Github user tianyi commented on a diff in the pull request:
https://github.com/apache/spark/pull/3362#discussion_r20843639
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashOuterJoin.scala
---
@@ -0,0 +1,164 @@
+/*
+ * 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 java.util.{HashMap => JavaHashMap}
+
+import scala.collection.JavaConversions._
+
+import org.apache.spark.annotation.DeveloperApi
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.plans.physical.{Partitioning}
+import org.apache.spark.sql.catalyst.plans.{JoinType, LeftOuter,
RightOuter}
+import org.apache.spark.sql.execution.{BinaryNode, SparkPlan}
+import org.apache.spark.util.collection.CompactBuffer
+
+
+/**
+ * :: DeveloperApi ::
+ * Performs a hash based outer 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.
+ * Comment:In left(right) outer join only the right(left) table has an
+ * estimated physical size smaller than the user-settable threshold
+ * [[org.apache.spark.sql.SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]] the
planner
+ * would mark it as the broadcasted relation.
+ */
+@DeveloperApi
+case class BroadcastHashOuterJoin(
+ leftKeys: Seq[Expression],
+ rightKeys: Seq[Expression],
+ joinType: JoinType,
+ condition: Option[Expression],
+ left: SparkPlan,
+ right: SparkPlan)
+ extends BinaryNode {
+
+ private val (streamedPlan, broadcastPlan) = joinType match {
+ case LeftOuter => (left, right)
+ case RightOuter => (right, left)
+ }
+
+ private val (streamedKeys, broadcastKeys) = joinType match {
+ case LeftOuter => (leftKeys, rightKeys)
+ case RightOuter => (rightKeys, leftKeys)
+ }
+
+ override def outputPartitioning: Partitioning = joinType match {
+ case LeftOuter => left.outputPartitioning
+ case RightOuter => right.outputPartitioning
+ case x => throw new Exception(s"HashOuterJoin should not take $x as
the JoinType")
+ }
+
+ override def output = {
+ joinType match {
+ case LeftOuter =>
+ left.output ++ right.output.map(_.withNullability(true))
+ case RightOuter =>
+ left.output.map(_.withNullability(true)) ++ right.output
+ case x =>
+ throw new Exception(s"HashOuterJoin should not take $x as the
JoinType")
+ }
+ }
+
+ @transient private[this] lazy val BroadcastSideKeyGenerator: Projection =
+ newProjection(broadcastKeys, broadcastPlan.output)
+
+ @transient private[this] lazy val streamSideKeyGenerator: () =>
MutableProjection =
+ newMutableProjection(streamedKeys, streamedPlan.output)
+
+ @transient private[this] lazy val DUMMY_LIST = Seq[Row](null)
+ @transient private[this] lazy val EMPTY_LIST = Seq.empty[Row]
+
+ private[this] def buildHashTable(
+ iter: Iterator[Row], keyGenerator: Projection): JavaHashMap[Row,
CompactBuffer[Row]] = {
+ val hashTable = new JavaHashMap[Row, CompactBuffer[Row]]()
+ while (iter.hasNext) {
+ val currentRow = iter.next()
+ val rowKey = keyGenerator(currentRow)
+
+ var existingMatchList = hashTable.get(rowKey)
+ if (existingMatchList == null) {
+ existingMatchList = new CompactBuffer[Row]()
+ hashTable.put(rowKey, existingMatchList)
+ }
+
+ existingMatchList += currentRow.copy()
+ }
+
+ hashTable
+ }
+
+ override def execute() = {
+ val input: Array[Row] = broadcastPlan.execute().map(_.copy()).collect()
+ val hashed = buildHashTable(input.iterator, BroadcastSideKeyGenerator)
+ val broadcastHashTable = sparkContext.broadcast(hashed)
+ val boundCondition =
+ condition.map(newPredicate(_, left.output ++
right.output)).getOrElse((row: Row) => true)
+
+ streamedPlan.execute().mapPartitions {
+ streamedIter =>
+ var i = 0
+ val joinedRow = new JoinedRow
+ val joinKey = streamSideKeyGenerator()
+ val broadcastNulls = new
GenericMutableRow(broadcastPlan.output.size)
+
+ streamedIter.flatMap {
+ streamedRow =>
+ val rowKey = joinKey(streamedRow)
+ val broadcastRow = broadcastHashTable.value.getOrElse(rowKey,
EMPTY_LIST)
+ var matched = false
+ joinType match {
+ case LeftOuter =>
+ joinedRow.withLeft(streamedRow)
+ (if (!rowKey.anyNull) broadcastRow.collect {
+ case r if (boundCondition(joinedRow.withRight(r))) =>
+ matched = true
+ joinedRow.copy
+ } else {
+ Nil
+ }) ++ DUMMY_LIST.filter(_ => !matched).map(_ => {
+ // DUMMY_LIST.filter(_ => !matched) is a tricky way to
add additional row,
+ // as we don't know whether we need to append it until
finish iterating all of the
+ // records in right side.
+ // If we didn't get any proper row, then append a single
row with empty right
+ joinedRow.withRight(broadcastNulls).copy
+ })
+ case RightOuter =>
+ joinedRow.withRight(streamedRow)
+ (if (!rowKey.anyNull) broadcastRow.collect {
+ case r if (boundCondition(joinedRow.withLeft(r))) =>
+ matched = true
+ joinedRow.copy
+ } else {
+ Nil
+ }) ++ DUMMY_LIST.filter(_ => !matched).map(_ => {
+ // DUMMY_LIST.filter(_ => !matched) is a tricky way to
add additional row,
+ // as we don't know whether we need to append it until
finish iterating all of the
+ // records in left side.
+ // If we didn't get any proper row, then append a single
row with empty left
+ joinedRow.withLeft(broadcastNulls).copy
+ })
+ case _ => Nil
--- End diff --
I think we should throw a exception here, because other types of outer join
should not use `BroadcastHashOuterJoin`
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