DBPecker: A Graph-Based Compound Anomaly Diagnosis System for Distributed RDBMSs
Summary: Graph-based modeling of inter-node dependencies to localize compound anomalies in distributed RDBMSs. Causality-aware metric prioritization plus unified detection+RCA pipeline for automatic, fast root-cause isolation; validated on multi-node OceanBase. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Qingliu Wu
- 2. Qingfeng Xiang
- 3. Yingxia Shao
- 4. Qiyao Luo
- 5. Quanqing Xu
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 760 | Automatic Performance Diagnosis and Tuning in Oracle | 2005 | CIDR | 0.00017003914 |
| 1,024 | DBSherlock: A Performance Diagnostic Tool for Transactional Databases | 2016 | SIGMOD | 0.00014601525 |
| 1,953 | D-Bot: Database Diagnosis System using Large Language Models | 2024 | VLDB | 9.9701097e-05 |
| 2,140 | Diagnosing Root Causes of Intermittent Slow Queries in Cloud Databases | 2020 | VLDB | 9.4565836e-05 |
| 3,641 | OceanBase: A 707 Million tpmC Distributed Relational Database System | 2022 | VLDB | 6.8877808e-05 |
| 4,870 | DBPA: A Benchmark for Transactional Database Performance Anomalies | 2023 | SIGMOD | 5.8583776e-05 |
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