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Waffle: In-memory Grid Index for Moving Objects with Reinforcement Learning-based Configuration Tuning System

Summary: Waffle is an in-memory grid index for moving objects that groups neighboring cells into tunable chunks to balance heavy updates and scan queries. WaffleMaker uses online reinforcement learning to tune index knobs and rebuild non-blockingly as movement workloads evolve. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12918
Venue
VLDB
Year
2022
Pagerank
5.227679e-05
Overall Rank
9,739 | 33.19%
DOI
10.14778/3551793.3551800

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{choi_vldb22,
        title = {{Waffle: In-memory Grid Index for Moving Objects with Reinforcement Learning-based Configuration Tuning System}},
        author = {Choi, Dalsu and Yoon, Hyunsik and Lee, Hyubjin and Chung, Yon Dohn},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {11},
        pages = {2375--2388},
        doi = {10.14778/3551793.3551800},
        url = {https://doi.org/10.14778/3551793.3551800},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,469 LM-Tree: A Hybrid Learned Index for Similarity Search in Metric Spaces 2026 SIGMOD 5.093636e-05
11,478 Demonstrating Waffle: A Self-driving Grid Index 2023 VLDB 5.093636e-05
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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
43 The Case for Learned Index Structures 2018 SIGMOD 0.00046060254
86 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00035316107
334 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00020875082
347 Tuning Database Configuration Parameters with iTuned 2009 VLDB 0.00020651582
498 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00017440583
873 Learning Multi-dimensional Indexes 2020 SIGMOD 0.00013481915
1,174 Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads 2021 VLDB 0.00011817414
1,279 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011361878
1,344 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00011094717
1,418 LISA: A Learned Index Structure for Spatial Data 2020 SIGMOD 0.00010835539
1,840 Effectively Learning Spatial Indices 2020 VLDB 9.6404567e-05
3,116 ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases 2021 SIGMOD 7.7390737e-05
3,219 iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases 2019 VLDB 7.6283153e-05
3,346 CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions 2021 VLDB 7.4967834e-05
4,751 The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data 2023 SIGMOD 6.5241784e-05
6,488 Parallel Main-Memory Indexing for Moving-Object Query and Update Workloads 2012 SIGMOD 5.865078e-05
8,127 The Case for NLP-Enhanced Database Tuning: Towards Tuning Tools that “Read the Manual” 2021 VLDB 5.4826853e-05
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