Class GoogleCloudAiplatformV1FeatureViewIndexConfig

Configuration for vector indexing.

Inheritance

object

GoogleCloudAiplatformV1FeatureViewIndexConfig

Implements

IDirectResponseSchema

Inherited Members

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Namespace: Google.Apis.Aiplatform.v1.Data

Assembly: Google.Apis.Aiplatform.v1.dll

Syntax

public class GoogleCloudAiplatformV1FeatureViewIndexConfig : IDirectResponseSchema

Properties

BruteForceConfig

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.

Declaration

[JsonProperty("bruteForceConfig")]
public virtual GoogleCloudAiplatformV1FeatureViewIndexConfigBruteForceConfig BruteForceConfig { get; set; }

Property Value

Type	Description
GoogleCloudAiplatformV1FeatureViewIndexConfigBruteForceConfig

CrowdingColumn

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.

Declaration

[JsonProperty("crowdingColumn")]
public virtual string CrowdingColumn { get; set; }

Property Value

Type	Description
string

DistanceMeasureType

Optional. The distance measure used in nearest neighbor search.

Declaration

[JsonProperty("distanceMeasureType")]
public virtual string DistanceMeasureType { get; set; }

Property Value

Type	Description
string

ETag

The ETag of the item.

Declaration

public virtual string ETag { get; set; }

Property Value

Type	Description
string

EmbeddingColumn

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.

Declaration

[JsonProperty("embeddingColumn")]
public virtual string EmbeddingColumn { get; set; }

Property Value

Type	Description
string

EmbeddingDimension

Optional. The number of dimensions of the input embedding.

Declaration

[JsonProperty("embeddingDimension")]
public virtual int? EmbeddingDimension { get; set; }

Property Value

Type	Description
int?

FilterColumns

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

Declaration

[JsonProperty("filterColumns")]
public virtual IList<string> FilterColumns { get; set; }

Property Value

Type	Description
IList<string>

TreeAhConfig

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

Declaration

[JsonProperty("treeAhConfig")]
public virtual GoogleCloudAiplatformV1FeatureViewIndexConfigTreeAHConfig TreeAhConfig { get; set; }

Property Value

Type	Description
GoogleCloudAiplatformV1FeatureViewIndexConfigTreeAHConfig

Implements

IDirectResponseSchema