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From "dhruba borthakur (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HADOOP-885) Reduce CPU usage on namenode: gettimeofday
Date Fri, 02 Feb 2007 17:55:05 GMT

    [ https://issues.apache.org/jira/browse/HADOOP-885?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#action_12469815
] 

dhruba borthakur commented on HADOOP-885:
-----------------------------------------

I included the change to maxIdleTime in that patch because this patch reduces CPU consumption
on the namenode. Regarding epoll(), it appears to me that is could be very platform specific
and currently implemented only on Linux 2.6. If this is true, then I would like to avoid using
it at present. Please let me know if you concur.


> Reduce CPU usage on namenode: gettimeofday
> ------------------------------------------
>
>                 Key: HADOOP-885
>                 URL: https://issues.apache.org/jira/browse/HADOOP-885
>             Project: Hadoop
>          Issue Type: Bug
>          Components: dfs
>    Affects Versions: 0.10.1
>            Reporter: dhruba borthakur
>         Assigned To: dhruba borthakur
>         Attachments: gettime1.patch, WallClock.java
>
>
> On a 900 node idle cluster, the namenode spends about  20% of CPU. Most of this CPU is
spent processing pure heartbeats. No jobs are running on this cluster and all nodes are alive
and acting well.
> Of the total namenode CPU usage, about 12% is in usermode and about 70% is in kernel
mode! The question that natually arises is why is heartbeat processing taking so much time
in kernel mode?
> An strace of namenode reveals that a 20 second period has about 52000 syscalls with the
following breakup:
> gettimeofday  :       18000 calls
> accept             :          2655 calls
> close               :          2655 calls
> shutdown       :          2655 calls
> fcntl                  :          7965 calls
> read                 :          7965 calls
> futex                 :          5295 calls
> poll                   :          4894 calls
> A code inspection reveals that the code is doing multiple (about 5) calls to System.currentTimeMillis()
in processing a single request in the RPC.java and Server.java classes. This might mean that
there is a possibility of optimization.

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