You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2021/08/12 01:19:00 UTC
[jira] [Commented] (SPARK-32285) Add PySpark support for nested
timestamps with arrow
[ https://issues.apache.org/jira/browse/SPARK-32285?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17397729#comment-17397729 ]
Hyukjin Kwon commented on SPARK-32285:
--------------------------------------
Arrow version is 2.0.0 now. Can we fix this ticket?
> Add PySpark support for nested timestamps with arrow
> ----------------------------------------------------
>
> Key: SPARK-32285
> URL: https://issues.apache.org/jira/browse/SPARK-32285
> Project: Spark
> Issue Type: Improvement
> Components: PySpark, SQL
> Affects Versions: 3.0.0
> Reporter: Bryan Cutler
> Priority: Major
>
> Currently with arrow optimizations, there is post-processing done in pandas for timestamp columns to localize timezone. This is not done for nested columns with timestamps such as StructType or ArrayType.
> Adding support for this is needed for Apache Arrow 1.0.0 upgrade due to use of structs with timestamps in groupedby key over a window.
> As a simple first step, timestamps with 1 level nesting could be done first and this will satisfy the immediate need.
> NOTE: with Arrow 1.0.0, it might be possible to do the timezone processing with pyarrow.array.cast, which could be easier done than in pandas.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org