Big Data

principles and best practices of scalable real-time data systems

Paperback

English language

Published Jan. 25, 2015 by Manning.

ISBN:
978-1-61729-034-3
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3 stars (3 reviews)

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. What's inside: Introduction to big data systems; Real-time processing of web-scale data; Tools like Hadoop, Cassandra, and Storm; Extensions to …

1 edition

Review of 'Big Data' on 'Goodreads'

3 stars

Sadly not my kind of book. Starting with several examples that use "Gender". From a Gender-Field inside of the database that just knows "Male" and "Female" to an example that tries to guess the "Gender" based on the first name.

On top of that it is filled with unnecessary and bad diagrams that basically are explained in one sentence, but the authors thought that it might be good to also put 3 boxes and some arrows between them.

The source code examples are not very good too. With arrows pointing to explain what the code is doing. One hint: if you need 5 arrows explaining things in a 7 line function, maybe you should try to find a better code example that doesn't need this?

Review of 'Big Data' on 'Goodreads'

3 stars

This is a book about Lambda Architecture and how it is used in the context of Big Data.
I enjoyed reading about lambda architecture and other related concepts and found them useful since I was a complete beginner in this domain.

The first few chapters are definitely worth the read, the rest of the chapters I consider architecture reference material (too detailed to be remembered and, at the same time, requiring knowledge about the technologies being discussed). There were quite a few moments while reading it when my mind started to wonder off...

To sum up: read the first few chapters and then let google (plus the source code that accompanies the book) be your guide

And of course, the review would not be complete without the criticism of the architecture.

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4 stars