SkinnerMT: Parallelizing for Efficiency and Robustness in Adaptive Query Processing on Multicore Platforms
Summary: SkinnerMT parallelizes adaptive query processing via concurrent plan exploration, data-parallel multi-way joins, and hybrids on multicore systems. Runtime-feedback cost optimization balances average performance with robustness, outperforming conventional and prior adaptive engines when optimization is difficult. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ziyun Wei (Cornell University)
- 2. Immanuel Trummer (Cornell University)
BibTeX Citation
@article{wei_vldb23,
title = {{SkinnerMT: Parallelizing for Efficiency and Robustness in Adaptive Query Processing on Multicore Platforms}},
author = {Wei, Ziyun and Trummer, Immanuel},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {4},
pages = {905--917},
doi = {10.14778/3574245.3574272},
url = {https://doi.org/10.14778/3574245.3574272},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,978 | ADOPT: Adaptively Optimizing Attribute Orders for Worst-Case Optimal Join Algorithms via Reinforcement Learning | 2023 | VLDB | 5.514996e-05 |
| 8,494 | POLAR: Adaptive and Non-invasive Join Order Selection via Plans of Least Resistance | 2024 | VLDB | 5.4142129e-05 |
| 9,280 | Themis: A GPU-accelerated Relational Query Execution Engine | 2025 | VLDB | 5.2933689e-05 |
| 10,749 | AJOSC: Adaptive Join Order Selection for Continuous Queries | 2025 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 23 of 23 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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