[BioC] Installation memory demands (GO, humanLLMappings)

[Jan T. Kim]

Dear Bioconductors,

yesterday, I tried to install Bioconductor on a notebook running Linux,
with 512 MB RAM, 1 GB swap, Linux 2.6.0, gcc 3.3.2, Debian, R 2.0.1
compiled from source (also yesterday). However, the installation got
stuck upon installing GO. While working on GOTERM, the system started
swapping in excessive amounts, slowing the R process down to a crawl,
finally to 0.1% of CPU time. At this point, I lost patience and killed
the process. I found a report on the same kind of problem by searching
the mailing list archive:

    https://stat.ethz.ch/pipermail/bioconductor/2004-November/006881.html

I have desktop Linux box on which Bioconductor installs without such
problems, this system has 1 GB RAM which, perhaps, makes the difference.
I created a local installation of Bioconductor on that and copied the
GO directory across to the notebook, which seems to have fixed the
problem for now. Continuing the installation from there, humanLLMapping 
ran into the same kind of problem, so I killed R again and "installed"
that package by again rsyncing the directory form the desktop.

I'm somewhat puzzled because a number of weeks ago, I installed
Bioconductor on a notebook with similar hardware, without such problems.

I have the following questions / remarks:

    * does the installation generally require this much memory, or
      is this a quirk of that particular notebook (e.g. a buggy library
      version with an unfortunate memory leak or the like)?

    * are there workarounds, such as installing these packages
      manually in some clever way? The standard approach of downloading
      GO_1.6.8.tar.gz and R CMD INSTALLing that doesn't improve
      anything...

    * if this is a general thing, I'd suggest to mention this in the
      installation howto or the FAQ -- I googled for "memory installation
      site:www.bioconductor.org", with no relevant results.

    * what do you think about my "cross-installation" fix, is that
      reasonable here? With the same version of R and a reasonably
      similar platform, it seemed worth a try and there are no
      obvious problems, but I haven't been able to test this
      thoroughly until now.

Best regards & thanks in advance for any comment,
Jan
-- 
 +- Jan T. Kim -------------------------------------------------------+
 |    *NEW*    email: jtk at cmp.uea.ac.uk                               |
 |    *NEW*    WWW:   http://www.cmp.uea.ac.uk/people/jtk             |
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