Data Pipelines with Apache Airflow

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  • Engels
  • Paperback
  • 9781617296901
  • 07 juni 2021
  • 425 pagina's
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Samenvatting

Pipelines can be challenging to manage, especially when your data has to flow through a collection of application components, servers, and cloud services. Airflow lets you schedule, restart, and backfill pipelines, and its easy-to-use UI and workflows with Python scripting has users praising its incredible flexibility. Data Pipelines with Apache Airflow takes you through best practices for creating pipelines for multiple tasks, including data lakes, cloud deployments, and data science.

Data Pipelines with Apache Airflow teaches you the ins-and-outs of the Directed Acyclic Graphs (DAGs) that power Airflow, and how to write your own DAGs to meet the needs of your projects. With complete coverage of both foundational and lesser-known features, when you’re done you’ll be set to start using Airflow for seamless data pipeline development and management.

Key Features

Framework foundation and best practices

Airflow's execution and dependency system

Testing Airflow DAGs

Running Airflow in production

For data-savvy developers, DevOps and data engineers, and system

administrators with intermediate Python skills.

About the technology

Data pipelines are used to extract, transform and load data to and from multiple sources, routing it wherever it’s needed -- whether that’s visualisation tools, business intelligence dashboards, or machine learning models. Airflow streamlines the whole process, giving you one tool for programmatically developing and monitoring batch data pipelines, and integrating all the pieces you use in your data stack.

Bas Harenslak and Julian de Ruiter are data engineers with extensive experience using Airflow to develop pipelines for major companies including Heineken, Unilever, and Booking.com. Bas is a committer, and both Bas and Julian are active contributors to Apache Airflow.



Pipelines can be challenging to manage, especially when your data has to flow through a collection of application components, servers, and cloud services. Airflow lets you schedule, restart, and backfill pipelines, and its easy-to-use UI and workflows with Python scripting has users praising its incredible flexibility. Data Pipelines with Apache Airflow takes you through best practices for creating pipelines for multiple tasks, including data lakes, cloud deployments, and data science.

Data Pipelines with Apache Airflow teaches you the ins-and-outs of the Directed Acyclic Graphs (DAGs) that power Airflow, and how to write your own DAGs to meet the needs of your projects. With complete coverage of both foundational and lesser-known features, when you’re done you’ll be set to start using Airflow for seamless data pipeline development and management.

Key Features

Framework foundation and best practices

Airflow's execution and dependency system

Testing Airflow DAGs

Running Airflow in production

For data-savvy developers, DevOps and data engineers, and system

administrators with intermediate Python skills.

About the technology

Data pipelines are used to extract, transform and load data to and from multiple sources, routing it wherever it’s needed -- whether that’s visualisation tools, business intelligence dashboards, or machine learning models. Airflow streamlines the whole process, giving you one tool for programmatically developing and monitoring batch data pipelines, and integrating all the pieces you use in your data stack.

Bas Harenslak and Julian de Ruiter are data engineers with extensive experience using Airflow to develop pipelines for major companies including Heineken, Unilever, and Booking.com. Bas is a committer, and both Bas and Julian are active contributors to Apache Airflow.

Productspecificaties

Inhoud

Taal
en
Bindwijze
Paperback
Oorspronkelijke releasedatum
07 juni 2021
Aantal pagina's
425
Illustraties
Nee

Betrokkenen

Hoofdauteur
Bas Harenslak
Tweede Auteur
Julian Ruiter
Hoofduitgeverij
Manning Publications

Overige kenmerken

Extra groot lettertype
Nee
Product breedte
186 mm
Product hoogte
28 mm
Product lengte
234 mm
Studieboek
Ja
Verpakking breedte
185 mm
Verpakking hoogte
26 mm
Verpakking lengte
233 mm
Verpakkingsgewicht
933 g

EAN

EAN
9781617296901

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