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


Книга Big DataАвтор:  Nathan Marz, James Warren
Издательство: Manning Publications

Год: May 10, 2015
Страниц: 328
Язык: английский
Формат:
ISBN: 1617290343

 
Аннотация:

 Summary (кратко о книге)

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.

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

About the Book (о книге подробнее)

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 (что включает книга)

  • Introduction to big data systems (введение в системы Больших данных)
  • Real-time processing of web-scale data (процесс обработки в реальном времени web-масштабируемых данных)
  • Tools like Hadoop, Cassandra, and Storm (обзор инструментария: Hadoop, Cassandra, Storm)
  • Extensions to traditional database skills (расширение навыков по работе с традиционными базами данных)

About the Authors (об авторах книги)

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 (оглавление книги)

  1. A new paradigm for Big Data
  2. PART 1 BATCH LAYER
  3. Data model for Big Data
  4. Data model for Big Data: Illustration
  5. Data storage on the batch layer
  6. Data storage on the batch layer: Illustration
  7. Batch layer
  8. Batch layer: Illustration
  9. An example batch layer: Architecture and algorithms
  10. An example batch layer: Implementation
  11. PART 2 SERVING LAYER
  12. Serving layer
  13. Serving layer: Illustration
  14. PART 3 SPEED LAYER
  15. Realtime views
  16. Realtime views: Illustration
  17. Queuing and stream processing
  18. Queuing and stream processing: Illustration
  19. Micro-batch stream processing
  20. Micro-batch stream processing: Illustration
  21. Lambda Architecture in depth

 

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