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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.
*/
package org.apache.spark.sql.execution.joins
import org.apache.spark.broadcast.Broadcast
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.catalyst.InternalRow
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.{BinaryExecNode, SparkPlan}
import org.apache.spark.sql.execution.metric.SQLMetrics
import org.apache.spark.util.collection.{BitSet, CompactBuffer}
case class BroadcastNestedLoopJoinExec(
left: SparkPlan,
right: SparkPlan,
buildSide: BuildSide,
joinType: JoinType,
condition: Option[Expression]) extends BinaryExecNode {
override private[sql] lazy val metrics = Map(
"numOutputRows" -> SQLMetrics.createMetric(sparkContext, "number of output rows"))
/** BuildRight means the right relation <=> the broadcast relation. */
private val (streamed, broadcast) = buildSide match {
case BuildRight => (left, right)
case BuildLeft => (right, left)
}
override def requiredChildDistribution: Seq[Distribution] = buildSide match {
case BuildLeft =>
BroadcastDistribution(IdentityBroadcastMode) :: UnspecifiedDistribution :: Nil
case BuildRight =>
UnspecifiedDistribution :: BroadcastDistribution(IdentityBroadcastMode) :: Nil
}
private[this] def genResultProjection: InternalRow => InternalRow = joinType match {
case LeftExistence(j) =>
UnsafeProjection.create(output, output)
case other =>
// Always put the stream side on left to simplify implementation
// both of left and right side could be null
UnsafeProjection.create(
output, (streamed.output ++ broadcast.output).map(_.withNullability(true)))
}
override def output: Seq[Attribute] = {
joinType match {
case Inner =>
left.output ++ right.output
case LeftOuter =>
left.output ++ right.output.map(_.withNullability(true))
case RightOuter =>
left.output.map(_.withNullability(true)) ++ right.output
case FullOuter =>
left.output.map(_.withNullability(true)) ++ right.output.map(_.withNullability(true))
case j: ExistenceJoin =>
left.output :+ j.exists
case LeftExistence(_) =>
left.output
case x =>
throw new IllegalArgumentException(
s"BroadcastNestedLoopJoin should not take $x as the JoinType")
}
}
@transient private lazy val boundCondition = {
if (condition.isDefined) {
newPredicate(condition.get, streamed.output ++ broadcast.output)
} else {
(r: InternalRow) => true
}
}
/**
* The implementation for InnerJoin.
*/
private def innerJoin(relation: Broadcast[Array[InternalRow]]): RDD[InternalRow] = {
streamed.execute().mapPartitionsInternal { streamedIter =>
val buildRows = relation.value
val joinedRow = new JoinedRow
streamedIter.flatMap { streamedRow =>
val joinedRows = buildRows.iterator.map(r => joinedRow(streamedRow, r))
if (condition.isDefined) {
joinedRows.filter(boundCondition)
} else {
joinedRows
}
}
}
}
/**
* The implementation for these joins:
*
* LeftOuter with BuildRight
* RightOuter with BuildLeft
*/
private def outerJoin(relation: Broadcast[Array[InternalRow]]): RDD[InternalRow] = {
streamed.execute().mapPartitionsInternal { streamedIter =>
val buildRows = relation.value
val joinedRow = new JoinedRow
val nulls = new GenericMutableRow(broadcast.output.size)
// Returns an iterator to avoid copy the rows.
new Iterator[InternalRow] {
// current row from stream side
private var streamRow: InternalRow = null
// have found a match for current row or not
private var foundMatch: Boolean = false
// the matched result row
private var resultRow: InternalRow = null
// the next index of buildRows to try
private var nextIndex: Int = 0
private def findNextMatch(): Boolean = {
if (streamRow == null) {
if (!streamedIter.hasNext) {
return false
}
streamRow = streamedIter.next()
nextIndex = 0
foundMatch = false
}
while (nextIndex < buildRows.length) {
resultRow = joinedRow(streamRow, buildRows(nextIndex))
nextIndex += 1
if (boundCondition(resultRow)) {
foundMatch = true
return true
}
}
if (!foundMatch) {
resultRow = joinedRow(streamRow, nulls)
streamRow = null
true
} else {
resultRow = null
streamRow = null
findNextMatch()
}
}
override def hasNext(): Boolean = {
resultRow != null || findNextMatch()
}
override def next(): InternalRow = {
val r = resultRow
resultRow = null
r
}
}
}
}
/**
* The implementation for these joins:
*
* LeftSemi with BuildRight
* Anti with BuildRight
*/
private def leftExistenceJoin(
relation: Broadcast[Array[InternalRow]],
exists: Boolean): RDD[InternalRow] = {
assert(buildSide == BuildRight)
streamed.execute().mapPartitionsInternal { streamedIter =>
val buildRows = relation.value
val joinedRow = new JoinedRow
if (condition.isDefined) {
streamedIter.filter(l =>
buildRows.exists(r => boundCondition(joinedRow(l, r))) == exists
)
} else if (buildRows.nonEmpty == exists) {
streamedIter
} else {
Iterator.empty
}
}
}
private def existenceJoin(relation: Broadcast[Array[InternalRow]]): RDD[InternalRow] = {
assert(buildSide == BuildRight)
streamed.execute().mapPartitionsInternal { streamedIter =>
val buildRows = relation.value
val joinedRow = new JoinedRow
if (condition.isDefined) {
val resultRow = new GenericMutableRow(Array[Any](null))
streamedIter.map { row =>
val result = buildRows.exists(r => boundCondition(joinedRow(row, r)))
resultRow.setBoolean(0, result)
joinedRow(row, resultRow)
}
} else {
val resultRow = new GenericMutableRow(Array[Any](buildRows.nonEmpty))
streamedIter.map { row =>
joinedRow(row, resultRow)
}
}
}
}
/**
* The implementation for these joins:
*
* LeftOuter with BuildLeft
* RightOuter with BuildRight
* FullOuter
* LeftSemi with BuildLeft
* LeftAnti with BuildLeft
* ExistenceJoin with BuildLeft
*/
private def defaultJoin(relation: Broadcast[Array[InternalRow]]): RDD[InternalRow] = {
/** All rows that either match both-way, or rows from streamed joined with nulls. */
val streamRdd = streamed.execute()
val matchedBuildRows = streamRdd.mapPartitionsInternal { streamedIter =>
val buildRows = relation.value
val matched = new BitSet(buildRows.length)
val joinedRow = new JoinedRow
streamedIter.foreach { streamedRow =>
var i = 0
while (i < buildRows.length) {
if (boundCondition(joinedRow(streamedRow, buildRows(i)))) {
matched.set(i)
}
i += 1
}
}
Seq(matched).toIterator
}
val matchedBroadcastRows = matchedBuildRows.fold(
new BitSet(relation.value.length)
)(_ | _)
joinType match {
case LeftSemi =>
assert(buildSide == BuildLeft)
val buf: CompactBuffer[InternalRow] = new CompactBuffer()
var i = 0
val rel = relation.value
while (i < rel.length) {
if (matchedBroadcastRows.get(i)) {
buf += rel(i).copy()
}
i += 1
}
return sparkContext.makeRDD(buf)
case j: ExistenceJoin =>
val buf: CompactBuffer[InternalRow] = new CompactBuffer()
var i = 0
val rel = relation.value
while (i < rel.length) {
val result = new GenericInternalRow(Array[Any](matchedBroadcastRows.get(i)))
buf += new JoinedRow(rel(i).copy(), result)
i += 1
}
return sparkContext.makeRDD(buf)
case LeftAnti =>
val notMatched: CompactBuffer[InternalRow] = new CompactBuffer()
var i = 0
val rel = relation.value
while (i < rel.length) {
if (!matchedBroadcastRows.get(i)) {
notMatched += rel(i).copy()
}
i += 1
}
return sparkContext.makeRDD(notMatched)
case o =>
}
val notMatchedBroadcastRows: Seq[InternalRow] = {
val nulls = new GenericMutableRow(streamed.output.size)
val buf: CompactBuffer[InternalRow] = new CompactBuffer()
val joinedRow = new JoinedRow
joinedRow.withLeft(nulls)
var i = 0
val buildRows = relation.value
while (i < buildRows.length) {
if (!matchedBroadcastRows.get(i)) {
buf += joinedRow.withRight(buildRows(i)).copy()
}
i += 1
}
buf
}
val matchedStreamRows = streamRdd.mapPartitionsInternal { streamedIter =>
val buildRows = relation.value
val joinedRow = new JoinedRow
val nulls = new GenericMutableRow(broadcast.output.size)
streamedIter.flatMap { streamedRow =>
var i = 0
var foundMatch = false
val matchedRows = new CompactBuffer[InternalRow]
while (i < buildRows.length) {
if (boundCondition(joinedRow(streamedRow, buildRows(i)))) {
matchedRows += joinedRow.copy()
foundMatch = true
}
i += 1
}
if (!foundMatch && joinType == FullOuter) {
matchedRows += joinedRow(streamedRow, nulls).copy()
}
matchedRows.iterator
}
}
sparkContext.union(
matchedStreamRows,
sparkContext.makeRDD(notMatchedBroadcastRows)
)
}
protected override def doExecute(): RDD[InternalRow] = {
val broadcastedRelation = broadcast.executeBroadcast[Array[InternalRow]]()
val resultRdd = (joinType, buildSide) match {
case (Inner, _) =>
innerJoin(broadcastedRelation)
case (LeftOuter, BuildRight) | (RightOuter, BuildLeft) =>
outerJoin(broadcastedRelation)
case (LeftSemi, BuildRight) =>
leftExistenceJoin(broadcastedRelation, exists = true)
case (LeftAnti, BuildRight) =>
leftExistenceJoin(broadcastedRelation, exists = false)
case (j: ExistenceJoin, BuildRight) =>
existenceJoin(broadcastedRelation)
case _ =>
/**
* LeftOuter with BuildLeft
* RightOuter with BuildRight
* FullOuter
* LeftSemi with BuildLeft
* LeftAnti with BuildLeft
* ExistenceJoin with BuildLeft
*/
defaultJoin(broadcastedRelation)
}
val numOutputRows = longMetric("numOutputRows")
resultRdd.mapPartitionsInternal { iter =>
val resultProj = genResultProjection
iter.map { r =>
numOutputRows += 1
resultProj(r)
}
}
}
}
