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[SPARK-51184][CORE] Remove TaskState.LOST logic from TaskSchedulerImpl #49913

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[SPARK-51184][CORE] Remove TaskState.LOST logic from TaskSchedulerImpl #49913

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21 changes: 2 additions & 19 deletions core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -786,30 +786,13 @@ private[spark] class TaskSchedulerImpl(
try {
Option(taskIdToTaskSetManager.get(tid)) match {
case Some(taskSet) =>
if (state == TaskState.LOST) {
// TaskState.LOST is only used by the deprecated Mesos fine-grained scheduling mode,
// where each executor corresponds to a single task, so mark the executor as failed.
val execId = taskIdToExecutorId.getOrElse(tid, {
val errorMsg =
"taskIdToTaskSetManager.contains(tid) <=> taskIdToExecutorId.contains(tid)"
taskSet.abort(errorMsg)
throw new SparkException(
"taskIdToTaskSetManager.contains(tid) <=> taskIdToExecutorId.contains(tid)")
})
if (executorIdToRunningTaskIds.contains(execId)) {
reason = Some(
ExecutorProcessLost(
s"Task $tid was lost, so marking the executor as lost as well."))
removeExecutor(execId, reason.get)
failedExecutor = Some(execId)
}
}
assert(state != TaskState.LOST)
if (TaskState.isFinished(state)) {
cleanupTaskState(tid)
taskSet.removeRunningTask(tid)
if (state == TaskState.FINISHED) {
taskResultGetter.enqueueSuccessfulTask(taskSet, tid, serializedData)
} else if (Set(TaskState.FAILED, TaskState.KILLED, TaskState.LOST).contains(state)) {
} else if (Set(TaskState.FAILED, TaskState.KILLED).contains(state)) {
taskResultGetter.enqueueFailedTask(taskSet, tid, state, serializedData)
}
}
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36 changes: 0 additions & 36 deletions core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala
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Expand Up @@ -1369,42 +1369,6 @@ class TaskSchedulerImplSuite extends SparkFunSuite with LocalSparkContext
assert(taskScheduler.runningTasksByExecutors.get("executor0").isEmpty)
}

test("if a task finishes with TaskState.LOST its executor is marked as dead") {
sc = new SparkContext("local", "TaskSchedulerImplSuite")
val taskScheduler = new TaskSchedulerImpl(sc)
taskScheduler.initialize(new FakeSchedulerBackend)
// Need to initialize a DAGScheduler for the taskScheduler to use for callbacks.
new DAGScheduler(sc, taskScheduler) {
override def taskStarted(task: Task[_], taskInfo: TaskInfo): Unit = {}
override def executorAdded(execId: String, host: String): Unit = {}
}

val e0Offers = IndexedSeq(WorkerOffer("executor0", "host0", 1))
val attempt1 = FakeTask.createTaskSet(1)

// submit attempt 1, offer resources, task gets scheduled
taskScheduler.submitTasks(attempt1)
val taskDescriptions = taskScheduler.resourceOffers(e0Offers).flatten
assert(1 === taskDescriptions.length)

// Report the task as failed with TaskState.LOST
taskScheduler.statusUpdate(
tid = taskDescriptions.head.taskId,
state = TaskState.LOST,
serializedData = ByteBuffer.allocate(0)
)

// Check that state associated with the lost task attempt is cleaned up:
assert(taskScheduler.taskIdToExecutorId.isEmpty)
assert(taskScheduler.taskIdToTaskSetManager.isEmpty)
assert(taskScheduler.runningTasksByExecutors.get("executor0").isEmpty)

// Check that the executor has been marked as dead
assert(!taskScheduler.isExecutorAlive("executor0"))
assert(!taskScheduler.hasExecutorsAliveOnHost("host0"))
assert(taskScheduler.getExecutorsAliveOnHost("host0").isEmpty)
}

test("Locality should be used for bulk offers even with delay scheduling off") {
val conf = new SparkConf()
.set(config.LOCALITY_WAIT.key, "0")
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