Submitting an R script as an sbatch job

Owned by Juan Jose Garcia Mesa
Last updated: Dec 02, 2024
2 min read

This guide walks you through the process of running an R script as an sbatch job on Sol. This is useful when you have a long-running, computationally-intensive R script that you want to run on Sol.

Step 1: Convert an R markdown file to an R script

If you already have an R script (.R) file, you can skip this step and proceed to Step 2. If you are working with an R markdown file (.Rmd), you will need to convert it to an R script (.R) before you can run it as an sbatch job. You can do this by following these steps:

  1. Open an RStudio session on sol.asu.edu or request a lightwork interactive session with aux-interactive, load R with module load r-4.4.0-gcc-12.1.0 and start an R session with R.

  2. Use the knitr package to convert the R markdown file to an R script:

library(knitr) purl("example.Rmd", output = "example.R")

Step 2: Prepare the R script for sbatch submission

Review the generated example.R script and make any necessary adjustments to ensure compatibility with non-interactive execution. A few common adjustments include:

  • Removing or modifying any interactive elements (e.g., readline, shiny).

  • Ensuring any file paths, inputs, or outputs are explicitly defined and relative to the working directory where the script will run.

  • If the script includes plotting or graphical outputs, consider saving them to files (e.g., PNG, PDF) instead of displaying them interactively.

  • Removing any cells that are not necessary for the sbatch job.

  • Adding necessary imports and environment setup at the beginning of the script.

Step 3: Create an sbatch script

To submit the R script as an sbatch job, you need to create an sbatch script that specifies the resources and the commands required to run the job. Below is an example sbatch script (submit_job.sbatch). Note that you must load the appropriate R module on the script; interactive sessions use the latest version by default.

#!/bin/bash #SBATCH -N 1 # number of nodes #SBATCH -c 8 # number of cores #SBATCH -t 0-01:00:00 # time in d-hh:mm:ss #SBATCH -p general # partition #SBATCH -q public # QOS #SBATCH -o slurm.%j.out # file to save job's STDOUT (%j = JobId) #SBATCH -e slurm.%j.err # file to save job's STDERR (%j = JobId) #SBATCH --mail-type=ALL # Send an e-mail when a job starts, stops, or fails #SBATCH --mail-user="%u@asu.edu" #SBATCH --export=NONE # Purge the job-submitting shell environment #Load R module module load r-4.4.0-gcc-12.1.0 #Run the R script Rscript example.R

Step 4: Submit the sbatch job

  1. Use the sbatch command to submit the sbatch script:

sbatch submit_job.sbatch

  1. Monitor the job status using the squeue command:

  1. Once the job completes, review the output and error logs slurm.<jobid>.out and
    slurm.<jobid>.err, respectively.

Additional notes

  • Make sure to save your work in the R markdown before converting it to an R script.

  • Ensure that all necessary files and dependencies are available in the working directory where the sbatch job will run.

  • You can test and troubleshoot the R script using the debug QOS by running
    interactive -q debug -t 15.

Arizona State University