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https://issues.apache.org/jira/browse/ARROW-300?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15963751#comment-15963751
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Kazuaki Ishizaki commented on ARROW-300:
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Current Apache Spark supports [the following compression
schemes|https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/compression/CompressionScheme.scala#L66]
for in-memory columnar storage. Currently, compressed in-memory columnar
storage is used when DataFrame.cache or Dataset.cache method is executed.
Would it be possible to support these schemes in addition to
LZ4/(current)DictonaryEncoding?
* RunLengthEncoding: Generic run-length encoding (e.g. 1,1,1,2,2,2,2 -> [3, 1],
[4, 2])
* IntDelta: Represent a sequence using a base value with byte deltas from
previous one. (e.g. 1,3,5,7,10 -> [1, 2, 2, 2, 3])
* LongDelta: Represent a sequence using a base value with byte deltas from
previous one. (e.g. 1,3,5,7,10 -> [1, 2, 2, 2, 3])
> [Format] Add buffer compression option to IPC file format
> ---------------------------------------------------------
>
> Key: ARROW-300
> URL: https://issues.apache.org/jira/browse/ARROW-300
> Project: Apache Arrow
> Issue Type: New Feature
> Components: Format
> Reporter: Wes McKinney
>
> It may be useful if data is to be sent over the wire to compress the data
> buffers themselves as their being written in the file layout.
> I would propose that we keep this extremely simple with a global buffer
> compression setting in the file Footer. Probably only two compressors worth
> supporting out of the box would be zlib (higher compression ratios) and lz4
> (better performance).
> What does everyone think?
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