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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

Setting up StatsD for monitoring

As introduced in Chapter 10, StatsD is an open source daemon that gathers and aggregates metrics about application behaviors. Due to its flexibility and lightweight, StatsD is used on several monitoring and observability tools, such as Grafana, Prometheus, and ElasticSearch, to visualize and analyze the collected metrics.

In this recipe, we will configure StatsD using a Docker image as the first step in building a monitoring pipeline. Here, StatsD will collect and aggregate Airflow information and make it available to Prometheus, our monitoring database, in the Setting up Prometheus for storing metrics recipe.

Getting ready

Refer to the Technical requirements section for this recipe since we will handle it with the same technology.

How to do it…

Here are the steps to perform this recipe:

  1. Let’s start by defining our Docker configurations for StatsD. These lines will be added under the services section inside the docker...
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