R-trees,9781852339777

R-trees

by ; ; ;
ISBN13: 9781852339777
ISBN10: 1852339772
Format: Hardcover
Pub. Date: 2005-11-30
Publisher(s): Springer-Verlag New York Inc
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Summary

Space support in databases poses new challenges in every part of a database management system & the capability of spatial support in the physical layer is considered very important. This has led to the design of spatial access methods to enable the effective & efficient management of spatial objects. R-trees have a simplicity of structure & together with their resemblance to the B-tree, allow developers to incorporate them easily into existing database management systems for the support of spatial query processing. This book provides an extensive survey of the R-tree evolution, studying the applicability of the structure & its variations to efficient query processing, accurate proposed cost models, & implementation issues like concurrency control and parallelism. Written for database researchers, designers & programmers as well as graduate students, this comprehensive monograph will be a welcome addition to the field.

Table of Contents

Preface vii
List of Figures
xv
List of Tables
xix
Part I. FUNDAMENTAL CONCEPTS
Introduction
3(12)
The Original R-tree
7(6)
Summary
13(2)
Dynamic Versions of R-trees
15(20)
The R+-tree
15(3)
The R*-tree
18(2)
The Hilbert R-tree
20(2)
Linear Node Splitting
22(2)
Optimal Node Splitting
24(1)
Branch Grafting
25(2)
Compact R-trees
27(1)
cR-trees
27(2)
Deviating Variations
29(5)
PR-trees
30(1)
LR-trees
31(3)
Summary
34(1)
Static Versions of R-trees
35(16)
The Packed R-tree
35(1)
The Hilbert Packed R-tree
36(1)
The STR R-tree
37(1)
Top-Down Packing Techniques
38(2)
Small-Tree-Large-Tree and GBI
40(2)
Bulk Insertion by Seeded Clustering
42(2)
The Buffer R-tree
44(1)
R-tree with Low Stabbing Number
45(1)
Merging R-trees
45(2)
Summary
47(4)
Part II. QUERY PROCESSING ISSUES
Fundamental Query Processing Techniques
51(18)
Two-step Processing
51(2)
Range and Topological Queries
53(2)
Nearest-Neighbor Queries
55(7)
A Branch-and-Bound Algorithm
56(2)
An Improvement to the Original Algorithm
58(1)
Incremental Nearest-Neighbor Searching
59(2)
Comparison of Nearest Neighbor Algorithms
61(1)
Spatial Join Queries
62(6)
Algorithm Based on Depth-First Traversal
62(3)
Algorithm Based on Breadth-First Traversal
65(2)
Join Between an R-tree-Indexed and a Non-Indexed Dataset
67(1)
Summary
68(1)
Processing More Complex Queries
69(30)
Categorical Range Queries
69(3)
Reverse and Constrained Nearest-Neighbor Queries
72(5)
Reverse Nearest Neighbors
72(3)
Generalized Constrained Nearest Neighbor Searching
75(2)
Multi-way Spatial Join Queries
77(3)
Incremental Distance-Join and Closest-Pair Queries
80(5)
Incremental Distance Join
80(3)
Distance Semi-Join Query
83(1)
Finding Closest Pairs
83(2)
All Nearest-Neighbor Queries
85(2)
Approximate Query Processing on R-trees
87(6)
Classification of R-tree-Based Query Processing Algorithms
93(1)
Summary
94(5)
Part III. R-TREES IN MODERN APPLICATIONS
R-trees in Spatiotemporal Databases
99(18)
Preliminaries
99(2)
The RT-tree
101(1)
The 3D R-tree
101(1)
The 2+3 R-tree
102(1)
The Historical R-tree
103(1)
The RST -tree
104(1)
The Partially Persistent R-tree
105(1)
The MV3R-tree
106(2)
The TB-tree
108(1)
Scalable and Efficient Trajectory Index (SETI)
109(1)
The Q+R-tree
110(1)
The FNR-tree and the MON-tree
111(1)
The Time-Parameterized R-tree
112(2)
The VCI R-tree
114(1)
Summary
115(2)
R-trees for Multimedia, Warehousing and Mining
117(16)
R-trees in Multimedia Databases
117(9)
Generic Multimedia Indexing (GEMINI)
117(4)
High-Dimensional Access Methods
121(4)
R-trees and Hidden Markov Models in Music Retrieval
125(1)
R-trees and Self-Organizing Maps
126(1)
R-trees in Data Warehousing and Data Mining
126(4)
Summary
130(3)
Part IV. ADVANCED ISSUES
Query Optimization Issues
133(18)
Selectivity and Cost Models for Selection Queries
133(9)
Formulae for Range Queries
133(7)
Formulae for Nearest-Neighbor Queries
140(2)
Selectivity and Cost Models for Join Queries
142(5)
Formulae for Pair-Wise Joins
142(2)
Formulae for Multiway Joins
144(2)
Formulae for Distance-Join Queries
146(1)
Spatiotemporal Query Optimization
147(2)
Sampling and Histogram-Based Techniques
149(1)
Summary
150(1)
Implementation Issues
151(22)
Parallel Systems
151(8)
Multidisk Systems
152(4)
Multiprocessor Systems
156(3)
Concurrency Control
159(3)
R-link Method
160(1)
Top-down Approaches
161(1)
Issues in Relational Implementations
162(9)
Stochastic Driven Relational R-trees
162(2)
Lazy Deletion Methods
164(1)
R-trees in Research Prototypes
165(4)
R-trees in Commercial Database Systems
169(2)
Summary
171(2)
Epilogue 173(2)
References 175(16)
Index 191

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