An apology: it takes roughly a couple of minutes on my laptop, running Debian. I had been running some other simulations for quite some time and, though it looks odd for Linux, the subsequent work I did with R was slowed down. Many thanks
Lorenzo Peter Dalgaard wrote: > Prof Brian Ripley wrote: >> On Tue, 15 May 2007, Lorenzo Isella wrote: >> >> >>> Dear All, >>> Hope I am not bumping into a FAQ, but so far my online search has >>> been fruitless >>> I need to read some data file using R. I am using the (I think) >>> standard command: >>> >>> data_150<-read.table("y_complete06000", header=FALSE) >>> >>> where y_complete06000 is a 6000 by 40 table of numbers. >>> I am puzzled at the fact that R is taking several minutes to read >>> this file. >>> First I thought it may have been due to its shape, but even >>> re-expressing and saving the matrix as a 1D array does not help. >>> It is not a small file, but not even huge (it amounts to about 5Mb of >>> text file). >>> Is there anything I can do to speed up the file reading? >>> >> >> You could try reading the help page or the 'R Data Import/Export' >> manual. >> Both point out things like >> >> 'read.table' is not the right tool for reading large matrices, >> especially those with many columns: it is designed to read _data >> frames_ which may have columns of very different classes. Use >> 'scan' instead. >> >> On the other hand I am surprised at several minutes, but as you >> haven't even told us your OS, it is hard to know what to expect. My >> Linux box took 3 secs for a 6000x40 matrix with read.table, 0.8 sec >> with scan. >> >> > If it is 40 rows and 6000 columns, then it might explain it: > > > x <- as.data.frame(matrix(rnorm(40*6000),6000)) > > write.table(x,file="xx.txt") > > system.time(y <- read.table("xx.txt")) > user system elapsed > 1.229 0.007 1.250 > > write.table(t(x),file="xx.txt") > > system.time(y <- read.table("xx.txt")) > user system elapsed > 92.986 0.188 93.912 > > > However, this is still not _several_ minutes, and it is on my laptop > which is not particularly fast. > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.