On the Interdependencies between Record Structure and Access Path Design
研究了数据库中记录结构与访问路径之间的相互依赖关系，提出了一种联合设计方法，扩展了现有数据库设计系统，支持冗余数据存储、多文件组织设计和性能约束。
Abstract:The physical organization of data within a database has two major components: record structures and access paths. Record structures specify the grouping of data items into data records that are physically stored and accessed together. Access paths specify the algorithms and system data used to determine the physical location of data records and to efficiently support content-dependent searching. Choosing efficient record structures and access paths is complicated by the fact that they are interdependent. This paper formalizes these interdependencies and proposes an approach to solving the combined record structure-access path design problem. This work extends an existing database design system in four ways: (1) record segmentation is extended to include redundantly stored data in any number of independently processed segments; (2) dependent access paths are added allowing us to design multiple, interrelated file organizations at the same time; (3) new methods are proposed to assist in the generation of potentially useful record structures; and (4) inter-file organization performance constraints can be specified.Key Words and Phrases: Record segmentationaccess pathsphysical database design Additional informationNotes on contributorsSalvatore T. MarchSalvatore T. March is an Associate Professor of Management Information Systems (mis) in the Management Sciences Department of the University of Minnesota. He received his B.S., M.S., and Ph.D. degrees in Operations Research from Cornell University. Dr. March is active in teaching, research, and consulting in the area of database design. He has published widely in the database literature including such journals as ACM Transactions on Database Systems, ACM Computing Surveys, Information and Management, and Management Science. He is currently the Editor-in-Chief of ACM Computing Surveys.John V. CarlisJohn V. Carlis is Associate Professor of Computer Science at the University of Minnesota. His research interests include physical database design, conceptual data modeling, and extending of query languages. He is a member of ACM and IEEE.