cloud-fan commented on code in PR #32298: URL: https://github.com/apache/spark/pull/32298#discussion_r851999569
########## sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/MergeScalarSubqueries.scala: ########## @@ -0,0 +1,357 @@ +/* + * 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.catalyst.optimizer + +import scala.collection.mutable +import scala.collection.mutable.ListBuffer + +import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.catalyst.expressions.aggregate.AggregateExpression +import org.apache.spark.sql.catalyst.plans.logical.{Aggregate, CTERelationDef, CTERelationRef, Filter, Join, LogicalPlan, Project, Subquery, WithCTE} +import org.apache.spark.sql.catalyst.rules.Rule +import org.apache.spark.sql.catalyst.trees.TreePattern.{SCALAR_SUBQUERY, SCALAR_SUBQUERY_REFERENCE, TreePattern} +import org.apache.spark.sql.types.DataType + +/** + * This rule tries to merge multiple non-correlated [[ScalarSubquery]]s to compute multiple scalar + * values once. + * + * The process is the following: + * - While traversing through the plan each [[ScalarSubquery]] plan is tried to merge into the cache + * of already seen subquery plans. If merge is possible then cache is updated with the merged + * subquery plan, if not then the new subquery plan is added to the cache. + * During this first traversal each [[ScalarSubquery]] expression is replaced to a temporal + * [[ScalarSubqueryReference]] reference pointing to its cached version. + * The cache uses a flag to keep track of if a cache entry is a result of merging 2 or more + * plans, or it is a plan that was seen only once. + * Merged plans in the cache get a "Header", that contains the list of attributes form the scalar + * return value of a merged subquery. + * - A second traversal checks if there are merged subqueries in the cache and builds a `WithCTE` + * node from these queries. The `CTERelationDef` nodes contain the merged subquery in the + * following form: + * `Project(Seq(CreateNamedStruct(name1, attribute1, ...) AS mergedValue), mergedSubqueryPlan)` + * and the definitions are flagged that they host a subquery, that can return maximum one row. + * During the second traversal [[ScalarSubqueryReference]] expressions that pont to a merged + * subquery is either transformed to a `GetStructField(ScalarSubquery(CTERelationRef(...)))` + * expression or restored to the original [[ScalarSubquery]]. + * + * Eg. the following query: + * + * SELECT + * (SELECT avg(a) FROM t), + * (SELECT sum(b) FROM t) + * + * is optimized from: + * + * == Optimized Logical Plan == + * Project [scalar-subquery#242 [] AS scalarsubquery()#253, + * scalar-subquery#243 [] AS scalarsubquery()#254L] + * : :- Aggregate [avg(a#244) AS avg(a)#247] + * : : +- Project [a#244] + * : : +- Relation default.t[a#244,b#245] parquet + * : +- Aggregate [sum(a#251) AS sum(a)#250L] + * : +- Project [a#251] + * : +- Relation default.t[a#251,b#252] parquet + * +- OneRowRelation + * + * to: + * + * WithCTE + * :- CTERelationDef 0 + * : +- Project [named_struct(avg(a), avg(a)#247, sum(a), sum(a)#250L) AS mergedValue#260] + * : +- Aggregate [avg(a#244) AS avg(a)#247, sum(a#244) AS sum(a)#250L] + * : +- Project [a#244] + * : +- Relation default.t[a#244,b#245] parquet + * +- Project [scalar-subquery#242 [].avg(a) AS scalarsubquery()#253, + * scalar-subquery#243 [].sum(a) AS scalarsubquery()#254L] + * : :- CTERelationRef 0, true, [mergedValue#260], true + * : +- CTERelationRef 0, true, [mergedValue#260], true + * +- OneRowRelation + */ +object MergeScalarSubqueries extends Rule[LogicalPlan] with PredicateHelper { + def apply(plan: LogicalPlan): LogicalPlan = { + plan match { + case s: Subquery => s.copy(child = extractCommonScalarSubqueries(s.child)) Review Comment: The entire optimizer will be recursively called to optimize subqueries in the rule `OptimizeSubqueries`. Since this rule transforms subqueries already, we should not recursively run it when optimizing subqueries. I think we need to skip this rule if the root node is `Subquery`, which indicates that this rule is being called for subqueires. -- 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. To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
