R Packages in the Cluster
On the CRAN system for R (http://www.r-project.org), one can find more than 7000 packages. When the CRMDA started in early 2010, we noted there were 2400 packages. CRAN is a rapidly growing collection.
At one time, we would install every package and keep all of them up to date every day. That is not possible any longer. Rather, the system administrators install R and a selection of about 250 packages that we believe are most heavily used and then we leave the users to install additional packages into their own home directories.
It may be that a package is urgently needed by many users. If so, we will install it in the system-wide R library. To make a request, contact either Paul Johnson <firstname.lastname@example.org> or write to <email@example.com>.
That is not truly unnecessary, because running install.packages() as a user will trigger a popup message, saying something like "we notice you are not an administrator, do you want to install this in your personal library".
> install.packages("zipfR", dep = TRUE, repos = "http://rweb.crmda.ku.edu/cran") Warning in install.packages("zipfR") : argument 'lib' is missing: using '/panfs/pfs.acf.ku.edu/crmda/tools/lib64/R/site-library' Warning in install.packages("zipfR") : 'lib = "/panfs/pfs.acf.ku.edu/crmda/tools/lib64/R/site-library"' is not writable Would you like to create a personal library '~/R/x86_64-redhat-linux-gnu-library/3.2.1' to install packages into? (y/n) y
The user says yes, R installs the package, and then when the user starts R, the system looks for the user's packages in that spot, and then it looks in the system libraries.
There may be some trouble in the installation process. If so, write an email to firstname.lastname@example.org and the technicians will check into it. Be sure to include the input & output from the attempted install as well as the return from running sessionInfo().
Common R package functions:
Find out what packages are currently installed in the system
This combines the system-wide R package collection and the user's collection.
To find out where R is currently searching for packages, run this function
The first letter of the function's name is a period, don't forget that part. This is an important function because it helps to make sure that the user's R folder is in the path.
Users that have not yet installed any packages in their home folders see this:
> .libPaths()  "/panfs/pfs.acf.ku.edu/crmda/tools/lib64/R/3.1/site-library"  "/panfs/pfs.acf.ku.edu/cluster/6.2/R/3.1.0/lib64/R/library"
While users who have installed packages see this:
Additional R Resources
We are learning ways to make R models run faster on the cluster. I believe, at this time, it is not possible to provide a simple 1-2-3 step approach to this, but I have seen some tips.
Dirk Eddelbuettel, "Introduction to High-Performance Computing with R: UseR! 2009 Tutorial", Universite Rennes II, Agrocampus Quest, Laboratorie de Mathematiques Appliquees, 7 July 2009. Put simply, this one is about as good as it gets. R 2009 HPC Tutorial »
Hana Sevcikova, "snowFT: Generic Framework for Parallel Statistical Computing" Generic Framework for Parallel Statistical Computing »
"The snowFT package eliminates a few drawbacks of snow and makes it much easier to use (one needs only one function). It can be used on a cluster as well as on a multi-core machines."