Managing intervals efficiently in object-relational databases

Abstract

Modern database applications show a growing demand for efficient and dynamic management of intervals, particularly for temporal and spatial data or for constraint handling. Common approaches require the augmentation of index structures which, however, is not supported by existing relational database systems. By design, the new Relational Interval Tree' (RI-tree) employs built-in indexes on an as-they-are basis and is easy to implement. Whereas the functionality and efficiency of the RI-tree is supported by any off-the-shelf relational DBMS, it is perfectly encapsulated by the object-relational data model. The RI-tree requires O(n/b) disk blocks of size b to store n intervals, O(logn) 110 operations for insertion or deletion, and O(h . logan + rib) I/Os for an intersection query producing r results. The height h of the virtual backbone tree corresponds to the current expansion and granularity of the data space but does not depend on n. As demonstrated by our experimental evaluation on an Oracle8i server, competing dynamic interval access methods axe outperformed by factors of up to 42 for disk accesses and 4.9 for query response time.