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Rstudio on the Urblauna cluster

Rstudio can be run on the curnaglUrblauna cluster from within a singularity container, with an interactive interface provided on the web browser of anya givenGuacamole workstation.session.

Running interactively with Rstudio on the clusters is only meant for testing. Development must be carried out on the users workstations, and production runs must be accomplished from within R scripts/codes in batch mode.

Preparatory steps on Curnagl side

A few operations have to be executed on the Curnagl cluster:

  1. IfCreate thea workstationdirectory isin outsideyour of/work theproject campus, first connectdedicated to thebe VPNused as an R library, for instance:
    mkdir /work/FAC/FBM/DBC/mypi/project/R_ROOT 
  2. LoginOptional to: theinstall cluster
    3. required
  3. Create/chooseR apackages, folderfor underinstance the /scratch or the /work filesystems under your project (ex. /work/FAC/.../rstudio); this folder will appear as your HOME inside the Rstudio environment, and we will refer to it as ${WORK}
  4. (This step is optional and only applies if you need RStudio version >4.2.2) Create the singularity image inside the cluster (substitute ${WORK} appropriately):ggplot2

    [me@curnagl ~]$ module load singularitygcc [me@curnaglr
~]$export singularityR_LIBS_USER=/work/FAC/FBM/DBC/mypi/project/R_ROOT
pullR
--dir=>>>install.packages("${WORK}" --name=rstudio-server.sif docker://rocker/rstudioggplot2")
    This last step might take a while...

The batch script

Create a file rstudio-server.sbatch with the following contents (it must be on the cluster, but the exact location does not matter):

#!/bin/bash -l

#SBATCH --account ACCOUNT_NAME
#SBATCH --mail-type BEGIN 
#SBATCH --mail-user <first.lastname>@unil.ch

#SBATCH --chdir ${WORK}
#SBATCH --job-name rstudio-server
#SBATCH --signal=USR2
#SBATCH --output=rstudio-server.job.%j

#SBATCH --partition interactivejob
#SBATCH --nodes 1
#SBATCH --ntasks 1
#SBATCH --cpus-per-task 1
#SBATCH --mem 8G
#SBATCH --time 01:59:5902:00:00
#SBATCH --export NONE

RLIBS_USER_DIR=${WORK}
RSTUDIO_CWD=~
RSTUDIO_SIF="/dcsrsoft/singularity/containers/rstudio-4.2.1.sif"

module load gcc python singularity
RSTUDIO_CWD=module load r
RLIBS_DIR=$(pwd){R_ROOT}/rlib/R/library
RSTUDIO_SIF="/dcsrsoft/singularity/containers/rstudio-4.2.2.sif"module LOCAL_PORT=8787unload r


# Create temp directory for ephemeral content to bind-mount in the container
RSTUDIO_TMP=$(mktemp --tmpdir -d rstudio.XXX)

mkdir -p -m 700 \
        ${RSTUDIO_TMP}/run \
        ${RSTUDIO_TMP}/tmp \
        ${RSTUDIO_TMP}/var/lib/rstudio-server

mkdir -p ${RSTUDIO_CWD}/.R

cat > ${RSTUDIO_TMP}/database.conf <<END
provider=sqlite
directory=/var/lib/rstudio-server
END

# Set OMP_NUM_THREADS to prevent OpenBLAS (and any other OpenMP-enhanced
# libraries used by R) from spawning more threads than the number of processors
# allocated to the job.
#
# Set R_LIBS_USER to a path specific to rocker/rstudio to avoid conflicts with
# personal libraries from any R installation in the host environment

cat > ${RSTUDIO_TMP}/rsession.sh <<END
#!/bin/sh

export OMP_NUM_THREADS=${SLURM_CPUS_PER_TASK:-1}
export R_LIBS=${RLIBS_DIR}
export R_LIBS_USER=${RSTUDIO_CWD}/.RRLIBS_USER_DIR}
export PATH=${PATH}:/usr/lib/rstudio-server/bin
exec rsession "\${@}"
END

chmod +x ${RSTUDIO_TMP}/rsession.sh

SINGULARITY_BIND+="${RSTUDIO_CWD}:${RSTUDIO_CWD},"
SINGULARITY_BIND+="${RSTUDIO_TMP}/run:/run,"
SINGULARITY_BIND+="${RSTUDIO_TMP}/tmp:/tmp,"
SINGULARITY_BIND+="${RSTUDIO_TMP}/database.conf:/etc/rstudio/database.conf,"
SINGULARITY_BIND+="${RSTUDIO_TMP}/rsession.sh:/etc/rstudio/rsession.sh,"
SINGULARITY_BIND+="${RSTUDIO_TMP}/var/lib/rstudio-server:/var/lib/rstudio-server,"
SINGULARITY_BIND+="/users:/users,/scratch:/scratch,/work:/work"work,/dcsrsoft"
export SINGULARITY_BIND

# Do not suspend idle sessions.
# Alternative to setting session-timeout-minutes=0 in /etc/rstudio/rsession.conf
export SINGULARITYENV_RSTUDIO_SESSION_TIMEOUT=0

export SINGULARITYENV_USER=$(id -un)
export SINGULARITYENV_PASSWORD=$(openssl rand -base64 15)

# get unused socket per https://unix.stackexchange.com/a/132524
# tiny race condition between the python & singularity commands
readonly PORT=$(python -c 'import socket; s=socket.socket(); s.bind(("", 0)); print(s.getsockname()[1]); s.close()')
cat 1>&2 <<END
1. SSH tunnel from your workstation usingopen the following command:

   ssh -n -N -J ${SINGULARITYENV_USER}@curnagl.dcsr.unil.ch -L ${LOCAL_PORT}:localhost:${PORT} ${HOSTNAME}

   and point yourGuacamole web browser to http://localhost:${LOCAL_PORT}HOSTNAME}:${PORT}

2. log in to RStudio Server using the following credentials:

   user: ${SINGULARITYENV_USER}
   password: ${SINGULARITYENV_PASSWORD}

When done using RStudio Server, terminate the job by:

1. Exit the RStudio Session ("power" button in the top right corner of the RStudio window)
2. Issue the following command on the login node:

      scancel -f ${SLURM_JOB_ID}
END

#singularity exec --env R_LIBS=${RLIBS_DIR} --home ${RSTUDIO_CWD} --cleanenv ${RSTUDIO_SIF} \
singularity exec --home ${RSTUDIO_CWD} --cleanenv ${RSTUDIO_SIF} \
    rserver --www-port ${PORT} \
            --auth-none=0 \
            --auth-pam-helper-path=pam-helper \
            --auth-stay-signed-in-days=30 \
            --auth-timeout-minutes=0 \
            --rsession-path=/etc/rstudio/rsession.sh \
            --server-user=${SINGULARITYENV_USER}

SINGULARITY_EXIT_CODE=$?
echo "rserver exited $SINGULARITY_EXIT_CODE" 1>&2
exit $SINGULARITY_EXIT_CODE

You need to carefully replace, at the beginning of the file, the following elements:

  • On line 3: ACCOUNT_NAME with the project id that was attributed to your PI for the given project
  • On line 5: <first.lastname>@unil.ch with your e-mail address
  • On line 7: ${WORK} must be replaced with the absolute path (ex. /work/FAC/.../rstudio) to the chosen folder you created on the preparatory steps
  • On line 24: if (and only if) you went through the optional fourth preparatory step, then you need to redefine RSTUDIO_SIF so that the line reads RSTUDIO_SIF=${RSTUDIO_CWD}/rstudio-server.sif

Running Rstudio

Submit a job for running Rstudio from within the cluster with:

[me@curnagl ~]$ sbatch rstudio-server.sbatch

You will receive a notification by e-mail as soon as the job is running.

A new file ${WORK}/rstudio-server.job.### (with ### some given job id number) is then automatically created. Its contents will give you instructions on how to proceed in order to start a new Rstudio remote session from your workstation.

You will have 2h time to test your code.

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