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https://issues.apache.org/jira/browse/HADOOP-10681?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14029965#comment-14029965
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Gopal V commented on HADOOP-10681:
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Added a SnappyCode impl into hive, which should come before in the classpath
for hive+tez.
Tested out TPC-H Query5, which has a spill-merge on the JOIN.
Query times went from 539.8 seconds to 464.89 seconds, mostly from speedup to a
single reducer stage.
> Remove synchronized blocks from SnappyCodec and ZlibCodec buffering
> -------------------------------------------------------------------
>
> Key: HADOOP-10681
> URL: https://issues.apache.org/jira/browse/HADOOP-10681
> Project: Hadoop Common
> Issue Type: Bug
> Components: performance
> Affects Versions: 2.2.0, 2.4.0, 2.5.0
> Reporter: Gopal V
> Assignee: Gopal V
> Labels: perfomance
> Attachments: compress-cmpxchg-small.png, perf-top-spill-merge.png,
> snappy-perf-unsync.png
>
>
> The current implementation of SnappyCompressor spends more time within the
> java loop of copying from the user buffer into the direct buffer allocated to
> the compressor impl, than the time it takes to compress the buffers.
> !perf-top-spill-merge.png!
> The bottleneck was found to be java monitor code inside SnappyCompressor.
> The methods are neatly inlined by the JIT into the parent caller
> (BlockCompressorStream::write), which unfortunately does not flatten out the
> synchronized blocks.
> !compress-cmpxchg-small.png!
> The loop does a write of small byte[] buffers (each IFile key+value).
> I counted approximately 6 monitor enter/exit blocks per k-v pair written.
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