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Apache Airflow Best Practices

You're reading from   Apache Airflow Best Practices A practical guide to orchestrating data workflow with Apache Airflow

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Product type Paperback
Published in Oct 2024
Publisher Packt
ISBN-13 9781805123750
Length 188 pages
Edition 1st Edition
Languages
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Authors (3):
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Dylan Storey Dylan Storey
Author Profile Icon Dylan Storey
Dylan Storey
Dylan Intorf Dylan Intorf
Author Profile Icon Dylan Intorf
Dylan Intorf
Kendrick van Doorn Kendrick van Doorn
Author Profile Icon Kendrick van Doorn
Kendrick van Doorn
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Toc

Table of Contents (20) Chapters Close

Preface 1. Part 1: Apache Airflow: History, What, and Why
2. Chapter 1: Getting Started with Airflow 2.0 FREE CHAPTER 3. Chapter 2: Core Airflow Concepts 4. Part 2: Airflow Basics
5. Chapter 3: Components of Airflow 6. Chapter 4: Basics of Airflow and DAG Authoring 7. Part 3: Common Use Cases
8. Chapter 5: Connecting to External Sources 9. Chapter 6: Extending Functionality with UI Plugins 10. Chapter 7: Writing and Distributing Custom Providers 11. Chapter 8: Orchestrating a Machine Learning Workflow 12. Chapter 9: Using Airflow as a Driving Service 13. Part 4: Scale with Your Deployed Instance
14. Chapter 10: Airflow Ops: Development and Deployment 15. Chapter 11: Airflow Ops Best Practices: Observation and Monitoring 16. Chapter 12: Multi-Tenancy in Airflow 17. Chapter 13: Migrating Airflow 18. Index 19. Other Books You May Enjoy

Summary

In this chapter, we introduced the basics of DAGs, tasks, operators, Xcoms, task groups, triggers, and the airflowctl CLI. We covered interacting with the Airflow console and reviewing the basics of DAG authoring, with a typical example included in the initial locally run version of Airflow.

Each of these topics is critical to understand and master before attempting to create large ETL pipelines or other ML/AI use cases with Airflow. It is recommended that you spend time reviewing the basic DAG example and practice the different triggers or operators identified in this chapter, ensuring that you feel comfortable building larger-scale systems as you grow as an engineer.

In the next few chapters, we will expand on this initial basic DAG example with a real ETL pipeline and perform our first data extraction.

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