public static final class FeatureView.VectorSearchConfig extends GeneratedMessageV3 implements FeatureView.VectorSearchConfigOrBuilder
Configuration for vector search.
Protobuf type google.cloud.aiplatform.v1beta1.FeatureView.VectorSearchConfig
Inherited Members
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT)
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT,int)
com.google.protobuf.GeneratedMessageV3.<T>emptyList(java.lang.Class<T>)
Static Fields
public static final int BRUTE_FORCE_CONFIG_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int CROWDING_COLUMN_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int DISTANCE_MEASURE_TYPE_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int EMBEDDING_COLUMN_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int EMBEDDING_DIMENSION_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int FILTER_COLUMNS_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int TREE_AH_CONFIG_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
Static Methods
public static FeatureView.VectorSearchConfig getDefaultInstance()
public static final Descriptors.Descriptor getDescriptor()
public static FeatureView.VectorSearchConfig.Builder newBuilder()
public static FeatureView.VectorSearchConfig.Builder newBuilder(FeatureView.VectorSearchConfig prototype)
public static FeatureView.VectorSearchConfig parseDelimitedFrom(InputStream input)
public static FeatureView.VectorSearchConfig parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static FeatureView.VectorSearchConfig parseFrom(byte[] data)
| Parameter |
|---|
| Name | Description |
data | byte[]
|
public static FeatureView.VectorSearchConfig parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static FeatureView.VectorSearchConfig parseFrom(ByteString data)
public static FeatureView.VectorSearchConfig parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static FeatureView.VectorSearchConfig parseFrom(CodedInputStream input)
public static FeatureView.VectorSearchConfig parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static FeatureView.VectorSearchConfig parseFrom(InputStream input)
public static FeatureView.VectorSearchConfig parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static FeatureView.VectorSearchConfig parseFrom(ByteBuffer data)
public static FeatureView.VectorSearchConfig parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static Parser<FeatureView.VectorSearchConfig> parser()
Methods
public boolean equals(Object obj)
| Parameter |
|---|
| Name | Description |
obj | Object
|
Overrides
public FeatureView.VectorSearchConfig.AlgorithmConfigCase getAlgorithmConfigCase()
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];
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];
public String getCrowdingColumn()
Optional. 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 crowding_attribute.
string crowding_column = 5 [(.google.api.field_behavior) = OPTIONAL];
| Returns |
|---|
| Type | Description |
String | The crowdingColumn.
|
public ByteString getCrowdingColumnBytes()
Optional. 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 crowding_attribute.
string crowding_column = 5 [(.google.api.field_behavior) = OPTIONAL];
| Returns |
|---|
| Type | Description |
ByteString | The bytes for crowdingColumn.
|
public FeatureView.VectorSearchConfig getDefaultInstanceForType()
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];
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.
|
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.
|
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.
|
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.
|
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 | int
The index of the element to return.
|
| Returns |
|---|
| Type | Description |
String | The filterColumns at the given 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 | int
The index of the value to return.
|
| Returns |
|---|
| Type | Description |
ByteString | The bytes of the filterColumns at the given index.
|
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.
|
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];
public Parser<FeatureView.VectorSearchConfig> getParserForType()
Overrides
public int getSerializedSize()
| Returns |
|---|
| Type | Description |
int | |
Overrides
public FeatureView.VectorSearchConfig.TreeAHConfig getTreeAhConfig()
Optional. Configuration options for the tree-AH algorithm (Shallow tree
.google.cloud.aiplatform.v1beta1.FeatureView.VectorSearchConfig.TreeAHConfig tree_ah_config = 8 [(.google.api.field_behavior) = OPTIONAL];
public FeatureView.VectorSearchConfig.TreeAHConfigOrBuilder getTreeAhConfigOrBuilder()
Optional. Configuration options for the tree-AH algorithm (Shallow tree
.google.cloud.aiplatform.v1beta1.FeatureView.VectorSearchConfig.TreeAHConfig tree_ah_config = 8 [(.google.api.field_behavior) = OPTIONAL];
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.
|
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.
|
public boolean hasTreeAhConfig()
Optional. Configuration options for the tree-AH algorithm (Shallow tree
.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.
|
| Returns |
|---|
| Type | Description |
int | |
Overrides
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Overrides
public final boolean isInitialized()
Overrides
public FeatureView.VectorSearchConfig.Builder newBuilderForType()
protected FeatureView.VectorSearchConfig.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Overrides
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Overrides
public FeatureView.VectorSearchConfig.Builder toBuilder()
public void writeTo(CodedOutputStream output)
Overrides
