@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.
| Constructor and Description | 
|---|
| DataProcessing() | 
| 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. | 
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"
 
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"
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"
 
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"
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"
 
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"
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']"
 
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']"
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']"
 
$. If you specify indexes that aren't within the dimension size of
         the joined dataset, you get an error.
         
         Examples: "$", "$[0,5:]", "$['id','SageMakerOutput']"
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']"
 
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']"
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.
 
 For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds the transformed data to the input JSON
 object in an attribute called SageMakerOutput. The joined result for JSON must be a key-value pair
 object. If the input is not a key-value pair object, Amazon SageMaker creates a new JSON file. In the new JSON
 file, and the input data is stored under the SageMakerInput key and the results are stored in
 SageMakerOutput.
 
For CSV files, Amazon SageMaker combines the transformed data with the input data at the end of the input data and stores it in the output file. The joined data has the joined input data followed by the transformed data and the output is a CSV file.
joinSource - Specifies the source of the data to join with the transformed data. The valid values are None
        and Input. The default value is None, which specifies not to join the input with
        the transformed data. If you want the batch transform job to join the original input data with the
        transformed data, set JoinSource to Input. 
        
        For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds the transformed data to the
        input JSON object in an attribute called SageMakerOutput. The joined result for JSON must be
        a key-value pair object. If the input is not a key-value pair object, Amazon SageMaker creates a new JSON
        file. In the new JSON file, and the input data is stored under the SageMakerInput key and the
        results are stored in SageMakerOutput.
        
For CSV files, Amazon SageMaker combines the transformed data with the input data at the end of the input data and stores it in the output file. The joined data has the joined input data followed by the transformed data and the output is a CSV file.
JoinSourcepublic 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.
 
 For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds the transformed data to the input JSON
 object in an attribute called SageMakerOutput. The joined result for JSON must be a key-value pair
 object. If the input is not a key-value pair object, Amazon SageMaker creates a new JSON file. In the new JSON
 file, and the input data is stored under the SageMakerInput key and the results are stored in
 SageMakerOutput.
 
For CSV files, Amazon SageMaker combines the transformed data with the input data at the end of the input data and stores it in the output file. The joined data has the joined input data followed by the transformed data and the output is a CSV file.
None and Input. The default value is None, which specifies not to
         join the input with the transformed data. If you want the batch transform job to join the original input
         data with the transformed data, set JoinSource to Input. 
         
         For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds the transformed data to the
         input JSON object in an attribute called SageMakerOutput. The joined result for JSON must be
         a key-value pair object. If the input is not a key-value pair object, Amazon SageMaker creates a new JSON
         file. In the new JSON file, and the input data is stored under the SageMakerInput key and
         the results are stored in SageMakerOutput.
         
For CSV files, Amazon SageMaker combines the transformed data with the input data at the end of the input data and stores it in the output file. The joined data has the joined input data followed by the transformed data and the output is a CSV file.
JoinSourcepublic 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.
 
 For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds the transformed data to the input JSON
 object in an attribute called SageMakerOutput. The joined result for JSON must be a key-value pair
 object. If the input is not a key-value pair object, Amazon SageMaker creates a new JSON file. In the new JSON
 file, and the input data is stored under the SageMakerInput key and the results are stored in
 SageMakerOutput.
 
For CSV files, Amazon SageMaker combines the transformed data with the input data at the end of the input data and stores it in the output file. The joined data has the joined input data followed by the transformed data and the output is a CSV file.
joinSource - Specifies the source of the data to join with the transformed data. The valid values are None
        and Input. The default value is None, which specifies not to join the input with
        the transformed data. If you want the batch transform job to join the original input data with the
        transformed data, set JoinSource to Input. 
        
        For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds the transformed data to the
        input JSON object in an attribute called SageMakerOutput. The joined result for JSON must be
        a key-value pair object. If the input is not a key-value pair object, Amazon SageMaker creates a new JSON
        file. In the new JSON file, and the input data is stored under the SageMakerInput key and the
        results are stored in SageMakerOutput.
        
For CSV files, Amazon SageMaker combines the transformed data with the input data at the end of the input data and stores it in the output file. The joined data has the joined input data followed by the transformed data and the output is a CSV file.
JoinSourcepublic 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.
 
 For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds the transformed data to the input JSON
 object in an attribute called SageMakerOutput. The joined result for JSON must be a key-value pair
 object. If the input is not a key-value pair object, Amazon SageMaker creates a new JSON file. In the new JSON
 file, and the input data is stored under the SageMakerInput key and the results are stored in
 SageMakerOutput.
 
For CSV files, Amazon SageMaker combines the transformed data with the input data at the end of the input data and stores it in the output file. The joined data has the joined input data followed by the transformed data and the output is a CSV file.
joinSource - Specifies the source of the data to join with the transformed data. The valid values are None
        and Input. The default value is None, which specifies not to join the input with
        the transformed data. If you want the batch transform job to join the original input data with the
        transformed data, set JoinSource to Input. 
        
        For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds the transformed data to the
        input JSON object in an attribute called SageMakerOutput. The joined result for JSON must be
        a key-value pair object. If the input is not a key-value pair object, Amazon SageMaker creates a new JSON
        file. In the new JSON file, and the input data is stored under the SageMakerInput key and the
        results are stored in SageMakerOutput.
        
For CSV files, Amazon SageMaker combines the transformed data with the input data at the end of the input data and stores it in the output file. The joined data has the joined input data followed by the transformed data and the output is a CSV file.
JoinSourcepublic String toString()
toString in class ObjectObject.toString()public DataProcessing clone()
public void marshall(ProtocolMarshaller protocolMarshaller)
StructuredPojoProtocolMarshaller.marshall in interface StructuredPojoprotocolMarshaller - Implementation of ProtocolMarshaller used to marshall this object's data.