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http://dx.doi.org/10.3745/KIPSTD.2004.11D.2.325

A Genetic Algorithm for Materialized View Selection in Data Warehouses  

Lee, Min-Soo (이화여자대학교 컴퓨터학과)
Publication Information
The KIPS Transactions:PartD / v.11D, no.2, 2004 , pp. 325-338 More about this Journal
Abstract
A data warehouse stores information that is collected from multiple, heterogeneous information sources for the purpose of complex querying and analysis. Information in the warehouse is typically stored In the form of materialized views, which represent pre-computed portions of frequently asked queries. One of the most important tasks of designing a warehouse is the selection of materialized views to be maintained in the warehouse. The goal is to select a set of views so that the total query response time over all queries can be minimized while a limited amount of time for maintaining the views is given(maintenance-cost view selection problem). In this paper, we propose an efficient solution to the maintenance-cost view selection problem using a genetic algorithm for computing a near-optimal set of views. Specifically, we explore the maintenance-cost view selection problem in the context of OR view graphs. We show that our approach represents a dramatic improvement in terms of time complexity over existing search-based approaches that use heuristics. Our analysis shows that the algorithm consistently yields a solution that only has an additional 10% of query cost of over the optimal query cost while at the same time exhibits an impressive performance of only a linear increase in execution time. We have implemented a prototype version of our algorithm that is used to evaluate our approach.
Keywords
Data Warehouse; Genetic Algorithm; View Maintenance; View Materialization; View Selection; Warehouse Configuration;
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