personalize

package module
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 Go to latest Published: Oct 17, 2020 License: Apache-2.0 Imports: 26 Imported by: 7

Documentation

Overview

Package personalize provides the API client, operations, and parameter types for Amazon Personalize.

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

Index

Constants

View Source 
const ServiceAPIVersion = "2018-05-22"
View Source 
const ServiceID = "Personalize"

Variables

This section is empty.

Functions

func NewDefaultEndpointResolver 

func NewDefaultEndpointResolver() *internalendpoints.Resolver

NewDefaultEndpointResolver constructs a new service endpoint resolver

Types

type Client 

type Client struct {
	// contains filtered or unexported fields
}

Client provides the API client to make operations call for Amazon Personalize.

func New 

func New(options Options, optFns ...func(*Options)) *Client

New returns an initialized Client based on the functional options. Provide additional functional options to further configure the behavior of the client, such as changing the client's endpoint or adding custom middleware behavior.

func NewFromConfig 

func NewFromConfig(cfg aws.Config, optFns ...func(*Options)) *Client

NewFromConfig returns a new client from the provided config.

func (*Client) CreateBatchInferenceJob 

func (c *Client) CreateBatchInferenceJob(ctx context.Context, params *CreateBatchInferenceJobInput, optFns ...func(*Options)) (*CreateBatchInferenceJobOutput, error)

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.

func (*Client) CreateCampaign 

func (c *Client) CreateCampaign(ctx context.Context, params *CreateCampaignInput, optFns ...func(*Options)) (*CreateCampaignOutput, error)

Creates a campaign by deploying a solution version. When a client calls the GetRecommendations (https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html) and GetPersonalizedRanking (https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetPersonalizedRanking.html) 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

func (*Client) CreateDataset 

func (c *Client) CreateDataset(ctx context.Context, params *CreateDatasetInput, optFns ...func(*Options)) (*CreateDatasetOutput, error)

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

func (*Client) CreateDatasetGroup 

func (c *Client) CreateDatasetGroup(ctx context.Context, params *CreateDatasetGroupInput, optFns ...func(*Options)) (*CreateDatasetGroupOutput, error)

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

func (*Client) CreateDatasetImportJob 

func (c *Client) CreateDatasetImportJob(ctx context.Context, params *CreateDatasetImportJobInput, optFns ...func(*Options)) (*CreateDatasetImportJobOutput, error)

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. 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

func (*Client) CreateEventTracker 

func (c *Client) CreateEventTracker(ctx context.Context, params *CreateEventTrackerInput, optFns ...func(*Options)) (*CreateEventTrackerOutput, error)

Creates an event tracker that you use when sending event data to the specified dataset group using the PutEvents (https://docs.aws.amazon.com/personalize/latest/dg/API_UBS_PutEvents.html) 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

func (*Client) CreateFilter 

func (c *Client) CreateFilter(ctx context.Context, params *CreateFilterInput, optFns ...func(*Options)) (*CreateFilterOutput, error)

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

func (*Client) CreateSchema 

func (c *Client) CreateSchema(ctx context.Context, params *CreateSchemaInput, optFns ...func(*Options)) (*CreateSchemaOutput, error)

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

func (*Client) CreateSolution 

func (c *Client) CreateSolution(ctx context.Context, params *CreateSolutionInput, optFns ...func(*Options)) (*CreateSolutionOutput, error)

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 (https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html) 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

func (*Client) CreateSolutionVersion 

func (c *Client) CreateSolutionVersion(ctx context.Context, params *CreateSolutionVersionInput, optFns ...func(*Options)) (*CreateSolutionVersionOutput, error)

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

func (*Client) DeleteCampaign 

func (c *Client) DeleteCampaign(ctx context.Context, params *DeleteCampaignInput, optFns ...func(*Options)) (*DeleteCampaignOutput, error)

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 (https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html) request. For more information on campaigns, see CreateCampaign.

func (*Client) DeleteDataset 

func (c *Client) DeleteDataset(ctx context.Context, params *DeleteDatasetInput, optFns ...func(*Options)) (*DeleteDatasetOutput, error)

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.

func (*Client) DeleteDatasetGroup 

func (c *Client) DeleteDatasetGroup(ctx context.Context, params *DeleteDatasetGroupInput, optFns ...func(*Options)) (*DeleteDatasetGroupOutput, error)

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.

func (*Client) DeleteEventTracker 

func (c *Client) DeleteEventTracker(ctx context.Context, params *DeleteEventTrackerInput, optFns ...func(*Options)) (*DeleteEventTrackerOutput, error)

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

func (*Client) DeleteFilter 

func (c *Client) DeleteFilter(ctx context.Context, params *DeleteFilterInput, optFns ...func(*Options)) (*DeleteFilterOutput, error)

Deletes a filter.

func (*Client) DeleteSchema 

func (c *Client) DeleteSchema(ctx context.Context, params *DeleteSchemaInput, optFns ...func(*Options)) (*DeleteSchemaOutput, error)

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

func (*Client) DeleteSolution 

func (c *Client) DeleteSolution(ctx context.Context, params *DeleteSolutionInput, optFns ...func(*Options)) (*DeleteSolutionOutput, error)

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.

func (*Client) DescribeAlgorithm 

func (c *Client) DescribeAlgorithm(ctx context.Context, params *DescribeAlgorithmInput, optFns ...func(*Options)) (*DescribeAlgorithmOutput, error)

Describes the given algorithm.

func (*Client) DescribeBatchInferenceJob 

func (c *Client) DescribeBatchInferenceJob(ctx context.Context, params *DescribeBatchInferenceJobInput, optFns ...func(*Options)) (*DescribeBatchInferenceJobOutput, error)

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.

func (*Client) DescribeCampaign 

func (c *Client) DescribeCampaign(ctx context.Context, params *DescribeCampaignInput, optFns ...func(*Options)) (*DescribeCampaignOutput, error)

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.

func (*Client) DescribeDataset 

func (c *Client) DescribeDataset(ctx context.Context, params *DescribeDatasetInput, optFns ...func(*Options)) (*DescribeDatasetOutput, error)

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

func (*Client) DescribeDatasetGroup 

func (c *Client) DescribeDatasetGroup(ctx context.Context, params *DescribeDatasetGroupInput, optFns ...func(*Options)) (*DescribeDatasetGroupOutput, error)

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

func (*Client) DescribeDatasetImportJob 

func (c *Client) DescribeDatasetImportJob(ctx context.Context, params *DescribeDatasetImportJobInput, optFns ...func(*Options)) (*DescribeDatasetImportJobOutput, error)

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

func (*Client) DescribeEventTracker 

func (c *Client) DescribeEventTracker(ctx context.Context, params *DescribeEventTrackerInput, optFns ...func(*Options)) (*DescribeEventTrackerOutput, error)

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

func (*Client) DescribeFeatureTransformation 

func (c *Client) DescribeFeatureTransformation(ctx context.Context, params *DescribeFeatureTransformationInput, optFns ...func(*Options)) (*DescribeFeatureTransformationOutput, error)

Describes the given feature transformation.

func (*Client) DescribeFilter 

func (c *Client) DescribeFilter(ctx context.Context, params *DescribeFilterInput, optFns ...func(*Options)) (*DescribeFilterOutput, error)

Describes a filter's properties.

func (*Client) DescribeRecipe 

func (c *Client) DescribeRecipe(ctx context.Context, params *DescribeRecipeInput, optFns ...func(*Options)) (*DescribeRecipeOutput, error)

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 (https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html) API.

func (*Client) DescribeSchema 

func (c *Client) DescribeSchema(ctx context.Context, params *DescribeSchemaInput, optFns ...func(*Options)) (*DescribeSchemaOutput, error)

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

func (*Client) DescribeSolution 

func (c *Client) DescribeSolution(ctx context.Context, params *DescribeSolutionInput, optFns ...func(*Options)) (*DescribeSolutionOutput, error)

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

func (*Client) DescribeSolutionVersion 

func (c *Client) DescribeSolutionVersion(ctx context.Context, params *DescribeSolutionVersionInput, optFns ...func(*Options)) (*DescribeSolutionVersionOutput, error)

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

func (*Client) GetSolutionMetrics 

func (c *Client) GetSolutionMetrics(ctx context.Context, params *GetSolutionMetricsInput, optFns ...func(*Options)) (*GetSolutionMetricsOutput, error)

Gets the metrics for the specified solution version.

func (*Client) ListBatchInferenceJobs 

func (c *Client) ListBatchInferenceJobs(ctx context.Context, params *ListBatchInferenceJobsInput, optFns ...func(*Options)) (*ListBatchInferenceJobsOutput, error)

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

func (*Client) ListCampaigns 

func (c *Client) ListCampaigns(ctx context.Context, params *ListCampaignsInput, optFns ...func(*Options)) (*ListCampaignsOutput, error)

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.

func (*Client) ListDatasetGroups 

func (c *Client) ListDatasetGroups(ctx context.Context, params *ListDatasetGroupsInput, optFns ...func(*Options)) (*ListDatasetGroupsOutput, error)

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.

func (*Client) ListDatasetImportJobs 

func (c *Client) ListDatasetImportJobs(ctx context.Context, params *ListDatasetImportJobsInput, optFns ...func(*Options)) (*ListDatasetImportJobsOutput, error)

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.

func (*Client) ListDatasets 

func (c *Client) ListDatasets(ctx context.Context, params *ListDatasetsInput, optFns ...func(*Options)) (*ListDatasetsOutput, error)

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.

func (*Client) ListEventTrackers 

func (c *Client) ListEventTrackers(ctx context.Context, params *ListEventTrackersInput, optFns ...func(*Options)) (*ListEventTrackersOutput, error)

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.

func (*Client) ListFilters 

func (c *Client) ListFilters(ctx context.Context, params *ListFiltersInput, optFns ...func(*Options)) (*ListFiltersOutput, error)

Lists all filters that belong to a given dataset group.

func (*Client) ListRecipes 

func (c *Client) ListRecipes(ctx context.Context, params *ListRecipesInput, optFns ...func(*Options)) (*ListRecipesOutput, error)

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

func (*Client) ListSchemas 

func (c *Client) ListSchemas(ctx context.Context, params *ListSchemasInput, optFns ...func(*Options)) (*ListSchemasOutput, error)

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.

func (*Client) ListSolutionVersions 

func (c *Client) ListSolutionVersions(ctx context.Context, params *ListSolutionVersionsInput, optFns ...func(*Options)) (*ListSolutionVersionsOutput, error)

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.

func (*Client) ListSolutions 

func (c *Client) ListSolutions(ctx context.Context, params *ListSolutionsInput, optFns ...func(*Options)) (*ListSolutionsOutput, error)

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.

func (*Client) UpdateCampaign 

func (c *Client) UpdateCampaign(ctx context.Context, params *UpdateCampaignInput, optFns ...func(*Options)) (*UpdateCampaignOutput, error)

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.

type CreateBatchInferenceJobInput 

type CreateBatchInferenceJobInput struct {

	// The Amazon S3 path that leads to the input file to base your recommendations on.
	// The input material must be in JSON format.
	//
	// This member is required.
	JobInput *types.BatchInferenceJobInput

	// The name of the batch inference job to create.
	//
	// This member is required.
	JobName *string

	// The path to the Amazon S3 bucket where the job's output will be stored.
	//
	// This member is required.
	JobOutput *types.BatchInferenceJobOutput

	// The ARN of the Amazon Identity and Access Management role that has permissions
	// to read and write to your input and out Amazon S3 buckets respectively.
	//
	// This member is required.
	RoleArn *string

	// The Amazon Resource Name (ARN) of the solution version that will be used to
	// generate the batch inference recommendations.
	//
	// This member is required.
	SolutionVersionArn *string

	// The ARN of the filter to apply to the batch inference job. For more information
	// on using filters, see Using Filters with Amazon Personalize.
	FilterArn *string

	// The number of recommendations to retreive.
	NumResults *int32
}

type CreateBatchInferenceJobOutput 

type CreateBatchInferenceJobOutput struct {

	// The ARN of the batch inference job.
	BatchInferenceJobArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateCampaignInput 

type CreateCampaignInput struct {

	// Specifies the requested minimum provisioned transactions (recommendations) per
	// second that Amazon Personalize will support.
	//
	// This member is required.
	MinProvisionedTPS *int32

	// A name for the new campaign. The campaign name must be unique within your
	// account.
	//
	// This member is required.
	Name *string

	// The Amazon Resource Name (ARN) of the solution version to deploy.
	//
	// This member is required.
	SolutionVersionArn *string
}

type CreateCampaignOutput 

type CreateCampaignOutput struct {

	// The Amazon Resource Name (ARN) of the campaign.
	CampaignArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateDatasetGroupInput 

type CreateDatasetGroupInput struct {

	// The name for the new dataset group.
	//
	// This member is required.
	Name *string

	// The Amazon Resource Name (ARN) of a KMS key used to encrypt the datasets.
	KmsKeyArn *string

	// The ARN of the IAM role that has permissions to access the KMS key. Supplying an
	// IAM role is only valid when also specifying a KMS key.
	RoleArn *string
}

type CreateDatasetGroupOutput 

type CreateDatasetGroupOutput struct {

	// The Amazon Resource Name (ARN) of the new dataset group.
	DatasetGroupArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateDatasetImportJobInput 

type CreateDatasetImportJobInput struct {

	// The Amazon S3 bucket that contains the training data to import.
	//
	// This member is required.
	DataSource *types.DataSource

	// The ARN of the dataset that receives the imported data.
	//
	// This member is required.
	DatasetArn *string

	// The name for the dataset import job.
	//
	// This member is required.
	JobName *string

	// The ARN of the IAM role that has permissions to read from the Amazon S3 data
	// source.
	//
	// This member is required.
	RoleArn *string
}

type CreateDatasetImportJobOutput 

type CreateDatasetImportJobOutput struct {

	// The ARN of the dataset import job.
	DatasetImportJobArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateDatasetInput 

type CreateDatasetInput struct {

	// The Amazon Resource Name (ARN) of the dataset group to add the dataset to.
	//
	// This member is required.
	DatasetGroupArn *string

	// The type of dataset. One of the following (case insensitive) values:
	//
	//     *
	// Interactions
	//
	//     * Items
	//
	//     * Users
	//
	// This member is required.
	DatasetType *string

	// The name for the dataset.
	//
	// This member is required.
	Name *string

	// The ARN of the schema to associate with the dataset. The schema defines the
	// dataset fields.
	//
	// This member is required.
	SchemaArn *string
}

type CreateDatasetOutput 

type CreateDatasetOutput struct {

	// The ARN of the dataset.
	DatasetArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateEventTrackerInput 

type CreateEventTrackerInput struct {

	// The Amazon Resource Name (ARN) of the dataset group that receives the event
	// data.
	//
	// This member is required.
	DatasetGroupArn *string

	// The name for the event tracker.
	//
	// This member is required.
	Name *string
}

type CreateEventTrackerOutput 

type CreateEventTrackerOutput struct {

	// The ARN of the event tracker.
	EventTrackerArn *string

	// The ID of the event tracker. Include this ID in requests to the PutEvents
	// (https://docs.aws.amazon.com/personalize/latest/dg/API_UBS_PutEvents.html) API.
	TrackingId *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateFilterInput 

type CreateFilterInput struct {

	// The ARN of the dataset group that the filter will belong to.
	//
	// This member is required.
	DatasetGroupArn *string

	// The filter expression that designates the interaction types that the filter will
	// filter out. A filter expression must follow the following format: EXCLUDE itemId
	// WHERE INTERACTIONS.event_type in ("EVENT_TYPE") Where "EVENT_TYPE" is the type
	// of event to filter out. To filter out all items with any interactions history,
	// set "*" as the EVENT_TYPE. For more information, see Using Filters with Amazon
	// Personalize.
	//
	// This member is required.
	FilterExpression *string

	// The name of the filter to create.
	//
	// This member is required.
	Name *string
}

type CreateFilterOutput 

type CreateFilterOutput struct {

	// The ARN of the new filter.
	FilterArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateSchemaInput 

type CreateSchemaInput struct {

	// The name for the schema.
	//
	// This member is required.
	Name *string

	// A schema in Avro JSON format.
	//
	// This member is required.
	Schema *string
}

type CreateSchemaOutput 

type CreateSchemaOutput struct {

	// The Amazon Resource Name (ARN) of the created schema.
	SchemaArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateSolutionInput 

type CreateSolutionInput struct {

	// The Amazon Resource Name (ARN) of the dataset group that provides the training
	// data.
	//
	// This member is required.
	DatasetGroupArn *string

	// The name for the solution.
	//
	// This member is required.
	Name *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.
	EventType *string

	// 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.
	PerformAutoML *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.
	PerformHPO *bool

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

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

type CreateSolutionOutput 

type CreateSolutionOutput struct {

	// The ARN of the solution.
	SolutionArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateSolutionVersionInput 

type CreateSolutionVersionInput struct {

	// The Amazon Resource Name (ARN) of the solution containing the training
	// configuration information.
	//
	// This member is required.
	SolutionArn *string

	// 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 native-recipe-hrnn-coldstart recipe.
	TrainingMode types.TrainingMode
}

type CreateSolutionVersionOutput 

type CreateSolutionVersionOutput struct {

	// The ARN of the new solution version.
	SolutionVersionArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteCampaignInput 

type DeleteCampaignInput struct {

	// The Amazon Resource Name (ARN) of the campaign to delete.
	//
	// This member is required.
	CampaignArn *string
}

type DeleteCampaignOutput 

type DeleteCampaignOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteDatasetGroupInput 

type DeleteDatasetGroupInput struct {

	// The ARN of the dataset group to delete.
	//
	// This member is required.
	DatasetGroupArn *string
}

type DeleteDatasetGroupOutput 

type DeleteDatasetGroupOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteDatasetInput 

type DeleteDatasetInput struct {

	// The Amazon Resource Name (ARN) of the dataset to delete.
	//
	// This member is required.
	DatasetArn *string
}

type DeleteDatasetOutput 

type DeleteDatasetOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteEventTrackerInput 

type DeleteEventTrackerInput struct {

	// The Amazon Resource Name (ARN) of the event tracker to delete.
	//
	// This member is required.
	EventTrackerArn *string
}

type DeleteEventTrackerOutput 

type DeleteEventTrackerOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteFilterInput 

type DeleteFilterInput struct {

	// The ARN of the filter to delete.
	//
	// This member is required.
	FilterArn *string
}

type DeleteFilterOutput 

type DeleteFilterOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteSchemaInput 

type DeleteSchemaInput struct {

	// The Amazon Resource Name (ARN) of the schema to delete.
	//
	// This member is required.
	SchemaArn *string
}

type DeleteSchemaOutput 

type DeleteSchemaOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteSolutionInput 

type DeleteSolutionInput struct {

	// The ARN of the solution to delete.
	//
	// This member is required.
	SolutionArn *string
}

type DeleteSolutionOutput 

type DeleteSolutionOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeAlgorithmInput 

type DescribeAlgorithmInput struct {

	// The Amazon Resource Name (ARN) of the algorithm to describe.
	//
	// This member is required.
	AlgorithmArn *string
}

type DescribeAlgorithmOutput 

type DescribeAlgorithmOutput struct {

	// A listing of the properties of the algorithm.
	Algorithm *types.Algorithm

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeBatchInferenceJobInput 

type DescribeBatchInferenceJobInput struct {

	// The ARN of the batch inference job to describe.
	//
	// This member is required.
	BatchInferenceJobArn *string
}

type DescribeBatchInferenceJobOutput 

type DescribeBatchInferenceJobOutput struct {

	// Information on the specified batch inference job.
	BatchInferenceJob *types.BatchInferenceJob

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeCampaignInput 

type DescribeCampaignInput struct {

	// The Amazon Resource Name (ARN) of the campaign.
	//
	// This member is required.
	CampaignArn *string
}

type DescribeCampaignOutput 

type DescribeCampaignOutput struct {

	// The properties of the campaign.
	Campaign *types.Campaign

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeDatasetGroupInput 

type DescribeDatasetGroupInput struct {

	// The Amazon Resource Name (ARN) of the dataset group to describe.
	//
	// This member is required.
	DatasetGroupArn *string
}

type DescribeDatasetGroupOutput 

type DescribeDatasetGroupOutput struct {

	// A listing of the dataset group's properties.
	DatasetGroup *types.DatasetGroup

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeDatasetImportJobInput 

type DescribeDatasetImportJobInput struct {

	// The Amazon Resource Name (ARN) of the dataset import job to describe.
	//
	// This member is required.
	DatasetImportJobArn *string
}

type DescribeDatasetImportJobOutput 

type DescribeDatasetImportJobOutput struct {

	// 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
	DatasetImportJob *types.DatasetImportJob

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeDatasetInput 

type DescribeDatasetInput struct {

	// The Amazon Resource Name (ARN) of the dataset to describe.
	//
	// This member is required.
	DatasetArn *string
}

type DescribeDatasetOutput 

type DescribeDatasetOutput struct {

	// A listing of the dataset's properties.
	Dataset *types.Dataset

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeEventTrackerInput 

type DescribeEventTrackerInput struct {

	// The Amazon Resource Name (ARN) of the event tracker to describe.
	//
	// This member is required.
	EventTrackerArn *string
}

type DescribeEventTrackerOutput 

type DescribeEventTrackerOutput struct {

	// An object that describes the event tracker.
	EventTracker *types.EventTracker

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeFeatureTransformationInput 

type DescribeFeatureTransformationInput struct {

	// The Amazon Resource Name (ARN) of the feature transformation to describe.
	//
	// This member is required.
	FeatureTransformationArn *string
}

type DescribeFeatureTransformationOutput 

type DescribeFeatureTransformationOutput struct {

	// A listing of the FeatureTransformation properties.
	FeatureTransformation *types.FeatureTransformation

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeFilterInput 

type DescribeFilterInput struct {

	// The ARN of the filter to describe.
	//
	// This member is required.
	FilterArn *string
}

type DescribeFilterOutput 

type DescribeFilterOutput struct {

	// The filter's details.
	Filter *types.Filter

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeRecipeInput 

type DescribeRecipeInput struct {

	// The Amazon Resource Name (ARN) of the recipe to describe.
	//
	// This member is required.
	RecipeArn *string
}

type DescribeRecipeOutput 

type DescribeRecipeOutput struct {

	// An object that describes the recipe.
	Recipe *types.Recipe

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeSchemaInput 

type DescribeSchemaInput struct {

	// The Amazon Resource Name (ARN) of the schema to retrieve.
	//
	// This member is required.
	SchemaArn *string
}

type DescribeSchemaOutput 

type DescribeSchemaOutput struct {

	// The requested schema.
	Schema *types.DatasetSchema

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeSolutionInput 

type DescribeSolutionInput struct {

	// The Amazon Resource Name (ARN) of the solution to describe.
	//
	// This member is required.
	SolutionArn *string
}

type DescribeSolutionOutput 

type DescribeSolutionOutput struct {

	// An object that describes the solution.
	Solution *types.Solution

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeSolutionVersionInput 

type DescribeSolutionVersionInput struct {

	// The Amazon Resource Name (ARN) of the solution version.
	//
	// This member is required.
	SolutionVersionArn *string
}

type DescribeSolutionVersionOutput 

type DescribeSolutionVersionOutput struct {

	// The solution version.
	SolutionVersion *types.SolutionVersion

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type EndpointResolver 

type EndpointResolver interface {
	ResolveEndpoint(region string, options ResolverOptions) (aws.Endpoint, error)
}

EndpointResolver interface for resolving service endpoints.

func WithEndpointResolver 

func WithEndpointResolver(awsResolver aws.EndpointResolver, fallbackResolver EndpointResolver) EndpointResolver

WithEndpointResolver returns an EndpointResolver that first delegates endpoint resolution to the awsResolver. If awsResolver returns aws.EndpointNotFoundError error, the resolver will use the the provided fallbackResolver for resolution. awsResolver and fallbackResolver must not be nil

type EndpointResolverFunc 

type EndpointResolverFunc func(region string, options ResolverOptions) (aws.Endpoint, error)

EndpointResolverFunc is a helper utility that wraps a function so it satisfies the EndpointResolver interface. This is useful when you want to add additional endpoint resolving logic, or stub out specific endpoints with custom values.

func (EndpointResolverFunc) ResolveEndpoint 

func (fn EndpointResolverFunc) ResolveEndpoint(region string, options ResolverOptions) (endpoint aws.Endpoint, err error)

type GetSolutionMetricsInput 

type GetSolutionMetricsInput struct {

	// The Amazon Resource Name (ARN) of the solution version for which to get metrics.
	//
	// This member is required.
	SolutionVersionArn *string
}

type GetSolutionMetricsOutput 

type GetSolutionMetricsOutput struct {

	// The metrics for the solution version.
	Metrics map[string]*float64

	// The same solution version ARN as specified in the request.
	SolutionVersionArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type HTTPClient 

type HTTPClient interface {
	Do(*http.Request) (*http.Response, error)
}

type HTTPSignerV4 

type HTTPSignerV4 interface {
	SignHTTP(ctx context.Context, credentials aws.Credentials, r *http.Request, payloadHash string, service string, region string, signingTime time.Time) error
}

type ListBatchInferenceJobsInput 

type ListBatchInferenceJobsInput struct {

	// The maximum number of batch inference job results to return in each page. The
	// default value is 100.
	MaxResults *int32

	// The token to request the next page of results.
	NextToken *string

	// The Amazon Resource Name (ARN) of the solution version from which the batch
	// inference jobs were created.
	SolutionVersionArn *string
}

type ListBatchInferenceJobsOutput 

type ListBatchInferenceJobsOutput struct {

	// A list containing information on each job that is returned.
	BatchInferenceJobs []*types.BatchInferenceJobSummary

	// The token to use to retreive the next page of results. The value is null when
	// there are no more results to return.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListCampaignsInput 

type ListCampaignsInput struct {

	// The maximum number of campaigns to return.
	MaxResults *int32

	// A token returned from the previous call to ListCampaigns for getting the next
	// set of campaigns (if they exist).
	NextToken *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.
	SolutionArn *string
}

type ListCampaignsOutput 

type ListCampaignsOutput struct {

	// A list of the campaigns.
	Campaigns []*types.CampaignSummary

	// A token for getting the next set of campaigns (if they exist).
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListDatasetGroupsInput 

type ListDatasetGroupsInput struct {

	// The maximum number of dataset groups to return.
	MaxResults *int32

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

type ListDatasetGroupsOutput 

type ListDatasetGroupsOutput struct {

	// The list of your dataset groups.
	DatasetGroups []*types.DatasetGroupSummary

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

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListDatasetImportJobsInput 

type ListDatasetImportJobsInput struct {

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

	// The maximum number of dataset import jobs to return.
	MaxResults *int32

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

type ListDatasetImportJobsOutput 

type ListDatasetImportJobsOutput struct {

	// The list of dataset import jobs.
	DatasetImportJobs []*types.DatasetImportJobSummary

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

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListDatasetsInput 

type ListDatasetsInput struct {

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

	// The maximum number of datasets to return.
	MaxResults *int32

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

type ListDatasetsOutput 

type ListDatasetsOutput struct {

	// An array of Dataset objects. Each object provides metadata information.
	Datasets []*types.DatasetSummary

	// A token for getting the next set of datasets (if they exist).
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListEventTrackersInput 

type ListEventTrackersInput struct {

	// The ARN of a dataset group used to filter the response.
	DatasetGroupArn *string

	// The maximum number of event trackers to return.
	MaxResults *int32

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

type ListEventTrackersOutput 

type ListEventTrackersOutput struct {

	// A list of event trackers.
	EventTrackers []*types.EventTrackerSummary

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

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListFiltersInput 

type ListFiltersInput struct {

	// The ARN of the dataset group that contains the filters.
	DatasetGroupArn *string

	// The maximum number of filters to return.
	MaxResults *int32

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

type ListFiltersOutput 

type ListFiltersOutput struct {

	// A list of returned filters.
	Filters []*types.FilterSummary

	// A token for getting the next set of filters (if they exist).
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListRecipesInput 

type ListRecipesInput struct {

	// The maximum number of recipes to return.
	MaxResults *int32

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

	// The default is SERVICE.
	RecipeProvider types.RecipeProvider
}

type ListRecipesOutput 

type ListRecipesOutput struct {

	// A token for getting the next set of recipes.
	NextToken *string

	// The list of available recipes.
	Recipes []*types.RecipeSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListSchemasInput 

type ListSchemasInput struct {

	// The maximum number of schemas to return.
	MaxResults *int32

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

type ListSchemasOutput 

type ListSchemasOutput struct {

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

	// A list of schemas.
	Schemas []*types.DatasetSchemaSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListSolutionVersionsInput 

type ListSolutionVersionsInput struct {

	// The maximum number of solution versions to return.
	MaxResults *int32

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

	// The Amazon Resource Name (ARN) of the solution.
	SolutionArn *string
}

type ListSolutionVersionsOutput 

type ListSolutionVersionsOutput struct {

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

	// A list of solution versions describing the version properties.
	SolutionVersions []*types.SolutionVersionSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListSolutionsInput 

type ListSolutionsInput struct {

	// The Amazon Resource Name (ARN) of the dataset group.
	DatasetGroupArn *string

	// The maximum number of solutions to return.
	MaxResults *int32

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

type ListSolutionsOutput 

type ListSolutionsOutput struct {

	// A token for getting the next set of solutions (if they exist).
	NextToken *string

	// A list of the current solutions.
	Solutions []*types.SolutionSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type Options 

type Options struct {
	// Set of options to modify how an operation is invoked. These apply to all
	// operations invoked for this client. Use functional options on operation call to
	// modify this list for per operation behavior.
	APIOptions []func(*middleware.Stack) error

	// The credentials object to use when signing requests.
	Credentials aws.CredentialsProvider

	// The endpoint options to be used when attempting to resolve an endpoint.
	EndpointOptions ResolverOptions

	// The service endpoint resolver.
	EndpointResolver EndpointResolver

	// Signature Version 4 (SigV4) Signer
	HTTPSignerV4 HTTPSignerV4

	// The region to send requests to. (Required)
	Region string

	// Retryer guides how HTTP requests should be retried in case of recoverable
	// failures. When nil the API client will use a default retryer.
	Retryer retry.Retryer

	// The HTTP client to invoke API calls with. Defaults to client's default HTTP
	// implementation if nil.
	HTTPClient HTTPClient
}

func (Options) Copy 

func (o Options) Copy() Options

Copy creates a clone where the APIOptions list is deep copied.

type ResolveEndpoint 

type ResolveEndpoint struct {
	Resolver EndpointResolver
	Options  ResolverOptions
}

func (*ResolveEndpoint) HandleSerialize 

func (m *ResolveEndpoint) HandleSerialize(ctx context.Context, in middleware.SerializeInput, next middleware.SerializeHandler) (
	out middleware.SerializeOutput, metadata middleware.Metadata, err error,
)

func (*ResolveEndpoint) ID 

func (*ResolveEndpoint) ID() string

type ResolverOptions 

type ResolverOptions = internalendpoints.Options

ResolverOptions is the service endpoint resolver options

type UpdateCampaignInput 

type UpdateCampaignInput struct {

	// The Amazon Resource Name (ARN) of the campaign.
	//
	// This member is required.
	CampaignArn *string

	// Specifies the requested minimum provisioned transactions (recommendations) per
	// second that Amazon Personalize will support.
	MinProvisionedTPS *int32

	// The ARN of a new solution version to deploy.
	SolutionVersionArn *string
}

type UpdateCampaignOutput 

type UpdateCampaignOutput struct {

	// The same campaign ARN as given in the request.
	CampaignArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

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