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Looking at installed packages

You can see the list of installed R libraries by the library() call in R


We have a lot of packages already installed, you can ask us to install more, or just install them quickly in your homedir.

Which R are you using?

Try run

 which R

Try run

 R --version

Installing CRAN Packages

Most CRAN packages can be installed per-user by running install.packages() in an interactive session:

install.packages("package_name", dependencies = TRUE)

R initially attempts to install to /usr/local/lib/R, and you don't have permissions to write there, so it will prompt for the creation of a library subdirectory in ~/R (if necessary) and fall back to installation there when the initial attempt fails. If your package requires dependencies available from the standard Ubuntu repositories you can e-mail us requesting installation. We can install from the Debian/Ubuntu package repositories or into the shared FarmShare filesystem.

You can, of course, install R libraries into any arbitrary path and just add that path to your R env. That will probably break the next time R is upgraded to a new version, since your packages are built with the older version.

NOTE: when you install a package in corn, it will be available to you in Barley.

R Sample Job

Here's an example R file that generates a large array, fills it with some random numbers, then sleeps for 5mins. This happens to use up almost exactly 8GB of RAM.

Save this as 8GB.R:

x <- array(1:1073741824, dim=c(1024,1024,1024)) 
x <- gaussian()

Here's an example SGE submit script that runs that R file.


# use the current directory
#$ -cwd
#$ -S /bin/bash

# mail this address
#$ -M chekh@stanford.edu
# send mail on begin, end, suspend
#$ -m bes

R --vanilla --no-save < 8GB.R

You can submit it with just

 qsub r_test.script

Here are the output files that I get, one from stderr, one from stdout

$ cat r_test.script.o497 
R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- array(1:1073741824, dim=c(1024,1024,1024)) 
> x <- gaussian()
> Sys.sleep(300)

In the mail that you get about the ending of the job, the maxvmem number is actually incorrect, it is a known bug in this version of SGE. The R script on this page actually uses 8GB of vmem.

Another R Sample Job

R script, let's call it R-rjags.R

print("Hello World")
#this just loaded some settings from that library

Job script, let's call it R-jags.submit.script


# use the current directory
#$ -cwd
#$ -S /bin/bash

# mail this address
#$ -M chekh@stanford.edu
# send mail on begin, end, suspend
#$ -m bes

R --vanilla --no-save < R-jags.R

Submit it to the test queue with a small memory requirement:

 qsub -l mem_free=200M -l testq=1 R-jags.submit.script

Looking at the output files, it errored out because R can't find the package rjags. You have two alternatives:

  • include the R library from /mnt/glusterfs/software
  • use modules to specify the full R install from /mnt/glusterfs/software

The first way, you would add this line to your R script:

 .libPaths(c("/mnt/glusterfs/software/free/R-2.15.0/lib/R/library", "/usr/lib/R/library"))

The second way, your script will look like this:

$ cat R-jags.submit.script

# use the current directory
#$ -cwd
#$ -S /bin/bash

# mail this address
#$ -M chekh@stanford.edu
# send mail on begin, end, suspend
#$ -m bes

eval `tclsh /mnt/glusterfs/software/free/modules/tcl/modulecmd.tcl sh autoinit`
module load R-2.15.0
R --vanilla --no-save < R-jags.R


Some other departments have some other more detailed examples:

building our local R

Here's how I usually do it.


R 3.1.1 released today, I compiled it as chekh on corn40 (Ubuntu 13.10)

R is now configured for x86_64-unknown-linux-gnu

  Source directory:          .
  Installation directory:    /usr/local

  C compiler:                gcc -std=gnu99  -g -O2
  Fortran 77 compiler:       gfortran  -g -O2

  C++ compiler:              g++  -g -O2
  C++ 11 compiler:           g++  -std=c++11 -g -O2
  Fortran 90/95 compiler:    gfortran -g -O2
  Obj-C compiler:	     gcc -g -O2 -fobjc-exceptions

  Interfaces supported:      X11, tcltk
  External libraries:        readline, ICU, lzma
  Additional capabilities:   PNG, JPEG, TIFF, NLS, cairo
  Options enabled:           shared R library, shared BLAS, R profiling

  Recommended packages:      yes
  • make
  • write /farmshare/software/mf/saucy/r/3.1.1.lua

lapack issues

If you see messages like:

  unable to load shared object '/usr/lib/R/modules//lapack.so':

most likely you're mixing R versions and libraries.

Double check that you are not setting R library path to point to directories with older libraries.

This test script should run fine if you have everything set correctly

$ cat lapack.r 
zz = lm(Sepal.Length ~., data = iris) 

$ R --no-save < lapack.r 
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