#!/usr/bin/env bash # # 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. # SCALA_VERSION=2.9.3 # Figure out where the Scala framework is installed FWDIR="$(cd `dirname $0`; pwd)" # Export this as SPARK_HOME export SPARK_HOME="$FWDIR" # Load environment variables from conf/spark-env.sh, if it exists if [ -e $FWDIR/conf/spark-env.sh ] ; then . $FWDIR/conf/spark-env.sh fi if [ -z "$1" ]; then echo "Usage: run []" >&2 exit 1 fi # If this is a standalone cluster daemon, reset SPARK_JAVA_OPTS and SPARK_MEM to reasonable # values for that; it doesn't need a lot if [ "$1" = "spark.deploy.master.Master" -o "$1" = "spark.deploy.worker.Worker" ]; then SPARK_MEM=${SPARK_DAEMON_MEMORY:-512m} SPARK_DAEMON_JAVA_OPTS="$SPARK_DAEMON_JAVA_OPTS -Dspark.akka.logLifecycleEvents=true" # Do not overwrite SPARK_JAVA_OPTS environment variable in this script OUR_JAVA_OPTS="$SPARK_DAEMON_JAVA_OPTS" # Empty by default else OUR_JAVA_OPTS="$SPARK_JAVA_OPTS" fi # Add java opts for master, worker, executor. The opts maybe null case "$1" in 'spark.deploy.master.Master') OUR_JAVA_OPTS="$OUR_JAVA_OPTS $SPARK_MASTER_OPTS" ;; 'spark.deploy.worker.Worker') OUR_JAVA_OPTS="$OUR_JAVA_OPTS $SPARK_WORKER_OPTS" ;; 'spark.executor.StandaloneExecutorBackend') OUR_JAVA_OPTS="$OUR_JAVA_OPTS $SPARK_EXECUTOR_OPTS" ;; 'spark.executor.MesosExecutorBackend') OUR_JAVA_OPTS="$OUR_JAVA_OPTS $SPARK_EXECUTOR_OPTS" ;; 'spark.repl.Main') OUR_JAVA_OPTS="$OUR_JAVA_OPTS $SPARK_REPL_OPTS" ;; esac # Figure out whether to run our class with java or with the scala launcher. # In most cases, we'd prefer to execute our process with java because scala # creates a shell script as the parent of its Java process, which makes it # hard to kill the child with stuff like Process.destroy(). However, for # the Spark shell, the wrapper is necessary to properly reset the terminal # when we exit, so we allow it to set a variable to launch with scala. # We still fall back on java for the shell if this is a "release" created # from make-distribution.sh since it's possible scala is not installed # but we have everything we need to run the shell. if [[ "$SPARK_LAUNCH_WITH_SCALA" == "1" && ! -f "$FWDIR/RELEASE" ]]; then if [ "$SCALA_HOME" ]; then RUNNER="${SCALA_HOME}/bin/scala" else if [ `command -v scala` ]; then RUNNER="scala" else echo "SCALA_HOME is not set and scala is not in PATH" >&2 exit 1 fi fi else if [ -n "${JAVA_HOME}" ]; then RUNNER="${JAVA_HOME}/bin/java" else if [ `command -v java` ]; then RUNNER="java" else echo "JAVA_HOME is not set" >&2 exit 1 fi fi if [[ ! -f "$FWDIR/RELEASE" && -z "$SCALA_LIBRARY_PATH" ]]; then if [ -z "$SCALA_HOME" ]; then echo "SCALA_HOME is not set" >&2 exit 1 fi SCALA_LIBRARY_PATH="$SCALA_HOME/lib" fi fi # Figure out how much memory to use per executor and set it as an environment # variable so that our process sees it and can report it to Mesos if [ -z "$SPARK_MEM" ] ; then SPARK_MEM="512m" fi export SPARK_MEM # Set JAVA_OPTS to be able to load native libraries and to set heap size JAVA_OPTS="$OUR_JAVA_OPTS" JAVA_OPTS="$JAVA_OPTS -Djava.library.path=$SPARK_LIBRARY_PATH" JAVA_OPTS="$JAVA_OPTS -Xms$SPARK_MEM -Xmx$SPARK_MEM" # Load extra JAVA_OPTS from conf/java-opts, if it exists if [ -e $FWDIR/conf/java-opts ] ; then JAVA_OPTS="$JAVA_OPTS `cat $FWDIR/conf/java-opts`" fi export JAVA_OPTS # Attention: when changing the way the JAVA_OPTS are assembled, the change must be reflected in ExecutorRunner.scala! if [ ! -f "$FWDIR/RELEASE" ]; then CORE_DIR="$FWDIR/core" EXAMPLES_DIR="$FWDIR/examples" REPL_DIR="$FWDIR/repl" # Exit if the user hasn't compiled Spark if [ ! -e "$CORE_DIR/target" ]; then echo "Failed to find Spark classes in $CORE_DIR/target" >&2 echo "You need to compile Spark before running this program" >&2 exit 1 fi if [[ "$@" = *repl* && ! -e "$REPL_DIR/target" ]]; then echo "Failed to find Spark classes in $REPL_DIR/target" >&2 echo "You need to compile Spark repl module before running this program" >&2 exit 1 fi # Figure out the JAR file that our examples were packaged into. This includes a bit of a hack # to avoid the -sources and -doc packages that are built by publish-local. if [ -e "$EXAMPLES_DIR/target/scala-$SCALA_VERSION/spark-examples"*[0-9T].jar ]; then # Use the JAR from the SBT build export SPARK_EXAMPLES_JAR=`ls "$EXAMPLES_DIR/target/scala-$SCALA_VERSION/spark-examples"*[0-9T].jar` fi if [ -e "$EXAMPLES_DIR/target/spark-examples"*[0-9T].jar ]; then # Use the JAR from the Maven build export SPARK_EXAMPLES_JAR=`ls "$EXAMPLES_DIR/target/spark-examples"*[0-9T].jar` fi fi # Compute classpath using external script CLASSPATH=`$FWDIR/bin/compute-classpath.sh` export CLASSPATH if [ "$SPARK_LAUNCH_WITH_SCALA" == "1" ]; then EXTRA_ARGS="" # Java options will be passed to scala as JAVA_OPTS else # The JVM doesn't read JAVA_OPTS by default so we need to pass it in EXTRA_ARGS="$JAVA_OPTS" fi command="$RUNNER -cp \"$CLASSPATH\" $EXTRA_ARGS $@" if [ "$SPARK_PRINT_LAUNCH_COMMAND" == "1" ]; then echo "Spark Command: $command" echo "========================================" echo fi exec $command