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https://issues.apache.org/jira/browse/BEAM-3737?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16387286#comment-16387286
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Kenneth Knowles commented on BEAM-3737:
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Actually I may have misinterpreted this, but I think [~robertwb] has context
for this. Unassigning for now.
> 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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