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

Product type Paperback

Published in May 2023

Publisher Packt

ISBN-13 9781837632602

Length 414 pages

Edition 1st Edition

Languages

Python

Tools

Apache Airflow

Concepts

Data Engineering

Author (1):

Gláucia Esppenchutz

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Table of Contents (17) Chapters

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

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Ingesting data from a JDBC database using SQL

With the connection tested and SparkSession configured, the next step is to ingest the data from PostgreSQL, filter it, and save it in an analytical format called a Parquet file. Don’t worry about how Parquet files work for now; we will cover it in the following chapters.

This recipe aims to use the connection we created with our JDBC database and ingest the data from the world_population table.

Getting ready

This recipe will use the same dataset and code as the Configuring a JDBC connection recipe to connect to the PostgreSQL database. Ensure your Docker container is running or your PostgreSQL server is up.

This recipe continues from the content presented in Configuring a JDBC connection. We will now learn how to ingest the data inside the Postgres database.