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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

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781837633357
Length 438 pages
Edition 1st Edition
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Author (1):
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Pulkit Chadha Pulkit Chadha
Author Profile Icon Pulkit Chadha
Pulkit Chadha
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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...

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