apache-airflow-granulate-databricks 0.2.1

The Granulate Airflow-Databricks Integration is an open-source plugin for Apache Airflow. It's specifically designed to set environment variables that allow Granulate's performance monitoring agent to identify and integrate with Databricks jobs orchestrated by Airflow. This plugin tags Databricks jobs, aiding the Granulate optimizing agent.

Granulate Airflow-Databricks Integration

Overview

The Granulate Airflow-Databricks Integration is an open-source plugin for Apache Airflow. It's specifically designed to set environment variables that allow Granulate's performance monitoring agent to identify and integrate with Databricks jobs orchestrated by Airflow. This plugin tags Databricks jobs, aiding the Granulate optimizing agent.

Modes of Operation

The Granulate plugin can operate in three different modes:

1. Passive Mode: In this mode, you need to manually replace DatabricksSubmitRunOperator and DatabricksSubmitRunDeferrableOperator with GranulateDatabricksSubmitRunOperator and GranulateDatabricksSubmitRunDeferrableOperator respectively in your DAGs. This mode allows you to selectively apply Granulate to specific operators. The Granulate operators are drop-in replacement for their respective operators, so you can just swap them in code for relevant DAGs.

2. Auto-Patch for Specific DAGs: To enable auto-patching on specific DAGs, import and invoke the patch function from the plugin at the beginning of your DAG file:

   from apache_airflow_granulate_databricks.granulate_plugin import patch
   patch()
   

   This method patches the Databricks operators in the DAG where it's called, enabling the Granulate environment variable.

3. Auto-Patch for All DAGs: For an all-encompassing approach, install the plugin with the 'auto-patch' extra: pip install apache-airflow-granulate-databricks[auto-patch] This mode patches all Databricks operators across all DAGs in your Airflow environment, automatically applying Granulate enhancements.

Installation

To install the apache-airflow-granulate-databricks package, choose the method that best fits your setup:

• Using pip:
  • For a standard installation, run: pip install apache-airflow-granulate-databricks
  • To enable automatic DAG patching, include the auto-patch extra: pip install apache-airflow-granulate-databricks[auto-patch]
• Using _PIP_ADDITIONAL_REQUIREMENTS in Airflow:
  • Append the following line to your _PIP_ADDITIONAL_REQUIREMENTS: apache-airflow-granulate-databricks
  • For auto-patching, use: apache-airflow-granulate-databricks[auto-patch]
  • Restart your Airflow services to apply these changes.

Package Removal

• If you used pip to install, run: pip uninstall apache-airflow-granulate-databricks
• If you used _PIP_ADDITIONAL_REQUIREMENTS, remove apache-airflow-granulate-databricks
• Make sure to revert your code if you used Granulate's operators, or you you used the patch function.
• Restart your Airflow services to apply these changes.

Requirements

• Tested on Databricks Airflow Provider (4.2.0 <= version <= 6.5.0)
• Python version 3.8 or higher

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Support

For support, questions, or issues, please open an issue in the GitHub repository.