Java Job.getTask方法代码示例

import org.apache.hadoop.mapreduce.v2.app.job.Job; //导入方法依赖的package包/类
/**
 * Child checking whether it can commit.
 * 
 * <br>
 * Commit is a two-phased protocol. First the attempt informs the
 * ApplicationMaster that it is
 * {@link #commitPending(TaskAttemptID, TaskStatus)}. Then it repeatedly polls
 * the ApplicationMaster whether it {@link #canCommit(TaskAttemptID)} This is
 * a legacy from the centralized commit protocol handling by the JobTracker.
 */
@Override
public boolean canCommit(TaskAttemptID taskAttemptID) throws IOException {
  LOG.info("Commit go/no-go request from " + taskAttemptID.toString());
  // An attempt is asking if it can commit its output. This can be decided
  // only by the task which is managing the multiple attempts. So redirect the
  // request there.
  org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId attemptID =
      TypeConverter.toYarn(taskAttemptID);

  taskHeartbeatHandler.progressing(attemptID);

  // tell task to retry later if AM has not heard from RM within the commit
  // window to help avoid double-committing in a split-brain situation
  long now = context.getClock().getTime();
  if (now - rmHeartbeatHandler.getLastHeartbeatTime() > commitWindowMs) {
    return false;
  }

  Job job = context.getJob(attemptID.getTaskId().getJobId());
  Task task = job.getTask(attemptID.getTaskId());
  return task.canCommit(attemptID);
}
 

import org.apache.hadoop.mapreduce.v2.app.job.Job; //导入方法依赖的package包/类
protected DataStatistics dataStatisticsForTask(TaskId taskID) {
  JobId jobID = taskID.getJobId();
  Job job = context.getJob(jobID);

  if (job == null) {
    return null;
  }

  Task task = job.getTask(taskID);

  if (task == null) {
    return null;
  }

  return task.getType() == TaskType.MAP
          ? mapperStatistics.get(job)
          : task.getType() == TaskType.REDUCE
              ? reducerStatistics.get(job)
              : null;
}
 

import org.apache.hadoop.mapreduce.v2.app.job.Job; //导入方法依赖的package包/类
private long storedPerAttemptValue
     (Map<TaskAttempt, AtomicLong> data, TaskAttemptId attemptID) {
  TaskId taskID = attemptID.getTaskId();
  JobId jobID = taskID.getJobId();
  Job job = context.getJob(jobID);

  Task task = job.getTask(taskID);

  if (task == null) {
    return -1L;
  }

  TaskAttempt taskAttempt = task.getAttempt(attemptID);

  if (taskAttempt == null) {
    return -1L;
  }

  AtomicLong estimate = data.get(taskAttempt);

  return estimate == null ? -1L : estimate.get();

}
 

import org.apache.hadoop.mapreduce.v2.app.job.Job; //导入方法依赖的package包/类
@Test public void testSingleTaskCounterView() {
  AppContext appContext = new MockAppContext(0, 1, 1, 2);
  Map<String, String> params = getTaskParams(appContext);
  params.put(AMParams.COUNTER_GROUP, 
      "org.apache.hadoop.mapreduce.FileSystemCounter");
  params.put(AMParams.COUNTER_NAME, "HDFS_WRITE_OPS");
  
  // remove counters from one task attempt
  // to test handling of missing counters
  TaskId taskID = MRApps.toTaskID(params.get(AMParams.TASK_ID));
  Job job = appContext.getJob(taskID.getJobId());
  Task task = job.getTask(taskID);
  TaskAttempt attempt = task.getAttempts().values().iterator().next();
  attempt.getReport().setCounters(null);
  
  WebAppTests.testPage(SingleCounterPage.class, AppContext.class,
                       appContext, params);
}
 

import org.apache.hadoop.mapreduce.v2.app.job.Job; //导入方法依赖的package包/类
@GET
@Path("/mapreduce/jobs/{jobid}/tasks/{taskid}/counters")
@Produces({ MediaType.APPLICATION_JSON, MediaType.APPLICATION_XML })
public JobTaskCounterInfo getSingleTaskCounters(
    @Context HttpServletRequest hsr, @PathParam("jobid") String jid,
    @PathParam("taskid") String tid) {

  init();
  Job job = AMWebServices.getJobFromJobIdString(jid, ctx);
  checkAccess(job, hsr);
  TaskId taskID = MRApps.toTaskID(tid);
  if (taskID == null) {
    throw new NotFoundException("taskid " + tid + " not found or invalid");
  }
  Task task = job.getTask(taskID);
  if (task == null) {
    throw new NotFoundException("task not found with id " + tid);
  }
  return new JobTaskCounterInfo(task);
}
 

import org.apache.hadoop.mapreduce.v2.app.job.Job; //导入方法依赖的package包/类
/**
 * Absorbs one TaskAttemptStatus
 *
 * @param reportedStatus the status report that we got from a task attempt
 *        that we want to fold into the speculation data for this job
 * @param timestamp the time this status corresponds to.  This matters
 *        because statuses contain progress.
 */
protected void statusUpdate(TaskAttemptStatus reportedStatus, long timestamp) {

  String stateString = reportedStatus.taskState.toString();

  TaskAttemptId attemptID = reportedStatus.id;
  TaskId taskID = attemptID.getTaskId();
  Job job = context.getJob(taskID.getJobId());

  if (job == null) {
    return;
  }

  Task task = job.getTask(taskID);

  if (task == null) {
    return;
  }

  estimator.updateAttempt(reportedStatus, timestamp);

  if (stateString.equals(TaskAttemptState.RUNNING.name())) {
    runningTasks.putIfAbsent(taskID, Boolean.TRUE);
  } else {
    runningTasks.remove(taskID, Boolean.TRUE);
    if (!stateString.equals(TaskAttemptState.STARTING.name())) {
      runningTaskAttemptStatistics.remove(attemptID);
    }
  }
}
 

import org.apache.hadoop.mapreduce.v2.app.job.Job; //导入方法依赖的package包/类
boolean canSpeculate(AppContext context, TaskId taskID) {
  // This class rejects speculating any task that already has speculations,
  //  or isn't running.
  //  Subclasses should call TaskSpeculationPredicate.canSpeculate(...) , but
  //  can be even more restrictive.
  JobId jobID = taskID.getJobId();
  Job job = context.getJob(jobID);
  Task task = job.getTask(taskID);
  return task.getAttempts().size() == 1;
}
 

import org.apache.hadoop.mapreduce.v2.app.job.Job; //导入方法依赖的package包/类
@SuppressWarnings("unchecked")
@Override
public void handle(TaskAttemptEvent event) {
  Job job = context.getJob(event.getTaskAttemptID().getTaskId().getJobId());
  Task task = job.getTask(event.getTaskAttemptID().getTaskId());
  TaskAttempt attempt = task.getAttempt(event.getTaskAttemptID());
  ((EventHandler<TaskAttemptEvent>) attempt).handle(event);
}
 

import org.apache.hadoop.mapreduce.v2.app.job.Job; //导入方法依赖的package包/类
@Override
public void updateAttempt(TaskAttemptStatus status, long timestamp) {

  TaskAttemptId attemptID = status.id;
  TaskId taskID = attemptID.getTaskId();
  JobId jobID = taskID.getJobId();
  Job job = context.getJob(jobID);

  if (job == null) {
    return;
  }

  Task task = job.getTask(taskID);

  if (task == null) {
    return;
  }

  Long boxedStart = startTimes.get(attemptID);
  long start = boxedStart == null ? Long.MIN_VALUE : boxedStart;
  
  TaskAttempt taskAttempt = task.getAttempt(attemptID);

  if (taskAttempt.getState() == TaskAttemptState.SUCCEEDED) {
    boolean isNew = false;
    // is this  a new success?
    synchronized (doneTasks) {
      if (!doneTasks.contains(task)) {
        doneTasks.add(task);
        isNew = true;
      }
    }

    // It's a new completion
    // Note that if a task completes twice [because of a previous speculation
    //  and a race, or a success followed by loss of the machine with the
    //  local data] we only count the first one.
    if (isNew) {
      long finish = timestamp;
      if (start > 1L && finish > 1L && start <= finish) {
        long duration = finish - start;

        DataStatistics statistics
        = dataStatisticsForTask(taskID);

        if (statistics != null) {
          statistics.add(duration);
        }
      }
    }
  }
}
 

import org.apache.hadoop.mapreduce.v2.app.job.Job; //导入方法依赖的package包/类
@Override
public void updateAttempt(TaskAttemptStatus status, long timestamp) {
  super.updateAttempt(status, timestamp);
  

  TaskAttemptId attemptID = status.id;
  TaskId taskID = attemptID.getTaskId();
  JobId jobID = taskID.getJobId();
  Job job = context.getJob(jobID);

  if (job == null) {
    return;
  }

  Task task = job.getTask(taskID);

  if (task == null) {
    return;
  }

  TaskAttempt taskAttempt = task.getAttempt(attemptID);

  if (taskAttempt == null) {
    return;
  }

  Long boxedStart = startTimes.get(attemptID);
  long start = boxedStart == null ? Long.MIN_VALUE : boxedStart;

  // We need to do two things.
  //  1: If this is a completion, we accumulate statistics in the superclass
  //  2: If this is not a completion, we learn more about it.

  // This is not a completion, but we're cooking.
  //
  if (taskAttempt.getState() == TaskAttemptState.RUNNING) {
    // See if this task is already in the registry
    AtomicLong estimateContainer = attemptRuntimeEstimates.get(taskAttempt);
    AtomicLong estimateVarianceContainer
        = attemptRuntimeEstimateVariances.get(taskAttempt);

    if (estimateContainer == null) {
      if (attemptRuntimeEstimates.get(taskAttempt) == null) {
        attemptRuntimeEstimates.put(taskAttempt, new AtomicLong());

        estimateContainer = attemptRuntimeEstimates.get(taskAttempt);
      }
    }

    if (estimateVarianceContainer == null) {
      attemptRuntimeEstimateVariances.putIfAbsent(taskAttempt, new AtomicLong());
      estimateVarianceContainer = attemptRuntimeEstimateVariances.get(taskAttempt);
    }


    long estimate = -1;
    long varianceEstimate = -1;

    // This code assumes that we'll never consider starting a third
    //  speculative task attempt if two are already running for this task
    if (start > 0 && timestamp > start) {
      estimate = (long) ((timestamp - start) / Math.max(0.0001, status.progress));
      varianceEstimate = (long) (estimate * status.progress / 10);
    }
    if (estimateContainer != null) {
      estimateContainer.set(estimate);
    }
    if (estimateVarianceContainer != null) {
      estimateVarianceContainer.set(varianceEstimate);
    }
  }
}