StartMLModelTransformJobRequest (AWS SDK for Java

java.lang.Object
- com.amazonaws.AmazonWebServiceRequest
- - com.amazonaws.services.neptunedata.model.StartMLModelTransformJobRequest

All Implemented Interfaces:: HandlerContextAware, ReadLimitInfo, Serializable, Cloneable

@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class StartMLModelTransformJobRequest
extends AmazonWebServiceRequest
implements Serializable, Cloneable

See Also:: AWS API Documentation, Serialized Form

Field Summary
- Fields inherited from class com.amazonaws.AmazonWebServiceRequest
  NOOP

Constructor Summary

Constructors
Constructor and Description

StartMLModelTransformJobRequest()

Constructors
Constructor and Description
`StartMLModelTransformJobRequest()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`StartMLModelTransformJobRequest`	`clone()` Creates a shallow clone of this object for all fields except the handler context.
`boolean`	`equals(Object obj)`
`String`	`getBaseProcessingInstanceType()` The type of ML instance used in preparing and managing training of ML models.
`Integer`	`getBaseProcessingInstanceVolumeSizeInGB()` The disk volume size of the training instance in gigabytes.
`CustomModelTransformParameters`	`getCustomModelTransformParameters()` Configuration information for a model transform using a custom model.
`String`	`getDataProcessingJobId()` The job ID of a completed data-processing job.
`String`	`getId()` A unique identifier for the new job.
`String`	`getMlModelTrainingJobId()` The job ID of a completed model-training job.
`String`	`getModelTransformOutputS3Location()` The location in Amazon S3 where the model artifacts are to be stored.
`String`	`getNeptuneIamRoleArn()` The ARN of an IAM role that provides Neptune access to SageMaker and Amazon S3 resources.
`String`	`getS3OutputEncryptionKMSKey()` The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job.
`String`	`getSagemakerIamRoleArn()` The ARN of an IAM role for SageMaker execution.
`List<String>`	`getSecurityGroupIds()` The VPC security group IDs.
`List<String>`	`getSubnets()` The IDs of the subnets in the Neptune VPC.
`String`	`getTrainingJobName()` The name of a completed SageMaker training job.
`String`	`getVolumeEncryptionKMSKey()` The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instances that run the training job.
`int`	`hashCode()`
`void`	`setBaseProcessingInstanceType(String baseProcessingInstanceType)` The type of ML instance used in preparing and managing training of ML models.
`void`	`setBaseProcessingInstanceVolumeSizeInGB(Integer baseProcessingInstanceVolumeSizeInGB)` The disk volume size of the training instance in gigabytes.
`void`	`setCustomModelTransformParameters(CustomModelTransformParameters customModelTransformParameters)` Configuration information for a model transform using a custom model.
`void`	`setDataProcessingJobId(String dataProcessingJobId)` The job ID of a completed data-processing job.
`void`	`setId(String id)` A unique identifier for the new job.
`void`	`setMlModelTrainingJobId(String mlModelTrainingJobId)` The job ID of a completed model-training job.
`void`	`setModelTransformOutputS3Location(String modelTransformOutputS3Location)` The location in Amazon S3 where the model artifacts are to be stored.
`void`	`setNeptuneIamRoleArn(String neptuneIamRoleArn)` The ARN of an IAM role that provides Neptune access to SageMaker and Amazon S3 resources.
`void`	`setS3OutputEncryptionKMSKey(String s3OutputEncryptionKMSKey)` The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job.
`void`	`setSagemakerIamRoleArn(String sagemakerIamRoleArn)` The ARN of an IAM role for SageMaker execution.
`void`	`setSecurityGroupIds(Collection<String> securityGroupIds)` The VPC security group IDs.
`void`	`setSubnets(Collection<String> subnets)` The IDs of the subnets in the Neptune VPC.
`void`	`setTrainingJobName(String trainingJobName)` The name of a completed SageMaker training job.
`void`	`setVolumeEncryptionKMSKey(String volumeEncryptionKMSKey)` The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instances that run the training job.
`String`	`toString()` Returns a string representation of this object.
`StartMLModelTransformJobRequest`	`withBaseProcessingInstanceType(String baseProcessingInstanceType)` The type of ML instance used in preparing and managing training of ML models.
`StartMLModelTransformJobRequest`	`withBaseProcessingInstanceVolumeSizeInGB(Integer baseProcessingInstanceVolumeSizeInGB)` The disk volume size of the training instance in gigabytes.
`StartMLModelTransformJobRequest`	`withCustomModelTransformParameters(CustomModelTransformParameters customModelTransformParameters)` Configuration information for a model transform using a custom model.
`StartMLModelTransformJobRequest`	`withDataProcessingJobId(String dataProcessingJobId)` The job ID of a completed data-processing job.
`StartMLModelTransformJobRequest`	`withId(String id)` A unique identifier for the new job.
`StartMLModelTransformJobRequest`	`withMlModelTrainingJobId(String mlModelTrainingJobId)` The job ID of a completed model-training job.
`StartMLModelTransformJobRequest`	`withModelTransformOutputS3Location(String modelTransformOutputS3Location)` The location in Amazon S3 where the model artifacts are to be stored.
`StartMLModelTransformJobRequest`	`withNeptuneIamRoleArn(String neptuneIamRoleArn)` The ARN of an IAM role that provides Neptune access to SageMaker and Amazon S3 resources.
`StartMLModelTransformJobRequest`	`withS3OutputEncryptionKMSKey(String s3OutputEncryptionKMSKey)` The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job.
`StartMLModelTransformJobRequest`	`withSagemakerIamRoleArn(String sagemakerIamRoleArn)` The ARN of an IAM role for SageMaker execution.
`StartMLModelTransformJobRequest`	`withSecurityGroupIds(Collection<String> securityGroupIds)` The VPC security group IDs.
`StartMLModelTransformJobRequest`	`withSecurityGroupIds(String... securityGroupIds)` The VPC security group IDs.
`StartMLModelTransformJobRequest`	`withSubnets(Collection<String> subnets)` The IDs of the subnets in the Neptune VPC.
`StartMLModelTransformJobRequest`	`withSubnets(String... subnets)` The IDs of the subnets in the Neptune VPC.
`StartMLModelTransformJobRequest`	`withTrainingJobName(String trainingJobName)` The name of a completed SageMaker training job.
`StartMLModelTransformJobRequest`	`withVolumeEncryptionKMSKey(String volumeEncryptionKMSKey)` The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instances that run the training job.

Methods inherited from class java.lang.Object
getClass, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - StartMLModelTransformJobRequest
```
public StartMLModelTransformJobRequest()
```
- Method Detail
  - setId
```
public void setId(String id)
```
    A unique identifier for the new job. The default is an autogenerated UUID.
    
    Parameters:
    
    id - A unique identifier for the new job. The default is an autogenerated UUID.
  - getId
```
public String getId()
```
    A unique identifier for the new job. The default is an autogenerated UUID.
    
    Returns:
    
    A unique identifier for the new job. The default is an autogenerated UUID.
  - withId
```
public StartMLModelTransformJobRequest withId(String id)
```
    A unique identifier for the new job. The default is an autogenerated UUID.
    
    Parameters:
    
    id - A unique identifier for the new job. The default is an autogenerated UUID.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setDataProcessingJobId
```
public void setDataProcessingJobId(String dataProcessingJobId)
```
    The job ID of a completed data-processing job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
    
    Parameters:
    
    dataProcessingJobId - The job ID of a completed data-processing job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
  - getDataProcessingJobId
```
public String getDataProcessingJobId()
```
    The job ID of a completed data-processing job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
    
    Returns:
    
    The job ID of a completed data-processing job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
  - withDataProcessingJobId
```
public StartMLModelTransformJobRequest withDataProcessingJobId(String dataProcessingJobId)
```
    The job ID of a completed data-processing job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
    
    Parameters:
    
    dataProcessingJobId - The job ID of a completed data-processing job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setMlModelTrainingJobId
```
public void setMlModelTrainingJobId(String mlModelTrainingJobId)
```
    The job ID of a completed model-training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
    
    Parameters:
    
    mlModelTrainingJobId - The job ID of a completed model-training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
  - getMlModelTrainingJobId
```
public String getMlModelTrainingJobId()
```
    The job ID of a completed model-training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
    
    Returns:
    
    The job ID of a completed model-training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
  - withMlModelTrainingJobId
```
public StartMLModelTransformJobRequest withMlModelTrainingJobId(String mlModelTrainingJobId)
```
    The job ID of a completed model-training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
    
    Parameters:
    
    mlModelTrainingJobId - The job ID of a completed model-training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setTrainingJobName
```
public void setTrainingJobName(String trainingJobName)
```
    The name of a completed SageMaker training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
    
    Parameters:
    
    trainingJobName - The name of a completed SageMaker training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
  - getTrainingJobName
```
public String getTrainingJobName()
```
    The name of a completed SageMaker training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
    
    Returns:
    
    The name of a completed SageMaker training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
  - withTrainingJobName
```
public StartMLModelTransformJobRequest withTrainingJobName(String trainingJobName)
```
    The name of a completed SageMaker training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
    
    Parameters:
    
    trainingJobName - The name of a completed SageMaker training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setModelTransformOutputS3Location
```
public void setModelTransformOutputS3Location(String modelTransformOutputS3Location)
```
    The location in Amazon S3 where the model artifacts are to be stored.
    
    Parameters:
    
    modelTransformOutputS3Location - The location in Amazon S3 where the model artifacts are to be stored.
  - getModelTransformOutputS3Location
```
public String getModelTransformOutputS3Location()
```
    The location in Amazon S3 where the model artifacts are to be stored.
    
    Returns:
    
    The location in Amazon S3 where the model artifacts are to be stored.
  - withModelTransformOutputS3Location
```
public StartMLModelTransformJobRequest withModelTransformOutputS3Location(String modelTransformOutputS3Location)
```
    The location in Amazon S3 where the model artifacts are to be stored.
    
    Parameters:
    
    modelTransformOutputS3Location - The location in Amazon S3 where the model artifacts are to be stored.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setSagemakerIamRoleArn
```
public void setSagemakerIamRoleArn(String sagemakerIamRoleArn)
```
    The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or an error will occur.
    
    Parameters:
    
    sagemakerIamRoleArn - The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or an error will occur.
  - getSagemakerIamRoleArn
```
public String getSagemakerIamRoleArn()
```
    The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or an error will occur.
    
    Returns:
    
    The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or an error will occur.
  - withSagemakerIamRoleArn
```
public StartMLModelTransformJobRequest withSagemakerIamRoleArn(String sagemakerIamRoleArn)
```
    The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or an error will occur.
    
    Parameters:
    
    sagemakerIamRoleArn - The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or an error will occur.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setNeptuneIamRoleArn
```
public void setNeptuneIamRoleArn(String neptuneIamRoleArn)
```
    The ARN of an IAM role that provides Neptune access to SageMaker and Amazon S3 resources. This must be listed in your DB cluster parameter group or an error will occur.
    
    Parameters:
    
    neptuneIamRoleArn - The ARN of an IAM role that provides Neptune access to SageMaker and Amazon S3 resources. This must be listed in your DB cluster parameter group or an error will occur.
  - getNeptuneIamRoleArn
```
public String getNeptuneIamRoleArn()
```
    The ARN of an IAM role that provides Neptune access to SageMaker and Amazon S3 resources. This must be listed in your DB cluster parameter group or an error will occur.
    
    Returns:
    
    The ARN of an IAM role that provides Neptune access to SageMaker and Amazon S3 resources. This must be listed in your DB cluster parameter group or an error will occur.
  - withNeptuneIamRoleArn
```
public StartMLModelTransformJobRequest withNeptuneIamRoleArn(String neptuneIamRoleArn)
```
    The ARN of an IAM role that provides Neptune access to SageMaker and Amazon S3 resources. This must be listed in your DB cluster parameter group or an error will occur.
    
    Parameters:
    
    neptuneIamRoleArn - The ARN of an IAM role that provides Neptune access to SageMaker and Amazon S3 resources. This must be listed in your DB cluster parameter group or an error will occur.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setCustomModelTransformParameters
```
public void setCustomModelTransformParameters(CustomModelTransformParameters customModelTransformParameters)
```
    Configuration information for a model transform using a custom model. The customModelTransformParameters object contains the following fields, which must have values compatible with the saved model parameters from the training job:
    
    Parameters:
    
    customModelTransformParameters - Configuration information for a model transform using a custom model. The customModelTransformParameters object contains the following fields, which must have values compatible with the saved model parameters from the training job:
  - getCustomModelTransformParameters
```
public CustomModelTransformParameters getCustomModelTransformParameters()
```
    Configuration information for a model transform using a custom model. The customModelTransformParameters object contains the following fields, which must have values compatible with the saved model parameters from the training job:
    
    Returns:
    
    Configuration information for a model transform using a custom model. The customModelTransformParameters object contains the following fields, which must have values compatible with the saved model parameters from the training job:
  - withCustomModelTransformParameters
```
public StartMLModelTransformJobRequest withCustomModelTransformParameters(CustomModelTransformParameters customModelTransformParameters)
```
    Configuration information for a model transform using a custom model. The customModelTransformParameters object contains the following fields, which must have values compatible with the saved model parameters from the training job:
    
    Parameters:
    
    customModelTransformParameters - Configuration information for a model transform using a custom model. The customModelTransformParameters object contains the following fields, which must have values compatible with the saved model parameters from the training job:
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setBaseProcessingInstanceType
```
public void setBaseProcessingInstanceType(String baseProcessingInstanceType)
```
    The type of ML instance used in preparing and managing training of ML models. This is an ML compute instance chosen based on memory requirements for processing the training data and model.
    
    Parameters:
    
    baseProcessingInstanceType - The type of ML instance used in preparing and managing training of ML models. This is an ML compute instance chosen based on memory requirements for processing the training data and model.
  - getBaseProcessingInstanceType
```
public String getBaseProcessingInstanceType()
```
    The type of ML instance used in preparing and managing training of ML models. This is an ML compute instance chosen based on memory requirements for processing the training data and model.
    
    Returns:
    
    The type of ML instance used in preparing and managing training of ML models. This is an ML compute instance chosen based on memory requirements for processing the training data and model.
  - withBaseProcessingInstanceType
```
public StartMLModelTransformJobRequest withBaseProcessingInstanceType(String baseProcessingInstanceType)
```
    The type of ML instance used in preparing and managing training of ML models. This is an ML compute instance chosen based on memory requirements for processing the training data and model.
    
    Parameters:
    
    baseProcessingInstanceType - The type of ML instance used in preparing and managing training of ML models. This is an ML compute instance chosen based on memory requirements for processing the training data and model.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setBaseProcessingInstanceVolumeSizeInGB
```
public void setBaseProcessingInstanceVolumeSizeInGB(Integer baseProcessingInstanceVolumeSizeInGB)
```
    The disk volume size of the training instance in gigabytes. The default is 0. Both input data and the output model are stored on disk, so the volume size must be large enough to hold both data sets. If not specified or 0, Neptune ML selects a disk volume size based on the recommendation generated in the data processing step.
    
    Parameters:
    
    baseProcessingInstanceVolumeSizeInGB - The disk volume size of the training instance in gigabytes. The default is 0. Both input data and the output model are stored on disk, so the volume size must be large enough to hold both data sets. If not specified or 0, Neptune ML selects a disk volume size based on the recommendation generated in the data processing step.
  - getBaseProcessingInstanceVolumeSizeInGB
```
public Integer getBaseProcessingInstanceVolumeSizeInGB()
```
    The disk volume size of the training instance in gigabytes. The default is 0. Both input data and the output model are stored on disk, so the volume size must be large enough to hold both data sets. If not specified or 0, Neptune ML selects a disk volume size based on the recommendation generated in the data processing step.
    
    Returns:
    
    The disk volume size of the training instance in gigabytes. The default is 0. Both input data and the output model are stored on disk, so the volume size must be large enough to hold both data sets. If not specified or 0, Neptune ML selects a disk volume size based on the recommendation generated in the data processing step.
  - withBaseProcessingInstanceVolumeSizeInGB
```
public StartMLModelTransformJobRequest withBaseProcessingInstanceVolumeSizeInGB(Integer baseProcessingInstanceVolumeSizeInGB)
```
    The disk volume size of the training instance in gigabytes. The default is 0. Both input data and the output model are stored on disk, so the volume size must be large enough to hold both data sets. If not specified or 0, Neptune ML selects a disk volume size based on the recommendation generated in the data processing step.
    
    Parameters:
    
    baseProcessingInstanceVolumeSizeInGB - The disk volume size of the training instance in gigabytes. The default is 0. Both input data and the output model are stored on disk, so the volume size must be large enough to hold both data sets. If not specified or 0, Neptune ML selects a disk volume size based on the recommendation generated in the data processing step.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - getSubnets
```
public List<String> getSubnets()
```
    The IDs of the subnets in the Neptune VPC. The default is None.
    
    Returns:
    
    The IDs of the subnets in the Neptune VPC. The default is None.
  - setSubnets
```
public void setSubnets(Collection<String> subnets)
```
    The IDs of the subnets in the Neptune VPC. The default is None.
    
    Parameters:
    
    subnets - The IDs of the subnets in the Neptune VPC. The default is None.
  - withSubnets
```
public StartMLModelTransformJobRequest withSubnets(String... subnets)
```
    The IDs of the subnets in the Neptune VPC. The default is None.
    
    NOTE: This method appends the values to the existing list (if any). Use setSubnets(java.util.Collection) or withSubnets(java.util.Collection) if you want to override the existing values.
    
    Parameters:
    
    subnets - The IDs of the subnets in the Neptune VPC. The default is None.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - withSubnets
```
public StartMLModelTransformJobRequest withSubnets(Collection<String> subnets)
```
    The IDs of the subnets in the Neptune VPC. The default is None.
    
    Parameters:
    
    subnets - The IDs of the subnets in the Neptune VPC. The default is None.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - getSecurityGroupIds
```
public List<String> getSecurityGroupIds()
```
    The VPC security group IDs. The default is None.
    
    Returns:
    
    The VPC security group IDs. The default is None.
  - setSecurityGroupIds
```
public void setSecurityGroupIds(Collection<String> securityGroupIds)
```
    The VPC security group IDs. The default is None.
    
    Parameters:
    
    securityGroupIds - The VPC security group IDs. The default is None.
  - withSecurityGroupIds
```
public StartMLModelTransformJobRequest withSecurityGroupIds(String... securityGroupIds)
```
    The VPC security group IDs. The default is None.
    
    NOTE: This method appends the values to the existing list (if any). Use setSecurityGroupIds(java.util.Collection) or withSecurityGroupIds(java.util.Collection) if you want to override the existing values.
    
    Parameters:
    
    securityGroupIds - The VPC security group IDs. The default is None.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - withSecurityGroupIds
```
public StartMLModelTransformJobRequest withSecurityGroupIds(Collection<String> securityGroupIds)
```
    The VPC security group IDs. The default is None.
    
    Parameters:
    
    securityGroupIds - The VPC security group IDs. The default is None.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setVolumeEncryptionKMSKey
```
public void setVolumeEncryptionKMSKey(String volumeEncryptionKMSKey)
```
    The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instances that run the training job. The default is None.
    
    Parameters:
    
    volumeEncryptionKMSKey - The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instances that run the training job. The default is None.
  - getVolumeEncryptionKMSKey
```
public String getVolumeEncryptionKMSKey()
```
    The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instances that run the training job. The default is None.
    
    Returns:
    
    The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instances that run the training job. The default is None.
  - withVolumeEncryptionKMSKey
```
public StartMLModelTransformJobRequest withVolumeEncryptionKMSKey(String volumeEncryptionKMSKey)
```
    The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instances that run the training job. The default is None.
    
    Parameters:
    
    volumeEncryptionKMSKey - The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instances that run the training job. The default is None.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setS3OutputEncryptionKMSKey
```
public void setS3OutputEncryptionKMSKey(String s3OutputEncryptionKMSKey)
```
    The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job. The default is none.
    
    Parameters:
    
    s3OutputEncryptionKMSKey - The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job. The default is none.
  - getS3OutputEncryptionKMSKey
```
public String getS3OutputEncryptionKMSKey()
```
    The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job. The default is none.
    
    Returns:
    
    The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job. The default is none.
  - withS3OutputEncryptionKMSKey
```
public StartMLModelTransformJobRequest withS3OutputEncryptionKMSKey(String s3OutputEncryptionKMSKey)
```
    The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job. The default is none.
    
    Parameters:
    
    s3OutputEncryptionKMSKey - The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job. The default is none.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - toString
```
public String toString()
```
    Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    
    A string representation of this object.
    
    See Also:
    
    Object.toString()
  - equals
```
public boolean equals(Object obj)
```
    Overrides:
    
    equals in class Object
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class Object
  - clone
```
public StartMLModelTransformJobRequest clone()
```
    Description copied from class: AmazonWebServiceRequest
    
    Creates a shallow clone of this object for all fields except the handler context. Explicitly does not clone the deep structure of the other fields in the message.
    
    Overrides:
    
    clone in class AmazonWebServiceRequest
    
    See Also:
    
    Object.clone()

AWS SDK for Java 1.x API Reference - 1.12.779

Class StartMLModelTransformJobRequest

Field Summary

Fields inherited from class com.amazonaws.AmazonWebServiceRequest

Constructor Summary

Method Summary

Methods inherited from class com.amazonaws.AmazonWebServiceRequest

Methods inherited from class java.lang.Object

Constructor Detail

StartMLModelTransformJobRequest

Method Detail

setId

getId

withId

setDataProcessingJobId

getDataProcessingJobId

withDataProcessingJobId

setMlModelTrainingJobId

getMlModelTrainingJobId

withMlModelTrainingJobId

setTrainingJobName

getTrainingJobName

withTrainingJobName

setModelTransformOutputS3Location

getModelTransformOutputS3Location

withModelTransformOutputS3Location

setSagemakerIamRoleArn

getSagemakerIamRoleArn

withSagemakerIamRoleArn

setNeptuneIamRoleArn

getNeptuneIamRoleArn

withNeptuneIamRoleArn

setCustomModelTransformParameters

getCustomModelTransformParameters

withCustomModelTransformParameters

setBaseProcessingInstanceType

getBaseProcessingInstanceType

withBaseProcessingInstanceType

setBaseProcessingInstanceVolumeSizeInGB

getBaseProcessingInstanceVolumeSizeInGB

withBaseProcessingInstanceVolumeSizeInGB

getSubnets

setSubnets

withSubnets

withSubnets

getSecurityGroupIds

setSecurityGroupIds

withSecurityGroupIds

withSecurityGroupIds

setVolumeEncryptionKMSKey

getVolumeEncryptionKMSKey

withVolumeEncryptionKMSKey

setS3OutputEncryptionKMSKey

getS3OutputEncryptionKMSKey

withS3OutputEncryptionKMSKey

toString

equals

hashCode

clone