A data warehouse stores materialized views derived from one or more sources for the purpose of efficiently implementing decision-support or OLAP queries. One of the most important decisions in designing a data warehouse is the selection of materialized views to be maintained at the warehouse. The goal is to select an appropriate set of views that minimizes total query response time and/or the cost of maintaining the selected views, given a limited amount of resource such as materialization time, storage space, or total view maintenance time. In this article, we develop algorithms to select a set of views to materialize in a data warehouse in order to minimize the total query response time under the constraint of a given total view maintenance time. As the above maintenance-cost view-selection problem is extremely intractable, we tackle some special cases and design approximation algorithms. First, we design an approximation greedy algorithm for the maintenance-cost view-selection problem in OR view graphs, which arise in many practical applications, e.g., data cubes. We prove that the query benefit of the solution delivered by the proposed greedy heuristic is within 63% of that of the optimal solution. Second, we also design an A~* heuristic, that delivers an optimal solution, for the general case of AND-OR view graphs. We implemented our algorithms and a performance study of the algorithms shows that the proposed greedy algorithm for OR view graphs almost always delivers an optimal solution.
展开▼
