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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)

Paper ID
h7665b705f07b7db4
Venue
VLDB
Year
2023
Pagerank
5.3450708e-05
Overall Rank
8,369 | 43.74%
DOI
10.14778/3574245.3574253

Incoming Non-self Citations Over Time

Authors

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
9,145 One Seed, Two Birds: A Unified Learned Structure for Exact and Approximate Counting 2024 SIGMOD 5.220115e-05
10,168 PLATON: Top-down R-tree Packing with Learned Partition Policy 2023 SIGMOD 5.0682654e-05
11,057 A Workload-Aware Encrypted Index for Efficient Privacy-Preserving Range Queries 2026 VLDB 4.9793485e-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.

Rank Cited Paper Year Venue Pagerank
2 R-Trees: A Dynamic Index Structure For Spatial Searching 1984 SIGMOD 0.001992968
4 The R*-tree: An Efficient and Robust Access Method for Points and Rectangles 1990 SIGMOD 0.0011405675
8 The K-D-B-Tree: A Search Structure for Large Multidimensional Dynamic Indexes 1981 SIGMOD 0.0008122792
28 Nearest Neighbor Queries 1995 SIGMOD 0.00051312804
40 The Case for Learned Index Structures 2018 SIGMOD 0.00046284649
44 The R+-Tree: A Dynamic Multi-Dimensional Index for Objects 1987 VLDB 0.00045337853
56 M-tree: An Efficient Access Method for Similarity Search in Metric Spaces 1997 VLDB 0.00040370171
116 Direct Spatial Search on Pictorial Databases Using Packed R-trees 1985 SIGMOD 0.00031645463
146 Efficient Processing of Spatial Joins Using R-trees 1993 SIGMOD 0.00029061754
279 The SR-tree: An Index Structure for High-Dimensional Nearest Neighbor Queries 1997 SIGMOD 0.00022308048
335 Hilbert R-tree: An Improved R-tree Using Fractals 1994 VLDB 0.00020660268
574 Indexing the Positions of Continuously Moving Objects 2000 SIGMOD 0.00016173068
677 Voronoi-Based K Nearest Neighbor Search for Spatial Network Databases 2004 VLDB 0.00014843441
868 Learning Multi-dimensional Indexes 2020 SIGMOD 0.00013354403
985 The TPR*-Tree: An Optimized Spatio-Temporal Access Method for Predictive Queries 2003 VLDB 0.00012685169
1,191 Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads 2021 VLDB 0.00011590153
1,446 LISA: A Learned Index Structure for Spatial Data 2020 SIGMOD 0.00010629222
1,571 Reverse kNN Search in Arbitrary Dimensionality 2004 VLDB 0.00010201796
1,719 Closest Pair Queries in Spatial Databases 2000 SIGMOD 9.7976056e-05
1,878 Effectively Learning Spatial Indices 2020 VLDB 9.4451309e-05
1,903 The LSD tree: spatial access to multidimensional point and non-point objects 1989 VLDB 9.4032472e-05
2,016 Optimizing Multidimensional Index Trees for Main Memory Access 2001 SIGMOD 9.1771614e-05
2,243 Conceptual Partitioning: An Efficient Method for Continuous Nearest Neighbor Monitoring 2005 SIGMOD 8.7678247e-05
2,740 The Spatial Skyline Queries 2006 VLDB 8.0720377e-05
3,034 A Revised R*-tree in Comparison with Related Index Structures 2009 SIGMOD 7.7330662e-05
3,669 The Priority R-Tree: A Practically Efficient and Worst-Case Optimal R-Tree 2004 SIGMOD 7.1125618e-05
5,863 A Benchmark for Evaluating Moving Object Indexes 2008 VLDB 5.9667924e-05
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