由於資訊技術的進步神速，近年來對於資料庫系統資料處理效率而言，無論在處 理計算速度、記憶體存取速度及容量均已有相當大的改善，而今資料處理效率的瓶頸 乃在於資料從儲存設備存取至記憶體之速度。為此，本文探討一個提高效率的方法， 以多磁碟資料庫系統之表格配置模式，提高資料平行處理的效率，進而縮短資料查詢 等待存取的時間，增進資料庫系統整體運作的效能。過去諸多資料配置文獻都以研究 演算方法為主，唯探討的表格樣本數量都很少，而且需透過資料庫管理人員針對資料 彼此間關聯性來分析及演譯，而一般企業ERP資料庫内含的表格數量相當多，且表格 之間關聯性複雜，難以透過人員來詳細分析。因此，為了解決此複雜問題，本文引用 資料探勘（datamining)的觀念，透過表格擷取記錄，從中探勘表格之間的關聯性， 進而應用關聯演算法來規劃較隹之表格配置方式。

Due to the continuous innovations of information technology, the improvement of computation speed and storage capacity for database systems is impressively significant. The vital bottleneck is currently on the process of accessing data from hard disk to memory. Therefore, a highly efficient way of accessing approach in dealing with the space allocation problem for multi-disk database systems to enhance the effectiveness of parallel processing in order for reducing the time for querying useful data and leveraging the value for operating the holistic system. A vast amount of literature focused on developing the algorithms for impro-ving such a problem, yet these algorithms failed to manipulate enough data for convincing discussions, and the intervention of operators for analyzing associations among data is usually necessary but impractically executable. In this paper, a conceptual idea of data mining is employed to analyzing the triggered records from database systems for associations among data, and thus an as sociation algorithm is developed to derive the optimal space allocation for multi-disk database systems.