
Data Pipelines with Apache Airflow
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Narrated by:
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Julie Brierley
About this listen
Data Pipelines with Apache Airflow teaches you how to build and maintain effective data pipelines.
Summary
A successful pipeline moves data efficiently, minimizing pauses and blockages between tasks, and keeping processes along the way operational. Apache Airflow provides a single customizable environment for building and managing data pipelines, eliminating the need for a hodgepodge collection of tools, snowflake code, and homegrown processes. Using real-world scenarios and examples, this book teaches you how to simplify and automate data pipelines, reduce operational overhead, and smoothly integrate all the technologies in your stack.
About the Technology
Data pipelines manage the flow of data from initial collection through consolidation, cleaning, analysis, visualization, and more. Apache Airflow provides a single platform you can use to design, implement, monitor, and maintain your pipelines. It features easy-to-use UI, plug-and-play options, and flexible Python scripting.
About the Book
Data Pipelines with Apache Airflow teaches you how to build and maintain effective data pipelines. You’ll explore the most common usage patterns, including aggregating multiple data sources, connecting to and from data lakes, and cloud deployment. Part reference and part tutorial, this practical guide covers every aspect of the directed acyclic graphs (DAGs) that power Airflow, and how to customize them for your pipeline’s needs.
What's Inside
- Build, test, and deploy Airflow pipelines as DAGs
- Automate moving and transforming data
- Analyze historical datasets using backfilling
- Develop custom components
- Set up Airflow in production environments
About the Audience
For DevOps, data engineers, machine learning engineers, and sysadmins with intermediate Python skills.
About the Authors
Bas Harenslak and Julian de Ruiter are data engineers with extensive experience using Airflow to develop pipelines for major companies. Bas is also an Airflow committer.
PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
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- Unabridged
-
Overall
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Performance
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Story
A web API is an efficient way to communicate with an application or service. However, this convenience opens your systems to new security risks. API Security in Action gives you the skills to build strong, safe APIs you can confidently expose to the world.
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Missing content
- By mslightn on 03-08-23
By: Neil Madden
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Microservices Patterns
- With Examples in Java
- By: Chris Richardson
- Narrated by: Aiden Humphreys, Lou Fernandez
- Length: 18 hrs and 28 mins
- Unabridged
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Overall
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Performance
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Story
Microservices Patterns teaches you how to develop and deploy production-quality microservices-based applications. This invaluable set of design patterns builds on decades of distributed system experience, adding new patterns for writing services and composing them into systems that scale and perform reliably under real-world conditions. More than just a patterns catalog, this practical guide offers experience-driven advice to help you design, implement, test, and deploy your microservices-based application.
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There is lack of pdf with diagrams and images.
- By BoshTls on 10-28-19
By: Chris Richardson
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Deep Learning with Python (Second Edition)
- By: Francois Chollet
- Narrated by: Derek Dysart
- Length: 15 hrs and 1 min
- Unabridged
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Overall
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Performance
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Story
Deep Learning with Python (Second Edition) introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, you’ll build your understanding through intuitive explanations and clear examples. You’ll quickly pick up the skills you need to start developing deep learning applications.
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Audible version is useless - has no PDF
- By Jim on 03-04-22
By: Francois Chollet