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https://issues.apache.org/jira/browse/SPARK-21375?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16100572#comment-16100572
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Bryan Cutler commented on SPARK-21375:
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Also, there has been some discussion about Timestamps on the dev-list and if
I'm reading it right, there is a proposal to add a new TimestampType that
specifies a timezone. If that happens, then it could be used to make a time
zone naive timestamp. The discussion is
[here|http://apache-spark-developers-list.1001551.n3.nabble.com/SQL-TIMESTAMP-semantics-vs-SPARK-18350-td21621.html]
> 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
>
> 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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