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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:
-------------------------------

    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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