[jira] [Commented] (SPARK-4633) Support gzip in spark.compression.io.codec

["Adam Roberts (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-4633?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15484488#comment-15484488 ] 

Adam Roberts commented on SPARK-4633:
-------------------------------------

Very interested in this and I know Nasser Ebrahim is also (full disclosure that we both work for IBM).

https://www.rootusers.com/gzip-vs-bzip2-vs-xz-performance-comparison/ shows promising results

Would be interesting to code up a quick prototype (perhaps based on the pull request here) and to see what performance difference we can gain, looks like Takeshi has done the starting work for us

> Support gzip in spark.compression.io.codec
> ------------------------------------------
>
>                 Key: SPARK-4633
>                 URL: https://issues.apache.org/jira/browse/SPARK-4633
>             Project: Spark
>          Issue Type: Improvement
>          Components: Input/Output
>            Reporter: Takeshi Yamamuro
>            Priority: Trivial
>
> gzip is widely used in other frameowrks such as hadoop mapreduce and tez, and also
> I think that gizip is more stable than other codecs in terms of both performance
> and space overheads.
> I have one open question; current spark configuratios have a block size option
> for each codec (spark.io.compression.[gzip|lz4|snappy].block.size).
> As # of codecs increases, the configurations have more options and
> I think that it is sort of complicated for non-expert users.
> To mitigate it, my thought follows;
> the three configurations are replaced with a single option for block size
> (spark.io.compression.block.size). Then, 'Meaning' in configurations
> will describe "This option makes an effect on gzip, lz4, and snappy. 
> Block size (in bytes) used in compression, in the case when these compression
> codecs are used. Lowering...".



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