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Posted to issues@spark.apache.org by "Reynold Xin (JIRA)" <ji...@apache.org> on 2014/07/15 08:14:04 UTC
[jira] [Updated] (SPARK-2469) Lower shuffle compression buffer
memory usage (replace LZF with Snappy for default compression codec)
[ https://issues.apache.org/jira/browse/SPARK-2469?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Reynold Xin updated SPARK-2469:
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Summary: Lower shuffle compression buffer memory usage (replace LZF with Snappy for default compression codec) (was: Lower shuffle compression buffer memory usage)
> Lower shuffle compression buffer memory usage (replace LZF with Snappy for default compression codec)
> -----------------------------------------------------------------------------------------------------
>
> Key: SPARK-2469
> URL: https://issues.apache.org/jira/browse/SPARK-2469
> Project: Spark
> Issue Type: Improvement
> Components: Shuffle, Spark Core
> Reporter: Reynold Xin
>
> I was looking into the memory usage of shuffle and one annoying thing is the default compression codec (LZF) is that the implementation we use allocates buffers pretty generously. I did a simple experiment and found that creating 1000 LZFOutputStream allocated 198976424 bytes (~190MB). If we have a shuffle task that uses 10k reducers and 32 threads running currently, the memory used by the lzf stream alone would be ~ 60GB.
> In comparison, Snappy only allocates ~ 65MB for every 1k SnappyOutputStream. However, Snappy's compression is slightly lower than LZF's. In my experience, it leads to 10 - 20% increase in size. Compression ratio does matter here because we are sending data across the network.
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