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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
h89216567e06b1114
Venue
VLDB
Year
2025
Pagerank
5.5790509e-05
Overall Rank
7,236 | 51.35%
DOI
10.14778/3717755.3717774

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{ouyang_vldb25,
        title = {{RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems}},
        author = {Ouyang, Biao and Zhang, Yingying and Cheng, Hanyin and Shu, Yang and Guo, Chenjuan and Yang, Bin and Wen, Qingsong and Fan, Lunting and Jensen, Christian S.},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {4},
        pages = {1169--1182},
        doi = {10.14778/3717755.3717774},
        url = {https://doi.org/10.14778/3717755.3717774},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

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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
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061066921
78 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036684414
85 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035864347
145 Neo: A Learned Query Optimizer 2019 VLDB 0.0002908188
362 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019989474
460 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017842695
461 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00017829982
555 SageDB: A Learned Database System 2019 CIDR 0.00016506678
782 DBSherlock: A Performance Diagnostic Tool for Transactional Databases 2016 SIGMOD 0.00014022168
1,279 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011226878
1,516 Automatically Indexing Millions of Databases in Microsoft Azure SQL Database 2019 SIGMOD 0.00010402594
1,658 D-Bot: Database Diagnosis System using Large Language Models 2024 VLDB 9.9642078e-05
1,857 Diagnosing Root Causes of Intermittent Slow Queries in Cloud Databases 2020 VLDB 9.4929201e-05
2,210 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 8.8257742e-05
2,250 QueryFormer: A Tree Transformer Model for Query Plan Representation 2022 VLDB 8.7533306e-05
3,423 AutoTQA: Towards Autonomous Tabular Question Answering through Multi-Agent Large Language Models 2024 VLDB 7.313499e-05
3,433 TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods 2024 VLDB 7.3030444e-05
3,682 openGauss: An Autonomous Database System 2021 VLDB 7.1013922e-05
4,025 MagicScaler: Uncertainty-aware, Predictive Autoscaling 2023 VLDB 6.8460581e-05
4,058 Semi-Automatic Index Tuning: Keeping DBAs in the Loop 2012 VLDB 6.8257215e-05
4,609 ExplainIt! - A Declarative Root-cause Analysis Engine for Time Series Data 2019 SIGMOD 6.503039e-05
4,707 PreQR: Pre-training Representation for SQL Understanding 2022 SIGMOD 6.4587914e-05
6,202 Multiple Time Series Forecasting with Dynamic Graph Modeling 2024 VLDB 5.8507344e-05
6,536 AutoCTS+: Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting 2023 SIGMOD 5.7538492e-05
7,492 DBMind: A Self-Driving Platform in openGauss 2021 VLDB 5.510397e-05
11,668 Weakly Guided Adaptation for Robust Time Series Forecasting 2024 VLDB 4.9793485e-05
11,717 LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation 2023 SIGMOD 4.9793485e-05
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