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[GitHub] [spark] wangyum opened a new pull request #33914: vvvvcchhgrdnhljftuvfejeecuhiulbkginuclffteknSpark 32268 2

wangyum opened a new pull request #33914:
URL: https://github.com/apache/spark/pull/33914


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[GitHub] [spark] PengleiShi commented on a change in pull request #33914: [SPARK-32268][SQL] Dynamic bloom filter join pruning

Posted by GitBox <gi...@apache.org>.
PengleiShi commented on a change in pull request #33914:
URL: https://github.com/apache/spark/pull/33914#discussion_r733515433



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/dynamicpruning/DynamicBloomFilterPruning.scala
##########
@@ -0,0 +1,191 @@
+/*
+ * 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.execution.dynamicpruning
+
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.expressions.aggregate.BuildBloomFilter
+import org.apache.spark.sql.catalyst.optimizer.JoinSelectionHelper
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.plans.logical.statsEstimation.EstimationUtils
+import org.apache.spark.sql.catalyst.rules.Rule
+
+/**
+ * Dynamic bloom filter pruning optimization is performed based on the type and
+ * selectivity of the join operation. During query optimization, we insert a
+ * predicate on the filterable table using the filter from the other side of
+ * the join and a custom wrapper called DynamicPruning.
+ */
+object DynamicBloomFilterPruning extends Rule[LogicalPlan]
+  with PredicateHelper
+  with JoinSelectionHelper
+  with DynamicPruningHelper {
+
+  private def getFilterableTableScan(
+      exp: Expression,
+      plan: LogicalPlan): Option[LogicalPlan] = plan match {
+    case p @ Project(_, child) =>
+      getFilterableTableScan(replaceAlias(exp, getAliasMap(p)), child)
+    // we can unwrap only if there are row projections, and no aggregation operation
+    case a @ Aggregate(_, _, child) =>
+      getFilterableTableScan(replaceAlias(exp, getAliasMap(a)), child)
+    case f @ Filter(_, l: LeafNode)
+      if exp.references.subsetOf(f.outputSet) && exp.references.subsetOf(l.outputSet) =>
+      Some(f)
+    case l: LeafNode if exp.references.subsetOf(l.outputSet) =>
+      Some(l)
+    case other =>
+      other.children.flatMap {
+        child => if (exp.references.subsetOf(child.outputSet)) {
+          getFilterableTableScan(exp, child)
+        } else {
+          None
+        }
+      }.headOption
+  }
+
+  private def rowCounts(plan: LogicalPlan): BigInt = {
+    plan.stats.rowCount
+      .getOrElse(plan.stats.sizeInBytes / EstimationUtils.getSizePerRow(plan.output))
+  }
+
+  /**
+   * Insert a dynamic bloom filter pruning predicate on one side of the join using the filter on the
+   * other side of the join.
+   *  - to be able to identify this filter during query planning, we use a custom
+   *    DynamicPruning expression that wraps a regular InBloomFilter expression
+   */
+  private def insertPredicate(
+      pruningKey: Expression,
+      pruningPlan: LogicalPlan,
+      filteringKey: Expression,
+      filteringPlan: LogicalPlan,
+      joinKeys: Seq[Expression],
+      distinctCnt: Option[BigInt],
+      rowCount: BigInt): LogicalPlan = {
+    val expectedNumItems = distinctCnt.getOrElse(rowCount)
+    val coalescePartitions = math.max(math.ceil(expectedNumItems.toDouble / 4000000.0).toInt, 1)
+    // Use EnsureRequirements shuffle origin to reuse the exchange.
+    val repartition = RepartitionByExpression(joinKeys, filteringPlan,
+      optNumPartitions = Some(conf.numShufflePartitions),
+      withEnsureRequirementsShuffleOrigin = true)
+    // Coalesce partitions to improve build bloom filter performance.
+    val coalesce = Repartition(coalescePartitions, shuffle = false, repartition)
+    val bloomFilter = Aggregate(Nil,
+      Seq(BuildBloomFilter(filteringKey, expectedNumItems.toLong, distinctCnt.isEmpty, 0, 0)
+        .toAggregateExpression()).map(e => Alias(e, e.sql)()), coalesce)
+
+    Filter(
+      DynamicBloomFilterPruningSubquery(
+        pruningKey,
+        bloomFilter,
+        joinKeys,
+        joinKeys.indexOf(filteringKey)),
+      pruningPlan)
+  }
+
+  private def pruningHasBenefit(
+       filteringRowCount: BigInt,
+       filteringDistinctCnt: Option[BigInt],
+       pruningDistinctCnt: Option[BigInt],
+       pruningScan: LogicalPlan): Boolean = {
+    val filterRatio = filteringDistinctCnt
+      .flatMap(x => pruningDistinctCnt.map(x.toFloat / _.toFloat)).filter(_ < 1.0).map(1.0 - _)
+      .getOrElse(conf.dynamicPartitionPruningPruningSideExtraFilterRatio)
+    filteringRowCount.toFloat / (rowCounts(pruningScan).toFloat * filterRatio) < 0.04

Review comment:
       If `filterRatio ` uses the default value 0.04, that is `filteringRowCount` should be less than pruningRowCount * 0.04 * 0.04, could you explain the purpose?




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[GitHub] [spark] SparkQA commented on pull request #33914: [SPARK-32268][SQL] Dynamic bloom filter join pruning

Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #33914:
URL: https://github.com/apache/spark/pull/33914#issuecomment-916037369


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    * This patch passes all tests.
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[GitHub] [spark] wangyum commented on pull request #33914: [SPARK-32268][SQL] Dynamic bloom filter join pruning

Posted by GitBox <gi...@apache.org>.
wangyum commented on pull request #33914:
URL: https://github.com/apache/spark/pull/33914#issuecomment-915082161


   > I think we should probably at least have a design doc to explain this .. from a cursory look the change looks huge.
   
   I’m still doing an evaluation in our production environment, and I’ll prepare the design doc after the evaluation done.


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[GitHub] [spark] jaceklaskowski commented on a change in pull request #33914: [SPARK-32268][SQL] Dynamic bloom filter join pruning

Posted by GitBox <gi...@apache.org>.
jaceklaskowski commented on a change in pull request #33914:
URL: https://github.com/apache/spark/pull/33914#discussion_r703286889



##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
##########
@@ -353,6 +353,23 @@ object SQLConf {
       .checkValue(ratio => ratio > 0.0 && ratio <= 1.0, "The ratio value must be in (0.0, 1.0].")
       .createWithDefault(0.04)
 
+  val DYNAMIC_BLOOM_FILTER_JOIN_PRUNING_ENABLED =
+    buildConf("spark.sql.optimizer.dynamicBloomFilterJoinPruning.enabled")
+      .doc("When true, we will generate bloom filter predicate for column when it's used as join " +

Review comment:
       nit: "generates a bloom filter predicate for a join key column"

##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
##########
@@ -353,6 +353,23 @@ object SQLConf {
       .checkValue(ratio => ratio > 0.0 && ratio <= 1.0, "The ratio value must be in (0.0, 1.0].")
       .createWithDefault(0.04)
 
+  val DYNAMIC_BLOOM_FILTER_JOIN_PRUNING_ENABLED =
+    buildConf("spark.sql.optimizer.dynamicBloomFilterJoinPruning.enabled")
+      .doc("When true, we will generate bloom filter predicate for column when it's used as join " +
+        "key. Note that, dynamic bloom filter join pruning only works if exchange reuse enabled.")
+      .version("3.3.0")
+      .booleanConf
+      .createWithDefault(true)
+
+  val DYNAMIC_BLOOM_FILTER_JOIN_PRUNING_MAX_BLOOM_FILTER_ENTRIES =
+    buildConf("spark.sql.optimizer.dynamicBloomFilterJoinPruning.maxBloomFilterEntries")
+      .doc("The maximum number of bloom filter entries allowed when building dynamic bloom filter" +

Review comment:
       nit: s/when building/for

##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
##########
@@ -353,6 +353,23 @@ object SQLConf {
       .checkValue(ratio => ratio > 0.0 && ratio <= 1.0, "The ratio value must be in (0.0, 1.0].")
       .createWithDefault(0.04)
 
+  val DYNAMIC_BLOOM_FILTER_JOIN_PRUNING_ENABLED =
+    buildConf("spark.sql.optimizer.dynamicBloomFilterJoinPruning.enabled")
+      .doc("When true, we will generate bloom filter predicate for column when it's used as join " +
+        "key. Note that, dynamic bloom filter join pruning only works if exchange reuse enabled.")

Review comment:
       Use the config property so it becomes `s"only works with ${SQLConf.EXCHANGE_REUSE_ENABLED.key} enabled"`




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[GitHub] [spark] SparkQA commented on pull request #33914: [SPARK-32268][SQL] Dynamic bloom filter join pruning

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    * This patch passes all tests.
    * This patch merges cleanly.
    * This patch adds no public classes.


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[GitHub] [spark] HyukjinKwon commented on pull request #33914: [SPARK-32268][SQL] Dynamic bloom filter join pruning

Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #33914:
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   I think we should probably at least have a design doc to explain this .. from a cursory look the change looks huge.


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[GitHub] [spark] wangyum commented on pull request #33914: [SPARK-32268][SQL] Dynamic bloom filter join pruning

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wangyum commented on pull request #33914:
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   Example of TPC-DS q37.
   
   Before this PR | After this PR
   --- | ---
   ![image](https://user-images.githubusercontent.com/5399861/132122605-0b4e9972-0c03-4a0d-ab8c-27b30eb67b94.png) | ![image](https://user-images.githubusercontent.com/5399861/132122644-3718416b-49bf-4765-8adb-48256fc3bd81.png)
   
   


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wangyum edited a comment on pull request #33914:
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   Example of TPC-DS q37.
   
   Before this PR | After this PR
   --- | ---
   ![image](https://user-images.githubusercontent.com/5399861/132122605-0b4e9972-0c03-4a0d-ab8c-27b30eb67b94.png) | ![image](https://user-images.githubusercontent.com/5399861/132122644-3718416b-49bf-4765-8adb-48256fc3bd81.png)
   
   
   Real case from cluster:
   
   Before this PR | After this PR
   --- | ---
   ![image](https://user-images.githubusercontent.com/5399861/132151002-fa12614c-aa7a-4d4e-814b-c1a92234d234.png) | ![image](https://user-images.githubusercontent.com/5399861/132150972-de6fe669-8a99-46ed-ab1a-7812f2de5af7.png)
   
   
   
   
   


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[GitHub] [spark] wangyum commented on a change in pull request #33914: [SPARK-32268][SQL] Dynamic bloom filter join pruning

Posted by GitBox <gi...@apache.org>.
wangyum commented on a change in pull request #33914:
URL: https://github.com/apache/spark/pull/33914#discussion_r704250838



##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
##########
@@ -353,6 +353,23 @@ object SQLConf {
       .checkValue(ratio => ratio > 0.0 && ratio <= 1.0, "The ratio value must be in (0.0, 1.0].")
       .createWithDefault(0.04)
 
+  val DYNAMIC_BLOOM_FILTER_JOIN_PRUNING_ENABLED =
+    buildConf("spark.sql.optimizer.dynamicBloomFilterJoinPruning.enabled")
+      .doc("When true, we will generate bloom filter predicate for column when it's used as join " +

Review comment:
       Thank you @jaceklaskowski 




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[GitHub] [spark] PengleiShi commented on a change in pull request #33914: [SPARK-32268][SQL] Dynamic bloom filter join pruning

Posted by GitBox <gi...@apache.org>.
PengleiShi commented on a change in pull request #33914:
URL: https://github.com/apache/spark/pull/33914#discussion_r733515433



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/dynamicpruning/DynamicBloomFilterPruning.scala
##########
@@ -0,0 +1,191 @@
+/*
+ * 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.execution.dynamicpruning
+
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.expressions.aggregate.BuildBloomFilter
+import org.apache.spark.sql.catalyst.optimizer.JoinSelectionHelper
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.plans.logical.statsEstimation.EstimationUtils
+import org.apache.spark.sql.catalyst.rules.Rule
+
+/**
+ * Dynamic bloom filter pruning optimization is performed based on the type and
+ * selectivity of the join operation. During query optimization, we insert a
+ * predicate on the filterable table using the filter from the other side of
+ * the join and a custom wrapper called DynamicPruning.
+ */
+object DynamicBloomFilterPruning extends Rule[LogicalPlan]
+  with PredicateHelper
+  with JoinSelectionHelper
+  with DynamicPruningHelper {
+
+  private def getFilterableTableScan(
+      exp: Expression,
+      plan: LogicalPlan): Option[LogicalPlan] = plan match {
+    case p @ Project(_, child) =>
+      getFilterableTableScan(replaceAlias(exp, getAliasMap(p)), child)
+    // we can unwrap only if there are row projections, and no aggregation operation
+    case a @ Aggregate(_, _, child) =>
+      getFilterableTableScan(replaceAlias(exp, getAliasMap(a)), child)
+    case f @ Filter(_, l: LeafNode)
+      if exp.references.subsetOf(f.outputSet) && exp.references.subsetOf(l.outputSet) =>
+      Some(f)
+    case l: LeafNode if exp.references.subsetOf(l.outputSet) =>
+      Some(l)
+    case other =>
+      other.children.flatMap {
+        child => if (exp.references.subsetOf(child.outputSet)) {
+          getFilterableTableScan(exp, child)
+        } else {
+          None
+        }
+      }.headOption
+  }
+
+  private def rowCounts(plan: LogicalPlan): BigInt = {
+    plan.stats.rowCount
+      .getOrElse(plan.stats.sizeInBytes / EstimationUtils.getSizePerRow(plan.output))
+  }
+
+  /**
+   * Insert a dynamic bloom filter pruning predicate on one side of the join using the filter on the
+   * other side of the join.
+   *  - to be able to identify this filter during query planning, we use a custom
+   *    DynamicPruning expression that wraps a regular InBloomFilter expression
+   */
+  private def insertPredicate(
+      pruningKey: Expression,
+      pruningPlan: LogicalPlan,
+      filteringKey: Expression,
+      filteringPlan: LogicalPlan,
+      joinKeys: Seq[Expression],
+      distinctCnt: Option[BigInt],
+      rowCount: BigInt): LogicalPlan = {
+    val expectedNumItems = distinctCnt.getOrElse(rowCount)
+    val coalescePartitions = math.max(math.ceil(expectedNumItems.toDouble / 4000000.0).toInt, 1)
+    // Use EnsureRequirements shuffle origin to reuse the exchange.
+    val repartition = RepartitionByExpression(joinKeys, filteringPlan,
+      optNumPartitions = Some(conf.numShufflePartitions),
+      withEnsureRequirementsShuffleOrigin = true)
+    // Coalesce partitions to improve build bloom filter performance.
+    val coalesce = Repartition(coalescePartitions, shuffle = false, repartition)
+    val bloomFilter = Aggregate(Nil,
+      Seq(BuildBloomFilter(filteringKey, expectedNumItems.toLong, distinctCnt.isEmpty, 0, 0)
+        .toAggregateExpression()).map(e => Alias(e, e.sql)()), coalesce)
+
+    Filter(
+      DynamicBloomFilterPruningSubquery(
+        pruningKey,
+        bloomFilter,
+        joinKeys,
+        joinKeys.indexOf(filteringKey)),
+      pruningPlan)
+  }
+
+  private def pruningHasBenefit(
+       filteringRowCount: BigInt,
+       filteringDistinctCnt: Option[BigInt],
+       pruningDistinctCnt: Option[BigInt],
+       pruningScan: LogicalPlan): Boolean = {
+    val filterRatio = filteringDistinctCnt
+      .flatMap(x => pruningDistinctCnt.map(x.toFloat / _.toFloat)).filter(_ < 1.0).map(1.0 - _)
+      .getOrElse(conf.dynamicPartitionPruningPruningSideExtraFilterRatio)
+    filteringRowCount.toFloat / (rowCounts(pruningScan).toFloat * filterRatio) < 0.04

Review comment:
       If `filterRatio ` uses the default value 0.04, that is `filteringRowCount` should be less than pruningRowCount * 0.04 * 0.04, could you explain the purpose?




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[GitHub] [spark] wangyum commented on a change in pull request #33914: [SPARK-32268][SQL] Dynamic bloom filter join pruning

Posted by GitBox <gi...@apache.org>.
wangyum commented on a change in pull request #33914:
URL: https://github.com/apache/spark/pull/33914#discussion_r704258121



##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
##########
@@ -353,6 +353,23 @@ object SQLConf {
       .checkValue(ratio => ratio > 0.0 && ratio <= 1.0, "The ratio value must be in (0.0, 1.0].")
       .createWithDefault(0.04)
 
+  val DYNAMIC_BLOOM_FILTER_JOIN_PRUNING_ENABLED =
+    buildConf("spark.sql.optimizer.dynamicBloomFilterJoinPruning.enabled")
+      .doc("When true, we will generate bloom filter predicate for column when it's used as join " +
+        "key. Note that, dynamic bloom filter join pruning only works if exchange reuse enabled.")

Review comment:
       Fixed.




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[GitHub] [spark] wangyum commented on a change in pull request #33914: [SPARK-32268][SQL] Dynamic bloom filter join pruning

Posted by GitBox <gi...@apache.org>.
wangyum commented on a change in pull request #33914:
URL: https://github.com/apache/spark/pull/33914#discussion_r704260274



##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
##########
@@ -353,6 +353,23 @@ object SQLConf {
       .checkValue(ratio => ratio > 0.0 && ratio <= 1.0, "The ratio value must be in (0.0, 1.0].")
       .createWithDefault(0.04)
 
+  val DYNAMIC_BLOOM_FILTER_JOIN_PRUNING_ENABLED =
+    buildConf("spark.sql.optimizer.dynamicBloomFilterJoinPruning.enabled")
+      .doc("When true, we will generate bloom filter predicate for column when it's used as join " +
+        "key. Note that, dynamic bloom filter join pruning only works if exchange reuse enabled.")
+      .version("3.3.0")
+      .booleanConf
+      .createWithDefault(true)
+
+  val DYNAMIC_BLOOM_FILTER_JOIN_PRUNING_MAX_BLOOM_FILTER_ENTRIES =
+    buildConf("spark.sql.optimizer.dynamicBloomFilterJoinPruning.maxBloomFilterEntries")
+      .doc("The maximum number of bloom filter entries allowed when building dynamic bloom filter" +

Review comment:
       Fixed.




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