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Waffle: In-memory Grid Index for Moving Objects with Reinforcement Learning-based Configuration Tuning System
Summary: In-memory grid index for moving objects uses fixed cells and neighbor chunks (Waffle) to speed updates and scans. Online RL-based tuner (WaffleMaker) automatically tunes knobs and timing, enabling non-blocking rebuilds with concurrency control.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 12730
- Venue
- VLDB
- Year
- 2022
- Pagerank
- 4.3177432e-05
- Overall Rank
- 9,605 | 33.18%
- DOI
-
10.14778/3551793.3551800
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 17 of 17 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 102 |
The Case for Learned Index Structures |
2018 |
SIGMOD |
0.00049545203 |
| 183 |
Automatic Database Management System Tuning Through Large-scale Machine Learning |
2017 |
SIGMOD |
0.00036721403 |
| 424 |
Tuning Database Configuration Parameters with iTuned |
2009 |
VLDB |
0.00023616398 |
| 514 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.0002124895 |
| 782 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.00016729063 |
| 1,478 |
Learning Multi-dimensional Indexes |
2020 |
SIGMOD |
0.00011762542 |
| 1,827 |
An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems |
2021 |
VLDB |
0.00010390548 |
| 1,855 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00010315245 |
| 1,889 |
Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads |
2021 |
VLDB |
0.00010200865 |
| 2,115 |
LISA: A Learned Index Structure for Spatial Data |
2020 |
SIGMOD |
9.5257379e-05 |
| 2,678 |
Effectively Learning Spatial Indices |
2020 |
VLDB |
8.3252088e-05 |
| 3,269 |
iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases |
2019 |
VLDB |
7.2998062e-05 |
| 3,522 |
ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases |
2021 |
SIGMOD |
7.0096727e-05 |
| 4,265 |
CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions |
2021 |
VLDB |
6.3097793e-05 |
| 5,572 |
The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data |
2023 |
SIGMOD |
5.4277273e-05 |
| 6,537 |
Parallel Main-Memory Indexing for Moving-Object Query and Update Workloads |
2012 |
SIGMOD |
5.0235647e-05 |
| 8,615 |
The Case for NLP-Enhanced Database Tuning: Towards Tuning Tools that "Read the Manual" |
2021 |
VLDB |
4.484683e-05 |
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