Method: Aws::ForecastService::Client#create_dataset_import_job
- Defined in:
- lib/aws-sdk-forecastservice/client.rb
#create_dataset_import_job(params = {}) ⇒ Types::CreateDatasetImportJobResponse
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.
[1]: docs.aws.amazon.com/forecast/latest/dg/API_DataSource.html [2]: docs.aws.amazon.com/forecast/latest/dg/aws-forecast-iam-roles.html [3]: docs.aws.amazon.com/forecast/latest/dg/API_ListDatasetImportJobs.html
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# File 'lib/aws-sdk-forecastservice/client.rb', line 1204 def create_dataset_import_job(params = {}, = {}) req = build_request(:create_dataset_import_job, params) req.send_request() end |