Using RStudio via OnDemand

RStudio is a code development environment for R. It provides an intuitive web interface for developing your R workflow interactively. Using RStudio on Apocrita via OnDemand allows you to scale to much larger datasets and workloads without putting a strain on your local machine. Please refer to the overview section for instructions on how to login to OnDemand.

Starting an RStudio session

Select RStudio Server from the Servers list of the Interactive Apps drop-down menu, or from the My Interactive Sessions page.

Choose the resources your job will need. Choosing a 1 hour maximum running time is the best option for getting a session quickly, unless you have access to owned nodes which may offer sessions immediately for up to 240hrs if resources are available.

Choose your core request wisely

R will only use multiple cores if your code calls an appropriate parallelisation library such as parallel or parallelly. Please ensure your code is parallelised in short test sessions before requesting a large number of cores for a long runtime.

Long-running sessions requesting a large core count without using these effectively may be terminated by the ITSR admin team.

Choose your RAM request wisely

Please establish a baseline of expected RAM usage in short test sessions before requesting a large amount of RAM for a long runtime.

Long-running sessions requesting a large amount of RAM without using this effectively may be terminated by the ITSR admin team.

Once clicking Launch, the request will be queued, and when resources have been allocated, you will be presented with the option to connect to the session by clicking on the blue Connect to RStudio Server button.

Once connected, the familiar RStudio interface is presented, and you will be able to use the allocated resources, and access your research data located on Apocrita.

Installing packages

Think twice before using renv!

The renv project manager has become popular, but we strongly advise users to think twice before using it on Apocrita. It aggressively caches existing binaries, but sometimes the cached binaries for personal installs aren't compatible with all environments and can cause issues.

Additionally, renv also enables the "use the Posit Public Package Manager by default?" setting when R projects are initialised by renv::init(). Whilst you may think that the "Rocky 9" packages from PPM would make life simpler, you may run into compatibility issues when running R on Apocrita, hence why we do not recommend this method.

We use Spack environments and modules to provide additional software on Apocrita, and tend to compile almost everything from source. The PPM provides binaries based on dependencies from Rocky 9's software repositories, which we will often not be using actually - we will be using manually compiled versions instead. This is likely to lead to version mismatches and errors.

If you still choose to use renv on Apocrita despite this, the ITSR team can't really offer any support in doing so. There are details for using alternative locations for your libraries on Apocrita here.

It's likely your scripts will require additional R libraries; these can be installed using the install.packages() command in the console window of RStudio. If the package cannot be installed due to missing dependencies, please contact us and we will try to add them to the Spack environment that is activated alongside RStudio.

Known issues

Web browser security

For security reasons, modern browsers will restrict OnDemand from embedding certain content in the RStudio application. When this occurs, you will be prompted to view the content in a new window instead.

Rprojects and renv

As detailed above, the use of renv is not recommended. If you use the Rproject feature of RStudio, the default is to use renv as well. We recommend un-checking this box:

Exiting the session

If a session exceeds the requested running time, it will be killed. You may receive a message "The previous R session was abnormally terminated...". Click OK to acknowledge the message and continue. To avoid this message, it's good practice to exit the session cleanly when you have finished.

To cleanly exit RStudio, click File -> Quit Session... and then release resources back to the cluster queues by clicking the red Delete button for the relevant session on the My Interactive Sessions page.