Trait mz_transform::attribute::cardinality::Factorizer

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pub trait Factorizer {
    // Required methods
    fn flat_map(&self, tf: &TableFunc, input: &SymExp) -> SymExp;
    fn predicate(
        &self,
        expr: &MirScalarExpr,
        unique_columns: &BTreeSet<usize>
    ) -> SymExp;
    fn filter(
        &self,
        predicates: &Vec<MirScalarExpr>,
        keys: &Vec<Vec<usize>>,
        input: &SymExp
    ) -> SymExp;
    fn join(
        &self,
        equivalences: &Vec<Vec<MirScalarExpr>>,
        implementation: &JoinImplementation,
        unique_columns: BTreeMap<usize, usize>,
        inputs: Vec<&SymExp>
    ) -> SymExp;
    fn reduce(
        &self,
        group_key: &Vec<MirScalarExpr>,
        expected_group_size: &Option<u64>,
        input: &SymExp
    ) -> SymExp;
    fn topk(
        &self,
        group_key: &Vec<usize>,
        limit: &Option<MirScalarExpr>,
        expected_group_size: &Option<u64>,
        input: &SymExp
    ) -> SymExp;
    fn threshold(&self, input: &SymExp) -> SymExp;
}
Expand description

A Factorizer computes selectivity factors

Required Methods§

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fn flat_map(&self, tf: &TableFunc, input: &SymExp) -> SymExp

Compute selectivity for the flat map of tf

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fn predicate( &self, expr: &MirScalarExpr, unique_columns: &BTreeSet<usize> ) -> SymExp

Computes selectivity of the predicate expr, given that unique_columns are indexed/unique

The result should be in the range [0, 1.0]

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fn filter( &self, predicates: &Vec<MirScalarExpr>, keys: &Vec<Vec<usize>>, input: &SymExp ) -> SymExp

Computes selectivity for a filter

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fn join( &self, equivalences: &Vec<Vec<MirScalarExpr>>, implementation: &JoinImplementation, unique_columns: BTreeMap<usize, usize>, inputs: Vec<&SymExp> ) -> SymExp

Computes selectivity for a join; the cardinality estimate for each input is paired with the keys on that input

unique_columns maps column references (that are indexed/unique) to their relation’s index in inputs

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fn reduce( &self, group_key: &Vec<MirScalarExpr>, expected_group_size: &Option<u64>, input: &SymExp ) -> SymExp

Computes selectivity for a reduce

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fn topk( &self, group_key: &Vec<usize>, limit: &Option<MirScalarExpr>, expected_group_size: &Option<u64>, input: &SymExp ) -> SymExp

Computes selectivity for a topk

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fn threshold(&self, input: &SymExp) -> SymExp

Computes slectivity for a threshold

Implementors§