Efficient cost models for spatial queries using R-trees

Selection and join queries are fundamental operations in database management systems (DBMS). Support for nontraditional data, including spatial objects, in an efficient manner is of ongoing interest in database research. Toward this goal, access methods and cost models for spatial queries are necess...

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Vydáno v:IEEE transactions on knowledge and data engineering Ročník 12; číslo 1; s. 19 - 32
Hlavní autoři: Theodoridis, Y., Stefanakis, E., Sellis, T.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.01.2000
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Analytical models
Cost function
Data base management systems
Data structures
Design automation
Disks
Geographic Information Systems
Image databases
Mathematical analysis
Multidimensional systems
Multimedia databases
Nonuniform
Optimization
Queries
Query processing
Spatial databases
ISSN:1041-4347, 1558-2191
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Shrnutí:Selection and join queries are fundamental operations in database management systems (DBMS). Support for nontraditional data, including spatial objects, in an efficient manner is of ongoing interest in database research. Toward this goal, access methods and cost models for spatial queries are necessary tools for spatial query processing and optimization. We present analytical models that estimate the cost (in terms of node and disk accesses) of selection and join queries using R-tree-based structures. The proposed formulae need no knowledge of the underlying R-tree structure(s) and are applicable to uniform-like and nonuniform data distributions. In addition, experimental results are presented which show the accuracy of the analytical estimations when compared to actual runs on both synthetic and real data sets.
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ISSN:1041-4347
1558-2191
DOI:10.1109/69.842247