On Wed, 25 Mar 2009, Guillaume Filteau wrote:
Hello Thomas,
Thanks for your help!
Sadly your code does not work for the last chunk, because its length is shorter
than nrows.
You just need to move the test to the bottom of the loop
repeat{
chunk<-read.table(conn, nrows=10000,col.names=nms)
## do something to the chunk
if(length(chunk)<10000) break
}
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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Thomas Lumley Assoc. Professor, Biostatistics
tlum...@u.washington.edu University of Washington, Seattle
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