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Data Ingestion with Python Cookbook

Data Ingestion with Python Cookbook

By : Gláucia Esppenchutz
4.5 (4)
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Data Ingestion with Python Cookbook

Data Ingestion with Python Cookbook

4.5 (4)
By: Gláucia Esppenchutz

Overview of this book

Data Ingestion with Python Cookbook offers a practical approach to designing and implementing data ingestion pipelines. It presents real-world examples with the most widely recognized open source tools on the market to answer commonly asked questions and overcome challenges. You’ll be introduced to designing and working with or without data schemas, as well as creating monitored pipelines with Airflow and data observability principles, all while following industry best practices. The book also addresses challenges associated with reading different data sources and data formats. As you progress through the book, you’ll gain a broader understanding of error logging best practices, troubleshooting techniques, data orchestration, monitoring, and storing logs for further consultation. By the end of the book, you’ll have a fully automated set that enables you to start ingesting and monitoring your data pipeline effortlessly, facilitating seamless integration with subsequent stages of the ETL process.
Table of Contents (17 chapters)
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1
Part 1: Fundamentals of Data Ingestion
9
Part 2: Structuring the Ingestion Pipeline

Ingesting data from MongoDB using PySpark

Even though it seems impractical to create and ingest the data ourselves, this exercise can be applied to real-life projects. People who work with data are often involved in the architectural process of defining the type of database, helping other engineers to insert data from applications into a database server, and later ingesting only the relevant information for dashboards or other analytical tools.

So far, we have created and evaluated our server and then created collections inside our MongoDB instance. With all this preparation, we can now ingest our data using PySpark.

Getting ready

This recipe requires the execution of the Creating our NoSQL table in MongoDB recipe due to data insertion. However, you can create and insert other documents into the MongoDB database and use them here. If you do this, ensure you set the suitable configurations to make it run properly.

Also, as in the Creating our NoSQL table in MongoDB recipe...

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