path: root/bin/compute-classpath.sh

#!/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.
#

# This script computes Spark's classpath and prints it to stdout; it's used by both the "run"
# script and the ExecutorRunner in standalone cluster mode.

SCALA_VERSION=2.10

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

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

# Build up classpath
CLASSPATH="$SPARK_CLASSPATH:$SPARK_SUBMIT_CLASSPATH:$FWDIR/conf"

ASSEMBLY_DIR="$FWDIR/assembly/target/scala-$SCALA_VERSION"

if [ -n "$JAVA_HOME" ]; then
  JAR_CMD="$JAVA_HOME/bin/jar"
else
  JAR_CMD="jar"
fi

# First check if we have a dependencies jar. If so, include binary classes with the deps jar
if [ -f "$ASSEMBLY_DIR"/spark-assembly*hadoop*-deps.jar ]; then
  CLASSPATH="$CLASSPATH:$FWDIR/core/target/scala-$SCALA_VERSION/classes"
  CLASSPATH="$CLASSPATH:$FWDIR/repl/target/scala-$SCALA_VERSION/classes"
  CLASSPATH="$CLASSPATH:$FWDIR/mllib/target/scala-$SCALA_VERSION/classes"
  CLASSPATH="$CLASSPATH:$FWDIR/bagel/target/scala-$SCALA_VERSION/classes"
  CLASSPATH="$CLASSPATH:$FWDIR/graphx/target/scala-$SCALA_VERSION/classes"
  CLASSPATH="$CLASSPATH:$FWDIR/streaming/target/scala-$SCALA_VERSION/classes"
  CLASSPATH="$CLASSPATH:$FWDIR/tools/target/scala-$SCALA_VERSION/classes"
  CLASSPATH="$CLASSPATH:$FWDIR/sql/catalyst/target/scala-$SCALA_VERSION/classes"
  CLASSPATH="$CLASSPATH:$FWDIR/sql/core/target/scala-$SCALA_VERSION/classes"
  CLASSPATH="$CLASSPATH:$FWDIR/sql/hive/target/scala-$SCALA_VERSION/classes"
  CLASSPATH="$CLASSPATH:$FWDIR/yarn/stable/target/scala-$SCALA_VERSION/classes"

  ASSEMBLY_JAR=$(ls "$ASSEMBLY_DIR"/spark-assembly*hadoop*-deps.jar 2>/dev/null)
else
  # Else use spark-assembly jar from either RELEASE or assembly directory
  if [ -f "$FWDIR/RELEASE" ]; then
    ASSEMBLY_JAR=$(ls "$FWDIR"/lib/spark-assembly*hadoop*.jar 2>/dev/null)
  else
    ASSEMBLY_JAR=$(ls "$ASSEMBLY_DIR"/spark-assembly*hadoop*.jar 2>/dev/null)
  fi
fi

# Verify that versions of java used to build the jars and run Spark are compatible
jar_error_check=$("$JAR_CMD" -tf "$ASSEMBLY_JAR" nonexistent/class/path 2>&1)
if [[ "$jar_error_check" =~ "invalid CEN header" ]]; then
  echo "Loading Spark jar with '$JAR_CMD' failed. "
  echo "This is likely because Spark was compiled with Java 7 and run "
  echo "with Java 6. (see SPARK-1703). Please use Java 7 to run Spark "
  echo "or build Spark with Java 6."
  exit 1
fi

CLASSPATH="$CLASSPATH:$ASSEMBLY_JAR"

# When Hive support is needed, Datanucleus jars must be included on the classpath.
# Datanucleus jars do not work if only included in the uber jar as plugin.xml metadata is lost.
# Both sbt and maven will populate "lib_managed/jars/" with the datanucleus jars when Spark is
# built with Hive, so first check if the datanucleus jars exist, and then ensure the current Spark
# assembly is built for Hive, before actually populating the CLASSPATH with the jars.
# Note that this check order is faster (by up to half a second) in the case where Hive is not used.
if [ -f "$FWDIR/RELEASE" ]; then
  datanucleus_dir="$FWDIR"/lib
else
  datanucleus_dir="$FWDIR"/lib_managed/jars
fi

datanucleus_jars=$(find "$datanucleus_dir" 2>/dev/null | grep "datanucleus-.*\\.jar")
datanucleus_jars=$(echo "$datanucleus_jars" | tr "\n" : | sed s/:$//g)

if [ -n "$datanucleus_jars" ]; then
  hive_files=$("$JAR_CMD" -tf "$ASSEMBLY_JAR" org/apache/hadoop/hive/ql/exec 2>/dev/null)
  if [ -n "$hive_files" ]; then
    echo "Spark assembly has been built with Hive, including Datanucleus jars on classpath" 1>&2
    CLASSPATH="$CLASSPATH:$datanucleus_jars"
  fi
fi

# Add test classes if we're running from SBT or Maven with SPARK_TESTING set to 1
if [[ $SPARK_TESTING == 1 ]]; then
  CLASSPATH="$CLASSPATH:$FWDIR/core/target/scala-$SCALA_VERSION/test-classes"
  CLASSPATH="$CLASSPATH:$FWDIR/repl/target/scala-$SCALA_VERSION/test-classes"
  CLASSPATH="$CLASSPATH:$FWDIR/mllib/target/scala-$SCALA_VERSION/test-classes"
  CLASSPATH="$CLASSPATH:$FWDIR/bagel/target/scala-$SCALA_VERSION/test-classes"
  CLASSPATH="$CLASSPATH:$FWDIR/graphx/target/scala-$SCALA_VERSION/test-classes"
  CLASSPATH="$CLASSPATH:$FWDIR/streaming/target/scala-$SCALA_VERSION/test-classes"
  CLASSPATH="$CLASSPATH:$FWDIR/sql/catalyst/target/scala-$SCALA_VERSION/test-classes"
  CLASSPATH="$CLASSPATH:$FWDIR/sql/core/target/scala-$SCALA_VERSION/test-classes"
  CLASSPATH="$CLASSPATH:$FWDIR/sql/hive/target/scala-$SCALA_VERSION/test-classes"
fi

# Add hadoop conf dir if given -- otherwise FileSystem.*, etc fail !
# Note, this assumes that there is either a HADOOP_CONF_DIR or YARN_CONF_DIR which hosts
# the configurtion files.
if [ -n "$HADOOP_CONF_DIR" ]; then
  CLASSPATH="$CLASSPATH:$HADOOP_CONF_DIR"
fi
if [ -n "$YARN_CONF_DIR" ]; then
  CLASSPATH="$CLASSPATH:$YARN_CONF_DIR"
fi

echo "$CLASSPATH"