databricks/databricks-asset-bundles-dais2023

databricks/databricks-asset-bundles-dais2023

Language: Python

License: NOASSERTION

Stars: 66

Forks: 75

Open issues: 10

Created: 2023-06-22T15:27:48Z

Pushed: 2024-07-15T15:12:09Z

Default branch: main

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README:

Databricks Asset Bundles

_Write code once, deploy to lakehouses everywhere..._

_Click here to watch the talk on Databricks Asset Bundles at Data & AI Summit 2023._

_The slides from the presentation are available here._

Introduction

_Databricks Asset Bundles_, also known simply as bundles, enable you to programmatically validate, deploy, and run the projects you are working on in Databricks via the Databricks CLI. A bundle is a collection of one or more related files that contain:

• Any local artifacts (such as source code) to deploy to a remote Databricks workspace prior to running any related Databricks workflows.

• The declarations and settings for the Databricks jobs, Delta Live Tables pipelines, or MLOps Stacks that act upon the artifacts that were deployed into the workspace.

For more information on bundles, please see the following pages in Databricks documentation:

Tutorials

• Bundle development tasks
• How to use Bundles with Databricks Workflows (aka Jobs)
• Automate a DLT pipeline with DABs
• Run A CI/CD process with DABs and GitHub Actions

Reference

• bundle settings reference
• bundle command group reference

Analyzing Databricks Medium Posts from Field Engineering

In this repo you'll find a simple project consisting of:

1. A CSV containing URLs of Medium.com blogs written by Field Engineers at Databricks. 2. A Delta Live Tables pipeline to ingest and process that data, including logic to scrape Medium.com for the number of claps and reading time. 3. A notebook report that reads the processed data and visualizes it. 4. A Databricks Workflow with two tasks - the first to refresh the DLT pipeline and the second to execute the notebook report.

These data assets are represented in the bundle.yml file in the project root directory.

Deploying and running this repo

Make sure you have the Databricks CLI installed, then you can use the databricks bundle commands. You'll also want to edit the bundle.yml and specify the Databricks Workspace that you plan to deploy to. Once you've got that sorted out, you can deploy and run the project using the following commands:

databricks bundle deploy
databricks bundle run fe_medium_metrics

Questions?

Please email dabs-preview@databricks.com if you have questions on DABs or if you have questions on the code in this repo, please email rafi.kurlansik@databricks.com