You can use 'rm' to remove objects.  Are you remembering to do a 'detach'
after the 'attach'?  Why are you using 'attach' (I personally avoid it)?
Think about using 'with'.  Take a look at the size of the objects you are
working with (object.size) to understand where you might have problems.  Use
'search' to see what still might be attached.  I think that as long as
something is 'attached' memory is not freed up after 'rm' until you do the
'detach'

On Tue, Jun 30, 2009 at 5:15 AM, gug <guygreen@netvigator.com> wrote:

>
> Hello,
>
> Is there a command for freeing up the memory used by R in holding data
> tables?
>
> The structure of the procedure I have is as follows:
>
> 1)  Read multiple txt files in using read.table(...).
> 2)  Combine the read tables using rbind(...).
> 3)  Attach the data using attach(...) and then use do a multiple regression
> using lm(...).
>
> So far so good, but when I then perform a further regression by taking out
> factors, I run into memory issues, getting warnings such as:
>
>    "1: In as.list.data.frame(X) :
>       Reached total allocation of 1535Mb: see help(memory.size)"
>
> As it stands, I have to close and then restart R, read in the same data
> again and run with the new reduced number of factors.
>
> My thinking was that, if I could reclaim the memory held by the already
> read
> data files, keeping only the result of the rbind process, I could avoid the
> duplication.  I have therefore tried (very amateurishly) to reset the read
> data to zero using:
>
> Read_data_1=(0)
> Read_data_2=(0)... etc
>
> Followed by:
>
> gc()
>
> However this doesn't get solve the problem.  Is there a better way of
> getting R to "forget" the data tables it was holding and free up the
> memory?
>
> For info: I am also specifying colClasses when first reading the data in,
> to
> try to make it more memory-efficient (following:
> http://www.biostat.jhsph.edu/~rpeng/docs/R-large-tables.html).
>
> Other alternatives are trying the 3GB switch (XP Home, with 4GB RAM).
> Another alternative is trying to use the sqldf package to bring the data
> in,
> which one poster very helpfully suggested in response to an earlier
> question.  I may end up trying that, but as I have not used SQL, I am a
> little daunted by the prospect.
>
> I would really appreciate any suggestions.  Thanks.
>
> Guy Green
> --
> View this message in context:
> http://www.nabble.com/Clearing-out-or-reclaiming-memory-tp24268680p24268680.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
> and provide commented, minimal, self-contained, reproducible code.
>



-- 
Jim Holtman
Cincinnati, OH
+1 513 646 9390

What is the problem that you are trying to solve?

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