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Big Data

3.83 of 5 stars 3.83  ·  rating details  ·  96 ratings  ·  11 reviews
Services like social networks, web analytics, and intelligent e-commerce often need to manage data at a scale too big for a traditional database. As scale and demand increase, so does Complexity. Fortunately, scalability and simplicity are not mutually exclusive—rather than using some trendy technology, a different approach is needed. Big data systems use many machines wor ...more
ebook, 425 pages
Published September 2012 by Manning (first published January 1st 2012)
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The first chapter is definitely worth reading. Maybe second one too. The rest is way too focused on specific technologies. And so it happens, the technologies happen to be created by the authors. Too much advertising, not enough of the big picture.
Gaelan D'costa
This book was my first exposure to an architecture for dealing with large amounts of data in a holistic way; while I'm familiar with individual concepts like MapReduce, Column Stores, CAP, etc... I've never thought about them all at as part of the same ecosystem. As such, my rating is based on the accessibility and readability of the book, not of the correctness and feasibility of the content.

This is the kind of technology stack my current employer is forming a business around and I want to get
Sebastian Gebski
Controversial book.

1. Worst title ever. If it wasn't Nathan Marz (father of Storm), I'd never pick it up.
2. It's not just bad title - this book is NOT about Big Data - or rather, it's about one particular "pattern" of Big Data usage - Lambda Architecture.
3. It's great in terms of distributed processing / storage considerations - best micro-batching description / analysis ever
4. Particular product (Kafka, Hadoop, Storm) descriptions are ... controversial. Not a deep dive, but author(s) don't cons
Mind turned to mush after chapter 3 . First 3 chapters are kick ass, then I began to wander. It is as though he is channelling Perl programming; wherein everything makes sense as you code, but later on you lack context and rationale. What is "Pail?" How are you supposed to run it? The code samples are all Java, so you better know that before even bothering to read this. It may get better, but I don't have the stomach, nor the time for this.
Pandeeswaran Bhoopathy
Nice work on explaining the details of lambda acrchitecture in an elegant way . I have come to know some of the technologies such as thrift, JCascalog and Pail while reading this book. This provides me a great opportunity on investigating further about the aforementioned technologies. I recommend this book to all level of audience from novice to expert in big data implementation.
The book was super interesting and exciting when they started it (3 years ago), but it's "meh" and I would say some of technologies that looked promising 3 years ago, are not doing well nowadays.
Anyway, I'm giving it 4 stars because of the excitement I was having reading it 3 years ago.

But you should definitely read critics of proposed approach
Ana Todor
Very good to get a general overview on big data, but way too focused on specific technologies. Worth reading the theory, but only breeze through the code if you are using different technologies.
Bilal Salih
this is a useful book, really simple and clear
Sep 07, 2012 Michael marked it as to-read
Shelves: on-hold
Reading the draft as it's written.
The best book on the subject.
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