Struct FeaturestoreMonitoringConfig 

#[non_exhaustive]
pub struct FeaturestoreMonitoringConfig {
    pub snapshot_analysis: Option<SnapshotAnalysis>,
    pub import_features_analysis: Option<ImportFeaturesAnalysis>,
    pub numerical_threshold_config: Option<ThresholdConfig>,
    pub categorical_threshold_config: Option<ThresholdConfig>,
    /* private fields */
}

Available on crate feature featurestore-service only.

Configuration of how features in Featurestore are monitored.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

snapshot_analysis: Option<SnapshotAnalysis>

The config for Snapshot Analysis Based Feature Monitoring.

import_features_analysis: Option<ImportFeaturesAnalysis>

The config for ImportFeatures Analysis Based Feature Monitoring.

numerical_threshold_config: Option<ThresholdConfig>

Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).

categorical_threshold_config: Option<ThresholdConfig>

Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).

Implementations

impl FeaturestoreMonitoringConfig

pub fn new() -> Self

pub fn set_snapshot_analysis<T>(self, v: T) -> Self

where T: Into<SnapshotAnalysis>,

Sets the value of snapshot_analysis.

Example

use google_cloud_aiplatform_v1::model::featurestore_monitoring_config::SnapshotAnalysis;
let x = FeaturestoreMonitoringConfig::new().set_snapshot_analysis(SnapshotAnalysis::default()/* use setters */);

pub fn set_or_clear_snapshot_analysis<T>(self, v: Option<T>) -> Self

where T: Into<SnapshotAnalysis>,

Sets or clears the value of snapshot_analysis.

Example

use google_cloud_aiplatform_v1::model::featurestore_monitoring_config::SnapshotAnalysis;
let x = FeaturestoreMonitoringConfig::new().set_or_clear_snapshot_analysis(Some(SnapshotAnalysis::default()/* use setters */));
let x = FeaturestoreMonitoringConfig::new().set_or_clear_snapshot_analysis(None::<SnapshotAnalysis>);

pub fn set_import_features_analysis<T>(self, v: T) -> Self

where T: Into<ImportFeaturesAnalysis>,

Sets the value of import_features_analysis.

Example

use google_cloud_aiplatform_v1::model::featurestore_monitoring_config::ImportFeaturesAnalysis;
let x = FeaturestoreMonitoringConfig::new().set_import_features_analysis(ImportFeaturesAnalysis::default()/* use setters */);

pub fn set_or_clear_import_features_analysis<T>(self, v: Option<T>) -> Self

where T: Into<ImportFeaturesAnalysis>,

Sets or clears the value of import_features_analysis.

Example

use google_cloud_aiplatform_v1::model::featurestore_monitoring_config::ImportFeaturesAnalysis;
let x = FeaturestoreMonitoringConfig::new().set_or_clear_import_features_analysis(Some(ImportFeaturesAnalysis::default()/* use setters */));
let x = FeaturestoreMonitoringConfig::new().set_or_clear_import_features_analysis(None::<ImportFeaturesAnalysis>);

pub fn set_numerical_threshold_config<T>(self, v: T) -> Self

where T: Into<ThresholdConfig>,

Sets the value of numerical_threshold_config.

Example

use google_cloud_aiplatform_v1::model::featurestore_monitoring_config::ThresholdConfig;
let x = FeaturestoreMonitoringConfig::new().set_numerical_threshold_config(ThresholdConfig::default()/* use setters */);

pub fn set_or_clear_numerical_threshold_config<T>(self, v: Option<T>) -> Self

where T: Into<ThresholdConfig>,

Sets or clears the value of numerical_threshold_config.

Example

use google_cloud_aiplatform_v1::model::featurestore_monitoring_config::ThresholdConfig;
let x = FeaturestoreMonitoringConfig::new().set_or_clear_numerical_threshold_config(Some(ThresholdConfig::default()/* use setters */));
let x = FeaturestoreMonitoringConfig::new().set_or_clear_numerical_threshold_config(None::<ThresholdConfig>);

pub fn set_categorical_threshold_config<T>(self, v: T) -> Self

where T: Into<ThresholdConfig>,

Sets the value of categorical_threshold_config.

Example

use google_cloud_aiplatform_v1::model::featurestore_monitoring_config::ThresholdConfig;
let x = FeaturestoreMonitoringConfig::new().set_categorical_threshold_config(ThresholdConfig::default()/* use setters */);

pub fn set_or_clear_categorical_threshold_config<T>(self, v: Option<T>) -> Self

where T: Into<ThresholdConfig>,

Sets or clears the value of categorical_threshold_config.

Example

use google_cloud_aiplatform_v1::model::featurestore_monitoring_config::ThresholdConfig;
let x = FeaturestoreMonitoringConfig::new().set_or_clear_categorical_threshold_config(Some(ThresholdConfig::default()/* use setters */));
let x = FeaturestoreMonitoringConfig::new().set_or_clear_categorical_threshold_config(None::<ThresholdConfig>);

Trait Implementations

impl Clone for FeaturestoreMonitoringConfig

fn clone(&self) -> FeaturestoreMonitoringConfig

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for FeaturestoreMonitoringConfig

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

Formats the value using the given formatter.

impl Default for FeaturestoreMonitoringConfig

fn default() -> FeaturestoreMonitoringConfig

Returns the “default value” for a type.

impl Message for FeaturestoreMonitoringConfig

fn typename() -> &'static str

The typename of this message.

impl PartialEq for FeaturestoreMonitoringConfig

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

Tests for self and other values to be equal, and is used by ==.

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

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

impl StructuralPartialEq for FeaturestoreMonitoringConfig