Andrey Gubichev created SPARK-43778:
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Summary: RewriteCorrelatedScalarSubquery should handle duplicate
attributes
Key: SPARK-43778
URL: https://issues.apache.org/jira/browse/SPARK-43778
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 3.4.0
Reporter: Andrey Gubichev
This is a correctness problem caused by the fact that the decorrelation rule
does not dedup join attributes properly. This leads to the join on (c1 = c1),
which is simplified to True and the join becomes a cross product.
Example query:
create view t(c1, c2) as values (0, 1), (0, 2), (1, 2);
select c1, c2, (select count(*) cnt from t t2 where t1.c1 = t2.c1 having cnt =
0) from t t1
-- Correct answer: [(0, 1, null), (0, 2, null), (1, 2, null)]
+---+---+------------------+
|c1 |c2 |scalarsubquery(c1)|
+---+---+------------------+
|0 |1 |null |
|0 |1 |null |
|0 |2 |null |
|0 |2 |null |
|1 |2 |null |
|1 |2 |null |
+---+---+------------------+
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