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From "Doug Cutting (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HADOOP-445) Parallel data/socket writing for DFSOutputStream
Date Fri, 11 Aug 2006 20:22:15 GMT
    [ http://issues.apache.org/jira/browse/HADOOP-445?page=comments#action_12427616 ] 
            
Doug Cutting commented on HADOOP-445:
-------------------------------------

It used to work the way you propose.

http://svn.apache.org/viewvc?view=rev&revision=390262

As I recall, the TestFileSystem benchmark was much more reliable after this patch.

You say that this improves serial write performance, but how does it affect overall MapReduce
job performance on a large cluster?

> Parallel data/socket writing for DFSOutputStream
> ------------------------------------------------
>
>                 Key: HADOOP-445
>                 URL: http://issues.apache.org/jira/browse/HADOOP-445
>             Project: Hadoop
>          Issue Type: Improvement
>    Affects Versions: 0.5.0
>            Reporter: Benjamin Reed
>         Attachments: fastClientWrite.patch
>
>
> Currently, as DFS clients output blocks they write the entire block to disk before starting
to transmit to the datanode. By writing to disk the client is able to retry a block write
if the datanode files in the middle of a block transfer. Writing to disk and then to the datanode
adds latency. Hopefully, the common case is that block transfers to datanodes are successful.
This patch writes to the datanode and the disk in parallel. If the write to the datanode fails,
it falls back to current behavior.
> In my tests of transmits of 237M and 946M datasets using -copyFromLocal I'm seeing a
20-25% improvement in throughput.

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