一种提高数据立方体查询速度的聚类矮结构

Q3 Engineering
Y. Bao, Fangling Leng, Daling Wang, Ge Yu
{"title":"一种提高数据立方体查询速度的聚类矮结构","authors":"Y. Bao, Fangling Leng, Daling Wang, Ge Yu","doi":"10.5626/jcse.2007.1.2.195","DOIUrl":null,"url":null,"abstract":"Dwarf is a highly compressed structure, which compresses the cube by eliminating the semantic redundancies while computing a data cube. Although it has high compression ratio, Dwarf is slower in querying and more difficult in updating due to its structure characteristics. We all know that the original intention of data cube is to speed up the query performance, so we propose two novel clustering methods for query optimization: the recursion clustering method which clusters the nodes in a recursive manner to speed up point queries and the hierarchical clustering method which clusters the nodes of the same dimension to speed up range queries. To facilitate the implementation, we design a partition strategy and a logical clustering mechanism. Experimental results show our methods can effectively improve the query performance on data cubes, and the recursion clustering method is suitable for both point queries and range queries.","PeriodicalId":37773,"journal":{"name":"Journal of Computing Science and Engineering","volume":"584 1","pages":"170-180"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A Clustered Dwarf Structure to Speed up Queries on Data Cubes\",\"authors\":\"Y. Bao, Fangling Leng, Daling Wang, Ge Yu\",\"doi\":\"10.5626/jcse.2007.1.2.195\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dwarf is a highly compressed structure, which compresses the cube by eliminating the semantic redundancies while computing a data cube. Although it has high compression ratio, Dwarf is slower in querying and more difficult in updating due to its structure characteristics. We all know that the original intention of data cube is to speed up the query performance, so we propose two novel clustering methods for query optimization: the recursion clustering method which clusters the nodes in a recursive manner to speed up point queries and the hierarchical clustering method which clusters the nodes of the same dimension to speed up range queries. To facilitate the implementation, we design a partition strategy and a logical clustering mechanism. Experimental results show our methods can effectively improve the query performance on data cubes, and the recursion clustering method is suitable for both point queries and range queries.\",\"PeriodicalId\":37773,\"journal\":{\"name\":\"Journal of Computing Science and Engineering\",\"volume\":\"584 1\",\"pages\":\"170-180\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computing Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5626/jcse.2007.1.2.195\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computing Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5626/jcse.2007.1.2.195","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 4

摘要

Dwarf是一种高度压缩的结构,它在计算数据立方体时通过消除语义冗余来压缩立方体。虽然它具有很高的压缩比,但由于它的结构特点,查询速度较慢,更新难度较大。我们都知道数据立方体的本意是为了提高查询性能,因此我们提出了两种新的查询优化聚类方法:递归聚类方法,通过递归方式聚类节点来加快点查询的速度;分层聚类方法,通过聚类相同维度的节点来加快范围查询的速度。为了便于实现,我们设计了分区策略和逻辑集群机制。实验结果表明,我们的方法可以有效地提高数据立方体的查询性能,递归聚类方法适用于点查询和范围查询。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Clustered Dwarf Structure to Speed up Queries on Data Cubes
Dwarf is a highly compressed structure, which compresses the cube by eliminating the semantic redundancies while computing a data cube. Although it has high compression ratio, Dwarf is slower in querying and more difficult in updating due to its structure characteristics. We all know that the original intention of data cube is to speed up the query performance, so we propose two novel clustering methods for query optimization: the recursion clustering method which clusters the nodes in a recursive manner to speed up point queries and the hierarchical clustering method which clusters the nodes of the same dimension to speed up range queries. To facilitate the implementation, we design a partition strategy and a logical clustering mechanism. Experimental results show our methods can effectively improve the query performance on data cubes, and the recursion clustering method is suitable for both point queries and range queries.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Computing Science and Engineering
Journal of Computing Science and Engineering Engineering-Engineering (all)
CiteScore
1.00
自引率
0.00%
发文量
11
期刊介绍: Journal of Computing Science and Engineering (JCSE) is a peer-reviewed quarterly journal that publishes high-quality papers on all aspects of computing science and engineering. The primary objective of JCSE is to be an authoritative international forum for delivering both theoretical and innovative applied researches in the field. JCSE publishes original research contributions, surveys, and experimental studies with scientific advances. The scope of JCSE covers all topics related to computing science and engineering, with a special emphasis on the following areas: Embedded Computing, Ubiquitous Computing, Convergence Computing, Green Computing, Smart and Intelligent Computing, Human Computing.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信