spark-class

#!/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: spark-class <class> [<args>]" >&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" = "org.apache.spark.deploy.master.Master" -o "$1" = "org.apache.spark.deploy.worker.Worker" ]; then
  SPARK_MEM=${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 "$1" in
  'org.apache.spark.deploy.master.Master')
    OUR_JAVA_OPTS="$OUR_JAVA_OPTS $SPARK_MASTER_OPTS"
    ;;
  'org.apache.spark.deploy.worker.Worker')
    OUR_JAVA_OPTS="$OUR_JAVA_OPTS $SPARK_WORKER_OPTS"
    ;;
  'org.apache.spark.executor.StandaloneExecutorBackend')
    OUR_JAVA_OPTS="$OUR_JAVA_OPTS $SPARK_EXECUTOR_OPTS"
    ;;
  'org.apache.spark.executor.MesosExecutorBackend')
    OUR_JAVA_OPTS="$OUR_JAVA_OPTS $SPARK_EXECUTOR_OPTS"
    ;;
  'org.apache.spark.repl.Main')
    OUR_JAVA_OPTS="$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

# 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" $JAVA_OPTS "$@"