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Support coalesce table cache stage partitions
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76 changes: 76 additions & 0 deletions
76
sql/core/src/main/scala/org/apache/spark/sql/execution/CachedRDD.scala
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| /* | ||
| * 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 | ||
|
|
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| import scala.reflect.ClassTag | ||
|
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| import org.apache.spark.{Dependency, NarrowDependency, Partition, TaskContext} | ||
| import org.apache.spark.rdd.RDD | ||
|
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| /** | ||
| * The [[Partition]] used by [[CachedRDD]]. | ||
| */ | ||
| case class CachedRDDPartition( | ||
| index: Int, | ||
| originalPartitions: Array[Partition], | ||
| @transient originalPreferredLocations: Seq[String]) extends Partition | ||
|
|
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| /** | ||
| * It wraps the real cached RDD with coalesced partitions. | ||
| * | ||
| * @param prev The real cached RDD | ||
| * @param partitionSpecs the coalesced partitions | ||
| */ | ||
| class CachedRDD[T: ClassTag]( | ||
| @transient var prev: RDD[T], | ||
| partitionSpecs: Seq[CoalescedPartitionSpec]) | ||
| extends RDD[T](prev.context, Nil) { // Nil since we implement getDependencies | ||
|
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| override protected def getPartitions: Array[Partition] = { | ||
| Array.tabulate[Partition](partitionSpecs.length) { i => | ||
| val spec = partitionSpecs(i) | ||
| val originalPartitions = spec.startReducerIndex.until(spec.endReducerIndex) | ||
| .map(prev.partitions).toArray | ||
| val originalPreferredLocations = originalPartitions.flatMap(prev.preferredLocations) | ||
| .distinct.toSeq | ||
| CachedRDDPartition(i, originalPartitions, originalPreferredLocations) | ||
| } | ||
| } | ||
|
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| override protected def getPreferredLocations(split: Partition): Seq[String] = { | ||
| split.asInstanceOf[CachedRDDPartition].originalPreferredLocations | ||
| } | ||
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| override def compute(split: Partition, context: TaskContext): Iterator[T] = { | ||
| split.asInstanceOf[CachedRDDPartition].originalPartitions.iterator.flatMap { partition => | ||
| firstParent[T].iterator(partition, context) | ||
| } | ||
| } | ||
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| override def getDependencies: Seq[Dependency[_]] = { | ||
| Seq(new NarrowDependency(prev) { | ||
| def getParents(id: Int): Seq[Int] = | ||
| partitions(id).asInstanceOf[CachedRDDPartition].originalPartitions.map(_.index).toSeq | ||
| }) | ||
| } | ||
|
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| override def clearDependencies(): Unit = { | ||
| super.clearDependencies() | ||
| prev = null | ||
| } | ||
| } |
71 changes: 71 additions & 0 deletions
71
sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/AQECacheReadExec.scala
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,71 @@ | ||
| /* | ||
| * 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. | ||
| */ | ||
|
|
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| package org.apache.spark.sql.execution.adaptive | ||
|
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| import org.apache.spark.rdd.RDD | ||
| import org.apache.spark.sql.catalyst.InternalRow | ||
| import org.apache.spark.sql.catalyst.plans.physical.Partitioning | ||
| import org.apache.spark.sql.execution.{CachedRDD, CoalescedPartitionSpec, ShufflePartitionSpec, SparkPlan, SQLExecution} | ||
| import org.apache.spark.sql.execution.metric.{SQLMetric, SQLMetrics} | ||
| import org.apache.spark.sql.vectorized.ColumnarBatch | ||
|
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| /** | ||
| * A wrapper of table cache query stage, which follows the given partition arrangement. | ||
| * The RDD cache block is based on partition level, so we can not split the partition if it's | ||
| * skewed. When [[AQECacheReadExec]] happen that means there are some partitions can be coalesced. | ||
| * | ||
| * @param child It should always be [[TableCacheQueryStageExec]]. | ||
| * @param partitionSpecs The partition specs that defines the arrangement, requires at least one | ||
| * partition. | ||
| */ | ||
| case class AQECacheReadExec( | ||
| child: SparkPlan, | ||
| partitionSpecs: Seq[ShufflePartitionSpec]) extends AQERead { | ||
| assert(partitionSpecs.forall(_.isInstanceOf[CoalescedPartitionSpec])) | ||
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| override def outputPartitioning: Partitioning = { | ||
| outputPartitionWithCoalesced(partitionSpecs.length) | ||
| } | ||
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| override lazy val metrics: Map[String, SQLMetric] = | ||
| Map("numPartitions" -> SQLMetrics.createMetric(sparkContext, "number of partitions")) | ||
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| private def updateMetrics(): Unit = { | ||
| metrics("numPartitions") += partitionSpecs.length | ||
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| val executionId = sparkContext.getLocalProperty(SQLExecution.EXECUTION_ID_KEY) | ||
| SQLMetrics.postDriverMetricUpdates(sparkContext, executionId, metrics.values.toSeq) | ||
| } | ||
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| override def stringArgs: Iterator[Any] = Iterator("coalesced") | ||
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| override protected def doExecute(): RDD[InternalRow] = { | ||
| updateMetrics() | ||
| val rdd = child.execute() | ||
| new CachedRDD(rdd, partitionSpecs.asInstanceOf[Seq[CoalescedPartitionSpec]]) | ||
| } | ||
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| override protected def doExecuteColumnar(): RDD[ColumnarBatch] = { | ||
| updateMetrics() | ||
| val rdd = child.executeColumnar() | ||
| new CachedRDD(rdd, partitionSpecs.asInstanceOf[Seq[CoalescedPartitionSpec]]) | ||
| } | ||
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| override protected def withNewChildInternal(newChild: SparkPlan): SparkPlan = | ||
| copy(child = newChild) | ||
| } |
57 changes: 57 additions & 0 deletions
57
sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/AQERead.scala
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,57 @@ | ||
| /* | ||
| * 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. | ||
| */ | ||
|
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| package org.apache.spark.sql.execution.adaptive | ||
|
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| import org.apache.spark.sql.catalyst.expressions.Attribute | ||
| import org.apache.spark.sql.catalyst.plans.physical.{HashPartitioning, Partitioning, RangePartitioning, RoundRobinPartitioning, SinglePartition, UnknownPartitioning} | ||
| import org.apache.spark.sql.catalyst.trees.CurrentOrigin | ||
| import org.apache.spark.sql.execution.{ShufflePartitionSpec, SparkPlan, UnaryExecNode} | ||
|
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| abstract class AQERead extends UnaryExecNode { | ||
| def child: SparkPlan | ||
| def partitionSpecs: Seq[ShufflePartitionSpec] | ||
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| assert(partitionSpecs.nonEmpty, s"${getClass.getSimpleName} requires at least one partition") | ||
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| override final def output: Seq[Attribute] = child.output | ||
| override final def supportsColumnar: Boolean = child.supportsColumnar | ||
| override final def supportsRowBased: Boolean = child.supportsRowBased | ||
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| def outputPartitionWithCoalesced(numPartitions: Int): Partitioning = { | ||
| // For coalesced shuffle read, the data distribution is not changed, only the number of | ||
| // partitions is changed. | ||
| child.outputPartitioning match { | ||
| case h: HashPartitioning => | ||
| CurrentOrigin.withOrigin(h.origin)(h.copy(numPartitions = numPartitions)) | ||
| case r: RangePartitioning => | ||
| CurrentOrigin.withOrigin(r.origin)(r.copy(numPartitions = numPartitions)) | ||
| // This can only happen for `REBALANCE_PARTITIONS_BY_NONE`, which uses | ||
| // `RoundRobinPartitioning` but we don't need to retain the number of partitions. | ||
| case r: RoundRobinPartitioning => | ||
| r.copy(numPartitions = numPartitions) | ||
| case other@SinglePartition => | ||
| throw new IllegalStateException( | ||
| "Unexpected partitioning for coalesced shuffle read: " + other) | ||
| case _ => | ||
| // Spark plugins may have custom partitioning and may replace this operator | ||
| // during the postStageOptimization phase, so return UnknownPartitioning here | ||
| // rather than throw an exception | ||
| UnknownPartitioning(numPartitions) | ||
| } | ||
| } | ||
| } |
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76 changes: 76 additions & 0 deletions
76
...core/src/main/scala/org/apache/spark/sql/execution/adaptive/CoalesceCachePartitions.scala
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,76 @@ | ||
| /* | ||
| * 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. | ||
| */ | ||
|
|
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| package org.apache.spark.sql.execution.adaptive | ||
|
|
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| import org.apache.spark.sql.SparkSession | ||
| import org.apache.spark.sql.catalyst.rules.Rule | ||
| import org.apache.spark.sql.execution.{ShufflePartitionSpec, SparkPlan, UnaryExecNode, UnionExec} | ||
| import org.apache.spark.sql.internal.SQLConf | ||
|
|
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| /** | ||
| * A rule to coalesce the cache partitions based on the statistics, which can | ||
| * avoid many small reduce tasks that hurt performance. | ||
| */ | ||
| case class CoalesceCachePartitions(session: SparkSession) extends Rule[SparkPlan] { | ||
| override def apply(plan: SparkPlan): SparkPlan = { | ||
| if (!conf.getConf(SQLConf.COALESCE_CACHE_PARTITIONS_ENABLED)) { | ||
| return plan | ||
| } | ||
|
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| val coalesceGroups = collectCoalesceGroups(plan) | ||
| val groups = coalesceGroups.map { tableCacheStages => | ||
| val stageIds = tableCacheStages.map(_.id) | ||
| val bytesByPartitionIds = tableCacheStages.map(_.outputStats().map(_.bytesByPartitionId)) | ||
| val inputPartitionSpecs = Seq.fill(bytesByPartitionIds.length)(None) | ||
| (tableCacheStages.map(_.id), | ||
| conf.getConf(SQLConf.ADVISORY_PARTITION_SIZE_IN_BYTES), | ||
| bytesByPartitionIds, | ||
| inputPartitionSpecs, | ||
| s"For table cache stage(${stageIds.mkString(", ")})") | ||
| } | ||
| val specsMap = ShufflePartitionsUtil.coalescePartitionsByGroup( | ||
| groups, session.sparkContext.defaultParallelism) | ||
| if (specsMap.nonEmpty) { | ||
| updateCacheReads(plan, specsMap) | ||
| } else { | ||
| plan | ||
| } | ||
| } | ||
|
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| private def updateCacheReads( | ||
| plan: SparkPlan, | ||
| specsMap: Map[Int, Seq[ShufflePartitionSpec]]): SparkPlan = plan match { | ||
| case stage: TableCacheQueryStageExec if specsMap.contains(stage.id) => | ||
| AQECacheReadExec(stage, specsMap(stage.id)) | ||
| case other => other.mapChildren(updateCacheReads(_, specsMap)) | ||
| } | ||
|
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| private def collectCoalesceGroups( | ||
| plan: SparkPlan): Seq[Seq[TableCacheQueryStageExec]] = plan match { | ||
| case unary: UnaryExecNode => collectCoalesceGroups(unary.child) | ||
| case union: UnionExec => union.children.flatMap(collectCoalesceGroups) | ||
| case p if p.collectLeaves().forall(_.isInstanceOf[TableCacheQueryStageExec]) => | ||
| collectTableCacheStages(p) :: Nil | ||
| case _ => Seq.empty | ||
| } | ||
|
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| private def collectTableCacheStages(plan: SparkPlan): Seq[TableCacheQueryStageExec] = plan match { | ||
| case tableCacheStage: TableCacheQueryStageExec => Seq(tableCacheStage) | ||
| case _ => plan.children.flatMap(collectTableCacheStages) | ||
| } | ||
| } |
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