Got it. Thanks!

On Mon, Oct 17, 2011 at 9:40 AM, Prof Brian Ripley <ripley@stats.ox.ac.uk>wrote:

> On Mon, 17 Oct 2011, Brian Smith 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?
>>
>
> Use a pipe() connection.
>
>
>> thanks!
>>
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>>
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>>
> --
> Brian D. Ripley,                  ripley@stats.ox.ac.uk
> Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~**ripley/<http://www.stats.ox.ac.uk/%7Eripley/>
> University of Oxford,             Tel:  +44 1865 272861 (self)
> 1 South Parks Road,                     +44 1865 272866 (PA)
> Oxford OX1 3TG, UK                Fax:  +44 1865 272595
>

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