spark ResultStage 源码
spark ResultStage 代码
文件路径：/core/src/main/scala/org/apache/spark/scheduler/ResultStage.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.scheduler
import org.apache.spark.TaskContext
import org.apache.spark.rdd.RDD
import org.apache.spark.util.CallSite
/**
* ResultStages apply a function on some partitions of an RDD to compute the result of an action.
* The ResultStage object captures the function to execute, `func`, which will be applied to each
* partition, and the set of partition IDs, `partitions`. Some stages may not run on all partitions
* of the RDD, for actions like first() and lookup().
*/
private[spark] class ResultStage(
id: Int,
rdd: RDD[_],
val func: (TaskContext, Iterator[_]) => _,
val partitions: Array[Int],
parents: List[Stage],
firstJobId: Int,
callSite: CallSite,
resourceProfileId: Int)
extends Stage(id, rdd, partitions.length, parents, firstJobId, callSite, resourceProfileId) {
/**
* The active job for this result stage. Will be empty if the job has already finished
* (e.g., because the job was cancelled).
*/
private[this] var _activeJob: Option[ActiveJob] = None
def activeJob: Option[ActiveJob] = _activeJob
def setActiveJob(job: ActiveJob): Unit = {
_activeJob = Option(job)
}
def removeActiveJob(): Unit = {
_activeJob = None
}
/**
* Returns the sequence of partition ids that are missing (i.e. needs to be computed).
*
* This can only be called when there is an active job.
*/
override def findMissingPartitions(): Seq[Int] = {
val job = activeJob.get
(0 until job.numPartitions).filter(id => !job.finished(id))
}
override def toString: String = "ResultStage " + id
}
相关信息
相关文章
spark BarrierJobAllocationFailed 源码
0
赞
- 所属分类： 前端技术
- 本文标签：
热门推荐
-
2、 - 优质文章
-
3、 gate.io
-
8、 golang
-
9、 openharmony
-
10、 Vue中input框自动聚焦