On Mon, Oct 17, 2011 at 9:23 AM, Brian Smith <bsmith030...@gmail.com> wrote: > Hi, > > I had a large file for which I require a subset of rows. Instead of reading > it all into memory, I use the awk command to get the relevant rows. However, > I'm doing it pretty inefficiently as I write the subset to disk, before > reading it into R. Is there a way that I can read it into an R object > without writing to disk? For example, this is what I do currently: > > ## write test sample file > mat1 <- matrix(sample(1:100,16),8,2) > fname1 <- 'temp1.txt' > fname2 <- 'temp2.txt' > write.table(mat1,fname1,sep='\t',row.names=F,col.names=F) > > ## Read a subset of rows, write to file, and read from file > system(paste("awk '(NR > 1 && NR < 4) {print $0}' ",fname1," > > ",fname2,sep='')) > mat2 <- read.table(fname2,sep='\t') > > print(mat2) > ##### > > Is there a way that I can skip writing to disk? >
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