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Building Big Data Pipelines with Apache Beam

You're reading from   Building Big Data Pipelines with Apache Beam Use a single programming model for both batch and stream data processing

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Product type Paperback
Published in Jan 2022
Publisher Packt
ISBN-13 9781800564930
Length 342 pages
Edition 1st Edition
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Author (1):
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Jan Lukavský Jan Lukavský
Author Profile Icon Jan Lukavský
Jan Lukavský
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Table of Contents (13) Chapters Close

Preface 1. Section 1 Apache Beam: Essentials
2. Chapter 1: Introduction to Data Processing with Apache Beam FREE CHAPTER 3. Chapter 2: Implementing, Testing, and Deploying Basic Pipelines 4. Chapter 3: Implementing Pipelines Using Stateful Processing 5. Section 2 Apache Beam: Toward Improving Usability
6. Chapter 4: Structuring Code for Reusability 7. Chapter 5: Using SQL for Pipeline Implementation 8. Chapter 6: Using Your Preferred Language with Portability 9. Section 3 Apache Beam: Advanced Concepts
10. Chapter 7: Extending Apache Beam's I/O Connectors 11. Chapter 8: Understanding How Runners Execute Pipelines 12. Other Books You May Enjoy

Technical requirements

In this chapter, we will introduce some elementary pipelines written using Beam's Java Software Development Kit (SDK).

We will use the code located in the GitHub repository for this book: https://github.com/PacktPublishing/Building-Big-Data-Pipelines-with-Apache-Beam.

We will also need the following tools to be installed:

  • Java Development Kit (JDK) 11 (possibly OpenJDK 11), with JAVA_HOME set appropriately
  • Git
  • Bash

    Important note

    Although it is possible to run many tools in this book using the Windows shell, we will focus on using Bash scripting only. We hope Windows users will be able to run Bash using virtualization or Windows Subsystem for Linux (or any similar technology).

First of all, we need to clone the repository:

  1. To do this, we create a suitable directory, and then we run the following command:
    $ git clone https://github.com/PacktPublishing/Building-Big-Data-Pipelines-with-Apache-Beam.git
  2. This will result in a directory, Building-Big-Data-Pipelines-with-Apache-Beam, being created in the working directory. We then run the following command in this newly created directory:
    $ ./mvnw clean install 

Throughout this book, the $ character will denote a Bash shell. Therefore, $ ./mvnw clean install would mean to run the ./mvnw command in the top-level directory of the git clone (that is, Building-Big-Data-Pipelines-with-Apache-Beam). By using chapter1$ ../mvnw clean install, we mean to run the specified command in the subdirectory called chapter1.

You have been reading a chapter from
Building Big Data Pipelines with Apache Beam
Published in: Jan 2022
Publisher: Packt
ISBN-13: 9781800564930
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