Java TaskType类代码示例

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
private AtomicInteger containerNeed(TaskId taskID) {
  JobId jobID = taskID.getJobId();
  TaskType taskType = taskID.getTaskType();

  ConcurrentMap<JobId, AtomicInteger> relevantMap
      = taskType == TaskType.MAP ? mapContainerNeeds : reduceContainerNeeds;

  AtomicInteger result = relevantMap.get(jobID);

  if (result == null) {
    relevantMap.putIfAbsent(jobID, new AtomicInteger(0));
    result = relevantMap.get(jobID);
  }

  return result;
}
 

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
public ReduceTaskAttemptInfo(TaskAttempt ta, TaskType type) {
  super(ta, type, false);

  this.shuffleFinishTime = ta.getShuffleFinishTime();
  this.mergeFinishTime = ta.getSortFinishTime();
  this.elapsedShuffleTime = Times.elapsed(this.startTime,
      this.shuffleFinishTime, false);
  if (this.elapsedShuffleTime == -1) {
    this.elapsedShuffleTime = 0;
  }
  this.elapsedMergeTime = Times.elapsed(this.shuffleFinishTime,
      this.mergeFinishTime, false);
  if (this.elapsedMergeTime == -1) {
    this.elapsedMergeTime = 0;
  }
  this.elapsedReduceTime = Times.elapsed(this.mergeFinishTime,
      this.finishTime, false);
  if (this.elapsedReduceTime == -1) {
    this.elapsedReduceTime = 0;
  }
}
 

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
public TaskInfo(Task task) {
  TaskType ttype = task.getType();
  this.type = ttype.toString();
  TaskReport report = task.getReport();
  this.startTime = report.getStartTime();
  this.finishTime = report.getFinishTime();
  this.state = report.getTaskState();
  this.elapsedTime = Times.elapsed(this.startTime, this.finishTime,
    this.state == TaskState.RUNNING);
  if (this.elapsedTime == -1) {
    this.elapsedTime = 0;
  }
  this.progress = report.getProgress() * 100;
  this.status =  report.getStatus();
  this.id = MRApps.toString(task.getID());
  this.taskNum = task.getID().getId();
  this.successful = getSuccessfulAttempt(task);
  if (successful != null) {
    this.successfulAttempt = MRApps.toString(successful.getID());
  } else {
    this.successfulAttempt = "";
  }
}
 

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
@GET
@Path("/jobs/{jobid}/tasks")
@Produces({ MediaType.APPLICATION_JSON, MediaType.APPLICATION_XML })
public TasksInfo getJobTasks(@Context HttpServletRequest hsr,
    @PathParam("jobid") String jid, @QueryParam("type") String type) {

  init();
  Job job = getJobFromJobIdString(jid, appCtx);
  checkAccess(job, hsr);
  TasksInfo allTasks = new TasksInfo();
  for (Task task : job.getTasks().values()) {
    TaskType ttype = null;
    if (type != null && !type.isEmpty()) {
      try {
        ttype = MRApps.taskType(type);
      } catch (YarnRuntimeException e) {
        throw new BadRequestException("tasktype must be either m or r");
      }
    }
    if (ttype != null && task.getType() != ttype) {
      continue;
    }
    allTasks.add(new TaskInfo(task));
  }
  return allTasks;
}
 

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
@GET
@Path("/jobs/{jobid}/tasks/{taskid}/attempts")
@Produces({ MediaType.APPLICATION_JSON, MediaType.APPLICATION_XML })
public TaskAttemptsInfo getJobTaskAttempts(@Context HttpServletRequest hsr,
    @PathParam("jobid") String jid, @PathParam("taskid") String tid) {

  init();
  TaskAttemptsInfo attempts = new TaskAttemptsInfo();
  Job job = getJobFromJobIdString(jid, appCtx);
  checkAccess(job, hsr);
  Task task = getTaskFromTaskIdString(tid, job);

  for (TaskAttempt ta : task.getAttempts().values()) {
    if (ta != null) {
      if (task.getType() == TaskType.REDUCE) {
        attempts.add(new ReduceTaskAttemptInfo(ta, task.getType()));
      } else {
        attempts.add(new TaskAttemptInfo(ta, task.getType(), true));
      }
    }
  }
  return attempts;
}
 

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
@Override
protected Collection<TaskAttempt> getTaskAttempts() {
  List<TaskAttempt> fewTaskAttemps = new ArrayList<TaskAttempt>();
  String taskTypeStr = $(TASK_TYPE);
  TaskType taskType = MRApps.taskType(taskTypeStr);
  String attemptStateStr = $(ATTEMPT_STATE);
  TaskAttemptStateUI neededState = MRApps
      .taskAttemptState(attemptStateStr);
  Job j = app.getJob();
  Map<TaskId, Task> tasks = j.getTasks(taskType);
  for (Task task : tasks.values()) {
    Map<TaskAttemptId, TaskAttempt> attempts = task.getAttempts();
    for (TaskAttempt attempt : attempts.values()) {
      if (neededState.correspondsTo(attempt.getState())) {
        fewTaskAttemps.add(attempt);
      }
    }
  }
  return fewTaskAttemps;
}
 

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
private ContainerRequestEvent
    createReq(JobId jobId, int taskAttemptId, int memory, String[] hosts,
        boolean earlierFailedAttempt, boolean reduce) {
  TaskId taskId;
  if (reduce) {
    taskId = MRBuilderUtils.newTaskId(jobId, 0, TaskType.REDUCE);
  } else {
    taskId = MRBuilderUtils.newTaskId(jobId, 0, TaskType.MAP);
  }
  TaskAttemptId attemptId = MRBuilderUtils.newTaskAttemptId(taskId,
      taskAttemptId);
  Resource containerNeed = Resource.newInstance(memory, 1);
  if (earlierFailedAttempt) {
    return ContainerRequestEvent
        .createContainerRequestEventForFailedContainer(attemptId,
            containerNeed);
  }
  return new ContainerRequestEvent(attemptId, containerNeed, hosts,
      new String[] { NetworkTopology.DEFAULT_RACK });
}
 

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
@SuppressWarnings("unchecked")
private void sendLaunchedEvents() {
  JobCounterUpdateEvent jce = new JobCounterUpdateEvent(attemptId.getTaskId()
      .getJobId());
  jce.addCounterUpdate(attemptId.getTaskId().getTaskType() == TaskType.MAP ?
      JobCounter.TOTAL_LAUNCHED_MAPS : JobCounter.TOTAL_LAUNCHED_REDUCES, 1);
  eventHandler.handle(jce);

  LOG.info("TaskAttempt: [" + attemptId
      + "] using containerId: [" + container.getId() + " on NM: ["
      + StringInterner.weakIntern(container.getNodeId().toString()) + "]");
  TaskAttemptStartedEvent tase =
    new TaskAttemptStartedEvent(TypeConverter.fromYarn(attemptId),
        TypeConverter.fromYarn(attemptId.getTaskId().getTaskType()),
        launchTime, trackerName, httpPort, shufflePort, container.getId(),
        locality.toString(), avataar.toString());
  eventHandler.handle(
      new JobHistoryEvent(attemptId.getTaskId().getJobId(), tase));
}
 

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
@SuppressWarnings("unchecked")
@Override
public void transition(TaskAttemptImpl taskAttempt, TaskAttemptEvent event) {
  // too many fetch failure can only happen for map tasks
  Preconditions
      .checkArgument(taskAttempt.getID().getTaskId().getTaskType() == TaskType.MAP);
  //add to diagnostic
  taskAttempt.addDiagnosticInfo("Too Many fetch failures.Failing the attempt");
  
  if (taskAttempt.getLaunchTime() != 0) {
    taskAttempt.eventHandler
        .handle(createJobCounterUpdateEventTAFailed(taskAttempt, true));
    TaskAttemptUnsuccessfulCompletionEvent tauce =
        createTaskAttemptUnsuccessfulCompletionEvent(taskAttempt,
            TaskAttemptStateInternal.FAILED);
    taskAttempt.eventHandler.handle(new JobHistoryEvent(
        taskAttempt.attemptId.getTaskId().getJobId(), tauce));
  }else {
    LOG.debug("Not generating HistoryFinish event since start event not " +
        "generated for taskAttempt: " + taskAttempt.getID());
  }
  taskAttempt.eventHandler.handle(new TaskTAttemptEvent(
      taskAttempt.attemptId, TaskEventType.T_ATTEMPT_FAILED));
}
 

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
private void computeProgress() {
  this.readLock.lock();
  try {
    float mapProgress = 0f;
    float reduceProgress = 0f;
    for (Task task : this.tasks.values()) {
      if (task.getType() == TaskType.MAP) {
        mapProgress += (task.isFinished() ? 1f : task.getProgress());
      } else {
        reduceProgress += (task.isFinished() ? 1f : task.getProgress());
      }
    }
    if (this.numMapTasks != 0) {
      mapProgress = mapProgress / this.numMapTasks;
    }
    if (this.numReduceTasks != 0) {
      reduceProgress = reduceProgress / this.numReduceTasks;
    }
    this.mapProgress = mapProgress;
    this.reduceProgress = reduceProgress;
  } finally {
    this.readLock.unlock();
  }
}
 

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
@Override
public Map<TaskId,Task> getTasks(TaskType taskType) {
  Map<TaskId, Task> localTasksCopy = tasks;
  Map<TaskId, Task> result = new HashMap<TaskId, Task>();
  Set<TaskId> tasksOfGivenType = null;
  readLock.lock();
  try {
    if (TaskType.MAP == taskType) {
      tasksOfGivenType = mapTasks;
    } else {
      tasksOfGivenType = reduceTasks;
    }
    for (TaskId taskID : tasksOfGivenType)
    result.put(taskID, localTasksCopy.get(taskID));
    return result;
  } finally {
    readLock.unlock();
  }
}
 

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
@Override
public GetTaskReportsResponse getTaskReports(
    GetTaskReportsRequest request) throws IOException {
  JobId jobId = request.getJobId();
  TaskType taskType = request.getTaskType();
  
  GetTaskReportsResponse response = 
    recordFactory.newRecordInstance(GetTaskReportsResponse.class);
  
  Job job = verifyAndGetJob(jobId, JobACL.VIEW_JOB, true);
  Collection<Task> tasks = job.getTasks(taskType).values();
  LOG.info("Getting task report for " + taskType + "   " + jobId
      + ". Report-size will be " + tasks.size());

  // Take lock to allow only one call, otherwise heap will blow up because
  // of counters in the report when there are multiple callers.
  synchronized (getTaskReportsLock) {
    for (Task task : tasks) {
      response.addTaskReport(task.getReport());
    }
  }

  return response;
}
 

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
boolean remove(TaskAttemptId tId) {
  ContainerId containerId = null;
  if (tId.getTaskId().getTaskType().equals(TaskType.MAP)) {
    containerId = maps.remove(tId).getId();
  } else {
    containerId = reduces.remove(tId).getId();
    if (containerId != null) {
      boolean preempted = preemptionWaitingReduces.remove(tId);
      if (preempted) {
        LOG.info("Reduce preemption successful " + tId);
      }
    }
  }
  
  if (containerId != null) {
    containerToAttemptMap.remove(containerId);
    return true;
  }
  return false;
}
 

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
private float getReduceProgress() {
  Job job = myAppContext.getJob(myAttemptID.getTaskId().getJobId());
  float runtime = getCodeRuntime();

  Collection<Task> allMapTasks = job.getTasks(TaskType.MAP).values();

  int numberMaps = allMapTasks.size();
  int numberDoneMaps = 0;

  for (Task mapTask : allMapTasks) {
    if (mapTask.isFinished()) {
      ++numberDoneMaps;
    }
  }

  if (numberMaps == numberDoneMaps) {
    shuffleCompletedTime = Math.min(shuffleCompletedTime, clock.getTime());

    return Math.min
        ((float) (clock.getTime() - shuffleCompletedTime)
                    / (runtime * 2000.0F) + 0.5F,
         1.0F);
  } else {
    return ((float) numberDoneMaps) / numberMaps * 0.5F;
  }
}
 

import org.apache.hadoop.mapreduce.v2.api.records.TaskType; //导入依赖的package包/类
public void verifyAMTaskAttempt(JSONObject info, TaskAttempt att,
    TaskType ttype) throws JSONException {
  if (ttype == TaskType.REDUCE) {
    assertEquals("incorrect number of elements", 17, info.length());
  } else {
    assertEquals("incorrect number of elements", 12, info.length());
  }

  verifyTaskAttemptGeneric(att, ttype, info.getString("id"),
      info.getString("state"), info.getString("type"),
      info.getString("rack"), info.getString("nodeHttpAddress"),
      info.getString("diagnostics"), info.getString("assignedContainerId"),
      info.getLong("startTime"), info.getLong("finishTime"),
      info.getLong("elapsedTime"), (float) info.getDouble("progress"));

  if (ttype == TaskType.REDUCE) {
    verifyReduceTaskAttemptGeneric(att, info.getLong("shuffleFinishTime"),
        info.getLong("mergeFinishTime"), info.getLong("elapsedShuffleTime"),
        info.getLong("elapsedMergeTime"), info.getLong("elapsedReduceTime"));
  }
}