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https://issues.apache.org/jira/browse/SPARK-46536?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-46536.
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Fix Version/s: 4.0.0
Resolution: Fixed
Issue resolved by pull request 44538
[https://github.com/apache/spark/pull/44538]
> Support GROUP BY calendar_interval_type
> ---------------------------------------
>
> Key: SPARK-46536
> URL: https://issues.apache.org/jira/browse/SPARK-46536
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 4.0.0
> Reporter: Wenchen Fan
> Priority: Major
> Labels: pull-request-available
> Fix For: 4.0.0
>
>
> Currently, Spark GROUP BY only allows orderable data types, otherwise the
> plan analysis fails:
> [https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ExprUtils.scala#L197-L203]
> However, this is too strict as GROUP BY only cares about equality, not
> ordering. The CalendarInterval type is not orderable (1 month and 30 days, we
> don't know which one is larger), but has well-defined equality. In fact, we
> already support `SELECT DISTINCT calendar_interval_type` in some cases (when
> hash aggregate is picked by the planner).
> The proposal here is to officially support calendar interval type in GROUP
> BY. We should relax the check inside `CheckAnalysis`, and make
> `CalendarInterval` implements `Comparable` using natural ordering (compare
> months first, then days, then seconds), and test with both hash aggregate and
> sort aggregate.
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