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    Mastering Apache Storm

    Posted By: AlenMiler
    Mastering Apache Storm

    Mastering Apache Storm by Ankit Jain
    English | 16 Aug. 2017 | ASIN: B074M54PXB | ISBN: 1787125637 | 284 Pages | AZW3 | 3.31 MB

    Key Features

    Exploit the various real-time processing functionalities offered by Apache Storm such as parallelism, data partitioning, and more
    Integrate Storm with other Big Data technologies like Hadoop, HBase, and Apache Kafka
    An easy-to-understand guide to effortlessly create distributed applications with Storm

    Book Description

    Apache Storm is a real-time Big Data processing framework that processes large amounts of data reliably, guaranteeing that every message will be processed. Storm allows you to scale your data as it grows, making it an excellent platform to solve your big data problems. This extensive guide will help you understand right from the basics to the advanced topics of Storm.

    The book begins with a detailed introduction to real-time processing and where Storm fits in to solve these problems. You'll get an understanding of deploying Storm on clusters by writing a basic Storm Hello World example. Next we'll introduce you to Trident and you'll get a clear understanding of how you can develop and deploy a trident topology. We cover topics such as monitoring, Storm Parallelism, scheduler and log processing, in a very easy to understand manner. You will also learn how to integrate Storm with other well-known Big Data technologies such as HBase, Redis, Kafka, and Hadoop to realize the full potential of Storm.

    With real-world examples and clear explanations, this book will ensure you will have a thorough mastery of Apache Storm. You will be able to use this knowledge to develop efficient, distributed real-time applications to cater to your business needs.

    What you will learn

    Understand the core concepts of Apache Storm and real-time processing
    Follow the steps to deploy multiple nodes of Storm Cluster
    Create Trident topologies to support various message-processing semantics
    Make your cluster sharing effective using Storm scheduling
    Integrate Apache Storm with other Big Data technologies such as Hadoop, HBase, Kafka, and more
    Monitor the health of your Storm cluster

    About the Author

    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.

    Table of Contents

    Real-Time Processing and Storm Introduction
    Deploying Storm in Cluster
    Storm Parallelism and Data Partitioning
    Trident Introduction
    Trident Topology and Uses
    Storm Scheduler
    Monitoring of Storm Cluster
    Integration of Storm and Kafka
    Storm and Hadoop Integration
    Storm Integration with Redis, Elasticsearch and HBase
    Apache Log Processing
    Twitter Tweets Collection and Machine learning