Struct google_api_proto::google::cloud::aiplatform::v1beta1::Feature

pub struct Feature {

    pub name: String,
    pub description: String,
    pub value_type: i32,
    pub create_time: Option<Timestamp>,
    pub update_time: Option<Timestamp>,
    pub labels: BTreeMap<String, String>,
    pub etag: String,
    pub monitoring_config: Option<FeaturestoreMonitoringConfig>,
    pub disable_monitoring: bool,
    pub monitoring_stats: Vec<FeatureStatsAnomaly>,
    pub monitoring_stats_anomalies: Vec<MonitoringStatsAnomaly>,
    pub version_column_name: String,
    pub point_of_contact: String,
}

Feature Metadata information. For example, color is a feature that describes an apple.

Fields

name: String

Immutable. Name of the Feature. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature} projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}

The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.

description: String

Description of the Feature.

value_type: i32

Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.

create_time: Option<Timestamp>

Output only. Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.

update_time: Option<Timestamp>

Output only. Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.

labels: BTreeMap<String, String>

Optional. The labels with user-defined metadata to organize your Features.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.

See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded).“ System reserved label keys are prefixed with “aiplatform.googleapis.com/” and are immutable.

etag: String

Used to perform a consistent read-modify-write updates. If not set, a blind “overwrite” update happens.

monitoring_config: Option<FeaturestoreMonitoringConfig>

👎Deprecated

Optional. Only applicable for Vertex AI Feature Store (Legacy). Deprecated: The custom monitoring configuration for this Feature, if not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type ([Feature.ValueType][google.cloud.aiplatform.v1beta1.Feature.ValueType]) BOOL, STRING, DOUBLE or INT64 can enable monitoring.

If this is populated with [FeaturestoreMonitoringConfig.disabled][] = true, snapshot analysis monitoring is disabled; if [FeaturestoreMonitoringConfig.monitoring_interval][] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring config is same as the EntityType’s this Feature belongs to.

disable_monitoring: bool

Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type ([Feature.ValueType][google.cloud.aiplatform.v1beta1.Feature.ValueType]) BOOL, STRING, DOUBLE or INT64 can enable monitoring.

If set to true, all types of data monitoring are disabled despite the config on EntityType.

monitoring_stats: Vec<FeatureStatsAnomaly>

Output only. Only applicable for Vertex AI Feature Store (Legacy). A list of historical [SnapshotAnalysis][google.cloud.aiplatform.v1beta1.FeaturestoreMonitoringConfig.SnapshotAnalysis] stats requested by user, sorted by [FeatureStatsAnomaly.start_time][google.cloud.aiplatform.v1beta1.FeatureStatsAnomaly.start_time] descending.

monitoring_stats_anomalies: Vec<MonitoringStatsAnomaly>

Output only. Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.

version_column_name: String

Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View column hosting data for this version. If no value is provided, will use feature_id.

point_of_contact: String

Entity responsible for maintaining this feature. Can be comma separated list of email addresses or URIs.

Implementations

impl Feature

pub fn value_type(&self) -> ValueType

Returns the enum value of value_type, or the default if the field is set to an invalid enum value.

pub fn set_value_type(&mut self, value: ValueType)

Sets value_type to the provided enum value.

Trait Implementations

impl Clone for Feature

fn clone(&self) -> Feature

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Feature

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for Feature

fn default() -> Self

Returns the “default value” for a type.

impl Message for Feature

fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)

Clears the message, resetting all fields to their default.

fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message to a buffer.

fn encode_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message to a newly allocated buffer.

fn encode_length_delimited( &self, buf: &mut impl BufMut, ) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message with a length-delimiter to a buffer.

fn encode_length_delimited_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message with a length-delimiter to a newly allocated buffer.

fn decode(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes an instance of the message from a buffer.

fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes a length-delimited instance of the message from the buffer.

fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes an instance of the message from a buffer, and merges it into self.

fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq for Feature

fn eq(&self, other: &Feature) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for Feature