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public static final class FeatureView.VectorSearchConfig.Builder extends GeneratedMessageV3.Builder<FeatureView.VectorSearchConfig.Builder> implements FeatureView.VectorSearchConfigOrBuilderDeprecated. Use IndexConfig instead.
Protobuf type google.cloud.aiplatform.v1beta1.FeatureView.VectorSearchConfig
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > FeatureView.VectorSearchConfig.BuilderImplements
FeatureView.VectorSearchConfigOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()| Returns | |
|---|---|
| Type | Description |
Descriptor |
|
Methods
addAllFilterColumns(Iterable<String> values)
public FeatureView.VectorSearchConfig.Builder addAllFilterColumns(Iterable<String> values)Optional. Columns of features that're used to filter vector search results.
repeated string filter_columns = 4 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
values |
Iterable<String>The filterColumns to add. |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
addFilterColumns(String value)
public FeatureView.VectorSearchConfig.Builder addFilterColumns(String value)Optional. Columns of features that're used to filter vector search results.
repeated string filter_columns = 4 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
StringThe filterColumns to add. |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
addFilterColumnsBytes(ByteString value)
public FeatureView.VectorSearchConfig.Builder addFilterColumnsBytes(ByteString value)Optional. Columns of features that're used to filter vector search results.
repeated string filter_columns = 4 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
ByteStringThe bytes of the filterColumns to add. |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public FeatureView.VectorSearchConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
build()
public FeatureView.VectorSearchConfig build()| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig |
|
buildPartial()
public FeatureView.VectorSearchConfig buildPartial()| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig |
|
clear()
public FeatureView.VectorSearchConfig.Builder clear()| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
clearAlgorithmConfig()
public FeatureView.VectorSearchConfig.Builder clearAlgorithmConfig()| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
clearBruteForceConfig()
public FeatureView.VectorSearchConfig.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.v1beta1.FeatureView.VectorSearchConfig.BruteForceConfig brute_force_config = 9 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
clearCrowdingColumn()
public FeatureView.VectorSearchConfig.Builder clearCrowdingColumn()Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response.
string crowding_column = 5 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
clearDistanceMeasureType()
public FeatureView.VectorSearchConfig.Builder clearDistanceMeasureType()Optional. The distance measure used in nearest neighbor search.
.google.cloud.aiplatform.v1beta1.FeatureView.VectorSearchConfig.DistanceMeasureType distance_measure_type = 7 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
clearEmbeddingColumn()
public FeatureView.VectorSearchConfig.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 = 3 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
clearEmbeddingDimension()
public FeatureView.VectorSearchConfig.Builder clearEmbeddingDimension()Optional. The number of dimensions of the input embedding.
optional int32 embedding_dimension = 6 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
clearField(Descriptors.FieldDescriptor field)
public FeatureView.VectorSearchConfig.Builder clearField(Descriptors.FieldDescriptor field)| Parameter | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
clearFilterColumns()
public FeatureView.VectorSearchConfig.Builder clearFilterColumns()Optional. Columns of features that're used to filter vector search results.
repeated string filter_columns = 4 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
clearOneof(Descriptors.OneofDescriptor oneof)
public FeatureView.VectorSearchConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)| Parameter | |
|---|---|
| Name | Description |
oneof |
OneofDescriptor |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
clearTreeAhConfig()
public FeatureView.VectorSearchConfig.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.v1beta1.FeatureView.VectorSearchConfig.TreeAHConfig tree_ah_config = 8 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
clone()
public FeatureView.VectorSearchConfig.Builder clone()| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
getAlgorithmConfigCase()
public FeatureView.VectorSearchConfig.AlgorithmConfigCase getAlgorithmConfigCase()| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.AlgorithmConfigCase |
|
getBruteForceConfig()
public FeatureView.VectorSearchConfig.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.VectorSearchConfig.BruteForceConfig brute_force_config = 9 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.BruteForceConfig |
The bruteForceConfig. |
getBruteForceConfigBuilder()
public FeatureView.VectorSearchConfig.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.v1beta1.FeatureView.VectorSearchConfig.BruteForceConfig brute_force_config = 9 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.BruteForceConfig.Builder |
|
getBruteForceConfigOrBuilder()
public FeatureView.VectorSearchConfig.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.VectorSearchConfig.BruteForceConfig brute_force_config = 9 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.BruteForceConfigOrBuilder |
|
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 to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response.
string crowding_column = 5 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
String |
The crowdingColumn. |
getCrowdingColumnBytes()
public ByteString getCrowdingColumnBytes()Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response.
string crowding_column = 5 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes for crowdingColumn. |
getDefaultInstanceForType()
public FeatureView.VectorSearchConfig getDefaultInstanceForType()| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig |
|
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()| Returns | |
|---|---|
| Type | Description |
Descriptor |
|
getDistanceMeasureType()
public FeatureView.VectorSearchConfig.DistanceMeasureType getDistanceMeasureType()Optional. The distance measure used in nearest neighbor search.
.google.cloud.aiplatform.v1beta1.FeatureView.VectorSearchConfig.DistanceMeasureType distance_measure_type = 7 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.DistanceMeasureType |
The distanceMeasureType. |
getDistanceMeasureTypeValue()
public int getDistanceMeasureTypeValue()Optional. The distance measure used in nearest neighbor search.
.google.cloud.aiplatform.v1beta1.FeatureView.VectorSearchConfig.DistanceMeasureType distance_measure_type = 7 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
int |
The enum numeric value on the wire for distanceMeasureType. |
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 = 3 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
String |
The embeddingColumn. |
getEmbeddingColumnBytes()
public 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 = 3 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes for embeddingColumn. |
getEmbeddingDimension()
public int getEmbeddingDimension()Optional. The number of dimensions of the input embedding.
optional int32 embedding_dimension = 6 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
int |
The embeddingDimension. |
getFilterColumns(int index)
public String getFilterColumns(int index)Optional. Columns of features that're used to filter vector search results.
repeated string filter_columns = 4 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
index |
intThe index of the element to return. |
| Returns | |
|---|---|
| Type | Description |
String |
The filterColumns at the given index. |
getFilterColumnsBytes(int index)
public ByteString getFilterColumnsBytes(int index)Optional. Columns of features that're used to filter vector search results.
repeated string filter_columns = 4 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
index |
intThe index of the value to return. |
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes of the filterColumns at the given index. |
getFilterColumnsCount()
public int getFilterColumnsCount()Optional. Columns of features that're used to filter vector search results.
repeated string filter_columns = 4 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
int |
The count of filterColumns. |
getFilterColumnsList()
public ProtocolStringList getFilterColumnsList()Optional. Columns of features that're used to filter vector search results.
repeated string filter_columns = 4 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
ProtocolStringList |
A list containing the filterColumns. |
getTreeAhConfig()
public FeatureView.VectorSearchConfig.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.VectorSearchConfig.TreeAHConfig tree_ah_config = 8 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.TreeAHConfig |
The treeAhConfig. |
getTreeAhConfigBuilder()
public FeatureView.VectorSearchConfig.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.v1beta1.FeatureView.VectorSearchConfig.TreeAHConfig tree_ah_config = 8 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.TreeAHConfig.Builder |
|
getTreeAhConfigOrBuilder()
public FeatureView.VectorSearchConfig.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.VectorSearchConfig.TreeAHConfig tree_ah_config = 8 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.TreeAHConfigOrBuilder |
|
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.v1beta1.FeatureView.VectorSearchConfig.BruteForceConfig brute_force_config = 9 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
boolean |
Whether the bruteForceConfig field is set. |
hasEmbeddingDimension()
public boolean hasEmbeddingDimension()Optional. The number of dimensions of the input embedding.
optional int32 embedding_dimension = 6 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
boolean |
Whether the embeddingDimension field is set. |
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.v1beta1.FeatureView.VectorSearchConfig.TreeAHConfig tree_ah_config = 8 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
boolean |
Whether the treeAhConfig field is set. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()| Returns | |
|---|---|
| Type | Description |
FieldAccessorTable |
|
isInitialized()
public final boolean isInitialized()| Returns | |
|---|---|
| Type | Description |
boolean |
|
mergeBruteForceConfig(FeatureView.VectorSearchConfig.BruteForceConfig value)
public FeatureView.VectorSearchConfig.Builder mergeBruteForceConfig(FeatureView.VectorSearchConfig.BruteForceConfig value)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.VectorSearchConfig.BruteForceConfig brute_force_config = 9 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
FeatureView.VectorSearchConfig.BruteForceConfig |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
mergeFrom(FeatureView.VectorSearchConfig other)
public FeatureView.VectorSearchConfig.Builder mergeFrom(FeatureView.VectorSearchConfig other)| Parameter | |
|---|---|
| Name | Description |
other |
FeatureView.VectorSearchConfig |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public FeatureView.VectorSearchConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)| Parameters | |
|---|---|
| Name | Description |
input |
CodedInputStream |
extensionRegistry |
ExtensionRegistryLite |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
mergeFrom(Message other)
public FeatureView.VectorSearchConfig.Builder mergeFrom(Message other)| Parameter | |
|---|---|
| Name | Description |
other |
Message |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
mergeTreeAhConfig(FeatureView.VectorSearchConfig.TreeAHConfig value)
public FeatureView.VectorSearchConfig.Builder mergeTreeAhConfig(FeatureView.VectorSearchConfig.TreeAHConfig value)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.VectorSearchConfig.TreeAHConfig tree_ah_config = 8 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
FeatureView.VectorSearchConfig.TreeAHConfig |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
mergeUnknownFields(UnknownFieldSet unknownFields)
public final FeatureView.VectorSearchConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)| Parameter | |
|---|---|
| Name | Description |
unknownFields |
UnknownFieldSet |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
setBruteForceConfig(FeatureView.VectorSearchConfig.BruteForceConfig value)
public FeatureView.VectorSearchConfig.Builder setBruteForceConfig(FeatureView.VectorSearchConfig.BruteForceConfig value)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.VectorSearchConfig.BruteForceConfig brute_force_config = 9 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
FeatureView.VectorSearchConfig.BruteForceConfig |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
setBruteForceConfig(FeatureView.VectorSearchConfig.BruteForceConfig.Builder builderForValue)
public FeatureView.VectorSearchConfig.Builder setBruteForceConfig(FeatureView.VectorSearchConfig.BruteForceConfig.Builder builderForValue)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.VectorSearchConfig.BruteForceConfig brute_force_config = 9 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
builderForValue |
FeatureView.VectorSearchConfig.BruteForceConfig.Builder |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
setCrowdingColumn(String value)
public FeatureView.VectorSearchConfig.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 to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response.
string crowding_column = 5 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
StringThe crowdingColumn to set. |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
setCrowdingColumnBytes(ByteString value)
public FeatureView.VectorSearchConfig.Builder setCrowdingColumnBytes(ByteString value)Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response.
string crowding_column = 5 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
ByteStringThe bytes for crowdingColumn to set. |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
setDistanceMeasureType(FeatureView.VectorSearchConfig.DistanceMeasureType value)
public FeatureView.VectorSearchConfig.Builder setDistanceMeasureType(FeatureView.VectorSearchConfig.DistanceMeasureType value)Optional. The distance measure used in nearest neighbor search.
.google.cloud.aiplatform.v1beta1.FeatureView.VectorSearchConfig.DistanceMeasureType distance_measure_type = 7 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
FeatureView.VectorSearchConfig.DistanceMeasureTypeThe distanceMeasureType to set. |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
setDistanceMeasureTypeValue(int value)
public FeatureView.VectorSearchConfig.Builder setDistanceMeasureTypeValue(int value)Optional. The distance measure used in nearest neighbor search.
.google.cloud.aiplatform.v1beta1.FeatureView.VectorSearchConfig.DistanceMeasureType distance_measure_type = 7 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
intThe enum numeric value on the wire for distanceMeasureType to set. |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
setEmbeddingColumn(String value)
public FeatureView.VectorSearchConfig.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 = 3 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
StringThe embeddingColumn to set. |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
setEmbeddingColumnBytes(ByteString value)
public FeatureView.VectorSearchConfig.Builder setEmbeddingColumnBytes(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 = 3 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
ByteStringThe bytes for embeddingColumn to set. |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
setEmbeddingDimension(int value)
public FeatureView.VectorSearchConfig.Builder setEmbeddingDimension(int value)Optional. The number of dimensions of the input embedding.
optional int32 embedding_dimension = 6 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
intThe embeddingDimension to set. |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
setField(Descriptors.FieldDescriptor field, Object value)
public FeatureView.VectorSearchConfig.Builder setField(Descriptors.FieldDescriptor field, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
setFilterColumns(int index, String value)
public FeatureView.VectorSearchConfig.Builder setFilterColumns(int index, String value)Optional. Columns of features that're used to filter vector search results.
repeated string filter_columns = 4 [(.google.api.field_behavior) = OPTIONAL];
| Parameters | |
|---|---|
| Name | Description |
index |
intThe index to set the value at. |
value |
StringThe filterColumns to set. |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
This builder for chaining. |
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public FeatureView.VectorSearchConfig.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
index |
int |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
setTreeAhConfig(FeatureView.VectorSearchConfig.TreeAHConfig value)
public FeatureView.VectorSearchConfig.Builder setTreeAhConfig(FeatureView.VectorSearchConfig.TreeAHConfig value)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.VectorSearchConfig.TreeAHConfig tree_ah_config = 8 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
FeatureView.VectorSearchConfig.TreeAHConfig |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
setTreeAhConfig(FeatureView.VectorSearchConfig.TreeAHConfig.Builder builderForValue)
public FeatureView.VectorSearchConfig.Builder setTreeAhConfig(FeatureView.VectorSearchConfig.TreeAHConfig.Builder builderForValue)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.VectorSearchConfig.TreeAHConfig tree_ah_config = 8 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
builderForValue |
FeatureView.VectorSearchConfig.TreeAHConfig.Builder |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|
setUnknownFields(UnknownFieldSet unknownFields)
public final FeatureView.VectorSearchConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)| Parameter | |
|---|---|
| Name | Description |
unknownFields |
UnknownFieldSet |
| Returns | |
|---|---|
| Type | Description |
FeatureView.VectorSearchConfig.Builder |
|