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Get_Started_Notebooks_ARCHER2.md

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Spark with Python on ARCHER2

Set up a conda environment

Initialise the conda installation when you log in:

eval "$(/work/xxx/xxx/shared/miniconda3/bin/conda shell.bash hook)"

Create and populate the environment:

conda create -p /work/xxx/xxx/username/envs/spark python=3.9
conda activate /work/xxx/xxx/username/envs/envs/spark
conda install -c conda-forge jupyterlab

PySpark with Jupyterlab

Submit a job to start Jupyterlab on a backend node:

sbatch run_spark_interactive.slurm

The contents of this file:

#!/bin/bash

eval "$(/work/xxx/xxx/shared/miniconda3/bin/conda shell.bash hook)"
conda activate /work/xxx/xxx/shared/envs/envs/spark

export PYSPARK_DRIVER_PYTHON=jupyter
export PYSPARK_DRIVER_PYTHON_OPTS='lab --ip 0.0.0.0'

export HOME=/work/xxx/xxx/username/

/work/xxx/xxx/username/spark-3.1.2-bin-hadoop3.2/bin/pyspark

This job runs a Jupyterlab instance on a backend node.

Make a note of the node that it runs on, and log in to ARCHER2 again:

ssh username@login.archer2.ac.uk -L8888:NODENAME:8888

Now open localhost:8888 in your local browser with the token from jupyterlab.