Struct aws_sdk_cleanroomsml::client::Client

pub struct Client { /* private fields */ }

Client for AWS Clean Rooms ML

Client for invoking operations on AWS Clean Rooms ML. Each operation on AWS Clean Rooms ML is a method on this this struct. .send() MUST be invoked on the generated operations to dispatch the request to the service.

Constructing a Client

A Config is required to construct a client. For most use cases, the aws-config crate should be used to automatically resolve this config using aws_config::load_from_env(), since this will resolve an SdkConfig which can be shared across multiple different AWS SDK clients. This config resolution process can be customized by calling aws_config::from_env() instead, which returns a ConfigLoader that uses the builder pattern to customize the default config.

In the simplest case, creating a client looks as follows:

let config = aws_config::load_from_env().await;
let client = aws_sdk_cleanroomsml::Client::new(&config);

Occasionally, SDKs may have additional service-specific values that can be set on the Config that is absent from SdkConfig, or slightly different settings for a specific client may be desired. The Config struct implements From<&SdkConfig>, so setting these specific settings can be done as follows:

let sdk_config = ::aws_config::load_from_env().await;
let config = aws_sdk_cleanroomsml::config::Builder::from(&sdk_config)
    .some_service_specific_setting("value")
    .build();

See the aws-config docs and Config for more information on customizing configuration.

Note: Client construction is expensive due to connection thread pool initialization, and should be done once at application start-up.

Using the Client

A client has a function for every operation that can be performed by the service. For example, the ListTagsForResource operation has a Client::list_tags_for_resource, function which returns a builder for that operation. The fluent builder ultimately has a send() function that returns an async future that returns a result, as illustrated below:

let result = client.list_tags_for_resource()
    .resource_arn("example")
    .send()
    .await;

The underlying HTTP requests that get made by this can be modified with the customize_operation function on the fluent builder. See the customize module for more information.

Implementations

impl Client

pub fn create_audience_model(&self) -> CreateAudienceModelFluentBuilder

Constructs a fluent builder for the CreateAudienceModel operation.

• The fluent builder is configurable:
  • training_data_start_time(DateTime) / set_training_data_start_time(Option<DateTime>):
    required: false
    

    The start date and time of the training window.

    
    
  • training_data_end_time(DateTime) / set_training_data_end_time(Option<DateTime>):
    required: false
    

    The end date and time of the training window.

    
    
  • name(impl Into<String>) / set_name(Option<String>):
    required: true
    

    The name of the audience model resource.

    
    
  • training_dataset_arn(impl Into<String>) / set_training_dataset_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the training dataset for this audience model.

    
    
  • kms_key_arn(impl Into<String>) / set_kms_key_arn(Option<String>):
    required: false
    

    The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the trained ML model and the associated data.

    
    
  • tags(impl Into<String>, impl Into<String>) / set_tags(Option<HashMap::<String, String>>):
    required: false
    

    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.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    The description of the audience model.

    
    
• On success, responds with CreateAudienceModelOutput with field(s):
  • audience_model_arn(String):

    The Amazon Resource Name (ARN) of the audience model.

• On failure, responds with SdkError<CreateAudienceModelError>

impl Client

pub fn create_configured_audience_model( &self ) -> CreateConfiguredAudienceModelFluentBuilder

Constructs a fluent builder for the CreateConfiguredAudienceModel operation.

• The fluent builder is configurable:
  • name(impl Into<String>) / set_name(Option<String>):
    required: true
    

    The name of the configured audience model.

    
    
  • audience_model_arn(impl Into<String>) / set_audience_model_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the audience model to use for the configured audience model.

    
    
  • output_config(ConfiguredAudienceModelOutputConfig) / set_output_config(Option<ConfiguredAudienceModelOutputConfig>):
    required: true
    

    Configure the Amazon S3 location and IAM Role for audiences created using this configured audience model. Each audience will have a unique location. The IAM Role must have s3:PutObject permission on the destination Amazon S3 location. If the destination is protected with Amazon S3 KMS-SSE, then the Role must also have the required KMS permissions.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    The description of the configured audience model.

    
    
  • shared_audience_metrics(SharedAudienceMetrics) / set_shared_audience_metrics(Option<Vec::<SharedAudienceMetrics>>):
    required: true
    

    Whether audience metrics are shared.

    
    
  • min_matching_seed_size(i32) / set_min_matching_seed_size(Option<i32>):
    required: false
    

    The minimum number of users from the seed audience that must match with users in the training data of the audience model. The default value is 500.

    
    
  • audience_size_config(AudienceSizeConfig) / set_audience_size_config(Option<AudienceSizeConfig>):
    required: false
    

    Configure the list of output sizes of audiences that can be created using this configured audience model. A request to StartAudienceGenerationJob that uses this configured audience model must have an audienceSize selected from this list. You can use the ABSOLUTE AudienceSize to configure out audience sizes using the count of identifiers in the output. You can use the Percentage AudienceSize to configure sizes in the range 1-100 percent.

    
    
  • tags(impl Into<String>, impl Into<String>) / set_tags(Option<HashMap::<String, String>>):
    required: false
    

    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.

    
    
  • child_resource_tag_on_create_policy(TagOnCreatePolicy) / set_child_resource_tag_on_create_policy(Option<TagOnCreatePolicy>):
    required: false
    

    Configure how the service tags audience generation jobs created using this configured audience model. If you specify NONE, the tags from the StartAudienceGenerationJob request determine the tags of the audience generation job. If you specify FROM_PARENT_RESOURCE, the audience generation job inherits the tags from the configured audience model, by default. Tags in the StartAudienceGenerationJob will override the default.

    When the client is in a different account than the configured audience model, the tags from the client are never applied to a resource in the caller’s account.

    
    
• On success, responds with CreateConfiguredAudienceModelOutput with field(s):
  • configured_audience_model_arn(String):

    The Amazon Resource Name (ARN) of the configured audience model.

• On failure, responds with SdkError<CreateConfiguredAudienceModelError>

impl Client

pub fn create_training_dataset(&self) -> CreateTrainingDatasetFluentBuilder

Constructs a fluent builder for the CreateTrainingDataset operation.

• The fluent builder is configurable:
  • name(impl Into<String>) / set_name(Option<String>):
    required: true
    

    The name of the training dataset. This name must be unique in your account and region.

    
    
  • role_arn(impl Into<String>) / set_role_arn(Option<String>):
    required: true
    

    The ARN of the IAM role that Clean Rooms ML can assume to read the data referred to in the dataSource field of each dataset.

    Passing a role across AWS accounts is not allowed. If you pass a role that isn’t in your account, you get an AccessDeniedException error.

    
    
  • training_data(Dataset) / set_training_data(Option<Vec::<Dataset>>):
    required: true
    

    An array of information that lists the Dataset objects, which specifies the dataset type and details on its location and schema. You must provide a role that has read access to these tables.

    
    
  • tags(impl Into<String>, impl Into<String>) / set_tags(Option<HashMap::<String, String>>):
    required: false
    

    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.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    The description of the training dataset.

    
    
• On success, responds with CreateTrainingDatasetOutput with field(s):
  • training_dataset_arn(String):

    The Amazon Resource Name (ARN) of the training dataset resource.

• On failure, responds with SdkError<CreateTrainingDatasetError>

impl Client

pub fn delete_audience_generation_job( &self ) -> DeleteAudienceGenerationJobFluentBuilder

Constructs a fluent builder for the DeleteAudienceGenerationJob operation.

• The fluent builder is configurable:
  • audience_generation_job_arn(impl Into<String>) / set_audience_generation_job_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the audience generation job that you want to delete.

    
    
• On success, responds with DeleteAudienceGenerationJobOutput
• On failure, responds with SdkError<DeleteAudienceGenerationJobError>

impl Client

pub fn delete_audience_model(&self) -> DeleteAudienceModelFluentBuilder

Constructs a fluent builder for the DeleteAudienceModel operation.

• The fluent builder is configurable:
  • audience_model_arn(impl Into<String>) / set_audience_model_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the audience model that you want to delete.

    
    
• On success, responds with DeleteAudienceModelOutput
• On failure, responds with SdkError<DeleteAudienceModelError>

impl Client

pub fn delete_configured_audience_model( &self ) -> DeleteConfiguredAudienceModelFluentBuilder

Constructs a fluent builder for the DeleteConfiguredAudienceModel operation.

• The fluent builder is configurable:
  • configured_audience_model_arn(impl Into<String>) / set_configured_audience_model_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the configured audience model that you want to delete.

    
    
• On success, responds with DeleteConfiguredAudienceModelOutput
• On failure, responds with SdkError<DeleteConfiguredAudienceModelError>

impl Client

pub fn delete_configured_audience_model_policy( &self ) -> DeleteConfiguredAudienceModelPolicyFluentBuilder

Constructs a fluent builder for the DeleteConfiguredAudienceModelPolicy operation.

• The fluent builder is configurable:
  • configured_audience_model_arn(impl Into<String>) / set_configured_audience_model_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the configured audience model policy that you want to delete.

    
    
• On success, responds with DeleteConfiguredAudienceModelPolicyOutput
• On failure, responds with SdkError<DeleteConfiguredAudienceModelPolicyError>

impl Client

pub fn delete_training_dataset(&self) -> DeleteTrainingDatasetFluentBuilder

Constructs a fluent builder for the DeleteTrainingDataset operation.

• The fluent builder is configurable:
  • training_dataset_arn(impl Into<String>) / set_training_dataset_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the training dataset that you want to delete.

    
    
• On success, responds with DeleteTrainingDatasetOutput
• On failure, responds with SdkError<DeleteTrainingDatasetError>

impl Client

pub fn get_audience_generation_job( &self ) -> GetAudienceGenerationJobFluentBuilder

Constructs a fluent builder for the GetAudienceGenerationJob operation.

• The fluent builder is configurable:
  • audience_generation_job_arn(impl Into<String>) / set_audience_generation_job_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the audience generation job that you are interested in.

    
    
• On success, responds with GetAudienceGenerationJobOutput with field(s):
  • create_time(DateTime):

    The time at which the audience generation job was created.

  • update_time(DateTime):

    The most recent time at which the audience generation job was updated.

  • audience_generation_job_arn(String):

    The Amazon Resource Name (ARN) of the audience generation job.

  • name(String):

    The name of the audience generation job.

  • description(Option<String>):

    The description of the audience generation job.

  • status(AudienceGenerationJobStatus):

    The status of the audience generation job.

  • status_details(Option<StatusDetails>):

    Details about the status of the audience generation job.

  • configured_audience_model_arn(String):

    The Amazon Resource Name (ARN) of the configured audience model used for this audience generation job.

  • seed_audience(Option<AudienceGenerationJobDataSource>):

    The seed audience that was used for this audience generation job. This field will be null if the account calling the API is the account that started this audience generation job.

  • include_seed_in_output(Option<bool>):

    Configure whether the seed users are included in the output audience. By default, Clean Rooms ML removes seed users from the output audience. If you specify TRUE, the seed users will appear first in the output. Clean Rooms ML does not explicitly reveal whether a user was in the seed, but the recipient of the audience will know that the first minimumSeedSize count of users are from the seed.

  • collaboration_id(Option<String>):

    The identifier of the collaboration that this audience generation job is associated with.

  • metrics(Option<AudienceQualityMetrics>):

    The relevance scores for different audience sizes and the recall score of the generated audience.

  • started_by(Option<String>):

    The AWS account that started this audience generation job.

  • tags(Option<HashMap::<String, String>>):

    The tags that are associated to this audience generation job.

• On failure, responds with SdkError<GetAudienceGenerationJobError>

impl Client

pub fn get_audience_model(&self) -> GetAudienceModelFluentBuilder

Constructs a fluent builder for the GetAudienceModel operation.

• The fluent builder is configurable:
  • audience_model_arn(impl Into<String>) / set_audience_model_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the audience model that you are interested in.

    
    
• On success, responds with GetAudienceModelOutput with field(s):
  • create_time(DateTime):

    The time at which the audience model was created.

  • update_time(DateTime):

    The most recent time at which the audience model was updated.

  • training_data_start_time(Option<DateTime>):

    The start date specified for the training window.

  • training_data_end_time(Option<DateTime>):

    The end date specified for the training window.

  • audience_model_arn(String):

    The Amazon Resource Name (ARN) of the audience model.

  • name(String):

    The name of the audience model.

  • training_dataset_arn(String):

    The Amazon Resource Name (ARN) of the training dataset that was used for this audience model.

  • status(AudienceModelStatus):

    The status of the audience model.

  • status_details(Option<StatusDetails>):

    Details about the status of the audience model.

  • kms_key_arn(Option<String>):

    The KMS key ARN used for the audience model.

  • tags(Option<HashMap::<String, String>>):

    The tags that are assigned to the audience model.

  • description(Option<String>):

    The description of the audience model.

• On failure, responds with SdkError<GetAudienceModelError>

impl Client

pub fn get_configured_audience_model( &self ) -> GetConfiguredAudienceModelFluentBuilder

Constructs a fluent builder for the GetConfiguredAudienceModel operation.

• The fluent builder is configurable:
  • configured_audience_model_arn(impl Into<String>) / set_configured_audience_model_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the configured audience model that you are interested in.

    
    
• On success, responds with GetConfiguredAudienceModelOutput with field(s):
  • create_time(DateTime):

    The time at which the configured audience model was created.

  • update_time(DateTime):

    The most recent time at which the configured audience model was updated.

  • configured_audience_model_arn(String):

    The Amazon Resource Name (ARN) of the configured audience model.

  • name(String):

    The name of the configured audience model.

  • audience_model_arn(String):

    The Amazon Resource Name (ARN) of the audience model used for this configured audience model.

  • output_config(Option<ConfiguredAudienceModelOutputConfig>):

    The output configuration of the configured audience model

  • description(Option<String>):

    The description of the configured audience model.

  • status(ConfiguredAudienceModelStatus):

    The status of the configured audience model.

  • shared_audience_metrics(Vec::<SharedAudienceMetrics>):

    Whether audience metrics are shared.

  • min_matching_seed_size(Option<i32>):

    The minimum number of users from the seed audience that must match with users in the training data of the audience model.

  • audience_size_config(Option<AudienceSizeConfig>):

    The list of output sizes of audiences that can be created using this configured audience model. A request to StartAudienceGenerationJob that uses this configured audience model must have an audienceSize selected from this list. You can use the ABSOLUTE AudienceSize to configure out audience sizes using the count of identifiers in the output. You can use the Percentage AudienceSize to configure sizes in the range 1-100 percent.

  • tags(Option<HashMap::<String, String>>):

    The tags that are associated to this configured audience model.

  • child_resource_tag_on_create_policy(Option<TagOnCreatePolicy>):

    Provides the childResourceTagOnCreatePolicy that was used for this configured audience model.

• On failure, responds with SdkError<GetConfiguredAudienceModelError>

impl Client

pub fn get_configured_audience_model_policy( &self ) -> GetConfiguredAudienceModelPolicyFluentBuilder

Constructs a fluent builder for the GetConfiguredAudienceModelPolicy operation.

• The fluent builder is configurable:
  • configured_audience_model_arn(impl Into<String>) / set_configured_audience_model_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the configured audience model that you are interested in.

    
    
• On success, responds with GetConfiguredAudienceModelPolicyOutput with field(s):
  • configured_audience_model_arn(String):

    The Amazon Resource Name (ARN) of the configured audience model.

  • configured_audience_model_policy(String):

    The configured audience model policy. This is a JSON IAM resource policy.

  • policy_hash(String):

    A cryptographic hash of the contents of the policy used to prevent unexpected concurrent modification of the policy.

• On failure, responds with SdkError<GetConfiguredAudienceModelPolicyError>

impl Client

pub fn get_training_dataset(&self) -> GetTrainingDatasetFluentBuilder

Constructs a fluent builder for the GetTrainingDataset operation.

• The fluent builder is configurable:
  • training_dataset_arn(impl Into<String>) / set_training_dataset_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the training dataset that you are interested in.

    
    
• On success, responds with GetTrainingDatasetOutput with field(s):
  • create_time(DateTime):

    The time at which the training dataset was created.

  • update_time(DateTime):

    The most recent time at which the training dataset was updated.

  • training_dataset_arn(String):

    The Amazon Resource Name (ARN) of the training dataset.

  • name(String):

    The name of the training dataset.

  • training_data(Vec::<Dataset>):

    Metadata about the requested training data.

  • status(TrainingDatasetStatus):

    The status of the training dataset.

  • role_arn(String):

    The IAM role used to read the training data.

  • tags(Option<HashMap::<String, String>>):

    The tags that are assigned to this training dataset.

  • description(Option<String>):

    The description of the training dataset.

• On failure, responds with SdkError<GetTrainingDatasetError>

impl Client

pub fn list_audience_export_jobs(&self) -> ListAudienceExportJobsFluentBuilder

Constructs a fluent builder for the ListAudienceExportJobs operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    The token value retrieved from a previous call to access the next page of results.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum size of the results that is returned per call.

    
    
  • audience_generation_job_arn(impl Into<String>) / set_audience_generation_job_arn(Option<String>):
    required: false
    

    The Amazon Resource Name (ARN) of the audience generation job that you are interested in.

    
    
• On success, responds with ListAudienceExportJobsOutput with field(s):
  • next_token(Option<String>):

    The token value retrieved from a previous call to access the next page of results.

  • audience_export_jobs(Vec::<AudienceExportJobSummary>):

    The audience export jobs that match the request.

• On failure, responds with SdkError<ListAudienceExportJobsError>

impl Client

pub fn list_audience_generation_jobs( &self ) -> ListAudienceGenerationJobsFluentBuilder

Constructs a fluent builder for the ListAudienceGenerationJobs operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    The token value retrieved from a previous call to access the next page of results.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum size of the results that is returned per call.

    
    
  • configured_audience_model_arn(impl Into<String>) / set_configured_audience_model_arn(Option<String>):
    required: false
    

    The Amazon Resource Name (ARN) of the configured audience model that was used for the audience generation jobs that you are interested in.

    
    
  • collaboration_id(impl Into<String>) / set_collaboration_id(Option<String>):
    required: false
    

    The identifier of the collaboration that contains the audience generation jobs that you are interested in.

    
    
• On success, responds with ListAudienceGenerationJobsOutput with field(s):
  • next_token(Option<String>):

    The token value retrieved from a previous call to access the next page of results.

  • audience_generation_jobs(Vec::<AudienceGenerationJobSummary>):

    The audience generation jobs that match the request.

• On failure, responds with SdkError<ListAudienceGenerationJobsError>

impl Client

pub fn list_audience_models(&self) -> ListAudienceModelsFluentBuilder

Constructs a fluent builder for the ListAudienceModels operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    The token value retrieved from a previous call to access the next page of results.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum size of the results that is returned per call.

    
    
• On success, responds with ListAudienceModelsOutput with field(s):
  • next_token(Option<String>):

    The token value retrieved from a previous call to access the next page of results.

  • audience_models(Vec::<AudienceModelSummary>):

    The audience models that match the request.

• On failure, responds with SdkError<ListAudienceModelsError>

impl Client

pub fn list_configured_audience_models( &self ) -> ListConfiguredAudienceModelsFluentBuilder

Constructs a fluent builder for the ListConfiguredAudienceModels operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    The token value retrieved from a previous call to access the next page of results.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum size of the results that is returned per call.

    
    
• On success, responds with ListConfiguredAudienceModelsOutput with field(s):
  • next_token(Option<String>):

    The token value retrieved from a previous call to access the next page of results.

  • configured_audience_models(Vec::<ConfiguredAudienceModelSummary>):

    The configured audience models.

• On failure, responds with SdkError<ListConfiguredAudienceModelsError>

impl Client

pub fn list_tags_for_resource(&self) -> ListTagsForResourceFluentBuilder

Constructs a fluent builder for the ListTagsForResource operation.

• The fluent builder is configurable:
  • resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the resource that you are interested in.

    
    
• On success, responds with ListTagsForResourceOutput with field(s):
  • tags(HashMap::<String, String>):

    The tags that are associated with the resource.

• On failure, responds with SdkError<ListTagsForResourceError>

impl Client

pub fn list_training_datasets(&self) -> ListTrainingDatasetsFluentBuilder

Constructs a fluent builder for the ListTrainingDatasets operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    The token value retrieved from a previous call to access the next page of results.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum size of the results that is returned per call.

    
    
• On success, responds with ListTrainingDatasetsOutput with field(s):
  • next_token(Option<String>):

    The token value retrieved from a previous call to access the next page of results.

  • training_datasets(Vec::<TrainingDatasetSummary>):

    The training datasets that match the request.

• On failure, responds with SdkError<ListTrainingDatasetsError>

impl Client

pub fn put_configured_audience_model_policy( &self ) -> PutConfiguredAudienceModelPolicyFluentBuilder

Constructs a fluent builder for the PutConfiguredAudienceModelPolicy operation.

• The fluent builder is configurable:
  • configured_audience_model_arn(impl Into<String>) / set_configured_audience_model_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the configured audience model that the resource policy will govern.

    
    
  • configured_audience_model_policy(impl Into<String>) / set_configured_audience_model_policy(Option<String>):
    required: true
    

    The IAM resource policy.

    
    
  • previous_policy_hash(impl Into<String>) / set_previous_policy_hash(Option<String>):
    required: false
    

    A cryptographic hash of the contents of the policy used to prevent unexpected concurrent modification of the policy.

    
    
  • policy_existence_condition(PolicyExistenceCondition) / set_policy_existence_condition(Option<PolicyExistenceCondition>):
    required: false
    

    Use this to prevent unexpected concurrent modification of the policy.

    
    
• On success, responds with PutConfiguredAudienceModelPolicyOutput with field(s):
  • configured_audience_model_policy(String):

    The IAM resource policy.

  • policy_hash(String):

    A cryptographic hash of the contents of the policy used to prevent unexpected concurrent modification of the policy.

• On failure, responds with SdkError<PutConfiguredAudienceModelPolicyError>

impl Client

pub fn start_audience_export_job(&self) -> StartAudienceExportJobFluentBuilder

Constructs a fluent builder for the StartAudienceExportJob operation.

• The fluent builder is configurable:
  • name(impl Into<String>) / set_name(Option<String>):
    required: true
    

    The name of the audience export job.

    
    
  • audience_generation_job_arn(impl Into<String>) / set_audience_generation_job_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the audience generation job that you want to export.

    
    
  • audience_size(AudienceSize) / set_audience_size(Option<AudienceSize>):
    required: true
    

    The size of the generated audience. Must match one of the sizes in the configured audience model.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    The description of the audience export job.

    
    
• On success, responds with StartAudienceExportJobOutput
• On failure, responds with SdkError<StartAudienceExportJobError>

impl Client

pub fn start_audience_generation_job( &self ) -> StartAudienceGenerationJobFluentBuilder

Constructs a fluent builder for the StartAudienceGenerationJob operation.

• The fluent builder is configurable:
  • name(impl Into<String>) / set_name(Option<String>):
    required: true
    

    The name of the audience generation job.

    
    
  • configured_audience_model_arn(impl Into<String>) / set_configured_audience_model_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the configured audience model that is used for this audience generation job.

    
    
  • seed_audience(AudienceGenerationJobDataSource) / set_seed_audience(Option<AudienceGenerationJobDataSource>):
    required: true
    

    The seed audience that is used to generate the audience.

    
    
  • include_seed_in_output(bool) / set_include_seed_in_output(Option<bool>):
    required: false
    

    Whether the seed audience is included in the audience generation output.

    
    
  • collaboration_id(impl Into<String>) / set_collaboration_id(Option<String>):
    required: false
    

    The identifier of the collaboration that contains the audience generation job.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    The description of the audience generation job.

    
    
  • tags(impl Into<String>, impl Into<String>) / set_tags(Option<HashMap::<String, String>>):
    required: false
    

    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.

    
    
• On success, responds with StartAudienceGenerationJobOutput with field(s):
  • audience_generation_job_arn(String):

    The Amazon Resource Name (ARN) of the audience generation job.

• On failure, responds with SdkError<StartAudienceGenerationJobError>

impl Client

pub fn tag_resource(&self) -> TagResourceFluentBuilder

Constructs a fluent builder for the TagResource operation.

• The fluent builder is configurable:
  • resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the resource that you want to assign tags.

    
    
  • tags(impl Into<String>, impl Into<String>) / set_tags(Option<HashMap::<String, String>>):
    required: true
    

    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 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.

    
    
• On success, responds with TagResourceOutput
• On failure, responds with SdkError<TagResourceError>

impl Client

pub fn untag_resource(&self) -> UntagResourceFluentBuilder

Constructs a fluent builder for the UntagResource operation.

• The fluent builder is configurable:
  • resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the resource that you want to remove tags from.

    
    
  • tag_keys(impl Into<String>) / set_tag_keys(Option<Vec::<String>>):
    required: true
    

    The key values of tags that you want to remove.

    
    
• On success, responds with UntagResourceOutput
• On failure, responds with SdkError<UntagResourceError>

impl Client

pub fn update_configured_audience_model( &self ) -> UpdateConfiguredAudienceModelFluentBuilder

Constructs a fluent builder for the UpdateConfiguredAudienceModel operation.

• The fluent builder is configurable:
  • configured_audience_model_arn(impl Into<String>) / set_configured_audience_model_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the configured audience model that you want to update.

    
    
  • output_config(ConfiguredAudienceModelOutputConfig) / set_output_config(Option<ConfiguredAudienceModelOutputConfig>):
    required: false
    

    The new output configuration.

    
    
  • audience_model_arn(impl Into<String>) / set_audience_model_arn(Option<String>):
    required: false
    

    The Amazon Resource Name (ARN) of the new audience model that you want to use.

    
    
  • shared_audience_metrics(SharedAudienceMetrics) / set_shared_audience_metrics(Option<Vec::<SharedAudienceMetrics>>):
    required: false
    

    The new value for whether to share audience metrics.

    
    
  • min_matching_seed_size(i32) / set_min_matching_seed_size(Option<i32>):
    required: false
    

    The minimum number of users from the seed audience that must match with users in the training data of the audience model.

    
    
  • audience_size_config(AudienceSizeConfig) / set_audience_size_config(Option<AudienceSizeConfig>):
    required: false
    

    The new audience size configuration.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    The new description of the configured audience model.

    
    
• On success, responds with UpdateConfiguredAudienceModelOutput with field(s):
  • configured_audience_model_arn(String):

    The Amazon Resource Name (ARN) of the configured audience model that was updated.

• On failure, responds with SdkError<UpdateConfiguredAudienceModelError>

impl Client

pub fn from_conf(conf: Config) -> Self

Creates a new client from the service Config.

Panics

This method will panic in the following cases:

• Retries or timeouts are enabled without a sleep_impl configured.
• Identity caching is enabled without a sleep_impl and time_source configured.
• No behavior_version is provided.

The panic message for each of these will have instructions on how to resolve them.

pub fn config(&self) -> &Config

Returns the client’s configuration.

impl Client

pub fn new(sdk_config: &SdkConfig) -> Self

Creates a new client from an SDK Config.

Panics

• This method will panic if the sdk_config is missing an async sleep implementation. If you experience this panic, set the sleep_impl on the Config passed into this function to fix it.
• This method will panic if the sdk_config is missing an HTTP connector. If you experience this panic, set the http_connector on the Config passed into this function to fix it.
• This method will panic if no BehaviorVersion is provided. If you experience this panic, set behavior_version on the Config or enable the behavior-version-latest Cargo feature.

Trait Implementations

impl Clone for Client

fn clone(&self) -> Client

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Client

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

Formats the value using the given formatter.