DataProcessing (AWS SDK for Java

java.lang.Object
- com.amazonaws.services.sagemaker.model.DataProcessing

All Implemented Interfaces:

StructuredPojo, Serializable, Cloneable
```
@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class DataProcessing
extends Object
implements Serializable, Cloneable, StructuredPojo
```
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 Documentation, Serialized Form

Constructor Summary

Constructors
Constructor and Description

DataProcessing()

Constructors
Constructor and Description
`DataProcessing()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`DataProcessing`	`clone()`
`boolean`	`equals(Object obj)`
`String`	`getInputFilter()` A JSONPath expression used to select a portion of the input data to pass to the algorithm.
`String`	`getJoinSource()` Specifies the source of the data to join with the transformed data.
`String`	`getOutputFilter()` A JSONPath expression used to select a portion of the joined dataset to save in the output file for a batch transform job.
`int`	`hashCode()`
`void`	`marshall(ProtocolMarshaller protocolMarshaller)` Marshalls this structured data using the given `ProtocolMarshaller`.
`void`	`setInputFilter(String inputFilter)` A JSONPath expression used to select a portion of the input data to pass to the algorithm.
`void`	`setJoinSource(String joinSource)` Specifies the source of the data to join with the transformed data.
`void`	`setOutputFilter(String outputFilter)` A JSONPath expression used to select a portion of the joined dataset to save in the output file for a batch transform job.
`String`	`toString()` Returns a string representation of this object.
`DataProcessing`	`withInputFilter(String inputFilter)` A JSONPath expression used to select a portion of the input data to pass to the algorithm.
`DataProcessing`	`withJoinSource(JoinSource joinSource)` Specifies the source of the data to join with the transformed data.
`DataProcessing`	`withJoinSource(String joinSource)` Specifies the source of the data to join with the transformed data.
`DataProcessing`	`withOutputFilter(String outputFilter)` A JSONPath expression used to select a portion of the joined dataset to save in the output file for a batch transform job.

Methods inherited from class java.lang.Object
getClass, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - DataProcessing
```
public DataProcessing()
```
- Method Detail
  - setInputFilter
```
public void setInputFilter(String 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"
    
    Parameters:
    
    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"
  - getInputFilter
```
public String getInputFilter()
```
    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"
    
    Returns:
    
    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"
  - withInputFilter
```
public DataProcessing withInputFilter(String 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"
    
    Parameters:
    
    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"
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setOutputFilter
```
public void setOutputFilter(String 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']"
    
    Parameters:
    
    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']"
  - getOutputFilter
```
public String getOutputFilter()
```
    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']"
    
    Returns:
    
    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']"
  - withOutputFilter
```
public DataProcessing withOutputFilter(String 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']"
    
    Parameters:
    
    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']"
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setJoinSource
```
public void setJoinSource(String 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. 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, 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, 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, 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.
    
    Parameters:
    
    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. 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, 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, 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, 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.
    
    See Also:
    
    JoinSource
  - getJoinSource
```
public String getJoinSource()
```
    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, 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, 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, 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.
    
    Returns:
    
    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, 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, 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, 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.
    
    See Also:
    
    JoinSource
  - withJoinSource
```
public DataProcessing withJoinSource(String 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. 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, 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, 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, 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.
    
    Parameters:
    
    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. 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, 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, 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, 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.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    JoinSource
  - withJoinSource
```
public DataProcessing withJoinSource(JoinSource 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. 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, 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, 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, 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.
    
    Parameters:
    
    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. 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, 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, 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, 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.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    JoinSource
  - toString
```
public String toString()
```
    Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    
    A string representation of this object.
    
    See Also:
    
    Object.toString()
  - equals
```
public boolean equals(Object obj)
```
    Overrides:
    
    equals in class Object
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class Object
  - clone
```
public DataProcessing clone()
```
    Overrides:
    
    clone in class Object
  - marshall
```
public void marshall(ProtocolMarshaller protocolMarshaller)
```
    Description copied from interface: StructuredPojo
    
    Marshalls this structured data using the given ProtocolMarshaller.
    
    Specified by:
    
    marshall in interface StructuredPojo
    
    Parameters:
    
    protocolMarshaller - Implementation of ProtocolMarshaller used to marshall this object's data.

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Class DataProcessing

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

DataProcessing

Method Detail

setInputFilter

getInputFilter

withInputFilter

setOutputFilter

getOutputFilter

withOutputFilter

setJoinSource

getJoinSource

withJoinSource

withJoinSource

toString

equals

hashCode

clone

marshall