spark-instrumented-optimizer/bin/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.
#

cygwin=false
case "`uname`" in
    CYGWIN*) cygwin=true;;
esac

SCALA_VERSION=2.10

# Figure out where the Scala framework is installed
FWDIR="$(cd `dirname $0`/..; pwd)"

# Export this as SPARK_HOME
export SPARK_HOME="$FWDIR"

. $FWDIR/bin/load-spark-env.sh

if [ -z "$1" ]; then
  echo "Usage: spark-class <class> [<args>]" >&2
  exit 1
fi

if [ -n "$SPARK_MEM" ]; then
  echo "Warning: SPARK_MEM is deprecated, please use a more specific config option"
  echo "(e.g., spark.executor.memory or SPARK_DRIVER_MEMORY)."
fi

# Use SPARK_MEM or 512m as the default memory, to be overridden by specific options
DEFAULT_MEM=${SPARK_MEM:-512m}

SPARK_DAEMON_JAVA_OPTS="$SPARK_DAEMON_JAVA_OPTS -Dspark.akka.logLifecycleEvents=true"

# Add java opts and memory settings for master, worker, history server, executors, and repl.
case "$1" in
  # Master, Worker, and HistoryServer use SPARK_DAEMON_JAVA_OPTS (and specific opts) + SPARK_DAEMON_MEMORY.
  'org.apache.spark.deploy.master.Master')
    OUR_JAVA_OPTS="$SPARK_DAEMON_JAVA_OPTS $SPARK_MASTER_OPTS"
    OUR_JAVA_MEM=${SPARK_DAEMON_MEMORY:-$DEFAULT_MEM}
    ;;
  'org.apache.spark.deploy.worker.Worker')
    OUR_JAVA_OPTS="$SPARK_DAEMON_JAVA_OPTS $SPARK_WORKER_OPTS"
    OUR_JAVA_MEM=${SPARK_DAEMON_MEMORY:-$DEFAULT_MEM}
    ;;
  'org.apache.spark.deploy.history.HistoryServer')
    OUR_JAVA_OPTS="$SPARK_DAEMON_JAVA_OPTS $SPARK_HISTORY_OPTS"
    OUR_JAVA_MEM=${SPARK_DAEMON_MEMORY:-$DEFAULT_MEM}
    ;;

  # Executors use SPARK_JAVA_OPTS + SPARK_EXECUTOR_MEMORY.
  'org.apache.spark.executor.CoarseGrainedExecutorBackend')
    OUR_JAVA_OPTS="$SPARK_JAVA_OPTS $SPARK_EXECUTOR_OPTS"
    OUR_JAVA_MEM=${SPARK_EXECUTOR_MEMORY:-$DEFAULT_MEM}
    ;;
  'org.apache.spark.executor.MesosExecutorBackend')
    OUR_JAVA_OPTS="$SPARK_JAVA_OPTS $SPARK_EXECUTOR_OPTS"
    OUR_JAVA_MEM=${SPARK_EXECUTOR_MEMORY:-$DEFAULT_MEM}
    ;;

  # All drivers use SPARK_JAVA_OPTS + SPARK_DRIVER_MEMORY. The repl also uses SPARK_REPL_OPTS.
  'org.apache.spark.repl.Main')
    OUR_JAVA_OPTS="$SPARK_JAVA_OPTS $SPARK_REPL_OPTS"
    OUR_JAVA_MEM=${SPARK_DRIVER_MEMORY:-$DEFAULT_MEM}
    ;;
  *)
    OUR_JAVA_OPTS="$SPARK_JAVA_OPTS"
    OUR_JAVA_MEM=${SPARK_DRIVER_MEMORY:-$DEFAULT_MEM}
    ;;
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 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$OUR_JAVA_MEM -Xmx$OUR_JAVA_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 "$FWDIR/RELEASE" ]; then
  # Exit if the user hasn't compiled Spark
  num_jars=$(ls "$FWDIR"/assembly/target/scala-$SCALA_VERSION/ | grep "spark-assembly.*hadoop.*.jar" | wc -l)
  jars_list=$(ls "$FWDIR"/assembly/target/scala-$SCALA_VERSION/ | grep "spark-assembly.*hadoop.*.jar")
  if [ "$num_jars" -eq "0" ]; then
    echo "Failed to find Spark assembly in $FWDIR/assembly/target/scala-$SCALA_VERSION/" >&2
    echo "You need to build Spark with 'sbt/sbt assembly' before running this program." >&2
    exit 1
  fi
  if [ "$num_jars" -gt "1" ]; then
    echo "Found multiple Spark assembly jars in $FWDIR/assembly/target/scala-$SCALA_VERSION:" >&2
    echo "$jars_list"
    echo "Please remove all but one jar."
    exit 1
  fi
fi

TOOLS_DIR="$FWDIR"/tools
SPARK_TOOLS_JAR=""
if [ -e "$TOOLS_DIR"/target/scala-$SCALA_VERSION/*assembly*[0-9Tg].jar ]; then
  # Use the JAR from the SBT build
  export SPARK_TOOLS_JAR=`ls "$TOOLS_DIR"/target/scala-$SCALA_VERSION/*assembly*[0-9Tg].jar`
fi
if [ -e "$TOOLS_DIR"/target/spark-tools*[0-9Tg].jar ]; then
  # Use the JAR from the Maven build
  # TODO: this also needs to become an assembly!
  export SPARK_TOOLS_JAR=`ls "$TOOLS_DIR"/target/spark-tools*[0-9Tg].jar`
fi

# Compute classpath using external script
CLASSPATH=`$FWDIR/bin/compute-classpath.sh`
if [[ "$1" =~ org.apache.spark.tools.* ]]; then
  CLASSPATH="$CLASSPATH:$SPARK_TOOLS_JAR"
fi

if $cygwin; then
  CLASSPATH=`cygpath -wp $CLASSPATH`
  if [ "$1" == "org.apache.spark.tools.JavaAPICompletenessChecker" ]; then
    export SPARK_TOOLS_JAR=`cygpath -w $SPARK_TOOLS_JAR`
  fi
fi
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" $JAVA_OPTS "$@"