forecastservice_list_dataset_import_jobs: Returns a list of dataset import jobs created using the...

View source: R/forecastservice_operations.R

forecastservice_list_dataset_import_jobsR Documentation

Returns a list of dataset import jobs created using the CreateDatasetImportJob operation

Description

Returns a list of dataset import jobs created using the create_dataset_import_job operation. For each import job, this operation returns a summary of its properties, including its Amazon Resource Name (ARN). You can retrieve the complete set of properties by using the ARN with the describe_dataset_import_job operation. You can filter the list by providing an array of Filter objects.

See https://www.paws-r-sdk.com/docs/forecastservice_list_dataset_import_jobs/ for full documentation.

Usage

forecastservice_list_dataset_import_jobs(
  NextToken = NULL,
  MaxResults = NULL,
  Filters = NULL
)

Arguments

NextToken

If the result of the previous request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request. Tokens expire after 24 hours.

MaxResults

The number of items to return in the response.

Filters

An array of filters. For each filter, you provide a condition and a match statement. The condition is either IS or IS_NOT, which specifies whether to include or exclude the datasets that match the statement from the list, respectively. The match statement consists of a key and a value.

Filter properties

  • Condition - The condition to apply. Valid values are IS and IS_NOT. To include the datasets that match the statement, specify IS. To exclude matching datasets, specify IS_NOT.

  • Key - The name of the parameter to filter on. Valid values are DatasetArn and Status.

  • Value - The value to match.

For example, to list all dataset import jobs whose status is ACTIVE, you specify the following filter:

⁠"Filters": [ { "Condition": "IS", "Key": "Status", "Value": "ACTIVE" } ]⁠


paws.machine.learning documentation built on Sept. 12, 2024, 6:23 a.m.