@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public interface AmazonPersonalizeAsync extends AmazonPersonalize
AsyncHandler can be used to receive
notification when an asynchronous operation completes.
Note: Do not directly implement this interface, new methods are added to it regularly. Extend from
AbstractAmazonPersonalizeAsync instead.
Amazon Personalize is a machine learning service that makes it easy to add individualized recommendations to customers.
ENDPOINT_PREFIXcreateBatchInferenceJob, createBatchSegmentJob, createCampaign, createDataset, createDatasetExportJob, createDatasetGroup, createDatasetImportJob, createEventTracker, createFilter, createMetricAttribution, createRecommender, createSchema, createSolution, createSolutionVersion, deleteCampaign, deleteDataset, deleteDatasetGroup, deleteEventTracker, deleteFilter, deleteMetricAttribution, deleteRecommender, deleteSchema, deleteSolution, describeAlgorithm, describeBatchInferenceJob, describeBatchSegmentJob, describeCampaign, describeDataset, describeDatasetExportJob, describeDatasetGroup, describeDatasetImportJob, describeEventTracker, describeFeatureTransformation, describeFilter, describeMetricAttribution, describeRecipe, describeRecommender, describeSchema, describeSolution, describeSolutionVersion, getCachedResponseMetadata, getSolutionMetrics, listBatchInferenceJobs, listBatchSegmentJobs, listCampaigns, listDatasetExportJobs, listDatasetGroups, listDatasetImportJobs, listDatasets, listEventTrackers, listFilters, listMetricAttributionMetrics, listMetricAttributions, listRecipes, listRecommenders, listSchemas, listSolutions, listSolutionVersions, listTagsForResource, shutdown, startRecommender, stopRecommender, stopSolutionVersionCreation, tagResource, untagResource, updateCampaign, updateDataset, updateMetricAttribution, updateRecommenderFuture<CreateBatchInferenceJobResult> createBatchInferenceJobAsync(CreateBatchInferenceJobRequest createBatchInferenceJobRequest)
Generates batch recommendations based on a list of items or users stored in Amazon S3 and exports the recommendations to an Amazon S3 bucket.
To generate batch recommendations, specify the ARN of a solution version and an Amazon S3 URI for the input and output data. For user personalization, popular items, and personalized ranking solutions, the batch inference job generates a list of recommended items for each user ID in the input file. For related items solutions, the job generates a list of recommended items for each item ID in the input file.
For more information, see Creating a batch inference job .
If you use the Similar-Items recipe, Amazon Personalize can add descriptive themes to batch recommendations. To
generate themes, set the job's mode to THEME_GENERATION and specify the name of the field that
contains item names in the input data.
For more information about generating themes, see Batch recommendations with themes from Content Generator .
You can't get batch recommendations with the Trending-Now or Next-Best-Action recipes.
createBatchInferenceJobRequest - Future<CreateBatchInferenceJobResult> createBatchInferenceJobAsync(CreateBatchInferenceJobRequest createBatchInferenceJobRequest, AsyncHandler<CreateBatchInferenceJobRequest,CreateBatchInferenceJobResult> asyncHandler)
Generates batch recommendations based on a list of items or users stored in Amazon S3 and exports the recommendations to an Amazon S3 bucket.
To generate batch recommendations, specify the ARN of a solution version and an Amazon S3 URI for the input and output data. For user personalization, popular items, and personalized ranking solutions, the batch inference job generates a list of recommended items for each user ID in the input file. For related items solutions, the job generates a list of recommended items for each item ID in the input file.
For more information, see Creating a batch inference job .
If you use the Similar-Items recipe, Amazon Personalize can add descriptive themes to batch recommendations. To
generate themes, set the job's mode to THEME_GENERATION and specify the name of the field that
contains item names in the input data.
For more information about generating themes, see Batch recommendations with themes from Content Generator .
You can't get batch recommendations with the Trending-Now or Next-Best-Action recipes.
createBatchInferenceJobRequest - asyncHandler - 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.Future<CreateBatchSegmentJobResult> createBatchSegmentJobAsync(CreateBatchSegmentJobRequest createBatchSegmentJobRequest)
Creates a batch segment job. The operation can handle up to 50 million records and the input file must be in JSON format. For more information, see Getting batch recommendations and user segments.
createBatchSegmentJobRequest - Future<CreateBatchSegmentJobResult> createBatchSegmentJobAsync(CreateBatchSegmentJobRequest createBatchSegmentJobRequest, AsyncHandler<CreateBatchSegmentJobRequest,CreateBatchSegmentJobResult> asyncHandler)
Creates a batch segment job. The operation can handle up to 50 million records and the input file must be in JSON format. For more information, see Getting batch recommendations and user segments.
createBatchSegmentJobRequest - asyncHandler - 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.Future<CreateCampaignResult> createCampaignAsync(CreateCampaignRequest createCampaignRequest)
Creates a campaign that deploys a solution version. When a client calls the GetRecommendations and GetPersonalizedRanking APIs, a campaign is specified in the request.
Minimum Provisioned TPS and Auto-Scaling
A high minProvisionedTPS will increase your bill. We recommend starting with 1 for
minProvisionedTPS (the default). Track your usage using Amazon CloudWatch metrics, and increase the
minProvisionedTPS as necessary.
A transaction is a single GetRecommendations or GetPersonalizedRanking call.
Transactions per second (TPS) is the throughput and unit of billing for Amazon Personalize. The minimum
provisioned TPS (minProvisionedTPS) specifies the baseline throughput provisioned by Amazon
Personalize, and thus, the minimum billing charge.
If your TPS increases beyond minProvisionedTPS, Amazon Personalize auto-scales the provisioned
capacity up and down, but never below minProvisionedTPS. There's a short time delay while the
capacity is increased that might cause loss of transactions.
The actual TPS used is calculated as the average requests/second within a 5-minute window. You pay for maximum of
either the minimum provisioned TPS or the actual TPS. We recommend starting with a low
minProvisionedTPS, track your usage using Amazon CloudWatch metrics, and then increase the
minProvisionedTPS as necessary.
Status
A campaign can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
To get the campaign status, call DescribeCampaign.
Wait until the status of the campaign is ACTIVE before asking the campaign for
recommendations.
Related APIs
createCampaignRequest - Future<CreateCampaignResult> createCampaignAsync(CreateCampaignRequest createCampaignRequest, AsyncHandler<CreateCampaignRequest,CreateCampaignResult> asyncHandler)
Creates a campaign that deploys a solution version. When a client calls the GetRecommendations and GetPersonalizedRanking APIs, a campaign is specified in the request.
Minimum Provisioned TPS and Auto-Scaling
A high minProvisionedTPS will increase your bill. We recommend starting with 1 for
minProvisionedTPS (the default). Track your usage using Amazon CloudWatch metrics, and increase the
minProvisionedTPS as necessary.
A transaction is a single GetRecommendations or GetPersonalizedRanking call.
Transactions per second (TPS) is the throughput and unit of billing for Amazon Personalize. The minimum
provisioned TPS (minProvisionedTPS) specifies the baseline throughput provisioned by Amazon
Personalize, and thus, the minimum billing charge.
If your TPS increases beyond minProvisionedTPS, Amazon Personalize auto-scales the provisioned
capacity up and down, but never below minProvisionedTPS. There's a short time delay while the
capacity is increased that might cause loss of transactions.
The actual TPS used is calculated as the average requests/second within a 5-minute window. You pay for maximum of
either the minimum provisioned TPS or the actual TPS. We recommend starting with a low
minProvisionedTPS, track your usage using Amazon CloudWatch metrics, and then increase the
minProvisionedTPS as necessary.
Status
A campaign can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
To get the campaign status, call DescribeCampaign.
Wait until the status of the campaign is ACTIVE before asking the campaign for
recommendations.
Related APIs
createCampaignRequest - asyncHandler - 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.Future<CreateDatasetResult> createDatasetAsync(CreateDatasetRequest createDatasetRequest)
Creates an empty dataset and adds it to the specified dataset group. Use CreateDatasetImportJob to import your training data to a dataset.
There are 5 types of datasets:
Item interactions
Items
Users
Action interactions
Actions
Each dataset type has an associated schema with required field types. Only the Item interactions
dataset is required in order to train a model (also referred to as creating a solution).
A dataset can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
To get the status of the dataset, call DescribeDataset.
Related APIs
createDatasetRequest - Future<CreateDatasetResult> createDatasetAsync(CreateDatasetRequest createDatasetRequest, AsyncHandler<CreateDatasetRequest,CreateDatasetResult> asyncHandler)
Creates an empty dataset and adds it to the specified dataset group. Use CreateDatasetImportJob to import your training data to a dataset.
There are 5 types of datasets:
Item interactions
Items
Users
Action interactions
Actions
Each dataset type has an associated schema with required field types. Only the Item interactions
dataset is required in order to train a model (also referred to as creating a solution).
A dataset can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
To get the status of the dataset, call DescribeDataset.
Related APIs
createDatasetRequest - asyncHandler - 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.Future<CreateDatasetExportJobResult> createDatasetExportJobAsync(CreateDatasetExportJobRequest createDatasetExportJobRequest)
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.
createDatasetExportJobRequest - Future<CreateDatasetExportJobResult> createDatasetExportJobAsync(CreateDatasetExportJobRequest createDatasetExportJobRequest, AsyncHandler<CreateDatasetExportJobRequest,CreateDatasetExportJobResult> asyncHandler)
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.
createDatasetExportJobRequest - asyncHandler - 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.Future<CreateDatasetGroupResult> createDatasetGroupAsync(CreateDatasetGroupRequest createDatasetGroupRequest)
Creates an empty dataset group. A dataset group is a container for Amazon Personalize resources. A dataset group can contain at most three datasets, one for each type of dataset:
Item interactions
Items
Users
Actions
Action interactions
A dataset group can be a Domain dataset group, where you specify a domain and use pre-configured resources like recommenders, or a Custom dataset group, where you use custom resources, such as a solution with a solution version, that you deploy with a campaign. If you start with a Domain dataset group, you can still add custom resources such as solutions and solution versions trained with recipes for custom use cases and deployed with campaigns.
A dataset group can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING
To get the status of the dataset group, call DescribeDatasetGroup.
If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why
the creation failed.
You must wait until the status of the dataset group is ACTIVE before adding a dataset
to the group.
You can specify an Key Management Service (KMS) key to encrypt the datasets in the group. If you specify a KMS key, you must also include an Identity and Access Management (IAM) role that has permission to access the key.
APIs that require a dataset group ARN in the request
Related APIs
createDatasetGroupRequest - Future<CreateDatasetGroupResult> createDatasetGroupAsync(CreateDatasetGroupRequest createDatasetGroupRequest, AsyncHandler<CreateDatasetGroupRequest,CreateDatasetGroupResult> asyncHandler)
Creates an empty dataset group. A dataset group is a container for Amazon Personalize resources. A dataset group can contain at most three datasets, one for each type of dataset:
Item interactions
Items
Users
Actions
Action interactions
A dataset group can be a Domain dataset group, where you specify a domain and use pre-configured resources like recommenders, or a Custom dataset group, where you use custom resources, such as a solution with a solution version, that you deploy with a campaign. If you start with a Domain dataset group, you can still add custom resources such as solutions and solution versions trained with recipes for custom use cases and deployed with campaigns.
A dataset group can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING
To get the status of the dataset group, call DescribeDatasetGroup.
If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why
the creation failed.
You must wait until the status of the dataset group is ACTIVE before adding a dataset
to the group.
You can specify an Key Management Service (KMS) key to encrypt the datasets in the group. If you specify a KMS key, you must also include an Identity and Access Management (IAM) role that has permission to access the key.
APIs that require a dataset group ARN in the request
Related APIs
createDatasetGroupRequest - asyncHandler - 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.Future<CreateDatasetImportJobResult> createDatasetImportJobAsync(CreateDatasetImportJobRequest createDatasetImportJobRequest)
Creates a job that imports training data from your data source (an Amazon S3 bucket) to an Amazon Personalize dataset. To allow Amazon Personalize to ACTIVE -or- CREATE FAILED
To get the status of the import job, call DescribeDatasetImportJob, providing the Amazon Resource Name (ARN) of the dataset import job. The dataset
import is complete when the status shows as ACTIVE. If the status shows as CREATE FAILED, the response includes a
failureReason key, which describes why the job failed.
Importing takes time. You must wait until the status shows as ACTIVE before training a model using the dataset.
Related APIs
createDatasetImportJobRequest - Future<CreateDatasetImportJobResult> createDatasetImportJobAsync(CreateDatasetImportJobRequest createDatasetImportJobRequest, AsyncHandler<CreateDatasetImportJobRequest,CreateDatasetImportJobResult> asyncHandler)
Creates a job that imports training data from your data source (an Amazon S3 bucket) to an Amazon Personalize dataset. To allow Amazon Personalize to import the training data, you must specify an 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
createDatasetImportJobRequest - asyncHandler - 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.Future<CreateEventTrackerResult> createEventTrackerAsync(CreateEventTrackerRequest createEventTrackerRequest)
Creates an event tracker that you use when adding event data to a specified dataset group using the PutEvents API.
Only one event tracker can be associated with a dataset group. You will get an error if you call
CreateEventTracker using the same dataset group as an existing event tracker.
When you create an event tracker, the response includes a tracking ID, which you pass as a parameter when you use the PutEvents operation. Amazon Personalize then appends the event data to the Item interactions dataset of the dataset group you specify in your event tracker.
The event tracker can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
To get the status of the event tracker, call DescribeEventTracker.
The event tracker must be in the ACTIVE state before using the tracking ID.
Related APIs
createEventTrackerRequest - Future<CreateEventTrackerResult> createEventTrackerAsync(CreateEventTrackerRequest createEventTrackerRequest, AsyncHandler<CreateEventTrackerRequest,CreateEventTrackerResult> asyncHandler)
Creates an event tracker that you use when adding event data to a specified dataset group using the PutEvents API.
Only one event tracker can be associated with a dataset group. You will get an error if you call
CreateEventTracker using the same dataset group as an existing event tracker.
When you create an event tracker, the response includes a tracking ID, which you pass as a parameter when you use the PutEvents operation. Amazon Personalize then appends the event data to the Item interactions dataset of the dataset group you specify in your event tracker.
The event tracker can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
To get the status of the event tracker, call DescribeEventTracker.
The event tracker must be in the ACTIVE state before using the tracking ID.
Related APIs
createEventTrackerRequest - asyncHandler - 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.Future<CreateFilterResult> createFilterAsync(CreateFilterRequest createFilterRequest)
Creates a recommendation filter. For more information, see Filtering recommendations and user segments.
createFilterRequest - Future<CreateFilterResult> createFilterAsync(CreateFilterRequest createFilterRequest, AsyncHandler<CreateFilterRequest,CreateFilterResult> asyncHandler)
Creates a recommendation filter. For more information, see Filtering recommendations and user segments.
createFilterRequest - asyncHandler - 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.Future<CreateMetricAttributionResult> createMetricAttributionAsync(CreateMetricAttributionRequest createMetricAttributionRequest)
Creates a metric attribution. A metric attribution creates reports on the data that you import into Amazon Personalize. Depending on how you imported the data, you can view reports in Amazon CloudWatch or Amazon S3. For more information, see Measuring impact of recommendations.
createMetricAttributionRequest - Future<CreateMetricAttributionResult> createMetricAttributionAsync(CreateMetricAttributionRequest createMetricAttributionRequest, AsyncHandler<CreateMetricAttributionRequest,CreateMetricAttributionResult> asyncHandler)
Creates a metric attribution. A metric attribution creates reports on the data that you import into Amazon Personalize. Depending on how you imported the data, you can view reports in Amazon CloudWatch or Amazon S3. For more information, see Measuring impact of recommendations.
createMetricAttributionRequest - asyncHandler - 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.Future<CreateRecommenderResult> createRecommenderAsync(CreateRecommenderRequest createRecommenderRequest)
Creates a recommender with the recipe (a Domain dataset group use case) you specify. You create recommenders for a Domain dataset group and specify the recommender's Amazon Resource Name (ARN) when you make a GetRecommendations request.
Minimum recommendation requests per second
A high minRecommendationRequestsPerSecond will increase your bill. We recommend starting with 1 for
minRecommendationRequestsPerSecond (the default). Track your usage using Amazon CloudWatch metrics,
and increase the minRecommendationRequestsPerSecond as necessary.
When you create a recommender, you can configure the recommender's minimum recommendation requests per second.
The minimum recommendation requests per second (minRecommendationRequestsPerSecond) specifies the
baseline recommendation request throughput provisioned by Amazon Personalize. The default
minRecommendationRequestsPerSecond is 1. A recommendation request is a single
GetRecommendations operation. Request throughput is measured in requests per second and Amazon
Personalize uses your requests per second to derive your requests per hour and the price of your recommender
usage.
If your requests per second increases beyond minRecommendationRequestsPerSecond, Amazon Personalize
auto-scales the provisioned capacity up and down, but never below minRecommendationRequestsPerSecond
. There's a short time delay while the capacity is increased that might cause loss of requests.
Your bill is the greater of either the minimum requests per hour (based on minRecommendationRequestsPerSecond) or
the actual number of requests. The actual request throughput used is calculated as the average requests/second
within a one-hour window. We recommend starting with the default minRecommendationRequestsPerSecond,
track your usage using Amazon CloudWatch metrics, and then increase the
minRecommendationRequestsPerSecond as necessary.
Status
A recommender can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
DELETE PENDING > DELETE IN_PROGRESS
To get the recommender status, call DescribeRecommender.
Wait until the status of the recommender is ACTIVE before asking the recommender for
recommendations.
Related APIs
createRecommenderRequest - Future<CreateRecommenderResult> createRecommenderAsync(CreateRecommenderRequest createRecommenderRequest, AsyncHandler<CreateRecommenderRequest,CreateRecommenderResult> asyncHandler)
Creates a recommender with the recipe (a Domain dataset group use case) you specify. You create recommenders for a Domain dataset group and specify the recommender's Amazon Resource Name (ARN) when you make a GetRecommendations request.
Minimum recommendation requests per second
A high minRecommendationRequestsPerSecond will increase your bill. We recommend starting with 1 for
minRecommendationRequestsPerSecond (the default). Track your usage using Amazon CloudWatch metrics,
and increase the minRecommendationRequestsPerSecond as necessary.
When you create a recommender, you can configure the recommender's minimum recommendation requests per second.
The minimum recommendation requests per second (minRecommendationRequestsPerSecond) specifies the
baseline recommendation request throughput provisioned by Amazon Personalize. The default
minRecommendationRequestsPerSecond is 1. A recommendation request is a single
GetRecommendations operation. Request throughput is measured in requests per second and Amazon
Personalize uses your requests per second to derive your requests per hour and the price of your recommender
usage.
If your requests per second increases beyond minRecommendationRequestsPerSecond, Amazon Personalize
auto-scales the provisioned capacity up and down, but never below minRecommendationRequestsPerSecond
. There's a short time delay while the capacity is increased that might cause loss of requests.
Your bill is the greater of either the minimum requests per hour (based on minRecommendationRequestsPerSecond) or
the actual number of requests. The actual request throughput used is calculated as the average requests/second
within a one-hour window. We recommend starting with the default minRecommendationRequestsPerSecond,
track your usage using Amazon CloudWatch metrics, and then increase the
minRecommendationRequestsPerSecond as necessary.
Status
A recommender can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
DELETE PENDING > DELETE IN_PROGRESS
To get the recommender status, call DescribeRecommender.
Wait until the status of the recommender is ACTIVE before asking the recommender for
recommendations.
Related APIs
createRecommenderRequest - asyncHandler - 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.Future<CreateSchemaResult> createSchemaAsync(CreateSchemaRequest createSchemaRequest)
Creates an Amazon Personalize schema from the specified schema string. The schema you create must be in Avro JSON format.
Amazon Personalize recognizes three schema variants. Each schema is associated with a dataset type and has a set of required field and keywords. If you are creating a schema for a dataset in a Domain dataset group, you provide the domain of the Domain dataset group. You specify a schema when you call CreateDataset.
Related APIs
createSchemaRequest - Future<CreateSchemaResult> createSchemaAsync(CreateSchemaRequest createSchemaRequest, AsyncHandler<CreateSchemaRequest,CreateSchemaResult> asyncHandler)
Creates an Amazon Personalize schema from the specified schema string. The schema you create must be in Avro JSON format.
Amazon Personalize recognizes three schema variants. Each schema is associated with a dataset type and has a set of required field and keywords. If you are creating a schema for a dataset in a Domain dataset group, you provide the domain of the Domain dataset group. You specify a schema when you call CreateDataset.
Related APIs
createSchemaRequest - asyncHandler - 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.Future<CreateSolutionResult> createSolutionAsync(CreateSolutionRequest createSolutionRequest)
Creates the configuration for training a model. A trained model is known as a solution version. After the
configuration is created, you train the model (create a solution version) by calling the CreateSolutionVersion
operation. Every time you call CreateSolutionVersion, a new version of the solution is created.
After creating a solution version, you check its accuracy by calling GetSolutionMetrics. When you are satisfied with the version, you deploy it using CreateCampaign. The campaign provides recommendations to a client through the GetRecommendations API.
To train a model, Amazon Personalize requires training data and a recipe. The training data comes from the dataset group that you provide in the request. A recipe specifies the training algorithm and a feature transformation. You can specify one of the predefined recipes provided by Amazon Personalize.
Amazon Personalize doesn't support configuring the hpoObjective for solution hyperparameter
optimization at this time.
Status
A solution can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
To get the status of the solution, call DescribeSolution. Wait
until the status shows as ACTIVE before calling CreateSolutionVersion.
Related APIs
createSolutionRequest - Future<CreateSolutionResult> createSolutionAsync(CreateSolutionRequest createSolutionRequest, AsyncHandler<CreateSolutionRequest,CreateSolutionResult> asyncHandler)
Creates the configuration for training a model. A trained model is known as a solution version. After the
configuration is created, you train the model (create a solution version) by calling the CreateSolutionVersion
operation. Every time you call CreateSolutionVersion, a new version of the solution is created.
After creating a solution version, you check its accuracy by calling GetSolutionMetrics. When you are satisfied with the version, you deploy it using CreateCampaign. The campaign provides recommendations to a client through the GetRecommendations API.
To train a model, Amazon Personalize requires training data and a recipe. The training data comes from the dataset group that you provide in the request. A recipe specifies the training algorithm and a feature transformation. You can specify one of the predefined recipes provided by Amazon Personalize.
Amazon Personalize doesn't support configuring the hpoObjective for solution hyperparameter
optimization at this time.
Status
A solution can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
To get the status of the solution, call DescribeSolution. Wait
until the status shows as ACTIVE before calling CreateSolutionVersion.
Related APIs
createSolutionRequest - asyncHandler - 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.Future<CreateSolutionVersionResult> createSolutionVersionAsync(CreateSolutionVersionRequest createSolutionVersionRequest)
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
createSolutionVersionRequest - Future<CreateSolutionVersionResult> createSolutionVersionAsync(CreateSolutionVersionRequest createSolutionVersionRequest, AsyncHandler<CreateSolutionVersionRequest,CreateSolutionVersionResult> asyncHandler)
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
createSolutionVersionRequest - asyncHandler - 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.Future<DeleteCampaignResult> deleteCampaignAsync(DeleteCampaignRequest deleteCampaignRequest)
Removes a campaign by deleting the solution deployment. The solution that the campaign is based on is not deleted and can be redeployed when needed. A deleted campaign can no longer be specified in a GetRecommendations request. For information on creating campaigns, see CreateCampaign.
deleteCampaignRequest - Future<DeleteCampaignResult> deleteCampaignAsync(DeleteCampaignRequest deleteCampaignRequest, AsyncHandler<DeleteCampaignRequest,DeleteCampaignResult> asyncHandler)
Removes a campaign by deleting the solution deployment. The solution that the campaign is based on is not deleted and can be redeployed when needed. A deleted campaign can no longer be specified in a GetRecommendations request. For information on creating campaigns, see CreateCampaign.
deleteCampaignRequest - asyncHandler - 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.Future<DeleteDatasetResult> deleteDatasetAsync(DeleteDatasetRequest deleteDatasetRequest)
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.
deleteDatasetRequest - Future<DeleteDatasetResult> deleteDatasetAsync(DeleteDatasetRequest deleteDatasetRequest, AsyncHandler<DeleteDatasetRequest,DeleteDatasetResult> asyncHandler)
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.
deleteDatasetRequest - asyncHandler - 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.Future<DeleteDatasetGroupResult> deleteDatasetGroupAsync(DeleteDatasetGroupRequest deleteDatasetGroupRequest)
Deletes a dataset group. Before you delete a dataset group, you must delete the following:
All associated event trackers.
All associated solutions.
All datasets in the dataset group.
deleteDatasetGroupRequest - Future<DeleteDatasetGroupResult> deleteDatasetGroupAsync(DeleteDatasetGroupRequest deleteDatasetGroupRequest, AsyncHandler<DeleteDatasetGroupRequest,DeleteDatasetGroupResult> asyncHandler)
Deletes a dataset group. Before you delete a dataset group, you must delete the following:
All associated event trackers.
All associated solutions.
All datasets in the dataset group.
deleteDatasetGroupRequest - asyncHandler - 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.Future<DeleteEventTrackerResult> deleteEventTrackerAsync(DeleteEventTrackerRequest deleteEventTrackerRequest)
Deletes the event tracker. Does not delete the dataset from the dataset group. For more information on event trackers, see CreateEventTracker.
deleteEventTrackerRequest - Future<DeleteEventTrackerResult> deleteEventTrackerAsync(DeleteEventTrackerRequest deleteEventTrackerRequest, AsyncHandler<DeleteEventTrackerRequest,DeleteEventTrackerResult> asyncHandler)
Deletes the event tracker. Does not delete the dataset from the dataset group. For more information on event trackers, see CreateEventTracker.
deleteEventTrackerRequest - asyncHandler - 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.Future<DeleteFilterResult> deleteFilterAsync(DeleteFilterRequest deleteFilterRequest)
Deletes a filter.
deleteFilterRequest - Future<DeleteFilterResult> deleteFilterAsync(DeleteFilterRequest deleteFilterRequest, AsyncHandler<DeleteFilterRequest,DeleteFilterResult> asyncHandler)
Deletes a filter.
deleteFilterRequest - asyncHandler - 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.Future<DeleteMetricAttributionResult> deleteMetricAttributionAsync(DeleteMetricAttributionRequest deleteMetricAttributionRequest)
Deletes a metric attribution.
deleteMetricAttributionRequest - Future<DeleteMetricAttributionResult> deleteMetricAttributionAsync(DeleteMetricAttributionRequest deleteMetricAttributionRequest, AsyncHandler<DeleteMetricAttributionRequest,DeleteMetricAttributionResult> asyncHandler)
Deletes a metric attribution.
deleteMetricAttributionRequest - asyncHandler - 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.Future<DeleteRecommenderResult> deleteRecommenderAsync(DeleteRecommenderRequest deleteRecommenderRequest)
Deactivates and removes a recommender. A deleted recommender can no longer be specified in a GetRecommendations request.
deleteRecommenderRequest - Future<DeleteRecommenderResult> deleteRecommenderAsync(DeleteRecommenderRequest deleteRecommenderRequest, AsyncHandler<DeleteRecommenderRequest,DeleteRecommenderResult> asyncHandler)
Deactivates and removes a recommender. A deleted recommender can no longer be specified in a GetRecommendations request.
deleteRecommenderRequest - asyncHandler - 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.Future<DeleteSchemaResult> deleteSchemaAsync(DeleteSchemaRequest deleteSchemaRequest)
Deletes a schema. Before deleting a schema, you must delete all datasets referencing the schema. For more information on schemas, see CreateSchema.
deleteSchemaRequest - Future<DeleteSchemaResult> deleteSchemaAsync(DeleteSchemaRequest deleteSchemaRequest, AsyncHandler<DeleteSchemaRequest,DeleteSchemaResult> asyncHandler)
Deletes a schema. Before deleting a schema, you must delete all datasets referencing the schema. For more information on schemas, see CreateSchema.
deleteSchemaRequest - asyncHandler - 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.Future<DeleteSolutionResult> deleteSolutionAsync(DeleteSolutionRequest deleteSolutionRequest)
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.
deleteSolutionRequest - Future<DeleteSolutionResult> deleteSolutionAsync(DeleteSolutionRequest deleteSolutionRequest, AsyncHandler<DeleteSolutionRequest,DeleteSolutionResult> asyncHandler)
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.
deleteSolutionRequest - asyncHandler - 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.Future<DescribeAlgorithmResult> describeAlgorithmAsync(DescribeAlgorithmRequest describeAlgorithmRequest)
Describes the given algorithm.
describeAlgorithmRequest - Future<DescribeAlgorithmResult> describeAlgorithmAsync(DescribeAlgorithmRequest describeAlgorithmRequest, AsyncHandler<DescribeAlgorithmRequest,DescribeAlgorithmResult> asyncHandler)
Describes the given algorithm.
describeAlgorithmRequest - asyncHandler - 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.Future<DescribeBatchInferenceJobResult> describeBatchInferenceJobAsync(DescribeBatchInferenceJobRequest describeBatchInferenceJobRequest)
Gets the properties of a batch inference job including name, Amazon Resource Name (ARN), status, input and output configurations, and the ARN of the solution version used to generate the recommendations.
describeBatchInferenceJobRequest - Future<DescribeBatchInferenceJobResult> describeBatchInferenceJobAsync(DescribeBatchInferenceJobRequest describeBatchInferenceJobRequest, AsyncHandler<DescribeBatchInferenceJobRequest,DescribeBatchInferenceJobResult> asyncHandler)
Gets the properties of a batch inference job including name, Amazon Resource Name (ARN), status, input and output configurations, and the ARN of the solution version used to generate the recommendations.
describeBatchInferenceJobRequest - asyncHandler - 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.Future<DescribeBatchSegmentJobResult> describeBatchSegmentJobAsync(DescribeBatchSegmentJobRequest describeBatchSegmentJobRequest)
Gets the properties of a batch segment job including name, Amazon Resource Name (ARN), status, input and output configurations, and the ARN of the solution version used to generate segments.
describeBatchSegmentJobRequest - Future<DescribeBatchSegmentJobResult> describeBatchSegmentJobAsync(DescribeBatchSegmentJobRequest describeBatchSegmentJobRequest, AsyncHandler<DescribeBatchSegmentJobRequest,DescribeBatchSegmentJobResult> asyncHandler)
Gets the properties of a batch segment job including name, Amazon Resource Name (ARN), status, input and output configurations, and the ARN of the solution version used to generate segments.
describeBatchSegmentJobRequest - asyncHandler - 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.Future<DescribeCampaignResult> describeCampaignAsync(DescribeCampaignRequest describeCampaignRequest)
Describes the given campaign, including its status.
A campaign can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
When the status is CREATE FAILED, the response includes the failureReason
key, which describes why.
For more information on campaigns, see CreateCampaign.
describeCampaignRequest - Future<DescribeCampaignResult> describeCampaignAsync(DescribeCampaignRequest describeCampaignRequest, AsyncHandler<DescribeCampaignRequest,DescribeCampaignResult> asyncHandler)
Describes the given campaign, including its status.
A campaign can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
When the status is CREATE FAILED, the response includes the failureReason
key, which describes why.
For more information on campaigns, see CreateCampaign.
describeCampaignRequest - asyncHandler - 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.Future<DescribeDatasetResult> describeDatasetAsync(DescribeDatasetRequest describeDatasetRequest)
Describes the given dataset. For more information on datasets, see CreateDataset.
describeDatasetRequest - Future<DescribeDatasetResult> describeDatasetAsync(DescribeDatasetRequest describeDatasetRequest, AsyncHandler<DescribeDatasetRequest,DescribeDatasetResult> asyncHandler)
Describes the given dataset. For more information on datasets, see CreateDataset.
describeDatasetRequest - asyncHandler - 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.Future<DescribeDatasetExportJobResult> describeDatasetExportJobAsync(DescribeDatasetExportJobRequest describeDatasetExportJobRequest)
Describes the dataset export job created by CreateDatasetExportJob, including the export job status.
describeDatasetExportJobRequest - Future<DescribeDatasetExportJobResult> describeDatasetExportJobAsync(DescribeDatasetExportJobRequest describeDatasetExportJobRequest, AsyncHandler<DescribeDatasetExportJobRequest,DescribeDatasetExportJobResult> asyncHandler)
Describes the dataset export job created by CreateDatasetExportJob, including the export job status.
describeDatasetExportJobRequest - asyncHandler - 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.Future<DescribeDatasetGroupResult> describeDatasetGroupAsync(DescribeDatasetGroupRequest describeDatasetGroupRequest)
Describes the given dataset group. For more information on dataset groups, see CreateDatasetGroup.
describeDatasetGroupRequest - Future<DescribeDatasetGroupResult> describeDatasetGroupAsync(DescribeDatasetGroupRequest describeDatasetGroupRequest, AsyncHandler<DescribeDatasetGroupRequest,DescribeDatasetGroupResult> asyncHandler)
Describes the given dataset group. For more information on dataset groups, see CreateDatasetGroup.
describeDatasetGroupRequest - asyncHandler - 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.Future<DescribeDatasetImportJobResult> describeDatasetImportJobAsync(DescribeDatasetImportJobRequest describeDatasetImportJobRequest)
Describes the dataset import job created by CreateDatasetImportJob, including the import job status.
describeDatasetImportJobRequest - Future<DescribeDatasetImportJobResult> describeDatasetImportJobAsync(DescribeDatasetImportJobRequest describeDatasetImportJobRequest, AsyncHandler<DescribeDatasetImportJobRequest,DescribeDatasetImportJobResult> asyncHandler)
Describes the dataset import job created by CreateDatasetImportJob, including the import job status.
describeDatasetImportJobRequest - asyncHandler - 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.Future<DescribeEventTrackerResult> describeEventTrackerAsync(DescribeEventTrackerRequest describeEventTrackerRequest)
Describes an event tracker. The response includes the trackingId and status of the
event tracker. For more information on event trackers, see CreateEventTracker.
describeEventTrackerRequest - Future<DescribeEventTrackerResult> describeEventTrackerAsync(DescribeEventTrackerRequest describeEventTrackerRequest, AsyncHandler<DescribeEventTrackerRequest,DescribeEventTrackerResult> asyncHandler)
Describes an event tracker. The response includes the trackingId and status of the
event tracker. For more information on event trackers, see CreateEventTracker.
describeEventTrackerRequest - asyncHandler - 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.Future<DescribeFeatureTransformationResult> describeFeatureTransformationAsync(DescribeFeatureTransformationRequest describeFeatureTransformationRequest)
Describes the given feature transformation.
describeFeatureTransformationRequest - Future<DescribeFeatureTransformationResult> describeFeatureTransformationAsync(DescribeFeatureTransformationRequest describeFeatureTransformationRequest, AsyncHandler<DescribeFeatureTransformationRequest,DescribeFeatureTransformationResult> asyncHandler)
Describes the given feature transformation.
describeFeatureTransformationRequest - asyncHandler - 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.Future<DescribeFilterResult> describeFilterAsync(DescribeFilterRequest describeFilterRequest)
Describes a filter's properties.
describeFilterRequest - Future<DescribeFilterResult> describeFilterAsync(DescribeFilterRequest describeFilterRequest, AsyncHandler<DescribeFilterRequest,DescribeFilterResult> asyncHandler)
Describes a filter's properties.
describeFilterRequest - asyncHandler - 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.Future<DescribeMetricAttributionResult> describeMetricAttributionAsync(DescribeMetricAttributionRequest describeMetricAttributionRequest)
Describes a metric attribution.
describeMetricAttributionRequest - Future<DescribeMetricAttributionResult> describeMetricAttributionAsync(DescribeMetricAttributionRequest describeMetricAttributionRequest, AsyncHandler<DescribeMetricAttributionRequest,DescribeMetricAttributionResult> asyncHandler)
Describes a metric attribution.
describeMetricAttributionRequest - asyncHandler - 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.Future<DescribeRecipeResult> describeRecipeAsync(DescribeRecipeRequest describeRecipeRequest)
Describes a recipe.
A recipe contains three items:
An algorithm that trains a model.
Hyperparameters that govern the training.
Feature transformation information for modifying the input data before training.
Amazon Personalize provides a set of predefined recipes. You specify a recipe when you create a solution with the
CreateSolution API.
CreateSolution trains a model by using the algorithm in the specified recipe and a training dataset.
The solution, when deployed as a campaign, can provide recommendations using the GetRecommendations
API.
describeRecipeRequest - Future<DescribeRecipeResult> describeRecipeAsync(DescribeRecipeRequest describeRecipeRequest, AsyncHandler<DescribeRecipeRequest,DescribeRecipeResult> asyncHandler)
Describes a recipe.
A recipe contains three items:
An algorithm that trains a model.
Hyperparameters that govern the training.
Feature transformation information for modifying the input data before training.
Amazon Personalize provides a set of predefined recipes. You specify a recipe when you create a solution with the
CreateSolution API.
CreateSolution trains a model by using the algorithm in the specified recipe and a training dataset.
The solution, when deployed as a campaign, can provide recommendations using the GetRecommendations
API.
describeRecipeRequest - asyncHandler - 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.Future<DescribeRecommenderResult> describeRecommenderAsync(DescribeRecommenderRequest describeRecommenderRequest)
Describes the given recommender, including its status.
A recommender can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
DELETE PENDING > DELETE IN_PROGRESS
When the status is CREATE FAILED, the response includes the failureReason
key, which describes why.
The modelMetrics key is null when the recommender is being created or deleted.
For more information on recommenders, see CreateRecommender.
describeRecommenderRequest - Future<DescribeRecommenderResult> describeRecommenderAsync(DescribeRecommenderRequest describeRecommenderRequest, AsyncHandler<DescribeRecommenderRequest,DescribeRecommenderResult> asyncHandler)
Describes the given recommender, including its status.
A recommender can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
DELETE PENDING > DELETE IN_PROGRESS
When the status is CREATE FAILED, the response includes the failureReason
key, which describes why.
The modelMetrics key is null when the recommender is being created or deleted.
For more information on recommenders, see CreateRecommender.
describeRecommenderRequest - asyncHandler - 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.Future<DescribeSchemaResult> describeSchemaAsync(DescribeSchemaRequest describeSchemaRequest)
Describes a schema. For more information on schemas, see CreateSchema.
describeSchemaRequest - Future<DescribeSchemaResult> describeSchemaAsync(DescribeSchemaRequest describeSchemaRequest, AsyncHandler<DescribeSchemaRequest,DescribeSchemaResult> asyncHandler)
Describes a schema. For more information on schemas, see CreateSchema.
describeSchemaRequest - asyncHandler - 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.Future<DescribeSolutionResult> describeSolutionAsync(DescribeSolutionRequest describeSolutionRequest)
Describes a solution. For more information on solutions, see CreateSolution.
describeSolutionRequest - Future<DescribeSolutionResult> describeSolutionAsync(DescribeSolutionRequest describeSolutionRequest, AsyncHandler<DescribeSolutionRequest,DescribeSolutionResult> asyncHandler)
Describes a solution. For more information on solutions, see CreateSolution.
describeSolutionRequest - asyncHandler - 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.Future<DescribeSolutionVersionResult> describeSolutionVersionAsync(DescribeSolutionVersionRequest describeSolutionVersionRequest)
Describes a specific version of a solution. For more information on solutions, see CreateSolution
describeSolutionVersionRequest - Future<DescribeSolutionVersionResult> describeSolutionVersionAsync(DescribeSolutionVersionRequest describeSolutionVersionRequest, AsyncHandler<DescribeSolutionVersionRequest,DescribeSolutionVersionResult> asyncHandler)
Describes a specific version of a solution. For more information on solutions, see CreateSolution
describeSolutionVersionRequest - asyncHandler - 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.Future<GetSolutionMetricsResult> getSolutionMetricsAsync(GetSolutionMetricsRequest getSolutionMetricsRequest)
Gets the metrics for the specified solution version.
getSolutionMetricsRequest - Future<GetSolutionMetricsResult> getSolutionMetricsAsync(GetSolutionMetricsRequest getSolutionMetricsRequest, AsyncHandler<GetSolutionMetricsRequest,GetSolutionMetricsResult> asyncHandler)
Gets the metrics for the specified solution version.
getSolutionMetricsRequest - asyncHandler - 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.Future<ListBatchInferenceJobsResult> listBatchInferenceJobsAsync(ListBatchInferenceJobsRequest listBatchInferenceJobsRequest)
Gets a list of the batch inference jobs that have been performed off of a solution version.
listBatchInferenceJobsRequest - Future<ListBatchInferenceJobsResult> listBatchInferenceJobsAsync(ListBatchInferenceJobsRequest listBatchInferenceJobsRequest, AsyncHandler<ListBatchInferenceJobsRequest,ListBatchInferenceJobsResult> asyncHandler)
Gets a list of the batch inference jobs that have been performed off of a solution version.
listBatchInferenceJobsRequest - asyncHandler - 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.Future<ListBatchSegmentJobsResult> listBatchSegmentJobsAsync(ListBatchSegmentJobsRequest listBatchSegmentJobsRequest)
Gets a list of the batch segment jobs that have been performed off of a solution version that you specify.
listBatchSegmentJobsRequest - Future<ListBatchSegmentJobsResult> listBatchSegmentJobsAsync(ListBatchSegmentJobsRequest listBatchSegmentJobsRequest, AsyncHandler<ListBatchSegmentJobsRequest,ListBatchSegmentJobsResult> asyncHandler)
Gets a list of the batch segment jobs that have been performed off of a solution version that you specify.
listBatchSegmentJobsRequest - asyncHandler - 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.Future<ListCampaignsResult> listCampaignsAsync(ListCampaignsRequest listCampaignsRequest)
Returns a list of campaigns that use the given solution. When a solution is not specified, all the campaigns associated with the account are listed. The response provides the properties for each campaign, including the Amazon Resource Name (ARN). For more information on campaigns, see CreateCampaign.
listCampaignsRequest - Future<ListCampaignsResult> listCampaignsAsync(ListCampaignsRequest listCampaignsRequest, AsyncHandler<ListCampaignsRequest,ListCampaignsResult> asyncHandler)
Returns a list of campaigns that use the given solution. When a solution is not specified, all the campaigns associated with the account are listed. The response provides the properties for each campaign, including the Amazon Resource Name (ARN). For more information on campaigns, see CreateCampaign.
listCampaignsRequest - asyncHandler - 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.Future<ListDatasetExportJobsResult> listDatasetExportJobsAsync(ListDatasetExportJobsRequest listDatasetExportJobsRequest)
Returns a list of dataset export jobs that use the given dataset. When a dataset is not specified, all the dataset export jobs associated with the account are listed. The response provides the properties for each dataset export job, including the Amazon Resource Name (ARN). For more information on dataset export jobs, see CreateDatasetExportJob. For more information on datasets, see CreateDataset.
listDatasetExportJobsRequest - Future<ListDatasetExportJobsResult> listDatasetExportJobsAsync(ListDatasetExportJobsRequest listDatasetExportJobsRequest, AsyncHandler<ListDatasetExportJobsRequest,ListDatasetExportJobsResult> asyncHandler)
Returns a list of dataset export jobs that use the given dataset. When a dataset is not specified, all the dataset export jobs associated with the account are listed. The response provides the properties for each dataset export job, including the Amazon Resource Name (ARN). For more information on dataset export jobs, see CreateDatasetExportJob. For more information on datasets, see CreateDataset.
listDatasetExportJobsRequest - asyncHandler - 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.Future<ListDatasetGroupsResult> listDatasetGroupsAsync(ListDatasetGroupsRequest listDatasetGroupsRequest)
Returns a list of dataset groups. The response provides the properties for each dataset group, including the Amazon Resource Name (ARN). For more information on dataset groups, see CreateDatasetGroup.
listDatasetGroupsRequest - Future<ListDatasetGroupsResult> listDatasetGroupsAsync(ListDatasetGroupsRequest listDatasetGroupsRequest, AsyncHandler<ListDatasetGroupsRequest,ListDatasetGroupsResult> asyncHandler)
Returns a list of dataset groups. The response provides the properties for each dataset group, including the Amazon Resource Name (ARN). For more information on dataset groups, see CreateDatasetGroup.
listDatasetGroupsRequest - asyncHandler - 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.Future<ListDatasetImportJobsResult> listDatasetImportJobsAsync(ListDatasetImportJobsRequest listDatasetImportJobsRequest)
Returns a list of dataset import jobs that use the given dataset. When a dataset is not specified, all the dataset import jobs associated with the account are listed. The response provides the properties for each dataset import job, including the Amazon Resource Name (ARN). For more information on dataset import jobs, see CreateDatasetImportJob. For more information on datasets, see CreateDataset.
listDatasetImportJobsRequest - Future<ListDatasetImportJobsResult> listDatasetImportJobsAsync(ListDatasetImportJobsRequest listDatasetImportJobsRequest, AsyncHandler<ListDatasetImportJobsRequest,ListDatasetImportJobsResult> asyncHandler)
Returns a list of dataset import jobs that use the given dataset. When a dataset is not specified, all the dataset import jobs associated with the account are listed. The response provides the properties for each dataset import job, including the Amazon Resource Name (ARN). For more information on dataset import jobs, see CreateDatasetImportJob. For more information on datasets, see CreateDataset.
listDatasetImportJobsRequest - asyncHandler - 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.Future<ListDatasetsResult> listDatasetsAsync(ListDatasetsRequest listDatasetsRequest)
Returns the list of datasets contained in the given dataset group. The response provides the properties for each dataset, including the Amazon Resource Name (ARN). For more information on datasets, see CreateDataset.
listDatasetsRequest - Future<ListDatasetsResult> listDatasetsAsync(ListDatasetsRequest listDatasetsRequest, AsyncHandler<ListDatasetsRequest,ListDatasetsResult> asyncHandler)
Returns the list of datasets contained in the given dataset group. The response provides the properties for each dataset, including the Amazon Resource Name (ARN). For more information on datasets, see CreateDataset.
listDatasetsRequest - asyncHandler - 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.Future<ListEventTrackersResult> listEventTrackersAsync(ListEventTrackersRequest listEventTrackersRequest)
Returns the list of event trackers associated with the account. The response provides the properties for each event tracker, including the Amazon Resource Name (ARN) and tracking ID. For more information on event trackers, see CreateEventTracker.
listEventTrackersRequest - Future<ListEventTrackersResult> listEventTrackersAsync(ListEventTrackersRequest listEventTrackersRequest, AsyncHandler<ListEventTrackersRequest,ListEventTrackersResult> asyncHandler)
Returns the list of event trackers associated with the account. The response provides the properties for each event tracker, including the Amazon Resource Name (ARN) and tracking ID. For more information on event trackers, see CreateEventTracker.
listEventTrackersRequest - asyncHandler - 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.Future<ListFiltersResult> listFiltersAsync(ListFiltersRequest listFiltersRequest)
Lists all filters that belong to a given dataset group.
listFiltersRequest - Future<ListFiltersResult> listFiltersAsync(ListFiltersRequest listFiltersRequest, AsyncHandler<ListFiltersRequest,ListFiltersResult> asyncHandler)
Lists all filters that belong to a given dataset group.
listFiltersRequest - asyncHandler - 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.Future<ListMetricAttributionMetricsResult> listMetricAttributionMetricsAsync(ListMetricAttributionMetricsRequest listMetricAttributionMetricsRequest)
Lists the metrics for the metric attribution.
listMetricAttributionMetricsRequest - Future<ListMetricAttributionMetricsResult> listMetricAttributionMetricsAsync(ListMetricAttributionMetricsRequest listMetricAttributionMetricsRequest, AsyncHandler<ListMetricAttributionMetricsRequest,ListMetricAttributionMetricsResult> asyncHandler)
Lists the metrics for the metric attribution.
listMetricAttributionMetricsRequest - asyncHandler - 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.Future<ListMetricAttributionsResult> listMetricAttributionsAsync(ListMetricAttributionsRequest listMetricAttributionsRequest)
Lists metric attributions.
listMetricAttributionsRequest - Future<ListMetricAttributionsResult> listMetricAttributionsAsync(ListMetricAttributionsRequest listMetricAttributionsRequest, AsyncHandler<ListMetricAttributionsRequest,ListMetricAttributionsResult> asyncHandler)
Lists metric attributions.
listMetricAttributionsRequest - asyncHandler - 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.Future<ListRecipesResult> listRecipesAsync(ListRecipesRequest listRecipesRequest)
Returns a list of available recipes. The response provides the properties for each recipe, including the recipe's Amazon Resource Name (ARN).
listRecipesRequest - Future<ListRecipesResult> listRecipesAsync(ListRecipesRequest listRecipesRequest, AsyncHandler<ListRecipesRequest,ListRecipesResult> asyncHandler)
Returns a list of available recipes. The response provides the properties for each recipe, including the recipe's Amazon Resource Name (ARN).
listRecipesRequest - asyncHandler - 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.Future<ListRecommendersResult> listRecommendersAsync(ListRecommendersRequest listRecommendersRequest)
Returns a list of recommenders in a given Domain dataset group. When a Domain dataset group is not specified, all the recommenders associated with the account are listed. The response provides the properties for each recommender, including the Amazon Resource Name (ARN). For more information on recommenders, see CreateRecommender.
listRecommendersRequest - Future<ListRecommendersResult> listRecommendersAsync(ListRecommendersRequest listRecommendersRequest, AsyncHandler<ListRecommendersRequest,ListRecommendersResult> asyncHandler)
Returns a list of recommenders in a given Domain dataset group. When a Domain dataset group is not specified, all the recommenders associated with the account are listed. The response provides the properties for each recommender, including the Amazon Resource Name (ARN). For more information on recommenders, see CreateRecommender.
listRecommendersRequest - asyncHandler - 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.Future<ListSchemasResult> listSchemasAsync(ListSchemasRequest listSchemasRequest)
Returns the list of schemas associated with the account. The response provides the properties for each schema, including the Amazon Resource Name (ARN). For more information on schemas, see CreateSchema.
listSchemasRequest - Future<ListSchemasResult> listSchemasAsync(ListSchemasRequest listSchemasRequest, AsyncHandler<ListSchemasRequest,ListSchemasResult> asyncHandler)
Returns the list of schemas associated with the account. The response provides the properties for each schema, including the Amazon Resource Name (ARN). For more information on schemas, see CreateSchema.
listSchemasRequest - asyncHandler - 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.Future<ListSolutionVersionsResult> listSolutionVersionsAsync(ListSolutionVersionsRequest listSolutionVersionsRequest)
Returns a list of solution versions for the given solution. When a solution is not specified, all the solution versions associated with the account are listed. The response provides the properties for each solution version, including the Amazon Resource Name (ARN).
listSolutionVersionsRequest - Future<ListSolutionVersionsResult> listSolutionVersionsAsync(ListSolutionVersionsRequest listSolutionVersionsRequest, AsyncHandler<ListSolutionVersionsRequest,ListSolutionVersionsResult> asyncHandler)
Returns a list of solution versions for the given solution. When a solution is not specified, all the solution versions associated with the account are listed. The response provides the properties for each solution version, including the Amazon Resource Name (ARN).
listSolutionVersionsRequest - asyncHandler - 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.Future<ListSolutionsResult> listSolutionsAsync(ListSolutionsRequest listSolutionsRequest)
Returns a list of solutions that use the given dataset group. When a dataset group is not specified, all the solutions associated with the account are listed. The response provides the properties for each solution, including the Amazon Resource Name (ARN). For more information on solutions, see CreateSolution.
listSolutionsRequest - Future<ListSolutionsResult> listSolutionsAsync(ListSolutionsRequest listSolutionsRequest, AsyncHandler<ListSolutionsRequest,ListSolutionsResult> asyncHandler)
Returns a list of solutions that use the given dataset group. When a dataset group is not specified, all the solutions associated with the account are listed. The response provides the properties for each solution, including the Amazon Resource Name (ARN). For more information on solutions, see CreateSolution.
listSolutionsRequest - asyncHandler - 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.Future<ListTagsForResourceResult> listTagsForResourceAsync(ListTagsForResourceRequest listTagsForResourceRequest)
Get a list of tags attached to a resource.
listTagsForResourceRequest - Future<ListTagsForResourceResult> listTagsForResourceAsync(ListTagsForResourceRequest listTagsForResourceRequest, AsyncHandler<ListTagsForResourceRequest,ListTagsForResourceResult> asyncHandler)
Get a list of tags attached to a resource.
listTagsForResourceRequest - asyncHandler - 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.Future<StartRecommenderResult> startRecommenderAsync(StartRecommenderRequest startRecommenderRequest)
Starts a recommender that is INACTIVE. Starting a recommender does not create any new models, but resumes billing and automatic retraining for the recommender.
startRecommenderRequest - Future<StartRecommenderResult> startRecommenderAsync(StartRecommenderRequest startRecommenderRequest, AsyncHandler<StartRecommenderRequest,StartRecommenderResult> asyncHandler)
Starts a recommender that is INACTIVE. Starting a recommender does not create any new models, but resumes billing and automatic retraining for the recommender.
startRecommenderRequest - asyncHandler - 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.Future<StopRecommenderResult> stopRecommenderAsync(StopRecommenderRequest stopRecommenderRequest)
Stops a recommender that is ACTIVE. Stopping a recommender halts billing and automatic retraining for the recommender.
stopRecommenderRequest - Future<StopRecommenderResult> stopRecommenderAsync(StopRecommenderRequest stopRecommenderRequest, AsyncHandler<StopRecommenderRequest,StopRecommenderResult> asyncHandler)
Stops a recommender that is ACTIVE. Stopping a recommender halts billing and automatic retraining for the recommender.
stopRecommenderRequest - asyncHandler - 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.Future<StopSolutionVersionCreationResult> stopSolutionVersionCreationAsync(StopSolutionVersionCreationRequest stopSolutionVersionCreationRequest)
Stops creating a solution version that is in a state of CREATE_PENDING or CREATE IN_PROGRESS.
Depending on the current state of the solution version, the solution version state changes as follows:
CREATE_PENDING > CREATE_STOPPED
or
CREATE_IN_PROGRESS > CREATE_STOPPING > CREATE_STOPPED
You are billed for all of the training completed up until you stop the solution version creation. You cannot resume creating a solution version once it has been stopped.
stopSolutionVersionCreationRequest - Future<StopSolutionVersionCreationResult> stopSolutionVersionCreationAsync(StopSolutionVersionCreationRequest stopSolutionVersionCreationRequest, AsyncHandler<StopSolutionVersionCreationRequest,StopSolutionVersionCreationResult> asyncHandler)
Stops creating a solution version that is in a state of CREATE_PENDING or CREATE IN_PROGRESS.
Depending on the current state of the solution version, the solution version state changes as follows:
CREATE_PENDING > CREATE_STOPPED
or
CREATE_IN_PROGRESS > CREATE_STOPPING > CREATE_STOPPED
You are billed for all of the training completed up until you stop the solution version creation. You cannot resume creating a solution version once it has been stopped.
stopSolutionVersionCreationRequest - asyncHandler - 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.Future<TagResourceResult> tagResourceAsync(TagResourceRequest tagResourceRequest)
Add a list of tags to a resource.
tagResourceRequest - Future<TagResourceResult> tagResourceAsync(TagResourceRequest tagResourceRequest, AsyncHandler<TagResourceRequest,TagResourceResult> asyncHandler)
Add a list of tags to a resource.
tagResourceRequest - asyncHandler - 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.Future<UntagResourceResult> untagResourceAsync(UntagResourceRequest untagResourceRequest)
Remove tags that are attached to a resource.
untagResourceRequest - Future<UntagResourceResult> untagResourceAsync(UntagResourceRequest untagResourceRequest, AsyncHandler<UntagResourceRequest,UntagResourceResult> asyncHandler)
Remove tags that are attached to a resource.
untagResourceRequest - asyncHandler - 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.Future<UpdateCampaignResult> updateCampaignAsync(UpdateCampaignRequest updateCampaignRequest)
Updates a campaign to deploy a retrained solution version with an existing campaign, change your campaign's
minProvisionedTPS, or modify your campaign's configuration, such as the exploration configuration.
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.
updateCampaignRequest - Future<UpdateCampaignResult> updateCampaignAsync(UpdateCampaignRequest updateCampaignRequest, AsyncHandler<UpdateCampaignRequest,UpdateCampaignResult> asyncHandler)
Updates a campaign to deploy a retrained solution version with an existing campaign, change your campaign's
minProvisionedTPS, or modify your campaign's configuration, such as the exploration configuration.
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.
updateCampaignRequest - asyncHandler - 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.Future<UpdateDatasetResult> updateDatasetAsync(UpdateDatasetRequest updateDatasetRequest)
Update a dataset to replace its schema with a new or existing one. For more information, see Replacing a dataset's schema.
updateDatasetRequest - Future<UpdateDatasetResult> updateDatasetAsync(UpdateDatasetRequest updateDatasetRequest, AsyncHandler<UpdateDatasetRequest,UpdateDatasetResult> asyncHandler)
Update a dataset to replace its schema with a new or existing one. For more information, see Replacing a dataset's schema.
updateDatasetRequest - asyncHandler - 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.Future<UpdateMetricAttributionResult> updateMetricAttributionAsync(UpdateMetricAttributionRequest updateMetricAttributionRequest)
Updates a metric attribution.
updateMetricAttributionRequest - Future<UpdateMetricAttributionResult> updateMetricAttributionAsync(UpdateMetricAttributionRequest updateMetricAttributionRequest, AsyncHandler<UpdateMetricAttributionRequest,UpdateMetricAttributionResult> asyncHandler)
Updates a metric attribution.
updateMetricAttributionRequest - asyncHandler - 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.Future<UpdateRecommenderResult> updateRecommenderAsync(UpdateRecommenderRequest updateRecommenderRequest)
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.
updateRecommenderRequest - Future<UpdateRecommenderResult> updateRecommenderAsync(UpdateRecommenderRequest updateRecommenderRequest, AsyncHandler<UpdateRecommenderRequest,UpdateRecommenderResult> asyncHandler)
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.
updateRecommenderRequest - asyncHandler - 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.