Big data read subsamples R

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I'm most grateful for your time to read this.

I have a uber size 30GB file of 6 million records and 3000 (mostly categorical data) columns in csv format. I want to bootstrap subsamples for multinomial regression, but it's proving difficult even with my 64GB RAM in my machine and twice that swap file , the process becomes super slow and halts.

I'm thinking about generating subsample indicies in R and feeding them into a system command using sed or awk, but don't know how to do this. If someone knew of a clean way to do this using just R commands, I would be really grateful.

One problem is that I need to pick complete observations of subsamples, that is I need to have all the rows of a particular multinomial observation - they are not the same length from observation to observation. I plan to use glmnet and then some fancy transforms to get an approximation to the multinomial case. One other point is that I don't know how to choose sample size to fit around memory limits.

Appreciate your thoughts greatly.

R.version
platform       x86_64-pc-linux-gnu          
arch           x86_64                       
os             linux-gnu                    
system         x86_64, linux-gnu            
status                                      
major          2                            
minor          15.1                         
year           2012                         
month          06                           
day            22                           
svn rev        59600                        
language       R                            
version.string R version 2.15.1 (2012-06-22)
nickname       Roasted Marshmallows   

Yoda

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