use of org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt in project hadoop by apache.
the class TestKill method testKillTaskWaitKillJobAfterTA_DONE.
@Test
public void testKillTaskWaitKillJobAfterTA_DONE() throws Exception {
CountDownLatch latch = new CountDownLatch(1);
final Dispatcher dispatcher = new MyAsyncDispatch(latch, TaskAttemptEventType.TA_DONE);
MRApp app = new MRApp(1, 1, false, this.getClass().getName(), true) {
@Override
public Dispatcher createDispatcher() {
return dispatcher;
}
};
Job job = app.submit(new Configuration());
JobId jobId = app.getJobId();
app.waitForState(job, JobState.RUNNING);
Assert.assertEquals("Num tasks not correct", 2, job.getTasks().size());
Iterator<Task> it = job.getTasks().values().iterator();
Task mapTask = it.next();
Task reduceTask = it.next();
app.waitForState(mapTask, TaskState.RUNNING);
app.waitForState(reduceTask, TaskState.RUNNING);
TaskAttempt mapAttempt = mapTask.getAttempts().values().iterator().next();
app.waitForState(mapAttempt, TaskAttemptState.RUNNING);
TaskAttempt reduceAttempt = reduceTask.getAttempts().values().iterator().next();
app.waitForState(reduceAttempt, TaskAttemptState.RUNNING);
// The order in the dispatch event queue, from first to last
// TA_DONE
// JobEventType.JOB_KILL
// TaskAttemptEventType.TA_CONTAINER_COMPLETED ( from TA_DONE handling )
// TaskEventType.T_KILL ( from JobEventType.JOB_KILL handling )
// TaskEventType.T_ATTEMPT_SUCCEEDED ( from TA_CONTAINER_COMPLETED handling )
// Finish map
app.getContext().getEventHandler().handle(new TaskAttemptEvent(mapAttempt.getID(), TaskAttemptEventType.TA_DONE));
// Now kill the job
app.getContext().getEventHandler().handle(new JobEvent(jobId, JobEventType.JOB_KILL));
//unblock
latch.countDown();
app.waitForInternalState((JobImpl) job, JobStateInternal.KILLED);
}
use of org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt in project hadoop by apache.
the class TestKill method testKillTaskAttempt.
@Test
public void testKillTaskAttempt() throws Exception {
final CountDownLatch latch = new CountDownLatch(1);
MRApp app = new BlockingMRApp(2, 0, latch);
//this will start the job but job won't complete as Task is blocked
Job job = app.submit(new Configuration());
//wait and vailidate for Job to become RUNNING
app.waitForState(job, JobState.RUNNING);
Map<TaskId, Task> tasks = job.getTasks();
Assert.assertEquals("No of tasks is not correct", 2, tasks.size());
Iterator<Task> it = tasks.values().iterator();
Task task1 = it.next();
Task task2 = it.next();
//wait for tasks to become running
app.waitForState(task1, TaskState.SCHEDULED);
app.waitForState(task2, TaskState.SCHEDULED);
//send the kill signal to the first Task's attempt
TaskAttempt attempt = task1.getAttempts().values().iterator().next();
app.getContext().getEventHandler().handle(new TaskAttemptEvent(attempt.getID(), TaskAttemptEventType.TA_KILL));
//unblock
latch.countDown();
//wait and validate for Job to become SUCCEEDED
//job will still succeed
app.waitForState(job, JobState.SUCCEEDED);
//first Task will have two attempts 1st is killed, 2nd Succeeds
//both Tasks and Job succeeds
Assert.assertEquals("Task state not correct", TaskState.SUCCEEDED, task1.getReport().getTaskState());
Assert.assertEquals("Task state not correct", TaskState.SUCCEEDED, task2.getReport().getTaskState());
Map<TaskAttemptId, TaskAttempt> attempts = task1.getAttempts();
Assert.assertEquals("No of attempts is not correct", 2, attempts.size());
Iterator<TaskAttempt> iter = attempts.values().iterator();
Assert.assertEquals("Attempt state not correct", TaskAttemptState.KILLED, iter.next().getReport().getTaskAttemptState());
Assert.assertEquals("Attempt state not correct", TaskAttemptState.SUCCEEDED, iter.next().getReport().getTaskAttemptState());
attempts = task2.getAttempts();
Assert.assertEquals("No of attempts is not correct", 1, attempts.size());
iter = attempts.values().iterator();
Assert.assertEquals("Attempt state not correct", TaskAttemptState.SUCCEEDED, iter.next().getReport().getTaskAttemptState());
}
use of org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt in project hadoop by apache.
the class TestKill method testKillTaskWaitKillJobBeforeTA_DONE.
@Test
public void testKillTaskWaitKillJobBeforeTA_DONE() throws Exception {
CountDownLatch latch = new CountDownLatch(1);
final Dispatcher dispatcher = new MyAsyncDispatch(latch, JobEventType.JOB_KILL);
MRApp app = new MRApp(1, 1, false, this.getClass().getName(), true) {
@Override
public Dispatcher createDispatcher() {
return dispatcher;
}
};
Job job = app.submit(new Configuration());
JobId jobId = app.getJobId();
app.waitForState(job, JobState.RUNNING);
Assert.assertEquals("Num tasks not correct", 2, job.getTasks().size());
Iterator<Task> it = job.getTasks().values().iterator();
Task mapTask = it.next();
Task reduceTask = it.next();
app.waitForState(mapTask, TaskState.RUNNING);
app.waitForState(reduceTask, TaskState.RUNNING);
TaskAttempt mapAttempt = mapTask.getAttempts().values().iterator().next();
app.waitForState(mapAttempt, TaskAttemptState.RUNNING);
TaskAttempt reduceAttempt = reduceTask.getAttempts().values().iterator().next();
app.waitForState(reduceAttempt, TaskAttemptState.RUNNING);
// The order in the dispatch event queue, from first to last
// JobEventType.JOB_KILL
// TA_DONE
// TaskEventType.T_KILL ( from JobEventType.JOB_KILL handling )
// TaskAttemptEventType.TA_CONTAINER_COMPLETED ( from TA_DONE handling )
// TaskAttemptEventType.TA_KILL ( from TaskEventType.T_KILL handling )
// TaskEventType.T_ATTEMPT_SUCCEEDED ( from TA_CONTAINER_COMPLETED handling )
// TaskEventType.T_ATTEMPT_KILLED ( from TA_KILL handling )
// Now kill the job
app.getContext().getEventHandler().handle(new JobEvent(jobId, JobEventType.JOB_KILL));
// Finish map
app.getContext().getEventHandler().handle(new TaskAttemptEvent(mapAttempt.getID(), TaskAttemptEventType.TA_DONE));
//unblock
latch.countDown();
app.waitForInternalState((JobImpl) job, JobStateInternal.KILLED);
}
use of org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt in project hadoop by apache.
the class MRApp method waitForState.
public void waitForState(TaskAttempt attempt, TaskAttemptState finalState) throws Exception {
int timeoutSecs = 0;
TaskAttemptReport report = attempt.getReport();
while (!finalState.equals(report.getTaskAttemptState()) && timeoutSecs++ < 20) {
System.out.println("TaskAttempt State is : " + report.getTaskAttemptState() + " Waiting for state : " + finalState + " progress : " + report.getProgress());
report = attempt.getReport();
Thread.sleep(500);
}
System.out.println("TaskAttempt State is : " + report.getTaskAttemptState());
Assert.assertEquals("TaskAttempt state is not correct (timedout)", finalState, report.getTaskAttemptState());
}
use of org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt in project hadoop by apache.
the class MRApp method verifyCompleted.
public void verifyCompleted() {
for (Job job : getContext().getAllJobs().values()) {
JobReport jobReport = job.getReport();
System.out.println("Job start time :" + jobReport.getStartTime());
System.out.println("Job finish time :" + jobReport.getFinishTime());
Assert.assertTrue("Job start time is not less than finish time", jobReport.getStartTime() <= jobReport.getFinishTime());
Assert.assertTrue("Job finish time is in future", jobReport.getFinishTime() <= System.currentTimeMillis());
for (Task task : job.getTasks().values()) {
TaskReport taskReport = task.getReport();
System.out.println("Task start time : " + taskReport.getStartTime());
System.out.println("Task finish time : " + taskReport.getFinishTime());
Assert.assertTrue("Task start time is not less than finish time", taskReport.getStartTime() <= taskReport.getFinishTime());
for (TaskAttempt attempt : task.getAttempts().values()) {
TaskAttemptReport attemptReport = attempt.getReport();
Assert.assertTrue("Attempt start time is not less than finish time", attemptReport.getStartTime() <= attemptReport.getFinishTime());
}
}
}
}
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