Query Performance Prediction for Concurrent Queries using Graph Embedding

Summary: First graph-embedding-based model for concurrent query performance prediction. Queries mapped to a plan graph; edges encode lock conflicts and buffering correlations; graph embeddings + predictor forecast runtime; dynamic workloads handled via graph update/compaction; real-world tests beat state-of-the-art. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12053
Venue: VLDB
Year: 2020
Pagerank: 6.9460425e-05
Overall Rank: 3,580 | 75.13%
DOI: 10.14778/3397230.3397238

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 35 of 35 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,241	A Learned Query Rewrite System using Monte Carlo Tree Search	2022	VLDB	7.32744e-05
3,345	Lero: A Learning-to-Rank Query Optimizer	2023	VLDB	7.1908499e-05
3,455	Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation	2022	VLDB	7.0760196e-05
3,466	AI Meets Database: AI4DB and DB4AI	2021	SIGMOD	7.0645718e-05
3,819	Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction	2022	VLDB	6.7267885e-05
4,151	openGauss: An Autonomous Database System	2021	VLDB	6.4020605e-05
4,216	Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation	2021	VLDB	6.3448176e-05
4,431	Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process	2022	SIGMOD	6.1870601e-05
4,543	FACE: A Normalizing Flow based Cardinality Estimator	2022	VLDB	6.0953507e-05
4,587	MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems	2021	SIGMOD	6.0594195e-05
5,289	LearnedSQLGen: Constraint-aware SQL Generation using Reinforcement Learning	2022	SIGMOD	5.5790771e-05
5,373	Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing	2022	VLDB	5.5410059e-05
5,477	Learned Cardinality Estimation for Similarity Queries	2021	SIGMOD	5.4856699e-05
5,787	Machine Learning for Databases	2021	VLDB	5.3256401e-05
5,844	Stage: Query Execution Time Prediction in Amazon Redshift	2024	SIGMOD	5.3060581e-05
5,925	HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning	2023	VLDB	5.2669029e-05
6,507	Expand your Training Limits! Generating Training Data for ML-based Data Management	2021	SIGMOD	5.0273414e-05
6,687	How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks	2025	SIGMOD	4.957987e-05
6,883	PilotScope: Steering Databases with Machine Learning Drivers	2024	VLDB	4.8918682e-05
7,308	DBMind: A Self-Driving Platform in openGauss	2021	VLDB	4.7620018e-05
7,326	Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries	2023	SIGMOD	4.7563708e-05
7,332	Refactoring Index Tuning Process with Benefit Estimation	2024	VLDB	4.7553758e-05
7,564	Modeling Shifting Workloads for Learned Database Systems	2024	SIGMOD	4.7049893e-05
7,742	Rethinking Learned Cost Models: Why Start from Scratch?	2023	SIGMOD	4.6585812e-05
8,003	The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions	2024	VLDB	4.6049527e-05
8,036	Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems	2022	SIGMOD	4.5965825e-05
8,095	Grep: A Graph Learning Based Database Partitioning System	2023	SIGMOD	4.5837691e-05
8,702	Multiple Dynamic Outlier-Detection from a Data Stream by Exploiting Duality of Data and Queries	2021	SIGMOD	4.4596411e-05
8,961	T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees	2025	SIGMOD	4.4171776e-05
9,012	Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems	2024	VLDB	4.4059413e-05
10,032	Rainbow: Risk-aware Index Benefit Estimation Facing Out Of Distribution Workloads	2026	SIGMOD	4.1905499e-05
10,050	APQO: An Adaptive Framework for Parametric Query Optimization	2026	SIGMOD	4.1905499e-05
10,573	PlanRGCN: Predicting SPARQL Query Performance	2025	VLDB	4.1905499e-05
10,733	Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries	2025	VLDB	4.1905499e-05
10,736	TxnSails: Achieving Serializable Transaction Scheduling with Self-Adaptive Isolation Level Selection	2025	VLDB	4.1905499e-05

Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 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	0.00059446482
527	Self-tuning Histograms: Building Histograms Without Looking at Data	1999	SIGMOD	0.00020862475
716	Performance Prediction for Concurrent Database Workloads	2011	SIGMOD	0.00017623897
779	QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning	2019	VLDB	0.00016719473
804	An End-to-End Learning-based Cost Estimator	2020	VLDB	0.0001643674
876	Plan-Structured Deep Neural Network Models for Query Performance Prediction	2019	VLDB	0.00015660534
1,017	Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques	2012	VLDB	0.00014627121
1,683	Cardinality Estimation: An Experimental Survey	2018	VLDB	0.0001091276
2,085	The Case for Predictive Database Systems: Opportunities and Challenges	2011	CIDR	9.5749968e-05
2,372	Predictable Performance for Unpredictable Workloads	2009	VLDB	8.940791e-05
2,667	Statistical Learning Techniques for Costing XML Queries	2005	VLDB	8.3444649e-05
4,075	Towards Predicting Query Execution Time for Concurrent and Dynamic Database Workloads	2013	VLDB	6.4699689e-05

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