[R] Performance Difference? Windows vs. Linux

Prof Brian Ripley ripley at stats.ox.ac.uk
Sat Mar 19 09:59:36 CET 2011


On Fri, 18 Mar 2011, Shige Song wrote:

> One thing that Linux makes trivially easy is to interpolate R with C++
> through the Rcpp package. The GCC compiler collection is part of all
> mainstream Linux distro. This is, however, not the case with Windows:
> you may be able to do it eventually (not sure about this point), but
> it takes quite some tweaks...

Oh, come on: you admit don't know what you are talking about, but you 
then give advice on something unrelated to the command line.  That 
forces other people to correct your erroneous advice for the record.

You do not need Rcpp to use C++ with R, and only a very small minority 
of C++-using packages do whereas Rcpp leans very heavily on the work 
of the core team to support C++.

There is a C++ compiler which is part of the Rtools collection which 
you need to use compiled code on Windows.  But actually that is no 
different from Linux, where the person who installed Linux has to 
arrange to install the compilers from the distro.

>
> Shige
>
> On Fri, Mar 18, 2011 at 6:00 PM, Brigid Mooney <bkmooney at gmail.com> wrote:
>> I'm not trying to start a Windows vs. Linux debate, but I've been
>> using R on a Windows machine for a while, and was recently wondering
>> if R's performance would be faster on a Linux machine.  And similarly,
>> if any incremental increase in processing speed would be worth the
>> time it would take me to migrate my entire system to Linux (including
>> a database that I access via an R package.)
>>
>> I don't know how much it matters what R is doing - but I've got R
>> pulling a large amount data from a database, performing many complex
>> computations on that data, and then writing output data to a database.
>>
>> Thanks so much for the input,
>> Brigid
>>
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>>
>
> ______________________________________________
> R-help at r-project.org mailing list
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595


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