A tunable class hierarchy index for object-oriented databases using a multidimensional index structure

Abstract

This paper presents a tunable two-dimensional class hierarchy indexing technique (2D-CHI) for object-oriented databases. We use a two-dimensional file organization as the index structure. 2D-CHI deals with the problem of clustering objects in a two-dimensional domain space consisting of the key attribute domain and the class identifier domain. In conventional class indexing techniques using one-dimensional index structures such as the B +-tree, the clustering property is owned exclusively by one attribute. These indexing techniques do not handle the queries that address both the attribute keys and the class identifiers efficiently. 2D-CHI enhances query performance by adjusting the degree of clustering between the key value domain and the class identifier domain based on the precollected usage pattern. For performance evaluation, we first compare 2D-CHI with the conventional class indexing techniques using an analytic cost model based on the assumption of uniform object distribution, and then, verify the cost model through experiments using the multilevel grid file as the two-dimensional index. We further perform experiments with nonuniform object distributions. The experiments show that our proposed method builds optimal class index structures in terms of the total number of page accesses for given the precollected usage pattern regardless of query types and object distributions.