Accurate estimation of the cost of spatial selections

Ashraf Aboulnaga, Jeffrey F. Naughton

Research output: Contribution to conferencePaper

Abstract

Optimizing queries that involve operations on spatial data requires estimating the selectivity and cost of these operations. In this paper, we focus on estimating the cost of spatial selections, or window queries, where the query windows and data objects are general polygons. Cost estimation techniques previously proposed in the literature only handle rectangular query windows over rectangular data objects, thus ignoring the very significant cost of exact geometry, comparison (the refinement step in a `filter and refine' query processing strategy). The cost of the exact geometry comparison depends on the selectivity of the filtering step and the average number of vertices in the candidate objects identified by this step. In this paper, we introduce a new type of histogram for spatial data that captures the complexity and size of the spatial objects as well as their location. Capturing these attributes makes this type of histogram useful for accurate estimation, as we experimentally demonstrate. We also investigate sampling-based estimation approaches. Sampling can yield better selectivity estimates than histograms for polygon data, but at the high cost of performing exact geometry comparisons for all the sampled objects.

Original languageEnglish
Pages123-134
Number of pages12
Publication statusPublished - 1 Jan 2000
Event2000 IEEE 16th International Conference on Data Engineering (ICDE'00) - San Diego, CA, USA
Duration: 29 Feb 20003 Mar 2000

Other

Other2000 IEEE 16th International Conference on Data Engineering (ICDE'00)
CitySan Diego, CA, USA
Period29/2/003/3/00

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ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

Cite this

Aboulnaga, A., & Naughton, J. F. (2000). Accurate estimation of the cost of spatial selections. 123-134. Paper presented at 2000 IEEE 16th International Conference on Data Engineering (ICDE'00), San Diego, CA, USA, .