[R] increasing memory

[Liaw, Andy]

> From: Roger D. Peng
> 
> Just a note, R 1.9.0 is the most recent version.
> 
> It sounds like your computer might just be running out of memory 
> and thrashing.  620MB of RAM is unfortunately not an enormous 
> amount of RAM with which to be using R.  These are the trade 
> offs.  If you can't read in your table using scan() then we may 
> be running out of R options.

`Easy' ones anyway.  One can always use `lower level' things like
connections and readLines() to read in chunks at a time...

BTW (for Janet) `crash' and `freeze' aren't exactly the same (at least to
me).  To me `crash' is something like segfaults, or if the program abruptly
exits, or BSOD, etc.  If you still can run top, then the computer hasn't
really frozen, either.  I suspect the reason you can't kill the program is
that the computer is running _really_ low on memory and thrashing, thus not
really responding to `kill' in a timely manner.  I have gotten into that
situation on a Linux box (w/ 2GB RAM), and can't even log in as root to try
the `kill'.  Similarly, the only option was to hit that big red (or maybe
not so `big' or `red') button...

We do need accurate descriptions of what happened to be able to be more
helpful, including some basic descriptions of the data file (e.g., how many
rows/columns, delimiters, column types, etc.)

Andy

 
> -roger
> 
> Janet Rosenbaum wrote:
> 
> >  
> > 
> >>If it actually crashes there is a bug, but I suspect that 
> it stops with an
> >>error message -- please do read the posting guide and tell 
> us exactly what
> >>happens.
> > 
> > 
> > Sorry, I hadn't realized that "crash" means to give an 
> error message on
> > this mailing list.  
> > 
> > To me, "crash" means that the computer freezes entirely, or if I'm
> > lucky it just runs for several hours without doing 
> anything, and the 
> > process can't even be killed with  -9, and the computer can't be
> > shutdown, but has to be powercycled. 
> > 
> > For instance, I left it doing a read.table on a text format 
> file from this 
> > data (a few hundred megs) and eight hours later it was 
> still "going".
> > I watched the process with "top" for awhile and the 
> computer had plenty 
> > of free memory -- over 100 M this whole time, and R was 
> using almost no
> > CPU.
> > 
> > I have tried all sorts of ways of reading in the data.  
> It's best if I
> > can read the xport file since that has all the original labels which
> > don't get to the text file, but read.xport actually freezes the
> > computer.  
> > 
> > As I said, I am running R 1.8.1 which claims to be the most recent
> > version (when I type is.RAqua.updated()) on an ibook G3/800 
> with 620 M
> > RAM (the maximum) running 10.3.3.  
> > 
> > The command really doesn't much matter.  These are totally 
> normal files
> > and I can load in the normal sized files with the exact same
> > commands.  
> > 
> >>w<-read.table("pedagogue.csv",header=T, sep=",")
> >>library(foreign)
> >>w<-read.xport("demagogue.xpt")
> > 
> > 
> > The xpt files are up to 400 M, and the csv files are about 100 M.  
> > 
> > Janet
> 
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> 


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