spark CheckpointRDD 源码
spark CheckpointRDD 代码
文件路径：/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala
/*
* 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.rdd
import scala.reflect.ClassTag
import org.apache.spark.{Partition, SparkContext, TaskContext}
/**
* An RDD partition used to recover checkpointed data.
*/
private[spark] class CheckpointRDDPartition(val index: Int) extends Partition
/**
* An RDD that recovers checkpointed data from storage.
*/
private[spark] abstract class CheckpointRDD[T: ClassTag](sc: SparkContext)
extends RDD[T](sc, Nil) {
// CheckpointRDD should not be checkpointed again
override def doCheckpoint(): Unit = { }
override def checkpoint(): Unit = { }
override def localCheckpoint(): this.type = this
// Note: There is a bug in MiMa that complains about `AbstractMethodProblem`s in the
// base [[org.apache.spark.rdd.RDD]] class if we do not override the following methods.
// scalastyle:off
protected override def getPartitions: Array[Partition] = ???
override def compute(p: Partition, tc: TaskContext): Iterator[T] = ???
// scalastyle:on
}
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