Struct gcp_bigquery_client::model::model::Model

pub struct Model {

    pub description: Option<String>,
    pub location: Option<String>,
    pub expiration_time: Option<i64>,
    pub training_runs: Option<Vec<TrainingRun>>,
    pub etag: Option<String>,
    pub creation_time: Option<i64>,
    pub last_modified_time: Option<i64>,
    pub feature_columns: Option<Vec<StandardSqlField>>,
    pub model_reference: ModelReference,
    pub label_columns: Option<Vec<StandardSqlField>>,
    pub encryption_configuration: Option<EncryptionConfiguration>,
    pub friendly_name: Option<String>,
    pub labels: Option<HashMap<String, String>>,
    pub model_type: Option<ModelType>,
}

Fields

description: Option<String>

Optional. A user-friendly description of this model.

location: Option<String>

Output only. The geographic location where the model resides. This value is inherited from the dataset.

expiration_time: Option<i64>

Optional. The time when this model expires, in milliseconds since the epoch. If not present, the model will persist indefinitely. Expired models will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created models.

training_runs: Option<Vec<TrainingRun>>

Output only. Information for all training runs in increasing order of start_time.

etag: Option<String>

Output only. A hash of this resource.

creation_time: Option<i64>

Output only. The time when this model was created, in millisecs since the epoch.

last_modified_time: Option<i64>

Output only. The time when this model was last modified, in millisecs since the epoch.

feature_columns: Option<Vec<StandardSqlField>>

Output only. Input feature columns that were used to train this model.

model_reference: ModelReference

Required. Unique identifier for this model.

label_columns: Option<Vec<StandardSqlField>>

Output only. Label columns that were used to train this model. The output of the model will have a “predicted_” prefix to these columns.

encryption_configuration: Option<EncryptionConfiguration>

Custom encryption configuration (e.g., Cloud KMS keys). This shows the encryption configuration of the model data while stored in BigQuery storage. This field can be used with PatchModel to update encryption key for an already encrypted model.

friendly_name: Option<String>

Optional. A descriptive name for this model.

labels: Option<HashMap<String, String>>

The labels associated with this model. You can use these to organize and group your models. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.

model_type: Option<ModelType>

Output only. Type of the model resource.

Trait Implementations

impl Clone for Model

fn clone(&self) -> Model

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Model

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

Formats the value using the given formatter.

impl Default for Model

fn default() -> Model

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for Model

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for Model

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.