Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries
Summary: IconqSched is a non-intrusive, cross-engine scheduler whose black-box Iconq predictor models concurrent-query runtime across system states. Greedy admission and timing decisions reduce end-to-end runtime by up to 16.5% on average and 33.6% at the tail on PostgreSQL/Redshift. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Ziniu Wu (Massachusetts Institute of Technology)
- 2. Markos Markakis (Massachusetts Institute of Technology)
- 3. Chunwei Liu (Massachusetts Institute of Technology)
- 4. Peter Baile Chen (Massachusetts Institute of Technology)
- 5. Balakrishnan Narayanaswamy (Amazon)
- 6. Tim Kraska (Amazon; Massachusetts Institute of Technology)
- 7. Samuel Madden (Massachusetts Institute of Technology)
BibTeX Citation
@article{wu_vldb25,
title = {{Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries}},
author = {Wu, Ziniu and Markakis, Markos and Liu, Chunwei and Chen, Peter Baile and Narayanaswamy, Balakrishnan and Kraska, Tim and Madden, Samuel},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {11},
pages = {4185--4198},
doi = {10.14778/3749466.3749686},
url = {https://doi.org/10.14778/3749466.3749686},
year = {2025}
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