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Integrating RStudio Workbench with Slurm#

Overview#

These steps describe how to integrate RStudio Workbench, formerly RStudio Server Pro1, with Launcher and Slurm.

In this configuration, the RStudio Workbench and Launcher services will be installed to one node in the Slurm cluster, and the RStudio Workbench Session Components will be installed on all other Slurm nodes.

Info

Launcher is a new feature of RStudio Workbench 1.22 that is only available under named user licensing. RStudio Workbench 1.2 without Launcher is available under existing server-based licensing. For questions about using Launcher with RStudio Workbench, please contact sales@rstudio.com.

Prerequisites#

  • An existing Slurm cluster

Pre-Flight Configuration Checks#

Verifying active Slurm compute nodes

  • On a machine with Slurm configured, ensure that you have one or more worker nodes that are ready to accept jobs as part of the Slurm cluster by running the following command:

    Terminal
    $ sinfo

Verifying functionality with a test job

  • On a machine with Slurm configured, ensure that you are able to deploy a sample jobs to your Slurm cluster by running a test command:

    Terminal
    $ srun date

  • You can also create a sample script called submit.sh:

    File: submit.sh
    #!/bin/bash
#
#SBATCH --job-name=test
#SBATCH --output=res.txt
#
#SBATCH --ntasks=1
#SBATCH --time=10:00

srun hostname
srun sleep 60

  • Then submit the job by running the following command:

    Terminal
    $ sbatch submit.sh

  • Verify that it runs successfully on the Slurm cluster.

Step 1. Install RStudio Workbench on one Slurm node#

You can install RStudio Workbench on any Slurm node that has access to the Slurm tooling such as sbatch, srun, sinfo, etc. This can be a Slurm login/submission node, controller node, or compute node.

Note

You only need to install RStudio Workbench on one node. In later steps, you will install R and the RStudio Workbench Session Components on other Slurm nodes.

Step 2. Configure RStudio Workbench with Launcher#

  • On the node where RStudio Workbench is installed, add the following lines to the RStudio Workbench configuration file:

    File: /etc/rstudio/rserver.conf
    # Launcher Config
launcher-address=127.0.0.1
launcher-port=5559
launcher-sessions-enabled=1
launcher-default-cluster=Slurm
launcher-sessions-callback-address=http://<SERVER-ADDRESS>:8787

  • We recommend that you do the following:

    • In the launcher-sessions-callback-address setting, you should replace <SERVER-ADDRESS> with the hostname or IP address of RStudio Workbench.

    • You should also change the protocol and port if you are using HTTPS or a different port.

      Note

      If HTTPS is being used, ensure you have launcher-use-ssl=1 configured in the rserver.conf file.

  • Ensure that the launcher-sessions-callback-address is reachable from the Slurm compute nodes.

Step 3. Configure Launcher settings and plugins#

  • On the node where RStudio Workbench is installed, add the following lines to the Launcher configuration file:

    File: /etc/rstudio/launcher.conf
    [server]
address=127.0.0.1
port=5559
server-user=rstudio-server
admin-group=rstudio-server
authorization-enabled=1
thread-pool-size=4
enable-debug-logging=1

[cluster]
name=Slurm
type=Slurm

Step 4. Configure profile for Launcher Slurm plugin#

  • On the node where RStudio Workbench is installed, add the following lines to the Launcher profiles configuration file:

    File: /etc/rstudio/launcher.slurm.profiles.conf
    [*]
default-cpus=1
default-mem-mb=512
max-cpus=2
max-mem-mb=1024

Step 5. Configure Launcher with Slurm#

  • On the node where RStudio Workbench is installed, add the following lines to the Launcher Slurm configuration file:

    File: /etc/rstudio/launcher.slurm.conf
    slurm-service-user=slurm
enable-debug-logging=1

The slurm-service-user should match the Slurm service user in your cluster.

Step 6. Verify Slurm configuration and cluster environment#

  • Verify that the following requirements are satisfied for RStudio Workbench and Launcher to work with your Slurm cluster:

    • All Slurm nodes should have user's home directories mounted via shared file storage with matching user and group IDs across all nodes.
    • The root user should have read access to all users' home directories.

    • In your Slurm configuration file (slurm.conf), the MinJobAge setting should be equal to or greater than the job-expiry-time setting in /etc/rstudio/launcher.conf, which is 24 h by default. For both of them to be 24 h, you would need to set MinJobAge=86400 in your slurm.conf.

      Note

      The MinJobAge setting in slurm.conf is configured in seconds, rather than hours.

Step 7. Ensure that R is available on Slurm compute nodes#

  • On each Slurm compute node in the cluster (where you did not install RStudio Workbench), you will need to install one or more versions of R and associated R packages to be able to start R sessions via Slurm.

  • We recommend installing R to a shared file server or network drive location so that any installed packages are also available across all compute nodes. You can also make use of existing versions of R and environment modules that are available on the cluster.

    Info

    For more information on using Launcher and Slurm with multiple versions of R and module loading, refer to the Multiple Versions of R and Module Loading section of the RStudio Workbench Launcher Administration Guide and the R Versions section of the RStudio Workbench Administration Guide.

    • Alternatively, you can manually install R and R packages by following the steps to Install R on each Slurm compute node.

Step 8. Install RStudio Workbench session components on Slurm compute nodes#

On each Slurm compute node in the cluster (where you did not install RStudio Workbench), you will need to install the RStudio Workbench session components and create an rstudio-server user to be able to start R sessions via Slurm.

  • Use the following commands to install the RStudio Workbench session components on each Slurm compute node:

    sudo yum install libcurl-devel libuser-devel openssl-devel rrdtool

curl -O https://s3.amazonaws.com/rstudio-ide-build/session/centos7/rsp-session-centos7-1.4.1717-3.tar.gz
sudo mkdir -p /usr/lib/rstudio-server
sudo tar -zxvf ./rsp-session-centos7-1.4.1717-3.tar.gz -C /usr/lib/rstudio-server/
sudo mv /usr/lib/rstudio-server/rsp-session*/* /usr/lib/rstudio-server/
sudo rm -rf /usr/lib/rstudio-server/rsp-session*
rm -f ./rsp-session-centos7-1.4.1717-3.tar.gz

    sudo apt-get install curl libcurl4-gnutls-dev libssl1.0.0 libssl-dev libuser libuser1-dev rrdtool

curl -O https://s3.amazonaws.com/rstudio-ide-build/session/xenial/rsp-session-xenial-1.4.1717-3.tar.gz
sudo mkdir -p /usr/lib/rstudio-server
sudo tar -zxvf ./rsp-session-xenial-1.4.1717-3.tar.gz -C /usr/lib/rstudio-server/
sudo mv /usr/lib/rstudio-server/rsp-session*/* /usr/lib/rstudio-server/
sudo rm -rf /usr/lib/rstudio-server/rsp-session*
rm -f ./rsp-session-xenial-1.4.1717-3.tar.gz

    sudo apt-get install rrdtool libuser libuser1-dev

curl -O https://s3.amazonaws.com/rstudio-ide-build/session/debian9/rsp-session-debian9-1.4.1717-3.tar.gz
sudo mkdir -p /usr/lib/rstudio-server
sudo tar -zxvf ./rsp-session-debian9-1.4.1717-3.tar.gz -C /usr/lib/rstudio-server/
sudo mv /usr/lib/rstudio-server/rsp-session*/* /usr/lib/rstudio-server/
sudo rm -rf /usr/lib/rstudio-server/rsw-session*
rm -f ./rsp-session-debian9-1.4.1717-3.tar.gz

    sudo zypper install libuser-devel

curl -O https://s3.amazonaws.com/rstudio-ide-build/session/opensuse/rsp-session-opensuse-1.4.1717-3.tar.gz
sudo mkdir -p /usr/lib/rstudio-server
sudo tar -zxvf ./rsp-session-opensuse-1.4.1717-3.tar.gz -C /usr/lib/rstudio-server/
sudo mv /usr/lib/rstudio-server/rsp-session*/* /usr/lib/rstudio-server/
sudo rm -rf /usr/lib/rstudio-server/rsp-session*
rm -f ./rsp-session-opensuse-1.4.1717-3.tar.gz

  • To create rstudio-server user on each Slurm compute node, first check the uid and gid of the rstudio-server user by running id rstudio-server on the RStudio Workbench host machine. Then, on each compute node run the following commands:

Terminal
$ sudo groupadd --system --gid <gid of rstudio-server> rstudio-server
$ sudo useraedd --system --gid rstudio-server --uid <uid of rstudio-server> rstudio-server

Step 9. Restart RStudio Workbench and Launcher Services#

  • Run the following to restart services:

    Terminal
    $ sudo rstudio-server restart
$ sudo rstudio-launcher restart

Step 10. Test RStudio Workbench with Launcher and Slurm#

  • In your browser, navigate to the RStudio Workbench interface and log in.
  • Select New Session, then click the Start Session button.
  • You can then use the RStudio Session, which will be running as a Slurm job.

Additional Documentation#

For more information on RStudio Workbench and Launcher, refer to the following reference documentation:

Troubleshooting RStudio Workbench and Slurm#

Refer to the support article on Troubleshooting Launcher and Slurm in RStudio Workbench for additional information on troubleshooting RStudio Workbench with Launcher and Slurm.

  1. We have renamed RStudio Server Pro to RStudio Workbench. This change reflects the product’s growing support for a wide range of different development environments. RStudio Workbench enables R and Python data scientists to use their preferred IDE in a secure, scalable, and collaborative environment -- whether that is the RStudio IDE, JupyterLab, Jupyter Notebooks, or VS Code. We want RStudio Workbench to be the best single platform to support open source, code-first data science, whether your team is using R or Python. Please see our official Announcement and review our FAQ regarding the name change from RStudio Server Pro to RStudio Workbench. ↩

  2. We will continue to use the RStudio Server Pro name for references to versions prior to 1.4. ↩

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