How to Deploy Databricks Unity Catalog Table with CI/CD: A Step-by-Step Guide

Are you tired of manually deploying your Databricks Unity Catalog tables, only to find that they’re not up-to-date or worse, broken? Do you want to streamline your deployment process and ensure that your tables are always in sync with your code changes? Look no further! In this article, we’ll show you how to deploy Databricks Unity Catalog tables with CI/CD, so you can focus on what matters most – building amazing data products.

What is Databricks Unity Catalog?

Before we dive into the deployment process, let’s quickly cover what Databricks Unity Catalog is. Unity Catalog is a centralized metadata management system in Databricks that allows you to manage and share datasets, tables, and models across your organization. It provides a single source of truth for your data assets, making it easier to collaborate, version, and reproduce your work.

Why Deploy Databricks Unity Catalog Tables with CI/CD?

Deploying your Unity Catalog tables with CI/CD offers several benefits, including:

• Consistency: Ensure that your tables are always up-to-date and consistent across environments.
• Automation: Automate the deployment process, reducing the risk of human error and freeing up your time.
• Version Control: Track changes to your tables and roll back to previous versions if needed.
• Collaboration: Enable collaboration among team members and stakeholders by providing a single source of truth.

Prerequisites

Before we begin, make sure you have:

• A Databricks workspace with Unity Catalog enabled.
• A code repository (e.g., GitHub, GitLab) for your table definitions.
• A CI/CD tool (e.g., Jenkins, GitHub Actions) set up and configured.

Step 1: Define Your Table in a Code Repository

Create a new file in your code repository (e.g., `tables/my_table.json`) with the following contents:

{
  "name": "my_table",
  "description": "My awesome table",
  "columns": [
    {
      "name": "id",
      "dataType": "integer"
    },
    {
      "name": "name",
      "dataType": "string"
    }
  ]
}

This file defines a simple table with two columns: `id` and `name`. You can add more columns, data types, and other properties as needed.

Step 2: Create a Databricks Unity Catalog API Token

Log in to your Databricks workspace and navigate to the Unity Catalog page. Click on your profile picture in the top right corner and select “API Tokens” from the dropdown menu. Create a new API token with the ” Unity Catalog” scope.

Save the API token securely in a secrets manager or environment variable. We’ll use it later to authenticate with the Unity Catalog API.

Step 3: Configure Your CI/CD Tool

Set up a new CI/CD pipeline in your chosen tool (e.g., Jenkins, GitHub Actions) with the following steps:

Step 3.1: Checkout Code

Checkout your code repository containing the table definition file.

Step 3.2: Install Databricks Unity Catalog CLI

Install the Databricks Unity Catalog CLI using pip:

pip install databricks-unity-catalog

Step 3.3: Authenticate with Unity Catalog API

Set the Unity Catalog API token as an environment variable:

export UNITY_CATALOG_API_TOKEN=<your_api_token>

Step 3.4: Deploy Table

Use the Unity Catalog CLI to deploy your table:

databricks unity-catalog tables deploy --token $UNITY_CATALOG_API_TOKEN --file tables/my_table.json

This command deploys the `my_table.json` file to the Unity Catalog, creating a new table or updating an existing one.

Step 3.5: Verify Deployment

Verify that the table has been deployed successfully:

databricks unity-catalog tables get --token $UNITY_CATALOG_API_TOKEN --name my_table

This command retrieves the table definition from the Unity Catalog, ensuring that it matches your code repository.

Step 4: Configure Automated Deployment

Configure your CI/CD tool to trigger the pipeline automatically on code changes:

For example, in GitHub Actions, add a webhook to trigger the pipeline on push events:

on:
  push:
    branches:
      - main
jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
        uses: actions/checkout@v2
      - name: Install Unity Catalog CLI
        run: pip install databricks-unity-catalog
      - name: Deploy table
        env:
          UNITY_CATALOG_API_TOKEN: ${{ secrets.UNITY_CATALOG_API_TOKEN }}
        run: databricks unity-catalog tables deploy --token $UNITY_CATALOG_API_TOKEN --file tables/my_table.json
      - name: Verify deployment
        run: databricks unity-catalog tables get --token $UNITY_CATALOG_API_TOKEN --name my_table

In Jenkins, configure a webhook to trigger the pipeline on push events:

pipeline {
  agent any
  triggers {
    webhook {
      url 'https://your-jenkins-instance.com/github-webhook/'
    }
  }
  stages {
    stage('Deploy') {
      steps {
        sh 'pip install databricks-unity-catalog'
        sh 'databricks unity-catalog tables deploy --token $UNITY_CATALOG_API_TOKEN --file tables/my_table.json'
        sh 'databricks unity-catalog tables get --token $UNITY_CATALOG_API_TOKEN --name my_table'
      }
    }
  }
}

Conclusion

That’s it! You’ve successfully deployed your Databricks Unity Catalog table with CI/CD. From now on, any changes to your table definition will be automatically deployed to your Unity Catalog, ensuring consistency and version control across your organization.

Remember to test your pipeline thoroughly and adapt it to your specific use case. Happy deploying!

Step	Description
1	Define your table in a code repository
2	Create a Databricks Unity Catalog API token
3	Configure your CI/CD tool
4	Configure automated deployment

FAQs

Q: What if I have multiple tables to deploy?

A: You can deploy multiple tables by creating a separate pipeline step for each table or by using a wildcard in your pipeline script to deploy all tables in a specific directory.

Q: How do I handle errors during deployment?

A: You can use try-catch blocks in your pipeline script to handle errors during deployment. For example, you can catch exceptions and send notifications to your team or stakeholders.

Q: Can I use this approach for other Databricks assets, such as models and datasets?

A: Yes, you can adapt this approach to deploy other Databricks assets, such as models and datasets, by using the corresponding Unity Catalog CLI commands.

By following these steps, you’ll be able to deploy your Databricks Unity Catalog tables with CI/CD, ensuring that your data assets are always up-to-date and consistent across your organization. Happy deploying!

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Frequently Asked Questions

Get ready to unleash the power of Databricks Unity Catalog with CI/CD deployment! Here are the top questions and answers to get you started.

I hope this helps! Let me know if you have any further requests.