dongjoon-hyun commented on code in PR #46497:
URL: https://github.com/apache/spark/pull/46497#discussion_r1594967837


##########
docs/sql-migration-guide.md:
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@@ -50,6 +50,7 @@ license: |
 - Since Spark 4.0, Oracle JDBC datasource will write TimestampType as 
TIMESTAMP WITH LOCAL TIME ZONE, while in Spark 3.5 and previous, write as 
TIMESTAMP. To restore the previous behavior, set 
`spark.sql.legacy.oracle.timestampMapping.enabled` to `true`.
 - Since Spark 4.0, MsSQL Server JDBC datasource will read TINYINT as 
ShortType, while in Spark 3.5 and previous, read as IntegerType. To restore the 
previous behavior, set `spark.sql.legacy.mssqlserver.numericMapping.enabled` to 
`true`.
 - Since Spark 4.0, MsSQL Server JDBC datasource will read DATETIMEOFFSET as 
TimestampType, while in Spark 3.5 and previous, read as StringType. To restore 
the previous behavior, set 
`spark.sql.legacy.mssqlserver.datetimeoffsetMapping.enabled` to `true`.
+- Since Spark 4.0, DB2 JDBC datasource will read SMALLINT as ShortType, while 
in Spark 3.5 and previous, it was read as IntegerType. To restore the previous 
behavior, you can cast the column to the old type.

Review Comment:
   Hmm, it means we need to edit SQL statement, right?



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