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https://issues.apache.org/jira/browse/HADOOP-15124?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16524425#comment-16524425
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Igor Dvorzhak edited comment on HADOOP-15124 at 6/27/18 1:21 AM:
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If I will have a time I will test your patch to compare performance, but from 
looking at it, seems that AtomicLong-based implementation should be faster 
because it's lock-free.

The main performance bottle-neck in my patch right now is access to 
ThreadLocal, but looks like nothing could be done about it.


was (Author: medb):
If I will have a time I will test your patch to compare performance, but from 
looking at it, looks like AtomicLong-based implementation should be faster 
because it's lock-free.

The main performance bottle-neck in my patch right now is access to 
ThreadLocal, but looks like nothing could be done about it.

> 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, 3.1.0
>            Reporter: Igor Dvorzhak
>            Assignee: Igor Dvorzhak
>            Priority: Major
>              Labels: common, filesystem, fs, statistics
>         Attachments: HADOOP-15124.001.patch
>
>
> 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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