Package com.hashicorp.cdktf.providers.google.vertex_ai_index

Class VertexAiIndexMetadataConfig.Builder

    • Constructor Detail

      • Builder

        public Builder()

    • Method Detail

      • dimensions

        @Stability(Stable)
public VertexAiIndexMetadataConfig.Builder dimensions​(Number dimensions)
        Sets the value of VertexAiIndexMetadataConfig.getDimensions()
        Parameters:
        dimensions - The number of dimensions of the input vectors. This parameter is required. Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/vertex_ai_index#dimensions VertexAiIndex#dimensions}
        Returns:
        this

      • approximateNeighborsCount

        @Stability(Stable)
public VertexAiIndexMetadataConfig.Builder approximateNeighborsCount​(Number approximateNeighborsCount)
        Sets the value of VertexAiIndexMetadataConfig.getApproximateNeighborsCount()
        Parameters:
        approximateNeighborsCount - The default number of neighbors to find via approximate search before exact reordering is performed. Exact reordering is a procedure where results returned by an approximate search algorithm are reordered via a more expensive distance computation. Required if tree-AH algorithm is used. Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/vertex_ai_index#approximate_neighbors_count VertexAiIndex#approximate_neighbors_count}
        Returns:
        this

      • distanceMeasureType

        @Stability(Stable)
public VertexAiIndexMetadataConfig.Builder distanceMeasureType​(String distanceMeasureType)
        Sets the value of VertexAiIndexMetadataConfig.getDistanceMeasureType()
        Parameters:
        distanceMeasureType - The distance measure used in nearest neighbor search. The value must be one of the followings: * SQUARED_L2_DISTANCE: Euclidean (L_2) Distance * L1_DISTANCE: Manhattan (L_1) Distance * COSINE_DISTANCE: Cosine Distance. Defined as 1 - cosine similarity. * DOT_PRODUCT_DISTANCE: Dot Product Distance. Defined as a negative of the dot product Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/vertex_ai_index#distance_measure_type VertexAiIndex#distance_measure_type}
        Returns:
        this

      • featureNormType

        @Stability(Stable)
public VertexAiIndexMetadataConfig.Builder featureNormType​(String featureNormType)
        Sets the value of VertexAiIndexMetadataConfig.getFeatureNormType()
        Parameters:
        featureNormType - Type of normalization to be carried out on each vector. The value must be one of the followings: * UNIT_L2_NORM: Unit L2 normalization type * NONE: No normalization type is specified. Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/vertex_ai_index#feature_norm_type VertexAiIndex#feature_norm_type}
        Returns:
        this

      • shardSize

        @Stability(Stable)
public VertexAiIndexMetadataConfig.Builder shardSize​(String shardSize)
        Sets the value of VertexAiIndexMetadataConfig.getShardSize()
        Parameters:
        shardSize - Index data is split into equal parts to be processed. These are called "shards". The shard size must be specified when creating an index. The value must be one of the followings: * SHARD_SIZE_SMALL: Small (2GB) * SHARD_SIZE_MEDIUM: Medium (20GB) * SHARD_SIZE_LARGE: Large (50GB) Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/vertex_ai_index#shard_size VertexAiIndex#shard_size}
        Returns:
        this