AQETuner: Reliable Query-level Configuration Tuning for Analytical Query Engines
Summary: AQETuner: BO-based per-query tuner for analytical query engines using attention to jointly encode knobs + query plans, capturing knob→plan effects. Dual-task Neural Process predicts latency and failures while PSO supplies parallel cold-start samples, improving latency 23.7% and failures 51.2%. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Lixiang Chen (ByteDance; East China Normal University)
- 2. Yuxing Han (ByteDance)
- 3. Yu Chen (ByteDance; East China Normal University)
- 4. Xing Chen (ByteDance)
- 5. Chengcheng Yang (East China Normal University)
- 6. Weining Qian (East China Normal University)
BibTeX Citation
@article{chen_vldb25,
title = {{AQETuner: Reliable Query-level Configuration Tuning for Analytical Query Engines}},
author = {Chen, Lixiang and Han, Yuxing and Chen, Yu and Chen, Xing and Yang, Chengcheng and Qian, Weining},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {8},
pages = {2709--2721},
doi = {10.14778/3742728.3742759},
url = {https://doi.org/10.14778/3742728.3742759},
year = {2025}
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,721 | Pisco: An Isolation Bug Case Reduction and Deduplication Framework | 2026 | VLDB | 4.9793485e-05 |
| 11,015 | Vodka: Rethink Benchmarking Philosophy in HTAP Systems | 2026 | VLDB | 4.9793485e-05 |
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