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https://issues.apache.org/jira/browse/SPARK-41455?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17655277#comment-17655277
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Apache Spark commented on SPARK-41455:
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User 'zhengruifeng' has created a pull request for this issue:
https://github.com/apache/spark/pull/39426
> Resolve dtypes inconsistencies of date/timestamp functions
> ----------------------------------------------------------
>
> Key: SPARK-41455
> URL: https://issues.apache.org/jira/browse/SPARK-41455
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark
> Affects Versions: 3.4.0
> Reporter: Xinrong Meng
> Priority: Major
>
> When implementing date/timestamp functions, we notice inconsistent dtypes
> with PySpark, as shown below.
> {code:python}
> >> sdf.select(SF.current_timestamp()).toPandas().dtypes
> current_timestamp() datetime64[ns]
> dtype: object
> >>> cdf.select(CF.current_timestamp()).toPandas().dtypes
> current_timestamp() datetime64[ns, America/Los_Angeles]
> {code}
> Affected functions include:
> {code:python}
> to_timestamp, from_utc_timestamp, to_utc_timestamp, timestamp_seconds,
> current_timestamp, date_trunc
> {code}
> We may have to implement `is_timestamp_ntz_preferred` for Connect.
> After the fix, tests of those date/timestamp functions which use
> `compare_by_show` should be switched to `toPandas` comparison.
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