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Building Big Data Pipelines with Apache Beam

You're reading from Building Big Data Pipelines with Apache Beam

Product type Book

Published in Jan 2022

Publisher Packt

ISBN-13 9781800564930

Pages 342 pages

Edition 1st Edition

Languages

Concepts

Data Processing

Author (1):

Jan Lukavský

Table of Contents (13) Chapters

Preface

Section 1 Apache Beam: Essentials

Chapter 1: Introduction to Data Processing with Apache Beam

Chapter 2: Implementing, Testing, and Deploying Basic Pipelines

Chapter 3: Implementing Pipelines Using Stateful Processing

Section 2 Apache Beam: Toward Improving Usability

Chapter 4: Structuring Code for Reusability

Chapter 5: Using SQL for Pipeline Implementation

Chapter 6: Using Your Preferred Language with Portability

Section 3 Apache Beam: Advanced Concepts

Chapter 7: Extending Apache Beam's I/O Connectors

Chapter 8: Understanding How Runners Execute Pipelines

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To get the most out of this book

This book builds on at least a basic knowledge of the Java and Python programming languages. It also requires the ability to run Bash and Docker (minikube). All other technologies are included.

Installation instructions are provided in the book.

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book's GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

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Authors (1)

Jan Lukavský

Jan Lukavský is a freelance big data architect and engineer who is also a committer of Apache Beam. He is a certified Apache Hadoop professional. He is working on open source big data systems combining batch and streaming data pipelines in a unified model, enabling the rise of real-time, data-driven applications.

See other products by Jan Lukavský

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