NDLI: Grid based methods for estimating spatial join selectivity

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Grid based methods for estimating spatial join selectivity

Content Provider	ACM Digital Library
Author	Nucita, A. Bertino, E. Belussi, A.
Abstract	Spatial join is a fundamental operation for many spatial queries in Geographical Information Systems (GIS). Therefore, the query optimizer of a GIS needs to evaluate the selectivity of spatial joins, in order to find the best execution plan for a given query. This situation has made it necessary to find good and efficient estimators for spatial join selectivity. In particular, spatial join estimation with respect to sets of rectangles is necessary. Indeed, in GIS sets of rectangles are generated in order to produce a synthetic representation of real geometric values through the Minimum Bounding Rectangles (MBR). Several methods for this estimation have been proposed in literature. One of the best methods is based on precalculated histograms, that describe the distribution of rectangles in the reference space using grid based data structures. The size of an histogram for a given dataset can be comparable to the size of the R-tree built on the same dataset [4]. In this paper we present a new technique for estimating spatial join selectivity considering sets of rectangles as datasets. In particular, we propose a technique that is independent of the distribution of the rectangles in the reference space and produces an auxiliary structure which is an order of magnitude smaller than the corresponding histogram. Indeed, the proposed technique is based on very few statistical parameters and on a unique grid shared by all datasets.
Starting Page	92
Ending Page	100
Page Count	9
File Format	PDF
ISBN	1581139799
DOI	10.1145/1032222.1032238
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2004-11-12
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Gis Spatial join Query optimization
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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