com.google.cloud.aiplatform.v1beta1

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 Summary

Modifier and Type	Method and Description
FeatureView.IndexConfig.AlgorithmConfigCase	getAlgorithmConfigCase()
FeatureView.IndexConfig.BruteForceConfig	getBruteForceConfig() Optional.
FeatureView.IndexConfig.BruteForceConfigOrBuilder	getBruteForceConfigOrBuilder() Optional.
String	getCrowdingColumn() Optional.
com.google.protobuf.ByteString	getCrowdingColumnBytes() Optional.
FeatureView.IndexConfig.DistanceMeasureType	getDistanceMeasureType() Optional.
int	getDistanceMeasureTypeValue() Optional.
String	getEmbeddingColumn() Optional.
com.google.protobuf.ByteString	getEmbeddingColumnBytes() Optional.
int	getEmbeddingDimension() Optional.
String	getFilterColumns(int index) Optional.
com.google.protobuf.ByteString	getFilterColumnsBytes(int index) Optional.
int	getFilterColumnsCount() Optional.
List<String>	getFilterColumnsList() Optional.
FeatureView.IndexConfig.TreeAHConfig	getTreeAhConfig() Optional.
FeatureView.IndexConfig.TreeAHConfigOrBuilder	getTreeAhConfigOrBuilder() Optional.
boolean	hasBruteForceConfig() Optional.
boolean	hasEmbeddingDimension() Optional.
boolean	hasTreeAhConfig() Optional.

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.FeatureOnlineStoreService.SearchNearestEntities]
 to diversify search results. If
 [NearestNeighborQuery.per_crowding_attribute_neighbor_count][google.cloud.aiplatform.v1beta1.NearestNeighborQuery.per_crowding_attribute_neighbor_count]
 is set to K in
 [SearchNearestEntitiesRequest][google.cloud.aiplatform.v1beta1.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.v1beta1.FeatureOnlineStoreService.SearchNearestEntities]
 to diversify search results. If
 [NearestNeighborQuery.per_crowding_attribute_neighbor_count][google.cloud.aiplatform.v1beta1.NearestNeighborQuery.per_crowding_attribute_neighbor_count]
 is set to K in
 [SearchNearestEntitiesRequest][google.cloud.aiplatform.v1beta1.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.v1beta1.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.v1beta1.FeatureView.IndexConfig.DistanceMeasureType distance_measure_type = 5 [(.google.api.field_behavior) = OPTIONAL];

Returns:

The distanceMeasureType.

getAlgorithmConfigCase

FeatureView.IndexConfig.AlgorithmConfigCase getAlgorithmConfigCase()