cloud-fan commented on code in PR #38799: URL: https://github.com/apache/spark/pull/38799#discussion_r1100265866
########## sql/core/src/main/scala/org/apache/spark/sql/execution/window/WindowGroupLimitExec.scala: ########## @@ -0,0 +1,245 @@ +/* + * 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.window + +import org.apache.spark.rdd.RDD +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.expressions.{Ascending, Attribute, DenseRank, Expression, Rank, RowNumber, SortOrder, UnsafeProjection, UnsafeRow} +import org.apache.spark.sql.catalyst.expressions.codegen.GenerateOrdering +import org.apache.spark.sql.catalyst.plans.physical.{AllTuples, ClusteredDistribution, Distribution, Partitioning} +import org.apache.spark.sql.execution.{SparkPlan, UnaryExecNode} + +sealed trait WindowGroupLimitMode + +case object Partial extends WindowGroupLimitMode + +case object Final extends WindowGroupLimitMode + +/** + * This operator is designed to filter out unnecessary rows before WindowExec + * for top-k computation. + * @param partitionSpec Should be the same as [[WindowExec#partitionSpec]]. + * @param orderSpec Should be the same as [[WindowExec#orderSpec]]. + * @param rankLikeFunction The function to compute row rank, should be RowNumber/Rank/DenseRank. + * @param limit The limit for rank value. + * @param mode The mode describes [[WindowGroupLimitExec]] before or after shuffle. + * @param child The child spark plan. + */ +case class WindowGroupLimitExec( + partitionSpec: Seq[Expression], + orderSpec: Seq[SortOrder], + rankLikeFunction: Expression, + limit: Int, + mode: WindowGroupLimitMode, + child: SparkPlan) extends UnaryExecNode { + + override def output: Seq[Attribute] = child.output + + override def requiredChildDistribution: Seq[Distribution] = mode match { + case Partial => super.requiredChildDistribution + case Final => + if (partitionSpec.isEmpty) { + AllTuples :: Nil + } else { + ClusteredDistribution(partitionSpec) :: Nil + } + } + + override def requiredChildOrdering: Seq[Seq[SortOrder]] = + Seq(partitionSpec.map(SortOrder(_, Ascending)) ++ orderSpec) + + override def outputOrdering: Seq[SortOrder] = child.outputOrdering + + override def outputPartitioning: Partitioning = child.outputPartitioning + + protected override def doExecute(): RDD[InternalRow] = rankLikeFunction match { + case _: RowNumber => + child.execute().mapPartitionsInternal( + SimpleGroupLimitIterator(partitionSpec, output, _, limit)) + case _: Rank => + child.execute().mapPartitionsInternal( + RankGroupLimitIterator(partitionSpec, output, _, orderSpec, limit)) + case _: DenseRank => + child.execute().mapPartitionsInternal( + DenseRankGroupLimitIterator(partitionSpec, output, _, orderSpec, limit)) + } + + override protected def withNewChildInternal(newChild: SparkPlan): WindowGroupLimitExec = + copy(child = newChild) +} + +abstract class WindowIterator extends Iterator[InternalRow] { + + def partitionSpec: Seq[Expression] + + def output: Seq[Attribute] + + def input: Iterator[InternalRow] + + def limit: Int + + val grouping = UnsafeProjection.create(partitionSpec, output) Review Comment: I'm wondering if we should optimize for the special case where the function is row_number and the partition spec is empty. For this case, we just need to do a top n, no need to sort the entire input. -- 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: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
