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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: 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
> Assignee: Apache Spark
> 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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