yaooqinn commented on a change in pull request #28592:
URL: https://github.com/apache/spark/pull/28592#discussion_r429110475
##########
File path: sql/core/src/test/resources/sql-tests/results/datetime.sql.out
##########
@@ -750,3 +750,164 @@ select to_timestamp("2019 10:10:10", "yyyy hh:mm:ss")
struct<to_timestamp(2019 10:10:10, yyyy hh:mm:ss):timestamp>
-- !query output
2019-01-01 10:10:10
+
+
+-- !query
+select date_format(date '2020-05-23', '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 'GGGGG' pattern in the new parser. 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 date_format(date '2020-05-23', 'MMMMM')
+-- !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 'MMMMM' pattern in the new parser. 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 date_format(date '2020-05-23', 'LLLLL')
+-- !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 'LLLLL' pattern in the new parser. 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 date_format(timestamp '2020-05-23', 'EEEEE')
+-- !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 'EEEEE' pattern in the new parser. 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 date_format(timestamp '2020-05-23', 'uuuuu')
+-- !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 'uuuuu' pattern in the new parser. 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 date_format('2020-05-23', 'QQQQQ')
+-- !query schema
+struct<>
+-- !query output
+java.lang.IllegalArgumentException
+Too many pattern letters: Q
+
+
+-- !query
+select date_format('2020-05-23', 'qqqqq')
+-- !query schema
+struct<>
+-- !query output
+java.lang.IllegalArgumentException
+Too many pattern letters: q
+
+
+-- !query
+select to_timestamp('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 new parser. 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('22 05 2020 Friday', 'dd MM yyyy EEEEEE')
+-- !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 'dd MM yyyy EEEEEE' pattern in the new parser. 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('22 05 2020 Friday', 'dd MM yyyy EEEEE')
+-- !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 'dd MM yyyy EEEEE' pattern in the new parser. 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 unix_timestamp('22 05 2020 Friday', 'dd MM yyyy EEEEE')
+-- !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 'dd MM yyyy EEEEE' pattern in the new parser. 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 from_unixtime(12345, 'MMMMM')
+-- !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 'MMMMM' pattern in the new parser. 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 from_unixtime(54321, 'QQQQQ')
Review comment:
Due to diff exception handling at the call sides, the results are not
same
https://github.com/apache/spark/pull/28592/files#diff-79dd276be45ede6f34e24ad7005b0a7cR801-R806
cc @cloud-fan
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