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Posted to commits@beam.apache.org by "Robert Bradshaw (JIRA)" <ji...@apache.org> on 2018/04/04 22:35:00 UTC
[jira] [Commented] (BEAM-3737) Key-aware batching function
[ https://issues.apache.org/jira/browse/BEAM-3737?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16426269#comment-16426269 ]
Robert Bradshaw commented on BEAM-3737:
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It seems that GroupByKey() would already give you values batched per key, right? Or are you looking for something you can place before the GBK that enables combiner lifting?
> Key-aware batching function
> ---------------------------
>
> Key: BEAM-3737
> URL: https://issues.apache.org/jira/browse/BEAM-3737
> Project: Beam
> Issue Type: New Feature
> Components: sdk-py-core
> Reporter: Chuan Yu Foo
> Priority: Major
>
> I have a CombineFn for which add_input has very large overhead. I would like to batch the incoming elements into a large batch before each call to add_input to reduce this overhead. In other words, I would like to do something like:
> {{elements | GroupByKey() | BatchElements() | CombineValues(MyCombineFn())}}
> Unfortunately, BatchElements is not key-aware, and can't be used after a GroupByKey to batch elements per key. I'm working around this by doing the batching within CombineValues, which makes the CombineFn rather messy. It would be nice if there were a key-aware BatchElements transform which could be used in this context.
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