372 lines
21 KiB
C++
372 lines
21 KiB
C++
/**
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* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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* SPDX-License-Identifier: Apache-2.0.
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*/
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#pragma once
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#include <aws/sagemaker/SageMaker_EXPORTS.h>
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#include <aws/core/utils/memory/stl/AWSString.h>
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#include <aws/sagemaker/model/JoinSource.h>
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#include <utility>
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namespace Aws
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{
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namespace Utils
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{
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namespace Json
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{
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class JsonValue;
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class JsonView;
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} // namespace Json
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} // namespace Utils
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namespace SageMaker
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{
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namespace Model
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{
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/**
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* <p>The data structure used to specify the data to be used for inference in a
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* batch transform job and to associate the data that is relevant to the prediction
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* results in the output. The input filter provided allows you to exclude input
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* data that is not needed for inference in a batch transform job. The output
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* filter provided allows you to include input data relevant to interpreting the
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* predictions in the output from the job. For more information, see <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html">Associate
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* Prediction Results with their Corresponding Input Records</a>.</p><p><h3>See
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* Also:</h3> <a
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* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DataProcessing">AWS
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* API Reference</a></p>
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*/
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class AWS_SAGEMAKER_API DataProcessing
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{
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public:
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DataProcessing();
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DataProcessing(Aws::Utils::Json::JsonView jsonValue);
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DataProcessing& operator=(Aws::Utils::Json::JsonView jsonValue);
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Aws::Utils::Json::JsonValue Jsonize() const;
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the input data to pass to the algorithm.
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* Use the <code>InputFilter</code> parameter to exclude fields, such as an ID
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* column, from the input. If you want Amazon SageMaker to pass the entire input
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* dataset to the algorithm, accept the default value <code>$</code>.</p>
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* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
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* </p>
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*/
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inline const Aws::String& GetInputFilter() const{ return m_inputFilter; }
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the input data to pass to the algorithm.
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* Use the <code>InputFilter</code> parameter to exclude fields, such as an ID
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* column, from the input. If you want Amazon SageMaker to pass the entire input
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* dataset to the algorithm, accept the default value <code>$</code>.</p>
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* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
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* </p>
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*/
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inline bool InputFilterHasBeenSet() const { return m_inputFilterHasBeenSet; }
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the input data to pass to the algorithm.
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* Use the <code>InputFilter</code> parameter to exclude fields, such as an ID
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* column, from the input. If you want Amazon SageMaker to pass the entire input
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* dataset to the algorithm, accept the default value <code>$</code>.</p>
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* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
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* </p>
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*/
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inline void SetInputFilter(const Aws::String& value) { m_inputFilterHasBeenSet = true; m_inputFilter = value; }
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the input data to pass to the algorithm.
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* Use the <code>InputFilter</code> parameter to exclude fields, such as an ID
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* column, from the input. If you want Amazon SageMaker to pass the entire input
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* dataset to the algorithm, accept the default value <code>$</code>.</p>
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* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
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* </p>
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*/
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inline void SetInputFilter(Aws::String&& value) { m_inputFilterHasBeenSet = true; m_inputFilter = std::move(value); }
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the input data to pass to the algorithm.
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* Use the <code>InputFilter</code> parameter to exclude fields, such as an ID
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* column, from the input. If you want Amazon SageMaker to pass the entire input
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* dataset to the algorithm, accept the default value <code>$</code>.</p>
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* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
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* </p>
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*/
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inline void SetInputFilter(const char* value) { m_inputFilterHasBeenSet = true; m_inputFilter.assign(value); }
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the input data to pass to the algorithm.
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* Use the <code>InputFilter</code> parameter to exclude fields, such as an ID
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* column, from the input. If you want Amazon SageMaker to pass the entire input
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* dataset to the algorithm, accept the default value <code>$</code>.</p>
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* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
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* </p>
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*/
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inline DataProcessing& WithInputFilter(const Aws::String& value) { SetInputFilter(value); return *this;}
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the input data to pass to the algorithm.
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* Use the <code>InputFilter</code> parameter to exclude fields, such as an ID
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* column, from the input. If you want Amazon SageMaker to pass the entire input
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* dataset to the algorithm, accept the default value <code>$</code>.</p>
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* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
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* </p>
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*/
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inline DataProcessing& WithInputFilter(Aws::String&& value) { SetInputFilter(std::move(value)); return *this;}
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the input data to pass to the algorithm.
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* Use the <code>InputFilter</code> parameter to exclude fields, such as an ID
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* column, from the input. If you want Amazon SageMaker to pass the entire input
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* dataset to the algorithm, accept the default value <code>$</code>.</p>
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* <p>Examples: <code>"$"</code>, <code>"$[1:]"</code>, <code>"$.features"</code>
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* </p>
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*/
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inline DataProcessing& WithInputFilter(const char* value) { SetInputFilter(value); return *this;}
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the joined dataset to save in the output
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* file for a batch transform job. If you want Amazon SageMaker to store the entire
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* input dataset in the output file, leave the default value, <code>$</code>. If
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* you specify indexes that aren't within the dimension size of the joined dataset,
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* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
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* <code>"$['id','SageMakerOutput']"</code> </p>
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*/
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inline const Aws::String& GetOutputFilter() const{ return m_outputFilter; }
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the joined dataset to save in the output
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* file for a batch transform job. If you want Amazon SageMaker to store the entire
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* input dataset in the output file, leave the default value, <code>$</code>. If
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* you specify indexes that aren't within the dimension size of the joined dataset,
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* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
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* <code>"$['id','SageMakerOutput']"</code> </p>
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*/
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inline bool OutputFilterHasBeenSet() const { return m_outputFilterHasBeenSet; }
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the joined dataset to save in the output
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* file for a batch transform job. If you want Amazon SageMaker to store the entire
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* input dataset in the output file, leave the default value, <code>$</code>. If
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* you specify indexes that aren't within the dimension size of the joined dataset,
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* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
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* <code>"$['id','SageMakerOutput']"</code> </p>
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*/
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inline void SetOutputFilter(const Aws::String& value) { m_outputFilterHasBeenSet = true; m_outputFilter = value; }
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the joined dataset to save in the output
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* file for a batch transform job. If you want Amazon SageMaker to store the entire
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* input dataset in the output file, leave the default value, <code>$</code>. If
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* you specify indexes that aren't within the dimension size of the joined dataset,
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* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
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* <code>"$['id','SageMakerOutput']"</code> </p>
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*/
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inline void SetOutputFilter(Aws::String&& value) { m_outputFilterHasBeenSet = true; m_outputFilter = std::move(value); }
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the joined dataset to save in the output
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* file for a batch transform job. If you want Amazon SageMaker to store the entire
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* input dataset in the output file, leave the default value, <code>$</code>. If
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* you specify indexes that aren't within the dimension size of the joined dataset,
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* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
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* <code>"$['id','SageMakerOutput']"</code> </p>
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*/
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inline void SetOutputFilter(const char* value) { m_outputFilterHasBeenSet = true; m_outputFilter.assign(value); }
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the joined dataset to save in the output
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* file for a batch transform job. If you want Amazon SageMaker to store the entire
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* input dataset in the output file, leave the default value, <code>$</code>. If
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* you specify indexes that aren't within the dimension size of the joined dataset,
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* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
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* <code>"$['id','SageMakerOutput']"</code> </p>
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*/
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inline DataProcessing& WithOutputFilter(const Aws::String& value) { SetOutputFilter(value); return *this;}
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the joined dataset to save in the output
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* file for a batch transform job. If you want Amazon SageMaker to store the entire
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* input dataset in the output file, leave the default value, <code>$</code>. If
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* you specify indexes that aren't within the dimension size of the joined dataset,
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* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
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* <code>"$['id','SageMakerOutput']"</code> </p>
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*/
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inline DataProcessing& WithOutputFilter(Aws::String&& value) { SetOutputFilter(std::move(value)); return *this;}
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/**
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* <p>A <a
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* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators">JSONPath</a>
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* expression used to select a portion of the joined dataset to save in the output
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* file for a batch transform job. If you want Amazon SageMaker to store the entire
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* input dataset in the output file, leave the default value, <code>$</code>. If
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* you specify indexes that aren't within the dimension size of the joined dataset,
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* you get an error.</p> <p>Examples: <code>"$"</code>, <code>"$[0,5:]"</code>,
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* <code>"$['id','SageMakerOutput']"</code> </p>
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*/
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inline DataProcessing& WithOutputFilter(const char* value) { SetOutputFilter(value); return *this;}
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/**
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* <p>Specifies the source of the data to join with the transformed data. The valid
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* values are <code>None</code> and <code>Input</code>. The default value is
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* <code>None</code>, which specifies not to join the input with the transformed
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* data. If you want the batch transform job to join the original input data with
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* the transformed data, set <code>JoinSource</code> to <code>Input</code>. </p>
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* <p>For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds
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* the transformed data to the input JSON object in an attribute called
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* <code>SageMakerOutput</code>. The joined result for JSON must be a key-value
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* pair object. If the input is not a key-value pair object, Amazon SageMaker
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* creates a new JSON file. In the new JSON file, and the input data is stored
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* under the <code>SageMakerInput</code> key and the results are stored in
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* <code>SageMakerOutput</code>.</p> <p>For CSV files, Amazon SageMaker combines
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* the transformed data with the input data at the end of the input data and stores
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* it in the output file. The joined data has the joined input data followed by the
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* transformed data and the output is a CSV file. </p>
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*/
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inline const JoinSource& GetJoinSource() const{ return m_joinSource; }
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/**
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* <p>Specifies the source of the data to join with the transformed data. The valid
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* values are <code>None</code> and <code>Input</code>. The default value is
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* <code>None</code>, which specifies not to join the input with the transformed
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* data. If you want the batch transform job to join the original input data with
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* the transformed data, set <code>JoinSource</code> to <code>Input</code>. </p>
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* <p>For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds
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* the transformed data to the input JSON object in an attribute called
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* <code>SageMakerOutput</code>. The joined result for JSON must be a key-value
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* pair object. If the input is not a key-value pair object, Amazon SageMaker
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* creates a new JSON file. In the new JSON file, and the input data is stored
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* under the <code>SageMakerInput</code> key and the results are stored in
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* <code>SageMakerOutput</code>.</p> <p>For CSV files, Amazon SageMaker combines
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* the transformed data with the input data at the end of the input data and stores
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* it in the output file. The joined data has the joined input data followed by the
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* transformed data and the output is a CSV file. </p>
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*/
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inline bool JoinSourceHasBeenSet() const { return m_joinSourceHasBeenSet; }
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/**
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* <p>Specifies the source of the data to join with the transformed data. The valid
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* values are <code>None</code> and <code>Input</code>. The default value is
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* <code>None</code>, which specifies not to join the input with the transformed
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* data. If you want the batch transform job to join the original input data with
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* the transformed data, set <code>JoinSource</code> to <code>Input</code>. </p>
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* <p>For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds
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* the transformed data to the input JSON object in an attribute called
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* <code>SageMakerOutput</code>. The joined result for JSON must be a key-value
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* pair object. If the input is not a key-value pair object, Amazon SageMaker
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* creates a new JSON file. In the new JSON file, and the input data is stored
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* under the <code>SageMakerInput</code> key and the results are stored in
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* <code>SageMakerOutput</code>.</p> <p>For CSV files, Amazon SageMaker combines
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* the transformed data with the input data at the end of the input data and stores
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* it in the output file. The joined data has the joined input data followed by the
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* transformed data and the output is a CSV file. </p>
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*/
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inline void SetJoinSource(const JoinSource& value) { m_joinSourceHasBeenSet = true; m_joinSource = value; }
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/**
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* <p>Specifies the source of the data to join with the transformed data. The valid
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* values are <code>None</code> and <code>Input</code>. The default value is
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* <code>None</code>, which specifies not to join the input with the transformed
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* data. If you want the batch transform job to join the original input data with
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* the transformed data, set <code>JoinSource</code> to <code>Input</code>. </p>
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* <p>For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds
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* the transformed data to the input JSON object in an attribute called
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* <code>SageMakerOutput</code>. The joined result for JSON must be a key-value
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* pair object. If the input is not a key-value pair object, Amazon SageMaker
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* creates a new JSON file. In the new JSON file, and the input data is stored
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* under the <code>SageMakerInput</code> key and the results are stored in
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* <code>SageMakerOutput</code>.</p> <p>For CSV files, Amazon SageMaker combines
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* the transformed data with the input data at the end of the input data and stores
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* it in the output file. The joined data has the joined input data followed by the
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* transformed data and the output is a CSV file. </p>
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*/
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inline void SetJoinSource(JoinSource&& value) { m_joinSourceHasBeenSet = true; m_joinSource = std::move(value); }
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/**
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* <p>Specifies the source of the data to join with the transformed data. The valid
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* values are <code>None</code> and <code>Input</code>. The default value is
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* <code>None</code>, which specifies not to join the input with the transformed
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* data. If you want the batch transform job to join the original input data with
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* the transformed data, set <code>JoinSource</code> to <code>Input</code>. </p>
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* <p>For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds
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* the transformed data to the input JSON object in an attribute called
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* <code>SageMakerOutput</code>. The joined result for JSON must be a key-value
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* pair object. If the input is not a key-value pair object, Amazon SageMaker
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* creates a new JSON file. In the new JSON file, and the input data is stored
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* under the <code>SageMakerInput</code> key and the results are stored in
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* <code>SageMakerOutput</code>.</p> <p>For CSV files, Amazon SageMaker combines
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* the transformed data with the input data at the end of the input data and stores
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* it in the output file. The joined data has the joined input data followed by the
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* transformed data and the output is a CSV file. </p>
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*/
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inline DataProcessing& WithJoinSource(const JoinSource& value) { SetJoinSource(value); return *this;}
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/**
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* <p>Specifies the source of the data to join with the transformed data. The valid
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* values are <code>None</code> and <code>Input</code>. The default value is
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* <code>None</code>, which specifies not to join the input with the transformed
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* data. If you want the batch transform job to join the original input data with
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* the transformed data, set <code>JoinSource</code> to <code>Input</code>. </p>
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* <p>For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds
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* the transformed data to the input JSON object in an attribute called
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* <code>SageMakerOutput</code>. The joined result for JSON must be a key-value
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* pair object. If the input is not a key-value pair object, Amazon SageMaker
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* creates a new JSON file. In the new JSON file, and the input data is stored
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* under the <code>SageMakerInput</code> key and the results are stored in
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* <code>SageMakerOutput</code>.</p> <p>For CSV files, Amazon SageMaker combines
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* the transformed data with the input data at the end of the input data and stores
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* it in the output file. The joined data has the joined input data followed by the
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* transformed data and the output is a CSV file. </p>
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*/
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inline DataProcessing& WithJoinSource(JoinSource&& value) { SetJoinSource(std::move(value)); return *this;}
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private:
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Aws::String m_inputFilter;
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bool m_inputFilterHasBeenSet;
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Aws::String m_outputFilter;
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bool m_outputFilterHasBeenSet;
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JoinSource m_joinSource;
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bool m_joinSourceHasBeenSet;
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};
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} // namespace Model
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} // namespace SageMaker
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} // namespace Aws
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