Title :
A Top-k query algorithm for big data based on MapReduce
Author_Institution :
Information School, Ningbo City College of vocational technology(Vocational Education Faculty of Ningbo University), Zhejiang Province, China
Abstract :
Big data has brought new challenges to Top-k in data partitioning and parallel programming model. In order to overcome these problems, a new Top-k query algorithm for big data based on MapReduce is proposed. Based on the features of MapReduce, this paper presents an in-depth study of Top-k query on big data from the perspective of data partitioning, data reduce, etc. Theoretical and experimental results show the proposed Algorithm makes a sharp increase in efficiency.
Keywords :
"Big data","Partitioning algorithms","Algorithm design and analysis","Data models","Parallel programming","Programming profession"
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2015 6th IEEE International Conference on
Print_ISBN :
978-1-4799-8352-0
Electronic_ISBN :
2327-0594
DOI :
10.1109/ICSESS.2015.7339218
