Integrating the UB-tree into a database system kernel

Abstract

Multidimensional access methods have showa high potential for significant performance improvements in various application domains. However, only few approaches have made their way into commercial products. In convnercial database management systems (DBMS5) the B- Tree is still the prevalent indexing technique. Integrating new indexing methods into existing database kernels is in general a very complex and costly task. Exceptions exist, as our experience of integrating the UB-Tree into TransBase, a commercial DBMS, shows. The UB-Tree is a very promising multidimensional index, which has showa its superiority over traditional access methods in different scenarios, especially in OLAP applications. In this paper we discuss the major issues of a UB-Tree integration. As we will show, the complexity and cost of this task is reduced significantly due to the fact that the UBTree relies on the classical B-Tree. Even though commercial DBMSs provide interfaces for index extensions, we favor the kernel integration because of the tight coupling with the query opt imizer, which allows for optimal usage of the UBTree in execution plans. Measurements on a real-world data warehouse show that the kernel integration leads to an additional performance improvement compared to our prototype implementation and competing index methods.