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

Interface VertexAiIndexMetadataConfig

  • All Superinterfaces:
    software.amazon.jsii.JsiiSerializable
    All Known Implementing Classes:
    VertexAiIndexMetadataConfig.Jsii$Proxy
    @Generated(value="jsii-pacmak/1.102.0 (build e354887)",
           date="2024-08-31T03:59:22.979Z")
@Stability(Stable)
public interface VertexAiIndexMetadataConfig
extends software.amazon.jsii.JsiiSerializable

    • Method Detail

      • getDimensions

        @Stability(Stable)
@NotNull
Number getDimensions()
        The number of dimensions of the input vectors.

        Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/vertex_ai_index#dimensions VertexAiIndex#dimensions}

      • getAlgorithmConfig

        @Stability(Stable)
@Nullable
default VertexAiIndexMetadataConfigAlgorithmConfig getAlgorithmConfig()
        algorithm_config block.

        Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/vertex_ai_index#algorithm_config VertexAiIndex#algorithm_config}

      • getApproximateNeighborsCount

        @Stability(Stable)
@Nullable
default Number getApproximateNeighborsCount()
        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}

      • getDistanceMeasureType

        @Stability(Stable)
@Nullable
default String getDistanceMeasureType()
        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}

      • getFeatureNormType

        @Stability(Stable)
@Nullable
default String getFeatureNormType()
        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}

      • getShardSize

        @Stability(Stable)
@Nullable
default String getShardSize()
        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}