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Data Ingestion with Python Cookbook

You're reading from   Data Ingestion with Python Cookbook A practical guide to ingesting, monitoring, and identifying errors in the data ingestion process

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Product type Paperback
Published in May 2023
Publisher Packt
ISBN-13 9781837632602
Length 414 pages
Edition 1st Edition
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Author (1):
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Gláucia Esppenchutz Gláucia Esppenchutz
Author Profile Icon Gláucia Esppenchutz
Gláucia Esppenchutz
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Fundamentals of Data Ingestion
2. Chapter 1: Introduction to Data Ingestion FREE CHAPTER 3. Chapter 2: Principals of Data Access – Accessing Your Data 4. Chapter 3: Data Discovery – Understanding Our Data before Ingesting It 5. Chapter 4: Reading CSV and JSON Files and Solving Problems 6. Chapter 5: Ingesting Data from Structured and Unstructured Databases 7. Chapter 6: Using PySpark with Defined and Non-Defined Schemas 8. Chapter 7: Ingesting Analytical Data 9. Part 2: Structuring the Ingestion Pipeline
10. Chapter 8: Designing Monitored Data Workflows 11. Chapter 9: Putting Everything Together with Airflow 12. Chapter 10: Logging and Monitoring Your Data Ingest in Airflow 13. Chapter 11: Automating Your Data Ingestion Pipelines 14. Chapter 12: Using Data Observability for Debugging, Error Handling, and Preventing Downtime 15. Index 16. Other Books You May Enjoy

Configuring Airflow

Apache Airflow has many capabilities and a quick setup, which helps us start designing our workflows as code. Some additional configurations might be required as we progress with the workflows and into data processing. Gladly, Airflow has a dedicated file for inserting other arrangements without changing anything within its core.

In this recipe, we will learn more about the airflow.conf file, how to use it, and other valuable configurations required to execute the other recipes in this chapter. We will also cover where to find this file and how other environment variables work with this tool. Understanding these concepts in practice helps us to identify potential improvements or solve problems.

Getting ready

Before moving on to the code, ensure your Airflow runs correctly. You can do that by checking the Airflow UI at this link: http://localhost:8080.

If you are using a Docker container (as I am) to host your Airflow application, you can check its status...

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