Max Gekk created SPARK-35097:
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Summary: 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
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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