[jira] [Commented] (SPARK-22010) Slow fromInternal conversion for TimestampType

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-22010?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16166097#comment-16166097 ] 

Hyukjin Kwon commented on SPARK-22010:
--------------------------------------

I don't think this is worth fixing for now. The improvement looks quite trivial but it sounds we should reinvent the wheel. Do you know a simple and well-known workaround or any measurement between the custom fix and the current status? Otherwise, I'd close this as {{Won't Fix}}.

> Slow fromInternal conversion for TimestampType
> ----------------------------------------------
>
>                 Key: SPARK-22010
>                 URL: https://issues.apache.org/jira/browse/SPARK-22010
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 2.2.0
>            Reporter: Maciej Bryński
>
> To convert timestamp type to python we are using 
> `datetime.datetime.fromtimestamp(ts // 1000000).replace(microsecond=ts % 1000000)`
> code.
> {code}
> In [34]: %%timeit
>     ...: datetime.datetime.fromtimestamp(1505383647).replace(microsecond=12344)
>     ...:
> 4.2 µs ± 558 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
> {code}
> It's slow, because:
> # we're trying to get TZ on every conversion
> # we're using replace method
> Proposed solution: custom datetime conversion and move calculation of TZ to module



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