dwsmith1983 commented on code in PR #6785: URL: https://github.com/apache/datafusion-comet/pull/6785#discussion_r4371595549
########## spark/src/main/scala/org/apache/comet/rules/CometShuffledHashJoinStrategy.scala: ########## @@ -0,0 +1,175 @@ +/* + * 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.comet.rules + +import org.apache.spark.sql.SparkSession +import org.apache.spark.sql.catalyst.expressions.RowOrdering +import org.apache.spark.sql.catalyst.optimizer.{BuildLeft, BuildRight, BuildSide} +import org.apache.spark.sql.catalyst.planning.ExtractEquiJoinKeys +import org.apache.spark.sql.catalyst.plans.{ExistenceJoin, LeftSemi} +import org.apache.spark.sql.catalyst.plans.logical.{Join, JoinHint, JoinStrategyHint, LogicalPlan} +import org.apache.spark.sql.execution.{SparkPlan, SparkStrategy} +import org.apache.spark.sql.execution.adaptive.{BroadcastQueryStageExec, LogicalQueryStage} +import org.apache.spark.sql.execution.joins.{ShuffledHashJoinExec, SortMergeJoinExec} +import org.apache.spark.sql.internal.SQLConf + +import org.apache.comet.CometConf +import org.apache.comet.CometSparkSessionExtensions.{isCometLoaded, withFallbackReason, withInfo} +import org.apache.comet.shims.ShimJoinSelection + +/** + * Plans a ShuffledHashJoinExec in place of a SortMergeJoinExec, before EnsureRequirements and + * RemoveRedundantSorts, so the sorts above the join survive. Adapted from Apache Gluten. + */ +case class CometShuffledHashJoinStrategy(session: SparkSession) + extends SparkStrategy + with ShimJoinSelection { + + override def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { + case join: Join if isEnabled(join) => planJoin(join) + case _ => Nil + } + + private def sqlConf: SQLConf = session.sessionState.conf + + // Planner strategies run with Comet off and before CometRule, which applies plan-only mode. + private def isEnabled(join: Join): Boolean = + CometConf.COMET_FORCE_SHJ.get(sqlConf) && + CometConf.COMET_EXEC_ENABLED.get(sqlConf) && + !CometConf.COMET_EXPLAIN_PLAN_ONLY_ENABLED.get(sqlConf) && + !join.isStreaming && + isCometLoaded(sqlConf) + + private def planJoin(join: Join): Seq[SparkPlan] = join match { + case ExtractEquiJoinKeys(joinType, leftKeys, rightKeys, condition, _, left, right, hint) + if !isLeftToSpark(join, hint) && canSortMergeJoin(joinType) && + RowOrdering.isOrderable(leftKeys) && hashJoinSupportedShim(leftKeys, rightKeys) => + buildSide(join) match { + case Some(BuildRight) if joinType == LeftSemi || joinType.isInstanceOf[ExistenceJoin] => + // LeftSemi https://github.com/apache/datafusion-comet/issues/2667 + // ExistenceJoin https://github.com/apache/datafusion-comet/issues/2697 + planBySpark(join) { smj => + withFallbackReason(smj, declineReason(s"BuildRight with $joinType is not supported")) + } + case Some(side) => + buildSideOverLimit(join, side) match { + case Some(reason) => + // Not a fallback: the kept sort-merge join still runs natively. + planBySpark(join)(smj => withInfo(smj, declineReason(reason))) + case None => + Seq( + ShuffledHashJoinExec( Review Comment: The nested loop join is the part that loses the order, and main has the same problem: your query with `SHUFFLE_HASH(b)` or `BROADCAST(b)` on the outer join, or the nested loop join alone under `ORDER BY x`, comes back out of order there too (#6898). Spark's `BroadcastNestedLoopJoinExec` keeps its streamed side's order and reports it, while DataFusion's emits its rows build row by build row. `CometBroadcastNestedLoopJoinExec` now stays in Spark whenever Spark reports an output order for the join, so the sort Spark drops is no longer needed. That fixes #6898 as well. `BroadcastNestedLoopJoin over an ordered streamed side falls back and keeps its order` in `CometJoinSuite` runs your query with forcing on, the two hinted variants, and the nested loop join alone under `ORDER BY x`, and checks that the rows come back sorted. -- 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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