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Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

google-native.aiplatform/v1.FeatureGroupFeature

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Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

    Creates a new Feature in a given FeatureGroup. Auto-naming is currently not supported for this resource.

    Create FeatureGroupFeature Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new FeatureGroupFeature(name: string, args: FeatureGroupFeatureArgs, opts?: CustomResourceOptions);
    @overload
def FeatureGroupFeature(resource_name: str,
                        args: FeatureGroupFeatureArgs,
                        opts: Optional[ResourceOptions] = None)

@overload
def FeatureGroupFeature(resource_name: str,
                        opts: Optional[ResourceOptions] = None,
                        feature_group_id: Optional[str] = None,
                        feature_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[FeatureGroupFeatureValueType] = None,
                        version_column_name: Optional[str] = None)
    func NewFeatureGroupFeature(ctx *Context, name string, args FeatureGroupFeatureArgs, opts ...ResourceOption) (*FeatureGroupFeature, error)
    public FeatureGroupFeature(string name, FeatureGroupFeatureArgs args, CustomResourceOptions? opts = null)
    public FeatureGroupFeature(String name, FeatureGroupFeatureArgs args)
public FeatureGroupFeature(String name, FeatureGroupFeatureArgs args, CustomResourceOptions options)

    type: google-native:aiplatform/v1:FeatureGroupFeature
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 FeatureGroupFeatureArgs
    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 FeatureGroupFeatureArgs
    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 FeatureGroupFeatureArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args FeatureGroupFeatureArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args FeatureGroupFeatureArgs
    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 featureGroupFeatureResource = new GoogleNative.Aiplatform.V1.FeatureGroupFeature("featureGroupFeatureResource", new()
{
    FeatureGroupId = "string",
    FeatureId = "string",
    Description = "string",
    DisableMonitoring = false,
    Etag = "string",
    Labels = 
    {
        { "string", "string" },
    },
    Location = "string",
    Name = "string",
    Project = "string",
    ValueType = GoogleNative.Aiplatform.V1.FeatureGroupFeatureValueType.ValueTypeUnspecified,
    VersionColumnName = "string",
});

    example, err := aiplatform.NewFeatureGroupFeature(ctx, "featureGroupFeatureResource", &aiplatform.FeatureGroupFeatureArgs{
FeatureGroupId: pulumi.String("string"),
FeatureId: 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.FeatureGroupFeatureValueTypeValueTypeUnspecified,
VersionColumnName: pulumi.String("string"),
})

    var featureGroupFeatureResource = new FeatureGroupFeature("featureGroupFeatureResource", FeatureGroupFeatureArgs.builder()
    .featureGroupId("string")
    .featureId("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_group_feature_resource = google_native.aiplatform.v1.FeatureGroupFeature("featureGroupFeatureResource",
    feature_group_id="string",
    feature_id="string",
    description="string",
    disable_monitoring=False,
    etag="string",
    labels={
        "string": "string",
    },
    location="string",
    name="string",
    project="string",
    value_type=google_native.aiplatform.v1.FeatureGroupFeatureValueType.VALUE_TYPE_UNSPECIFIED,
    version_column_name="string")

    const featureGroupFeatureResource = new google_native.aiplatform.v1.FeatureGroupFeature("featureGroupFeatureResource", {
    featureGroupId: "string",
    featureId: "string",
    description: "string",
    disableMonitoring: false,
    etag: "string",
    labels: {
        string: "string",
    },
    location: "string",
    name: "string",
    project: "string",
    valueType: google_native.aiplatform.v1.FeatureGroupFeatureValueType.ValueTypeUnspecified,
    versionColumnName: "string",
});

    type: google-native:aiplatform/v1:FeatureGroupFeature
properties:
    description: string
    disableMonitoring: false
    etag: string
    featureGroupId: string
    featureId: string
    labels:
        string: string
    location: string
    name: string
    project: string
    valueType: VALUE_TYPE_UNSPECIFIED
    versionColumnName: string

    FeatureGroupFeature 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 FeatureGroupFeature resource accepts the following input properties:

    FeatureGroupId string
    FeatureId 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.
    Description string
    Description of the Feature.
    DisableMonitoring 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
    ValueType Pulumi.GoogleNative.Aiplatform.V1.FeatureGroupFeatureValueType
    Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
    VersionColumnName string
    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.
    FeatureGroupId string
    FeatureId 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.
    Description string
    Description of the Feature.
    DisableMonitoring 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
    ValueType FeatureGroupFeatureValueType
    Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
    VersionColumnName string
    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.
    featureGroupId String
    featureId 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.
    description String
    Description of the Feature.
    disableMonitoring 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
    valueType FeatureGroupFeatureValueType
    Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
    versionColumnName String
    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.
    featureGroupId string
    featureId 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.
    description string
    Description of the Feature.
    disableMonitoring 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
    valueType FeatureGroupFeatureValueType
    Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
    versionColumnName string
    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.
    feature_group_id str
    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.
    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 FeatureGroupFeatureValueType
    Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
    version_column_name str
    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.
    featureGroupId String
    featureId 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.
    description String
    Description of the Feature.
    disableMonitoring 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
    valueType "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.
    versionColumnName String
    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 FeatureGroupFeature resource produces the following output properties:

    CreateTime 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.
    MonitoringStatsAnomalies List<Pulumi.GoogleNative.Aiplatform.V1.Outputs.GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponse>
    Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
    UpdateTime string
    Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
    CreateTime 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.
    MonitoringStatsAnomalies []GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponse
    Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
    UpdateTime string
    Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
    createTime 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.
    monitoringStatsAnomalies List<GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponse>
    Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
    updateTime String
    Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
    createTime 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.
    monitoringStatsAnomalies GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponse[]
    Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
    updateTime 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_anomalies Sequence[GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponse]
    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.
    createTime 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.
    monitoringStatsAnomalies List<Property Map>
    Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
    updateTime String
    Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.

    Supporting Types

    FeatureGroupFeatureValueType, FeatureGroupFeatureValueTypeArgs

    ValueTypeUnspecified
    VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
    Bool
    BOOLUsed for Feature that is a boolean.
    BoolArray
    BOOL_ARRAYUsed for Feature that is a list of boolean.
    Double
    DOUBLEUsed for Feature that is double.
    DoubleArray
    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.
    StringArray
    STRING_ARRAYUsed for Feature that is a list of String.
    Bytes
    BYTESUsed for Feature that is bytes.
    FeatureGroupFeatureValueTypeValueTypeUnspecified
    VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
    FeatureGroupFeatureValueTypeBool
    BOOLUsed for Feature that is a boolean.
    FeatureGroupFeatureValueTypeBoolArray
    BOOL_ARRAYUsed for Feature that is a list of boolean.
    FeatureGroupFeatureValueTypeDouble
    DOUBLEUsed for Feature that is double.
    FeatureGroupFeatureValueTypeDoubleArray
    DOUBLE_ARRAYUsed for Feature that is a list of double.
    FeatureGroupFeatureValueTypeInt64
    INT64Used for Feature that is INT64.
    FeatureGroupFeatureValueTypeInt64Array
    INT64_ARRAYUsed for Feature that is a list of INT64.
    FeatureGroupFeatureValueTypeString
    STRINGUsed for Feature that is string.
    FeatureGroupFeatureValueTypeStringArray
    STRING_ARRAYUsed for Feature that is a list of String.
    FeatureGroupFeatureValueTypeBytes
    BYTESUsed for Feature that is bytes.
    ValueTypeUnspecified
    VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
    Bool
    BOOLUsed for Feature that is a boolean.
    BoolArray
    BOOL_ARRAYUsed for Feature that is a list of boolean.
    Double
    DOUBLEUsed for Feature that is double.
    DoubleArray
    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.
    StringArray
    STRING_ARRAYUsed for Feature that is a list of String.
    Bytes
    BYTESUsed for Feature that is bytes.
    ValueTypeUnspecified
    VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
    Bool
    BOOLUsed for Feature that is a boolean.
    BoolArray
    BOOL_ARRAYUsed for Feature that is a list of boolean.
    Double
    DOUBLEUsed for Feature that is double.
    DoubleArray
    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.
    StringArray
    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

    FeatureStatsAnomaly Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeatureStatsAnomalyResponse
    The stats and anomalies generated at specific timestamp.
    Objective string
    The objective for each stats.
    FeatureStatsAnomaly GoogleCloudAiplatformV1FeatureStatsAnomalyResponse
    The stats and anomalies generated at specific timestamp.
    Objective string
    The objective for each stats.
    featureStatsAnomaly GoogleCloudAiplatformV1FeatureStatsAnomalyResponse
    The stats and anomalies generated at specific timestamp.
    objective String
    The objective for each stats.
    featureStatsAnomaly GoogleCloudAiplatformV1FeatureStatsAnomalyResponse
    The stats and anomalies generated at specific timestamp.
    objective string
    The objective for each stats.
    feature_stats_anomaly GoogleCloudAiplatformV1FeatureStatsAnomalyResponse
    The stats and anomalies generated at specific timestamp.
    objective str
    The objective for each stats.
    featureStatsAnomaly Property Map
    The stats and anomalies generated at specific timestamp.
    objective String
    The objective for each stats.

    GoogleCloudAiplatformV1FeatureStatsAnomalyResponse, GoogleCloudAiplatformV1FeatureStatsAnomalyResponseArgs

    AnomalyDetectionThreshold double
    This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
    AnomalyUri 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).
    DistributionDeviation 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.
    EndTime 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.
    StartTime 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).
    StatsUri 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.
    AnomalyDetectionThreshold float64
    This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
    AnomalyUri 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).
    DistributionDeviation 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.
    EndTime 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.
    StartTime 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).
    StatsUri 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.
    anomalyDetectionThreshold Double
    This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
    anomalyUri 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).
    distributionDeviation 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.
    endTime 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.
    startTime 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).
    statsUri 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.
    anomalyDetectionThreshold number
    This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
    anomalyUri 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).
    distributionDeviation 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.
    endTime 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.
    startTime 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).
    statsUri 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_threshold float
    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.
    anomalyDetectionThreshold Number
    This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
    anomalyUri 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).
    distributionDeviation 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.
    endTime 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.
    startTime 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).
    statsUri 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-native logo

    Google Cloud Native is in preview. Google Cloud Classic is fully supported.

    Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
    pulumi/pulumi-google-native