Back to papers
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
- 14233
- Venue
- VLDB
- Year
- 2025
- Pagerank
- 4.1945683e-05
- Overall Rank
- 10,872 | 24.37%
- DOI
-
10.14778/3712221.3712239
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| 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 |
0.00059038975 |
| 183 |
Automatic Database Management System Tuning Through Large-scale Machine Learning |
2017 |
SIGMOD |
0.00036721403 |
| 204 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034784455 |
| 514 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.0002124895 |
| 758 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.0001706608 |
| 782 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.00016729063 |
| 826 |
ALEX: An Updatable Adaptive Learned Index |
2020 |
SIGMOD |
0.00016224841 |
| 2,115 |
LISA: A Learned Index Structure for Spatial Data |
2020 |
SIGMOD |
9.5257379e-05 |
| 2,459 |
Multi-dimensional Resource Scheduling for Parallel Queries |
1996 |
SIGMOD |
8.7676516e-05 |
| 2,691 |
Greenplum: A Hybrid Database for Transactional and Analytical Workloads |
2021 |
SIGMOD |
8.2909126e-05 |
| 3,821 |
Locality-aware Partitioning in Parallel Database Systems |
2015 |
SIGMOD |
6.7281515e-05 |
| 4,152 |
openGauss: An Autonomous Database System |
2021 |
VLDB |
6.4060406e-05 |
| 4,543 |
FACE: A Normalizing Flow based Cardinality Estimator |
2022 |
VLDB |
6.1011198e-05 |
| 4,593 |
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift |
2023 |
SIGMOD |
6.0606891e-05 |
| 4,610 |
Deployment of Query Plans on Multicores |
2015 |
VLDB |
6.0516573e-05 |
| 5,212 |
Self-Tuning Query Scheduling for Analytical Workloads |
2021 |
SIGMOD |
5.6262923e-05 |
| 5,531 |
Presto: A Decade of SQL Analytics at Meta |
2023 |
SIGMOD |
5.4549499e-05 |
| 5,671 |
LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems |
2022 |
SIGMOD |
5.3803919e-05 |
| 7,221 |
Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation |
2023 |
SIGMOD |
4.797194e-05 |
| 7,388 |
Distribution-Based Query Scheduling |
2013 |
VLDB |
4.7437725e-05 |
Semantically Similar Papers