RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems

Summary: RCRank treats slow-query root-cause analysis as a multimodal ML task, aligning query text, plans, logs and KPIs via self-supervised pretraining to obtain cross-modal embeddings. Root-cause-adaptive cross-Transformers with an impact-aware loss jointly identify and rank causes, improving prioritization. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 13787
Venue: VLDB
Year: 2025
Pagerank: 4.6124681e-05
Overall Rank: 7,989 | 44.43%
DOI: 10.14778/3717755.3717774

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,093	MCTuner: Spatial Decomposition-Enhanced Database Tuning via LLM-Guided Exploration	2026	SIGMOD	4.1945683e-05
10,217	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	4.1945683e-05
10,244	DBAIOps: A Reasoning LLM-Enhanced Database Operation and Maintenance System using Knowledge Graphs	2026	VLDB	4.1945683e-05
10,784	Towards Automated Cross-domain Exploratory Data Analysis through Large Language Models	2025	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 27 of 27 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
183	Automatic Database Management System Tuning Through Large-scale Machine Learning	2017	SIGMOD	0.00036721403
204	Learned Cardinalities: Estimating Correlated Joins with Deep Learning	2019	CIDR	0.00034784455
333	Neo: A Learned Query Optimizer	2019	VLDB	0.00027206884
640	Bao: Making Learned Query Optimization Practical	2021	SIGMOD	0.00018759152
716	Query-based Workload Forecasting for Self-Driving Database Management Systems	2018	SIGMOD	0.00017723171
801	SageDB: A Learned Database System	2019	CIDR	0.00016505496
806	An End-to-End Learning-based Cost Estimator	2020	VLDB	0.00016434274
1,022	DBSherlock: A Performance Diagnostic Tool for Transactional Databases	2016	SIGMOD	0.00014614917
1,855	AI Meets AI: Leveraging Query Executions to Improve Index Recommendations	2019	SIGMOD	0.00010315245
1,956	D-Bot: Database Diagnosis System using Large Language Models	2024	VLDB	9.960627e-05
2,047	Automatically Indexing Millions of Databases in Microsoft Azure SQL Database	2019	SIGMOD	9.6920209e-05
2,139	Diagnosing Root Causes of Intermittent Slow Queries in Cloud Databases	2020	VLDB	9.4640037e-05
2,298	TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods	2024	VLDB	9.0742746e-05
3,169	QueryFormer: A Tree Transformer Model for Query Plan Representation	2022	VLDB	7.4498425e-05
3,348	Lero: A Learning-to-Rank Query Optimizer	2023	VLDB	7.1904529e-05
3,869	MagicScaler: Uncertainty-aware, Predictive Autoscaling	2023	VLDB	6.6802432e-05
4,152	openGauss: An Autonomous Database System	2021	VLDB	6.4060406e-05
4,415	Semi-Automatic Index Tuning: Keeping DBAs in the Loop	2012	VLDB	6.205081e-05
4,658	ExplainIt! - A Declarative Root-cause Analysis Engine for Time Series Data	2019	SIGMOD	6.0183783e-05
4,661	PreQR: Pre-training Representation for SQL Understanding	2022	SIGMOD	6.0137947e-05
4,739	AutoTQA: Towards Autonomous Tabular Question Answering through Multi-Agent Large Language Models	2024	VLDB	5.959592e-05
5,438	Multiple Time Series Forecasting with Dynamic Graph Modeling	2024	VLDB	5.5033018e-05
6,589	AutoCTS+: Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting	2023	SIGMOD	5.001285e-05
7,309	DBMind: A Self-Driving Platform in openGauss	2021	VLDB	4.766574e-05
11,144	Weakly Guided Adaptation for Robust Time Series Forecasting	2024	VLDB	4.1945683e-05
11,200	LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation	2023	SIGMOD	4.1945683e-05

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