Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts

Summary: Warper accelerates adaptation of learned cardinality estimators to data/workload drift by generating a small query set and guiding updates. Works for single-table and join predicates; fast, low-cost adaptation reduces optimizer misestimation. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: h71b08cc4b3c44135
Venue: SIGMOD
Year: 2022
Pagerank: 6.5320994e-05
Overall Rank: 4,563 | 69.33%
DOI: 10.1145/3514221.3526179

Incoming Non-self Citations Over Time

Authors

1. Beibin Li (Microsoft; University of Washington)
2. Yao Lu (Microsoft)
3. Srikanth Kandula (Microsoft)

BibTeX Citation

@inproceedings{li_sigmod22,
        title = {{Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts}},
        author = {Li, Beibin and Lu, Yao and Kandula, Srikanth},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3526179},
        url = {https://dl.acm.org/doi/10.1145/3514221.3526179},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 17 of 17 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,327	Robust Query Driven Cardinality Estimation under Changing Workloads	2023	VLDB	7.4207879e-05
5,456	Eraser: Eliminating Performance Regression on Learned Query Optimizer	2024	VLDB	6.1239873e-05
5,865	Modeling Shifting Workloads for Learned Database Systems	2024	SIGMOD	5.9659203e-05
6,105	Breaking It Down: An In-depth Study of Index Advisors	2024	VLDB	5.8860941e-05
6,818	ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation	2024	SIGMOD	5.672718e-05
8,385	NeurDB: On the Design and Implementation of an AI-powered Autonomous Database	2025	CIDR	5.3420959e-05
8,800	PACE: Poisoning Attacks on Learned Cardinality Estimation	2024	SIGMOD	5.2742531e-05
8,947	Machine Unlearning in Learned Databases: An Experimental Analysis	2024	SIGMOD	5.2532248e-05
9,372	Efficient and Effective Cardinality Estimation for Skyline Family	2023	SIGMOD	5.1868213e-05
9,610	LIMAO: A Framework for Lifelong Modular Learned Query Optimization	2025	VLDB	5.1526493e-05
10,290	This is Going to Sound Crazy, But What If We Used Large Language Models to Boost Automatic Database Tuning Algorithms By Leveraging Prior History? We Will Find Better Configurations More Quickly Than Retraining From Scratch!	2026	SIGMOD	5.0431863e-05
10,412	Are Learned DBMS Components Robust to Workload Drift?: [Experiments & Analysis]	2026	SIGMOD	4.9793485e-05
10,627	CorrBound: Cardinality Estimation Accounting for Inter- and Intra-relation Correlations	2026	SIGMOD	4.9793485e-05
10,693	Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking	2026	SIGMOD	4.9793485e-05
10,751	Toward Drift-Aware Database Benchmarking	2026	VLDB	4.9793485e-05
10,802	BaCon: Efficient Batch Processing of Counting Queries	2026	VLDB	4.9793485e-05
10,924	TATA: An Efficient Framework for Task Transfer in Query Plan Representation	2026	VLDB	4.9793485e-05

Outgoing Citations (Sorted by Pagerank)

Showing 16 of 16 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
15	How Good Are Query Optimizers, Really?	2016	VLDB	0.00061066921
40	The Case for Learned Index Structures	2018	SIGMOD	0.00046284649
85	Learned Cardinalities: Estimating Correlated Joins with Deep Learning	2019	CIDR	0.00035864347
145	Neo: A Learned Query Optimizer	2019	VLDB	0.0002908188
272	An Overview of Query Optimization in Relational Systems	1998	PODS	0.00022509573
281	Accelerating Machine Learning Inference with Probabilistic Predicates	2018	SIGMOD	0.00022295232
286	Selectivity Estimation using Probabilistic Models	2001	SIGMOD	0.0002211981
318	DeepDB: Learn from Data, not from Queries!	2020	VLDB	0.00021167555
371	STHoles: A Multidimensional Workload-Aware Histogram	2001	SIGMOD	0.00019829769
406	Deep Unsupervised Cardinality Estimation	2020	VLDB	0.00019045544
692	Selectivity Estimation for Range Predicates using Lightweight Models	2019	VLDB	0.00014741011
1,542	Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses	2018	VLDB	0.00010308631
2,275	Active Learning for ML Enhanced Database Systems	2020	SIGMOD	8.7090584e-05
3,210	Efficiently Approximating Selectivity Functions using Low Overhead Regression Models	2020	VLDB	7.5363533e-05
3,736	Snorkel: Fast Training Set Generation for Information Extraction	2017	SIGMOD	7.0642592e-05
4,329	Relational Data Synthesis using Generative Adversarial Networks: A Design Space Exploration	2020	VLDB	6.6597797e-05

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