Exemple #1
0
 public synchronized TaskReport[] getReduceTaskReports(String jobid) {
   JobInProgress job = (JobInProgress) jobs.get(jobid);
   if (job == null) {
     return new TaskReport[0];
   } else {
     Vector reports = new Vector();
     Vector completeReduceTasks = job.reportTasksInProgress(false, true);
     for (Iterator it = completeReduceTasks.iterator(); it.hasNext(); ) {
       TaskInProgress tip = (TaskInProgress) it.next();
       reports.add(tip.generateSingleReport());
     }
     Vector incompleteReduceTasks = job.reportTasksInProgress(false, false);
     for (Iterator it = incompleteReduceTasks.iterator(); it.hasNext(); ) {
       TaskInProgress tip = (TaskInProgress) it.next();
       reports.add(tip.generateSingleReport());
     }
     return (TaskReport[]) reports.toArray(new TaskReport[reports.size()]);
   }
 }
Exemple #2
0
  /**
   * A tracker wants to know if there's a Task to run. Returns a task we'd like the TaskTracker to
   * execute right now.
   *
   * <p>Eventually this function should compute load on the various TaskTrackers, and incorporate
   * knowledge of DFS file placement. But for right now, it just grabs a single item out of the
   * pending task list and hands it back.
   */
  public synchronized Task pollForNewTask(String taskTracker) {
    //
    // Compute average map and reduce task numbers across pool
    //
    int avgMaps = 0;
    int avgReduces = 0;
    int numTaskTrackers;
    TaskTrackerStatus tts;
    synchronized (taskTrackers) {
      numTaskTrackers = taskTrackers.size();
      tts = (TaskTrackerStatus) taskTrackers.get(taskTracker);
    }
    if (numTaskTrackers > 0) {
      avgMaps = totalMaps / numTaskTrackers;
      avgReduces = totalReduces / numTaskTrackers;
    }
    int totalCapacity = numTaskTrackers * maxCurrentTasks;
    //
    // Get map + reduce counts for the current tracker.
    //
    if (tts == null) {
      LOG.warning("Unknown task tracker polling; ignoring: " + taskTracker);
      return null;
    }

    int numMaps = tts.countMapTasks();
    int numReduces = tts.countReduceTasks();

    //
    // In the below steps, we allocate first a map task (if appropriate),
    // and then a reduce task if appropriate.  We go through all jobs
    // in order of job arrival; jobs only get serviced if their
    // predecessors are serviced, too.
    //

    //
    // We hand a task to the current taskTracker if the given machine
    // has a workload that's equal to or less than the averageMaps
    // +/- TASK_ALLOC_EPSILON.  (That epsilon is in place in case
    // there is an odd machine that is failing for some reason but
    // has not yet been removed from the pool, making capacity seem
    // larger than it really is.)
    //
    synchronized (jobsByArrival) {
      if ((numMaps < maxCurrentTasks) && (numMaps <= (avgMaps + TASK_ALLOC_EPSILON))) {

        int totalNeededMaps = 0;
        for (Iterator it = jobsByArrival.iterator(); it.hasNext(); ) {
          JobInProgress job = (JobInProgress) it.next();
          if (job.getStatus().getRunState() != JobStatus.RUNNING) {
            continue;
          }

          Task t = job.obtainNewMapTask(taskTracker, tts);
          if (t != null) {
            return t;
          }

          //
          // Beyond the highest-priority task, reserve a little
          // room for failures and speculative executions; don't
          // schedule tasks to the hilt.
          //
          totalNeededMaps += job.desiredMaps();
          double padding = 0;
          if (totalCapacity > MIN_SLOTS_FOR_PADDING) {
            padding = Math.min(maxCurrentTasks, totalNeededMaps * PAD_FRACTION);
          }
          if (totalNeededMaps + padding >= totalCapacity) {
            break;
          }
        }
      }

      //
      // Same thing, but for reduce tasks
      //
      if ((numReduces < maxCurrentTasks) && (numReduces <= (avgReduces + TASK_ALLOC_EPSILON))) {

        int totalNeededReduces = 0;
        for (Iterator it = jobsByArrival.iterator(); it.hasNext(); ) {
          JobInProgress job = (JobInProgress) it.next();
          if (job.getStatus().getRunState() != JobStatus.RUNNING) {
            continue;
          }

          Task t = job.obtainNewReduceTask(taskTracker, tts);
          if (t != null) {
            return t;
          }

          //
          // Beyond the highest-priority task, reserve a little
          // room for failures and speculative executions; don't
          // schedule tasks to the hilt.
          //
          totalNeededReduces += job.desiredReduces();
          double padding = 0;
          if (totalCapacity > MIN_SLOTS_FOR_PADDING) {
            padding = Math.min(maxCurrentTasks, totalNeededReduces * PAD_FRACTION);
          }
          if (totalNeededReduces + padding >= totalCapacity) {
            break;
          }
        }
      }
    }
    return null;
  }