EBOOK

Big Data

Principles and best practices of scalable realtime data systems

James Warren
(0)
Pages
328
Year
2015
Language
English

About

Summary

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.

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

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

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