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From "Scott Chen (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAPREDUCE-2212) MapTask and ReduceTask should only compress/decompress the final map output file
Date Wed, 08 Dec 2010 01:55:03 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-2212?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12969137#action_12969137
] 

Scott Chen commented on MAPREDUCE-2212:
---------------------------------------

bq. In our case, the resource is usually CPU or network bounded.

Let me take this back. I don't have number for this one.

I think the intuition is that the latency should be better if we do lzo compression for intermediate
data.
For throughput, it varies. If TT is constantly running with 100% cpu, we should probably trade
cpu with some disk io.

> MapTask and ReduceTask should only compress/decompress the final map output file
> --------------------------------------------------------------------------------
>
>                 Key: MAPREDUCE-2212
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-2212
>             Project: Hadoop Map/Reduce
>          Issue Type: Improvement
>          Components: task
>    Affects Versions: 0.23.0
>            Reporter: Scott Chen
>            Assignee: Scott Chen
>             Fix For: 0.23.0
>
>
> Currently if we set mapred.map.output.compression.codec
> 1. MapTask will compress every spill, decompress every spill, merge and compress the
final map output file
> 2. ReduceTask will decompress, merge and compress every map output file. And repeat the
compression/decompression every pass.
> This causes all the data being compressed/decompressed many times.
> The reason we need mapred.map.output.compression.codec is for network traffic.
> We should not compress/decompress the data again and again during merge sort.
> We should only compress the final map output file that will be transmitted over the network.

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