#[non_exhaustive]
pub struct ProcessingJob {
Show 22 fields pub processing_inputs: Option<Vec<ProcessingInput>>, pub processing_output_config: Option<ProcessingOutputConfig>, pub processing_job_name: Option<String>, pub processing_resources: Option<ProcessingResources>, pub stopping_condition: Option<ProcessingStoppingCondition>, pub app_specification: Option<AppSpecification>, pub environment: Option<HashMap<String, String>>, pub network_config: Option<NetworkConfig>, pub role_arn: Option<String>, pub experiment_config: Option<ExperimentConfig>, pub processing_job_arn: Option<String>, pub processing_job_status: Option<ProcessingJobStatus>, pub exit_message: Option<String>, pub failure_reason: Option<String>, pub processing_end_time: Option<DateTime>, pub processing_start_time: Option<DateTime>, pub last_modified_time: Option<DateTime>, pub creation_time: Option<DateTime>, pub monitoring_schedule_arn: Option<String>, pub auto_ml_job_arn: Option<String>, pub training_job_arn: Option<String>, pub tags: Option<Vec<Tag>>,
}
Expand description

An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more information, see Process Data and Evaluate Models.

Fields (Non-exhaustive)

This struct is marked as 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.
processing_inputs: Option<Vec<ProcessingInput>>

List of input configurations for the processing job.

processing_output_config: Option<ProcessingOutputConfig>

Configuration for uploading output from the processing container.

processing_job_name: Option<String>

The name of the processing job.

processing_resources: Option<ProcessingResources>

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.

stopping_condition: Option<ProcessingStoppingCondition>

Configures conditions under which the processing job should be stopped, such as how long the processing job has been running. After the condition is met, the processing job is stopped.

app_specification: Option<AppSpecification>

Configuration to run a processing job in a specified container image.

environment: Option<HashMap<String, String>>

Sets the environment variables in the Docker container.

network_config: Option<NetworkConfig>

Networking options for a job, such as network traffic encryption between containers, whether to allow inbound and outbound network calls to and from containers, and the VPC subnets and security groups to use for VPC-enabled jobs.

role_arn: Option<String>

The ARN of the role used to create the processing job.

experiment_config: Option<ExperimentConfig>

Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:

  • CreateProcessingJob

  • CreateTrainingJob

  • CreateTransformJob

processing_job_arn: Option<String>

The ARN of the processing job.

processing_job_status: Option<ProcessingJobStatus>

The status of the processing job.

exit_message: Option<String>

A string, up to one KB in size, that contains metadata from the processing container when the processing job exits.

failure_reason: Option<String>

A string, up to one KB in size, that contains the reason a processing job failed, if it failed.

processing_end_time: Option<DateTime>

The time that the processing job ended.

processing_start_time: Option<DateTime>

The time that the processing job started.

last_modified_time: Option<DateTime>

The time the processing job was last modified.

creation_time: Option<DateTime>

The time the processing job was created.

monitoring_schedule_arn: Option<String>

The ARN of a monitoring schedule for an endpoint associated with this processing job.

auto_ml_job_arn: Option<String>

The Amazon Resource Name (ARN) of the AutoML job associated with this processing job.

training_job_arn: Option<String>

The ARN of the training job associated with this processing job.

tags: Option<Vec<Tag>>

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.

Implementations

List of input configurations for the processing job.

Configuration for uploading output from the processing container.

The name of the processing job.

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.

Configures conditions under which the processing job should be stopped, such as how long the processing job has been running. After the condition is met, the processing job is stopped.

Configuration to run a processing job in a specified container image.

Sets the environment variables in the Docker container.

Networking options for a job, such as network traffic encryption between containers, whether to allow inbound and outbound network calls to and from containers, and the VPC subnets and security groups to use for VPC-enabled jobs.

The ARN of the role used to create the processing job.

Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:

  • CreateProcessingJob

  • CreateTrainingJob

  • CreateTransformJob

The ARN of the processing job.

The status of the processing job.

A string, up to one KB in size, that contains metadata from the processing container when the processing job exits.

A string, up to one KB in size, that contains the reason a processing job failed, if it failed.

The time that the processing job ended.

The time that the processing job started.

The time the processing job was last modified.

The time the processing job was created.

The ARN of a monitoring schedule for an endpoint associated with this processing job.

The Amazon Resource Name (ARN) of the AutoML job associated with this processing job.

The ARN of the training job associated with this processing job.

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.

Creates a new builder-style object to manufacture ProcessingJob

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