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[SPARK-4485][SQL] (1) Add broadcast hash outer join, (2) Fix SparkPlanTest #7162
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120 changes: 120 additions & 0 deletions
120
sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashOuterJoin.scala
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/* | ||
* 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. | ||
*/ | ||
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package org.apache.spark.sql.execution.joins | ||
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import org.apache.spark.annotation.DeveloperApi | ||
import org.apache.spark.rdd.RDD | ||
import org.apache.spark.sql.catalyst.expressions._ | ||
import org.apache.spark.sql.catalyst.plans.physical.{Distribution, UnspecifiedDistribution} | ||
import org.apache.spark.sql.catalyst.plans.{JoinType, LeftOuter, RightOuter} | ||
import org.apache.spark.sql.execution.{BinaryNode, SparkPlan} | ||
import org.apache.spark.util.ThreadUtils | ||
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import scala.concurrent._ | ||
import scala.concurrent.duration._ | ||
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/** | ||
* :: DeveloperApi :: | ||
* Performs a outer hash join for two child relations. When the output RDD of this operator is | ||
* being constructed, a Spark job is asynchronously started to calculate the values for the | ||
* broadcasted relation. This data is then placed in a Spark broadcast variable. The streamed | ||
* relation is not shuffled. | ||
*/ | ||
@DeveloperApi | ||
case class BroadcastHashOuterJoin( | ||
leftKeys: Seq[Expression], | ||
rightKeys: Seq[Expression], | ||
joinType: JoinType, | ||
condition: Option[Expression], | ||
left: SparkPlan, | ||
right: SparkPlan) extends BinaryNode with HashOuterJoin { | ||
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val timeout = { | ||
val timeoutValue = sqlContext.conf.broadcastTimeout | ||
if (timeoutValue < 0) { | ||
Duration.Inf | ||
} else { | ||
timeoutValue.seconds | ||
} | ||
} | ||
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override def requiredChildDistribution: Seq[Distribution] = | ||
UnspecifiedDistribution :: UnspecifiedDistribution :: Nil | ||
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private[this] lazy val (buildPlan, streamedPlan) = joinType match { | ||
case RightOuter => (left, right) | ||
case LeftOuter => (right, left) | ||
case x => | ||
throw new IllegalArgumentException( | ||
s"BroadcastHashOuterJoin should not take $x as the JoinType") | ||
} | ||
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private[this] lazy val (buildKeys, streamedKeys) = joinType match { | ||
case RightOuter => (leftKeys, rightKeys) | ||
case LeftOuter => (rightKeys, leftKeys) | ||
case x => | ||
throw new IllegalArgumentException( | ||
s"BroadcastHashOuterJoin should not take $x as the JoinType") | ||
} | ||
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@transient | ||
private val broadcastFuture = future { | ||
// Note that we use .execute().collect() because we don't want to convert data to Scala types | ||
val input: Array[InternalRow] = buildPlan.execute().map(_.copy()).collect() | ||
// buildHashTable uses code-generated rows as keys, which are not serializable | ||
val hashed = new GeneralHashedRelation( | ||
buildHashTable(input.iterator, newProjection(buildKeys, buildPlan.output))) | ||
sparkContext.broadcast(hashed) | ||
}(BroadcastHashOuterJoin.broadcastHashOuterJoinExecutionContext) | ||
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override def doExecute(): RDD[InternalRow] = { | ||
val broadcastRelation = Await.result(broadcastFuture, timeout) | ||
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streamedPlan.execute().mapPartitions { streamedIter => | ||
val joinedRow = new JoinedRow() | ||
val hashTable = broadcastRelation.value | ||
val keyGenerator = newProjection(streamedKeys, streamedPlan.output) | ||
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joinType match { | ||
case LeftOuter => | ||
streamedIter.flatMap(currentRow => { | ||
val rowKey = keyGenerator(currentRow) | ||
joinedRow.withLeft(currentRow) | ||
leftOuterIterator(rowKey, joinedRow, hashTable.getOrElse(rowKey, EMPTY_LIST)) | ||
}) | ||
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case RightOuter => | ||
streamedIter.flatMap(currentRow => { | ||
val rowKey = keyGenerator(currentRow) | ||
joinedRow.withRight(currentRow) | ||
rightOuterIterator(rowKey, hashTable.getOrElse(rowKey, EMPTY_LIST), joinedRow) | ||
}) | ||
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case x => | ||
throw new IllegalArgumentException( | ||
s"BroadcastHashOuterJoin should not take $x as the JoinType") | ||
} | ||
} | ||
} | ||
} | ||
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object BroadcastHashOuterJoin { | ||
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private val broadcastHashOuterJoinExecutionContext = ExecutionContext.fromExecutorService( | ||
ThreadUtils.newDaemonCachedThreadPool("broadcast-hash-outer-join", 128)) | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. It would probably be reasonable to have a single threadpool that we share for all broadcasting. |
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} |
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I think you need to use
new InterpretedProjection
here, otherwise you try to broadcast code-generatedSpecificRow
s, which fails when in non-local mode. See: #7213.@davies / @rxin , I'm now officially in favor of removing
GenerateProjection
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@marmbrus Yeah, that's why I used GeneralHashedRelation to wrap the hash table. Which way do you think is better?
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This still fails for me when I run it on a real cluster. I'd just change this to
buildHashTable(input.iterator, new InterpretedProjection(buildKeys, buildPlan.output)))
or we might even just changenewProjection
to always useInterpretedProjection
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Sure