@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class AbstractAmazonPersonalize extends Object implements AmazonPersonalize
AmazonPersonalize. Convenient method forms pass through to the corresponding
 overload that takes a request object, which throws an UnsupportedOperationException.ENDPOINT_PREFIX| Modifier and Type | Method and Description | 
|---|---|
| CreateBatchInferenceJobResult | createBatchInferenceJob(CreateBatchInferenceJobRequest request)
 Creates a batch inference job. | 
| CreateCampaignResult | createCampaign(CreateCampaignRequest request)
 Creates a campaign by deploying a solution version. | 
| 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. | 
| CreateSchemaResult | createSchema(CreateSchemaRequest request)
 Creates an Amazon Personalize schema from the specified schema string. | 
| CreateSolutionResult | createSolution(CreateSolutionRequest request)
 Creates the configuration for training a model. | 
| CreateSolutionVersionResult | createSolutionVersion(CreateSolutionVersionRequest request)
 Trains or retrains an active solution. | 
| 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. | 
| DeleteSchemaResult | deleteSchema(DeleteSchemaRequest request)
 Deletes a schema. | 
| DeleteSolutionResult | deleteSolution(DeleteSolutionRequest request)
 Deletes all versions of a solution and the  Solutionobject 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. | 
| DescribeCampaignResult | describeCampaign(DescribeCampaignRequest request)
 Describes the given campaign, including its 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. | 
| DescribeRecipeResult | describeRecipe(DescribeRecipeRequest request)
 Describes a recipe. | 
| 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. | 
| ListCampaignsResult | listCampaigns(ListCampaignsRequest request)
 Returns a list of campaigns that use the given solution. | 
| 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. | 
| ListRecipesResult | listRecipes(ListRecipesRequest request)
 Returns a list of available recipes. | 
| ListSchemasResult | listSchemas(ListSchemasRequest request)
 Returns the list of schemas associated with the account. | 
| ListSolutionsResult | listSolutions(ListSolutionsRequest request)
 Returns a list of solutions that use the given dataset group. | 
| ListSolutionVersionsResult | listSolutionVersions(ListSolutionVersionsRequest request)
 Returns a list of solution versions for the given solution. | 
| void | shutdown()Shuts down this client object, releasing any resources that might be held open. | 
| UpdateCampaignResult | updateCampaign(UpdateCampaignRequest request)
 Updates a campaign by either deploying a new solution or changing the value of the campaign's
  minProvisionedTPSparameter. | 
public CreateBatchInferenceJobResult createBatchInferenceJob(CreateBatchInferenceJobRequest request)
AmazonPersonalizeCreates 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.
createBatchInferenceJob in interface AmazonPersonalizepublic CreateCampaignResult createCampaign(CreateCampaignRequest request)
AmazonPersonalizeCreates a campaign by deploying a solution version. When a client calls the GetRecommendations and GetPersonalizedRanking APIs, a campaign is specified in the request.
Minimum Provisioned TPS and Auto-Scaling
 A transaction is a single GetRecommendations or GetPersonalizedRanking call.
 Transactions per second (TPS) is the throughput and unit of billing for Amazon Personalize. The minimum
 provisioned TPS (minProvisionedTPS) specifies the baseline throughput provisioned by Amazon
 Personalize, and thus, the minimum billing charge.
 
 If your TPS increases beyond minProvisionedTPS, Amazon Personalize auto-scales the provisioned
 capacity up and down, but never below minProvisionedTPS. There's a short time delay while the
 capacity is increased that might cause loss of transactions.
 
 The actual TPS used is calculated as the average requests/second within a 5-minute window. You pay for maximum of
 either the minimum provisioned TPS or the actual TPS. We recommend starting 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
createCampaign in interface AmazonPersonalizepublic CreateDatasetResult createDataset(CreateDatasetRequest request)
AmazonPersonalizeCreates 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
createDataset in interface AmazonPersonalizepublic CreateDatasetExportJobResult createDatasetExportJob(CreateDatasetExportJobRequest request)
AmazonPersonalize
 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 AWS Identity and Access Management (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 AmazonPersonalizepublic CreateDatasetGroupResult createDatasetGroup(CreateDatasetGroupRequest request)
AmazonPersonalizeCreates 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
Related APIs
createDatasetGroup in interface AmazonPersonalizepublic CreateDatasetImportJobResult createDatasetImportJob(CreateDatasetImportJobRequest request)
AmazonPersonalizeCreates 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) service role that has permission to read from the data source, as Amazon Personalize makes a copy of your data and processes it in an internal AWS system. For information on granting access to your Amazon S3 bucket, see Giving Amazon Personalize Access to Amazon S3 Resources.
The dataset import job replaces any existing data in the dataset that you imported in bulk.
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
createDatasetImportJob in interface AmazonPersonalizepublic CreateEventTrackerResult createEventTracker(CreateEventTrackerRequest request)
AmazonPersonalizeCreates 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 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 AmazonPersonalizepublic CreateFilterResult createFilter(CreateFilterRequest request)
AmazonPersonalizeCreates a recommendation filter. For more information, see filter.
createFilter in interface AmazonPersonalizepublic CreateSchemaResult createSchema(CreateSchemaRequest request)
AmazonPersonalizeCreates 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
createSchema in interface AmazonPersonalizepublic CreateSolutionResult createSolution(CreateSolutionRequest request)
AmazonPersonalize
 Creates the configuration for training a model. A trained model is known as a solution. After the configuration
 is created, you train the model (create a solution) by calling the CreateSolutionVersion operation. Every
 time you call CreateSolutionVersion, a new version of the solution is created.
 
After creating a solution version, you check its accuracy by calling GetSolutionMetrics. When you are satisfied with the version, you deploy it using CreateCampaign. The campaign provides recommendations to a client through the GetRecommendations API.
 To train a model, Amazon Personalize requires training data and a recipe. The training data comes from the
 dataset group that you provide in the request. A recipe specifies the training algorithm and a feature
 transformation. You can specify one of the predefined recipes provided by Amazon Personalize. Alternatively, you
 can specify performAutoML and Amazon Personalize will analyze your data and select the optimum
 USER_PERSONALIZATION recipe for you.
 
 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. Wait until the status shows as ACTIVE before
 calling CreateSolutionVersion.
 
Related APIs
createSolution in interface AmazonPersonalizepublic CreateSolutionVersionResult createSolutionVersion(CreateSolutionVersionRequest request)
AmazonPersonalize
 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
createSolutionVersion in interface AmazonPersonalizepublic DeleteCampaignResult deleteCampaign(DeleteCampaignRequest request)
AmazonPersonalizeRemoves a campaign by deleting the solution deployment. The solution that the campaign is based on is not deleted and can be redeployed when needed. A deleted campaign can no longer be specified in a GetRecommendations request. For more information on campaigns, see CreateCampaign.
deleteCampaign in interface AmazonPersonalizepublic DeleteDatasetResult deleteDataset(DeleteDatasetRequest request)
AmazonPersonalize
 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 AmazonPersonalizepublic DeleteDatasetGroupResult deleteDatasetGroup(DeleteDatasetGroupRequest request)
AmazonPersonalizeDeletes 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 AmazonPersonalizepublic DeleteEventTrackerResult deleteEventTracker(DeleteEventTrackerRequest request)
AmazonPersonalizeDeletes the event tracker. Does not delete the event-interactions dataset from the associated dataset group. For more information on event trackers, see CreateEventTracker.
deleteEventTracker in interface AmazonPersonalizepublic DeleteFilterResult deleteFilter(DeleteFilterRequest request)
AmazonPersonalizeDeletes a filter.
deleteFilter in interface AmazonPersonalizepublic DeleteSchemaResult deleteSchema(DeleteSchemaRequest request)
AmazonPersonalizeDeletes a schema. Before deleting a schema, you must delete all datasets referencing the schema. For more information on schemas, see CreateSchema.
deleteSchema in interface AmazonPersonalizepublic DeleteSolutionResult deleteSolution(DeleteSolutionRequest request)
AmazonPersonalize
 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 AmazonPersonalizepublic DescribeAlgorithmResult describeAlgorithm(DescribeAlgorithmRequest request)
AmazonPersonalizeDescribes the given algorithm.
describeAlgorithm in interface AmazonPersonalizepublic DescribeBatchInferenceJobResult describeBatchInferenceJob(DescribeBatchInferenceJobRequest request)
AmazonPersonalizeGets 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 AmazonPersonalizepublic DescribeCampaignResult describeCampaign(DescribeCampaignRequest request)
AmazonPersonalizeDescribes 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 AmazonPersonalizepublic DescribeDatasetResult describeDataset(DescribeDatasetRequest request)
AmazonPersonalizeDescribes the given dataset. For more information on datasets, see CreateDataset.
describeDataset in interface AmazonPersonalizepublic DescribeDatasetExportJobResult describeDatasetExportJob(DescribeDatasetExportJobRequest request)
AmazonPersonalizeDescribes the dataset export job created by CreateDatasetExportJob, including the export job status.
describeDatasetExportJob in interface AmazonPersonalizepublic DescribeDatasetGroupResult describeDatasetGroup(DescribeDatasetGroupRequest request)
AmazonPersonalizeDescribes the given dataset group. For more information on dataset groups, see CreateDatasetGroup.
describeDatasetGroup in interface AmazonPersonalizepublic DescribeDatasetImportJobResult describeDatasetImportJob(DescribeDatasetImportJobRequest request)
AmazonPersonalizeDescribes the dataset import job created by CreateDatasetImportJob, including the import job status.
describeDatasetImportJob in interface AmazonPersonalizepublic DescribeEventTrackerResult describeEventTracker(DescribeEventTrackerRequest request)
AmazonPersonalize
 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 AmazonPersonalizepublic DescribeFeatureTransformationResult describeFeatureTransformation(DescribeFeatureTransformationRequest request)
AmazonPersonalizeDescribes the given feature transformation.
describeFeatureTransformation in interface AmazonPersonalizepublic DescribeFilterResult describeFilter(DescribeFilterRequest request)
AmazonPersonalizeDescribes a filter's properties.
describeFilter in interface AmazonPersonalizepublic DescribeRecipeResult describeRecipe(DescribeRecipeRequest request)
AmazonPersonalizeDescribes 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 AmazonPersonalizepublic DescribeSchemaResult describeSchema(DescribeSchemaRequest request)
AmazonPersonalizeDescribes a schema. For more information on schemas, see CreateSchema.
describeSchema in interface AmazonPersonalizepublic DescribeSolutionResult describeSolution(DescribeSolutionRequest request)
AmazonPersonalizeDescribes a solution. For more information on solutions, see CreateSolution.
describeSolution in interface AmazonPersonalizepublic DescribeSolutionVersionResult describeSolutionVersion(DescribeSolutionVersionRequest request)
AmazonPersonalizeDescribes a specific version of a solution. For more information on solutions, see CreateSolution.
describeSolutionVersion in interface AmazonPersonalizepublic GetSolutionMetricsResult getSolutionMetrics(GetSolutionMetricsRequest request)
AmazonPersonalizeGets the metrics for the specified solution version.
getSolutionMetrics in interface AmazonPersonalizepublic ListBatchInferenceJobsResult listBatchInferenceJobs(ListBatchInferenceJobsRequest request)
AmazonPersonalizeGets a list of the batch inference jobs that have been performed off of a solution version.
listBatchInferenceJobs in interface AmazonPersonalizepublic ListCampaignsResult listCampaigns(ListCampaignsRequest request)
AmazonPersonalizeReturns 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 AmazonPersonalizepublic ListDatasetExportJobsResult listDatasetExportJobs(ListDatasetExportJobsRequest request)
AmazonPersonalizeReturns 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 AmazonPersonalizepublic ListDatasetGroupsResult listDatasetGroups(ListDatasetGroupsRequest request)
AmazonPersonalizeReturns 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 AmazonPersonalizepublic ListDatasetImportJobsResult listDatasetImportJobs(ListDatasetImportJobsRequest request)
AmazonPersonalizeReturns 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 AmazonPersonalizepublic ListDatasetsResult listDatasets(ListDatasetsRequest request)
AmazonPersonalizeReturns 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 AmazonPersonalizepublic ListEventTrackersResult listEventTrackers(ListEventTrackersRequest request)
AmazonPersonalizeReturns 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 AmazonPersonalizepublic ListFiltersResult listFilters(ListFiltersRequest request)
AmazonPersonalizeLists all filters that belong to a given dataset group.
listFilters in interface AmazonPersonalizepublic ListRecipesResult listRecipes(ListRecipesRequest request)
AmazonPersonalizeReturns a list of available recipes. The response provides the properties for each recipe, including the recipe's Amazon Resource Name (ARN).
listRecipes in interface AmazonPersonalizepublic ListSchemasResult listSchemas(ListSchemasRequest request)
AmazonPersonalizeReturns 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 AmazonPersonalizepublic ListSolutionVersionsResult listSolutionVersions(ListSolutionVersionsRequest request)
AmazonPersonalizeReturns 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.
listSolutionVersions in interface AmazonPersonalizepublic ListSolutionsResult listSolutions(ListSolutionsRequest request)
AmazonPersonalizeReturns 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.
listSolutions in interface AmazonPersonalizepublic UpdateCampaignResult updateCampaign(UpdateCampaignRequest request)
AmazonPersonalize
 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.
updateCampaign in interface AmazonPersonalizepublic void shutdown()
AmazonPersonalizeshutdown in interface AmazonPersonalizepublic ResponseMetadata getCachedResponseMetadata(AmazonWebServiceRequest request)
AmazonPersonalizeResponse 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 a request.
getCachedResponseMetadata in interface AmazonPersonalizerequest - The originally executed request.