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Posted to issues@spark.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2025/01/16 00:47:00 UTC
[jira] [Updated] (SPARK-50840) TimestampType wrongly gets mapped to TimestampNTZ when reloading metadata from Hive, if timestamp alias is set to NTZ
[ https://issues.apache.org/jira/browse/SPARK-50840?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
ASF GitHub Bot updated SPARK-50840:
-----------------------------------
Labels: pull-request-available spark-sql (was: spark-sql)
> TimestampType wrongly gets mapped to TimestampNTZ when reloading metadata from Hive, if timestamp alias is set to NTZ
> ---------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-50840
> URL: https://issues.apache.org/jira/browse/SPARK-50840
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 4.0.0, 3.5.4
> Reporter: Asif
> Priority: Major
> Labels: pull-request-available, spark-sql
>
> 1) Hive does not support spark's TimeStampNTZType
> 2) the mapping of the default spark's LTZ timestamp is incorrect, which is a separate and much bigger issue.
> If we create a hive table with timestamp field such that timestamp alias ( defined by property spark.sql.timestampType) is pointing to TimestampTypes.TIMESTAMP_LTZ, the metadata in Hive will be "timestamp".
> Later if we change the Timestamp alias to TimestampTypes.TIMESTAMP_NTZ, and do any operation, such that table metadata is reloaded from Hive, the timestamp type generated in Spark would get value of TimestampTypes.TIMESTAMP_NTZ, instead of TimestampType ( i.e LTZ).
> This would eventually result in parsing exception in Hive layer as it does not recognize timestamp NTZ.
> Will be opening a PR, with bug test
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