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https://issues.apache.org/jira/browse/FLINK-16645?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17071055#comment-17071055
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Jiayi Liao edited comment on FLINK-16645 at 3/30/20, 3:09 PM:
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[~pnowojski]
One thing I'm not very sure is the counter usage in
#ResultPartition#getAvailableFuture. The counter(no volatile decorator) will be
accessed concurrently but I think it should be fine, because
#availabilityHelper will help do the second check even if the counter has no
concurrency gurantee.
Anyway, I've submitted a PR, could you spare time to take a look?
was (Author: wind_ljy):
[~pnowojski]
One thing I'm not very sure is the counter usage in
#ResultPartition#getAvailableFuture. The counter(no volatile decorator) will be
accessed concurrently but I think it should fine, because #availabilityHelper
will help do the second check even if the counter has no concurrency gurantee.
Anyway, I've submitted a PR, could you spare time to take a look?
> Limit the maximum backlogs in subpartitions for data skew case
> --------------------------------------------------------------
>
> Key: FLINK-16645
> URL: https://issues.apache.org/jira/browse/FLINK-16645
> Project: Flink
> Issue Type: Sub-task
> Components: Runtime / Network
> Reporter: Zhijiang
> Assignee: Jiayi Liao
> Priority: Major
> Labels: pull-request-available
> Fix For: 1.11.0
>
> Time Spent: 10m
> Remaining Estimate: 0h
>
> In the case of data skew, most of the buffers in partition's LocalBufferPool
> are probably requested away and accumulated in certain subpartition, which
> would increase in-flight data to slow down the barrier alignment.
> We can set up a proper config to control how many backlogs are allowed for
> one subpartition. If one subpartition reaches this threshold, it will make
> the buffer pool unavailable which blocks task processing continuously. Then
> we can reduce the in-flight data for speeding up checkpoint process a bit and
> not impact on the performance.
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