@ThreadSafe @Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class AmazonPersonalizeClient extends AmazonWebServiceClient implements AmazonPersonalize
Amazon Personalize is a machine learning service that makes it easy to add individualized recommendations to customers.
LOGGING_AWS_REQUEST_METRIC ENDPOINT_PREFIX | Modifier and Type | Method and Description |
|---|---|
static AmazonPersonalizeClientBuilder |
builder () |
CreateBatchInferenceJobResult |
createBatchInferenceJob (CreateBatchInferenceJobRequest request)
Generates batch recommendations based on a list of items or users stored in Amazon S3 and exports the
recommendations to an Amazon S3 bucket.
|
CreateBatchSegmentJobResult |
createBatchSegmentJob (CreateBatchSegmentJobRequest request)
Creates a batch segment job.
|
CreateCampaignResult |
createCampaign (CreateCampaignRequest request)
|
CreateDataDeletionJobResult |
createDataDeletionJob (CreateDataDeletionJobRequest request)
Creates a batch job that deletes all references to specific users from an Amazon Personalize dataset group in
batches.
|
CreateDatasetResult |
createDataset (CreateDatasetRequest request)
Creates an empty dataset and adds it to the specified dataset group.
|
CreateDatasetExportJobResult |
createDatasetExportJob (CreateDatasetExportJobRequest request)
Creates a job that exports data from your dataset to an Amazon S3 bucket.
|
CreateDatasetGroupResult |
createDatasetGroup (CreateDatasetGroupRequest request)
Creates an empty dataset group.
|
CreateDatasetImportJobResult |
createDatasetImportJob (CreateDatasetImportJobRequest request)
Creates a job that imports training data from your data source (an Amazon S3 bucket) to an Amazon Personalize
dataset.
|
CreateEventTrackerResult |
createEventTracker (CreateEventTrackerRequest request)
Creates an event tracker that you use when adding event data to a specified dataset group using the PutEvents API.
|
CreateFilterResult |
createFilter (CreateFilterRequest request)
Creates a recommendation filter.
|
CreateMetricAttributionResult |
createMetricAttribution (CreateMetricAttributionRequest request)
Creates a metric attribution.
|
CreateRecommenderResult |
createRecommender (CreateRecommenderRequest request)
Creates a recommender with the recipe (a Domain dataset group use case) you specify.
|
CreateSchemaResult |
createSchema (CreateSchemaRequest request)
Creates an Amazon Personalize schema from the specified schema string.
|
CreateSolutionResult |
createSolution (CreateSolutionRequest request)
|
CreateSolutionVersionResult |
createSolutionVersion (CreateSolutionVersionRequest request)
Trains or retrains an active solution in a Custom dataset group.
|
DeleteCampaignResult |
deleteCampaign (DeleteCampaignRequest request)
Removes a campaign by deleting the solution deployment.
|
DeleteDatasetResult |
deleteDataset (DeleteDatasetRequest request)
Deletes a dataset.
|
DeleteDatasetGroupResult |
deleteDatasetGroup (DeleteDatasetGroupRequest request)
Deletes a dataset group.
|
DeleteEventTrackerResult |
deleteEventTracker (DeleteEventTrackerRequest request)
Deletes the event tracker.
|
DeleteFilterResult |
deleteFilter (DeleteFilterRequest request)
Deletes a filter.
|
DeleteMetricAttributionResult |
deleteMetricAttribution (DeleteMetricAttributionRequest request)
Deletes a metric attribution.
|
DeleteRecommenderResult |
deleteRecommender (DeleteRecommenderRequest request)
Deactivates and removes a recommender.
|
DeleteSchemaResult |
deleteSchema (DeleteSchemaRequest request)
Deletes a schema.
|
DeleteSolutionResult |
deleteSolution (DeleteSolutionRequest request)
Deletes all versions of a solution and the
Solution object itself. |
DescribeAlgorithmResult |
describeAlgorithm (DescribeAlgorithmRequest request)
Describes the given algorithm.
|
DescribeBatchInferenceJobResult |
describeBatchInferenceJob (DescribeBatchInferenceJobRequest request)
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.
|
DescribeBatchSegmentJobResult |
describeBatchSegmentJob (DescribeBatchSegmentJobRequest request)
Gets the properties of a batch segment job including name, Amazon Resource Name (ARN), status, input and output
configurations, and the ARN of the solution version used to generate segments.
|
DescribeCampaignResult |
describeCampaign (DescribeCampaignRequest request)
Describes the given campaign, including its status.
|
DescribeDataDeletionJobResult |
describeDataDeletionJob (DescribeDataDeletionJobRequest request)
Describes the data deletion job created by CreateDataDeletionJob, including the job status.
|
DescribeDatasetResult |
describeDataset (DescribeDatasetRequest request)
Describes the given dataset.
|
DescribeDatasetExportJobResult |
describeDatasetExportJob (DescribeDatasetExportJobRequest request)
Describes the dataset export job created by CreateDatasetExportJob, including the export job status.
|
DescribeDatasetGroupResult |
describeDatasetGroup (DescribeDatasetGroupRequest request)
Describes the given dataset group.
|
DescribeDatasetImportJobResult |
describeDatasetImportJob (DescribeDatasetImportJobRequest request)
Describes the dataset import job created by CreateDatasetImportJob, including the import job status.
|
DescribeEventTrackerResult |
describeEventTracker (DescribeEventTrackerRequest request)
Describes an event tracker.
|
DescribeFeatureTransformationResult |
describeFeatureTransformation (DescribeFeatureTransformationRequest request)
Describes the given feature transformation.
|
DescribeFilterResult |
describeFilter (DescribeFilterRequest request)
Describes a filter's properties.
|
DescribeMetricAttributionResult |
describeMetricAttribution (DescribeMetricAttributionRequest request)
Describes a metric attribution.
|
DescribeRecipeResult |
describeRecipe (DescribeRecipeRequest request)
Describes a recipe.
|
DescribeRecommenderResult |
describeRecommender (DescribeRecommenderRequest request)
Describes the given recommender, including its status.
|
DescribeSchemaResult |
describeSchema (DescribeSchemaRequest request)
Describes a schema.
|
DescribeSolutionResult |
describeSolution (DescribeSolutionRequest request)
Describes a solution.
|
DescribeSolutionVersionResult |
describeSolutionVersion (DescribeSolutionVersionRequest request)
Describes a specific version of a solution.
|
ResponseMetadata |
getCachedResponseMetadata (AmazonWebServiceRequest request)
Returns additional metadata for a previously executed successful, request, typically used for debugging issues
where a service isn't acting as expected.
|
GetSolutionMetricsResult |
getSolutionMetrics (GetSolutionMetricsRequest request)
Gets the metrics for the specified solution version.
|
ListBatchInferenceJobsResult |
listBatchInferenceJobs (ListBatchInferenceJobsRequest request)
Gets a list of the batch inference jobs that have been performed off of a solution version.
|
ListBatchSegmentJobsResult |
listBatchSegmentJobs (ListBatchSegmentJobsRequest request)
Gets a list of the batch segment jobs that have been performed off of a solution version that you specify.
|
ListCampaignsResult |
listCampaigns (ListCampaignsRequest request)
Returns a list of campaigns that use the given solution.
|
ListDataDeletionJobsResult |
listDataDeletionJobs (ListDataDeletionJobsRequest request)
Returns a list of data deletion jobs for a dataset group ordered by creation time, with the most recent first.
|
ListDatasetExportJobsResult |
listDatasetExportJobs (ListDatasetExportJobsRequest request)
Returns a list of dataset export jobs that use the given dataset.
|
ListDatasetGroupsResult |
listDatasetGroups (ListDatasetGroupsRequest request)
Returns a list of dataset groups.
|
ListDatasetImportJobsResult |
listDatasetImportJobs (ListDatasetImportJobsRequest request)
Returns a list of dataset import jobs that use the given dataset.
|
ListDatasetsResult |
listDatasets (ListDatasetsRequest request)
Returns the list of datasets contained in the given dataset group.
|
ListEventTrackersResult |
listEventTrackers (ListEventTrackersRequest request)
Returns the list of event trackers associated with the account.
|
ListFiltersResult |
listFilters (ListFiltersRequest request)
Lists all filters that belong to a given dataset group.
|
ListMetricAttributionMetricsResult |
listMetricAttributionMetrics (ListMetricAttributionMetricsRequest request)
Lists the metrics for the metric attribution.
|
ListMetricAttributionsResult |
listMetricAttributions (ListMetricAttributionsRequest request)
Lists metric attributions.
|
ListRecipesResult |
listRecipes (ListRecipesRequest request)
Returns a list of available recipes.
|
ListRecommendersResult |
listRecommenders (ListRecommendersRequest request)
Returns a list of recommenders in a given Domain dataset group.
|
ListSchemasResult |
listSchemas (ListSchemasRequest request)
Returns the list of schemas associated with the account.
|
ListSolutionsResult |
listSolutions (ListSolutionsRequest request)
Returns a list of solutions in a given dataset group.
|
ListSolutionVersionsResult |
listSolutionVersions (ListSolutionVersionsRequest request)
Returns a list of solution versions for the given solution.
|
ListTagsForResourceResult |
listTagsForResource (ListTagsForResourceRequest request)
Get a list of tags
attached to a resource.
|
void |
shutdown ()
Shuts down this client object, releasing any resources that might be held
open.
|
StartRecommenderResult |
startRecommender (StartRecommenderRequest request)
Starts a recommender that is INACTIVE.
|
StopRecommenderResult |
stopRecommender (StopRecommenderRequest request)
Stops a recommender that is ACTIVE.
|
StopSolutionVersionCreationResult |
stopSolutionVersionCreation (StopSolutionVersionCreationRequest request)
Stops creating a solution version that is in a state of CREATE_PENDING or CREATE IN_PROGRESS.
|
TagResourceResult |
tagResource (TagResourceRequest request)
Add a list of tags to a resource.
|
UntagResourceResult |
untagResource (UntagResourceRequest request)
Removes the specified tags that are attached to a resource.
|
UpdateCampaignResult |
updateCampaign (UpdateCampaignRequest request)
Updates a campaign to deploy a retrained solution version with an existing campaign, change your campaign's
minProvisionedTPS, or modify your campaign's configuration. |
UpdateDatasetResult |
updateDataset (UpdateDatasetRequest request)
Update a dataset to replace its schema with a new or existing one.
|
UpdateMetricAttributionResult |
updateMetricAttribution (UpdateMetricAttributionRequest request)
Updates a metric attribution.
|
UpdateRecommenderResult |
updateRecommender (UpdateRecommenderRequest request)
Updates the recommender to modify the recommender configuration.
|
addRequestHandler, addRequestHandler, configureRegion, getClientConfiguration, getEndpointPrefix, getMonitoringListeners, getRequestMetricsCollector, getServiceName, getSignerByURI, getSignerOverride, getSignerRegionOverride, getTimeOffset, makeImmutable, removeRequestHandler, removeRequestHandler, setEndpoint, setEndpoint, setRegion, setServiceNameIntern, setSignerRegionOverride, setTimeOffset, withEndpoint, withRegion, withRegion, withTimeOffset public static AmazonPersonalizeClientBuilder builder()
public CreateBatchInferenceJobResult createBatchInferenceJob(CreateBatchInferenceJobRequest request)
Generates batch recommendations based on a list of items or users stored in Amazon S3 and exports the recommendations to an Amazon S3 bucket.
To generate batch recommendations, specify the ARN of a solution version and an Amazon S3 URI for the input and output data. For user personalization, popular items, and personalized ranking solutions, the batch inference job generates a list of recommended items for each user ID in the input file. For related items solutions, the job generates a list of recommended items for each item ID in the input file.
For more information, see Creating a batch inference job .
If you use the Similar-Items recipe, Amazon Personalize can add descriptive themes to batch recommendations. To
generate themes, set the job's mode to THEME_GENERATION and specify the name of the field that
contains item names in the input data.
For more information about generating themes, see Batch recommendations with themes from Content Generator .
You can't get batch recommendations with the Trending-Now or Next-Best-Action recipes.
createBatchInferenceJob in interface AmazonPersonalize createBatchInferenceJobRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceAlreadyExistsException - The specified resource already exists.LimitExceededException - The limit on the number of requests per second has been exceeded.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.TooManyTagsException - You have exceeded the maximum number of tags you can apply to this resource.public CreateBatchSegmentJobResult createBatchSegmentJob(CreateBatchSegmentJobRequest request)
Creates a batch segment job. The operation can handle up to 50 million records and the input file must be in JSON format. For more information, see Getting batch recommendations and user segments.
createBatchSegmentJob in interface AmazonPersonalize createBatchSegmentJobRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceAlreadyExistsException - The specified resource already exists.LimitExceededException - The limit on the number of requests per second has been exceeded.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.TooManyTagsException - You have exceeded the maximum number of tags you can apply to this resource.public CreateCampaignResult createCampaign(CreateCampaignRequest request)
You incur campaign costs while it is active. To avoid unnecessary costs, make sure to delete the campaign when you are finished. For information about campaign costs, see Amazon Personalize pricing.
Creates a campaign that deploys 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 high minProvisionedTPS will increase your cost. We recommend starting with 1 for
minProvisionedTPS (the default). Track your usage using Amazon CloudWatch metrics, and increase the
minProvisionedTPS as necessary.
When you create an Amazon Personalize campaign, you can specify the minimum provisioned transactions per second (
minProvisionedTPS) for the campaign. This is the baseline transaction throughput for the campaign
provisioned by Amazon Personalize. It sets the minimum billing charge for the campaign while it is active. A
transaction is a single GetRecommendations or GetPersonalizedRanking request. The
default minProvisionedTPS is 1.
If your TPS increases beyond the minProvisionedTPS, Amazon Personalize auto-scales the provisioned
capacity up and down, but never below minProvisionedTPS. There's a short time delay while the
capacity is increased that might cause loss of transactions. When your traffic reduces, capacity returns to the
minProvisionedTPS.
You are charged for the the minimum provisioned TPS or, if your requests exceed the
minProvisionedTPS, the actual TPS. The actual TPS is the total number of recommendation requests you
make. We recommend starting with a low minProvisionedTPS, track your usage using Amazon CloudWatch
metrics, and then increase the minProvisionedTPS as necessary.
For more information about campaign costs, see Amazon Personalize pricing.
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
createCampaign in interface AmazonPersonalize createCampaignRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceAlreadyExistsException - The specified resource already exists.LimitExceededException - The limit on the number of requests per second has been exceeded.ResourceInUseException - The specified resource is in use.TooManyTagsException - You have exceeded the maximum number of tags you can apply to this resource.public CreateDataDeletionJobResult createDataDeletionJob(CreateDataDeletionJobRequest request)
Creates a batch job that deletes all references to specific users from an Amazon Personalize dataset group in batches. You specify the users to delete in a CSV file of userIds in an Amazon S3 bucket. After a job completes, Amazon Personalize no longer trains on the users’ data and no longer considers the users when generating user segments. For more information about creating a data deletion job, see Deleting users.
Your input file must be a CSV file with a single USER_ID column that lists the users IDs. For more information about preparing the CSV file, see Preparing your data deletion file and uploading it to Amazon S3.
To give Amazon Personalize permission to access your input CSV file of userIds, you must specify an IAM service
role that has permission to read from the data source. This role needs GetObject and
ListBucket permissions for the bucket and its content. These permissions are the same as importing
data. For information on granting access to your Amazon S3 bucket, see Giving Amazon
Personalize Access to Amazon S3 Resources.
After you create a job, it can take up to a day to delete all references to the users from datasets and models. Until the job completes, Amazon Personalize continues to use the data when training. And if you use a User Segmentation recipe, the users might appear in user segments.
Status
A data deletion job can have one of the following statuses:
PENDING > IN_PROGRESS > COMPLETED -or- FAILED
To get the status of the data deletion job, call DescribeDataDeletionJob API operation and specify the Amazon Resource Name (ARN) of the job. If the status
is FAILED, the response includes a failureReason key, which describes why the job failed.
Related APIs
createDataDeletionJob in interface AmazonPersonalize createDataDeletionJobRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceAlreadyExistsException - The specified resource already exists.LimitExceededException - The limit on the number of requests per second has been exceeded.ResourceInUseException - The specified resource is in use.TooManyTagsException - You have exceeded the maximum number of tags you can apply to this resource.public CreateDatasetResult createDataset(CreateDatasetRequest request)
Creates an empty dataset and adds it to the specified dataset group. Use CreateDatasetImportJob to import your training data to a dataset.
There are 5 types of datasets:
Item interactions
Items
Users
Action interactions
Actions
Each dataset type has an associated schema with required field types. Only the Item 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
createDataset in interface AmazonPersonalize createDatasetRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceAlreadyExistsException - The specified resource already exists.LimitExceededException - The limit on the number of requests per second has been exceeded.ResourceInUseException - The specified resource is in use.TooManyTagsException - You have exceeded the maximum number of tags you can apply to this resource.public CreateDatasetExportJobResult createDatasetExportJob(CreateDatasetExportJobRequest request)
Creates a job that exports data from your dataset to an Amazon S3 bucket. To allow Amazon Personalize to export
the training data, you must specify an service-linked IAM role that gives Amazon Personalize
PutObject permissions for your Amazon S3 bucket. For information, see Exporting a dataset in the Amazon
Personalize developer guide.
Status
A dataset export job can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
To get the status of the export job, call DescribeDatasetExportJob, and specify the Amazon Resource Name (ARN) of the dataset export job. The dataset
export 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.
createDatasetExportJob in interface AmazonPersonalize createDatasetExportJobRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceAlreadyExistsException - The specified resource already exists.LimitExceededException - The limit on the number of requests per second has been exceeded.ResourceInUseException - The specified resource is in use.TooManyTagsException - You have exceeded the maximum number of tags you can apply to this resource.public CreateDatasetGroupResult createDatasetGroup(CreateDatasetGroupRequest request)
Creates an empty dataset group. A dataset group is a container for Amazon Personalize resources. A dataset group can contain at most three datasets, one for each type of dataset:
Item interactions
Items
Users
Actions
Action interactions
A dataset group can be a Domain dataset group, where you specify a domain and use pre-configured resources like recommenders, or a Custom dataset group, where you use custom resources, such as a solution with a solution version, that you deploy with a campaign. If you start with a Domain dataset group, you can still add custom resources such as solutions and solution versions trained with recipes for custom use cases and deployed with campaigns.
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 Key Management Service (KMS) key to encrypt the datasets in the group. If you specify a KMS key, you must also include an Identity and Access Management (IAM) role that has permission to access the key.
APIs that require a dataset group ARN in the request
Related APIs
createDatasetGroup in interface AmazonPersonalize createDatasetGroupRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceAlreadyExistsException - The specified resource already exists.LimitExceededException - The limit on the number of requests per second has been exceeded.TooManyTagsException - You have exceeded the maximum number of tags you can apply to this resource.public CreateDatasetImportJobResult createDatasetImportJob(CreateDatasetImportJobRequest request)
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 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
createDatasetImportJob in interface AmazonPersonalize createDatasetImportJobRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceAlreadyExistsException - The specified resource already exists.LimitExceededException - The limit on the number of requests per second has been exceeded.ResourceInUseException - The specified resource is in use.TooManyTagsException - You have exceeded the maximum number of tags you can apply to this resource.public CreateEventTrackerResult createEventTracker(CreateEventTrackerRequest request)
Creates an event tracker that you use when adding event data to a specified dataset group using the PutEvents API.
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 create an event tracker, the response includes a tracking ID, which you pass as a parameter when you use the PutEvents operation. Amazon Personalize then appends the event data to the Item interactions dataset of the dataset group you specify in your event tracker.
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
createEventTracker in interface AmazonPersonalize createEventTrackerRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceAlreadyExistsException - The specified resource already exists.ResourceNotFoundException - Could not find the specified resource.LimitExceededException - The limit on the number of requests per second has been exceeded.ResourceInUseException - The specified resource is in use.TooManyTagsException - You have exceeded the maximum number of tags you can apply to this resource.public CreateFilterResult createFilter(CreateFilterRequest request)
Creates a recommendation filter. For more information, see Filtering recommendations and user segments.
createFilter in interface AmazonPersonalize createFilterRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceAlreadyExistsException - The specified resource already exists.ResourceNotFoundException - Could not find the specified resource.LimitExceededException - The limit on the number of requests per second has been exceeded.TooManyTagsException - You have exceeded the maximum number of tags you can apply to this resource.public CreateMetricAttributionResult createMetricAttribution(CreateMetricAttributionRequest request)
Creates a metric attribution. A metric attribution creates reports on the data that you import into Amazon Personalize. Depending on how you imported the data, you can view reports in Amazon CloudWatch or Amazon S3. For more information, see Measuring impact of recommendations.
createMetricAttribution in interface AmazonPersonalize createMetricAttributionRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceAlreadyExistsException - The specified resource already exists.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of requests per second has been exceeded.public CreateRecommenderResult createRecommender(CreateRecommenderRequest request)
Creates a recommender with the recipe (a Domain dataset group use case) you specify. You create recommenders for a Domain dataset group and specify the recommender's Amazon Resource Name (ARN) when you make a GetRecommendations request.
Minimum recommendation requests per second
A high minRecommendationRequestsPerSecond will increase your bill. We recommend starting with 1 for
minRecommendationRequestsPerSecond (the default). Track your usage using Amazon CloudWatch metrics,
and increase the minRecommendationRequestsPerSecond as necessary.
When you create a recommender, you can configure the recommender's minimum recommendation requests per second.
The minimum recommendation requests per second (minRecommendationRequestsPerSecond) specifies the
baseline recommendation request throughput provisioned by Amazon Personalize. The default
minRecommendationRequestsPerSecond is 1. A recommendation request is a single
GetRecommendations operation. Request throughput is measured in requests per second and Amazon
Personalize uses your requests per second to derive your requests per hour and the price of your recommender
usage.
If your requests per second increases beyond minRecommendationRequestsPerSecond, Amazon Personalize
auto-scales the provisioned capacity up and down, but never below minRecommendationRequestsPerSecond
. There's a short time delay while the capacity is increased that might cause loss of requests.
Your bill is the greater of either the minimum requests per hour (based on minRecommendationRequestsPerSecond) or
the actual number of requests. The actual request throughput used is calculated as the average requests/second
within a one-hour window. We recommend starting with the default minRecommendationRequestsPerSecond,
track your usage using Amazon CloudWatch metrics, and then increase the
minRecommendationRequestsPerSecond as necessary.
Status
A recommender can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
DELETE PENDING > DELETE IN_PROGRESS
To get the recommender status, call DescribeRecommender.
Wait until the status of the recommender is ACTIVE before asking the recommender for
recommendations.
Related APIs
createRecommender in interface AmazonPersonalize createRecommenderRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceAlreadyExistsException - The specified resource already exists.ResourceNotFoundException - Could not find the specified resource.LimitExceededException - The limit on the number of requests per second has been exceeded.ResourceInUseException - The specified resource is in use.TooManyTagsException - You have exceeded the maximum number of tags you can apply to this resource.public CreateSchemaResult createSchema(CreateSchemaRequest request)
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. If you are creating a schema for a dataset in a Domain dataset group, you provide the domain of the Domain dataset group. You specify a schema when you call CreateDataset.
Related APIs
createSchema in interface AmazonPersonalize createSchemaRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceAlreadyExistsException - The specified resource already exists.LimitExceededException - The limit on the number of requests per second has been exceeded.public CreateSolutionResult createSolution(CreateSolutionRequest request)
After you create a solution, you can’t change its configuration. By default, all new solutions use automatic training. With automatic training, you incur training costs while your solution is active. You can't stop automatic training for a solution. To avoid unnecessary costs, make sure to delete the solution when you are finished. For information about training costs, see Amazon Personalize pricing.
Creates the configuration for training a model (creating a solution version). This configuration includes the recipe to use for model training and optional training configuration, such as columns to use in training and feature transformation parameters. For more information about configuring a solution, see Creating and configuring a solution.
By default, new solutions use automatic training to create solution versions every 7 days. You can change the training frequency. Automatic solution version creation starts one hour after the solution is ACTIVE. If you manually create a solution version within the hour, the solution skips the first automatic training. For more information, see Configuring automatic training.
To turn off automatic training, set performAutoTraining to false. If you turn off automatic
training, you must manually create a solution version by calling the CreateSolutionVersion
operation.
After training starts, you can get the solution version's Amazon Resource Name (ARN) with the ListSolutionVersions API operation. To get its status, use the DescribeSolutionVersion.
After training completes you can evaluate model accuracy by calling GetSolutionMetrics. When you are satisfied with the solution version, you deploy it using CreateCampaign. The campaign provides recommendations to a client through the GetRecommendations API.
Amazon Personalize doesn't support configuring the hpoObjective for solution hyperparameter
optimization at this time.
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. If you
use manual training, the status must be ACTIVE before you call CreateSolutionVersion.
Related APIs
createSolution in interface AmazonPersonalize createSolutionRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceAlreadyExistsException - The specified resource already exists.ResourceNotFoundException - Could not find the specified resource.LimitExceededException - The limit on the number of requests per second has been exceeded.ResourceInUseException - The specified resource is in use.TooManyTagsException - You have exceeded the maximum number of tags you can apply to this resource.public CreateSolutionVersionResult createSolutionVersion(CreateSolutionVersionRequest request)
Trains or retrains an active solution in a Custom dataset group. 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
CREATE FAILED
CREATE STOPPING
CREATE STOPPED
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
createSolutionVersion in interface AmazonPersonalize createSolutionVersionRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.LimitExceededException - The limit on the number of requests per second has been exceeded.ResourceInUseException - The specified resource is in use.TooManyTagsException - You have exceeded the maximum number of tags you can apply to this resource.ResourceAlreadyExistsException - The specified resource already exists.public DeleteCampaignResult deleteCampaign(DeleteCampaignRequest request)
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 information on creating campaigns, see CreateCampaign.
deleteCampaign in interface AmazonPersonalize deleteCampaignRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public DeleteDatasetResult deleteDataset(DeleteDatasetRequest request)
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.
deleteDataset in interface AmazonPersonalize deleteDatasetRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public DeleteDatasetGroupResult deleteDatasetGroup(DeleteDatasetGroupRequest request)
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.
deleteDatasetGroup in interface AmazonPersonalize deleteDatasetGroupRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public DeleteEventTrackerResult deleteEventTracker(DeleteEventTrackerRequest request)
Deletes the event tracker. Does not delete the dataset from the dataset group. For more information on event trackers, see CreateEventTracker.
deleteEventTracker in interface AmazonPersonalize deleteEventTrackerRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public DeleteFilterResult deleteFilter(DeleteFilterRequest request)
Deletes a filter.
deleteFilter in interface AmazonPersonalize deleteFilterRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public DeleteMetricAttributionResult deleteMetricAttribution(DeleteMetricAttributionRequest request)
Deletes a metric attribution.
deleteMetricAttribution in interface AmazonPersonalize deleteMetricAttributionRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public DeleteRecommenderResult deleteRecommender(DeleteRecommenderRequest request)
Deactivates and removes a recommender. A deleted recommender can no longer be specified in a GetRecommendations request.
deleteRecommender in interface AmazonPersonalize deleteRecommenderRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public DeleteSchemaResult deleteSchema(DeleteSchemaRequest request)
Deletes a schema. Before deleting a schema, you must delete all datasets referencing the schema. For more information on schemas, see CreateSchema.
deleteSchema in interface AmazonPersonalize deleteSchemaRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public DeleteSolutionResult deleteSolution(DeleteSolutionRequest request)
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.
deleteSolution in interface AmazonPersonalize deleteSolutionRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public DescribeAlgorithmResult describeAlgorithm(DescribeAlgorithmRequest request)
Describes the given algorithm.
describeAlgorithm in interface AmazonPersonalize describeAlgorithmRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeBatchInferenceJobResult describeBatchInferenceJob(DescribeBatchInferenceJobRequest request)
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.
describeBatchInferenceJob in interface AmazonPersonalize describeBatchInferenceJobRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeBatchSegmentJobResult describeBatchSegmentJob(DescribeBatchSegmentJobRequest request)
Gets the properties of a batch segment job including name, Amazon Resource Name (ARN), status, input and output configurations, and the ARN of the solution version used to generate segments.
describeBatchSegmentJob in interface AmazonPersonalize describeBatchSegmentJobRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeCampaignResult describeCampaign(DescribeCampaignRequest request)
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.
describeCampaign in interface AmazonPersonalize describeCampaignRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeDataDeletionJobResult describeDataDeletionJob(DescribeDataDeletionJobRequest request)
Describes the data deletion job created by CreateDataDeletionJob, including the job status.
describeDataDeletionJob in interface AmazonPersonalize describeDataDeletionJobRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeDatasetResult describeDataset(DescribeDatasetRequest request)
Describes the given dataset. For more information on datasets, see CreateDataset.
describeDataset in interface AmazonPersonalize describeDatasetRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeDatasetExportJobResult describeDatasetExportJob(DescribeDatasetExportJobRequest request)
Describes the dataset export job created by CreateDatasetExportJob, including the export job status.
describeDatasetExportJob in interface AmazonPersonalize describeDatasetExportJobRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeDatasetGroupResult describeDatasetGroup(DescribeDatasetGroupRequest request)
Describes the given dataset group. For more information on dataset groups, see CreateDatasetGroup.
describeDatasetGroup in interface AmazonPersonalize describeDatasetGroupRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeDatasetImportJobResult describeDatasetImportJob(DescribeDatasetImportJobRequest request)
Describes the dataset import job created by CreateDatasetImportJob, including the import job status.
describeDatasetImportJob in interface AmazonPersonalize describeDatasetImportJobRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeEventTrackerResult describeEventTracker(DescribeEventTrackerRequest request)
Describes an event tracker. The response includes the trackingId and status of the
event tracker. For more information on event trackers, see CreateEventTracker.
describeEventTracker in interface AmazonPersonalize describeEventTrackerRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeFeatureTransformationResult describeFeatureTransformation(DescribeFeatureTransformationRequest request)
Describes the given feature transformation.
describeFeatureTransformation in interface AmazonPersonalize describeFeatureTransformationRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeFilterResult describeFilter(DescribeFilterRequest request)
Describes a filter's properties.
describeFilter in interface AmazonPersonalize describeFilterRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeMetricAttributionResult describeMetricAttribution(DescribeMetricAttributionRequest request)
Describes a metric attribution.
describeMetricAttribution in interface AmazonPersonalize describeMetricAttributionRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeRecipeResult describeRecipe(DescribeRecipeRequest request)
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.
describeRecipe in interface AmazonPersonalize describeRecipeRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeRecommenderResult describeRecommender(DescribeRecommenderRequest request)
Describes the given recommender, including its status.
A recommender can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
DELETE PENDING > DELETE IN_PROGRESS
When the status is CREATE FAILED, the response includes the failureReason
key, which describes why.
The modelMetrics key is null when the recommender is being created or deleted.
For more information on recommenders, see CreateRecommender.
describeRecommender in interface AmazonPersonalize describeRecommenderRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeSchemaResult describeSchema(DescribeSchemaRequest request)
Describes a schema. For more information on schemas, see CreateSchema.
describeSchema in interface AmazonPersonalize describeSchemaRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeSolutionResult describeSolution(DescribeSolutionRequest request)
Describes a solution. For more information on solutions, see CreateSolution.
describeSolution in interface AmazonPersonalize describeSolutionRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public DescribeSolutionVersionResult describeSolutionVersion(DescribeSolutionVersionRequest request)
Describes a specific version of a solution. For more information on solutions, see CreateSolution
describeSolutionVersion in interface AmazonPersonalize describeSolutionVersionRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.public GetSolutionMetricsResult getSolutionMetrics(GetSolutionMetricsRequest request)
Gets the metrics for the specified solution version.
getSolutionMetrics in interface AmazonPersonalize getSolutionMetricsRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public ListBatchInferenceJobsResult listBatchInferenceJobs(ListBatchInferenceJobsRequest request)
Gets a list of the batch inference jobs that have been performed off of a solution version.
listBatchInferenceJobs in interface AmazonPersonalize listBatchInferenceJobsRequest - InvalidInputException - Provide a valid value for the field or parameter.InvalidNextTokenException - The token is not valid.public ListBatchSegmentJobsResult listBatchSegmentJobs(ListBatchSegmentJobsRequest request)
Gets a list of the batch segment jobs that have been performed off of a solution version that you specify.
listBatchSegmentJobs in interface AmazonPersonalize listBatchSegmentJobsRequest - InvalidInputException - Provide a valid value for the field or parameter.InvalidNextTokenException - The token is not valid.public ListCampaignsResult listCampaigns(ListCampaignsRequest request)
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.
listCampaigns in interface AmazonPersonalize listCampaignsRequest - InvalidInputException - Provide a valid value for the field or parameter.InvalidNextTokenException - The token is not valid.public ListDataDeletionJobsResult listDataDeletionJobs(ListDataDeletionJobsRequest request)
Returns a list of data deletion jobs for a dataset group ordered by creation time, with the most recent first. When a dataset group is not specified, all the data deletion jobs associated with the account are listed. The response provides the properties for each job, including the Amazon Resource Name (ARN). For more information on data deletion jobs, see Deleting users.
listDataDeletionJobs in interface AmazonPersonalize listDataDeletionJobsRequest - InvalidInputException - Provide a valid value for the field or parameter.InvalidNextTokenException - The token is not valid.public ListDatasetExportJobsResult listDatasetExportJobs(ListDatasetExportJobsRequest request)
Returns a list of dataset export jobs that use the given dataset. When a dataset is not specified, all the dataset export jobs associated with the account are listed. The response provides the properties for each dataset export job, including the Amazon Resource Name (ARN). For more information on dataset export jobs, see CreateDatasetExportJob. For more information on datasets, see CreateDataset.
listDatasetExportJobs in interface AmazonPersonalize listDatasetExportJobsRequest - InvalidInputException - Provide a valid value for the field or parameter.InvalidNextTokenException - The token is not valid.public ListDatasetGroupsResult listDatasetGroups(ListDatasetGroupsRequest request)
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.
listDatasetGroups in interface AmazonPersonalize listDatasetGroupsRequest - InvalidNextTokenException - The token is not valid.public ListDatasetImportJobsResult listDatasetImportJobs(ListDatasetImportJobsRequest request)
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.
listDatasetImportJobs in interface AmazonPersonalize listDatasetImportJobsRequest - InvalidInputException - Provide a valid value for the field or parameter.InvalidNextTokenException - The token is not valid.public ListDatasetsResult listDatasets(ListDatasetsRequest request)
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.
listDatasets in interface AmazonPersonalize listDatasetsRequest - InvalidInputException - Provide a valid value for the field or parameter.InvalidNextTokenException - The token is not valid.public ListEventTrackersResult listEventTrackers(ListEventTrackersRequest request)
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.
listEventTrackers in interface AmazonPersonalize listEventTrackersRequest - InvalidInputException - Provide a valid value for the field or parameter.InvalidNextTokenException - The token is not valid.public ListFiltersResult listFilters(ListFiltersRequest request)
Lists all filters that belong to a given dataset group.
listFilters in interface AmazonPersonalize listFiltersRequest - InvalidInputException - Provide a valid value for the field or parameter.InvalidNextTokenException - The token is not valid.public ListMetricAttributionMetricsResult listMetricAttributionMetrics(ListMetricAttributionMetricsRequest request)
Lists the metrics for the metric attribution.
listMetricAttributionMetrics in interface AmazonPersonalize listMetricAttributionMetricsRequest - InvalidInputException - Provide a valid value for the field or parameter.InvalidNextTokenException - The token is not valid.public ListMetricAttributionsResult listMetricAttributions(ListMetricAttributionsRequest request)
Lists metric attributions.
listMetricAttributions in interface AmazonPersonalize listMetricAttributionsRequest - InvalidInputException - Provide a valid value for the field or parameter.InvalidNextTokenException - The token is not valid.public ListRecipesResult listRecipes(ListRecipesRequest request)
Returns a list of available recipes. The response provides the properties for each recipe, including the recipe's Amazon Resource Name (ARN).
listRecipes in interface AmazonPersonalize listRecipesRequest - InvalidNextTokenException - The token is not valid.InvalidInputException - Provide a valid value for the field or parameter.public ListRecommendersResult listRecommenders(ListRecommendersRequest request)
Returns a list of recommenders in a given Domain dataset group. When a Domain dataset group is not specified, all the recommenders associated with the account are listed. The response provides the properties for each recommender, including the Amazon Resource Name (ARN). For more information on recommenders, see CreateRecommender.
listRecommenders in interface AmazonPersonalize listRecommendersRequest - InvalidInputException - Provide a valid value for the field or parameter.InvalidNextTokenException - The token is not valid.public ListSchemasResult listSchemas(ListSchemasRequest request)
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.
listSchemas in interface AmazonPersonalize listSchemasRequest - InvalidNextTokenException - The token is not valid.public ListSolutionVersionsResult listSolutionVersions(ListSolutionVersionsRequest request)
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).
listSolutionVersions in interface AmazonPersonalize listSolutionVersionsRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.InvalidNextTokenException - The token is not valid.public ListSolutionsResult listSolutions(ListSolutionsRequest request)
Returns a list of solutions in a 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.
listSolutions in interface AmazonPersonalize listSolutionsRequest - InvalidInputException - Provide a valid value for the field or parameter.InvalidNextTokenException - The token is not valid.public ListTagsForResourceResult listTagsForResource(ListTagsForResourceRequest request)
Get a list of tags attached to a resource.
listTagsForResource in interface AmazonPersonalize listTagsForResourceRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public StartRecommenderResult startRecommender(StartRecommenderRequest request)
Starts a recommender that is INACTIVE. Starting a recommender does not create any new models, but resumes billing and automatic retraining for the recommender.
startRecommender in interface AmazonPersonalize startRecommenderRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public StopRecommenderResult stopRecommender(StopRecommenderRequest request)
Stops a recommender that is ACTIVE. Stopping a recommender halts billing and automatic retraining for the recommender.
stopRecommender in interface AmazonPersonalize stopRecommenderRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public StopSolutionVersionCreationResult stopSolutionVersionCreation(StopSolutionVersionCreationRequest request)
Stops creating a solution version that is in a state of CREATE_PENDING or CREATE IN_PROGRESS.
Depending on the current state of the solution version, the solution version state changes as follows:
CREATE_PENDING > CREATE_STOPPED
or
CREATE_IN_PROGRESS > CREATE_STOPPING > CREATE_STOPPED
You are billed for all of the training completed up until you stop the solution version creation. You cannot resume creating a solution version once it has been stopped.
stopSolutionVersionCreation in interface AmazonPersonalize stopSolutionVersionCreationRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public TagResourceResult tagResource(TagResourceRequest request)
Add a list of tags to a resource.
tagResource in interface AmazonPersonalize tagResourceRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.TooManyTagsException - You have exceeded the maximum number of tags you can apply to this resource.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of requests per second has been exceeded.public UntagResourceResult untagResource(UntagResourceRequest request)
Removes the specified tags that are attached to a resource. For more information, see Removing tags from Amazon Personalize resources.
untagResource in interface AmazonPersonalize untagResourceRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.TooManyTagKeysException - The request contains more tag keys than can be associated with a resource (50 tag keys per resource).ResourceInUseException - The specified resource is in use.public UpdateCampaignResult updateCampaign(UpdateCampaignRequest request)
Updates a campaign to deploy a retrained solution version with an existing campaign, change your campaign's
minProvisionedTPS, or modify your campaign's configuration. For example, you can set
enableMetadataWithRecommendations to true for an existing campaign.
To update a campaign to start automatically using the latest solution version, specify the following:
For the SolutionVersionArn parameter, specify the Amazon Resource Name (ARN) of your solution in
SolutionArn/$LATEST format.
In the campaignConfig, set syncWithLatestSolutionVersion to true.
To update a campaign, the campaign status must be ACTIVE or CREATE FAILED. Check the campaign status using the DescribeCampaign operation.
You can still get recommendations from a campaign while an update is in progress. The campaign will use the
previous solution version and campaign configuration to generate recommendations until the latest campaign update
status is Active.
For more information about updating a campaign, including code samples, see Updating a campaign. For more information about campaigns, see Creating a campaign.
updateCampaign in interface AmazonPersonalize updateCampaignRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public UpdateDatasetResult updateDataset(UpdateDatasetRequest request)
Update a dataset to replace its schema with a new or existing one. For more information, see Replacing a dataset's schema.
updateDataset in interface AmazonPersonalize updateDatasetRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public UpdateMetricAttributionResult updateMetricAttribution(UpdateMetricAttributionRequest request)
Updates a metric attribution.
updateMetricAttribution in interface AmazonPersonalize updateMetricAttributionRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.ResourceAlreadyExistsException - The specified resource already exists.public UpdateRecommenderResult updateRecommender(UpdateRecommenderRequest request)
Updates the recommender to modify the recommender configuration. If you update the recommender to modify the
columns used in training, Amazon Personalize automatically starts a full retraining of the models backing your
recommender. While the update completes, you can still get recommendations from the recommender. The recommender
uses the previous configuration until the update completes. To track the status of this update, use the
latestRecommenderUpdate returned in the DescribeRecommender
operation.
updateRecommender in interface AmazonPersonalize updateRecommenderRequest - InvalidInputException - Provide a valid value for the field or parameter.ResourceNotFoundException - Could not find the specified resource.ResourceInUseException - The specified resource is in use.public ResponseMetadata getCachedResponseMetadata(AmazonWebServiceRequest request)
Response metadata is only cached for a limited period of time, so if you need to access this extra diagnostic information for an executed request, you should use this method to retrieve it as soon as possible after executing the request.
getCachedResponseMetadata in interface AmazonPersonalize request - The originally executed requestpublic void shutdown()
AmazonWebServiceClient shutdown in interface AmazonPersonalize shutdown in class AmazonWebServiceClient