* The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web * Services account. *
*/ private String transformJobName; /** *
* 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 Amazon Web Services Region in an Amazon Web Services account.
*
* 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.
*
* Configures the timeout and maximum number of retries for processing a transform job invocation. *
*/ private ModelClientConfig modelClientConfig; /** *
* 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.
*
* The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify the
* MaxConcurrentTransforms parameter, the value of
* (MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100 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.
*
* 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 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.
*
* The environment variables to set in the Docker container. We support up to 16 key and values entries in the map. *
*/ private java.util.Map* Describes the input source and the way the transform job consumes it. *
*/ private TransformInput transformInput; /** ** Describes the results of the transform job. *
*/ private TransformOutput transformOutput; /** ** Configuration to control how SageMaker captures inference data. *
*/ private BatchDataCaptureConfig dataCaptureConfig; /** ** Describes the resources, including ML instance types and ML instance count, to use for the transform job. *
*/ private TransformResources transformResources; /** ** 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. *
*/ private DataProcessing dataProcessing; /** ** (Optional) An array of key-value pairs. For more information, see Using * Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide. *
*/ private java.util.List* The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web * Services account. *
* * @param transformJobName * The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon * Web Services account. */ public void setTransformJobName(String transformJobName) { this.transformJobName = transformJobName; } /** ** The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web * Services account. *
* * @return The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon * Web Services account. */ public String getTransformJobName() { return this.transformJobName; } /** ** The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web * Services account. *
* * @param transformJobName * The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon * Web Services account. * @return Returns a reference to this object so that method calls can be chained together. */ public CreateTransformJobRequest withTransformJobName(String transformJobName) { setTransformJobName(transformJobName); return this; } /** *
* 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 Amazon Web Services Region in an Amazon Web Services account.
*
ModelName must be the name
* of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services
* account.
*/
public void setModelName(String modelName) {
this.modelName = 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 Amazon Web Services Region in an Amazon Web Services account.
*
ModelName must be the name
* of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services
* account.
*/
public String getModelName() {
return this.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 Amazon Web Services Region in an Amazon Web Services account.
*
ModelName must be the name
* of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services
* account.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public CreateTransformJobRequest withModelName(String modelName) {
setModelName(modelName);
return this;
}
/**
*
* 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.
*
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.
*/
public void setMaxConcurrentTransforms(Integer maxConcurrentTransforms) {
this.maxConcurrentTransforms = 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.
*
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.
*/
public Integer getMaxConcurrentTransforms() {
return this.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.
*
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.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public CreateTransformJobRequest withMaxConcurrentTransforms(Integer maxConcurrentTransforms) {
setMaxConcurrentTransforms(maxConcurrentTransforms);
return this;
}
/**
* * Configures the timeout and maximum number of retries for processing a transform job invocation. *
* * @param modelClientConfig * Configures the timeout and maximum number of retries for processing a transform job invocation. */ public void setModelClientConfig(ModelClientConfig modelClientConfig) { this.modelClientConfig = modelClientConfig; } /** ** Configures the timeout and maximum number of retries for processing a transform job invocation. *
* * @return Configures the timeout and maximum number of retries for processing a transform job invocation. */ public ModelClientConfig getModelClientConfig() { return this.modelClientConfig; } /** ** Configures the timeout and maximum number of retries for processing a transform job invocation. *
* * @param modelClientConfig * Configures the timeout and maximum number of retries for processing a transform job invocation. * @return Returns a reference to this object so that method calls can be chained together. */ public CreateTransformJobRequest withModelClientConfig(ModelClientConfig modelClientConfig) { setModelClientConfig(modelClientConfig); return this; } /** *
* 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.
*
* The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify the
* MaxConcurrentTransforms parameter, the value of
* (MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100 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.
*
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.
*
* The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify the
* MaxConcurrentTransforms parameter, the value of
* (MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100 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.
*/
public void setMaxPayloadInMB(Integer maxPayloadInMB) {
this.maxPayloadInMB = 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.
*
* The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify the
* MaxConcurrentTransforms parameter, the value of
* (MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100 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.
*
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.
*
* The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify the
* MaxConcurrentTransforms parameter, the value of
* (MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100 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.
*/
public Integer getMaxPayloadInMB() {
return this.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.
*
* The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify the
* MaxConcurrentTransforms parameter, the value of
* (MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100 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.
*
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.
*
* The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify the
* MaxConcurrentTransforms parameter, the value of
* (MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100 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.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public CreateTransformJobRequest withMaxPayloadInMB(Integer maxPayloadInMB) {
setMaxPayloadInMB(maxPayloadInMB);
return this;
}
/**
*
* 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 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.
*
* To enable the batch strategy, you must set the SplitType property 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 BatchStrategy
*/
public void setBatchStrategy(String batchStrategy) {
this.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 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.
*
* To enable the batch strategy, you must set the SplitType property 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 BatchStrategy
*/
public String getBatchStrategy() {
return this.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 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.
*
* To enable the batch strategy, you must set the SplitType property 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.
* @return Returns a reference to this object so that method calls can be chained together.
* @see BatchStrategy
*/
public CreateTransformJobRequest withBatchStrategy(String batchStrategy) {
setBatchStrategy(batchStrategy);
return this;
}
/**
*
* 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 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.
*
* To enable the batch strategy, you must set the SplitType property 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.
* @return Returns a reference to this object so that method calls can be chained together.
* @see BatchStrategy
*/
public CreateTransformJobRequest withBatchStrategy(BatchStrategy batchStrategy) {
this.batchStrategy = batchStrategy.toString();
return this;
}
/**
*
* The environment variables to set in the Docker container. We support up to 16 key and values entries in the map. *
* * @return The environment variables to set in the Docker container. We support up to 16 key and values entries in * the map. */ public java.util.Map* The environment variables to set in the Docker container. We support up to 16 key and values entries in the map. *
* * @param environment * The environment variables to set in the Docker container. We support up to 16 key and values entries in * the map. */ public void setEnvironment(java.util.Map* The environment variables to set in the Docker container. We support up to 16 key and values entries in the map. *
* * @param environment * The environment variables to set in the Docker container. We support up to 16 key and values entries in * the map. * @return Returns a reference to this object so that method calls can be chained together. */ public CreateTransformJobRequest withEnvironment(java.util.Map* Describes the input source and the way the transform job consumes it. *
* * @param transformInput * Describes the input source and the way the transform job consumes it. */ public void setTransformInput(TransformInput transformInput) { this.transformInput = transformInput; } /** ** Describes the input source and the way the transform job consumes it. *
* * @return Describes the input source and the way the transform job consumes it. */ public TransformInput getTransformInput() { return this.transformInput; } /** ** Describes the input source and the way the transform job consumes it. *
* * @param transformInput * Describes the input source and the way the transform job consumes it. * @return Returns a reference to this object so that method calls can be chained together. */ public CreateTransformJobRequest withTransformInput(TransformInput transformInput) { setTransformInput(transformInput); return this; } /** ** Describes the results of the transform job. *
* * @param transformOutput * Describes the results of the transform job. */ public void setTransformOutput(TransformOutput transformOutput) { this.transformOutput = transformOutput; } /** ** Describes the results of the transform job. *
* * @return Describes the results of the transform job. */ public TransformOutput getTransformOutput() { return this.transformOutput; } /** ** Describes the results of the transform job. *
* * @param transformOutput * Describes the results of the transform job. * @return Returns a reference to this object so that method calls can be chained together. */ public CreateTransformJobRequest withTransformOutput(TransformOutput transformOutput) { setTransformOutput(transformOutput); return this; } /** ** Configuration to control how SageMaker captures inference data. *
* * @param dataCaptureConfig * Configuration to control how SageMaker captures inference data. */ public void setDataCaptureConfig(BatchDataCaptureConfig dataCaptureConfig) { this.dataCaptureConfig = dataCaptureConfig; } /** ** Configuration to control how SageMaker captures inference data. *
* * @return Configuration to control how SageMaker captures inference data. */ public BatchDataCaptureConfig getDataCaptureConfig() { return this.dataCaptureConfig; } /** ** Configuration to control how SageMaker captures inference data. *
* * @param dataCaptureConfig * Configuration to control how SageMaker captures inference data. * @return Returns a reference to this object so that method calls can be chained together. */ public CreateTransformJobRequest withDataCaptureConfig(BatchDataCaptureConfig dataCaptureConfig) { setDataCaptureConfig(dataCaptureConfig); return this; } /** ** Describes the resources, including ML instance types and ML instance count, to use for the transform job. *
* * @param transformResources * Describes the resources, including ML instance types and ML instance count, to use for the transform job. */ public void setTransformResources(TransformResources transformResources) { this.transformResources = transformResources; } /** ** Describes the resources, including ML instance types and ML instance count, to use for the transform job. *
* * @return Describes the resources, including ML instance types and ML instance count, to use for the transform job. */ public TransformResources getTransformResources() { return this.transformResources; } /** ** Describes the resources, including ML instance types and ML instance count, to use for the transform job. *
* * @param transformResources * Describes the resources, including ML instance types and ML instance count, to use for the transform job. * @return Returns a reference to this object so that method calls can be chained together. */ public CreateTransformJobRequest withTransformResources(TransformResources transformResources) { setTransformResources(transformResources); return this; } /** ** 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. *
* * @param 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. */ public void setDataProcessing(DataProcessing dataProcessing) { this.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. *
* * @return 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. */ public DataProcessing getDataProcessing() { return this.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. *
* * @param 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. * @return Returns a reference to this object so that method calls can be chained together. */ public CreateTransformJobRequest withDataProcessing(DataProcessing dataProcessing) { setDataProcessing(dataProcessing); return this; } /** ** (Optional) An array of key-value pairs. For more information, see Using * Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide. *
* * @return (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide. */ public java.util.List* (Optional) An array of key-value pairs. For more information, see Using * Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide. *
* * @param tags * (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide. */ public void setTags(java.util.Collection* (Optional) An array of key-value pairs. For more information, see Using * Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide. *
** NOTE: This method appends the values to the existing list (if any). Use * {@link #setTags(java.util.Collection)} or {@link #withTags(java.util.Collection)} if you want to override the * existing values. *
* * @param tags * (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide. * @return Returns a reference to this object so that method calls can be chained together. */ public CreateTransformJobRequest withTags(Tag... tags) { if (this.tags == null) { setTags(new java.util.ArrayList* (Optional) An array of key-value pairs. For more information, see Using * Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide. *
* * @param tags * (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide. * @return Returns a reference to this object so that method calls can be chained together. */ public CreateTransformJobRequest withTags(java.util.Collection