Libra: One-Shot Parameter Sensitivity Estimation for Transfer Learning in Database Performance Prediction

Summary: Libra is a transfer-learning framework for DBMS performance prediction that predicts a target context’s parameter-sensitivity profile in one shot, then retrieves the most similar source context. It avoids negative transfer by focusing sampling on high-impact parameters, yielding up to 32x less sampling and large error reductions across 161 contexts. (summarized by gpt-5.4-mini on Apr 12 2026)

Paper ID: 14371
Venue: VLDB
Year: 2026
Pagerank: 4.1945683e-05
Overall Rank: 10,328 | 28.16%
DOI: 10.14778/3796195.3796207

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Authors

1. Tatsuhiro Nakamori
2. Hideyuki Kawashima

Incoming Citations (Sorted by Pagerank)

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Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 15 of 15 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
183	Automatic Database Management System Tuning Through Large-scale Machine Learning	2017	SIGMOD	0.00036721403
424	Tuning Database Configuration Parameters with iTuned	2009	VLDB	0.00023616398
514	An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning	2019	SIGMOD	0.0002124895
884	Plan-Structured Deep Neural Network Models for Query Performance Prediction	2019	VLDB	0.00015654004
1,827	An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems	2021	VLDB	0.00010390548
3,169	QueryFormer: A Tree Transformer Model for Query Plan Representation	2022	VLDB	7.4498425e-05
3,522	ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases	2021	SIGMOD	7.0096727e-05
3,812	Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation	2022	VLDB	6.7373184e-05
3,828	Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction	2022	VLDB	6.7208524e-05
4,380	LlamaTune: Sample-Efficient DBMS Configuration Tuning	2022	VLDB	6.2396606e-05
4,842	Towards Dynamic and Safe Configuration Tuning for Cloud Databases	2022	SIGMOD	5.8826802e-05
5,832	Stage: Query Execution Time Prediction in Amazon Redshift	2024	SIGMOD	5.3111109e-05
6,151	An Efficient Transfer Learning Based Configuration Adviser for Database Tuning	2024	VLDB	5.183652e-05
8,956	T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees	2025	SIGMOD	4.4214154e-05
8,999	DBSeer: Pain-free Database Administration through Workload Intelligence	2015	VLDB	4.4117211e-05

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7,828	Modeling Shifting Workloads for Learned Database Systems	2024	SIGMOD	4.6407986e-05
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