AWS Cloud Control v1.32.0, Aug 13 25

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AWS Cloud Control v1.32.0 published on Wednesday, Aug 13, 2025 by Pulumi

pulumi/pulumi-aws-native

aws-native.sagemaker.ProcessingJob

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We recommend new projects start with resources from the AWS provider.

AWS Cloud Control v1.32.0 published on Wednesday, Aug 13, 2025 by Pulumi

pulumi/pulumi-aws-native

Create ProcessingJob Resource

Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

Constructor syntax

new ProcessingJob(name: string, args: ProcessingJobArgs, opts?: CustomResourceOptions);

@overload
def ProcessingJob(resource_name: str,
                  args: ProcessingJobArgs,
                  opts: Optional[ResourceOptions] = None)

@overload
def ProcessingJob(resource_name: str,
                  opts: Optional[ResourceOptions] = None,
                  app_specification: Optional[ProcessingJobAppSpecificationArgs] = None,
                  processing_resources: Optional[ProcessingJobProcessingResourcesArgs] = None,
                  role_arn: Optional[str] = None,
                  environment: Optional[ProcessingJobEnvironmentArgs] = None,
                  experiment_config: Optional[ProcessingJobExperimentConfigArgs] = None,
                  network_config: Optional[ProcessingJobNetworkConfigArgs] = None,
                  processing_inputs: Optional[Sequence[ProcessingJobProcessingInputsObjectArgs]] = None,
                  processing_job_name: Optional[str] = None,
                  processing_output_config: Optional[ProcessingJobProcessingOutputConfigArgs] = None,
                  stopping_condition: Optional[ProcessingJobStoppingConditionArgs] = None,
                  tags: Optional[Sequence[_root_inputs.CreateOnlyTagArgs]] = None)

func NewProcessingJob(ctx *Context, name string, args ProcessingJobArgs, opts ...ResourceOption) (*ProcessingJob, error)

public ProcessingJob(string name, ProcessingJobArgs args, CustomResourceOptions? opts = null)

public ProcessingJob(String name, ProcessingJobArgs args)
public ProcessingJob(String name, ProcessingJobArgs args, CustomResourceOptions options)

type: aws-native:sagemaker:ProcessingJob
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

Parameters

name string: The unique name of the resource.
args ProcessingJobArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

resource_name str: The unique name of the resource.
args ProcessingJobArgs: The arguments to resource properties.
opts ResourceOptions: Bag of options to control resource's behavior.

ctx Context: Context object for the current deployment.
name string: The unique name of the resource.
args ProcessingJobArgs: The arguments to resource properties.
opts ResourceOption: Bag of options to control resource's behavior.

name string: The unique name of the resource.
args ProcessingJobArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

name String: The unique name of the resource.
args ProcessingJobArgs: The arguments to resource properties.
options CustomResourceOptions: Bag of options to control resource's behavior.

ProcessingJob Resource Properties

To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

Inputs

In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

The ProcessingJob resource accepts the following input properties:

AppSpecification Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobAppSpecification: Configuration to run a processing job in a specified container image.
ProcessingResources Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobProcessingResources: 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.
RoleArn string: The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
Environment Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobEnvironment: Sets the environment variables in the Docker container.
ExperimentConfig Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobExperimentConfig: Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the CreateProcessingJob API.
NetworkConfig Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobNetworkConfig: 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.
ProcessingInputs List<Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobProcessingInputsObject>: An array of inputs configuring the data to download into the processing container.
ProcessingJobName string: The name of the processing job. The name must be unique within an AWS Region in the AWS account.
ProcessingOutputConfig Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobProcessingOutputConfig: Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice list, use TargetPlatform to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.
StoppingCondition Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobStoppingCondition: 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.
Tags List<Pulumi.AwsNative.Inputs.CreateOnlyTag>: (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags(https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL) in the AWS Billing and Cost Management User Guide.

AppSpecification ProcessingJobAppSpecificationArgs: Configuration to run a processing job in a specified container image.
ProcessingResources ProcessingJobProcessingResourcesArgs: 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.
RoleArn string: The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
Environment ProcessingJobEnvironmentArgs: Sets the environment variables in the Docker container.
ExperimentConfig ProcessingJobExperimentConfigArgs: Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the CreateProcessingJob API.
NetworkConfig ProcessingJobNetworkConfigArgs: 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.
ProcessingInputs []ProcessingJobProcessingInputsObjectArgs: An array of inputs configuring the data to download into the processing container.
ProcessingJobName string: The name of the processing job. The name must be unique within an AWS Region in the AWS account.
ProcessingOutputConfig ProcessingJobProcessingOutputConfigArgs: Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice list, use TargetPlatform to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.
StoppingCondition ProcessingJobStoppingConditionArgs: 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.
Tags CreateOnlyTagArgs: (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags(https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL) in the AWS Billing and Cost Management User Guide.

appSpecification ProcessingJobAppSpecification: Configuration to run a processing job in a specified container image.
processingResources ProcessingJobProcessingResources: 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.
roleArn String: The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
environment ProcessingJobEnvironment: Sets the environment variables in the Docker container.
experimentConfig ProcessingJobExperimentConfig: Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the CreateProcessingJob API.
networkConfig ProcessingJobNetworkConfig: 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.
processingInputs List<ProcessingJobProcessingInputsObject>: An array of inputs configuring the data to download into the processing container.
processingJobName String: The name of the processing job. The name must be unique within an AWS Region in the AWS account.
processingOutputConfig ProcessingJobProcessingOutputConfig: Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice list, use TargetPlatform to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.
stoppingCondition ProcessingJobStoppingCondition: 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.
tags List<CreateOnlyTag>: (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags(https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL) in the AWS Billing and Cost Management User Guide.

appSpecification ProcessingJobAppSpecification: Configuration to run a processing job in a specified container image.
processingResources ProcessingJobProcessingResources: 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.
roleArn string: The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
environment ProcessingJobEnvironment: Sets the environment variables in the Docker container.
experimentConfig ProcessingJobExperimentConfig: Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the CreateProcessingJob API.
networkConfig ProcessingJobNetworkConfig: 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.
processingInputs ProcessingJobProcessingInputsObject[]: An array of inputs configuring the data to download into the processing container.
processingJobName string: The name of the processing job. The name must be unique within an AWS Region in the AWS account.
processingOutputConfig ProcessingJobProcessingOutputConfig: Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice list, use TargetPlatform to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.
stoppingCondition ProcessingJobStoppingCondition: 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.
tags CreateOnlyTag[]: (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags(https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL) in the AWS Billing and Cost Management User Guide.

app_specification ProcessingJobAppSpecificationArgs: Configuration to run a processing job in a specified container image.
processing_resources ProcessingJobProcessingResourcesArgs: 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.
role_arn str: The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
environment ProcessingJobEnvironmentArgs: Sets the environment variables in the Docker container.
experiment_config ProcessingJobExperimentConfigArgs: Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the CreateProcessingJob API.
network_config ProcessingJobNetworkConfigArgs: 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.
processing_inputs Sequence[ProcessingJobProcessingInputsObjectArgs]: An array of inputs configuring the data to download into the processing container.
processing_job_name str: The name of the processing job. The name must be unique within an AWS Region in the AWS account.
processing_output_config ProcessingJobProcessingOutputConfigArgs: Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice list, use TargetPlatform to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.
stopping_condition ProcessingJobStoppingConditionArgs: 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.
tags Sequence[CreateOnlyTagArgs]: (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags(https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL) in the AWS Billing and Cost Management User Guide.

appSpecification Property Map: Configuration to run a processing job in a specified container image.
processingResources Property Map: 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.
roleArn String: The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
environment Property Map: Sets the environment variables in the Docker container.
experimentConfig Property Map: Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the CreateProcessingJob API.
networkConfig Property Map: 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.
processingInputs List<Property Map>: An array of inputs configuring the data to download into the processing container.
processingJobName String: The name of the processing job. The name must be unique within an AWS Region in the AWS account.
processingOutputConfig Property Map: Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice list, use TargetPlatform to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.
stoppingCondition Property Map: 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.
tags List<Property Map>: (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags(https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL) in the AWS Billing and Cost Management User Guide.

Outputs

All input properties are implicitly available as output properties. Additionally, the ProcessingJob resource produces the following output properties:

AutoMlJobArn string: The ARN of an AutoML job associated with this processing job.
CreationTime string: The time at which the processing job was created.
ExitMessage string: An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
FailureReason string: A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
Id string: The provider-assigned unique ID for this managed resource.
LastModifiedTime string: The time at which the processing job was last modified.
MonitoringScheduleArn string: The ARN of a monitoring schedule for an endpoint associated with this processing job.
ProcessingEndTime string: The time at which the processing job completed.
ProcessingJobArn string: The Amazon Resource Name (ARN) of the processing job.
ProcessingJobStatus Pulumi.AwsNative.SageMaker.ProcessingJobStatus: Provides the status of a processing job.
ProcessingStartTime string: The time at which the processing job started.
TrainingJobArn string: The ARN of a training job associated with this processing job

AutoMlJobArn string: The ARN of an AutoML job associated with this processing job.
CreationTime string: The time at which the processing job was created.
ExitMessage string: An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
FailureReason string: A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
Id string: The provider-assigned unique ID for this managed resource.
LastModifiedTime string: The time at which the processing job was last modified.
MonitoringScheduleArn string: The ARN of a monitoring schedule for an endpoint associated with this processing job.
ProcessingEndTime string: The time at which the processing job completed.
ProcessingJobArn string: The Amazon Resource Name (ARN) of the processing job.
ProcessingJobStatus ProcessingJobStatus: Provides the status of a processing job.
ProcessingStartTime string: The time at which the processing job started.
TrainingJobArn string: The ARN of a training job associated with this processing job

autoMlJobArn String: The ARN of an AutoML job associated with this processing job.
creationTime String: The time at which the processing job was created.
exitMessage String: An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
failureReason String: A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
id String: The provider-assigned unique ID for this managed resource.
lastModifiedTime String: The time at which the processing job was last modified.
monitoringScheduleArn String: The ARN of a monitoring schedule for an endpoint associated with this processing job.
processingEndTime String: The time at which the processing job completed.
processingJobArn String: The Amazon Resource Name (ARN) of the processing job.
processingJobStatus ProcessingJobStatus: Provides the status of a processing job.
processingStartTime String: The time at which the processing job started.
trainingJobArn String: The ARN of a training job associated with this processing job

autoMlJobArn string: The ARN of an AutoML job associated with this processing job.
creationTime string: The time at which the processing job was created.
exitMessage string: An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
failureReason string: A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
id string: The provider-assigned unique ID for this managed resource.
lastModifiedTime string: The time at which the processing job was last modified.
monitoringScheduleArn string: The ARN of a monitoring schedule for an endpoint associated with this processing job.
processingEndTime string: The time at which the processing job completed.
processingJobArn string: The Amazon Resource Name (ARN) of the processing job.
processingJobStatus ProcessingJobStatus: Provides the status of a processing job.
processingStartTime string: The time at which the processing job started.
trainingJobArn string: The ARN of a training job associated with this processing job

auto_ml_job_arn str: The ARN of an AutoML job associated with this processing job.
creation_time str: The time at which the processing job was created.
exit_message str: An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
failure_reason str: A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
id str: The provider-assigned unique ID for this managed resource.
last_modified_time str: The time at which the processing job was last modified.
monitoring_schedule_arn str: The ARN of a monitoring schedule for an endpoint associated with this processing job.
processing_end_time str: The time at which the processing job completed.
processing_job_arn str: The Amazon Resource Name (ARN) of the processing job.
processing_job_status ProcessingJobStatus: Provides the status of a processing job.
processing_start_time str: The time at which the processing job started.
training_job_arn str: The ARN of a training job associated with this processing job

autoMlJobArn String: The ARN of an AutoML job associated with this processing job.
creationTime String: The time at which the processing job was created.
exitMessage String: An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
failureReason String: A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
id String: The provider-assigned unique ID for this managed resource.
lastModifiedTime String: The time at which the processing job was last modified.
monitoringScheduleArn String: The ARN of a monitoring schedule for an endpoint associated with this processing job.
processingEndTime String: The time at which the processing job completed.
processingJobArn String: The Amazon Resource Name (ARN) of the processing job.
processingJobStatus "Completed" | "InProgress" | "Stopping" | "Stopped" | "Failed": Provides the status of a processing job.
processingStartTime String: The time at which the processing job started.
trainingJobArn String: The ARN of a training job associated with this processing job

Supporting Types

CreateOnlyTag, CreateOnlyTagArgs

Key string: The key name of the tag
Value string: The value of the tag

Key string: The key name of the tag
Value string: The value of the tag

key String: The key name of the tag
value String: The value of the tag

key string: The key name of the tag
value string: The value of the tag

key str: The key name of the tag
value str: The value of the tag

key String: The key name of the tag
value String: The value of the tag

ProcessingJobAppSpecification, ProcessingJobAppSpecificationArgs

ImageUri string: The container image to be run by the processing job.
ContainerArguments List<string>: The arguments for a container used to run a processing job.
ContainerEntrypoint List<string>: The entrypoint for a container used to run a processing job.

ImageUri string: The container image to be run by the processing job.
ContainerArguments []string: The arguments for a container used to run a processing job.
ContainerEntrypoint []string: The entrypoint for a container used to run a processing job.

imageUri String: The container image to be run by the processing job.
containerArguments List<String>: The arguments for a container used to run a processing job.
containerEntrypoint List<String>: The entrypoint for a container used to run a processing job.

imageUri string: The container image to be run by the processing job.
containerArguments string[]: The arguments for a container used to run a processing job.
containerEntrypoint string[]: The entrypoint for a container used to run a processing job.

image_uri str: The container image to be run by the processing job.
container_arguments Sequence[str]: The arguments for a container used to run a processing job.
container_entrypoint Sequence[str]: The entrypoint for a container used to run a processing job.

imageUri String: The container image to be run by the processing job.
containerArguments List<String>: The arguments for a container used to run a processing job.
containerEntrypoint List<String>: The entrypoint for a container used to run a processing job.

ProcessingJobAthenaDatasetDefinition, ProcessingJobAthenaDatasetDefinitionArgs

Catalog string: The name of the data catalog used in Athena query execution.
Database string: The name of the database used in the Athena query execution.
OutputFormat Pulumi.AwsNative.SageMaker.ProcessingJobAthenaDatasetDefinitionOutputFormat: The data storage format for Athena query results.
OutputS3Uri string: The location in Amazon S3 where Athena query results are stored.
QueryString string: The SQL query statements, to be executed.
KmsKeyId string: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data generated from an Athena query execution.
OutputCompression Pulumi.AwsNative.SageMaker.ProcessingJobAthenaDatasetDefinitionOutputCompression: The compression used for Athena query results.
WorkGroup string: The name of the workgroup in which the Athena query is being started.

Catalog string: The name of the data catalog used in Athena query execution.
Database string: The name of the database used in the Athena query execution.
OutputFormat ProcessingJobAthenaDatasetDefinitionOutputFormat: The data storage format for Athena query results.
OutputS3Uri string: The location in Amazon S3 where Athena query results are stored.
QueryString string: The SQL query statements, to be executed.
KmsKeyId string: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data generated from an Athena query execution.
OutputCompression ProcessingJobAthenaDatasetDefinitionOutputCompression: The compression used for Athena query results.
WorkGroup string: The name of the workgroup in which the Athena query is being started.

catalog String: The name of the data catalog used in Athena query execution.
database String: The name of the database used in the Athena query execution.
outputFormat ProcessingJobAthenaDatasetDefinitionOutputFormat: The data storage format for Athena query results.
outputS3Uri String: The location in Amazon S3 where Athena query results are stored.
queryString String: The SQL query statements, to be executed.
kmsKeyId String: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data generated from an Athena query execution.
outputCompression ProcessingJobAthenaDatasetDefinitionOutputCompression: The compression used for Athena query results.
workGroup String: The name of the workgroup in which the Athena query is being started.

catalog string: The name of the data catalog used in Athena query execution.
database string: The name of the database used in the Athena query execution.
outputFormat ProcessingJobAthenaDatasetDefinitionOutputFormat: The data storage format for Athena query results.
outputS3Uri string: The location in Amazon S3 where Athena query results are stored.
queryString string: The SQL query statements, to be executed.
kmsKeyId string: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data generated from an Athena query execution.
outputCompression ProcessingJobAthenaDatasetDefinitionOutputCompression: The compression used for Athena query results.
workGroup string: The name of the workgroup in which the Athena query is being started.

catalog str: The name of the data catalog used in Athena query execution.
database str: The name of the database used in the Athena query execution.
output_format ProcessingJobAthenaDatasetDefinitionOutputFormat: The data storage format for Athena query results.
output_s3_uri str: The location in Amazon S3 where Athena query results are stored.
query_string str: The SQL query statements, to be executed.
kms_key_id str: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data generated from an Athena query execution.
output_compression ProcessingJobAthenaDatasetDefinitionOutputCompression: The compression used for Athena query results.
work_group str: The name of the workgroup in which the Athena query is being started.

catalog String: The name of the data catalog used in Athena query execution.
database String: The name of the database used in the Athena query execution.
outputFormat "PARQUET" | "AVRO" | "ORC" | "JSON" | "TEXTFILE": The data storage format for Athena query results.
outputS3Uri String: The location in Amazon S3 where Athena query results are stored.
queryString String: The SQL query statements, to be executed.
kmsKeyId String: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data generated from an Athena query execution.
outputCompression "GZIP" | "SNAPPY" | "ZLIB": The compression used for Athena query results.
workGroup String: The name of the workgroup in which the Athena query is being started.

ProcessingJobAthenaDatasetDefinitionOutputCompression, ProcessingJobAthenaDatasetDefinitionOutputCompressionArgs

Gzip: GZIP
Snappy: SNAPPY
Zlib: ZLIB

ProcessingJobAthenaDatasetDefinitionOutputCompressionGzip: GZIP
ProcessingJobAthenaDatasetDefinitionOutputCompressionSnappy: SNAPPY
ProcessingJobAthenaDatasetDefinitionOutputCompressionZlib: ZLIB

Gzip: GZIP
Snappy: SNAPPY
Zlib: ZLIB

Gzip: GZIP
Snappy: SNAPPY
Zlib: ZLIB

GZIP: GZIP
SNAPPY: SNAPPY
ZLIB: ZLIB

"GZIP": GZIP
"SNAPPY": SNAPPY
"ZLIB": ZLIB

ProcessingJobAthenaDatasetDefinitionOutputFormat, ProcessingJobAthenaDatasetDefinitionOutputFormatArgs

Parquet: PARQUET
Avro: AVRO
Orc: ORC
Json: JSON
Textfile: TEXTFILE

ProcessingJobAthenaDatasetDefinitionOutputFormatParquet: PARQUET
ProcessingJobAthenaDatasetDefinitionOutputFormatAvro: AVRO
ProcessingJobAthenaDatasetDefinitionOutputFormatOrc: ORC
ProcessingJobAthenaDatasetDefinitionOutputFormatJson: JSON
ProcessingJobAthenaDatasetDefinitionOutputFormatTextfile: TEXTFILE

Parquet: PARQUET
Avro: AVRO
Orc: ORC
Json: JSON
Textfile: TEXTFILE

Parquet: PARQUET
Avro: AVRO
Orc: ORC
Json: JSON
Textfile: TEXTFILE

PARQUET: PARQUET
AVRO: AVRO
ORC: ORC
JSON: JSON
TEXTFILE: TEXTFILE

"PARQUET": PARQUET
"AVRO": AVRO
"ORC": ORC
"JSON": JSON
"TEXTFILE": TEXTFILE

ProcessingJobClusterConfig, ProcessingJobClusterConfigArgs

InstanceCount int: The number of ML compute instances to use in the processing job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
InstanceType Pulumi.AwsNative.SageMaker.ProcessingJobClusterConfigInstanceType: The ML compute instance type for the processing job.
VolumeSizeInGb int: The size of the ML storage volume in gigabytes that you want to provision. You must specify sufficient ML storage for your scenario.
VolumeKmsKeyId string: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the processing job.

InstanceCount int: The number of ML compute instances to use in the processing job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
InstanceType ProcessingJobClusterConfigInstanceType: The ML compute instance type for the processing job.
VolumeSizeInGb int: The size of the ML storage volume in gigabytes that you want to provision. You must specify sufficient ML storage for your scenario.
VolumeKmsKeyId string: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the processing job.

instanceCount Integer: The number of ML compute instances to use in the processing job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
instanceType ProcessingJobClusterConfigInstanceType: The ML compute instance type for the processing job.
volumeSizeInGb Integer: The size of the ML storage volume in gigabytes that you want to provision. You must specify sufficient ML storage for your scenario.
volumeKmsKeyId String: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the processing job.

instanceCount number: The number of ML compute instances to use in the processing job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
instanceType ProcessingJobClusterConfigInstanceType: The ML compute instance type for the processing job.
volumeSizeInGb number: The size of the ML storage volume in gigabytes that you want to provision. You must specify sufficient ML storage for your scenario.
volumeKmsKeyId string: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the processing job.

instance_count int: The number of ML compute instances to use in the processing job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
instance_type ProcessingJobClusterConfigInstanceType: The ML compute instance type for the processing job.
volume_size_in_gb int: The size of the ML storage volume in gigabytes that you want to provision. You must specify sufficient ML storage for your scenario.
volume_kms_key_id str: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the processing job.

instanceCount Number: The number of ML compute instances to use in the processing job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
instanceType "ml.t3.medium" | "ml.t3.large" | "ml.t3.xlarge" | "ml.t3.2xlarge" | "ml.m4.xlarge" | "ml.m4.2xlarge" | "ml.m4.4xlarge" | "ml.m4.10xlarge" | "ml.m4.16xlarge" | "ml.c4.xlarge" | "ml.c4.2xlarge" | "ml.c4.4xlarge" | "ml.c4.8xlarge" | "ml.c5.xlarge" | "ml.c5.2xlarge" | "ml.c5.4xlarge" | "ml.c5.9xlarge" | "ml.c5.18xlarge" | "ml.m5.large" | "ml.m5.xlarge" | "ml.m5.2xlarge" | "ml.m5.4xlarge" | "ml.m5.12xlarge" | "ml.m5.24xlarge" | "ml.r5.large" | "ml.r5.xlarge" | "ml.r5.2xlarge" | "ml.r5.4xlarge" | "ml.r5.8xlarge" | "ml.r5.12xlarge" | "ml.r5.16xlarge" | "ml.r5.24xlarge" | "ml.g4dn.xlarge" | "ml.g4dn.2xlarge" | "ml.g4dn.4xlarge" | "ml.g4dn.8xlarge" | "ml.g4dn.12xlarge" | "ml.g4dn.16xlarge" | "ml.g5.xlarge" | "ml.g5.2xlarge" | "ml.g5.4xlarge" | "ml.g5.8xlarge" | "ml.g5.16xlarge" | "ml.g5.12xlarge" | "ml.g5.24xlarge" | "ml.g5.48xlarge" | "ml.r5d.large" | "ml.r5d.xlarge" | "ml.r5d.2xlarge" | "ml.r5d.4xlarge" | "ml.r5d.8xlarge" | "ml.r5d.12xlarge" | "ml.r5d.16xlarge" | "ml.r5d.24xlarge" | "ml.g6.xlarge" | "ml.g6.2xlarge" | "ml.g6.4xlarge" | "ml.g6.8xlarge" | "ml.g6.12xlarge" | "ml.g6.16xlarge" | "ml.g6.24xlarge" | "ml.g6.48xlarge" | "ml.g6e.xlarge" | "ml.g6e.2xlarge" | "ml.g6e.4xlarge" | "ml.g6e.8xlarge" | "ml.g6e.12xlarge" | "ml.g6e.16xlarge" | "ml.g6e.24xlarge" | "ml.g6e.48xlarge" | "ml.m6i.large" | "ml.m6i.xlarge" | "ml.m6i.2xlarge" | "ml.m6i.4xlarge" | "ml.m6i.8xlarge" | "ml.m6i.12xlarge" | "ml.m6i.16xlarge" | "ml.m6i.24xlarge" | "ml.m6i.32xlarge" | "ml.c6i.xlarge" | "ml.c6i.2xlarge" | "ml.c6i.4xlarge" | "ml.c6i.8xlarge" | "ml.c6i.12xlarge" | "ml.c6i.16xlarge" | "ml.c6i.24xlarge" | "ml.c6i.32xlarge" | "ml.m7i.large" | "ml.m7i.xlarge" | "ml.m7i.2xlarge" | "ml.m7i.4xlarge" | "ml.m7i.8xlarge" | "ml.m7i.12xlarge" | "ml.m7i.16xlarge" | "ml.m7i.24xlarge" | "ml.m7i.48xlarge" | "ml.c7i.large" | "ml.c7i.xlarge" | "ml.c7i.2xlarge" | "ml.c7i.4xlarge" | "ml.c7i.8xlarge" | "ml.c7i.12xlarge" | "ml.c7i.16xlarge" | "ml.c7i.24xlarge" | "ml.c7i.48xlarge" | "ml.r7i.large" | "ml.r7i.xlarge" | "ml.r7i.2xlarge" | "ml.r7i.4xlarge" | "ml.r7i.8xlarge" | "ml.r7i.12xlarge" | "ml.r7i.16xlarge" | "ml.r7i.24xlarge" | "ml.r7i.48xlarge": The ML compute instance type for the processing job.
volumeSizeInGb Number: The size of the ML storage volume in gigabytes that you want to provision. You must specify sufficient ML storage for your scenario.
volumeKmsKeyId String: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the processing job.

ProcessingJobClusterConfigInstanceType, ProcessingJobClusterConfigInstanceTypeArgs

MlT3Medium: ml.t3.medium
MlT3Large: ml.t3.large
MlT3Xlarge: ml.t3.xlarge
MlT32xlarge: ml.t3.2xlarge
MlM4Xlarge: ml.m4.xlarge
MlM42xlarge: ml.m4.2xlarge
MlM44xlarge: ml.m4.4xlarge
MlM410xlarge: ml.m4.10xlarge
MlM416xlarge: ml.m4.16xlarge
MlC4Xlarge: ml.c4.xlarge
MlC42xlarge: ml.c4.2xlarge
MlC44xlarge: ml.c4.4xlarge
MlC48xlarge: ml.c4.8xlarge
MlC5Xlarge: ml.c5.xlarge
MlC52xlarge: ml.c5.2xlarge
MlC54xlarge: ml.c5.4xlarge
MlC59xlarge: ml.c5.9xlarge
MlC518xlarge: ml.c5.18xlarge
MlM5Large: ml.m5.large
MlM5Xlarge: ml.m5.xlarge
MlM52xlarge: ml.m5.2xlarge
MlM54xlarge: ml.m5.4xlarge
MlM512xlarge: ml.m5.12xlarge
MlM524xlarge: ml.m5.24xlarge
MlR5Large: ml.r5.large
MlR5Xlarge: ml.r5.xlarge
MlR52xlarge: ml.r5.2xlarge
MlR54xlarge: ml.r5.4xlarge
MlR58xlarge: ml.r5.8xlarge
MlR512xlarge: ml.r5.12xlarge
MlR516xlarge: ml.r5.16xlarge
MlR524xlarge: ml.r5.24xlarge
MlG4dnXlarge: ml.g4dn.xlarge
MlG4dn2xlarge: ml.g4dn.2xlarge
MlG4dn4xlarge: ml.g4dn.4xlarge
MlG4dn8xlarge: ml.g4dn.8xlarge
MlG4dn12xlarge: ml.g4dn.12xlarge
MlG4dn16xlarge: ml.g4dn.16xlarge
MlG5Xlarge: ml.g5.xlarge
MlG52xlarge: ml.g5.2xlarge
MlG54xlarge: ml.g5.4xlarge
MlG58xlarge: ml.g5.8xlarge
MlG516xlarge: ml.g5.16xlarge
MlG512xlarge: ml.g5.12xlarge
MlG524xlarge: ml.g5.24xlarge
MlG548xlarge: ml.g5.48xlarge
MlR5dLarge: ml.r5d.large
MlR5dXlarge: ml.r5d.xlarge
MlR5d2xlarge: ml.r5d.2xlarge
MlR5d4xlarge: ml.r5d.4xlarge
MlR5d8xlarge: ml.r5d.8xlarge
MlR5d12xlarge: ml.r5d.12xlarge
MlR5d16xlarge: ml.r5d.16xlarge
MlR5d24xlarge: ml.r5d.24xlarge
MlG6Xlarge: ml.g6.xlarge
MlG62xlarge: ml.g6.2xlarge
MlG64xlarge: ml.g6.4xlarge
MlG68xlarge: ml.g6.8xlarge
MlG612xlarge: ml.g6.12xlarge
MlG616xlarge: ml.g6.16xlarge
MlG624xlarge: ml.g6.24xlarge
MlG648xlarge: ml.g6.48xlarge
MlG6eXlarge: ml.g6e.xlarge
MlG6e2xlarge: ml.g6e.2xlarge
MlG6e4xlarge: ml.g6e.4xlarge
MlG6e8xlarge: ml.g6e.8xlarge
MlG6e12xlarge: ml.g6e.12xlarge
MlG6e16xlarge: ml.g6e.16xlarge
MlG6e24xlarge: ml.g6e.24xlarge
MlG6e48xlarge: ml.g6e.48xlarge
MlM6iLarge: ml.m6i.large
MlM6iXlarge: ml.m6i.xlarge
MlM6i2xlarge: ml.m6i.2xlarge
MlM6i4xlarge: ml.m6i.4xlarge
MlM6i8xlarge: ml.m6i.8xlarge
MlM6i12xlarge: ml.m6i.12xlarge
MlM6i16xlarge: ml.m6i.16xlarge
MlM6i24xlarge: ml.m6i.24xlarge
MlM6i32xlarge: ml.m6i.32xlarge
MlC6iXlarge: ml.c6i.xlarge
MlC6i2xlarge: ml.c6i.2xlarge
MlC6i4xlarge: ml.c6i.4xlarge
MlC6i8xlarge: ml.c6i.8xlarge
MlC6i12xlarge: ml.c6i.12xlarge
MlC6i16xlarge: ml.c6i.16xlarge
MlC6i24xlarge: ml.c6i.24xlarge
MlC6i32xlarge: ml.c6i.32xlarge
MlM7iLarge: ml.m7i.large
MlM7iXlarge: ml.m7i.xlarge
MlM7i2xlarge: ml.m7i.2xlarge
MlM7i4xlarge: ml.m7i.4xlarge
MlM7i8xlarge: ml.m7i.8xlarge
MlM7i12xlarge: ml.m7i.12xlarge
MlM7i16xlarge: ml.m7i.16xlarge
MlM7i24xlarge: ml.m7i.24xlarge
MlM7i48xlarge: ml.m7i.48xlarge
MlC7iLarge: ml.c7i.large
MlC7iXlarge: ml.c7i.xlarge
MlC7i2xlarge: ml.c7i.2xlarge
MlC7i4xlarge: ml.c7i.4xlarge
MlC7i8xlarge: ml.c7i.8xlarge
MlC7i12xlarge: ml.c7i.12xlarge
MlC7i16xlarge: ml.c7i.16xlarge
MlC7i24xlarge: ml.c7i.24xlarge
MlC7i48xlarge: ml.c7i.48xlarge
MlR7iLarge: ml.r7i.large
MlR7iXlarge: ml.r7i.xlarge
MlR7i2xlarge: ml.r7i.2xlarge
MlR7i4xlarge: ml.r7i.4xlarge
MlR7i8xlarge: ml.r7i.8xlarge
MlR7i12xlarge: ml.r7i.12xlarge
MlR7i16xlarge: ml.r7i.16xlarge
MlR7i24xlarge: ml.r7i.24xlarge
MlR7i48xlarge: ml.r7i.48xlarge

ProcessingJobClusterConfigInstanceTypeMlT3Medium: ml.t3.medium
ProcessingJobClusterConfigInstanceTypeMlT3Large: ml.t3.large
ProcessingJobClusterConfigInstanceTypeMlT3Xlarge: ml.t3.xlarge
ProcessingJobClusterConfigInstanceTypeMlT32xlarge: ml.t3.2xlarge
ProcessingJobClusterConfigInstanceTypeMlM4Xlarge: ml.m4.xlarge
ProcessingJobClusterConfigInstanceTypeMlM42xlarge: ml.m4.2xlarge
ProcessingJobClusterConfigInstanceTypeMlM44xlarge: ml.m4.4xlarge
ProcessingJobClusterConfigInstanceTypeMlM410xlarge: ml.m4.10xlarge
ProcessingJobClusterConfigInstanceTypeMlM416xlarge: ml.m4.16xlarge
ProcessingJobClusterConfigInstanceTypeMlC4Xlarge: ml.c4.xlarge
ProcessingJobClusterConfigInstanceTypeMlC42xlarge: ml.c4.2xlarge
ProcessingJobClusterConfigInstanceTypeMlC44xlarge: ml.c4.4xlarge
ProcessingJobClusterConfigInstanceTypeMlC48xlarge: ml.c4.8xlarge
ProcessingJobClusterConfigInstanceTypeMlC5Xlarge: ml.c5.xlarge
ProcessingJobClusterConfigInstanceTypeMlC52xlarge: ml.c5.2xlarge
ProcessingJobClusterConfigInstanceTypeMlC54xlarge: ml.c5.4xlarge
ProcessingJobClusterConfigInstanceTypeMlC59xlarge: ml.c5.9xlarge
ProcessingJobClusterConfigInstanceTypeMlC518xlarge: ml.c5.18xlarge
ProcessingJobClusterConfigInstanceTypeMlM5Large: ml.m5.large
ProcessingJobClusterConfigInstanceTypeMlM5Xlarge: ml.m5.xlarge
ProcessingJobClusterConfigInstanceTypeMlM52xlarge: ml.m5.2xlarge
ProcessingJobClusterConfigInstanceTypeMlM54xlarge: ml.m5.4xlarge
ProcessingJobClusterConfigInstanceTypeMlM512xlarge: ml.m5.12xlarge
ProcessingJobClusterConfigInstanceTypeMlM524xlarge: ml.m5.24xlarge
ProcessingJobClusterConfigInstanceTypeMlR5Large: ml.r5.large
ProcessingJobClusterConfigInstanceTypeMlR5Xlarge: ml.r5.xlarge
ProcessingJobClusterConfigInstanceTypeMlR52xlarge: ml.r5.2xlarge
ProcessingJobClusterConfigInstanceTypeMlR54xlarge: ml.r5.4xlarge
ProcessingJobClusterConfigInstanceTypeMlR58xlarge: ml.r5.8xlarge
ProcessingJobClusterConfigInstanceTypeMlR512xlarge: ml.r5.12xlarge
ProcessingJobClusterConfigInstanceTypeMlR516xlarge: ml.r5.16xlarge
ProcessingJobClusterConfigInstanceTypeMlR524xlarge: ml.r5.24xlarge
ProcessingJobClusterConfigInstanceTypeMlG4dnXlarge: ml.g4dn.xlarge
ProcessingJobClusterConfigInstanceTypeMlG4dn2xlarge: ml.g4dn.2xlarge
ProcessingJobClusterConfigInstanceTypeMlG4dn4xlarge: ml.g4dn.4xlarge
ProcessingJobClusterConfigInstanceTypeMlG4dn8xlarge: ml.g4dn.8xlarge
ProcessingJobClusterConfigInstanceTypeMlG4dn12xlarge: ml.g4dn.12xlarge
ProcessingJobClusterConfigInstanceTypeMlG4dn16xlarge: ml.g4dn.16xlarge
ProcessingJobClusterConfigInstanceTypeMlG5Xlarge: ml.g5.xlarge
ProcessingJobClusterConfigInstanceTypeMlG52xlarge: ml.g5.2xlarge
ProcessingJobClusterConfigInstanceTypeMlG54xlarge: ml.g5.4xlarge
ProcessingJobClusterConfigInstanceTypeMlG58xlarge: ml.g5.8xlarge
ProcessingJobClusterConfigInstanceTypeMlG516xlarge: ml.g5.16xlarge
ProcessingJobClusterConfigInstanceTypeMlG512xlarge: ml.g5.12xlarge
ProcessingJobClusterConfigInstanceTypeMlG524xlarge: ml.g5.24xlarge
ProcessingJobClusterConfigInstanceTypeMlG548xlarge: ml.g5.48xlarge
ProcessingJobClusterConfigInstanceTypeMlR5dLarge: ml.r5d.large
ProcessingJobClusterConfigInstanceTypeMlR5dXlarge: ml.r5d.xlarge
ProcessingJobClusterConfigInstanceTypeMlR5d2xlarge: ml.r5d.2xlarge
ProcessingJobClusterConfigInstanceTypeMlR5d4xlarge: ml.r5d.4xlarge
ProcessingJobClusterConfigInstanceTypeMlR5d8xlarge: ml.r5d.8xlarge
ProcessingJobClusterConfigInstanceTypeMlR5d12xlarge: ml.r5d.12xlarge
ProcessingJobClusterConfigInstanceTypeMlR5d16xlarge: ml.r5d.16xlarge
ProcessingJobClusterConfigInstanceTypeMlR5d24xlarge: ml.r5d.24xlarge
ProcessingJobClusterConfigInstanceTypeMlG6Xlarge: ml.g6.xlarge
ProcessingJobClusterConfigInstanceTypeMlG62xlarge: ml.g6.2xlarge
ProcessingJobClusterConfigInstanceTypeMlG64xlarge: ml.g6.4xlarge
ProcessingJobClusterConfigInstanceTypeMlG68xlarge: ml.g6.8xlarge
ProcessingJobClusterConfigInstanceTypeMlG612xlarge: ml.g6.12xlarge
ProcessingJobClusterConfigInstanceTypeMlG616xlarge: ml.g6.16xlarge
ProcessingJobClusterConfigInstanceTypeMlG624xlarge: ml.g6.24xlarge
ProcessingJobClusterConfigInstanceTypeMlG648xlarge: ml.g6.48xlarge
ProcessingJobClusterConfigInstanceTypeMlG6eXlarge: ml.g6e.xlarge
ProcessingJobClusterConfigInstanceTypeMlG6e2xlarge: ml.g6e.2xlarge
ProcessingJobClusterConfigInstanceTypeMlG6e4xlarge: ml.g6e.4xlarge
ProcessingJobClusterConfigInstanceTypeMlG6e8xlarge: ml.g6e.8xlarge
ProcessingJobClusterConfigInstanceTypeMlG6e12xlarge: ml.g6e.12xlarge
ProcessingJobClusterConfigInstanceTypeMlG6e16xlarge: ml.g6e.16xlarge
ProcessingJobClusterConfigInstanceTypeMlG6e24xlarge: ml.g6e.24xlarge
ProcessingJobClusterConfigInstanceTypeMlG6e48xlarge: ml.g6e.48xlarge
ProcessingJobClusterConfigInstanceTypeMlM6iLarge: ml.m6i.large
ProcessingJobClusterConfigInstanceTypeMlM6iXlarge: ml.m6i.xlarge
ProcessingJobClusterConfigInstanceTypeMlM6i2xlarge: ml.m6i.2xlarge
ProcessingJobClusterConfigInstanceTypeMlM6i4xlarge: ml.m6i.4xlarge
ProcessingJobClusterConfigInstanceTypeMlM6i8xlarge: ml.m6i.8xlarge
ProcessingJobClusterConfigInstanceTypeMlM6i12xlarge: ml.m6i.12xlarge
ProcessingJobClusterConfigInstanceTypeMlM6i16xlarge: ml.m6i.16xlarge
ProcessingJobClusterConfigInstanceTypeMlM6i24xlarge: ml.m6i.24xlarge
ProcessingJobClusterConfigInstanceTypeMlM6i32xlarge: ml.m6i.32xlarge
ProcessingJobClusterConfigInstanceTypeMlC6iXlarge: ml.c6i.xlarge
ProcessingJobClusterConfigInstanceTypeMlC6i2xlarge: ml.c6i.2xlarge
ProcessingJobClusterConfigInstanceTypeMlC6i4xlarge: ml.c6i.4xlarge
ProcessingJobClusterConfigInstanceTypeMlC6i8xlarge: ml.c6i.8xlarge
ProcessingJobClusterConfigInstanceTypeMlC6i12xlarge: ml.c6i.12xlarge
ProcessingJobClusterConfigInstanceTypeMlC6i16xlarge: ml.c6i.16xlarge
ProcessingJobClusterConfigInstanceTypeMlC6i24xlarge: ml.c6i.24xlarge
ProcessingJobClusterConfigInstanceTypeMlC6i32xlarge: ml.c6i.32xlarge
ProcessingJobClusterConfigInstanceTypeMlM7iLarge: ml.m7i.large
ProcessingJobClusterConfigInstanceTypeMlM7iXlarge: ml.m7i.xlarge
ProcessingJobClusterConfigInstanceTypeMlM7i2xlarge: ml.m7i.2xlarge
ProcessingJobClusterConfigInstanceTypeMlM7i4xlarge: ml.m7i.4xlarge
ProcessingJobClusterConfigInstanceTypeMlM7i8xlarge: ml.m7i.8xlarge
ProcessingJobClusterConfigInstanceTypeMlM7i12xlarge: ml.m7i.12xlarge
ProcessingJobClusterConfigInstanceTypeMlM7i16xlarge: ml.m7i.16xlarge
ProcessingJobClusterConfigInstanceTypeMlM7i24xlarge: ml.m7i.24xlarge
ProcessingJobClusterConfigInstanceTypeMlM7i48xlarge: ml.m7i.48xlarge
ProcessingJobClusterConfigInstanceTypeMlC7iLarge: ml.c7i.large
ProcessingJobClusterConfigInstanceTypeMlC7iXlarge: ml.c7i.xlarge
ProcessingJobClusterConfigInstanceTypeMlC7i2xlarge: ml.c7i.2xlarge
ProcessingJobClusterConfigInstanceTypeMlC7i4xlarge: ml.c7i.4xlarge
ProcessingJobClusterConfigInstanceTypeMlC7i8xlarge: ml.c7i.8xlarge
ProcessingJobClusterConfigInstanceTypeMlC7i12xlarge: ml.c7i.12xlarge
ProcessingJobClusterConfigInstanceTypeMlC7i16xlarge: ml.c7i.16xlarge
ProcessingJobClusterConfigInstanceTypeMlC7i24xlarge: ml.c7i.24xlarge
ProcessingJobClusterConfigInstanceTypeMlC7i48xlarge: ml.c7i.48xlarge
ProcessingJobClusterConfigInstanceTypeMlR7iLarge: ml.r7i.large
ProcessingJobClusterConfigInstanceTypeMlR7iXlarge: ml.r7i.xlarge
ProcessingJobClusterConfigInstanceTypeMlR7i2xlarge: ml.r7i.2xlarge
ProcessingJobClusterConfigInstanceTypeMlR7i4xlarge: ml.r7i.4xlarge
ProcessingJobClusterConfigInstanceTypeMlR7i8xlarge: ml.r7i.8xlarge
ProcessingJobClusterConfigInstanceTypeMlR7i12xlarge: ml.r7i.12xlarge
ProcessingJobClusterConfigInstanceTypeMlR7i16xlarge: ml.r7i.16xlarge
ProcessingJobClusterConfigInstanceTypeMlR7i24xlarge: ml.r7i.24xlarge
ProcessingJobClusterConfigInstanceTypeMlR7i48xlarge: ml.r7i.48xlarge

MlT3Medium: ml.t3.medium
MlT3Large: ml.t3.large
MlT3Xlarge: ml.t3.xlarge
MlT32xlarge: ml.t3.2xlarge
MlM4Xlarge: ml.m4.xlarge
MlM42xlarge: ml.m4.2xlarge
MlM44xlarge: ml.m4.4xlarge
MlM410xlarge: ml.m4.10xlarge
MlM416xlarge: ml.m4.16xlarge
MlC4Xlarge: ml.c4.xlarge
MlC42xlarge: ml.c4.2xlarge
MlC44xlarge: ml.c4.4xlarge
MlC48xlarge: ml.c4.8xlarge
MlC5Xlarge: ml.c5.xlarge
MlC52xlarge: ml.c5.2xlarge
MlC54xlarge: ml.c5.4xlarge
MlC59xlarge: ml.c5.9xlarge
MlC518xlarge: ml.c5.18xlarge
MlM5Large: ml.m5.large
MlM5Xlarge: ml.m5.xlarge
MlM52xlarge: ml.m5.2xlarge
MlM54xlarge: ml.m5.4xlarge
MlM512xlarge: ml.m5.12xlarge
MlM524xlarge: ml.m5.24xlarge
MlR5Large: ml.r5.large
MlR5Xlarge: ml.r5.xlarge
MlR52xlarge: ml.r5.2xlarge
MlR54xlarge: ml.r5.4xlarge
MlR58xlarge: ml.r5.8xlarge
MlR512xlarge: ml.r5.12xlarge
MlR516xlarge: ml.r5.16xlarge
MlR524xlarge: ml.r5.24xlarge
MlG4dnXlarge: ml.g4dn.xlarge
MlG4dn2xlarge: ml.g4dn.2xlarge
MlG4dn4xlarge: ml.g4dn.4xlarge
MlG4dn8xlarge: ml.g4dn.8xlarge
MlG4dn12xlarge: ml.g4dn.12xlarge
MlG4dn16xlarge: ml.g4dn.16xlarge
MlG5Xlarge: ml.g5.xlarge
MlG52xlarge: ml.g5.2xlarge
MlG54xlarge: ml.g5.4xlarge
MlG58xlarge: ml.g5.8xlarge
MlG516xlarge: ml.g5.16xlarge
MlG512xlarge: ml.g5.12xlarge
MlG524xlarge: ml.g5.24xlarge
MlG548xlarge: ml.g5.48xlarge
MlR5dLarge: ml.r5d.large
MlR5dXlarge: ml.r5d.xlarge
MlR5d2xlarge: ml.r5d.2xlarge
MlR5d4xlarge: ml.r5d.4xlarge
MlR5d8xlarge: ml.r5d.8xlarge
MlR5d12xlarge: ml.r5d.12xlarge
MlR5d16xlarge: ml.r5d.16xlarge
MlR5d24xlarge: ml.r5d.24xlarge
MlG6Xlarge: ml.g6.xlarge
MlG62xlarge: ml.g6.2xlarge
MlG64xlarge: ml.g6.4xlarge
MlG68xlarge: ml.g6.8xlarge
MlG612xlarge: ml.g6.12xlarge
MlG616xlarge: ml.g6.16xlarge
MlG624xlarge: ml.g6.24xlarge
MlG648xlarge: ml.g6.48xlarge
MlG6eXlarge: ml.g6e.xlarge
MlG6e2xlarge: ml.g6e.2xlarge
MlG6e4xlarge: ml.g6e.4xlarge
MlG6e8xlarge: ml.g6e.8xlarge
MlG6e12xlarge: ml.g6e.12xlarge
MlG6e16xlarge: ml.g6e.16xlarge
MlG6e24xlarge: ml.g6e.24xlarge
MlG6e48xlarge: ml.g6e.48xlarge
MlM6iLarge: ml.m6i.large
MlM6iXlarge: ml.m6i.xlarge
MlM6i2xlarge: ml.m6i.2xlarge
MlM6i4xlarge: ml.m6i.4xlarge
MlM6i8xlarge: ml.m6i.8xlarge
MlM6i12xlarge: ml.m6i.12xlarge
MlM6i16xlarge: ml.m6i.16xlarge
MlM6i24xlarge: ml.m6i.24xlarge
MlM6i32xlarge: ml.m6i.32xlarge
MlC6iXlarge: ml.c6i.xlarge
MlC6i2xlarge: ml.c6i.2xlarge
MlC6i4xlarge: ml.c6i.4xlarge
MlC6i8xlarge: ml.c6i.8xlarge
MlC6i12xlarge: ml.c6i.12xlarge
MlC6i16xlarge: ml.c6i.16xlarge
MlC6i24xlarge: ml.c6i.24xlarge
MlC6i32xlarge: ml.c6i.32xlarge
MlM7iLarge: ml.m7i.large
MlM7iXlarge: ml.m7i.xlarge
MlM7i2xlarge: ml.m7i.2xlarge
MlM7i4xlarge: ml.m7i.4xlarge
MlM7i8xlarge: ml.m7i.8xlarge
MlM7i12xlarge: ml.m7i.12xlarge
MlM7i16xlarge: ml.m7i.16xlarge
MlM7i24xlarge: ml.m7i.24xlarge
MlM7i48xlarge: ml.m7i.48xlarge
MlC7iLarge: ml.c7i.large
MlC7iXlarge: ml.c7i.xlarge
MlC7i2xlarge: ml.c7i.2xlarge
MlC7i4xlarge: ml.c7i.4xlarge
MlC7i8xlarge: ml.c7i.8xlarge
MlC7i12xlarge: ml.c7i.12xlarge
MlC7i16xlarge: ml.c7i.16xlarge
MlC7i24xlarge: ml.c7i.24xlarge
MlC7i48xlarge: ml.c7i.48xlarge
MlR7iLarge: ml.r7i.large
MlR7iXlarge: ml.r7i.xlarge
MlR7i2xlarge: ml.r7i.2xlarge
MlR7i4xlarge: ml.r7i.4xlarge
MlR7i8xlarge: ml.r7i.8xlarge
MlR7i12xlarge: ml.r7i.12xlarge
MlR7i16xlarge: ml.r7i.16xlarge
MlR7i24xlarge: ml.r7i.24xlarge
MlR7i48xlarge: ml.r7i.48xlarge

MlT3Medium: ml.t3.medium
MlT3Large: ml.t3.large
MlT3Xlarge: ml.t3.xlarge
MlT32xlarge: ml.t3.2xlarge
MlM4Xlarge: ml.m4.xlarge
MlM42xlarge: ml.m4.2xlarge
MlM44xlarge: ml.m4.4xlarge
MlM410xlarge: ml.m4.10xlarge
MlM416xlarge: ml.m4.16xlarge
MlC4Xlarge: ml.c4.xlarge
MlC42xlarge: ml.c4.2xlarge
MlC44xlarge: ml.c4.4xlarge
MlC48xlarge: ml.c4.8xlarge
MlC5Xlarge: ml.c5.xlarge
MlC52xlarge: ml.c5.2xlarge
MlC54xlarge: ml.c5.4xlarge
MlC59xlarge: ml.c5.9xlarge
MlC518xlarge: ml.c5.18xlarge
MlM5Large: ml.m5.large
MlM5Xlarge: ml.m5.xlarge
MlM52xlarge: ml.m5.2xlarge
MlM54xlarge: ml.m5.4xlarge
MlM512xlarge: ml.m5.12xlarge
MlM524xlarge: ml.m5.24xlarge
MlR5Large: ml.r5.large
MlR5Xlarge: ml.r5.xlarge
MlR52xlarge: ml.r5.2xlarge
MlR54xlarge: ml.r5.4xlarge
MlR58xlarge: ml.r5.8xlarge
MlR512xlarge: ml.r5.12xlarge
MlR516xlarge: ml.r5.16xlarge
MlR524xlarge: ml.r5.24xlarge
MlG4dnXlarge: ml.g4dn.xlarge
MlG4dn2xlarge: ml.g4dn.2xlarge
MlG4dn4xlarge: ml.g4dn.4xlarge
MlG4dn8xlarge: ml.g4dn.8xlarge
MlG4dn12xlarge: ml.g4dn.12xlarge
MlG4dn16xlarge: ml.g4dn.16xlarge
MlG5Xlarge: ml.g5.xlarge
MlG52xlarge: ml.g5.2xlarge
MlG54xlarge: ml.g5.4xlarge
MlG58xlarge: ml.g5.8xlarge
MlG516xlarge: ml.g5.16xlarge
MlG512xlarge: ml.g5.12xlarge
MlG524xlarge: ml.g5.24xlarge
MlG548xlarge: ml.g5.48xlarge
MlR5dLarge: ml.r5d.large
MlR5dXlarge: ml.r5d.xlarge
MlR5d2xlarge: ml.r5d.2xlarge
MlR5d4xlarge: ml.r5d.4xlarge
MlR5d8xlarge: ml.r5d.8xlarge
MlR5d12xlarge: ml.r5d.12xlarge
MlR5d16xlarge: ml.r5d.16xlarge
MlR5d24xlarge: ml.r5d.24xlarge
MlG6Xlarge: ml.g6.xlarge
MlG62xlarge: ml.g6.2xlarge
MlG64xlarge: ml.g6.4xlarge
MlG68xlarge: ml.g6.8xlarge
MlG612xlarge: ml.g6.12xlarge
MlG616xlarge: ml.g6.16xlarge
MlG624xlarge: ml.g6.24xlarge
MlG648xlarge: ml.g6.48xlarge
MlG6eXlarge: ml.g6e.xlarge
MlG6e2xlarge: ml.g6e.2xlarge
MlG6e4xlarge: ml.g6e.4xlarge
MlG6e8xlarge: ml.g6e.8xlarge
MlG6e12xlarge: ml.g6e.12xlarge
MlG6e16xlarge: ml.g6e.16xlarge
MlG6e24xlarge: ml.g6e.24xlarge
MlG6e48xlarge: ml.g6e.48xlarge
MlM6iLarge: ml.m6i.large
MlM6iXlarge: ml.m6i.xlarge
MlM6i2xlarge: ml.m6i.2xlarge
MlM6i4xlarge: ml.m6i.4xlarge
MlM6i8xlarge: ml.m6i.8xlarge
MlM6i12xlarge: ml.m6i.12xlarge
MlM6i16xlarge: ml.m6i.16xlarge
MlM6i24xlarge: ml.m6i.24xlarge
MlM6i32xlarge: ml.m6i.32xlarge
MlC6iXlarge: ml.c6i.xlarge
MlC6i2xlarge: ml.c6i.2xlarge
MlC6i4xlarge: ml.c6i.4xlarge
MlC6i8xlarge: ml.c6i.8xlarge
MlC6i12xlarge: ml.c6i.12xlarge
MlC6i16xlarge: ml.c6i.16xlarge
MlC6i24xlarge: ml.c6i.24xlarge
MlC6i32xlarge: ml.c6i.32xlarge
MlM7iLarge: ml.m7i.large
MlM7iXlarge: ml.m7i.xlarge
MlM7i2xlarge: ml.m7i.2xlarge
MlM7i4xlarge: ml.m7i.4xlarge
MlM7i8xlarge: ml.m7i.8xlarge
MlM7i12xlarge: ml.m7i.12xlarge
MlM7i16xlarge: ml.m7i.16xlarge
MlM7i24xlarge: ml.m7i.24xlarge
MlM7i48xlarge: ml.m7i.48xlarge
MlC7iLarge: ml.c7i.large
MlC7iXlarge: ml.c7i.xlarge
MlC7i2xlarge: ml.c7i.2xlarge
MlC7i4xlarge: ml.c7i.4xlarge
MlC7i8xlarge: ml.c7i.8xlarge
MlC7i12xlarge: ml.c7i.12xlarge
MlC7i16xlarge: ml.c7i.16xlarge
MlC7i24xlarge: ml.c7i.24xlarge
MlC7i48xlarge: ml.c7i.48xlarge
MlR7iLarge: ml.r7i.large
MlR7iXlarge: ml.r7i.xlarge
MlR7i2xlarge: ml.r7i.2xlarge
MlR7i4xlarge: ml.r7i.4xlarge
MlR7i8xlarge: ml.r7i.8xlarge
MlR7i12xlarge: ml.r7i.12xlarge
MlR7i16xlarge: ml.r7i.16xlarge
MlR7i24xlarge: ml.r7i.24xlarge
MlR7i48xlarge: ml.r7i.48xlarge

ML_T3_MEDIUM: ml.t3.medium
ML_T3_LARGE: ml.t3.large
ML_T3_XLARGE: ml.t3.xlarge
ML_T32XLARGE: ml.t3.2xlarge
ML_M4_XLARGE: ml.m4.xlarge
ML_M42XLARGE: ml.m4.2xlarge
ML_M44XLARGE: ml.m4.4xlarge
ML_M410XLARGE: ml.m4.10xlarge
ML_M416XLARGE: ml.m4.16xlarge
ML_C4_XLARGE: ml.c4.xlarge
ML_C42XLARGE: ml.c4.2xlarge
ML_C44XLARGE: ml.c4.4xlarge
ML_C48XLARGE: ml.c4.8xlarge
ML_C5_XLARGE: ml.c5.xlarge
ML_C52XLARGE: ml.c5.2xlarge
ML_C54XLARGE: ml.c5.4xlarge
ML_C59XLARGE: ml.c5.9xlarge
ML_C518XLARGE: ml.c5.18xlarge
ML_M5_LARGE: ml.m5.large
ML_M5_XLARGE: ml.m5.xlarge
ML_M52XLARGE: ml.m5.2xlarge
ML_M54XLARGE: ml.m5.4xlarge
ML_M512XLARGE: ml.m5.12xlarge
ML_M524XLARGE: ml.m5.24xlarge
ML_R5_LARGE: ml.r5.large
ML_R5_XLARGE: ml.r5.xlarge
ML_R52XLARGE: ml.r5.2xlarge
ML_R54XLARGE: ml.r5.4xlarge
ML_R58XLARGE: ml.r5.8xlarge
ML_R512XLARGE: ml.r5.12xlarge
ML_R516XLARGE: ml.r5.16xlarge
ML_R524XLARGE: ml.r5.24xlarge
ML_G4DN_XLARGE: ml.g4dn.xlarge
ML_G4DN2XLARGE: ml.g4dn.2xlarge
ML_G4DN4XLARGE: ml.g4dn.4xlarge
ML_G4DN8XLARGE: ml.g4dn.8xlarge
ML_G4DN12XLARGE: ml.g4dn.12xlarge
ML_G4DN16XLARGE: ml.g4dn.16xlarge
ML_G5_XLARGE: ml.g5.xlarge
ML_G52XLARGE: ml.g5.2xlarge
ML_G54XLARGE: ml.g5.4xlarge
ML_G58XLARGE: ml.g5.8xlarge
ML_G516XLARGE: ml.g5.16xlarge
ML_G512XLARGE: ml.g5.12xlarge
ML_G524XLARGE: ml.g5.24xlarge
ML_G548XLARGE: ml.g5.48xlarge
ML_R5D_LARGE: ml.r5d.large
ML_R5D_XLARGE: ml.r5d.xlarge
ML_R5D2XLARGE: ml.r5d.2xlarge
ML_R5D4XLARGE: ml.r5d.4xlarge
ML_R5D8XLARGE: ml.r5d.8xlarge
ML_R5D12XLARGE: ml.r5d.12xlarge
ML_R5D16XLARGE: ml.r5d.16xlarge
ML_R5D24XLARGE: ml.r5d.24xlarge
ML_G6_XLARGE: ml.g6.xlarge
ML_G62XLARGE: ml.g6.2xlarge
ML_G64XLARGE: ml.g6.4xlarge
ML_G68XLARGE: ml.g6.8xlarge
ML_G612XLARGE: ml.g6.12xlarge
ML_G616XLARGE: ml.g6.16xlarge
ML_G624XLARGE: ml.g6.24xlarge
ML_G648XLARGE: ml.g6.48xlarge
ML_G6E_XLARGE: ml.g6e.xlarge
ML_G6E2XLARGE: ml.g6e.2xlarge
ML_G6E4XLARGE: ml.g6e.4xlarge
ML_G6E8XLARGE: ml.g6e.8xlarge
ML_G6E12XLARGE: ml.g6e.12xlarge
ML_G6E16XLARGE: ml.g6e.16xlarge
ML_G6E24XLARGE: ml.g6e.24xlarge
ML_G6E48XLARGE: ml.g6e.48xlarge
ML_M6I_LARGE: ml.m6i.large
ML_M6I_XLARGE: ml.m6i.xlarge
ML_M6I2XLARGE: ml.m6i.2xlarge
ML_M6I4XLARGE: ml.m6i.4xlarge
ML_M6I8XLARGE: ml.m6i.8xlarge
ML_M6I12XLARGE: ml.m6i.12xlarge
ML_M6I16XLARGE: ml.m6i.16xlarge
ML_M6I24XLARGE: ml.m6i.24xlarge
ML_M6I32XLARGE: ml.m6i.32xlarge
ML_C6I_XLARGE: ml.c6i.xlarge
ML_C6I2XLARGE: ml.c6i.2xlarge
ML_C6I4XLARGE: ml.c6i.4xlarge
ML_C6I8XLARGE: ml.c6i.8xlarge
ML_C6I12XLARGE: ml.c6i.12xlarge
ML_C6I16XLARGE: ml.c6i.16xlarge
ML_C6I24XLARGE: ml.c6i.24xlarge
ML_C6I32XLARGE: ml.c6i.32xlarge
ML_M7I_LARGE: ml.m7i.large
ML_M7I_XLARGE: ml.m7i.xlarge
ML_M7I2XLARGE: ml.m7i.2xlarge
ML_M7I4XLARGE: ml.m7i.4xlarge
ML_M7I8XLARGE: ml.m7i.8xlarge
ML_M7I12XLARGE: ml.m7i.12xlarge
ML_M7I16XLARGE: ml.m7i.16xlarge
ML_M7I24XLARGE: ml.m7i.24xlarge
ML_M7I48XLARGE: ml.m7i.48xlarge
ML_C7I_LARGE: ml.c7i.large
ML_C7I_XLARGE: ml.c7i.xlarge
ML_C7I2XLARGE: ml.c7i.2xlarge
ML_C7I4XLARGE: ml.c7i.4xlarge
ML_C7I8XLARGE: ml.c7i.8xlarge
ML_C7I12XLARGE: ml.c7i.12xlarge
ML_C7I16XLARGE: ml.c7i.16xlarge
ML_C7I24XLARGE: ml.c7i.24xlarge
ML_C7I48XLARGE: ml.c7i.48xlarge
ML_R7I_LARGE: ml.r7i.large
ML_R7I_XLARGE: ml.r7i.xlarge
ML_R7I2XLARGE: ml.r7i.2xlarge
ML_R7I4XLARGE: ml.r7i.4xlarge
ML_R7I8XLARGE: ml.r7i.8xlarge
ML_R7I12XLARGE: ml.r7i.12xlarge
ML_R7I16XLARGE: ml.r7i.16xlarge
ML_R7I24XLARGE: ml.r7i.24xlarge
ML_R7I48XLARGE: ml.r7i.48xlarge

"ml.t3.medium": ml.t3.medium
"ml.t3.large": ml.t3.large
"ml.t3.xlarge": ml.t3.xlarge
"ml.t3.2xlarge": ml.t3.2xlarge
"ml.m4.xlarge": ml.m4.xlarge
"ml.m4.2xlarge": ml.m4.2xlarge
"ml.m4.4xlarge": ml.m4.4xlarge
"ml.m4.10xlarge": ml.m4.10xlarge
"ml.m4.16xlarge": ml.m4.16xlarge
"ml.c4.xlarge": ml.c4.xlarge
"ml.c4.2xlarge": ml.c4.2xlarge
"ml.c4.4xlarge": ml.c4.4xlarge
"ml.c4.8xlarge": ml.c4.8xlarge
"ml.c5.xlarge": ml.c5.xlarge
"ml.c5.2xlarge": ml.c5.2xlarge
"ml.c5.4xlarge": ml.c5.4xlarge
"ml.c5.9xlarge": ml.c5.9xlarge
"ml.c5.18xlarge": ml.c5.18xlarge
"ml.m5.large": ml.m5.large
"ml.m5.xlarge": ml.m5.xlarge
"ml.m5.2xlarge": ml.m5.2xlarge
"ml.m5.4xlarge": ml.m5.4xlarge
"ml.m5.12xlarge": ml.m5.12xlarge
"ml.m5.24xlarge": ml.m5.24xlarge
"ml.r5.large": ml.r5.large
"ml.r5.xlarge": ml.r5.xlarge
"ml.r5.2xlarge": ml.r5.2xlarge
"ml.r5.4xlarge": ml.r5.4xlarge
"ml.r5.8xlarge": ml.r5.8xlarge
"ml.r5.12xlarge": ml.r5.12xlarge
"ml.r5.16xlarge": ml.r5.16xlarge
"ml.r5.24xlarge": ml.r5.24xlarge
"ml.g4dn.xlarge": ml.g4dn.xlarge
"ml.g4dn.2xlarge": ml.g4dn.2xlarge
"ml.g4dn.4xlarge": ml.g4dn.4xlarge
"ml.g4dn.8xlarge": ml.g4dn.8xlarge
"ml.g4dn.12xlarge": ml.g4dn.12xlarge
"ml.g4dn.16xlarge": ml.g4dn.16xlarge
"ml.g5.xlarge": ml.g5.xlarge
"ml.g5.2xlarge": ml.g5.2xlarge
"ml.g5.4xlarge": ml.g5.4xlarge
"ml.g5.8xlarge": ml.g5.8xlarge
"ml.g5.16xlarge": ml.g5.16xlarge
"ml.g5.12xlarge": ml.g5.12xlarge
"ml.g5.24xlarge": ml.g5.24xlarge
"ml.g5.48xlarge": ml.g5.48xlarge
"ml.r5d.large": ml.r5d.large
"ml.r5d.xlarge": ml.r5d.xlarge
"ml.r5d.2xlarge": ml.r5d.2xlarge
"ml.r5d.4xlarge": ml.r5d.4xlarge
"ml.r5d.8xlarge": ml.r5d.8xlarge
"ml.r5d.12xlarge": ml.r5d.12xlarge
"ml.r5d.16xlarge": ml.r5d.16xlarge
"ml.r5d.24xlarge": ml.r5d.24xlarge
"ml.g6.xlarge": ml.g6.xlarge
"ml.g6.2xlarge": ml.g6.2xlarge
"ml.g6.4xlarge": ml.g6.4xlarge
"ml.g6.8xlarge": ml.g6.8xlarge
"ml.g6.12xlarge": ml.g6.12xlarge
"ml.g6.16xlarge": ml.g6.16xlarge
"ml.g6.24xlarge": ml.g6.24xlarge
"ml.g6.48xlarge": ml.g6.48xlarge
"ml.g6e.xlarge": ml.g6e.xlarge
"ml.g6e.2xlarge": ml.g6e.2xlarge
"ml.g6e.4xlarge": ml.g6e.4xlarge
"ml.g6e.8xlarge": ml.g6e.8xlarge
"ml.g6e.12xlarge": ml.g6e.12xlarge
"ml.g6e.16xlarge": ml.g6e.16xlarge
"ml.g6e.24xlarge": ml.g6e.24xlarge
"ml.g6e.48xlarge": ml.g6e.48xlarge
"ml.m6i.large": ml.m6i.large
"ml.m6i.xlarge": ml.m6i.xlarge
"ml.m6i.2xlarge": ml.m6i.2xlarge
"ml.m6i.4xlarge": ml.m6i.4xlarge
"ml.m6i.8xlarge": ml.m6i.8xlarge
"ml.m6i.12xlarge": ml.m6i.12xlarge
"ml.m6i.16xlarge": ml.m6i.16xlarge
"ml.m6i.24xlarge": ml.m6i.24xlarge
"ml.m6i.32xlarge": ml.m6i.32xlarge
"ml.c6i.xlarge": ml.c6i.xlarge
"ml.c6i.2xlarge": ml.c6i.2xlarge
"ml.c6i.4xlarge": ml.c6i.4xlarge
"ml.c6i.8xlarge": ml.c6i.8xlarge
"ml.c6i.12xlarge": ml.c6i.12xlarge
"ml.c6i.16xlarge": ml.c6i.16xlarge
"ml.c6i.24xlarge": ml.c6i.24xlarge
"ml.c6i.32xlarge": ml.c6i.32xlarge
"ml.m7i.large": ml.m7i.large
"ml.m7i.xlarge": ml.m7i.xlarge
"ml.m7i.2xlarge": ml.m7i.2xlarge
"ml.m7i.4xlarge": ml.m7i.4xlarge
"ml.m7i.8xlarge": ml.m7i.8xlarge
"ml.m7i.12xlarge": ml.m7i.12xlarge
"ml.m7i.16xlarge": ml.m7i.16xlarge
"ml.m7i.24xlarge": ml.m7i.24xlarge
"ml.m7i.48xlarge": ml.m7i.48xlarge
"ml.c7i.large": ml.c7i.large
"ml.c7i.xlarge": ml.c7i.xlarge
"ml.c7i.2xlarge": ml.c7i.2xlarge
"ml.c7i.4xlarge": ml.c7i.4xlarge
"ml.c7i.8xlarge": ml.c7i.8xlarge
"ml.c7i.12xlarge": ml.c7i.12xlarge
"ml.c7i.16xlarge": ml.c7i.16xlarge
"ml.c7i.24xlarge": ml.c7i.24xlarge
"ml.c7i.48xlarge": ml.c7i.48xlarge
"ml.r7i.large": ml.r7i.large
"ml.r7i.xlarge": ml.r7i.xlarge
"ml.r7i.2xlarge": ml.r7i.2xlarge
"ml.r7i.4xlarge": ml.r7i.4xlarge
"ml.r7i.8xlarge": ml.r7i.8xlarge
"ml.r7i.12xlarge": ml.r7i.12xlarge
"ml.r7i.16xlarge": ml.r7i.16xlarge
"ml.r7i.24xlarge": ml.r7i.24xlarge
"ml.r7i.48xlarge": ml.r7i.48xlarge

ProcessingJobDatasetDefinition, ProcessingJobDatasetDefinitionArgs

AthenaDatasetDefinition Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobAthenaDatasetDefinition: Configuration for Athena Dataset Definition input.
DataDistributionType Pulumi.AwsNative.SageMaker.ProcessingJobDatasetDefinitionDataDistributionType: Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).
InputMode Pulumi.AwsNative.SageMaker.ProcessingJobDatasetDefinitionInputMode: Whether to use File or Pipe input mode. In File (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
LocalPath string: The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath is an absolute path to the input data. This is a required parameter when AppManaged is False (default).
RedshiftDatasetDefinition Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobRedshiftDatasetDefinition: Configuration for Redshift Dataset Definition input.

AthenaDatasetDefinition ProcessingJobAthenaDatasetDefinition: Configuration for Athena Dataset Definition input.
DataDistributionType ProcessingJobDatasetDefinitionDataDistributionType: Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).
InputMode ProcessingJobDatasetDefinitionInputMode: Whether to use File or Pipe input mode. In File (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
LocalPath string: The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath is an absolute path to the input data. This is a required parameter when AppManaged is False (default).
RedshiftDatasetDefinition ProcessingJobRedshiftDatasetDefinition: Configuration for Redshift Dataset Definition input.

athenaDatasetDefinition ProcessingJobAthenaDatasetDefinition: Configuration for Athena Dataset Definition input.
dataDistributionType ProcessingJobDatasetDefinitionDataDistributionType: Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).
inputMode ProcessingJobDatasetDefinitionInputMode: Whether to use File or Pipe input mode. In File (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
localPath String: The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath is an absolute path to the input data. This is a required parameter when AppManaged is False (default).
redshiftDatasetDefinition ProcessingJobRedshiftDatasetDefinition: Configuration for Redshift Dataset Definition input.

athenaDatasetDefinition ProcessingJobAthenaDatasetDefinition: Configuration for Athena Dataset Definition input.
dataDistributionType ProcessingJobDatasetDefinitionDataDistributionType: Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).
inputMode ProcessingJobDatasetDefinitionInputMode: Whether to use File or Pipe input mode. In File (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
localPath string: The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath is an absolute path to the input data. This is a required parameter when AppManaged is False (default).
redshiftDatasetDefinition ProcessingJobRedshiftDatasetDefinition: Configuration for Redshift Dataset Definition input.

athena_dataset_definition ProcessingJobAthenaDatasetDefinition: Configuration for Athena Dataset Definition input.
data_distribution_type ProcessingJobDatasetDefinitionDataDistributionType: Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).
input_mode ProcessingJobDatasetDefinitionInputMode: Whether to use File or Pipe input mode. In File (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
local_path str: The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath is an absolute path to the input data. This is a required parameter when AppManaged is False (default).
redshift_dataset_definition ProcessingJobRedshiftDatasetDefinition: Configuration for Redshift Dataset Definition input.

athenaDatasetDefinition Property Map: Configuration for Athena Dataset Definition input.
dataDistributionType "FullyReplicated" | "ShardedByS3Key": Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).
inputMode "File" | "Pipe": Whether to use File or Pipe input mode. In File (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
localPath String: The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath is an absolute path to the input data. This is a required parameter when AppManaged is False (default).
redshiftDatasetDefinition Property Map: Configuration for Redshift Dataset Definition input.

ProcessingJobDatasetDefinitionDataDistributionType, ProcessingJobDatasetDefinitionDataDistributionTypeArgs

FullyReplicated: FullyReplicated
ShardedByS3Key: ShardedByS3Key

ProcessingJobDatasetDefinitionDataDistributionTypeFullyReplicated: FullyReplicated
ProcessingJobDatasetDefinitionDataDistributionTypeShardedByS3Key: ShardedByS3Key

FullyReplicated: FullyReplicated
ShardedByS3Key: ShardedByS3Key

FullyReplicated: FullyReplicated
ShardedByS3Key: ShardedByS3Key

FULLY_REPLICATED: FullyReplicated
SHARDED_BY_S3_KEY: ShardedByS3Key

"FullyReplicated": FullyReplicated
"ShardedByS3Key": ShardedByS3Key

ProcessingJobDatasetDefinitionInputMode, ProcessingJobDatasetDefinitionInputModeArgs

File: File
Pipe: Pipe

ProcessingJobDatasetDefinitionInputModeFile: File
ProcessingJobDatasetDefinitionInputModePipe: Pipe

File: File
Pipe: Pipe

File: File
Pipe: Pipe

FILE: File
PIPE: Pipe

"File": File
"Pipe": Pipe

ProcessingJobExperimentConfig, ProcessingJobExperimentConfigArgs

ExperimentName string: The name of an existing experiment to associate with the trial component.
RunName string: The name of the experiment run to associate with the trial component.
TrialComponentDisplayName string: The display name for the trial component. If this key isn't specified, the display name is the trial component name.
TrialName string: The name of an existing trial to associate the trial component with. If not specified, a new trial is created.

ExperimentName string: The name of an existing experiment to associate with the trial component.
RunName string: The name of the experiment run to associate with the trial component.
TrialComponentDisplayName string: The display name for the trial component. If this key isn't specified, the display name is the trial component name.
TrialName string: The name of an existing trial to associate the trial component with. If not specified, a new trial is created.

experimentName String: The name of an existing experiment to associate with the trial component.
runName String: The name of the experiment run to associate with the trial component.
trialComponentDisplayName String: The display name for the trial component. If this key isn't specified, the display name is the trial component name.
trialName String: The name of an existing trial to associate the trial component with. If not specified, a new trial is created.

experimentName string: The name of an existing experiment to associate with the trial component.
runName string: The name of the experiment run to associate with the trial component.
trialComponentDisplayName string: The display name for the trial component. If this key isn't specified, the display name is the trial component name.
trialName string: The name of an existing trial to associate the trial component with. If not specified, a new trial is created.

experiment_name str: The name of an existing experiment to associate with the trial component.
run_name str: The name of the experiment run to associate with the trial component.
trial_component_display_name str: The display name for the trial component. If this key isn't specified, the display name is the trial component name.
trial_name str: The name of an existing trial to associate the trial component with. If not specified, a new trial is created.

experimentName String: The name of an existing experiment to associate with the trial component.
runName String: The name of the experiment run to associate with the trial component.
trialComponentDisplayName String: The display name for the trial component. If this key isn't specified, the display name is the trial component name.
trialName String: The name of an existing trial to associate the trial component with. If not specified, a new trial is created.

ProcessingJobFeatureStoreOutput, ProcessingJobFeatureStoreOutputArgs

FeatureGroupName string: The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. Note that your processing script is responsible for putting records into your Feature Store.

FeatureGroupName string: The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. Note that your processing script is responsible for putting records into your Feature Store.

featureGroupName String: The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. Note that your processing script is responsible for putting records into your Feature Store.

featureGroupName string: The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. Note that your processing script is responsible for putting records into your Feature Store.

feature_group_name str: The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. Note that your processing script is responsible for putting records into your Feature Store.

featureGroupName String: The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. Note that your processing script is responsible for putting records into your Feature Store.

ProcessingJobNetworkConfig, ProcessingJobNetworkConfigArgs

EnableInterContainerTrafficEncryption bool: Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
EnableNetworkIsolation bool: Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
VpcConfig Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobVpcConfig: Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC .

EnableInterContainerTrafficEncryption bool: Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
EnableNetworkIsolation bool: Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
VpcConfig ProcessingJobVpcConfig: Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC .

enableInterContainerTrafficEncryption Boolean: Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
enableNetworkIsolation Boolean: Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
vpcConfig ProcessingJobVpcConfig: Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC .

enableInterContainerTrafficEncryption boolean: Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
enableNetworkIsolation boolean: Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
vpcConfig ProcessingJobVpcConfig: Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC .

enable_inter_container_traffic_encryption bool: Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
enable_network_isolation bool: Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
vpc_config ProcessingJobVpcConfig: Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC .

enableInterContainerTrafficEncryption Boolean: Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
enableNetworkIsolation Boolean: Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
vpcConfig Property Map: Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC .

ProcessingJobProcessingInputsObject, ProcessingJobProcessingInputsObjectArgs

InputName string: The name for the processing job input.
AppManaged bool: When True, input operations such as data download are managed natively by the processing job application. When False (default), input operations are managed by Amazon SageMaker.
DatasetDefinition Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobDatasetDefinition: Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition or RedshiftDatasetDefinition types.
S3Input Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobS3Input: Configuration for downloading input data from Amazon S3 into the processing container.

InputName string: The name for the processing job input.
AppManaged bool: When True, input operations such as data download are managed natively by the processing job application. When False (default), input operations are managed by Amazon SageMaker.
DatasetDefinition ProcessingJobDatasetDefinition: Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition or RedshiftDatasetDefinition types.
S3Input ProcessingJobS3Input: Configuration for downloading input data from Amazon S3 into the processing container.

inputName String: The name for the processing job input.
appManaged Boolean: When True, input operations such as data download are managed natively by the processing job application. When False (default), input operations are managed by Amazon SageMaker.
datasetDefinition ProcessingJobDatasetDefinition: Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition or RedshiftDatasetDefinition types.
s3Input ProcessingJobS3Input: Configuration for downloading input data from Amazon S3 into the processing container.

inputName string: The name for the processing job input.
appManaged boolean: When True, input operations such as data download are managed natively by the processing job application. When False (default), input operations are managed by Amazon SageMaker.
datasetDefinition ProcessingJobDatasetDefinition: Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition or RedshiftDatasetDefinition types.
s3Input ProcessingJobS3Input: Configuration for downloading input data from Amazon S3 into the processing container.

input_name str: The name for the processing job input.
app_managed bool: When True, input operations such as data download are managed natively by the processing job application. When False (default), input operations are managed by Amazon SageMaker.
dataset_definition ProcessingJobDatasetDefinition: Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition or RedshiftDatasetDefinition types.
s3_input ProcessingJobS3Input: Configuration for downloading input data from Amazon S3 into the processing container.

inputName String: The name for the processing job input.
appManaged Boolean: When True, input operations such as data download are managed natively by the processing job application. When False (default), input operations are managed by Amazon SageMaker.
datasetDefinition Property Map: Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition or RedshiftDatasetDefinition types.
s3Input Property Map: Configuration for downloading input data from Amazon S3 into the processing container.

ProcessingJobProcessingOutputConfig, ProcessingJobProcessingOutputConfigArgs

Outputs List<Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobProcessingOutputsObject>: An array of outputs configuring the data to upload from the processing container.
KmsKeyId string: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a KMS key, or alias of a KMS key. The KmsKeyId is applied to all outputs.

Outputs []ProcessingJobProcessingOutputsObject: An array of outputs configuring the data to upload from the processing container.
KmsKeyId string: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a KMS key, or alias of a KMS key. The KmsKeyId is applied to all outputs.

outputs List<ProcessingJobProcessingOutputsObject>: An array of outputs configuring the data to upload from the processing container.
kmsKeyId String: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a KMS key, or alias of a KMS key. The KmsKeyId is applied to all outputs.

outputs ProcessingJobProcessingOutputsObject[]: An array of outputs configuring the data to upload from the processing container.
kmsKeyId string: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a KMS key, or alias of a KMS key. The KmsKeyId is applied to all outputs.

outputs Sequence[ProcessingJobProcessingOutputsObject]: An array of outputs configuring the data to upload from the processing container.
kms_key_id str: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a KMS key, or alias of a KMS key. The KmsKeyId is applied to all outputs.

outputs List<Property Map>: An array of outputs configuring the data to upload from the processing container.
kmsKeyId String: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a KMS key, or alias of a KMS key. The KmsKeyId is applied to all outputs.

ProcessingJobProcessingOutputsObject, ProcessingJobProcessingOutputsObjectArgs

OutputName string: The name for the processing job output.
AppManaged bool: When True, output operations such as data upload are managed natively by the processing job application. When False (default), output operations are managed by Amazon SageMaker.
FeatureStoreOutput Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobFeatureStoreOutput: Configuration for processing job outputs in Amazon SageMaker Feature Store.
S3Output Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobS3Output: Configuration for uploading output data to Amazon S3 from the processing container.

OutputName string: The name for the processing job output.
AppManaged bool: When True, output operations such as data upload are managed natively by the processing job application. When False (default), output operations are managed by Amazon SageMaker.
FeatureStoreOutput ProcessingJobFeatureStoreOutput: Configuration for processing job outputs in Amazon SageMaker Feature Store.
S3Output ProcessingJobS3Output: Configuration for uploading output data to Amazon S3 from the processing container.

outputName String: The name for the processing job output.
appManaged Boolean: When True, output operations such as data upload are managed natively by the processing job application. When False (default), output operations are managed by Amazon SageMaker.
featureStoreOutput ProcessingJobFeatureStoreOutput: Configuration for processing job outputs in Amazon SageMaker Feature Store.
s3Output ProcessingJobS3Output: Configuration for uploading output data to Amazon S3 from the processing container.

outputName string: The name for the processing job output.
appManaged boolean: When True, output operations such as data upload are managed natively by the processing job application. When False (default), output operations are managed by Amazon SageMaker.
featureStoreOutput ProcessingJobFeatureStoreOutput: Configuration for processing job outputs in Amazon SageMaker Feature Store.
s3Output ProcessingJobS3Output: Configuration for uploading output data to Amazon S3 from the processing container.

output_name str: The name for the processing job output.
app_managed bool: When True, output operations such as data upload are managed natively by the processing job application. When False (default), output operations are managed by Amazon SageMaker.
feature_store_output ProcessingJobFeatureStoreOutput: Configuration for processing job outputs in Amazon SageMaker Feature Store.
s3_output ProcessingJobS3Output: Configuration for uploading output data to Amazon S3 from the processing container.

outputName String: The name for the processing job output.
appManaged Boolean: When True, output operations such as data upload are managed natively by the processing job application. When False (default), output operations are managed by Amazon SageMaker.
featureStoreOutput Property Map: Configuration for processing job outputs in Amazon SageMaker Feature Store.
s3Output Property Map: Configuration for uploading output data to Amazon S3 from the processing container.

ProcessingJobProcessingResources, ProcessingJobProcessingResourcesArgs

ClusterConfig Pulumi.AwsNative.SageMaker.Inputs.ProcessingJobClusterConfig: The configuration for the resources in a cluster used to run the processing job.

ClusterConfig ProcessingJobClusterConfig: The configuration for the resources in a cluster used to run the processing job.

clusterConfig ProcessingJobClusterConfig: The configuration for the resources in a cluster used to run the processing job.

clusterConfig ProcessingJobClusterConfig: The configuration for the resources in a cluster used to run the processing job.

cluster_config ProcessingJobClusterConfig: The configuration for the resources in a cluster used to run the processing job.

clusterConfig Property Map: The configuration for the resources in a cluster used to run the processing job.

ProcessingJobRedshiftDatasetDefinition, ProcessingJobRedshiftDatasetDefinitionArgs

ClusterId string: The Redshift cluster Identifier.
ClusterRoleArn string: The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate datasets.
Database string: The name of the Redshift database used in Redshift query execution.
DbUser string: The database user name used in Redshift query execution.
OutputFormat Pulumi.AwsNative.SageMaker.ProcessingJobRedshiftDatasetDefinitionOutputFormat: The data storage format for Redshift query results.
OutputS3Uri string: The location in Amazon S3 where the Redshift query results are stored.
QueryString string: The SQL query statements to be executed.
KmsKeyId string: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data from a Redshift execution.
OutputCompression Pulumi.AwsNative.SageMaker.ProcessingJobRedshiftDatasetDefinitionOutputCompression: The compression used for Redshift query results.

ClusterId string: The Redshift cluster Identifier.
ClusterRoleArn string: The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate datasets.
Database string: The name of the Redshift database used in Redshift query execution.
DbUser string: The database user name used in Redshift query execution.
OutputFormat ProcessingJobRedshiftDatasetDefinitionOutputFormat: The data storage format for Redshift query results.
OutputS3Uri string: The location in Amazon S3 where the Redshift query results are stored.
QueryString string: The SQL query statements to be executed.
KmsKeyId string: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data from a Redshift execution.
OutputCompression ProcessingJobRedshiftDatasetDefinitionOutputCompression: The compression used for Redshift query results.

clusterId String: The Redshift cluster Identifier.
clusterRoleArn String: The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate datasets.
database String: The name of the Redshift database used in Redshift query execution.
dbUser String: The database user name used in Redshift query execution.
outputFormat ProcessingJobRedshiftDatasetDefinitionOutputFormat: The data storage format for Redshift query results.
outputS3Uri String: The location in Amazon S3 where the Redshift query results are stored.
queryString String: The SQL query statements to be executed.
kmsKeyId String: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data from a Redshift execution.
outputCompression ProcessingJobRedshiftDatasetDefinitionOutputCompression: The compression used for Redshift query results.

clusterId string: The Redshift cluster Identifier.
clusterRoleArn string: The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate datasets.
database string: The name of the Redshift database used in Redshift query execution.
dbUser string: The database user name used in Redshift query execution.
outputFormat ProcessingJobRedshiftDatasetDefinitionOutputFormat: The data storage format for Redshift query results.
outputS3Uri string: The location in Amazon S3 where the Redshift query results are stored.
queryString string: The SQL query statements to be executed.
kmsKeyId string: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data from a Redshift execution.
outputCompression ProcessingJobRedshiftDatasetDefinitionOutputCompression: The compression used for Redshift query results.

cluster_id str: The Redshift cluster Identifier.
cluster_role_arn str: The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate datasets.
database str: The name of the Redshift database used in Redshift query execution.
db_user str: The database user name used in Redshift query execution.
output_format ProcessingJobRedshiftDatasetDefinitionOutputFormat: The data storage format for Redshift query results.
output_s3_uri str: The location in Amazon S3 where the Redshift query results are stored.
query_string str: The SQL query statements to be executed.
kms_key_id str: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data from a Redshift execution.
output_compression ProcessingJobRedshiftDatasetDefinitionOutputCompression: The compression used for Redshift query results.

clusterId String: The Redshift cluster Identifier.
clusterRoleArn String: The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate datasets.
database String: The name of the Redshift database used in Redshift query execution.
dbUser String: The database user name used in Redshift query execution.
outputFormat "PARQUET" | "CSV": The data storage format for Redshift query results.
outputS3Uri String: The location in Amazon S3 where the Redshift query results are stored.
queryString String: The SQL query statements to be executed.
kmsKeyId String: The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data from a Redshift execution.
outputCompression "None" | "GZIP" | "SNAPPY" | "ZSTD" | "BZIP2": The compression used for Redshift query results.

ProcessingJobRedshiftDatasetDefinitionOutputCompression, ProcessingJobRedshiftDatasetDefinitionOutputCompressionArgs

None: None
Gzip: GZIP
Snappy: SNAPPY
Zstd: ZSTD
Bzip2: BZIP2

ProcessingJobRedshiftDatasetDefinitionOutputCompressionNone: None
ProcessingJobRedshiftDatasetDefinitionOutputCompressionGzip: GZIP
ProcessingJobRedshiftDatasetDefinitionOutputCompressionSnappy: SNAPPY
ProcessingJobRedshiftDatasetDefinitionOutputCompressionZstd: ZSTD
ProcessingJobRedshiftDatasetDefinitionOutputCompressionBzip2: BZIP2

None: None
Gzip: GZIP
Snappy: SNAPPY
Zstd: ZSTD
Bzip2: BZIP2

None: None
Gzip: GZIP
Snappy: SNAPPY
Zstd: ZSTD
Bzip2: BZIP2

NONE: None
GZIP: GZIP
SNAPPY: SNAPPY
ZSTD: ZSTD
BZIP2: BZIP2

"None": None
"GZIP": GZIP
"SNAPPY": SNAPPY
"ZSTD": ZSTD
"BZIP2": BZIP2

ProcessingJobRedshiftDatasetDefinitionOutputFormat, ProcessingJobRedshiftDatasetDefinitionOutputFormatArgs

Parquet: PARQUET
Csv: CSV

ProcessingJobRedshiftDatasetDefinitionOutputFormatParquet: PARQUET
ProcessingJobRedshiftDatasetDefinitionOutputFormatCsv: CSV

Parquet: PARQUET
Csv: CSV

Parquet: PARQUET
Csv: CSV

PARQUET: PARQUET
CSV: CSV

"PARQUET": PARQUET
"CSV": CSV

ProcessingJobS3Input, ProcessingJobS3InputArgs

S3DataType Pulumi.AwsNative.SageMaker.ProcessingJobS3InputS3DataType: Whether you use an S3Prefix or a ManifestFile for the data type. If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.
S3Uri string: The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.
LocalPath string: The local path in your container where you want Amazon SageMaker to write input data to. LocalPath is an absolute path to the input data and must begin with /opt/ml/processing/. LocalPath is a required parameter when AppManaged is False (default).
S3CompressionType Pulumi.AwsNative.SageMaker.ProcessingJobS3InputS3CompressionType: Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip can only be used when Pipe mode is specified as the S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.
S3DataDistributionType Pulumi.AwsNative.SageMaker.ProcessingJobS3InputS3DataDistributionType: Whether to distribute the data from Amazon S3 to all processing instances with FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.
S3InputMode Pulumi.AwsNative.SageMaker.ProcessingJobS3InputS3InputMode: Whether to use File or Pipe input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.

S3DataType ProcessingJobS3InputS3DataType: Whether you use an S3Prefix or a ManifestFile for the data type. If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.
S3Uri string: The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.
LocalPath string: The local path in your container where you want Amazon SageMaker to write input data to. LocalPath is an absolute path to the input data and must begin with /opt/ml/processing/. LocalPath is a required parameter when AppManaged is False (default).
S3CompressionType ProcessingJobS3InputS3CompressionType: Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip can only be used when Pipe mode is specified as the S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.
S3DataDistributionType ProcessingJobS3InputS3DataDistributionType: Whether to distribute the data from Amazon S3 to all processing instances with FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.
S3InputMode ProcessingJobS3InputS3InputMode: Whether to use File or Pipe input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.

s3DataType ProcessingJobS3InputS3DataType: Whether you use an S3Prefix or a ManifestFile for the data type. If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.
s3Uri String: The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.
localPath String: The local path in your container where you want Amazon SageMaker to write input data to. LocalPath is an absolute path to the input data and must begin with /opt/ml/processing/. LocalPath is a required parameter when AppManaged is False (default).
s3CompressionType ProcessingJobS3InputS3CompressionType: Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip can only be used when Pipe mode is specified as the S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.
s3DataDistributionType ProcessingJobS3InputS3DataDistributionType: Whether to distribute the data from Amazon S3 to all processing instances with FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.
s3InputMode ProcessingJobS3InputS3InputMode: Whether to use File or Pipe input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.

s3DataType ProcessingJobS3InputS3DataType: Whether you use an S3Prefix or a ManifestFile for the data type. If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.
s3Uri string: The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.
localPath string: The local path in your container where you want Amazon SageMaker to write input data to. LocalPath is an absolute path to the input data and must begin with /opt/ml/processing/. LocalPath is a required parameter when AppManaged is False (default).
s3CompressionType ProcessingJobS3InputS3CompressionType: Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip can only be used when Pipe mode is specified as the S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.
s3DataDistributionType ProcessingJobS3InputS3DataDistributionType: Whether to distribute the data from Amazon S3 to all processing instances with FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.
s3InputMode ProcessingJobS3InputS3InputMode: Whether to use File or Pipe input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.

s3_data_type ProcessingJobS3InputS3DataType: Whether you use an S3Prefix or a ManifestFile for the data type. If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.
s3_uri str: The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.
local_path str: The local path in your container where you want Amazon SageMaker to write input data to. LocalPath is an absolute path to the input data and must begin with /opt/ml/processing/. LocalPath is a required parameter when AppManaged is False (default).
s3_compression_type ProcessingJobS3InputS3CompressionType: Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip can only be used when Pipe mode is specified as the S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.
s3_data_distribution_type ProcessingJobS3InputS3DataDistributionType: Whether to distribute the data from Amazon S3 to all processing instances with FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.
s3_input_mode ProcessingJobS3InputS3InputMode: Whether to use File or Pipe input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.

s3DataType "ManifestFile" | "S3Prefix": Whether you use an S3Prefix or a ManifestFile for the data type. If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.
s3Uri String: The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.
localPath String: The local path in your container where you want Amazon SageMaker to write input data to. LocalPath is an absolute path to the input data and must begin with /opt/ml/processing/. LocalPath is a required parameter when AppManaged is False (default).
s3CompressionType "None" | "Gzip": Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip can only be used when Pipe mode is specified as the S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.
s3DataDistributionType "FullyReplicated" | "ShardedByS3Key": Whether to distribute the data from Amazon S3 to all processing instances with FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.
s3InputMode "File" | "Pipe": Whether to use File or Pipe input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.

ProcessingJobS3InputS3CompressionType, ProcessingJobS3InputS3CompressionTypeArgs

None: None
Gzip: Gzip

ProcessingJobS3InputS3CompressionTypeNone: None
ProcessingJobS3InputS3CompressionTypeGzip: Gzip

None: None
Gzip: Gzip

None: None
Gzip: Gzip

NONE: None
GZIP: Gzip

"None": None
"Gzip": Gzip

ProcessingJobS3InputS3DataDistributionType, ProcessingJobS3InputS3DataDistributionTypeArgs

FullyReplicated: FullyReplicated
ShardedByS3Key: ShardedByS3Key

ProcessingJobS3InputS3DataDistributionTypeFullyReplicated: FullyReplicated
ProcessingJobS3InputS3DataDistributionTypeShardedByS3Key: ShardedByS3Key

FullyReplicated: FullyReplicated
ShardedByS3Key: ShardedByS3Key

FullyReplicated: FullyReplicated
ShardedByS3Key: ShardedByS3Key

FULLY_REPLICATED: FullyReplicated
SHARDED_BY_S3_KEY: ShardedByS3Key

"FullyReplicated": FullyReplicated
"ShardedByS3Key": ShardedByS3Key

ProcessingJobS3InputS3DataType, ProcessingJobS3InputS3DataTypeArgs

ManifestFile: ManifestFile
S3Prefix: S3Prefix

ProcessingJobS3InputS3DataTypeManifestFile: ManifestFile
ProcessingJobS3InputS3DataTypeS3Prefix: S3Prefix

ManifestFile: ManifestFile
S3Prefix: S3Prefix

ManifestFile: ManifestFile
S3Prefix: S3Prefix

MANIFEST_FILE: ManifestFile
S3_PREFIX: S3Prefix

"ManifestFile": ManifestFile
"S3Prefix": S3Prefix

ProcessingJobS3InputS3InputMode, ProcessingJobS3InputS3InputModeArgs

File: File
Pipe: Pipe

ProcessingJobS3InputS3InputModeFile: File
ProcessingJobS3InputS3InputModePipe: Pipe

File: File
Pipe: Pipe

File: File
Pipe: Pipe

FILE: File
PIPE: Pipe

"File": File
"Pipe": Pipe

ProcessingJobS3Output, ProcessingJobS3OutputArgs

S3UploadMode Pulumi.AwsNative.SageMaker.ProcessingJobS3OutputS3UploadMode: Whether to upload the results of the processing job continuously or after the job completes.
S3Uri string: A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.
LocalPath string: The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3. LocalPath is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container's entrypoint is invoked.

S3UploadMode ProcessingJobS3OutputS3UploadMode: Whether to upload the results of the processing job continuously or after the job completes.
S3Uri string: A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.
LocalPath string: The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3. LocalPath is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container's entrypoint is invoked.

s3UploadMode ProcessingJobS3OutputS3UploadMode: Whether to upload the results of the processing job continuously or after the job completes.
s3Uri String: A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.
localPath String: The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3. LocalPath is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container's entrypoint is invoked.

s3UploadMode ProcessingJobS3OutputS3UploadMode: Whether to upload the results of the processing job continuously or after the job completes.
s3Uri string: A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.
localPath string: The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3. LocalPath is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container's entrypoint is invoked.

s3_upload_mode ProcessingJobS3OutputS3UploadMode: Whether to upload the results of the processing job continuously or after the job completes.
s3_uri str: A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.
local_path str: The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3. LocalPath is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container's entrypoint is invoked.

s3UploadMode "Continuous" | "EndOfJob": Whether to upload the results of the processing job continuously or after the job completes.
s3Uri String: A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.
localPath String: The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3. LocalPath is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container's entrypoint is invoked.

ProcessingJobS3OutputS3UploadMode, ProcessingJobS3OutputS3UploadModeArgs

Continuous: Continuous
EndOfJob: EndOfJob

ProcessingJobS3OutputS3UploadModeContinuous: Continuous
ProcessingJobS3OutputS3UploadModeEndOfJob: EndOfJob

Continuous: Continuous
EndOfJob: EndOfJob

Continuous: Continuous
EndOfJob: EndOfJob

CONTINUOUS: Continuous
END_OF_JOB: EndOfJob

"Continuous": Continuous
"EndOfJob": EndOfJob

ProcessingJobStatus, ProcessingJobStatusArgs

Completed: Completed
InProgress: InProgress
Stopping: Stopping
Stopped: Stopped
Failed: Failed

ProcessingJobStatusCompleted: Completed
ProcessingJobStatusInProgress: InProgress
ProcessingJobStatusStopping: Stopping
ProcessingJobStatusStopped: Stopped
ProcessingJobStatusFailed: Failed

Completed: Completed
InProgress: InProgress
Stopping: Stopping
Stopped: Stopped
Failed: Failed

Completed: Completed
InProgress: InProgress
Stopping: Stopping
Stopped: Stopped
Failed: Failed

COMPLETED: Completed
IN_PROGRESS: InProgress
STOPPING: Stopping
STOPPED: Stopped
FAILED: Failed

"Completed": Completed
"InProgress": InProgress
"Stopping": Stopping
"Stopped": Stopped
"Failed": Failed

ProcessingJobStoppingCondition, ProcessingJobStoppingConditionArgs

MaxRuntimeInSeconds int: Specifies the maximum runtime in seconds.

MaxRuntimeInSeconds int: Specifies the maximum runtime in seconds.

maxRuntimeInSeconds Integer: Specifies the maximum runtime in seconds.

maxRuntimeInSeconds number: Specifies the maximum runtime in seconds.

max_runtime_in_seconds int: Specifies the maximum runtime in seconds.

maxRuntimeInSeconds Number: Specifies the maximum runtime in seconds.

ProcessingJobVpcConfig, ProcessingJobVpcConfigArgs

SecurityGroupIds List<string>: The VPC security group IDs, in the form 'sg-xxxxxxxx'. Specify the security groups for the VPC that is specified in the 'Subnets' field.
Subnets List<string>: The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see https://docs.aws.amazon.com/sagemaker/latest/dg/regions-quotas.html

SecurityGroupIds []string: The VPC security group IDs, in the form 'sg-xxxxxxxx'. Specify the security groups for the VPC that is specified in the 'Subnets' field.
Subnets []string: The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see https://docs.aws.amazon.com/sagemaker/latest/dg/regions-quotas.html

securityGroupIds List<String>: The VPC security group IDs, in the form 'sg-xxxxxxxx'. Specify the security groups for the VPC that is specified in the 'Subnets' field.
subnets List<String>: The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see https://docs.aws.amazon.com/sagemaker/latest/dg/regions-quotas.html

securityGroupIds string[]: The VPC security group IDs, in the form 'sg-xxxxxxxx'. Specify the security groups for the VPC that is specified in the 'Subnets' field.
subnets string[]: The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see https://docs.aws.amazon.com/sagemaker/latest/dg/regions-quotas.html

security_group_ids Sequence[str]: The VPC security group IDs, in the form 'sg-xxxxxxxx'. Specify the security groups for the VPC that is specified in the 'Subnets' field.
subnets Sequence[str]: The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see https://docs.aws.amazon.com/sagemaker/latest/dg/regions-quotas.html

securityGroupIds List<String>: The VPC security group IDs, in the form 'sg-xxxxxxxx'. Specify the security groups for the VPC that is specified in the 'Subnets' field.
subnets List<String>: The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see https://docs.aws.amazon.com/sagemaker/latest/dg/regions-quotas.html

Package Details

Repository: AWS Native pulumi/pulumi-aws-native
License: Apache-2.0

We recommend new projects start with resources from the AWS provider.

AWS Cloud Control v1.32.0 published on Wednesday, Aug 13, 2025 by Pulumi

pulumi/pulumi-aws-native

aws-native.sagemaker.ProcessingJob

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Create ProcessingJob Resource

Constructor syntax

Parameters

ProcessingJob Resource Properties

Inputs

Outputs

Supporting Types

CreateOnlyTag, CreateOnlyTagArgs

ProcessingJobAppSpecification, ProcessingJobAppSpecificationArgs

ProcessingJobAthenaDatasetDefinition, ProcessingJobAthenaDatasetDefinitionArgs

ProcessingJobAthenaDatasetDefinitionOutputCompression, ProcessingJobAthenaDatasetDefinitionOutputCompressionArgs

ProcessingJobAthenaDatasetDefinitionOutputFormat, ProcessingJobAthenaDatasetDefinitionOutputFormatArgs

ProcessingJobClusterConfig, ProcessingJobClusterConfigArgs

ProcessingJobClusterConfigInstanceType, ProcessingJobClusterConfigInstanceTypeArgs

ProcessingJobDatasetDefinition, ProcessingJobDatasetDefinitionArgs

ProcessingJobDatasetDefinitionDataDistributionType, ProcessingJobDatasetDefinitionDataDistributionTypeArgs

ProcessingJobDatasetDefinitionInputMode, ProcessingJobDatasetDefinitionInputModeArgs

ProcessingJobExperimentConfig, ProcessingJobExperimentConfigArgs

ProcessingJobFeatureStoreOutput, ProcessingJobFeatureStoreOutputArgs

ProcessingJobNetworkConfig, ProcessingJobNetworkConfigArgs

ProcessingJobProcessingInputsObject, ProcessingJobProcessingInputsObjectArgs

ProcessingJobProcessingOutputConfig, ProcessingJobProcessingOutputConfigArgs

ProcessingJobProcessingOutputsObject, ProcessingJobProcessingOutputsObjectArgs

ProcessingJobProcessingResources, ProcessingJobProcessingResourcesArgs

ProcessingJobRedshiftDatasetDefinition, ProcessingJobRedshiftDatasetDefinitionArgs

ProcessingJobRedshiftDatasetDefinitionOutputCompression, ProcessingJobRedshiftDatasetDefinitionOutputCompressionArgs

ProcessingJobRedshiftDatasetDefinitionOutputFormat, ProcessingJobRedshiftDatasetDefinitionOutputFormatArgs

ProcessingJobS3Input, ProcessingJobS3InputArgs

ProcessingJobS3InputS3CompressionType, ProcessingJobS3InputS3CompressionTypeArgs

ProcessingJobS3InputS3DataDistributionType, ProcessingJobS3InputS3DataDistributionTypeArgs

ProcessingJobS3InputS3DataType, ProcessingJobS3InputS3DataTypeArgs

ProcessingJobS3InputS3InputMode, ProcessingJobS3InputS3InputModeArgs

ProcessingJobS3Output, ProcessingJobS3OutputArgs

ProcessingJobS3OutputS3UploadMode, ProcessingJobS3OutputS3UploadModeArgs

ProcessingJobStatus, ProcessingJobStatusArgs

ProcessingJobStoppingCondition, ProcessingJobStoppingConditionArgs

ProcessingJobVpcConfig, ProcessingJobVpcConfigArgs

Package Details

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