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Posted to jira@arrow.apache.org by "Antoine Pitrou (Jira)" <ji...@apache.org> on 2022/10/03 14:17:00 UTC

[jira] [Commented] (ARROW-12787) [Python] pyarrow.compute not consistent on memory_pool usage

    [ https://issues.apache.org/jira/browse/ARROW-12787?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17612312#comment-17612312 ] 

Antoine Pitrou commented on ARROW-12787:
----------------------------------------

I'm not sure this issue still applies. [~milesgranger] Do you want to take a look and see if there's anything left to do here?

> [Python] pyarrow.compute not consistent on memory_pool usage
> ------------------------------------------------------------
>
>                 Key: ARROW-12787
>                 URL: https://issues.apache.org/jira/browse/ARROW-12787
>             Project: Apache Arrow
>          Issue Type: Improvement
>          Components: Python
>            Reporter: Weston Pace
>            Priority: Major
>
> Generally it seems that pyarrow is pretty consistent about offering an optional memory_pool parameter if a function might allocate.  However, some of the compute work is a little inconsistent...
> pa.Array.unique does not accept a memory_pool
> pa.Array.cast does not accept a memory_pool
> pc.cast does not accept a memory_pool
> pc.count does accept a memory_pool but should it?
> pc.fill_null does not accept a memory_pool
> pc.filter does not accept a memory_pool
> pc.match_substring* does not accept a memory_pool
> pc.mean does accept a memory_pool while pc.mode does not



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