spark-instrumented-optimizer/sql/catalyst
Gengliang Wang ce53b7199d [SPARK-35854][SQL] Improve the error message of to_timestamp_ntz with invalid format pattern
### What changes were proposed in this pull request?

When SQL function `to_timestamp_ntz` has invalid format pattern input, throw a runtime exception with hints for the valid patterns, instead of throwing an upgrade exception with suggestions to use legacy formatters.

### Why are the changes needed?

As discussed in https://github.com/apache/spark/pull/32995/files#r655148980, there is an error message saying
"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"

This is not true for function to_timestamp_ntz, which only uses the Iso8601TimestampFormatter and added since Spark 3.2. We should improve it.

### Does this PR introduce _any_ user-facing change?

No, the new SQL function is not released yet.

### How was this patch tested?

Unit test

Closes #33019 from gengliangwang/improveError.

Authored-by: Gengliang Wang <gengliang@apache.org>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
2021-06-22 23:45:54 +08:00
..
benchmarks [SPARK-34950][TESTS] Update benchmark results to the ones created by GitHub Actions machines 2021-04-03 23:02:56 +03:00
src [SPARK-35854][SQL] Improve the error message of to_timestamp_ntz with invalid format pattern 2021-06-22 23:45:54 +08:00
pom.xml [SPARK-33212][BUILD] Upgrade to Hadoop 3.2.2 and move to shaded clients for Hadoop 3.x profile 2021-01-15 14:06:50 -08:00