PLANSIEVE uses a transformer and L1-error to classify query plans as suboptimal during optimization, using surrogate cardinalities refined with observed execution results.
Q-error Bounds of Random Uniform Sampling for Cardinality Estimation
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abstract
Random uniform sampling has been studied in various statistical tasks but few of them have covered the Q-error metric for cardinality estimation (CE). In this paper, we analyze the confidence intervals of random uniform sampling with and without replacement for single-table CE. Results indicate that the upper Q-error bound depends on the sample size and true cardinality. Our bound gives a rule-of-thumb for how large a sample should be kept for single-table CE.
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PLANSIEVE: Real-time Suboptimal Query Plan Detection Through Incremental Refinements
PLANSIEVE uses a transformer and L1-error to classify query plans as suboptimal during optimization, using surrogate cardinalities refined with observed execution results.