spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "huangweiyi (Jira)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-30246) Spark on Yarn External Shuffle Service Memory Leak
Date Thu, 19 Dec 2019 07:27:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-30246?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

huangweiyi updated SPARK-30246:
-------------------------------
    Description: 
In our large busy yarn cluster which deploy Spark external shuffle service as part of YARN
NM aux service, we encountered OOM in some NMs.
after i dump the heap memory and found there are some StremState objects still in heap, but
the app which the StreamState belongs to is already finished.

Here is some relate Figures:
!https://raw.githubusercontent.com/012huang/public_source/master/SparkPRFigures/nm_oom.png|width=100%!

The heap dump below shows that the memory consumption mainly consists of two parts:
*(1) OneForOneStreamManager (4,429,796,424 (77.11%) bytes)*
*(2) PoolChunk(occupy 1,059,201,712 (18.44%) bytes. )*

!https://raw.githubusercontent.com/012huang/public_source/master/SparkPRFigures/nm_heap_overview.png|width=100%!

dig into the OneForOneStreamManager, there are some StreaStates still remained :
!https://raw.githubusercontent.com/012huang/public_source/master/SparkPRFigures/streamState.png|width=100%!


!https://raw.githubusercontent.com/012huang/public_source/master/SparkPRFigures/associatedChannel_incomming_reference.png|width=100%!

  was:
In our large busy yarn cluster which deploy Spark external shuffle service as part of YARN
NM aux service, we encountered OOM in some NMs.
after i dump the heap memory and found there are some StremState objects still in heap, but
the app which the StreamState belongs to is already finished.

Here is some relate Figures:
!https://raw.githubusercontent.com/012huang/public_source/master/SparkPRFigures/nm_oom.png|width=100%!

The heap dump below shows that the memory consumption mainly consists of two parts:
*(1) OneForOneStreamManager (4,429,796,424 (77.11%) bytes)*
*(2) PoolChunk(occupy 1,059,201,712 (18.44%) bytes. )*

!https://raw.githubusercontent.com/012huang/public_source/master/SparkPRFigures/nm_heap_overview.png|width=100%!

dig into the OneForOneStreamManager, there are some StreaStates still remained :
!https://raw.githubusercontent.com/012huang/public_source/master/SparkPRFigures/streamState.png|width=100%!




> Spark on Yarn External Shuffle Service Memory Leak
> --------------------------------------------------
>
>                 Key: SPARK-30246
>                 URL: https://issues.apache.org/jira/browse/SPARK-30246
>             Project: Spark
>          Issue Type: Bug
>          Components: Shuffle, Spark Core
>    Affects Versions: 2.4.3
>         Environment: hadoop 2.7.3
> spark 2.4.3
> jdk 1.8.0_60
>            Reporter: huangweiyi
>            Priority: Major
>
> In our large busy yarn cluster which deploy Spark external shuffle service as part of
YARN NM aux service, we encountered OOM in some NMs.
> after i dump the heap memory and found there are some StremState objects still in heap,
but the app which the StreamState belongs to is already finished.
> Here is some relate Figures:
> !https://raw.githubusercontent.com/012huang/public_source/master/SparkPRFigures/nm_oom.png|width=100%!
> The heap dump below shows that the memory consumption mainly consists of two parts:
> *(1) OneForOneStreamManager (4,429,796,424 (77.11%) bytes)*
> *(2) PoolChunk(occupy 1,059,201,712 (18.44%) bytes. )*
> !https://raw.githubusercontent.com/012huang/public_source/master/SparkPRFigures/nm_heap_overview.png|width=100%!
> dig into the OneForOneStreamManager, there are some StreaStates still remained :
> !https://raw.githubusercontent.com/012huang/public_source/master/SparkPRFigures/streamState.png|width=100%!
> !https://raw.githubusercontent.com/012huang/public_source/master/SparkPRFigures/associatedChannel_incomming_reference.png|width=100%!



--
This message was sent by Atlassian Jira
(v8.3.4#803005)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org


Mime
View raw message