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-rw-r--r--core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala14
1 files changed, 13 insertions, 1 deletions
diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala
index c3adc28685..8e1d957568 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala
@@ -352,9 +352,11 @@ private[spark] class TaskSchedulerImpl(
}
taskIdToTaskSetManager.get(tid) match {
case Some(taskSet) =>
+ var executorId: String = null
if (TaskState.isFinished(state)) {
taskIdToTaskSetManager.remove(tid)
taskIdToExecutorId.remove(tid).foreach { execId =>
+ executorId = execId
if (executorIdToTaskCount.contains(execId)) {
executorIdToTaskCount(execId) -= 1
}
@@ -362,7 +364,17 @@ private[spark] class TaskSchedulerImpl(
}
if (state == TaskState.FINISHED) {
taskSet.removeRunningTask(tid)
- taskResultGetter.enqueueSuccessfulTask(taskSet, tid, serializedData)
+ // In some case, executor has already been removed by driver for heartbeats timeout,
+ // but at sometime, before executor killed by cluster, the task of running on this
+ // executor is finished and return task success state to driver. However, this kinds
+ // of task should be ignored, because the task on this executor is already re-queued
+ // by driver. For more details, can check in SPARK-14485.
+ if (executorId != null && !executorIdToTaskCount.contains(executorId)) {
+ logInfo(s"Ignoring update with state $state for TID $tid because its executor " +
+ s"has already been removed by driver")
+ } else {
+ taskResultGetter.enqueueSuccessfulTask(taskSet, tid, serializedData)
+ }
} else if (Set(TaskState.FAILED, TaskState.KILLED, TaskState.LOST).contains(state)) {
taskSet.removeRunningTask(tid)
taskResultGetter.enqueueFailedTask(taskSet, tid, state, serializedData)