Huge data frames?

Hi,

You should use scan() to read large ASCII tables.  If you save a dataframe
using save(), you get a binary file which works pretty fast.

Note that similar problems arise if you try to save big dataframes in ASCII
(you may consider my package savetable at
http://www.obs.ee/~siim/savetable_0.1.0.tar.gz in order to do that).

Best wishes,

Ott

|A friend of mine recently mentioned that he had painlessly imported a
  |data file with 8 columns and 500,000 rows into matlab. When I tried
  |the same thing in R (both Unix and Windows variants) I had little
  |success. The Windows version hung for a very long time, until I
  |eventually more or less ran out of virtual memory; I tried to set the
  |proper memory allocations for the Unix version, but it never seemed
  |satisfied :]
  |
  |I used read.table -- should I have used something else? Is it even
  |possible to work with this large files? I assume a memory-mapped
  |binary file would have been quite efficient (as opposed to an
  |in-memory parsed text file) -- is something like that even possible in
  |R?
  |
  |

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