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https://issues.apache.org/jira/browse/FLINK-10941?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16718684#comment-16718684
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ASF GitHub Bot commented on FLINK-10941:
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QiLuo-BD commented on issue #7186: [FLINK-10941] Keep slots which contain
unconsumed result partitions
URL: https://github.com/apache/flink/pull/7186#issuecomment-446522886
Hi Zhijiang, I've updated the code according to your comments. Could you
kindly help review this?
Thanks!
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> Slots prematurely released which still contain unconsumed data
> ---------------------------------------------------------------
>
> Key: FLINK-10941
> URL: https://issues.apache.org/jira/browse/FLINK-10941
> Project: Flink
> Issue Type: Bug
> Components: ResourceManager
> Affects Versions: 1.5.5, 1.6.2, 1.7.0
> Reporter: Qi
> Assignee: Qi
> Priority: Critical
> Labels: pull-request-available
> Fix For: 1.8.0
>
>
> Our case is: Flink 1.5 batch mode, 32 parallelism to read data source and 4
> parallelism to write data sink.
>
> The read task worked perfectly with 32 TMs. However when the job was
> executing the write task, since only 4 TMs were needed, other 28 TMs were
> released. This caused RemoteTransportException in the write task:
>
> org.apache.flink.runtime.io.network.netty.exception.RemoteTransportException:
> Connection unexpectedly closed by remote task manager
> ’the_previous_TM_used_by_read_task'. This might indicate that the remote task
> manager was lost.
> at
> org.apache.flink.runtime.io.network.netty.PartitionRequestClientHandler.channelInactive(PartitionRequestClientHandler.java:133)
> at
> org.apache.flink.shaded.netty4.io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:237)
> ...
>
> After skimming YarnFlinkResourceManager related code, it seems to me that
> Flink is releasing TMs when they’re idle, regardless of whether working TMs
> need them.
>
> Put in another way, Flink seems to prematurely release slots which contain
> unconsumed data and, thus, eventually release a TM which then fails a
> consuming task.
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