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https://issues.apache.org/jira/browse/SPARK-5005?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14324646#comment-14324646
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Sean Owen commented on SPARK-5005:
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I'm running exactly this on CDH 5.3 (Spark 1.2.0), and it succeeds:
{code}
spark-submit --class org.apache.spark.examples.JavaSparkPi --master yarn-client
--num-executors 2 --executor-cores 1 --executor-memory 1g
/opt/cloudera/parcels/CDH/lib/spark/lib/spark-examples-1.2.0-cdh5.3.0-hadoop2.5.0-cdh5.3.0.jar
3
{code}
I'm inclined to close this since your error shows something fairly strange is
happening. Something is causing you to submit these args directly to the YARN
app master. The Spark code doesn't do that. Did you modify anything? anything
funny in your Spark env variable conf? those are the likely culprits.
> 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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