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From "smarthan (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (MAPREDUCE-7074) Shuffle get stuck in fetch failures loop, when a few mapoutput were lost or corrupted and task timeout was set to 0
Date Mon, 09 Apr 2018 15:43:00 GMT

     [ https://issues.apache.org/jira/browse/MAPREDUCE-7074?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

smarthan updated MAPREDUCE-7074:
--------------------------------
    Description: 
When a MR job like this:
 - MR job with many map tasks, such as 10000 or more
 - a few map output were lost or corrupted after map task complete successfully and before
shuffle start
 - mapreduce.task.timeout was set to 0 and mapreduce.task.progress-report.interval was not
set

the shuffle of reduce task will get stuck in fetch failures loop for a long time, several
or even dozens of hours.

It was caused by MAPREDUCE-6740, it releate mapreduce.task.timeout with mapreduce.task.progress-report.interval
by MRJobConfUtil.getTaskProgressReportInterval()
{code:java}
  public static long getTaskProgressReportInterval(final Configuration conf) {
    long taskHeartbeatTimeOut = conf.getLong(
        MRJobConfig.TASK_TIMEOUT, MRJobConfig.DEFAULT_TASK_TIMEOUT_MILLIS);
    return conf.getLong(MRJobConfig.TASK_PROGRESS_REPORT_INTERVAL,
        (long) (TASK_REPORT_INTERVAL_TO_TIMEOUT_RATIO * taskHeartbeatTimeOut));
  }
{code}
When mapreduce.task.timeout was set to 0 and mapreduce.task.progress-report.interval was not
set, getTaskProgressReportInterval will retrun 0L.
 In the class TaskReporter which is used to report task progress and status to AM, it set
taskProgressInterval= MRJobConfUtil.getTaskProgressReportInterval(), and lock.wait(taskProgressInterval)
before every progress report.
{code:java}
 public void run() {
      ...skip...
      long taskProgressInterval = MRJobConfUtil.
          getTaskProgressReportInterval(conf);
      while (!taskDone.get()) {
        ...skip...
        try {
          // sleep for a bit
          synchronized(lock) {
            if (taskDone.get()) {
              break;
            }
            lock.wait(taskProgressInterval);
          }
          if (taskDone.get()) {
            break;
          }
          if (sendProgress) {
            // we need to send progress update
            updateCounters();
            taskStatus.statusUpdate(taskProgress.get(),
                                    taskProgress.toString(), 
                                    counters);
            taskFound = umbilical.statusUpdate(taskId, taskStatus);
            taskStatus.clearStatus();
          }
          ...skip...
        } 
        ...skip...
      }
   }
{code}
When mapreduce.task.timeout was set to 0, lock.wait(taskProgressInterval) will be lock.wait(0),
and because there is no operation to notify it ,the reporter will wait all the time and don't
report anything to AM. 
 So, when fetch failures happend in shuffle, TaskReporter will not report fetch failures to
AM , although the log of reducer show message"Reporting fetch failure...", and the fetch failures
loop will not stop util reduce task failed for exceeded MAX_FAILED_UNIQUE_FETCHES.

So, it's necessary to set a TASK_PROGRESS_REPORT_INTERVAL_MAX value (such as 30s) when the
taskProgressInterval return by MRJobConfUtil.getTaskProgressReportInterval() equals 0 or beyond
the max value, set the taskProgressInterval = TASK_PROGRESS_REPORT_INTERVAL_MAX. 

  was:
When a MR job like this:
 - MR job with many map tasks, such as 10000 or more
 - a few map output were lost or corrupted after map task complete successfully and before
shuffle start
 - mapreduce.task.timeout was set to 0 and mapreduce.task.progress-report.interval was not
set

the shuffle of reduce task will get stuck in fetch failures loop for a long time, several
or even dozens of hours.

It was caused by MAPREDUCE-6740, it releate mapreduce.task.timeout with mapreduce.task.progress-report.interval
by MRJobConfUtil.getTaskProgressReportInterval()
{code:java}
  public static long getTaskProgressReportInterval(final Configuration conf) {
    long taskHeartbeatTimeOut = conf.getLong(
        MRJobConfig.TASK_TIMEOUT, MRJobConfig.DEFAULT_TASK_TIMEOUT_MILLIS);
    return conf.getLong(MRJobConfig.TASK_PROGRESS_REPORT_INTERVAL,
        (long) (TASK_REPORT_INTERVAL_TO_TIMEOUT_RATIO * taskHeartbeatTimeOut));
  }
{code}
When mapreduce.task.timeout was set to 0 and mapreduce.task.progress-report.interval was not
set, getTaskProgressReportInterval will retrun 0L.
 In the class TaskReporter which is used to report task progress and status to AM, it set
taskProgressInterval= MRJobConfUtil.getTaskProgressReportInterval(), and lock.wait(taskProgressInterval)
before every progress report.
{code:java}
 public void run() {
      ...skip...
      long taskProgressInterval = MRJobConfUtil.
          getTaskProgressReportInterval(conf);
      while (!taskDone.get()) {
        ...skip...
        try {
          // sleep for a bit
          synchronized(lock) {
            if (taskDone.get()) {
              break;
            }
            lock.wait(taskProgressInterval);
          }
          if (taskDone.get()) {
            break;
          }
          if (sendProgress) {
            // we need to send progress update
            updateCounters();
            taskStatus.statusUpdate(taskProgress.get(),
                                    taskProgress.toString(), 
                                    counters);
            taskFound = umbilical.statusUpdate(taskId, taskStatus);
            taskStatus.clearStatus();
          }
          ...skip...
        } 
        ...skip...
      }
   }
{code}
When mapreduce.task.timeout was set to 0, lock.wait(taskProgressInterval) will be lock.wait(0),
and because there is no operation to notify it ,the reporter will wait all the time and don't
report anything to AM. 
 So, when fetch failures happend in shuffle, TaskReporter will not report fetch failures to
AM , although the log of reducer show message"Reporting fetch failure...", and the fetch failures
loop will not stop util reduce task failed for exceeded MAX_FAILED_UNIQUE_FETCHES.

So, it's necessary to set a TASK_PROGRESS_REPORT_INTERVAL_MAX value (such as 30s) when the
taskProgressInterval return by MRJobConfUtil.getTaskProgressReportInterval() equals 0 or beyond
the max value, set the taskProgressInterval = TASK_PROGRESS_REPORT_INTERVAL_MAX.

Exception Message:

2018-04-09 14:57:08,610 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.Fetcher:
for url=6562/mapOutput?job=job_1523233330039_13196&reduce=0&map=attempt_1523233330039_13196_m_003652_0,attempt_1523233330039_13196_m_001331_0,attempt_1523233330039_13196_m_000342_0,attempt_1523233330039_13196_m_000105_0,attempt_1523233330039_13196_m_001211_0,attempt_1523233330039_13196_m_002219_0,attempt_1523233330039_13196_m_004747_0,attempt_1523233330039_13196_m_000062_0
sent hash and received reply
2018-04-09 14:57:08,612 WARN [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.Fetcher:
Invalid map id 
java.lang.IllegalArgumentException: TaskAttemptId string : TTP/1.1 500 Internal Server Error
Content-Type: text/plain; charset=UTF is not properly formed
	at org.apache.hadoop.mapreduce.TaskAttemptID.forName(TaskAttemptID.java:201)
	at org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyMapOutput(Fetcher.java:510)
	at org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyFromHost(Fetcher.java:348)
	at org.apache.hadoop.mapreduce.task.reduce.Fetcher.run(Fetcher.java:198)
2018-04-09 14:57:08,612 WARN [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.Fetcher:
copyMapOutput failed for tasks [attempt_1523233330039_13196_m_003652_0, attempt_1523233330039_13196_m_001331_0,
attempt_1523233330039_13196_m_000342_0, attempt_1523233330039_13196_m_000105_0, attempt_1523233330039_13196_m_001211_0,
attempt_1523233330039_13196_m_002219_0, attempt_1523233330039_13196_m_004747_0, attempt_1523233330039_13196_m_000062_0]
2018-04-09 14:57:08,612 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_003652_0 to jobtracker.
2018-04-09 14:57:08,612 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_001331_0 to jobtracker.
2018-04-09 14:57:08,612 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_000342_0 to jobtracker.
2018-04-09 14:57:08,612 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_000105_0 to jobtracker.
2018-04-09 14:57:08,612 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_001211_0 to jobtracker.
2018-04-09 14:57:08,612 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_002219_0 to jobtracker.
2018-04-09 14:57:08,612 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_004747_0 to jobtracker.
2018-04-09 14:57:08,612 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_000062_0 to jobtracker.
...
2018-04-09 22:51:02,142 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.Fetcher:
for url=6562/mapOutput?job=job_1523233330039_13196&reduce=0&map=attempt_1523233330039_13196_m_003652_0,attempt_1523233330039_13196_m_001331_0,attempt_1523233330039_13196_m_000342_0,attempt_1523233330039_13196_m_000105_0,attempt_1523233330039_13196_m_001211_0,attempt_1523233330039_13196_m_002219_0,attempt_1523233330039_13196_m_004747_0,attempt_1523233330039_13196_m_000062_0
sent hash and received reply
2018-04-09 22:51:02,154 WARN [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.Fetcher:
Invalid map id 
java.lang.IllegalArgumentException: TaskAttemptId string : TTP/1.1 500 Internal Server Error
Content-Type: text/plain; charset=UTF is not properly formed
  at org.apache.hadoop.mapreduce.TaskAttemptID.forName(TaskAttemptID.java:201)
  at org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyMapOutput(Fetcher.java:510)
  at org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyFromHost(Fetcher.java:348)
  at org.apache.hadoop.mapreduce.task.reduce.Fetcher.run(Fetcher.java:198)
2018-04-09 22:51:02,156 WARN [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.Fetcher:
copyMapOutput failed for tasks [attempt_1523233330039_13196_m_003652_0, attempt_1523233330039_13196_m_001331_0,
attempt_1523233330039_13196_m_000342_0, attempt_1523233330039_13196_m_000105_0, attempt_1523233330039_13196_m_001211_0,
attempt_1523233330039_13196_m_002219_0, attempt_1523233330039_13196_m_004747_0, attempt_1523233330039_13196_m_000062_0]
2018-04-09 22:51:02,157 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_003652_0 to jobtracker.
2018-04-09 22:51:02,157 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_001331_0 to jobtracker.
2018-04-09 22:51:02,157 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_000342_0 to jobtracker.
2018-04-09 22:51:02,157 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_000105_0 to jobtracker.
2018-04-09 22:51:02,157 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_001211_0 to jobtracker.
2018-04-09 22:51:02,157 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_002219_0 to jobtracker.
2018-04-09 22:51:02,157 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_004747_0 to jobtracker.
2018-04-09 22:51:02,157 INFO [fetcher#3] org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl:
Reporting fetch failure for attempt_1523233330039_13196_m_000062_0 to jobtracker.


 


> Shuffle  get stuck in fetch failures loop, when a few mapoutput were lost or corrupted
and task timeout was set to 0
> --------------------------------------------------------------------------------------------------------------------
>
>                 Key: MAPREDUCE-7074
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-7074
>             Project: Hadoop Map/Reduce
>          Issue Type: Bug
>          Components: mrv2, task
>    Affects Versions: 2.8.0, 3.0.0
>         Environment: cdh 5.10.0 ,  apache hadoop 2.8.0
>            Reporter: smarthan
>            Priority: Major
>             Fix For: 2.8.0
>
>
> When a MR job like this:
>  - MR job with many map tasks, such as 10000 or more
>  - a few map output were lost or corrupted after map task complete successfully and before
shuffle start
>  - mapreduce.task.timeout was set to 0 and mapreduce.task.progress-report.interval was
not set
> the shuffle of reduce task will get stuck in fetch failures loop for a long time, several
or even dozens of hours.
> It was caused by MAPREDUCE-6740, it releate mapreduce.task.timeout with mapreduce.task.progress-report.interval
by MRJobConfUtil.getTaskProgressReportInterval()
> {code:java}
>   public static long getTaskProgressReportInterval(final Configuration conf) {
>     long taskHeartbeatTimeOut = conf.getLong(
>         MRJobConfig.TASK_TIMEOUT, MRJobConfig.DEFAULT_TASK_TIMEOUT_MILLIS);
>     return conf.getLong(MRJobConfig.TASK_PROGRESS_REPORT_INTERVAL,
>         (long) (TASK_REPORT_INTERVAL_TO_TIMEOUT_RATIO * taskHeartbeatTimeOut));
>   }
> {code}
> When mapreduce.task.timeout was set to 0 and mapreduce.task.progress-report.interval
was not set, getTaskProgressReportInterval will retrun 0L.
>  In the class TaskReporter which is used to report task progress and status to AM, it
set taskProgressInterval= MRJobConfUtil.getTaskProgressReportInterval(), and lock.wait(taskProgressInterval)
before every progress report.
> {code:java}
>  public void run() {
>       ...skip...
>       long taskProgressInterval = MRJobConfUtil.
>           getTaskProgressReportInterval(conf);
>       while (!taskDone.get()) {
>         ...skip...
>         try {
>           // sleep for a bit
>           synchronized(lock) {
>             if (taskDone.get()) {
>               break;
>             }
>             lock.wait(taskProgressInterval);
>           }
>           if (taskDone.get()) {
>             break;
>           }
>           if (sendProgress) {
>             // we need to send progress update
>             updateCounters();
>             taskStatus.statusUpdate(taskProgress.get(),
>                                     taskProgress.toString(), 
>                                     counters);
>             taskFound = umbilical.statusUpdate(taskId, taskStatus);
>             taskStatus.clearStatus();
>           }
>           ...skip...
>         } 
>         ...skip...
>       }
>    }
> {code}
> When mapreduce.task.timeout was set to 0, lock.wait(taskProgressInterval) will be lock.wait(0),
and because there is no operation to notify it ,the reporter will wait all the time and don't
report anything to AM. 
>  So, when fetch failures happend in shuffle, TaskReporter will not report fetch failures
to AM , although the log of reducer show message"Reporting fetch failure...", and the fetch
failures loop will not stop util reduce task failed for exceeded MAX_FAILED_UNIQUE_FETCHES.
> So, it's necessary to set a TASK_PROGRESS_REPORT_INTERVAL_MAX value (such as 30s) when
the taskProgressInterval return by MRJobConfUtil.getTaskProgressReportInterval() equals 0
or beyond the max value, set the taskProgressInterval = TASK_PROGRESS_REPORT_INTERVAL_MAX. 



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