GWF Cuizinart

The Cuizinart is a cloud-based platform that provides an interactive portal for researchers to "slice and dice" large NetCDF datasets across the GWF program and beyond. The platform provides an easy-to-use interface similar to Google Maps: researchers select products and variables of interest, provide geographical bounds, and after a short wait, are delivered a custom dataset that meets their exact specifications.

Setup

For the production setup of Cuizinart and CaSPAr, refer to https://github.com/gwf-uwaterloo/production.

Dependencies (if not using Docker)

• Install packages: pip install -r requirements.txt
• PySpark backend:
  • Make sure $SPARK_HOME is set
  • Run geopyspark install-jar
• Frontend: Run npm install in frontend

Backend and Database

• Create a file .env in the base folder, as described in docs/env.md

• Create an ssh keyfile that will be used to transfer requests to the remote data processing engine:

  • Run ssh-keygen -f cuizinart/.id_rsa -t rsa -N ''
  • Transfer the created .id_rsa.pub to the remote server

• If not using Docker: Create the metadata database:

  • In a psql shell, type: create database cuizinart
  • In the base directory, run flask db init, flask db migrate, flask db upgrade to create the tables.
  • Run flask pyspark-init <pwd> to create a user for the PySpark slicer.

Run

Currently, we have a development deployment in tuna under /home/mgauch/dev-cuizinart/ (running the master branch, no nginx server) and

• a cuizinart production deployment in /home/mgauch/cuizinart-prod/ (running the cuizinart-prod branch)
• a CaSPAr production deployment in /home/mgauch/caspar-prod/ (running the caspar-prod branch). The production deployments are accessed through an nginx server, deployed from /home/mgauch/production. Once code is known to run fine on dev-cuizinart, we git merge master into *-prod.

Docker

• Run docker-compose up or start containers cuizinart, postgres, pyspark as needed.
• To deploy code changes, run docker-compose stop cuizinart, docker-compose build cuizinart, docker-compose up cuizinart.

Without Docker

• Serving the frontend:

  • For development and debugging, run npm start in cuizinart/frontend/ to start the frontend server on port 3000.
  • To deploy for production, run npm run build in cuininart/frontend/

• Run python cuizinart/main.py to start the backend facade. In case you chose npm run build in the previous step, this Flask app will serve the webpage.

• Run python cuizinart_pyspark/pyspark_app.py to start the PySpark cuizinart.

Adding Users

• Run flask users create <email> --password <pwd> -a. (When using Docker, you need to run this in the cuizinart container.)