Github user squito commented on the issue:
https://github.com/apache/spark/pull/16781
@ueshin sorry it took me a while to figure out how a table partitioned by
timestamps work (I didn't even realize that was possible, I don't think it is
in hive?) and I was traveling.
The good news is that partitioning by timestamp works just fine. Since the
ts is stored as a string anyway, and [converted using the session tz
already](https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/interface.scala#L135),
it already works. I added one minimal test on this -- when the partitioned
table is written, the correct partition dirs are created regardless of the
timezone combinations.
In particular, it doesn't make sense to do tests like the existing ones,
where we write or read "unadjusted" data, bypassing the hive tables, and then
make sure the right adjustments are applied when you perform the reverse action
via the hive table; the partition values are correct whether you use the hive
table & adjustment property or not.
Let me know if you think more tests are required.
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