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Posted to issues@spark.apache.org by "Sujith (JIRA)" <ji...@apache.org> on 2018/08/23 11:29:00 UTC

[jira] [Comment Edited] (SPARK-25073) Spark-submit on Yarn Task : When the yarn.nodemanager.resource.memory-mb and/or yarn.scheduler.maximum-allocation-mb is insufficient, Spark always reports an error request to adjust yarn.scheduler.maximum-allocation-mb

    [ https://issues.apache.org/jira/browse/SPARK-25073?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16590089#comment-16590089 ] 

Sujith edited comment on SPARK-25073 at 8/23/18 11:28 AM:
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cc [~hyukjin.kwon] [gatorsmile|https://github.com/gatorsmile] [~srowen] 


was (Author: s71955):
@ [~hyukjin.kwon] [@gatorsmile|https://github.com/gatorsmile]

> Spark-submit on Yarn Task : When the yarn.nodemanager.resource.memory-mb and/or yarn.scheduler.maximum-allocation-mb is insufficient, Spark always reports an error request to adjust yarn.scheduler.maximum-allocation-mb
> --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-25073
>                 URL: https://issues.apache.org/jira/browse/SPARK-25073
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Submit
>    Affects Versions: 2.3.0, 2.3.1
>            Reporter: vivek kumar
>            Priority: Minor
>
> When the yarn.nodemanager.resource.memory-mb and/or yarn.scheduler.maximum-allocation-mb is insufficient, Spark *always* reports an error request to adjust Yarn.scheduler.maximum-allocation-mb. Expecting the error request to be  more around yarn.scheduler.maximum-allocation-mb' and/or 'yarn.nodemanager.resource.memory-mb'.
>  
> Scenario 1. yarn.scheduler.maximum-allocation-mb =4g and yarn.nodemanager.resource.memory-mb =8G
>  # Launch shell on Yarn with am.memory less than nodemanager.resource memory but greater than yarn.scheduler.maximum-allocation-mb
> eg; spark-shell --master yarn --conf spark.yarn.am.memory 5g
>  Error: java.lang.IllegalArgumentException: Required AM memory (5120+512 MB) is above the max threshold (4096 MB) of this cluster! Please increase the value of 'yarn.scheduler.maximum-allocation-mb'.
> at org.apache.spark.deploy.yarn.Client.verifyClusterResources(Client.scala:325)
>  
> *Scenario 2*. yarn.scheduler.maximum-allocation-mb =15g and yarn.nodemanager.resource.memory-mb =8g
> a. Launch shell on Yarn with am.memory greater than nodemanager.resource memory but less than yarn.scheduler.maximum-allocation-mb
> eg; *spark-shell --master yarn --conf spark.yarn.am.memory=10g*
>  Error :
> java.lang.IllegalArgumentException: Required AM memory (10240+1024 MB) is above the max threshold (*8096 MB*) of this cluster! *Please increase the value of 'yarn.scheduler.maximum-allocation-mb'.*
> at org.apache.spark.deploy.yarn.Client.verifyClusterResources(Client.scala:325)
>  
> b. Launch shell on Yarn with am.memory greater than nodemanager.resource memory and yarn.scheduler.maximum-allocation-mb
> eg; *spark-shell --master yarn --conf spark.yarn.am.memory=17g*
>  Error:
> java.lang.IllegalArgumentException: Required AM memory (17408+1740 MB) is above the max threshold (*8096 MB*) of this cluster! *Please increase the value of 'yarn.scheduler.maximum-allocation-mb'.*
> at org.apache.spark.deploy.yarn.Client.verifyClusterResources(Client.scala:325)
>  
> *Expected* : Error request for scenario2 should be more around yarn.scheduler.maximum-allocation-mb' and/or 'yarn.nodemanager.resource.memory-mb'.



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