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研究生:李義偉
研究生(外文):YI-WEI LEE
論文名稱:在XML資料倉儲中實體化資料方體選取之研究
論文名稱(外文):The Optimization of Data Cube Selection on XML-based Data Warehouse
指導教授:邱紹豐邱紹豐引用關係
學位類別:碩士
校院名稱:大葉大學
系所名稱:資訊工程學系碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2004
畢業學年度:95
語文別:中文
論文頁數:47
中文關鍵詞:資料方體
外文關鍵詞:LatticeData CubeXML
相關次數:
  • 被引用被引用:1
  • 點閱點閱:143
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  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:2
傳統資料庫存放的資料異動性高,並不利於資料分析。為了有效分析資料庫的資料,企業都會建立資料倉儲(Data Warehouse),以滿足資料分析的需求。藉由分析出來的資訊,協助公司經營的決策方向。
查詢資料倉儲中的資料時,其匯總運算(Aggregation)耗費的資源很高,為了提升查詢能,以預先建置資料方體(Data Cube)的方法,降低匯總運算所耗費得資源。但在儲存空間有限之情況下,該如何挑選資料方體建置,以提升查詢效能,非常的重要。因此,本文利用Lattice架構挑選資料方體建置,儘量滿足每一種查詢方式為目標。
此外,隨著網際網路的興起,許多的資料藉由網路傳遞,若公司間欲交換資料倉儲中的資料時,會有異質性資料庫間相容的問題。因此,本文以XCube架構為基礎,用XML(eXtensible Markup Language)來建立資料倉儲,以解決此問題。本文同時在XML資料倉儲中,加入Lattice架構,以方便使用者快速的查詢資料方體。
The data in the traditional database often change, and is unfavorable to data analysis. In order to effectively analyzes the data of the database, the enterprise is build up the Data Warehouse to satisfy the data analysis. Through the information of analyzing, help the decision direction with the company manages.
When query data in the Data Warehouse, the Aggregation consumption resources is very high, in order to promote the query efficiency, reduces resources with Aggregation. The Data Warehouse storage space limited situation, how to select Data Cube to establish, to promote the query efficiency is very important. Therefore, this article is using Lattice structure to select some Data Cube to be preserved, try to satisfy with each kind of query for main goal.
In addition, because of the Internet to spring up, a lot data are transmitting with Internet, when to exchange the data in the Data Warehouse among the companies, it is apt to have questing among the heterogeneity databases. Therefore, this article is based on XCube structure, set up the Data Warehouse with XML, in order to solve this problem. At the same time, this article in XML Data Warehouse add the Lattice Structure, let users query Data Cube fast.
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簽名頁
授權書.............................................................iii
中文摘要...........................................................iv
英文摘要...........................................................v
誌謝...............................................................vi
目錄...............................................................vii
圖目錄.............................................................ix

第一章 緒論.......................................................1
第一節 研究動機............................................2
第二節 研究目的............................................2
第三節 論文架構............................................3
第二章 相關研究....................................................4
第一節 資料倉儲基本概念.....................................4
第二節 XML相關技術........................................10
第三節 XML資料倉儲相關技術.................................13
第四節 Lattice相關技術....................................19
第三章 系統流程...................................................23
第一節 資料方體大小之預估 ..................................24
第二節 挑選資料方體實體化之演算法...........................23
第三節 支援Lattice之XCube架構.............................28
第四節 搜尋資料方體之演算法................................30
第四章 系統實作...................................................33
第一節 實作挑選資料方體....................................34
第二節 實作資料方體查詢....................................37
第五章 效能評估...................................................38
第六章 結論.......................................................43

參考文獻...........................................................45
[1] W.H. Inmon, “Building the data warehouse”, 1996.
[2] Surajit Chaudhuri and Umeshwar Dayal, “An Overview of Data
Warehousing and OLAP Technology”, SIGMOD Record Volume 26.,
pp.65-74, 1997.
[3] 曾守正和周韻寰,“資料庫系統進階實務”,華泰出版社,2003。
[4] XML, http://www.w3.org/XML.
[5] Bergholz A., “Extrending Your Markup: An XML Tutorial”, IEEE
Internet Computing, Vol 4, No.4, pp.74-79, July-August 2000.
[6] XSLT, http://www.w3.org/TR/xslt.
[7] XQuery, http://www.w3.org/XML/Query.
[8] XML Schema, http://www.w3.org/XML/Schema.
[9] DOM, http://www.w3.org/DOM.
[10] Roy, J. and A. Rammanujan, “XML: Data’s Universal Language” ,
IEEE IT Professional, Vol.2 No.3, pp.32-36, May-June 2000.
[11] Jason McHugh, Serge Abiteboul, Roy Goldman, Dallan Quass and
Jennifer Widom, “Lore: A Database Management System for
Semistructured Data” , ACM SIGMOD Record Volume26, pp54-66,
1997.
[12] Roy Goldman, Jason McHugh and Jennifer Widom, “From
Semistructured Data to XML: Migrating the Lore Data Model and
Query Language”, WebDB99, pp25-30, 1999.
[13] Roy Goldman, Sudarshan Chawathe, Arturo Crespo and Jason
Mchugh, “A Standard Textual Interchange Format for the Object
Exchange Model”, Stanford university, 1996.
[14] Andreas Bauer, Gunnar Harde and Wolfgang Hümmer, “XCube – XML
For Data Warehouses” ,The 6th ACM international workshop on
Data warehousing and OLAP., pp.33-40, 2003.
[15] Laura Irina Rusu, Wenny Rahayu and David Taniar, “A
Methodoloogy for Building XML Data Warehouses”, International
Journal of Data Warehousing & Mining., pp.23-48, 2005.
[16] Laura Irina Rusu, Wenny Rahayu and David Taniar, “On Building
XML Data Warehouses”, IDEAL 2004., LNCS 3117, pp.3293-299, 2004.
[17] Andrew Nierman, Divesh Srivastava, H.V. Jagadish, Laks
Lakshmanan, shurug Al-Khalifa, Stelios Paparizos and Yuqing
Wu, “Grouping in XML” EDBT 2002 Workshops., LNCS 2409, pp.128-
147, 2002.
[18] Stelios Paparizos, Shurug AI-Khalifa, Adriane Chapman, H. V.
Jagadish, Laks V. S. Lakshmanan, Andrew Nierman, Jignesh M.
Patel, Divesh Srivastava, Nuwee Wiwatwattana, Yuging Wu and
Cong Yu, “TIMBER: A native system for querying XML”, ACM
SIGMOD., pp.672-672, 2003.
[19] Anand Rajaraman, Jeffrey D. Ullman and Venky
Harinarayan, “Implementing Data Cubes Efficiently”, SIGMOD
Record, 25:2, pp.205-227, 1996.
[20] 林志麟與邱承凡, “資料倉儲實體化視域選取之研究 – 以資料方體之建置為
例”,元智大學,資訊研究所碩士論文,2000.
[21] 陳耀輝與劉宇昌,“在資料倉儲中針對查詢選擇實體化視域之研究”,屏東技術學
院,資訊管理技術研究所碩士論文,1997。
[22] Amit Shukla, Jeffrey F. Naughton, Karthikeyan Ramasamy, Kristin
Tufte, Prasad Deshpande and Yihong Zhao, “Cubing Algorithms,
Storage Estimation, and Storage and Processing Alternatives for
OLAP”, IEEE Data Eng.Bull.20(1). pp.3-11.,1997.
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