c21 commented on a change in pull request #29804: URL: https://github.com/apache/spark/pull/29804#discussion_r496084586
########## File path: sql/core/src/main/scala/org/apache/spark/sql/execution/bucketing/DisableUnnecessaryBucketedScan.scala ########## @@ -0,0 +1,147 @@ +/* + * 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.bucketing + +import org.apache.spark.sql.catalyst.plans.physical.{ClusteredDistribution, HashClusteredDistribution} +import org.apache.spark.sql.catalyst.rules.Rule +import org.apache.spark.sql.execution.{FileSourceScanExec, FilterExec, ProjectExec, SortExec, SparkPlan} +import org.apache.spark.sql.execution.aggregate.BaseAggregateExec +import org.apache.spark.sql.execution.exchange.Exchange +import org.apache.spark.sql.internal.SQLConf + +/** + * Disable unnecessary bucketed table scan based on actual physical query plan. + * NOTE: this rule is designed to be applied right after [[EnsureRequirements]], + * where all [[ShuffleExchangeExec]] and [[SortExec]] have been added to plan properly. + * + * When BUCKETING_ENABLED and AUTO_BUCKETED_SCAN_ENABLED are set to true, go through + * query plan to check where bucketed table scan is unnecessary, and disable bucketed table + * scan if: + * + * 1.The sub-plan from the nearest downstream [[hasInterestingPartition]] operator + * to the bucketed table scan, contains only [[isAllowedUnaryExecNode]] operators + * and at least one [[Exchange]]. + * + * 2.The sub-plan from root to bucketed table scan, does not contain + * [[hasInterestingPartition]] operator. + * + * Examples: + * 1.join: + * SortMergeJoin(t1.i = t2.j) + * / \ + * Sort(i) Sort(j) + * / \ + * Shuffle(i) Scan(t2: i, j) + * / (bucketed on column j, enable bucketed scan) + * Scan(t1: i, j) + * (bucketed on column j, DISABLE bucketed scan) + * + * 2.aggregate: + * HashAggregate(i, ..., Final) + * | + * Shuffle(i) + * | + * HashAggregate(i, ..., Partial) + * | + * Filter + * | + * Scan(t1: i, j) + * (bucketed on column j, DISABLE bucketed scan) + * + * The idea of [[hasInterestingPartition]] is inspired from "interesting order" in + * the paper "Access Path Selection in a Relational Database Management System" + * (https://dl.acm.org/doi/10.1145/582095.582099). + */ +case class DisableUnnecessaryBucketedScan(conf: SQLConf) extends Rule[SparkPlan] { + + /** + * Disable bucketed table scan with pre-order traversal of plan. + * + * @param withInterestingPartition The traversed plan has operator with interesting partition. + * @param withExchange The traversed plan has [[Exchange]] operator. + * @param withAllowedNode The traversed plan has only [[isAllowedUnaryExecNode]] operators. + */ + private def disableBucketWithInterestingPartition( + plan: SparkPlan, + withInterestingPartition: Boolean, + withExchange: Boolean, + withAllowedNode: Boolean): SparkPlan = { + plan match { + case p if hasInterestingPartition(p) => + // Operator with interesting partition, propagates `withInterestingPartition` as true + // to its children, and resets `withExchange` and `withAllowedNode`. + p.mapChildren(disableBucketWithInterestingPartition(_, true, false, true)) + case exchange: Exchange => + // Exchange operator propagates `withExchange` as true to its child. + exchange.mapChildren(disableBucketWithInterestingPartition( + _, withInterestingPartition, true, withAllowedNode)) + case scan: FileSourceScanExec => + if (isBucketedScanWithoutFilter(scan)) { + if (!withInterestingPartition || (withExchange && withAllowedNode)) { + scan.copy(disableBucketedScan = true) + } else { + scan + } + } else { + scan + } + case o => + o.mapChildren(disableBucketWithInterestingPartition( + _, + withInterestingPartition, + withExchange, + withAllowedNode && isAllowedUnaryExecNode(o))) + } + } + + private def hasInterestingPartition(plan: SparkPlan): Boolean = { + plan.requiredChildDistribution.exists { + case _: ClusteredDistribution | _: HashClusteredDistribution => true + case _ => false + } + } + + private def isAllowedUnaryExecNode(plan: SparkPlan): Boolean = { Review comment: I already added a comment in last iteration. 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