[GitHub] [spark] yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL] Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates if run multiple times
yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL]
Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates
if run multiple times
URL: https://github.com/apache/spark/pull/25164#discussion_r304766364
##
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala
##
@@ -275,13 +275,16 @@ object PullupCorrelatedPredicates extends
Rule[LogicalPlan] with PredicateHelper
plan transformExpressions {
case ScalarSubquery(sub, children, exprId) if children.nonEmpty =>
val (newPlan, newCond) = pullOutCorrelatedPredicates(sub, outerPlans)
-ScalarSubquery(newPlan, newCond, exprId)
+val conds = newCond ++ children.filter(_.isInstanceOf[Predicate])
Review comment:
TBH subquery resolution and optimzation are super tricky and can be
error-prone. The current code is a bit complex and fragile, because one piece
of code might have some pre-conditions on some other parts of the codebase,
which might change over time.
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[GitHub] [spark] yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL] Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates if run multiple times
yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL]
Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates
if run multiple times
URL: https://github.com/apache/spark/pull/25164#discussion_r304765685
##
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala
##
@@ -275,13 +275,16 @@ object PullupCorrelatedPredicates extends
Rule[LogicalPlan] with PredicateHelper
plan transformExpressions {
case ScalarSubquery(sub, children, exprId) if children.nonEmpty =>
val (newPlan, newCond) = pullOutCorrelatedPredicates(sub, outerPlans)
-ScalarSubquery(newPlan, newCond, exprId)
+val conds = newCond ++ children.filter(_.isInstanceOf[Predicate])
Review comment:
I doubt it... Because the logic for checking `OuterReferences` and the logic
for actually pulling up predicates are slightly different. With that being
said, even though `l.children` is non-empty, it does not necessarily mean that
`newCond` is non-empty.
The most natural way I can think of is that we combine these two rule
`PullupCorrelatedPredicates` and `RewriteSubqueryPredicates`,
`RewriteSubqueryPredicates` completely removes those hacky list subqueries. I
don't think the plan can change if we apply these two rules in a single `Once`
batch.
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[GitHub] [spark] yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL] Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates if run multiple times
yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL]
Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates
if run multiple times
URL: https://github.com/apache/spark/pull/25164#discussion_r304765685
##
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala
##
@@ -275,13 +275,16 @@ object PullupCorrelatedPredicates extends
Rule[LogicalPlan] with PredicateHelper
plan transformExpressions {
case ScalarSubquery(sub, children, exprId) if children.nonEmpty =>
val (newPlan, newCond) = pullOutCorrelatedPredicates(sub, outerPlans)
-ScalarSubquery(newPlan, newCond, exprId)
+val conds = newCond ++ children.filter(_.isInstanceOf[Predicate])
Review comment:
I doubt it... Because the logic for checking `OuterReferences` and the logic
for actually pulling up predicates are slightly different. With that being
said, even though `l.children` is non-empty, it does not necessarily mean that
`newCond` is non-empty.
The most natural way I can think of is that we combine these two rule
`PullupCorrelatedPredicates` and `RewriteSubqueryPredicates`, and
`RewriteSubqueryPredicates` completely removes those hacky list subqueries. I
don't think the plan can change if we apply these two rules in a single `Once`
batch.
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[GitHub] [spark] yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL] Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates if run multiple times
yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL]
Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates
if run multiple times
URL: https://github.com/apache/spark/pull/25164#discussion_r304766364
##
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala
##
@@ -275,13 +275,16 @@ object PullupCorrelatedPredicates extends
Rule[LogicalPlan] with PredicateHelper
plan transformExpressions {
case ScalarSubquery(sub, children, exprId) if children.nonEmpty =>
val (newPlan, newCond) = pullOutCorrelatedPredicates(sub, outerPlans)
-ScalarSubquery(newPlan, newCond, exprId)
+val conds = newCond ++ children.filter(_.isInstanceOf[Predicate])
Review comment:
TBH subquery resolution and optimzation are super tricky and can be
error-prone. The current code is a bit complex and fragile, because one piece
of code might have some pre-conditions on some other part of the codebase,
which might change over time.
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[GitHub] [spark] yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL] Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates if run multiple times
yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL]
Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates
if run multiple times
URL: https://github.com/apache/spark/pull/25164#discussion_r304765685
##
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala
##
@@ -275,13 +275,16 @@ object PullupCorrelatedPredicates extends
Rule[LogicalPlan] with PredicateHelper
plan transformExpressions {
case ScalarSubquery(sub, children, exprId) if children.nonEmpty =>
val (newPlan, newCond) = pullOutCorrelatedPredicates(sub, outerPlans)
-ScalarSubquery(newPlan, newCond, exprId)
+val conds = newCond ++ children.filter(_.isInstanceOf[Predicate])
Review comment:
I doubt it... Because the logic for checking `OuterReferences` and the logic
for actually pulling up predicates are slightly different. With that being
said, even though `l.children` is non-empty, it does not necessarily mean that
`newCond` is empty.
The most natural way I can think of is that we combine these two rule
`PullupCorrelatedPredicates` and `RewriteSubqueryPredicates`,
`RewriteSubqueryPredicates` completely removes those hacky list subqueries. I
don't think the plan can change if we apply these two rules in a single `Once`
batch.
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[GitHub] [spark] yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL] Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates if run multiple times
yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL]
Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates
if run multiple times
URL: https://github.com/apache/spark/pull/25164#discussion_r304557504
##
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala
##
@@ -275,13 +275,16 @@ object PullupCorrelatedPredicates extends
Rule[LogicalPlan] with PredicateHelper
plan transformExpressions {
case ScalarSubquery(sub, children, exprId) if children.nonEmpty =>
val (newPlan, newCond) = pullOutCorrelatedPredicates(sub, outerPlans)
-ScalarSubquery(newPlan, newCond, exprId)
+val conds = newCond ++ children.filter(_.isInstanceOf[Predicate])
Review comment:
@dilipbiswal Then I'll close this PR for now and wait till you combine those
two rules. (or you can do that yourself). Thanks!
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[GitHub] [spark] yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL] Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates if run multiple times
yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL]
Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates
if run multiple times
URL: https://github.com/apache/spark/pull/25164#discussion_r304219902
##
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala
##
@@ -275,13 +275,16 @@ object PullupCorrelatedPredicates extends
Rule[LogicalPlan] with PredicateHelper
plan transformExpressions {
case ScalarSubquery(sub, children, exprId) if children.nonEmpty =>
val (newPlan, newCond) = pullOutCorrelatedPredicates(sub, outerPlans)
-ScalarSubquery(newPlan, newCond, exprId)
+val conds = newCond ++ children.filter(_.isInstanceOf[Predicate])
Review comment:
Ahh, got it. Thanks for your detailed explanation!
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[GitHub] [spark] yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL] Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates if run multiple times
yeshengm commented on a change in pull request #25164: [SPARK-28375][SQL]
Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates
if run multiple times
URL: https://github.com/apache/spark/pull/25164#discussion_r304215574
##
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala
##
@@ -275,13 +275,16 @@ object PullupCorrelatedPredicates extends
Rule[LogicalPlan] with PredicateHelper
plan transformExpressions {
case ScalarSubquery(sub, children, exprId) if children.nonEmpty =>
val (newPlan, newCond) = pullOutCorrelatedPredicates(sub, outerPlans)
-ScalarSubquery(newPlan, newCond, exprId)
+val conds = newCond ++ children.filter(_.isInstanceOf[Predicate])
Review comment:
@dilipbiswal According to jira, it seems that spark-19712 is already
resolved. That said, we can safely combine the two now, right?
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