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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2018/07/11 06:48:00 UTC
[jira] [Commented] (SPARK-23858) Need to apply pyarrow adjustments
to complex types with DateType/TimestampType
[ https://issues.apache.org/jira/browse/SPARK-23858?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16539634#comment-16539634 ]
Hyukjin Kwon commented on SPARK-23858:
--------------------------------------
[~semanticbeeng], create a pandas udf that takes nested date or timestamps in a array and normal date or timestamps, and then compare the output. That would be easier to check what this ticket targets.
> Need to apply pyarrow adjustments to complex types with DateType/TimestampType
> -------------------------------------------------------------------------------
>
> Key: SPARK-23858
> URL: https://issues.apache.org/jira/browse/SPARK-23858
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark, SQL
> Affects Versions: 2.3.0
> Reporter: Bryan Cutler
> Priority: Major
>
> Currently, ArrayTypes with DateType and TimestampType need to perform the same adjustments as simple types, e.g. {{_check_series_localize_timestamps}}, and that should work for nested types as well.
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