com.amazonaws.services.sagemaker.model

Class CreateTransformJobRequest

java.lang.Object

com.amazonaws.AmazonWebServiceRequest

com.amazonaws.services.sagemaker.model.CreateTransformJobRequest

All Implemented Interfaces:

HandlerContextAware, ReadLimitInfo, Serializable, Cloneable

@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class CreateTransformJobRequest
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
CreateTransformJobRequest()

Method Summary

Modifier and Type	Method and Description
CreateTransformJobRequest	addEnvironmentEntry(String key, String value)
CreateTransformJobRequest	clearEnvironmentEntries() Removes all the entries added into Environment.
CreateTransformJobRequest	clone()
boolean	equals(Object obj)
String	getBatchStrategy() Specifies the number of records to include in a mini-batch for an HTTP inference request.
DataProcessing	getDataProcessing() The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output.
Map<String,String>	getEnvironment() The environment variables to set in the Docker container.
ExperimentConfig	getExperimentConfig()
Integer	getMaxConcurrentTransforms() The maximum number of parallel requests that can be sent to each instance in a transform job.
Integer	getMaxPayloadInMB() The maximum allowed size of the payload, in MB.
String	getModelName() The name of the model that you want to use for the transform job.
List<Tag>	getTags() (Optional) An array of key-value pairs.
TransformInput	getTransformInput() Describes the input source and the way the transform job consumes it.
String	getTransformJobName() The name of the transform job.
TransformOutput	getTransformOutput() Describes the results of the transform job.
TransformResources	getTransformResources() Describes the resources, including ML instance types and ML instance count, to use for the transform job.
int	hashCode()
void	setBatchStrategy(String batchStrategy) Specifies the number of records to include in a mini-batch for an HTTP inference request.
void	setDataProcessing(DataProcessing dataProcessing) The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output.
void	setEnvironment(Map<String,String> environment) The environment variables to set in the Docker container.
void	setExperimentConfig(ExperimentConfig experimentConfig)
void	setMaxConcurrentTransforms(Integer maxConcurrentTransforms) The maximum number of parallel requests that can be sent to each instance in a transform job.
void	setMaxPayloadInMB(Integer maxPayloadInMB) The maximum allowed size of the payload, in MB.
void	setModelName(String modelName) The name of the model that you want to use for the transform job.
void	setTags(Collection<Tag> tags) (Optional) An array of key-value pairs.
void	setTransformInput(TransformInput transformInput) Describes the input source and the way the transform job consumes it.
void	setTransformJobName(String transformJobName) The name of the transform job.
void	setTransformOutput(TransformOutput transformOutput) Describes the results of the transform job.
void	setTransformResources(TransformResources transformResources) Describes the resources, including ML instance types and ML instance count, to use for the transform job.
String	toString() Returns a string representation of this object.
CreateTransformJobRequest	withBatchStrategy(BatchStrategy batchStrategy) Specifies the number of records to include in a mini-batch for an HTTP inference request.
CreateTransformJobRequest	withBatchStrategy(String batchStrategy) Specifies the number of records to include in a mini-batch for an HTTP inference request.
CreateTransformJobRequest	withDataProcessing(DataProcessing dataProcessing) The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output.
CreateTransformJobRequest	withEnvironment(Map<String,String> environment) The environment variables to set in the Docker container.
CreateTransformJobRequest	withExperimentConfig(ExperimentConfig experimentConfig)
CreateTransformJobRequest	withMaxConcurrentTransforms(Integer maxConcurrentTransforms) The maximum number of parallel requests that can be sent to each instance in a transform job.
CreateTransformJobRequest	withMaxPayloadInMB(Integer maxPayloadInMB) The maximum allowed size of the payload, in MB.
CreateTransformJobRequest	withModelName(String modelName) The name of the model that you want to use for the transform job.
CreateTransformJobRequest	withTags(Collection<Tag> tags) (Optional) An array of key-value pairs.
CreateTransformJobRequest	withTags(Tag... tags) (Optional) An array of key-value pairs.
CreateTransformJobRequest	withTransformInput(TransformInput transformInput) Describes the input source and the way the transform job consumes it.
CreateTransformJobRequest	withTransformJobName(String transformJobName) The name of the transform job.
CreateTransformJobRequest	withTransformOutput(TransformOutput transformOutput) Describes the results of the transform job.
CreateTransformJobRequest	withTransformResources(TransformResources transformResources) Describes the resources, including ML instance types and ML instance count, to use for the transform job.

Methods inherited from class com.amazonaws.AmazonWebServiceRequest

addHandlerContext, copyBaseTo, getCloneRoot, getCloneSource, getCustomQueryParameters, getCustomRequestHeaders, getGeneralProgressListener, getHandlerContext, getReadLimit, getRequestClientOptions, getRequestCredentials, getRequestCredentialsProvider, getRequestMetricCollector, getSdkClientExecutionTimeout, getSdkRequestTimeout, putCustomQueryParameter, putCustomRequestHeader, setGeneralProgressListener, setRequestCredentials, setRequestCredentialsProvider, setRequestMetricCollector, setSdkClientExecutionTimeout, setSdkRequestTimeout, withGeneralProgressListener, withRequestCredentialsProvider, withRequestMetricCollector, withSdkClientExecutionTimeout, withSdkRequestTimeout

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

CreateTransformJobRequest

public CreateTransformJobRequest()

Method Detail

setTransformJobName

public void setTransformJobName(String transformJobName)

The name of the transform job. The name must be unique within an AWS Region in an AWS account.

Parameters:

transformJobName - The name of the transform job. The name must be unique within an AWS Region in an AWS account.

getTransformJobName

public String getTransformJobName()

The name of the transform job. The name must be unique within an AWS Region in an AWS account.

Returns:

The name of the transform job. The name must be unique within an AWS Region in an AWS account.

withTransformJobName

public CreateTransformJobRequest withTransformJobName(String transformJobName)

The name of the transform job. The name must be unique within an AWS Region in an AWS account.

Parameters:

transformJobName - The name of the transform job. The name must be unique within an AWS Region in an AWS account.

Returns:

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

setModelName

public void setModelName(String modelName)

The name of the model that you want to use for the transform job. ModelName must be the name of an existing Amazon SageMaker model within an AWS Region in an AWS account.

Parameters:

modelName - The name of the model that you want to use for the transform job. ModelName must be the name of an existing Amazon SageMaker model within an AWS Region in an AWS account.

getModelName

public String getModelName()

The name of the model that you want to use for the transform job. ModelName must be the name of an existing Amazon SageMaker model within an AWS Region in an AWS account.

Returns:

The name of the model that you want to use for the transform job. ModelName must be the name of an existing Amazon SageMaker model within an AWS Region in an AWS account.

withModelName

public CreateTransformJobRequest withModelName(String modelName)

The name of the model that you want to use for the transform job. ModelName must be the name of an existing Amazon SageMaker model within an AWS Region in an AWS account.

Parameters:

modelName - The name of the model that you want to use for the transform job. ModelName must be the name of an existing Amazon SageMaker model within an AWS Region in an AWS account.

Returns:

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

setMaxConcurrentTransforms

public void setMaxConcurrentTransforms(Integer maxConcurrentTransforms)

The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.

Parameters:

maxConcurrentTransforms - The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.

getMaxConcurrentTransforms

public Integer getMaxConcurrentTransforms()

The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.

Returns:

The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.

withMaxConcurrentTransforms

public CreateTransformJobRequest withMaxConcurrentTransforms(Integer maxConcurrentTransforms)

The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.

Parameters:

maxConcurrentTransforms - The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.

Returns:

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

setMaxPayloadInMB

public void setMaxPayloadInMB(Integer maxPayloadInMB)

The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB.

For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.

Parameters:

maxPayloadInMB - The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB.

For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.

getMaxPayloadInMB

public Integer getMaxPayloadInMB()

The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB.

For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.

Returns:

The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB.

For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.

withMaxPayloadInMB

public CreateTransformJobRequest withMaxPayloadInMB(Integer maxPayloadInMB)

The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB.

For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.

Parameters:

maxPayloadInMB - The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB.

For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.

Returns:

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

setBatchStrategy

public void setBatchStrategy(String batchStrategy)

Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.

To enable the batch strategy, you must set the SplitType property of the DataProcessing object to Line, RecordIO, or TFRecord.

To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line.

To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.

Parameters:

batchStrategy - Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.

To enable the batch strategy, you must set the SplitType property of the DataProcessing object to Line, RecordIO, or TFRecord.

To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line.

To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.

See Also:

BatchStrategy

getBatchStrategy

public String getBatchStrategy()

Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.

To enable the batch strategy, you must set the SplitType property of the DataProcessing object to Line, RecordIO, or TFRecord.

To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line.

To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.

Returns:

Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.

To enable the batch strategy, you must set the SplitType property of the DataProcessing object to Line, RecordIO, or TFRecord.

To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line.

To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.

See Also:

BatchStrategy

withBatchStrategy

public CreateTransformJobRequest withBatchStrategy(String batchStrategy)

Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.

To enable the batch strategy, you must set the SplitType property of the DataProcessing object to Line, RecordIO, or TFRecord.

To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line.

To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.

Parameters:

batchStrategy - Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.

To enable the batch strategy, you must set the SplitType property of the DataProcessing object to Line, RecordIO, or TFRecord.

To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line.

To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.

Returns:

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

See Also:

BatchStrategy

withBatchStrategy

public CreateTransformJobRequest withBatchStrategy(BatchStrategy batchStrategy)

Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.

To enable the batch strategy, you must set the SplitType property of the DataProcessing object to Line, RecordIO, or TFRecord.

To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line.

To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.

Parameters:

batchStrategy - Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.

To enable the batch strategy, you must set the SplitType property of the DataProcessing object to Line, RecordIO, or TFRecord.

To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line.

To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.

Returns:

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

See Also:

BatchStrategy

getEnvironment

public Map<String,String> getEnvironment()

The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.

Returns:

The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.

setEnvironment

public void setEnvironment(Map<String,String> environment)

The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.

Parameters:

environment - The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.

withEnvironment

public CreateTransformJobRequest withEnvironment(Map<String,String> environment)

The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.

Parameters:

environment - The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.

Returns:

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

addEnvironmentEntry

public CreateTransformJobRequest addEnvironmentEntry(String key,
                                                     String value)

clearEnvironmentEntries

public CreateTransformJobRequest clearEnvironmentEntries()

Removes all the entries added into Environment.

Returns:

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

setTransformInput

public void setTransformInput(TransformInput transformInput)

Describes the input source and the way the transform job consumes it.

Parameters:

transformInput - Describes the input source and the way the transform job consumes it.

getTransformInput

public TransformInput getTransformInput()

Describes the input source and the way the transform job consumes it.

Returns:

Describes the input source and the way the transform job consumes it.

withTransformInput

public CreateTransformJobRequest withTransformInput(TransformInput transformInput)

Describes the input source and the way the transform job consumes it.

Parameters:

transformInput - Describes the input source and the way the transform job consumes it.

Returns:

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

setTransformOutput

public void setTransformOutput(TransformOutput transformOutput)

Describes the results of the transform job.

Parameters:

transformOutput - Describes the results of the transform job.

getTransformOutput

public TransformOutput getTransformOutput()

Describes the results of the transform job.

Returns:

Describes the results of the transform job.

withTransformOutput

public CreateTransformJobRequest withTransformOutput(TransformOutput transformOutput)

Describes the results of the transform job.

Parameters:

transformOutput - Describes the results of the transform job.

Returns:

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

setTransformResources

public void setTransformResources(TransformResources transformResources)

Describes the resources, including ML instance types and ML instance count, to use for the transform job.

Parameters:

transformResources - Describes the resources, including ML instance types and ML instance count, to use for the transform job.

getTransformResources

public TransformResources getTransformResources()

Describes the resources, including ML instance types and ML instance count, to use for the transform job.

Returns:

Describes the resources, including ML instance types and ML instance count, to use for the transform job.

withTransformResources

public CreateTransformJobRequest withTransformResources(TransformResources transformResources)

Describes the resources, including ML instance types and ML instance count, to use for the transform job.

Parameters:

transformResources - Describes the resources, including ML instance types and ML instance count, to use for the transform job.

Returns:

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

setDataProcessing

public void setDataProcessing(DataProcessing dataProcessing)

The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.

Parameters:

dataProcessing - The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.

getDataProcessing

public DataProcessing getDataProcessing()

The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.

Returns:

The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.

withDataProcessing

public CreateTransformJobRequest withDataProcessing(DataProcessing dataProcessing)

The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.

Parameters:

dataProcessing - The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.

Returns:

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

getTags

public List<Tag> getTags()

(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.

Returns:

(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.

setTags

public void setTags(Collection<Tag> tags)

(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.

Parameters:

tags - (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.

withTags

public CreateTransformJobRequest withTags(Tag... tags)

(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.

NOTE: This method appends the values to the existing list (if any). Use setTags(java.util.Collection) or withTags(java.util.Collection) if you want to override the existing values.

Parameters:

tags - (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.

Returns:

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

withTags

public CreateTransformJobRequest withTags(Collection<Tag> tags)

(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.

Parameters:

tags - (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.

Returns:

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

setExperimentConfig

public void setExperimentConfig(ExperimentConfig experimentConfig)

Parameters:

experimentConfig -

getExperimentConfig

public ExperimentConfig getExperimentConfig()

Returns:

withExperimentConfig

public CreateTransformJobRequest withExperimentConfig(ExperimentConfig experimentConfig)

Parameters:

experimentConfig -

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 CreateTransformJobRequest clone()

Overrides:

clone in class AmazonWebServiceRequest