MOSE: A Monotonic Selectivity Estimator Using Learned CDF (Extended abstract)
Luming Sun, Cuiping Li, Tao Ji, Hong Chen · 2022 IEEE 38th International Conference on Data Engineering (ICDE) · 2022
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.