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https://issues.apache.org/jira/browse/SPARK-35854?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17367180#comment-17367180
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Apache Spark commented on SPARK-35854:
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User 'gengliangwang' has created a pull request for this issue:
https://github.com/apache/spark/pull/33019
> Improve the error message of to_timestamp_ntz with invalid format pattern
> -------------------------------------------------------------------------
>
> Key: SPARK-35854
> URL: https://issues.apache.org/jira/browse/SPARK-35854
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 3.2.0
> Reporter: Gengliang Wang
> Assignee: Gengliang Wang
> Priority: Major
>
> 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.
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