Query Estimation By Adaptive Sampling

The ability to provide accurate and efficient result estimations of user queriesis very important for the query optimizer in database systems.In this paper, we show that the traditional estimation techniques with data reductionpoints of view do not produce satisfiable estimation results ifthe query patterns are dynamically changing.We further show that to reduce query estimation error, instead ofaccurately capturing the data distribution, it is moreeffective to capture the user query patterns.In this paper, we propose query estimation techniques that canadapt to user query patterns for more accurateestimates of the size of selection or range queriesover databases.