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http://dx.doi.org/10.3745/KIPSTD.2004.11D.2.281

Selectivity Estimation Using Compressed Spatial Histogram  

Chi, Jeong-Hee (충북대학교 대학원 전자계산학)
Lee, Jin-Yul (포인트 아이)
Kim, Sang-Ho (충북대학교 대학원 전자계산학)
Ryu, Keun-Ho (충북대학교 전기전자 및 컴퓨터공학부)
Publication Information
The KIPS Transactions:PartD / v.11D, no.2, 2004 , pp. 281-292 More about this Journal
Abstract
Selectivity estimation for spatial query is very important process used in finding the most efficient execution plan. Many works have been performed to estimate accurate selectivity. Although they deal with some problems such as false-count, multi-count, they can not get such effects in little memory space. Therefore, we propose a new technique called MW Histogram which is able to compress summary data and get reasonable results and has a flexible structure to react dynamic update. Our method is based on two techniques : (a) MinSkew partitioning algorithm which deal with skewed spatial datasets efficiently (b) Wavelet transformation which compression effect is proven. The experimental results showed that the MW Histogram which the buckets and wavelet coefficients ratio is 0.3 is lower relative error than MinSkew Histogram about 5%-20% queries, demonstrates that MW histogram gets a good selectivity in little memory.
Keywords
Query Processing; Selectivity Estimation; Compression; Spatial Histogram; Wavelet;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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