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.
"This book provides useful background on the use of MapReduce and Hadoop, but it is not a tutorial for developers new to those tools; the book assumes prior knowledge and experience...Although Google has moved on and replaced its MapReduce implementation with the more scalable Dataflow, there are still many current big data problems applicable to MapReduce. For those experienced developers working on such implementations, this book is a useful reference."
--Harry J. Foxwell, Computing Reviews
"A clear exposition of MapReduce programs for common data processing patterns--this book is indispensable for anyone using Hadoop."
"Although the MapReduce programming model is deceptively simple, using it to solve real problems at scale effectively requires a different way of thinking. MapReduce Design Patterns clearly delivers the insight previously gained only after years of experience."