Dear Jeff,

R works fine for 220000 rows that i tested on a home PC with XP . Memory is
limited to hardware that you have. I suggest beefing up RAM to 2 GB and hard
disk space and then  working it out. I evaluated R too on my site
www.decisionstats.com and I found it comparable if not better to SPSS , SAS.


As a beginner , and in corporate projects try using the *GUI* R Commander or
the *Data Mining GUI Rattle *, its faster and will help you skip some steps,
you can also look at code generated side by side to learn the
language.........

I am not sure on the server client version, but that should work too ......

Also look at the book http://oit.utk.edu/scc/RforSAS&SPSSusers.pdf

that helps you as a reference guide. Rest of details are on my site
www.decisionstats.com

Also *try the software WPS* http://www.teamwpc.co.uk/products/wps, which
uses SAS language and provides the same functionality at 10-20 % of cost for
millions of rows.


Hope this helps,

Ajay


On Tue, Apr 8, 2008 at 7:56 PM, Jeff Royce <Jeff.Royce@wnco.com> wrote:

> We are new to R and evaluating if we can use it for a project we need to
> do.  We have read that R is not well suited to handle very large data
> sets.  Assuming we have the data prepped and stored in an RDBMS (Oracle,
> Teradata, SQL Server), what can R reasonably handle from a volume
> perspective?   Are there some guidelines on memory/machine sizing based
> on data volume?  We need to be able to handle Millions of Rows from
> several sources.  Any advice is much appreciated.  Thanks.
>
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