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Posted to issues@spark.apache.org by "Steve Loughran (JIRA)" <ji...@apache.org> on 2015/05/07 22:44:00 UTC

[jira] [Updated] (SPARK-5034) Spark on Yarn launch failure on HDInsight on Windows

     [ https://issues.apache.org/jira/browse/SPARK-5034?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Steve Loughran updated SPARK-5034:
----------------------------------
    Summary: Spark on Yarn launch failure on HDInsight on Windows  (was: Spark on Yarn within HDInsight on Windows)

> Spark on Yarn launch failure on HDInsight on Windows
> ----------------------------------------------------
>
>                 Key: SPARK-5034
>                 URL: https://issues.apache.org/jira/browse/SPARK-5034
>             Project: Spark
>          Issue Type: Bug
>          Components: Windows, YARN
>    Affects Versions: 1.1.0, 1.1.1, 1.2.0
>         Environment: Spark on Yarn within HDInsight on Windows Azure
>            Reporter: Rice
>
> Windows Environment
> I'm trying to run JavaSparkPi example on YARN with master = yarn-client but I have a problem. 
> It runs smoothly with submitting application, first container for Application Master works too. 
> When job is starting and there are some tasks to do I'm getting this warning on console (I'm using windows cmd if this makes any difference): 
> WARN cluster.YarnClientClusterScheduler: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient memory 
> When I'm checking logs for container with Application Masters it is launching containers for executors "properly", then goes with: 
> INFO YarnAllocationHandler: Completed container container_1409217202587_0003_01_000002 (state: COMPLETE, exit status: 1) 
> INFO YarnAllocationHandler: Container marked as failed: container_1409217202587_0003_01_000002 
> And tries to re-launch them. 
> On failed container log there is only this: 
> Error: Could not find or load main class PWD..spark@GBV06758291.my.secret.address.net:63680.user.CoarseGrainedScheduler 



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