Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload

Summary: Divo tackles LQO brittleness on highly diverse workloads via template-evolving query generation, a two-phase training pipeline with 100K+ static plan experiences, and a diversity-aware probabilistic loss. The result is a more stable optimizer on PostgreSQL mixed workloads, yielding 1.3x over PG and far outperforming prior LQOs. (summarized by gpt-5-mini on Apr 11 2026)

Paper ID: he656cb5c9108f166
Venue: SIGMOD
Year: 2026
Pagerank: 4.9793485e-05
Overall Rank: 10,633 | 28.51%
DOI: 10.1145/3786641

Incoming Non-self Citations Over Time

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Authors

1. Tianyi Chen (Peking University)
2. Jun Gao (Peking University)
3. Yaofeng Tu (ZTE Corporation)
4. Yang Lin (ZTE Corporation)
5. Mo Xu (ZTE Corporation)
6. Yinjun Han (ZTE Corporation)

BibTeX Citation

@inproceedings{chen_sigmod26,
        title = {{Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload}},
        author = {Chen, Tianyi and Gao, Jun and Tu, Yaofeng and Lin, Yang and Xu, Mo and Han, Yinjun},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3786641},
        url = {https://dl.acm.org/doi/10.1145/3786641},
        year = {2026}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 19 of 19 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
145	Neo: A Learned Query Optimizer	2019	VLDB	0.0002908188
362	Bao: Making Learned Query Optimization Practical	2021	SIGMOD	0.00019989474
383	Massive Stochastic Testing of SQL	1998	VLDB	0.00019484034
437	QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning	2019	VLDB	0.00018315867
982	Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation	2022	VLDB	0.00012714044
1,199	Balsa: Learning a Query Optimizer Without Expert Demonstrations	2022	SIGMOD	0.00011563985
1,515	DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems	2021	VLDB	0.00010417728
1,603	SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning	2019	SIGMOD	0.00010097649
1,890	Generating Targeted Queries for Database Testing	2008	SIGMOD	9.4193315e-05
2,210	Lero: A Learning-to-Rank Query Optimizer	2023	VLDB	8.8257742e-05
2,250	QueryFormer: A Tree Transformer Model for Query Plan Representation	2022	VLDB	8.7533306e-05
2,690	Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection	2022	VLDB	8.1258173e-05
2,719	TPC-DS, Taking Decision Support Benchmarking to the Next Level	2002	SIGMOD	8.0967665e-05
3,487	LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans	2023	VLDB	7.263041e-05
4,482	LearnedSQLGen: Constraint-aware SQL Generation using Reinforcement Learning	2022	SIGMOD	6.5802486e-05
5,241	FASTgres: Making Learned Query Optimizer Hinting Effective	2023	VLDB	6.2154384e-05
5,456	Eraser: Eliminating Performance Regression on Learned Query Optimizer	2024	VLDB	6.1239873e-05
9,610	LIMAO: A Framework for Lifelong Modular Learned Query Optimization	2025	VLDB	5.1526493e-05

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