AbstractAmazonPersonalize (AWS SDK for Java

java.lang.Object
- com.amazonaws.services.personalize.AbstractAmazonPersonalize

All Implemented Interfaces:

AmazonPersonalize

Direct Known Subclasses:

AbstractAmazonPersonalizeAsync
```
@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class AbstractAmazonPersonalize
extends Object
implements AmazonPersonalize
```
Abstract implementation of AmazonPersonalize. Convenient method forms pass through to the corresponding overload that takes a request object, which throws an UnsupportedOperationException.

Field Summary
- Fields inherited from interface com.amazonaws.services.personalize.AmazonPersonalize
  ENDPOINT_PREFIX

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`CreateBatchInferenceJobResult`	`createBatchInferenceJob(CreateBatchInferenceJobRequest request)` Creates a batch inference job.
`CreateBatchSegmentJobResult`	`createBatchSegmentJob(CreateBatchSegmentJobRequest request)` Creates a batch segment job.
`CreateCampaignResult`	`createCampaign(CreateCampaignRequest request)` Creates a campaign that deploys 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.
`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)` Creates the configuration for training a model.
`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.
`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.
`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 that use the 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)` Remove tags that are attached to a resource.
`UpdateCampaignResult`	`updateCampaign(UpdateCampaignRequest request)` Updates a campaign by either deploying a new solution or changing the value of the campaign's `minProvisionedTPS` parameter.
`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.

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Method Detail
  - createBatchInferenceJob
```
public CreateBatchInferenceJobResult createBatchInferenceJob(CreateBatchInferenceJobRequest request)
```
    Description copied from interface: AmazonPersonalize
    
    Creates a batch inference job. The operation can handle up to 50 million records and the input file must be in JSON format. For more information, see Creating a batch inference job.
    
    Specified by:
    
    createBatchInferenceJob in interface AmazonPersonalize
    
    Returns:
    
    Result of the CreateBatchInferenceJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createBatchSegmentJob
```
public CreateBatchSegmentJobResult createBatchSegmentJob(CreateBatchSegmentJobRequest request)
```
    Description copied from interface: AmazonPersonalize
    
    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.
    
    Specified by:
    
    createBatchSegmentJob in interface AmazonPersonalize
    
    Returns:
    
    Result of the CreateBatchSegmentJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createCampaign
```
public CreateCampaignResult createCampaign(CreateCampaignRequest request)
```
    Description copied from interface: AmazonPersonalize
    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 bill. We recommend starting with 1 for minProvisionedTPS (the default). Track your usage using Amazon CloudWatch metrics, and increase the minProvisionedTPS as necessary.
    
    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
    Specified by:
    
    createCampaign in interface AmazonPersonalize
    
    Returns:
    
    Result of the CreateCampaign operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createDataset
```
public CreateDatasetResult createDataset(CreateDatasetRequest request)
```
    Description copied from interface: AmazonPersonalize
    Creates an empty dataset and adds it to the specified dataset group. Use CreateDatasetImportJob to import your training data to a dataset.
    
    There are three types of datasets:
    - Interactions
    - Items
    - Users
    Each dataset type has an associated schema with required field types. Only the Interactions dataset is required in order to train a model (also referred to as creating a solution).
    
    A dataset can be in one of the following states:
    - CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
    - DELETE PENDING > DELETE IN_PROGRESS
    To get the status of the dataset, call DescribeDataset.
    
    Related APIs
    Specified by:
    
    createDataset in interface AmazonPersonalize
    
    Returns:
    
    Result of the CreateDataset operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createDatasetExportJob
```
public CreateDatasetExportJobResult createDatasetExportJob(CreateDatasetExportJobRequest request)
```
    Description copied from interface: 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 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.
    Specified by:
    
    createDatasetExportJob in interface AmazonPersonalize
    
    Returns:
    
    Result of the CreateDatasetExportJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createDatasetGroup
```
public CreateDatasetGroupResult createDatasetGroup(CreateDatasetGroupRequest request)
```
    Description copied from interface: AmazonPersonalize
    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:
    - Interactions
    - Items
    - Users
    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
    Specified by:
    
    createDatasetGroup in interface AmazonPersonalize
    
    Returns:
    
    Result of the CreateDatasetGroup operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createDatasetImportJob
```
public CreateDatasetImportJobResult createDatasetImportJob(CreateDatasetImportJobRequest request)
```
    Description copied from interface: AmazonPersonalize
    
    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
  - ListDatasetImportJobs
  - DescribeDatasetImportJob

Specified by:: createDatasetImportJob in interface AmazonPersonalize
Returns:: Result of the CreateDatasetImportJob operation returned by the service.
See Also:: AWS API Documentation

createEventTracker
```
public CreateEventTrackerResult createEventTracker(CreateEventTrackerRequest request)
```
Description copied from interface: AmazonPersonalize
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 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
Specified by:

createEventTracker in interface AmazonPersonalize

Returns:

Result of the CreateEventTracker operation returned by the service.

See Also:

AWS API Documentation

createFilter
```
public CreateFilterResult createFilter(CreateFilterRequest request)
```
Description copied from interface: AmazonPersonalize

Creates a recommendation filter. For more information, see Filtering recommendations and user segments.

Specified by:

createFilter in interface AmazonPersonalize

Returns:

Result of the CreateFilter operation returned by the service.

See Also:

AWS API Documentation

createMetricAttribution
```
public CreateMetricAttributionResult createMetricAttribution(CreateMetricAttributionRequest request)
```
Description copied from interface: AmazonPersonalize

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.

Specified by:

createMetricAttribution in interface AmazonPersonalize

Returns:

Result of the CreateMetricAttribution operation returned by the service.

See Also:

AWS API Documentation

createRecommender
```
public CreateRecommenderResult createRecommender(CreateRecommenderRequest request)
```
Description copied from interface: AmazonPersonalize
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
Specified by:

createRecommender in interface AmazonPersonalize

Returns:

Result of the CreateRecommender operation returned by the service.

See Also:

AWS API Documentation

createSchema
```
public CreateSchemaResult createSchema(CreateSchemaRequest request)
```
Description copied from interface: AmazonPersonalize
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
Specified by:

createSchema in interface AmazonPersonalize

Returns:

Result of the CreateSchema operation returned by the service.

See Also:

AWS API Documentation

createSolution
```
public CreateSolutionResult createSolution(CreateSolutionRequest request)
```
Description copied from interface: AmazonPersonalize
Creates the configuration for training a model. A trained model is known as a solution version. After the configuration is created, you train the model (create a solution version) 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.

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
- ListSolutionVersions
- DescribeSolutionVersion
Specified by:

createSolution in interface AmazonPersonalize

Returns:

Result of the CreateSolution operation returned by the service.

See Also:

AWS API Documentation

createSolutionVersion
```
public CreateSolutionVersionResult createSolutionVersion(CreateSolutionVersionRequest request)
```
Description copied from interface: AmazonPersonalize
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
Specified by:

createSolutionVersion in interface AmazonPersonalize

Returns:

Result of the CreateSolutionVersion operation returned by the service.

See Also:

AWS API Documentation

deleteCampaign
```
public DeleteCampaignResult deleteCampaign(DeleteCampaignRequest request)
```
Description copied from interface: AmazonPersonalize

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.

Specified by:

deleteCampaign in interface AmazonPersonalize

Returns:

Result of the DeleteCampaign operation returned by the service.

See Also:

AWS API Documentation

deleteDataset
```
public DeleteDatasetResult deleteDataset(DeleteDatasetRequest request)
```
Description copied from interface: 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.

Specified by:

deleteDataset in interface AmazonPersonalize

Returns:

Result of the DeleteDataset operation returned by the service.

See Also:

AWS API Documentation

deleteDatasetGroup
```
public DeleteDatasetGroupResult deleteDatasetGroup(DeleteDatasetGroupRequest request)
```
Description copied from interface: AmazonPersonalize
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.
Specified by:

deleteDatasetGroup in interface AmazonPersonalize

Returns:

Result of the DeleteDatasetGroup operation returned by the service.

See Also:

AWS API Documentation

deleteEventTracker
```
public DeleteEventTrackerResult deleteEventTracker(DeleteEventTrackerRequest request)
```
Description copied from interface: AmazonPersonalize

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

Specified by:

deleteEventTracker in interface AmazonPersonalize

Returns:

Result of the DeleteEventTracker operation returned by the service.

See Also:

AWS API Documentation

deleteFilter
```
public DeleteFilterResult deleteFilter(DeleteFilterRequest request)
```
Description copied from interface: AmazonPersonalize

Deletes a filter.

Specified by:

deleteFilter in interface AmazonPersonalize

Returns:

Result of the DeleteFilter operation returned by the service.

See Also:

AWS API Documentation

deleteMetricAttribution
```
public DeleteMetricAttributionResult deleteMetricAttribution(DeleteMetricAttributionRequest request)
```
Description copied from interface: AmazonPersonalize

Deletes a metric attribution.

Specified by:

deleteMetricAttribution in interface AmazonPersonalize

Returns:

Result of the DeleteMetricAttribution operation returned by the service.

See Also:

AWS API Documentation

deleteRecommender
```
public DeleteRecommenderResult deleteRecommender(DeleteRecommenderRequest request)
```
Description copied from interface: AmazonPersonalize

Deactivates and removes a recommender. A deleted recommender can no longer be specified in a GetRecommendations request.

Specified by:

deleteRecommender in interface AmazonPersonalize

Returns:

Result of the DeleteRecommender operation returned by the service.

See Also:

AWS API Documentation

deleteSchema
```
public DeleteSchemaResult deleteSchema(DeleteSchemaRequest request)
```
Description copied from interface: AmazonPersonalize

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

Specified by:

deleteSchema in interface AmazonPersonalize

Returns:

Result of the DeleteSchema operation returned by the service.

See Also:

AWS API Documentation

deleteSolution
```
public DeleteSolutionResult deleteSolution(DeleteSolutionRequest request)
```
Description copied from interface: 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.

Specified by:

deleteSolution in interface AmazonPersonalize

Returns:

Result of the DeleteSolution operation returned by the service.

See Also:

AWS API Documentation

describeAlgorithm
```
public DescribeAlgorithmResult describeAlgorithm(DescribeAlgorithmRequest request)
```
Description copied from interface: AmazonPersonalize

Describes the given algorithm.

Specified by:

describeAlgorithm in interface AmazonPersonalize

Returns:

Result of the DescribeAlgorithm operation returned by the service.

See Also:

AWS API Documentation

describeBatchInferenceJob
```
public DescribeBatchInferenceJobResult describeBatchInferenceJob(DescribeBatchInferenceJobRequest request)
```
Description copied from interface: AmazonPersonalize

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.

Specified by:

describeBatchInferenceJob in interface AmazonPersonalize

Returns:

Result of the DescribeBatchInferenceJob operation returned by the service.

See Also:

AWS API Documentation

describeBatchSegmentJob
```
public DescribeBatchSegmentJobResult describeBatchSegmentJob(DescribeBatchSegmentJobRequest request)
```
Description copied from interface: AmazonPersonalize

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.

Specified by:

describeBatchSegmentJob in interface AmazonPersonalize

Returns:

Result of the DescribeBatchSegmentJob operation returned by the service.

See Also:

AWS API Documentation

describeCampaign
```
public DescribeCampaignResult describeCampaign(DescribeCampaignRequest request)
```
Description copied from interface: AmazonPersonalize
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.
Specified by:

describeCampaign in interface AmazonPersonalize

Returns:

Result of the DescribeCampaign operation returned by the service.

See Also:

AWS API Documentation

describeDataset
```
public DescribeDatasetResult describeDataset(DescribeDatasetRequest request)
```
Description copied from interface: AmazonPersonalize

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

Specified by:

describeDataset in interface AmazonPersonalize

Returns:

Result of the DescribeDataset operation returned by the service.

See Also:

AWS API Documentation

describeDatasetExportJob
```
public DescribeDatasetExportJobResult describeDatasetExportJob(DescribeDatasetExportJobRequest request)
```
Description copied from interface: AmazonPersonalize

Describes the dataset export job created by CreateDatasetExportJob, including the export job status.

Specified by:

describeDatasetExportJob in interface AmazonPersonalize

Returns:

Result of the DescribeDatasetExportJob operation returned by the service.

See Also:

AWS API Documentation

describeDatasetGroup
```
public DescribeDatasetGroupResult describeDatasetGroup(DescribeDatasetGroupRequest request)
```
Description copied from interface: AmazonPersonalize

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

Specified by:

describeDatasetGroup in interface AmazonPersonalize

Returns:

Result of the DescribeDatasetGroup operation returned by the service.

See Also:

AWS API Documentation

describeDatasetImportJob
```
public DescribeDatasetImportJobResult describeDatasetImportJob(DescribeDatasetImportJobRequest request)
```
Description copied from interface: AmazonPersonalize

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

Specified by:

describeDatasetImportJob in interface AmazonPersonalize

Returns:

Result of the DescribeDatasetImportJob operation returned by the service.

See Also:

AWS API Documentation

describeEventTracker
```
public DescribeEventTrackerResult describeEventTracker(DescribeEventTrackerRequest request)
```
Description copied from interface: AmazonPersonalize

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

Specified by:

describeEventTracker in interface AmazonPersonalize

Returns:

Result of the DescribeEventTracker operation returned by the service.

See Also:

AWS API Documentation

describeFeatureTransformation
```
public DescribeFeatureTransformationResult describeFeatureTransformation(DescribeFeatureTransformationRequest request)
```
Description copied from interface: AmazonPersonalize

Describes the given feature transformation.

Specified by:

describeFeatureTransformation in interface AmazonPersonalize

Returns:

Result of the DescribeFeatureTransformation operation returned by the service.

See Also:

AWS API Documentation

describeFilter
```
public DescribeFilterResult describeFilter(DescribeFilterRequest request)
```
Description copied from interface: AmazonPersonalize

Describes a filter's properties.

Specified by:

describeFilter in interface AmazonPersonalize

Returns:

Result of the DescribeFilter operation returned by the service.

See Also:

AWS API Documentation

describeMetricAttribution
```
public DescribeMetricAttributionResult describeMetricAttribution(DescribeMetricAttributionRequest request)
```
Description copied from interface: AmazonPersonalize

Describes a metric attribution.

Specified by:

describeMetricAttribution in interface AmazonPersonalize

Returns:

Result of the DescribeMetricAttribution operation returned by the service.

See Also:

AWS API Documentation

describeRecipe
```
public DescribeRecipeResult describeRecipe(DescribeRecipeRequest request)
```
Description copied from interface: AmazonPersonalize
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.
Specified by:

describeRecipe in interface AmazonPersonalize

Returns:

Result of the DescribeRecipe operation returned by the service.

See Also:

AWS API Documentation

describeRecommender
```
public DescribeRecommenderResult describeRecommender(DescribeRecommenderRequest request)
```
Description copied from interface: AmazonPersonalize
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.
Specified by:

describeRecommender in interface AmazonPersonalize

Returns:

Result of the DescribeRecommender operation returned by the service.

See Also:

AWS API Documentation

describeSchema
```
public DescribeSchemaResult describeSchema(DescribeSchemaRequest request)
```
Description copied from interface: AmazonPersonalize

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

Specified by:

describeSchema in interface AmazonPersonalize

Returns:

Result of the DescribeSchema operation returned by the service.

See Also:

AWS API Documentation

describeSolution
```
public DescribeSolutionResult describeSolution(DescribeSolutionRequest request)
```
Description copied from interface: AmazonPersonalize

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

Specified by:

describeSolution in interface AmazonPersonalize

Returns:

Result of the DescribeSolution operation returned by the service.

See Also:

AWS API Documentation

describeSolutionVersion
```
public DescribeSolutionVersionResult describeSolutionVersion(DescribeSolutionVersionRequest request)
```
Description copied from interface: AmazonPersonalize

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

Specified by:

describeSolutionVersion in interface AmazonPersonalize

Returns:

Result of the DescribeSolutionVersion operation returned by the service.

See Also:

AWS API Documentation

getSolutionMetrics
```
public GetSolutionMetricsResult getSolutionMetrics(GetSolutionMetricsRequest request)
```
Description copied from interface: AmazonPersonalize

Gets the metrics for the specified solution version.

Specified by:

getSolutionMetrics in interface AmazonPersonalize

Returns:

Result of the GetSolutionMetrics operation returned by the service.

See Also:

AWS API Documentation

listBatchInferenceJobs
```
public ListBatchInferenceJobsResult listBatchInferenceJobs(ListBatchInferenceJobsRequest request)
```
Description copied from interface: AmazonPersonalize

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

Specified by:

listBatchInferenceJobs in interface AmazonPersonalize

Returns:

Result of the ListBatchInferenceJobs operation returned by the service.

See Also:

AWS API Documentation

listBatchSegmentJobs
```
public ListBatchSegmentJobsResult listBatchSegmentJobs(ListBatchSegmentJobsRequest request)
```
Description copied from interface: AmazonPersonalize

Gets a list of the batch segment jobs that have been performed off of a solution version that you specify.

Specified by:

listBatchSegmentJobs in interface AmazonPersonalize

Returns:

Result of the ListBatchSegmentJobs operation returned by the service.

See Also:

AWS API Documentation

listCampaigns
```
public ListCampaignsResult listCampaigns(ListCampaignsRequest request)
```
Description copied from interface: AmazonPersonalize

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.

Specified by:

listCampaigns in interface AmazonPersonalize

Returns:

Result of the ListCampaigns operation returned by the service.

See Also:

AWS API Documentation

listDatasetExportJobs
```
public ListDatasetExportJobsResult listDatasetExportJobs(ListDatasetExportJobsRequest request)
```
Description copied from interface: AmazonPersonalize

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.

Specified by:

listDatasetExportJobs in interface AmazonPersonalize

Returns:

Result of the ListDatasetExportJobs operation returned by the service.

See Also:

AWS API Documentation

listDatasetGroups
```
public ListDatasetGroupsResult listDatasetGroups(ListDatasetGroupsRequest request)
```
Description copied from interface: AmazonPersonalize

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.

Specified by:

listDatasetGroups in interface AmazonPersonalize

Returns:

Result of the ListDatasetGroups operation returned by the service.

See Also:

AWS API Documentation

listDatasetImportJobs
```
public ListDatasetImportJobsResult listDatasetImportJobs(ListDatasetImportJobsRequest request)
```
Description copied from interface: AmazonPersonalize

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.

Specified by:

listDatasetImportJobs in interface AmazonPersonalize

Returns:

Result of the ListDatasetImportJobs operation returned by the service.

See Also:

AWS API Documentation

listDatasets
```
public ListDatasetsResult listDatasets(ListDatasetsRequest request)
```
Description copied from interface: AmazonPersonalize

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.

Specified by:

listDatasets in interface AmazonPersonalize

Returns:

Result of the ListDatasets operation returned by the service.

See Also:

AWS API Documentation

listEventTrackers
```
public ListEventTrackersResult listEventTrackers(ListEventTrackersRequest request)
```
Description copied from interface: AmazonPersonalize

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.

Specified by:

listEventTrackers in interface AmazonPersonalize

Returns:

Result of the ListEventTrackers operation returned by the service.

See Also:

AWS API Documentation

listFilters
```
public ListFiltersResult listFilters(ListFiltersRequest request)
```
Description copied from interface: AmazonPersonalize

Lists all filters that belong to a given dataset group.

Specified by:

listFilters in interface AmazonPersonalize

Returns:

Result of the ListFilters operation returned by the service.

See Also:

AWS API Documentation

listMetricAttributionMetrics
```
public ListMetricAttributionMetricsResult listMetricAttributionMetrics(ListMetricAttributionMetricsRequest request)
```
Description copied from interface: AmazonPersonalize

Lists the metrics for the metric attribution.

Specified by:

listMetricAttributionMetrics in interface AmazonPersonalize

Returns:

Result of the ListMetricAttributionMetrics operation returned by the service.

See Also:

AWS API Documentation

listMetricAttributions
```
public ListMetricAttributionsResult listMetricAttributions(ListMetricAttributionsRequest request)
```
Description copied from interface: AmazonPersonalize

Lists metric attributions.

Specified by:

listMetricAttributions in interface AmazonPersonalize

Returns:

Result of the ListMetricAttributions operation returned by the service.

See Also:

AWS API Documentation

listRecipes
```
public ListRecipesResult listRecipes(ListRecipesRequest request)
```
Description copied from interface: AmazonPersonalize

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

Specified by:

listRecipes in interface AmazonPersonalize

Returns:

Result of the ListRecipes operation returned by the service.

See Also:

AWS API Documentation

listRecommenders
```
public ListRecommendersResult listRecommenders(ListRecommendersRequest request)
```
Description copied from interface: AmazonPersonalize

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.

Specified by:

listRecommenders in interface AmazonPersonalize

Returns:

Result of the ListRecommenders operation returned by the service.

See Also:

AWS API Documentation

listSchemas
```
public ListSchemasResult listSchemas(ListSchemasRequest request)
```
Description copied from interface: AmazonPersonalize

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.

Specified by:

listSchemas in interface AmazonPersonalize

Returns:

Result of the ListSchemas operation returned by the service.

See Also:

AWS API Documentation

listSolutionVersions
```
public ListSolutionVersionsResult listSolutionVersions(ListSolutionVersionsRequest request)
```
Description copied from interface: AmazonPersonalize

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).

Specified by:

listSolutionVersions in interface AmazonPersonalize

Returns:

Result of the ListSolutionVersions operation returned by the service.

See Also:

AWS API Documentation

listSolutions
```
public ListSolutionsResult listSolutions(ListSolutionsRequest request)
```
Description copied from interface: AmazonPersonalize

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

Specified by:

listSolutions in interface AmazonPersonalize

Returns:

Result of the ListSolutions operation returned by the service.

See Also:

AWS API Documentation

listTagsForResource
```
public ListTagsForResourceResult listTagsForResource(ListTagsForResourceRequest request)
```
Description copied from interface: AmazonPersonalize

Get a list of tags attached to a resource.

Specified by:

listTagsForResource in interface AmazonPersonalize

Returns:

Result of the ListTagsForResource operation returned by the service.

See Also:

AWS API Documentation

startRecommender
```
public StartRecommenderResult startRecommender(StartRecommenderRequest request)
```
Description copied from interface: AmazonPersonalize

Starts a recommender that is INACTIVE. Starting a recommender does not create any new models, but resumes billing and automatic retraining for the recommender.

Specified by:

startRecommender in interface AmazonPersonalize

Returns:

Result of the StartRecommender operation returned by the service.

See Also:

AWS API Documentation

stopRecommender
```
public StopRecommenderResult stopRecommender(StopRecommenderRequest request)
```
Description copied from interface: AmazonPersonalize

Stops a recommender that is ACTIVE. Stopping a recommender halts billing and automatic retraining for the recommender.

Specified by:

stopRecommender in interface AmazonPersonalize

Returns:

Result of the StopRecommender operation returned by the service.

See Also:

AWS API Documentation

stopSolutionVersionCreation
```
public StopSolutionVersionCreationResult stopSolutionVersionCreation(StopSolutionVersionCreationRequest request)
```
Description copied from interface: AmazonPersonalize
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.
Specified by:

stopSolutionVersionCreation in interface AmazonPersonalize

Returns:

Result of the StopSolutionVersionCreation operation returned by the service.

See Also:

AWS API Documentation

tagResource
```
public TagResourceResult tagResource(TagResourceRequest request)
```
Description copied from interface: AmazonPersonalize

Add a list of tags to a resource.

Specified by:

tagResource in interface AmazonPersonalize

Returns:

Result of the TagResource operation returned by the service.

See Also:

AWS API Documentation

untagResource
```
public UntagResourceResult untagResource(UntagResourceRequest request)
```
Description copied from interface: AmazonPersonalize

Remove tags that are attached to a resource.

Specified by:

untagResource in interface AmazonPersonalize

Returns:

Result of the UntagResource operation returned by the service.

See Also:

AWS API Documentation

updateCampaign
```
public UpdateCampaignResult updateCampaign(UpdateCampaignRequest request)
```
Description copied from interface: 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 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 on campaigns, see CreateCampaign.

Specified by:

updateCampaign in interface AmazonPersonalize

Returns:

Result of the UpdateCampaign operation returned by the service.

See Also:

AWS API Documentation

updateDataset
```
public UpdateDatasetResult updateDataset(UpdateDatasetRequest request)
```
Description copied from interface: AmazonPersonalize

Update a dataset to replace its schema with a new or existing one. For more information, see Replacing a dataset's schema.

Specified by:

updateDataset in interface AmazonPersonalize

Returns:

Result of the UpdateDataset operation returned by the service.

See Also:

AWS API Documentation

updateMetricAttribution
```
public UpdateMetricAttributionResult updateMetricAttribution(UpdateMetricAttributionRequest request)
```
Description copied from interface: AmazonPersonalize

Updates a metric attribution.

Specified by:

updateMetricAttribution in interface AmazonPersonalize

Returns:

Result of the UpdateMetricAttribution operation returned by the service.

See Also:

AWS API Documentation

updateRecommender
```
public UpdateRecommenderResult updateRecommender(UpdateRecommenderRequest request)
```
Description copied from interface: AmazonPersonalize

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.

Specified by:

updateRecommender in interface AmazonPersonalize

Returns:

Result of the UpdateRecommender operation returned by the service.

See Also:

AWS API Documentation

shutdown
```
public void shutdown()
```
Description copied from interface: AmazonPersonalize

Shuts down this client object, releasing any resources that might be held open. This is an optional method, and callers are not expected to call it, but can if they want to explicitly release any open resources. Once a client has been shutdown, it should not be used to make any more requests.

Specified by:

shutdown in interface AmazonPersonalize

getCachedResponseMetadata
```
public ResponseMetadata getCachedResponseMetadata(AmazonWebServiceRequest request)
```
Description copied from interface: AmazonPersonalize

Returns additional metadata for a previously executed successful request, typically used for debugging issues where a service isn't acting as expected. This data isn't considered part of the result data returned by an operation, so it's available through this separate, diagnostic interface.
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 a request.

Specified by:

getCachedResponseMetadata in interface AmazonPersonalize

Parameters:

request - The originally executed request.

Returns:

The response metadata for the specified request, or null if none is available.

AWS SDK for Java 1.x API Reference - 1.12.524

Class AbstractAmazonPersonalize

Field Summary

Fields inherited from interface com.amazonaws.services.personalize.AmazonPersonalize

Method Summary

Methods inherited from class java.lang.Object

Method Detail

createBatchInferenceJob

createBatchSegmentJob

createCampaign

createDataset

createDatasetExportJob

createDatasetGroup

createDatasetImportJob

createEventTracker

createFilter

createMetricAttribution

createRecommender

createSchema

createSolution

createSolutionVersion

deleteCampaign

deleteDataset

deleteDatasetGroup

deleteEventTracker

deleteFilter

deleteMetricAttribution

deleteRecommender

deleteSchema

deleteSolution

describeAlgorithm

describeBatchInferenceJob

describeBatchSegmentJob

describeCampaign

describeDataset

describeDatasetExportJob

describeDatasetGroup

describeDatasetImportJob

describeEventTracker

describeFeatureTransformation

describeFilter

describeMetricAttribution

describeRecipe

describeRecommender

describeSchema

describeSolution

describeSolutionVersion

getSolutionMetrics

listBatchInferenceJobs

listBatchSegmentJobs

listCampaigns

listDatasetExportJobs

listDatasetGroups

listDatasetImportJobs

listDatasets

listEventTrackers

listFilters

listMetricAttributionMetrics

listMetricAttributions

listRecipes

listRecommenders

listSchemas

listSolutionVersions

listSolutions

listTagsForResource

startRecommender

stopRecommender

stopSolutionVersionCreation

tagResource

untagResource

updateCampaign

updateDataset

updateMetricAttribution

updateRecommender

shutdown

getCachedResponseMetadata