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From "Brian Bockelman (JIRA)" <j...@apache.org>
Subject [jira] Updated: (HDFS-425) Major performance drop on slower machines
Date Wed, 23 Feb 2011 00:55:38 GMT

     [ https://issues.apache.org/jira/browse/HDFS-425?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel

Brian Bockelman updated HDFS-425:

      Priority: Minor  (was: Major)
    Issue Type: Improvement  (was: Bug)

Marking this as an improvement, not a bug.

> Major performance drop on slower machines
> -----------------------------------------
>                 Key: HDFS-425
>                 URL: https://issues.apache.org/jira/browse/HDFS-425
>             Project: Hadoop HDFS
>          Issue Type: Improvement
>          Components: contrib/fuse-dfs
>            Reporter: Marc-Olivier Fleury
>            Priority: Minor
> When running fuse_dfs on machines that have different CPU characteristics, I noticed
that the performance of fuse_dfs is very sensitive to the machine power. 
> The command I used was simply a cat over a rather large amount of data stored on HDFS.
Here are the comparative times for the different types of machines:
> Intel(R) Pentium(R) 4 CPU 2.40GHz :                                2 min 40 s 
> Intel(R) Pentium(R) 4 CPU 3.06GHz:                                 1 min 50 s 
> 2 x Intel(R) Pentium(R) 4 CPU 3.00GHz:                           0 min 40 s 
> 2 x Intel(R) Xeon(TM) MP CPU 3.33GHz:                           0 min 28 s 
> Intel(R) Core(TM)2 Quad CPU    Q6600  @ 2.40GHz      0 min 15 s
> I tried to find other explanations for the drop in performance, such as network configuration,
or data locality, but the faster machines are the ones that are "further away" from the others
considering the network configuration, and that don't run datanodes.
> top shows that the CPU usage of fuse_dfs is between 80-90% on the slower machines, and
about 40% on the fastest one.
> This leads me to the conclusion that fuse_dfs consumes a lot of CPU resources, much more
than expected.
> Any help or insight concerning this issue will be greatly appreciated, since these difference
actually result in days of computations for a given job.
> Thank you

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