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https://issues.apache.org/jira/browse/SPARK-20686?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-20686:
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Assignee: Apache Spark (was: Josh Rosen)
> PropagateEmptyRelation incorrectly handles aggregate without grouping
> expressions
> ---------------------------------------------------------------------------------
>
> Key: SPARK-20686
> URL: https://issues.apache.org/jira/browse/SPARK-20686
> Project: Spark
> Issue Type: Bug
> Components: Optimizer, SQL
> Affects Versions: 2.1.0
> Reporter: Josh Rosen
> Assignee: Apache Spark
> Labels: correctness
>
> The query
> {code}
> SELECT 1 FROM (SELECT COUNT(*) WHERE FALSE) t1
> {code}
> should return a single row of output because the subquery is an aggregate
> without a group-by and thus should return a single row. However, Spark
> incorrectly returns zero rows.
> This is caused by SPARK-16208, a patch which added an optimizer rule to
> propagate EmptyRelation through operators. The logic for handling aggregates
> is wrong: it checks whether aggregate expressions are non-empty for deciding
> whether the output should be empty, whereas it should be checking grouping
> expressions instead:
> An aggregate with non-empty group expression will return one output row per
> group. If the input to the grouped aggregate is empty then all groups will be
> empty and thus the output will be empty. It doesn't matter whether the SELECT
> statement includes aggregate expressions since that won't affect the number
> of output rows.
> If the grouping expressions are empty, however, then the aggregate will
> always produce a single output row and thus we cannot propagate the
> EmptyRelation.
> The current implementation is incorrect (since it returns a wrong answer) and
> also misses an optimization opportunity by not propagating EmptyRelation in
> the case where a grouped aggregate has aggregate expressions.
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