Parallel Data Processing with MapReduce: A Survey

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Provided by: Korea University
Topic: Data Management
Format: PDF
A prominent parallel data processing tool MapReduce is gaining significant momentum from both industry and academia as the volume of data to analyze grows rapidly. While MapReduce is used in many areas where massive data analysis is required, there are still debates on its performance, efficiency per node, and simple abstraction. This paper intends to assist the database and open source communities in understanding various technical aspects of the MapReduce framework. In this paper, the authors characterize the MapReduce framework and discuss its inherent pros and cons.
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