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Data Ingestion with Python Cookbook

You're reading from Data Ingestion with Python Cookbook

Product type Book

Published in May 2023

Publisher Packt

ISBN-13 9781837632602

Pages 414 pages

Edition 1st Edition

Languages

Concepts

Data Engineering

Author (1):

Gláucia Esppenchutz

Table of Contents (17) Chapters

Preface

1. Part 1: Fundamentals of Data Ingestion

2. Chapter 1: Introduction to Data Ingestion

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

Why subscribe?

16. Other Books You May Enjoy

Putting Everything Together with Airﬂow

So far, we have covered the different aspects and steps of data ingestion. We have seen how to configure and ingest structured and unstructured data, what analytical data is, and how to improve logs for more insightful monitoring and error handling. Now is the time to group all this information to create something similar to a real-world project.

From now on, in the following chapters, we will use Apache Airflow, an open source platform that allows us to create, schedule, and monitor workflows. Let’s start our journey by configuring and understanding the fundamental concepts of Apache Airflow and how powerful this tool is.

In this chapter, you will learn about the following topics:

Configuring Airflow
Creating DAGs
Creating custom operators
Conﬁguring sensors
Creating connectors in Airﬂow
Creating parallel ingest tasks
Deﬁning ingest-dependent DAGs

By the end of this...

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Authors (1)

Gláucia Esppenchutz

Gláucia Esppenchutz is a data engineer with expertise in managing data pipelines and vast amounts of data using cloud and on-premises technologies. She worked in companies such as Globo, BMW Group, and Cloudera. Currently, she works at AiFi, specializing in the field of data operations for autonomous systems. She comes from the biomedical field and shifted her career ten years ago to chase the dream of working closely with technology and data. She is in constant contact with the open source community, mentoring people and helping to manage projects, and has collaborated with the Apache, PyLadies group, FreeCodeCamp, Udacity, and MentorColor communities.

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