Cloud AI Platform v1 API - Class FeatureView.Types.IndexConfig (2.27.0)

public sealed class FeatureView.Types.IndexConfig : IMessage<FeatureView.Types.IndexConfig>, IEquatable<FeatureView.Types.IndexConfig>, IDeepCloneable<FeatureView.Types.IndexConfig>, IBufferMessage, IMessage

Reference documentation and code samples for the Cloud AI Platform v1 API class FeatureView.Types.IndexConfig.

Configuration for vector indexing.

Inheritance

object > FeatureView.Types.IndexConfig

Implements

IMessage FeatureView Types IndexConfig, IEquatable FeatureView Types IndexConfig, IDeepCloneable FeatureView Types IndexConfig, IBufferMessage, IMessage

Inherited Members

object.GetHashCode()

object.GetType()

object.ToString()

Namespace

Google.Cloud.AIPlatform.V1

Assembly

Google.Cloud.AIPlatform.V1.dll

Constructors

IndexConfig()

public IndexConfig()

IndexConfig(IndexConfig)

public IndexConfig(FeatureView.Types.IndexConfig other)

Parameter
Name	Description
`other`	`FeatureViewTypesIndexConfig`

Properties

AlgorithmConfigCase

public FeatureView.Types.IndexConfig.AlgorithmConfigOneofCase AlgorithmConfigCase { get; }

Property Value
Type	Description
`FeatureViewTypesIndexConfigAlgorithmConfigOneofCase`

BruteForceConfig

public FeatureView.Types.IndexConfig.Types.BruteForceConfig BruteForceConfig { get; set; }

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.

Property Value
Type	Description
`FeatureViewTypesIndexConfigTypesBruteForceConfig`

CrowdingColumn

public string CrowdingColumn { get; set; }

Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by [FeatureOnlineStoreService.SearchNearestEntities][google.cloud.aiplatform.v1.FeatureOnlineStoreService.SearchNearestEntities] to diversify search results. If [NearestNeighborQuery.per_crowding_attribute_neighbor_count][google.cloud.aiplatform.v1.NearestNeighborQuery.per_crowding_attribute_neighbor_count] is set to K in [SearchNearestEntitiesRequest][google.cloud.aiplatform.v1.SearchNearestEntitiesRequest], it's guaranteed that no more than K entities of the same crowding attribute are returned in the response.

Property Value
Type	Description
`string`

DistanceMeasureType

public FeatureView.Types.IndexConfig.Types.DistanceMeasureType DistanceMeasureType { get; set; }

Optional. The distance measure used in nearest neighbor search.

Property Value
Type	Description
`FeatureViewTypesIndexConfigTypesDistanceMeasureType`

EmbeddingColumn

public string EmbeddingColumn { get; set; }

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.

Property Value
Type	Description
`string`

EmbeddingDimension

public int EmbeddingDimension { get; set; }

Optional. The number of dimensions of the input embedding.

Property Value
Type	Description
`int`

FilterColumns

public RepeatedField<string> FilterColumns { get; }

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

Property Value
Type	Description
`RepeatedFieldstring`

HasEmbeddingDimension

public bool HasEmbeddingDimension { get; }

Gets whether the "embedding_dimension" field is set

Property Value
Type	Description
`bool`

TreeAhConfig

public FeatureView.Types.IndexConfig.Types.TreeAHConfig TreeAhConfig { get; set; }

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

Property Value
Type	Description
`FeatureViewTypesIndexConfigTypesTreeAHConfig`