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)
Incoming Non-self Citations Over Time
Authors
- 1. Biao Ouyang (East China Normal University)
- 2. Yingying Zhang (Alibaba)
- 3. Hanyin Cheng (East China Normal University)
- 4. Yang Shu (East China Normal University)
- 5. Chenjuan Guo (East China Normal University)
- 6. Bin Yang (East China Normal University)
- 7. Qingsong Wen (Squirrel Ai Learning)
- 8. Lunting Fan (Alibaba)
- 9. Christian S. Jensen (Aalborg University)
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 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,384 | MCTuner: Spatial Decomposition-Enhanced Database Tuning via LLM-Guided Exploration | 2026 | SIGMOD | 5.093636e-05 |
| 10,506 | 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 | 5.093636e-05 |
| 10,532 | DBAIOps: A Reasoning LLM-Enhanced Database Operation and Maintenance System using Knowledge Graphs | 2026 | VLDB | 5.093636e-05 |
| 11,013 | Towards Automated Cross-domain Exploratory Data Analysis through Large Language Models | 2025 | VLDB | 5.093636e-05 |
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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.
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