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: 13788
Venue: VLDB
Year: 2025
Pagerank: 4.6080455e-05
Overall Rank: 7,993 | 44.45%
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	4.1905499e-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	4.1905499e-05
10,244	DBAIOps: A Reasoning LLM-Enhanced Database Operation and Maintenance System using Knowledge Graphs	2026	VLDB	4.1905499e-05
10,790	Towards Automated Cross-domain Exploratory Data Analysis through Large Language Models	2025	VLDB	4.1905499e-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	0.00059446482
183	Automatic Database Management System Tuning Through Large-scale Machine Learning	2017	SIGMOD	0.00036859633
203	Learned Cardinalities: Estimating Correlated Joins with Deep Learning	2019	CIDR	0.00034868567
329	Neo: A Learned Query Optimizer	2019	VLDB	0.00027301488
634	Bao: Making Learned Query Optimization Practical	2021	SIGMOD	0.00018844568
704	Query-based Workload Forecasting for Self-Driving Database Management Systems	2018	SIGMOD	0.00017785557
796	SageDB: A Learned Database System	2019	CIDR	0.00016541749
804	An End-to-End Learning-based Cost Estimator	2020	VLDB	0.0001643674
1,024	DBSherlock: A Performance Diagnostic Tool for Transactional Databases	2016	SIGMOD	0.00014601525
1,856	AI Meets AI: Leveraging Query Executions to Improve Index Recommendations	2019	SIGMOD	0.00010319105
1,953	D-Bot: Database Diagnosis System using Large Language Models	2024	VLDB	9.9701097e-05
2,050	Automatically Indexing Millions of Databases in Microsoft Azure SQL Database	2019	SIGMOD	9.6883066e-05
2,140	Diagnosing Root Causes of Intermittent Slow Queries in Cloud Databases	2020	VLDB	9.4565836e-05
2,305	TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods	2024	VLDB	9.0655355e-05
3,167	QueryFormer: A Tree Transformer Model for Query Plan Representation	2022	VLDB	7.4561078e-05
3,345	Lero: A Learning-to-Rank Query Optimizer	2023	VLDB	7.1908499e-05
3,871	MagicScaler: Uncertainty-aware, Predictive Autoscaling	2023	VLDB	6.6738199e-05
4,151	openGauss: An Autonomous Database System	2021	VLDB	6.4020605e-05
4,412	Semi-Automatic Index Tuning: Keeping DBAs in the Loop	2012	VLDB	6.1999789e-05
4,655	ExplainIt! - A Declarative Root-cause Analysis Engine for Time Series Data	2019	SIGMOD	6.0126689e-05
4,658	PreQR: Pre-training Representation for SQL Understanding	2022	SIGMOD	6.0084453e-05
4,735	AutoTQA: Towards Autonomous Tabular Question Answering through Multi-Agent Large Language Models	2024	VLDB	5.9538651e-05
5,449	Multiple Time Series Forecasting with Dynamic Graph Modeling	2024	VLDB	5.4980173e-05
6,589	AutoCTS+: Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting	2023	SIGMOD	4.9964862e-05
7,308	DBMind: A Self-Driving Platform in openGauss	2021	VLDB	4.7620018e-05
11,147	Weakly Guided Adaptation for Robust Time Series Forecasting	2024	VLDB	4.1905499e-05
11,202	LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation	2023	SIGMOD	4.1905499e-05

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