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https://issues.apache.org/jira/browse/KAFKA-3769?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15311179#comment-15311179
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Greg Fodor commented on KAFKA-3769:
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Thanks Jay!
Guozhang, what are your thoughts on instead of trying to reduce the granularity
of the metrics, potentially having a way to just disable the process/latency
metrics collection? I'm still pretty new to KStreams, and haven't used these
metrics, but I'm guessing they will be used for occasionally tuning the job
against production data but not necessarily for operational monitoring. (I
could be wrong about this.) As such, it seems that you may want to just have a
switch you flip when you are running in production that will disable the
metrics and maximize the throughput of the job, and then turn it on selectively
when you want to perform performance measurement.
> 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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