Journal of Database Management, 20(4), 1-25, October-December 2009 1 Copyright © 2009, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Keywords: Cost Model, Query-Mapping, Query Processing, Relational Databases, Top-K Query, Tradeoff Analysis, Uncertainty Modeling INTrODuCTION Relational databases are increasingly being used to support a wide range of interactive applications that require efficient methods for exploratory search and retrieval (for example, search for airline tickets, hotel rooms, real estates, used cars). In such applications, us- ers specify target values for certain attributes without necessarily requiring exact matches to these values in return. However, relational queries normally establish rigid qualification to deal only with data that exactly match selection conditions (Motro, 1988). Due to the exactness in nature of relational databases and the query A Cost-Based range Estimation for Mapping Top-k Selection Queries over relational Databases Anteneh Ayanso, Brock University, Canada Paulo B. Goes, University of Arizona, USA Kumar Mehta, George Mason University, USA ABSTrACT Finding effcient methods for supporting top-k relational queries has received signifcant attention in academic research. One of the approaches in the recent literature is query-mapping, in which top-k queries are mapped (translated) into equivalent range queries that relational database systems (RDBMSs) normally support. This approach combines the advantage of simplicity as well as practicality by avoiding the need for modifcations to the query engine, or specialized data structures or indexing techniques to handle top-k queries separately. However, existing methods following this approach fall short of adequately modeling the problem environment and providing consistent results. In this article, the authors propose a cost-based range estimation model for the query-mapping approach. They provide a methodology for trading-off relevant query execution cost com- ponents and mapping a top-k query into a cost-optimal range query for effcient execution. Their experiments on real world and synthetic data sets show that the proposed strategy not only avoids the need to calibrate workloads on specifc database contents, but also performs at least as well as prior methods. DOI: 10.4018/jdm.2009062501 IGI PUBLISHING This paper appears in the publication, Journal of Database Management, Volume 20, Issue 4 edited by Keng Siau © 2009, IGI Global 701 E. Chocolate Avenue, Hershey PA 17033-1240, USA Tel: 717/533-8845; Fax 717/533-8661; URL-http://www.igi-global.com ITJ 5257