{-# LANGUAGE DeriveDataTypeable #-}
{-# LANGUAGE DeriveGeneric      #-}
{-# LANGUAGE OverloadedStrings  #-}
{-# LANGUAGE RecordWildCards    #-}
{-# LANGUAGE TypeFamilies       #-}

{-# OPTIONS_GHC -fno-warn-unused-imports #-}
{-# OPTIONS_GHC -fno-warn-unused-binds   #-}
{-# OPTIONS_GHC -fno-warn-unused-matches #-}

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

-- |
-- Module      : Network.AWS.MachineLearning.CreateDataSourceFromS3
-- Copyright   : (c) 2013-2016 Brendan Hay
-- License     : Mozilla Public License, v. 2.0.
-- Maintainer  : Brendan Hay <brendan.g.hay@gmail.com>
-- Stability   : auto-generated
-- Portability : non-portable (GHC extensions)
--
-- Creates a 'DataSource' object. A 'DataSource' references data that can be used to perform < CreateMLModel>, < CreateEvaluation>, or < CreateBatchPrediction> operations.
--
-- 'CreateDataSourceFromS3' is an asynchronous operation. In response to 'CreateDataSourceFromS3', Amazon Machine Learning (Amazon ML) immediately returns and sets the 'DataSource' status to 'PENDING'. After the 'DataSource' is created and ready for use, Amazon ML sets the 'Status' parameter to 'COMPLETED'. 'DataSource' in 'COMPLETED' or 'PENDING' status can only be used to perform < CreateMLModel>, < CreateEvaluation> or < CreateBatchPrediction> operations.
--
-- If Amazon ML cannot accept the input source, it sets the 'Status' parameter to 'FAILED' and includes an error message in the 'Message' attribute of the < GetDataSource> operation response.
--
-- The observation data used in a 'DataSource' should be ready to use; that is, it should have a consistent structure, and missing data values should be kept to a minimum. The observation data must reside in one or more CSV files in an Amazon Simple Storage Service (Amazon S3) bucket, along with a schema that describes the data items by name and type. The same schema must be used for all of the data files referenced by the 'DataSource'.
--
-- After the 'DataSource' has been created, it\'s ready to use in evaluations and batch predictions. If you plan to use the 'DataSource' to train an 'MLModel', the 'DataSource' requires another item: a recipe. A recipe describes the observation variables that participate in training an 'MLModel'. A recipe describes how each input variable will be used in training. Will the variable be included or excluded from training? Will the variable be manipulated, for example, combined with another variable, or split apart into word combinations? The recipe provides answers to these questions. For more information, see the <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.
module Network.AWS.MachineLearning.CreateDataSourceFromS3
    (
    -- * Creating a Request
      createDataSourceFromS3
    , CreateDataSourceFromS3
    -- * Request Lenses
    , cdsfsDataSourceName
    , cdsfsComputeStatistics
    , cdsfsDataSourceId
    , cdsfsDataSpec

    -- * Destructuring the Response
    , createDataSourceFromS3Response
    , CreateDataSourceFromS3Response
    -- * Response Lenses
    , cdsfsrsDataSourceId
    , cdsfsrsResponseStatus
    ) where

import           Network.AWS.Lens
import           Network.AWS.MachineLearning.Types
import           Network.AWS.MachineLearning.Types.Product
import           Network.AWS.Prelude
import           Network.AWS.Request
import           Network.AWS.Response

-- | /See:/ 'createDataSourceFromS3' smart constructor.
data CreateDataSourceFromS3 = CreateDataSourceFromS3'
    { _cdsfsDataSourceName    :: !(Maybe Text)
    , _cdsfsComputeStatistics :: !(Maybe Bool)
    , _cdsfsDataSourceId      :: !Text
    , _cdsfsDataSpec          :: !S3DataSpec
    } deriving (Eq,Read,Show,Data,Typeable,Generic)

-- | Creates a value of 'CreateDataSourceFromS3' with the minimum fields required to make a request.
--
-- Use one of the following lenses to modify other fields as desired:
--
-- * 'cdsfsDataSourceName'
--
-- * 'cdsfsComputeStatistics'
--
-- * 'cdsfsDataSourceId'
--
-- * 'cdsfsDataSpec'
createDataSourceFromS3
    :: Text -- ^ 'cdsfsDataSourceId'
    -> S3DataSpec -- ^ 'cdsfsDataSpec'
    -> CreateDataSourceFromS3
createDataSourceFromS3 pDataSourceId_ pDataSpec_ =
    CreateDataSourceFromS3'
    { _cdsfsDataSourceName = Nothing
    , _cdsfsComputeStatistics = Nothing
    , _cdsfsDataSourceId = pDataSourceId_
    , _cdsfsDataSpec = pDataSpec_
    }

-- | A user-supplied name or description of the 'DataSource'.
cdsfsDataSourceName :: Lens' CreateDataSourceFromS3 (Maybe Text)
cdsfsDataSourceName = lens _cdsfsDataSourceName (\ s a -> s{_cdsfsDataSourceName = a});

-- | The compute statistics for a 'DataSource'. The statistics are generated from the observation data referenced by a 'DataSource'. Amazon ML uses the statistics internally during an 'MLModel' training. This parameter must be set to 'true' if the ''DataSource'' needs to be used for 'MLModel' training
cdsfsComputeStatistics :: Lens' CreateDataSourceFromS3 (Maybe Bool)
cdsfsComputeStatistics = lens _cdsfsComputeStatistics (\ s a -> s{_cdsfsComputeStatistics = a});

-- | A user-supplied identifier that uniquely identifies the 'DataSource'.
cdsfsDataSourceId :: Lens' CreateDataSourceFromS3 Text
cdsfsDataSourceId = lens _cdsfsDataSourceId (\ s a -> s{_cdsfsDataSourceId = a});

-- | The data specification of a 'DataSource':
--
-- -   DataLocationS3 - Amazon Simple Storage Service (Amazon S3) location of the observation data.
--
-- -   DataSchemaLocationS3 - Amazon S3 location of the 'DataSchema'.
--
-- -   DataSchema - A JSON string representing the schema. This is not required if 'DataSchemaUri' is specified.
--
-- -   DataRearrangement - A JSON string representing the splitting requirement of a 'Datasource'.
--
--     Sample - ' \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"'
--
cdsfsDataSpec :: Lens' CreateDataSourceFromS3 S3DataSpec
cdsfsDataSpec = lens _cdsfsDataSpec (\ s a -> s{_cdsfsDataSpec = a});

instance AWSRequest CreateDataSourceFromS3 where
        type Rs CreateDataSourceFromS3 =
             CreateDataSourceFromS3Response
        request = postJSON machineLearning
        response
          = receiveJSON
              (\ s h x ->
                 CreateDataSourceFromS3Response' <$>
                   (x .?> "DataSourceId") <*> (pure (fromEnum s)))

instance Hashable CreateDataSourceFromS3

instance NFData CreateDataSourceFromS3

instance ToHeaders CreateDataSourceFromS3 where
        toHeaders
          = const
              (mconcat
                 ["X-Amz-Target" =#
                    ("AmazonML_20141212.CreateDataSourceFromS3" ::
                       ByteString),
                  "Content-Type" =#
                    ("application/x-amz-json-1.1" :: ByteString)])

instance ToJSON CreateDataSourceFromS3 where
        toJSON CreateDataSourceFromS3'{..}
          = object
              (catMaybes
                 [("DataSourceName" .=) <$> _cdsfsDataSourceName,
                  ("ComputeStatistics" .=) <$> _cdsfsComputeStatistics,
                  Just ("DataSourceId" .= _cdsfsDataSourceId),
                  Just ("DataSpec" .= _cdsfsDataSpec)])

instance ToPath CreateDataSourceFromS3 where
        toPath = const "/"

instance ToQuery CreateDataSourceFromS3 where
        toQuery = const mempty

-- | Represents the output of a < CreateDataSourceFromS3> operation, and is an acknowledgement that Amazon ML received the request.
--
-- The < CreateDataSourceFromS3> operation is asynchronous. You can poll for updates by using the < GetBatchPrediction> operation and checking the 'Status' parameter.
--
-- /See:/ 'createDataSourceFromS3Response' smart constructor.
data CreateDataSourceFromS3Response = CreateDataSourceFromS3Response'
    { _cdsfsrsDataSourceId   :: !(Maybe Text)
    , _cdsfsrsResponseStatus :: !Int
    } deriving (Eq,Read,Show,Data,Typeable,Generic)

-- | Creates a value of 'CreateDataSourceFromS3Response' with the minimum fields required to make a request.
--
-- Use one of the following lenses to modify other fields as desired:
--
-- * 'cdsfsrsDataSourceId'
--
-- * 'cdsfsrsResponseStatus'
createDataSourceFromS3Response
    :: Int -- ^ 'cdsfsrsResponseStatus'
    -> CreateDataSourceFromS3Response
createDataSourceFromS3Response pResponseStatus_ =
    CreateDataSourceFromS3Response'
    { _cdsfsrsDataSourceId = Nothing
    , _cdsfsrsResponseStatus = pResponseStatus_
    }

-- | A user-supplied ID that uniquely identifies the datasource. This value should be identical to the value of the 'DataSourceID' in the request.
cdsfsrsDataSourceId :: Lens' CreateDataSourceFromS3Response (Maybe Text)
cdsfsrsDataSourceId = lens _cdsfsrsDataSourceId (\ s a -> s{_cdsfsrsDataSourceId = a});

-- | The response status code.
cdsfsrsResponseStatus :: Lens' CreateDataSourceFromS3Response Int
cdsfsrsResponseStatus = lens _cdsfsrsResponseStatus (\ s a -> s{_cdsfsrsResponseStatus = a});

instance NFData CreateDataSourceFromS3Response