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Posted to issues@beam.apache.org by "Beam JIRA Bot (Jira)" <ji...@apache.org> on 2021/07/17 17:21:01 UTC

[jira] [Updated] (BEAM-12351) combine should be parallelizable in many cases

     [ https://issues.apache.org/jira/browse/BEAM-12351?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Beam JIRA Bot updated BEAM-12351:
---------------------------------
    Labels: dataframe-api stale-P2  (was: dataframe-api)

> combine should be parallelizable in many cases
> ----------------------------------------------
>
>                 Key: BEAM-12351
>                 URL: https://issues.apache.org/jira/browse/BEAM-12351
>             Project: Beam
>          Issue Type: Improvement
>          Components: dsl-dataframe, sdk-py-core
>            Reporter: Brian Hulette
>            Priority: P2
>              Labels: dataframe-api, stale-P2
>
> Relevant discussion: https://lists.apache.org/thread.html/r9e7d9527eb1d4c9c097c91c010a25dabf4a5f8053d50dc3b6d90d36a%40%3Cdev.beam.apache.org%3E
> Currently we require Singleton partitioning for combine() because func *might* operate on the full dataset, but in many cases func is actually an elementwise method. We should detect this when possible (e.g. when func is an np.ufunc), and/or provide a flag to let the user indicate the function is elementwise.



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