[ https://issues.apache.org/jira/browse/SPARK-23314?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16351333#comment-16351333 ]
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) -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org