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Example 46 with TaskAttemptEvent

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

the class TestTaskAttempt method testSingleRackRequest.

@Test
public void testSingleRackRequest() throws Exception {
    TaskAttemptImpl.RequestContainerTransition rct = new TaskAttemptImpl.RequestContainerTransition(false);
    EventHandler eventHandler = mock(EventHandler.class);
    String[] hosts = new String[3];
    hosts[0] = "host1";
    hosts[1] = "host2";
    hosts[2] = "host3";
    TaskSplitMetaInfo splitInfo = new TaskSplitMetaInfo(hosts, 0, 128 * 1024 * 1024l);
    TaskAttemptImpl mockTaskAttempt = createMapTaskAttemptImplForTest(eventHandler, splitInfo);
    TaskAttemptEvent mockTAEvent = mock(TaskAttemptEvent.class);
    rct.transition(mockTaskAttempt, mockTAEvent);
    ArgumentCaptor<Event> arg = ArgumentCaptor.forClass(Event.class);
    verify(eventHandler, times(2)).handle(arg.capture());
    if (!(arg.getAllValues().get(1) instanceof ContainerRequestEvent)) {
        Assert.fail("Second Event not of type ContainerRequestEvent");
    }
    ContainerRequestEvent cre = (ContainerRequestEvent) arg.getAllValues().get(1);
    String[] requestedRacks = cre.getRacks();
    //Only a single occurrence of /DefaultRack
    assertEquals(1, requestedRacks.length);
}
Also used : MapTaskAttemptImpl(org.apache.hadoop.mapred.MapTaskAttemptImpl) EventHandler(org.apache.hadoop.yarn.event.EventHandler) TaskAttemptContainerLaunchedEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptContainerLaunchedEvent) TaskTAttemptKilledEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskTAttemptKilledEvent) ContainerRequestEvent(org.apache.hadoop.mapreduce.v2.app.rm.ContainerRequestEvent) Event(org.apache.hadoop.yarn.event.Event) TaskAttemptDiagnosticsUpdateEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptDiagnosticsUpdateEvent) TaskAttemptTooManyFetchFailureEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptTooManyFetchFailureEvent) JobHistoryEvent(org.apache.hadoop.mapreduce.jobhistory.JobHistoryEvent) TaskAttemptContainerAssignedEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptContainerAssignedEvent) JobEvent(org.apache.hadoop.mapreduce.v2.app.job.event.JobEvent) TaskAttemptKillEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptKillEvent) TaskAttemptEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent) TaskEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskEvent) TaskSplitMetaInfo(org.apache.hadoop.mapreduce.split.JobSplit.TaskSplitMetaInfo) TaskAttemptEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent) ContainerRequestEvent(org.apache.hadoop.mapreduce.v2.app.rm.ContainerRequestEvent) Test(org.junit.Test)

Example 47 with TaskAttemptEvent

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

the class TestRecovery method testRecoveryWithOldCommiter.

@Test
public void testRecoveryWithOldCommiter() throws Exception {
    int runCount = 0;
    MRApp app = new MRAppWithHistory(1, 2, false, this.getClass().getName(), true, ++runCount);
    Configuration conf = new Configuration();
    conf.setBoolean("mapred.mapper.new-api", false);
    conf.setBoolean("mapred.reducer.new-api", false);
    conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
    conf.set(FileOutputFormat.OUTDIR, outputDir.toString());
    Job job = app.submit(conf);
    app.waitForState(job, JobState.RUNNING);
    Assert.assertEquals("No of tasks not correct", 3, job.getTasks().size());
    Iterator<Task> it = job.getTasks().values().iterator();
    Task mapTask1 = it.next();
    Task reduceTask1 = it.next();
    // all maps must be running
    app.waitForState(mapTask1, TaskState.RUNNING);
    TaskAttempt task1Attempt1 = mapTask1.getAttempts().values().iterator().next();
    //before sending the TA_DONE, event make sure attempt has come to 
    //RUNNING state
    app.waitForState(task1Attempt1, TaskAttemptState.RUNNING);
    //send the done signal to the map
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(task1Attempt1.getID(), TaskAttemptEventType.TA_DONE));
    //wait for map task to complete
    app.waitForState(mapTask1, TaskState.SUCCEEDED);
    // Verify the shuffle-port
    Assert.assertEquals(5467, task1Attempt1.getShufflePort());
    app.waitForState(reduceTask1, TaskState.RUNNING);
    TaskAttempt reduce1Attempt1 = reduceTask1.getAttempts().values().iterator().next();
    // write output corresponding to reduce1
    writeOutput(reduce1Attempt1, conf);
    //send the done signal to the 1st reduce
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(reduce1Attempt1.getID(), TaskAttemptEventType.TA_DONE));
    //wait for first reduce task to complete
    app.waitForState(reduceTask1, TaskState.SUCCEEDED);
    //stop the app before the job completes.
    app.stop();
    //rerun
    //in rerun the map will be recovered from previous run
    app = new MRAppWithHistory(1, 2, false, this.getClass().getName(), false, ++runCount);
    conf = new Configuration();
    conf.setBoolean(MRJobConfig.MR_AM_JOB_RECOVERY_ENABLE, true);
    conf.setBoolean("mapred.mapper.new-api", false);
    conf.setBoolean("mapred.reducer.new-api", false);
    conf.set(FileOutputFormat.OUTDIR, outputDir.toString());
    conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
    job = app.submit(conf);
    app.waitForState(job, JobState.RUNNING);
    Assert.assertEquals("No of tasks not correct", 3, job.getTasks().size());
    it = job.getTasks().values().iterator();
    mapTask1 = it.next();
    reduceTask1 = it.next();
    Task reduceTask2 = it.next();
    // map will be recovered, no need to send done
    app.waitForState(mapTask1, TaskState.SUCCEEDED);
    // Verify the shuffle-port after recovery
    task1Attempt1 = mapTask1.getAttempts().values().iterator().next();
    Assert.assertEquals(5467, task1Attempt1.getShufflePort());
    // first reduce will be recovered, no need to send done
    app.waitForState(reduceTask1, TaskState.SUCCEEDED);
    app.waitForState(reduceTask2, TaskState.RUNNING);
    TaskAttempt reduce2Attempt = reduceTask2.getAttempts().values().iterator().next();
    //before sending the TA_DONE, event make sure attempt has come to 
    //RUNNING state
    app.waitForState(reduce2Attempt, TaskAttemptState.RUNNING);
    //send the done signal to the 2nd reduce task
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(reduce2Attempt.getID(), TaskAttemptEventType.TA_DONE));
    //wait to get it completed
    app.waitForState(reduceTask2, TaskState.SUCCEEDED);
    app.waitForState(job, JobState.SUCCEEDED);
    app.verifyCompleted();
    validateOutput();
}
Also used : Task(org.apache.hadoop.mapreduce.v2.app.job.Task) Configuration(org.apache.hadoop.conf.Configuration) TaskAttemptEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent) TaskAttempt(org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt) Job(org.apache.hadoop.mapreduce.v2.app.job.Job) Test(org.junit.Test)

Example 48 with TaskAttemptEvent

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

the class TestRecovery method testRecoveryWithSpillEncryption.

@Test
public void testRecoveryWithSpillEncryption() throws Exception {
    int runCount = 0;
    MRApp app = new MRAppWithHistory(1, 1, false, this.getClass().getName(), true, ++runCount) {
    };
    Configuration conf = new Configuration();
    conf.setBoolean(MRJobConfig.MR_AM_JOB_RECOVERY_ENABLE, true);
    conf.setBoolean("mapred.mapper.new-api", true);
    conf.setBoolean("mapred.reducer.new-api", true);
    conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
    conf.set(FileOutputFormat.OUTDIR, outputDir.toString());
    conf.setBoolean(MRJobConfig.MR_ENCRYPTED_INTERMEDIATE_DATA, true);
    // run the MR job at the first attempt
    Job jobAttempt1 = app.submit(conf);
    app.waitForState(jobAttempt1, JobState.RUNNING);
    Iterator<Task> tasks = jobAttempt1.getTasks().values().iterator();
    // finish the map task but the reduce task
    Task mapper = tasks.next();
    app.waitForState(mapper, TaskState.RUNNING);
    TaskAttempt mapAttempt = mapper.getAttempts().values().iterator().next();
    app.waitForState(mapAttempt, TaskAttemptState.RUNNING);
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(mapAttempt.getID(), TaskAttemptEventType.TA_DONE));
    app.waitForState(mapper, TaskState.SUCCEEDED);
    // crash the first attempt of the MR job
    app.stop();
    // run the MR job again at the second attempt
    app = new MRAppWithHistory(1, 1, false, this.getClass().getName(), false, ++runCount);
    Job jobAttempt2 = app.submit(conf);
    Assert.assertTrue("Recovery from previous job attempt is processed even " + "though intermediate data encryption is enabled.", !app.recovered());
    // The map task succeeded from previous job attempt will not be recovered
    // because the data spill encryption is enabled.
    // Let's finish the job at the second attempt and verify its completion.
    app.waitForState(jobAttempt2, JobState.RUNNING);
    tasks = jobAttempt2.getTasks().values().iterator();
    mapper = tasks.next();
    Task reducer = tasks.next();
    // finish the map task first
    app.waitForState(mapper, TaskState.RUNNING);
    mapAttempt = mapper.getAttempts().values().iterator().next();
    app.waitForState(mapAttempt, TaskAttemptState.RUNNING);
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(mapAttempt.getID(), TaskAttemptEventType.TA_DONE));
    app.waitForState(mapper, TaskState.SUCCEEDED);
    // then finish the reduce task
    TaskAttempt redAttempt = reducer.getAttempts().values().iterator().next();
    app.waitForState(redAttempt, TaskAttemptState.RUNNING);
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(redAttempt.getID(), TaskAttemptEventType.TA_DONE));
    app.waitForState(reducer, TaskState.SUCCEEDED);
    // verify that the job succeeds at the 2rd attempt
    app.waitForState(jobAttempt2, JobState.SUCCEEDED);
}
Also used : Task(org.apache.hadoop.mapreduce.v2.app.job.Task) Configuration(org.apache.hadoop.conf.Configuration) TaskAttemptEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent) TaskAttempt(org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt) Job(org.apache.hadoop.mapreduce.v2.app.job.Job) Test(org.junit.Test)

Example 49 with TaskAttemptEvent

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

the class TestRecovery method testSpeculative.

/**
   * AM with 2 maps and 1 reduce. For 1st map, one attempt fails, one attempt
   * completely disappears because of failed launch, one attempt gets killed and
   * one attempt succeeds. AM crashes after the first tasks finishes and
   * recovers completely and succeeds in the second generation.
   * 
   * @throws Exception
   */
@Test
public void testSpeculative() throws Exception {
    int runCount = 0;
    long am1StartTimeEst = System.currentTimeMillis();
    MRApp app = new MRAppWithHistory(2, 1, false, this.getClass().getName(), true, ++runCount);
    Configuration conf = new Configuration();
    conf.setBoolean("mapred.mapper.new-api", true);
    conf.setBoolean("mapred.reducer.new-api", true);
    conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
    conf.set(FileOutputFormat.OUTDIR, outputDir.toString());
    Job job = app.submit(conf);
    app.waitForState(job, JobState.RUNNING);
    long jobStartTime = job.getReport().getStartTime();
    //all maps would be running
    Assert.assertEquals("No of 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);
    // Launch a Speculative Task for the first Task
    app.getContext().getEventHandler().handle(new TaskEvent(mapTask1.getID(), TaskEventType.T_ADD_SPEC_ATTEMPT));
    int timeOut = 0;
    while (mapTask1.getAttempts().size() != 2 && timeOut++ < 10) {
        Thread.sleep(1000);
        LOG.info("Waiting for next attempt to start");
    }
    Iterator<TaskAttempt> t1it = mapTask1.getAttempts().values().iterator();
    TaskAttempt task1Attempt1 = t1it.next();
    TaskAttempt task1Attempt2 = t1it.next();
    TaskAttempt task2Attempt = mapTask2.getAttempts().values().iterator().next();
    // wait for the second task attempt to be assigned.
    waitForContainerAssignment(task1Attempt2);
    ContainerId t1a2contId = task1Attempt2.getAssignedContainerID();
    LOG.info(t1a2contId.toString());
    LOG.info(task1Attempt1.getID().toString());
    LOG.info(task1Attempt2.getID().toString());
    // Launch container for speculative attempt
    app.getContext().getEventHandler().handle(new TaskAttemptContainerLaunchedEvent(task1Attempt2.getID(), runCount));
    //before sending the TA_DONE, event make sure attempt has come to 
    //RUNNING state
    app.waitForState(task1Attempt1, TaskAttemptState.RUNNING);
    app.waitForState(task1Attempt2, TaskAttemptState.RUNNING);
    app.waitForState(task2Attempt, TaskAttemptState.RUNNING);
    app.waitForState(reduceTask, TaskState.RUNNING);
    //send the done signal to the map 1 attempt 1
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(task1Attempt1.getID(), TaskAttemptEventType.TA_DONE));
    app.waitForState(task1Attempt1, TaskAttemptState.SUCCEEDED);
    //wait for first map task to complete
    app.waitForState(mapTask1, TaskState.SUCCEEDED);
    long task1StartTime = mapTask1.getReport().getStartTime();
    long task1FinishTime = mapTask1.getReport().getFinishTime();
    //stop the app
    app.stop();
    //rerun
    //in rerun the 1st map will be recovered from previous run
    long am2StartTimeEst = System.currentTimeMillis();
    app = new MRAppWithHistory(2, 1, false, this.getClass().getName(), false, ++runCount);
    conf = new Configuration();
    conf.setBoolean(MRJobConfig.MR_AM_JOB_RECOVERY_ENABLE, true);
    conf.setBoolean("mapred.mapper.new-api", true);
    conf.setBoolean("mapred.reducer.new-api", true);
    conf.set(FileOutputFormat.OUTDIR, outputDir.toString());
    conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
    job = app.submit(conf);
    app.waitForState(job, JobState.RUNNING);
    //all maps would be running
    Assert.assertEquals("No of tasks not correct", 3, job.getTasks().size());
    it = job.getTasks().values().iterator();
    mapTask1 = it.next();
    mapTask2 = it.next();
    reduceTask = it.next();
    // first map will be recovered, no need to send done
    app.waitForState(mapTask1, TaskState.SUCCEEDED);
    app.waitForState(mapTask2, TaskState.RUNNING);
    task2Attempt = mapTask2.getAttempts().values().iterator().next();
    //before sending the TA_DONE, event make sure attempt has come to 
    //RUNNING state
    app.waitForState(task2Attempt, TaskAttemptState.RUNNING);
    //send the done signal to the 2nd map task
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(mapTask2.getAttempts().values().iterator().next().getID(), TaskAttemptEventType.TA_DONE));
    //wait to get it completed
    app.waitForState(mapTask2, TaskState.SUCCEEDED);
    //wait for reduce to be running before sending done
    app.waitForState(reduceTask, TaskState.RUNNING);
    //send the done signal to the reduce
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(reduceTask.getAttempts().values().iterator().next().getID(), TaskAttemptEventType.TA_DONE));
    app.waitForState(job, JobState.SUCCEEDED);
    app.verifyCompleted();
    Assert.assertEquals("Job Start time not correct", jobStartTime, job.getReport().getStartTime());
    Assert.assertEquals("Task Start time not correct", task1StartTime, mapTask1.getReport().getStartTime());
    Assert.assertEquals("Task Finish time not correct", task1FinishTime, mapTask1.getReport().getFinishTime());
    Assert.assertEquals(2, job.getAMInfos().size());
    int attemptNum = 1;
    // Verify AMInfo
    for (AMInfo amInfo : job.getAMInfos()) {
        Assert.assertEquals(attemptNum++, amInfo.getAppAttemptId().getAttemptId());
        Assert.assertEquals(amInfo.getAppAttemptId(), amInfo.getContainerId().getApplicationAttemptId());
        Assert.assertEquals(MRApp.NM_HOST, amInfo.getNodeManagerHost());
        Assert.assertEquals(MRApp.NM_PORT, amInfo.getNodeManagerPort());
        Assert.assertEquals(MRApp.NM_HTTP_PORT, amInfo.getNodeManagerHttpPort());
    }
    long am1StartTimeReal = job.getAMInfos().get(0).getStartTime();
    long am2StartTimeReal = job.getAMInfos().get(1).getStartTime();
    Assert.assertTrue(am1StartTimeReal >= am1StartTimeEst && am1StartTimeReal <= am2StartTimeEst);
    Assert.assertTrue(am2StartTimeReal >= am2StartTimeEst && am2StartTimeReal <= System.currentTimeMillis());
}
Also used : Task(org.apache.hadoop.mapreduce.v2.app.job.Task) Configuration(org.apache.hadoop.conf.Configuration) TaskAttemptEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent) TaskAttemptContainerLaunchedEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptContainerLaunchedEvent) AMInfo(org.apache.hadoop.mapreduce.v2.api.records.AMInfo) ContainerId(org.apache.hadoop.yarn.api.records.ContainerId) JobTaskEvent(org.apache.hadoop.mapreduce.v2.app.job.event.JobTaskEvent) TaskEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskEvent) TaskAttempt(org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt) Job(org.apache.hadoop.mapreduce.v2.app.job.Job) Test(org.junit.Test)

Example 50 with TaskAttemptEvent

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

the class TestTaskAttempt method testKillMapTaskWhileFailFinishing.

@Test
public void testKillMapTaskWhileFailFinishing() throws Exception {
    MockEventHandler eventHandler = new MockEventHandler();
    TaskAttemptImpl taImpl = createTaskAttemptImpl(eventHandler);
    taImpl.handle(new TaskAttemptEvent(taImpl.getID(), TaskAttemptEventType.TA_FAILMSG));
    assertEquals("Task attempt is not in FAILED state", taImpl.getState(), TaskAttemptState.FAILED);
    assertEquals("Task attempt's internal state is not " + "FAIL_FINISHING_CONTAINER", taImpl.getInternalState(), TaskAttemptStateInternal.FAIL_FINISHING_CONTAINER);
    // If the map task is killed when it is in FAIL_FINISHING_CONTAINER state,
    // the state will stay in FAIL_FINISHING_CONTAINER.
    taImpl.handle(new TaskAttemptEvent(taImpl.getID(), TaskAttemptEventType.TA_KILL));
    assertEquals("Task attempt is not in RUNNING state", taImpl.getState(), TaskAttemptState.FAILED);
    assertEquals("Task attempt's internal state is not " + "FAIL_FINISHING_CONTAINER", taImpl.getInternalState(), TaskAttemptStateInternal.FAIL_FINISHING_CONTAINER);
    taImpl.handle(new TaskAttemptEvent(taImpl.getID(), TaskAttemptEventType.TA_TIMED_OUT));
    assertEquals("Task attempt's internal state is not FAIL_CONTAINER_CLEANUP", taImpl.getInternalState(), TaskAttemptStateInternal.FAIL_CONTAINER_CLEANUP);
    taImpl.handle(new TaskAttemptEvent(taImpl.getID(), TaskAttemptEventType.TA_CONTAINER_CLEANED));
    assertEquals("Task attempt's internal state is not FAIL_TASK_CLEANUP", taImpl.getInternalState(), TaskAttemptStateInternal.FAIL_TASK_CLEANUP);
    taImpl.handle(new TaskAttemptEvent(taImpl.getID(), TaskAttemptEventType.TA_CLEANUP_DONE));
    assertEquals("Task attempt is not in KILLED state", taImpl.getState(), TaskAttemptState.FAILED);
    assertFalse("InternalError occurred", eventHandler.internalError);
}
Also used : MapTaskAttemptImpl(org.apache.hadoop.mapred.MapTaskAttemptImpl) TaskAttemptEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent) Test(org.junit.Test)

Aggregations

TaskAttemptEvent (org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent)60 Test (org.junit.Test)46 TaskAttempt (org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt)30 Configuration (org.apache.hadoop.conf.Configuration)27 Job (org.apache.hadoop.mapreduce.v2.app.job.Job)27 Task (org.apache.hadoop.mapreduce.v2.app.job.Task)27 MapTaskAttemptImpl (org.apache.hadoop.mapred.MapTaskAttemptImpl)21 TaskAttemptId (org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId)21 TaskId (org.apache.hadoop.mapreduce.v2.api.records.TaskId)19 JobId (org.apache.hadoop.mapreduce.v2.api.records.JobId)16 TaskSplitMetaInfo (org.apache.hadoop.mapreduce.split.JobSplit.TaskSplitMetaInfo)14 ApplicationId (org.apache.hadoop.yarn.api.records.ApplicationId)14 ContainerId (org.apache.hadoop.yarn.api.records.ContainerId)14 AppContext (org.apache.hadoop.mapreduce.v2.app.AppContext)13 NodeId (org.apache.hadoop.yarn.api.records.NodeId)13 Path (org.apache.hadoop.fs.Path)12 JobConf (org.apache.hadoop.mapred.JobConf)12 TaskAttemptListener (org.apache.hadoop.mapreduce.v2.app.TaskAttemptListener)12 TaskAttemptContainerAssignedEvent (org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptContainerAssignedEvent)12 Credentials (org.apache.hadoop.security.Credentials)12