Image from Amazon Title: Complete Guide to Open Source Big Data Stack
Author(s): Michael Frampton
Publisher: Apress Category: Data
Amazon wrote:See a Mesos-based big data stack created and the components used. You will use currently available Apache full and incubating systems. The components are introduced by example and you learn how they work together.
In the Complete Guide to Open Source Big Data Stack, the author begins by creating a private cloud and then installs and examines Apache Brooklyn. After that, he uses each chapter to introduce one piece of the big data stack―sharing how to source the software and how to install it. You learn by simple example, step by step and chapter by chapter, as a real big data stack is created. The book concentrates on Apache-based systems and shares detailed examples of cloud storage, release management, resource management, processing, queuing, frameworks, data visualization, and more.
I came across “Complete Guide to Open Source Big Data Stack” at the library. I picked it up because I figured it would be a good way to get an overview of some of the tools and libraries out there. It was. Chapters 1 and 10 provided an overview (or review) of a lot of tools. I hadn't heard of some like Apache Brooklyn (model/install/monitor apps). Others, like Apache Spark and Meso, I had heard of. It was helpful to see how everything fit together.
The architecture diagrams were helpful in understanding how everything relates. While I had read about Akka, I really liked the Pinger/Ponger example to fit everything together. The warnings were also helpful.
There were a lot of long sections of commands/outputs. This is useful in getting an install of the stack going. It felt long when reading (and not following it) though. I also worry that the level of detail will get out of date. But right now, it just came out so no worries there!