If you need to analyze something bigger than memory can hold, one option is the biglm package which will fit linear regression models (and a lot of different analyses can be restructured as linear regression models) on blocks of data so that the entire dataset is not in memory all at the same time.
I tested it out with a database with over 23 million rows and it worked great. It computed the exact same answers (to about 7 decimal places, I didn't bother to look beyond that) as a couple of other methods used for the same values. Hope this helps, -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare [EMAIL PROTECTED] (801) 408-8111 -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Carl Hauser Sent: Tuesday, June 13, 2006 9:22 PM To: r-help@stat.math.ethz.ch Subject: [R] data set size question Hi there, I'm very new to R and am only in the beginning stages of investigating it for possible use. A document by John Maindonald at the r-project website entitled "Using R for Data Analysis and Graphics: Introduction, Code and Commentary" contains the following paragraph, "The R system may struggle to handle very large data sets. Depending on available computer memory, the processing of a data set containing one hundred thousand observations and perhaps twenty variables may press the limits of what R can easily handle". This document was written in 2004. My questions are: Is this still the case? If so, has anyone come up with creative solutions to mitigate these limitations? If you work with large data sets in R, what have your experiences been? >From what I've seen so far, R seems to have enormous potential and capabilities. I routinely work with data sets of several hundred thousand to several million. It would be unfortunate if such potential and capabilities were not realized because of (effective) data set size limitations. Please tell me it ain't so. Thanks for any help or suggestions. Carl [[alternative HTML version deleted]] ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html