Research On Spatial Join Query Optimization Of Multi-WFSs Services

With the development of spatial information acquisition technology and the rapid increase of geographic information demand,the spatial database technology became more important.Spatial data exchange and integration is still a hot issue In many Geographic Information System(GIS)application domains.As one of the standards of Open Geospatial Consortium(OGC),Web Feature Service(WFS)is an important and promising standard for transferring spatial data over the Internet.In the distributed environment,because of the specificity of the environment,the complexity of spatial join operations and the restriction of network environment that produced the overheads for this spatial join query and the network data transmission costs.Which seriously affect the performance of multi-way spatial joins of WFSs,and restrict the development and application of distributed WFSs spatial query.The main content of this paper is how to reduce the operation cost and the network transmission cost,so as to improve the efficiency of multi-way spatial joins.The basis of multi-way spatial joins query is two-way join.The core problem is the estimation of selecting rate and filtering rate,and their precision will direct impact on the estimation of cost of spatial join query.At present,histogram method is one of the most commonly used to estimate the selecting rate.In spatial query join operations,there are three general situations where there is an index based on the spatial dataset that participates in the operation.As for non-indexed spatial datasets,it usually used the method of spatial partitioning to process.In this paper,improved the method of quad-tree histogram,and combined with the advantages of the DSJ(Distributed Spatial Join)strategy and the SQ(Structural Quad-tree)strategy that partitioning the query range into sub-areas and adaptively downloaded.The experimental results show that the estimation accuracy of the selection rate and the filtering rate is improved,and the response time of the spatial query operation is accelerated with the increase of the estimation accuracy.The key to solving the problem of multi-way spatial joins query efficiency is to choose a suitable execution plan for it.For multi-way spatial joins of WFSs,in this paper,an optimization strategy based on the highest filtering rate is proposed.The main idea of the strategy is to first execute the highest filtering rate of the join,and decomposed the query graph into a concatenation of multiple two WFSs spatial joins to find the best execution plan.This paper will take chain type with four-way spatial joins query diagram as an example to design experiment.The implementation process of the optimization strategy is described in detail,and compared with the direct download strategy and the sequential download strategy.The experimental results show that as the number of matched pairs increases,the overall execution time also increases,but the optimization effect is more obvious.That is only when the total number of spatial factors in the query area is greater than a certain amount the optimization strategy is more obvious.The experimental results of above three strategies are compared,and the results show that in most cases,the optimization strategy consumes the shortest download time,direct download strategy contrary.In the 75 test,the ratio of the optimization effect reached 88%.As a whole,the optimization strategy proposed in this paper that can improve the execution efficiency of multi-way spatial join queries in most cases.