use of org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt in project hadoop by apache.
the class AMWebServices method getJobTaskAttemptState.
@GET
@Path("/jobs/{jobid}/tasks/{taskid}/attempts/{attemptid}/state")
@Produces({ MediaType.APPLICATION_JSON + "; " + JettyUtils.UTF_8, MediaType.APPLICATION_XML + "; " + JettyUtils.UTF_8 })
public JobTaskAttemptState getJobTaskAttemptState(@Context HttpServletRequest hsr, @PathParam("jobid") String jid, @PathParam("taskid") String tid, @PathParam("attemptid") String attId) throws IOException, InterruptedException {
init();
Job job = getJobFromJobIdString(jid, appCtx);
checkAccess(job, hsr);
Task task = getTaskFromTaskIdString(tid, job);
TaskAttempt ta = getTaskAttemptFromTaskAttemptString(attId, task);
return new JobTaskAttemptState(ta.getState().toString());
}
use of org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt in project hadoop by apache.
the class AMWebServices method getJobTaskAttemptId.
@GET
@Path("/jobs/{jobid}/tasks/{taskid}/attempts/{attemptid}")
@Produces({ MediaType.APPLICATION_JSON + "; " + JettyUtils.UTF_8, MediaType.APPLICATION_XML + "; " + JettyUtils.UTF_8 })
public TaskAttemptInfo getJobTaskAttemptId(@Context HttpServletRequest hsr, @PathParam("jobid") String jid, @PathParam("taskid") String tid, @PathParam("attemptid") String attId) {
init();
Job job = getJobFromJobIdString(jid, appCtx);
checkAccess(job, hsr);
Task task = getTaskFromTaskIdString(tid, job);
TaskAttempt ta = getTaskAttemptFromTaskAttemptString(attId, task);
if (task.getType() == TaskType.REDUCE) {
return new ReduceTaskAttemptInfo(ta, task.getType());
} else {
return new TaskAttemptInfo(ta, task.getType(), true);
}
}
use of org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt in project hadoop by apache.
the class TestRuntimeEstimators method coreTestEstimator.
private void coreTestEstimator(TaskRuntimeEstimator testedEstimator, int expectedSpeculations) {
estimator = testedEstimator;
clock = new ControlledClock();
dispatcher = new AsyncDispatcher();
myJob = null;
slotsInUse.set(0);
completedMaps.set(0);
completedReduces.set(0);
successfulSpeculations.set(0);
taskTimeSavedBySpeculation.set(0);
clock.tickMsec(1000);
Configuration conf = new Configuration();
myAppContext = new MyAppContext(MAP_TASKS, REDUCE_TASKS);
myJob = myAppContext.getAllJobs().values().iterator().next();
estimator.contextualize(conf, myAppContext);
conf.setLong(MRJobConfig.SPECULATIVE_RETRY_AFTER_NO_SPECULATE, 500L);
conf.setLong(MRJobConfig.SPECULATIVE_RETRY_AFTER_SPECULATE, 5000L);
conf.setDouble(MRJobConfig.SPECULATIVECAP_RUNNING_TASKS, 0.1);
conf.setDouble(MRJobConfig.SPECULATIVECAP_TOTAL_TASKS, 0.001);
conf.setInt(MRJobConfig.SPECULATIVE_MINIMUM_ALLOWED_TASKS, 5);
speculator = new DefaultSpeculator(conf, myAppContext, estimator, clock);
Assert.assertEquals("wrong SPECULATIVE_RETRY_AFTER_NO_SPECULATE value", 500L, speculator.getSoonestRetryAfterNoSpeculate());
Assert.assertEquals("wrong SPECULATIVE_RETRY_AFTER_SPECULATE value", 5000L, speculator.getSoonestRetryAfterSpeculate());
Assert.assertEquals(speculator.getProportionRunningTasksSpeculatable(), 0.1, 0.00001);
Assert.assertEquals(speculator.getProportionTotalTasksSpeculatable(), 0.001, 0.00001);
Assert.assertEquals("wrong SPECULATIVE_MINIMUM_ALLOWED_TASKS value", 5, speculator.getMinimumAllowedSpeculativeTasks());
dispatcher.register(Speculator.EventType.class, speculator);
dispatcher.register(TaskEventType.class, new SpeculationRequestEventHandler());
dispatcher.init(conf);
dispatcher.start();
speculator.init(conf);
speculator.start();
// Now that the plumbing is hooked up, we do the following:
// do until all tasks are finished, ...
// 1: If we have spare capacity, assign as many map tasks as we can, then
// assign as many reduce tasks as we can. Note that an odd reduce
// task might be started while there are still map tasks, because
// map tasks take 3 slots and reduce tasks 2 slots.
// 2: Send a speculation event for every task attempt that's running
// note that new attempts might get started by the speculator
// discover undone tasks
int undoneMaps = MAP_TASKS;
int undoneReduces = REDUCE_TASKS;
// build a task sequence where all the maps precede any of the reduces
List<Task> allTasksSequence = new LinkedList<Task>();
allTasksSequence.addAll(myJob.getTasks(TaskType.MAP).values());
allTasksSequence.addAll(myJob.getTasks(TaskType.REDUCE).values());
while (undoneMaps + undoneReduces > 0) {
undoneMaps = 0;
undoneReduces = 0;
// start all attempts which are new but for which there is enough slots
for (Task task : allTasksSequence) {
if (!task.isFinished()) {
if (task.getType() == TaskType.MAP) {
++undoneMaps;
} else {
++undoneReduces;
}
}
for (TaskAttempt attempt : task.getAttempts().values()) {
if (attempt.getState() == TaskAttemptState.NEW && INITIAL_NUMBER_FREE_SLOTS - slotsInUse.get() >= taskTypeSlots(task.getType())) {
MyTaskAttemptImpl attemptImpl = (MyTaskAttemptImpl) attempt;
SpeculatorEvent event = new SpeculatorEvent(attempt.getID(), false, clock.getTime());
speculator.handle(event);
attemptImpl.startUp();
} else {
// If a task attempt is in progress we should send the news to
// the Speculator.
TaskAttemptStatus status = new TaskAttemptStatus();
status.id = attempt.getID();
status.progress = attempt.getProgress();
status.stateString = attempt.getState().name();
status.taskState = attempt.getState();
SpeculatorEvent event = new SpeculatorEvent(status, clock.getTime());
speculator.handle(event);
}
}
}
long startTime = System.currentTimeMillis();
// drain the speculator event queue
while (!speculator.eventQueueEmpty()) {
Thread.yield();
if (System.currentTimeMillis() > startTime + 130000) {
return;
}
}
clock.tickMsec(1000L);
if (clock.getTime() % 10000L == 0L) {
speculator.scanForSpeculations();
}
}
Assert.assertEquals("We got the wrong number of successful speculations.", expectedSpeculations, successfulSpeculations.get());
}
use of org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt in project hadoop by apache.
the class TestJobImpl method testUnusableNodeTransition.
@Test(timeout = 20000)
public void testUnusableNodeTransition() throws Exception {
Configuration conf = new Configuration();
conf.set(MRJobConfig.MR_AM_STAGING_DIR, stagingDir);
conf.setInt(MRJobConfig.NUM_REDUCES, 1);
DrainDispatcher dispatcher = new DrainDispatcher();
dispatcher.init(conf);
dispatcher.start();
CyclicBarrier syncBarrier = new CyclicBarrier(2);
OutputCommitter committer = new TestingOutputCommitter(syncBarrier, true);
CommitterEventHandler commitHandler = createCommitterEventHandler(dispatcher, committer);
commitHandler.init(conf);
commitHandler.start();
final JobImpl job = createRunningStubbedJob(conf, dispatcher, 2, null);
// add a special task event handler to put the task back to running in case
// of task rescheduling/killing
EventHandler<TaskAttemptEvent> taskAttemptEventHandler = new EventHandler<TaskAttemptEvent>() {
@Override
public void handle(TaskAttemptEvent event) {
if (event.getType() == TaskAttemptEventType.TA_KILL) {
job.decrementSucceededMapperCount();
}
}
};
dispatcher.register(TaskAttemptEventType.class, taskAttemptEventHandler);
// replace the tasks with spied versions to return the right attempts
Map<TaskId, Task> spiedTasks = new HashMap<TaskId, Task>();
List<NodeReport> nodeReports = new ArrayList<NodeReport>();
Map<NodeReport, TaskId> nodeReportsToTaskIds = new HashMap<NodeReport, TaskId>();
for (Map.Entry<TaskId, Task> e : job.tasks.entrySet()) {
TaskId taskId = e.getKey();
Task task = e.getValue();
if (taskId.getTaskType() == TaskType.MAP) {
// add an attempt to the task to simulate nodes
NodeId nodeId = mock(NodeId.class);
TaskAttempt attempt = mock(TaskAttempt.class);
when(attempt.getNodeId()).thenReturn(nodeId);
TaskAttemptId attemptId = MRBuilderUtils.newTaskAttemptId(taskId, 0);
when(attempt.getID()).thenReturn(attemptId);
// create a spied task
Task spied = spy(task);
doReturn(attempt).when(spied).getAttempt(any(TaskAttemptId.class));
spiedTasks.put(taskId, spied);
// create a NodeReport based on the node id
NodeReport report = mock(NodeReport.class);
when(report.getNodeState()).thenReturn(NodeState.UNHEALTHY);
when(report.getNodeId()).thenReturn(nodeId);
nodeReports.add(report);
nodeReportsToTaskIds.put(report, taskId);
}
}
// replace the tasks with the spied tasks
job.tasks.putAll(spiedTasks);
// complete all mappers first
for (TaskId taskId : job.tasks.keySet()) {
if (taskId.getTaskType() == TaskType.MAP) {
// generate a task attempt completed event first to populate the
// nodes-to-succeeded-attempts map
TaskAttemptCompletionEvent tce = Records.newRecord(TaskAttemptCompletionEvent.class);
TaskAttemptId attemptId = MRBuilderUtils.newTaskAttemptId(taskId, 0);
tce.setAttemptId(attemptId);
tce.setStatus(TaskAttemptCompletionEventStatus.SUCCEEDED);
job.handle(new JobTaskAttemptCompletedEvent(tce));
// complete the task itself
job.handle(new JobTaskEvent(taskId, TaskState.SUCCEEDED));
Assert.assertEquals(JobState.RUNNING, job.getState());
}
}
// add an event for a node transition
NodeReport firstMapperNodeReport = nodeReports.get(0);
NodeReport secondMapperNodeReport = nodeReports.get(1);
job.handle(new JobUpdatedNodesEvent(job.getID(), Collections.singletonList(firstMapperNodeReport)));
dispatcher.await();
// complete the reducer
for (TaskId taskId : job.tasks.keySet()) {
if (taskId.getTaskType() == TaskType.REDUCE) {
job.handle(new JobTaskEvent(taskId, TaskState.SUCCEEDED));
}
}
// add another event for a node transition for the other mapper
// this should not trigger rescheduling
job.handle(new JobUpdatedNodesEvent(job.getID(), Collections.singletonList(secondMapperNodeReport)));
// complete the first mapper that was rescheduled
TaskId firstMapper = nodeReportsToTaskIds.get(firstMapperNodeReport);
job.handle(new JobTaskEvent(firstMapper, TaskState.SUCCEEDED));
// verify the state is moving to committing
assertJobState(job, JobStateInternal.COMMITTING);
// let the committer complete and verify the job succeeds
syncBarrier.await();
assertJobState(job, JobStateInternal.SUCCEEDED);
dispatcher.stop();
commitHandler.stop();
}
use of org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt in project hadoop by apache.
the class TestContainerLauncher method testSlowNM.
@Test(timeout = 15000)
public void testSlowNM() throws Exception {
conf = new Configuration();
int maxAttempts = 1;
conf.setInt(MRJobConfig.MAP_MAX_ATTEMPTS, maxAttempts);
conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
// set timeout low for the test
conf.setInt("yarn.rpc.nm-command-timeout", 3000);
conf.set(YarnConfiguration.IPC_RPC_IMPL, HadoopYarnProtoRPC.class.getName());
YarnRPC rpc = YarnRPC.create(conf);
String bindAddr = "localhost:0";
InetSocketAddress addr = NetUtils.createSocketAddr(bindAddr);
NMTokenSecretManagerInNM tokenSecretManager = new NMTokenSecretManagerInNM();
MasterKey masterKey = Records.newRecord(MasterKey.class);
masterKey.setBytes(ByteBuffer.wrap("key".getBytes()));
tokenSecretManager.setMasterKey(masterKey);
conf.set(CommonConfigurationKeysPublic.HADOOP_SECURITY_AUTHENTICATION, "token");
server = rpc.getServer(ContainerManagementProtocol.class, new DummyContainerManager(), addr, conf, tokenSecretManager, 1);
server.start();
MRApp app = new MRAppWithSlowNM(tokenSecretManager);
try {
Job job = app.submit(conf);
app.waitForState(job, JobState.RUNNING);
Map<TaskId, Task> tasks = job.getTasks();
Assert.assertEquals("Num tasks is not correct", 1, tasks.size());
Task task = tasks.values().iterator().next();
app.waitForState(task, TaskState.SCHEDULED);
Map<TaskAttemptId, TaskAttempt> attempts = tasks.values().iterator().next().getAttempts();
Assert.assertEquals("Num attempts is not correct", maxAttempts, attempts.size());
TaskAttempt attempt = attempts.values().iterator().next();
app.waitForInternalState((TaskAttemptImpl) attempt, TaskAttemptStateInternal.ASSIGNED);
app.waitForState(job, JobState.FAILED);
String diagnostics = attempt.getDiagnostics().toString();
LOG.info("attempt.getDiagnostics: " + diagnostics);
Assert.assertTrue(diagnostics.contains("Container launch failed for " + "container_0_0000_01_000000 : "));
Assert.assertTrue(diagnostics.contains("java.net.SocketTimeoutException: 3000 millis timeout while waiting for channel"));
} finally {
server.stop();
app.stop();
}
}
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