NAME

Paws::SageMaker::DataProcessing

USAGE

This class represents one of two things:

Arguments in a call to a service

Use the attributes of this class as arguments to methods. You shouldn't make instances of this class. Each attribute should be used as a named argument in the calls that expect this type of object.

As an example, if Att1 is expected to be a Paws::SageMaker::DataProcessing object:

  $service_obj->Method(Att1 => { InputFilter => $value, ..., OutputFilter => $value  });

Results returned from an API call

Use accessors for each attribute. If Att1 is expected to be an Paws::SageMaker::DataProcessing object:

  $result = $service_obj->Method(...);
  $result->Att1->InputFilter

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 (https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html).

ATTRIBUTES

InputFilter => Str

A JSONPath (https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators) 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"

JoinSource => Str

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 (https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#batch-transform-data-processing-workflow).

OutputFilter => Str

A JSONPath (https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators) 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']"

BUGS and CONTRIBUTIONS

The source code is located here: <https://github.com/pplu/aws-sdk-perl>

Please report bugs to: <https://github.com/pplu/aws-sdk-perl/issues>