Personalize

public struct Personalize

Client object for interacting with AWS Personalize service.

Amazon Personalize is a machine learning service that makes it easy to add individualized recommendations to customers.

Member variables

Initialization

  • Initialize the Personalize client

    Declaration

    Swift

    public init(accessKeyId: String? = nil, secretAccessKey: String? = nil, sessionToken: String? = nil, region: AWSSDKSwiftCore.Region? = nil, endpoint: String? = nil, middlewares: [AWSServiceMiddleware] = [], eventLoopGroupProvider: AWSClient.EventLoopGroupProvider = .useAWSClientShared)

    Parameters

    accessKeyId

    Public access key provided by AWS
    secretAccessKey

    Private access key provided by AWS
    sessionToken

    Token provided by STS.AssumeRole() which allows access to another AWS account
    region

    Region of server you want to communicate with
    endpoint

    Custom endpoint URL to use instead of standard AWS servers
    middlewares

    Array of middlewares to apply to requests and responses
    eventLoopGroupProvider

    EventLoopGroup to use. Use useAWSClientShared if the client shall manage its own EventLoopGroup.

API Calls

  • Creates a batch inference job. The operation can handle up to 50 million records and the input file must be in JSON format. For more information, see recommendations-batch.

    Declaration

    Swift

    public func createBatchInferenceJob(_ input: CreateBatchInferenceJobRequest) -> EventLoopFuture<CreateBatchInferenceJobResponse>

  • Creates a campaign by deploying a solution version. When a client calls the GetRecommendations and GetPersonalizedRanking APIs, a campaign is specified in the request. Minimum Provisioned TPS and Auto-Scaling A transaction is a single GetRecommendations or GetPersonalizedRanking call. Transactions per second (TPS) is the throughput and unit of billing for Amazon Personalize. The minimum provisioned TPS (minProvisionedTPS) specifies the baseline throughput provisioned by Amazon Personalize, and thus, the minimum billing charge. If your TPS increases beyond minProvisionedTPS, Amazon Personalize auto-scales the provisioned capacity up and down, but never below minProvisionedTPS, to maintain a 70% utilization. There’s a short time delay while the capacity is increased that might cause loss of transactions. It’s recommended to start with a low minProvisionedTPS, track your usage using Amazon CloudWatch metrics, and then increase the minProvisionedTPS as necessary. Status A campaign can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS To get the campaign status, call DescribeCampaign. Wait until the status of the campaign is ACTIVE before asking the campaign for recommendations. Related APIs ListCampaigns DescribeCampaign UpdateCampaign DeleteCampaign

    Declaration

    Swift

    public func createCampaign(_ input: CreateCampaignRequest) -> EventLoopFuture<CreateCampaignResponse>

  • Creates an empty dataset and adds it to the specified dataset group. Use CreateDatasetImportJob to import your training data to a dataset. There are three types of datasets: Interactions Items Users Each dataset type has an associated schema with required field types. Only the Interactions dataset is required in order to train a model (also referred to as creating a solution). A dataset can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS To get the status of the dataset, call DescribeDataset. Related APIs CreateDatasetGroup ListDatasets DescribeDataset DeleteDataset

    Declaration

    Swift

    public func createDataset(_ input: CreateDatasetRequest) -> EventLoopFuture<CreateDatasetResponse>

  • Creates an empty dataset group. A dataset group contains related datasets that supply data for training a model. A dataset group can contain at most three datasets, one for each type of dataset: Interactions Items Users To train a model (create a solution), a dataset group that contains an Interactions dataset is required. Call CreateDataset to add a dataset to the group. A dataset group can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING To get the status of the dataset group, call DescribeDatasetGroup. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the creation failed. You must wait until the status of the dataset group is ACTIVE before adding a dataset to the group. You can specify an AWS Key Management Service (KMS) key to encrypt the datasets in the group. If you specify a KMS key, you must also include an AWS Identity and Access Management (IAM) role that has permission to access the key. APIs that require a dataset group ARN in the request CreateDataset CreateEventTracker CreateSolution Related APIs ListDatasetGroups DescribeDatasetGroup DeleteDatasetGroup

    Declaration

    Swift

    public func createDatasetGroup(_ input: CreateDatasetGroupRequest) -> EventLoopFuture<CreateDatasetGroupResponse>

  • Creates a job that imports training data from your data source (an Amazon S3 bucket) to an Amazon Personalize dataset. To allow Amazon Personalize to import the training data, you must specify an AWS Identity and Access Management (IAM) role that has permission to read from the data source, as Amazon Personalize makes a copy of your data and processes it in an internal AWS system. The dataset import job replaces any previous data in the dataset. Status A dataset import job can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED To get the status of the import job, call DescribeDatasetImportJob, providing the Amazon Resource Name (ARN) of the dataset import job. The dataset import is complete when the status shows as ACTIVE. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the job failed. Importing takes time. You must wait until the status shows as ACTIVE before training a model using the dataset. Related APIs ListDatasetImportJobs DescribeDatasetImportJob

    Declaration

    Swift

    public func createDatasetImportJob(_ input: CreateDatasetImportJobRequest) -> EventLoopFuture<CreateDatasetImportJobResponse>

  • Creates an event tracker that you use when sending event data to the specified dataset group using the PutEvents API. When Amazon Personalize creates an event tracker, it also creates an event-interactions dataset in the dataset group associated with the event tracker. The event-interactions dataset stores the event data from the PutEvents call. The contents of this dataset are not available to the user. Only one event tracker can be associated with a dataset group. You will get an error if you call CreateEventTracker using the same dataset group as an existing event tracker. When you send event data you include your tracking ID. The tracking ID identifies the customer and authorizes the customer to send the data. The event tracker can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS To get the status of the event tracker, call DescribeEventTracker. The event tracker must be in the ACTIVE state before using the tracking ID. Related APIs ListEventTrackers DescribeEventTracker DeleteEventTracker

    Declaration

    Swift

    public func createEventTracker(_ input: CreateEventTrackerRequest) -> EventLoopFuture<CreateEventTrackerResponse>

  • Creates a recommendation filter. For more information, see Using Filters with Amazon Personalize.

    Declaration

    Swift

    public func createFilter(_ input: CreateFilterRequest) -> EventLoopFuture<CreateFilterResponse>

  • Creates an Amazon Personalize schema from the specified schema string. The schema you create must be in Avro JSON format. Amazon Personalize recognizes three schema variants. Each schema is associated with a dataset type and has a set of required field and keywords. You specify a schema when you call CreateDataset. Related APIs ListSchemas DescribeSchema DeleteSchema

    Declaration

    Swift

    public func createSchema(_ input: CreateSchemaRequest) -> EventLoopFuture<CreateSchemaResponse>

  • Creates the configuration for training a model. A trained model is known as a solution. After the configuration is created, you train the model (create a solution) by calling the CreateSolutionVersion operation. Every time you call CreateSolutionVersion, a new version of the solution is created. After creating a solution version, you check its accuracy by calling GetSolutionMetrics. When you are satisfied with the version, you deploy it using CreateCampaign. The campaign provides recommendations to a client through the GetRecommendations API. To train a model, Amazon Personalize requires training data and a recipe. The training data comes from the dataset group that you provide in the request. A recipe specifies the training algorithm and a feature transformation. You can specify one of the predefined recipes provided by Amazon Personalize. Alternatively, you can specify performAutoML and Amazon Personalize will analyze your data and select the optimum USER_PERSONALIZATION recipe for you. Status A solution can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS To get the status of the solution, call DescribeSolution. Wait until the status shows as ACTIVE before calling CreateSolutionVersion. Related APIs ListSolutions CreateSolutionVersion DescribeSolution DeleteSolution ListSolutionVersions DescribeSolutionVersion

    Declaration

    Swift

    public func createSolution(_ input: CreateSolutionRequest) -> EventLoopFuture<CreateSolutionResponse>

  • Trains or retrains an active solution. A solution is created using the CreateSolution operation and must be in the ACTIVE state before calling CreateSolutionVersion. A new version of the solution is created every time you call this operation. Status A solution version can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED To get the status of the version, call DescribeSolutionVersion. Wait until the status shows as ACTIVE before calling CreateCampaign. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the job failed. Related APIs ListSolutionVersions DescribeSolutionVersion ListSolutions CreateSolution DescribeSolution DeleteSolution

    Declaration

    Swift

    public func createSolutionVersion(_ input: CreateSolutionVersionRequest) -> EventLoopFuture<CreateSolutionVersionResponse>

  • Removes a campaign by deleting the solution deployment. The solution that the campaign is based on is not deleted and can be redeployed when needed. A deleted campaign can no longer be specified in a GetRecommendations request. For more information on campaigns, see CreateCampaign.

    Declaration

    Swift

    @discardableResult
public func deleteCampaign(_ input: DeleteCampaignRequest) -> EventLoopFuture<Void>

  • Deletes a dataset. You can’t delete a dataset if an associated DatasetImportJob or SolutionVersion is in the CREATE PENDING or IN PROGRESS state. For more information on datasets, see CreateDataset.

    Declaration

    Swift

    @discardableResult
public func deleteDataset(_ input: DeleteDatasetRequest) -> EventLoopFuture<Void>

  • Deletes a dataset group. Before you delete a dataset group, you must delete the following: All associated event trackers. All associated solutions. All datasets in the dataset group.

    Declaration

    Swift

    @discardableResult
public func deleteDatasetGroup(_ input: DeleteDatasetGroupRequest) -> EventLoopFuture<Void>

  • Deletes the event tracker. Does not delete the event-interactions dataset from the associated dataset group. For more information on event trackers, see CreateEventTracker.

    Declaration

    Swift

    @discardableResult
public func deleteEventTracker(_ input: DeleteEventTrackerRequest) -> EventLoopFuture<Void>

  • Deletes a filter.

    Declaration

    Swift

    @discardableResult
public func deleteFilter(_ input: DeleteFilterRequest) -> EventLoopFuture<Void>

  • Deletes a schema. Before deleting a schema, you must delete all datasets referencing the schema. For more information on schemas, see CreateSchema.

    Declaration

    Swift

    @discardableResult
public func deleteSchema(_ input: DeleteSchemaRequest) -> EventLoopFuture<Void>

  • Deletes all versions of a solution and the Solution object itself. Before deleting a solution, you must delete all campaigns based on the solution. To determine what campaigns are using the solution, call ListCampaigns and supply the Amazon Resource Name (ARN) of the solution. You can’t delete a solution if an associated SolutionVersion is in the CREATE PENDING or IN PROGRESS state. For more information on solutions, see CreateSolution.

    Declaration

    Swift

    @discardableResult
public func deleteSolution(_ input: DeleteSolutionRequest) -> EventLoopFuture<Void>

  • Describes the given algorithm.

    Declaration

    Swift

    public func describeAlgorithm(_ input: DescribeAlgorithmRequest) -> EventLoopFuture<DescribeAlgorithmResponse>

  • Gets the properties of a batch inference job including name, Amazon Resource Name (ARN), status, input and output configurations, and the ARN of the solution version used to generate the recommendations.

    Declaration

    Swift

    public func describeBatchInferenceJob(_ input: DescribeBatchInferenceJobRequest) -> EventLoopFuture<DescribeBatchInferenceJobResponse>

  • Describes the given campaign, including its status. A campaign can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS When the status is CREATE FAILED, the response includes the failureReason key, which describes why. For more information on campaigns, see CreateCampaign.

    Declaration

    Swift

    public func describeCampaign(_ input: DescribeCampaignRequest) -> EventLoopFuture<DescribeCampaignResponse>

  • Describes the given dataset. For more information on datasets, see CreateDataset.

    Declaration

    Swift

    public func describeDataset(_ input: DescribeDatasetRequest) -> EventLoopFuture<DescribeDatasetResponse>

  • Describes the given dataset group. For more information on dataset groups, see CreateDatasetGroup.

    Declaration

    Swift

    public func describeDatasetGroup(_ input: DescribeDatasetGroupRequest) -> EventLoopFuture<DescribeDatasetGroupResponse>

  • Describes the dataset import job created by CreateDatasetImportJob, including the import job status.

    Declaration

    Swift

    public func describeDatasetImportJob(_ input: DescribeDatasetImportJobRequest) -> EventLoopFuture<DescribeDatasetImportJobResponse>

  • Describes an event tracker. The response includes the trackingId and status of the event tracker. For more information on event trackers, see CreateEventTracker.

    Declaration

    Swift

    public func describeEventTracker(_ input: DescribeEventTrackerRequest) -> EventLoopFuture<DescribeEventTrackerResponse>

  • Describes the given feature transformation.

    Declaration

    Swift

    public func describeFeatureTransformation(_ input: DescribeFeatureTransformationRequest) -> EventLoopFuture<DescribeFeatureTransformationResponse>

  • Describes a filter’s properties.

    Declaration

    Swift

    public func describeFilter(_ input: DescribeFilterRequest) -> EventLoopFuture<DescribeFilterResponse>

  • Describes a recipe. A recipe contains three items: An algorithm that trains a model. Hyperparameters that govern the training. Feature transformation information for modifying the input data before training. Amazon Personalize provides a set of predefined recipes. You specify a recipe when you create a solution with the CreateSolution API. CreateSolution trains a model by using the algorithm in the specified recipe and a training dataset. The solution, when deployed as a campaign, can provide recommendations using the GetRecommendations API.

    Declaration

    Swift

    public func describeRecipe(_ input: DescribeRecipeRequest) -> EventLoopFuture<DescribeRecipeResponse>

  • Describes a schema. For more information on schemas, see CreateSchema.

    Declaration

    Swift

    public func describeSchema(_ input: DescribeSchemaRequest) -> EventLoopFuture<DescribeSchemaResponse>

  • Describes a solution. For more information on solutions, see CreateSolution.

    Declaration

    Swift

    public func describeSolution(_ input: DescribeSolutionRequest) -> EventLoopFuture<DescribeSolutionResponse>

  • Describes a specific version of a solution. For more information on solutions, see CreateSolution.

    Declaration

    Swift

    public func describeSolutionVersion(_ input: DescribeSolutionVersionRequest) -> EventLoopFuture<DescribeSolutionVersionResponse>

  • Gets the metrics for the specified solution version.

    Declaration

    Swift

    public func getSolutionMetrics(_ input: GetSolutionMetricsRequest) -> EventLoopFuture<GetSolutionMetricsResponse>

  • Gets a list of the batch inference jobs that have been performed off of a solution version.

    Declaration

    Swift

    public func listBatchInferenceJobs(_ input: ListBatchInferenceJobsRequest) -> EventLoopFuture<ListBatchInferenceJobsResponse>

  • Returns a list of campaigns that use the given solution. When a solution is not specified, all the campaigns associated with the account are listed. The response provides the properties for each campaign, including the Amazon Resource Name (ARN). For more information on campaigns, see CreateCampaign.

    Declaration

    Swift

    public func listCampaigns(_ input: ListCampaignsRequest) -> EventLoopFuture<ListCampaignsResponse>

  • Returns a list of dataset groups. The response provides the properties for each dataset group, including the Amazon Resource Name (ARN). For more information on dataset groups, see CreateDatasetGroup.

    Declaration

    Swift

    public func listDatasetGroups(_ input: ListDatasetGroupsRequest) -> EventLoopFuture<ListDatasetGroupsResponse>

  • Returns a list of dataset import jobs that use the given dataset. When a dataset is not specified, all the dataset import jobs associated with the account are listed. The response provides the properties for each dataset import job, including the Amazon Resource Name (ARN). For more information on dataset import jobs, see CreateDatasetImportJob. For more information on datasets, see CreateDataset.

    Declaration

    Swift

    public func listDatasetImportJobs(_ input: ListDatasetImportJobsRequest) -> EventLoopFuture<ListDatasetImportJobsResponse>

  • Returns the list of datasets contained in the given dataset group. The response provides the properties for each dataset, including the Amazon Resource Name (ARN). For more information on datasets, see CreateDataset.

    Declaration

    Swift

    public func listDatasets(_ input: ListDatasetsRequest) -> EventLoopFuture<ListDatasetsResponse>

  • Returns the list of event trackers associated with the account. The response provides the properties for each event tracker, including the Amazon Resource Name (ARN) and tracking ID. For more information on event trackers, see CreateEventTracker.

    Declaration

    Swift

    public func listEventTrackers(_ input: ListEventTrackersRequest) -> EventLoopFuture<ListEventTrackersResponse>

  • Lists all filters that belong to a given dataset group.

    Declaration

    Swift

    public func listFilters(_ input: ListFiltersRequest) -> EventLoopFuture<ListFiltersResponse>

  • Returns a list of available recipes. The response provides the properties for each recipe, including the recipe’s Amazon Resource Name (ARN).

    Declaration

    Swift

    public func listRecipes(_ input: ListRecipesRequest) -> EventLoopFuture<ListRecipesResponse>

  • Returns the list of schemas associated with the account. The response provides the properties for each schema, including the Amazon Resource Name (ARN). For more information on schemas, see CreateSchema.

    Declaration

    Swift

    public func listSchemas(_ input: ListSchemasRequest) -> EventLoopFuture<ListSchemasResponse>

  • Returns a list of solution versions for the given solution. When a solution is not specified, all the solution versions associated with the account are listed. The response provides the properties for each solution version, including the Amazon Resource Name (ARN). For more information on solutions, see CreateSolution.

    Declaration

    Swift

    public func listSolutionVersions(_ input: ListSolutionVersionsRequest) -> EventLoopFuture<ListSolutionVersionsResponse>

  • Returns a list of solutions that use the given dataset group. When a dataset group is not specified, all the solutions associated with the account are listed. The response provides the properties for each solution, including the Amazon Resource Name (ARN). For more information on solutions, see CreateSolution.

    Declaration

    Swift

    public func listSolutions(_ input: ListSolutionsRequest) -> EventLoopFuture<ListSolutionsResponse>

  • Updates a campaign by either deploying a new solution or changing the value of the campaign’s minProvisionedTPS parameter. To update a campaign, the campaign status must be ACTIVE or CREATE FAILED. Check the campaign status using the DescribeCampaign API. You must wait until the status of the updated campaign is ACTIVE before asking the campaign for recommendations. For more information on campaigns, see CreateCampaign.

    Declaration

    Swift

    public func updateCampaign(_ input: UpdateCampaignRequest) -> EventLoopFuture<UpdateCampaignResponse>

Paginators

  • Gets a list of the batch inference jobs that have been performed off of a solution version.

    Declaration

    Swift

    public func listBatchInferenceJobsPaginator(_ input: ListBatchInferenceJobsRequest, onPage: @escaping (ListBatchInferenceJobsResponse, EventLoop) -> EventLoopFuture<Bool>) -> EventLoopFuture<Void>

  • Returns a list of campaigns that use the given solution. When a solution is not specified, all the campaigns associated with the account are listed. The response provides the properties for each campaign, including the Amazon Resource Name (ARN). For more information on campaigns, see CreateCampaign.

    Declaration

    Swift

    public func listCampaignsPaginator(_ input: ListCampaignsRequest, onPage: @escaping (ListCampaignsResponse, EventLoop) -> EventLoopFuture<Bool>) -> EventLoopFuture<Void>

  • Returns a list of dataset groups. The response provides the properties for each dataset group, including the Amazon Resource Name (ARN). For more information on dataset groups, see CreateDatasetGroup.

    Declaration

    Swift

    public func listDatasetGroupsPaginator(_ input: ListDatasetGroupsRequest, onPage: @escaping (ListDatasetGroupsResponse, EventLoop) -> EventLoopFuture<Bool>) -> EventLoopFuture<Void>

  • Returns a list of dataset import jobs that use the given dataset. When a dataset is not specified, all the dataset import jobs associated with the account are listed. The response provides the properties for each dataset import job, including the Amazon Resource Name (ARN). For more information on dataset import jobs, see CreateDatasetImportJob. For more information on datasets, see CreateDataset.

    Declaration

    Swift

    public func listDatasetImportJobsPaginator(_ input: ListDatasetImportJobsRequest, onPage: @escaping (ListDatasetImportJobsResponse, EventLoop) -> EventLoopFuture<Bool>) -> EventLoopFuture<Void>

  • Returns the list of datasets contained in the given dataset group. The response provides the properties for each dataset, including the Amazon Resource Name (ARN). For more information on datasets, see CreateDataset.

    Declaration

    Swift

    public func listDatasetsPaginator(_ input: ListDatasetsRequest, onPage: @escaping (ListDatasetsResponse, EventLoop) -> EventLoopFuture<Bool>) -> EventLoopFuture<Void>

  • Returns the list of event trackers associated with the account. The response provides the properties for each event tracker, including the Amazon Resource Name (ARN) and tracking ID. For more information on event trackers, see CreateEventTracker.

    Declaration

    Swift

    public func listEventTrackersPaginator(_ input: ListEventTrackersRequest, onPage: @escaping (ListEventTrackersResponse, EventLoop) -> EventLoopFuture<Bool>) -> EventLoopFuture<Void>

  • Returns a list of available recipes. The response provides the properties for each recipe, including the recipe’s Amazon Resource Name (ARN).

    Declaration

    Swift

    public func listRecipesPaginator(_ input: ListRecipesRequest, onPage: @escaping (ListRecipesResponse, EventLoop) -> EventLoopFuture<Bool>) -> EventLoopFuture<Void>

  • Returns the list of schemas associated with the account. The response provides the properties for each schema, including the Amazon Resource Name (ARN). For more information on schemas, see CreateSchema.

    Declaration

    Swift

    public func listSchemasPaginator(_ input: ListSchemasRequest, onPage: @escaping (ListSchemasResponse, EventLoop) -> EventLoopFuture<Bool>) -> EventLoopFuture<Void>

  • Returns a list of solution versions for the given solution. When a solution is not specified, all the solution versions associated with the account are listed. The response provides the properties for each solution version, including the Amazon Resource Name (ARN). For more information on solutions, see CreateSolution.

    Declaration

    Swift

    public func listSolutionVersionsPaginator(_ input: ListSolutionVersionsRequest, onPage: @escaping (ListSolutionVersionsResponse, EventLoop) -> EventLoopFuture<Bool>) -> EventLoopFuture<Void>

  • Returns a list of solutions that use the given dataset group. When a dataset group is not specified, all the solutions associated with the account are listed. The response provides the properties for each solution, including the Amazon Resource Name (ARN). For more information on solutions, see CreateSolution.

    Declaration

    Swift

    public func listSolutionsPaginator(_ input: ListSolutionsRequest, onPage: @escaping (ListSolutionsResponse, EventLoop) -> EventLoopFuture<Bool>) -> EventLoopFuture<Void>

Shapes

Enums

  • Undocumented

    See more

    Declaration

    Swift

    public enum RecipeProvider : String, CustomStringConvertible, Codable

  • Undocumented

    See more

    Declaration

    Swift

    public enum TrainingMode : String, CustomStringConvertible, Codable