Struct google_api_proto::google::cloud::aiplatform::v1beta1::feature_view::VectorSearchConfig

pub struct VectorSearchConfig {
    pub embedding_column: String,
    pub filter_columns: Vec<String>,
    pub crowding_column: String,
    pub embedding_dimension: Option<i32>,
    pub distance_measure_type: i32,
    pub algorithm_config: Option<AlgorithmConfig>,
}

Deprecated. Use [IndexConfig][google.cloud.aiplatform.v1beta1.FeatureView.IndexConfig] instead.

Fields

embedding_column: String

Optional. Column of embedding. This column contains the source data to create index for vector search. embedding_column must be set when using vector search.

filter_columns: Vec<String>

Optional. Columns of features that’re used to filter vector search results.

crowding_column: String

Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by [FeatureOnlineStoreService.SearchNearestEntities][google.cloud.aiplatform.v1beta1.FeatureOnlineStoreService.SearchNearestEntities] to diversify search results. If [NearestNeighborQuery.per_crowding_attribute_neighbor_count][google.cloud.aiplatform.v1beta1.NearestNeighborQuery.per_crowding_attribute_neighbor_count] is set to K in [SearchNearestEntitiesRequest][google.cloud.aiplatform.v1beta1.SearchNearestEntitiesRequest], it’s guaranteed that no more than K entities of the same crowding attribute are returned in the response.

embedding_dimension: Option<i32>

Optional. The number of dimensions of the input embedding.

distance_measure_type: i32

Optional. The distance measure used in nearest neighbor search.

algorithm_config: Option<AlgorithmConfig>

The configuration with regard to the algorithms used for efficient search.

Implementations

impl VectorSearchConfig

pub fn embedding_dimension(&self) -> i32

Returns the value of embedding_dimension, or the default value if embedding_dimension is unset.

pub fn distance_measure_type(&self) -> DistanceMeasureType

Returns the enum value of distance_measure_type, or the default if the field is set to an invalid enum value.

pub fn set_distance_measure_type(&mut self, value: DistanceMeasureType)

Sets distance_measure_type to the provided enum value.

Trait Implementations

impl Clone for VectorSearchConfig

fn clone(&self) -> VectorSearchConfig

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for VectorSearchConfig

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

Formats the value using the given formatter.

impl Default for VectorSearchConfig

fn default() -> Self

Returns the “default value” for a type.

impl Message for VectorSearchConfig

fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)

Clears the message, resetting all fields to their default.

fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message to a buffer.

fn encode_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message to a newly allocated buffer.

fn encode_length_delimited( &self, buf: &mut impl BufMut, ) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message with a length-delimiter to a buffer.

fn encode_length_delimited_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message with a length-delimiter to a newly allocated buffer.

fn decode(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes an instance of the message from a buffer.

fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes a length-delimited instance of the message from the buffer.

fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes an instance of the message from a buffer, and merges it into self.

fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq for VectorSearchConfig

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

This method tests for self and other values to be equal, and is used by ==.

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

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

impl StructuralPartialEq for VectorSearchConfig