Struct aws_sdk_personalize::client::fluent_builders::CreateRecommender

pub struct CreateRecommender { /* private fields */ }

Fluent builder constructing a request to CreateRecommender.

Creates a recommender with the recipe (a Domain dataset group use case) you specify. You create recommenders for a Domain dataset group and specify the recommender's Amazon Resource Name (ARN) when you make a GetRecommendations request.

Minimum recommendation requests per second

When you create a recommender, you can configure the recommender's minimum recommendation requests per second. The minimum recommendation requests per second (minRecommendationRequestsPerSecond) specifies the baseline recommendation request throughput provisioned by Amazon Personalize. The default minRecommendationRequestsPerSecond is 1. A recommendation request is a single GetRecommendations operation. Request throughput is measured in requests per second and Amazon Personalize uses your requests per second to derive your requests per hour and the price of your recommender usage.

If your requests per second increases beyond minRecommendationRequestsPerSecond, Amazon Personalize auto-scales the provisioned capacity up and down, but never below minRecommendationRequestsPerSecond. There's a short time delay while the capacity is increased that might cause loss of requests.

Your bill is the greater of either the minimum requests per hour (based on minRecommendationRequestsPerSecond) or the actual number of requests. The actual request throughput used is calculated as the average requests/second within a one-hour window. We recommend starting with the default minRecommendationRequestsPerSecond, track your usage using Amazon CloudWatch metrics, and then increase the minRecommendationRequestsPerSecond as necessary.

Status

A recommender can be in one of the following states:

• CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED

• STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE

• DELETE PENDING > DELETE IN_PROGRESS

To get the recommender status, call DescribeRecommender.

Wait until the status of the recommender is ACTIVE before asking the recommender for recommendations.

Related APIs

• ListRecommenders

• DescribeRecommender

• UpdateRecommender

• DeleteRecommender

Implementations

impl CreateRecommender

pub async fn customize(
    self
) -> Result<CustomizableOperation<CreateRecommender, AwsResponseRetryClassifier>, SdkError<CreateRecommenderError>>

Consume this builder, creating a customizable operation that can be modified before being sent. The operation’s inner http::Request can be modified as well.

pub async fn send(
    self
) -> Result<CreateRecommenderOutput, SdkError<CreateRecommenderError>>

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

The name of the recommender.

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

The name of the recommender.

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

The Amazon Resource Name (ARN) of the destination domain dataset group for the recommender.

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

The Amazon Resource Name (ARN) of the destination domain dataset group for the recommender.

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

The Amazon Resource Name (ARN) of the recipe that the recommender will use. For a recommender, a recipe is a Domain dataset group use case. Only Domain dataset group use cases can be used to create a recommender. For information about use cases see Choosing recommender use cases.

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

The Amazon Resource Name (ARN) of the recipe that the recommender will use. For a recommender, a recipe is a Domain dataset group use case. Only Domain dataset group use cases can be used to create a recommender. For information about use cases see Choosing recommender use cases.

pub fn recommender_config(self, input: RecommenderConfig) -> Self

The configuration details of the recommender.

pub fn set_recommender_config(self, input: Option<RecommenderConfig>) -> Self

The configuration details of the recommender.

pub fn tags(self, input: Tag) -> Self

Appends an item to tags.

To override the contents of this collection use set_tags.

A list of tags to apply to the recommender.

pub fn set_tags(self, input: Option<Vec<Tag>>) -> Self

A list of tags to apply to the recommender.

Trait Implementations

impl Clone for CreateRecommender

fn clone(&self) -> CreateRecommender

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for CreateRecommender

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

Formats the value using the given formatter.