Struct aws_sdk_forecast::input::CreateWhatIfForecastInput
source · #[non_exhaustive]pub struct CreateWhatIfForecastInput { /* private fields */ }Implementations§
source§impl CreateWhatIfForecastInput
impl CreateWhatIfForecastInput
sourcepub async fn make_operation(
&self,
_config: &Config
) -> Result<Operation<CreateWhatIfForecast, AwsResponseRetryClassifier>, BuildError>
pub async fn make_operation(
&self,
_config: &Config
) -> Result<Operation<CreateWhatIfForecast, AwsResponseRetryClassifier>, BuildError>
Consumes the builder and constructs an Operation<CreateWhatIfForecast>
sourcepub fn builder() -> Builder
pub fn builder() -> Builder
Creates a new builder-style object to manufacture CreateWhatIfForecastInput.
source§impl CreateWhatIfForecastInput
impl CreateWhatIfForecastInput
sourcepub fn what_if_forecast_name(&self) -> Option<&str>
pub fn what_if_forecast_name(&self) -> Option<&str>
The name of the what-if forecast. Names must be unique within each what-if analysis.
sourcepub fn what_if_analysis_arn(&self) -> Option<&str>
pub fn what_if_analysis_arn(&self) -> Option<&str>
The Amazon Resource Name (ARN) of the what-if analysis.
sourcepub fn time_series_transformations(&self) -> Option<&[TimeSeriesTransformation]>
pub fn time_series_transformations(&self) -> Option<&[TimeSeriesTransformation]>
The transformations that are applied to the baseline time series. Each transformation contains an action and a set of conditions. An action is applied only when all conditions are met. If no conditions are provided, the action is applied to all items.
sourcepub fn time_series_replacements_data_source(
&self
) -> Option<&TimeSeriesReplacementsDataSource>
pub fn time_series_replacements_data_source(
&self
) -> Option<&TimeSeriesReplacementsDataSource>
The replacement time series dataset, which contains the rows that you want to change in the related time series dataset. A replacement time series does not need to contain all rows that are in the baseline related time series. Include only the rows (measure-dimension combinations) that you want to include in the what-if forecast. This dataset is merged with the original time series to create a transformed dataset that is used for the what-if analysis.
This dataset should contain the items to modify (such as item_id or workforce_type), any relevant dimensions, the timestamp column, and at least one of the related time series columns. This file should not contain duplicate timestamps for the same time series.
Timestamps and item_ids not included in this dataset are not included in the what-if analysis.
A list of tags to apply to the what if forecast.
Trait Implementations§
source§impl Clone for CreateWhatIfForecastInput
impl Clone for CreateWhatIfForecastInput
source§fn clone(&self) -> CreateWhatIfForecastInput
fn clone(&self) -> CreateWhatIfForecastInput
1.0.0 · source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source. Read moresource§impl Debug for CreateWhatIfForecastInput
impl Debug for CreateWhatIfForecastInput
source§impl PartialEq<CreateWhatIfForecastInput> for CreateWhatIfForecastInput
impl PartialEq<CreateWhatIfForecastInput> for CreateWhatIfForecastInput
source§fn eq(&self, other: &CreateWhatIfForecastInput) -> bool
fn eq(&self, other: &CreateWhatIfForecastInput) -> bool
self and other values to be equal, and is used
by ==.