cloud-fan commented on a change in pull request #32995:
URL: https://github.com/apache/spark/pull/32995#discussion_r655543423



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File path: sql/core/src/test/resources/sql-tests/results/ansi/datetime.sql.out
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@@ -936,6 +1198,33 @@ org.apache.spark.SparkUpgradeException
 You may get a different result due to the upgrading of Spark 3.0: Fail to 
recognize 'dd MM yyyy EEEEE' pattern in the DateTimeFormatter. 1) You can set 
spark.sql.legacy.timeParserPolicy to LEGACY to restore the behavior before 
Spark 3.0. 2) You can form a valid datetime pattern with the guide from 
https://spark.apache.org/docs/latest/sql-ref-datetime-pattern.html
 
 
+-- !query
+select to_timestamp_ntz('2019-10-06 A', 'yyyy-MM-dd GGGGG')
+-- !query schema
+struct<>
+-- !query output
+org.apache.spark.SparkUpgradeException
+You may get a different result due to the upgrading of Spark 3.0: Fail to 
recognize 'yyyy-MM-dd GGGGG' pattern in the DateTimeFormatter. 1) You can set 
spark.sql.legacy.timeParserPolicy to LEGACY to restore the behavior before 
Spark 3.0. 2) You can form a valid datetime pattern with the guide from 
https://spark.apache.org/docs/latest/sql-ref-datetime-pattern.html

Review comment:
       good point. The new function should bypass this upgrade check in the 
timestamp formatter.




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