[
https://issues.apache.org/jira/browse/SPARK-25073?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
vivek kumar updated SPARK-25073:
--------------------------------
Description:
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'.
was:
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'.
> 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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