Databricks

PROD

Available In

Feature List

Metadata

Query Usage

Lineage

Column-level Lineage

Data Profiler

Data Quality

dbt

Sample Data

Reverse Metadata (Collate Only)

Auto-Classification

Stored Procedures

Tags

Owners

In this section, we provide guides and references to use the Databricks connector.

Configure and schedule Databricks metadata and profiler workflows from the OpenMetadata UI:

• Requirements
• Unity Catalog
• Metadata Ingestion
• Query Usage
• Data Profiler
• Data Quality
• Lineage
• dbt Integration
• Troubleshooting

Ingestion Deployment

To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with custom Airflow plugins to handle the workflow deployment. If you want to install it manually in an already existing Airflow host, you can follow this guide.

If you don't want to use the OpenMetadata Ingestion container to configure the workflows via the UI, then you can check the following docs to run the Ingestion Framework in any orchestrator externally.

How to Run the Connector Externally

To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with custom Airflow plugins to handle the workflow deployment.

If, instead, you want to manage your workflows externally on your preferred orchestrator, you can check the following docs to run the Ingestion Framework anywhere.

Requirements

Python Requirements

We have support for Python versions 3.9-3.11

To run the Databricks ingestion, you will need to install:

Authentication Types

Databricks connector supports three authentication methods:

1. Personal Access Token (PAT): Generated Personal Access Token for Databricks workspace authentication.
2. Databricks OAuth (Service Principal): OAuth2 Machine-to-Machine authentication using a Service Principal.
3. Azure AD Setup: Specifically for Azure Databricks workspaces that use Azure Active Directory for identity management. Uses Azure Service Principal authentication through Azure AD.

Permission Requirements

The required permissions vary based on the authentication method used:

Personal Access Token Permissions

When using PAT, the token inherits the permissions of the user who created it. Ensure the user has:

Service Principal Permissions (OAuth/Azure AD)

For Service Principal authentication, grant permissions to the Service Principal:

Unity Catalog

If you are using unity catalog in Databricks, then checkout the Unity Catalog connector.

Metadata Ingestion

1. Visit the Services Page

Click Settings in the side navigation bar and then Services.

The first step is to ingest the metadata from your sources. To do that, you first need to create a Service connection first.

This Service will be the bridge between OpenMetadata and your source system.

Once a Service is created, it can be used to configure your ingestion workflows.

Select your Service Type and Add a New Service

2. Create a New Service

Click on Add New Service to start the Service creation.

Add a new Service from the Services page

3. Select the Service Type

Select Databricks as the Service type and click Next.

Select your Service from the list

4. Name and Describe your Service

Provide a name and description for your Service.

Service Name

OpenMetadata uniquely identifies Services by their Service Name. Provide a name that distinguishes your deployment from other Services, including the other Databricks Services that you might be ingesting metadata from.

Note that when the name is set, it cannot be changed.

Provide a Name and description for your Service

5. Configure the Service Connection

In this step, we will configure the connection settings required for Databricks.

Please follow the instructions below to properly configure the Service to read from your sources. You will also find helper documentation on the right-hand side panel in the UI.

Configure the Service connection by filling the form