Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Data Engineering with Databricks Cookbook

You're reading from   Data Engineering with Databricks Cookbook Build effective data and AI solutions using Apache Spark, Databricks, and Delta Lake

Arrow left icon
Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781837633357
Length 438 pages
Edition 1st Edition
Arrow right icon
Author (1):
Arrow left icon
Pulkit Chadha Pulkit Chadha
Author Profile Icon Pulkit Chadha
Pulkit Chadha
Arrow right icon
View More author details
Toc

Table of Contents (16) Chapters Close

Preface 1. Part 1 – Working with Apache Spark and Delta Lake FREE CHAPTER
2. Chapter 1: Data Ingestion and Data Extraction with Apache Spark 3. Chapter 2: Data Transformation and Data Manipulation with Apache Spark 4. Chapter 3: Data Management with Delta Lake 5. Chapter 4: Ingesting Streaming Data 6. Chapter 5: Processing Streaming Data 7. Chapter 6: Performance Tuning with Apache Spark 8. Chapter 7: Performance Tuning in Delta Lake 9. Part 2 – Data Engineering Capabilities within Databricks
10. Chapter 8: Orchestration and Scheduling Data Pipeline with Databricks Workflows 11. Chapter 9: Building Data Pipelines with Delta Live Tables 12. Chapter 10: Data Governance with Unity Catalog 13. Chapter 11: Implementing DataOps and DevOps on Databricks 14. Index 15. Other Books You May Enjoy

Deploying Delta Live Tables pipelines with Databricks Asset Bundles

Databricks Asset Bundles is a new feature that allows you to deploy your data, analytics, and machine learning projects as a collection of source files. You can use a YAML file to specify the resources and settings for your project, such as jobs, pipelines, endpoints, experiments, and models. This way, you can easily manage your code and infrastructure in a consistent and automated way.

The following are some of the benefits of using Databricks Asset Bundles:

  • You can use best practice tools and processes to work with source code, such as source control, code review, testing, and CI/CD
  • You can streamline your local development with IDEs and run your resources before deploying them to production
  • You can configure your deployments across multiple workspaces, regions, and clouds

In this recipe, you will learn how to package your pipeline as a Databricks Access Bundle and deploy it to a production...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime