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 <[EMAIL PROTECTED]> 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. > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
