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Posted to jira@arrow.apache.org by "Ben Kietzman (Jira)" <ji...@apache.org> on 2020/09/28 17:15:00 UTC

[jira] [Resolved] (ARROW-9983) [C++][Dataset][Python] Use larger default batch size than 32K for Datasets API

     [ https://issues.apache.org/jira/browse/ARROW-9983?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Ben Kietzman resolved ARROW-9983.
---------------------------------
      Assignee: Ben Kietzman
    Resolution: Fixed

> [C++][Dataset][Python] Use larger default batch size than 32K for Datasets API
> ------------------------------------------------------------------------------
>
>                 Key: ARROW-9983
>                 URL: https://issues.apache.org/jira/browse/ARROW-9983
>             Project: Apache Arrow
>          Issue Type: Improvement
>          Components: C++
>            Reporter: Wes McKinney
>            Assignee: Ben Kietzman
>            Priority: Major
>              Labels: dataset
>             Fix For: 2.0.0
>
>
> Dremio uses 64K batch sizes. We could probably get away with even larger batch sizes (e.g. 256K or 1M) and allow memory-constrained users to elect a smaller batch size. 
> See example of some performance issues related to this in ARROW-9924



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