Package com.google.cloud.aiplatform.v1

Interface FeatureView.IndexConfigOrBuilder

All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
All Known Implementing Classes:
FeatureView.IndexConfig, FeatureView.IndexConfig.Builder
Enclosing class:
FeatureView
public static interface FeatureView.IndexConfigOrBuilder extends com.google.protobuf.MessageOrBuilder

  • Method Details

    • hasTreeAhConfig

      boolean hasTreeAhConfig()
       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
      .google.cloud.aiplatform.v1.FeatureView.IndexConfig.TreeAHConfig tree_ah_config = 6 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      Whether the treeAhConfig field is set.

    • getTreeAhConfig

      FeatureView.IndexConfig.TreeAHConfig getTreeAhConfig()
       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
      .google.cloud.aiplatform.v1.FeatureView.IndexConfig.TreeAHConfig tree_ah_config = 6 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The treeAhConfig.

    • getTreeAhConfigOrBuilder

      FeatureView.IndexConfig.TreeAHConfigOrBuilder getTreeAhConfigOrBuilder()
       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
      .google.cloud.aiplatform.v1.FeatureView.IndexConfig.TreeAHConfig tree_ah_config = 6 [(.google.api.field_behavior) = OPTIONAL];

    • hasBruteForceConfig

      boolean hasBruteForceConfig()
       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.
      .google.cloud.aiplatform.v1.FeatureView.IndexConfig.BruteForceConfig brute_force_config = 7 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      Whether the bruteForceConfig field is set.

    • getBruteForceConfig

      FeatureView.IndexConfig.BruteForceConfig getBruteForceConfig()
       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.
      .google.cloud.aiplatform.v1.FeatureView.IndexConfig.BruteForceConfig brute_force_config = 7 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The bruteForceConfig.

    • getBruteForceConfigOrBuilder

      FeatureView.IndexConfig.BruteForceConfigOrBuilder getBruteForceConfigOrBuilder()
       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.
      .google.cloud.aiplatform.v1.FeatureView.IndexConfig.BruteForceConfig brute_force_config = 7 [(.google.api.field_behavior) = OPTIONAL];

    • getEmbeddingColumn

      String getEmbeddingColumn()
       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.
      string embedding_column = 1 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The embeddingColumn.

    • getEmbeddingColumnBytes

      com.google.protobuf.ByteString getEmbeddingColumnBytes()
       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.
      string embedding_column = 1 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The bytes for embeddingColumn.

    • getFilterColumnsList

      List<String> getFilterColumnsList()
       Optional. Columns of features that're used to filter vector search
 results.
      repeated string filter_columns = 2 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      A list containing the filterColumns.

    • getFilterColumnsCount

      int getFilterColumnsCount()
       Optional. Columns of features that're used to filter vector search
 results.
      repeated string filter_columns = 2 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The count of filterColumns.

    • getFilterColumns

      String getFilterColumns(int index)
       Optional. Columns of features that're used to filter vector search
 results.
      repeated string filter_columns = 2 [(.google.api.field_behavior) = OPTIONAL];
      Parameters:
      index - The index of the element to return.
      Returns:
      The filterColumns at the given index.

    • getFilterColumnsBytes

      com.google.protobuf.ByteString getFilterColumnsBytes(int index)
       Optional. Columns of features that're used to filter vector search
 results.
      repeated string filter_columns = 2 [(.google.api.field_behavior) = OPTIONAL];
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the filterColumns at the given index.

    • getCrowdingColumn

      String getCrowdingColumn()
       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.
      string crowding_column = 3 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The crowdingColumn.

    • getCrowdingColumnBytes

      com.google.protobuf.ByteString getCrowdingColumnBytes()
       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.
      string crowding_column = 3 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The bytes for crowdingColumn.

    • hasEmbeddingDimension

      boolean hasEmbeddingDimension()
       Optional. The number of dimensions of the input embedding.
      optional int32 embedding_dimension = 4 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      Whether the embeddingDimension field is set.

    • getEmbeddingDimension

      int getEmbeddingDimension()
       Optional. The number of dimensions of the input embedding.
      optional int32 embedding_dimension = 4 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The embeddingDimension.

    • getDistanceMeasureTypeValue

      int getDistanceMeasureTypeValue()
       Optional. The distance measure used in nearest neighbor search.
      .google.cloud.aiplatform.v1.FeatureView.IndexConfig.DistanceMeasureType distance_measure_type = 5 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The enum numeric value on the wire for distanceMeasureType.

    • getDistanceMeasureType

      FeatureView.IndexConfig.DistanceMeasureType getDistanceMeasureType()
       Optional. The distance measure used in nearest neighbor search.
      .google.cloud.aiplatform.v1.FeatureView.IndexConfig.DistanceMeasureType distance_measure_type = 5 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The distanceMeasureType.

    • getAlgorithmConfigCase

      FeatureView.IndexConfig.AlgorithmConfigCase getAlgorithmConfigCase()