Research On Selectivity Estimation Method In Spatial Database

Spatial query and optimization are difficult points and breakthrough of the related technologies in spatial database, the technology of selectivity estimation has become a hot subject of spatial query and optimization. Now, the technology of selectivity estimation is still at the initial stage, and the technical aspects are not mature, which still has some shortcomings. In this paper, the technologies of selectivity estimation are analyzed synthetically, and some new selectivity estimation methods are proposed based on these, the material contents are as follows.Firstly, using the MBR buffer area and line segment buffer area of spatial object, according to the data set's characteristic in spatial join and distributed law of characteristic data, line segment buffer area, key point and point buffer area definition is given. putting forward a selectivity estimation method based on line segment buffer area and point buffer area, which are used in spatial join selectivity estimation of line segment set,and can use in estimation of characteristic line segment set by rebuilding the point buffer area.Secondly, the technology of window quert selectivity estimation about moving objects is studied. The definitions of spatial density, spatial skew and bucket are presented, and then putting forward a selectivity estimation method by dividing the bucket generated by space partition into some layers,and extend the method to selectivity estimation of multi-dimensional spaces.Finally, the algorithms in this paper are validated. By analying the results,we found that the selectivity estimation method based on point buffer area can be good in use of the spatial join selectivity estimation of characteristic line segment set.The selectivity estimation method through dividing the bucket into layers can decrease the relative error clearly whenmoving objects's window query is estimating.