Struct CreateMLInputChannelFluentBuilder 

pub struct CreateMLInputChannelFluentBuilder { /* private fields */ }

Fluent builder constructing a request to CreateMLInputChannel.

Provides the information to create an ML input channel. An ML input channel is the result of a query that can be used for ML modeling.

Implementations

impl CreateMLInputChannelFluentBuilder

pub fn as_input(&self) -> &CreateMlInputChannelInputBuilder

Access the CreateMLInputChannel as a reference.

pub async fn send( self, ) -> Result<CreateMlInputChannelOutput, SdkError<CreateMLInputChannelError, HttpResponse>>

Sends the request and returns the response.

If an error occurs, an SdkError will be returned with additional details that can be matched against.

By default, any retryable failures will be retried twice. Retry behavior is configurable with the RetryConfig, which can be set when configuring the client.

pub fn customize( self, ) -> CustomizableOperation<CreateMlInputChannelOutput, CreateMLInputChannelError, Self>

Consumes this builder, creating a customizable operation that can be modified before being sent.

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

The membership ID of the member that is creating the ML input channel.

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

The membership ID of the member that is creating the ML input channel.

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

The membership ID of the member that is creating the ML input channel.

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

Appends an item to configuredModelAlgorithmAssociations.

To override the contents of this collection use set_configured_model_algorithm_associations.

The associated configured model algorithms that are necessary to create this ML input channel.

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

The associated configured model algorithms that are necessary to create this ML input channel.

pub fn get_configured_model_algorithm_associations( &self, ) -> &Option<Vec<String>>

The associated configured model algorithms that are necessary to create this ML input channel.

pub fn input_channel(self, input: InputChannel) -> Self

The input data that is used to create this ML input channel.

pub fn set_input_channel(self, input: Option<InputChannel>) -> Self

The input data that is used to create this ML input channel.

pub fn get_input_channel(&self) -> &Option<InputChannel>

The input data that is used to create this ML input channel.

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

The name of the ML input channel.

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

The name of the ML input channel.

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

The name of the ML input channel.

pub fn retention_in_days(self, input: i32) -> Self

The number of days that the data in the ML input channel is retained.

pub fn set_retention_in_days(self, input: Option<i32>) -> Self

The number of days that the data in the ML input channel is retained.

pub fn get_retention_in_days(&self) -> &Option<i32>

The number of days that the data in the ML input channel is retained.

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

The description of the ML input channel.

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

The description of the ML input channel.

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

The description of the ML input channel.

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

The Amazon Resource Name (ARN) of the KMS key that is used to access the input channel.

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

The Amazon Resource Name (ARN) of the KMS key that is used to access the input channel.

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

The Amazon Resource Name (ARN) of the KMS key that is used to access the input channel.

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

Adds a key-value pair to tags.

To override the contents of this collection use set_tags.

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

• Maximum number of tags per resource - 50.

• For each resource, each tag key must be unique, and each tag key can have only one value.

• Maximum key length - 128 Unicode characters in UTF-8.

• Maximum value length - 256 Unicode characters in UTF-8.

• If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.

• Tag keys and values are case sensitive.

• Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Clean Rooms ML considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

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

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

• Maximum number of tags per resource - 50.

• For each resource, each tag key must be unique, and each tag key can have only one value.

• Maximum key length - 128 Unicode characters in UTF-8.

• Maximum value length - 256 Unicode characters in UTF-8.

• If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.

• Tag keys and values are case sensitive.

• Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Clean Rooms ML considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

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

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

• Maximum number of tags per resource - 50.

• For each resource, each tag key must be unique, and each tag key can have only one value.

• Maximum key length - 128 Unicode characters in UTF-8.

• Maximum value length - 256 Unicode characters in UTF-8.

• If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.

• Tag keys and values are case sensitive.

• Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Clean Rooms ML considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

Trait Implementations

impl Clone for CreateMLInputChannelFluentBuilder

fn clone(&self) -> CreateMLInputChannelFluentBuilder

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for CreateMLInputChannelFluentBuilder

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

Formats the value using the given formatter.