#!/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 $SPARK_REPL_OPTS" ;; esac # Find the java binary if [ -n "${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="$SCALA_HOME/lib" fi # Set SPARK_MEM if it isn't already set since we also use it for this process SPARK_MEM=${SPARK_MEM:-512m} 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 # Exit if the user hasn't compiled Spark ls "$FWDIR"/assembly/target/scala-$SCALA_VERSION/spark-assembly*hadoop*.jar >& /dev/null if [[ $? != 0 ]]; then echo "Failed to find Spark assembly in $FWDIR/assembly/target" >&2 echo "You need to build Spark with sbt/sbt assembly before running this program" >&2 exit 1 fi fi # Compute classpath using external script CLASSPATH=`$FWDIR/bin/compute-classpath.sh` export CLASSPATH if [ "$SPARK_PRINT_LAUNCH_COMMAND" == "1" ]; then echo -n "Spark Command: " echo "$RUNNER" -cp "$CLASSPATH" $JAVA_OPTS "$@" echo "========================================" echo fi exec "$RUNNER" -cp "$CLASSPATH" $JAVA_OPTS "$@"