Title :
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
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;
Conference_Titel :
Web Information System and Application Conference (WISA), 2013 10th
Conference_Location :
Yangzhou
Print_ISBN :
978-1-4799-3218-4
DOI :
10.1109/WISA.2013.62
