Big Data: Principles and Best Practices of Scalable Realtime Data Systems

  • 9h 15m 20s
  • James Warren, Nathan Marz
  • Manning Publications
  • 2018

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.

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.

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.

In this Audiobook

  • Chapter 1 - A New Paradigm for Big Data
  • Chapter 2 - Data Model for Big Data
  • Chapter 3 - Data Model for Big Data: Illustration
  • Chapter 4 - Data Storage on the Batch Layer
  • Chapter 5 - Data Storage on the Batch Layer: Illustration
  • Chapter 6 - Batch Layer
  • Chapter 7 - Batch Layer: Illustration
  • Chapter 8 - An Example Batch Layer: Architecture and Algorithms
  • Chapter 9 - An Example Batch Layer: Implementation
  • Chapter 10 - Serving Layer
  • Chapter 11 - Serving Layer: Illustration
  • Chapter 12 - Realtime Views
  • Chapter 13 - Realtime Views: Illustration
  • Chapter 14 - Queuing and Stream Processing
  • Chapter 15 - Queuing and Stream Processing: Illustration
  • Chapter 16 - Micro-Batch Stream Processing
  • Chapter 17 - Micro-Batch Stream Processing: Illustration
  • Chapter 18 - Lambda Architecture in Depth