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https://issues.apache.org/jira/browse/HADOOP-18389?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18035712#comment-18035712
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ASF GitHub Bot commented on HADOOP-18389:
-----------------------------------------

github-actions[bot] commented on PR #4691:
URL: https://github.com/apache/hadoop/pull/4691#issuecomment-3494234029

   We're closing this stale PR because it has been open for 100 days with no 
activity. This isn't a judgement on the merit of the PR in any way. It's just a 
way of keeping the PR queue manageable.
   If you feel like this was a mistake, or you would like to continue working 
on it, please feel free to re-open it and ask for a committer to remove the 
stale tag and review again.
   Thanks all for your contribution.




> Limit stacked call of one connection in client to avoid possible oom in server
> ------------------------------------------------------------------------------
>
>                 Key: HADOOP-18389
>                 URL: https://issues.apache.org/jira/browse/HADOOP-18389
>             Project: Hadoop Common
>          Issue Type: Bug
>            Reporter: ZanderXu
>            Assignee: ZanderXu
>            Priority: Major
>              Labels: pull-request-available
>         Attachments: image-2022-08-04-00-22-28-865.png, 
> image-2022-08-04-00-23-18-427.png
>
>          Time Spent: 0.5h
>  Remaining Estimate: 0h
>
> In our prod environment, we encountered an accident that JN OOM because 
> Server#Connection#responseQueue used 97% memory.
> After analyzed the memory of JN and found that there are 2w+ called stacked 
> in one Server#Connection#responseQueue, because the network between NN and JN 
> jitters with some tcp packet loss.
> !image-2022-08-04-00-22-28-865.png|width=561,height=254!
> !image-2022-08-04-00-23-18-427.png|width=559,height=356!
>  
> In this case, I think Client.java should support limit the stacked calls of 
> one connection to avoid the possible OOM in Server.  When the number of 
> stacked calls is more than the limit size, we can just throw one IOException 
> to the method caller.



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