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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