Thank you all! I got very useful advice and I saw some nice solutions that even made me drool! ;-)

Cheers!!
Albert-Jan

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In the face of ambiguity, refuse the temptation to guess.
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--- On Wed, 12/16/09, Søren Højsgaard <Soren.Hojsgaard@agrsci.dk> wrote:


From: Søren Højsgaard <Soren.Hojsgaard@agrsci.dk>
Subject: SV: [R] R & very large files
To: "Albert-Jan Roskam" <fomcl@yahoo.com>, "r-help@r-project.org" <r-help@r-project.org>
Date: Wednesday, December 16, 2009, 12:13 PM


The sqldf package may be of help to you.
Regards
Søren 




-----Oprindelig meddelelse-----
Fra: r-help-bounces@r-project.org [mailto:r-help-bounces@r-project.org] På vegne af Albert-Jan Roskam
Sendt: 16. december 2009 11:59
Til: r-help@r-project.org
Emne: [R] R & very large files

Hi,
 
I very recently started using R (as in: last week) and I was wondering if anyone could point me to website(s) with sample code to deal with large datasets (length- and/or breadthwise). I understood that R was never designed to work with datasets larger than, say, a couple of hundred Mb. One way is (as I also read) to let R work in conjunction with SQL. That's one interesting approach I'd like to know more about. But I was also hoping that there also were pure R solutions for working with very large tables (was 'scan' designed for that?). In any case, a standard approach would be desirable.
 
Thanks in advance.

Cheers!!
Albert-Jan

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In the face of ambiguity, refuse the temptation to guess.
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