big data file versus ram memory

1) I would like very much to use R for processing some big data files 
(around 1.7 or more GB) for spatial analysis, wavelets, and power 
spectra estimation; is this possible with R? Within IDL, such a big data 
set seems to be tractable...

2) I have heard/read that R "puts all its data on ram"? Does this really 
mean my data file cannot be bigger than my ram memory?

3) If I have a big enough ram, would I be able to process whatever data 
set?? What constrains the practical limits of my data sets??

Hi Mauricio,

Mauricio Calvao schrieb:

1) I would like very much to use R for processing some big data  
files (around 1.7 or more GB) for spatial analysis, wavelets, and  
power spectra estimation; is this possible with R? Within IDL, such  
a big data set seems to be tractable...

There are some packages to handle large datasets, e.g., bigmemoRy.  
There were a couple of presentations on various ways to work with  
large datasets at the last useR conference - take a look at the  
presentations at
http://www.statistik.uni-dortmund.de/useR-2008/
You'll probably be most interested in the "High Performance" streams.

2) I have heard/read that R "puts all its data on ram"? Does this  
really mean my data file cannot be bigger than my ram memory?

The philosophy is basically to use RAM. Anything working outside RAM  
is not exactly heretical to R, but it does require some additional  
effort.

3) If I have a big enough ram, would I be able to process whatever  
data set?? What constrains the practical limits of my data sets??

From what I understand - little to nothing, beyond the time needed  
for computations.