R Servers
Details on creating and using R server resources for R
An R resource is a resource that provides access to the R IDE for interactive development. It is best used when your primarily programming in R.
To create a R Server resource, click the Create R Server button at the top right of the Resources page. You will be presented with the following form:
In the above form, you’ll supply the following details:
- Name: Identify the resource with a name of your choosing, and if you like, provide a description. If you want to use SSH to access this resource, check that box.
- Disk Space: The default of 10GB is a good place to start, but if you plan to store very big data files, you may want to increase this.
- Hardware: Whether the resource uses only a CPU or also a GPU.
- Size: How powerful the machine will be. This adjusts the CPU and memory, and in the case of GPU hardware the size and number of GPUs.
- Image: An image is a Docker image that describes the libraries and packages you need to run your code. Make sure that if you choose a GPU based machine, you also choose a GPU image. If you don’t know what sort of image you want, or need to set up a custom image, consult our Images documentation. Note that if there is a Dask cluster associated with the resource, it will use the same image.
- Working Directory: This is your working directory at resource startup. Most times, you can leave this as the default.
- Shutoff After: [R server resources do not currently support the auto-shutoff feature]
- Advanced Settings (optional): You can customize the Start Script and/or Environment Variables for the client and the workers your resource might contain. These settings are applied every time the R server starts.
Click Create to have your new resource built. After this, you’ll be taken to the resource page that shows the parameters you’ve requested.