Hi,
I understand that given a file, the file is split across 'n' mapper
instances, which is the normal case.
The scenario i have is :
1. Two files which are not totally identical in terms of number of columns
(but have data that is similar in a few columns) need to be processed and
after computation a single output file has to be generated.
Note : CV - computedvalue
File1 belonging to one dataset has data for :
Date,counter1,counter2, CV1,CV2
File2 belonging to another dataset has data for :
Date,counter1,counter2,CV3,CV4,CV5
Computation to be carried out on these two files is :
CV6 =(CV1*CV5)/100
And the final emitted output file should have data in the sequence:
Date,counter1,counter2,CV6
The idea is to have two mappers (not instances) run on each of the file, and
a single reducer that emits the final result file.
Thanks,
Sahana
On Wed, Sep 7, 2011 at 2:40 PM, Harsh J <[email protected]> wrote:
> Sahana,
>
> Yes. But, isn't that how it is normally? What makes you question this
> capability?
>
> On Wed, Sep 7, 2011 at 2:37 PM, Sahana Bhat <[email protected]> wrote:
> > Hi,
> > Is it possible to have multiple mappers where each mapper is
> > operating on a different input file and whose result (which is a key
> value
> > pair from different mappers) is processed by a single reducer?
> > Regards,
> > Sahana
>
>
>
> --
> Harsh J
>
