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[GitHub] [spark] maryannxue opened a new pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
maryannxue opened a new pull request #34929:
URL: https://github.com/apache/spark/pull/34929
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### What changes were proposed in this pull request?
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This PR adds predicate push-down and column pruning to CTEs that are not inlined as well as fixes a few potential correctness issues:
1) Replace (previously not inlined) CTE refs with Repartition operations at the end of logical plan optimization so that WithCTE is not carried over to physical plan. As a result, we can simplify the logic of physical planning, as well as avoid a correctness issue where the logical link of a physical plan node can point to `WithCTE` and lead to unexpected behaviors in AQE, e.g., class cast exceptions in DPP/DFP.
2) Pull (not inlined) CTE defs from subqueries up to the main query level, in order to avoid creating copies of the same CTE def during predicate push-downs and other transformations.
3) Make CTE IDs more deterministic by starting from 0 for each query.
### Why are the changes needed?
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1. If you propose a new API, clarify the use case for a new API.
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Improve de-duped CTEs' performance with predicate pushdown and column pruning; fixes de-duped CTEs' correctness issues.
### Does this PR introduce _any_ user-facing change?
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No.
### How was this patch tested?
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Added UTs.
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[GitHub] [spark] SparkQA commented on pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #34929:
URL: https://github.com/apache/spark/pull/34929#issuecomment-996491348
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[GitHub] [spark] SparkQA commented on pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #34929:
URL: https://github.com/apache/spark/pull/34929#issuecomment-996465568
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[GitHub] [spark] SparkQA commented on pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #34929:
URL: https://github.com/apache/spark/pull/34929#issuecomment-996501165
**[Test build #146315 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/146315/testReport)** for PR 34929 at commit [`841aa2a`](https://github.com/apache/spark/commit/841aa2abd7a697bc402e4321f771bf7cbba22089).
* This patch **fails Spark unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] [spark] cloud-fan commented on a change in pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #34929:
URL: https://github.com/apache/spark/pull/34929#discussion_r779665758
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/PushdownPredicatesAndPruneColumnsForCTEDef.scala
##########
@@ -0,0 +1,171 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.catalyst.optimizer
+
+import scala.collection.mutable
+
+import org.apache.spark.sql.catalyst.expressions.{And, Attribute, AttributeSet, Expression, Literal, Or, SubqueryExpression}
+import org.apache.spark.sql.catalyst.planning.ScanOperation
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.catalyst.trees.TreePattern.CTE
+
+/**
+ * Infer predicates and column pruning for [[CTERelationDef]] from its reference points, and push
+ * the disjunctive predicates as well as the union of attributes down the CTE plan.
+ */
+object PushdownPredicatesAndPruneColumnsForCTEDef extends Rule[LogicalPlan] {
+
+ // CTE_id - (CTE_definition, precedence, predicates_to_push_down, attributes_to_prune)
+ private type CteMap = mutable.HashMap[Long, (CTERelationDef, Int, Seq[Expression], AttributeSet)]
+
+ override def apply(plan: LogicalPlan): LogicalPlan = {
+ if (!plan.isInstanceOf[Subquery] && plan.containsPattern(CTE)) {
+ val cteMap = new CteMap
+ gatherPredicatesAndAttributes(plan, cteMap)
+ pushdownPredicatesAndAttributes(plan, cteMap)
+ } else {
+ plan
+ }
+ }
+
+ private def reverseMapExpressions(
Review comment:
`restoreCTEDefAttrs`?
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[GitHub] [spark] cloud-fan commented on a change in pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #34929:
URL: https://github.com/apache/spark/pull/34929#discussion_r779653096
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/PushdownPredicatesAndPruneColumnsForCTEDef.scala
##########
@@ -0,0 +1,171 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.catalyst.optimizer
+
+import scala.collection.mutable
+
+import org.apache.spark.sql.catalyst.expressions.{And, Attribute, AttributeSet, Expression, Literal, Or, SubqueryExpression}
+import org.apache.spark.sql.catalyst.planning.ScanOperation
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.catalyst.trees.TreePattern.CTE
+
+/**
+ * Infer predicates and column pruning for [[CTERelationDef]] from its reference points, and push
+ * the disjunctive predicates as well as the union of attributes down the CTE plan.
+ */
+object PushdownPredicatesAndPruneColumnsForCTEDef extends Rule[LogicalPlan] {
+
+ // CTE_id - (CTE_definition, precedence, predicates_to_push_down, attributes_to_prune)
+ private type CteMap = mutable.HashMap[Long, (CTERelationDef, Int, Seq[Expression], AttributeSet)]
+
+ override def apply(plan: LogicalPlan): LogicalPlan = {
+ if (!plan.isInstanceOf[Subquery] && plan.containsPattern(CTE)) {
+ val cteMap = new CteMap
+ gatherPredicatesAndAttributes(plan, cteMap)
+ pushdownPredicatesAndAttributes(plan, cteMap)
+ } else {
+ plan
+ }
+ }
+
+ private def reverseMapExpressions(
+ input: Seq[Expression],
+ mapping: Map[Attribute, Expression]): Seq[Expression] = {
+ input.map(e => e.transform {
+ case a: Attribute =>
+ mapping.keys.find(_.semanticEquals(a)).map(mapping).getOrElse(a)
+ })
+ }
+
+ /**
+ * Gather all the predicates and referenced attributes on different points of CTE references
+ * using pattern `ScanOperation` (which takes care of determinism) and combine those predicates
+ * and attributes that belong to the same CTE definition.
+ * For the same CTE definition, if any of its references does not have predicates, the combined
+ * predicate will be a TRUE literal, which means there will be no predicate push-down.
+ */
+ private def gatherPredicatesAndAttributes(plan: LogicalPlan, cteMap: CteMap): Unit = {
+ plan match {
+ case WithCTE(child, cteDefs) =>
+ cteDefs.zipWithIndex.foreach { case (cteDef, precedence) =>
+ gatherPredicatesAndAttributes(cteDef.child, cteMap)
+ cteMap.put(cteDef.id, (cteDef, precedence, Seq.empty, AttributeSet.empty))
+ }
+ gatherPredicatesAndAttributes(child, cteMap)
+
+ case ScanOperation(projects, predicates, ref: CTERelationRef) =>
+ val (cteDef, precedence, preds, attrs) = cteMap(ref.cteId)
+ val mapping = ref.output.zip(cteDef.output).map{ case (r, d) => r -> d }.toMap
Review comment:
```suggestion
val attrMapping = ref.output.zip(cteDef.output).map { case (r, d) => r -> d }.toMap
```
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[GitHub] [spark] cloud-fan commented on a change in pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #34929:
URL: https://github.com/apache/spark/pull/34929#discussion_r779653096
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/PushdownPredicatesAndPruneColumnsForCTEDef.scala
##########
@@ -0,0 +1,171 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.catalyst.optimizer
+
+import scala.collection.mutable
+
+import org.apache.spark.sql.catalyst.expressions.{And, Attribute, AttributeSet, Expression, Literal, Or, SubqueryExpression}
+import org.apache.spark.sql.catalyst.planning.ScanOperation
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.catalyst.trees.TreePattern.CTE
+
+/**
+ * Infer predicates and column pruning for [[CTERelationDef]] from its reference points, and push
+ * the disjunctive predicates as well as the union of attributes down the CTE plan.
+ */
+object PushdownPredicatesAndPruneColumnsForCTEDef extends Rule[LogicalPlan] {
+
+ // CTE_id - (CTE_definition, precedence, predicates_to_push_down, attributes_to_prune)
+ private type CteMap = mutable.HashMap[Long, (CTERelationDef, Int, Seq[Expression], AttributeSet)]
+
+ override def apply(plan: LogicalPlan): LogicalPlan = {
+ if (!plan.isInstanceOf[Subquery] && plan.containsPattern(CTE)) {
+ val cteMap = new CteMap
+ gatherPredicatesAndAttributes(plan, cteMap)
+ pushdownPredicatesAndAttributes(plan, cteMap)
+ } else {
+ plan
+ }
+ }
+
+ private def reverseMapExpressions(
+ input: Seq[Expression],
+ mapping: Map[Attribute, Expression]): Seq[Expression] = {
+ input.map(e => e.transform {
+ case a: Attribute =>
+ mapping.keys.find(_.semanticEquals(a)).map(mapping).getOrElse(a)
+ })
+ }
+
+ /**
+ * Gather all the predicates and referenced attributes on different points of CTE references
+ * using pattern `ScanOperation` (which takes care of determinism) and combine those predicates
+ * and attributes that belong to the same CTE definition.
+ * For the same CTE definition, if any of its references does not have predicates, the combined
+ * predicate will be a TRUE literal, which means there will be no predicate push-down.
+ */
+ private def gatherPredicatesAndAttributes(plan: LogicalPlan, cteMap: CteMap): Unit = {
+ plan match {
+ case WithCTE(child, cteDefs) =>
+ cteDefs.zipWithIndex.foreach { case (cteDef, precedence) =>
+ gatherPredicatesAndAttributes(cteDef.child, cteMap)
+ cteMap.put(cteDef.id, (cteDef, precedence, Seq.empty, AttributeSet.empty))
+ }
+ gatherPredicatesAndAttributes(child, cteMap)
+
+ case ScanOperation(projects, predicates, ref: CTERelationRef) =>
+ val (cteDef, precedence, preds, attrs) = cteMap(ref.cteId)
+ val mapping = ref.output.zip(cteDef.output).map{ case (r, d) => r -> d }.toMap
Review comment:
```suggestion
val mapping = ref.output.zip(cteDef.output).map { case (r, d) => r -> d }.toMap
```
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[GitHub] [spark] SparkQA commented on pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #34929:
URL: https://github.com/apache/spark/pull/34929#issuecomment-996449332
**[Test build #146315 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/146315/testReport)** for PR 34929 at commit [`841aa2a`](https://github.com/apache/spark/commit/841aa2abd7a697bc402e4321f771bf7cbba22089).
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[GitHub] [spark] cloud-fan commented on a change in pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #34929:
URL: https://github.com/apache/spark/pull/34929#discussion_r779611578
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
##########
@@ -1012,6 +1016,24 @@ class Analyzer(override val catalogManager: CatalogManager)
// inside a view maybe resolved incorrectly.
checkAnalysis(newChild)
view.copy(child = newChild)
+ case view @ View(_, _, child) =>
Review comment:
Let's add a comment before this case
```
// This is DataFrame view, not SQL view. We need to reassign CTE IDs as the plan
// is already resolved but the CTE IDs may conflict with main query.
```
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[GitHub] [spark] cloud-fan commented on a change in pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #34929:
URL: https://github.com/apache/spark/pull/34929#discussion_r779667322
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/PushdownPredicatesAndPruneColumnsForCTEDef.scala
##########
@@ -0,0 +1,171 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.catalyst.optimizer
+
+import scala.collection.mutable
+
+import org.apache.spark.sql.catalyst.expressions.{And, Attribute, AttributeSet, Expression, Literal, Or, SubqueryExpression}
+import org.apache.spark.sql.catalyst.planning.ScanOperation
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.catalyst.trees.TreePattern.CTE
+
+/**
+ * Infer predicates and column pruning for [[CTERelationDef]] from its reference points, and push
+ * the disjunctive predicates as well as the union of attributes down the CTE plan.
+ */
+object PushdownPredicatesAndPruneColumnsForCTEDef extends Rule[LogicalPlan] {
+
+ // CTE_id - (CTE_definition, precedence, predicates_to_push_down, attributes_to_prune)
+ private type CteMap = mutable.HashMap[Long, (CTERelationDef, Int, Seq[Expression], AttributeSet)]
+
+ override def apply(plan: LogicalPlan): LogicalPlan = {
+ if (!plan.isInstanceOf[Subquery] && plan.containsPattern(CTE)) {
+ val cteMap = new CteMap
+ gatherPredicatesAndAttributes(plan, cteMap)
+ pushdownPredicatesAndAttributes(plan, cteMap)
+ } else {
+ plan
+ }
+ }
+
+ private def reverseMapExpressions(
+ input: Seq[Expression],
+ mapping: Map[Attribute, Expression]): Seq[Expression] = {
+ input.map(e => e.transform {
+ case a: Attribute =>
+ mapping.keys.find(_.semanticEquals(a)).map(mapping).getOrElse(a)
+ })
+ }
+
+ /**
+ * Gather all the predicates and referenced attributes on different points of CTE references
+ * using pattern `ScanOperation` (which takes care of determinism) and combine those predicates
+ * and attributes that belong to the same CTE definition.
+ * For the same CTE definition, if any of its references does not have predicates, the combined
+ * predicate will be a TRUE literal, which means there will be no predicate push-down.
+ */
+ private def gatherPredicatesAndAttributes(plan: LogicalPlan, cteMap: CteMap): Unit = {
+ plan match {
+ case WithCTE(child, cteDefs) =>
+ cteDefs.zipWithIndex.foreach { case (cteDef, precedence) =>
+ gatherPredicatesAndAttributes(cteDef.child, cteMap)
+ cteMap.put(cteDef.id, (cteDef, precedence, Seq.empty, AttributeSet.empty))
+ }
+ gatherPredicatesAndAttributes(child, cteMap)
+
+ case ScanOperation(projects, predicates, ref: CTERelationRef) =>
+ val (cteDef, precedence, preds, attrs) = cteMap(ref.cteId)
+ val mapping = ref.output.zip(cteDef.output).map{ case (r, d) => r -> d }.toMap
+ val newPredicates = if (isTruePredicate(preds)) {
+ preds
+ } else {
+ val filteredPredicates = reverseMapExpressions(predicates.filter(_.find {
+ case s: SubqueryExpression => s.plan.find {
+ case r: CTERelationRef =>
+ !cteMap.contains(r.cteId) || cteMap(r.cteId)._2 >= precedence
Review comment:
`!cteMap.contains(r.cteId)` is kind of a sanity check, as we should collect Def first before hitting its Ref. But I don't quite understand what `cteMap(r.cteId)._2 >= precedence` means.
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[GitHub] [spark] cloud-fan commented on a change in pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #34929:
URL: https://github.com/apache/spark/pull/34929#discussion_r779643115
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/InlineCTE.scala
##########
@@ -93,25 +101,24 @@ object InlineCTE extends Rule[LogicalPlan] {
private def inlineCTE(
plan: LogicalPlan,
cteMap: mutable.HashMap[Long, (CTERelationDef, Int)],
- forceInline: Boolean): LogicalPlan = {
- val (stripped, notInlined) = plan match {
+ notInlined: mutable.ArrayBuffer[CTERelationDef]): LogicalPlan = {
+ plan match {
case WithCTE(child, cteDefs) =>
- val notInlined = mutable.ArrayBuffer.empty[CTERelationDef]
cteDefs.foreach { cteDef =>
val (cte, refCount) = cteMap(cteDef.id)
if (refCount > 0) {
- val inlined = cte.copy(child = inlineCTE(cte.child, cteMap, forceInline))
+ val inlined = cte.copy(child = inlineCTE(cte.child, cteMap, notInlined))
cteMap.update(cteDef.id, (inlined, refCount))
- if (!forceInline && !shouldInline(inlined, refCount)) {
+ if (!shouldInline(inlined, refCount)) {
notInlined.append(inlined)
}
}
}
- (inlineCTE(child, cteMap, forceInline), notInlined.toSeq)
+ inlineCTE(child, cteMap, notInlined)
case ref: CTERelationRef =>
val (cteDef, refCount) = cteMap(ref.cteId)
- val newRef = if (forceInline || shouldInline(cteDef, refCount)) {
+ if (shouldInline(cteDef, refCount)) {
if (ref.outputSet == cteDef.outputSet) {
Review comment:
why do we compare output set, not output? is it possible that the ref and def have different output column order?
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[GitHub] [spark] cloud-fan commented on a change in pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #34929:
URL: https://github.com/apache/spark/pull/34929#discussion_r779673282
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/ReplaceCTERefWithRepartition.scala
##########
@@ -0,0 +1,81 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.catalyst.optimizer
+
+import scala.collection.mutable
+
+import org.apache.spark.sql.catalyst.expressions.{Alias, SubqueryExpression}
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.catalyst.trees.TreePattern.{CTE, PLAN_EXPRESSION}
+
+/**
+ * Replaces CTE references that have not been previously inlined with [[Repartition]] operations
+ * which will then be planned as shuffles and reused across different reference points.
+ *
+ * Note that this rule should be called at the very end of the optimization phase to best guarantee
+ * that CTE repartition shuffles are reused.
+ */
+object ReplaceCTERefWithRepartition extends Rule[LogicalPlan] {
+
+ override def apply(plan: LogicalPlan): LogicalPlan = plan match {
+ case _: Subquery => plan
+ case _ =>
+ replaceWithRepartition(plan, mutable.HashMap.empty[Long, LogicalPlan])
+ }
+
+ private def replaceWithRepartition(
+ plan: LogicalPlan,
+ cteMap: mutable.HashMap[Long, LogicalPlan]): LogicalPlan = plan match {
+ case WithCTE(child, cteDefs) =>
+ cteDefs.foreach { cteDef =>
+ val inlined = replaceWithRepartition(cteDef.child, cteMap)
+ val originalPlan = cteDef.originalPlanWithPredicates.map(_._1).getOrElse(cteDef.child)
Review comment:
I think `originalPlanWithPredicates` must be none here?
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[GitHub] [spark] cloud-fan commented on a change in pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #34929:
URL: https://github.com/apache/spark/pull/34929#discussion_r779649059
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/PushdownPredicatesAndPruneColumnsForCTEDef.scala
##########
@@ -0,0 +1,171 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.catalyst.optimizer
+
+import scala.collection.mutable
+
+import org.apache.spark.sql.catalyst.expressions.{And, Attribute, AttributeSet, Expression, Literal, Or, SubqueryExpression}
+import org.apache.spark.sql.catalyst.planning.ScanOperation
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.catalyst.trees.TreePattern.CTE
+
+/**
+ * Infer predicates and column pruning for [[CTERelationDef]] from its reference points, and push
+ * the disjunctive predicates as well as the union of attributes down the CTE plan.
+ */
+object PushdownPredicatesAndPruneColumnsForCTEDef extends Rule[LogicalPlan] {
+
+ // CTE_id - (CTE_definition, precedence, predicates_to_push_down, attributes_to_prune)
+ private type CteMap = mutable.HashMap[Long, (CTERelationDef, Int, Seq[Expression], AttributeSet)]
Review comment:
nit: in other classes we always upper case CTE, how about naming it `CTEMap`?
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[GitHub] [spark] SparkQA removed a comment on pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
SparkQA removed a comment on pull request #34929:
URL: https://github.com/apache/spark/pull/34929#issuecomment-996449332
**[Test build #146315 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/146315/testReport)** for PR 34929 at commit [`841aa2a`](https://github.com/apache/spark/commit/841aa2abd7a697bc402e4321f771bf7cbba22089).
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[GitHub] [spark] cloud-fan commented on a change in pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #34929:
URL: https://github.com/apache/spark/pull/34929#discussion_r779612590
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
##########
@@ -1012,6 +1016,24 @@ class Analyzer(override val catalogManager: CatalogManager)
// inside a view maybe resolved incorrectly.
checkAnalysis(newChild)
view.copy(child = newChild)
+ case view @ View(_, _, child) =>
+ // Refresh CTE IDs in view's child that has been analyzed with a different AnalysisContext.
Review comment:
```
// This is DataFrame view, not SQL view. We need to refresh the CTE IDs in view's child,
// as it's already resolved but the CTE IDs may conflict with the main query.
```
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[GitHub] [spark] cloud-fan commented on a change in pull request #34929: [SPARK-37670][SQL] Support predicate pushdown and column pruning for de-duped CTEs
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #34929:
URL: https://github.com/apache/spark/pull/34929#discussion_r779666326
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/PushdownPredicatesAndPruneColumnsForCTEDef.scala
##########
@@ -0,0 +1,171 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.catalyst.optimizer
+
+import scala.collection.mutable
+
+import org.apache.spark.sql.catalyst.expressions.{And, Attribute, AttributeSet, Expression, Literal, Or, SubqueryExpression}
+import org.apache.spark.sql.catalyst.planning.ScanOperation
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.catalyst.trees.TreePattern.CTE
+
+/**
+ * Infer predicates and column pruning for [[CTERelationDef]] from its reference points, and push
+ * the disjunctive predicates as well as the union of attributes down the CTE plan.
+ */
+object PushdownPredicatesAndPruneColumnsForCTEDef extends Rule[LogicalPlan] {
+
+ // CTE_id - (CTE_definition, precedence, predicates_to_push_down, attributes_to_prune)
+ private type CteMap = mutable.HashMap[Long, (CTERelationDef, Int, Seq[Expression], AttributeSet)]
+
+ override def apply(plan: LogicalPlan): LogicalPlan = {
+ if (!plan.isInstanceOf[Subquery] && plan.containsPattern(CTE)) {
+ val cteMap = new CteMap
+ gatherPredicatesAndAttributes(plan, cteMap)
+ pushdownPredicatesAndAttributes(plan, cteMap)
+ } else {
+ plan
+ }
+ }
+
+ private def reverseMapExpressions(
+ input: Seq[Expression],
+ mapping: Map[Attribute, Expression]): Seq[Expression] = {
+ input.map(e => e.transform {
+ case a: Attribute =>
+ mapping.keys.find(_.semanticEquals(a)).map(mapping).getOrElse(a)
+ })
+ }
+
+ /**
+ * Gather all the predicates and referenced attributes on different points of CTE references
+ * using pattern `ScanOperation` (which takes care of determinism) and combine those predicates
+ * and attributes that belong to the same CTE definition.
+ * For the same CTE definition, if any of its references does not have predicates, the combined
+ * predicate will be a TRUE literal, which means there will be no predicate push-down.
+ */
+ private def gatherPredicatesAndAttributes(plan: LogicalPlan, cteMap: CteMap): Unit = {
+ plan match {
+ case WithCTE(child, cteDefs) =>
+ cteDefs.zipWithIndex.foreach { case (cteDef, precedence) =>
+ gatherPredicatesAndAttributes(cteDef.child, cteMap)
+ cteMap.put(cteDef.id, (cteDef, precedence, Seq.empty, AttributeSet.empty))
+ }
+ gatherPredicatesAndAttributes(child, cteMap)
+
+ case ScanOperation(projects, predicates, ref: CTERelationRef) =>
+ val (cteDef, precedence, preds, attrs) = cteMap(ref.cteId)
+ val mapping = ref.output.zip(cteDef.output).map{ case (r, d) => r -> d }.toMap
+ val newPredicates = if (isTruePredicate(preds)) {
+ preds
+ } else {
+ val filteredPredicates = reverseMapExpressions(predicates.filter(_.find {
+ case s: SubqueryExpression => s.plan.find {
+ case r: CTERelationRef =>
+ !cteMap.contains(r.cteId) || cteMap(r.cteId)._2 >= precedence
Review comment:
Can you add some comments to explain this condition?
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