Examples with TaskAttemptEvent org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent used on opensource projects

Example 16 with TaskAttemptEvent

use of org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent 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);
}

Example 17 with TaskAttemptEvent

use of org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent 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());
}

Example 18 with TaskAttemptEvent

use of org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent 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);
}

Example 19 with TaskAttemptEvent

use of org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent in project hadoop by apache.

the class TestMRApp method testCommitPending.

@Test
public void testCommitPending() throws Exception {
    MRApp app = new MRApp(1, 0, false, this.getClass().getName(), true);
    Job job = app.submit(new Configuration());
    app.waitForState(job, JobState.RUNNING);
    Assert.assertEquals("Num tasks not correct", 1, job.getTasks().size());
    Iterator<Task> it = job.getTasks().values().iterator();
    Task task = it.next();
    app.waitForState(task, TaskState.RUNNING);
    TaskAttempt attempt = task.getAttempts().values().iterator().next();
    app.waitForState(attempt, TaskAttemptState.RUNNING);
    //send the commit pending signal to the task
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(attempt.getID(), TaskAttemptEventType.TA_COMMIT_PENDING));
    //wait for first attempt to commit pending
    app.waitForState(attempt, TaskAttemptState.COMMIT_PENDING);
    //re-send the commit pending signal to the task
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(attempt.getID(), TaskAttemptEventType.TA_COMMIT_PENDING));
    //the task attempt should be still at COMMIT_PENDING
    app.waitForState(attempt, TaskAttemptState.COMMIT_PENDING);
    //send the done signal to the task
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(task.getAttempts().values().iterator().next().getID(), TaskAttemptEventType.TA_DONE));
    app.waitForState(job, JobState.SUCCEEDED);
}

Example 20 with TaskAttemptEvent

use of org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent in project hadoop by apache.

the class TestMRApp method testCompletedMapsForReduceSlowstart.

//@Test
public void testCompletedMapsForReduceSlowstart() throws Exception {
    MRApp app = new MRApp(2, 1, false, this.getClass().getName(), true);
    Configuration conf = new Configuration();
    //after half of the map completion, reduce will start
    conf.setFloat(MRJobConfig.COMPLETED_MAPS_FOR_REDUCE_SLOWSTART, 0.5f);
    //uberization forces full slowstart (1.0), so disable that
    conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
    Job job = app.submit(conf);
    app.waitForState(job, JobState.RUNNING);
    //all maps would be running
    Assert.assertEquals("Num tasks not correct", 3, job.getTasks().size());
    Iterator<Task> it = job.getTasks().values().iterator();
    Task mapTask1 = it.next();
    Task mapTask2 = it.next();
    Task reduceTask = it.next();
    // all maps must be running
    app.waitForState(mapTask1, TaskState.RUNNING);
    app.waitForState(mapTask2, TaskState.RUNNING);
    TaskAttempt task1Attempt = mapTask1.getAttempts().values().iterator().next();
    TaskAttempt task2Attempt = mapTask2.getAttempts().values().iterator().next();
    //before sending the TA_DONE, event make sure attempt has come to 
    //RUNNING state
    app.waitForState(task1Attempt, TaskAttemptState.RUNNING);
    app.waitForState(task2Attempt, TaskAttemptState.RUNNING);
    // reduces must be in NEW state
    Assert.assertEquals("Reduce Task state not correct", TaskState.NEW, reduceTask.getReport().getTaskState());
    //send the done signal to the 1st map task
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(mapTask1.getAttempts().values().iterator().next().getID(), TaskAttemptEventType.TA_DONE));
    //wait for first map task to complete
    app.waitForState(mapTask1, TaskState.SUCCEEDED);
    //Once the first map completes, it will schedule the reduces
    //now reduce must be running
    app.waitForState(reduceTask, TaskState.RUNNING);
    //send the done signal to 2nd map and the reduce to complete the job
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(mapTask2.getAttempts().values().iterator().next().getID(), TaskAttemptEventType.TA_DONE));
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(reduceTask.getAttempts().values().iterator().next().getID(), TaskAttemptEventType.TA_DONE));
    app.waitForState(job, JobState.SUCCEEDED);
}