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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : Dream Books Co., Denver, CO, Etats-Unis
Etat : acceptable. This copy has clearly been enjoyedâ"expect noticeable shelf wear and some minor creases to the cover. Binding is strong, and all pages are legible. May contain previous library markings or stamps. N° de réf. du vendeur DBV.1617296902.A
Quantité disponible : 1 disponible(s)
Vendeur : HPB-Red, Dallas, TX, Etats-Unis
paperback. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! N° de réf. du vendeur S_480469416
Quantité disponible : 1 disponible(s)
Vendeur : BooksRun, Philadelphia, PA, Etats-Unis
Paperback. Etat : Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. N° de réf. du vendeur 1617296902-8-1
Quantité disponible : 2 disponible(s)
Vendeur : WorldofBooks, Goring-By-Sea, WS, Royaume-Uni
Paperback. Etat : Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged. N° de réf. du vendeur GOR012040616
Quantité disponible : 3 disponible(s)
Vendeur : Half Price Books Inc., Dallas, TX, Etats-Unis
paperback. Etat : Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority! N° de réf. du vendeur S_488156561
Quantité disponible : 1 disponible(s)
Vendeur : WeBuyBooks, Rossendale, LANCS, Royaume-Uni
paperback. Etat : Very Good. Most items will be dispatched the same or the next working day. A copy that has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged. N° de réf. du vendeur rev9576011072
Quantité disponible : 1 disponible(s)
Vendeur : medimops, Berlin, Allemagne
Etat : very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages. N° de réf. du vendeur M01617296902-V
Quantité disponible : 2 disponible(s)
Vendeur : Books Puddle, Woodside, NY, Etats-Unis
Etat : New. pp. 325. N° de réf. du vendeur 26382195570
Quantité disponible : 1 disponible(s)
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. pp. 325. N° de réf. du vendeur 380659885
Quantité disponible : 1 disponible(s)
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Etat : New. pp. 325. N° de réf. du vendeur 18382195576
Quantité disponible : 1 disponible(s)