Database optimizer extensions using preprocessing layer in temporal environment

Temporal databases forming intelligent information systems store wide range of data structures with significant data amount evolved over the time. In this paper, history of temporal models is described with regards on their usage a limitations. Performance is important part and main technology characteristics and must be handled with emphasis. Therefore, we propose two layers extending the optimizer evaluations by transforming the original user query. Preprocessing layer deals with undefined states as well as condition management of the query, which is transformed based on defined index structures and data dictionary statistics. The aim is to improve performance highlighting conversions and reducing condition evaluations. Therefore, index access paths are used, which are reflected also in the Experiment section of this paper.