Interface IndexDatapointOrBuilder (3.29.0)

public interface IndexDatapointOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

getCrowdingTag()

public abstract 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.v1.IndexDatapoint.CrowdingTag crowding_tag = 5 [(.google.api.field_behavior) = OPTIONAL];

Returns
TypeDescription
IndexDatapoint.CrowdingTag

The crowdingTag.

getCrowdingTagOrBuilder()

public abstract 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.v1.IndexDatapoint.CrowdingTag crowding_tag = 5 [(.google.api.field_behavior) = OPTIONAL];

Returns
TypeDescription
IndexDatapoint.CrowdingTagOrBuilder

getDatapointId()

public abstract String getDatapointId()

Required. Unique identifier of the datapoint.

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

Returns
TypeDescription
String

The datapointId.

getDatapointIdBytes()

public abstract ByteString getDatapointIdBytes()

Required. Unique identifier of the datapoint.

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

Returns
TypeDescription
ByteString

The bytes for datapointId.

getFeatureVector(int index)

public abstract float getFeatureVector(int index)

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

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

Parameter
NameDescription
indexint

The index of the element to return.

Returns
TypeDescription
float

The featureVector at the given index.

getFeatureVectorCount()

public abstract int getFeatureVectorCount()

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

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

Returns
TypeDescription
int

The count of featureVector.

getFeatureVectorList()

public abstract List<Float> getFeatureVectorList()

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

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

Returns
TypeDescription
List<Float>

A list containing the featureVector.

getRestricts(int index)

public abstract 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.v1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameter
NameDescription
indexint
Returns
TypeDescription
IndexDatapoint.Restriction

getRestrictsCount()

public abstract 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.v1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Returns
TypeDescription
int

getRestrictsList()

public abstract 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.v1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Returns
TypeDescription
List<Restriction>

getRestrictsOrBuilder(int index)

public abstract 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.v1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameter
NameDescription
indexint
Returns
TypeDescription
IndexDatapoint.RestrictionOrBuilder

getRestrictsOrBuilderList()

public abstract 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.v1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Returns
TypeDescription
List<? extends com.google.cloud.aiplatform.v1.IndexDatapoint.RestrictionOrBuilder>

hasCrowdingTag()

public abstract boolean hasCrowdingTag()

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

.google.cloud.aiplatform.v1.IndexDatapoint.CrowdingTag crowding_tag = 5 [(.google.api.field_behavior) = OPTIONAL];

Returns
TypeDescription
boolean

Whether the crowdingTag field is set.