DataProcessing.hs

{-# LANGUAGE DeriveGeneric #-}
{-# LANGUAGE DuplicateRecordFields #-}
{-# LANGUAGE NamedFieldPuns #-}
{-# LANGUAGE OverloadedStrings #-}
{-# LANGUAGE RecordWildCards #-}
{-# LANGUAGE StrictData #-}
{-# LANGUAGE NoImplicitPrelude #-}
{-# OPTIONS_GHC -fno-warn-unused-imports #-}
{-# OPTIONS_GHC -fno-warn-unused-matches #-}

-- Derived from AWS service descriptions, licensed under Apache 2.0.

-- |
-- Module : Amazonka.SageMaker.Types.DataProcessing
-- Copyright : (c) 2013-2023 Brendan Hay
-- License : Mozilla Public License, v. 2.0.
-- Maintainer : Brendan Hay
-- Stability : auto-generated
-- Portability : non-portable (GHC extensions)
module Amazonka.SageMaker.Types.DataProcessing where

import qualified Amazonka.Core as Core
import qualified Amazonka.Core.Lens.Internal as Lens
import qualified Amazonka.Data as Data
import qualified Amazonka.Prelude as Prelude
import Amazonka.SageMaker.Types.JoinSource

-- | 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
-- <https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html Associate Prediction Results with their Corresponding Input Records>.
--
-- /See:/ 'newDataProcessing' smart constructor.
data DataProcessing = DataProcessing'
{ -- | A
-- <https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators 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 SageMaker to pass the entire
-- input dataset to the algorithm, accept the default value @$@.
--
-- Examples: @\"$\"@, @\"$[1:]\"@, @\"$.features\"@
inputFilter :: Prelude.Maybe Prelude.Text,
-- | 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
-- <https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#batch-transform-data-processing-workflow Workflow for Associating Inferences with Input Records>.
joinSource :: Prelude.Maybe JoinSource,
-- | A
-- <https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators 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 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 :: Prelude.Maybe Prelude.Text
}
deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)

-- |
-- Create a value of 'DataProcessing' with all optional fields omitted.
--
-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.
--
-- The following record fields are available, with the corresponding lenses provided
-- for backwards compatibility:
--
-- 'inputFilter', 'dataProcessing_inputFilter' - A
-- <https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators 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 SageMaker to pass the entire
-- input dataset to the algorithm, accept the default value @$@.
--
-- Examples: @\"$\"@, @\"$[1:]\"@, @\"$.features\"@
--
-- 'joinSource', 'dataProcessing_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
-- <https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#batch-transform-data-processing-workflow Workflow for Associating Inferences with Input Records>.
--
-- 'outputFilter', 'dataProcessing_outputFilter' - A
-- <https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators 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 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\']\"@
newDataProcessing ::
DataProcessing
newDataProcessing =
DataProcessing'
{ inputFilter = Prelude.Nothing,
joinSource = Prelude.Nothing,
outputFilter = Prelude.Nothing
}

-- | A
-- <https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators 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 SageMaker to pass the entire
-- input dataset to the algorithm, accept the default value @$@.
--
-- Examples: @\"$\"@, @\"$[1:]\"@, @\"$.features\"@
dataProcessing_inputFilter :: Lens.Lens' DataProcessing (Prelude.Maybe Prelude.Text)
dataProcessing_inputFilter = Lens.lens (\DataProcessing' {inputFilter} -> inputFilter) (\s@DataProcessing' {} a -> s {inputFilter = a} :: DataProcessing)

-- | 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
-- <https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#batch-transform-data-processing-workflow Workflow for Associating Inferences with Input Records>.
dataProcessing_joinSource :: Lens.Lens' DataProcessing (Prelude.Maybe JoinSource)
dataProcessing_joinSource = Lens.lens (\DataProcessing' {joinSource} -> joinSource) (\s@DataProcessing' {} a -> s {joinSource = a} :: DataProcessing)

-- | A
-- <https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators 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 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\']\"@
dataProcessing_outputFilter :: Lens.Lens' DataProcessing (Prelude.Maybe Prelude.Text)
dataProcessing_outputFilter = Lens.lens (\DataProcessing' {outputFilter} -> outputFilter) (\s@DataProcessing' {} a -> s {outputFilter = a} :: DataProcessing)

instance Data.FromJSON DataProcessing where
parseJSON =
Data.withObject
"DataProcessing"
( \x ->
DataProcessing'
Prelude.<$> (x Data..:? "InputFilter")
Prelude.<*> (x Data..:? "JoinSource")
Prelude.<*> (x Data..:? "OutputFilter")
)

instance Prelude.Hashable DataProcessing where
hashWithSalt _salt DataProcessing' {..} =
_salt
`Prelude.hashWithSalt` inputFilter
`Prelude.hashWithSalt` joinSource
`Prelude.hashWithSalt` outputFilter

instance Prelude.NFData DataProcessing where
rnf DataProcessing' {..} =
Prelude.rnf inputFilter
`Prelude.seq` Prelude.rnf joinSource
`Prelude.seq` Prelude.rnf outputFilter

instance Data.ToJSON DataProcessing where
toJSON DataProcessing' {..} =
Data.object
( Prelude.catMaybes
[ ("InputFilter" Data..=) Prelude.<$> inputFilter,
("JoinSource" Data..=) Prelude.<$> joinSource,
("OutputFilter" Data..=) Prelude.<$> outputFilter
]
)