Interface AutoMLComputeConfig.Builder

All Superinterfaces:
Buildable, CopyableBuilder<AutoMLComputeConfig.Builder,AutoMLComputeConfig>, SdkBuilder<AutoMLComputeConfig.Builder,AutoMLComputeConfig>, SdkPojo
Enclosing class:
AutoMLComputeConfig
public static interface AutoMLComputeConfig.Builder extends SdkPojo, CopyableBuilder<AutoMLComputeConfig.Builder,AutoMLComputeConfig>

  • Method Details

    • emrServerlessComputeConfig

      AutoMLComputeConfig.Builder emrServerlessComputeConfig(EmrServerlessComputeConfig 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.

      Parameters:
      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.

      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • emrServerlessComputeConfig

      default AutoMLComputeConfig.Builder emrServerlessComputeConfig(Consumer<EmrServerlessComputeConfig.Builder> 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.

      This is a convenience method that creates an instance of the EmrServerlessComputeConfig.Builder avoiding the need to create one manually via EmrServerlessComputeConfig.builder().

      When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to emrServerlessComputeConfig(EmrServerlessComputeConfig).

      Parameters:
      emrServerlessComputeConfig - a consumer that will call methods on EmrServerlessComputeConfig.Builder
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also: