JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2015, Vol. 50 ›› Issue (07): 66-70.doi: 10.6040/j.issn.1671-9352.0.2014.461

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Optimization on MapReduce algorithm based on Hash table

LI Rui-xia, LIU Ren-jin, ZHOU Xian-cun   

  1. School of Information Engineering, West Anhui University, Lu'an 237012, Anhui, China
  • Received:2014-10-20 Online:2015-07-20 Published:2015-07-31

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Abstract: Distributed parallel computing is commonly used to improve computer performance. But according to different demands, there is not a uniform way to design and implement parallel program. Parallel programming depends on the experience of developer. MapReduce, a distributed parallel programming model, put forward by Google, can perform special parallel program development and operation. MapReduce was optimized by using Hash table, which would decrease fragment of Map function, skip other redundancy function such as Combiner function, reduce transmission load and improve computing efficiency. Meanwhile, the attributes of Map function and Reduce function were kept to make MapReduce maintaining parallel.

Key words: distributed, MapReduce, Map function, Hash table, parallel, Hadoop

CLC Number: 

  • TP311
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