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https://issues.apache.org/jira/browse/BEAM-68?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15896589#comment-15896589
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Xu Mingmin commented on BEAM-68:
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Notice this task when tuning a Beam job on Flink.
Would like to bring another perspective, that users want to have more control
on the parallelism of a data pipeline, to allocate more resource for the busy
steps, and less for the costless. A fixed parallelism could have performance
bottleneck, several use cases like:
1. source from a Kafka topic, the parallelism could not be larger then topic
partition number; similar for other splittable IOs?
2. fewer grouped keys than parallelism;
3. process on a small portion from large input;
4. +1 for case2, to address quota limitation on external dependencies;
> Support for limiting parallelism of a step
> ------------------------------------------
>
> Key: BEAM-68
> URL: https://issues.apache.org/jira/browse/BEAM-68
> Project: Beam
> Issue Type: New Feature
> Components: beam-model
> Reporter: Daniel Halperin
>
> Users may want to limit the parallelism of a step. Two classic uses cases are:
> - User wants to produce at most k files, so sets
> TextIO.Write.withNumShards(k).
> - External API only supports k QPS, so user sets a limit of k/(expected
> QPS/step) on the ParDo that makes the API call.
> Unfortunately, there is no way to do this effectively within the Beam model.
> A GroupByKey with exactly k keys will guarantee that only k elements are
> produced, but runners are free to break fusion in ways that each element may
> be processed in parallel later.
> To implement this functionaltiy, I believe we need to add this support to the
> Beam Model.
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