Storm Blueprints: Patterns for Distributed Real-time Computation

Nonfiction, Computers, Advanced Computing, Parallel Processing, Database Management, Programming
Cover of the book Storm Blueprints: Patterns for Distributed Real-time Computation by P. Taylor Goetz, Brian O'Neill, Packt Publishing
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Author: P. Taylor Goetz, Brian O'Neill ISBN: 9781782168300
Publisher: Packt Publishing Publication: March 26, 2014
Imprint: Packt Publishing Language: English
Author: P. Taylor Goetz, Brian O'Neill
ISBN: 9781782168300
Publisher: Packt Publishing
Publication: March 26, 2014
Imprint: Packt Publishing
Language: English
A blueprints book with 10 different projects built in 10 different chapters which demonstrate the various use cases of storm for both beginner and intermediate users, grounded in real-world example applications. Although the book focuses primarily on Java development with Storm, the patterns are more broadly applicable and the tips, techniques, and approaches described in the book apply to architects, developers, and operations. Additionally, the book should provoke and inspire applications of distributed computing to other industries and domains. Hadoop enthusiasts will also find this book a good introduction to Storm, providing a potential migration path from batch processing to the world of real-time analytics.
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
A blueprints book with 10 different projects built in 10 different chapters which demonstrate the various use cases of storm for both beginner and intermediate users, grounded in real-world example applications. Although the book focuses primarily on Java development with Storm, the patterns are more broadly applicable and the tips, techniques, and approaches described in the book apply to architects, developers, and operations. Additionally, the book should provoke and inspire applications of distributed computing to other industries and domains. Hadoop enthusiasts will also find this book a good introduction to Storm, providing a potential migration path from batch processing to the world of real-time analytics.

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