You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Xiao Li (Jira)" <ji...@apache.org> on 2021/04/16 16:54:00 UTC
[jira] [Commented] (SPARK-35097) Add column name to
SparkUpgradeException about ancient datetime
[ https://issues.apache.org/jira/browse/SPARK-35097?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17323943#comment-17323943 ]
Xiao Li commented on SPARK-35097:
---------------------------------
Can you help fix this, [~angerszhuuu] ?
> 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.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org