aokolnychyi commented on code in PR #36304: URL: https://github.com/apache/spark/pull/36304#discussion_r984981183
########## sql/core/src/main/scala/org/apache/spark/sql/execution/dynamicpruning/RowLevelOperationRuntimeGroupFiltering.scala: ########## @@ -0,0 +1,98 @@ +/* + * 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.dynamicpruning + +import org.apache.spark.sql.catalyst.expressions.{And, Attribute, DynamicPruningSubquery, Expression, PredicateHelper, V2ExpressionUtils} +import org.apache.spark.sql.catalyst.expressions.Literal.TrueLiteral +import org.apache.spark.sql.catalyst.planning.GroupBasedRowLevelOperation +import org.apache.spark.sql.catalyst.plans.logical.{Filter, LogicalPlan, Project} +import org.apache.spark.sql.catalyst.rules.Rule +import org.apache.spark.sql.connector.read.SupportsRuntimeV2Filtering +import org.apache.spark.sql.execution.datasources.v2.{DataSourceV2Implicits, DataSourceV2Relation, DataSourceV2ScanRelation} + +/** + * A rule that assigns a subquery to filter groups in row-level operations at runtime. + * + * Data skipping during job planning for row-level operations is limited to expressions that can be + * converted to data source filters. Since not all expressions can be pushed down that way and + * rewriting groups is expensive, Spark allows data sources to filter group at runtime. + * If the primary scan in a group-based row-level operation supports runtime filtering, this rule + * will inject a subquery to find all rows that match the condition so that data sources know + * exactly which groups must be rewritten. + * + * Note this rule only applies to group-based row-level operations. + */ +case class RowLevelOperationRuntimeGroupFiltering(optimizeSubqueries: Rule[LogicalPlan]) + extends Rule[LogicalPlan] with PredicateHelper { + + import DataSourceV2Implicits._ + + override def apply(plan: LogicalPlan): LogicalPlan = plan transformDown { + // apply special dynamic filtering only for group-based row-level operations + case GroupBasedRowLevelOperation(replaceData, cond, + DataSourceV2ScanRelation(_, scan: SupportsRuntimeV2Filtering, _, _, _)) Review Comment: This is the optimizer rule that checks whether the primary row-level scan supports runtime filtering. As long as a data source implements `SupportsRuntimeV2Filtering`, it should be sufficient to benefit from the new functionality. Also, the runtime group filter uses the existing framework for runtime filtering in DS V2, meaning we get all the benefits like subquery reuse, etc. -- 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
