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https://issues.apache.org/jira/browse/FLINK-15981?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17036237#comment-17036237
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Stephan Ewen commented on FLINK-15981:
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Thank you for the ideas!
I think we can pretty much rule it out to keep the buffer pool around as long
as the partition (longer than the task), because it would make it unpredictable
whether a TM or a slot can take new tasks. When a task is released, it cannot
occupy any pooled resources any more.
Considering the buffers per Netty thread: The Netty threads are not blocked
when the socket is not writable, the thread would go to the next writable
socket. So we would need buffers per TCP channel. That is often fewer than per
subpartition (because if multiplexing) but not always (one slot TMs).
> Control the direct memory in FileChannelBoundedData.FileBufferReader
> --------------------------------------------------------------------
>
> Key: FLINK-15981
> URL: https://issues.apache.org/jira/browse/FLINK-15981
> Project: Flink
> Issue Type: Improvement
> Components: Runtime / Network
> Affects Versions: 1.10.0
> Reporter: Jingsong Lee
> Priority: Critical
> Fix For: 1.10.1, 1.11.0
>
>
> Now, the default blocking BoundedData is FileChannelBoundedData. In its
> reader, will create new direct buffer 64KB.
> When parallelism greater than 100, users need configure
> "taskmanager.memory.task.off-heap.size" to avoid direct memory OOM. It is
> hard to configure, and it cost a lot of memory. Consider 1000 parallelism,
> maybe we need 1GB+ for a task manager.
> This is not conducive to the scenario of less slots and large parallelism.
> Batch jobs could run little by little, but memory shortage would consume a
> lot.
> If we provided N-Input operators, maybe things will be worse. This means the
> number of subpartitions that can be requested at the same time will be more.
> We have no idea how much memory.
> Here are my rough thoughts:
> * Obtain memory from network buffers.
> * provide "The maximum number of subpartitions that can be requested at the
> same time".
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