Transcription of i Data-Intensive Text Processing with MapReduce
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i Data-Intensive Text Processing with MapReduce
IData-Intensive Text Processingwith MapReduceJimmy Lin and Chris DyerUniversity of Maryland, College ParkManuscript prepared April 11, 2010 This is the pre-production manuscript of a book in the Morgan & Claypool SynthesisLectures on Human Language Technologies. Anticipated publication date is .. ii1 Introduction .. in the Clouds .. Ideas .. Is This Different? .. This Book Is Not .. 172 MapReduce Basics .. Programming Roots .. and Reducers .. Execution Framework .. and Combiners .. Distributed File System .. Cluster Architecture .. 383 MapReduce Algorithm Design .. Aggregation .. Combiners and In-Mapper Algorithmic Correctness with Local and Stripes .. Relative Frequencies .. Sorting .. Joins .. Reduce-Side Map-Side Memory-Backed Join67 CONTENTS .. 684 Inverted Indexing for Text Retrieval .. Crawling .. Indexes .. Indexing: Baseline Implementation .. Indexing: Revised Implementation.
with MapReduce in 2008 [46]. In April 2009, a blog post1 was written about eBay’s two enormous data warehouses: one with 2 petabytes of user data, and the other with 6.5 petabytes of user data spanning 170 trillion records and growing by 150 billion new records per day. Shortly thereafter, Facebook revealed2 similarly impressive numbers,
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