计算机与数字工程2017，Vol.45Issue(6)：1121-1126,6.DOI:10.3969/j.issn.1672-9722.2017.06.023
CSSAQP:一种基于聚类的分层抽样近似查询处理算法
CSSAQP:An Approximate Query Algorithm Based On Clustering Stratified Samping
摘要
Abstract
The approximate query processing technique is often applied to multidimensional analysis of massive data to short?en the execution time of the query and return the results as accurate as possible. Because of many extreme values in massive data,it will seriously affect the results of approximate query processing. Therefore,for the aggregation of massive data,this paper proposes a algorithm CSSAQP,which first clustered the original data set into three categories by a column,representing large clusters,small clusters and constant clusters,then use stratified sampling for each cluster by the group attribute,and constructed the overall sam?ple,finally,the query is rewritten on the overall sample set to reduce the query time of the massive data aggregation operation,and improve the accuracy of the query task. Experiments show that the algorithm can not only shorten the time of aggregation query,but also improve the accuracy of query results.关键词
近似查询处理/聚集查询/聚类/分层抽样Key words
AQP/aggregate query/clustering/stratified sampling分类
信息技术与安全科学引用本文复制引用
谢金星,李晖,陈梅,戴振宇..CSSAQP:一种基于聚类的分层抽样近似查询处理算法[J].计算机与数字工程,2017,45(6):1121-1126,6.基金项目
国家自然科学基金项目(编号:61462012,61562010,U1531246) （编号:61462012,61562010,U1531246）
基于云计算的医疗信息管理系统关键技术研究及应用(编号:GY[2014]3018) （编号:GY[2014]3018）
贵州省重大应用基础研究项目(编号:JZ20142001) （编号:JZ20142001）
贵州省教育厅自然科学项目(编号:黔科合人才团队字[2015]53号) （编号:黔科合人才团队字[2015]53号）
贵州大学研究生创新基金(院级)资助. （院级）
