[jira] [Updated] (SPARK-43778) RewriteCorrelatedScalarSubquery should handle duplicate attributes
[
https://issues.apache.org/jira/browse/SPARK-43778?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
ASF GitHub Bot updated SPARK-43778:
---
Labels: pull-request-available (was: )
> 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
>Priority: Major
> Labels: pull-request-available
> Fix For: 4.0.0
>
>
> 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:
>
> {code:java}
> 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 |
> +---+---+--+ {code}
>
>
>
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[jira] [Updated] (SPARK-43778) RewriteCorrelatedScalarSubquery should handle duplicate attributes
[
https://issues.apache.org/jira/browse/SPARK-43778?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Andrey Gubichev updated SPARK-43778:
Description:
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:
{code:java}
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 |
+---+---+--+ {code}
was:
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|
{+}--{-}{-}{+}-{-}++{-}-
> 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
>Priority: Major
>
> 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:
>
> {code:java}
> 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 |
> +---+---+--+ {code}
>
>
>
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[jira] [Updated] (SPARK-43778) RewriteCorrelatedScalarSubquery should handle duplicate attributes
[
https://issues.apache.org/jira/browse/SPARK-43778?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Andrey Gubichev updated SPARK-43778:
Description:
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|
{+}--{-}{-}{+}-{-}++{-}-
was:
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 |
+---+---+--+
> 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
>Priority: Major
>
> 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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