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Posted to issues@spark.apache.org by "Anton Ippolitov (Jira)" <ji...@apache.org> on 2019/10/25 15:29:00 UTC
[jira] [Updated] (SPARK-28743) YarnShuffleService leads to
NodeManager OOM because ChannelOutboundBuffer has too many entries
[ https://issues.apache.org/jira/browse/SPARK-28743?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Anton Ippolitov updated SPARK-28743:
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Attachment: Screen Shot 2019-10-25 at 17.24.10.png
> YarnShuffleService leads to NodeManager OOM because ChannelOutboundBuffer has too many entries
> ----------------------------------------------------------------------------------------------
>
> Key: SPARK-28743
> URL: https://issues.apache.org/jira/browse/SPARK-28743
> Project: Spark
> Issue Type: Bug
> Components: Shuffle
> Affects Versions: 2.3.0
> Reporter: Jiandan Yang
> Priority: Major
> Attachments: Screen Shot 2019-10-25 at 17.24.10.png, dominator.jpg, histo.jpg
>
>
> NodeManager heap size is 4G, io.netty.channel.ChannelOutboundBuffer$Entry occupied about 2.8G by looking at Histogram of Mat, and those Entries were hold by ChannelOutboundBuffer by looking at dominator_tree of mat. By analyzing one fo ChannelOutboundBuffer object, I found there were 248867 entries in the object of ChannelOutboundBuffer (ChannelOutboundBuffer#flushed=248867), and ChannelOutboundBuffer#totalPengdingSize=23891232 which is more than highwaterMark(64K), and unwritable=1 meaning sending buffer was full. But ChannelHandler seems not check unwritable flag when write message, and finally NodeManager occurs OOM.
> Histogram:
> !histo.jpg!
> dominator_tree:
> !dominator.jpg!
>
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