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Title: View selection using randomized search
Authors: Kalnis, Panagiotis
Mamoulis, Nikos
Papadias, Dimitris
Keywords: View selection
Data warehouse
Issue Date: 2002
Citation: Data and knowledge engineering, v. 42, no. 1, 2002, p. 89-111
Abstract: An important issue in data warehouse development is the selection of a set of views to materialize in order to accelerate OLAP queries, given certain space and maintenance time constraints. Existing methods provide good results but their high execution cost limits their applicability for large problems. In this paper, we explore the application of randomized, local search algorithms to the view selection problem. The efficiency of the proposed techniques is evaluated using synthetic datasets, which cover a wide range of data and query distributions. The results show that randomized search methods provide near-optimal solutions in limited time, being robust to data and query skew. Furthermore, they can be easily adapted for various versions of the problem, including the simultaneous existence of size and time constraints, and view selection in dynamic environments. The proposed heuristics scale well with the problem size, and are therefore particularly useful for real life warehouses, which need to be analyzed by numerous business perspectives.
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