Class: Aws::SageMaker::Types::DataProcessing
- Inherits:
-
Struct
- Object
- Struct
- Aws::SageMaker::Types::DataProcessing
- Defined in:
- gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb
Overview
When making an API call, you may pass DataProcessing data as a hash:
{
input_filter: "JsonPath",
output_filter: "JsonPath",
join_source: "Input", # accepts Input, None
}
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.
Constant Summary collapse
- SENSITIVE =
[]
Instance Attribute Summary collapse
-
#input_filter ⇒ String
A [JSONPath][1] expression used to select a portion of the input data to pass to the algorithm.
-
#join_source ⇒ String
Specifies the source of the data to join with the transformed data.
-
#output_filter ⇒ String
A [JSONPath][1] expression used to select a portion of the joined dataset to save in the output file for a batch transform job.
Instance Attribute Details
#input_filter ⇒ String
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"
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 8942 class DataProcessing < Struct.new( :input_filter, :output_filter, :join_source) SENSITIVE = [] include Aws::Structure end |
#join_source ⇒ String
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.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 8942 class DataProcessing < Struct.new( :input_filter, :output_filter, :join_source) SENSITIVE = [] include Aws::Structure end |
#output_filter ⇒ String
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']"
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 8942 class DataProcessing < Struct.new( :input_filter, :output_filter, :join_source) SENSITIVE = [] include Aws::Structure end |