Installing R Packages on Cypress

If you want to use some R packages that are not yet installed in your desired version of R on Cypress, then you have several alternatives, as prescribed below, for locations for installing those packages. Those locations include either your user home directory or lustre sub-directory, and the methods will vary depending on your desired level of reproducibility.

Alternative 1 - default to home sub-directory

From your R session, you may choose to have R install its packages into a sub-directory under your home directory. By default R will create such a sub-directory whose name corresponds to the R version of your current R session and install your packages there.

> R.version.string
[1] "R version 3.4.1 (2017-06-30)"
> install.packages("copula")
Installing package into ‘/share/apps/spark/spark-2.0.0-bin-hadoop2.6/R/lib’
(as ‘lib’ is unspecified)
Warning in install.packages("copula") :
  'lib = "/share/apps/spark/spark-2.0.0-bin-hadoop2.6/R/lib"' is not writable
Would you like to use a personal library instead?  (y/n) y
Would you like to create a personal library
~/R/x86_64-pc-linux-gnu-library/3.4
to install packages into?  (y/n) y
--- Please select a CRAN mirror for use in this session ---
PuTTY X11 proxy: unable to connect to forwarded X server: Network error: Connection refused
HTTPS CRAN mirror

 1: 0-Cloud [https]                   2: Algeria [https]
...
79: Vietnam [https]                  80: (HTTP mirrors)


Selection: 77
...

Note that the above example was performed without X11 forwarding, resulting in a prompt at the command line for selection of a CRAN mirror site in the above, at which point you should enter the number corresponding to the desired mirror site, e.g. 77.

Alternative 2 - specify your lustre sub-directory via exported environment variable

Alternatively, if you prefer to use, say, your lustre sub-directory rather than your home directory, then you may do so via an exported environment variable setting as in the following. The environmental variable R_LIBS_USER points the desired location of user package(s).

First, create a directory and export the environment variable.

mkdir -p /lustre/project/<your-group-name>/R/Library
export R_LIBS_USER=/lustre/project/<your-group-name>/R/Library

Then run R and install a package. Note that we can use the R function .libPaths() as confirmation of the user library location.

> .libPaths()
[1] "/lustre/project/<your-group-name>/R/Library"
[2] "/share/apps/spark/spark-2.0.0-bin-hadoop2.6/R/lib"
[3] "/share/apps/R/3.4.1-intel/lib64/R/library"
> install.packages("copula")
Installing package into ‘/lustre/project/<your-group-name>/R/Library’
(as ‘lib’ is unspecified)
...

Alternative 3 - specify lustre sub-directory via environment file

Similarly, you may accomplish the above via the same environment variable setting as above but in a local file as in the following.

First, create a directory as above.

mkdir -p /lustre/project/<your-group-name>/R/Library

Then setting R_LIBS_USER in the file ~/.Renviron will tell R a default location.

Note however that setting or unsetting the environment variable R_LIBS_USER in the file ~/.Renviron will override any previously exported value of that same environment variable!

echo 'R_LIBS_USER="/lustre/project/<your-group-name>/R/Library"' > ~/.Renviron

Or use a text editor in order to create and edit the file ~/.Renviron so that the file includes the following line.

R_LIBS_USER="/lustre/project/<your-group-name>/R/Library"

Then run R and install a package. Note again the use of R function .libPaths() as confirmation of the user library location.

> .libPaths()
[1] "/lustre/project/<your-group-name>/R/Library"
[2] "/share/apps/spark/spark-2.0.0-bin-hadoop2.6/R/lib"
[3] "/share/apps/R/3.4.1-intel/lib64/R/library"
> install.packages("copula")
Installing package into ‘/lustre/project/<your-group-name>/R/Library’
(as ‘lib’ is unspecified)
...

Alternative 4 - specify lustre sub-directory via R profile file

Similarly, you may set the sub-directory depending on R major.minor version via the R profile file as in the following.

Edit the file ~/.Rprofile as follows.

majorMinorPatch <- paste(R.version[c("major", "minor")], collapse=".")
majorMinor <- gsub("(.*)\\..*", "\\1", majorMinorPatch)
#print(paste0("majorMinor=", majorMinor))
myLibPath <- paste0("/lustre/project/<your-group-name>/R/Library/", majorMinor)
dir.create(myLibPath, showWarnings = FALSE)
#print(paste0("myLibPath=", myLibPath))
newLibPaths <- c(myLibPath, .libPaths())
.libPaths(newLibPaths)

Note that setting the R library trees directly via the R function .libPaths() in the file ~/.Rprofile can thus either override or append to that of any previously set value of R_LIBS_USER!

Then run R and install a package. Note again the use of R function .libPaths() as confirmation of the user library location.

> .libPaths()
[1] "/lustre/project/<your-group-name>/R/Library/3.4"
[2] "/share/apps/spark/spark-2.0.0-bin-hadoop2.6/R/lib"
[3] "/share/apps/R/3.4.1-intel/lib64/R/library"
> install.packages("copula")
Installing package into ‘/lustre/project/<your-group-name>/R/Library/3.4’
(as ‘lib’ is unspecified)
...

Alternative 5 - specify lustre sub-directory via R code

As for yet another alternative, you can accomplish the above entirely in your R code via the following. First, create a directory as before.

mkdir -p /lustre/project/<your-group-name>/R/Library

Then run R and install a package, but note that you must also specify the location from which to load the package in the ensuing call to the R function library().

> myLib := "/lustre/project/<your-group-name>/R/Library"
> install.packages("copula",lib=myLib)
...
> library(copula, lib.loc=myLib)