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https://issues.apache.org/jira/browse/KAFKA-3769?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15325148#comment-15325148
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ASF GitHub Bot commented on KAFKA-3769:
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GitHub user guozhangwang opened a pull request:
https://github.com/apache/kafka/pull/1490
KAFKA-3769: Optimize metrics recording overhead
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/guozhangwang/kafka K3769-optimize-metrics
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/kafka/pull/1490.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #1490
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commit 68c889e1cba59280e4c1a37007efcdec6c784878
Author: Guozhang Wang <wangg...@gmail.com>
Date: 2016-06-10T17:50:29Z
reduce time.milliseconds
commit ad5403c919fe6ee9e5c5e7e3d9c9f2534a5a3717
Author: Guozhang Wang <wangg...@gmail.com>
Date: 2016-06-10T19:38:05Z
use milliseconds instead of nanoseconds for state store metrics
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> KStream job spending 60% of time writing metrics
> ------------------------------------------------
>
> Key: KAFKA-3769
> URL: https://issues.apache.org/jira/browse/KAFKA-3769
> Project: Kafka
> Issue Type: Bug
> Components: streams
> Affects Versions: 0.10.0.0
> Reporter: Greg Fodor
> Assignee: Guozhang Wang
> Priority: Critical
>
> I've been profiling a complex streams job, and found two major hotspots when
> writing metrics, which take up about 60% of the CPU time of the job. (!) A PR
> is attached.
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