You are viewing a plain text version of this content. The canonical link for it is here.
Posted to jira@arrow.apache.org by "Weston Pace (Jira)" <ji...@apache.org> on 2021/05/13 23:23:00 UTC
[jira] [Created] (ARROW-12787) [Python] pyarrow.compute not
consistent on memory_pool usage
Weston Pace created ARROW-12787:
-----------------------------------
Summary: [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
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
--
This message was sent by Atlassian Jira
(v8.3.4#803005)