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  3. org.apache.hadoop.mapreduce.v2.app.job.event.JobTaskAttemptFetchFailureEvent

Java 类org.apache.hadoop.mapreduce.v2.app.job.event.JobTaskAttemptFetchFailureEvent 实例源码

项目：hadoop    文件：TaskAttemptImpl.java    
@SuppressWarnings("unchecked")
@Override
public void transition(TaskAttemptImpl taskAttempt, 
    TaskAttemptEvent event) {
  // Status update calls don't really change the state of the attempt.
  TaskAttemptStatus newReportedStatus =
      ((TaskAttemptStatusUpdateEvent) event)
          .getReportedTaskAttemptStatus();
  // Now switch the information in the reportedStatus
  taskAttempt.reportedStatus = newReportedStatus;
  taskAttempt.reportedStatus.taskState = taskAttempt.getState();

  // send event to speculator about the reported status
  taskAttempt.eventHandler.handle
      (new SpeculatorEvent
          (taskAttempt.reportedStatus, taskAttempt.clock.getTime()));

  taskAttempt.updateProgressSplits();

  //if fetch failures are present, send the fetch failure event to job
  //this only will happen in reduce attempt type
  if (taskAttempt.reportedStatus.fetchFailedMaps != null && 
      taskAttempt.reportedStatus.fetchFailedMaps.size() > 0) {
    taskAttempt.eventHandler.handle(new JobTaskAttemptFetchFailureEvent(
        taskAttempt.attemptId, taskAttempt.reportedStatus.fetchFailedMaps));
  }
}
项目：hadoop    文件：JobImpl.java    
@Override
public void transition(JobImpl job, JobEvent event) {
  //get number of shuffling reduces
  int shufflingReduceTasks = 0;
  for (TaskId taskId : job.reduceTasks) {
    Task task = job.tasks.get(taskId);
    if (TaskState.RUNNING.equals(task.getState())) {
      for(TaskAttempt attempt : task.getAttempts().values()) {
        if(attempt.getPhase() == Phase.SHUFFLE) {
          shufflingReduceTasks++;
          break;
        }
      }
    }
  }

  JobTaskAttemptFetchFailureEvent fetchfailureEvent = 
    (JobTaskAttemptFetchFailureEvent) event;
  for (org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId mapId : 
        fetchfailureEvent.getMaps()) {
    Integer fetchFailures = job.fetchFailuresMapping.get(mapId);
    fetchFailures = (fetchFailures == null) ? 1 : (fetchFailures+1);
    job.fetchFailuresMapping.put(mapId, fetchFailures);

    float failureRate = shufflingReduceTasks == 0 ? 1.0f : 
      (float) fetchFailures / shufflingReduceTasks;
    // declare faulty if fetch-failures >= max-allowed-failures
    if (fetchFailures >= job.getMaxFetchFailuresNotifications()
        && failureRate >= job.getMaxAllowedFetchFailuresFraction()) {
      LOG.info("Too many fetch-failures for output of task attempt: " + 
          mapId + " ... raising fetch failure to map");
      job.eventHandler.handle(new TaskAttemptEvent(mapId, 
          TaskAttemptEventType.TA_TOO_MANY_FETCH_FAILURE));
      job.fetchFailuresMapping.remove(mapId);
    }
  }
}
项目：hadoop    文件：TestFetchFailure.java    
private void sendFetchFailure(MRApp app, TaskAttempt reduceAttempt, 
    TaskAttempt mapAttempt) {
  app.getContext().getEventHandler().handle(
      new JobTaskAttemptFetchFailureEvent(
          reduceAttempt.getID(), 
          Arrays.asList(new TaskAttemptId[] {mapAttempt.getID()})));
}
项目：aliyun-oss-hadoop-fs    文件：TaskAttemptImpl.java    
@SuppressWarnings("unchecked")
@Override
public void transition(TaskAttemptImpl taskAttempt, 
    TaskAttemptEvent event) {
  // Status update calls don't really change the state of the attempt.
  TaskAttemptStatus newReportedStatus =
      ((TaskAttemptStatusUpdateEvent) event)
          .getReportedTaskAttemptStatus();
  // Now switch the information in the reportedStatus
  taskAttempt.reportedStatus = newReportedStatus;
  taskAttempt.reportedStatus.taskState = taskAttempt.getState();

  // send event to speculator about the reported status
  taskAttempt.eventHandler.handle
      (new SpeculatorEvent
          (taskAttempt.reportedStatus, taskAttempt.clock.getTime()));

  taskAttempt.updateProgressSplits();

  //if fetch failures are present, send the fetch failure event to job
  //this only will happen in reduce attempt type
  if (taskAttempt.reportedStatus.fetchFailedMaps != null && 
      taskAttempt.reportedStatus.fetchFailedMaps.size() > 0) {
    String hostname = taskAttempt.container == null ? "UNKNOWN"
        : taskAttempt.container.getNodeId().getHost();
    taskAttempt.eventHandler.handle(new JobTaskAttemptFetchFailureEvent(
        taskAttempt.attemptId, taskAttempt.reportedStatus.fetchFailedMaps,
            hostname));
  }
}
项目：aliyun-oss-hadoop-fs    文件：JobImpl.java    
@Override
public void transition(JobImpl job, JobEvent event) {
  //get number of shuffling reduces
  int shufflingReduceTasks = 0;
  for (TaskId taskId : job.reduceTasks) {
    Task task = job.tasks.get(taskId);
    if (TaskState.RUNNING.equals(task.getState())) {
      for(TaskAttempt attempt : task.getAttempts().values()) {
        if(attempt.getPhase() == Phase.SHUFFLE) {
          shufflingReduceTasks++;
          break;
        }
      }
    }
  }

  JobTaskAttemptFetchFailureEvent fetchfailureEvent = 
    (JobTaskAttemptFetchFailureEvent) event;
  for (org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId mapId : 
        fetchfailureEvent.getMaps()) {
    Integer fetchFailures = job.fetchFailuresMapping.get(mapId);
    fetchFailures = (fetchFailures == null) ? 1 : (fetchFailures+1);
    job.fetchFailuresMapping.put(mapId, fetchFailures);

    float failureRate = shufflingReduceTasks == 0 ? 1.0f : 
      (float) fetchFailures / shufflingReduceTasks;
    // declare faulty if fetch-failures >= max-allowed-failures
    if (fetchFailures >= job.getMaxFetchFailuresNotifications()
        && failureRate >= job.getMaxAllowedFetchFailuresFraction()) {
      LOG.info("Too many fetch-failures for output of task attempt: " + 
          mapId + " ... raising fetch failure to map");
      job.eventHandler.handle(new TaskAttemptTooManyFetchFailureEvent(mapId,
          fetchfailureEvent.getReduce(), fetchfailureEvent.getHost()));
      job.fetchFailuresMapping.remove(mapId);
    }
  }
}
项目：aliyun-oss-hadoop-fs    文件：TestFetchFailure.java    
private void sendFetchFailure(MRApp app, TaskAttempt reduceAttempt, 
    TaskAttempt mapAttempt, String hostname) {
  app.getContext().getEventHandler().handle(
      new JobTaskAttemptFetchFailureEvent(
          reduceAttempt.getID(), 
          Arrays.asList(new TaskAttemptId[] {mapAttempt.getID()}),
              hostname));
}
项目：big-c    文件：TaskAttemptImpl.java    
@SuppressWarnings("unchecked")
@Override
public void transition(TaskAttemptImpl taskAttempt, 
    TaskAttemptEvent event) {
  // Status update calls don't really change the state of the attempt.
  TaskAttemptStatus newReportedStatus =
      ((TaskAttemptStatusUpdateEvent) event)
          .getReportedTaskAttemptStatus();
  // Now switch the information in the reportedStatus
  taskAttempt.reportedStatus = newReportedStatus;
  taskAttempt.reportedStatus.taskState = taskAttempt.getState();

  // send event to speculator about the reported status
  taskAttempt.eventHandler.handle
      (new SpeculatorEvent
          (taskAttempt.reportedStatus, taskAttempt.clock.getTime()));

  taskAttempt.updateProgressSplits();

  //if fetch failures are present, send the fetch failure event to job
  //this only will happen in reduce attempt type
  if (taskAttempt.reportedStatus.fetchFailedMaps != null && 
      taskAttempt.reportedStatus.fetchFailedMaps.size() > 0) {
    taskAttempt.eventHandler.handle(new JobTaskAttemptFetchFailureEvent(
        taskAttempt.attemptId, taskAttempt.reportedStatus.fetchFailedMaps));
  }
}
项目：big-c    文件：JobImpl.java    
@Override
public void transition(JobImpl job, JobEvent event) {
  //get number of shuffling reduces
  int shufflingReduceTasks = 0;
  for (TaskId taskId : job.reduceTasks) {
    Task task = job.tasks.get(taskId);
    if (TaskState.RUNNING.equals(task.getState())) {
      for(TaskAttempt attempt : task.getAttempts().values()) {
        if(attempt.getPhase() == Phase.SHUFFLE) {
          shufflingReduceTasks++;
          break;
        }
      }
    }
  }

  JobTaskAttemptFetchFailureEvent fetchfailureEvent = 
    (JobTaskAttemptFetchFailureEvent) event;
  for (org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId mapId : 
        fetchfailureEvent.getMaps()) {
    Integer fetchFailures = job.fetchFailuresMapping.get(mapId);
    fetchFailures = (fetchFailures == null) ? 1 : (fetchFailures+1);
    job.fetchFailuresMapping.put(mapId, fetchFailures);

    float failureRate = shufflingReduceTasks == 0 ? 1.0f : 
      (float) fetchFailures / shufflingReduceTasks;
    // declare faulty if fetch-failures >= max-allowed-failures
    if (fetchFailures >= job.getMaxFetchFailuresNotifications()
        && failureRate >= job.getMaxAllowedFetchFailuresFraction()) {
      LOG.info("Too many fetch-failures for output of task attempt: " + 
          mapId + " ... raising fetch failure to map");
      job.eventHandler.handle(new TaskAttemptEvent(mapId, 
          TaskAttemptEventType.TA_TOO_MANY_FETCH_FAILURE));
      job.fetchFailuresMapping.remove(mapId);
    }
  }
}
项目：big-c    文件：TestFetchFailure.java    
private void sendFetchFailure(MRApp app, TaskAttempt reduceAttempt, 
    TaskAttempt mapAttempt) {
  app.getContext().getEventHandler().handle(
      new JobTaskAttemptFetchFailureEvent(
          reduceAttempt.getID(), 
          Arrays.asList(new TaskAttemptId[] {mapAttempt.getID()})));
}
项目：hadoop-2.6.0-cdh5.4.3    文件：TaskAttemptImpl.java    
@SuppressWarnings("unchecked")
@Override
public void transition(TaskAttemptImpl taskAttempt, 
    TaskAttemptEvent event) {
  // Status update calls don't really change the state of the attempt.
  TaskAttemptStatus newReportedStatus =
      ((TaskAttemptStatusUpdateEvent) event)
          .getReportedTaskAttemptStatus();
  // Now switch the information in the reportedStatus
  taskAttempt.reportedStatus = newReportedStatus;
  taskAttempt.reportedStatus.taskState = taskAttempt.getState();

  // send event to speculator about the reported status
  taskAttempt.eventHandler.handle
      (new SpeculatorEvent
          (taskAttempt.reportedStatus, taskAttempt.clock.getTime()));

  taskAttempt.updateProgressSplits();

  //if fetch failures are present, send the fetch failure event to job
  //this only will happen in reduce attempt type
  if (taskAttempt.reportedStatus.fetchFailedMaps != null && 
      taskAttempt.reportedStatus.fetchFailedMaps.size() > 0) {
    taskAttempt.eventHandler.handle(new JobTaskAttemptFetchFailureEvent(
        taskAttempt.attemptId, taskAttempt.reportedStatus.fetchFailedMaps));
  }
}
项目：hadoop-2.6.0-cdh5.4.3    文件：JobImpl.java    
@Override
public void transition(JobImpl job, JobEvent event) {
  //get number of shuffling reduces
  int shufflingReduceTasks = 0;
  for (TaskId taskId : job.reduceTasks) {
    Task task = job.tasks.get(taskId);
    if (TaskState.RUNNING.equals(task.getState())) {
      for(TaskAttempt attempt : task.getAttempts().values()) {
        if(attempt.getPhase() == Phase.SHUFFLE) {
          shufflingReduceTasks++;
          break;
        }
      }
    }
  }

  JobTaskAttemptFetchFailureEvent fetchfailureEvent = 
    (JobTaskAttemptFetchFailureEvent) event;
  for (org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId mapId : 
        fetchfailureEvent.getMaps()) {
    Integer fetchFailures = job.fetchFailuresMapping.get(mapId);
    fetchFailures = (fetchFailures == null) ? 1 : (fetchFailures+1);
    job.fetchFailuresMapping.put(mapId, fetchFailures);

    float failureRate = shufflingReduceTasks == 0 ? 1.0f : 
      (float) fetchFailures / shufflingReduceTasks;
    // declare faulty if fetch-failures >= max-allowed-failures
    if (fetchFailures >= job.getMaxFetchFailuresNotifications()
        && failureRate >= job.getMaxAllowedFetchFailuresFraction()) {
      LOG.info("Too many fetch-failures for output of task attempt: " + 
          mapId + " ... raising fetch failure to map");
      job.eventHandler.handle(new TaskAttemptEvent(mapId, 
          TaskAttemptEventType.TA_TOO_MANY_FETCH_FAILURE));
      job.fetchFailuresMapping.remove(mapId);
    }
  }
}
项目：hadoop-2.6.0-cdh5.4.3    文件：TestFetchFailure.java    
private void sendFetchFailure(MRApp app, TaskAttempt reduceAttempt, 
    TaskAttempt mapAttempt) {
  app.getContext().getEventHandler().handle(
      new JobTaskAttemptFetchFailureEvent(
          reduceAttempt.getID(), 
          Arrays.asList(new TaskAttemptId[] {mapAttempt.getID()})));
}
项目：hadoop-plus    文件：TaskAttemptImpl.java    
@SuppressWarnings("unchecked")
@Override
public void transition(TaskAttemptImpl taskAttempt, 
    TaskAttemptEvent event) {
  // Status update calls don't really change the state of the attempt.
  TaskAttemptStatus newReportedStatus =
      ((TaskAttemptStatusUpdateEvent) event)
          .getReportedTaskAttemptStatus();
  // Now switch the information in the reportedStatus
  taskAttempt.reportedStatus = newReportedStatus;
  taskAttempt.reportedStatus.taskState = taskAttempt.getState();

  // send event to speculator about the reported status
  taskAttempt.eventHandler.handle
      (new SpeculatorEvent
          (taskAttempt.reportedStatus, taskAttempt.clock.getTime()));

  taskAttempt.updateProgressSplits();

  //if fetch failures are present, send the fetch failure event to job
  //this only will happen in reduce attempt type
  if (taskAttempt.reportedStatus.fetchFailedMaps != null && 
      taskAttempt.reportedStatus.fetchFailedMaps.size() > 0) {
    taskAttempt.eventHandler.handle(new JobTaskAttemptFetchFailureEvent(
        taskAttempt.attemptId, taskAttempt.reportedStatus.fetchFailedMaps));
  }
}
项目：hadoop-plus    文件：JobImpl.java    
@Override
public void transition(JobImpl job, JobEvent event) {
  //get number of shuffling reduces
  int shufflingReduceTasks = 0;
  for (TaskId taskId : job.reduceTasks) {
    Task task = job.tasks.get(taskId);
    if (TaskState.RUNNING.equals(task.getState())) {
      for(TaskAttempt attempt : task.getAttempts().values()) {
        if(attempt.getPhase() == Phase.SHUFFLE) {
          shufflingReduceTasks++;
          break;
        }
      }
    }
  }

  JobTaskAttemptFetchFailureEvent fetchfailureEvent = 
    (JobTaskAttemptFetchFailureEvent) event;
  for (org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId mapId : 
        fetchfailureEvent.getMaps()) {
    Integer fetchFailures = job.fetchFailuresMapping.get(mapId);
    fetchFailures = (fetchFailures == null) ? 1 : (fetchFailures+1);
    job.fetchFailuresMapping.put(mapId, fetchFailures);

    float failureRate = shufflingReduceTasks == 0 ? 1.0f : 
      (float) fetchFailures / shufflingReduceTasks;
    // declare faulty if fetch-failures >= max-allowed-failures
    boolean isMapFaulty =
        (failureRate >= MAX_ALLOWED_FETCH_FAILURES_FRACTION);
    if (fetchFailures >= MAX_FETCH_FAILURES_NOTIFICATIONS && isMapFaulty) {
      LOG.info("Too many fetch-failures for output of task attempt: " + 
          mapId + " ... raising fetch failure to map");
      job.eventHandler.handle(new TaskAttemptEvent(mapId, 
          TaskAttemptEventType.TA_TOO_MANY_FETCH_FAILURE));
      job.fetchFailuresMapping.remove(mapId);
    }
  }
}
项目：hadoop-plus    文件：TestFetchFailure.java    
private void sendFetchFailure(MRApp app, TaskAttempt reduceAttempt, 
    TaskAttempt mapAttempt) {
  app.getContext().getEventHandler().handle(
      new JobTaskAttemptFetchFailureEvent(
          reduceAttempt.getID(), 
          Arrays.asList(new TaskAttemptId[] {mapAttempt.getID()})));
}
项目：FlexMap    文件：TaskAttemptImpl.java    
@SuppressWarnings("unchecked")
@Override
public void transition(TaskAttemptImpl taskAttempt, 
    TaskAttemptEvent event) {
  // Status update calls don't really change the state of the attempt.
  TaskAttemptStatus newReportedStatus =
      ((TaskAttemptStatusUpdateEvent) event)
          .getReportedTaskAttemptStatus();
  // Now switch the information in the reportedStatus
  taskAttempt.reportedStatus = newReportedStatus;    
  taskAttempt.reportedStatus.taskState = taskAttempt.getState();

  // send event to speculator about the reported status
  taskAttempt.eventHandler.handle
      (new SpeculatorEvent
          (taskAttempt.reportedStatus, taskAttempt.clock.getTime()));

  taskAttempt.updateProgressSplits();

  //if fetch failures are present, send the fetch failure event to job
  //this only will happen in reduce attempt type
  if (taskAttempt.reportedStatus.fetchFailedMaps != null && 
      taskAttempt.reportedStatus.fetchFailedMaps.size() > 0) {
    taskAttempt.eventHandler.handle(new JobTaskAttemptFetchFailureEvent(
        taskAttempt.attemptId, taskAttempt.reportedStatus.fetchFailedMaps));
  }
}
项目：FlexMap    文件：JobImpl.java    
@Override
public void transition(JobImpl job, JobEvent event) {
  //get number of shuffling reduces
  int shufflingReduceTasks = 0;
  for (TaskId taskId : job.reduceTasks) {
    Task task = job.tasks.get(taskId);
    if (TaskState.RUNNING.equals(task.getState())) {
      for(TaskAttempt attempt : task.getAttempts().values()) {
        if(attempt.getPhase() == Phase.SHUFFLE) {
          shufflingReduceTasks++;
          break;
        }
      }
    }
  }

  JobTaskAttemptFetchFailureEvent fetchfailureEvent = 
    (JobTaskAttemptFetchFailureEvent) event;
  for (org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId mapId : 
        fetchfailureEvent.getMaps()) {
    Integer fetchFailures = job.fetchFailuresMapping.get(mapId);
    fetchFailures = (fetchFailures == null) ? 1 : (fetchFailures+1);
    job.fetchFailuresMapping.put(mapId, fetchFailures);

    float failureRate = shufflingReduceTasks == 0 ? 1.0f : 
      (float) fetchFailures / shufflingReduceTasks;
    // declare faulty if fetch-failures >= max-allowed-failures
    if (fetchFailures >= job.getMaxFetchFailuresNotifications()
        && failureRate >= job.getMaxAllowedFetchFailuresFraction()) {
      LOG.info("Too many fetch-failures for output of task attempt: " + 
          mapId + " ... raising fetch failure to map");
      job.eventHandler.handle(new TaskAttemptEvent(mapId, 
          TaskAttemptEventType.TA_TOO_MANY_FETCH_FAILURE));
      job.fetchFailuresMapping.remove(mapId);
    }
  }
}
项目：FlexMap    文件：TestFetchFailure.java    
private void sendFetchFailure(MRApp app, TaskAttempt reduceAttempt, 
    TaskAttempt mapAttempt) {
  app.getContext().getEventHandler().handle(
      new JobTaskAttemptFetchFailureEvent(
          reduceAttempt.getID(), 
          Arrays.asList(new TaskAttemptId[] {mapAttempt.getID()})));
}
项目：hops    文件：TaskAttemptImpl.java    
@SuppressWarnings("unchecked")
@Override
public void transition(TaskAttemptImpl taskAttempt, 
    TaskAttemptEvent event) {
  // Status update calls don't really change the state of the attempt.
  TaskAttemptStatus newReportedStatus =
      ((TaskAttemptStatusUpdateEvent) event)
          .getReportedTaskAttemptStatus();
  // Now switch the information in the reportedStatus
  taskAttempt.reportedStatus = newReportedStatus;
  taskAttempt.reportedStatus.taskState = taskAttempt.getState();

  // send event to speculator about the reported status
  taskAttempt.eventHandler.handle
      (new SpeculatorEvent
          (taskAttempt.reportedStatus, taskAttempt.clock.getTime()));

  taskAttempt.updateProgressSplits();

  //if fetch failures are present, send the fetch failure event to job
  //this only will happen in reduce attempt type
  if (taskAttempt.reportedStatus.fetchFailedMaps != null && 
      taskAttempt.reportedStatus.fetchFailedMaps.size() > 0) {
    String hostname = taskAttempt.container == null ? "UNKNOWN"
        : taskAttempt.container.getNodeId().getHost();
    taskAttempt.eventHandler.handle(new JobTaskAttemptFetchFailureEvent(
        taskAttempt.attemptId, taskAttempt.reportedStatus.fetchFailedMaps,
            hostname));
  }
}
项目：hops    文件：JobImpl.java    
@Override
public void transition(JobImpl job, JobEvent event) {
  //get number of shuffling reduces
  int shufflingReduceTasks = 0;
  for (TaskId taskId : job.reduceTasks) {
    Task task = job.tasks.get(taskId);
    if (TaskState.RUNNING.equals(task.getState())) {
      for(TaskAttempt attempt : task.getAttempts().values()) {
        if(attempt.getPhase() == Phase.SHUFFLE) {
          shufflingReduceTasks++;
          break;
        }
      }
    }
  }

  JobTaskAttemptFetchFailureEvent fetchfailureEvent = 
    (JobTaskAttemptFetchFailureEvent) event;
  for (org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId mapId : 
        fetchfailureEvent.getMaps()) {
    Integer fetchFailures = job.fetchFailuresMapping.get(mapId);
    fetchFailures = (fetchFailures == null) ? 1 : (fetchFailures+1);
    job.fetchFailuresMapping.put(mapId, fetchFailures);

    float failureRate = shufflingReduceTasks == 0 ? 1.0f : 
      (float) fetchFailures / shufflingReduceTasks;
    // declare faulty if fetch-failures >= max-allowed-failures
    if (fetchFailures >= job.getMaxFetchFailuresNotifications()
        && failureRate >= job.getMaxAllowedFetchFailuresFraction()) {
      LOG.info("Too many fetch-failures for output of task attempt: " + 
          mapId + " ... raising fetch failure to map");
      job.eventHandler.handle(new TaskAttemptTooManyFetchFailureEvent(mapId,
          fetchfailureEvent.getReduce(), fetchfailureEvent.getHost()));
      job.fetchFailuresMapping.remove(mapId);
    }
  }
}
项目：hops    文件：TestFetchFailure.java    
private void sendFetchFailure(MRApp app, TaskAttempt reduceAttempt, 
    TaskAttempt mapAttempt, String hostname) {
  app.getContext().getEventHandler().handle(
      new JobTaskAttemptFetchFailureEvent(
          reduceAttempt.getID(), 
          Arrays.asList(new TaskAttemptId[] {mapAttempt.getID()}),
              hostname));
}
项目：hadoop-TCP    文件：TaskAttemptImpl.java    
@SuppressWarnings("unchecked")
@Override
public void transition(TaskAttemptImpl taskAttempt, 
    TaskAttemptEvent event) {
  // Status update calls don't really change the state of the attempt.
  TaskAttemptStatus newReportedStatus =
      ((TaskAttemptStatusUpdateEvent) event)
          .getReportedTaskAttemptStatus();
  // Now switch the information in the reportedStatus
  taskAttempt.reportedStatus = newReportedStatus;
  taskAttempt.reportedStatus.taskState = taskAttempt.getState();

  // send event to speculator about the reported status
  taskAttempt.eventHandler.handle
      (new SpeculatorEvent
          (taskAttempt.reportedStatus, taskAttempt.clock.getTime()));

  taskAttempt.updateProgressSplits();

  //if fetch failures are present, send the fetch failure event to job
  //this only will happen in reduce attempt type
  if (taskAttempt.reportedStatus.fetchFailedMaps != null && 
      taskAttempt.reportedStatus.fetchFailedMaps.size() > 0) {
    taskAttempt.eventHandler.handle(new JobTaskAttemptFetchFailureEvent(
        taskAttempt.attemptId, taskAttempt.reportedStatus.fetchFailedMaps));
  }
}
项目：hadoop-TCP    文件：JobImpl.java    
@Override
public void transition(JobImpl job, JobEvent event) {
  //get number of shuffling reduces
  int shufflingReduceTasks = 0;
  for (TaskId taskId : job.reduceTasks) {
    Task task = job.tasks.get(taskId);
    if (TaskState.RUNNING.equals(task.getState())) {
      for(TaskAttempt attempt : task.getAttempts().values()) {
        if(attempt.getPhase() == Phase.SHUFFLE) {
          shufflingReduceTasks++;
          break;
        }
      }
    }
  }

  JobTaskAttemptFetchFailureEvent fetchfailureEvent = 
    (JobTaskAttemptFetchFailureEvent) event;
  for (org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId mapId : 
        fetchfailureEvent.getMaps()) {
    Integer fetchFailures = job.fetchFailuresMapping.get(mapId);
    fetchFailures = (fetchFailures == null) ? 1 : (fetchFailures+1);
    job.fetchFailuresMapping.put(mapId, fetchFailures);

    float failureRate = shufflingReduceTasks == 0 ? 1.0f : 
      (float) fetchFailures / shufflingReduceTasks;
    // declare faulty if fetch-failures >= max-allowed-failures
    boolean isMapFaulty =
        (failureRate >= MAX_ALLOWED_FETCH_FAILURES_FRACTION);
    if (fetchFailures >= MAX_FETCH_FAILURES_NOTIFICATIONS && isMapFaulty) {
      LOG.info("Too many fetch-failures for output of task attempt: " + 
          mapId + " ... raising fetch failure to map");
      job.eventHandler.handle(new TaskAttemptEvent(mapId, 
          TaskAttemptEventType.TA_TOO_MANY_FETCH_FAILURE));
      job.fetchFailuresMapping.remove(mapId);
    }
  }
}
项目：hadoop-TCP    文件：TestFetchFailure.java    
private void sendFetchFailure(MRApp app, TaskAttempt reduceAttempt, 
    TaskAttempt mapAttempt) {
  app.getContext().getEventHandler().handle(
      new JobTaskAttemptFetchFailureEvent(
          reduceAttempt.getID(), 
          Arrays.asList(new TaskAttemptId[] {mapAttempt.getID()})));
}
项目：hardfs    文件：TaskAttemptImpl.java    
@SuppressWarnings("unchecked")
@Override
public void transition(TaskAttemptImpl taskAttempt, 
    TaskAttemptEvent event) {
  // Status update calls don't really change the state of the attempt.
  TaskAttemptStatus newReportedStatus =
      ((TaskAttemptStatusUpdateEvent) event)
          .getReportedTaskAttemptStatus();
  // Now switch the information in the reportedStatus
  taskAttempt.reportedStatus = newReportedStatus;
  taskAttempt.reportedStatus.taskState = taskAttempt.getState();

  // send event to speculator about the reported status
  taskAttempt.eventHandler.handle
      (new SpeculatorEvent
          (taskAttempt.reportedStatus, taskAttempt.clock.getTime()));

  taskAttempt.updateProgressSplits();

  //if fetch failures are present, send the fetch failure event to job
  //this only will happen in reduce attempt type
  if (taskAttempt.reportedStatus.fetchFailedMaps != null && 
      taskAttempt.reportedStatus.fetchFailedMaps.size() > 0) {
    taskAttempt.eventHandler.handle(new JobTaskAttemptFetchFailureEvent(
        taskAttempt.attemptId, taskAttempt.reportedStatus.fetchFailedMaps));
  }
}
项目：hardfs    文件：JobImpl.java    
@Override
public void transition(JobImpl job, JobEvent event) {
  //get number of shuffling reduces
  int shufflingReduceTasks = 0;
  for (TaskId taskId : job.reduceTasks) {
    Task task = job.tasks.get(taskId);
    if (TaskState.RUNNING.equals(task.getState())) {
      for(TaskAttempt attempt : task.getAttempts().values()) {
        if(attempt.getPhase() == Phase.SHUFFLE) {
          shufflingReduceTasks++;
          break;
        }
      }
    }
  }

  JobTaskAttemptFetchFailureEvent fetchfailureEvent = 
    (JobTaskAttemptFetchFailureEvent) event;
  for (org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId mapId : 
        fetchfailureEvent.getMaps()) {
    Integer fetchFailures = job.fetchFailuresMapping.get(mapId);
    fetchFailures = (fetchFailures == null) ? 1 : (fetchFailures+1);
    job.fetchFailuresMapping.put(mapId, fetchFailures);

    float failureRate = shufflingReduceTasks == 0 ? 1.0f : 
      (float) fetchFailures / shufflingReduceTasks;
    // declare faulty if fetch-failures >= max-allowed-failures
    boolean isMapFaulty =
        (failureRate >= MAX_ALLOWED_FETCH_FAILURES_FRACTION);
    if (fetchFailures >= MAX_FETCH_FAILURES_NOTIFICATIONS && isMapFaulty) {
      LOG.info("Too many fetch-failures for output of task attempt: " + 
          mapId + " ... raising fetch failure to map");
      job.eventHandler.handle(new TaskAttemptEvent(mapId, 
          TaskAttemptEventType.TA_TOO_MANY_FETCH_FAILURE));
      job.fetchFailuresMapping.remove(mapId);
    }
  }
}
项目：hardfs    文件：TestFetchFailure.java    
private void sendFetchFailure(MRApp app, TaskAttempt reduceAttempt, 
    TaskAttempt mapAttempt) {
  app.getContext().getEventHandler().handle(
      new JobTaskAttemptFetchFailureEvent(
          reduceAttempt.getID(), 
          Arrays.asList(new TaskAttemptId[] {mapAttempt.getID()})));
}
项目：hadoop-on-lustre2    文件：TaskAttemptImpl.java    
@SuppressWarnings("unchecked")
@Override
public void transition(TaskAttemptImpl taskAttempt, 
    TaskAttemptEvent event) {
  // Status update calls don't really change the state of the attempt.
  TaskAttemptStatus newReportedStatus =
      ((TaskAttemptStatusUpdateEvent) event)
          .getReportedTaskAttemptStatus();
  // Now switch the information in the reportedStatus
  taskAttempt.reportedStatus = newReportedStatus;
  taskAttempt.reportedStatus.taskState = taskAttempt.getState();

  // send event to speculator about the reported status
  taskAttempt.eventHandler.handle
      (new SpeculatorEvent
          (taskAttempt.reportedStatus, taskAttempt.clock.getTime()));

  taskAttempt.updateProgressSplits();

  //if fetch failures are present, send the fetch failure event to job
  //this only will happen in reduce attempt type
  if (taskAttempt.reportedStatus.fetchFailedMaps != null && 
      taskAttempt.reportedStatus.fetchFailedMaps.size() > 0) {
    taskAttempt.eventHandler.handle(new JobTaskAttemptFetchFailureEvent(
        taskAttempt.attemptId, taskAttempt.reportedStatus.fetchFailedMaps));
  }
}
项目：hadoop-on-lustre2    文件：JobImpl.java    
@Override
public void transition(JobImpl job, JobEvent event) {
  //get number of shuffling reduces
  int shufflingReduceTasks = 0;
  for (TaskId taskId : job.reduceTasks) {
    Task task = job.tasks.get(taskId);
    if (TaskState.RUNNING.equals(task.getState())) {
      for(TaskAttempt attempt : task.getAttempts().values()) {
        if(attempt.getPhase() == Phase.SHUFFLE) {
          shufflingReduceTasks++;
          break;
        }
      }
    }
  }

  JobTaskAttemptFetchFailureEvent fetchfailureEvent = 
    (JobTaskAttemptFetchFailureEvent) event;
  for (org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId mapId : 
        fetchfailureEvent.getMaps()) {
    Integer fetchFailures = job.fetchFailuresMapping.get(mapId);
    fetchFailures = (fetchFailures == null) ? 1 : (fetchFailures+1);
    job.fetchFailuresMapping.put(mapId, fetchFailures);

    float failureRate = shufflingReduceTasks == 0 ? 1.0f : 
      (float) fetchFailures / shufflingReduceTasks;
    // declare faulty if fetch-failures >= max-allowed-failures
    boolean isMapFaulty =
        (failureRate >= MAX_ALLOWED_FETCH_FAILURES_FRACTION);
    if (fetchFailures >= MAX_FETCH_FAILURES_NOTIFICATIONS && isMapFaulty) {
      LOG.info("Too many fetch-failures for output of task attempt: " + 
          mapId + " ... raising fetch failure to map");
      job.eventHandler.handle(new TaskAttemptEvent(mapId, 
          TaskAttemptEventType.TA_TOO_MANY_FETCH_FAILURE));
      job.fetchFailuresMapping.remove(mapId);
    }
  }
}
项目：hadoop-on-lustre2    文件：TestFetchFailure.java    
private void sendFetchFailure(MRApp app, TaskAttempt reduceAttempt, 
    TaskAttempt mapAttempt) {
  app.getContext().getEventHandler().handle(
      new JobTaskAttemptFetchFailureEvent(
          reduceAttempt.getID(), 
          Arrays.asList(new TaskAttemptId[] {mapAttempt.getID()})));
}