Josh Rosen created SPARK-20686:
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Summary: 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: Josh Rosen
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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