Storm Applied: Strategies for real-time event processing

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9781617291890: Storm Applied: Strategies for real-time event processing
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Summary

Storm Applied is a practical guide to using Apache Storm for the real-world tasks associated with processing and analyzing real-time data streams. This immediately useful book starts by building a solid foundation of Storm essentials so that you learn how to think about designing Storm solutions the right way from day one. But it quickly dives into real-world case studies that will bring the novice up to speed with productionizing Storm.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Summary

Storm Applied is a practical guide to using Apache Storm for the real-world tasks associated with processing and analyzing real-time data streams. This immediately useful book starts by building a solid foundation of Storm essentials so that you learn how to think about designing Storm solutions the right way from day one. But it quickly dives into real-world case studies that will bring the novice up to speed with productionizing Storm.

About the Technology

It's hard to make sense out of data when it's coming at you fast. Like Hadoop, Storm processes large amounts of data but it does it reliably and in real time, guaranteeing that every message will be processed. Storm allows you to scale with your data as it grows, making it an excellent platform to solve your big data problems.

About the Book

Storm Applied is an example-driven guide to processing and analyzing real-time data streams. This immediately useful book starts by teaching you how to design Storm solutions the right way. Then, it quickly dives into real-world case studies that show you how to scale a high-throughput stream processor, ensure smooth operation within a production cluster, and more. Along the way, you'll learn to use Trident for stateful stream processing, along with other tools from the Storm ecosystem.

This book moves through the basics quickly. While prior experience with Storm is not assumed, some experience with big data and real-time systems is helpful.

What's Inside

  • Mapping real problems to Storm components
  • Performance tuning and scaling
  • Practical troubleshooting and debugging
  • Exactly-once processing with Trident

About the Authors

Sean Allen, Matthew Jankowski, and Peter Pathirana lead the development team for a high-volume, search-intensive commercial web application at TheLadders.

Table of Contents

  1. Introducing Storm
  2. Core Storm concepts
  3. Topology design
  4. Creating robust topologies
  5. Moving from local to remote topologies
  6. Tuning in Storm
  7. Resource contention
  8. Storm internals
  9. Trident

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About the Author:

Sean T. Allen has worked in software for over 20 years. He works as Principal Architect for TheLadders. He is one of the developers of Redline Smalltalk; an implementation of the Smalltalk programming language that runs on the JVM. You can often follow Sean on Twitter at @SeanTAllen.

Matthew Jankowski has been involved in the development of software systems for over 10 years. Throughout his career, he has participated in a wide variety of projects, with a majority of the focus on the development of RESTful web services. He has spent the last two years integrating Storm into TheLadders and continues to search for new use cases for Storm within the company.

Peter Pathirana is a Lead Software Engineer at TheLadders.com at the vanguard of the Recommendations platform architecture. He has over 10 years of experience in designing comprehensive solutions for hard problems and he enjoys tinkering with Storm, Elastic Search, Solr, and RabbitMQ for starters.

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Book Description Manning Publications, United States, 2015. Paperback. Condition: New. Language: English. Brand new Book. It's a lot harder to make sense out of data when it's coming at full speed. Apache Storm's efficient stream processing capabilities are relied upon by giants like Twitter and Yahoo for swiftly extracting intelligence from their Big Data streams. Fault tolerant guarantees of Storm make it an invaluable and versatile platform in the Big Data landscape. It integrates seamlessly with battle-tested message queuing systems (like Kafka) and NoSQL databases (like Cassandra). Storm is built to run on the JVM but provides straightforward extensions for working with non-JVM languages like Ruby and Python. Storm Applied is a practical guide to using Apache Storm for the real-world tasks associated with processing and analyzing real-time data streams. The book starts by building a solid foundation of the Storm essentials. Then, it quickly dives into real-world case studies that will bring the novice up to speed with productionizing Storm: the knowledge needed to scale a high throughput stream processor and ensure smooth operation within a production cluster. It moves on to teach readers how to use Trident to treat streams as batches for solving a different class of problems, and covers the tools available within the Storm open source community that are crucial for any seasoned Storm developer. RETAIL SELLING POINTS Immediately useful practical guide Applies Storm to real-world use cases Takes Storm from development to a fully tuned and optimized production setup AUDIENCE While prior experience with Storm is not necessary, acquaintance with related Big Data problem solving is helpful. Basic understanding of Java or similar JVM language and concurrency is assumed. DESCRIBE THE TECHNOLOGY Storm is a tool that can be used for processing "big data" in real-time. Think performing real-time analysis of all the tweets going through Twitter. Seller Inventory # AAK9781617291890

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Book Description Manning Publications, United States, 2015. Paperback. Condition: New. Language: English. Brand new Book. It's a lot harder to make sense out of data when it's coming at full speed. Apache Storm's efficient stream processing capabilities are relied upon by giants like Twitter and Yahoo for swiftly extracting intelligence from their Big Data streams. Fault tolerant guarantees of Storm make it an invaluable and versatile platform in the Big Data landscape. It integrates seamlessly with battle-tested message queuing systems (like Kafka) and NoSQL databases (like Cassandra). Storm is built to run on the JVM but provides straightforward extensions for working with non-JVM languages like Ruby and Python. Storm Applied is a practical guide to using Apache Storm for the real-world tasks associated with processing and analyzing real-time data streams. The book starts by building a solid foundation of the Storm essentials. Then, it quickly dives into real-world case studies that will bring the novice up to speed with productionizing Storm: the knowledge needed to scale a high throughput stream processor and ensure smooth operation within a production cluster. It moves on to teach readers how to use Trident to treat streams as batches for solving a different class of problems, and covers the tools available within the Storm open source community that are crucial for any seasoned Storm developer. RETAIL SELLING POINTS Immediately useful practical guide Applies Storm to real-world use cases Takes Storm from development to a fully tuned and optimized production setup AUDIENCE While prior experience with Storm is not necessary, acquaintance with related Big Data problem solving is helpful. Basic understanding of Java or similar JVM language and concurrency is assumed. DESCRIBE THE TECHNOLOGY Storm is a tool that can be used for processing "big data" in real-time. Think performing real-time analysis of all the tweets going through Twitter. Seller Inventory # AAK9781617291890

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