Class FeatureView.IndexConfig.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<FeatureView.IndexConfig.Builder>
com.google.cloud.aiplatform.v1.FeatureView.IndexConfig.Builder
All Implemented Interfaces:
FeatureView.IndexConfigOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
Enclosing class:
FeatureView.IndexConfig

public static final class FeatureView.IndexConfig.Builder extends com.google.protobuf.GeneratedMessage.Builder<FeatureView.IndexConfig.Builder> implements FeatureView.IndexConfigOrBuilder
 Configuration for vector indexing.
 
Protobuf type google.cloud.aiplatform.v1.FeatureView.IndexConfig
  • Method Details

    • getDescriptor

      public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()
    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<FeatureView.IndexConfig.Builder>
    • clear

      Specified by:
      clear in interface com.google.protobuf.Message.Builder
      Specified by:
      clear in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      clear in class com.google.protobuf.GeneratedMessage.Builder<FeatureView.IndexConfig.Builder>
    • getDescriptorForType

      public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
      Specified by:
      getDescriptorForType in interface com.google.protobuf.Message.Builder
      Specified by:
      getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
      Overrides:
      getDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<FeatureView.IndexConfig.Builder>
    • getDefaultInstanceForType

      public FeatureView.IndexConfig getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder
    • build

      public FeatureView.IndexConfig build()
      Specified by:
      build in interface com.google.protobuf.Message.Builder
      Specified by:
      build in interface com.google.protobuf.MessageLite.Builder
    • buildPartial

      public FeatureView.IndexConfig buildPartial()
      Specified by:
      buildPartial in interface com.google.protobuf.Message.Builder
      Specified by:
      buildPartial in interface com.google.protobuf.MessageLite.Builder
    • mergeFrom

      public FeatureView.IndexConfig.Builder mergeFrom(com.google.protobuf.Message other)
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<FeatureView.IndexConfig.Builder>
    • mergeFrom

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessage.Builder<FeatureView.IndexConfig.Builder>
    • mergeFrom

      public FeatureView.IndexConfig.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Specified by:
      mergeFrom in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<FeatureView.IndexConfig.Builder>
      Throws:
      IOException
    • getAlgorithmConfigCase

      public FeatureView.IndexConfig.AlgorithmConfigCase getAlgorithmConfigCase()
      Specified by:
      getAlgorithmConfigCase in interface FeatureView.IndexConfigOrBuilder
    • clearAlgorithmConfig

      public FeatureView.IndexConfig.Builder clearAlgorithmConfig()
    • hasTreeAhConfig

      public 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];
      Specified by:
      hasTreeAhConfig in interface FeatureView.IndexConfigOrBuilder
      Returns:
      Whether the treeAhConfig field is set.
    • getTreeAhConfig

      public 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];
      Specified by:
      getTreeAhConfig in interface FeatureView.IndexConfigOrBuilder
      Returns:
      The treeAhConfig.
    • setTreeAhConfig

       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];
    • setTreeAhConfig

       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];
    • mergeTreeAhConfig

       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];
    • clearTreeAhConfig

      public FeatureView.IndexConfig.Builder clearTreeAhConfig()
       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];
    • getTreeAhConfigBuilder

      public FeatureView.IndexConfig.TreeAHConfig.Builder getTreeAhConfigBuilder()
       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];
    • getTreeAhConfigOrBuilder

      public 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];
      Specified by:
      getTreeAhConfigOrBuilder in interface FeatureView.IndexConfigOrBuilder
    • hasBruteForceConfig

      public 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];
      Specified by:
      hasBruteForceConfig in interface FeatureView.IndexConfigOrBuilder
      Returns:
      Whether the bruteForceConfig field is set.
    • getBruteForceConfig

      public 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];
      Specified by:
      getBruteForceConfig in interface FeatureView.IndexConfigOrBuilder
      Returns:
      The bruteForceConfig.
    • setBruteForceConfig

       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];
    • setBruteForceConfig

       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];
    • mergeBruteForceConfig

       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];
    • clearBruteForceConfig

      public FeatureView.IndexConfig.Builder clearBruteForceConfig()
       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];
    • getBruteForceConfigBuilder

      public FeatureView.IndexConfig.BruteForceConfig.Builder getBruteForceConfigBuilder()
       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];
    • getBruteForceConfigOrBuilder

      public 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];
      Specified by:
      getBruteForceConfigOrBuilder in interface FeatureView.IndexConfigOrBuilder
    • getEmbeddingColumn

      public 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];
      Specified by:
      getEmbeddingColumn in interface FeatureView.IndexConfigOrBuilder
      Returns:
      The embeddingColumn.
    • getEmbeddingColumnBytes

      public 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];
      Specified by:
      getEmbeddingColumnBytes in interface FeatureView.IndexConfigOrBuilder
      Returns:
      The bytes for embeddingColumn.
    • setEmbeddingColumn

      public FeatureView.IndexConfig.Builder setEmbeddingColumn(String value)
       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];
      Parameters:
      value - The embeddingColumn to set.
      Returns:
      This builder for chaining.
    • clearEmbeddingColumn

      public FeatureView.IndexConfig.Builder clearEmbeddingColumn()
       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:
      This builder for chaining.
    • setEmbeddingColumnBytes

      public FeatureView.IndexConfig.Builder setEmbeddingColumnBytes(com.google.protobuf.ByteString value)
       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];
      Parameters:
      value - The bytes for embeddingColumn to set.
      Returns:
      This builder for chaining.
    • getFilterColumnsList

      public com.google.protobuf.ProtocolStringList getFilterColumnsList()
       Optional. Columns of features that're used to filter vector search
       results.
       
      repeated string filter_columns = 2 [(.google.api.field_behavior) = OPTIONAL];
      Specified by:
      getFilterColumnsList in interface FeatureView.IndexConfigOrBuilder
      Returns:
      A list containing the filterColumns.
    • getFilterColumnsCount

      public int getFilterColumnsCount()
       Optional. Columns of features that're used to filter vector search
       results.
       
      repeated string filter_columns = 2 [(.google.api.field_behavior) = OPTIONAL];
      Specified by:
      getFilterColumnsCount in interface FeatureView.IndexConfigOrBuilder
      Returns:
      The count of filterColumns.
    • getFilterColumns

      public 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];
      Specified by:
      getFilterColumns in interface FeatureView.IndexConfigOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The filterColumns at the given index.
    • getFilterColumnsBytes

      public 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];
      Specified by:
      getFilterColumnsBytes in interface FeatureView.IndexConfigOrBuilder
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the filterColumns at the given index.
    • setFilterColumns

      public FeatureView.IndexConfig.Builder setFilterColumns(int index, String value)
       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 to set the value at.
      value - The filterColumns to set.
      Returns:
      This builder for chaining.
    • addFilterColumns

      public FeatureView.IndexConfig.Builder addFilterColumns(String value)
       Optional. Columns of features that're used to filter vector search
       results.
       
      repeated string filter_columns = 2 [(.google.api.field_behavior) = OPTIONAL];
      Parameters:
      value - The filterColumns to add.
      Returns:
      This builder for chaining.
    • addAllFilterColumns

      public FeatureView.IndexConfig.Builder addAllFilterColumns(Iterable<String> values)
       Optional. Columns of features that're used to filter vector search
       results.
       
      repeated string filter_columns = 2 [(.google.api.field_behavior) = OPTIONAL];
      Parameters:
      values - The filterColumns to add.
      Returns:
      This builder for chaining.
    • clearFilterColumns

      public FeatureView.IndexConfig.Builder clearFilterColumns()
       Optional. Columns of features that're used to filter vector search
       results.
       
      repeated string filter_columns = 2 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      This builder for chaining.
    • addFilterColumnsBytes

      public FeatureView.IndexConfig.Builder addFilterColumnsBytes(com.google.protobuf.ByteString value)
       Optional. Columns of features that're used to filter vector search
       results.
       
      repeated string filter_columns = 2 [(.google.api.field_behavior) = OPTIONAL];
      Parameters:
      value - The bytes of the filterColumns to add.
      Returns:
      This builder for chaining.
    • getCrowdingColumn

      public 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];
      Specified by:
      getCrowdingColumn in interface FeatureView.IndexConfigOrBuilder
      Returns:
      The crowdingColumn.
    • getCrowdingColumnBytes

      public 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];
      Specified by:
      getCrowdingColumnBytes in interface FeatureView.IndexConfigOrBuilder
      Returns:
      The bytes for crowdingColumn.
    • setCrowdingColumn

      public FeatureView.IndexConfig.Builder setCrowdingColumn(String value)
       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];
      Parameters:
      value - The crowdingColumn to set.
      Returns:
      This builder for chaining.
    • clearCrowdingColumn

      public FeatureView.IndexConfig.Builder clearCrowdingColumn()
       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:
      This builder for chaining.
    • setCrowdingColumnBytes

      public FeatureView.IndexConfig.Builder setCrowdingColumnBytes(com.google.protobuf.ByteString value)
       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];
      Parameters:
      value - The bytes for crowdingColumn to set.
      Returns:
      This builder for chaining.
    • hasEmbeddingDimension

      public boolean hasEmbeddingDimension()
       Optional. The number of dimensions of the input embedding.
       
      optional int32 embedding_dimension = 4 [(.google.api.field_behavior) = OPTIONAL];
      Specified by:
      hasEmbeddingDimension in interface FeatureView.IndexConfigOrBuilder
      Returns:
      Whether the embeddingDimension field is set.
    • getEmbeddingDimension

      public int getEmbeddingDimension()
       Optional. The number of dimensions of the input embedding.
       
      optional int32 embedding_dimension = 4 [(.google.api.field_behavior) = OPTIONAL];
      Specified by:
      getEmbeddingDimension in interface FeatureView.IndexConfigOrBuilder
      Returns:
      The embeddingDimension.
    • setEmbeddingDimension

      public FeatureView.IndexConfig.Builder setEmbeddingDimension(int value)
       Optional. The number of dimensions of the input embedding.
       
      optional int32 embedding_dimension = 4 [(.google.api.field_behavior) = OPTIONAL];
      Parameters:
      value - The embeddingDimension to set.
      Returns:
      This builder for chaining.
    • clearEmbeddingDimension

      public FeatureView.IndexConfig.Builder clearEmbeddingDimension()
       Optional. The number of dimensions of the input embedding.
       
      optional int32 embedding_dimension = 4 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      This builder for chaining.
    • getDistanceMeasureTypeValue

      public 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];
      Specified by:
      getDistanceMeasureTypeValue in interface FeatureView.IndexConfigOrBuilder
      Returns:
      The enum numeric value on the wire for distanceMeasureType.
    • setDistanceMeasureTypeValue

      public FeatureView.IndexConfig.Builder setDistanceMeasureTypeValue(int value)
       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];
      Parameters:
      value - The enum numeric value on the wire for distanceMeasureType to set.
      Returns:
      This builder for chaining.
    • getDistanceMeasureType

      public 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];
      Specified by:
      getDistanceMeasureType in interface FeatureView.IndexConfigOrBuilder
      Returns:
      The distanceMeasureType.
    • setDistanceMeasureType

       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];
      Parameters:
      value - The distanceMeasureType to set.
      Returns:
      This builder for chaining.
    • clearDistanceMeasureType

      public FeatureView.IndexConfig.Builder clearDistanceMeasureType()
       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:
      This builder for chaining.