SemCEB is the first benchmark for cardinality estimation over semantic operators, evaluating sampling methods and Semantic Histograms on accuracy, cost, latency, and memory using 102 queries on a real-world dataset.
Proceedings of the VLDB Endowment 12, 11 (July 2019), 1692–1704
7 Pith papers cite this work. Polarity classification is still indexing.
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Spectral aggregate tests prune up to 51% of candidates in CSM but leave enumeration intermediates unchanged beyond initial bindings across tested workloads.
SPA trains LLMs via plan-aware RL with adaptive reward shaping and self-improvement on slowdowns to produce faster query rewrites than rule-based or standard LLM methods on IID and OOD workloads.
Geo is a framework for optimizing graph pattern matching queries via rewrite rules and equality saturation that discovers equivalences and reduces costs by up to 99%.
Co-evolving LLM-generated solutions with their evaluators enables discovery of novel database algorithms that outperform state-of-the-art baselines, including a query rewrite policy with up to 6.8x lower latency.
Hermes enables constant-time global aggregations and in-place updates on homomorphically encrypted databases by embedding precomputed statistics in packed ciphertexts and using polynomial slot masking and shifting.
LLMs can outperform DTA on index recommendations for some workloads but remain less reliable with practical adoption challenges.
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Can Aggregate Invariants Accelerate Continuous Subgraph Matching? Limits, Laws, and a Dynamic Spectral Index
Spectral aggregate tests prune up to 51% of candidates in CSM but leave enumeration intermediates unchanged beyond initial bindings across tested workloads.