Indexing temporal data using existing B + -trees

Abstract

Research in temporal databases has largely focused on extensions of existing data models for the proper handling of temporal information. One approach is to store temporal data on existing DBMS and build some new indexes to provide support for the efficient retrieval of temporal data. This paper describes mapping strategies to linearize the data such that existing B +-trees can be used directly. With such an implementation, a temporal relation is mapped to points in a multi-dimensional space, with each time interval being translated to a two-dimensional coordinate, and a temporal selection operation is constructed as a spatial search operation. The proposed approach has two advantages. First, mapping a temporal relation to a multi-dimensional space provides a uniform framework for dealing with temporal queries involving transaction and valid time, as well as other non-temporal attributes. Second, linearization of the multi-dimensional search space allows classical indexing methods (such as the B +-tree) to be used; this means that index support for temporal selection can be accomplished without modification to the underlying storage components of the DBMS. Both analytical and simulation study show that the proposed indexing scheme is more efficient than the time index in both its disk utilization and access time.