Books for Hadoop & Map Reduce
- The Definitive guide is in some ways the ‘hadoop bible’, and can be an excellent reference when working on Hadoop, but do not expect it to provide a simple getting started tutorial for writing a Map Reduce. This book is great for really understanding how everything works and how all the systems fit together.
- This is the book if you need to know the ins and outs of prototyping, deploying, configuring, optimizing, and tweaking a production Hadoop system. Eric Sammer is a very knowledgeable engineer, so this book is chock full of goodies.
- Design Patterns is a great resource to get some insight into how to do non-trivial things with Hadoop. This book goes into useful detail on how to design specific types of algorithms, outlines why they should be designed that way, and provides examples.
- One of the few non-O’Reilly books in this list, Hadoop in Action is similar to the definitive guide in that it provides a good reference for what Hadoop is and how to use it. It seems like this book provides a more gentle introduction to Hadoop compared to the other books in this list.
- A slightly more advanced guide to running Hadoop. It includes chapters that detail how to best move data around, how to think in Map Reduce, and (importantly) how to debug and optimize your jobs.
- Another Hadoop intro book, Hadoop Essentials focuses on providing a more practical introduction to Hadoop which seems ideal for a CS classroom setting
- A book which aims to provide real-world examples of common hadoop problems. It also covers building integrated solutions using surrounding tools (hive, pig, girafe, etc)
- The cookbook provides an introduction to installing / configuring Hadoop along with ‘more than 50 ready-to-use Hadoop MapReduce recipes’.
- Released July 2013 this book promises to guide readers through writing and testing Cascading based workflows. This is one of the few books written about higher level Map Reduce frameworks, so I’m excited to give it a read.
- A front to back guide to YARN, the next generation task management layer for Hadoop. This book is written (in part) by the YARN project founder, and the project lead.
- This book is built around seven map reduce ‘recipes’ to learn from. It aims to be a consise, practical guide to get you coding.
Books for related projects
- A detailed guide for understanding, running, debugging, and extending Hive
- Programming Pig describes pig, walks you through how to use it, and helps you understand how to extend it
- This book is to HBase what the Hadoop Guide is to Hadoop, a comprehensive walk-through of HBase, how it works, how to use it, and how it is designed.
- A standalone Sqoop recipe book which covers common usage and integrations
- Apache Mahout is a set of machine learning libraries for Hadoop. This book provides a hands-on introduction and some sample use-cases.
- Holden walks through the ins and outs of Apache Spark including set up, interactive querying, and job deployment. Fun fact - I used to work with Holden, he’s a super smart guy so I’m sure this book is excellent.
- Russell introduces his own version of an agile tool-set for data analysis and exploration. The book covers both investigative tools (like Apache Pig), and visualization tools like D3. His pitch is pretty compelling