On 03/08/2010 2:28 PM, Dimitri Liakhovitski wrote:
And once one above the limit that Jim indicated - is there anything one can do?
Yes, there are several packages for handling datasets that are too big to fit in memory: biglm, ff, etc. You need to change your code to work with them, so it's a lot of work to do something unusual, but there are possibilities.
Duncan Murdoch
Thank you! Dimitri On Tue, Aug 3, 2010 at 2:12 PM, Dimitri Liakhovitski <dimitri.liakhovit...@gmail.com> wrote: > Thanks a lot, it's very helpful! > Dimitri > > On Tue, Aug 3, 2010 at 1:53 PM, Duncan Murdoch <murdoch.dun...@gmail.com> wrote: >> On 03/08/2010 1:10 PM, Dimitri Liakhovitski wrote: >>> >>> I understand the question I am about to ask is rather vague and >>> depends on the task and my PC memory. However, I'll give it a try: >>> >>> Let's assume the goal is just to read in the data frame into R and >>> then do some simple analyses with it (e.g., multiple regression of >>> some variables onto some - just a few - variables). >>> >>> Is there a limit to the number of columns of a data frame that R can >>> handle? I am asking because where I work many use SAS and they are >>> running into the limit of >~13,700columns there. >>> >>> Since I am asking - is there a limit to the number of rows? >>> >>> Or is the correct way of asking the question: my PC's memory is X. The >>> .txt tab-delimited file I am trying to read in has the size of YYY Mb, >>> can I read it in? >>> >> >> Besides what Jim said, there is a 2^31-1 limit on the number of elements in >> a vector. Dataframes are vectors of vectors, so you can have at most 2^31-1 >> rows and 2^31-1 columns. Matrices are vectors, so they're limited to 2^31-1 >> elements in total. >> This is only likely to be a limitation on a 64 bit machine; in 32 bits >> you'll run out of memory first. >> >> Duncan Murdoch >> > > > > -- > Dimitri Liakhovitski > Ninah Consulting > www.ninah.com >
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