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Books > Computing & IT > Computer communications & networking
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Data Pipelines with Apache Airflow (Paperback)
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Data Pipelines with Apache Airflow (Paperback)
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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.
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