{-# 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) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- -- Creates a @DataSource@ from a database hosted on an Amazon Redshift cluster. 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@ states can be used to perform only @CreateMLModel@ , @CreateEvaluation@ , or @CreateBatchPrediction@ operations. -- -- If Amazon ML can't 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 be contained in the database hosted on an Amazon Redshift cluster and should be specified by a @SelectSqlQuery@ query. Amazon ML executes an @Unload@ command in Amazon Redshift to transfer the result set of the @SelectSqlQuery@ query to @S3StagingLocation@ . -- -- After the @DataSource@ has been created, it's ready for use in evaluations and batch predictions. If you plan to use the @DataSource@ to train an @MLModel@ , the @DataSource@ also requires a recipe. A recipe describes how each input variable will be used in training an @MLModel@ . Will the variable be included or excluded from training? Will the variable be manipulated; for example, will it be combined with another variable or will it be split apart into word combinations? The recipe provides answers to these questions. -- -- You can't change an existing datasource, but you can copy and modify the settings from an existing Amazon Redshift datasource to create a new datasource. To do so, call @GetDataSource@ for an existing datasource and copy the values to a @CreateDataSource@ call. Change the settings that you want to change and make sure that all required fields have the appropriate values. -- 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 , cdsfrrsResponseStatus ) 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:/ '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' - A user-supplied name or description of the @DataSource@ . -- -- * 'cdsfrComputeStatistics' - 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. -- -- * 'cdsfrDataSourceId' - A user-supplied ID that uniquely identifies the @DataSource@ . -- -- * 'cdsfrDataSpec' - The data specification of an Amazon Redshift @DataSource@ : * DatabaseInformation - * @DatabaseName@ - The name of the Amazon Redshift database. * @ClusterIdentifier@ - The unique ID for the Amazon Redshift cluster. * DatabaseCredentials - The AWS Identity and Access Management (IAM) credentials that are used to connect to the Amazon Redshift database. * SelectSqlQuery - The query that is used to retrieve the observation data for the @Datasource@ . * S3StagingLocation - The Amazon Simple Storage Service (Amazon S3) location for staging Amazon Redshift data. The data retrieved from Amazon Redshift using the @SelectSqlQuery@ query is stored in this location. * DataSchemaUri - The 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 that represents the splitting and rearrangement requirements for the @DataSource@ . Sample - @"{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"@ -- -- * 'cdsfrRoleARN' - 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@ 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@ - The name of the Amazon Redshift database. * @ClusterIdentifier@ - The unique ID for the Amazon Redshift cluster. * DatabaseCredentials - The AWS Identity and Access Management (IAM) credentials that are used to connect to the Amazon Redshift database. * SelectSqlQuery - The query that is used to retrieve the observation data for the @Datasource@ . * S3StagingLocation - The Amazon Simple Storage Service (Amazon S3) location for staging Amazon Redshift data. The data retrieved from Amazon Redshift using the @SelectSqlQuery@ query is stored in this location. * DataSchemaUri - The 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 that represents the splitting and rearrangement requirements for the @DataSource@ . Sample - @"{\"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 Rs CreateDataSourceFromRedshift = CreateDataSourceFromRedshiftResponse request = postJSON machineLearning response = receiveJSON (\ s h x -> CreateDataSourceFromRedshiftResponse' <$> (x .?> "DataSourceId") <*> (pure (fromEnum s))) instance Hashable CreateDataSourceFromRedshift where instance NFData CreateDataSourceFromRedshift where instance ToHeaders CreateDataSourceFromRedshift where toHeaders = const (mconcat ["X-Amz-Target" =# ("AmazonML_20141212.CreateDataSourceFromRedshift" :: ByteString), "Content-Type" =# ("application/x-amz-json-1.1" :: ByteString)]) instance ToJSON CreateDataSourceFromRedshift where toJSON CreateDataSourceFromRedshift'{..} = object (catMaybes [("DataSourceName" .=) <$> _cdsfrDataSourceName, ("ComputeStatistics" .=) <$> _cdsfrComputeStatistics, Just ("DataSourceId" .= _cdsfrDataSourceId), Just ("DataSpec" .= _cdsfrDataSpec), Just ("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) , _cdsfrrsResponseStatus :: !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' - A user-supplied ID that uniquely identifies the datasource. This value should be identical to the value of the @DataSourceID@ in the request. -- -- * 'cdsfrrsResponseStatus' - -- | The response status code. createDataSourceFromRedshiftResponse :: Int -- ^ 'cdsfrrsResponseStatus' -> CreateDataSourceFromRedshiftResponse createDataSourceFromRedshiftResponse pResponseStatus_ = CreateDataSourceFromRedshiftResponse' {_cdsfrrsDataSourceId = Nothing, _cdsfrrsResponseStatus = pResponseStatus_} -- | 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. cdsfrrsResponseStatus :: Lens' CreateDataSourceFromRedshiftResponse Int cdsfrrsResponseStatus = lens _cdsfrrsResponseStatus (\ s a -> s{_cdsfrrsResponseStatus = a}) instance NFData CreateDataSourceFromRedshiftResponse where