Hi R folks, Here is my problem. *1.* I have a large data file (say, in .csv or .txt format) containing 1 million rows and 500 variables (columns). *2.* My statistical algorithm does not require the entire dataset but just a small random sample from the original 1 million rows. *3. *This algorithm needs to be applied 10000 times, each time generating a different random sample from the 'big' file as described in (2) above. Is there a way to 'import' only a (random) subset of rows from the .csv file without importing the entire dataset? A quick search on various R forums suggest that read.table() does not have this functionality. Obviously, I want to avoid importing the whole file because of memory issues. Looking forward to your help. Thanks, Khurram ------------------------ Khurram Nadeem Postdoctoral Research Fellow Department of Mathematics & Statistics Acadia University, NS, Canada. [[alternative HTML version deleted]]