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MapReduce >> mail # user >> number of mapper tasks


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Re: number of mapper tasks
Just to complement the last question, I have implemented the getSplits
method in my input format:
https://github.com/mvallebr/CSVInputFormat/blob/master/src/main/java/org/apache/hadoop/mapreduce/lib/input/CSVNLineInputFormat.java

However, it still doesn't create more than 2 map tasks. Is there something
I could do about it to assure more map tasks are created?

Thanks
Marcelo.
2013/1/28 Marcelo Elias Del Valle <[EMAIL PROTECTED]>

> Sorry for asking too many questions, but the answers are really happening.
>
>
> 2013/1/28 Harsh J <[EMAIL PROTECTED]>
>
>> This seems CPU-oriented. You probably want the NLineInputFormat? See
>>
>> http://hadoop.apache.org/common/docs/current/api/org/apache/hadoop/mapred/lib/NLineInputFormat.html
>> .
>> This should let you spawn more maps as we, based on your N factor.
>>
>
> Indeed, CPU is my bottleneck. That's why I want more things in parallel.
> Actually, I wrote my own InputFormat, to be able to process multiline
> CSVs: https://github.com/mvallebr/CSVInputFormat
> I could change it to read several lines at a time, but would this alone
> allow more tasks running in parallel?
>
>
>> Not really - "Slots" are capacities, rather than split factors
>> themselves. You can have N slots always available, but your job has to
>> supply as many map tasks (based on its input/needs/etc.) to use them
>> up.
>>
>
> But how can I do that (supply map tasks) in my job? changing its code?
> hadoop config?
>
>
>> Unless your job sets the number of reducers to 0 manually, 1 default
>> reducer is always run that waits to see if it has any outputs from
>> maps. If it does not receive any outputs after maps have all
>> completed, it dies out with behavior equivalent to a NOP.
>>
> Ok, I did job.setNumReduceTasks(0); , guess this will solve this part,
> thanks!
>
>
> --
> Marcelo Elias Del Valle
> http://mvalle.com - @mvallebr
>

--
Marcelo Elias Del Valle
http://mvalle.com - @mvallebr