Often we may need to add R external libraries that are not part of standard R installation. As a user, we could add the libraries in our home (or stash) directory and make the libraries available on remote machines for job executions.
In this tutorial, we learn how to add
sna package from Stanford's R-lab and perform
the social network analysis as a HTCondor job on OSG Connect.
Fig.1. An example outcome of social network analysis using the external R package
sna from Stanford's R-lab
Let us utilize the
tutorial command. In the command prompt, type
$ tutorial R-addlibSNA # Copies the required files to the directory tutorial-R-addlibSNA
This will create a directory
tutorial-R-addSNA with the following files
setup_sna_packages.R # Contains the list of sources to be installed for the sna related external packages. sna_R.3.2.0.tar.gz # The tarball of the installed sna packages provided for convinience. sna_lab_1.R # The example R program that does social network analysis sna_lab_1.sh # The wrapper script to execute the R program `sna_lab_1.sh` sna_lab_1.submit # The HTCondor job description file Log/ # Directory to store the standard error, log and output files from the HTcondor job.
How to build external packages for R under userspace
At first we define where to build the external R add-on libraries. We may choose a directory in our home or stash. The
add-on library path is defined via the shell variable
R_LIBS. Say, you decided to built the library in the path
/home/username/R_libs/sna_R.3.2.0. Type the following in your shell prompt
$ export R_LIBS="/home/username/R_libs/sna_R.3.2" $ mkdir -p R_libs/sna_R.3.2
After defining the path, we are ready to go into R prompt
$ module load R/3.2.0 $ R
To see the available libraries within R
> is the R-prompt)
If you want to install the package “XYZ”, within R do
> install.packages("XYZ", repos = "http://cran.cnr.berkeley.edu/", dependencies = TRUE)
Since we have a list of packages to be added, it is better to list them in a file and source the file
to R. The following packages are listed to be installed in
install.packages("igraph", repos = "http://cran.cnr.berkeley.edu/", dependencies = TRUE) install.packages("magrittr", repos = "http://cran.cnr.berkeley.edu/", dependencies = TRUE) install.packages("sna", repos = "http://cran.cnr.berkeley.edu/", dependencies = TRUE) install.packages("igraphtosonia", repos = "http://cran.cnr.berkeley.edu/", dependencies = TRUE)
Run the setup file within R.
the above command should install the packages in the path defined by the variable
R_LIBS. As mentioned above
R_LIBS path to
/home/username/R_libs/sna_R.3.2.0 so all of them would be installed in the specified path.
Prepare tarball of the add-on packages
The next step is create a tarball of san_R.3.2.0 so that we send the tarball along with the job.
Exit from the R prompt.
From the shell prompt
$ cd /home/username/R_libs $ tar -cvzf sna_R.3.2.0.tar.gz sna_R.3.2.0
Now copy the tarball to your job directory where you have R program, job wrapper script and condor job description file.
Porting your add-on packages
The example job description file
sna_lab_1.submit contains the following information
universe = vanilla Executable = sna_lab_1.sh arguments = sna_R.3.2.0.tar.gz sna_lab_1.R transfer_input_files = sna_R.3.2.0.tar.gz, sna_lab_1.R output = Log/job.out.$(Process) error = Log/job.error.$(Process) log = Log/job.log.$(Process) requirements = (HAS_CVMFS_oasis_opensciencegrid_org =?= TRUE) queue 1
In the above description file, we specify that the files
sna_lab_1.R are transferred along with the job to the remote worker machine. Also the name of these two files are passed as arguments.
Define the libPaths() in the wrapper script
The wrapper script takes care of executing the R job properly on the remote machine. The wrapper script
module load libgfortran module load R/3.2.0 tar -xzf $1 rlocal_lib="$PWD/sna_R.3.2.0" export R_LIBS=$rlocal_lib Rscript -e ".libPaths(c(.libPaths(), '$rlocal_lib')); source('$2')"
#!/bin/bash # Sets up the bash shell environment module load libgfortran # Load ligfortran module (R requires libgfortran library) module load R/3.2.0 # Loads the R/3.2.0 module tar -xzf $1 # Uncompress the tarball file (first argument defined in sna_lab_1.submit`) rlocal_lib="$PWD/sna_R.3.2.0" # Information about the location of add-on libraries Rscript -e ".libPaths(c(.libPaths(), '$rlocal_lib')); source('$2')" # Set up `.libPaths and run the R program `sub_lab_1.R` which is second argument defined in sna_lab_1.submit)
It is important to define
.libPaths() about the location of the add-on libraries.
Now submit the job
$ condor_submit sna_lab_1.submit
and check your job status
$ condor_q username
Once the job finished running, you will see the following pdf files
$ ls *.pdf 1.1_Krackhardt_Full.pdf 1.2_Krackhardt_Advice.pdf 1.3_Krackhardt_Friendship.pdf 1.4_Krackhardt_Reports.pdf 1.5_Krackhardt_Reports_Fruchterman_Reingold.pdf 1.6_Krackhardt_Reports_Color.pdf 1.7_Krackhardt_Reports_Vertex_Size.pdf 1.8_Krackhardt_Overlayed_Ties.pdf 1.9_Krackhardt_Overlayed_Structure.pdf
This page was updated on Apr 23, 2019 at 11:45 from tutorials/tutorial-R-addlibSNA/README.md.