Research on Improved A Priori Algorithm Based on Coding and MapReduce

Author

Jian Guo ; Yong-gong Ren

Author_Institution

Sch. of Comput. & Inf. Technol., Liaoning Normal Univ., Dalian, China

fYear

2013

Firstpage

294

Lastpage

299

Abstract

Based on the column-oriented database called Hbase, by using a distributed file system HDFS in Hadoop as the underlying storage system, and utilizing Map/Reduce data programming model as a distributed data processing engine, this paper proposes an improved Apriori algorithm based on coding and Map/Reduce (CMR-Apriori) which is able to process data in distributed cloud computing environment and is applicable in book sales system. Results of this study demonstrate that the system is capable of realizing various functions such as fast-analysis, low redundancy, and exhibiting good performance in terms of interactivity, scalability and high reliability.

Keywords

cloud computing; distributed databases; network operating systems; parallel programming; public domain software; CMR-Apriori; HDFS; Hadoop; Hbase; MapReduce; MapReduce data programming model; book sales system; coding; column-oriented database; distributed cloud computing environment; distributed data processing engine; distributed file system; improved a priori algorithm; parallel programming model; reliability; storage system; Algorithm design and analysis; Association rules; Cloud computing; Clustering algorithms; Distributed databases; Parallel processing; Apriori algorithm; Hadoop; Hbase; book sales; cloud computing;

fLanguage

English

Publisher

ieee

Conference_Titel

Web Information System and Application Conference (WISA), 2013 10th

Conference_Location

Yangzhou

Print_ISBN

978-1-4799-3218-4

Type

conf

DOI

10.1109/WISA.2013.62

Filename

6778653