[1]宋爱波,张若儒,赵经华,等.OLAP聚集计算中的维存储技术[J].东南大学学报(自然科学版),2012,42(5):797-802.[doi:10.3969/j.issn.1001-0505.2012.05.001]
 Song Aibo,Zhang Ruoru,Zhao Jinghua,et al.Dimensional-stores technology in OLAP aggregation[J].Journal of Southeast University (Natural Science Edition),2012,42(5):797-802.[doi:10.3969/j.issn.1001-0505.2012.05.001]
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OLAP聚集计算中的维存储技术()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
42
期数:
2012年第5期
页码:
797-802
栏目:
计算机科学与工程
出版日期:
2012-09-20

文章信息/Info

Title:
Dimensional-stores technology in OLAP aggregation
作者:
宋爱波 张若儒 赵经华 何战国
东南大学计算机科学与工程学院, 南京 211189
Author(s):
Song Aibo Zhang Ruoru Zhao Jinghua He Zhanguo
School of Computer Science and Engineering, Southeast University, Nanjing 211189, China
关键词:
OLAP HBase 维存储 B+树
Keywords:
OLAP(online analytical processing) HBase dimensional-stores B+tree
分类号:
TP311
DOI:
10.3969/j.issn.1001-0505.2012.05.001
摘要:
为解决传统行存储结构导致OLAP聚集计算效率低下的问题,设计了基于维存储的OLAP数据存取技术.首先,将OLAP事实表中的维属性集和度量属性集定义为2个列族,每张维表的所有属性定义为1个列族.对维表进行二进制编码,生成维层次编码,从而保持了维的层次语义特性.以(维层次编码,度量值)对形式按列组织数据,消除查询时维表与事实表的复杂连接操作运算.然后,采用自底向上方法构建B+树,对维层次编码进行索引,加快了数据读取效率.通过增删事实表和维层次编码-度量表中相应的列,实现维和度量的增加和删除.性能分析结果表明,这种OLAP数据存取技术具有良好的可扩展性,能高效地管理和存取OLAP海量多维数据,有效支持上层OLAP聚集计算.
Abstract:
To improve the efficiency of OLAP(online analytical processing)aggregation in traditional row-stores, a dimension-stores based OLAP data access technology is designed. First, the dimension attributes and measure attributes of the OLAP fact table are defined as two column families, and all attributes in a dimension table are defined as one column family. Dimension tables are encoded by using binary digit to generate dimension hierarchy codes, and thus the hierarchy semantics of dimension is maintained. The data are organized as(dimension hierarchy code, measure value)to eliminate the complex join operations between dimension tables and fact table in query. Then, a B+tree index is bottom-up built to index the dimension hierarchy codes, which accelerates the data access efficiency. Adding and deleting the corresponding columns in fact table and dimension hierarchy code-measure tables can realize the addition and deletion of dimensions and measures. The performance analysis results show that this OLAP data access technology has good expandability. It can efficiently manage and access massive OLAP multidimensional data, and effectively supports the upper OLAP aggregation.

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备注/Memo

备注/Memo:
作者简介: 宋爱波(1970—),男,博士,副教授, absong@seu.edu.cn.
基金项目: 国家重点基础研究发展计划(973计划)资助项目(2010CB328104)、国家自然科学基金资助项目(61070161, 60903161, 60903162, 61003257)、 “十一五”国家科技支撑计划资助项目(2010BAI88B03, 2011BAK21B02)、高等学校博士点学科专项科研基金资助项目(20110092130002)、江苏省自然科学基金资助项目(BK2008030)、 东南大学江苏省网络与信息安全重点实验室资助项目(BM2003201)、东南大学教育部计算机网络与信息集成重点实验室资助项目(93K-9)、浙江师范大学计算机软件与理论省级重中之重学科开放基金资助项目.
引文格式: 宋爱波,张若儒,赵经华,等.OLAP聚集计算中的维存储技术[J].东南大学学报:自然科学版,2012,42(5):797-802. [doi:10.3969/j.issn.1001-0505.2012.05.001]
更新日期/Last Update: 2012-09-20