NitroFlare Big Data Principles and best practices of scalable realtime data systems

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    kocogi Active Member

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    Big Data: Principles and best practices of scalable realtime data systems by James Warren
    English | 10 May 2015 | ISBN: 1617290343 | 328 Pages | EPUB/MOBI/PDF (True) | 23.91 MB

    Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data.

    It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built.

    About the Book

    Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive.

    Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases.

    This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful.

    What's Inside

    Introduction to big data systems
    Real-time processing of web-scale data
    Tools like Hadoop, Cassandra, and Storm
    Extensions to traditional database skills

    About the Authors

    Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing.

    Table of Contents

    A new paradigm for Big Data

    PART 1 BATCH LAYER

    Data model for Big Data
    Data model for Big Data: Illustration
    Data storage on the batch layer
    Data storage on the batch layer: Illustration
    Batch layer
    Batch layer: Illustration
    An example batch layer: Architecture and algorithms
    An example batch layer: Implementation

    PART 2 SERVING LAYER

    Serving layer
    Serving layer: Illustration

    PART 3 SPEED LAYER

    Realtime views
    Realtime views: Illustration
    Queuing and stream processing
    Queuing and stream processing: Illustration
    Micro-batch stream processing
    Micro-batch stream processing: Illustration
    Lambda Architecture in depth[​IMG]
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