Github user cloud-fan commented on a diff in the pull request: https://github.com/apache/spark/pull/13494#discussion_r70380410 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/OptimizeMetadataOnlyQuery.scala --- @@ -0,0 +1,162 @@ +/* + * 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 + +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.catalog.{CatalogRelation, SessionCatalog} +import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.catalyst.expressions.aggregate._ +import org.apache.spark.sql.catalyst.plans.logical._ +import org.apache.spark.sql.catalyst.rules.Rule +import org.apache.spark.sql.execution.datasources.{HadoopFsRelation, LogicalRelation} +import org.apache.spark.sql.internal.SQLConf + +/** + * This rule optimizes the execution of queries that can be answered by looking only at + * partition-level metadata. This applies when all the columns scanned are partition columns, and + * the query has an aggregate operator that satisfies the following conditions: + * 1. aggregate expression is partition columns. + * e.g. SELECT col FROM tbl GROUP BY col. + * 2. aggregate function on partition columns with DISTINCT. + * e.g. SELECT col1, count(DISTINCT col2) FROM tbl GROUP BY col1. + * 3. aggregate function on partition columns which have same result w or w/o DISTINCT keyword. + * e.g. SELECT col1, Max(col2) FROM tbl GROUP BY col1. + */ +case class OptimizeMetadataOnlyQuery( + catalog: SessionCatalog, + conf: SQLConf) extends Rule[LogicalPlan] { + + def apply(plan: LogicalPlan): LogicalPlan = { + if (!conf.optimizerMetadataOnly) { + return plan + } + + plan.transform { + case a @ Aggregate(_, aggExprs, child @ PartitionedRelation(partAttrs, relation)) => + // We only apply this optimization when only partitioned attributes are scanned. + if (a.references.subsetOf(partAttrs)) { + val aggFunctions = aggExprs.flatMap(_.collect { + case agg: AggregateExpression => agg + }) + val isAllDistinctAgg = aggFunctions.forall { agg => + agg.isDistinct || (agg.aggregateFunction match { + // `Max`, `Min`, `First` and `Last` are always distinct aggregate functions no matter + // they have DISTINCT keyword or not, as the result will be same. + case _: Max => true + case _: Min => true + case _: First => true + case _: Last => true + case _ => false + }) + } + if (isAllDistinctAgg) { + a.withNewChildren(Seq(replaceTableScanWithPartitionMetadata(child, relation))) + } else { + a + } + } else { + a + } + } + } + + /** + * Returns the partition attributes of the table relation plan. + */ + private def getPartitionAttrs( + partitionColumnNames: Seq[String], + relation: LogicalPlan): Seq[Attribute] = { + val partColumns = partitionColumnNames.map(_.toLowerCase).toSet + relation.output.filter(a => partColumns.contains(a.name.toLowerCase)) + } + + /** + * Transform the given plan, find its table scan nodes that matches the given relation, and then + * replace the table scan node with its corresponding partition values. + */ + private def replaceTableScanWithPartitionMetadata( + child: LogicalPlan, + relation: LogicalPlan): LogicalPlan = { + child transform { + case plan if plan eq relation => + relation match { + case l @ LogicalRelation(fsRelation: HadoopFsRelation, _, _) => + val partAttrs = getPartitionAttrs(fsRelation.partitionSchema.map(_.name), l) + val partitionData = fsRelation.location.listFiles(filters = Nil) + LocalRelation(partAttrs, partitionData.map(_.values)) + + case relation: CatalogRelation => + val partAttrs = getPartitionAttrs(relation.catalogTable.partitionColumnNames, relation) + val partitionData = catalog.listPartitions(relation.catalogTable.identifier).map { p => + InternalRow.fromSeq(partAttrs.map { attr => + Cast(Literal(p.spec(attr.name)), attr.dataType).eval() + }) + } + LocalRelation(partAttrs, partitionData) + + case _ => + throw new IllegalStateException(s"unrecognized table scan node: $relation, " + + s"please turn off ${SQLConf.OPTIMIZER_METADATA_ONLY.key} and try again.") + } + } + } + + /** + * A pattern that finds the partitioned table relation node inside the given plan, and returns a + * pair of the partition attributes and the table relation node. + * + * It keeps traversing down the given plan tree if there is a [[Project]] or [[Filter]] with + * deterministic expressions, and returns result after reaching the partitioned table relation + * node. + */ + object PartitionedRelation { + + def unapply(plan: LogicalPlan): Option[(AttributeSet, LogicalPlan)] = plan match { + case l @ LogicalRelation(fsRelation: HadoopFsRelation, _, _) + if fsRelation.partitionSchema.nonEmpty => + val partAttrs = getPartitionAttrs(fsRelation.partitionSchema.map(_.name), l) + Some(partAttrs, l) + + case relation: CatalogRelation if relation.catalogTable.partitionColumnNames.nonEmpty => + val partAttrs = getPartitionAttrs(relation.catalogTable.partitionColumnNames, relation) + Some(partAttrs, relation) + + case p @ Project(projectList, child) if projectList.forall(_.deterministic) => + unapply(child).flatMap { case (partAttrs, relation) => + if (p.references.subsetOf(partAttrs)) Some(p.outputSet, relation) else None + } + + case f @ Filter(condition, child) if condition.deterministic => + unapply(child).flatMap { case (partAttrs, relation) => + if (f.references.subsetOf(partAttrs)) Some(partAttrs, relation) else None + } + + case _ => None + } + + /** + * Returns the partition attributes of the table relation plan. + */ + private def getPartitionAttrs( --- End diff -- IIRC, inner class can access private member of outer class, we don't need to duplicate the method in inner class.
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