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v1

latestOpenAPI 3.0.0Apache 2.0 License2026-07-1463278347.3 KB

Imports your training data to an Amazon Forecast dataset. You provide the location of your training data in an Amazon Simple Storage Service (Amazon S3) bucket and the Amazon Resource Name (ARN) of the dataset that you want to import the data to.

You must specify a DataSource object that includes an Identity and Access Management (IAM) role that Amazon Forecast can assume to access the data, as Amazon Forecast makes a copy of your data and processes it in an internal Amazon Web Services system. For more information, see Set up permissions.

The training data must be in CSV or Parquet format. The delimiter must be a comma (,).

You can specify the path to a specific file, the S3 bucket, or to a folder in the S3 bucket. For the latter two cases, Amazon Forecast imports all files up to the limit of 10,000 files.

Because dataset imports are not aggregated, your most recent dataset import is the one that is used when training a predictor or generating a forecast. Make sure that your most recent dataset import contains all of the data you want to model off of, and not just the new data collected since the previous import.

To get a list of all your dataset import jobs, filtered by specified criteria, use the ListDatasetImportJobs operation.

post/#X-Amz-Target=AmazonForecast.CreateDatasetImportJob

Headers

X-Amz-Target'AmazonForecast.CreateDatasetImportJob' required

Request body

DatasetImportJobNamestring required

The name for the dataset import job. We recommend including the current timestamp in the name, for example, <code>20190721DatasetImport</code>. This can help you avoid getting a <code>ResourceAlreadyExistsException</code> exception.

DatasetArnstring required

The Amazon Resource Name (ARN) of the Amazon Forecast dataset that you want to import data to.

TimestampFormatstring
<p>The format of timestamps in the dataset. The format that you specify depends on the <code>DataFrequency</code> specified when the dataset was created. The following formats are supported</p> <ul> <li> <p>"yyyy-MM-dd"</p> <p>For the following data frequencies: Y, M, W, and D</p> </li> <li> <p>"yyyy-MM-dd HH:mm:ss"</p> <p>For the following data frequencies: H, 30min, 15min, and 1min; and optionally, for: Y, M, W, and D</p> </li> </ul> <p>If the format isn't specified, Amazon Forecast expects the format to be "yyyy-MM-dd HH:mm:ss".</p>
TimeZonestring
<p>A single time zone for every item in your dataset. This option is ideal for datasets with all timestamps within a single time zone, or if all timestamps are normalized to a single time zone. </p> <p>Refer to the <a href="http://joda-time.sourceforge.net/timezones.html">Joda-Time API</a> for a complete list of valid time zone names.</p>
UseGeolocationForTimeZoneboolean

Automatically derive time zone information from the geolocation attribute. This option is ideal for datasets that contain timestamps in multiple time zones and those timestamps are expressed in local time.

GeolocationFormatstring
<p>The format of the geolocation attribute. The geolocation attribute can be formatted in one of two ways:</p> <ul> <li> <p> <code>LAT_LONG</code> - the latitude and longitude in decimal format (Example: 47.61_-122.33).</p> </li> <li> <p> <code>CC_POSTALCODE</code> (US Only) - the country code (US), followed by the 5-digit ZIP code (Example: US_98121).</p> </li> </ul>
Formatstring

The format of the imported data, CSV or PARQUET. The default value is CSV.

ImportMode'FULL' | 'INCREMENTAL'

Specifies whether the dataset import job is a <code>FULL</code> or <code>INCREMENTAL</code> import. A <code>FULL</code> dataset import replaces all of the existing data with the newly imported data. An <code>INCREMENTAL</code> import appends the imported data to the existing data.

Response

Success

DatasetImportJobArnstring

The Amazon Resource Name (ARN) of the dataset import job.