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From marmbrus <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-2213] [SQL] sort merge join for spark s...
Date Sat, 11 Apr 2015 22:17:56 GMT
Github user marmbrus commented on a diff in the pull request:

    https://github.com/apache/spark/pull/5208#discussion_r28198938
  
    --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/joins/SortMergeJoin.scala
---
    @@ -0,0 +1,163 @@
    +/*
    + * 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.joins
    +
    +import org.apache.spark.annotation.DeveloperApi
    +import org.apache.spark.rdd.RDD
    +import org.apache.spark.sql.Row
    +import org.apache.spark.sql.catalyst.expressions._
    +import org.apache.spark.sql.catalyst.plans._
    +import org.apache.spark.sql.catalyst.plans.physical._
    +import org.apache.spark.sql.execution.{BinaryNode, SparkPlan}
    +import org.apache.spark.util.collection.CompactBuffer
    +
    +/**
    + * :: DeveloperApi ::
    + * Performs an sort merge join of two child relations.
    + */
    +@DeveloperApi
    +case class SortMergeJoin(
    +    leftKeys: Seq[Expression],
    +    rightKeys: Seq[Expression],
    +    left: SparkPlan,
    +    right: SparkPlan) extends BinaryNode {
    +
    +  override def output: Seq[Attribute] = left.output ++ right.output
    +
    +  override def outputPartitioning: Partitioning = left.outputPartitioning
    +
    +  override def requiredChildDistribution: Seq[Distribution] =
    +    ClusteredDistribution(leftKeys) :: ClusteredDistribution(rightKeys) :: Nil
    +
    +  private val orders: Seq[SortOrder] = leftKeys.zipWithIndex.map {
    +    case(expr, index) => SortOrder(BoundReference(index, expr.dataType, expr.nullable),
Ascending)
    +  }
    +  private val ordering: RowOrdering = new RowOrdering(orders, left.output)
    +
    +  private def requiredOrders(keys: Seq[Expression], side: SparkPlan): Seq[SortOrder]
= keys.map {
    +    k => SortOrder(BindReferences.bindReference(k, side.output, allowFailures = false),
Ascending)
    --- End diff --
    
    Why are we doing manual binding of references here?  It would be best of avoid this and
instead do it when constructing the `RowOrdering` (there is a second constructor that takes
the input schema).


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