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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 spark.rdd
import spark.{Partitioner, RDD, SparkEnv, ShuffleDependency, Partition, TaskContext}
import spark.SparkContext._
private[spark] class ShuffledRDDPartition(val idx: Int) extends Partition {
override val index = idx
override def hashCode(): Int = idx
}
/**
* The resulting RDD from a shuffle (e.g. repartitioning of data).
* @param prev the parent RDD.
* @param part the partitioner used to partition the RDD
* @param serializerClass class name of the serializer to use.
* @tparam K the key class.
* @tparam V the value class.
*/
class ShuffledRDD[K, V](
@transient prev: RDD[(K, V)],
part: Partitioner,
serializerClass: String = null)
extends RDD[(K, V)](prev.context, List(new ShuffleDependency(prev, part, serializerClass))) {
override val partitioner = Some(part)
override def getPartitions: Array[Partition] = {
Array.tabulate[Partition](part.numPartitions)(i => new ShuffledRDDPartition(i))
}
override def compute(split: Partition, context: TaskContext): Iterator[(K, V)] = {
val shuffledId = dependencies.head.asInstanceOf[ShuffleDependency[K, V]].shuffleId
SparkEnv.get.shuffleFetcher.fetch[K, V](shuffledId, split.index, context.taskMetrics,
SparkEnv.get.serializerManager.get(serializerClass))
}
}
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