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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

Using Databricks Asset Bundles (DABs)

DABs let you use an infrastructure-as-code (IaC) method to handle your Databricks projects. They enable you to define the infrastructure and resources of your project in a YAML configuration file. By automating your project’s tests, deployments, and configuration management with bundles, you can minimize errors while encouraging software best practices throughout your organization with templated projects.

Here are some advantages of using DABs:

  • You can handle complex projects that require multiple contributors and automation, as well as continuous integration and deployment/delivery (CI/CD).
  • You can work on data, analytics, and machine learning (ML) projects in a team-oriented environment. Bundles can assist you in organizing and managing various source files effectively. This guarantees smooth cooperation and simplified processes.
  • You can solve ML problems faster. Use ML projects to manage ML pipeline resources (such...
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