<p>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 <a href="https://docs.aws.amazon.com/personalize/latest/dg/granting-personalize-s3-access.html">Giving Amazon Personalize Access to Amazon S3 Resources</a>. </p> <important> <p>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.</p> </important> <p> <b>Status</b> </p> <p>A dataset import job can be in one of the following states:</p> <ul> <li> <p>CREATE PENDING &gt; CREATE IN_PROGRESS &gt; ACTIVE -or- CREATE FAILED</p> </li> </ul> <p>To get the status of the import job, call <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeDatasetImportJob.html">DescribeDatasetImportJob</a>, 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 <code>failureReason</code> key, which describes why the job failed.</p> <note> <p>Importing takes time. You must wait until the status shows as ACTIVE before training a model using the dataset.</p> </note> <p class="title"> <b>Related APIs</b> </p> <ul> <li> <p> <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_ListDatasetImportJobs.html">ListDatasetImportJobs</a> </p> </li> <li> <p> <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeDatasetImportJob.html">DescribeDatasetImportJob</a> </p> </li> </ul>

{
  "success": true,
  "data": {
    "id": "abc123",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

{
  "success": false,
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Invalid request parameters"
  }
}