Hi, I've been using large datasets (>GB) and I've stored them in MySQL databases and use RMySQL to access them. My feeling is that most of the times you don't need to keep the dataset in your workspace, but you need to access parts of it or aggregate it in some way, before run some analysis. So use what is best from each world, databases to store and perform partial selections and aggregations, and R to statistical analysis.
You'll be amazed with the speed of this 2 together (R & MySQL). Regards EJ On Wed, 2004-11-24 at 15:37, apollo wong wrote: > Hi, do any one have experience with loading dataset > that is larger than 2GB into R. My organization is a > SAS oriented shop and I'm in the process of switching > it to R. One of the complain about R has always been > it's inability to handle large dataset (>GB) > efficiently. I would like some comments from someone > with experience of working on >2GB dataset in R. > Thanks. > Apollo > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html