星型模型的轮廓连接查询算法  

Skyline-Join Algorithm in Star Model

作　　者：徐忠华[1,2] 张剡[1,2] 陈玲[1,2] 柏文阳[1,2] 

机构地区：[1]南京大学计算机软件新技术国家重点实验室,南京210093 [2]南京大学计算机科学与技术系,南京210093

出　　处：《计算机科学与探索》2010年第5期410-419,共10页Journal of Frontiers of Computer Science and Technology

基　　金：国家自然科学基金No.60721002~~

摘　　要：轮廓查询在多标准决策中具有重要应用价值,对于单表轮廓查询已有大量研究,但在实际中,轮廓查询的属性很可能分布在多张表中。如果在多表连接之后进行轮廓查询,随着维度和元组数目的增加,计算代价会越来越大。为此,针对数据仓库中星型模型的数据特点,提出了三种此模型下的多表连接轮廓查询算法并对算法进行了实验比较分析。结果表明,此算法比先连接再做单表轮廓查询的算法更为有效,并且这三种算法在不同特点的数据集合下会表现出各自的优势。Skyline query is valuable in multi-criteria decision making. Most of the exiting work is based on single table skyline query. However,the data retrieved by users for the targeting skyline may often be stored in multiple tables,especially in star model of data warehouse. As a result,the costs on computing skylines on the joined table will increase dramatically due to its increasing dimensionality and cardinality. Thus,based on the data characteristic of star model,three solutions to skyline-join in star model in data warehouse are proposed. Experiments demonstrate that the algorithms are better than naive skyline query,and they dominate others in its own data set.

关 键 词：轮廓查询 多表连接 数据仓库 星型模型 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]