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
Efficient processing of spatial joins using R-trees
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Partition based spatial-merge join
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Database System Concepts
A Robust and Self-tuning Page-Replacement Strategy for Spatial Database Systems
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Scalable Sweeping-Based Spatial Join
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Data Redundancy and Duplicate Detection in Spatial Join Processing
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
ACM Transactions on Database Systems (TODS)
Query optimizer for spatial join operations
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
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In this paper, a new algorithm for spatial join operations is introduced. The so-called NRQB (No Replication with Quadtrees and Buckets Spatial Merge Join) enhances the original PBSM by partitioning the space according to the spatial distribution of the objects. In addition, a hash file is created for each input data set and used to enhance both the storage of and the access to the minimum bounding rectangles (MBR) of the respective set elements. The paper also presents a performance evaluation of the proposed algorithm relying on the results obtained by the execution of a series of test cases concerning different spatial join scenarios. In each test case, the response time of NRQB is compared with that of some well-known algorithms. The test cases were conducted with both synthetic and real data sets. The results showed that the new algorithm is best suited for smaller buffer sizes, which are typical of mobile devices and database systems for desktop computers.