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https://issues.apache.org/jira/browse/FLINK-14845?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16977693#comment-16977693
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Stephan Ewen commented on FLINK-14845:
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[~lzljs3620320] Quick question for clarification: In the example you described,
the large table could (should) be connected to the join task by a pipelined
channel that does not spill (in memory, connecting source and join who run
co-located in the same slot).
I guess that should also be possible for the Blink query engine in 1.10 I
guess, with FLIP-53 ?
> Introduce data compression to blocking shuffle.
> -----------------------------------------------
>
> Key: FLINK-14845
> URL: https://issues.apache.org/jira/browse/FLINK-14845
> Project: Flink
> Issue Type: Sub-task
> Components: Runtime / Network
> Reporter: Yingjie Cao
> Priority: Major
>
> Currently, blocking shuffle writer writes raw output data to disk without
> compression. For IO bounded scenario, this can be optimized by compressing
> the output data. It is better to introduce a compression mechanism and offer
> users a config option to let the user decide whether to compress the shuffle
> data. Actually, we hava implemented compression in our inner Flink version
> and here are some key points:
> 1. Where to compress/decompress?
> Compressing at upstream and decompressing at downstream.
> 2. Which thread do compress/decompress?
> Task threads do compress/decompress.
> 3. Data compression granularity.
> Per buffer.
> 4. How to handle that when data size become even bigger after compression?
> Give up compression in this case and introduce an extra flag to identify if
> the data was compressed, that is, the output may be a mixture of compressed
> and uncompressed data.
>
> We'd like to introduce blocking shuffle data compression to Flink if there
> are interests.
>
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