Enum RetrievalExpr 

pub enum RetrievalExpr {
    Empty,
    Term {
        query: String,
        field: Option<String>,
        scoring: Option<TextScoringMode>,
    },
    Phrase {
        query: String,
        field: Option<String>,
        scoring: Option<TextScoringMode>,
    },
    Filter {
        field: String,
        predicate: Predicate,
        source: Option<Box<Self>>,
    },
    BayesianScore {
        source: Box<Self>,
        field: Option<String>,
    },
    BayesianMatchWithPrior {
        field: String,
        query: String,
        prior_field: String,
        mode: ExternalPriorMode,
    },
    Intersect(Vec<Self>),
    Union(Vec<Self>),
    Complement(Box<Self>),
    Composed(Vec<Self>),
    EncodeGraphPosting {
        source: Box<Self>,
    },
    KNN {
        query_vector: Vec<f32>,
        k: usize,
        field: String,
    },
    CalibratedVectorMatch {
        query_vector: Vec<f32>,
        k: usize,
        field: String,
        threshold: Option<f64>,
    },
    CosineProbability(Box<Self>),
    BayesianEvidenceFusion {
        signals: Vec<Self>,
        base_rate: Option<f64>,
    },
    RobustPositiveEvidencePool {
        signals: Vec<Self>,
        alpha: f64,
        gating: GatingSpec,
        weights: Option<Vec<f64>>,
        logit_min: Option<Vec<f64>>,
        logit_max: Option<Vec<f64>>,
        adaptive_weights: bool,
    },
    AttentionFusion {
        signals: Vec<Self>,
        options: AttentionSpec,
        function_name: String,
    },
    LearnedFusion {
        signals: Vec<Self>,
        alpha: f64,
    },
    SparseThreshold {
        source: Box<Self>,
        threshold: f64,
    },
    Traverse {
        start_vertex: u64,
        graph: String,
        label: Option<String>,
        max_hops: usize,
    },
    GraphNeighbors {
        vertex: u64,
        graph: String,
        label: Option<String>,
        direction: Direction,
    },
    GraphEdges {
        graph: String,
        label: Option<String>,
    },
    RegularPathQuery {
        rpq_source: String,
        start_vertex: u64,
        graph: String,
    },
    TemporalTraverse {
        start_vertex: u64,
        graph: String,
        label: Option<String>,
        max_hops: usize,
        temporal_filter: Option<TemporalFilterIR>,
    },
    PageRank {
        graph: String,
    },
    HITS {
        graph: String,
    },
    BetweennessCentrality {
        graph: String,
    },
    DeepPredict {
        model: String,
    },
    MultiStage {
        stages: Vec<MultiStageEntry>,
    },
    MultiFieldSearch {
        fields: Vec<String>,
        queries: Vec<String>,
        weights: Option<Vec<f64>>,
    },
    TextSimilarityJoin {
        left: Box<Self>,
        right: Box<Self>,
        threshold: f64,
    },
    VectorSimilarityJoin {
        left: Box<Self>,
        right: Box<Self>,
        threshold: f64,
    },
    GraphJoin {
        left: Box<Self>,
        right: Box<Self>,
        label: Option<String>,
        graph: String,
    },
    HybridJoin {
        left: Box<Self>,
        right: Box<Self>,
    },
    CrossParadigmJoin {
        left: Box<Self>,
        right: Box<Self>,
    },
}

SQL-owned retrieval algebra. Physical scorers, fusers, closures, index choices and top-k strategies do not belong to this representation.

Variants

Empty

Term

Fields

query: String

field: Option<String>

scoring: Option<TextScoringMode>

Phrase

Preserve the complete quoted input for one field-specific token-graph analysis.

Fields

query: String

field: Option<String>

scoring: Option<TextScoringMode>

Filter

Fields

field: String

predicate: Predicate

source: Option<Box<Self>>

BayesianScore

Fields

source: Box<Self>

field: Option<String>

BayesianMatchWithPrior

Fields

field: String

query: String

prior_field: String

mode: ExternalPriorMode

Intersect(Vec<Self>)

Union(Vec<Self>)

Complement(Box<Self>)

Composed(Vec<Self>)

EncodeGraphPosting

Fields

source: Box<Self>

KNN

Fields

query_vector: Vec<f32>

k: usize

field: String

CalibratedVectorMatch

Fields

query_vector: Vec<f32>

k: usize

field: String

threshold: Option<f64>

CosineProbability(Box<Self>)

BayesianEvidenceFusion

Fields

signals: Vec<Self>

base_rate: Option<f64>

RobustPositiveEvidencePool

Fields

signals: Vec<Self>

alpha: f64

gating: GatingSpec

weights: Option<Vec<f64>>

logit_min: Option<Vec<f64>>

logit_max: Option<Vec<f64>>

adaptive_weights: bool

AttentionFusion

Fields

signals: Vec<Self>

options: AttentionSpec

function_name: String

LearnedFusion

Fields

signals: Vec<Self>

alpha: f64

SparseThreshold

Fields

source: Box<Self>

threshold: f64

Traverse

Fields

start_vertex: u64

graph: String

label: Option<String>

max_hops: usize

GraphNeighbors

Fields

vertex: u64

graph: String

label: Option<String>

direction: Direction

GraphEdges

Fields

graph: String

label: Option<String>

RegularPathQuery

Fields

rpq_source: String

start_vertex: u64

graph: String

TemporalTraverse

Fields

start_vertex: u64

graph: String

label: Option<String>

max_hops: usize

temporal_filter: Option<TemporalFilterIR>

PageRank

Fields

graph: String

HITS

Fields

graph: String

BetweennessCentrality

Fields

graph: String

DeepPredict

Fields

model: String

MultiStage

Fields

stages: Vec<MultiStageEntry>

MultiFieldSearch

Fields

fields: Vec<String>

queries: Vec<String>

weights: Option<Vec<f64>>

TextSimilarityJoin

Fields

left: Box<Self>

right: Box<Self>

threshold: f64

VectorSimilarityJoin

Fields

left: Box<Self>

right: Box<Self>

threshold: f64

GraphJoin

Fields

left: Box<Self>

right: Box<Self>

label: Option<String>

graph: String

HybridJoin

Fields

left: Box<Self>

right: Box<Self>

CrossParadigmJoin

Fields

left: Box<Self>

right: Box<Self>

Trait Implementations

impl Clone for RetrievalExpr

fn clone(&self) -> RetrievalExpr

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for RetrievalExpr

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.