org.apache.spark.Dependency.scala Maven / Gradle / Ivy
/*
* 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
import scala.reflect.ClassTag
import org.apache.spark.annotation.DeveloperApi
import org.apache.spark.rdd.RDD
import org.apache.spark.serializer.Serializer
import org.apache.spark.shuffle.ShuffleHandle
/**
* :: DeveloperApi ::
* Base class for dependencies.
*/
@DeveloperApi
abstract class Dependency[T] extends Serializable {
def rdd: RDD[T]
}
/**
* :: DeveloperApi ::
* Base class for dependencies where each partition of the child RDD depends on a small number
* of partitions of the parent RDD. Narrow dependencies allow for pipelined execution.
*/
@DeveloperApi
abstract class NarrowDependency[T](_rdd: RDD[T]) extends Dependency[T] {
/**
* Get the parent partitions for a child partition.
* @param partitionId a partition of the child RDD
* @return the partitions of the parent RDD that the child partition depends upon
*/
def getParents(partitionId: Int): Seq[Int]
override def rdd: RDD[T] = _rdd
}
/**
* :: DeveloperApi ::
* Represents a dependency on the output of a shuffle stage. Note that in the case of shuffle,
* the RDD is transient since we don't need it on the executor side.
*
* @param _rdd the parent RDD
* @param partitioner partitioner used to partition the shuffle output
* @param serializer [[org.apache.spark.serializer.Serializer Serializer]] to use. If not set
* explicitly then the default serializer, as specified by `spark.serializer`
* config option, will be used.
* @param keyOrdering key ordering for RDD's shuffles
* @param aggregator map/reduce-side aggregator for RDD's shuffle
* @param mapSideCombine whether to perform partial aggregation (also known as map-side combine)
*/
@DeveloperApi
class ShuffleDependency[K: ClassTag, V: ClassTag, C: ClassTag](
@transient private val _rdd: RDD[_ <: Product2[K, V]],
val partitioner: Partitioner,
val serializer: Serializer = SparkEnv.get.serializer,
val keyOrdering: Option[Ordering[K]] = None,
val aggregator: Option[Aggregator[K, V, C]] = None,
val mapSideCombine: Boolean = false)
extends Dependency[Product2[K, V]] {
if (mapSideCombine) {
require(aggregator.isDefined, "Map-side combine without Aggregator specified!")
}
override def rdd: RDD[Product2[K, V]] = _rdd.asInstanceOf[RDD[Product2[K, V]]]
private[spark] val keyClassName: String = reflect.classTag[K].runtimeClass.getName
private[spark] val valueClassName: String = reflect.classTag[V].runtimeClass.getName
// Note: It's possible that the combiner class tag is null, if the combineByKey
// methods in PairRDDFunctions are used instead of combineByKeyWithClassTag.
private[spark] val combinerClassName: Option[String] =
Option(reflect.classTag[C]).map(_.runtimeClass.getName)
val shuffleId: Int = _rdd.context.newShuffleId()
val shuffleHandle: ShuffleHandle = _rdd.context.env.shuffleManager.registerShuffle(
shuffleId, _rdd.partitions.length, this)
_rdd.sparkContext.cleaner.foreach(_.registerShuffleForCleanup(this))
}
/**
* :: DeveloperApi ::
* Represents a one-to-one dependency between partitions of the parent and child RDDs.
*/
@DeveloperApi
class OneToOneDependency[T](rdd: RDD[T]) extends NarrowDependency[T](rdd) {
override def getParents(partitionId: Int): List[Int] = List(partitionId)
}
/**
* :: DeveloperApi ::
* Represents a one-to-one dependency between ranges of partitions in the parent and child RDDs.
* @param rdd the parent RDD
* @param inStart the start of the range in the parent RDD
* @param outStart the start of the range in the child RDD
* @param length the length of the range
*/
@DeveloperApi
class RangeDependency[T](rdd: RDD[T], inStart: Int, outStart: Int, length: Int)
extends NarrowDependency[T](rdd) {
override def getParents(partitionId: Int): List[Int] = {
if (partitionId >= outStart && partitionId < outStart + length) {
List(partitionId - outStart + inStart)
} else {
Nil
}
}
}