Parallel Data Processing with MapReduce: A Survey

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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 survey intends to assist the database and open source communities in understanding various technical aspects of the MapReduce framework. In this survey, we characterize the MapReduce framework and discuss its inherent pros and cons. We then introduce its optimization strategies reported in the recent literature. We also discuss the open issues and challenges raised on parallel data analysis with MapReduce.
Publisher
ASSOC COMPUTING MACHINERY
Issue Date
2011-12
Language
English
Article Type
Article
Citation

SIGMOD RECORD, v.40, no.4, pp.11 - 20

ISSN
0163-5808
URI
http://hdl.handle.net/10203/96872
Appears in Collection
CS-Journal Papers(저널논문)
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