LIO: A lightweight and interpretable query optimizer based on an evolutionary forest

Summary: LIO is a learning-based query optimizer that uses genetic programming to evolve feature subsets for a random forest, targeting the accuracy/overhead/interpretability tradeoff. Its forest outputs act as explanations to steer hint refinement, while tree pruning shrinks the model without large performance loss. (summarized by gpt-5.4-mini on Apr 12 2026)

Paper ID: 14261
Venue: VLDB
Year: 2026
Pagerank: 4.1945683e-05
Overall Rank: 10,225 | 28.87%
DOI: 10.14778/3797919.3797920

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Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 20 of 20 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
71	How Good Are Query Optimizers, Really?	2016	VLDB	0.00059038975
333	Neo: A Learned Query Optimizer	2019	VLDB	0.00027206884
640	Bao: Making Learned Query Optimization Practical	2021	SIGMOD	0.00018759152
806	An End-to-End Learning-based Cost Estimator	2020	VLDB	0.00016434274
884	Plan-Structured Deep Neural Network Models for Query Performance Prediction	2019	VLDB	0.00015654004
1,407	DB-BERT: A Database Tuning Tool that "Reads the Manual"	2022	SIGMOD	0.00012146739
1,855	AI Meets AI: Leveraging Query Executions to Improve Index Recommendations	2019	SIGMOD	0.00010315245
2,121	Balsa: Learning a Query Optimizer Without Expert Demonstrations	2022	SIGMOD	9.5017232e-05
2,783	Flow-Loss: Learning Cardinality Estimates That Matter	2021	VLDB	8.1293383e-05
2,985	DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems	2021	VLDB	7.7795847e-05
3,114	GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization	2024	VLDB	7.5451724e-05
3,169	QueryFormer: A Tree Transformer Model for Query Plan Representation	2022	VLDB	7.4498425e-05
3,241	TPC-DS, Taking Decision Support Benchmarking to the Next Level	2002	SIGMOD	7.3305643e-05
3,348	Lero: A Learning-to-Rank Query Optimizer	2023	VLDB	7.1904529e-05
3,727	Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection	2022	VLDB	6.8141709e-05
4,462	LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans	2023	VLDB	6.1611784e-05
4,804	Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload	2021	SIGMOD	5.910467e-05
5,930	FASTgres: Making Learned Query Optimizer Hinting Effective	2023	VLDB	5.2682075e-05
8,488	Can Large Language Models Be Query Optimizer for Relational Databases?	2026	SIGMOD	4.4998609e-05
9,190	MLOS in Action: Bridging the Gap Between Experimentation and Auto-Tuning in the Cloud	2024	VLDB	4.3768215e-05

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3,658	Towards a Hands-Free Query Optimizer through Deep Learning	2019	CIDR	6.8704209e-05
3,169	QueryFormer: A Tree Transformer Model for Query Plan Representation	2022	VLDB	7.4498425e-05
333	Neo: A Learned Query Optimizer	2019	VLDB	0.00027206884
11,350	DeepO: A Learned Query Optimizer	2022	SIGMOD	4.1945683e-05
10,156	Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload	2026	SIGMOD	4.1945683e-05
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