DocumentCode
739215
Title
A survey of mapreduce based parallel processing technologies
Author
Lu Jiamin ; Feng Jun
Author_Institution
Coll. of Comput. & Inf., Hehai Univ., Nanjing, China
Volume
11
Issue
14
fYear
2014
Firstpage
146
Lastpage
155
Abstract
Along with the increasing Big Data challenges, the MapReduce based systems are extensively welcomed, because of their remarkable simplicity and scalability. However, from the first day MapReduce is proposed, its argument with parallel DBMSs never stops, as it over-focuses on the scalability but overlooks the efficiency. Accordingly, extended systems are proposed in order to improve the performance on the limited scale clusters. In the meantime, traditional RDBMS technologies like structured data model, transaction, SQL, etc. are also getting more attention. This paper reviews such systems, from Google and also the third parties, trying to indicate the directions for the future research.
Keywords
parallel programming; relational databases; Big Data; Google; MapReduce based parallel processing technology; MapReduce based system; RDBMS technology; parallel DBMS; relational database management system; Computers; Data models; Distributed databases; Google; Parallel processing; Scalability; MapReduce; parallel processing; variants;
fLanguage
English
Journal_Title
Communications, China
Publisher
ieee
ISSN
1673-5447
Type
jour
DOI
10.1109/CC.2014.7085615
Filename
7085615
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