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.
"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."