Struct aws_sdk_sagemaker::types::AutoMlComputeConfig

#[non_exhaustive]
pub struct AutoMlComputeConfig {
    pub emr_serverless_compute_config: Option<EmrServerlessComputeConfig>,
}

This data type is intended for use exclusively by SageMaker Canvas and cannot be used in other contexts at the moment.

Specifies the compute configuration for an AutoML job V2.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

emr_serverless_compute_config: Option<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.

Implementations

impl AutoMlComputeConfig

pub fn emr_serverless_compute_config( &self, ) -> Option<&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.

impl AutoMlComputeConfig

pub fn builder() -> AutoMlComputeConfigBuilder

Creates a new builder-style object to manufacture AutoMlComputeConfig.

Trait Implementations

impl Clone for AutoMlComputeConfig

fn clone(&self) -> AutoMlComputeConfig

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for AutoMlComputeConfig

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq for AutoMlComputeConfig

fn eq(&self, other: &AutoMlComputeConfig) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for AutoMlComputeConfig