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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

Chapter 4: Working with Databases

In the previous chapter, you learned how to read and write text files. Reading log files or other text files from a data lake and moving them into a database or data warehouse is a common task for data engineers. In this chapter, you will use the skills you gained working with text files and learn how to move that data into a database. This chapter will also teach you how to extract data from relational and NoSQL databases. By the end of this chapter, you will have the skills needed to work with databases using Python, NiFi, and Airflow. It is more than likely that most of your data pipelines will end with a database and very likely that they will start with one as well. With these skills, you will be able to build data pipelines that can extract and load, as well as start and finish, with both relational and NoSQL databases.

In this chapter, we're going to cover the following main topics:

  • Inserting and extracting relational data in...
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