ulysses-you commented on code in PR #57181: URL: https://github.com/apache/spark/pull/57181#discussion_r3568249515
########## sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/ReplaceSortMergeJoinToShuffledHashJoin.scala: ########## @@ -0,0 +1,132 @@ +/* + * 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.adaptive + +import scala.annotation.tailrec + +import org.apache.spark.sql.catalyst.optimizer.{BuildLeft, BuildRight, BuildSide, JoinSelectionHelper} +import org.apache.spark.sql.catalyst.plans.LeftExistence +import org.apache.spark.sql.catalyst.rules.Rule +import org.apache.spark.sql.execution.{FilterExec, ProjectExec, SortExec, SparkPlan} +import org.apache.spark.sql.execution.aggregate.BaseAggregateExec +import org.apache.spark.sql.execution.exchange.{ENSURE_REQUIREMENTS, EnsureRequirements} +import org.apache.spark.sql.execution.joins.{BaseJoinExec, ShuffledHashJoinExec, SortMergeJoinExec} +import org.apache.spark.sql.execution.window.{WindowExecBase, WindowGroupLimitExec} + +/** + * Converts a [[SortMergeJoinExec]] into a [[ShuffledHashJoinExec]] during adaptive execution when + * a build side's materialized shuffle statistics show it is small enough for a local hash map. + * Unlike [[DynamicJoinSelection]], this runs on the physical plan, so it can reach the input + * shuffle through operators (aggregate, project, filter, window, etc...) sitting above it. + * + * The swap is shuffle-free since both joins are `ShuffledJoin`s with the same distribution and + * partitioning; only the child sorts become unnecessary. As a shuffled hash join loses the sort + * merge join's output ordering, [[EnsureRequirements]] is re-run to restore any ordering an + * ancestor still needs, and AQE's [[CostEvaluator]] decides whether to adopt the converted plan. + */ +case class ReplaceSortMergeJoinToShuffledHashJoin(ensureRequirements: EnsureRequirements) + extends Rule[SparkPlan] with JoinSelectionHelper { + + /** + * Chooses the build side for the shuffled hash join. A side is eligible only if it is allowed + * as a build side for this join type and its input shuffle is small enough to build a local + * hash map. When both sides are eligible, the smaller one (by total shuffle bytes) is chosen. + */ + private def selectBuildSide( + smj: SortMergeJoinExec, + left: ShuffleQueryStageExec, + right: ShuffleQueryStageExec): Option[BuildSide] = { + val canBuildLeft = canBuildShuffledHashJoinLeft(smj.joinType) && + preferShuffledHashJoin(left.mapStats.get) + val canBuildRight = canBuildShuffledHashJoinRight(smj.joinType) && + preferShuffledHashJoin(right.mapStats.get) + if (canBuildLeft && canBuildRight) { + if (left.mapStats.get.bytesByPartitionId.sum < right.mapStats.get.bytesByPartitionId.sum) { + Some(BuildLeft) + } else { + Some(BuildRight) + } + } else if (canBuildLeft) { + Some(BuildLeft) + } else if (canBuildRight) { + Some(BuildRight) + } else { + None + } + } + + override def apply(plan: SparkPlan): SparkPlan = { + if (!conf.convertSortMergeJoinToShuffledHashJoinEnabled) { + return plan + } + val optimizedPlan = plan.transformUp { + case smj @ SortMergeJoinExec(leftKeys, rightKeys, joinType, condition, + ExtractShuffleStage(left), ExtractShuffleStage(right), false) => + selectBuildSide(smj, left, right) match { + case Some(buildSide) => + ShuffledHashJoinExec(leftKeys, rightKeys, joinType, buildSide, condition, + stripSort(smj.left), stripSort(smj.right)) + case None => smj + } + } + if (optimizedPlan.fastEquals(plan)) { + plan + } else { + // A shuffled hash join does not preserve the sort merge join's output ordering. Re-run + // EnsureRequirements so any ordering an ancestor still needs is re-established, keeping the + // plan valid. AQE's CostEvaluator then decides between this plan and the current one. + ensureRequirements.apply(optimizedPlan) + } + } + + /** + * Drops a top-level [[SortExec]] since a shuffled hash join does not require sorted input; + * [[RemoveRedundantSorts]] cleans up any remaining redundant sorts afterwards. + */ + private def stripSort(plan: SparkPlan): SparkPlan = plan match { + case s: SortExec => s.child + case other => other + } + + /** + * Finds a join child's input shuffle, looking through the [[SortExec]] and other non-shuffle, + * non-data-inflating operators (aggregate, project, filter, window, left-existence join) above + * it. Descent stops at the first [[ShuffleQueryStageExec]], which is thus guaranteed to be the + * join's own input shuffle whose statistics bound (or, for a reducing aggregate, upper-bound) + * the build side. The stage must be materialized with stats and originate from + * [[EnsureRequirements]], so swapping the join type does not change the shuffle. + */ + object ExtractShuffleStage { + def unapply(plan: SparkPlan): Option[ShuffleQueryStageExec] = findShuffleStage(plan) + + @tailrec + private def findShuffleStage(plan: SparkPlan): Option[ShuffleQueryStageExec] = plan match { + case s: ShuffleQueryStageExec if s.isMaterialized && s.mapStats.isDefined && + s.shuffle.shuffleOrigin == ENSURE_REQUIREMENTS => Some(s) + case _: ProjectExec | _: FilterExec | _: SortExec | _: BaseAggregateExec | _: WindowExecBase | Review Comment: Addressed. The traversal now only looks through `Project`/`Aggregate`/`Window` when every output expression is size-bounded (`isSizeBoundedExpr`: attributes, fixed-width values, `cast`, and length-non-increasing string transforms) - a value-synthesizing expression like `repeat(max(c2), 10000)` stops the descent, so it can no longer build an `UnsafeHashedRelation` from widened rows. On top of that, the build-side estimate is scaled by a per-row widening factor (`getSizePerRow(buildOutput) / getSizePerRow(shuffleOutput)`), floored by the new `spark.sql.adaptive.convertSortMergeJoinToShuffledHashJoin.minWideningFactor` (default 1.0) so users can be more conservative. Added a widening-aggregate regression test (`repeat(max(c2), 500)` stays SMJ) and a size-bounded-operator test (`max`/`cast`/`substring` still convert). -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. 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