spark ShuffledJoin 源码

  • 2022-10-20
  • 浏览 (130)

spark ShuffledJoin 代码


 * 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
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * See the License for the specific language governing permissions and
 * limitations under the License.

package org.apache.spark.sql.execution.joins

import org.apache.spark.sql.catalyst.expressions.Attribute
import org.apache.spark.sql.catalyst.plans.{ExistenceJoin, FullOuter, InnerLike, LeftExistence, LeftOuter, RightOuter}
import org.apache.spark.sql.catalyst.plans.physical.{ClusteredDistribution, Distribution, Partitioning, PartitioningCollection, UnknownPartitioning, UnspecifiedDistribution}

 * Holds common logic for join operators by shuffling two child relations
 * using the join keys.
trait ShuffledJoin extends JoinCodegenSupport {
  def isSkewJoin: Boolean

  override def nodeName: String = {
    if (isSkewJoin) super.nodeName + "(skew=true)" else super.nodeName

  override def stringArgs: Iterator[Any] = super.stringArgs.toSeq.dropRight(1).iterator

  override def requiredChildDistribution: Seq[Distribution] = {
    if (isSkewJoin) {
      // We re-arrange the shuffle partitions to deal with skew join, and the new children
      // partitioning doesn't satisfy `HashClusteredDistribution`.
      UnspecifiedDistribution :: UnspecifiedDistribution :: Nil
    } else {
      ClusteredDistribution(leftKeys) :: ClusteredDistribution(rightKeys) :: Nil

  override def outputPartitioning: Partitioning = joinType match {
    case _: InnerLike =>
      PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
    case LeftOuter => left.outputPartitioning
    case RightOuter => right.outputPartitioning
    case FullOuter => UnknownPartitioning(left.outputPartitioning.numPartitions)
    case LeftExistence(_) => left.outputPartitioning
    case x =>
      throw new IllegalArgumentException(
        s"ShuffledJoin should not take $x as the JoinType")

  override def output: Seq[Attribute] = {
    joinType match {
      case _: InnerLike =>
        left.output ++ right.output
      case LeftOuter =>
        left.output ++
      case RightOuter => ++ right.output
      case FullOuter =>
        (left.output ++ right.output).map(_.withNullability(true))
      case j: ExistenceJoin =>
        left.output :+ j.exists
      case LeftExistence(_) =>
      case x =>
        throw new IllegalArgumentException(
          s"${getClass.getSimpleName} not take $x as the JoinType")


spark 源码目录


spark BaseJoinExec 源码

spark BroadcastHashJoinExec 源码

spark BroadcastNestedLoopJoinExec 源码

spark CartesianProductExec 源码

spark HashJoin 源码

spark HashedRelation 源码

spark JoinCodegenSupport 源码

spark ShuffledHashJoinExec 源码

spark SortMergeJoinExec 源码

0  赞