Github user devaraj-kavali commented on a diff in the pull request:

    https://github.com/apache/spark/pull/11996#discussion_r58563479
  
    --- Diff: 
core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala ---
    @@ -789,6 +791,51 @@ class TaskSetManagerSuite extends SparkFunSuite with 
LocalSparkContext with Logg
         assert(TaskLocation("executor_host1_3") === 
ExecutorCacheTaskLocation("host1", "3"))
       }
     
    +  test("Kill other task attempts when one attempt belonging to the same 
task succeeds") {
    +    sc = new SparkContext("local", "test")
    +    val sched = new FakeTaskScheduler(sc, ("exec1", "host1"), ("exec2", 
"host2"))
    +    val taskSet = FakeTask.createTaskSet(4)
    +    val manager = new TaskSetManager(sched, taskSet, MAX_TASK_FAILURES)
    +    val accumUpdatesByTask: Array[Seq[AccumulableInfo]] = 
taskSet.tasks.map { task =>
    +      task.initialAccumulators.map { a => a.toInfo(Some(0L), None) }
    +    }
    +    // Offer resources for 4 tasks to start
    +    for ((k, v) <- List(
    +        "exec1" -> "host1",
    +        "exec1" -> "host1",
    +        "exec2" -> "host2",
    +        "exec2" -> "host2")) {
    +      val taskOption = manager.resourceOffer(k, v, NO_PREF)
    +      assert(taskOption.isDefined)
    +      val task = taskOption.get
    +      assert(task.executorId === k)
    +    }
    +    assert(sched.startedTasks.toSet === Set(0, 1, 2, 3))
    +    // Complete the 3 tasks and leave 1 task in running
    +    for (id <- Set(0, 1, 2)) {
    +      manager.handleSuccessfulTask(id, createTaskResult(id, 
accumUpdatesByTask(id)))
    +      assert(sched.endedTasks(id) === Success)
    +    }
    +
    +    // Wait for the threshold time to start speculative attempt for the 
running task
    +    Thread.sleep(100)
    --- End diff --
    
    Thanks @tgravescs for your quick response.
    
    Here Thread.sleep(100) is to match the threshold value mentioned in 
TaskSetManager.checkSpeculatableTasks(). It is the minimum time where the task 
needs to run for this much of time before becoming eligible for launching a 
speculative attempt. I don't see any way to change this default value.
    
    > val medianDuration = durations(min((0.5 * tasksSuccessful).round.toInt, 
durations.length - 1))
    > val threshold = max(SPECULATION_MULTIPLIER * medianDuration, 100)
    > 
    
    I don't think this threshold value is related to the config 
‘spark.speculation.interval’ here.



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