A Study on Join Processing Techniques in Spatial Databases

Query processing is an essential task to obtain meaningful information in a data mining application. It needs to be optimized for its effective implementation in any application. A join operation of relational data base management system is one such technique that can optimize the query process efficiently. In a similar manner the join operation in a spatial data base management system can be utilized to optimize the query process. Join operation itself is accelerated by the implementation of join indexes further optimizing the query process. Efficient implementation of join indices is possible with such multidimensional indexing structures as R-trees, Grid files, Bi-partite graphs, Neighbourhood graphs, etc. An effective join processing algorithm in collusion with the join index enhances the query process further. A cost model with CPU cost, I/O cost, number of page and node accesses with a constraint of fixed buffer size has to be evaluated to check the feasibility of the join operation.