running RStudio Server on farm using R as installed in a conda environment

[ctb]

Running rstudio server on farm - June 19, 2023

Titus Brown, [email protected]

June 19, 2023

To edit: / latest on github

Log into farm

Via ssh, as usual!

Allocate computational resources with srun

Allocate computational resources interactively via srun, and use a high priority queue.

For example, this:

srun -p high2 --time=0:30:00 --nodes=1 \
    --cpus-per-task 2 --mem 5GB --pty /bin/bash

will allocate 5 GB of RAM for 30 minutes on the high2 partition/queue.

::::warning
Note: the memory, CPUs, and time you allocate here will apply to your RStudio Server session!
::::

Recommended: activate a conda environment

To use your own conda installation of R; if so, you'll need to have a pre-existing conda environment, or else you'll have to create one (see Appendix, below, for instructions). If you create one, you only need to do this once.

Activate the conda environment like so:

conda activate r_env

where r_env is the name of your conda environent with r-base installed.

::::info

Why use conda?

There are several good reasons to use conda to install your own version of R. These reasons include:

• you can install many R packages directly from conda-forge without compiling them; e.g. conda install r-tidyverse to install tidyverse.
• you can install your own packages from source as well, using e.g. devtools (conda install r-devtools)
• you can pick from a wide variety of R versions! List them all with conda list r-base

See the appendices to this document for instructions on installing conda and creating an R environment.
::::

An easy alternate: activate the R module

If, instead of using conda, you want to use a system-installed R package, run:

module load R

You can select specific versions as listed by module avail R.

::::warning
If you have conda installed, you may need to run the following to use the system provided R module:

conda deactivate
unset CONDA_EXE

::::

Load and run rstudio server

module load rstudio-server
rstudio-launch

This will print out some specific instructions; you will need the ssh information as well as the RStudio Server password.

Note that this information will change every time you run rstudio-launch: it is specific to your account and session!

::::warning
Note: rstudio-launch is what is running RStudio Server! If it exits (because srun runs out of time, or you hit CTRL-C), your RStudio Server will stop as well!
::::

Set up ssh tunnel

Create a new ssh connection into farm; on Mac OS and Linux computers, you can create a new terminal on your desktop/laptop computer and copy/paste from the instructions printed out by rstudio-launch above.

For example, you will want to run something like:

ssh -L35181:cpu-3-51:35181 [email protected]

in a new window on your Mac OS X/Linux laptop/desktop

On Windows it's slightly trickier and depends on what software you are running.

Open the RStudio Server Web page and log in

Now, open the URL printed out by rstudio-launch in a Web browser, and enter the provided username and password.

You should now be connected to RStudio Server! 🎉

Log out

At the end of your session, you can just close the tab and your ssh window(s).

If you want to be polite, you can more explicitly release the computational resources and shut things down by doing the following:

• use the File... menu in RStudio Server to close the session.
• type CTRL-C in the window where you ran srun and rstudio-launch.
• log out of your srun session by typing exit.
• log out of farm in both windows.

Appendix: create a conda environment containing R

(You'll need to have conda installed before this; see below. If you have (base) in your prompt, you're good to go!)

To create a conda environment named r_env with R v4.3.0 installed, run:

conda create -n r_env -y r-base=4.3.0

Appendix: installing conda

There are several ways to install conda; we recommend using mambaforge.

Here are some commands you can copy/paste:

echo source ~/.bashrc >> ~/.bash_profile
curl -LO https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-Linux-x86_64.sh
bash Mambaforge-Linux-x86_64.sh 

The last command will run a program that will ask a number of questions before installing conda; answer "yes" to all of them.

Then, log out and log back in.

Your shell prompt should now have (base) at the beginning, indicating that conda was installed and you are in the base conda environment.

For documentation on using conda, see this tutorial.

[ctb]

I'm not sure if high ports on farm head node itself are open, you might be able to do the tunneling on the farm head node and then access farm.cse.ucdavis.edu:port.

[camillescott]

I'm not sure if high ports on farm head node itself are open, you might be able to do the tunneling on the farm head node and then access farm.cse.ucdavis.edu:port.

I'm quite sure those are closed :)

[ctb]

ref also #51

[ccbaumler]

Is this virtual RStudio limited to the setting --nodes=1 --cpus-per-task 1 --mem 5GB?

[ctb]

nope, those are configurable!

[ctb]

(but if you go over what you set, e.g. load a 10 GB file into memory in R, then R and RStudio will be killed.)

[ccbaumler]

One note I think is important (and may be obvious to others), the RStudio is running on a Linux OS. Therefore, it can be difficult to install packages through install.packages() within the virtual RStudio IDE (eg devtools). However, simply using mamba install -c r <r-packagename> within the r_env conda environment will install the packages in the virtual RStudio IDE.

[ctb]

good catch @ccbaumler - can you give me an example of a package that install.packages() doesn't work with? I think there's a solution...

[ccbaumler]

I attempted to install the devtools package through install.packages() and multiple dependencies were unable to install such as the curl package.

[ctb]

updated top comment for june 19, 2023 functioning.

[PallaviShakya]

This is the module now:

rstudio-server/2022.12.0-353

[ctb]

This is the module now:

rstudio-server/2022.12.0-353

thank you! I think that module load rstudio-server should always get the latest version & that's what is in the top comment.

[ctb]

I attempted to install the devtools package through install.packages() and multiple dependencies were unable to install such as the curl package.

devtools is an example of a particularly tricky library, since it's literally a tool for installing more stuff into R! It likely needs many more things in your conda environment to be installed - in particular, C compilers. Suggest installing r-devtools with conda, which should bring all that in ;).

When I tried installing devtools with install.packages just now, in an environment with r-base=4.3.0 installed, I got:

ERROR: dependencies ‘usethis’, ‘pkgdown’, ‘profvis’, ‘rcmdcheck’, ‘roxygen2’, ‘rversions’, ‘urlchecker’ are not available for package ‘devtools’

...alas.