Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems
Summary: TScout collects training data for self-driving DBMSs by annotating source with hooks and generating kernel-level BPF probes. It aggregates workload, config, internal state, and hardware metrics in a PostgreSQL-compatible DBMS, with ~7% overhead, yielding better ML behavior models for OLTP/OLAP. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Matthew Butrovich (Carnegie Mellon University)
- 2. Wan Shen Lim (Carnegie Mellon University)
- 3. Lin Ma (Carnegie Mellon University)
- 4. John Rollinson (Army Research Laboratory)
- 5. William Zhang (Carnegie Mellon University)
- 6. Yu Xia (Massachusetts Institute of Technology)
- 7. Andrew Pavlo (Carnegie Mellon University)
BibTeX Citation
@inproceedings{butrovich_sigmod22,
title = {{Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems}},
author = {Butrovich, Matthew and Lim, Wan Shen and Ma, Lin and Rollinson, John and Zhang, William and Xia, Yu and Pavlo, Andrew},
series = {{SIGMOD} '22},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3514221.3517845},
url = {https://dl.acm.org/doi/10.1145/3514221.3517845},
year = {2022}
}
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