Storm Blueprints: Patterns for Distributed Real-time Computation
By P. Taylor Goetz, Brian O'Neill
Publisher: Packt Publishing
Final Release Date: March 2014
Pages: 336

In Detail

Storm is the most popular framework for real-time stream processing. Storm provides the fundamental primitives and guarantees required for fault-tolerant distributed computing in high-volume, mission critical applications. It is both an integration technology as well as a data flow and control mechanism, making it the core of many big data platforms. Storm is essential if you want to deploy, operate, and develop data processing flows capable of processing billions of transactions.

"Storm: Distributed Real-time Computation Blueprints" covers a broad range of distributed computing topics, including not only design and integration patterns, but also domains and applications to which the technology is immediately useful and commonly applied. This book introduces you to Storm using real-world examples, beginning with simple Storm topologies. The examples increase in complexity, introducing advanced Storm concepts as well as more sophisticated approaches to deployment and operational concerns.

This book covers the domains of real-time log processing, sensor data analysis, collective and artificial intelligence, financial market analysis, Natural Language Processing (NLP), graph analysis, polyglot persistence and online advertising. While exploring distributed computing applications in each of those domains, the book covers advanced Storm topics such as Trident and Distributed State, as well as integration patterns for Druid and Titan. Simultaneously, the book also describes the deployment of Storm to YARN and the Amazon infrastructure, as well as other key operational concerns such as centralized logging.

By the end of the book, you will have gained an understanding of the fundamentals of Storm and Trident and be able to identify and apply those fundamentals to any suitable problem.

Approach

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.

Who this book is for

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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4.0

Very, very detailed

By Nitin

from India

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Pros

  • Concise
  • Easy to understand
  • Helpful examples

Cons

    Best Uses

      Comments about oreilly Storm Blueprints: Patterns for Distributed Real-time Computation:

      This is a very good book for learning how to use Storm along with various tools, such as Trident, Hadoop and Titan. While there is an introduction to Storm, most of the book covers various scenarios in which Storm can be used.
      The book contains 10 chapters. The first chapter provides a short but thorough introduction to Storm. Configuring Storm for a production envoironment is covered in Chapters 2 and 10. The rest of the book contains several scenarios, including real-time trend analysis using Kafka, graph analytics,financial analytics, NLP and DRPC.
      The quality of this book is excellent. Each chapter covers specific topics in meticuous detail. Even the installation of the tools, which is left as an afterthought in most books, is covered in detail. Most of the code of all the usecases is also explained in detail in book. The author has also provided diagrams for most usecases - making the usecase easy to understand.
      The only problem with this book is the Kindle edition - the font is barely legible even at the maximum font size on my Kindle touch. I was able to get a better copy by converting the EPUB to Kindle using Calibre.

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