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https://issues.apache.org/jira/browse/YARN-5964?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15730808#comment-15730808
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zhengchenyu commented on YARN-5964:
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When I found this problem, the continuous scheduling turned off. In our
cluster, we added more jobs, then leads to lock contention.
Notes: continuous scheduling turned on later in our cluster, because the speed
of assigned container is too slow. But this cofiguration didn't lead to obvious
lock contention. Whatever, I support your opinion that continuous scheduling
could lead to lock contention, if continuous scheduling is too frequent.
> Lower the granularity of locks in FairScheduler
> -----------------------------------------------
>
> Key: YARN-5964
> URL: https://issues.apache.org/jira/browse/YARN-5964
> Project: Hadoop YARN
> Issue Type: Improvement
> Components: fairscheduler
> Affects Versions: 2.7.1
> Environment: CentOS-7.1
> Reporter: zhengchenyu
> Priority: Critical
> Fix For: 2.7.1
>
> Original Estimate: 2m
> Remaining Estimate: 2m
>
> When too many applications are running, we found that client couldn't submit
> the application, and a high callqueuelength of port 8032. I catch the jstack
> of resourcemanager when callqueuelength is too high. I found that the thread
> "IPC Server handler xxx on 8032" are waitting for the object lock of
> FairScheduler, nodeupdate holds the lock of the FairScheduler. Maybe high
> process time leads to the phenomenon that client can't submit the
> application.
> Here I don't consider the problem that client can't submit the application,
> only estimates the performance of the fairscheduler. We can see too many
> function which needs object lock are used, the granularity of object lock is
> too big. For example, nodeUpdate and getAppWeight wanna hold the same object
> lock. It is unresonable and inefficiency. I recommand that the low
> granularity lock replaces the current lock.
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