Book Image

Data Ingestion with Python Cookbook

By : Gláucia Esppenchutz
Book Image

Data Ingestion with Python Cookbook

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)
1
Part 1: Fundamentals of Data Ingestion
9
Part 2: Structuring the Ingestion Pipeline

Creating parallel ingest tasks

When working with data, we hardly ever just perform one ingestion at a time, and a real-world project involves many ingestions happening simultaneously, often in parallel. We know scheduling two or more DAGs to run alongside each other is possible, but what about tasks inside one DAG?

This recipe will illustrate how to create parallel task execution in Airflow.

Getting ready

Please refer to the Getting ready section of the Configuring Airflow recipe for this recipe since we will handle it with the same technology.

To avoid redundancy in this exercise, we won’t explicitly include the imports and main DAG configuration. Instead, the focus is on organizing the operator’s workflow. You can use the same logic to create your DAG structure as in the Creating DAGs recipe.

For the complete Python file used here, go to the GitHub page here: https://github.com/PacktPublishing/Data-Ingestion-with-Python-Cookbook/tree/main/Chapter_9/creating_parallel_ingest_tasks...