On Thu, Jul 21, 2011 at 1:44 AM, Madana_Babu <madana_babu@infosys.com>wrote:

> Hi all,
>
> I have R installed on a box, which is running on a machine with 16 core and
> Redhat - Linux. I am handling huge (size of dataset will be 5 GB) dataset.
> Lets assume that my data is in the form of structured (multiple) logs. I
> access the data by using all.files(). Since by default basic version of R
> utilizes single core, the processing of my analysis code is taking too much
> time. I got to know that mclapply() can be used to use all cores
> (processors) to make R much faster when we have multicores. Can anyone help
> me in understanding how to use mclapply() function in the above situation.
>

mclapply() works in the same way as lapply()  - if you use lapply, simply
replace it with mclapply, if you are using a loop, translate it into an
lapply / mclapply structure.

But be aware, that the bottleneck might be disk access!. So: rprof is your
friend.

Cheers,

Rainer


> Thanks in advance
>
> Regards,
> Madana
>
> --
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> Sent from the R help mailing list archive at Nabble.com.
>
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>



-- 
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
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