On Tue, 24 Mar 2009, Guillaume Filteau wrote:
> Hello all,
>
> I?m trying to take a huge dataset (1.5 GB) and separate it into smaller
chunks
> with R.
>
> So far I had nothing but problems.
>
> I cannot load the whole dataset in R due to memory problems. So, I instead
try
> to load a few (100000) lines at a time (with read.table).
>
> However, R kept crashing (with no error message) at about the 6800000 line.
> This is extremely frustrating.
>
> To try to fix this, I used connections with read.table. However, I now get
a
> cryptic error telling me ?no lines available in input?.
>
> Is there any way to make this work?
>
There might be an error in line 42 of your script. Or somewhere else. The error
message is cryptically saying that there were no lines of text available in the
input connection, so presumably the connection wasn't pointed at your file
correctly.
It's hard to guess without seeing what you are doing, but
conn <- file("mybigfile", open="r")
chunk<- read.table(conn, header=TRUE, nrows=10000)
nms <- names(chunk)
while(length(chunk)==10000){
chunk<-read.table(conn, nrows=10000,col.names=nms)
## do something to the chunk
}
close(conn)
should work. This sort of thing certainly does work routinely.
It's probably not worth reading 100,000 lines at a time unless your computer
has a lot of memory. Reducing the chunk size to 10,000 shouldn't introduce
much extra overhead and may well increase the speed by reducing memory use.
-thomas
Thomas Lumley Assoc. Professor, Biostatistics
tlumley at u.washington.edu University of Washington, Seattle