Abstract
The accuracy of selectivity estimation is of vital importance to create good query plans in database management systems. We propose MOSE, a learning-based MOnotonic Selectivity Estimator, to provide accurate, reliable, and efficient selectivity estimation for query optimization.
Type
Publication
In 2022 IEEE 38th International Conference on Data Engineering (Poster Track)
Luming Sun
Senior R&D Engineer
My research interests include AI4Sys, AI4DB (especially Query Optimization).