改进的图变换算法,解决顶点之间的传递依赖关系

Sutedi, T. B. Adji, N. A. Setiawan
{"title":"改进的图变换算法,解决顶点之间的传递依赖关系","authors":"Sutedi, T. B. Adji, N. A. Setiawan","doi":"10.1109/ICSIGSYS.2017.7967051","DOIUrl":null,"url":null,"abstract":"Rapid and vast growth of data volume triggers a need for data management system with good scalability, availability and reliability. NoSQL database comes as a database management system developed to answer the need for such large scale and distributed data management. It is considered more effective and efficient compared to relational database. This database characteristics are very different than relational database. Therefore, a good method is necessary in order to transform data from relational database to NoSQL database. The Graph Transforming Algorithm is one of the simple methods and easy to use for that purpose. However, the result of conversion using this method remains with a considerably high level of data redundancy, making it necessary to further develop the algorithm. This research proposes a new algorithm called Enhanced Graph Transforming Algorithm, a development of Graph Transforming Algorithm by adding rules to eliminate transitive dependency between vertices prior to joining the vertices. Based on the test conducted in the research, the Enhanced Graph Transforming Algorithm is proven capable of reducing the number of redundant attributes and suppressing waste of space on data storage by up to 39.68% lower than the result of transformation generated using Graph Transforming Algorithm.","PeriodicalId":212068,"journal":{"name":"2017 International Conference on Signals and Systems (ICSigSys)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Enhanced Graph Transforming Algorithm to solve transitive dependency between vertices\",\"authors\":\"Sutedi, T. B. Adji, N. A. Setiawan\",\"doi\":\"10.1109/ICSIGSYS.2017.7967051\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Rapid and vast growth of data volume triggers a need for data management system with good scalability, availability and reliability. NoSQL database comes as a database management system developed to answer the need for such large scale and distributed data management. It is considered more effective and efficient compared to relational database. This database characteristics are very different than relational database. Therefore, a good method is necessary in order to transform data from relational database to NoSQL database. The Graph Transforming Algorithm is one of the simple methods and easy to use for that purpose. However, the result of conversion using this method remains with a considerably high level of data redundancy, making it necessary to further develop the algorithm. This research proposes a new algorithm called Enhanced Graph Transforming Algorithm, a development of Graph Transforming Algorithm by adding rules to eliminate transitive dependency between vertices prior to joining the vertices. Based on the test conducted in the research, the Enhanced Graph Transforming Algorithm is proven capable of reducing the number of redundant attributes and suppressing waste of space on data storage by up to 39.68% lower than the result of transformation generated using Graph Transforming Algorithm.\",\"PeriodicalId\":212068,\"journal\":{\"name\":\"2017 International Conference on Signals and Systems (ICSigSys)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Signals and Systems (ICSigSys)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSIGSYS.2017.7967051\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Signals and Systems (ICSigSys)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSIGSYS.2017.7967051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

数据量的快速增长引发了对具有良好可扩展性、可用性和可靠性的数据管理系统的需求。NoSQL数据库是为满足这种大规模、分布式数据管理的需要而开发的数据库管理系统。它被认为比关系数据库更有效和高效。这种数据库的特点与关系数据库有很大的不同。因此,需要一种好的方法将数据从关系数据库转换为NoSQL数据库。图变换算法是实现这一目标的一种简单易行的方法。然而,使用该方法的转换结果仍然具有相当高的数据冗余水平,因此有必要进一步开发该算法。本文提出了一种新的增强图变换算法,该算法是对图变换算法的一种发展,通过在顶点连接之前添加规则来消除顶点之间的传递依赖关系。通过本研究的测试,证明了增强图变换算法在减少冗余属性数量和抑制数据存储空间浪费方面,比使用图变换算法生成的变换结果降低了39.68%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhanced Graph Transforming Algorithm to solve transitive dependency between vertices
Rapid and vast growth of data volume triggers a need for data management system with good scalability, availability and reliability. NoSQL database comes as a database management system developed to answer the need for such large scale and distributed data management. It is considered more effective and efficient compared to relational database. This database characteristics are very different than relational database. Therefore, a good method is necessary in order to transform data from relational database to NoSQL database. The Graph Transforming Algorithm is one of the simple methods and easy to use for that purpose. However, the result of conversion using this method remains with a considerably high level of data redundancy, making it necessary to further develop the algorithm. This research proposes a new algorithm called Enhanced Graph Transforming Algorithm, a development of Graph Transforming Algorithm by adding rules to eliminate transitive dependency between vertices prior to joining the vertices. Based on the test conducted in the research, the Enhanced Graph Transforming Algorithm is proven capable of reducing the number of redundant attributes and suppressing waste of space on data storage by up to 39.68% lower than the result of transformation generated using Graph Transforming Algorithm.
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
自引率
0.00%
发文量
0
×
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