-
Pigs and Elephants on the road to World Domination Jul 13, 2009 (10 of 10 found this helpful)
These days, one can't seem to attend technical conferences without hearing marketing-oriented speakers' world domination plans for their products. So imagine this: what if pigs and elephants are involved? Elephants would be Hadoop installations, and Pigs would be one of those animal-themed tools, smarter cousins of the elephants really, riding on top of Hadoops, directing them on how to perform their jobs. Would the world be a better place?
Hadoop is the brainchild of Doug Cutting, who named his creation after his kid's stuffed yellow elephant. Hadoop enables large datasets distributed over a cluster of machines to be processed in parallel. One machine or node in that cluster would usually house a JobTracker and a NameNode. The JobTracker schedules and manages processing jobs to be executed in the other machines, and the NameNode manages the metadata (e.g., file names and locations, etc) of the datasets to be processed. The processing jobs are programmed in the form of Map and Reduce functions. Inputs are usually split into blocks to be processed in parallel by two or more identical mappers. The close to final outputs are then fed to one or more identical reducers, whose job is to perform any final transformations on the intermediate data to produce data summaries in the expected format. Several companies are using Hadoop to extract knowledge from their extensive data.
I've read this book and Jason Venners' Pro Hadoop book. Although I like both, I like this book better for the following reasons: more comprehensive coverage of topics, and more insiders' information on design rationales and how certain Hadoop features really work behind the scenes.
Here's a breakdown of and some commentaries on the book's contents:
Chapter One introduces Hadoop, its history and how it's different from similar tools or frameworks. Kinda dry. Chapter Two introduces the MapReduce Programming model and its benefits when compared to, say, the use of Unix tools for achieving parallel processing of text files. This is also where readers are introduced to the concepts of: map, combiner, and reduce functions, shuffle and sort, streaming, etc. Chapters Three and Four are all about the Hadoop Distributed FileSystems and I/O and the design decisions that were made to address performance, reliability, and safety concerns.
Chapter Five shows you how to develop, configure, test, run and tune a MapReduce Application. Good chapter but Jason Venner's book has better materials on testing and debugging MapReduce applications.
Chapters Six through Eight discuss how MapReduce really works behind the scene, including advanced features. This is where you'll learn how flexible Hadoop is when it comes to handling different types of inputs and outputs in terms of numbers, sizes, formats, and usage scenarios. Excellent!
Chapters Nine and Ten are really good. They teach you how to set up and administer Hadoop clusters. There's even a brief but informative section on how to use Hadoop with Amazon EC2 servers.
Chapters 11-13 devote one chapter each on how to install and interact with frameworks built on top of Hadoop: Pig, HBase, and ZooKeeper. Chapter 14 provides Case Studies (e.g., How Facebook uses Hadoop to analyze ad campaign effectiveness, etc.).
Appendices A and B provide instructions on how to install Apache's Hadoop and Cloudera's distribution, respectively, and C gives you a runthrough of the steps to take when preparing to use the NCDC Weather Data used in the book.
Very thorough and well written book. 4.5 stars rating.
-
Partly succeeds Sep 8, 2009 (8 of 9 found this helpful)
Tom White certainly writes very well: this book is very readable. It is also quite comprehensive, falling somewhere between a tutorial and a reference.
That being said, I was ultimately rather disappointed. First, and most importantly, it was not clear to me after reading this book how I might use Hadoop for some of my projects, or if indeed they were good candidates for MapReduce. I feel it should have been possible to provide some generic guidance. Second, some chapters are written by other authors, and these did not uniformly provide the same quality of instruction, reading occasionally like advertisements.
I confess I am puzzled by the number of encapsulating and utility APIs that have grown up around Hadoop. Why do we need Pig, HBase, Hive, Zookeeper and Cascading? Apparently because (according to what I have read here), bare Hadoop is hard to program with (productively). Some indication of how these wrappers interact with each other would have been helpful.
As it is, I feel LESS urge to evangelize for Hadoop having read this book. Surely not the desired effect?
-
First 25 Pages Have You Up And Running! Aug 24, 2009 (2 of 2 found this helpful)
I picked up this book to catch up on Hadoop, which the rest of my team has been using for several months. Unfortunately I was too busy with other projects to spend any time on MapReduce and thought it'd be a grueling process to be brought up to speed on it. Within the first 25 pages and about 3 hours, Tom had me up and running my first MapReduce job which I successfully adapted for a specific metric we were trying to generate. The book does a great job of breaking down Hadoop's complex pieces into easy to understand components, but doesn't try and pump you full of conceptual BS before it lets you touch real code.
If I were to make any suggestions it would be to start the book off with some simple instructions for installing and getting Hadoop up and running on a local machine, followed by some simple explanations of DFS and Hadoop's commands for managing the file system. I would also explain much earlier how to get your classes recognized by Hadoop for those a bit rusty at Java. Fortunately, the online Wiki was very good about providing instructions to get me going on a Mac, and that took a majority of OS-specific needs off the burden of the book. You will, no doubt, have to be intelligent to read this book, but if you're using Hadoop, there is already a prerequisite for technical proficiency you'll need to satisfy. Overall good job, Tom.
-
Don't understand all the other negative reviews Jul 23, 2009 (2 of 3 found this helpful)
This is the book to get if you are actually doing something with Hadoop. It's been a lifesaver, and has answered all our questions of, "I wonder if I can do x in Hadoop?"
It gives a lot of information about the internals of Hadoop, which you will want to know when things go wrong or when you just want to get more out of Hadoop.
I normally don't post reviews as much, but I think Tom White and this book deserves way more than 5 stars, so I'm not sure why it only has 3 stars on Amazon.
-
Very comprehensive book Aug 31, 2009
I bookmarked this book for several months and bought it very rapidly after its availibility. It's a very comprehensive book, very deep and cover many various aspects of Hadoop and related technologies. I recommend it without any doubt, enjoy reading and learning.