Class: Aws::SageMaker::Types::AutoMLComputeConfig

Inherits:

Struct

• Object
• Struct
• Aws::SageMaker::Types::AutoMLComputeConfig

Includes:

Aws::Structure

Defined in:

lib/aws-sdk-sagemaker/types.rb

Overview

<note markdown=“1”> This data type is intended for use exclusively by SageMaker Canvas and cannot be used in other contexts at the moment.

</note>

Specifies the compute configuration for an AutoML job V2.

See Also:

• AWS API Documentation

Constant Summary

SENSITIVE =

[]

Instance Attribute Summary

• #emr_serverless_compute_config ⇒ Types::EmrServerlessComputeConfig

  The configuration for using [ EMR Serverless] to run the AutoML job V2.

Instance Attribute Details

#emr_serverless_compute_config ⇒ Types::EmrServerlessComputeConfig

The configuration for using [ EMR Serverless] to run the AutoML job V2.

To allow your AutoML job V2 to automatically initiate a remote job on EMR Serverless when additional compute resources are needed to process large datasets, you need to provide an ‘EmrServerlessComputeConfig` object, which includes an `ExecutionRoleARN` attribute, to the `AutoMLComputeConfig` of the AutoML job V2 input request.

By seamlessly transitioning to EMR Serverless when required, the AutoML job can handle datasets that would otherwise exceed the initially provisioned resources, without any manual intervention from you.

EMR Serverless is available for the tabular and time series problem types. We recommend setting up this option for tabular datasets larger than 5 GB and time series datasets larger than 30 GB.

[1]: docs.aws.amazon.com/emr/latest/EMR-Serverless-UserGuide/emr-serverless.html

Returns:

• (Types::EmrServerlessComputeConfig)

# File 'lib/aws-sdk-sagemaker/types.rb', line 2134

class AutoMLComputeConfig < Struct.new(
  :emr_serverless_compute_config)
  SENSITIVE = []
  include Aws::Structure
end