@ThreadSafe @Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class AmazonPersonalizeAsyncClient extends AmazonPersonalizeClient implements AmazonPersonalizeAsync
AsyncHandler can be used to receive
notification when an asynchronous operation completes.
Amazon Personalize is a machine learning service that makes it easy to add individualized recommendations to customers.
LOGGING_AWS_REQUEST_METRICENDPOINT_PREFIXbuilder, createBatchInferenceJob, createBatchSegmentJob, createCampaign, createDataDeletionJob, createDataset, createDatasetExportJob, createDatasetGroup, createDatasetImportJob, createEventTracker, createFilter, createMetricAttribution, createRecommender, createSchema, createSolution, createSolutionVersion, deleteCampaign, deleteDataset, deleteDatasetGroup, deleteEventTracker, deleteFilter, deleteMetricAttribution, deleteRecommender, deleteSchema, deleteSolution, describeAlgorithm, describeBatchInferenceJob, describeBatchSegmentJob, describeCampaign, describeDataDeletionJob, describeDataset, describeDatasetExportJob, describeDatasetGroup, describeDatasetImportJob, describeEventTracker, describeFeatureTransformation, describeFilter, describeMetricAttribution, describeRecipe, describeRecommender, describeSchema, describeSolution, describeSolutionVersion, getCachedResponseMetadata, getSolutionMetrics, listBatchInferenceJobs, listBatchSegmentJobs, listCampaigns, listDataDeletionJobs, listDatasetExportJobs, listDatasetGroups, listDatasetImportJobs, listDatasets, listEventTrackers, listFilters, listMetricAttributionMetrics, listMetricAttributions, listRecipes, listRecommenders, listSchemas, listSolutions, listSolutionVersions, listTagsForResource, startRecommender, stopRecommender, stopSolutionVersionCreation, tagResource, untagResource, updateCampaign, updateDataset, updateMetricAttribution, updateRecommenderaddRequestHandler, addRequestHandler, configureRegion, getClientConfiguration, getEndpointPrefix, getMonitoringListeners, getRequestMetricsCollector, getServiceName, getSignerByURI, getSignerOverride, getSignerRegionOverride, getTimeOffset, makeImmutable, removeRequestHandler, removeRequestHandler, setEndpoint, setEndpoint, setRegion, setServiceNameIntern, setSignerRegionOverride, setTimeOffset, withEndpoint, withRegion, withRegion, withTimeOffsetequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitcreateBatchInferenceJob, createBatchSegmentJob, createCampaign, createDataDeletionJob, createDataset, createDatasetExportJob, createDatasetGroup, createDatasetImportJob, createEventTracker, createFilter, createMetricAttribution, createRecommender, createSchema, createSolution, createSolutionVersion, deleteCampaign, deleteDataset, deleteDatasetGroup, deleteEventTracker, deleteFilter, deleteMetricAttribution, deleteRecommender, deleteSchema, deleteSolution, describeAlgorithm, describeBatchInferenceJob, describeBatchSegmentJob, describeCampaign, describeDataDeletionJob, describeDataset, describeDatasetExportJob, describeDatasetGroup, describeDatasetImportJob, describeEventTracker, describeFeatureTransformation, describeFilter, describeMetricAttribution, describeRecipe, describeRecommender, describeSchema, describeSolution, describeSolutionVersion, getCachedResponseMetadata, getSolutionMetrics, listBatchInferenceJobs, listBatchSegmentJobs, listCampaigns, listDataDeletionJobs, listDatasetExportJobs, listDatasetGroups, listDatasetImportJobs, listDatasets, listEventTrackers, listFilters, listMetricAttributionMetrics, listMetricAttributions, listRecipes, listRecommenders, listSchemas, listSolutions, listSolutionVersions, listTagsForResource, startRecommender, stopRecommender, stopSolutionVersionCreation, tagResource, untagResource, updateCampaign, updateDataset, updateMetricAttribution, updateRecommenderpublic static AmazonPersonalizeAsyncClientBuilder asyncBuilder()
public ExecutorService getExecutorService()
public Future<CreateBatchInferenceJobResult> createBatchInferenceJobAsync(CreateBatchInferenceJobRequest request)
AmazonPersonalizeAsyncGenerates 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.
createBatchInferenceJobAsync in interface AmazonPersonalizeAsyncpublic Future<CreateBatchInferenceJobResult> createBatchInferenceJobAsync(CreateBatchInferenceJobRequest request, AsyncHandler<CreateBatchInferenceJobRequest,CreateBatchInferenceJobResult> asyncHandler)
AmazonPersonalizeAsyncGenerates 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.
createBatchInferenceJobAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateBatchSegmentJobResult> createBatchSegmentJobAsync(CreateBatchSegmentJobRequest request)
AmazonPersonalizeAsyncCreates 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.
createBatchSegmentJobAsync in interface AmazonPersonalizeAsyncpublic Future<CreateBatchSegmentJobResult> createBatchSegmentJobAsync(CreateBatchSegmentJobRequest request, AsyncHandler<CreateBatchSegmentJobRequest,CreateBatchSegmentJobResult> asyncHandler)
AmazonPersonalizeAsyncCreates 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.
createBatchSegmentJobAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateCampaignResult> createCampaignAsync(CreateCampaignRequest request)
AmazonPersonalizeAsyncYou 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
createCampaignAsync in interface AmazonPersonalizeAsyncpublic Future<CreateCampaignResult> createCampaignAsync(CreateCampaignRequest request, AsyncHandler<CreateCampaignRequest,CreateCampaignResult> asyncHandler)
AmazonPersonalizeAsyncYou 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
createCampaignAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateDataDeletionJobResult> createDataDeletionJobAsync(CreateDataDeletionJobRequest request)
AmazonPersonalizeAsyncCreates 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
createDataDeletionJobAsync in interface AmazonPersonalizeAsyncpublic Future<CreateDataDeletionJobResult> createDataDeletionJobAsync(CreateDataDeletionJobRequest request, AsyncHandler<CreateDataDeletionJobRequest,CreateDataDeletionJobResult> asyncHandler)
AmazonPersonalizeAsyncCreates 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
createDataDeletionJobAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateDatasetResult> createDatasetAsync(CreateDatasetRequest request)
AmazonPersonalizeAsyncCreates 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
createDatasetAsync in interface AmazonPersonalizeAsyncpublic Future<CreateDatasetResult> createDatasetAsync(CreateDatasetRequest request, AsyncHandler<CreateDatasetRequest,CreateDatasetResult> asyncHandler)
AmazonPersonalizeAsyncCreates 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
createDatasetAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateDatasetExportJobResult> createDatasetExportJobAsync(CreateDatasetExportJobRequest request)
AmazonPersonalizeAsync
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.
createDatasetExportJobAsync in interface AmazonPersonalizeAsyncpublic Future<CreateDatasetExportJobResult> createDatasetExportJobAsync(CreateDatasetExportJobRequest request, AsyncHandler<CreateDatasetExportJobRequest,CreateDatasetExportJobResult> asyncHandler)
AmazonPersonalizeAsync
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.
createDatasetExportJobAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateDatasetGroupResult> createDatasetGroupAsync(CreateDatasetGroupRequest request)
AmazonPersonalizeAsyncCreates 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
createDatasetGroupAsync in interface AmazonPersonalizeAsyncpublic Future<CreateDatasetGroupResult> createDatasetGroupAsync(CreateDatasetGroupRequest request, AsyncHandler<CreateDatasetGroupRequest,CreateDatasetGroupResult> asyncHandler)
AmazonPersonalizeAsyncCreates 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
createDatasetGroupAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateDatasetImportJobResult> createDatasetImportJobAsync(CreateDatasetImportJobRequest request)
AmazonPersonalizeAsyncCreates 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
createDatasetImportJobAsync in interface AmazonPersonalizeAsyncpublic Future<CreateDatasetImportJobResult> createDatasetImportJobAsync(CreateDatasetImportJobRequest request, AsyncHandler<CreateDatasetImportJobRequest,CreateDatasetImportJobResult> asyncHandler)
AmazonPersonalizeAsyncCreates 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 IAM service role that has permission to read from the data source, as Amazon Personalize makes a copy of your data and processes it internally. For information on granting access to your Amazon S3 bucket, see Giving Amazon Personalize Access to Amazon S3 Resources.
If you already created a recommender or deployed a custom solution version with a campaign, how new bulk records influence recommendations depends on the domain use case or recipe that you use. For more information, see How new data influences real-time recommendations.
By default, a dataset import job replaces any existing data in the dataset that you imported in bulk. To add new records without replacing existing data, specify INCREMENTAL for the import mode in the CreateDatasetImportJob operation.
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
createDatasetImportJobAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateEventTrackerResult> createEventTrackerAsync(CreateEventTrackerRequest request)
AmazonPersonalizeAsyncCreates 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
createEventTrackerAsync in interface AmazonPersonalizeAsyncpublic Future<CreateEventTrackerResult> createEventTrackerAsync(CreateEventTrackerRequest request, AsyncHandler<CreateEventTrackerRequest,CreateEventTrackerResult> asyncHandler)
AmazonPersonalizeAsyncCreates 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
createEventTrackerAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateFilterResult> createFilterAsync(CreateFilterRequest request)
AmazonPersonalizeAsyncCreates a recommendation filter. For more information, see Filtering recommendations and user segments.
createFilterAsync in interface AmazonPersonalizeAsyncpublic Future<CreateFilterResult> createFilterAsync(CreateFilterRequest request, AsyncHandler<CreateFilterRequest,CreateFilterResult> asyncHandler)
AmazonPersonalizeAsyncCreates a recommendation filter. For more information, see Filtering recommendations and user segments.
createFilterAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateMetricAttributionResult> createMetricAttributionAsync(CreateMetricAttributionRequest request)
AmazonPersonalizeAsyncCreates 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.
createMetricAttributionAsync in interface AmazonPersonalizeAsyncpublic Future<CreateMetricAttributionResult> createMetricAttributionAsync(CreateMetricAttributionRequest request, AsyncHandler<CreateMetricAttributionRequest,CreateMetricAttributionResult> asyncHandler)
AmazonPersonalizeAsyncCreates 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.
createMetricAttributionAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateRecommenderResult> createRecommenderAsync(CreateRecommenderRequest request)
AmazonPersonalizeAsyncCreates 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
createRecommenderAsync in interface AmazonPersonalizeAsyncpublic Future<CreateRecommenderResult> createRecommenderAsync(CreateRecommenderRequest request, AsyncHandler<CreateRecommenderRequest,CreateRecommenderResult> asyncHandler)
AmazonPersonalizeAsyncCreates 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
createRecommenderAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateSchemaResult> createSchemaAsync(CreateSchemaRequest request)
AmazonPersonalizeAsyncCreates 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
createSchemaAsync in interface AmazonPersonalizeAsyncpublic Future<CreateSchemaResult> createSchemaAsync(CreateSchemaRequest request, AsyncHandler<CreateSchemaRequest,CreateSchemaResult> asyncHandler)
AmazonPersonalizeAsyncCreates 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
createSchemaAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateSolutionResult> createSolutionAsync(CreateSolutionRequest request)
AmazonPersonalizeAsyncAfter 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
createSolutionAsync in interface AmazonPersonalizeAsyncpublic Future<CreateSolutionResult> createSolutionAsync(CreateSolutionRequest request, AsyncHandler<CreateSolutionRequest,CreateSolutionResult> asyncHandler)
AmazonPersonalizeAsyncAfter 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
createSolutionAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateSolutionVersionResult> createSolutionVersionAsync(CreateSolutionVersionRequest request)
AmazonPersonalizeAsync
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
createSolutionVersionAsync in interface AmazonPersonalizeAsyncpublic Future<CreateSolutionVersionResult> createSolutionVersionAsync(CreateSolutionVersionRequest request, AsyncHandler<CreateSolutionVersionRequest,CreateSolutionVersionResult> asyncHandler)
AmazonPersonalizeAsync
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
createSolutionVersionAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteCampaignResult> deleteCampaignAsync(DeleteCampaignRequest request)
AmazonPersonalizeAsyncRemoves 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.
deleteCampaignAsync in interface AmazonPersonalizeAsyncpublic Future<DeleteCampaignResult> deleteCampaignAsync(DeleteCampaignRequest request, AsyncHandler<DeleteCampaignRequest,DeleteCampaignResult> asyncHandler)
AmazonPersonalizeAsyncRemoves 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.
deleteCampaignAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteDatasetResult> deleteDatasetAsync(DeleteDatasetRequest request)
AmazonPersonalizeAsync
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.
deleteDatasetAsync in interface AmazonPersonalizeAsyncpublic Future<DeleteDatasetResult> deleteDatasetAsync(DeleteDatasetRequest request, AsyncHandler<DeleteDatasetRequest,DeleteDatasetResult> asyncHandler)
AmazonPersonalizeAsync
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.
deleteDatasetAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteDatasetGroupResult> deleteDatasetGroupAsync(DeleteDatasetGroupRequest request)
AmazonPersonalizeAsyncDeletes 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.
deleteDatasetGroupAsync in interface AmazonPersonalizeAsyncpublic Future<DeleteDatasetGroupResult> deleteDatasetGroupAsync(DeleteDatasetGroupRequest request, AsyncHandler<DeleteDatasetGroupRequest,DeleteDatasetGroupResult> asyncHandler)
AmazonPersonalizeAsyncDeletes 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.
deleteDatasetGroupAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteEventTrackerResult> deleteEventTrackerAsync(DeleteEventTrackerRequest request)
AmazonPersonalizeAsyncDeletes the event tracker. Does not delete the dataset from the dataset group. For more information on event trackers, see CreateEventTracker.
deleteEventTrackerAsync in interface AmazonPersonalizeAsyncpublic Future<DeleteEventTrackerResult> deleteEventTrackerAsync(DeleteEventTrackerRequest request, AsyncHandler<DeleteEventTrackerRequest,DeleteEventTrackerResult> asyncHandler)
AmazonPersonalizeAsyncDeletes the event tracker. Does not delete the dataset from the dataset group. For more information on event trackers, see CreateEventTracker.
deleteEventTrackerAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteFilterResult> deleteFilterAsync(DeleteFilterRequest request)
AmazonPersonalizeAsyncDeletes a filter.
deleteFilterAsync in interface AmazonPersonalizeAsyncpublic Future<DeleteFilterResult> deleteFilterAsync(DeleteFilterRequest request, AsyncHandler<DeleteFilterRequest,DeleteFilterResult> asyncHandler)
AmazonPersonalizeAsyncDeletes a filter.
deleteFilterAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteMetricAttributionResult> deleteMetricAttributionAsync(DeleteMetricAttributionRequest request)
AmazonPersonalizeAsyncDeletes a metric attribution.
deleteMetricAttributionAsync in interface AmazonPersonalizeAsyncpublic Future<DeleteMetricAttributionResult> deleteMetricAttributionAsync(DeleteMetricAttributionRequest request, AsyncHandler<DeleteMetricAttributionRequest,DeleteMetricAttributionResult> asyncHandler)
AmazonPersonalizeAsyncDeletes a metric attribution.
deleteMetricAttributionAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteRecommenderResult> deleteRecommenderAsync(DeleteRecommenderRequest request)
AmazonPersonalizeAsyncDeactivates and removes a recommender. A deleted recommender can no longer be specified in a GetRecommendations request.
deleteRecommenderAsync in interface AmazonPersonalizeAsyncpublic Future<DeleteRecommenderResult> deleteRecommenderAsync(DeleteRecommenderRequest request, AsyncHandler<DeleteRecommenderRequest,DeleteRecommenderResult> asyncHandler)
AmazonPersonalizeAsyncDeactivates and removes a recommender. A deleted recommender can no longer be specified in a GetRecommendations request.
deleteRecommenderAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteSchemaResult> deleteSchemaAsync(DeleteSchemaRequest request)
AmazonPersonalizeAsyncDeletes a schema. Before deleting a schema, you must delete all datasets referencing the schema. For more information on schemas, see CreateSchema.
deleteSchemaAsync in interface AmazonPersonalizeAsyncpublic Future<DeleteSchemaResult> deleteSchemaAsync(DeleteSchemaRequest request, AsyncHandler<DeleteSchemaRequest,DeleteSchemaResult> asyncHandler)
AmazonPersonalizeAsyncDeletes a schema. Before deleting a schema, you must delete all datasets referencing the schema. For more information on schemas, see CreateSchema.
deleteSchemaAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteSolutionResult> deleteSolutionAsync(DeleteSolutionRequest request)
AmazonPersonalizeAsync
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.
deleteSolutionAsync in interface AmazonPersonalizeAsyncpublic Future<DeleteSolutionResult> deleteSolutionAsync(DeleteSolutionRequest request, AsyncHandler<DeleteSolutionRequest,DeleteSolutionResult> asyncHandler)
AmazonPersonalizeAsync
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.
deleteSolutionAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeAlgorithmResult> describeAlgorithmAsync(DescribeAlgorithmRequest request)
AmazonPersonalizeAsyncDescribes the given algorithm.
describeAlgorithmAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeAlgorithmResult> describeAlgorithmAsync(DescribeAlgorithmRequest request, AsyncHandler<DescribeAlgorithmRequest,DescribeAlgorithmResult> asyncHandler)
AmazonPersonalizeAsyncDescribes the given algorithm.
describeAlgorithmAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeBatchInferenceJobResult> describeBatchInferenceJobAsync(DescribeBatchInferenceJobRequest request)
AmazonPersonalizeAsyncGets 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.
describeBatchInferenceJobAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeBatchInferenceJobResult> describeBatchInferenceJobAsync(DescribeBatchInferenceJobRequest request, AsyncHandler<DescribeBatchInferenceJobRequest,DescribeBatchInferenceJobResult> asyncHandler)
AmazonPersonalizeAsyncGets 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.
describeBatchInferenceJobAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeBatchSegmentJobResult> describeBatchSegmentJobAsync(DescribeBatchSegmentJobRequest request)
AmazonPersonalizeAsyncGets 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.
describeBatchSegmentJobAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeBatchSegmentJobResult> describeBatchSegmentJobAsync(DescribeBatchSegmentJobRequest request, AsyncHandler<DescribeBatchSegmentJobRequest,DescribeBatchSegmentJobResult> asyncHandler)
AmazonPersonalizeAsyncGets 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.
describeBatchSegmentJobAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeCampaignResult> describeCampaignAsync(DescribeCampaignRequest request)
AmazonPersonalizeAsyncDescribes 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.
describeCampaignAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeCampaignResult> describeCampaignAsync(DescribeCampaignRequest request, AsyncHandler<DescribeCampaignRequest,DescribeCampaignResult> asyncHandler)
AmazonPersonalizeAsyncDescribes 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.
describeCampaignAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeDataDeletionJobResult> describeDataDeletionJobAsync(DescribeDataDeletionJobRequest request)
AmazonPersonalizeAsyncDescribes the data deletion job created by CreateDataDeletionJob, including the job status.
describeDataDeletionJobAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeDataDeletionJobResult> describeDataDeletionJobAsync(DescribeDataDeletionJobRequest request, AsyncHandler<DescribeDataDeletionJobRequest,DescribeDataDeletionJobResult> asyncHandler)
AmazonPersonalizeAsyncDescribes the data deletion job created by CreateDataDeletionJob, including the job status.
describeDataDeletionJobAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeDatasetResult> describeDatasetAsync(DescribeDatasetRequest request)
AmazonPersonalizeAsyncDescribes the given dataset. For more information on datasets, see CreateDataset.
describeDatasetAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeDatasetResult> describeDatasetAsync(DescribeDatasetRequest request, AsyncHandler<DescribeDatasetRequest,DescribeDatasetResult> asyncHandler)
AmazonPersonalizeAsyncDescribes the given dataset. For more information on datasets, see CreateDataset.
describeDatasetAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeDatasetExportJobResult> describeDatasetExportJobAsync(DescribeDatasetExportJobRequest request)
AmazonPersonalizeAsyncDescribes the dataset export job created by CreateDatasetExportJob, including the export job status.
describeDatasetExportJobAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeDatasetExportJobResult> describeDatasetExportJobAsync(DescribeDatasetExportJobRequest request, AsyncHandler<DescribeDatasetExportJobRequest,DescribeDatasetExportJobResult> asyncHandler)
AmazonPersonalizeAsyncDescribes the dataset export job created by CreateDatasetExportJob, including the export job status.
describeDatasetExportJobAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeDatasetGroupResult> describeDatasetGroupAsync(DescribeDatasetGroupRequest request)
AmazonPersonalizeAsyncDescribes the given dataset group. For more information on dataset groups, see CreateDatasetGroup.
describeDatasetGroupAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeDatasetGroupResult> describeDatasetGroupAsync(DescribeDatasetGroupRequest request, AsyncHandler<DescribeDatasetGroupRequest,DescribeDatasetGroupResult> asyncHandler)
AmazonPersonalizeAsyncDescribes the given dataset group. For more information on dataset groups, see CreateDatasetGroup.
describeDatasetGroupAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeDatasetImportJobResult> describeDatasetImportJobAsync(DescribeDatasetImportJobRequest request)
AmazonPersonalizeAsyncDescribes the dataset import job created by CreateDatasetImportJob, including the import job status.
describeDatasetImportJobAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeDatasetImportJobResult> describeDatasetImportJobAsync(DescribeDatasetImportJobRequest request, AsyncHandler<DescribeDatasetImportJobRequest,DescribeDatasetImportJobResult> asyncHandler)
AmazonPersonalizeAsyncDescribes the dataset import job created by CreateDatasetImportJob, including the import job status.
describeDatasetImportJobAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeEventTrackerResult> describeEventTrackerAsync(DescribeEventTrackerRequest request)
AmazonPersonalizeAsync
Describes an event tracker. The response includes the trackingId and status of the
event tracker. For more information on event trackers, see CreateEventTracker.
describeEventTrackerAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeEventTrackerResult> describeEventTrackerAsync(DescribeEventTrackerRequest request, AsyncHandler<DescribeEventTrackerRequest,DescribeEventTrackerResult> asyncHandler)
AmazonPersonalizeAsync
Describes an event tracker. The response includes the trackingId and status of the
event tracker. For more information on event trackers, see CreateEventTracker.
describeEventTrackerAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeFeatureTransformationResult> describeFeatureTransformationAsync(DescribeFeatureTransformationRequest request)
AmazonPersonalizeAsyncDescribes the given feature transformation.
describeFeatureTransformationAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeFeatureTransformationResult> describeFeatureTransformationAsync(DescribeFeatureTransformationRequest request, AsyncHandler<DescribeFeatureTransformationRequest,DescribeFeatureTransformationResult> asyncHandler)
AmazonPersonalizeAsyncDescribes the given feature transformation.
describeFeatureTransformationAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeFilterResult> describeFilterAsync(DescribeFilterRequest request)
AmazonPersonalizeAsyncDescribes a filter's properties.
describeFilterAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeFilterResult> describeFilterAsync(DescribeFilterRequest request, AsyncHandler<DescribeFilterRequest,DescribeFilterResult> asyncHandler)
AmazonPersonalizeAsyncDescribes a filter's properties.
describeFilterAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeMetricAttributionResult> describeMetricAttributionAsync(DescribeMetricAttributionRequest request)
AmazonPersonalizeAsyncDescribes a metric attribution.
describeMetricAttributionAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeMetricAttributionResult> describeMetricAttributionAsync(DescribeMetricAttributionRequest request, AsyncHandler<DescribeMetricAttributionRequest,DescribeMetricAttributionResult> asyncHandler)
AmazonPersonalizeAsyncDescribes a metric attribution.
describeMetricAttributionAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeRecipeResult> describeRecipeAsync(DescribeRecipeRequest request)
AmazonPersonalizeAsyncDescribes 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.
describeRecipeAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeRecipeResult> describeRecipeAsync(DescribeRecipeRequest request, AsyncHandler<DescribeRecipeRequest,DescribeRecipeResult> asyncHandler)
AmazonPersonalizeAsyncDescribes 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.
describeRecipeAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeRecommenderResult> describeRecommenderAsync(DescribeRecommenderRequest request)
AmazonPersonalizeAsyncDescribes 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.
describeRecommenderAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeRecommenderResult> describeRecommenderAsync(DescribeRecommenderRequest request, AsyncHandler<DescribeRecommenderRequest,DescribeRecommenderResult> asyncHandler)
AmazonPersonalizeAsyncDescribes 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.
describeRecommenderAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeSchemaResult> describeSchemaAsync(DescribeSchemaRequest request)
AmazonPersonalizeAsyncDescribes a schema. For more information on schemas, see CreateSchema.
describeSchemaAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeSchemaResult> describeSchemaAsync(DescribeSchemaRequest request, AsyncHandler<DescribeSchemaRequest,DescribeSchemaResult> asyncHandler)
AmazonPersonalizeAsyncDescribes a schema. For more information on schemas, see CreateSchema.
describeSchemaAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeSolutionResult> describeSolutionAsync(DescribeSolutionRequest request)
AmazonPersonalizeAsyncDescribes a solution. For more information on solutions, see CreateSolution.
describeSolutionAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeSolutionResult> describeSolutionAsync(DescribeSolutionRequest request, AsyncHandler<DescribeSolutionRequest,DescribeSolutionResult> asyncHandler)
AmazonPersonalizeAsyncDescribes a solution. For more information on solutions, see CreateSolution.
describeSolutionAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeSolutionVersionResult> describeSolutionVersionAsync(DescribeSolutionVersionRequest request)
AmazonPersonalizeAsyncDescribes a specific version of a solution. For more information on solutions, see CreateSolution
describeSolutionVersionAsync in interface AmazonPersonalizeAsyncpublic Future<DescribeSolutionVersionResult> describeSolutionVersionAsync(DescribeSolutionVersionRequest request, AsyncHandler<DescribeSolutionVersionRequest,DescribeSolutionVersionResult> asyncHandler)
AmazonPersonalizeAsyncDescribes a specific version of a solution. For more information on solutions, see CreateSolution
describeSolutionVersionAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<GetSolutionMetricsResult> getSolutionMetricsAsync(GetSolutionMetricsRequest request)
AmazonPersonalizeAsyncGets the metrics for the specified solution version.
getSolutionMetricsAsync in interface AmazonPersonalizeAsyncpublic Future<GetSolutionMetricsResult> getSolutionMetricsAsync(GetSolutionMetricsRequest request, AsyncHandler<GetSolutionMetricsRequest,GetSolutionMetricsResult> asyncHandler)
AmazonPersonalizeAsyncGets the metrics for the specified solution version.
getSolutionMetricsAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListBatchInferenceJobsResult> listBatchInferenceJobsAsync(ListBatchInferenceJobsRequest request)
AmazonPersonalizeAsyncGets a list of the batch inference jobs that have been performed off of a solution version.
listBatchInferenceJobsAsync in interface AmazonPersonalizeAsyncpublic Future<ListBatchInferenceJobsResult> listBatchInferenceJobsAsync(ListBatchInferenceJobsRequest request, AsyncHandler<ListBatchInferenceJobsRequest,ListBatchInferenceJobsResult> asyncHandler)
AmazonPersonalizeAsyncGets a list of the batch inference jobs that have been performed off of a solution version.
listBatchInferenceJobsAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListBatchSegmentJobsResult> listBatchSegmentJobsAsync(ListBatchSegmentJobsRequest request)
AmazonPersonalizeAsyncGets a list of the batch segment jobs that have been performed off of a solution version that you specify.
listBatchSegmentJobsAsync in interface AmazonPersonalizeAsyncpublic Future<ListBatchSegmentJobsResult> listBatchSegmentJobsAsync(ListBatchSegmentJobsRequest request, AsyncHandler<ListBatchSegmentJobsRequest,ListBatchSegmentJobsResult> asyncHandler)
AmazonPersonalizeAsyncGets a list of the batch segment jobs that have been performed off of a solution version that you specify.
listBatchSegmentJobsAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListCampaignsResult> listCampaignsAsync(ListCampaignsRequest request)
AmazonPersonalizeAsyncReturns 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.
listCampaignsAsync in interface AmazonPersonalizeAsyncpublic Future<ListCampaignsResult> listCampaignsAsync(ListCampaignsRequest request, AsyncHandler<ListCampaignsRequest,ListCampaignsResult> asyncHandler)
AmazonPersonalizeAsyncReturns 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.
listCampaignsAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListDataDeletionJobsResult> listDataDeletionJobsAsync(ListDataDeletionJobsRequest request)
AmazonPersonalizeAsyncReturns 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.
listDataDeletionJobsAsync in interface AmazonPersonalizeAsyncpublic Future<ListDataDeletionJobsResult> listDataDeletionJobsAsync(ListDataDeletionJobsRequest request, AsyncHandler<ListDataDeletionJobsRequest,ListDataDeletionJobsResult> asyncHandler)
AmazonPersonalizeAsyncReturns 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.
listDataDeletionJobsAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListDatasetExportJobsResult> listDatasetExportJobsAsync(ListDatasetExportJobsRequest request)
AmazonPersonalizeAsyncReturns 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.
listDatasetExportJobsAsync in interface AmazonPersonalizeAsyncpublic Future<ListDatasetExportJobsResult> listDatasetExportJobsAsync(ListDatasetExportJobsRequest request, AsyncHandler<ListDatasetExportJobsRequest,ListDatasetExportJobsResult> asyncHandler)
AmazonPersonalizeAsyncReturns 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.
listDatasetExportJobsAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListDatasetGroupsResult> listDatasetGroupsAsync(ListDatasetGroupsRequest request)
AmazonPersonalizeAsyncReturns 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.
listDatasetGroupsAsync in interface AmazonPersonalizeAsyncpublic Future<ListDatasetGroupsResult> listDatasetGroupsAsync(ListDatasetGroupsRequest request, AsyncHandler<ListDatasetGroupsRequest,ListDatasetGroupsResult> asyncHandler)
AmazonPersonalizeAsyncReturns 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.
listDatasetGroupsAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListDatasetImportJobsResult> listDatasetImportJobsAsync(ListDatasetImportJobsRequest request)
AmazonPersonalizeAsyncReturns 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.
listDatasetImportJobsAsync in interface AmazonPersonalizeAsyncpublic Future<ListDatasetImportJobsResult> listDatasetImportJobsAsync(ListDatasetImportJobsRequest request, AsyncHandler<ListDatasetImportJobsRequest,ListDatasetImportJobsResult> asyncHandler)
AmazonPersonalizeAsyncReturns 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.
listDatasetImportJobsAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListDatasetsResult> listDatasetsAsync(ListDatasetsRequest request)
AmazonPersonalizeAsyncReturns 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.
listDatasetsAsync in interface AmazonPersonalizeAsyncpublic Future<ListDatasetsResult> listDatasetsAsync(ListDatasetsRequest request, AsyncHandler<ListDatasetsRequest,ListDatasetsResult> asyncHandler)
AmazonPersonalizeAsyncReturns 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.
listDatasetsAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListEventTrackersResult> listEventTrackersAsync(ListEventTrackersRequest request)
AmazonPersonalizeAsyncReturns 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.
listEventTrackersAsync in interface AmazonPersonalizeAsyncpublic Future<ListEventTrackersResult> listEventTrackersAsync(ListEventTrackersRequest request, AsyncHandler<ListEventTrackersRequest,ListEventTrackersResult> asyncHandler)
AmazonPersonalizeAsyncReturns 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.
listEventTrackersAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListFiltersResult> listFiltersAsync(ListFiltersRequest request)
AmazonPersonalizeAsyncLists all filters that belong to a given dataset group.
listFiltersAsync in interface AmazonPersonalizeAsyncpublic Future<ListFiltersResult> listFiltersAsync(ListFiltersRequest request, AsyncHandler<ListFiltersRequest,ListFiltersResult> asyncHandler)
AmazonPersonalizeAsyncLists all filters that belong to a given dataset group.
listFiltersAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListMetricAttributionMetricsResult> listMetricAttributionMetricsAsync(ListMetricAttributionMetricsRequest request)
AmazonPersonalizeAsyncLists the metrics for the metric attribution.
listMetricAttributionMetricsAsync in interface AmazonPersonalizeAsyncpublic Future<ListMetricAttributionMetricsResult> listMetricAttributionMetricsAsync(ListMetricAttributionMetricsRequest request, AsyncHandler<ListMetricAttributionMetricsRequest,ListMetricAttributionMetricsResult> asyncHandler)
AmazonPersonalizeAsyncLists the metrics for the metric attribution.
listMetricAttributionMetricsAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListMetricAttributionsResult> listMetricAttributionsAsync(ListMetricAttributionsRequest request)
AmazonPersonalizeAsyncLists metric attributions.
listMetricAttributionsAsync in interface AmazonPersonalizeAsyncpublic Future<ListMetricAttributionsResult> listMetricAttributionsAsync(ListMetricAttributionsRequest request, AsyncHandler<ListMetricAttributionsRequest,ListMetricAttributionsResult> asyncHandler)
AmazonPersonalizeAsyncLists metric attributions.
listMetricAttributionsAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListRecipesResult> listRecipesAsync(ListRecipesRequest request)
AmazonPersonalizeAsyncReturns a list of available recipes. The response provides the properties for each recipe, including the recipe's Amazon Resource Name (ARN).
listRecipesAsync in interface AmazonPersonalizeAsyncpublic Future<ListRecipesResult> listRecipesAsync(ListRecipesRequest request, AsyncHandler<ListRecipesRequest,ListRecipesResult> asyncHandler)
AmazonPersonalizeAsyncReturns a list of available recipes. The response provides the properties for each recipe, including the recipe's Amazon Resource Name (ARN).
listRecipesAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListRecommendersResult> listRecommendersAsync(ListRecommendersRequest request)
AmazonPersonalizeAsyncReturns 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.
listRecommendersAsync in interface AmazonPersonalizeAsyncpublic Future<ListRecommendersResult> listRecommendersAsync(ListRecommendersRequest request, AsyncHandler<ListRecommendersRequest,ListRecommendersResult> asyncHandler)
AmazonPersonalizeAsyncReturns 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.
listRecommendersAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListSchemasResult> listSchemasAsync(ListSchemasRequest request)
AmazonPersonalizeAsyncReturns 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.
listSchemasAsync in interface AmazonPersonalizeAsyncpublic Future<ListSchemasResult> listSchemasAsync(ListSchemasRequest request, AsyncHandler<ListSchemasRequest,ListSchemasResult> asyncHandler)
AmazonPersonalizeAsyncReturns 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.
listSchemasAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListSolutionVersionsResult> listSolutionVersionsAsync(ListSolutionVersionsRequest request)
AmazonPersonalizeAsyncReturns 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).
listSolutionVersionsAsync in interface AmazonPersonalizeAsyncpublic Future<ListSolutionVersionsResult> listSolutionVersionsAsync(ListSolutionVersionsRequest request, AsyncHandler<ListSolutionVersionsRequest,ListSolutionVersionsResult> asyncHandler)
AmazonPersonalizeAsyncReturns 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).
listSolutionVersionsAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListSolutionsResult> listSolutionsAsync(ListSolutionsRequest request)
AmazonPersonalizeAsyncReturns 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.
listSolutionsAsync in interface AmazonPersonalizeAsyncpublic Future<ListSolutionsResult> listSolutionsAsync(ListSolutionsRequest request, AsyncHandler<ListSolutionsRequest,ListSolutionsResult> asyncHandler)
AmazonPersonalizeAsyncReturns 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.
listSolutionsAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListTagsForResourceResult> listTagsForResourceAsync(ListTagsForResourceRequest request)
AmazonPersonalizeAsyncGet a list of tags attached to a resource.
listTagsForResourceAsync in interface AmazonPersonalizeAsyncpublic Future<ListTagsForResourceResult> listTagsForResourceAsync(ListTagsForResourceRequest request, AsyncHandler<ListTagsForResourceRequest,ListTagsForResourceResult> asyncHandler)
AmazonPersonalizeAsyncGet a list of tags attached to a resource.
listTagsForResourceAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StartRecommenderResult> startRecommenderAsync(StartRecommenderRequest request)
AmazonPersonalizeAsyncStarts a recommender that is INACTIVE. Starting a recommender does not create any new models, but resumes billing and automatic retraining for the recommender.
startRecommenderAsync in interface AmazonPersonalizeAsyncpublic Future<StartRecommenderResult> startRecommenderAsync(StartRecommenderRequest request, AsyncHandler<StartRecommenderRequest,StartRecommenderResult> asyncHandler)
AmazonPersonalizeAsyncStarts a recommender that is INACTIVE. Starting a recommender does not create any new models, but resumes billing and automatic retraining for the recommender.
startRecommenderAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StopRecommenderResult> stopRecommenderAsync(StopRecommenderRequest request)
AmazonPersonalizeAsyncStops a recommender that is ACTIVE. Stopping a recommender halts billing and automatic retraining for the recommender.
stopRecommenderAsync in interface AmazonPersonalizeAsyncpublic Future<StopRecommenderResult> stopRecommenderAsync(StopRecommenderRequest request, AsyncHandler<StopRecommenderRequest,StopRecommenderResult> asyncHandler)
AmazonPersonalizeAsyncStops a recommender that is ACTIVE. Stopping a recommender halts billing and automatic retraining for the recommender.
stopRecommenderAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StopSolutionVersionCreationResult> stopSolutionVersionCreationAsync(StopSolutionVersionCreationRequest request)
AmazonPersonalizeAsyncStops 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.
stopSolutionVersionCreationAsync in interface AmazonPersonalizeAsyncpublic Future<StopSolutionVersionCreationResult> stopSolutionVersionCreationAsync(StopSolutionVersionCreationRequest request, AsyncHandler<StopSolutionVersionCreationRequest,StopSolutionVersionCreationResult> asyncHandler)
AmazonPersonalizeAsyncStops 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.
stopSolutionVersionCreationAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<TagResourceResult> tagResourceAsync(TagResourceRequest request)
AmazonPersonalizeAsyncAdd a list of tags to a resource.
tagResourceAsync in interface AmazonPersonalizeAsyncpublic Future<TagResourceResult> tagResourceAsync(TagResourceRequest request, AsyncHandler<TagResourceRequest,TagResourceResult> asyncHandler)
AmazonPersonalizeAsyncAdd a list of tags to a resource.
tagResourceAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UntagResourceResult> untagResourceAsync(UntagResourceRequest request)
AmazonPersonalizeAsyncRemoves the specified tags that are attached to a resource. For more information, see Removing tags from Amazon Personalize resources.
untagResourceAsync in interface AmazonPersonalizeAsyncpublic Future<UntagResourceResult> untagResourceAsync(UntagResourceRequest request, AsyncHandler<UntagResourceRequest,UntagResourceResult> asyncHandler)
AmazonPersonalizeAsyncRemoves the specified tags that are attached to a resource. For more information, see Removing tags from Amazon Personalize resources.
untagResourceAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateCampaignResult> updateCampaignAsync(UpdateCampaignRequest request)
AmazonPersonalizeAsync
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/$LATEST format.
In the campaignConfig, set syncWithLatestSolutionVersion to true.
To update a campaign, the campaign status must be ACTIVE or CREATE FAILED. Check the campaign status using the DescribeCampaign operation.
You can still get recommendations from a campaign while an update is in progress. The campaign will use the
previous solution version and campaign configuration to generate recommendations until the latest campaign update
status is Active.
For more information about updating a campaign, including code samples, see Updating a campaign. For more information about campaigns, see Creating a campaign.
updateCampaignAsync in interface AmazonPersonalizeAsyncpublic Future<UpdateCampaignResult> updateCampaignAsync(UpdateCampaignRequest request, AsyncHandler<UpdateCampaignRequest,UpdateCampaignResult> asyncHandler)
AmazonPersonalizeAsync
Updates a campaign to deploy a retrained solution version with an existing campaign, change your campaign's
minProvisionedTPS, or modify your campaign's configuration. For example, you can set
enableMetadataWithRecommendations to true for an existing campaign.
To update a campaign to start automatically using the latest solution version, specify the following:
For the SolutionVersionArn parameter, specify the Amazon Resource Name (ARN) of your solution in
SolutionArn/$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.
updateCampaignAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateDatasetResult> updateDatasetAsync(UpdateDatasetRequest request)
AmazonPersonalizeAsyncUpdate a dataset to replace its schema with a new or existing one. For more information, see Replacing a dataset's schema.
updateDatasetAsync in interface AmazonPersonalizeAsyncpublic Future<UpdateDatasetResult> updateDatasetAsync(UpdateDatasetRequest request, AsyncHandler<UpdateDatasetRequest,UpdateDatasetResult> asyncHandler)
AmazonPersonalizeAsyncUpdate a dataset to replace its schema with a new or existing one. For more information, see Replacing a dataset's schema.
updateDatasetAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateMetricAttributionResult> updateMetricAttributionAsync(UpdateMetricAttributionRequest request)
AmazonPersonalizeAsyncUpdates a metric attribution.
updateMetricAttributionAsync in interface AmazonPersonalizeAsyncpublic Future<UpdateMetricAttributionResult> updateMetricAttributionAsync(UpdateMetricAttributionRequest request, AsyncHandler<UpdateMetricAttributionRequest,UpdateMetricAttributionResult> asyncHandler)
AmazonPersonalizeAsyncUpdates a metric attribution.
updateMetricAttributionAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateRecommenderResult> updateRecommenderAsync(UpdateRecommenderRequest request)
AmazonPersonalizeAsync
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.
updateRecommenderAsync in interface AmazonPersonalizeAsyncpublic Future<UpdateRecommenderResult> updateRecommenderAsync(UpdateRecommenderRequest request, AsyncHandler<UpdateRecommenderRequest,UpdateRecommenderResult> asyncHandler)
AmazonPersonalizeAsync
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.
updateRecommenderAsync in interface AmazonPersonalizeAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public void shutdown()
getExecutorService().shutdown() followed by getExecutorService().awaitTermination() prior to
calling this method.shutdown in interface AmazonPersonalizeshutdown in class AmazonPersonalizeClient