Cost-driven storage schema selection for XML

Various models and approaches have been proposed for mapping XML data into relational tables recently. Most of those approaches produce relational schema for given XML data, based on pre-defined rules, heuristics, and user specifications, without considering workload As the result, the schema obtained is often not optimal with respect to query performance. In this paper, we present a cost-driven approach to generate a near-optimal relational schema fir a given XML data and expected workload, in the presence of space constraint. An efficient heuristic algorithm based on Hill Climbing is proposed together with a set of state transformation operations. Experimental study using the prototype system implementing the proposed algorithm, indicates that the produced schema can provide better performance than those well-known mapping approaches published in the literature.