On the propagation of errors in the size of join results
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
Selectivity estimation in spatial databases
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Cost Models for Join Queries in Spatial Databases
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
A Cost Model for Estimating the Performance of Spatial Joins Using R-trees
SSDBM '97 Proceedings of the Ninth International Conference on Scientific and Statistical Database Management
Multi-way Spatial Joins Using R-Trees: Methodology and Performance Evaluation
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
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In a real life environment, spatial data is highly skewed. In general, there are two kinds of skews in spatial data. One is the placement skew and the other is the area skew. This paper introduces methods and the characteristics of estimating the accurate result sizes of the multiway join for the area skewed spatial data. Especially, this paper describes the number and sort of the statistics which the optimizer should keep in order to calculate the multi-way join result size. Experimental results show our approach generally provides accurate estimation for the multi-way join for the area skewed spatial data.