Struct aws_sdk_personalize::client::Client

pub struct Client<C = DynConnector, M = DefaultMiddleware, R = Standard> { /* private fields */ }

Client for Amazon Personalize

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

Examples

Constructing a client and invoking an operation

    // create a shared configuration. This can be used & shared between multiple service clients.
    let shared_config = aws_config::load_from_env().await;
    let client = aws_sdk_personalize::Client::new(&shared_config);
    // invoke an operation
    /* let rsp = client
        .<operation_name>().
        .<param>("some value")
        .send().await; */

Constructing a client with custom configuration

use aws_config::RetryConfig;
    let shared_config = aws_config::load_from_env().await;
    let config = aws_sdk_personalize::config::Builder::from(&shared_config)
        .retry_config(RetryConfig::disabled())
        .build();
    let client = aws_sdk_personalize::Client::from_conf(config);

Implementations

impl<C, M, R> Client<C, M, R>

pub fn with_config(client: Client<C, M, R>, conf: Config) -> Self

Creates a client with the given service configuration.

pub fn conf(&self) -> &Config

Returns the client’s configuration.

impl<C, M, R> Client<C, M, R> where
    C: SmithyConnector,
    M: SmithyMiddleware<C>,
    R: NewRequestPolicy, 

pub fn create_batch_inference_job(&self) -> CreateBatchInferenceJob<C, M, R>

Constructs a fluent builder for the CreateBatchInferenceJob operation.

• The fluent builder is configurable:
  • job_name(impl Into<String>) / set_job_name(Option<String>):

    The name of the batch inference job to create.

  • solution_version_arn(impl Into<String>) / set_solution_version_arn(Option<String>):

    The Amazon Resource Name (ARN) of the solution version that will be used to generate the batch inference recommendations.

  • filter_arn(impl Into<String>) / set_filter_arn(Option<String>):

    The ARN of the filter to apply to the batch inference job. For more information on using filters, see Filtering Batch Recommendations..

  • num_results(i32) / set_num_results(Option<i32>):

    The number of recommendations to retreive.

  • job_input(BatchInferenceJobInput) / set_job_input(Option<BatchInferenceJobInput>):

    The Amazon S3 path that leads to the input file to base your recommendations on. The input material must be in JSON format.

  • job_output(BatchInferenceJobOutput) / set_job_output(Option<BatchInferenceJobOutput>):

    The path to the Amazon S3 bucket where the job’s output will be stored.

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

    The ARN of the Amazon Identity and Access Management role that has permissions to read and write to your input and output Amazon S3 buckets respectively.

  • batch_inference_job_config(BatchInferenceJobConfig) / set_batch_inference_job_config(Option<BatchInferenceJobConfig>):

    The configuration details of a batch inference job.

• On success, responds with CreateBatchInferenceJobOutput with field(s):
  • batch_inference_job_arn(Option<String>):

    The ARN of the batch inference job.

• On failure, responds with SdkError<CreateBatchInferenceJobError>

pub fn create_batch_segment_job(&self) -> CreateBatchSegmentJob<C, M, R>

Constructs a fluent builder for the CreateBatchSegmentJob operation.

• The fluent builder is configurable:
  • job_name(impl Into<String>) / set_job_name(Option<String>):

    The name of the batch segment job to create.

  • solution_version_arn(impl Into<String>) / set_solution_version_arn(Option<String>):

    The Amazon Resource Name (ARN) of the solution version you want the batch segment job to use to generate batch segments.

  • filter_arn(impl Into<String>) / set_filter_arn(Option<String>):

    The ARN of the filter to apply to the batch segment job. For more information on using filters, see filter-batch.

  • num_results(i32) / set_num_results(Option<i32>):

    The number of predicted users generated by the batch segment job for each line of input data.

  • job_input(BatchSegmentJobInput) / set_job_input(Option<BatchSegmentJobInput>):

    The Amazon S3 path for the input data used to generate the batch segment job.

  • job_output(BatchSegmentJobOutput) / set_job_output(Option<BatchSegmentJobOutput>):

    The Amazon S3 path for the bucket where the job’s output will be stored.

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

    The ARN of the Amazon Identity and Access Management role that has permissions to read and write to your input and output Amazon S3 buckets respectively.

• On success, responds with CreateBatchSegmentJobOutput with field(s):
  • batch_segment_job_arn(Option<String>):

    The ARN of the batch segment job.

• On failure, responds with SdkError<CreateBatchSegmentJobError>

pub fn create_campaign(&self) -> CreateCampaign<C, M, R>

Constructs a fluent builder for the CreateCampaign operation.

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

    A name for the new campaign. The campaign name must be unique within your account.

  • solution_version_arn(impl Into<String>) / set_solution_version_arn(Option<String>):

    The Amazon Resource Name (ARN) of the solution version to deploy.

  • min_provisioned_tps(i32) / set_min_provisioned_tps(Option<i32>):

    Specifies the requested minimum provisioned transactions (recommendations) per second that Amazon Personalize will support.

  • campaign_config(CampaignConfig) / set_campaign_config(Option<CampaignConfig>):

    The configuration details of a campaign.

• On success, responds with CreateCampaignOutput with field(s):
  • campaign_arn(Option<String>):

    The Amazon Resource Name (ARN) of the campaign.

• On failure, responds with SdkError<CreateCampaignError>

pub fn create_dataset(&self) -> CreateDataset<C, M, R>

Constructs a fluent builder for the CreateDataset operation.

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

    The name for the dataset.

  • schema_arn(impl Into<String>) / set_schema_arn(Option<String>):

    The ARN of the schema to associate with the dataset. The schema defines the dataset fields.

  • dataset_group_arn(impl Into<String>) / set_dataset_group_arn(Option<String>):

    The Amazon Resource Name (ARN) of the dataset group to add the dataset to.

  • dataset_type(impl Into<String>) / set_dataset_type(Option<String>):

    The type of dataset.

    One of the following (case insensitive) values:

    • Interactions

    • Items

    • Users

• On success, responds with CreateDatasetOutput with field(s):
  • dataset_arn(Option<String>):

    The ARN of the dataset.

• On failure, responds with SdkError<CreateDatasetError>

pub fn create_dataset_export_job(&self) -> CreateDatasetExportJob<C, M, R>

Constructs a fluent builder for the CreateDatasetExportJob operation.

• The fluent builder is configurable:
  • job_name(impl Into<String>) / set_job_name(Option<String>):

    The name for the dataset export job.

  • dataset_arn(impl Into<String>) / set_dataset_arn(Option<String>):

    The Amazon Resource Name (ARN) of the dataset that contains the data to export.

  • ingestion_mode(IngestionMode) / set_ingestion_mode(Option<IngestionMode>):

    The data to export, based on how you imported the data. You can choose to export only BULK data that you imported using a dataset import job, only PUT data that you imported incrementally (using the console, PutEvents, PutUsers and PutItems operations), or ALL for both types. The default value is PUT.

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

    The Amazon Resource Name (ARN) of the IAM service role that has permissions to add data to your output Amazon S3 bucket.

  • job_output(DatasetExportJobOutput) / set_job_output(Option<DatasetExportJobOutput>):

    The path to the Amazon S3 bucket where the job’s output is stored.

• On success, responds with CreateDatasetExportJobOutput with field(s):
  • dataset_export_job_arn(Option<String>):

    The Amazon Resource Name (ARN) of the dataset export job.

• On failure, responds with SdkError<CreateDatasetExportJobError>

pub fn create_dataset_group(&self) -> CreateDatasetGroup<C, M, R>

Constructs a fluent builder for the CreateDatasetGroup operation.

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

    The name for the new dataset group.

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

    The ARN of the Identity and Access Management (IAM) role that has permissions to access the Key Management Service (KMS) key. Supplying an IAM role is only valid when also specifying a KMS key.

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

    The Amazon Resource Name (ARN) of a Key Management Service (KMS) key used to encrypt the datasets.

  • domain(Domain) / set_domain(Option<Domain>):

    The domain of the dataset group. Specify a domain to create a Domain dataset group. The domain you specify determines the default schemas for datasets and the use cases available for recommenders. If you don’t specify a domain, you create a Custom dataset group with solution versions that you deploy with a campaign.

• On success, responds with CreateDatasetGroupOutput with field(s):
  • dataset_group_arn(Option<String>):

    The Amazon Resource Name (ARN) of the new dataset group.

  • domain(Option<Domain>):

    The domain for the new Domain dataset group.

• On failure, responds with SdkError<CreateDatasetGroupError>

pub fn create_dataset_import_job(&self) -> CreateDatasetImportJob<C, M, R>

Constructs a fluent builder for the CreateDatasetImportJob operation.

• The fluent builder is configurable:
  • job_name(impl Into<String>) / set_job_name(Option<String>):

    The name for the dataset import job.

  • dataset_arn(impl Into<String>) / set_dataset_arn(Option<String>):

    The ARN of the dataset that receives the imported data.

  • data_source(DataSource) / set_data_source(Option<DataSource>):

    The Amazon S3 bucket that contains the training data to import.

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

    The ARN of the IAM role that has permissions to read from the Amazon S3 data source.

• On success, responds with CreateDatasetImportJobOutput with field(s):
  • dataset_import_job_arn(Option<String>):

    The ARN of the dataset import job.

• On failure, responds with SdkError<CreateDatasetImportJobError>

pub fn create_event_tracker(&self) -> CreateEventTracker<C, M, R>

Constructs a fluent builder for the CreateEventTracker operation.

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

    The name for the event tracker.

  • dataset_group_arn(impl Into<String>) / set_dataset_group_arn(Option<String>):

    The Amazon Resource Name (ARN) of the dataset group that receives the event data.

• On success, responds with CreateEventTrackerOutput with field(s):
  • event_tracker_arn(Option<String>):

    The ARN of the event tracker.

  • tracking_id(Option<String>):

    The ID of the event tracker. Include this ID in requests to the PutEvents API.

• On failure, responds with SdkError<CreateEventTrackerError>

pub fn create_filter(&self) -> CreateFilter<C, M, R>

Constructs a fluent builder for the CreateFilter operation.

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

    The name of the filter to create.

  • dataset_group_arn(impl Into<String>) / set_dataset_group_arn(Option<String>):

    The ARN of the dataset group that the filter will belong to.

  • filter_expression(impl Into<String>) / set_filter_expression(Option<String>):

    The filter expression defines which items are included or excluded from recommendations. Filter expression must follow specific format rules. For information about filter expression structure and syntax, see filter-expressions.

• On success, responds with CreateFilterOutput with field(s):
  • filter_arn(Option<String>):

    The ARN of the new filter.

• On failure, responds with SdkError<CreateFilterError>

pub fn create_recommender(&self) -> CreateRecommender<C, M, R>

Constructs a fluent builder for the CreateRecommender operation.

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

    The name of the recommender.

  • dataset_group_arn(impl Into<String>) / set_dataset_group_arn(Option<String>):

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

  • recipe_arn(impl Into<String>) / set_recipe_arn(Option<String>):

    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.

  • recommender_config(RecommenderConfig) / set_recommender_config(Option<RecommenderConfig>):

    The configuration details of the recommender.

• On success, responds with CreateRecommenderOutput with field(s):
  • recommender_arn(Option<String>):

    The Amazon Resource Name (ARN) of the recommender.

• On failure, responds with SdkError<CreateRecommenderError>

pub fn create_schema(&self) -> CreateSchema<C, M, R>

Constructs a fluent builder for the CreateSchema operation.

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

    The name for the schema.

  • schema(impl Into<String>) / set_schema(Option<String>):

    A schema in Avro JSON format.

  • domain(Domain) / set_domain(Option<Domain>):

    The domain for the schema. If you are creating a schema for a dataset in a Domain dataset group, specify the domain you chose when you created the Domain dataset group.

• On success, responds with CreateSchemaOutput with field(s):
  • schema_arn(Option<String>):

    The Amazon Resource Name (ARN) of the created schema.

• On failure, responds with SdkError<CreateSchemaError>

pub fn create_solution(&self) -> CreateSolution<C, M, R>

Constructs a fluent builder for the CreateSolution operation.

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

    The name for the solution.

  • perform_hpo(bool) / set_perform_hpo(Option<bool>):

    Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false.

    When performing AutoML, this parameter is always true and you should not set it to false.

  • perform_auto_ml(bool) / set_perform_auto_ml(bool):

    Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.

    When set to true, Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit recipeArn. Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.

  • recipe_arn(impl Into<String>) / set_recipe_arn(Option<String>):

    The ARN of the recipe to use for model training. Only specified when performAutoML is false.

  • dataset_group_arn(impl Into<String>) / set_dataset_group_arn(Option<String>):

    The Amazon Resource Name (ARN) of the dataset group that provides the training data.

  • event_type(impl Into<String>) / set_event_type(Option<String>):

    When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, ‘click’ or ‘like’) is used for training the model.

    If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.

  • solution_config(SolutionConfig) / set_solution_config(Option<SolutionConfig>):

    The configuration to use with the solution. When performAutoML is set to true, Amazon Personalize only evaluates the autoMLConfig section of the solution configuration.

    Amazon Personalize doesn’t support configuring the hpoObjective at this time.

• On success, responds with CreateSolutionOutput with field(s):
  • solution_arn(Option<String>):

    The ARN of the solution.

• On failure, responds with SdkError<CreateSolutionError>

pub fn create_solution_version(&self) -> CreateSolutionVersion<C, M, R>

Constructs a fluent builder for the CreateSolutionVersion operation.

• The fluent builder is configurable:
  • solution_arn(impl Into<String>) / set_solution_arn(Option<String>):

    The Amazon Resource Name (ARN) of the solution containing the training configuration information.

  • training_mode(TrainingMode) / set_training_mode(Option<TrainingMode>):

    The scope of training to be performed when creating the solution version. The FULL option trains the solution version based on the entirety of the input solution’s training data, while the UPDATE option processes only the data that has changed in comparison to the input solution. Choose UPDATE when you want to incrementally update your solution version instead of creating an entirely new one.

    The UPDATE option can only be used when you already have an active solution version created from the input solution using the FULL option and the input solution was trained with the User-Personalization recipe or the HRNN-Coldstart recipe.

• On success, responds with CreateSolutionVersionOutput with field(s):
  • solution_version_arn(Option<String>):

    The ARN of the new solution version.

• On failure, responds with SdkError<CreateSolutionVersionError>

pub fn delete_campaign(&self) -> DeleteCampaign<C, M, R>

Constructs a fluent builder for the DeleteCampaign operation.

• The fluent builder is configurable:
  • campaign_arn(impl Into<String>) / set_campaign_arn(Option<String>):

    The Amazon Resource Name (ARN) of the campaign to delete.

• On success, responds with DeleteCampaignOutput
• On failure, responds with SdkError<DeleteCampaignError>

pub fn delete_dataset(&self) -> DeleteDataset<C, M, R>

Constructs a fluent builder for the DeleteDataset operation.

• The fluent builder is configurable:
  • dataset_arn(impl Into<String>) / set_dataset_arn(Option<String>):

    The Amazon Resource Name (ARN) of the dataset to delete.

• On success, responds with DeleteDatasetOutput
• On failure, responds with SdkError<DeleteDatasetError>

pub fn delete_dataset_group(&self) -> DeleteDatasetGroup<C, M, R>

Constructs a fluent builder for the DeleteDatasetGroup operation.

• The fluent builder is configurable:
  • dataset_group_arn(impl Into<String>) / set_dataset_group_arn(Option<String>):

    The ARN of the dataset group to delete.

• On success, responds with DeleteDatasetGroupOutput
• On failure, responds with SdkError<DeleteDatasetGroupError>

pub fn delete_event_tracker(&self) -> DeleteEventTracker<C, M, R>

Constructs a fluent builder for the DeleteEventTracker operation.

• The fluent builder is configurable:
  • event_tracker_arn(impl Into<String>) / set_event_tracker_arn(Option<String>):

    The Amazon Resource Name (ARN) of the event tracker to delete.

• On success, responds with DeleteEventTrackerOutput
• On failure, responds with SdkError<DeleteEventTrackerError>

pub fn delete_filter(&self) -> DeleteFilter<C, M, R>

Constructs a fluent builder for the DeleteFilter operation.

• The fluent builder is configurable:
  • filter_arn(impl Into<String>) / set_filter_arn(Option<String>):

    The ARN of the filter to delete.

• On success, responds with DeleteFilterOutput
• On failure, responds with SdkError<DeleteFilterError>

pub fn delete_recommender(&self) -> DeleteRecommender<C, M, R>

Constructs a fluent builder for the DeleteRecommender operation.

• The fluent builder is configurable:
  • recommender_arn(impl Into<String>) / set_recommender_arn(Option<String>):

    The Amazon Resource Name (ARN) of the recommender to delete.

• On success, responds with DeleteRecommenderOutput
• On failure, responds with SdkError<DeleteRecommenderError>

pub fn delete_schema(&self) -> DeleteSchema<C, M, R>

Constructs a fluent builder for the DeleteSchema operation.

• The fluent builder is configurable:
  • schema_arn(impl Into<String>) / set_schema_arn(Option<String>):

    The Amazon Resource Name (ARN) of the schema to delete.

• On success, responds with DeleteSchemaOutput
• On failure, responds with SdkError<DeleteSchemaError>

pub fn delete_solution(&self) -> DeleteSolution<C, M, R>

Constructs a fluent builder for the DeleteSolution operation.

• The fluent builder is configurable:
  • solution_arn(impl Into<String>) / set_solution_arn(Option<String>):

    The ARN of the solution to delete.

• On success, responds with DeleteSolutionOutput
• On failure, responds with SdkError<DeleteSolutionError>

pub fn describe_algorithm(&self) -> DescribeAlgorithm<C, M, R>

Constructs a fluent builder for the DescribeAlgorithm operation.

• The fluent builder is configurable:
  • algorithm_arn(impl Into<String>) / set_algorithm_arn(Option<String>):

    The Amazon Resource Name (ARN) of the algorithm to describe.

• On success, responds with DescribeAlgorithmOutput with field(s):
  • algorithm(Option<Algorithm>):

    A listing of the properties of the algorithm.

• On failure, responds with SdkError<DescribeAlgorithmError>

pub fn describe_batch_inference_job(&self) -> DescribeBatchInferenceJob<C, M, R>

Constructs a fluent builder for the DescribeBatchInferenceJob operation.

• The fluent builder is configurable:
  • batch_inference_job_arn(impl Into<String>) / set_batch_inference_job_arn(Option<String>):

    The ARN of the batch inference job to describe.

• On success, responds with DescribeBatchInferenceJobOutput with field(s):
  • batch_inference_job(Option<BatchInferenceJob>):

    Information on the specified batch inference job.

• On failure, responds with SdkError<DescribeBatchInferenceJobError>

pub fn describe_batch_segment_job(&self) -> DescribeBatchSegmentJob<C, M, R>

Constructs a fluent builder for the DescribeBatchSegmentJob operation.

• The fluent builder is configurable:
  • batch_segment_job_arn(impl Into<String>) / set_batch_segment_job_arn(Option<String>):

    The ARN of the batch segment job to describe.

• On success, responds with DescribeBatchSegmentJobOutput with field(s):
  • batch_segment_job(Option<BatchSegmentJob>):

    Information on the specified batch segment job.

• On failure, responds with SdkError<DescribeBatchSegmentJobError>

pub fn describe_campaign(&self) -> DescribeCampaign<C, M, R>

Constructs a fluent builder for the DescribeCampaign operation.

• The fluent builder is configurable:
  • campaign_arn(impl Into<String>) / set_campaign_arn(Option<String>):

    The Amazon Resource Name (ARN) of the campaign.

• On success, responds with DescribeCampaignOutput with field(s):
  • campaign(Option<Campaign>):

    The properties of the campaign.

• On failure, responds with SdkError<DescribeCampaignError>

pub fn describe_dataset(&self) -> DescribeDataset<C, M, R>

Constructs a fluent builder for the DescribeDataset operation.

• The fluent builder is configurable:
  • dataset_arn(impl Into<String>) / set_dataset_arn(Option<String>):

    The Amazon Resource Name (ARN) of the dataset to describe.

• On success, responds with DescribeDatasetOutput with field(s):
  • dataset(Option<Dataset>):

    A listing of the dataset’s properties.

• On failure, responds with SdkError<DescribeDatasetError>

pub fn describe_dataset_export_job(&self) -> DescribeDatasetExportJob<C, M, R>

Constructs a fluent builder for the DescribeDatasetExportJob operation.

• The fluent builder is configurable:
  • dataset_export_job_arn(impl Into<String>) / set_dataset_export_job_arn(Option<String>):

    The Amazon Resource Name (ARN) of the dataset export job to describe.

• On success, responds with DescribeDatasetExportJobOutput with field(s):
  • dataset_export_job(Option<DatasetExportJob>):

    Information about the dataset export job, including the status.

    The status is one of the following values:

    • CREATE PENDING

    • CREATE IN_PROGRESS

    • ACTIVE

    • CREATE FAILED

• On failure, responds with SdkError<DescribeDatasetExportJobError>

pub fn describe_dataset_group(&self) -> DescribeDatasetGroup<C, M, R>

Constructs a fluent builder for the DescribeDatasetGroup operation.

• The fluent builder is configurable:
  • dataset_group_arn(impl Into<String>) / set_dataset_group_arn(Option<String>):

    The Amazon Resource Name (ARN) of the dataset group to describe.

• On success, responds with DescribeDatasetGroupOutput with field(s):
  • dataset_group(Option<DatasetGroup>):

    A listing of the dataset group’s properties.

• On failure, responds with SdkError<DescribeDatasetGroupError>

pub fn describe_dataset_import_job(&self) -> DescribeDatasetImportJob<C, M, R>

Constructs a fluent builder for the DescribeDatasetImportJob operation.

• The fluent builder is configurable:
  • dataset_import_job_arn(impl Into<String>) / set_dataset_import_job_arn(Option<String>):

    The Amazon Resource Name (ARN) of the dataset import job to describe.

• On success, responds with DescribeDatasetImportJobOutput with field(s):
  • dataset_import_job(Option<DatasetImportJob>):

    Information about the dataset import job, including the status.

    The status is one of the following values:

    • CREATE PENDING

    • CREATE IN_PROGRESS

    • ACTIVE

    • CREATE FAILED

• On failure, responds with SdkError<DescribeDatasetImportJobError>

pub fn describe_event_tracker(&self) -> DescribeEventTracker<C, M, R>

Constructs a fluent builder for the DescribeEventTracker operation.

• The fluent builder is configurable:
  • event_tracker_arn(impl Into<String>) / set_event_tracker_arn(Option<String>):

    The Amazon Resource Name (ARN) of the event tracker to describe.

• On success, responds with DescribeEventTrackerOutput with field(s):
  • event_tracker(Option<EventTracker>):

    An object that describes the event tracker.

• On failure, responds with SdkError<DescribeEventTrackerError>

pub fn describe_feature_transformation(
    &self
) -> DescribeFeatureTransformation<C, M, R>

Constructs a fluent builder for the DescribeFeatureTransformation operation.

• The fluent builder is configurable:
  • feature_transformation_arn(impl Into<String>) / set_feature_transformation_arn(Option<String>):

    The Amazon Resource Name (ARN) of the feature transformation to describe.

• On success, responds with DescribeFeatureTransformationOutput with field(s):
  • feature_transformation(Option<FeatureTransformation>):

    A listing of the FeatureTransformation properties.

• On failure, responds with SdkError<DescribeFeatureTransformationError>

pub fn describe_filter(&self) -> DescribeFilter<C, M, R>

Constructs a fluent builder for the DescribeFilter operation.

• The fluent builder is configurable:
  • filter_arn(impl Into<String>) / set_filter_arn(Option<String>):

    The ARN of the filter to describe.

• On success, responds with DescribeFilterOutput with field(s):
  • filter(Option<Filter>):

    The filter’s details.

• On failure, responds with SdkError<DescribeFilterError>

pub fn describe_recipe(&self) -> DescribeRecipe<C, M, R>

Constructs a fluent builder for the DescribeRecipe operation.

• The fluent builder is configurable:
  • recipe_arn(impl Into<String>) / set_recipe_arn(Option<String>):

    The Amazon Resource Name (ARN) of the recipe to describe.

• On success, responds with DescribeRecipeOutput with field(s):
  • recipe(Option<Recipe>):

    An object that describes the recipe.

• On failure, responds with SdkError<DescribeRecipeError>

pub fn describe_recommender(&self) -> DescribeRecommender<C, M, R>

Constructs a fluent builder for the DescribeRecommender operation.

• The fluent builder is configurable:
  • recommender_arn(impl Into<String>) / set_recommender_arn(Option<String>):

    The Amazon Resource Name (ARN) of the recommender to describe.

• On success, responds with DescribeRecommenderOutput with field(s):
  • recommender(Option<Recommender>):

    The properties of the recommender.

• On failure, responds with SdkError<DescribeRecommenderError>

pub fn describe_schema(&self) -> DescribeSchema<C, M, R>

Constructs a fluent builder for the DescribeSchema operation.

• The fluent builder is configurable:
  • schema_arn(impl Into<String>) / set_schema_arn(Option<String>):

    The Amazon Resource Name (ARN) of the schema to retrieve.

• On success, responds with DescribeSchemaOutput with field(s):
  • schema(Option<DatasetSchema>):

    The requested schema.

• On failure, responds with SdkError<DescribeSchemaError>

pub fn describe_solution(&self) -> DescribeSolution<C, M, R>

Constructs a fluent builder for the DescribeSolution operation.

• The fluent builder is configurable:
  • solution_arn(impl Into<String>) / set_solution_arn(Option<String>):

    The Amazon Resource Name (ARN) of the solution to describe.

• On success, responds with DescribeSolutionOutput with field(s):
  • solution(Option<Solution>):

    An object that describes the solution.

• On failure, responds with SdkError<DescribeSolutionError>

pub fn describe_solution_version(&self) -> DescribeSolutionVersion<C, M, R>

Constructs a fluent builder for the DescribeSolutionVersion operation.

• The fluent builder is configurable:
  • solution_version_arn(impl Into<String>) / set_solution_version_arn(Option<String>):

    The Amazon Resource Name (ARN) of the solution version.

• On success, responds with DescribeSolutionVersionOutput with field(s):
  • solution_version(Option<SolutionVersion>):

    The solution version.

• On failure, responds with SdkError<DescribeSolutionVersionError>

pub fn get_solution_metrics(&self) -> GetSolutionMetrics<C, M, R>

Constructs a fluent builder for the GetSolutionMetrics operation.

• The fluent builder is configurable:
  • solution_version_arn(impl Into<String>) / set_solution_version_arn(Option<String>):

    The Amazon Resource Name (ARN) of the solution version for which to get metrics.

• On success, responds with GetSolutionMetricsOutput with field(s):
  • solution_version_arn(Option<String>):

    The same solution version ARN as specified in the request.

  • metrics(Option<HashMap<String, f64>>):

    The metrics for the solution version.

• On failure, responds with SdkError<GetSolutionMetricsError>

pub fn list_batch_inference_jobs(&self) -> ListBatchInferenceJobs<C, M, R>

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

• The fluent builder is configurable:
  • solution_version_arn(impl Into<String>) / set_solution_version_arn(Option<String>):

    The Amazon Resource Name (ARN) of the solution version from which the batch inference jobs were created.

  • next_token(impl Into<String>) / set_next_token(Option<String>):

    The token to request the next page of results.

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

    The maximum number of batch inference job results to return in each page. The default value is 100.

• On success, responds with ListBatchInferenceJobsOutput with field(s):
  • batch_inference_jobs(Option<Vec<BatchInferenceJobSummary>>):

    A list containing information on each job that is returned.

  • next_token(Option<String>):

    The token to use to retrieve the next page of results. The value is null when there are no more results to return.

• On failure, responds with SdkError<ListBatchInferenceJobsError>

pub fn list_batch_segment_jobs(&self) -> ListBatchSegmentJobs<C, M, R>

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

• The fluent builder is configurable:
  • solution_version_arn(impl Into<String>) / set_solution_version_arn(Option<String>):

    The Amazon Resource Name (ARN) of the solution version that the batch segment jobs used to generate batch segments.

  • next_token(impl Into<String>) / set_next_token(Option<String>):

    The token to request the next page of results.

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

    The maximum number of batch segment job results to return in each page. The default value is 100.

• On success, responds with ListBatchSegmentJobsOutput with field(s):
  • batch_segment_jobs(Option<Vec<BatchSegmentJobSummary>>):

    A list containing information on each job that is returned.

  • next_token(Option<String>):

    The token to use to retrieve the next page of results. The value is null when there are no more results to return.

• On failure, responds with SdkError<ListBatchSegmentJobsError>

pub fn list_campaigns(&self) -> ListCampaigns<C, M, R>

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

• The fluent builder is configurable:
  • solution_arn(impl Into<String>) / set_solution_arn(Option<String>):

    The Amazon Resource Name (ARN) of the solution to list the campaigns for. When a solution is not specified, all the campaigns associated with the account are listed.

  • next_token(impl Into<String>) / set_next_token(Option<String>):

    A token returned from the previous call to ListCampaigns for getting the next set of campaigns (if they exist).

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

    The maximum number of campaigns to return.

• On success, responds with ListCampaignsOutput with field(s):
  • campaigns(Option<Vec<CampaignSummary>>):

    A list of the campaigns.

  • next_token(Option<String>):

    A token for getting the next set of campaigns (if they exist).

• On failure, responds with SdkError<ListCampaignsError>

pub fn list_dataset_export_jobs(&self) -> ListDatasetExportJobs<C, M, R>

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

• The fluent builder is configurable:
  • dataset_arn(impl Into<String>) / set_dataset_arn(Option<String>):

    The Amazon Resource Name (ARN) of the dataset to list the dataset export jobs for.

  • next_token(impl Into<String>) / set_next_token(Option<String>):

    A token returned from the previous call to ListDatasetExportJobs for getting the next set of dataset export jobs (if they exist).

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

    The maximum number of dataset export jobs to return.

• On success, responds with ListDatasetExportJobsOutput with field(s):
  • dataset_export_jobs(Option<Vec<DatasetExportJobSummary>>):

    The list of dataset export jobs.

  • next_token(Option<String>):

    A token for getting the next set of dataset export jobs (if they exist).

• On failure, responds with SdkError<ListDatasetExportJobsError>

pub fn list_dataset_groups(&self) -> ListDatasetGroups<C, M, R>

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

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

    A token returned from the previous call to ListDatasetGroups for getting the next set of dataset groups (if they exist).

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

    The maximum number of dataset groups to return.

• On success, responds with ListDatasetGroupsOutput with field(s):
  • dataset_groups(Option<Vec<DatasetGroupSummary>>):

    The list of your dataset groups.

  • next_token(Option<String>):

    A token for getting the next set of dataset groups (if they exist).

• On failure, responds with SdkError<ListDatasetGroupsError>

pub fn list_dataset_import_jobs(&self) -> ListDatasetImportJobs<C, M, R>

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

• The fluent builder is configurable:
  • dataset_arn(impl Into<String>) / set_dataset_arn(Option<String>):

    The Amazon Resource Name (ARN) of the dataset to list the dataset import jobs for.

  • next_token(impl Into<String>) / set_next_token(Option<String>):

    A token returned from the previous call to ListDatasetImportJobs for getting the next set of dataset import jobs (if they exist).

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

    The maximum number of dataset import jobs to return.

• On success, responds with ListDatasetImportJobsOutput with field(s):
  • dataset_import_jobs(Option<Vec<DatasetImportJobSummary>>):

    The list of dataset import jobs.

  • next_token(Option<String>):

    A token for getting the next set of dataset import jobs (if they exist).

• On failure, responds with SdkError<ListDatasetImportJobsError>

pub fn list_datasets(&self) -> ListDatasets<C, M, R>

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

• The fluent builder is configurable:
  • dataset_group_arn(impl Into<String>) / set_dataset_group_arn(Option<String>):

    The Amazon Resource Name (ARN) of the dataset group that contains the datasets to list.

  • next_token(impl Into<String>) / set_next_token(Option<String>):

    A token returned from the previous call to ListDatasetImportJobs for getting the next set of dataset import jobs (if they exist).

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

    The maximum number of datasets to return.

• On success, responds with ListDatasetsOutput with field(s):
  • datasets(Option<Vec<DatasetSummary>>):

    An array of Dataset objects. Each object provides metadata information.

  • next_token(Option<String>):

    A token for getting the next set of datasets (if they exist).

• On failure, responds with SdkError<ListDatasetsError>

pub fn list_event_trackers(&self) -> ListEventTrackers<C, M, R>

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

• The fluent builder is configurable:
  • dataset_group_arn(impl Into<String>) / set_dataset_group_arn(Option<String>):

    The ARN of a dataset group used to filter the response.

  • next_token(impl Into<String>) / set_next_token(Option<String>):

    A token returned from the previous call to ListEventTrackers for getting the next set of event trackers (if they exist).

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

    The maximum number of event trackers to return.

• On success, responds with ListEventTrackersOutput with field(s):
  • event_trackers(Option<Vec<EventTrackerSummary>>):

    A list of event trackers.

  • next_token(Option<String>):

    A token for getting the next set of event trackers (if they exist).

• On failure, responds with SdkError<ListEventTrackersError>

pub fn list_filters(&self) -> ListFilters<C, M, R>

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

• The fluent builder is configurable:
  • dataset_group_arn(impl Into<String>) / set_dataset_group_arn(Option<String>):

    The ARN of the dataset group that contains the filters.

  • next_token(impl Into<String>) / set_next_token(Option<String>):

    A token returned from the previous call to ListFilters for getting the next set of filters (if they exist).

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

    The maximum number of filters to return.

• On success, responds with ListFiltersOutput with field(s):
  • filters(Option<Vec<FilterSummary>>):

    A list of returned filters.

  • next_token(Option<String>):

    A token for getting the next set of filters (if they exist).

• On failure, responds with SdkError<ListFiltersError>

pub fn list_recipes(&self) -> ListRecipes<C, M, R>

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

• The fluent builder is configurable:
  • recipe_provider(RecipeProvider) / set_recipe_provider(Option<RecipeProvider>):

    The default is SERVICE.

  • next_token(impl Into<String>) / set_next_token(Option<String>):

    A token returned from the previous call to ListRecipes for getting the next set of recipes (if they exist).

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

    The maximum number of recipes to return.

  • domain(Domain) / set_domain(Option<Domain>):

    Filters returned recipes by domain for a Domain dataset group. Only recipes (Domain dataset group use cases) for this domain are included in the response. If you don’t specify a domain, only non-domain recipes are returned.

• On success, responds with ListRecipesOutput with field(s):
  • recipes(Option<Vec<RecipeSummary>>):

    The list of available recipes.

  • next_token(Option<String>):

    A token for getting the next set of recipes.

• On failure, responds with SdkError<ListRecipesError>

pub fn list_recommenders(&self) -> ListRecommenders<C, M, R>

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

• The fluent builder is configurable:
  • dataset_group_arn(impl Into<String>) / set_dataset_group_arn(Option<String>):

    The Amazon Resource Name (ARN) of the Domain dataset group to list the recommenders for. When a Domain dataset group is not specified, all the recommenders associated with the account are listed.

  • next_token(impl Into<String>) / set_next_token(Option<String>):

    A token returned from the previous call to ListRecommenders for getting the next set of recommenders (if they exist).

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

    The maximum number of recommenders to return.

• On success, responds with ListRecommendersOutput with field(s):
  • recommenders(Option<Vec<RecommenderSummary>>):

    A list of the recommenders.

  • next_token(Option<String>):

    A token for getting the next set of recommenders (if they exist).

• On failure, responds with SdkError<ListRecommendersError>

pub fn list_schemas(&self) -> ListSchemas<C, M, R>

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

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

    A token returned from the previous call to ListSchemas for getting the next set of schemas (if they exist).

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

    The maximum number of schemas to return.

• On success, responds with ListSchemasOutput with field(s):
  • schemas(Option<Vec<DatasetSchemaSummary>>):

    A list of schemas.

  • next_token(Option<String>):

    A token used to get the next set of schemas (if they exist).

• On failure, responds with SdkError<ListSchemasError>

pub fn list_solutions(&self) -> ListSolutions<C, M, R>

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

• The fluent builder is configurable:
  • dataset_group_arn(impl Into<String>) / set_dataset_group_arn(Option<String>):

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

  • next_token(impl Into<String>) / set_next_token(Option<String>):

    A token returned from the previous call to ListSolutions for getting the next set of solutions (if they exist).

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

    The maximum number of solutions to return.

• On success, responds with ListSolutionsOutput with field(s):
  • solutions(Option<Vec<SolutionSummary>>):

    A list of the current solutions.

  • next_token(Option<String>):

    A token for getting the next set of solutions (if they exist).

• On failure, responds with SdkError<ListSolutionsError>

pub fn list_solution_versions(&self) -> ListSolutionVersions<C, M, R>

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

• The fluent builder is configurable:
  • solution_arn(impl Into<String>) / set_solution_arn(Option<String>):

    The Amazon Resource Name (ARN) of the solution.

  • next_token(impl Into<String>) / set_next_token(Option<String>):

    A token returned from the previous call to ListSolutionVersions for getting the next set of solution versions (if they exist).

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

    The maximum number of solution versions to return.

• On success, responds with ListSolutionVersionsOutput with field(s):
  • solution_versions(Option<Vec<SolutionVersionSummary>>):

    A list of solution versions describing the version properties.

  • next_token(Option<String>):

    A token for getting the next set of solution versions (if they exist).

• On failure, responds with SdkError<ListSolutionVersionsError>

pub fn stop_solution_version_creation(
    &self
) -> StopSolutionVersionCreation<C, M, R>

Constructs a fluent builder for the StopSolutionVersionCreation operation.

• The fluent builder is configurable:
  • solution_version_arn(impl Into<String>) / set_solution_version_arn(Option<String>):

    The Amazon Resource Name (ARN) of the solution version you want to stop creating.

• On success, responds with StopSolutionVersionCreationOutput
• On failure, responds with SdkError<StopSolutionVersionCreationError>

pub fn update_campaign(&self) -> UpdateCampaign<C, M, R>

Constructs a fluent builder for the UpdateCampaign operation.

• The fluent builder is configurable:
  • campaign_arn(impl Into<String>) / set_campaign_arn(Option<String>):

    The Amazon Resource Name (ARN) of the campaign.

  • solution_version_arn(impl Into<String>) / set_solution_version_arn(Option<String>):

    The ARN of a new solution version to deploy.

  • min_provisioned_tps(i32) / set_min_provisioned_tps(Option<i32>):

    Specifies the requested minimum provisioned transactions (recommendations) per second that Amazon Personalize will support.

  • campaign_config(CampaignConfig) / set_campaign_config(Option<CampaignConfig>):

    The configuration details of a campaign.

• On success, responds with UpdateCampaignOutput with field(s):
  • campaign_arn(Option<String>):

    The same campaign ARN as given in the request.

• On failure, responds with SdkError<UpdateCampaignError>

pub fn update_recommender(&self) -> UpdateRecommender<C, M, R>

Constructs a fluent builder for the UpdateRecommender operation.

• The fluent builder is configurable:
  • recommender_arn(impl Into<String>) / set_recommender_arn(Option<String>):

    The Amazon Resource Name (ARN) of the recommender to modify.

  • recommender_config(RecommenderConfig) / set_recommender_config(Option<RecommenderConfig>):

    The configuration details of the recommender.

• On success, responds with UpdateRecommenderOutput with field(s):
  • recommender_arn(Option<String>):

    The same recommender Amazon Resource Name (ARN) as given in the request.

• On failure, responds with SdkError<UpdateRecommenderError>

impl<C> Client<C, DefaultMiddleware, Standard>

pub fn from_conf_conn(conf: Config, conn: C) -> Self

Creates a client with the given service config and connector override.

impl Client<DynConnector, DefaultMiddleware, Standard>

pub fn new(config: &Config) -> Self

Creates a new client from a shared config.

pub fn from_conf(conf: Config) -> Self

Creates a new client from the service Config.

Trait Implementations

impl<C, M, R> Clone for Client<C, M, R>

fn clone(&self) -> Self

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<C: Debug, M: Debug, R: Debug> Debug for Client<C, M, R>

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

Formats the value using the given formatter.

impl<C, M, R> From<Client<C, M, R>> for Client<C, M, R>

fn from(client: Client<C, M, R>) -> Self

Performs the conversion.