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Building Big Data Pipelines with Apache Beam

Building Big Data Pipelines with Apache Beam

By : Jan Lukavský
3.7 (9)
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Building Big Data Pipelines with Apache Beam

Building Big Data Pipelines with Apache Beam

3.7 (9)
By: Jan Lukavský

Overview of this book

Apache Beam is an open source unified programming model for implementing and executing data processing pipelines, including Extract, Transform, and Load (ETL), batch, and stream processing. This book will help you to confidently build data processing pipelines with Apache Beam. You’ll start with an overview of Apache Beam and understand how to use it to implement basic pipelines. You’ll also learn how to test and run the pipelines efficiently. As you progress, you’ll explore how to structure your code for reusability and also use various Domain Specific Languages (DSLs). Later chapters will show you how to use schemas and query your data using (streaming) SQL. Finally, you’ll understand advanced Apache Beam concepts, such as implementing your own I/O connectors. By the end of this book, you’ll have gained a deep understanding of the Apache Beam model and be able to apply it to solve problems.
Table of Contents (13 chapters)
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1
Section 1 Apache Beam: Essentials
5
Section 2 Apache Beam: Toward Improving Usability
9
Section 3 Apache Beam: Advanced Concepts

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.

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