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pxz-hos-client-cpp-module/support/aws-sdk-cpp-master/aws-cpp-sdk-sagemaker/include/aws/sagemaker/model/DataProcessing.h

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/**
* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
* SPDX-License-Identifier: Apache-2.0.
*/
#pragma once
#include <aws/sagemaker/SageMaker_EXPORTS.h>
#include <aws/core/utils/memory/stl/AWSString.h>
#include <aws/sagemaker/model/JoinSource.h>
#include <utility>
namespace Aws
{
namespace Utils
{
namespace Json
{
class JsonValue;
class JsonView;
} // namespace Json
} // namespace Utils
namespace SageMaker
{
namespace Model
{
/**
* <p>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 <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html">Associate
* Prediction Results with their Corresponding Input Records</a>.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DataProcessing">AWS
* API Reference</a></p>
*/
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;
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* expression used to select a portion of the input data to pass to the algorithm.
* Use the <code>InputFilter</code> 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 <code>$</code>.</p>
* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
* </p>
*/
inline const Aws::String& GetInputFilter() const{ return m_inputFilter; }
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* expression used to select a portion of the input data to pass to the algorithm.
* Use the <code>InputFilter</code> 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 <code>$</code>.</p>
* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
* </p>
*/
inline bool InputFilterHasBeenSet() const { return m_inputFilterHasBeenSet; }
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* expression used to select a portion of the input data to pass to the algorithm.
* Use the <code>InputFilter</code> 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 <code>$</code>.</p>
* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
* </p>
*/
inline void SetInputFilter(const Aws::String& value) { m_inputFilterHasBeenSet = true; m_inputFilter = value; }
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* expression used to select a portion of the input data to pass to the algorithm.
* Use the <code>InputFilter</code> 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 <code>$</code>.</p>
* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
* </p>
*/
inline void SetInputFilter(Aws::String&& value) { m_inputFilterHasBeenSet = true; m_inputFilter = std::move(value); }
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* expression used to select a portion of the input data to pass to the algorithm.
* Use the <code>InputFilter</code> 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 <code>$</code>.</p>
* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
* </p>
*/
inline void SetInputFilter(const char* value) { m_inputFilterHasBeenSet = true; m_inputFilter.assign(value); }
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* expression used to select a portion of the input data to pass to the algorithm.
* Use the <code>InputFilter</code> 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 <code>$</code>.</p>
* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
* </p>
*/
inline DataProcessing& WithInputFilter(const Aws::String& value) { SetInputFilter(value); return *this;}
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* expression used to select a portion of the input data to pass to the algorithm.
* Use the <code>InputFilter</code> 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 <code>$</code>.</p>
* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
* </p>
*/
inline DataProcessing& WithInputFilter(Aws::String&& value) { SetInputFilter(std::move(value)); return *this;}
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* expression used to select a portion of the input data to pass to the algorithm.
* Use the <code>InputFilter</code> 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 <code>$</code>.</p>
* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
* </p>
*/
inline DataProcessing& WithInputFilter(const char* value) { SetInputFilter(value); return *this;}
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* 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, <code>$</code>. If
* you specify indexes that aren't within the dimension size of the joined dataset,
* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
* <code>"$['id','SageMakerOutput']"</code> </p>
*/
inline const Aws::String& GetOutputFilter() const{ return m_outputFilter; }
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* 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, <code>$</code>. If
* you specify indexes that aren't within the dimension size of the joined dataset,
* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
* <code>"$['id','SageMakerOutput']"</code> </p>
*/
inline bool OutputFilterHasBeenSet() const { return m_outputFilterHasBeenSet; }
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* 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, <code>$</code>. If
* you specify indexes that aren't within the dimension size of the joined dataset,
* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
* <code>"$['id','SageMakerOutput']"</code> </p>
*/
inline void SetOutputFilter(const Aws::String& value) { m_outputFilterHasBeenSet = true; m_outputFilter = value; }
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* 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, <code>$</code>. If
* you specify indexes that aren't within the dimension size of the joined dataset,
* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
* <code>"$['id','SageMakerOutput']"</code> </p>
*/
inline void SetOutputFilter(Aws::String&& value) { m_outputFilterHasBeenSet = true; m_outputFilter = std::move(value); }
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* 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, <code>$</code>. If
* you specify indexes that aren't within the dimension size of the joined dataset,
* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
* <code>"$['id','SageMakerOutput']"</code> </p>
*/
inline void SetOutputFilter(const char* value) { m_outputFilterHasBeenSet = true; m_outputFilter.assign(value); }
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* 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, <code>$</code>. If
* you specify indexes that aren't within the dimension size of the joined dataset,
* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
* <code>"$['id','SageMakerOutput']"</code> </p>
*/
inline DataProcessing& WithOutputFilter(const Aws::String& value) { SetOutputFilter(value); return *this;}
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* 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, <code>$</code>. If
* you specify indexes that aren't within the dimension size of the joined dataset,
* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
* <code>"$['id','SageMakerOutput']"</code> </p>
*/
inline DataProcessing& WithOutputFilter(Aws::String&& value) { SetOutputFilter(std::move(value)); return *this;}
/**
* <p>A <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
* 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, <code>$</code>. If
* you specify indexes that aren't within the dimension size of the joined dataset,
* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
* <code>"$['id','SageMakerOutput']"</code> </p>
*/
inline DataProcessing& WithOutputFilter(const char* value) { SetOutputFilter(value); return *this;}
/**
* <p>Specifies the source of the data to join with the transformed data. The valid
* values are <code>None</code> and <code>Input</code>. The default value is
* <code>None</code>, 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 <code>JoinSource</code> to <code>Input</code>. </p>
* <p>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
* <code>SageMakerOutput</code>. 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 <code>SageMakerInput</code> key and the results are stored in
* <code>SageMakerOutput</code>.</p> <p>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. </p>
*/
inline const JoinSource& GetJoinSource() const{ return m_joinSource; }
/**
* <p>Specifies the source of the data to join with the transformed data. The valid
* values are <code>None</code> and <code>Input</code>. The default value is
* <code>None</code>, 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 <code>JoinSource</code> to <code>Input</code>. </p>
* <p>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
* <code>SageMakerOutput</code>. 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 <code>SageMakerInput</code> key and the results are stored in
* <code>SageMakerOutput</code>.</p> <p>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. </p>
*/
inline bool JoinSourceHasBeenSet() const { return m_joinSourceHasBeenSet; }
/**
* <p>Specifies the source of the data to join with the transformed data. The valid
* values are <code>None</code> and <code>Input</code>. The default value is
* <code>None</code>, 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 <code>JoinSource</code> to <code>Input</code>. </p>
* <p>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
* <code>SageMakerOutput</code>. 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 <code>SageMakerInput</code> key and the results are stored in
* <code>SageMakerOutput</code>.</p> <p>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. </p>
*/
inline void SetJoinSource(const JoinSource& value) { m_joinSourceHasBeenSet = true; m_joinSource = value; }
/**
* <p>Specifies the source of the data to join with the transformed data. The valid
* values are <code>None</code> and <code>Input</code>. The default value is
* <code>None</code>, 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 <code>JoinSource</code> to <code>Input</code>. </p>
* <p>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
* <code>SageMakerOutput</code>. 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 <code>SageMakerInput</code> key and the results are stored in
* <code>SageMakerOutput</code>.</p> <p>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. </p>
*/
inline void SetJoinSource(JoinSource&& value) { m_joinSourceHasBeenSet = true; m_joinSource = std::move(value); }
/**
* <p>Specifies the source of the data to join with the transformed data. The valid
* values are <code>None</code> and <code>Input</code>. The default value is
* <code>None</code>, 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 <code>JoinSource</code> to <code>Input</code>. </p>
* <p>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
* <code>SageMakerOutput</code>. 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 <code>SageMakerInput</code> key and the results are stored in
* <code>SageMakerOutput</code>.</p> <p>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. </p>
*/
inline DataProcessing& WithJoinSource(const JoinSource& value) { SetJoinSource(value); return *this;}
/**
* <p>Specifies the source of the data to join with the transformed data. The valid
* values are <code>None</code> and <code>Input</code>. The default value is
* <code>None</code>, 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 <code>JoinSource</code> to <code>Input</code>. </p>
* <p>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
* <code>SageMakerOutput</code>. 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 <code>SageMakerInput</code> key and the results are stored in
* <code>SageMakerOutput</code>.</p> <p>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. </p>
*/
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