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google-native.aiplatform/v1.FeatureStoreFeature
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Google Cloud Native is in preview. Google Cloud Classic is fully supported.
Creates a new Feature in a given EntityType.
Create FeatureStoreFeature Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new FeatureStoreFeature(name: string, args: FeatureStoreFeatureArgs, opts?: CustomResourceOptions);
@overload
def FeatureStoreFeature(resource_name: str,
args: FeatureStoreFeatureArgs,
opts: Optional[ResourceOptions] = None)
@overload
def FeatureStoreFeature(resource_name: str,
opts: Optional[ResourceOptions] = None,
entity_type_id: Optional[str] = None,
feature_id: Optional[str] = None,
featurestore_id: Optional[str] = None,
description: Optional[str] = None,
disable_monitoring: Optional[bool] = None,
etag: Optional[str] = None,
labels: Optional[Mapping[str, str]] = None,
location: Optional[str] = None,
name: Optional[str] = None,
project: Optional[str] = None,
value_type: Optional[FeatureStoreFeatureValueType] = None,
version_column_name: Optional[str] = None)
func NewFeatureStoreFeature(ctx *Context, name string, args FeatureStoreFeatureArgs, opts ...ResourceOption) (*FeatureStoreFeature, error)
public FeatureStoreFeature(string name, FeatureStoreFeatureArgs args, CustomResourceOptions? opts = null)
public FeatureStoreFeature(String name, FeatureStoreFeatureArgs args)
public FeatureStoreFeature(String name, FeatureStoreFeatureArgs args, CustomResourceOptions options)
type: google-native:aiplatform/v1:FeatureStoreFeature
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
Parameters
- name string
- The unique name of the resource.
- args FeatureStoreFeatureArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- resource_name str
- The unique name of the resource.
- args FeatureStoreFeatureArgs
- The arguments to resource properties.
- opts ResourceOptions
- Bag of options to control resource's behavior.
- ctx Context
- Context object for the current deployment.
- name string
- The unique name of the resource.
- args FeatureStoreFeatureArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args FeatureStoreFeatureArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args FeatureStoreFeatureArgs
- The arguments to resource properties.
- options CustomResourceOptions
- Bag of options to control resource's behavior.
Constructor example
The following reference example uses placeholder values for all input properties.
var featureStoreFeatureResource = new GoogleNative.Aiplatform.V1.FeatureStoreFeature("featureStoreFeatureResource", new()
{
EntityTypeId = "string",
FeatureId = "string",
FeaturestoreId = "string",
Description = "string",
DisableMonitoring = false,
Etag = "string",
Labels =
{
{ "string", "string" },
},
Location = "string",
Name = "string",
Project = "string",
ValueType = GoogleNative.Aiplatform.V1.FeatureStoreFeatureValueType.ValueTypeUnspecified,
VersionColumnName = "string",
});
example, err := aiplatform.NewFeatureStoreFeature(ctx, "featureStoreFeatureResource", &aiplatform.FeatureStoreFeatureArgs{
EntityTypeId: pulumi.String("string"),
FeatureId: pulumi.String("string"),
FeaturestoreId: pulumi.String("string"),
Description: pulumi.String("string"),
DisableMonitoring: pulumi.Bool(false),
Etag: pulumi.String("string"),
Labels: pulumi.StringMap{
"string": pulumi.String("string"),
},
Location: pulumi.String("string"),
Name: pulumi.String("string"),
Project: pulumi.String("string"),
ValueType: aiplatform.FeatureStoreFeatureValueTypeValueTypeUnspecified,
VersionColumnName: pulumi.String("string"),
})
var featureStoreFeatureResource = new FeatureStoreFeature("featureStoreFeatureResource", FeatureStoreFeatureArgs.builder()
.entityTypeId("string")
.featureId("string")
.featurestoreId("string")
.description("string")
.disableMonitoring(false)
.etag("string")
.labels(Map.of("string", "string"))
.location("string")
.name("string")
.project("string")
.valueType("VALUE_TYPE_UNSPECIFIED")
.versionColumnName("string")
.build());
feature_store_feature_resource = google_native.aiplatform.v1.FeatureStoreFeature("featureStoreFeatureResource",
entity_type_id="string",
feature_id="string",
featurestore_id="string",
description="string",
disable_monitoring=False,
etag="string",
labels={
"string": "string",
},
location="string",
name="string",
project="string",
value_type=google_native.aiplatform.v1.FeatureStoreFeatureValueType.VALUE_TYPE_UNSPECIFIED,
version_column_name="string")
const featureStoreFeatureResource = new google_native.aiplatform.v1.FeatureStoreFeature("featureStoreFeatureResource", {
entityTypeId: "string",
featureId: "string",
featurestoreId: "string",
description: "string",
disableMonitoring: false,
etag: "string",
labels: {
string: "string",
},
location: "string",
name: "string",
project: "string",
valueType: google_native.aiplatform.v1.FeatureStoreFeatureValueType.ValueTypeUnspecified,
versionColumnName: "string",
});
type: google-native:aiplatform/v1:FeatureStoreFeature
properties:
description: string
disableMonitoring: false
entityTypeId: string
etag: string
featureId: string
featurestoreId: string
labels:
string: string
location: string
name: string
project: string
valueType: VALUE_TYPE_UNSPECIFIED
versionColumnName: string
FeatureStoreFeature Resource Properties
To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.
Inputs
The FeatureStoreFeature resource accepts the following input properties:
- Entity
Type stringId - Feature
Id string - Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are
[a-z0-9_]
. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup. - Featurestore
Id string - Description string
- Description of the Feature.
- 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) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
- Etag string
- Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
- Labels Dictionary<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.
- Location string
- 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. - Project string
- Value
Type Pulumi.Google Native. Aiplatform. V1. Feature Store Feature Value Type - Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
- Version
Column stringName - Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
- Entity
Type stringId - Feature
Id string - Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are
[a-z0-9_]
. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup. - Featurestore
Id string - Description string
- Description of the Feature.
- 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) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
- Etag string
- Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
- Labels map[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.
- Location string
- 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. - Project string
- Value
Type FeatureStore Feature Value Type - Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
- Version
Column stringName - Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
- entity
Type StringId - feature
Id String - Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are
[a-z0-9_]
. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup. - featurestore
Id String - description String
- Description of the Feature.
- disable
Monitoring Boolean - 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) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
- etag String
- Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
- labels Map<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.
- location String
- 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. - project String
- value
Type FeatureStore Feature Value Type - Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
- version
Column StringName - Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
- entity
Type stringId - feature
Id string - Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are
[a-z0-9_]
. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup. - featurestore
Id string - description string
- Description of the Feature.
- disable
Monitoring boolean - 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) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
- etag string
- Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
- labels {[key: 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.
- location string
- 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. - project string
- value
Type FeatureStore Feature Value Type - Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
- version
Column stringName - Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
- entity_
type_ strid - feature_
id str - Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are
[a-z0-9_]
. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup. - featurestore_
id str - description str
- Description of the Feature.
- 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) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
- etag str
- Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
- labels Mapping[str, str]
- 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.
- location str
- name str
- 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. - project str
- value_
type FeatureStore Feature Value Type - Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
- version_
column_ strname - Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
- entity
Type StringId - feature
Id String - Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are
[a-z0-9_]
. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup. - featurestore
Id String - description String
- Description of the Feature.
- disable
Monitoring Boolean - 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) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
- etag String
- Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
- labels Map<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.
- location String
- 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. - project String
- value
Type "VALUE_TYPE_UNSPECIFIED" | "BOOL" | "BOOL_ARRAY" | "DOUBLE" | "DOUBLE_ARRAY" | "INT64" | "INT64_ARRAY" | "STRING" | "STRING_ARRAY" | "BYTES" - Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
- version
Column StringName - Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
Outputs
All input properties are implicitly available as output properties. Additionally, the FeatureStoreFeature resource produces the following output properties:
- Create
Time string - Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
- Id string
- The provider-assigned unique ID for this managed resource.
- Monitoring
Stats List<Pulumi.Anomalies Google Native. Aiplatform. V1. Outputs. Google Cloud Aiplatform V1Feature Monitoring Stats Anomaly Response> - Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
- Update
Time string - Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
- Create
Time string - Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
- Id string
- The provider-assigned unique ID for this managed resource.
- Monitoring
Stats []GoogleAnomalies Cloud Aiplatform V1Feature Monitoring Stats Anomaly Response - Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
- Update
Time string - Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
- create
Time String - Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
- id String
- The provider-assigned unique ID for this managed resource.
- monitoring
Stats List<GoogleAnomalies Cloud Aiplatform V1Feature Monitoring Stats Anomaly Response> - Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
- update
Time String - Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
- create
Time string - Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
- id string
- The provider-assigned unique ID for this managed resource.
- monitoring
Stats GoogleAnomalies Cloud Aiplatform V1Feature Monitoring Stats Anomaly Response[] - Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
- update
Time string - Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
- create_
time str - Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
- id str
- The provider-assigned unique ID for this managed resource.
- monitoring_
stats_ Sequence[Googleanomalies Cloud Aiplatform V1Feature Monitoring Stats Anomaly Response] - Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
- update_
time str - Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
- create
Time String - Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
- id String
- The provider-assigned unique ID for this managed resource.
- monitoring
Stats List<Property Map>Anomalies - Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
- update
Time String - Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
Supporting Types
FeatureStoreFeatureValueType, FeatureStoreFeatureValueTypeArgs
- Value
Type Unspecified - VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
- Bool
- BOOLUsed for Feature that is a boolean.
- Bool
Array - BOOL_ARRAYUsed for Feature that is a list of boolean.
- Double
- DOUBLEUsed for Feature that is double.
- Double
Array - DOUBLE_ARRAYUsed for Feature that is a list of double.
- Int64
- INT64Used for Feature that is INT64.
- Int64Array
- INT64_ARRAYUsed for Feature that is a list of INT64.
- String
- STRINGUsed for Feature that is string.
- String
Array - STRING_ARRAYUsed for Feature that is a list of String.
- Bytes
- BYTESUsed for Feature that is bytes.
- Feature
Store Feature Value Type Value Type Unspecified - VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
- Feature
Store Feature Value Type Bool - BOOLUsed for Feature that is a boolean.
- Feature
Store Feature Value Type Bool Array - BOOL_ARRAYUsed for Feature that is a list of boolean.
- Feature
Store Feature Value Type Double - DOUBLEUsed for Feature that is double.
- Feature
Store Feature Value Type Double Array - DOUBLE_ARRAYUsed for Feature that is a list of double.
- Feature
Store Feature Value Type Int64 - INT64Used for Feature that is INT64.
- Feature
Store Feature Value Type Int64Array - INT64_ARRAYUsed for Feature that is a list of INT64.
- Feature
Store Feature Value Type String - STRINGUsed for Feature that is string.
- Feature
Store Feature Value Type String Array - STRING_ARRAYUsed for Feature that is a list of String.
- Feature
Store Feature Value Type Bytes - BYTESUsed for Feature that is bytes.
- Value
Type Unspecified - VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
- Bool
- BOOLUsed for Feature that is a boolean.
- Bool
Array - BOOL_ARRAYUsed for Feature that is a list of boolean.
- Double
- DOUBLEUsed for Feature that is double.
- Double
Array - DOUBLE_ARRAYUsed for Feature that is a list of double.
- Int64
- INT64Used for Feature that is INT64.
- Int64Array
- INT64_ARRAYUsed for Feature that is a list of INT64.
- String
- STRINGUsed for Feature that is string.
- String
Array - STRING_ARRAYUsed for Feature that is a list of String.
- Bytes
- BYTESUsed for Feature that is bytes.
- Value
Type Unspecified - VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
- Bool
- BOOLUsed for Feature that is a boolean.
- Bool
Array - BOOL_ARRAYUsed for Feature that is a list of boolean.
- Double
- DOUBLEUsed for Feature that is double.
- Double
Array - DOUBLE_ARRAYUsed for Feature that is a list of double.
- Int64
- INT64Used for Feature that is INT64.
- Int64Array
- INT64_ARRAYUsed for Feature that is a list of INT64.
- String
- STRINGUsed for Feature that is string.
- String
Array - STRING_ARRAYUsed for Feature that is a list of String.
- Bytes
- BYTESUsed for Feature that is bytes.
- VALUE_TYPE_UNSPECIFIED
- VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
- BOOL
- BOOLUsed for Feature that is a boolean.
- BOOL_ARRAY
- BOOL_ARRAYUsed for Feature that is a list of boolean.
- DOUBLE
- DOUBLEUsed for Feature that is double.
- DOUBLE_ARRAY
- DOUBLE_ARRAYUsed for Feature that is a list of double.
- INT64
- INT64Used for Feature that is INT64.
- INT64_ARRAY
- INT64_ARRAYUsed for Feature that is a list of INT64.
- STRING
- STRINGUsed for Feature that is string.
- STRING_ARRAY
- STRING_ARRAYUsed for Feature that is a list of String.
- BYTES
- BYTESUsed for Feature that is bytes.
- "VALUE_TYPE_UNSPECIFIED"
- VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
- "BOOL"
- BOOLUsed for Feature that is a boolean.
- "BOOL_ARRAY"
- BOOL_ARRAYUsed for Feature that is a list of boolean.
- "DOUBLE"
- DOUBLEUsed for Feature that is double.
- "DOUBLE_ARRAY"
- DOUBLE_ARRAYUsed for Feature that is a list of double.
- "INT64"
- INT64Used for Feature that is INT64.
- "INT64_ARRAY"
- INT64_ARRAYUsed for Feature that is a list of INT64.
- "STRING"
- STRINGUsed for Feature that is string.
- "STRING_ARRAY"
- STRING_ARRAYUsed for Feature that is a list of String.
- "BYTES"
- BYTESUsed for Feature that is bytes.
GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponse, GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArgs
- Feature
Stats Pulumi.Anomaly Google Native. Aiplatform. V1. Inputs. Google Cloud Aiplatform V1Feature Stats Anomaly Response - The stats and anomalies generated at specific timestamp.
- Objective string
- The objective for each stats.
- Feature
Stats GoogleAnomaly Cloud Aiplatform V1Feature Stats Anomaly Response - The stats and anomalies generated at specific timestamp.
- Objective string
- The objective for each stats.
- feature
Stats GoogleAnomaly Cloud Aiplatform V1Feature Stats Anomaly Response - The stats and anomalies generated at specific timestamp.
- objective String
- The objective for each stats.
- feature
Stats GoogleAnomaly Cloud Aiplatform V1Feature Stats Anomaly Response - The stats and anomalies generated at specific timestamp.
- objective string
- The objective for each stats.
- feature_
stats_ Googleanomaly Cloud Aiplatform V1Feature Stats Anomaly Response - The stats and anomalies generated at specific timestamp.
- objective str
- The objective for each stats.
- feature
Stats Property MapAnomaly - The stats and anomalies generated at specific timestamp.
- objective String
- The objective for each stats.
GoogleCloudAiplatformV1FeatureStatsAnomalyResponse, GoogleCloudAiplatformV1FeatureStatsAnomalyResponseArgs
- Anomaly
Detection doubleThreshold - This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
- Anomaly
Uri string - Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
- Distribution
Deviation double - Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.
- End
Time string - The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).
- Score double
- Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.
- Start
Time string - The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).
- Stats
Uri string - Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message tensorflow.metadata.v0.FeatureNameStatistics.
- Anomaly
Detection float64Threshold - This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
- Anomaly
Uri string - Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
- Distribution
Deviation float64 - Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.
- End
Time string - The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).
- Score float64
- Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.
- Start
Time string - The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).
- Stats
Uri string - Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message tensorflow.metadata.v0.FeatureNameStatistics.
- anomaly
Detection DoubleThreshold - This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
- anomaly
Uri String - Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
- distribution
Deviation Double - Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.
- end
Time String - The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).
- score Double
- Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.
- start
Time String - The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).
- stats
Uri String - Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message tensorflow.metadata.v0.FeatureNameStatistics.
- anomaly
Detection numberThreshold - This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
- anomaly
Uri string - Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
- distribution
Deviation number - Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.
- end
Time string - The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).
- score number
- Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.
- start
Time string - The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).
- stats
Uri string - Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message tensorflow.metadata.v0.FeatureNameStatistics.
- anomaly_
detection_ floatthreshold - This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
- anomaly_
uri str - Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
- distribution_
deviation float - Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.
- end_
time str - The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).
- score float
- Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.
- start_
time str - The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).
- stats_
uri str - Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message tensorflow.metadata.v0.FeatureNameStatistics.
- anomaly
Detection NumberThreshold - This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
- anomaly
Uri String - Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
- distribution
Deviation Number - Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.
- end
Time String - The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).
- score Number
- Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.
- start
Time String - The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).
- stats
Uri String - Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message tensorflow.metadata.v0.FeatureNameStatistics.
Package Details
- Repository
- Google Cloud Native pulumi/pulumi-google-native
- License
- Apache-2.0
Google Cloud Native is in preview. Google Cloud Classic is fully supported.