sagemaker_create_processing_job: Creates a processing job
In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

sagemaker_create_processing_job

R Documentation

Creates a processing job

Description

Creates a processing job.

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

Usage

sagemaker_create_processing_job(
  ProcessingInputs = NULL,
  ProcessingOutputConfig = NULL,
  ProcessingJobName,
  ProcessingResources,
  StoppingCondition = NULL,
  AppSpecification,
  Environment = NULL,
  NetworkConfig = NULL,
  RoleArn,
  Tags = NULL,
  ExperimentConfig = NULL
)

Arguments

`ProcessingInputs`	An array of inputs configuring the data to download into the processing container.
`ProcessingOutputConfig`	Output configuration for the processing job.
`ProcessingJobName`	[required] The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
`ProcessingResources`	[required] Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
`StoppingCondition`	The time limit for how long the processing job is allowed to run.
`AppSpecification`	[required] Configures the processing job to run a specified Docker container image.
`Environment`	The environment variables to set in the Docker container. Up to 100 key and values entries in the map are supported.
`NetworkConfig`	Networking options for a processing job, such as whether to allow inbound and outbound network calls to and from processing containers, and the VPC subnets and security groups to use for VPC-enabled processing jobs.
`RoleArn`	[required] The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
`Tags`	(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
`ExperimentConfig`