HERO combines an ensemble of context-aware models stored as a graph with a parameterized local search to recommend query hints and parallelism settings, reporting up to 3x speedup on JOB at lower inference cost than NN-based hint optimizers.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.DB 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
HERO: Hint-Based Efficient and Reliable Query Optimizer
HERO combines an ensemble of context-aware models stored as a graph with a parameterized local search to recommend query hints and parallelism settings, reporting up to 3x speedup on JOB at lower inference cost than NN-based hint optimizers.