Developing with Databricks-Connect & Azure DevOps
A guide of how to build good Data Pipelines with Databricks Connect using best practices. Details: https://datathirst.net/blog/2019/9/20/series-developing-a-pyspark-application
This is a sample Databricks-Connect PySpark application that is designed as a template for best practice and useability.
The project is designed for:
- Python local development in an IDE (VSCode) using Databricks-Connect
- Well structured PySpark application
- Simple data pipelines with reusable code
- Unit Testing with Pytest
- Build into a Python Wheel
- CI Build with Test results published
- Automated deployments/promotions
Create a Conda Environment (open Conda prompt):
conda create --name dbconnectappdemo python=3.5
Activate the environment:
conda activate dbconnectappdemo
IMPORTANT: Open the requirements.txt in the root folder and ensure the version of databrick-connect matches your cluster runtime.
Install the requirements into your environments:
pip install -r requirements.txt
If you need to setup databricks-connect then run:
If you would like to deploy from your local PC to Databricks create a file in the root called MyBearerToken.txt and paste in a bearer token from the Databricks UI.
Copyright Data Thirst Ltd (2019)