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...ala/org/apache/paimon/spark/execution/adaptive/DisableUnnecessaryPaimonBucketedScan.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. | ||
| */ | ||
|
|
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| package org.apache.paimon.spark.execution.adaptive | ||
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| import org.apache.paimon.spark.PaimonScan | ||
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| import org.apache.spark.sql.catalyst.plans.physical.{AllTuples, ClusteredDistribution} | ||
| import org.apache.spark.sql.catalyst.rules.Rule | ||
| import org.apache.spark.sql.execution._ | ||
| import org.apache.spark.sql.execution.aggregate.BaseAggregateExec | ||
| import org.apache.spark.sql.execution.datasources.v2.BatchScanExec | ||
| import org.apache.spark.sql.execution.exchange.{Exchange, ShuffleExchangeLike} | ||
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| // spotless:off | ||
| /** | ||
| * This rule is inspired from Spark [[DisableUnnecessaryBucketedScan]] but work for v2 scan. | ||
| * | ||
| * Disable unnecessary bucketed table scan based on actual physical query plan. | ||
| * NOTE: this rule is designed to be applied right after [[EnsureRequirements]], | ||
| * where all [[ShuffleExchangeLike]] 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 root to bucketed table scan, does not contain | ||
| * [[hasInterestingPartition]] operator. | ||
| * | ||
| * 2. The sub-plan from the nearest downstream [[hasInterestingPartition]] operator | ||
| * to the bucketed table scan and at least one [[ShuffleExchangeLike]]. | ||
| * | ||
| * Examples: | ||
| * 1. no [[hasInterestingPartition]] operator: | ||
| * Project | ||
| * | | ||
| * Filter | ||
| * | | ||
| * Scan(t1: i, j) | ||
| * (bucketed on column j, DISABLE bucketed scan) | ||
| * | ||
| * 2. 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) | ||
| * | ||
| * 3. 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). | ||
| */ | ||
| // spotless:on | ||
| object DisableUnnecessaryPaimonBucketedScan extends Rule[SparkPlan] { | ||
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| /** | ||
| * Disable bucketed table scan with pre-order traversal of plan. | ||
| * | ||
| * @param hashInterestingPartition | ||
| * The traversed plan has operator with interesting partition. | ||
| * @param hasExchange | ||
| * The traversed plan has [[Exchange]] operator. | ||
| */ | ||
| private def disableBucketScan( | ||
| plan: SparkPlan, | ||
| hashInterestingPartition: Boolean, | ||
| hasExchange: Boolean): SparkPlan = { | ||
| plan match { | ||
| case p if hasInterestingPartition(p) => | ||
| // Operator with interesting partition, propagates `hashInterestingPartition` as true | ||
| // to its children, and resets `hasExchange`. | ||
| p.mapChildren(disableBucketScan(_, hashInterestingPartition = true, hasExchange = false)) | ||
| case exchange: ShuffleExchangeLike => | ||
| // Exchange operator propagates `hasExchange` as true to its child. | ||
| exchange.mapChildren(disableBucketScan(_, hashInterestingPartition, hasExchange = true)) | ||
| case batch: BatchScanExec => | ||
| val paimonBucketedScan = extractPaimonBucketedScan(batch) | ||
| if (paimonBucketedScan.isDefined && (!hashInterestingPartition || hasExchange)) { | ||
| val (batch, paimonScan) = paimonBucketedScan.get | ||
| val newBatch = batch.copy(scan = paimonScan.withDisabledBucketedScan()) | ||
| newBatch.copyTagsFrom(batch) | ||
| newBatch | ||
| } else { | ||
| batch | ||
| } | ||
| case p if canPassThrough(p) => | ||
| p.mapChildren(disableBucketScan(_, hashInterestingPartition, hasExchange)) | ||
| case other => | ||
| other.mapChildren( | ||
| disableBucketScan(_, hashInterestingPartition = false, hasExchange = false)) | ||
| } | ||
| } | ||
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| private def hasInterestingPartition(plan: SparkPlan): Boolean = { | ||
| plan.requiredChildDistribution.exists { | ||
| case _: ClusteredDistribution | AllTuples => true | ||
| case _ => false | ||
| } | ||
| } | ||
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| /** | ||
| * Check if the operator is allowed single-child operator. We may revisit this method later as we | ||
| * probably can remove this restriction to allow arbitrary operator between bucketed table scan | ||
| * and operator with interesting partition. | ||
| */ | ||
| private def canPassThrough(plan: SparkPlan): Boolean = { | ||
| plan match { | ||
| case _: ProjectExec | _: FilterExec => true | ||
| case s: SortExec if !s.global => true | ||
| case partialAgg: BaseAggregateExec => | ||
| partialAgg.requiredChildDistributionExpressions.isEmpty | ||
| case _ => false | ||
| } | ||
| } | ||
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| def extractPaimonBucketedScan(plan: SparkPlan): Option[(BatchScanExec, PaimonScan)] = | ||
| plan match { | ||
| case batch: BatchScanExec => | ||
| batch.scan match { | ||
| case scan: PaimonScan if scan.lazyInputPartitions.forall(_.bucketed) => | ||
| Some((batch, scan)) | ||
| case _ => None | ||
| } | ||
| case _ => None | ||
| } | ||
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| def apply(plan: SparkPlan): SparkPlan = { | ||
| lazy val hasBucketedScan = plan.exists { | ||
| case p if extractPaimonBucketedScan(p).isDefined => true | ||
| case _ => false | ||
| } | ||
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| if (!conf.v2BucketingEnabled || !conf.autoBucketedScanEnabled || !hasBucketedScan) { | ||
| plan | ||
| } else { | ||
| disableBucketScan(plan, hashInterestingPartition = false, hasExchange = false) | ||
| } | ||
| } | ||
| } |
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