Spatial query processing in an object-oriented database system
SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
ACM Transactions on Database Systems (TODS)
EDBT '90 Proceedings of the 2nd international conference on extending database technology: Advances in Database Technology
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SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Rule-based optimization and query processing in an extensible geometric database system
ACM Transactions on Database Systems (TODS)
Efficient processing of spatial joins using R-trees
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Spatial data models and query processing
Modern database systems
Database Systems Concepts
Extending a DBMS for Geographic Applications
Proceedings of the Fifth International Conference on Data Engineering
Spatial Joins Using R-trees: Breadth-First Traversal with Global Optimizations
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Optimization for Spatial Query Processing
VLDB '91 Proceedings of the 17th International Conference on Very Large Data Bases
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Proceedings of the Fifth International Conference on Database Systems for Advanced Applications (DASFAA)
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IBM Systems Journal
ACM Transactions on Database Systems (TODS)
Heuristic approach for early separated filter and refinement strategy in spatial query optimization
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Multi-way Spatial Joins Using R-Trees: Methodology and Performance Evaluation
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
ACM Transactions on Database Systems (TODS)
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The spatial query has been processed in two steps, the filter step and the refinement step, due to a large volume and high complexity of the spatial data. However, this approach has been considered only in the query execution phase after completing the query optimization phase. This paper presents query optimization strategies which take the characteristics of spatial databases into account. The first strategy is the separation of filter and refinement steps not in the query execution phase but in the query optimization phase.As the second strategy, several refinement operations can be combined in processing a complex query, and as the third strategy several filter operations can also be combined. We call the optimization technique utilizing these strategies the Early Separated Filter And Refinement (ESFAR). This paper also presents a rule-based optimization technique for ESFAR.