DBPecker: A Graph-Based Compound Anomaly Diagnosis System for Distributed RDBMSs
Summary: DBPecker models inter-node dependencies as a graph to localize compound anomalies in distributed RDBMSs. Its causality-aware metric prioritization unifies detection and root-cause analysis, validated on a multinode OceanBase cluster. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Qingliu Wu (Beijing Institute of Technology)
- 2. Qingfeng Xiang (Beijing Institute of Technology)
- 3. Yingxia Shao (Beijing Institute of Technology)
- 4. Qiyao Luo (Independent)
- 5. Quanqing Xu (Independent)
BibTeX Citation
@article{wu_vldb25,
title = {{DBPecker: A Graph-Based Compound Anomaly Diagnosis System for Distributed RDBMSs}},
author = {Wu, Qingliu and Xiang, Qingfeng and Shao, Yingxia and Luo, Qiyao and Xu, Quanqing},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {12},
pages = {5383--5386},
doi = {10.14778/3750601.3750677},
url = {https://doi.org/10.14778/3750601.3750677},
year = {2025}
}
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 598 | Automatic Performance Diagnosis and Tuning in Oracle | 2005 | CIDR | 0.00015761263 |
| 782 | DBSherlock: A Performance Diagnostic Tool for Transactional Databases | 2016 | SIGMOD | 0.00014022168 |
| 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 |
| 2,812 | OceanBase: A 707 Million tpmC Distributed Relational Database System | 2022 | VLDB | 7.9811649e-05 |
| 5,077 | DBPA: A Benchmark for Transactional Database Performance Anomalies | 2023 | SIGMOD | 6.2858696e-05 |
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