Resource: Feature
feature metadata information. For example, color is a feature that describes an apple.
name
string
Immutable. name of the feature. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}/features/{feature}
projects/{project}/locations/{location}/featureGroups/{featureGroup}/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.
Immutable. Only applicable for Vertex AI feature Store (Legacy). type of feature value.
Output only. Only applicable for Vertex AI feature Store (Legacy). timestamp when this EntityType was created.
A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z"
and "2014-10-02T15:01:23.045123456Z"
.
Output only. Only applicable for Vertex AI feature Store (Legacy). timestamp when this EntityType was most recently updated.
A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z"
and "2014-10-02T15:01:23.045123456Z"
.
labels
map (key: string, value: 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.
Optional. Only applicable for Vertex AI feature Store (Legacy). Deprecated: The custom monitoring configuration for this feature, if not set, use the monitoringConfig defined for the EntityType this feature belongs to. Only Features with type (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.
disableMonitoring
boolean
Optional. Only applicable for Vertex AI feature Store (Legacy). If not set, use the monitoringConfig defined for the EntityType this feature belongs to. Only Features with type (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.
Output only. Only applicable for Vertex AI feature Store (Legacy). A list of historical SnapshotAnalysis
stats requested by user, sorted by FeatureStatsAnomaly.start_time
descending.
Output only. Only applicable for Vertex AI feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
versionColumnName
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 featureId.
pointOfContact
string
Entity responsible for maintaining this feature. Can be comma separated list of email addresses or URIs.
JSON representation |
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{ "name": string, "description": string, "valueType": enum ( |
Methods |
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Creates a batch of Features in a given EntityType. |
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Creates a new Feature in a given EntityType. |
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Deletes a single Feature. |
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Gets details of a single Feature. |
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Lists Features in a given EntityType. |
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Updates the parameters of a single Feature. |