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i Data-Intensive Text Processing with MapReduce

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IData-Intensive Text Processingwith MapReduceJimmy Lin and Chris DyerUniversity of Maryland, College ParkManuscript prepared April 11, 2010This is the pre-production manuscript of a book in the Morgan & Claypool SynthesisLectures on Human Language Technologies. Anticipated publication date is . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii1Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . in the Clouds.

Introduction MapReduce [45] is a programming model for expressing distributed computations on massive amounts of data and an execution framework for large-scale data processing on clusters of commodity servers. It was originally developed by Google and built on well-known principles in parallel and distributed processing dating back several ...

  Introduction

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