Waffle: A Workload-Aware and Query-Sensitive Framework for Disk-Based Spatial Indexing
Summary: Waffle is a workload-aware, query-sensitive disk spatial index balancing update and query performance for dynamic data. It unifies space/data partitioning with optimal static bulk loading, overlap-free updates, and adaptive workload-driven maintenance. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Moin Hussain Moti (Hong Kong University of Science and Technology)
- 2. Panagiotis Simatis (Hong Kong University of Science and Technology)
- 3. Dimitris Papadias (Hong Kong University of Science and Technology)
BibTeX Citation
@article{moti_vldb23,
title = {{Waffle: A Workload-Aware and Query-Sensitive Framework for Disk-Based Spatial Indexing}},
author = {Moti, Moin Hussain and Simatis, Panagiotis and Papadias, Dimitris},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {4},
pages = {670--683},
doi = {10.14778/3574245.3574253},
url = {https://doi.org/10.14778/3574245.3574253},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,986 | One Seed, Two Birds: A Unified Learned Structure for Exact and Approximate Counting | 2024 | SIGMOD | 5.3387783e-05 |
| 9,974 | PLATON: Top-down R-tree Packing with Learned Partition Policy | 2023 | SIGMOD | 5.1845938e-05 |
| 10,610 | A Workload-Aware Encrypted Index for Efficient Privacy-Preserving Range Queries | 2026 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 27 of 27 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 8 | 5,395 | AQWA: Adaptive Query-Workload-Aware Partitioning of Big Spatial Data | 2015 | VLDB |
| 9 | 11,478 | Demonstrating Waffle: A Self-driving Grid Index | 2023 | VLDB |
| 10 | 9,739 | Waffle: In-memory Grid Index for Moving Objects with Reinforcement Learning-based Configuration Tuning System | 2022 | VLDB |