物件關連式資料倉儲實體設計與綱要分割之研究

Physical Design and Schema Partitioning of Object-Relational Data Warehouse

王志文(Chihwen Wang)

指導教授 ： 劉俞志

元智大學/資訊學院/資訊管理學系/碩士(2001年)

摘要

近來物件關連式資料倉儲的研究已成為重要議題，為了輔助資料倉儲的設計，不同的概念層模式已相繼地被提出，亦有學者特別探討如何將來源資料庫的概念層模式轉換成物件關連式資料倉儲概念層模式；然而，轉換後的模式通常相當複雜，使得即便藉此模式來設計實體表格也並非易事。另一方面，許多分割技術已被用來改善查詢的效能，但這些技術並非針對物件而設計，因而無法直接應用在物件關連式資料倉儲上。
本研究的目的主要有兩項，第一，提出一自動對映演算法將物件關連式資料倉儲的概念層模式EDF model轉換為表格綱要，並探討如何修正轉換後的表格以符合物件關連式的特性，第二，提出一物件關連式資料倉儲的分割演算法，藉由水平分割技術，以減少磁碟的存取次數，加速查詢回應。

關鍵字

物件關連式資料倉儲 ； 概念層設計 ； 實體研究 ； 切割演算法

並列摘要

Object-relational data warehouse have gained much attention lately. Various conceptual models have been proposed in the past few decades to assist the design of data warehouses. One research specifically deals with the issue of transforming the conceptual model of the source databases into the conceptual model of an object-relational data warehouse. The resulting model, however, is usually quite complex, making it very difficult to use the model in designing the physical tables. Another issue worthy attention is that, many partitioning techniques have been proposed to improve the query performance, but those techniques are not design to work with objects. As a result, those partitioning techniques cannot be applied to object-relational data warehouse directly.
The objective of this research is twofold. First, we propose an auto-mapping algorithm to translate the EDF model (i.e., the conceptual model of a data warehouse) into tables. We also study how to modify the resulting tables in order to satisfy the object relational properties. Second, we propose a partitioning algorithm for object-relational data warehouse to reduce the disk access times based on the horizontal partitioning method.

並列關鍵字

object-relational data warehouse ； conceptual design ； physical design ； partitioning algorithm

參考文獻

[27]邱承凡，林志麟，”資料倉儲實體化視域選取之研究”，第十一屆全國資訊管理學術研討會，2000.

[1]M. Golfarelli and S. Rizzi. “Designing the data warehouse: key steps and crucial issues”, Journal of Computer Science and Information Management, vol. 2, n. 3, 1999.

[2]M. Golfarelli, D. Maio, and S. Rizzi, “The Dimensional Fact Model: A Conceptual Model for Data Warehouses”, International Journal of Cooperative Information Systems, vol. 7, n.2ſ, pp.215-247, 1998.

[5]Lars Baekgaard, “Event-Entity-Relationship Modeling In Data Warehouse Environments”, DOLAP, 1999.

[7]M. T. Özsu and J. Valduriez, Principles of Distributed Database Systems, Prentice Hall, 1991.