A New Query Processing Optimization Algorithm Based on Statistic
Weili Wang · Computer and Modernization · 2006
Modern optimizers generally explore many alternative query plans in a cost-based manner.The cost estimation for a plan depends on several factors,among these factors,the intermediate-result size estimation is the main source of low efficiency during optimization.To address this limitation,this thesis introduces the concept of SPS,which are statistics built on query expressions. SP directly and accurately models intermediate results in a query execution plan,and therefore avoid error-prone simplifying assumptions during cardinality estimation.