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https://issues.apache.org/jira/browse/SPARK-23314?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16351333#comment-16351333
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Felix Cheung commented on SPARK-23314:
--------------------------------------
I've isolated this down to this particular file
[https://raw.githubusercontent.com/BuzzFeedNews/2016-04-federal-surveillance-planes/master/data/feds/feds3.csv]
without converting to pandas it seems to read fine, so not if it's a data
problem.
> Pandas grouped udf on dataset with timestamp column error
> ----------------------------------------------------------
>
> Key: SPARK-23314
> URL: https://issues.apache.org/jira/browse/SPARK-23314
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark
> Affects Versions: 2.3.0
> Reporter: Felix Cheung
> Priority: Major
>
> Under SPARK-22216
> When testing pandas_udf on group bys, I saw this error with the timestamp
> column.
> File "pandas/_libs/tslib.pyx", line 3593, in
> pandas._libs.tslib.tz_localize_to_utc
> AmbiguousTimeError: Cannot infer dst time from Timestamp('2015-11-01
> 01:29:30'), try using the 'ambiguous' argument
> For details, see Comment box. I'm able to reproduce this on the latest
> branch-2.3 (last change from Feb 1 UTC)
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