Ankit Jain [Jain - Mastering Apache Storm

BIRMINGHAM - MUMBAI

Copyright 2017 Packt Publishing

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First published: August 2017

Production reference: 1140817

ISBN 978-1-78712-563-6

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Ankit Jain holds a bachelor's degree in computer science and engineering. He has 6 years, experience in designing and architecting solutions for the big data domain and has been involved with several complex engagements. His technical strengths include Hadoop, Storm, S4, HBase, Hive, Sqoop, Flume, Elasticsearch, machine learning, Kafka, Spring, Java, and J2EE.

He also shares his thoughts on his personal blog. You can follow him on Twitter at @mynameisanky. He spends most of his time reading books and playing with different technologies. When not at work, he spends time with his family and friends watching movies and playing games.

Doug Ortiz is a senior big data artechitect at ByteCubed who has been architecting, developing and integrating enterprise solutions throughout his whole career. Organizations that leverage high skillset have been able to rediscover and reuse their underutilized data via existing and emerging technologies such as: Microsoft BI Stack, Hadoop, NoSQL Databases, SharePoint, Hadoop, related toolsets and technologies.

He is the founder of Illustris, LLC and can be reached at dougortiz@illustris.org.

Interesting aspects of his profession:

• He has experience integrating multiple platforms and products
• He has big data, data science certifications, R and Python certifications
• He helps organizations gain a deeper understanding of, and value, their current investments in data and existing resources, turning them into useful sources of information
• He has improved, salvaged, and architected projects by utilizing unique and innovative techniques

His hobbies are yoga and scuba diving.

Oleg Okun is a machine learning expert and the author/editor of four books, numerous journal articles, and conference papers. His career spans more than a quarter of a century. He was employed in both academia and industry in his mother country, Belarus, and abroad (Finland, Sweden, and Germany). His work experience includes document image analysis, fingerprint biometrics, bioinformatics, online/offline marketing analytics, credit scoring analytics, and text analytics.

He is interested in all aspects of distributed machine learning and the Internet of Things. Oleg currently lives and works in Hamburg, Germany.

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Real-time data processing in no longer a luxury exercised by a few big companies but has become a necessity for businesses that want to compete, and Apache Storm is one of the de facto standards for developing real-time processing pipelines. The key features of Storm are that it is horizontally scalable, is fault tolerant, and provides guaranteed message processing. Storm can solve various types of analytic problem: machine learning, log processing, graph analysis, and so on.

Mastering Storm will serve both as a getting started guide to inexperienced developers and as a reference for implementing advanced use cases with Storm for experienced developers. In the first two chapters, you will learn the basics of a Storm topology and various components of a Storm cluster. In the later chapters, you will learn how to build a Storm application that can interact with various other big data technologies and how to create transactional topologies. Finally, the last two chapters cover case studies for log processing and machine learning. We are also going to cover how we can use the Storm scheduler to assign delicate work to delicate machines.