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Paws::Personalize(3) User Contributed Perl Documentation Paws::Personalize(3)

Paws::Personalize - Perl Interface to AWS Amazon Personalize

  use Paws;
  my $obj = Paws->service('Personalize');
  my $res = $obj->Method(
    Arg1 => $val1,
    Arg2 => [ 'V1', 'V2' ],
    # if Arg3 is an object, the HashRef will be used as arguments to the constructor
    # of the arguments type
    Arg3 => { Att1 => 'Val1' },
    # if Arg4 is an array of objects, the HashRefs will be passed as arguments to
    # the constructor of the arguments type
    Arg4 => [ { Att1 => 'Val1'  }, { Att1 => 'Val2' } ],
  );

Amazon Personalize is a machine learning service that makes it easy to add individualized recommendations to customers.

For the AWS API documentation, see <https://docs.aws.amazon.com/goto/WebAPI/personalize-2018-05-22>

[BatchInferenceJobConfig => Paws::Personalize::BatchInferenceJobConfig]
[FilterArn => Str]
[NumResults => Int]

Each argument is described in detail in: Paws::Personalize::CreateBatchInferenceJob

Returns: a Paws::Personalize::CreateBatchInferenceJobResponse instance

Creates a batch inference job. The operation can handle up to 50 million records and the input file must be in JSON format. For more information, see recommendations-batch.

[CampaignConfig => Paws::Personalize::CampaignConfig]

Each argument is described in detail in: Paws::Personalize::CreateCampaign

Returns: a Paws::Personalize::CreateCampaignResponse instance

Creates a campaign by deploying 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 transaction is a single "GetRecommendations" or "GetPersonalizedRanking" call. Transactions per second (TPS) is the throughput and unit of billing for Amazon Personalize. The minimum provisioned TPS ("minProvisionedTPS") specifies the baseline throughput provisioned by Amazon Personalize, and thus, the minimum billing charge.

If your TPS increases beyond "minProvisionedTPS", Amazon Personalize auto-scales the provisioned capacity up and down, but never below "minProvisionedTPS". There's a short time delay while the capacity is increased that might cause loss of transactions.

The actual TPS used is calculated as the average requests/second within a 5-minute window. You pay for maximum of either the minimum provisioned TPS or the actual TPS. We recommend starting with a low "minProvisionedTPS", track your usage using Amazon CloudWatch metrics, and then increase the "minProvisionedTPS" as necessary.

Status

A campaign can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
  • DELETE PENDING > DELETE IN_PROGRESS

To get the campaign status, call DescribeCampaign.

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

Related APIs

  • ListCampaigns
  • DescribeCampaign
  • UpdateCampaign
  • DeleteCampaign

Each argument is described in detail in: Paws::Personalize::CreateDataset

Returns: a Paws::Personalize::CreateDatasetResponse instance

Creates an empty dataset and adds it to the specified dataset group. Use CreateDatasetImportJob to import your training data to a dataset.

There are three types of datasets:

  • Interactions
  • Items
  • Users

Each dataset type has an associated schema with required field types. Only the "Interactions" dataset is required in order to train a model (also referred to as creating a solution).

A dataset can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
  • DELETE PENDING > DELETE IN_PROGRESS

To get the status of the dataset, call DescribeDataset.

Related APIs

  • CreateDatasetGroup
  • ListDatasets
  • DescribeDataset
  • DeleteDataset

[IngestionMode => Str]

Each argument is described in detail in: Paws::Personalize::CreateDatasetExportJob

Returns: a Paws::Personalize::CreateDatasetExportJobResponse instance

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 AWS Identity and Access Management (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

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.

[KmsKeyArn => Str]
[RoleArn => Str]

Each argument is described in detail in: Paws::Personalize::CreateDatasetGroup

Returns: a Paws::Personalize::CreateDatasetGroupResponse instance

Creates an empty dataset group. A dataset group contains related datasets that supply data for training a model. A dataset group can contain at most three datasets, one for each type of dataset:

  • Interactions
  • Items
  • Users

To train a model (create a solution), a dataset group that contains an "Interactions" dataset is required. Call CreateDataset to add a dataset to the group.

A dataset group can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
  • DELETE PENDING

To get the status of the dataset group, call DescribeDatasetGroup. If the status shows as CREATE FAILED, the response includes a "failureReason" key, which describes why the creation failed.

You must wait until the "status" of the dataset group is "ACTIVE" before adding a dataset to the group.

You can specify an AWS Key Management Service (KMS) key to encrypt the datasets in the group. If you specify a KMS key, you must also include an AWS Identity and Access Management (IAM) role that has permission to access the key.

APIs that require a dataset group ARN in the request

  • CreateDataset
  • CreateEventTracker
  • CreateSolution

Related APIs

  • ListDatasetGroups
  • DescribeDatasetGroup
  • DeleteDatasetGroup

Each argument is described in detail in: Paws::Personalize::CreateDatasetImportJob

Returns: a Paws::Personalize::CreateDatasetImportJobResponse instance

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 AWS Identity and Access Management (IAM) service role that has permission to read from the data source, as Amazon Personalize makes a copy of your data and processes it in an internal AWS system. 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).

The dataset import job replaces any existing data in the dataset that you imported in bulk.

Status

A dataset import job can be in one of the following states:

CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED

To get the status of the import job, call DescribeDatasetImportJob, providing the Amazon Resource Name (ARN) of the dataset import job. The dataset import is complete when the status shows as ACTIVE. If the status shows as CREATE FAILED, the response includes a "failureReason" key, which describes why the job failed.

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

Related APIs

  • ListDatasetImportJobs
  • DescribeDatasetImportJob

Each argument is described in detail in: Paws::Personalize::CreateEventTracker

Returns: a Paws::Personalize::CreateEventTrackerResponse instance

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 Interactions dataset of the dataset group you specify in your event tracker.

The event tracker can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
  • DELETE PENDING > DELETE IN_PROGRESS

To get the status of the event tracker, call DescribeEventTracker.

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

Related APIs

  • ListEventTrackers
  • DescribeEventTracker
  • DeleteEventTracker

Each argument is described in detail in: Paws::Personalize::CreateFilter

Returns: a Paws::Personalize::CreateFilterResponse instance

Creates a recommendation filter. For more information, see filter.

Each argument is described in detail in: Paws::Personalize::CreateSchema

Returns: a Paws::Personalize::CreateSchemaResponse instance

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. You specify a schema when you call CreateDataset.

Related APIs

  • ListSchemas
  • DescribeSchema
  • DeleteSchema

[EventType => Str]
[PerformAutoML => Bool]
[PerformHPO => Bool]
[RecipeArn => Str]
[SolutionConfig => Paws::Personalize::SolutionConfig]

Each argument is described in detail in: Paws::Personalize::CreateSolution

Returns: a Paws::Personalize::CreateSolutionResponse instance

Creates the configuration for training a model. A trained model is known as a solution. After the configuration is created, you train the model (create a solution) by calling the CreateSolutionVersion operation. Every time you call "CreateSolutionVersion", a new version of the solution is created.

After creating a solution version, you check its accuracy by calling GetSolutionMetrics. When you are satisfied with the version, you deploy it using CreateCampaign. The campaign provides recommendations to a client through the GetRecommendations (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. Alternatively, you can specify "performAutoML" and Amazon Personalize will analyze your data and select the optimum USER_PERSONALIZATION recipe for you.

Amazon Personalize doesn't support configuring the "hpoObjective" for solution hyperparameter optimization at this time.

Status

A solution can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
  • DELETE PENDING > DELETE IN_PROGRESS

To get the status of the solution, call DescribeSolution. Wait until the status shows as ACTIVE before calling "CreateSolutionVersion".

Related APIs

  • ListSolutions
  • CreateSolutionVersion
  • DescribeSolution
  • DeleteSolution
  • ListSolutionVersions
  • DescribeSolutionVersion

[TrainingMode => Str]

Each argument is described in detail in: Paws::Personalize::CreateSolutionVersion

Returns: a Paws::Personalize::CreateSolutionVersionResponse instance

Trains or retrains an active solution. 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
  • DescribeSolutionVersion
  • ListSolutions
  • CreateSolution
  • DescribeSolution
  • DeleteSolution

Each argument is described in detail in: Paws::Personalize::DeleteCampaign

Returns: nothing

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 (https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html) request. For more information on campaigns, see CreateCampaign.

Each argument is described in detail in: Paws::Personalize::DeleteDataset

Returns: nothing

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.

Each argument is described in detail in: Paws::Personalize::DeleteDatasetGroup

Returns: nothing

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.

Each argument is described in detail in: Paws::Personalize::DeleteEventTracker

Returns: nothing

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

Each argument is described in detail in: Paws::Personalize::DeleteFilter

Returns: nothing

Deletes a filter.

Each argument is described in detail in: Paws::Personalize::DeleteSchema

Returns: nothing

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

Each argument is described in detail in: Paws::Personalize::DeleteSolution

Returns: nothing

Deletes all versions of a solution and the "Solution" object itself. Before deleting a solution, you must delete all campaigns based on the solution. To determine what campaigns are using the solution, call ListCampaigns and supply the Amazon Resource Name (ARN) of the solution. You can't delete a solution if an associated "SolutionVersion" is in the CREATE PENDING or IN PROGRESS state. For more information on solutions, see CreateSolution.

Each argument is described in detail in: Paws::Personalize::DescribeAlgorithm

Returns: a Paws::Personalize::DescribeAlgorithmResponse instance

Describes the given algorithm.

Each argument is described in detail in: Paws::Personalize::DescribeBatchInferenceJob

Returns: a Paws::Personalize::DescribeBatchInferenceJobResponse instance

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.

Each argument is described in detail in: Paws::Personalize::DescribeCampaign

Returns: a Paws::Personalize::DescribeCampaignResponse instance

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.

Each argument is described in detail in: Paws::Personalize::DescribeDataset

Returns: a Paws::Personalize::DescribeDatasetResponse instance

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

Each argument is described in detail in: Paws::Personalize::DescribeDatasetExportJob

Returns: a Paws::Personalize::DescribeDatasetExportJobResponse instance

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

Each argument is described in detail in: Paws::Personalize::DescribeDatasetGroup

Returns: a Paws::Personalize::DescribeDatasetGroupResponse instance

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

Each argument is described in detail in: Paws::Personalize::DescribeDatasetImportJob

Returns: a Paws::Personalize::DescribeDatasetImportJobResponse instance

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

Each argument is described in detail in: Paws::Personalize::DescribeEventTracker

Returns: a Paws::Personalize::DescribeEventTrackerResponse instance

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

Each argument is described in detail in: Paws::Personalize::DescribeFeatureTransformation

Returns: a Paws::Personalize::DescribeFeatureTransformationResponse instance

Describes the given feature transformation.

Each argument is described in detail in: Paws::Personalize::DescribeFilter

Returns: a Paws::Personalize::DescribeFilterResponse instance

Describes a filter's properties.

Each argument is described in detail in: Paws::Personalize::DescribeRecipe

Returns: a Paws::Personalize::DescribeRecipeResponse instance

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 (https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html) API.

Each argument is described in detail in: Paws::Personalize::DescribeSchema

Returns: a Paws::Personalize::DescribeSchemaResponse instance

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

Each argument is described in detail in: Paws::Personalize::DescribeSolution

Returns: a Paws::Personalize::DescribeSolutionResponse instance

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

Each argument is described in detail in: Paws::Personalize::DescribeSolutionVersion

Returns: a Paws::Personalize::DescribeSolutionVersionResponse instance

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

Each argument is described in detail in: Paws::Personalize::GetSolutionMetrics

Returns: a Paws::Personalize::GetSolutionMetricsResponse instance

Gets the metrics for the specified solution version.

[MaxResults => Int]
[NextToken => Str]
[SolutionVersionArn => Str]

Each argument is described in detail in: Paws::Personalize::ListBatchInferenceJobs

Returns: a Paws::Personalize::ListBatchInferenceJobsResponse instance

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

[MaxResults => Int]
[NextToken => Str]
[SolutionArn => Str]

Each argument is described in detail in: Paws::Personalize::ListCampaigns

Returns: a Paws::Personalize::ListCampaignsResponse instance

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.

[DatasetArn => Str]
[MaxResults => Int]
[NextToken => Str]

Each argument is described in detail in: Paws::Personalize::ListDatasetExportJobs

Returns: a Paws::Personalize::ListDatasetExportJobsResponse instance

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.

[MaxResults => Int]
[NextToken => Str]

Each argument is described in detail in: Paws::Personalize::ListDatasetGroups

Returns: a Paws::Personalize::ListDatasetGroupsResponse instance

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.

[DatasetArn => Str]
[MaxResults => Int]
[NextToken => Str]

Each argument is described in detail in: Paws::Personalize::ListDatasetImportJobs

Returns: a Paws::Personalize::ListDatasetImportJobsResponse instance

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.

[DatasetGroupArn => Str]
[MaxResults => Int]
[NextToken => Str]

Each argument is described in detail in: Paws::Personalize::ListDatasets

Returns: a Paws::Personalize::ListDatasetsResponse instance

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.

[DatasetGroupArn => Str]
[MaxResults => Int]
[NextToken => Str]

Each argument is described in detail in: Paws::Personalize::ListEventTrackers

Returns: a Paws::Personalize::ListEventTrackersResponse instance

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.

[DatasetGroupArn => Str]
[MaxResults => Int]
[NextToken => Str]

Each argument is described in detail in: Paws::Personalize::ListFilters

Returns: a Paws::Personalize::ListFiltersResponse instance

Lists all filters that belong to a given dataset group.

[MaxResults => Int]
[NextToken => Str]
[RecipeProvider => Str]

Each argument is described in detail in: Paws::Personalize::ListRecipes

Returns: a Paws::Personalize::ListRecipesResponse instance

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

[MaxResults => Int]
[NextToken => Str]

Each argument is described in detail in: Paws::Personalize::ListSchemas

Returns: a Paws::Personalize::ListSchemasResponse instance

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.

[DatasetGroupArn => Str]
[MaxResults => Int]
[NextToken => Str]

Each argument is described in detail in: Paws::Personalize::ListSolutions

Returns: a Paws::Personalize::ListSolutionsResponse instance

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

[MaxResults => Int]
[NextToken => Str]
[SolutionArn => Str]

Each argument is described in detail in: Paws::Personalize::ListSolutionVersions

Returns: a Paws::Personalize::ListSolutionVersionsResponse instance

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). For more information on solutions, see CreateSolution.

Each argument is described in detail in: Paws::Personalize::StopSolutionVersionCreation

Returns: nothing

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.

[CampaignConfig => Paws::Personalize::CampaignConfig]
[MinProvisionedTPS => Int]
[SolutionVersionArn => Str]

Each argument is described in detail in: Paws::Personalize::UpdateCampaign

Returns: a Paws::Personalize::UpdateCampaignResponse instance

Updates a campaign by either deploying a new solution or changing the value of the campaign's "minProvisionedTPS" parameter.

To update a campaign, the campaign status must be ACTIVE or CREATE FAILED. Check the campaign status using the DescribeCampaign API.

You must wait until the "status" of the updated campaign is "ACTIVE" before asking the campaign for recommendations.

For more information on campaigns, see CreateCampaign.

Paginator methods are helpers that repetively call methods that return partial results

If passed a sub as first parameter, it will call the sub for each element found in :

 - batchInferenceJobs, passing the object as the first parameter, and the string 'batchInferenceJobs' as the second parameter

If not, it will return a a Paws::Personalize::ListBatchInferenceJobsResponse instance with all the "param"s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.

If passed a sub as first parameter, it will call the sub for each element found in :

 - campaigns, passing the object as the first parameter, and the string 'campaigns' as the second parameter

If not, it will return a a Paws::Personalize::ListCampaignsResponse instance with all the "param"s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.

If passed a sub as first parameter, it will call the sub for each element found in :

 - datasetExportJobs, passing the object as the first parameter, and the string 'datasetExportJobs' as the second parameter

If not, it will return a a Paws::Personalize::ListDatasetExportJobsResponse instance with all the "param"s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.

If passed a sub as first parameter, it will call the sub for each element found in :

 - datasetGroups, passing the object as the first parameter, and the string 'datasetGroups' as the second parameter

If not, it will return a a Paws::Personalize::ListDatasetGroupsResponse instance with all the "param"s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.

If passed a sub as first parameter, it will call the sub for each element found in :

 - datasetImportJobs, passing the object as the first parameter, and the string 'datasetImportJobs' as the second parameter

If not, it will return a a Paws::Personalize::ListDatasetImportJobsResponse instance with all the "param"s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.

If passed a sub as first parameter, it will call the sub for each element found in :

 - datasets, passing the object as the first parameter, and the string 'datasets' as the second parameter

If not, it will return a a Paws::Personalize::ListDatasetsResponse instance with all the "param"s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.

If passed a sub as first parameter, it will call the sub for each element found in :

 - eventTrackers, passing the object as the first parameter, and the string 'eventTrackers' as the second parameter

If not, it will return a a Paws::Personalize::ListEventTrackersResponse instance with all the "param"s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.

If passed a sub as first parameter, it will call the sub for each element found in :

 - Filters, passing the object as the first parameter, and the string 'Filters' as the second parameter

If not, it will return a a Paws::Personalize::ListFiltersResponse instance with all the "param"s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.

If passed a sub as first parameter, it will call the sub for each element found in :

 - recipes, passing the object as the first parameter, and the string 'recipes' as the second parameter

If not, it will return a a Paws::Personalize::ListRecipesResponse instance with all the "param"s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.

If passed a sub as first parameter, it will call the sub for each element found in :

 - schemas, passing the object as the first parameter, and the string 'schemas' as the second parameter

If not, it will return a a Paws::Personalize::ListSchemasResponse instance with all the "param"s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.

If passed a sub as first parameter, it will call the sub for each element found in :

 - solutions, passing the object as the first parameter, and the string 'solutions' as the second parameter

If not, it will return a a Paws::Personalize::ListSolutionsResponse instance with all the "param"s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.

If passed a sub as first parameter, it will call the sub for each element found in :

 - solutionVersions, passing the object as the first parameter, and the string 'solutionVersions' as the second parameter

If not, it will return a a Paws::Personalize::ListSolutionVersionsResponse instance with all the "param"s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.

This service class forms part of Paws

The source code is located here: <https://github.com/pplu/aws-sdk-perl>

Please report bugs to: <https://github.com/pplu/aws-sdk-perl/issues>

2022-06-01 perl v5.40.2

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