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Scaling Package Queries to a Billion Tuples via Hierarchical Partitioning and Customized Optimization

Summary: Progressive Shading: hierarchical partitioning and progressive optimization over ever‑finer relations to avoid premature discarding and scale package queries to billions of tuples while handling very tight constraints. Introduces Dynamic Low Variance partitioning that outperforms kd‑trees for multi‑attribute data and custom ILP/LP solvers (Dual Reducer, Parallel Dual Simplex) for orders‑of‑magnitude speedups. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13363
Venue
VLDB
Year
2024
Pagerank
4.6039546e-05
Overall Rank
8,021 | 44.20%
DOI
10.14778/3641204.3641222

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
3,147 Searchlight: Enabling Integrated Search and Exploration over Large Multidimensional Data 2015 VLDB 7.4771804e-05
3,254 Query Processing on Tensor Computation Runtimes 2022 VLDB 7.3161051e-05
3,441 Interactive Data Exploration Using Semantic Windows 2014 SIGMOD 7.0914601e-05
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