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Data Engineering with Python

You're reading from   Data Engineering with Python Work with massive datasets to design data models and automate data pipelines using Python

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Product type Paperback
Published in Oct 2020
Publisher Packt
ISBN-13 9781839214189
Length 356 pages
Edition 1st Edition
Languages
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Author (1):
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Paul Crickard Paul Crickard
Author Profile Icon Paul Crickard
Paul Crickard
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Toc

Table of Contents (21) Chapters Close

Preface 1. Section 1: Building Data Pipelines – Extract Transform, and Load
2. Chapter 1: What is Data Engineering? FREE CHAPTER 3. Chapter 2: Building Our Data Engineering Infrastructure 4. Chapter 3: Reading and Writing Files 5. Chapter 4: Working with Databases 6. Chapter 5: Cleaning, Transforming, and Enriching Data 7. Chapter 6: Building a 311 Data Pipeline 8. Section 2:Deploying Data Pipelines in Production
9. Chapter 7: Features of a Production Pipeline 10. Chapter 8: Version Control with the NiFi Registry 11. Chapter 9: Monitoring Data Pipelines 12. Chapter 10: Deploying Data Pipelines 13. Chapter 11: Building a Production Data Pipeline 14. Section 3:Beyond Batch – Building Real-Time Data Pipelines
15. Chapter 12: Building a Kafka Cluster 16. Chapter 13: Streaming Data with Apache Kafka 17. Chapter 14: Data Processing with Apache Spark 18. Chapter 15: Real-Time Edge Data with MiNiFi, Kafka, and Spark 19. Other Books You May Enjoy Appendix

Installing and configuring Apache Airflow

Apache Airflow performs the same role as Apache NiFi; however, it allows you to create your data flows using pure Python. If you are a strong Python developer, this is probably an ideal tool for you. It is currently one of the most popular open source data pipeline tools. What it lacks in a polished GUI – compared to NiFi – it more than makes up for in the power and freedom to create tasks.

Installing Apache Airflow can be accomplished using pip. But, before installing Apache Airflow, you can change the location of the Airflow install by exporting AIRFLOW_HOME. If you want Airflow to install to opt/airflow, export the AIRLFOW_HOME variable, as shown:

export AIRFLOW_HOME=/opt/airflow

The default location for Airflow is ~/airflow, and for this book, this is the location I will use. The next consideration before installing Airflow is to determine which sub-packages you want to install. If you do not specify any, Airflow...

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