зеркало из https://github.com/microsoft/spark.git
118 строки
3.7 KiB
Bash
Executable File
118 строки
3.7 KiB
Bash
Executable File
#!/usr/bin/env bash
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#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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SCALA_VERSION=2.9.3
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# Figure out where the Scala framework is installed
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FWDIR="$(cd `dirname $0`; pwd)"
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# Export this as SPARK_HOME
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export SPARK_HOME="$FWDIR"
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# Load environment variables from conf/spark-env.sh, if it exists
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if [ -e $FWDIR/conf/spark-env.sh ] ; then
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. $FWDIR/conf/spark-env.sh
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fi
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if [ -z "$1" ]; then
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echo "Usage: run <spark-class> [<args>]" >&2
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exit 1
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fi
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# If this is a standalone cluster daemon, reset SPARK_JAVA_OPTS and SPARK_MEM to reasonable
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# values for that; it doesn't need a lot
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if [ "$1" = "spark.deploy.master.Master" -o "$1" = "spark.deploy.worker.Worker" ]; then
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SPARK_MEM=${SPARK_DAEMON_MEMORY:-512m}
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SPARK_DAEMON_JAVA_OPTS="$SPARK_DAEMON_JAVA_OPTS -Dspark.akka.logLifecycleEvents=true"
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# Do not overwrite SPARK_JAVA_OPTS environment variable in this script
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OUR_JAVA_OPTS="$SPARK_DAEMON_JAVA_OPTS" # Empty by default
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else
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OUR_JAVA_OPTS="$SPARK_JAVA_OPTS"
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fi
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# Add java opts for master, worker, executor. The opts maybe null
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case "$1" in
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'spark.deploy.master.Master')
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OUR_JAVA_OPTS="$OUR_JAVA_OPTS $SPARK_MASTER_OPTS"
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;;
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'spark.deploy.worker.Worker')
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OUR_JAVA_OPTS="$OUR_JAVA_OPTS $SPARK_WORKER_OPTS"
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;;
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'spark.executor.StandaloneExecutorBackend')
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OUR_JAVA_OPTS="$OUR_JAVA_OPTS $SPARK_EXECUTOR_OPTS"
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;;
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'spark.executor.MesosExecutorBackend')
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OUR_JAVA_OPTS="$OUR_JAVA_OPTS $SPARK_EXECUTOR_OPTS"
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;;
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'spark.repl.Main')
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OUR_JAVA_OPTS="$OUR_JAVA_OPTS $SPARK_REPL_OPTS"
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;;
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esac
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# Find the java binary
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if [ -n "${JAVA_HOME}" ]; then
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RUNNER="${JAVA_HOME}/bin/java"
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else
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if [ `command -v java` ]; then
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RUNNER="java"
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else
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echo "JAVA_HOME is not set" >&2
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exit 1
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fi
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fi
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# Set SPARK_MEM if it isn't already set since we also use it for this process
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SPARK_MEM=${SPARK_MEM:-512m}
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export SPARK_MEM
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# Set JAVA_OPTS to be able to load native libraries and to set heap size
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JAVA_OPTS="$OUR_JAVA_OPTS"
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JAVA_OPTS="$JAVA_OPTS -Djava.library.path=$SPARK_LIBRARY_PATH"
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JAVA_OPTS="$JAVA_OPTS -Xms$SPARK_MEM -Xmx$SPARK_MEM"
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# Load extra JAVA_OPTS from conf/java-opts, if it exists
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if [ -e $FWDIR/conf/java-opts ] ; then
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JAVA_OPTS="$JAVA_OPTS `cat $FWDIR/conf/java-opts`"
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fi
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export JAVA_OPTS
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# Attention: when changing the way the JAVA_OPTS are assembled, the change must be reflected in ExecutorRunner.scala!
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if [ ! -f "$FWDIR/RELEASE" ]; then
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# Exit if the user hasn't compiled Spark
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ls "$FWDIR"/assembly/target/scala-$SCALA_VERSION/spark-assembly*hadoop*.jar >& /dev/null
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if [[ $? != 0 ]]; then
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echo "Failed to find Spark assembly in $FWDIR/assembly/target" >&2
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echo "You need to build Spark with sbt/sbt assembly before running this program" >&2
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exit 1
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fi
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fi
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# Compute classpath using external script
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CLASSPATH=`$FWDIR/bin/compute-classpath.sh`
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export CLASSPATH
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if [ "$SPARK_PRINT_LAUNCH_COMMAND" == "1" ]; then
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echo -n "Spark Command: "
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echo "$RUNNER" -cp "$CLASSPATH" $JAVA_OPTS "$@"
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echo "========================================"
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echo
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fi
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exec "$RUNNER" -cp "$CLASSPATH" $JAVA_OPTS "$@"
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