[R] How to skip re-installing CRAN packages when updating R?

Prof Brian Ripley ripley at stats.ox.ac.uk
Thu Dec 25 10:16:12 CET 2008

Please do study the posting guide: you have not told us your platform and 
it does matter.

For Windows and Mac OS X see the appropriate FAQ.

On Wed, 24 Dec 2008, Sean Zhang wrote:

> Dear R-helpers:
> I am new to R and would like to seek your expert opinion on installation
> tip. Many thanks in advance.
> I want to update my R  to the newest  version and wonder the following two
> questions:
> Question 1:
> How can I install R and its contributed packages in a way so when updating R
> in the future, I do NOT need to
> re-install contributed packages used by R of last version.

Use a separate library directory.  You will need to re-install for updates 
to dot-0 releases (e.g. 2.9.0) but update.packages(checkBuilt=TRUE) does 
that for you.

> Question 2:
> Is it an ok-practice to just install all the CRAN packages (i.e.,
> install.packages(available.packages()[,1]) ). Does someone do so?

Not a good idea as you already have some, the recommended packages.
install.packages(new.packages()) would be better.  And yes, quite a few 
sites do things like that, but do bear in mind the costs on the CRAN 
servers (we keep a local mirror and install from that).

> The reason I ask the second question is that if installing all available
> packages does Not consume too much time (say less than 2 hours), too much
> computer resource (I have big harddrive, so harddrive is probably not a
> concern. I guess computing speed will not be affected but not sure...)
> then, I do not need to bother Question 1 and will just install all available
> packages when updating R.

It will take more than 2 hours for a source install except for a parallel 
install on a very fast machine.  For example, the Windows build takes 8 
CPU hours 
(http://cran.r-project.org/bin/windows/contrib/checkSummaryWin.html) and I 
think my x86_64 Linux server takes about 3 elapsed hours and 3GB for the 
installed packages.  (There is no built-in support for parallel installs, 
although some of us have written private versions.)

> Many Thanks in advance.
> Merry Christmas!
> -Sean
> 	[[alternative HTML version deleted]]
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Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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