Struct aws_sdk_forecast::types::builders::AttributeConfigBuilder

#[non_exhaustive]
pub struct AttributeConfigBuilder { /* private fields */ }

A builder for AttributeConfig.

Implementations

impl AttributeConfigBuilder

pub fn attribute_name(self, input: impl Into<String>) -> Self

The name of the attribute as specified in the schema. Amazon Forecast supports the target field of the target time series and the related time series datasets. For example, for the RETAIL domain, the target is demand.

This field is required.

pub fn set_attribute_name(self, input: Option<String>) -> Self

The name of the attribute as specified in the schema. Amazon Forecast supports the target field of the target time series and the related time series datasets. For example, for the RETAIL domain, the target is demand.

pub fn get_attribute_name(&self) -> &Option<String>

The name of the attribute as specified in the schema. Amazon Forecast supports the target field of the target time series and the related time series datasets. For example, for the RETAIL domain, the target is demand.

pub fn transformations(self, k: impl Into<String>, v: impl Into<String>) -> Self

Adds a key-value pair to transformations.

To override the contents of this collection use set_transformations.

The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters to override the default values. Related Time Series attributes do not accept aggregation parameters.

The following list shows the parameters and their valid values for the "filling" featurization method for a Target Time Series dataset. Default values are bolded.

• aggregation: sum, avg, first, min, max

• frontfill: none

• middlefill: zero, nan (not a number), value, median, mean, min, max

• backfill: zero, nan, value, median, mean, min, max

The following list shows the parameters and their valid values for a Related Time Series featurization method (there are no defaults):

• middlefill: zero, value, median, mean, min, max

• backfill: zero, value, median, mean, min, max

• futurefill: zero, value, median, mean, min, max

To set a filling method to a specific value, set the fill parameter to value and define the value in a corresponding _value parameter. For example, to set backfilling to a value of 2, include the following: "backfill": "value" and "backfill_value":"2".

pub fn set_transformations(self, input: Option<HashMap<String, String>>) -> Self

The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters to override the default values. Related Time Series attributes do not accept aggregation parameters.

The following list shows the parameters and their valid values for the "filling" featurization method for a Target Time Series dataset. Default values are bolded.

• aggregation: sum, avg, first, min, max

• frontfill: none

• middlefill: zero, nan (not a number), value, median, mean, min, max

• backfill: zero, nan, value, median, mean, min, max

The following list shows the parameters and their valid values for a Related Time Series featurization method (there are no defaults):

• middlefill: zero, value, median, mean, min, max

• backfill: zero, value, median, mean, min, max

• futurefill: zero, value, median, mean, min, max

To set a filling method to a specific value, set the fill parameter to value and define the value in a corresponding _value parameter. For example, to set backfilling to a value of 2, include the following: "backfill": "value" and "backfill_value":"2".

pub fn get_transformations(&self) -> &Option<HashMap<String, String>>

The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters to override the default values. Related Time Series attributes do not accept aggregation parameters.

The following list shows the parameters and their valid values for the "filling" featurization method for a Target Time Series dataset. Default values are bolded.

• aggregation: sum, avg, first, min, max

• frontfill: none

• middlefill: zero, nan (not a number), value, median, mean, min, max

• backfill: zero, nan, value, median, mean, min, max

The following list shows the parameters and their valid values for a Related Time Series featurization method (there are no defaults):

• middlefill: zero, value, median, mean, min, max

• backfill: zero, value, median, mean, min, max

• futurefill: zero, value, median, mean, min, max

To set a filling method to a specific value, set the fill parameter to value and define the value in a corresponding _value parameter. For example, to set backfilling to a value of 2, include the following: "backfill": "value" and "backfill_value":"2".

pub fn build(self) -> Result<AttributeConfig, BuildError>

Consumes the builder and constructs a AttributeConfig. This method will fail if any of the following fields are not set:

• attribute_name
• transformations

Trait Implementations

impl Clone for AttributeConfigBuilder

fn clone(&self) -> AttributeConfigBuilder

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for AttributeConfigBuilder

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

Formats the value using the given formatter.

impl Default for AttributeConfigBuilder

fn default() -> AttributeConfigBuilder

Returns the “default value” for a type.

impl PartialEq for AttributeConfigBuilder

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

This method tests for self and other values to be equal, and is used by ==.

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

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

impl StructuralPartialEq for AttributeConfigBuilder