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Data Pipelines with Apache Airflow. Second Edition. Orchestration for data and AI. 2nd Edition (2026) [PDF]

Julian de Ruiter & Ismael Cabral & Kris Geusebroek & Daniel van der Ende & Bas Harenslak
Без рейтинга
Серия Программирование (книга #347)
Издатель Manning Publications Co.
Дата публикации 23.12.2025 21:58
Добавлена в библиотеку 17.05.2026 16:19
Последнее изменение 30.11.-0001 00:00
Теги
Форматы PDF (65837 KB)
Путь в библиотеке Julian de Ruiter/Data Pipelines with Apache Airflow (12730)
UUID 9f6f5bca-148b-4c3b-8e11-d535318ca6eb

Аннотация

Julian de Ruiter, Ismael Cabral, Kris Geusebroek и др. | Data Pipelines with Apache Airflow. Second Edition. Orchestration for data and AI. 2nd Edition (2026) [PDF]

picАвтор: Julian de Ruiter, Ismael Cabral, Kris Geusebroek и др.

Издательство: Manning Publications

ISBN: 978-1633436374

Жанр: Database Storage & Design, Data Warehousing, Cloud Computing

Язык: Английский

 

Формат: PDF

Качество: Изначально электронное (ebook)

Иллюстрации: Цветные и черно-белые

 

Описание:

Data Pipelines with Apache Airflow has empowered thousands of data engineers to build more successful data platforms. This new second edition has been fully revised for Airflow 3 with coverage of all the latest features of Apache Airflow, including the Taskflow API, deferrable operators, and Large Language Model integration. Filled with real-world scenarios and examples, you'll be carefully guided from Airflow novice to expert.

 

Using real-world scenarios and examples, this book teaches you how to simplify and automate data pipelines, reduce operational overhead, and smoothly integrate all the technologies in your stack. Part reference and part tutorial, each technique is illustrated with engaging hands-on examples, from training machine learning models for generative AI to optimizing delivery routes.

 

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Дополнительная информация:

In Data Pipelines with Apache Airflow, Second Edition you'll learn how to:

 

• Master the core concepts of Airflow architecture and workflow design

• Schedule data pipelines using the Dataset API and time tables, including complex irregular schedules

• Develop custom Airflow components for your specific needs

• Implement comprehensive testing strategies for your pipelines

• Apply industry best practices for building and maintaining Airflow workflows

• Deploy and operate Airflow in production environments

• Orchestrate workflows in container-native environments

• Build and deploy Machine Learning and Generative AI models using Airflow

 

About the Technology

 

Apache Airflow provides a unified platform for collecting, consolidating, cleaning, and analyzing data. With its easy-to-use UI, powerful scheduling and monitoring features, plug-and-play options, and flexible Python scripting, Airflow makes it easy to implement secure, consistent pipelines for any data or AI task.

 

About the book

 

Data Pipelines with Apache Airflow, Second Edition teaches you how to build, monitor, and maintain effective data workflows. This new edition adds comprehensive coverage of Airflow 3 features, such as event-driven scheduling, dynamic task mapping, DAG versioning, and Airflow’s entirely new UI. The numerous examples address common use cases like data ingestion and transformation and connecting to multiple data sources, along with AI-aware techniques such as building RAG systems.

 

What's inside