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From "Steve Loughran (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HADOOP-15124) Slow FileSystem.Statistics counters implementation
Date Thu, 21 Dec 2017 11:19:00 GMT

    [ https://issues.apache.org/jira/browse/HADOOP-15124?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16299879#comment-16299879

Steve Loughran commented on HADOOP-15124:

Making per-thread stats optional would seem a good idea. For multitenant programs per-thread
numbers are good, you can say "this query read X bytes, wrote Y bytes and experienced Z throttle
events from your storage infra". For single tenant programs, you just want to keep an eye
on the aggregate values. But it is more than just troubleshooting, it's assessing the work
performed across a cluster, if aggregated properly.

Don't want to do special hadoop threads as then you can't do the stat collection in downstream
apps which have their own thread pools. (spark, flink)

> Slow FileSystem.Statistics counters implementation
> --------------------------------------------------
>                 Key: HADOOP-15124
>                 URL: https://issues.apache.org/jira/browse/HADOOP-15124
>             Project: Hadoop Common
>          Issue Type: Sub-task
>          Components: common
>    Affects Versions: 2.9.0, 2.8.3, 2.7.5, 3.0.0
>            Reporter: Igor Dvorzhak
>            Assignee: Igor Dvorzhak
>              Labels: common, filesystem, statistics
> While profiling 1TB TeraGen job on Hadoop 2.8.2 cluster (Google Dataproc, 2 workers,
GCS connector) I saw that FileSystem.Statistics code paths Wall time is 5.58% and CPU time
is 26.5% of total execution time.
> After switching FileSystem.Statistics implementation to LongAdder, consumed Wall time
decreased to 0.006% and CPU time to 0.104% of total execution time.
> Total job runtime decreased from 66 mins to 61 mins.
> These results are not conclusive, because I didn't benchmark multiple times to average
results, but regardless of performance gains switching to LongAdder simplifies code and reduces
its complexity.

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