I set mapred.reduce.tasks from -1 to "AutoReduce"
And the hadoop created 450 tasks for Map. But 1 task for Reduce. It seems
that this reduce only run on 1 slave (I have two slaves).

But when it was running on 66%, the error report again "Task
attempt_201301150318_0001_r_000000_0 failed to report status for 601
seconds. Killing!"

2013/1/14 yaotian <[EMAIL PROTECTED]>

> How to judge which counter would work?
>
>
> 2013/1/11 <[EMAIL PROTECTED]>
>
> **
>> Hi
>>
>> To add on to Harsh's comments.
>>
>> You need not have to change the task time out.
>>
>> In your map/reduce code, you can increment a counter or report status
>> intermediate on intervals so that there is communication from the task and
>> hence won't have a task time out.
>>
>> Every map and reduce task run on its own jvm limited by a jvm size. If
>> you try to holds too much data in memory then it can go beyond the jvm size
>> and cause OOM errors.
>>
>> Regards
>> Bejoy KS
>>
>> Sent from remote device, Please excuse typos
>> ------------------------------
>> *From: * yaotian <[EMAIL PROTECTED]>
>> *Date: *Fri, 11 Jan 2013 14:35:07 +0800
>> *To: *<[EMAIL PROTECTED]>
>> *ReplyTo: * [EMAIL PROTECTED]
>> *Subject: *Re: I am running MapReduce on a 30G data on 1master/2 slave,
>> but failed.
>>
>> See inline.
>>
>>
>> 2013/1/11 Harsh J <[EMAIL PROTECTED]>
>>
>>> If the per-record processing time is very high, you will need to
>>> periodically report a status. Without a status change report from the task
>>> to the tracker, it will be killed away as a dead task after a default
>>> timeout of 10 minutes (600s).
>>>
>> =====================> Do you mean to increase the report time: "*
>> mapred.task.timeout"*?
>>
>>
>>> Also, beware of holding too much memory in a reduce JVM - you're still
>>> limited there. Best to let the framework do the sort or secondary sort.
>>>
>> =======================>  You mean use the default value ? This is my
>> value.
>> *mapred.job.reduce.memory.mb*-1
>>
>>>
>>>
>>> On Fri, Jan 11, 2013 at 10:58 AM, yaotian <[EMAIL PROTECTED]> wrote:
>>>
>>>> Yes, you are right. The data is GPS trace related to corresponding uid.
>>>> The reduce is doing this: Sort user to get this kind of result: uid, gps1,
>>>> gps2, gps3........
>>>> Yes, the gps data is big because this is 30G data.
>>>>
>>>> How to solve this?
>>>>
>>>>
>>>>
>>>> 2013/1/11 Mahesh Balija <[EMAIL PROTECTED]>
>>>>
>>>>> Hi,
>>>>>
>>>>>           2 reducers are successfully completed and 1498 have been
>>>>> killed. I assume that you have the data issues. (Either the data is huge or
>>>>> some issues with the data you are trying to process)
>>>>>           One possibility could be you have many values associated to
>>>>> a single key, which can cause these kind of issues based on the operation
>>>>> you do in your reducer.
>>>>>           Can you put some logs in your reducer and try to trace out
>>>>> what is happening.
>>>>>
>>>>> Best,
>>>>> Mahesh Balija,
>>>>> Calsoft Labs.
>>>>>
>>>>>
>>>>> On Fri, Jan 11, 2013 at 8:53 AM, yaotian <[EMAIL PROTECTED]> wrote:
>>>>>
>>>>>> I have 1 hadoop master which name node locates and 2 slave which
>>>>>> datanode locate.
>>>>>>
>>>>>> If i choose a small data like 200M, it can be done.
>>>>>>
>>>>>> But if i run 30G data, Map is done. But the reduce report error. Any
>>>>>> sugggestion?
>>>>>>
>>>>>>
>>>>>> This is the information.
>>>>>>
>>>>>> *Black-listed TaskTrackers:* 1<http://23.20.27.135:9003/jobblacklistedtrackers.jsp?jobid=job_201301090834_0041>
>>>>>> ------------------------------
>>>>>> Kind % CompleteNum Tasks PendingRunningComplete KilledFailed/Killed
>>>>>> Task Attempts<http://23.20.27.135:9003/jobfailures.jsp?jobid=job_201301090834_0041>
>>>>>> map<http://23.20.27.135:9003/jobtasks.jsp?jobid=job_201301090834_0041&type=map&pagenum=1>
>>>>>> 100.00%4500 0450<http://23.20.27.135:9003/jobtasks.jsp?jobid=job_201301090834_0041&type=map&pagenum=1&state=completed>
>>>>>> 00 / 1<http://23.20.27.135:9003/jobfailures.jsp?jobid=job_201301090834_0041&kind=map&cause=killed>

Hi, yaotian
I think you should check logs on the very tasktracker, it'll tell you why.
And here's some tips on deploying a MR job. http://blog.cloudera.com/blog/2009/12/7-tips-for-improving-mapreduce-performance/
Charlie

At 2013-01-15 16:34:27,yaotian <[EMAIL PROTECTED]> wrote:

I set mapred.reduce.tasks from -1 to "AutoReduce"

And the hadoop created 450 tasks for Map. But 1 task for Reduce. It seems that this reduce only run on 1 slave (I have two slaves).
But when it was running on 66%, the error report again "Task attempt_201301150318_0001_r_000000_0 failed to report status for 601 seconds. Killing!"

2013/1/14 yaotian <[EMAIL PROTECTED]>

How to judge which counter would work?

2013/1/11 <[EMAIL PROTECTED]>
Hi

To add on to Harsh's comments.

You need not have to change the task time out.

In your map/reduce code, you can increment a counter or report status intermediate on intervals so that there is communication from the task and hence won't have a task time out.

Every map and reduce task run on its own jvm limited by a jvm size. If you try to holds too much data in memory then it can go beyond the jvm size and cause OOM errors.
Regards
Bejoy KS

Sent from remote device, Please excuse typos
From: yaotian <[EMAIL PROTECTED]>
Date: Fri, 11 Jan 2013 14:35:07 +0800
To: <[EMAIL PROTECTED]>
ReplyTo: [EMAIL PROTECTED]
Subject: Re: I am running MapReduce on a 30G data on 1master/2 slave, but failed.
See inline.
2013/1/11 Harsh J <[EMAIL PROTECTED]>

If the per-record processing time is very high, you will need to periodically report a status. Without a status change report from the task to the tracker, it will be killed away as a dead task after a default timeout of 10 minutes (600s).
=====================> Do you mean to increase the report time: "mapred.task.timeout"?
Also, beware of holding too much memory in a reduce JVM - you're still limited there. Best to let the framework do the sort or secondary sort.
=======================>  You mean use the default value ? This is my value.
| mapred.job.reduce.memory.mb | -1 |

On Fri, Jan 11, 2013 at 10:58 AM, yaotian <[EMAIL PROTECTED]> wrote:

Yes, you are right. The data is GPS trace related to corresponding uid. The reduce is doing this: Sort user to get this kind of result: uid, gps1, gps2, gps3........
Yes, the gps data is big because this is 30G data.
How to solve this?

2013/1/11 Mahesh Balija <[EMAIL PROTECTED]>
Hi,

          2 reducers are successfully completed and 1498 have been killed. I assume that you have the data issues. (Either the data is huge or some issues with the data you are trying to process)
          One possibility could be you have many values associated to a single key, which can cause these kind of issues based on the operation you do in your reducer.
          Can you put some logs in your reducer and try to trace out what is happening.

Best,
Mahesh Balija,
Calsoft Labs.

On Fri, Jan 11, 2013 at 8:53 AM, yaotian <[EMAIL PROTECTED]> wrote:

I have 1 hadoop master which name node locates and 2 slave which datanode locate.
If i choose a small data like 200M, it can be done.
But if i run 30G data, Map is done. But the reduce report error. Any sugggestion?
This is the information.
Black-listed TaskTrackers: 1

| Kind | % Complete | Num Tasks | Pending | Running | Complete | Killed | Failed/Killed
Task Attempts |
| map | 100.00%
| |
| 450 | 0 | 0 | 450 | 0 | 0 / 1 |
| reduce | 100.00%
| |
| 1500 | 0 | 0 | 2 | 1498 | 12 / 3

|
| Task | Complete | Status | Start Time | Finish Time | Errors | Counters |
| task_201301090834_0041_r_000001 | 0.00%
| |
|
| 10-Jan-2013 04:18:54
| 10-Jan-2013 06:46:38 (2hrs, 27mins, 44sec)
|
Task attempt_201301090834_0041_r_000001_0 failed to report status for 600 seconds. Killing!
Task attempt_201301090834_0041_r_000001_1 failed to report status for 602 seconds. Killing!
Task attempt_201301090834_0041_r_000001_2 failed to report status for 602 seconds. Killing!
Task attempt_201301090834_0041_r_000001_3 failed to report status for 602 seconds. Killing!
| 0 |
| task_201301090834_0041_r_000002 | 0.00%
| |
|
| 10-Jan-2013 04:18:54
| 10-Jan-2013 06:46:38 (2hrs, 27mins, 43sec)
|
Task attempt_201301090834_0041_r_000002_0 failed to report status for 601 seconds. Killing!
Task attempt_201301090834_0041_r_000002_1 failed to report status for 600 seconds. Killing!
| 0 |
| task_201301090834_0041_r_000003 | 0.00%
| |
|
| 10-Jan-2013 04:18:57
| 10-Jan-2013 06:46:38 (2hrs, 27mins, 41sec)
|
Task attempt_201301090834_0041_r_000003_0 failed to report status for 602 seconds. Killing!
Task attempt_201301090834_0041_r_000003_1 failed to report status for 602 seconds. Killing!
Task attempt_201301090834_0041_r_000003_2 failed to report status for 602 seconds. Killing!
| 0 |
| task_201301090834_0041_r_000005 | 0.00%
| |
|
| 10-Jan-2013 06:11:07
| 10-Jan-2013 06:46:38 (35mins, 31sec)
|
Task attempt_201301090834_0041_r_000005_0 failed to report status for 600 seconds. Killing!
| 0 |

Harsh J

Thanks. I will read that document. I am new on this. So i attach the log
here for help. I can't understand this information.

These log from tasktrack log file:

2013-01-15 08:00:44,731 INFO org.apache.hadoop.mapred.TaskTracker:
attempt_201301150318_0001_r_000000_0 0.66737837% reduce > reduce
2013-01-15 08:00:47,757 INFO org.apache.hadoop.mapred.TaskTracker:
attempt_201301150318_0001_r_000000_0 0.66737837% reduce > reduce
2013-01-15 08:10:49,083 INFO org.apache.hadoop.mapred.TaskTracker:
attempt_201301150318_0001_r_000000_0: Task
attempt_201301150318_0001_r_000000_0 failed to report status for 601
seconds. Killing!
2013-01-15 08:10:49,092 INFO org.apache.hadoop.mapred.TaskTracker: Process
Thread Dump: lost task
24 active threads
Thread 219 (process reaper):
  State: RUNNABLE
  Blocked count: 0
  Waited count: 0
  Stack:
    java.lang.UNIXProcess.waitForProcessExit(Native Method)
    java.lang.UNIXProcess.access$900(UNIXProcess.java:20)
    java.lang.UNIXProcess$1$1.run(UNIXProcess.java:132)
Thread 218 (JVM Runner jvm_201301150318_0001_r_-641939786 spawned.):
  State: WAITING
  Blocked count: 1
  Waited count: 2
  Waiting on java.lang.UNIXProcess@1195929
  Stack:
    java.lang.Object.wait(Native Method)
    java.lang.Object.wait(Object.java:485)
    java.lang.UNIXProcess.waitFor(UNIXProcess.java:165)
    org.apache.hadoop.util.Shell.runCommand(Shell.java:244)
    org.apache.hadoop.util.Shell.run(Shell.java:182)

org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:375)

org.apache.hadoop.mapred.DefaultTaskController.launchTask(DefaultTaskController.java:131)

org.apache.hadoop.mapred.JvmManager$JvmManagerForType$JvmRunner.runChild(JvmManager.java:497)

org.apache.hadoop.mapred.JvmManager$JvmManagerForType$JvmRunner.run(JvmManager.java:471)
Thread 214 (Thread-135):
  State: WAITING
  Blocked count: 2
  Waited count: 3
  Waiting on java.lang.Object@1f35647
  Stack:
    java.lang.Object.wait(Native Method)
    java.lang.Object.wait(Object.java:485)

org.apache.hadoop.mapred.TaskRunner.launchJvmAndWait(TaskRunner.java:296)
    org.apache.hadoop.mapred.TaskRunner.run(TaskRunner.java:251)
Thread 38 (IPC Client (47) connection to master/10.120.253.32:9001 from
hadoop):
  State: TIMED_WAITING
  Blocked count: 11210
  Waited count: 11199
  Stack:
    java.lang.Object.wait(Native Method)
    org.apache.hadoop.ipc.Client$Connection.waitForWork(Client.java:702)
    org.apache.hadoop.ipc.Client$Connection.run(Client.java:744)
Thread 10 (taskCleanup):
  State: WAITING
  Blocked count: 4
  Waited count: 7
  Waiting on
java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject@104109e
  Stack:
    sun.misc.Unsafe.park(Native Method)
    java.util.concurrent.locks.LockSupport.park(LockSupport.java:158)

java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:1987)

java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:399)
    org.apache.hadoop.mapred.TaskTracker$1.run(TaskTracker.java:422)
    java.lang.Thread.run(Thread.java:662)
Thread 13 (Thread-5):
  State: WAITING
  Blocked count: 475
  Waited count: 646
  Waiting on
java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject@61bb9b
  Stack:
    sun.misc.Unsafe.park(Native Method)
    java.util.concurrent.locks.LockSupport.park(LockSupport.java:158)

java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:1987)

java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:399)

org.apache.hadoop.mapreduce.server.tasktracker.userlogs.UserLogManager.monitor(UserLogManager.java:131)

org.apache.hadoop.mapreduce.server.tasktracker.userlogs.UserLogManager$1.run(UserLogManager.java:66)
Thread 14 (Thread-6):
  State: TIMED_WAITING
  Blocked count: 0
  Waited count: 5
  Stack:
    java.lang.Thread.sleep(Native Method)
    org.apache.hadoop.mapred.UserLogCleaner.run(UserLogCleaner.java:93)
Thread 37 (Timer-0):
  State: TIMED_WAITING
  Blocked count: 0
  Waited count: 618
  Stack:
    java.lang.Object.wait(Native Method)
    java.util.TimerThread.mainLoop(Timer.java:509)
    java.util.TimerThread.run(Timer.java:462)
Thread 36 (23978087@qtp-7433399-0 - Acceptor0
SelectChannelConnector@0.0.0.0:50060):
  State: RUNNABLE
  Blocked count: 29509
  Waited count: 1
  Stack:
    sun.nio.ch.EPollArrayWrapper.epollWait(Native Method)
    sun.nio.ch.EPollArrayWrapper.poll(EPollArrayWrapper.java:210)
    sun.nio.ch.EPollSelectorImpl.doSelect(EPollSelectorImpl.java:65)
    sun.nio.ch.SelectorImpl.lockAndDoSelect(SelectorImpl.java:69)
    sun.nio.ch.SelectorImpl.select(SelectorImpl.java:80)

org.mortbay.io.nio.SelectorManager$SelectSet.doSelect(SelectorManager.java:498)
    org.mortbay.io.nio.SelectorManager.doSelect(SelectorManager.java:192)

org.mortbay.jetty.nio.SelectChannelConnector.accept(SelectChannelConnector.java:124)

org.mortbay.jetty.AbstractConnector$Acceptor.run(AbstractConnector.java:708)

org.mortbay.thread.QueuedThreadPool$PoolThread.run(QueuedThreadPool.java:582)
Thread 35 (TaskLauncher for REDUCE tasks):
  State: WAITING
  Blocked count: 1
  Waited count: 2
  Waiting on java.util.LinkedList@ca1038
  Stack:
    java.lang.Object.wait(Native Method)
    java.lang.Object.wait(Object.java:485)

org.apache.hadoop.mapred.TaskTracker$TaskLauncher.run(TaskTracker.java:2265)
Thread 34 (TaskLauncher for MAP tasks):
  State: WAITING
  Blocked count: 170
  Waited count: 171
  Waiting on java.util.LinkedList@1ddec9e
  Stack:
    java.lang.Object.wait(Native Method)
    java.lang.Object.wait(Object.java:485)

org.apache.hadoop.mapred.TaskTracker$TaskLauncher.run(TaskTracker.java:2265)
Thread 27 (Map-events fetcher for all reduce tasks on
tracker_ip-10-87-145-204.ec2.internal:localhost/127.0.0.1:60497):
  State: TIMED_WAITING
  Blocked count: 16184
  Waited count: 17896
  Stack:
    java.lang.Object.wait(Native Method)

org.apache.hadoop.mapred.TaskTracker$MapEventsFetcherThread.run(TaskTracker.java:975)
T