Class IndexDatapoint.Builder (3.55.0)

Version 3.55.0

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public static final class IndexDatapoint.Builder extends GeneratedMessageV3.Builder<IndexDatapoint.Builder> implements IndexDatapointOrBuilder

A datapoint of Index.

Protobuf type google.cloud.aiplatform.v1beta1.IndexDatapoint

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > IndexDatapoint.Builder

Implements

IndexDatapointOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMapFieldReflection(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMutableMapFieldReflection(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns
Type	Description
Descriptor

Methods

addAllFeatureVector(Iterable<? extends Float> values)

public IndexDatapoint.Builder addAllFeatureVector(Iterable<? extends Float> values)

Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].

repeated float feature_vector = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
values	Iterable<? extends java.lang.Float> The featureVector to add.

Returns
Type	Description
IndexDatapoint.Builder	This builder for chaining.

addAllNumericRestricts(Iterable<? extends IndexDatapoint.NumericRestriction> values)

public IndexDatapoint.Builder addAllNumericRestricts(Iterable<? extends IndexDatapoint.NumericRestriction> values)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
values	Iterable<? extends com.google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction>

Returns
Type	Description
IndexDatapoint.Builder

addAllRestricts(Iterable<? extends IndexDatapoint.Restriction> values)

public IndexDatapoint.Builder addAllRestricts(Iterable<? extends IndexDatapoint.Restriction> values)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
values	Iterable<? extends com.google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction>

Returns
Type	Description
IndexDatapoint.Builder

addFeatureVector(float value)

public IndexDatapoint.Builder addFeatureVector(float value)

Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].

repeated float feature_vector = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
value	float The featureVector to add.

Returns
Type	Description
IndexDatapoint.Builder	This builder for chaining.

addNumericRestricts(IndexDatapoint.NumericRestriction value)

public IndexDatapoint.Builder addNumericRestricts(IndexDatapoint.NumericRestriction value)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
value	IndexDatapoint.NumericRestriction

Returns
Type	Description
IndexDatapoint.Builder

addNumericRestricts(IndexDatapoint.NumericRestriction.Builder builderForValue)

public IndexDatapoint.Builder addNumericRestricts(IndexDatapoint.NumericRestriction.Builder builderForValue)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
builderForValue	IndexDatapoint.NumericRestriction.Builder

Returns
Type	Description
IndexDatapoint.Builder

addNumericRestricts(int index, IndexDatapoint.NumericRestriction value)

public IndexDatapoint.Builder addNumericRestricts(int index, IndexDatapoint.NumericRestriction value)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Parameters
Name	Description
index	int
value	IndexDatapoint.NumericRestriction

Returns
Type	Description
IndexDatapoint.Builder

addNumericRestricts(int index, IndexDatapoint.NumericRestriction.Builder builderForValue)

public IndexDatapoint.Builder addNumericRestricts(int index, IndexDatapoint.NumericRestriction.Builder builderForValue)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Parameters
Name	Description
index	int
builderForValue	IndexDatapoint.NumericRestriction.Builder

Returns
Type	Description
IndexDatapoint.Builder

addNumericRestrictsBuilder()

public IndexDatapoint.NumericRestriction.Builder addNumericRestrictsBuilder()

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
IndexDatapoint.NumericRestriction.Builder

addNumericRestrictsBuilder(int index)

public IndexDatapoint.NumericRestriction.Builder addNumericRestrictsBuilder(int index)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
index	int

Returns
Type	Description
IndexDatapoint.NumericRestriction.Builder

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public IndexDatapoint.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
field	FieldDescriptor
value	Object

Returns
Type	Description
IndexDatapoint.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

addRestricts(IndexDatapoint.Restriction value)

public IndexDatapoint.Builder addRestricts(IndexDatapoint.Restriction value)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
value	IndexDatapoint.Restriction

Returns
Type	Description
IndexDatapoint.Builder

addRestricts(IndexDatapoint.Restriction.Builder builderForValue)

public IndexDatapoint.Builder addRestricts(IndexDatapoint.Restriction.Builder builderForValue)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
builderForValue	IndexDatapoint.Restriction.Builder

Returns
Type	Description
IndexDatapoint.Builder

addRestricts(int index, IndexDatapoint.Restriction value)

public IndexDatapoint.Builder addRestricts(int index, IndexDatapoint.Restriction value)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameters
Name	Description
index	int
value	IndexDatapoint.Restriction

Returns
Type	Description
IndexDatapoint.Builder

addRestricts(int index, IndexDatapoint.Restriction.Builder builderForValue)

public IndexDatapoint.Builder addRestricts(int index, IndexDatapoint.Restriction.Builder builderForValue)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameters
Name	Description
index	int
builderForValue	IndexDatapoint.Restriction.Builder

Returns
Type	Description
IndexDatapoint.Builder

addRestrictsBuilder()

public IndexDatapoint.Restriction.Builder addRestrictsBuilder()

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
IndexDatapoint.Restriction.Builder

addRestrictsBuilder(int index)

public IndexDatapoint.Restriction.Builder addRestrictsBuilder(int index)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
index	int

Returns
Type	Description
IndexDatapoint.Restriction.Builder

build()

public IndexDatapoint build()

Returns
Type	Description
IndexDatapoint

buildPartial()

public IndexDatapoint buildPartial()

Returns
Type	Description
IndexDatapoint

clear()

public IndexDatapoint.Builder clear()

Returns
Type	Description
IndexDatapoint.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearCrowdingTag()

public IndexDatapoint.Builder clearCrowdingTag()

Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.CrowdingTag crowding_tag = 5 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
IndexDatapoint.Builder

clearDatapointId()

public IndexDatapoint.Builder clearDatapointId()

Required. Unique identifier of the datapoint.

string datapoint_id = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
IndexDatapoint.Builder	This builder for chaining.

clearFeatureVector()

public IndexDatapoint.Builder clearFeatureVector()

Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].

repeated float feature_vector = 2 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
IndexDatapoint.Builder	This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public IndexDatapoint.Builder clearField(Descriptors.FieldDescriptor field)

Parameter
Name	Description
field	FieldDescriptor

Returns
Type	Description
IndexDatapoint.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

clearNumericRestricts()

public IndexDatapoint.Builder clearNumericRestricts()

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
IndexDatapoint.Builder

clearOneof(Descriptors.OneofDescriptor oneof)

public IndexDatapoint.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter
Name	Description
oneof	OneofDescriptor

Returns
Type	Description
IndexDatapoint.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

clearRestricts()

public IndexDatapoint.Builder clearRestricts()

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
IndexDatapoint.Builder

clearSparseEmbedding()

public IndexDatapoint.Builder clearSparseEmbedding()

Optional. Feature embedding vector for sparse index.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.SparseEmbedding sparse_embedding = 7 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
IndexDatapoint.Builder

clone()

public IndexDatapoint.Builder clone()

Returns
Type	Description
IndexDatapoint.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

getCrowdingTag()

public IndexDatapoint.CrowdingTag getCrowdingTag()

Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.CrowdingTag crowding_tag = 5 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
IndexDatapoint.CrowdingTag	The crowdingTag.

getCrowdingTagBuilder()

public IndexDatapoint.CrowdingTag.Builder getCrowdingTagBuilder()

Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.CrowdingTag crowding_tag = 5 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
IndexDatapoint.CrowdingTag.Builder

getCrowdingTagOrBuilder()

public IndexDatapoint.CrowdingTagOrBuilder getCrowdingTagOrBuilder()

Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.CrowdingTag crowding_tag = 5 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
IndexDatapoint.CrowdingTagOrBuilder

getDatapointId()

public String getDatapointId()

Required. Unique identifier of the datapoint.

string datapoint_id = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
String	The datapointId.

getDatapointIdBytes()

public ByteString getDatapointIdBytes()

Required. Unique identifier of the datapoint.

string datapoint_id = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
ByteString	The bytes for datapointId.

getDefaultInstanceForType()

public IndexDatapoint getDefaultInstanceForType()

Returns
Type	Description
IndexDatapoint

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns
Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getFeatureVector(int index)

public float getFeatureVector(int index)

Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].

repeated float feature_vector = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
index	int The index of the element to return.

Returns
Type	Description
float	The featureVector at the given index.

getFeatureVectorCount()

public int getFeatureVectorCount()

Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].

repeated float feature_vector = 2 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
int	The count of featureVector.

getFeatureVectorList()

public List<Float> getFeatureVectorList()

Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].

repeated float feature_vector = 2 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
List<Float>	A list containing the featureVector.

getNumericRestricts(int index)

public IndexDatapoint.NumericRestriction getNumericRestricts(int index)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
index	int

Returns
Type	Description
IndexDatapoint.NumericRestriction

getNumericRestrictsBuilder(int index)

public IndexDatapoint.NumericRestriction.Builder getNumericRestrictsBuilder(int index)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
index	int

Returns
Type	Description
IndexDatapoint.NumericRestriction.Builder

getNumericRestrictsBuilderList()

public List<IndexDatapoint.NumericRestriction.Builder> getNumericRestrictsBuilderList()

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
List<Builder>

getNumericRestrictsCount()

public int getNumericRestrictsCount()

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
int

getNumericRestrictsList()

public List<IndexDatapoint.NumericRestriction> getNumericRestrictsList()

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
List<NumericRestriction>

getNumericRestrictsOrBuilder(int index)

public IndexDatapoint.NumericRestrictionOrBuilder getNumericRestrictsOrBuilder(int index)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
index	int

Returns
Type	Description
IndexDatapoint.NumericRestrictionOrBuilder

getNumericRestrictsOrBuilderList()

public List<? extends IndexDatapoint.NumericRestrictionOrBuilder> getNumericRestrictsOrBuilderList()

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
List<? extends com.google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestrictionOrBuilder>

getRestricts(int index)

public IndexDatapoint.Restriction getRestricts(int index)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
index	int

Returns
Type	Description
IndexDatapoint.Restriction

getRestrictsBuilder(int index)

public IndexDatapoint.Restriction.Builder getRestrictsBuilder(int index)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
index	int

Returns
Type	Description
IndexDatapoint.Restriction.Builder

getRestrictsBuilderList()

public List<IndexDatapoint.Restriction.Builder> getRestrictsBuilderList()

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
List<Builder>

getRestrictsCount()

public int getRestrictsCount()

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
int

getRestrictsList()

public List<IndexDatapoint.Restriction> getRestrictsList()

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
List<Restriction>

getRestrictsOrBuilder(int index)

public IndexDatapoint.RestrictionOrBuilder getRestrictsOrBuilder(int index)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
index	int

Returns
Type	Description
IndexDatapoint.RestrictionOrBuilder

getRestrictsOrBuilderList()

public List<? extends IndexDatapoint.RestrictionOrBuilder> getRestrictsOrBuilderList()

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
List<? extends com.google.cloud.aiplatform.v1beta1.IndexDatapoint.RestrictionOrBuilder>

getSparseEmbedding()

public IndexDatapoint.SparseEmbedding getSparseEmbedding()

Optional. Feature embedding vector for sparse index.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.SparseEmbedding sparse_embedding = 7 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
IndexDatapoint.SparseEmbedding	The sparseEmbedding.

getSparseEmbeddingBuilder()

public IndexDatapoint.SparseEmbedding.Builder getSparseEmbeddingBuilder()

Optional. Feature embedding vector for sparse index.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.SparseEmbedding sparse_embedding = 7 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
IndexDatapoint.SparseEmbedding.Builder

getSparseEmbeddingOrBuilder()

public IndexDatapoint.SparseEmbeddingOrBuilder getSparseEmbeddingOrBuilder()

Optional. Feature embedding vector for sparse index.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.SparseEmbedding sparse_embedding = 7 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
IndexDatapoint.SparseEmbeddingOrBuilder

hasCrowdingTag()

public boolean hasCrowdingTag()

Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.CrowdingTag crowding_tag = 5 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
boolean	Whether the crowdingTag field is set.

hasSparseEmbedding()

public boolean hasSparseEmbedding()

Optional. Feature embedding vector for sparse index.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.SparseEmbedding sparse_embedding = 7 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
boolean	Whether the sparseEmbedding field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns
Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

isInitialized()

public final boolean isInitialized()

Returns
Type	Description
boolean

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeCrowdingTag(IndexDatapoint.CrowdingTag value)

public IndexDatapoint.Builder mergeCrowdingTag(IndexDatapoint.CrowdingTag value)

Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.CrowdingTag crowding_tag = 5 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
value	IndexDatapoint.CrowdingTag

Returns
Type	Description
IndexDatapoint.Builder

mergeFrom(IndexDatapoint other)

public IndexDatapoint.Builder mergeFrom(IndexDatapoint other)

Parameter
Name	Description
other	IndexDatapoint

Returns
Type	Description
IndexDatapoint.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public IndexDatapoint.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
IndexDatapoint.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions
Type	Description
IOException

mergeFrom(Message other)

public IndexDatapoint.Builder mergeFrom(Message other)

Parameter
Name	Description
other	Message

Returns
Type	Description
IndexDatapoint.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

mergeSparseEmbedding(IndexDatapoint.SparseEmbedding value)

public IndexDatapoint.Builder mergeSparseEmbedding(IndexDatapoint.SparseEmbedding value)

Optional. Feature embedding vector for sparse index.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.SparseEmbedding sparse_embedding = 7 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
value	IndexDatapoint.SparseEmbedding

Returns
Type	Description
IndexDatapoint.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final IndexDatapoint.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
unknownFields	UnknownFieldSet

Returns
Type	Description
IndexDatapoint.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

removeNumericRestricts(int index)

public IndexDatapoint.Builder removeNumericRestricts(int index)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
index	int

Returns
Type	Description
IndexDatapoint.Builder

removeRestricts(int index)

public IndexDatapoint.Builder removeRestricts(int index)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
index	int

Returns
Type	Description
IndexDatapoint.Builder

setCrowdingTag(IndexDatapoint.CrowdingTag value)

public IndexDatapoint.Builder setCrowdingTag(IndexDatapoint.CrowdingTag value)

Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.CrowdingTag crowding_tag = 5 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
value	IndexDatapoint.CrowdingTag

Returns
Type	Description
IndexDatapoint.Builder

setCrowdingTag(IndexDatapoint.CrowdingTag.Builder builderForValue)

public IndexDatapoint.Builder setCrowdingTag(IndexDatapoint.CrowdingTag.Builder builderForValue)

Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.CrowdingTag crowding_tag = 5 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
builderForValue	IndexDatapoint.CrowdingTag.Builder

Returns
Type	Description
IndexDatapoint.Builder

setDatapointId(String value)

public IndexDatapoint.Builder setDatapointId(String value)

Required. Unique identifier of the datapoint.

string datapoint_id = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
value	String The datapointId to set.

Returns
Type	Description
IndexDatapoint.Builder	This builder for chaining.

setDatapointIdBytes(ByteString value)

public IndexDatapoint.Builder setDatapointIdBytes(ByteString value)

Required. Unique identifier of the datapoint.

string datapoint_id = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
value	ByteString The bytes for datapointId to set.

Returns
Type	Description
IndexDatapoint.Builder	This builder for chaining.

setFeatureVector(int index, float value)

public IndexDatapoint.Builder setFeatureVector(int index, float value)

Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].

repeated float feature_vector = 2 [(.google.api.field_behavior) = REQUIRED];

Parameters
Name	Description
index	int The index to set the value at.
value	float The featureVector to set.

Returns
Type	Description
IndexDatapoint.Builder	This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public IndexDatapoint.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
field	FieldDescriptor
value	Object

Returns
Type	Description
IndexDatapoint.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

setNumericRestricts(int index, IndexDatapoint.NumericRestriction value)

public IndexDatapoint.Builder setNumericRestricts(int index, IndexDatapoint.NumericRestriction value)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Parameters
Name	Description
index	int
value	IndexDatapoint.NumericRestriction

Returns
Type	Description
IndexDatapoint.Builder

setNumericRestricts(int index, IndexDatapoint.NumericRestriction.Builder builderForValue)

public IndexDatapoint.Builder setNumericRestricts(int index, IndexDatapoint.NumericRestriction.Builder builderForValue)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Parameters
Name	Description
index	int
builderForValue	IndexDatapoint.NumericRestriction.Builder

Returns
Type	Description
IndexDatapoint.Builder

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public IndexDatapoint.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

Parameters
Name	Description
field	FieldDescriptor
index	int
value	Object

Returns
Type	Description
IndexDatapoint.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

setRestricts(int index, IndexDatapoint.Restriction value)

public IndexDatapoint.Builder setRestricts(int index, IndexDatapoint.Restriction value)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameters
Name	Description
index	int
value	IndexDatapoint.Restriction

Returns
Type	Description
IndexDatapoint.Builder

setRestricts(int index, IndexDatapoint.Restriction.Builder builderForValue)

public IndexDatapoint.Builder setRestricts(int index, IndexDatapoint.Restriction.Builder builderForValue)

Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

repeated .google.cloud.aiplatform.v1beta1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameters
Name	Description
index	int
builderForValue	IndexDatapoint.Restriction.Builder

Returns
Type	Description
IndexDatapoint.Builder

setSparseEmbedding(IndexDatapoint.SparseEmbedding value)

public IndexDatapoint.Builder setSparseEmbedding(IndexDatapoint.SparseEmbedding value)

Optional. Feature embedding vector for sparse index.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.SparseEmbedding sparse_embedding = 7 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
value	IndexDatapoint.SparseEmbedding

Returns
Type	Description
IndexDatapoint.Builder

setSparseEmbedding(IndexDatapoint.SparseEmbedding.Builder builderForValue)

public IndexDatapoint.Builder setSparseEmbedding(IndexDatapoint.SparseEmbedding.Builder builderForValue)

Optional. Feature embedding vector for sparse index.

.google.cloud.aiplatform.v1beta1.IndexDatapoint.SparseEmbedding sparse_embedding = 7 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
builderForValue	IndexDatapoint.SparseEmbedding.Builder

Returns
Type	Description
IndexDatapoint.Builder

setUnknownFields(UnknownFieldSet unknownFields)

public final IndexDatapoint.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
unknownFields	UnknownFieldSet

Returns
Type	Description
IndexDatapoint.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)