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Posted to jira@arrow.apache.org by "Wes McKinney (Jira)" <ji...@apache.org> on 2020/09/12 20:04:00 UTC
[jira] [Updated] (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 ]
Wes McKinney updated ARROW-9983:
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Summary: [C++][Dataset][Python] Use larger default batch size than 32K for Datasets API (was: [C++][Dataset] Use larger default batch size than 32K for Datasets API)
> [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
> Priority: Major
> 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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