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https://issues.apache.org/jira/browse/SPARK-25073?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16590396#comment-16590396
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Sujith edited comment on SPARK-25073 at 8/23/18 3:48 PM:
---------------------------------------------------------

 Yes, in the executor memory validation check we are displaying the proper 
message considering both yarn.nodemanager.resource.memory-mb and 
yarn.scheduler.maximum-allocation-mb in org.apache.spark.deploy.yarn.Client 
class as below, where as for AM container memory allocation validation only 
yarn.scheduler.maximum-allocation-mb is mentioned

if (executorMem > maxMem)

{ throw new IllegalArgumentException(s"Required executor memory 
($executorMemory" + s"+$executorMemoryOverhead MB) is above the max threshold 
($maxMem MB) of this cluster! " + "Please check the values of 
'yarn.scheduler.maximum-allocation-mb' and/or " + 
"'yarn.nodemanager.resource.memory-mb and increase the memory appropriately." ) 
}

i think is we can mention about both  yarn.nodemanager.resource.memory-mb and 
yarn.scheduler.maximum-allocation-mb parameters for am memory validation as 
well,even though this issue sounds to be more kind of negative scenario

Please correct me if i am missing something.


was (Author: s71955):
 Yes, in the executor memory validation check we are displaying the proper 
message considering both yarn.nodemanager.resource.memory-mb and 
yarn.scheduler.maximum-allocation-mb in org.apache.spark.deploy.yarn.Client 
class as below, where as for AM container memory allocation validation only 
yarn.scheduler.maximum-allocation-mb is mentioned

if (executorMem > maxMem)

{

throw new IllegalArgumentException(s"Required executor memory ($executorMemory" 
+ s"+$executorMemoryOverhead MB) is above the max threshold ($maxMem MB) of 
this cluster! " + "Please check the values of 
'yarn.scheduler.maximum-allocation-mb' and/or " + 
"'yarn.nodemanager.resource.memory-mb and increase the memory appropriately." )

}

 i think is we can mention about both  yarn.nodemanager.resource.memory-mb and 
yarn.scheduler.maximum-allocation-mb parameters for am memory validation as 
well,

> 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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