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https://issues.apache.org/jira/browse/SPARK-5005?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14324737#comment-14324737
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Sean Owen commented on SPARK-5005:
----------------------------------
{code}
#!/usr/bin/env bash
# This file is sourced when running various Spark programs.
# Copy it as spark-env.sh and edit that to configure Spark for your site.
# Options read when launching programs locally with
# ./bin/run-example or ./bin/spark-submit
# - HADOOP_CONF_DIR, to point Spark towards Hadoop configuration files
# - SPARK_LOCAL_IP, to set the IP address Spark binds to on this node
# - SPARK_PUBLIC_DNS, to set the public dns name of the driver program
# - SPARK_CLASSPATH, default classpath entries to append
# Options read by executors and drivers running inside the cluster
# - SPARK_LOCAL_IP, to set the IP address Spark binds to on this node
# - SPARK_PUBLIC_DNS, to set the public DNS name of the driver program
# - SPARK_CLASSPATH, default classpath entries to append
# - SPARK_LOCAL_DIRS, storage directories to use on this node for shuffle and
RDD data
# - MESOS_NATIVE_LIBRARY, to point to your libmesos.so if you use Mesos
# Options read in YARN client mode
# - HADOOP_CONF_DIR, to point Spark towards Hadoop configuration files
# - SPARK_EXECUTOR_INSTANCES, Number of workers to start (Default: 2)
# - SPARK_EXECUTOR_CORES, Number of cores for the workers (Default: 1).
# - SPARK_EXECUTOR_MEMORY, Memory per Worker (e.g. 1000M, 2G) (Default: 1G)
# - SPARK_DRIVER_MEMORY, Memory for Master (e.g. 1000M, 2G) (Default: 512 Mb)
# - SPARK_YARN_APP_NAME, The name of your application (Default: Spark)
# - SPARK_YARN_QUEUE, The hadoop queue to use for allocation requests (Default:
‘default’)
# - SPARK_YARN_DIST_FILES, Comma separated list of files to be distributed with
the job.
# - SPARK_YARN_DIST_ARCHIVES, Comma separated list of archives to be
distributed with the job.
# Options for the daemons used in the standalone deploy mode
# - SPARK_MASTER_IP, to bind the master to a different IP address or hostname
# - SPARK_MASTER_PORT / SPARK_MASTER_WEBUI_PORT, to use non-default ports for
the master
# - SPARK_MASTER_OPTS, to set config properties only for the master (e.g.
"-Dx=y")
# - SPARK_WORKER_CORES, to set the number of cores to use on this machine
# - SPARK_WORKER_MEMORY, to set how much total memory workers have to give
executors (e.g. 1000m, 2g)
# - SPARK_WORKER_PORT / SPARK_WORKER_WEBUI_PORT, to use non-default ports for
the worker
# - SPARK_WORKER_INSTANCES, to set the number of worker processes per node
# - SPARK_WORKER_DIR, to set the working directory of worker processes
# - SPARK_WORKER_OPTS, to set config properties only for the worker (e.g.
"-Dx=y")
# - SPARK_HISTORY_OPTS, to set config properties only for the history server
(e.g. "-Dx=y")
# - SPARK_DAEMON_JAVA_OPTS, to set config properties for all daemons (e.g.
"-Dx=y")
# - SPARK_PUBLIC_DNS, to set the public dns name of the master or workers
# Generic options for the daemons used in the standalone deploy mode
# - SPARK_CONF_DIR Alternate conf dir. (Default: ${SPARK_HOME}/conf)
# - SPARK_LOG_DIR Where log files are stored. (Default:
${SPARK_HOME}/logs)
# - SPARK_PID_DIR Where the pid file is stored. (Default: /tmp)
# - SPARK_IDENT_STRING A string representing this instance of spark. (Default:
$USER)
# - SPARK_NICENESS The scheduling priority for daemons. (Default: 0)
###
### === IMPORTANT ===
### Change the following to specify a real cluster's Master host
###
export STANDALONE_SPARK_MASTER_HOST=`hostname`
export SPARK_MASTER_IP=$STANDALONE_SPARK_MASTER_HOST
### Let's run everything with JVM runtime, instead of Scala
export SPARK_LAUNCH_WITH_SCALA=0
export SPARK_LIBRARY_PATH=${SPARK_HOME}/lib
export SCALA_LIBRARY_PATH=${SPARK_HOME}/lib
export SPARK_MASTER_WEBUI_PORT=18080
export SPARK_MASTER_PORT=7077
export SPARK_WORKER_PORT=7078
export SPARK_WORKER_WEBUI_PORT=18081
export SPARK_WORKER_DIR=/var/run/spark/work
export SPARK_LOG_DIR=/var/log/spark
export SPARK_PID_DIR='/var/run/spark/'
if [ -n "$HADOOP_HOME" ]; then
export LD_LIBRARY_PATH=:/lib/native
fi
export HADOOP_CONF_DIR=${HADOOP_CONF_DIR:-etc/hadoop/conf}
### Comment above 2 lines and uncomment the following if
### you want to run with scala version, that is included with the package
#export SCALA_HOME=${SCALA_HOME:-/usr/lib/spark/scala}
#export PATH=$PATH:$SCALA_HOME/bin
{code}
> Failed to start spark-shell when using yarn-client mode with the Spark1.2.0
> ----------------------------------------------------------------------------
>
> Key: SPARK-5005
> URL: https://issues.apache.org/jira/browse/SPARK-5005
> Project: Spark
> Issue Type: Bug
> Components: Spark Core, Spark Shell, YARN
> Affects Versions: 1.2.0
> Environment: Spark 1.2.0
> Hadoop 2.2.0
> Reporter: yangping wu
> Priority: Minor
> Original Estimate: 8h
> Remaining Estimate: 8h
>
> I am using Spark 1.2.0, but when I starting spark-shell with yarn-client
> mode({code}MASTER=yarn-client bin/spark-shell{code}), It Failed and the error
> message is
> {code}
> Unknown/unsupported param List(--executor-memory, 1024m, --executor-cores, 8,
> --num-executors, 2)
> Usage: org.apache.spark.deploy.yarn.ApplicationMaster [options]
> Options:
> --jar JAR_PATH Path to your application's JAR file (required)
> --class CLASS_NAME Name of your application's main class (required)
> --args ARGS Arguments to be passed to your application's main
> class.
> Mutliple invocations are possible, each will be passed
> in order.
> --num-executors NUM Number of executors to start (Default: 2)
> --executor-cores NUM Number of cores for the executors (Default: 1)
> --executor-memory MEM Memory per executor (e.g. 1000M, 2G) (Default: 1G)
> {code}
> But when I using Spark 1.1.0,and also using {code}MASTER=yarn-client
> bin/spark-shell{code} to starting spark-shell,it works.
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