3 papers
cs.DB2026
Can Large Language Models be a Cardinality Estimator? An Empirical study
Liangzu Liu, Yiyan Wang, Yinjun Wu +8
Cardinality estimation (CardEst) still remains a challenging problem for DBMS. Recent years have witnessed the success of ML-based cardinality estimators in outperforming tradition…
cs.DB2025
Data-Agnostic Cardinality Learning from Imperfect Workloads
Peizhi Wu, Rong Kang, Tieying Zhang +3
Cardinality estimation (CardEst) is a critical aspect of query optimization. Traditionally, it leverages statistics built directly over the data. However, organizational policies (…
stat.ML2025
A Practical Theory of Generalization in Selectivity Learning
Peizhi Wu, Haoshu Xu, Ryan Marcus +1
Query-driven machine learning models have emerged as a promising estimation technique for query selectivities. Yet, surprisingly little is known about the efficacy of these techniq…