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[GitHub] [spark] chenzhx opened a new pull request #35660: [SPARK-37932][SQL] remove pruning the attributes mapping in QueryPlan…
chenzhx opened a new pull request #35660:
URL: https://github.com/apache/spark/pull/35660
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### What changes were proposed in this pull request?
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When the join with duplicate view like
```
SELECT l1.idFROM v1 l1
INNER JOIN (
SELECT id FROM v1
GROUP BY id HAVING COUNT(DISTINCT name) > 1
) l2
ON l1.id = l2.id
GROUP BY l1.name, l1.id;
```
The error stack is:
```
Resolved attribute(s) name#26 missing from id#31,name#32 in operator !Aggregate [id#31], [id#31, count(distinct name#26) AS count(distinct name#26)#33L]. Attribute(s) with the same name appear in the operation: name. Please check if the right attribute(s) are used.;
Aggregate [name#26, id#25], [id#25]
+- Join Inner, (id#25 = id#31)
:- SubqueryAlias l1
: +- SubqueryAlias spark_catalog.default.v1
: +- View (`default`.`v1`, [id#25,name#26])
: +- Project [cast(id#20 as int) AS id#25, cast(name#21 as string) AS name#26]
: +- Project [id#20, name#21]
: +- SubqueryAlias spark_catalog.default.t
: +- Relation default.t[id#20,name#21] parquet
+- SubqueryAlias l2
+- Project [id#31]
+- Filter (count(distinct name#26)#33L > cast(1 as bigint))
+- !Aggregate [id#31], [id#31, count(distinct name#26) AS count(distinct name#26)#33L]
+- SubqueryAlias spark_catalog.default.v1
+- View (`default`.`v1`, [id#31,name#32])
+- Project [cast(id#27 as int) AS id#31, cast(name#28 as string) AS name#32]
+- Project [id#27, name#28]
+- SubqueryAlias spark_catalog.default.t
+- Relation default.t[id#27,name#28] parquet
```
Spark will consider the two views to be duplicates, which will cause the query to fail.
Optimization plan after this change：
```
Aggregate [name#26, id#25], [id#25]
+- Join Inner, (id#25 = id#25)
:- SubqueryAlias l1
: +- SubqueryAlias spark_catalog.default.v1
: +- View (`default`.`v1`, [id#25,name#26])
: +- Project [cast(id#20 as int) AS id#25, cast(name#21 as string) AS name#26]
: +- Project [id#20, name#21]
: +- SubqueryAlias spark_catalog.default.t
: +- Relation default.t[id#20,name#21] parquet
+- SubqueryAlias l2
+- Project [id#25]
+- Filter (count(distinct name#26)#29L > cast(1 as bigint))
+- !Aggregate [id#25], [id#25, count(distinct name#26) AS count(distinct name#26)#33L]
+- SubqueryAlias spark_catalog.default.v1
+- View (`default`.`v1`, [id#25,name#26])
+- Project [cast(id#27 as int) AS id#25, cast(name#28 as string) AS name#26]
+- Project [id#27, name#28]
+- SubqueryAlias spark_catalog.default.t
+- Relation default.t[id#27,name#28] parquet
```
### Why are the changes needed?
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Please clarify why the changes are needed. For instance,
1. If you propose a new API, clarify the use case for a new API.
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Fix bug when using join in duplicate views.
### Does this PR introduce _any_ user-facing change?
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Note that it means *any* user-facing change including all aspects such as the documentation fix.
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Yes. When we join with duplicate view, the query would be successful.
Attribute mapping in pruned Aggregate will lose [name], resulting in an error when processing the upper filter.
### How was this patch tested?
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[GitHub] [spark] chenzhx commented on a change in pull request #35660: [SPARK-37932][SQL] Remove pruning the attributes mapping in QueryPlan
Posted by GitBox <gi...@apache.org>.
chenzhx commented on a change in pull request #35660:
URL: https://github.com/apache/spark/pull/35660#discussion_r815752475
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala
##########
@@ -327,16 +323,7 @@ abstract class QueryPlan[PlanType <: QueryPlan[PlanType]]
val existingAttrMappingSet = transferAttrMapping.map(_._2).toSet
newValidAttrMapping.filterNot { case (_, a) => existingAttrMappingSet.contains(a) }
}
- val resultAttrMapping = if (canGetOutput(plan)) {
- // We propagate the attributes mapping to the parent plan node to update attributes, so
- // the `newAttr` must be part of this plan's output.
Review comment:
As for why there is a problem with the view, there is no problem with the table because:
```
'Join Inner, ('l1.id = 'l2.id)
:- SubqueryAlias l1
: +- SubqueryAlias spark_catalog.default.t
: +- Relation default.t[id#20,name#21] parquet
+- SubqueryAlias l2
+- !Filter (count(distinct tempresolvedcolumn(name#23, name)) > cast(1 as bigint))
+- Aggregate [id#22], [id#22]
+- SubqueryAlias spark_catalog.default.t
+- Relation default.t[id#22,name#23] parquet
```
For tables, the id and name in join are different.
So it will not be considered duplicate and will not execute the following code.
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[GitHub] [spark] cloud-fan commented on a change in pull request #35660: [SPARK-37932][SQL] Remove pruning the attributes mapping in QueryPlan
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #35660:
URL: https://github.com/apache/spark/pull/35660#discussion_r815817246
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala
##########
@@ -327,16 +323,7 @@ abstract class QueryPlan[PlanType <: QueryPlan[PlanType]]
val existingAttrMappingSet = transferAttrMapping.map(_._2).toSet
newValidAttrMapping.filterNot { case (_, a) => existingAttrMappingSet.contains(a) }
}
- val resultAttrMapping = if (canGetOutput(plan)) {
- // We propagate the attributes mapping to the parent plan node to update attributes, so
- // the `newAttr` must be part of this plan's output.
Review comment:
I was not asking why table is fine but view hits the bug. I was asking why we produce an invalid Filter operator. Even with the table case, you can also see `!Filter (...`, and the `!` indicates invalid plan. This seems like a feature of DataFrame API and IIUC the rule `ResolveMissingReferences` can fix the invalid `Filter` operator.
So my suggestion is: `DeduplicateRelations` should only kick in if the plan's children are all resolved and valid. e.g.
```
val newPlan = renewDuplicatedRelations(mutable.HashSet.empty, plan)._1
if (newPlan.find(p => p.resolved && p.missingInput.nonEmpty).isDefined) {
// Wait for `ResolveMissingReferences` to resolve missing attributes first
newPlan
} else {
newPlan.resolveOperatorsUpWithPruning... {
case p: LogicalPlan if !p.childrenResolved => p
// To resolve duplicate expression IDs for Join.
case j @ Join(left, right, _, _, _) if !j.duplicateResolved =>
j.copy(right = dedupRight(left, right))
// Resolve duplicate output for LateralJoin.
...
}
}
```
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[GitHub] [spark] chenzhx commented on a change in pull request #35660: [SPARK-37932][SQL] Remove pruning the attributes mapping in QueryPlan
Posted by GitBox <gi...@apache.org>.
chenzhx commented on a change in pull request #35660:
URL: https://github.com/apache/spark/pull/35660#discussion_r814881466
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala
##########
@@ -327,16 +323,7 @@ abstract class QueryPlan[PlanType <: QueryPlan[PlanType]]
val existingAttrMappingSet = transferAttrMapping.map(_._2).toSet
newValidAttrMapping.filterNot { case (_, a) => existingAttrMappingSet.contains(a) }
}
- val resultAttrMapping = if (canGetOutput(plan)) {
Review comment:
But if keep the logic, it may lose the elements that the upper layer needs to use.
Do you have other ideas？
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[GitHub] [spark] beliefer commented on pull request #35660: [SPARK-37932][SQL] Remove pruning the attributes mapping in QueryPlan
Posted by GitBox <gi...@apache.org>.
beliefer commented on pull request #35660:
URL: https://github.com/apache/spark/pull/35660#issuecomment-1050811625
ping @cloud-fan
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[GitHub] [spark] cloud-fan commented on a change in pull request #35660: [SPARK-37932][SQL] Remove pruning the attributes mapping in QueryPlan
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #35660:
URL: https://github.com/apache/spark/pull/35660#discussion_r814854252
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala
##########
@@ -327,16 +323,7 @@ abstract class QueryPlan[PlanType <: QueryPlan[PlanType]]
val existingAttrMappingSet = transferAttrMapping.map(_._2).toSet
newValidAttrMapping.filterNot { case (_, a) => existingAttrMappingSet.contains(a) }
}
- val resultAttrMapping = if (canGetOutput(plan)) {
- // We propagate the attributes mapping to the parent plan node to update attributes, so
- // the `newAttr` must be part of this plan's output.
Review comment:
This logic itself is correct. An operator can only refer to an attribute if it's present in its child's output. I'm not sure how we produce such a plan
```
Filter (name#1 ...)
Aggregate ([id#2], group by id#2)
Scan [name#1, id#2]
```
The filter refers to `name` attribute but `Aggregate` does not output it. Can we investigate it further?
A safer fix can be: `DeduplicateRelations` should only dedup self-join if the two join children are resolved and have no missing attributes.
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[GitHub] [spark] chenzhx commented on a change in pull request #35660: [SPARK-37932][SQL] Remove pruning the attributes mapping in QueryPlan
Posted by GitBox <gi...@apache.org>.
chenzhx commented on a change in pull request #35660:
URL: https://github.com/apache/spark/pull/35660#discussion_r814881466
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala
##########
@@ -327,16 +323,7 @@ abstract class QueryPlan[PlanType <: QueryPlan[PlanType]]
val existingAttrMappingSet = transferAttrMapping.map(_._2).toSet
newValidAttrMapping.filterNot { case (_, a) => existingAttrMappingSet.contains(a) }
}
- val resultAttrMapping = if (canGetOutput(plan)) {
Review comment:
But if keep the logic, it may lose the elements that the upper layer needs to use.
Do you have other ideas？
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[GitHub] [spark] chenzhx closed pull request #35660: [SPARK-37932][SQL] Remove pruning the attributes mapping in QueryPlan
Posted by GitBox <gi...@apache.org>.
chenzhx closed pull request #35660:
URL: https://github.com/apache/spark/pull/35660
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[GitHub] [spark] chenzhx commented on a change in pull request #35660: [SPARK-37932][SQL] Remove pruning the attributes mapping in QueryPlan
Posted by GitBox <gi...@apache.org>.
chenzhx commented on a change in pull request #35660:
URL: https://github.com/apache/spark/pull/35660#discussion_r815836053
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala
##########
@@ -327,16 +323,7 @@ abstract class QueryPlan[PlanType <: QueryPlan[PlanType]]
val existingAttrMappingSet = transferAttrMapping.map(_._2).toSet
newValidAttrMapping.filterNot { case (_, a) => existingAttrMappingSet.contains(a) }
}
- val resultAttrMapping = if (canGetOutput(plan)) {
- // We propagate the attributes mapping to the parent plan node to update attributes, so
- // the `newAttr` must be part of this plan's output.
Review comment:
Thanks! I know how to do this.
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[GitHub] [spark] AmplabJenkins commented on pull request #35660: [SPARK-37932][SQL] Remove pruning the attributes mapping in QueryPlan
Posted by GitBox <gi...@apache.org>.
AmplabJenkins commented on pull request #35660:
URL: https://github.com/apache/spark/pull/35660#issuecomment-1051017735
Can one of the admins verify this patch?
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[GitHub] [spark] cloud-fan commented on a change in pull request #35660: [SPARK-37932][SQL] Remove pruning the attributes mapping in QueryPlan
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #35660:
URL: https://github.com/apache/spark/pull/35660#discussion_r814845277
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala
##########
@@ -327,16 +323,7 @@ abstract class QueryPlan[PlanType <: QueryPlan[PlanType]]
val existingAttrMappingSet = transferAttrMapping.map(_._2).toSet
newValidAttrMapping.filterNot { case (_, a) => existingAttrMappingSet.contains(a) }
}
- val resultAttrMapping = if (canGetOutput(plan)) {
Review comment:
It's risky to remove this logic completely, as it helps to avoid the attribute map growing too big.
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