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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
Author (1):
Gláucia Esppenchutz Gláucia Esppenchutz
Profile icon Gláucia Esppenchutz
Toc

Table of Contents (17) Chapters close

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 16. Other Books You May Enjoy

Scheduling daily ingestions

Data constantly changes in our dynamic world, with new information being added every day and even every second. Therefore, it is crucial to regularly update our data lake to reflect the latest scenarios and information.

Managing multiple projects or pipelines concurrently and manually triggering them while integrating new data from various sources can be daunting. To alleviate this issue, we can rely on schedulers, and Airflow provides a straightforward solution for this purpose.

In this recipe, we will create a simple Directed Acyclic Graph (DAG) in Airflow and explore how to use its parameters to schedule a pipeline to run daily.

Getting ready

Please refer to the Technical requirements section for this recipe since we will handle it with the same technology mentioned here.

In this exercise, we will create a simple DAG. The structure of your Airflow folder should look like the following:

Figure 11.3 – daily_ingestion_dag DAG folder structure

Figure 11.3 – daily_ingestion_dag...

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