AiFeatureOnlineStoreFeatureviewVectorSearchConfigArgs

data class AiFeatureOnlineStoreFeatureviewVectorSearchConfigArgs(val bruteForceConfig: Output<AiFeatureOnlineStoreFeatureviewVectorSearchConfigBruteForceConfigArgs>? = null, val crowdingColumn: Output<String>? = null, val distanceMeasureType: Output<String>? = null, val embeddingColumn: Output<String>, val embeddingDimension: Output<Int>? = null, val filterColumns: Output<List<String>>? = null, val treeAhConfig: Output<AiFeatureOnlineStoreFeatureviewVectorSearchConfigTreeAhConfigArgs>? = null) : ConvertibleToJava<AiFeatureOnlineStoreFeatureviewVectorSearchConfigArgs>

Constructors

constructor(bruteForceConfig: Output<AiFeatureOnlineStoreFeatureviewVectorSearchConfigBruteForceConfigArgs>? = null, crowdingColumn: Output<String>? = null, distanceMeasureType: Output<String>? = null, embeddingColumn: Output<String>, embeddingDimension: Output<Int>? = null, filterColumns: Output<List<String>>? = null, treeAhConfig: Output<AiFeatureOnlineStoreFeatureviewVectorSearchConfigTreeAhConfigArgs>? = null)

Properties

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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.

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val crowdingColumn: Output<String>? = null

Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowdingAttribute.

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val distanceMeasureType: Output<String>? = null

The distance measure used in nearest neighbor search. For details on allowed values, see the API documentation. Possible values are: SQUARED_L2_DISTANCE, COSINE_DISTANCE, DOT_PRODUCT_DISTANCE.

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val embeddingColumn: Output<String>

Column of embedding. This column contains the source data to create index for vector search.

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val embeddingDimension: Output<Int>? = null

The number of dimensions of the input embedding.

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val filterColumns: Output<List<String>>? = null

Columns of features that are used to filter vector search results.

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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 Structure is documented below.

Functions

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open override fun toJava(): AiFeatureOnlineStoreFeatureviewVectorSearchConfigArgs