Bloom Histogram: Path Selectivity Estimation for XML Data with Updates

Cost-based XML query optimization calls for accurate estimation of the selectivity of path expressions. Some other interactive and internet applications can also benefit from such estimations. While there are a number of estimation techniques proposed in the literature, almost none of them has any guarantee on the estimation accuracy within a given space limit. In addition, most of them assume that the XML data are more or less static, i.e., with few updates. In this paper, we present a framework for XML path selectivity estimation in a dynamic context. Specifically, we propose a novel data structure, bloom histogram, to approximate XML path frequency distribution within a small space budget and to estimate the path selectivity accurately with the bloom histogram. We obtain the upper bound of its estimation error and discuss the trade-offs between the accuracy and the space limit. To support updates of bloom histograms efficiently when underlying XML data change, a dynamic summary ...

• Type: Conference
• Year: 2004
• Where: VLDB
• Authors: Wei Wang 0011, Haifeng Jiang, Hongjun Lu, Jeffrey Xu Yu
• Keywords: Bloom Histograms, Database, Estimation, VLDB 2004, XML Path