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Trade-offs in Static and Dynamic Evaluation of Hierarchical Queries

Summary: Degree-aware heavy/light framework for static and dynamic evaluation of hierarchical queries with arbitrary free variables, trading preprocessing, update time, and enumeration delay via a tunable light/heavy threshold. Recovers prior bounds and, for a restricted subclass, achieves OMv‑conditioned worst-case optimal update time and enumeration delay. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1777
Venue
PODS
Year
2020
Pagerank
6.7723513e-05
Overall Rank
3,781 | 73.70%
DOI
10.1145/3375395.3387646

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