forked from mesos/spark
-
Notifications
You must be signed in to change notification settings - Fork 0
/
run
executable file
·164 lines (147 loc) · 5.29 KB
/
run
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
#!/bin/bash
SCALA_VERSION=2.9.2
# 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 <spark-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" = "spark.deploy.master.Master" -o "$1" = "spark.deploy.worker.Worker" ]; then
SPARK_MEM=${SPARK_DAEMON_MEMORY:-512m}
SPARK_JAVA_OPTS=$SPARK_DAEMON_JAVA_OPTS # Empty by default
fi
# Add java opts for master, worker, executor. The opts maybe null
case "$1" in
'spark.deploy.master.Master')
SPARK_JAVA_OPTS+=" $SPARK_MASTER_OPTS"
;;
'spark.deploy.worker.Worker')
SPARK_JAVA_OPTS+=" $SPARK_WORKER_OPTS"
;;
'spark.executor.StandaloneExecutorBackend')
SPARK_JAVA_OPTS+=" $SPARK_EXECUTOR_OPTS"
;;
'spark.executor.MesosExecutorBackend')
SPARK_JAVA_OPTS+=" $SPARK_EXECUTOR_OPTS"
;;
'spark.repl.Main')
SPARK_JAVA_OPTS+=" $SPARK_REPL_OPTS"
;;
esac
if [ "$SPARK_LAUNCH_WITH_SCALA" == "1" ]; then
if [ `command -v scala` ]; then
RUNNER="scala"
else
if [ -z "$SCALA_HOME" ]; then
echo "SCALA_HOME is not set" >&2
exit 1
fi
RUNNER="${SCALA_HOME}/bin/scala"
fi
else
if [ `command -v java` ]; then
RUNNER="java"
else
if [ -z "$JAVA_HOME" ]; then
echo "JAVA_HOME is not set" >&2
exit 1
fi
RUNNER="${JAVA_HOME}/bin/java"
fi
if [ -z "$SCALA_LIBRARY_PATH" ]; then
if [ -z "$SCALA_HOME" ]; then
echo "SCALA_HOME is not set" >&2
exit 1
fi
SCALA_LIBRARY_PATH="$SCALA_HOME/lib"
fi
fi
# Figure out how much memory to use per executor and set it as an environment
# variable so that our process sees it and can report it to Mesos
if [ -z "$SPARK_MEM" ] ; then
SPARK_MEM="512m"
fi
export SPARK_MEM
# Set JAVA_OPTS to be able to load native libraries and to set heap size
JAVA_OPTS="$SPARK_JAVA_OPTS"
JAVA_OPTS+=" -Djava.library.path=$SPARK_LIBRARY_PATH"
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+=" `cat $FWDIR/conf/java-opts`"
fi
export JAVA_OPTS
CORE_DIR="$FWDIR/core"
REPL_DIR="$FWDIR/repl"
EXAMPLES_DIR="$FWDIR/examples"
BAGEL_DIR="$FWDIR/bagel"
STREAMING_DIR="$FWDIR/streaming"
PYSPARK_DIR="$FWDIR/python"
# Exit if the user hasn't compiled Spark
if [ ! -e "$REPL_DIR/target" ]; then
echo "Failed to find Spark classes in $REPL_DIR/target" >&2
echo "You need to compile Spark before running this program" >&2
exit 1
fi
# Build up classpath
CLASSPATH="$SPARK_CLASSPATH"
CLASSPATH+=":$FWDIR/conf"
CLASSPATH+=":$CORE_DIR/target/scala-$SCALA_VERSION/classes"
if [ -n "$SPARK_TESTING" ] ; then
CLASSPATH+=":$CORE_DIR/target/scala-$SCALA_VERSION/test-classes"
CLASSPATH+=":$STREAMING_DIR/target/scala-$SCALA_VERSION/test-classes"
fi
CLASSPATH+=":$CORE_DIR/src/main/resources"
CLASSPATH+=":$REPL_DIR/target/scala-$SCALA_VERSION/classes"
CLASSPATH+=":$EXAMPLES_DIR/target/scala-$SCALA_VERSION/classes"
CLASSPATH+=":$STREAMING_DIR/target/scala-$SCALA_VERSION/classes"
CLASSPATH+=":$STREAMING_DIR/lib/org/apache/kafka/kafka/0.7.2-spark/*" # <-- our in-project Kafka Jar
if [ -e "$FWDIR/lib_managed" ]; then
CLASSPATH+=":$FWDIR/lib_managed/jars/*"
CLASSPATH+=":$FWDIR/lib_managed/bundles/*"
fi
CLASSPATH+=":$REPL_DIR/lib/*"
if [ -e repl-bin/target ]; then
for jar in `find "repl-bin/target" -name 'spark-repl-*-shaded-hadoop*.jar'`; do
CLASSPATH+=":$jar"
done
fi
CLASSPATH+=":$BAGEL_DIR/target/scala-$SCALA_VERSION/classes"
for jar in `find $PYSPARK_DIR/lib -name '*jar'`; do
CLASSPATH+=":$jar"
done
export CLASSPATH # Needed for spark-shell
# Figure out the JAR file that our examples were packaged into. This includes a bit of a hack
# to avoid the -sources and -doc packages that are built by publish-local.
if [ -e "$EXAMPLES_DIR/target/scala-$SCALA_VERSION/spark-examples"*[0-9T].jar ]; then
# Use the JAR from the SBT build
export SPARK_EXAMPLES_JAR=`ls "$EXAMPLES_DIR/target/scala-$SCALA_VERSION/spark-examples"*[0-9T].jar`
fi
if [ -e "$EXAMPLES_DIR/target/spark-examples-"*hadoop[12].jar ]; then
# Use the JAR from the Maven build
export SPARK_EXAMPLES_JAR=`ls "$EXAMPLES_DIR/target/spark-examples-"*hadoop[12].jar`
fi
# Figure out whether to run our class with java or with the scala launcher.
# In most cases, we'd prefer to execute our process with java because scala
# creates a shell script as the parent of its Java process, which makes it
# hard to kill the child with stuff like Process.destroy(). However, for
# the Spark shell, the wrapper is necessary to properly reset the terminal
# when we exit, so we allow it to set a variable to launch with scala.
if [ "$SPARK_LAUNCH_WITH_SCALA" == "1" ]; then
EXTRA_ARGS="" # Java options will be passed to scala as JAVA_OPTS
else
CLASSPATH+=":$SCALA_LIBRARY_PATH/scala-library.jar"
CLASSPATH+=":$SCALA_LIBRARY_PATH/scala-compiler.jar"
CLASSPATH+=":$SCALA_LIBRARY_PATH/jline.jar"
# The JVM doesn't read JAVA_OPTS by default so we need to pass it in
EXTRA_ARGS="$JAVA_OPTS"
fi
exec "$RUNNER" -cp "$CLASSPATH" $EXTRA_ARGS "$@"