Enum DistanceMetric 

pub enum DistanceMetric {
    L2,
    Cosine,
    Dot,
}

Distance metric used to rank candidates during vector search.

All variants are normalized so that a smaller value means a closer match, keeping the search ranking ascending regardless of metric.

Variants

L2

Euclidean (L2) distance. Default for backward compatibility.

Cosine

Cosine distance (1 - cosine_similarity). Common for normalized embeddings from most modern models.

Dot

Negated dot product (maximum inner product search).

Implementations

impl DistanceMetric

pub fn parse(value: &str) -> LanceResult<Self>

Parse a metric from its string identifier ("l2", "cosine", "dot"). Matching is case-insensitive.

Errors

Returns an error if the identifier is not a recognized metric.

pub fn distance(self, query: &[f32], candidate: &[f32]) -> f32

Compute the metric between a query and a candidate vector.

The returned value is always “smaller is better”.

pub fn as_str(self) -> &'static str

Stable string identifier for this metric, used when persisting it in dataset schema metadata. Round-trips through DistanceMetric::parse.

Trait Implementations

impl Clone for DistanceMetric

fn clone(&self) -> DistanceMetric

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Copy for DistanceMetric

impl Debug for DistanceMetric

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

Formats the value using the given formatter.

impl Default for DistanceMetric

fn default() -> DistanceMetric

Returns the “default value” for a type.

impl Eq for DistanceMetric

impl PartialEq for DistanceMetric

fn eq(&self, other: &DistanceMetric) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for DistanceMetric