Xiaoying Wang
2 Papers
2 Citations
Xiaoying Wang is an academic researcher. The author has contributed to research in topics: Query optimization & Cardinality (SQL statements). The author has an hindex of 2, co-authored 2 publications.
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Papers
Are We Ready For Learned Cardinality Estimation
TL;DR: This study compares five new learned methods with eight traditional methods on four real-world datasets under a unified workload setting and shows that learned models are indeed more accurate than traditional methods, but they often suffer from high training and inference costs.
•Proceedings Article
Are We Ready For Learned Cardinality Estimation
Xiaoying Wang,Changbo Qu,Weiyuan Wu,Jiannan Wang,Qingqing Zhou +4 more
- 01 Jan 2020
TL;DR: In this article, the authors compare five learned methods with eight traditional methods on four real-world datasets under a unified workload setting and find that learned models are indeed more accurate than traditional methods, but they often suffer from high training and inference costs.