Hello Thomas,
Thanks for your help!
Sadly your code does not work for the last chunk, because its length is
shorter than nrows.
I tried
try(chunk<-read.table(conn, nrows=10000,col.names=nms), silent=TRUE)
but it gives me an error (go figure!)
Best,
Guillaume
Quoting Thomas Lumley <tlum...@u.washington.edu>:
On Tue, 24 Mar 2009, Guillaume Filteau wrote:
Hello all,
Im 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
tlum...@u.washington.edu University of Washington, Seattle
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