Class: Aws::Personalize::Client
- Inherits:
-
Seahorse::Client::Base
- Object
- Seahorse::Client::Base
- Aws::Personalize::Client
- Includes:
- ClientStubs
- Defined in:
- lib/aws-sdk-personalize/client.rb
Overview
An API client for Personalize. To construct a client, you need to configure a ‘:region` and `:credentials`.
client = Aws::Personalize::Client.new(
region: region_name,
credentials: credentials,
# ...
)
For details on configuring region and credentials see the [developer guide](/sdk-for-ruby/v3/developer-guide/setup-config.html).
See #initialize for a full list of supported configuration options.
Class Attribute Summary collapse
- .identifier ⇒ Object readonly private
API Operations collapse
-
#create_batch_inference_job(params = {}) ⇒ Types::CreateBatchInferenceJobResponse
Generates batch recommendations based on a list of items or users stored in Amazon S3 and exports the recommendations to an Amazon S3 bucket.
-
#create_batch_segment_job(params = {}) ⇒ Types::CreateBatchSegmentJobResponse
Creates a batch segment job.
-
#create_campaign(params = {}) ⇒ Types::CreateCampaignResponse
You incur campaign costs while it is active.
-
#create_data_deletion_job(params = {}) ⇒ Types::CreateDataDeletionJobResponse
Creates a batch job that deletes all references to specific users from an Amazon Personalize dataset group in batches.
-
#create_dataset(params = {}) ⇒ Types::CreateDatasetResponse
Creates an empty dataset and adds it to the specified dataset group.
-
#create_dataset_export_job(params = {}) ⇒ Types::CreateDatasetExportJobResponse
Creates a job that exports data from your dataset to an Amazon S3 bucket.
-
#create_dataset_group(params = {}) ⇒ Types::CreateDatasetGroupResponse
Creates an empty dataset group.
-
#create_dataset_import_job(params = {}) ⇒ Types::CreateDatasetImportJobResponse
Creates a job that imports training data from your data source (an Amazon S3 bucket) to an Amazon Personalize dataset.
-
#create_event_tracker(params = {}) ⇒ Types::CreateEventTrackerResponse
Creates an event tracker that you use when adding event data to a specified dataset group using the [PutEvents] API.
-
#create_filter(params = {}) ⇒ Types::CreateFilterResponse
Creates a recommendation filter.
-
#create_metric_attribution(params = {}) ⇒ Types::CreateMetricAttributionResponse
Creates a metric attribution.
-
#create_recommender(params = {}) ⇒ Types::CreateRecommenderResponse
Creates a recommender with the recipe (a Domain dataset group use case) you specify.
-
#create_schema(params = {}) ⇒ Types::CreateSchemaResponse
Creates an Amazon Personalize schema from the specified schema string.
-
#create_solution(params = {}) ⇒ Types::CreateSolutionResponse
By default, all new solutions use automatic training.
-
#create_solution_version(params = {}) ⇒ Types::CreateSolutionVersionResponse
Trains or retrains an active solution in a Custom dataset group.
-
#delete_campaign(params = {}) ⇒ Struct
Removes a campaign by deleting the solution deployment.
-
#delete_dataset(params = {}) ⇒ Struct
Deletes a dataset.
-
#delete_dataset_group(params = {}) ⇒ Struct
Deletes a dataset group.
-
#delete_event_tracker(params = {}) ⇒ Struct
Deletes the event tracker.
-
#delete_filter(params = {}) ⇒ Struct
Deletes a filter.
-
#delete_metric_attribution(params = {}) ⇒ Struct
Deletes a metric attribution.
-
#delete_recommender(params = {}) ⇒ Struct
Deactivates and removes a recommender.
-
#delete_schema(params = {}) ⇒ Struct
Deletes a schema.
-
#delete_solution(params = {}) ⇒ Struct
Deletes all versions of a solution and the ‘Solution` object itself.
-
#describe_algorithm(params = {}) ⇒ Types::DescribeAlgorithmResponse
Describes the given algorithm.
-
#describe_batch_inference_job(params = {}) ⇒ Types::DescribeBatchInferenceJobResponse
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.
-
#describe_batch_segment_job(params = {}) ⇒ Types::DescribeBatchSegmentJobResponse
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.
-
#describe_campaign(params = {}) ⇒ Types::DescribeCampaignResponse
Describes the given campaign, including its status.
-
#describe_data_deletion_job(params = {}) ⇒ Types::DescribeDataDeletionJobResponse
Describes the data deletion job created by [CreateDataDeletionJob], including the job status.
-
#describe_dataset(params = {}) ⇒ Types::DescribeDatasetResponse
Describes the given dataset.
-
#describe_dataset_export_job(params = {}) ⇒ Types::DescribeDatasetExportJobResponse
Describes the dataset export job created by [CreateDatasetExportJob], including the export job status.
-
#describe_dataset_group(params = {}) ⇒ Types::DescribeDatasetGroupResponse
Describes the given dataset group.
-
#describe_dataset_import_job(params = {}) ⇒ Types::DescribeDatasetImportJobResponse
Describes the dataset import job created by [CreateDatasetImportJob], including the import job status.
-
#describe_event_tracker(params = {}) ⇒ Types::DescribeEventTrackerResponse
Describes an event tracker.
-
#describe_feature_transformation(params = {}) ⇒ Types::DescribeFeatureTransformationResponse
Describes the given feature transformation.
-
#describe_filter(params = {}) ⇒ Types::DescribeFilterResponse
Describes a filter’s properties.
-
#describe_metric_attribution(params = {}) ⇒ Types::DescribeMetricAttributionResponse
Describes a metric attribution.
-
#describe_recipe(params = {}) ⇒ Types::DescribeRecipeResponse
Describes a recipe.
-
#describe_recommender(params = {}) ⇒ Types::DescribeRecommenderResponse
Describes the given recommender, including its status.
-
#describe_schema(params = {}) ⇒ Types::DescribeSchemaResponse
Describes a schema.
-
#describe_solution(params = {}) ⇒ Types::DescribeSolutionResponse
Describes a solution.
-
#describe_solution_version(params = {}) ⇒ Types::DescribeSolutionVersionResponse
Describes a specific version of a solution.
-
#get_solution_metrics(params = {}) ⇒ Types::GetSolutionMetricsResponse
Gets the metrics for the specified solution version.
-
#list_batch_inference_jobs(params = {}) ⇒ Types::ListBatchInferenceJobsResponse
Gets a list of the batch inference jobs that have been performed off of a solution version.
-
#list_batch_segment_jobs(params = {}) ⇒ Types::ListBatchSegmentJobsResponse
Gets a list of the batch segment jobs that have been performed off of a solution version that you specify.
-
#list_campaigns(params = {}) ⇒ Types::ListCampaignsResponse
Returns a list of campaigns that use the given solution.
-
#list_data_deletion_jobs(params = {}) ⇒ Types::ListDataDeletionJobsResponse
Returns a list of data deletion jobs for a dataset group ordered by creation time, with the most recent first.
-
#list_dataset_export_jobs(params = {}) ⇒ Types::ListDatasetExportJobsResponse
Returns a list of dataset export jobs that use the given dataset.
-
#list_dataset_groups(params = {}) ⇒ Types::ListDatasetGroupsResponse
Returns a list of dataset groups.
-
#list_dataset_import_jobs(params = {}) ⇒ Types::ListDatasetImportJobsResponse
Returns a list of dataset import jobs that use the given dataset.
-
#list_datasets(params = {}) ⇒ Types::ListDatasetsResponse
Returns the list of datasets contained in the given dataset group.
-
#list_event_trackers(params = {}) ⇒ Types::ListEventTrackersResponse
Returns the list of event trackers associated with the account.
-
#list_filters(params = {}) ⇒ Types::ListFiltersResponse
Lists all filters that belong to a given dataset group.
-
#list_metric_attribution_metrics(params = {}) ⇒ Types::ListMetricAttributionMetricsResponse
Lists the metrics for the metric attribution.
-
#list_metric_attributions(params = {}) ⇒ Types::ListMetricAttributionsResponse
Lists metric attributions.
-
#list_recipes(params = {}) ⇒ Types::ListRecipesResponse
Returns a list of available recipes.
-
#list_recommenders(params = {}) ⇒ Types::ListRecommendersResponse
Returns a list of recommenders in a given Domain dataset group.
-
#list_schemas(params = {}) ⇒ Types::ListSchemasResponse
Returns the list of schemas associated with the account.
-
#list_solution_versions(params = {}) ⇒ Types::ListSolutionVersionsResponse
Returns a list of solution versions for the given solution.
-
#list_solutions(params = {}) ⇒ Types::ListSolutionsResponse
Returns a list of solutions in a given dataset group.
-
#list_tags_for_resource(params = {}) ⇒ Types::ListTagsForResourceResponse
Get a list of [tags] attached to a resource.
-
#start_recommender(params = {}) ⇒ Types::StartRecommenderResponse
Starts a recommender that is INACTIVE.
-
#stop_recommender(params = {}) ⇒ Types::StopRecommenderResponse
Stops a recommender that is ACTIVE.
-
#stop_solution_version_creation(params = {}) ⇒ Struct
Stops creating a solution version that is in a state of CREATE_PENDING or CREATE IN_PROGRESS.
-
#tag_resource(params = {}) ⇒ Struct
Add a list of tags to a resource.
-
#untag_resource(params = {}) ⇒ Struct
Removes the specified tags that are attached to a resource.
-
#update_campaign(params = {}) ⇒ Types::UpdateCampaignResponse
Updates a campaign to deploy a retrained solution version with an existing campaign, change your campaign’s ‘minProvisionedTPS`, or modify your campaign’s configuration.
-
#update_dataset(params = {}) ⇒ Types::UpdateDatasetResponse
Update a dataset to replace its schema with a new or existing one.
-
#update_metric_attribution(params = {}) ⇒ Types::UpdateMetricAttributionResponse
Updates a metric attribution.
-
#update_recommender(params = {}) ⇒ Types::UpdateRecommenderResponse
Updates the recommender to modify the recommender configuration.
-
#update_solution(params = {}) ⇒ Types::UpdateSolutionResponse
Updates an Amazon Personalize solution to use a different automatic training configuration.
Class Method Summary collapse
- .errors_module ⇒ Object private
Instance Method Summary collapse
- #build_request(operation_name, params = {}) ⇒ Object private
-
#initialize(options) ⇒ Client
constructor
A new instance of Client.
- #waiter_names ⇒ Object deprecated private Deprecated.
Constructor Details
#initialize(options) ⇒ Client
Returns a new instance of Client.
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# File 'lib/aws-sdk-personalize/client.rb', line 441 def initialize(*args) super end |
Class Attribute Details
.identifier ⇒ Object (readonly)
This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.
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# File 'lib/aws-sdk-personalize/client.rb', line 4872 def identifier @identifier end |
Class Method Details
.errors_module ⇒ Object
This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.
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# File 'lib/aws-sdk-personalize/client.rb', line 4875 def errors_module Errors end |
Instance Method Details
#build_request(operation_name, params = {}) ⇒ Object
This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.
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# File 'lib/aws-sdk-personalize/client.rb', line 4845 def build_request(operation_name, params = {}) handlers = @handlers.for(operation_name) tracer = config.telemetry_provider.tracer_provider.tracer( Aws::Telemetry.module_to_tracer_name('Aws::Personalize') ) context = Seahorse::Client::RequestContext.new( operation_name: operation_name, operation: config.api.operation(operation_name), client: self, params: params, config: config, tracer: tracer ) context[:gem_name] = 'aws-sdk-personalize' context[:gem_version] = '1.70.0' Seahorse::Client::Request.new(handlers, context) end |
#create_batch_inference_job(params = {}) ⇒ Types::CreateBatchInferenceJobResponse
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 ][1].
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 ][2].
You can’t get batch recommendations with the Trending-Now or Next-Best-Action recipes.
[1]: docs.aws.amazon.com/personalize/latest/dg/getting-batch-recommendations.html [2]: docs.aws.amazon.com/personalize/latest/dg/themed-batch-recommendations.html
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# File 'lib/aws-sdk-personalize/client.rb', line 588 def create_batch_inference_job(params = {}, = {}) req = build_request(:create_batch_inference_job, params) req.send_request() end |
#create_batch_segment_job(params = {}) ⇒ Types::CreateBatchSegmentJobResponse
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].
[1]: docs.aws.amazon.com/personalize/latest/dg/recommendations-batch.html
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# File 'lib/aws-sdk-personalize/client.rb', line 682 def create_batch_segment_job(params = {}, = {}) req = build_request(:create_batch_segment_job, params) req.send_request() end |
#create_campaign(params = {}) ⇒ Types::CreateCampaignResponse
You incur campaign costs while it is active. To avoid unnecessary costs, make sure to delete the campaign when you are finished. For information about campaign costs, see [Amazon Personalize pricing].
Creates a campaign that deploys a solution version. When a client calls the [GetRecommendations] and [GetPersonalizedRanking] APIs, a campaign is specified in the request.
**Minimum Provisioned TPS and Auto-Scaling**
A high ‘minProvisionedTPS` will increase your cost. We recommend starting with 1 for `minProvisionedTPS` (the default). Track your usage using Amazon CloudWatch metrics, and increase the `minProvisionedTPS` as necessary.
When you create an Amazon Personalize campaign, you can specify the minimum provisioned transactions per second (‘minProvisionedTPS`) for the campaign. This is the baseline transaction throughput for the campaign provisioned by Amazon Personalize. It sets the minimum billing charge for the campaign while it is active. A transaction is a single `GetRecommendations` or `GetPersonalizedRanking` request. The default `minProvisionedTPS` is 1.
If your TPS increases beyond the ‘minProvisionedTPS`, Amazon Personalize auto-scales the provisioned capacity up and down, but never below `minProvisionedTPS`. There’s a short time delay while the capacity is increased that might cause loss of transactions. When your traffic reduces, capacity returns to the ‘minProvisionedTPS`.
You are charged for the the minimum provisioned TPS or, if your requests exceed the ‘minProvisionedTPS`, the actual TPS. The actual TPS is the total number of recommendation requests you make. We recommend starting with a low `minProvisionedTPS`, track your usage using Amazon CloudWatch metrics, and then increase the `minProvisionedTPS` as necessary.
For more information about campaign costs, see [Amazon Personalize pricing].
Status
A campaign can be in one of the following states:
-
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
-
DELETE PENDING > DELETE IN_PROGRESS
To get the campaign status, call [DescribeCampaign].
<note markdown=“1”> Wait until the ‘status` of the campaign is `ACTIVE` before asking the campaign for recommendations.
</note>
**Related APIs**
- ListCampaigns][5
- DescribeCampaign][4
- UpdateCampaign][6
- DeleteCampaign][7
[1]: aws.amazon.com/personalize/pricing/ [2]: docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html [3]: docs.aws.amazon.com/personalize/latest/dg/API_RS_GetPersonalizedRanking.html [4]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeCampaign.html [5]: docs.aws.amazon.com/personalize/latest/dg/API_ListCampaigns.html [6]: docs.aws.amazon.com/personalize/latest/dg/API_UpdateCampaign.html [7]: docs.aws.amazon.com/personalize/latest/dg/API_DeleteCampaign.html
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# File 'lib/aws-sdk-personalize/client.rb', line 835 def create_campaign(params = {}, = {}) req = build_request(:create_campaign, params) req.send_request() end |
#create_data_deletion_job(params = {}) ⇒ Types::CreateDataDeletionJobResponse
Creates a batch job that deletes all references to specific users from an Amazon Personalize dataset group in batches. You specify the users to delete in a CSV file of userIds in an Amazon S3 bucket. After a job completes, Amazon Personalize no longer trains on the users’ data and no longer considers the users when generating user segments. For more information about creating a data deletion job, see [Deleting users].
-
Your input file must be a CSV file with a single USER_ID column that lists the users IDs. For more information about preparing the CSV file, see [Preparing your data deletion file and uploading it to Amazon S3].
-
To give Amazon Personalize permission to access your input CSV file of userIds, you must specify an IAM service role that has permission to read from the data source. This role needs ‘GetObject` and `ListBucket` permissions for the bucket and its content. These permissions are the same as importing data. For information on granting access to your Amazon S3 bucket, see [Giving Amazon Personalize Access to Amazon S3 Resources].
After you create a job, it can take up to a day to delete all references to the users from datasets and models. Until the job completes, Amazon Personalize continues to use the data when training. And if you use a User Segmentation recipe, the users might appear in user segments.
Status
A data deletion job can have one of the following statuses:
-
PENDING > IN_PROGRESS > COMPLETED -or- FAILED
^
To get the status of the data deletion job, call
- DescribeDataDeletionJob][4
-
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**
- ListDataDeletionJobs][5
- DescribeDataDeletionJob][4
[1]: docs.aws.amazon.com/personalize/latest/dg/delete-records.html [2]: docs.aws.amazon.com/personalize/latest/dg/prepare-deletion-input-file.html [3]: docs.aws.amazon.com/personalize/latest/dg/granting-personalize-s3-access.html [4]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeDataDeletionJob.html [5]: docs.aws.amazon.com/personalize/latest/dg/API_ListDataDeletionJobs.html
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# File 'lib/aws-sdk-personalize/client.rb', line 945 def create_data_deletion_job(params = {}, = {}) req = build_request(:create_data_deletion_job, params) req.send_request() end |
#create_dataset(params = {}) ⇒ Types::CreateDatasetResponse
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**
- CreateDatasetGroup][3
- ListDatasets][4
- DescribeDataset][2
- DeleteDataset][5
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDatasetImportJob.html [2]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeDataset.html [3]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDatasetGroup.html [4]: docs.aws.amazon.com/personalize/latest/dg/API_ListDatasets.html [5]: docs.aws.amazon.com/personalize/latest/dg/API_DeleteDataset.html
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# File 'lib/aws-sdk-personalize/client.rb', line 1057 def create_dataset(params = {}, = {}) req = build_request(:create_dataset, params) req.send_request() end |
#create_dataset_export_job(params = {}) ⇒ Types::CreateDatasetExportJobResponse
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.
[1]: docs.aws.amazon.com/personalize/latest/dg/export-data.html [2]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeDatasetExportJob.html
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# File 'lib/aws-sdk-personalize/client.rb', line 1151 def create_dataset_export_job(params = {}, = {}) req = build_request(:create_dataset_export_job, params) req.send_request() end |
#create_dataset_group(params = {}) ⇒ Types::CreateDatasetGroupResponse
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.
<note markdown=“1”> You must wait until the ‘status` of the dataset group is `ACTIVE` before adding a dataset to the group.
</note>
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**
- CreateDataset][2
- CreateEventTracker][3
- CreateSolution][4
**Related APIs**
- ListDatasetGroups][5
- DescribeDatasetGroup][1
- DeleteDatasetGroup][6
[1]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeDatasetGroup.html [2]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDataset.html [3]: docs.aws.amazon.com/personalize/latest/dg/API_CreateEventTracker.html [4]: docs.aws.amazon.com/personalize/latest/dg/API_CreateSolution.html [5]: docs.aws.amazon.com/personalize/latest/dg/API_ListDatasetGroups.html [6]: docs.aws.amazon.com/personalize/latest/dg/API_DeleteDatasetGroup.html
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# File 'lib/aws-sdk-personalize/client.rb', line 1280 def create_dataset_group(params = {}, = {}) req = build_request(:create_dataset_group, params) req.send_request() end |
#create_dataset_import_job(params = {}) ⇒ Types::CreateDatasetImportJobResponse
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.
<note markdown=“1”> Importing takes time. You must wait until the status shows as ACTIVE before training a model using the dataset.
</note>
**Related APIs**
- ListDatasetImportJobs][4
- DescribeDatasetImportJob][3
[1]: docs.aws.amazon.com/personalize/latest/dg/granting-personalize-s3-access.html [2]: docs.aws.amazon.com/personalize/latest/dg/how-new-data-influences-recommendations.html [3]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeDatasetImportJob.html [4]: docs.aws.amazon.com/personalize/latest/dg/API_ListDatasetImportJobs.html
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# File 'lib/aws-sdk-personalize/client.rb', line 1406 def create_dataset_import_job(params = {}, = {}) req = build_request(:create_dataset_import_job, params) req.send_request() end |
#create_event_tracker(params = {}) ⇒ Types::CreateEventTrackerResponse
Creates an event tracker that you use when adding event data to a specified dataset group using the [PutEvents] API.
<note markdown=“1”> 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.
</note>
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].
<note markdown=“1”> The event tracker must be in the ACTIVE state before using the tracking ID.
</note>
**Related APIs**
- ListEventTrackers][3
- DescribeEventTracker][2
- DeleteEventTracker][4
[1]: docs.aws.amazon.com/personalize/latest/dg/API_UBS_PutEvents.html [2]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeEventTracker.html [3]: docs.aws.amazon.com/personalize/latest/dg/API_ListEventTrackers.html [4]: docs.aws.amazon.com/personalize/latest/dg/API_DeleteEventTracker.html
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# File 'lib/aws-sdk-personalize/client.rb', line 1497 def create_event_tracker(params = {}, = {}) req = build_request(:create_event_tracker, params) req.send_request() end |
#create_filter(params = {}) ⇒ Types::CreateFilterResponse
Creates a recommendation filter. For more information, see [Filtering recommendations and user segments].
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# File 'lib/aws-sdk-personalize/client.rb', line 1558 def create_filter(params = {}, = {}) req = build_request(:create_filter, params) req.send_request() end |
#create_metric_attribution(params = {}) ⇒ Types::CreateMetricAttributionResponse
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].
[1]: docs.aws.amazon.com/personalize/latest/dg/measuring-recommendation-impact.html
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# File 'lib/aws-sdk-personalize/client.rb', line 1623 def create_metric_attribution(params = {}, = {}) req = build_request(:create_metric_attribution, params) req.send_request() end |
#create_recommender(params = {}) ⇒ Types::CreateRecommenderResponse
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].
<note markdown=“1”> Wait until the ‘status` of the recommender is `ACTIVE` before asking the recommender for recommendations.
</note>
**Related APIs**
- ListRecommenders][3
- DescribeRecommender][2
- UpdateRecommender][4
- DeleteRecommender][5
[1]: docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html [2]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeRecommender.html [3]: docs.aws.amazon.com/personalize/latest/dg/API_ListRecommenders.html [4]: docs.aws.amazon.com/personalize/latest/dg/API_UpdateRecommender.html [5]: docs.aws.amazon.com/personalize/latest/dg/API_DeleteRecommender.html
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# File 'lib/aws-sdk-personalize/client.rb', line 1767 def create_recommender(params = {}, = {}) req = build_request(:create_recommender, params) req.send_request() end |
#create_schema(params = {}) ⇒ Types::CreateSchemaResponse
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**
- ListSchemas][2
- DescribeSchema][3
- DeleteSchema][4
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDataset.html [2]: docs.aws.amazon.com/personalize/latest/dg/API_ListSchemas.html [3]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeSchema.html [4]: docs.aws.amazon.com/personalize/latest/dg/API_DeleteSchema.html
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# File 'lib/aws-sdk-personalize/client.rb', line 1827 def create_schema(params = {}, = {}) req = build_request(:create_schema, params) req.send_request() end |
#create_solution(params = {}) ⇒ Types::CreateSolutionResponse
By default, all new solutions use automatic training. With automatic training, you incur training costs while your solution is active. To avoid unnecessary costs, when you are finished you can [update the solution] to turn off automatic training. 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 within 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][10
-
API.
<note markdown=“1”> Amazon Personalize doesn’t support configuring the ‘hpoObjective` for solution hyperparameter optimization at this time.
</note>
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**
- UpdateSolution][1
- ListSolutions][12
- CreateSolutionVersion][5
- DescribeSolution][11
- DeleteSolution][13
^
- ListSolutionVersions][6
- DescribeSolutionVersion][7
[1]: docs.aws.amazon.com/personalize/latest/dg/API_UpdateSolution.html [2]: aws.amazon.com/personalize/pricing/ [3]: docs.aws.amazon.com/personalize/latest/dg/customizing-solution-config.html [4]: docs.aws.amazon.com/personalize/latest/dg/solution-config-auto-training.html [5]: docs.aws.amazon.com/personalize/latest/dg/API_CreateSolutionVersion.html [6]: docs.aws.amazon.com/personalize/latest/dg/API_ListSolutionVersions.html [7]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolutionVersion.html [8]: docs.aws.amazon.com/personalize/latest/dg/API_GetSolutionMetrics.html [9]: docs.aws.amazon.com/personalize/latest/dg/API_CreateCampaign.html [10]: docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html [11]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolution.html [12]: docs.aws.amazon.com/personalize/latest/dg/API_ListSolutions.html [13]: docs.aws.amazon.com/personalize/latest/dg/API_DeleteSolution.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2096 def create_solution(params = {}, = {}) req = build_request(:create_solution, params) req.send_request() end |
#create_solution_version(params = {}) ⇒ Types::CreateSolutionVersionResponse
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**
- ListSolutionVersions][3
- DescribeSolutionVersion][2
- ListSolutions][4
- CreateSolution][1
- DescribeSolution][5
- DeleteSolution][6
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateSolution.html [2]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolutionVersion.html [3]: docs.aws.amazon.com/personalize/latest/dg/API_ListSolutionVersions.html [4]: docs.aws.amazon.com/personalize/latest/dg/API_ListSolutions.html [5]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolution.html [6]: docs.aws.amazon.com/personalize/latest/dg/API_DeleteSolution.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2218 def create_solution_version(params = {}, = {}) req = build_request(:create_solution_version, params) req.send_request() end |
#delete_campaign(params = {}) ⇒ Struct
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][1
-
request. For information on creating
campaigns, see [CreateCampaign].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html [2]: docs.aws.amazon.com/personalize/latest/dg/API_CreateCampaign.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2249 def delete_campaign(params = {}, = {}) req = build_request(:delete_campaign, params) req.send_request() end |
#delete_dataset(params = {}) ⇒ Struct
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].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDataset.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2278 def delete_dataset(params = {}, = {}) req = build_request(:delete_dataset, params) req.send_request() end |
#delete_dataset_group(params = {}) ⇒ Struct
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.
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# File 'lib/aws-sdk-personalize/client.rb', line 2307 def delete_dataset_group(params = {}, = {}) req = build_request(:delete_dataset_group, params) req.send_request() end |
#delete_event_tracker(params = {}) ⇒ Struct
Deletes the event tracker. Does not delete the dataset from the dataset group. For more information on event trackers, see [CreateEventTracker].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateEventTracker.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2335 def delete_event_tracker(params = {}, = {}) req = build_request(:delete_event_tracker, params) req.send_request() end |
#delete_filter(params = {}) ⇒ Struct
Deletes a filter.
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# File 'lib/aws-sdk-personalize/client.rb', line 2357 def delete_filter(params = {}, = {}) req = build_request(:delete_filter, params) req.send_request() end |
#delete_metric_attribution(params = {}) ⇒ Struct
Deletes a metric attribution.
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# File 'lib/aws-sdk-personalize/client.rb', line 2379 def delete_metric_attribution(params = {}, = {}) req = build_request(:delete_metric_attribution, params) req.send_request() end |
#delete_recommender(params = {}) ⇒ Struct
Deactivates and removes a recommender. A deleted recommender can no longer be specified in a [GetRecommendations] request.
[1]: docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2406 def delete_recommender(params = {}, = {}) req = build_request(:delete_recommender, params) req.send_request() end |
#delete_schema(params = {}) ⇒ Struct
Deletes a schema. Before deleting a schema, you must delete all datasets referencing the schema. For more information on schemas, see [CreateSchema].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateSchema.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2434 def delete_schema(params = {}, = {}) req = build_request(:delete_schema, params) req.send_request() end |
#delete_solution(params = {}) ⇒ Struct
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][1
-
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].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_ListCampaigns.html [2]: docs.aws.amazon.com/personalize/latest/dg/API_CreateSolution.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2467 def delete_solution(params = {}, = {}) req = build_request(:delete_solution, params) req.send_request() end |
#describe_algorithm(params = {}) ⇒ Types::DescribeAlgorithmResponse
Describes the given algorithm.
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# File 'lib/aws-sdk-personalize/client.rb', line 2521 def describe_algorithm(params = {}, = {}) req = build_request(:describe_algorithm, params) req.send_request() end |
#describe_batch_inference_job(params = {}) ⇒ Types::DescribeBatchInferenceJobResponse
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.
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# File 'lib/aws-sdk-personalize/client.rb', line 2568 def describe_batch_inference_job(params = {}, = {}) req = build_request(:describe_batch_inference_job, params) req.send_request() end |
#describe_batch_segment_job(params = {}) ⇒ Types::DescribeBatchSegmentJobResponse
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.
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# File 'lib/aws-sdk-personalize/client.rb', line 2611 def describe_batch_segment_job(params = {}, = {}) req = build_request(:describe_batch_segment_job, params) req.send_request() end |
#describe_campaign(params = {}) ⇒ Types::DescribeCampaignResponse
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].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateCampaign.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2676 def describe_campaign(params = {}, = {}) req = build_request(:describe_campaign, params) req.send_request() end |
#describe_data_deletion_job(params = {}) ⇒ Types::DescribeDataDeletionJobResponse
Describes the data deletion job created by [CreateDataDeletionJob], including the job status.
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDataDeletionJob.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2718 def describe_data_deletion_job(params = {}, = {}) req = build_request(:describe_data_deletion_job, params) req.send_request() end |
#describe_dataset(params = {}) ⇒ Types::DescribeDatasetResponse
Describes the given dataset. For more information on datasets, see [CreateDataset].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDataset.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2764 def describe_dataset(params = {}, = {}) req = build_request(:describe_dataset, params) req.send_request() end |
#describe_dataset_export_job(params = {}) ⇒ Types::DescribeDatasetExportJobResponse
Describes the dataset export job created by [CreateDatasetExportJob], including the export job status.
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDatasetExportJob.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2807 def describe_dataset_export_job(params = {}, = {}) req = build_request(:describe_dataset_export_job, params) req.send_request() end |
#describe_dataset_group(params = {}) ⇒ Types::DescribeDatasetGroupResponse
Describes the given dataset group. For more information on dataset groups, see [CreateDatasetGroup].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDatasetGroup.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2848 def describe_dataset_group(params = {}, = {}) req = build_request(:describe_dataset_group, params) req.send_request() end |
#describe_dataset_import_job(params = {}) ⇒ Types::DescribeDatasetImportJobResponse
Describes the dataset import job created by [CreateDatasetImportJob], including the import job status.
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDatasetImportJob.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2891 def describe_dataset_import_job(params = {}, = {}) req = build_request(:describe_dataset_import_job, params) req.send_request() end |
#describe_event_tracker(params = {}) ⇒ Types::DescribeEventTrackerResponse
Describes an event tracker. The response includes the ‘trackingId` and `status` of the event tracker. For more information on event trackers, see [CreateEventTracker].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateEventTracker.html
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# File 'lib/aws-sdk-personalize/client.rb', line 2932 def describe_event_tracker(params = {}, = {}) req = build_request(:describe_event_tracker, params) req.send_request() end |
#describe_feature_transformation(params = {}) ⇒ Types::DescribeFeatureTransformationResponse
Describes the given feature transformation.
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# File 'lib/aws-sdk-personalize/client.rb', line 2967 def describe_feature_transformation(params = {}, = {}) req = build_request(:describe_feature_transformation, params) req.send_request() end |
#describe_filter(params = {}) ⇒ Types::DescribeFilterResponse
Describes a filter’s properties.
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# File 'lib/aws-sdk-personalize/client.rb', line 3002 def describe_filter(params = {}, = {}) req = build_request(:describe_filter, params) req.send_request() end |
#describe_metric_attribution(params = {}) ⇒ Types::DescribeMetricAttributionResponse
Describes a metric attribution.
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# File 'lib/aws-sdk-personalize/client.rb', line 3039 def describe_metric_attribution(params = {}, = {}) req = build_request(:describe_metric_attribution, params) req.send_request() end |
#describe_recipe(params = {}) ⇒ Types::DescribeRecipeResponse
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][2
-
API.
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateSolution.html [2]: docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html
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# File 'lib/aws-sdk-personalize/client.rb', line 3096 def describe_recipe(params = {}, = {}) req = build_request(:describe_recipe, params) req.send_request() end |
#describe_recommender(params = {}) ⇒ Types::DescribeRecommenderResponse
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].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateRecommender.html
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# File 'lib/aws-sdk-personalize/client.rb', line 3173 def describe_recommender(params = {}, = {}) req = build_request(:describe_recommender, params) req.send_request() end |
#describe_schema(params = {}) ⇒ Types::DescribeSchemaResponse
Describes a schema. For more information on schemas, see [CreateSchema].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateSchema.html
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# File 'lib/aws-sdk-personalize/client.rb', line 3211 def describe_schema(params = {}, = {}) req = build_request(:describe_schema, params) req.send_request() end |
#describe_solution(params = {}) ⇒ Types::DescribeSolutionResponse
Describes a solution. For more information on solutions, see [CreateSolution].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateSolution.html
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# File 'lib/aws-sdk-personalize/client.rb', line 3299 def describe_solution(params = {}, = {}) req = build_request(:describe_solution, params) req.send_request() end |
#describe_solution_version(params = {}) ⇒ Types::DescribeSolutionVersionResponse
Describes a specific version of a solution. For more information on solutions, see [CreateSolution]
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateSolution.html
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# File 'lib/aws-sdk-personalize/client.rb', line 3379 def describe_solution_version(params = {}, = {}) req = build_request(:describe_solution_version, params) req.send_request() end |
#get_solution_metrics(params = {}) ⇒ Types::GetSolutionMetricsResponse
Gets the metrics for the specified solution version.
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# File 'lib/aws-sdk-personalize/client.rb', line 3411 def get_solution_metrics(params = {}, = {}) req = build_request(:get_solution_metrics, params) req.send_request() end |
#list_batch_inference_jobs(params = {}) ⇒ Types::ListBatchInferenceJobsResponse
Gets a list of the batch inference jobs that have been performed off of a solution version.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 3462 def list_batch_inference_jobs(params = {}, = {}) req = build_request(:list_batch_inference_jobs, params) req.send_request() end |
#list_batch_segment_jobs(params = {}) ⇒ Types::ListBatchSegmentJobsResponse
Gets a list of the batch segment jobs that have been performed off of a solution version that you specify.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 3512 def list_batch_segment_jobs(params = {}, = {}) req = build_request(:list_batch_segment_jobs, params) req.send_request() end |
#list_campaigns(params = {}) ⇒ Types::ListCampaignsResponse
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].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateCampaign.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 3573 def list_campaigns(params = {}, = {}) req = build_request(:list_campaigns, params) req.send_request() end |
#list_data_deletion_jobs(params = {}) ⇒ Types::ListDataDeletionJobsResponse
Returns a list of data deletion jobs for a dataset group ordered by creation time, with the most recent first. When a dataset group is not specified, all the data deletion jobs associated with the account are listed. The response provides the properties for each job, including the Amazon Resource Name (ARN). For more information on data deletion jobs, see [Deleting users].
[1]: docs.aws.amazon.com/personalize/latest/dg/delete-records.html
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# File 'lib/aws-sdk-personalize/client.rb', line 3629 def list_data_deletion_jobs(params = {}, = {}) req = build_request(:list_data_deletion_jobs, params) req.send_request() end |
#list_dataset_export_jobs(params = {}) ⇒ Types::ListDatasetExportJobsResponse
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].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDatasetExportJob.html [2]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDataset.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 3688 def list_dataset_export_jobs(params = {}, = {}) req = build_request(:list_dataset_export_jobs, params) req.send_request() end |
#list_dataset_groups(params = {}) ⇒ Types::ListDatasetGroupsResponse
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].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDatasetGroup.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 3738 def list_dataset_groups(params = {}, = {}) req = build_request(:list_dataset_groups, params) req.send_request() end |
#list_dataset_import_jobs(params = {}) ⇒ Types::ListDatasetImportJobsResponse
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].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDatasetImportJob.html [2]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDataset.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 3798 def list_dataset_import_jobs(params = {}, = {}) req = build_request(:list_dataset_import_jobs, params) req.send_request() end |
#list_datasets(params = {}) ⇒ Types::ListDatasetsResponse
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].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateDataset.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 3853 def list_datasets(params = {}, = {}) req = build_request(:list_datasets, params) req.send_request() end |
#list_event_trackers(params = {}) ⇒ Types::ListEventTrackersResponse
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].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateEventTracker.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 3906 def list_event_trackers(params = {}, = {}) req = build_request(:list_event_trackers, params) req.send_request() end |
#list_filters(params = {}) ⇒ Types::ListFiltersResponse
Lists all filters that belong to a given dataset group.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 3954 def list_filters(params = {}, = {}) req = build_request(:list_filters, params) req.send_request() end |
#list_metric_attribution_metrics(params = {}) ⇒ Types::ListMetricAttributionMetricsResponse
Lists the metrics for the metric attribution.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 3999 def list_metric_attribution_metrics(params = {}, = {}) req = build_request(:list_metric_attribution_metrics, params) req.send_request() end |
#list_metric_attributions(params = {}) ⇒ Types::ListMetricAttributionsResponse
Lists metric attributions.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 4047 def list_metric_attributions(params = {}, = {}) req = build_request(:list_metric_attributions, params) req.send_request() end |
#list_recipes(params = {}) ⇒ Types::ListRecipesResponse
Returns a list of available recipes. The response provides the properties for each recipe, including the recipe’s Amazon Resource Name (ARN).
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 4103 def list_recipes(params = {}, = {}) req = build_request(:list_recipes, params) req.send_request() end |
#list_recommenders(params = {}) ⇒ Types::ListRecommendersResponse
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].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateRecommender.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 4168 def list_recommenders(params = {}, = {}) req = build_request(:list_recommenders, params) req.send_request() end |
#list_schemas(params = {}) ⇒ Types::ListSchemasResponse
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].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateSchema.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 4216 def list_schemas(params = {}, = {}) req = build_request(:list_schemas, params) req.send_request() end |
#list_solution_versions(params = {}) ⇒ Types::ListSolutionVersionsResponse
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).
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 4267 def list_solution_versions(params = {}, = {}) req = build_request(:list_solution_versions, params) req.send_request() end |
#list_solutions(params = {}) ⇒ Types::ListSolutionsResponse
Returns a list of solutions in a given dataset group. When a dataset group is not specified, all the solutions associated with the account are listed. The response provides the properties for each solution, including the Amazon Resource Name (ARN). For more information on solutions, see [CreateSolution].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_CreateSolution.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-personalize/client.rb', line 4322 def list_solutions(params = {}, = {}) req = build_request(:list_solutions, params) req.send_request() end |
#list_tags_for_resource(params = {}) ⇒ Types::ListTagsForResourceResponse
Get a list of [tags] attached to a resource.
[1]: docs.aws.amazon.com/personalize/latest/dg/tagging-resources.html
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# File 'lib/aws-sdk-personalize/client.rb', line 4356 def (params = {}, = {}) req = build_request(:list_tags_for_resource, params) req.send_request() end |
#start_recommender(params = {}) ⇒ Types::StartRecommenderResponse
Starts a recommender that is INACTIVE. Starting a recommender does not create any new models, but resumes billing and automatic retraining for the recommender.
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# File 'lib/aws-sdk-personalize/client.rb', line 4386 def start_recommender(params = {}, = {}) req = build_request(:start_recommender, params) req.send_request() end |
#stop_recommender(params = {}) ⇒ Types::StopRecommenderResponse
Stops a recommender that is ACTIVE. Stopping a recommender halts billing and automatic retraining for the recommender.
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# File 'lib/aws-sdk-personalize/client.rb', line 4415 def stop_recommender(params = {}, = {}) req = build_request(:stop_recommender, params) req.send_request() end |
#stop_solution_version_creation(params = {}) ⇒ Struct
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.
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# File 'lib/aws-sdk-personalize/client.rb', line 4452 def stop_solution_version_creation(params = {}, = {}) req = build_request(:stop_solution_version_creation, params) req.send_request() end |
#tag_resource(params = {}) ⇒ Struct
Add a list of tags to a resource.
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# File 'lib/aws-sdk-personalize/client.rb', line 4488 def tag_resource(params = {}, = {}) req = build_request(:tag_resource, params) req.send_request() end |
#untag_resource(params = {}) ⇒ Struct
Removes the specified tags that are attached to a resource. For more information, see [Removing tags from Amazon Personalize resources].
[1]: docs.aws.amazon.com/personalize/latest/dg/tags-remove.html
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# File 'lib/aws-sdk-personalize/client.rb', line 4519 def untag_resource(params = {}, = {}) req = build_request(:untag_resource, params) req.send_request() end |
#update_campaign(params = {}) ⇒ Types::UpdateCampaignResponse
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.
<note markdown=“1”> 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`.
</note>
For more information about updating a campaign, including code samples, see [Updating a campaign]. For more information about campaigns, see [Creating a campaign].
[1]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeCampaign.html [2]: docs.aws.amazon.com/personalize/latest/dg/update-campaigns.html [3]: docs.aws.amazon.com/personalize/latest/dg/campaigns.html
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# File 'lib/aws-sdk-personalize/client.rb', line 4618 def update_campaign(params = {}, = {}) req = build_request(:update_campaign, params) req.send_request() end |
#update_dataset(params = {}) ⇒ Types::UpdateDatasetResponse
Update a dataset to replace its schema with a new or existing one. For more information, see [Replacing a dataset’s schema].
[1]: docs.aws.amazon.com/personalize/latest/dg/updating-dataset-schema.html
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# File 'lib/aws-sdk-personalize/client.rb', line 4655 def update_dataset(params = {}, = {}) req = build_request(:update_dataset, params) req.send_request() end |
#update_metric_attribution(params = {}) ⇒ Types::UpdateMetricAttributionResponse
Updates a metric attribution.
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# File 'lib/aws-sdk-personalize/client.rb', line 4707 def update_metric_attribution(params = {}, = {}) req = build_request(:update_metric_attribution, params) req.send_request() end |
#update_recommender(params = {}) ⇒ Types::UpdateRecommenderResponse
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.
[1]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeRecommender.html
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# File 'lib/aws-sdk-personalize/client.rb', line 4761 def update_recommender(params = {}, = {}) req = build_request(:update_recommender, params) req.send_request() end |
#update_solution(params = {}) ⇒ Types::UpdateSolutionResponse
Updates an Amazon Personalize solution to use a different automatic training configuration. When you update a solution, you can change whether the solution uses automatic training, and you can change the training frequency. For more information about updating a solution, see [Updating a solution].
A solution update can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
To get the status of a solution update, call the [DescribeSolution] API operation and find the status in the ‘latestSolutionUpdate`.
[1]: docs.aws.amazon.com/personalize/latest/dg/updating-solution.html [2]: docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolution.html
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# File 'lib/aws-sdk-personalize/client.rb', line 4836 def update_solution(params = {}, = {}) req = build_request(:update_solution, params) req.send_request() end |
#waiter_names ⇒ Object
This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.
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# File 'lib/aws-sdk-personalize/client.rb', line 4865 def waiter_names [] end |