Interface IndexDatapointOrBuilder (3.48.0) 

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
Type Description
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
Type Description
IndexDatapoint.CrowdingTagOrBuilder

getDatapointId()

public abstract 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 abstract 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.

getFeatureVector(int index)

public abstract 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 abstract 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 abstract 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 abstract 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.v1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name Description
index int
Returns
Type Description
IndexDatapoint.NumericRestriction

getNumericRestrictsCount()

public abstract 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.v1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type Description
int

getNumericRestrictsList()

public abstract 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.v1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type Description
List<NumericRestriction>

getNumericRestrictsOrBuilder(int index)

public abstract 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.v1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name Description
index int
Returns
Type Description
IndexDatapoint.NumericRestrictionOrBuilder

getNumericRestrictsOrBuilderList()

public abstract 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.v1.IndexDatapoint.NumericRestriction numeric_restricts = 6 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type Description
List<? extends com.google.cloud.aiplatform.v1.IndexDatapoint.NumericRestrictionOrBuilder>

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
Name Description
index int
Returns
Type Description
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
Type Description
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
Type Description
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
Name Description
index int
Returns
Type Description
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
Type Description
List<? extends com.google.cloud.aiplatform.v1.IndexDatapoint.RestrictionOrBuilder>

getSparseEmbedding()

public abstract IndexDatapoint.SparseEmbedding getSparseEmbedding()

Optional. Feature embedding vector for sparse index.

.google.cloud.aiplatform.v1.IndexDatapoint.SparseEmbedding sparse_embedding = 7 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type Description
IndexDatapoint.SparseEmbedding

The sparseEmbedding.

getSparseEmbeddingOrBuilder()

public abstract IndexDatapoint.SparseEmbeddingOrBuilder getSparseEmbeddingOrBuilder()

Optional. Feature embedding vector for sparse index.

.google.cloud.aiplatform.v1.IndexDatapoint.SparseEmbedding sparse_embedding = 7 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type Description
IndexDatapoint.SparseEmbeddingOrBuilder

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
Type Description
boolean

Whether the crowdingTag field is set.

hasSparseEmbedding()

public abstract boolean hasSparseEmbedding()

Optional. Feature embedding vector for sparse index.

.google.cloud.aiplatform.v1.IndexDatapoint.SparseEmbedding sparse_embedding = 7 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type Description
boolean

Whether the sparseEmbedding field is set.