- Reading level: 10+ years
- Paperback: 272 pages
- Publisher: Shroff; First edition (29 December 2012)
- Language: English
- ISBN-10: 9350239817
- ISBN-13: 978-9350239810
- Package Dimensions: 23 x 17.8 x 1.2 cm
- Average Customer Review: 4 customer reviews
- Amazon Bestsellers Rank: #85,482 in Books (See Top 100 in Books)
Map Reduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop and Other Systems Paperback – 29 Dec 2012
Customers who bought this item also bought
Customers who viewed this item also viewed
About the Author
Donald Miner is an avid user of Apache Hadoop and a practitioner of data science. He serves as Chief Technology Officer at ClearEdge IT Solutions, a company that provides Big Data professional services. He is author of the O'Reilly book MapReduce Design Patterns, which is based on his experiences as a MapReduce developer. Donald has architected and implemented a number of mission-critical and large-scale Hadoop systems within the U.S. Government and Fortune 500 companies. He received his PhD from the University of Maryland, Baltimore County in Computer Science, where he focused on Machine Learning and Multi-Agent Systems. He lives in Maryland with his wife and two young sons.
Adam Shook is Founder and Principal Consultant at Datacatessen, LLC, a boutique big data solutions company specializing in data architecture and engineering. Shook graduated with a B.S. in Computer Science from the University of Maryland Baltimore County (UMBC) and took a job building a new high-performance graphics engine for a game studio. Looking for new challenges, he enrolled in the Computer Science graduate program at UMBC focusing on distributed computing technologies. Shook has worked on developing a wide variety of data applications and analytics deployed on large-scale production data platforms in both the commercial and government spaces. He is involved in developing and instructing graduate and undergraduate courses at UMBC, preparing young minds to work with big data. He spends what little free time he has playing video games and homebrewing.
Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.
To get the free app, enter mobile phone number.
What other items do customers buy after viewing this item?
Top customer reviews
There was a problem filtering reviews right now. Please try again later.
Most helpful customer reviews on Amazon.com
I had studied Jimmy Lin's book [...]before i read this which gives some really good examples of algorithm design. I was hoping to find something which focussed on how some of the design patterns can be leveraged to implement more complicated and non-trivial algorithms in Map-Reduce more effectively.
But i feel that the book uses some fairly straightforward algorithms to explain the pattern and does not go deep.
Another thing that i did not like is that the book is just too much Hadoop specific and ignores other Map Reduce implementations which are getting very popular.
Overall the book is a good step in introducing patterns and algorithms in a more systematic manner, in the Map Reduce programming paradigm. It gives a good survey of some of the emerging areas in last few chapters. The chapter on Meta Patterns was my favorite as it gives some good introductory material on building more complicated pipelines using Map Reduce, and how one could take steps in optimizing the runtime of bigger pipelines.