To delete all of the data in a dataset, you delete the dataset. You can delete a dataset with the Amazon Personalize console, AWS Command Line Interface (AWS CLI), or AWS SDKs. Before you delete a dataset, note the following:
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You must delete all filters before deleting any dataset.
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If you created an event tracker, you must delete it before you delete an Item interactions dataset.
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If you created a metric attribution that references the dataset, you must delete the metric attribution first.
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If you use User-Personalization-v2, User-Personalization, or Next-Best-Action recipes or Top picks for you and Recommended for you use cases, deleting a dataset halts automatic updates for any associated solution versions or recommenders.
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No associated
DatasetImportJob
can have a status of CREATE PENDING or IN PROGRESS. -
No associated
BatchInferenceJob
orBatchSegmentJob
can have a status of CREATE PENDING or IN PROGRESS. -
No associated
Recommender
,SolutionVersion
can have a status of CREATE PENDING or IN PROGRESS. -
No associated
Campaign
can have a status of CREATE PENDING or IN PROGRESS or ACTIVE.
Deleting a dataset
(console)
To delete a dataset with the Amazon Personalize console, navigate to the dataset details page and choose delete.
To delete a dataset
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Open the Amazon Personalize console at https://console.aws.amazon.com/personalize/home
. -
In the navigation pane, choose Dataset groups.
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On the Dataset groups page, choose your dataset group.
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In the navigation pane, choose Datasets.
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Choose the dataset to open its details page.
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On the dataset's details page, choose Delete and confirm dataset deletion.
Deleting a dataset
(AWS CLI)
The following code shows how to delete a dataset with the AWS CLI and the DeleteDataset operation.
aws personalize delete-dataset --dataset-arn
dataset-arn
Deleting a dataset (AWS
SDKs)
The following code shows how to delete a dataset with the AWS SDKs and the DeleteDataset operation.
import boto3
personalize = boto3.client('personalize')
response = personalize.delete_dataset(
datasetArn = 'dataset ARN
'
)