Orchestrating Airflow DAGs with GitHub Actions: A Lightweight Approach to Data Curation

Airflow, a popular open-source workflow management system, has taken the data engineering community by storm. With its ability to automate workflows, orchestrate tasks, and integrate with various tools, Airflow has become an essential tool for many data professionals. However, when it comes to integrating Airflow with other tools like Apache Spark, Dremio, and Snowflake, things can get complex.

This blog post from Alex Merced Coder provides a comprehensive guide on how to orchestrate Airflow DAGs with GitHub Actions. The author highlights common issues that can arise when setting up the environment, such as incorrect Spark master URL, firewall issues, and container resource limits. By following these troubleshooting guidelines, data engineers can identify and resolve common problems related to Python dependencies, environment variables, and PySpark configuration.

The post also emphasizes the importance of efficient data transport protocols like Apache Arrow Flight and leveraging high-performance data processing tools like Dremio Reflections. Additionally, it suggests customizing GitHub Actions workflows to meet specific data workflow requirements.

Source: https://dev.to/alexmercedcoder/orchestrating-airflow-dags-with-github-actions-a-lightweight-approach-to-data-curation-across-spark-dremio-and-snowflake-28eg