The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Segment indexes: dynamic indexing techniques for multi-dimensional interval data
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
Towards an analysis of range query performance in spatial data structures
PODS '93 Proceedings of the twelfth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
CIKM '93 Proceedings of the second international conference on Information and knowledge management
Beyond uniformity and independence: analysis of R-trees using the concept of fractal dimension
PODS '94 Proceedings of the thirteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Window query-optimal clustering of spatial objects
PODS '95 Proceedings of the fourteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Are window queries representative for arbitrary range queries?
PODS '96 Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
On the analysis of indexing schemes
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
A lower bound theorem for indexing schemes and its application to multidimensional range queries
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Tight bounds for 2-dimensional indexing schemes
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
AMDB: an access method debugging tool
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Multidimensional access methods
ACM Computing Surveys (CSUR)
Benchmark Handbook: For Database and Transaction Processing Systems
Benchmark Handbook: For Database and Transaction Processing Systems
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
An Implementation and Performance Analysis of Spatial Data Access Methods
Proceedings of the Fifth International Conference on Data Engineering
Generalized Search Trees for Database Systems
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Estimating the Selectivity of Spatial Queries Using the `Correlation' Fractal Dimension
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
The hBP-tree: A Modified hB-tree Supporting Concurrency, Recovery and Node Consolidation
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Multidimensional Access Methods: Trees Have Grown Everywhere
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Benchmarking Spatial Joins À La Carte
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
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A large number of database index structures have been proposed over the last two decades, and little consensus has emerged regarding their relative effectiveness. In order to empirically evaluate these indexes, it is helpful to have methodologies for generating random queries for performance testing. In this paper we propose a domain-independent approach to the generation of random queries: choose randomly among all logically distinct queries. We investigate this idea in the context of range queries over 2-dimensional points. We present an algorithm that chooses randomly among logically distinct 2-d range queries. It has constant-time expected performance over uniformly distributed data, and exhibited good performance in experiments over a variety of real and synthetic data sets. We observe nonuniformities in the way randomly chosen logical 2-d range queries are distributed over a variety of spatial properties. This raises questions about the quality of the workloads generated from such queries. We contrast our approach with previous work that generates workloads of random spatial ranges, and we sketch directions for future work on the robust generation of workloads for studying index performance.