Github user mateiz commented on a diff in the pull request:
https://github.com/apache/spark/pull/186#discussion_r11930502
--- Diff: core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
---
@@ -730,6 +588,100 @@ class DAGScheduler(
}
}
+ private[scheduler] def handleJobGroupCancelled(groupId: String) {
+ // Cancel all jobs belonging to this job group.
+ // First finds all active jobs with this group id, and then kill
stages for them.
+ val activeInGroup = activeJobs.filter(activeJob =>
+ groupId == activeJob.properties.get(SparkContext.SPARK_JOB_GROUP_ID))
+ val jobIds = activeInGroup.map(_.jobId)
+ jobIds.foreach(handleJobCancellation(_, "part of cancel job group"))
+ submitWaitingStages()
+ }
+
+ private[scheduler] def handleBeginEvent(task: Task[_], taskInfo:
TaskInfo) {
+ for (stage <- stageIdToStage.get(task.stageId); stageInfo <-
stageToInfos.get(stage)) {
+ if (taskInfo.serializedSize > DAGScheduler.TASK_SIZE_TO_WARN * 1024
&&
+ !stageInfo.emittedTaskSizeWarning) {
+ stageInfo.emittedTaskSizeWarning = true
+ logWarning(("Stage %d (%s) contains a task of very large " +
+ "size (%d KB). The maximum recommended task size is %d
KB.").format(
+ task.stageId, stageInfo.name, taskInfo.serializedSize / 1024,
+ DAGScheduler.TASK_SIZE_TO_WARN))
+ }
+ }
+ listenerBus.post(SparkListenerTaskStart(task.stageId, taskInfo))
+ submitWaitingStages()
+ }
+
+ private[scheduler] def handleTaskSetFailed(taskSet: TaskSet, reason:
String) {
+ stageIdToStage.get(taskSet.stageId).foreach {abortStage(_, reason) }
+ submitWaitingStages()
+ }
+
+ private[scheduler] def cleanUpAfterSchedulerStop() {
+ for (job <- activeJobs) {
+ val error = new SparkException("Job cancelled because SparkContext
was shut down")
+ job.listener.jobFailed(error)
+ // Tell the listeners that all of the running stages have ended.
Don't bother
+ // cancelling the stages because if the DAG scheduler is stopped,
the entire application
+ // is in the process of getting stopped.
+ val stageFailedMessage = "Stage cancelled because SparkContext was
shut down"
+ runningStages.foreach { stage =>
+ val info = stageToInfos(stage)
+ info.stageFailed(stageFailedMessage)
+ listenerBus.post(SparkListenerStageCompleted(info))
+ }
+ listenerBus.post(SparkListenerJobEnd(job.jobId, JobFailed(error)))
+ }
+ }
+
+ private[scheduler] def handleGetTaskResult(taskInfo: TaskInfo) {
+ listenerBus.post(SparkListenerTaskGettingResult(taskInfo))
+ submitWaitingStages()
+ }
+
+ private[scheduler] def handleJobSubmitted(jobId: Int,
+ finalRDD: RDD[_],
+ func: (TaskContext, Iterator[_]) => _,
+ partitions: Array[Int],
+ allowLocal: Boolean,
+ callSite: String,
+ listener: JobListener,
+ properties: Properties = null) {
+ var finalStage: Stage = null
+ try {
+ // New stage creation may throw an exception if, for example, jobs
are run on a
+ // HadoopRDD whose underlying HDFS files have been deleted.
+ finalStage = newStage(finalRDD, partitions.size, None, jobId,
Some(callSite))
+ } catch {
+ case e: Exception =>
+ logWarning("Creating new stage failed due to exception - job: " +
jobId, e)
+ listener.jobFailed(e)
--- End diff --
To match the previous behavior, you still need to do `return` here.
Otherwise it will keep going to the rest of the method, which would break.
Please add attest for this actually if you can (just create a text file, call
Spark.textFile on it, then delete the file on the filesystem and try to run a
job).
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