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https://issues.apache.org/jira/browse/SPARK-36227?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17405231#comment-17405231
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Apache Spark commented on SPARK-36227:
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User 'gengliangwang' has created a pull request for this issue:
https://github.com/apache/spark/pull/33851
> Remove TimestampNTZ type support in Spark 3.2
> ---------------------------------------------
>
> Key: SPARK-36227
> URL: https://issues.apache.org/jira/browse/SPARK-36227
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 3.3.0
> Reporter: Gengliang Wang
> Assignee: Gengliang Wang
> Priority: Major
> Fix For: 3.3.0
>
>
> As of now, there are some blockers for delivering the TimestampNTZ project in
> Spark 3.2:
> # In the Hive Thrift server, both TimestampType and TimestampNTZType are
> mapped to the same timestamp type, which can cause confusion for users.
> # For the Parquet data source, the new written TimestampNTZType Parquet
> columns will be read as TimestampType in old Spark releases. Also, we need to
> decide the merge schema for files mixed with TimestampType and TimestampNTZ
> type.
> # The type coercion rules for TimestampNTZType are incomplete. For example,
> what should the data type of the in clause "IN(Timestamp'2020-01-01
> 00:00:00', TimestampNtz'2020-01-01 00:00:00') be.
> # It is tricky to support TimestampNTZType in JSON/CSV data readers. We need
> to avoid regressions as possible as we can.
> There are 10 days left for the expected 3.2 RC date. So, I propose to release
> the TimestampNTZ type in Spark 3.3 instead of Spark 3.2. So that we have
> enough time to make considerate designs for the issues.
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