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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

Table of Contents (13) Chapters

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

Technical requirements

The toolset we are using will only change slightly in this chapter. Besides the classical Docker and minikube, we will need to install Python3. Let's take a look:

  1. Python can be installed by following the instructions at https://realpython.com/installing-python/.
  2. We will also need to install the apache_beam package using pip:
    $ python3 =m pip install apache_beam

    If something goes wrong, make sure you have the latest version of pip by using the following command:

    $ python3 =m pip install --upgrade pip
  3. The highest fully Apache Beam-supported version of Python is 3.7. If you have a higher version installed and do not want to downgrade, you can use the pack-beam pod in minikube, which has the correct Python version bundled with it. All the examples in this chapter can be run using the following command:
    $ kubectl exec -t packt-beam -- \
        /usr/local/bin/<name_of_script.py>

You will also need to have a basic understanding...

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