Optimizer Cost Estimation Framework and Implementation for Spatially-Enabled Database

Query optimizer is critical component in spatially enabled databases.Processing complex spatial and non-spatial queries in seamless fashion is responsiple.However,the lack of spatial statistics and spatial operators limits the accuracy of cost derivation and the generation of optimal query execution plan.We propose an integrated cost evaluation framework in optimizer.Based on the important keys of each node and the characteristic of pipeline,the cost of query execution plan is derived bottom-up.An improved cumulative density histogram is introduced to describe the distribution of spatial data,and is implemented as a module in database server through extensible server-side programming interface.Optimizer uses these statistics to improve the accuracy of cardinality estimation.The experiments illustrate that the cost evaluation framework can correctly and efficiently evaluate different execution plans.The results of different hybrid query statements show the positive correlation between estimated cost and actual cost.