Struct GoogleCloudAiplatformV1FeatureViewIndexConfig

pub struct GoogleCloudAiplatformV1FeatureViewIndexConfig {
    pub embedding_column: Option<String>,
    pub crowding_column: Option<String>,
    pub distance_measure_type: Option<String>,
    pub tree_ah_config: Option<GoogleCloudAiplatformV1FeatureViewIndexConfigTreeAHConfig>,
    pub embedding_dimension: Option<i32>,
    pub filter_columns: Option<Vec<String>>,
    pub brute_force_config: Option<GoogleCloudAiplatformV1FeatureViewIndexConfigBruteForceConfig>,
}

Configuration for vector indexing.

This type is not used in any activity, and only used as part of another schema.

Fields

embedding_column: Option<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.

crowding_column: Option<String>

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

distance_measure_type: Option<String>

Optional. The distance measure used in nearest neighbor search.

tree_ah_config: Option<GoogleCloudAiplatformV1FeatureViewIndexConfigTreeAHConfig>

Optional. Configuration options for the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396

embedding_dimension: Option<i32>

Optional. The number of dimensions of the input embedding.

filter_columns: Option<Vec<String>>

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

brute_force_config: Option<GoogleCloudAiplatformV1FeatureViewIndexConfigBruteForceConfig>

Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search.

Trait Implementations

impl Clone for GoogleCloudAiplatformV1FeatureViewIndexConfig

fn clone(&self) -> GoogleCloudAiplatformV1FeatureViewIndexConfig

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for GoogleCloudAiplatformV1FeatureViewIndexConfig

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

Formats the value using the given formatter.

impl Default for GoogleCloudAiplatformV1FeatureViewIndexConfig

fn default() -> GoogleCloudAiplatformV1FeatureViewIndexConfig

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for GoogleCloudAiplatformV1FeatureViewIndexConfig

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for GoogleCloudAiplatformV1FeatureViewIndexConfig

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Part for GoogleCloudAiplatformV1FeatureViewIndexConfig