Data Engineering Project Template using Kubernetes, Apache Airflow, and Apache Spark

Description

This project is a template for a data engineering project using Kubernetes, Apache Airflow, and Apache Spark. The project is structured as follows:

• airflow/: Contains the Apache Airflow DAGs and plugins.
• spark/: Contains the Apache Spark jobs.
• k8s/: Contains the Kubernetes manifests.
• scripts/: Contains the scripts to deploy the project.

Installation

Instructions on how to install your project. Steps:

1. Clone the repository.
2. Run the install.sh script.
3. Run the deploy.sh script.
4. Run the run.sh script.
5. Run the teardown.sh script.
6. Run the uninstall.sh script.
7. Done!

Usage

Instructions on how to use your project. Usage examples:

• Create DAGs in the airflow/dags/ directory.
• Create Spark jobs in the spark/jobs/ directory.
• Create Kubernetes manifests in the k8s/ directory.
• Sandbox your project using the jupyter notebook in the sandbox/ directory.
• Commit your changes to the repository to trigger the CI/CD pipeline.
• Done!

Contributing

Guidelines for contributing to your project. Steps:

1. Fork the repository.
2. Create a branch.
3. Make your changes.
4. Push your changes to the branch.
5. Create a pull request.
6. Done!

License

This project is licensed under the terms of the LICENSE file.