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`
--- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org