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LASER: Buffer-Aware Learned Query Scheduling in Master-Standby Databases
Summary: LASER introduces a buffer-aware query scheduler for master-standby DBs that uses a lightweight learned model to map queries to accessed data blocks and drive allocation/reordering to maximize buffer reuse. No pre-training, online updates and load-balanced scheduling yield ~80% lower query completion time vs heuristics.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 14234
- Venue
- VLDB
- Year
- 2025
- Pagerank
- 4.1905499e-05
- Overall Rank
- 10,876 | 24.42%
- DOI
-
10.14778/3712221.3712239
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Incoming Citations (Sorted by Pagerank)
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| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
Outgoing Citations (Sorted by Pagerank)
Showing 20 of 20 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 71 |
How Good Are Query Optimizers, Really? |
2016 |
VLDB |
0.00059446482 |
| 183 |
Automatic Database Management System Tuning Through Large-scale Machine Learning |
2017 |
SIGMOD |
0.00036859633 |
| 203 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034868567 |
| 510 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.00021420477 |
| 752 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.00017138049 |
| 779 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.00016719473 |
| 819 |
ALEX: An Updatable Adaptive Learned Index |
2020 |
SIGMOD |
0.00016237497 |
| 2,108 |
LISA: A Learned Index Structure for Spatial Data |
2020 |
SIGMOD |
9.5283642e-05 |
| 2,458 |
Multi-dimensional Resource Scheduling for Parallel Queries |
1996 |
SIGMOD |
8.7601979e-05 |
| 2,693 |
Greenplum: A Hybrid Database for Transactional and Analytical Workloads |
2021 |
SIGMOD |
8.2845883e-05 |
| 3,825 |
Locality-aware Partitioning in Parallel Database Systems |
2015 |
SIGMOD |
6.7225803e-05 |
| 4,151 |
openGauss: An Autonomous Database System |
2021 |
VLDB |
6.4020605e-05 |
| 4,543 |
FACE: A Normalizing Flow based Cardinality Estimator |
2022 |
VLDB |
6.0953507e-05 |
| 4,592 |
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift |
2023 |
SIGMOD |
6.056004e-05 |
| 4,609 |
Deployment of Query Plans on Multicores |
2015 |
VLDB |
6.0458679e-05 |
| 5,210 |
Self-Tuning Query Scheduling for Analytical Workloads |
2021 |
SIGMOD |
5.6244961e-05 |
| 5,537 |
Presto: A Decade of SQL Analytics at Meta |
2023 |
SIGMOD |
5.453017e-05 |
| 5,682 |
LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems |
2022 |
SIGMOD |
5.3752251e-05 |
| 7,220 |
Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation |
2023 |
SIGMOD |
4.7926382e-05 |
| 7,378 |
Distribution-Based Query Scheduling |
2013 |
VLDB |
4.7428007e-05 |
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