Query-based Workload Forecasting for Self-Driving Database Management Systems
Summary: QueryBot 5000 forecasts query arrivals from history via the logical query composition, not resource usage. Multi-horizon, clustering-based model reduction; real-trace evaluation; external controller for PostgreSQL/MySQL to guide index selection. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Lin Ma (Carnegie Mellon University)
- 2. Dana Van Aken (Carnegie Mellon University)
- 3. Ahmed Hefny (Carnegie Mellon University)
- 4. Gustavo Mezerhane (Carnegie Mellon University)
- 5. Andrew Pavlo (Carnegie Mellon University)
- 6. Geoffrey J. Gordon (Carnegie Mellon University)
BibTeX Citation
@inproceedings{ma_sigmod18,
title = {{Query-based Workload Forecasting for Self-Driving Database Management Systems}},
author = {Ma, Lin and Van Aken, Dana and Hefny, Ahmed and Mezerhane, Gustavo and Pavlo, Andrew and Gordon, Geoffrey J.},
series = {{SIGMOD} '18},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3183713.3196908},
url = {https://dl.acm.org/doi/10.1145/3183713.3196908},
year = {2018}
}
Incoming Citations (Sorted by Pagerank)
Showing 50 of 71 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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