Selectivity Estimation in Spatial Databases

Selectivity estimation of queries is an important and wellstudied problem in relational database systems. In this paper, we examine selectivity estimation in the context of Geographic Information Systems, which manage spatial data such as points, lines, poly-lines and polygons. In particular, we focus on point and range queries over two-dimensional rectangular data. We propose several techniques based on using spatial indices, histograms, binary space partitionings (BSPs), and the novel notion of spatial skew. Our techniques carefully partition the input rectangles into subsets and approximate each partition accurately. We present a detailed experimental study comparing the proposed techniques and the best known sampling and parametric techniques. We evaluate them using synthetic as well as real-life TIGER datasets. Based on our experiments, we identify a BSP based partitioning that we call Min-Skew which consistently provides the most accurate selectivity estimates for spatial querie...

• Type: Conference
• Year: 1999
• Where: SIGMOD
• Authors: Swarup Acharya, Viswanath Poosala, Sridhar Ramaswamy
• Keywords: Accurate Selectivity Estimates, Database, Selectivity Estimation, SIGMOD 1999, Spatial