/** * Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. * SPDX-License-Identifier: Apache-2.0. */ #pragma once #include #include #include #include namespace Aws { namespace Utils { namespace Json { class JsonValue; class JsonView; } // namespace Json } // namespace Utils namespace SageMaker { namespace Model { /** *

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.

See * Also:

AWS * API Reference

*/ class AWS_SAGEMAKER_API DataProcessing { public: DataProcessing(); DataProcessing(Aws::Utils::Json::JsonView jsonValue); DataProcessing& operator=(Aws::Utils::Json::JsonView jsonValue); Aws::Utils::Json::JsonValue Jsonize() const; /** *

A JSONPath * expression used to select a portion of the input data to pass to the algorithm. * Use the InputFilter parameter to exclude fields, such as an ID * column, from the input. If you want Amazon SageMaker to pass the entire input * dataset to the algorithm, accept the default value $.

*

Examples: "$", "$[1:]", "$.features" *

*/ inline const Aws::String& GetInputFilter() const{ return m_inputFilter; } /** *

A JSONPath * expression used to select a portion of the input data to pass to the algorithm. * Use the InputFilter parameter to exclude fields, such as an ID * column, from the input. If you want Amazon SageMaker to pass the entire input * dataset to the algorithm, accept the default value $.

*

Examples: "$", "$[1:]", "$.features" *

*/ inline bool InputFilterHasBeenSet() const { return m_inputFilterHasBeenSet; } /** *

A JSONPath * expression used to select a portion of the input data to pass to the algorithm. * Use the InputFilter parameter to exclude fields, such as an ID * column, from the input. If you want Amazon SageMaker to pass the entire input * dataset to the algorithm, accept the default value $.

*

Examples: "$", "$[1:]", "$.features" *

*/ inline void SetInputFilter(const Aws::String& value) { m_inputFilterHasBeenSet = true; m_inputFilter = value; } /** *

A JSONPath * expression used to select a portion of the input data to pass to the algorithm. * Use the InputFilter parameter to exclude fields, such as an ID * column, from the input. If you want Amazon SageMaker to pass the entire input * dataset to the algorithm, accept the default value $.

*

Examples: "$", "$[1:]", "$.features" *

*/ inline void SetInputFilter(Aws::String&& value) { m_inputFilterHasBeenSet = true; m_inputFilter = std::move(value); } /** *

A JSONPath * expression used to select a portion of the input data to pass to the algorithm. * Use the InputFilter parameter to exclude fields, such as an ID * column, from the input. If you want Amazon SageMaker to pass the entire input * dataset to the algorithm, accept the default value $.

*

Examples: "$", "$[1:]", "$.features" *

*/ inline void SetInputFilter(const char* value) { m_inputFilterHasBeenSet = true; m_inputFilter.assign(value); } /** *

A JSONPath * expression used to select a portion of the input data to pass to the algorithm. * Use the InputFilter parameter to exclude fields, such as an ID * column, from the input. If you want Amazon SageMaker to pass the entire input * dataset to the algorithm, accept the default value $.

*

Examples: "$", "$[1:]", "$.features" *

*/ inline DataProcessing& WithInputFilter(const Aws::String& value) { SetInputFilter(value); return *this;} /** *

A JSONPath * expression used to select a portion of the input data to pass to the algorithm. * Use the InputFilter parameter to exclude fields, such as an ID * column, from the input. If you want Amazon SageMaker to pass the entire input * dataset to the algorithm, accept the default value $.

*

Examples: "$", "$[1:]", "$.features" *

*/ inline DataProcessing& WithInputFilter(Aws::String&& value) { SetInputFilter(std::move(value)); return *this;} /** *

A JSONPath * expression used to select a portion of the input data to pass to the algorithm. * Use the InputFilter parameter to exclude fields, such as an ID * column, from the input. If you want Amazon SageMaker to pass the entire input * dataset to the algorithm, accept the default value $.

*

Examples: "$", "$[1:]", "$.features" *

*/ inline DataProcessing& WithInputFilter(const char* value) { SetInputFilter(value); return *this;} /** *

A JSONPath * expression used to select a portion of the joined dataset to save in the output * file for a batch transform job. If you want Amazon SageMaker to store the entire * input dataset in the output file, leave the default value, $. If * you specify indexes that aren't within the dimension size of the joined dataset, * you get an error.

Examples: "$", "$[0,5:]", * "$['id','SageMakerOutput']"

*/ inline const Aws::String& GetOutputFilter() const{ return m_outputFilter; } /** *

A JSONPath * expression used to select a portion of the joined dataset to save in the output * file for a batch transform job. If you want Amazon SageMaker to store the entire * input dataset in the output file, leave the default value, $. If * you specify indexes that aren't within the dimension size of the joined dataset, * you get an error.

Examples: "$", "$[0,5:]", * "$['id','SageMakerOutput']"

*/ inline bool OutputFilterHasBeenSet() const { return m_outputFilterHasBeenSet; } /** *

A JSONPath * expression used to select a portion of the joined dataset to save in the output * file for a batch transform job. If you want Amazon SageMaker to store the entire * input dataset in the output file, leave the default value, $. If * you specify indexes that aren't within the dimension size of the joined dataset, * you get an error.

Examples: "$", "$[0,5:]", * "$['id','SageMakerOutput']"

*/ inline void SetOutputFilter(const Aws::String& value) { m_outputFilterHasBeenSet = true; m_outputFilter = value; } /** *

A JSONPath * expression used to select a portion of the joined dataset to save in the output * file for a batch transform job. If you want Amazon SageMaker to store the entire * input dataset in the output file, leave the default value, $. If * you specify indexes that aren't within the dimension size of the joined dataset, * you get an error.

Examples: "$", "$[0,5:]", * "$['id','SageMakerOutput']"

*/ inline void SetOutputFilter(Aws::String&& value) { m_outputFilterHasBeenSet = true; m_outputFilter = std::move(value); } /** *

A JSONPath * expression used to select a portion of the joined dataset to save in the output * file for a batch transform job. If you want Amazon SageMaker to store the entire * input dataset in the output file, leave the default value, $. If * you specify indexes that aren't within the dimension size of the joined dataset, * you get an error.

Examples: "$", "$[0,5:]", * "$['id','SageMakerOutput']"

*/ inline void SetOutputFilter(const char* value) { m_outputFilterHasBeenSet = true; m_outputFilter.assign(value); } /** *

A JSONPath * expression used to select a portion of the joined dataset to save in the output * file for a batch transform job. If you want Amazon SageMaker to store the entire * input dataset in the output file, leave the default value, $. If * you specify indexes that aren't within the dimension size of the joined dataset, * you get an error.

Examples: "$", "$[0,5:]", * "$['id','SageMakerOutput']"

*/ inline DataProcessing& WithOutputFilter(const Aws::String& value) { SetOutputFilter(value); return *this;} /** *

A JSONPath * expression used to select a portion of the joined dataset to save in the output * file for a batch transform job. If you want Amazon SageMaker to store the entire * input dataset in the output file, leave the default value, $. If * you specify indexes that aren't within the dimension size of the joined dataset, * you get an error.

Examples: "$", "$[0,5:]", * "$['id','SageMakerOutput']"

*/ inline DataProcessing& WithOutputFilter(Aws::String&& value) { SetOutputFilter(std::move(value)); return *this;} /** *

A JSONPath * expression used to select a portion of the joined dataset to save in the output * file for a batch transform job. If you want Amazon SageMaker to store the entire * input dataset in the output file, leave the default value, $. If * you specify indexes that aren't within the dimension size of the joined dataset, * you get an error.

Examples: "$", "$[0,5:]", * "$['id','SageMakerOutput']"

*/ inline DataProcessing& WithOutputFilter(const char* value) { SetOutputFilter(value); return *this;} /** *

Specifies the source of the data to join with the transformed data. The valid * values are None and Input. The default value is * None, which specifies not to join the input with the transformed * data. If you want the batch transform job to join the original input data with * the transformed data, set JoinSource to Input.

*

For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds * the transformed data to the input JSON object in an attribute called * SageMakerOutput. The joined result for JSON must be a key-value * pair object. If the input is not a key-value pair object, Amazon SageMaker * creates a new JSON file. In the new JSON file, and the input data is stored * under the SageMakerInput key and the results are stored in * SageMakerOutput.

For CSV files, Amazon SageMaker combines * the transformed data with the input data at the end of the input data and stores * it in the output file. The joined data has the joined input data followed by the * transformed data and the output is a CSV file.

*/ inline const JoinSource& GetJoinSource() const{ return m_joinSource; } /** *

Specifies the source of the data to join with the transformed data. The valid * values are None and Input. The default value is * None, which specifies not to join the input with the transformed * data. If you want the batch transform job to join the original input data with * the transformed data, set JoinSource to Input.

*

For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds * the transformed data to the input JSON object in an attribute called * SageMakerOutput. The joined result for JSON must be a key-value * pair object. If the input is not a key-value pair object, Amazon SageMaker * creates a new JSON file. In the new JSON file, and the input data is stored * under the SageMakerInput key and the results are stored in * SageMakerOutput.

For CSV files, Amazon SageMaker combines * the transformed data with the input data at the end of the input data and stores * it in the output file. The joined data has the joined input data followed by the * transformed data and the output is a CSV file.

*/ inline bool JoinSourceHasBeenSet() const { return m_joinSourceHasBeenSet; } /** *

Specifies the source of the data to join with the transformed data. The valid * values are None and Input. The default value is * None, which specifies not to join the input with the transformed * data. If you want the batch transform job to join the original input data with * the transformed data, set JoinSource to Input.

*

For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds * the transformed data to the input JSON object in an attribute called * SageMakerOutput. The joined result for JSON must be a key-value * pair object. If the input is not a key-value pair object, Amazon SageMaker * creates a new JSON file. In the new JSON file, and the input data is stored * under the SageMakerInput key and the results are stored in * SageMakerOutput.

For CSV files, Amazon SageMaker combines * the transformed data with the input data at the end of the input data and stores * it in the output file. The joined data has the joined input data followed by the * transformed data and the output is a CSV file.

*/ inline void SetJoinSource(const JoinSource& value) { m_joinSourceHasBeenSet = true; m_joinSource = value; } /** *

Specifies the source of the data to join with the transformed data. The valid * values are None and Input. The default value is * None, which specifies not to join the input with the transformed * data. If you want the batch transform job to join the original input data with * the transformed data, set JoinSource to Input.

*

For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds * the transformed data to the input JSON object in an attribute called * SageMakerOutput. The joined result for JSON must be a key-value * pair object. If the input is not a key-value pair object, Amazon SageMaker * creates a new JSON file. In the new JSON file, and the input data is stored * under the SageMakerInput key and the results are stored in * SageMakerOutput.

For CSV files, Amazon SageMaker combines * the transformed data with the input data at the end of the input data and stores * it in the output file. The joined data has the joined input data followed by the * transformed data and the output is a CSV file.

*/ inline void SetJoinSource(JoinSource&& value) { m_joinSourceHasBeenSet = true; m_joinSource = std::move(value); } /** *

Specifies the source of the data to join with the transformed data. The valid * values are None and Input. The default value is * None, which specifies not to join the input with the transformed * data. If you want the batch transform job to join the original input data with * the transformed data, set JoinSource to Input.

*

For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds * the transformed data to the input JSON object in an attribute called * SageMakerOutput. The joined result for JSON must be a key-value * pair object. If the input is not a key-value pair object, Amazon SageMaker * creates a new JSON file. In the new JSON file, and the input data is stored * under the SageMakerInput key and the results are stored in * SageMakerOutput.

For CSV files, Amazon SageMaker combines * the transformed data with the input data at the end of the input data and stores * it in the output file. The joined data has the joined input data followed by the * transformed data and the output is a CSV file.

*/ inline DataProcessing& WithJoinSource(const JoinSource& value) { SetJoinSource(value); return *this;} /** *

Specifies the source of the data to join with the transformed data. The valid * values are None and Input. The default value is * None, which specifies not to join the input with the transformed * data. If you want the batch transform job to join the original input data with * the transformed data, set JoinSource to Input.

*

For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds * the transformed data to the input JSON object in an attribute called * SageMakerOutput. The joined result for JSON must be a key-value * pair object. If the input is not a key-value pair object, Amazon SageMaker * creates a new JSON file. In the new JSON file, and the input data is stored * under the SageMakerInput key and the results are stored in * SageMakerOutput.

For CSV files, Amazon SageMaker combines * the transformed data with the input data at the end of the input data and stores * it in the output file. The joined data has the joined input data followed by the * transformed data and the output is a CSV file.

*/ inline DataProcessing& WithJoinSource(JoinSource&& value) { SetJoinSource(std::move(value)); return *this;} private: Aws::String m_inputFilter; bool m_inputFilterHasBeenSet; Aws::String m_outputFilter; bool m_outputFilterHasBeenSet; JoinSource m_joinSource; bool m_joinSourceHasBeenSet; }; } // namespace Model } // namespace SageMaker } // namespace Aws