amazonka-ml-1.0.0: gen/Network/AWS/MachineLearning/CreateDataSourceFromRedshift.hs
{-# 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.CreateDataSourceFromRedshift
-- Copyright : (c) 2013-2015 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' from
-- <http://aws.amazon.com/redshift/ Amazon Redshift>. A 'DataSource'
-- references data that can be used to perform either CreateMLModel,
-- CreateEvaluation or CreateBatchPrediction operations.
--
-- 'CreateDataSourceFromRedshift' is an asynchronous operation. In response
-- to 'CreateDataSourceFromRedshift', 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 observations should exist in the database hosted on an Amazon
-- Redshift cluster and should be specified by a 'SelectSqlQuery'. Amazon
-- ML executes
-- <http://docs.aws.amazon.com/redshift/latest/dg/t_Unloading_tables.html Unload>
-- command in Amazon Redshift to transfer the result set of
-- 'SelectSqlQuery' to 'S3StagingLocation.'
--
-- After the 'DataSource' is created, it\'s ready for 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 Amazon Machine Learning
-- Developer Guide.
--
-- /See:/ <http://http://docs.aws.amazon.com/machine-learning/latest/APIReference/API_CreateDataSourceFromRedshift.html AWS API Reference> for CreateDataSourceFromRedshift.
module Network.AWS.MachineLearning.CreateDataSourceFromRedshift
(
-- * Creating a Request
createDataSourceFromRedshift
, CreateDataSourceFromRedshift
-- * Request Lenses
, cdsfrDataSourceName
, cdsfrComputeStatistics
, cdsfrDataSourceId
, cdsfrDataSpec
, cdsfrRoleARN
-- * Destructuring the Response
, createDataSourceFromRedshiftResponse
, CreateDataSourceFromRedshiftResponse
-- * Response Lenses
, cdsfrrsDataSourceId
, cdsfrrsStatus
) where
import Network.AWS.MachineLearning.Types
import Network.AWS.MachineLearning.Types.Product
import Network.AWS.Prelude
import Network.AWS.Request
import Network.AWS.Response
-- | /See:/ 'createDataSourceFromRedshift' smart constructor.
data CreateDataSourceFromRedshift = CreateDataSourceFromRedshift'
{ _cdsfrDataSourceName :: !(Maybe Text)
, _cdsfrComputeStatistics :: !(Maybe Bool)
, _cdsfrDataSourceId :: !Text
, _cdsfrDataSpec :: !RedshiftDataSpec
, _cdsfrRoleARN :: !Text
} deriving (Eq,Read,Show,Data,Typeable,Generic)
-- | Creates a value of 'CreateDataSourceFromRedshift' with the minimum fields required to make a request.
--
-- Use one of the following lenses to modify other fields as desired:
--
-- * 'cdsfrDataSourceName'
--
-- * 'cdsfrComputeStatistics'
--
-- * 'cdsfrDataSourceId'
--
-- * 'cdsfrDataSpec'
--
-- * 'cdsfrRoleARN'
createDataSourceFromRedshift
:: Text -- ^ 'cdsfrDataSourceId'
-> RedshiftDataSpec -- ^ 'cdsfrDataSpec'
-> Text -- ^ 'cdsfrRoleARN'
-> CreateDataSourceFromRedshift
createDataSourceFromRedshift pDataSourceId_ pDataSpec_ pRoleARN_ =
CreateDataSourceFromRedshift'
{ _cdsfrDataSourceName = Nothing
, _cdsfrComputeStatistics = Nothing
, _cdsfrDataSourceId = pDataSourceId_
, _cdsfrDataSpec = pDataSpec_
, _cdsfrRoleARN = pRoleARN_
}
-- | A user-supplied name or description of the 'DataSource'.
cdsfrDataSourceName :: Lens' CreateDataSourceFromRedshift (Maybe Text)
cdsfrDataSourceName = lens _cdsfrDataSourceName (\ s a -> s{_cdsfrDataSourceName = 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 'MLModel' training. This parameter must
-- be set to 'true' if the ''DataSource'' needs to be used for 'MLModel'
-- training
cdsfrComputeStatistics :: Lens' CreateDataSourceFromRedshift (Maybe Bool)
cdsfrComputeStatistics = lens _cdsfrComputeStatistics (\ s a -> s{_cdsfrComputeStatistics = a});
-- | A user-supplied ID that uniquely identifies the 'DataSource'.
cdsfrDataSourceId :: Lens' CreateDataSourceFromRedshift Text
cdsfrDataSourceId = lens _cdsfrDataSourceId (\ s a -> s{_cdsfrDataSourceId = a});
-- | The data specification of an Amazon Redshift 'DataSource':
--
-- - DatabaseInformation -
--
-- - 'DatabaseName ' - Name of the Amazon Redshift database.
-- - ' ClusterIdentifier ' - Unique ID for the Amazon Redshift
-- cluster.
-- - DatabaseCredentials - AWS Identity abd Access Management (IAM)
-- credentials that are used to connect to the Amazon Redshift
-- database.
--
-- - SelectSqlQuery - Query that is used to retrieve the observation data
-- for the 'Datasource'.
--
-- - S3StagingLocation - Amazon Simple Storage Service (Amazon S3)
-- location for staging Amazon Redshift data. The data retrieved from
-- Amazon Relational Database Service (Amazon RDS) using
-- 'SelectSqlQuery' is stored in this location.
--
-- - DataSchemaUri - 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 -
-- ' \"{\\\"randomSeed\\\":\\\"some-random-seed\\\", \\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"'
--
cdsfrDataSpec :: Lens' CreateDataSourceFromRedshift RedshiftDataSpec
cdsfrDataSpec = lens _cdsfrDataSpec (\ s a -> s{_cdsfrDataSpec = a});
-- | A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the
-- role on behalf of the user to create the following:
--
-- - A security group to allow Amazon ML to execute the 'SelectSqlQuery'
-- query on an Amazon Redshift cluster
--
-- - An Amazon S3 bucket policy to grant Amazon ML read\/write
-- permissions on the 'S3StagingLocation'
--
cdsfrRoleARN :: Lens' CreateDataSourceFromRedshift Text
cdsfrRoleARN = lens _cdsfrRoleARN (\ s a -> s{_cdsfrRoleARN = a});
instance AWSRequest CreateDataSourceFromRedshift
where
type Sv CreateDataSourceFromRedshift =
MachineLearning
type Rs CreateDataSourceFromRedshift =
CreateDataSourceFromRedshiftResponse
request = postJSON
response
= receiveJSON
(\ s h x ->
CreateDataSourceFromRedshiftResponse' <$>
(x .?> "DataSourceId") <*> (pure (fromEnum s)))
instance ToHeaders CreateDataSourceFromRedshift where
toHeaders
= const
(mconcat
["X-Amz-Target" =#
("AmazonML_20141212.CreateDataSourceFromRedshift" ::
ByteString),
"Content-Type" =#
("application/x-amz-json-1.1" :: ByteString)])
instance ToJSON CreateDataSourceFromRedshift where
toJSON CreateDataSourceFromRedshift'{..}
= object
["DataSourceName" .= _cdsfrDataSourceName,
"ComputeStatistics" .= _cdsfrComputeStatistics,
"DataSourceId" .= _cdsfrDataSourceId,
"DataSpec" .= _cdsfrDataSpec,
"RoleARN" .= _cdsfrRoleARN]
instance ToPath CreateDataSourceFromRedshift where
toPath = const "/"
instance ToQuery CreateDataSourceFromRedshift where
toQuery = const mempty
-- | Represents the output of a CreateDataSourceFromRedshift operation, and
-- is an acknowledgement that Amazon ML received the request.
--
-- The CreateDataSourceFromRedshift operation is asynchronous. You can poll
-- for updates by using the GetBatchPrediction operation and checking the
-- 'Status' parameter.
--
-- /See:/ 'createDataSourceFromRedshiftResponse' smart constructor.
data CreateDataSourceFromRedshiftResponse = CreateDataSourceFromRedshiftResponse'
{ _cdsfrrsDataSourceId :: !(Maybe Text)
, _cdsfrrsStatus :: !Int
} deriving (Eq,Read,Show,Data,Typeable,Generic)
-- | Creates a value of 'CreateDataSourceFromRedshiftResponse' with the minimum fields required to make a request.
--
-- Use one of the following lenses to modify other fields as desired:
--
-- * 'cdsfrrsDataSourceId'
--
-- * 'cdsfrrsStatus'
createDataSourceFromRedshiftResponse
:: Int -- ^ 'cdsfrrsStatus'
-> CreateDataSourceFromRedshiftResponse
createDataSourceFromRedshiftResponse pStatus_ =
CreateDataSourceFromRedshiftResponse'
{ _cdsfrrsDataSourceId = Nothing
, _cdsfrrsStatus = pStatus_
}
-- | A user-supplied ID that uniquely identifies the datasource. This value
-- should be identical to the value of the 'DataSourceID' in the request.
cdsfrrsDataSourceId :: Lens' CreateDataSourceFromRedshiftResponse (Maybe Text)
cdsfrrsDataSourceId = lens _cdsfrrsDataSourceId (\ s a -> s{_cdsfrrsDataSourceId = a});
-- | The response status code.
cdsfrrsStatus :: Lens' CreateDataSourceFromRedshiftResponse Int
cdsfrrsStatus = lens _cdsfrrsStatus (\ s a -> s{_cdsfrrsStatus = a});