# Remembering server installation details

I’ve been moving part of my work to university servers, where I’m just one more peasant user with little privileges. In exchange, I can access the jobs from anywhere and I can access multiple processors if needed. Given that I have a sieve-like memory, where configuration details quickly disappear through many small holes, I’m documenting the little steps needed to move my work environment there.

The server provides a default R installation but none of the additional packages I often install are available (most people accessing the servers don’t use R). I could contact the administrator to get them installed, but I’ve opted for installing them under my user space. For that I followed the instructions presented here, which in summary require adding the name of the default folder (/hpc/home/luis/rpackages) for the local library of packages to my .bashrc file:

R_LIBS="/hpc/home/luis/rpackages" export R_LIBS

I also have a temporary folder (called rpackages)in the account where I move the source of the packages to be installed (using SFTP). Once the R session is started it is possible to check that the local folder is first in the library path, confirming that R_LIBS has been made available to R.

Then I can install the packages I moved to the server with SFTP from the temporary folder to the local library using install.packages().

.libPaths() # [1] "/hpc/home/luis/rpackages" # [2] "/hpc/home/projects/packages/local.linux.ppc/pkg/R/2.15.1/lib64/R/library" # install.packages("~/temporary/plyr_1.8.tar.gz", lib="/hpc/home/luis/rpackages", repos=NULL)   # * installing *source* package 'plyr' ... # ** package 'plyr' successfully unpacked and MD5 sums checked # ** libs # gcc -std=gnu99 -I/usr/local/pkg/R/2.15.1/lib64/R/include -DNDEBUG -fPIC -O2 -c loop-apply.c -o loop-apply.o # gcc -std=gnu99 -I/usr/local/pkg/R/2.15.1/lib64/R/include -DNDEBUG -fPIC -O2 -c split-numeric.c -o split-numeric.o # gcc -std=gnu99 -shared -Wl,--as-needed -o plyr.so loop-apply.o split-numeric.o # installing to /hpc/home/luis/rpackages/plyr/libs # ** R # ** data # ** moving datasets to lazyload DB # ** inst # ** preparing package for lazy loading # ** help # *** installing help indices # ** building package indices # ** testing if installed package can be loaded # # * DONE (plyr)

Now we can load the package as normal:

require(plyr) # Loading required package: plyr

Nothing complicated or groundbreaking, just writing down the small details before I forget them.

Gratuitous picture: just different hardware (Photo: Luis, click to enlarge).