SHB+-Tree: A Segmentation Hybrid Index Structure for Temporal Data

Abstract

Temporal index provide an important way to accelerate query performance in temporal database. However, the current temporal index can not support the variety of queries very well, and it is hard to take account of both the efficiency of query execution and the index construction as well as maintenance. This paper propose a novel segmentation hybrid index SHB+-Tree for temporal data. First the temporal data in temporal table deposited is separated to fragments according to the time order. In each segment, the hybrid index is constructed which is a combination of temporal index and object index, and the temporal data is shared by them. By employing the segmented storage strategy and bottom-up index construction approaches for every part of the hybrid index, it greatly improves the performance of construction and maintenance. The experimental results on benchmark data set verify the effectiveness and efficiency of the proposed method.