <argument>build</argument>
+          </arguments>
+        </configuration>
+      </plugin>
     </plugins>
+    
+    <resources>
+      <resource>
+        <directory>src/main/resources</directory>
+      </resource>
+      <resource>
+        <directory>../python</directory>
+        <includes>
+          <include>pyspark/*.py</include>
+        </includes>
+      </resource>
+      <resource>
+        <directory>../python/build</directory>
+        <includes>
+          <include>py4j/*.py</include>
+        </includes>
+      </resource>
+    </resources>
   </build>
 </project>

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

@@ -156,13 +156,11 @@ object SparkEnv extends Logging {
       conf.set("spark.driver.port",  boundPort.toString)
     }
 
-    val classLoader = Thread.currentThread.getContextClassLoader
-
     // Create an instance of the class named by the given Java system property, or by
     // defaultClassName if the property is not set, and return it as a T
     def instantiateClass[T](propertyName: String, defaultClassName: String): T = {
       val name = conf.get(propertyName,  defaultClassName)
-      val cls = Class.forName(name, true, classLoader)
+      val cls = Class.forName(name, true, Utils.getContextOrSparkClassLoader)
       // First try with the constructor that takes SparkConf. If we can't find one,
       // use a no-arg constructor instead.
       try {

core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala

@@ -54,7 +54,16 @@ private[spark] class PythonRDD[T: ClassTag](
   override def compute(split: Partition, context: TaskContext): Iterator[Array[Byte]] = {
     val startTime = System.currentTimeMillis
     val env = SparkEnv.get
-    val worker = env.createPythonWorker(pythonExec, envVars.toMap)
+    val worker: Socket = env.createPythonWorker(pythonExec, envVars.toMap)
+
+    // Ensure worker socket is closed on task completion. Closing sockets is idempotent.
+    context.addOnCompleteCallback(() =>
+      try {
+        worker.close()
+      } catch {
+        case e: Exception => logWarning("Failed to close worker socket", e)
+      }
+    )
 
     @volatile var readerException: Exception = null
 

core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala

@@ -78,12 +78,9 @@ private[spark] class PythonWorkerFactory(pythonExec: String, envVars: Map[String
       serverSocket = new ServerSocket(0, 1, InetAddress.getByAddress(Array(127, 0, 0, 1)))
 
       // Create and start the worker
-      val sparkHome = new ProcessBuilder().environment().get("SPARK_HOME")
-      val pb = new ProcessBuilder(Seq(pythonExec, sparkHome + "/python/pyspark/worker.py"))
+      val pb = new ProcessBuilder(Seq(pythonExec, "-m", "pyspark.worker"))
       val workerEnv = pb.environment()
       workerEnv.putAll(envVars)
-      val pythonPath = sparkHome + "/python/" + File.pathSeparator + workerEnv.get("PYTHONPATH")
-      workerEnv.put("PYTHONPATH", pythonPath)
       val worker = pb.start()
 
       // Redirect the worker's stderr to ours
@@ -154,12 +151,9 @@ private[spark] class PythonWorkerFactory(pythonExec: String, envVars: Map[String
 
       try {
         // Create and start the daemon
-        val sparkHome = new ProcessBuilder().environment().get("SPARK_HOME")
-        val pb = new ProcessBuilder(Seq(pythonExec, sparkHome + "/python/pyspark/daemon.py"))
+        val pb = new ProcessBuilder(Seq(pythonExec, "-m", "pyspark.daemon"))
         val workerEnv = pb.environment()
         workerEnv.putAll(envVars)
-        val pythonPath = sparkHome + "/python/" + File.pathSeparator + workerEnv.get("PYTHONPATH")
-        workerEnv.put("PYTHONPATH", pythonPath)
         daemon = pb.start()
 
         // Redirect the stderr to ours