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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
Author (1):
Jan Lukavský Jan Lukavský
Profile icon Jan Lukavský
Toc

Table of Contents (13) Chapters close

Preface 1. Section 1 Apache Beam: Essentials
2. Chapter 1: Introduction to Data Processing with Apache Beam 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

Setting up the environment for this book

In this section, we will set up the environment needed for this chapter and the rest of the book. The technologies we will build upon are Docker and minikube.

Minikube is a local version of Kubernetes, which will enable us to easily set up the other technologies we need.

Let's set up everything we need for this chapter now:

  1. The steps to install minikube can be found at https://minikube.sigs.k8s.io/docs/start/.
  2. Next, make sure to install the kubectl tool using the official Kubernetes instructions, which can be found at https://kubernetes.io/docs/tasks/tools/.
  3. After installing minikube, we will start it by executing the following command:
    $ minikube start

    Important note

    minikube accepts as an optional parameter a configurable amount of memory and number of CPUs. The minikube start command takes the optional --cpus and --memory arguments, which can be used to tune these settings. We recommend using all of the CPUs available...

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