/pyspark-setup-demo

Demo of PySpark and Jupyter Notebook with the Jupyter Docker Stacks

Primary LanguageJupyter NotebookMIT LicenseMIT

Jupyter Notebook PySpark Demo

Demo of PySpark and Jupyter Notebook with the Jupyter Docker Stacks. Complete information for this project can be found by reading the related blog post, Getting Started with PySpark for Big Data Analytics, using Jupyter Notebooks and Docker

Architecture

Architecture

Set-up

  1. Clone this project from GitHub:

    git clone \
    --branch v2 --single-branch --depth 1 --no-tags \
    https://github.com/garystafford/pyspark-setup-demo.git

  2. Create $HOME/data/postgres directory for PostgreSQL files: mkdir -p ~/data/postgres

  3. Optional, for local development, install Python packages: python3 -m pip install -r requirements.txt

  4. Optional, pull docker images first:

    docker pull jupyter/all-spark-notebook:latest
docker pull postgres:12-alpine
docker pull adminer:latest

  5. Deploy Docker Stack: docker stack deploy -c stack.yml jupyter

  6. Retrieve the token to log into Jupyter: docker logs $(docker ps | grep jupyter_spark | awk '{print $NF}')

  7. From the Jupyter terminal, run the install script: sh bootstrap_jupyter.sh

  8. Export your Plotly username and api key to .env file:

    echo "PLOTLY_USERNAME=your-username" >> .env
echo "PLOTLY_API_KEY=your-api-key" >> .env

Demo

From a Jupyter terminal window:

  1. Sample Python script, run python3 01_simple_script.py from Jupyter terminal
  2. Sample PySpark job, run $SPARK_HOME/bin/spark-submit 02_pyspark_job.py from Jupyter terminal
  3. Load PostgreSQL sample data, run python3 03_load_sql.py from Jupyter terminal
  4. Sample Jupyter Notebook, open 04_notebook.ipynb from Jupyter Console
  5. Sample Jupyter Notebook, open 05_notebook.ipynb from Jupyter Console
  6. Try the alternate Jupyter stack with nbextensions pre-installed, first cd docker_nbextensions/, then run docker build -t garystafford/all-spark-notebook-nbext:latest . to build the new image
  7. Then, to delete the previous stack, run docker stack rm jupyter, followed by creating the new stack, run cd - and docker stack deploy -c stack-nbext.yml jupyter

Jupyter Notebook

References