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 : https://docs.aws.amazon.com/personalize/latest/dg/getting-batch-recommendations.html.

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 : https://docs.aws.amazon.com/personalize/latest/dg/themed-batch-recommendations.html.

Creates a batch segment job.

Creates a campaign that deploys a solution version.

When a client calls the GetRecommendations: https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html and GetPersonalizedRanking: https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetPersonalizedRanking.html 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: https://aws.amazon.com/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: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeCampaign.html.

Wait until the status of the campaign is ACTIVE before asking the campaign for recommendations.

Related APIs

• ListCampaigns: https://docs.aws.amazon.com/personalize/latest/dg/API_ListCampaigns.html

• DescribeCampaign: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeCampaign.html

• UpdateCampaign: https://docs.aws.amazon.com/personalize/latest/dg/API_UpdateCampaign.html

• DeleteCampaign: https://docs.aws.amazon.com/personalize/latest/dg/API_DeleteCampaign.html

Creates an empty dataset and adds it to the specified dataset group.

Use CreateDatasetImportJob: https://docs.aws.amazon.com/personalize/latest/dg/API_CreateDatasetImportJob.html 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: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeDataset.html.

Related APIs

• CreateDatasetGroup: https://docs.aws.amazon.com/personalize/latest/dg/API_CreateDatasetGroup.html

• ListDatasets: https://docs.aws.amazon.com/personalize/latest/dg/API_ListDatasets.html

• DescribeDataset: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeDataset.html

• DeleteDataset: https://docs.aws.amazon.com/personalize/latest/dg/API_DeleteDataset.html

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: https://docs.aws.amazon.com/personalize/latest/dg/export-data.html 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

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: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeDatasetGroup.html. 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

• CreateDataset: https://docs.aws.amazon.com/personalize/latest/dg/API_CreateDataset.html

• CreateEventTracker: https://docs.aws.amazon.com/personalize/latest/dg/API_CreateEventTracker.html

• CreateSolution: https://docs.aws.amazon.com/personalize/latest/dg/API_CreateSolution.html

== Related APIs ==

• ListDatasetGroups: https://docs.aws.amazon.com/personalize/latest/dg/API_ListDatasetGroups.html

• DescribeDatasetGroup: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeDatasetGroup.html

• DeleteDatasetGroup: https://docs.aws.amazon.com/personalize/latest/dg/API_DeleteDatasetGroup.html

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: https://docs.aws.amazon.com/personalize/latest/dg/granting-personalize-s3-access.html.

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: https://docs.aws.amazon.com/personalize/latest/dg/how-new-data-influences-recommendations.html.

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: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeDatasetImportJob.html, providing the Amazon Resource Name (ARN) of the dataset import job. The dataset import is complete when the status shows as ACTIVE. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the job failed.

Importing takes time. You must wait until the status shows as ACTIVE before training a model using the dataset.

Related APIs

• ListDatasetImportJobs: https://docs.aws.amazon.com/personalize/latest/dg/API_ListDatasetImportJobs.html

• DescribeDatasetImportJob: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeDatasetImportJob.html

Creates an event tracker that you use when adding event data to a specified dataset group using the PutEvents: https://docs.aws.amazon.com/personalize/latest/dg/API_UBS_PutEvents.html 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: https://docs.aws.amazon.com/personalize/latest/dg/API_UBS_PutEvents.html 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: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeEventTracker.html.

The event tracker must be in the ACTIVE state before using the tracking ID.

Related APIs

• ListEventTrackers: https://docs.aws.amazon.com/personalize/latest/dg/API_ListEventTrackers.html

• DescribeEventTracker: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeEventTracker.html

• DeleteEventTracker: https://docs.aws.amazon.com/personalize/latest/dg/API_DeleteEventTracker.html

Creates a recommendation filter.

Creates a metric attribution.

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: https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html 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: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeRecommender.html.

Wait until the status of the recommender is ACTIVE before asking the recommender for recommendations.

Related APIs

• ListRecommenders: https://docs.aws.amazon.com/personalize/latest/dg/API_ListRecommenders.html

• DescribeRecommender: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeRecommender.html

• UpdateRecommender: https://docs.aws.amazon.com/personalize/latest/dg/API_UpdateRecommender.html

• DeleteRecommender: https://docs.aws.amazon.com/personalize/latest/dg/API_DeleteRecommender.html

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: https://docs.aws.amazon.com/personalize/latest/dg/API_CreateDataset.html.

Related APIs

• ListSchemas: https://docs.aws.amazon.com/personalize/latest/dg/API_ListSchemas.html

• DescribeSchema: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSchema.html

• DeleteSchema: https://docs.aws.amazon.com/personalize/latest/dg/API_DeleteSchema.html

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: https://docs.aws.amazon.com/personalize/latest/dg/API_CreateSolutionVersion.html 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: https://docs.aws.amazon.com/personalize/latest/dg/API_GetSolutionMetrics.html. When you are satisfied with the version, you deploy it using CreateCampaign: https://docs.aws.amazon.com/personalize/latest/dg/API_CreateCampaign.html. The campaign provides recommendations to a client through the GetRecommendations: https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html 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: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolution.html. Wait until the status shows as ACTIVE before calling CreateSolutionVersion.

Related APIs

• ListSolutions: https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutions.html

• CreateSolutionVersion: https://docs.aws.amazon.com/personalize/latest/dg/API_CreateSolutionVersion.html

• DescribeSolution: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolution.html

• DeleteSolution: https://docs.aws.amazon.com/personalize/latest/dg/API_DeleteSolution.html

• ListSolutionVersions: https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutionVersions.html

• DescribeSolutionVersion: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolutionVersion.html

Trains or retrains an active solution in a Custom dataset group.

A solution is created using the CreateSolution: https://docs.aws.amazon.com/personalize/latest/dg/API_CreateSolution.html 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: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolutionVersion.html. 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: https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutionVersions.html

• DescribeSolutionVersion: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolutionVersion.html

• ListSolutions: https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutions.html

• CreateSolution: https://docs.aws.amazon.com/personalize/latest/dg/API_CreateSolution.html

• DescribeSolution: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolution.html

• DeleteSolution: https://docs.aws.amazon.com/personalize/latest/dg/API_DeleteSolution.html

Removes a campaign by deleting the solution deployment.

Deletes a dataset.

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.

Deletes the event tracker.

Deactivates and removes a recommender.

Deletes a schema.

Deletes all versions of a solution and the Solution object itself.

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.

Describes the given dataset.

Describes the given dataset group.

Describes an event tracker.

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.

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.

Describes a schema.

Describes a solution.

Describes a specific version of a solution.

Returns a list of campaigns that use the given solution.

Returns a list of dataset export jobs that use the given dataset.

Returns a list of dataset groups.

Returns a list of dataset import jobs that use the given dataset.

Returns the list of datasets contained in the given dataset group.

Returns the list of event trackers associated with the account.

Returns a list of available recipes.

Returns a list of recommenders in a given Domain dataset group.

Returns the list of schemas associated with the account.

Returns a list of solution versions for the given solution.

Returns a list of solutions that use the given dataset group.

Starts a recommender that is INACTIVE.

Stops a recommender that is ACTIVE.

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

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: https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeCampaign.html 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.

Update a dataset to replace its schema with a new or existing one.

Updates the recommender to modify the recommender configuration.