Struct CanvasAppSettings

#[non_exhaustive]
pub struct CanvasAppSettings {
    pub time_series_forecasting_settings: Option<TimeSeriesForecastingSettings>,
    pub model_register_settings: Option<ModelRegisterSettings>,
    pub workspace_settings: Option<WorkspaceSettings>,
    pub identity_provider_o_auth_settings: Option<Vec<IdentityProviderOAuthSetting>>,
    pub direct_deploy_settings: Option<DirectDeploySettings>,
    pub kendra_settings: Option<KendraSettings>,
    pub generative_ai_settings: Option<GenerativeAiSettings>,
    pub emr_serverless_settings: Option<EmrServerlessSettings>,
}

The SageMaker Canvas application settings.

Fields (Non-exhaustive)

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

time_series_forecasting_settings: Option<TimeSeriesForecastingSettings>

Time series forecast settings for the SageMaker Canvas application.

model_register_settings: Option<ModelRegisterSettings>

The model registry settings for the SageMaker Canvas application.

workspace_settings: Option<WorkspaceSettings>

The workspace settings for the SageMaker Canvas application.

identity_provider_o_auth_settings: Option<Vec<IdentityProviderOAuthSetting>>

The settings for connecting to an external data source with OAuth.

direct_deploy_settings: Option<DirectDeploySettings>

The model deployment settings for the SageMaker Canvas application.

kendra_settings: Option<KendraSettings>

The settings for document querying.

generative_ai_settings: Option<GenerativeAiSettings>

The generative AI settings for the SageMaker Canvas application.

emr_serverless_settings: Option<EmrServerlessSettings>

The settings for running Amazon EMR Serverless data processing jobs in SageMaker Canvas.

Implementations

impl CanvasAppSettings

pub fn time_series_forecasting_settings( &self, ) -> Option<&TimeSeriesForecastingSettings>

Time series forecast settings for the SageMaker Canvas application.

pub fn model_register_settings(&self) -> Option<&ModelRegisterSettings>

The model registry settings for the SageMaker Canvas application.

pub fn workspace_settings(&self) -> Option<&WorkspaceSettings>

The workspace settings for the SageMaker Canvas application.

pub fn identity_provider_o_auth_settings( &self, ) -> &[IdentityProviderOAuthSetting]

The settings for connecting to an external data source with OAuth.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .identity_provider_o_auth_settings.is_none().

pub fn direct_deploy_settings(&self) -> Option<&DirectDeploySettings>

The model deployment settings for the SageMaker Canvas application.

pub fn kendra_settings(&self) -> Option<&KendraSettings>

The settings for document querying.

pub fn generative_ai_settings(&self) -> Option<&GenerativeAiSettings>

The generative AI settings for the SageMaker Canvas application.

pub fn emr_serverless_settings(&self) -> Option<&EmrServerlessSettings>

The settings for running Amazon EMR Serverless data processing jobs in SageMaker Canvas.

impl CanvasAppSettings

pub fn builder() -> CanvasAppSettingsBuilder

Creates a new builder-style object to manufacture CanvasAppSettings.

Trait Implementations

impl Clone for CanvasAppSettings

fn clone(&self) -> CanvasAppSettings

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for CanvasAppSettings

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

Formats the value using the given formatter.

impl PartialEq for CanvasAppSettings

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

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

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

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

impl StructuralPartialEq for CanvasAppSettings