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https://issues.apache.org/jira/browse/SPARK-21375?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16586369#comment-16586369
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Bryan Cutler commented on SPARK-21375:
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Hi [~ewohlstadter], the timestamp values should be in UTC. I'm not sure if
that's what Hive uses or not, but if not then you will need to do a conversion
there. Then when building an Arrow TimeStampMicroTZVector, use the conf
"spark.sql.session.timeZone" for the timezone, which should make things
consistent. Hope that helps.
> Add date and timestamp support to ArrowConverters for toPandas() collection
> ---------------------------------------------------------------------------
>
> Key: SPARK-21375
> URL: https://issues.apache.org/jira/browse/SPARK-21375
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark, SQL
> Affects Versions: 2.3.0
> Reporter: Bryan Cutler
> Assignee: Bryan Cutler
> Priority: Major
> Fix For: 2.3.0
>
>
> Date and timestamp are not yet supported in DataFrame.toPandas() using
> ArrowConverters. These are common types for data analysis used in both Spark
> and Pandas and should be supported.
> There is a discrepancy with the way that PySpark and Arrow store timestamps,
> without timezone specified, internally. PySpark takes a UTC timestamp that
> is adjusted to local time and Arrow is in UTC time. Hopefully there is a
> clean way to resolve this.
> Spark internal storage spec:
> * *DateType* stored as days
> * *Timestamp* stored as microseconds
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