I suspect that the reason no-one is responding with good answers is that
fundamentally, it seems like what you are trying to do runs against the
reason Hadoop is designed the way it is. A parallel process framework is
defeated if you force it to not work concurrently...

Maybe you should look into Oozie, and set a workflow that runs your map
task as a map-only job, and then do the calculation that the reducer would
do in a different program?

There is a Hadoop parameter that allows for task JVM reuse that might solve
your problem also.

Or, add a combiner to your mr job if there is not one already, and then try
dropping the maximum heap sizes of the respective slots?

*Devin Suiter*
Jr. Data Solutions Software Engineer
100 Sandusky Street | 2nd Floor | Pittsburgh, PA 15212
Google Voice: 412-256-8556 | www.rdx.com


On Wed, Nov 6, 2013 at 5:09 AM, John <johnnyenglish...@gmail.com> wrote:

> Does no one have an idea if it is possible? In my example the heapsize of
> the tasktracker is 2gb. The max map heap size is 1gb and the mac heap size
> of the reduce process 1,5gb. If there are running 2 maps or just the reduce
> job everything is fine. But if there are running 2 maps + 1 reduce process
> I got a "Error: java.lang.OutOfMemoryError: Java heap space at" message.
>
> kind regards
>
>
> 2013/11/5 John <johnnyenglish...@gmail.com>
>
>> Because my node swaps the memory if the 2 map slots + 1 reduce is
>> occupied with my job. Sure I can minimize the max memory for the map/reduce
>> process. I tried this already, but I got a out of memory exception if set
>> the max heap size for the map/reduce process to low for my mr job.
>>
>> kind regards
>>
>>
>> 2013/11/5 Vinod Kumar Vavilapalli <vino...@hortonworks.com>
>>
>>> Why do you want to do this?
>>>
>>> +Vinod
>>>
>>> On Nov 5, 2013, at 9:17 AM, John wrote:
>>>
>>> Is it possible to force the jobtracker executing only 2 map jobs or 1
>>> reduce job per time?
>>>
>>>
>>>
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