AWS SDK for C++  1.9.46
AWS SDK for C++
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Aws::SageMaker::Model::DataProcessing Class Reference

#include <DataProcessing.h>

Public Member Functions

 DataProcessing ()
 
 DataProcessing (Aws::Utils::Json::JsonView jsonValue)
 
DataProcessingoperator= (Aws::Utils::Json::JsonView jsonValue)
 
Aws::Utils::Json::JsonValue Jsonize () const
 
const Aws::StringGetInputFilter () const
 
bool InputFilterHasBeenSet () const
 
void SetInputFilter (const Aws::String &value)
 
void SetInputFilter (Aws::String &&value)
 
void SetInputFilter (const char *value)
 
DataProcessingWithInputFilter (const Aws::String &value)
 
DataProcessingWithInputFilter (Aws::String &&value)
 
DataProcessingWithInputFilter (const char *value)
 
const Aws::StringGetOutputFilter () const
 
bool OutputFilterHasBeenSet () const
 
void SetOutputFilter (const Aws::String &value)
 
void SetOutputFilter (Aws::String &&value)
 
void SetOutputFilter (const char *value)
 
DataProcessingWithOutputFilter (const Aws::String &value)
 
DataProcessingWithOutputFilter (Aws::String &&value)
 
DataProcessingWithOutputFilter (const char *value)
 
const JoinSourceGetJoinSource () const
 
bool JoinSourceHasBeenSet () const
 
void SetJoinSource (const JoinSource &value)
 
void SetJoinSource (JoinSource &&value)
 
DataProcessingWithJoinSource (const JoinSource &value)
 
DataProcessingWithJoinSource (JoinSource &&value)
 

Detailed Description

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

Definition at line 40 of file DataProcessing.h.

Constructor & Destructor Documentation

◆ DataProcessing() [1/2]

Aws::SageMaker::Model::DataProcessing::DataProcessing ( )

◆ DataProcessing() [2/2]

Aws::SageMaker::Model::DataProcessing::DataProcessing ( Aws::Utils::Json::JsonView  jsonValue)

Member Function Documentation

◆ GetInputFilter()

const Aws::String& Aws::SageMaker::Model::DataProcessing::GetInputFilter ( ) const
inline

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"

Definition at line 59 of file DataProcessing.h.

◆ GetJoinSource()

const JoinSource& Aws::SageMaker::Model::DataProcessing::GetJoinSource ( ) const
inline

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. You can specify OutputFilter as an additional filter to select a portion of the joined dataset and store it in the output file.

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 data, Amazon SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.

For information on how joining in applied, see Workflow for Associating Inferences with Input Records.

Definition at line 264 of file DataProcessing.h.

◆ GetOutputFilter()

const Aws::String& Aws::SageMaker::Model::DataProcessing::GetOutputFilter ( ) const
inline

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']"

Definition at line 156 of file DataProcessing.h.

◆ InputFilterHasBeenSet()

bool Aws::SageMaker::Model::DataProcessing::InputFilterHasBeenSet ( ) const
inline

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"

Definition at line 71 of file DataProcessing.h.

◆ JoinSourceHasBeenSet()

bool Aws::SageMaker::Model::DataProcessing::JoinSourceHasBeenSet ( ) const
inline

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. You can specify OutputFilter as an additional filter to select a portion of the joined dataset and store it in the output file.

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 data, Amazon SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.

For information on how joining in applied, see Workflow for Associating Inferences with Input Records.

Definition at line 287 of file DataProcessing.h.

◆ Jsonize()

Aws::Utils::Json::JsonValue Aws::SageMaker::Model::DataProcessing::Jsonize ( ) const

◆ operator=()

DataProcessing& Aws::SageMaker::Model::DataProcessing::operator= ( Aws::Utils::Json::JsonView  jsonValue)

◆ OutputFilterHasBeenSet()

bool Aws::SageMaker::Model::DataProcessing::OutputFilterHasBeenSet ( ) const
inline

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']"

Definition at line 168 of file DataProcessing.h.

◆ SetInputFilter() [1/3]

void Aws::SageMaker::Model::DataProcessing::SetInputFilter ( Aws::String &&  value)
inline

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"

Definition at line 95 of file DataProcessing.h.

◆ SetInputFilter() [2/3]

void Aws::SageMaker::Model::DataProcessing::SetInputFilter ( const Aws::String value)
inline

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"

Definition at line 83 of file DataProcessing.h.

◆ SetInputFilter() [3/3]

void Aws::SageMaker::Model::DataProcessing::SetInputFilter ( const char *  value)
inline

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"

Definition at line 107 of file DataProcessing.h.

◆ SetJoinSource() [1/2]

void Aws::SageMaker::Model::DataProcessing::SetJoinSource ( const JoinSource value)
inline

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. You can specify OutputFilter as an additional filter to select a portion of the joined dataset and store it in the output file.

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 data, Amazon SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.

For information on how joining in applied, see Workflow for Associating Inferences with Input Records.

Definition at line 310 of file DataProcessing.h.

◆ SetJoinSource() [2/2]

void Aws::SageMaker::Model::DataProcessing::SetJoinSource ( JoinSource &&  value)
inline

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. You can specify OutputFilter as an additional filter to select a portion of the joined dataset and store it in the output file.

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 data, Amazon SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.

For information on how joining in applied, see Workflow for Associating Inferences with Input Records.

Definition at line 333 of file DataProcessing.h.

◆ SetOutputFilter() [1/3]

void Aws::SageMaker::Model::DataProcessing::SetOutputFilter ( Aws::String &&  value)
inline

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']"

Definition at line 192 of file DataProcessing.h.

◆ SetOutputFilter() [2/3]

void Aws::SageMaker::Model::DataProcessing::SetOutputFilter ( const Aws::String value)
inline

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']"

Definition at line 180 of file DataProcessing.h.

◆ SetOutputFilter() [3/3]

void Aws::SageMaker::Model::DataProcessing::SetOutputFilter ( const char *  value)
inline

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']"

Definition at line 204 of file DataProcessing.h.

◆ WithInputFilter() [1/3]

DataProcessing& Aws::SageMaker::Model::DataProcessing::WithInputFilter ( Aws::String &&  value)
inline

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"

Definition at line 131 of file DataProcessing.h.

◆ WithInputFilter() [2/3]

DataProcessing& Aws::SageMaker::Model::DataProcessing::WithInputFilter ( const Aws::String value)
inline

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"

Definition at line 119 of file DataProcessing.h.

◆ WithInputFilter() [3/3]

DataProcessing& Aws::SageMaker::Model::DataProcessing::WithInputFilter ( const char *  value)
inline

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"

Definition at line 143 of file DataProcessing.h.

◆ WithJoinSource() [1/2]

DataProcessing& Aws::SageMaker::Model::DataProcessing::WithJoinSource ( const JoinSource value)
inline

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. You can specify OutputFilter as an additional filter to select a portion of the joined dataset and store it in the output file.

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 data, Amazon SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.

For information on how joining in applied, see Workflow for Associating Inferences with Input Records.

Definition at line 356 of file DataProcessing.h.

◆ WithJoinSource() [2/2]

DataProcessing& Aws::SageMaker::Model::DataProcessing::WithJoinSource ( JoinSource &&  value)
inline

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. You can specify OutputFilter as an additional filter to select a portion of the joined dataset and store it in the output file.

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 data, Amazon SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.

For information on how joining in applied, see Workflow for Associating Inferences with Input Records.

Definition at line 379 of file DataProcessing.h.

◆ WithOutputFilter() [1/3]

DataProcessing& Aws::SageMaker::Model::DataProcessing::WithOutputFilter ( Aws::String &&  value)
inline

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']"

Definition at line 228 of file DataProcessing.h.

◆ WithOutputFilter() [2/3]

DataProcessing& Aws::SageMaker::Model::DataProcessing::WithOutputFilter ( const Aws::String value)
inline

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']"

Definition at line 216 of file DataProcessing.h.

◆ WithOutputFilter() [3/3]

DataProcessing& Aws::SageMaker::Model::DataProcessing::WithOutputFilter ( const char *  value)
inline

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']"

Definition at line 240 of file DataProcessing.h.


The documentation for this class was generated from the following file: