sadikovi commented on PR #36726:
URL: https://github.com/apache/spark/pull/36726#issuecomment-1154747718

   I think we can. JDBC dialects can configure how they map TimestampNTZ type.
   In the case you mentioned, both timestamps will be read as timestamp_ntz in 
MySQL and Postgres. In fact, the current timestamp type is stored as 
timestamp_ntz in those database systems.
   
   Even with dialects managing timestamp_ntz writes and reads, this would be 
the same problem unless you store them as different types.
   
   Also, the test passes in master:
   ```
   [ivan.sadikov@C02DV1TGMD6R spark-oss (master)]$ git log -n1
   commit 2349175e1b81b0a61e1ed90c2d051c01cf78de9b (HEAD -> master, 
upstream/master)
   Author: Ivan Sadikov <[email protected]>
   Date:   Mon Jun 13 21:22:15 2022 -0700
   
       [SPARK-39339][SQL] Support TimestampNTZ type in JDBC data source
       
   
   
   
   [info] JDBCSuite:
   05:53:04.233 WARN org.apache.hadoop.util.NativeCodeLoader: Unable to load 
native-hadoop library for your platform... using builtin-java classes where 
applicable
   05:53:07.936 ERROR 
org.apache.spark.sql.execution.datasources.jdbc.connection.ConnectionProvider: 
Failed to load built-in provider.
   [info] - SPARK-39339: Handle TimestampNTZType null values (1 second, 555 
milliseconds)
   [info] - SPARK-39339: TimestampNTZType with different local time zones (4 
seconds, 48 milliseconds)
   05:53:14.022 WARN org.apache.spark.sql.jdbc.JDBCSuite: 
   
   ===== POSSIBLE THREAD LEAK IN SUITE o.a.s.sql.jdbc.JDBCSuite, threads: 
Timer-2 (daemon=true), rpc-boss-3-1 (daemon=true), shuffle-boss-6-1 
(daemon=true) =====
   [info] Run completed in 11 seconds, 724 milliseconds.
   [info] Total number of tests run: 2
   [info] Suites: completed 1, aborted 0
   [info] Tests: succeeded 2, failed 0, canceled 0, ignored 0, pending 0
   [info] All tests passed.
   [success] Total time: 81 s (01:21), completed Jun 14, 2022 5:53:14 AM
   ```
   


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