Database Gyms
Summary: Introduces a "database gym": an integrated environment with a unified API of pluggable components that uses the DBMS itself to simulate workloads and collect training data exposing workload trends and cross-subsystem interactions. Outlines methods to meet DBMS-simulation challenges—performance, fidelity, and DBMS-generated hints—to enable holistic ML-driven tuning and accelerate model training and evaluation. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Wan Shen Lim (Carnegie Mellon University)
- 2. Matthew Butrovich (Carnegie Mellon University)
- 3. William Zhang (Carnegie Mellon University)
- 4. Andrew Crotty (Northwestern University)
- 5. Lin Ma (University of Michigan)
- 6. Peijing Xu (Carnegie Mellon University)
- 7. Johannes Gehrke (Microsoft)
- 8. Andrew Pavlo (Carnegie Mellon University)
BibTeX Citation
@inproceedings{lim_cidr23,
address = {Amsterdam, Netherlands},
series = {{CIDR} '23},
title = {{Database Gyms}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Lim, Wan Shen and Butrovich, Matthew and Zhang, William and Crotty, Andrew and Ma, Lin and Xu, Peijing and Gehrke, Johannes and Pavlo, Andrew},
year = {2023}
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