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https://issues.apache.org/jira/browse/SPARK-35097?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-35097:
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    Assignee:     (was: Apache Spark)

> Add column name to SparkUpgradeException about ancient datetime
> ---------------------------------------------------------------
>
>                 Key: SPARK-35097
>                 URL: https://issues.apache.org/jira/browse/SPARK-35097
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 3.2.0
>            Reporter: Max Gekk
>            Priority: Major
>
> The error message:
> {code:java}
> org.apache.spark.SparkUpgradeException: You may get a different result due to 
> the upgrading of Spark 3.0: reading dates before 1582-10-15 or timestamps 
> before 1900-01-01T00:00:00Z from Parquet files can be ambiguous, as the files 
> may be written by Spark 2.x or legacy versions of Hive, which uses a legacy 
> hybrid calendar that is different from Spark 3.0+'s Proleptic Gregorian 
> calendar. See more details in SPARK-31404. You can set 
> spark.sql.legacy.parquet.datetimeRebaseModeInRead to 'LEGACY' to rebase the 
> datetime values w.r.t. the calendar difference during reading. Or set 
> spark.sql.legacy.parquet.datetimeRebaseModeInRead to 'CORRECTED' to read the 
> datetime values as it is.
> {code}
> doesn't have any clues of which column causes the issue. Need to improve the 
> message and add column name to it.



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