amazonka-ml-1.3.6: Amazon Machine Learning SDK.

Copyright(c) 2013-2015 Brendan Hay
LicenseMozilla Public License, v. 2.0.
MaintainerBrendan Hay <>
Portabilitynon-portable (GHC extensions)
Safe HaskellNone




Creates a DataSource from 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 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: AWS API Reference for CreateDataSourceFromRedshift.


Creating a Request

createDataSourceFromRedshift Source

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:

Request Lenses

cdsfrDataSourceName :: Lens' CreateDataSourceFromRedshift (Maybe Text) Source

A user-supplied name or description of the DataSource.

cdsfrComputeStatistics :: Lens' CreateDataSourceFromRedshift (Maybe Bool) Source

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 :: Lens' CreateDataSourceFromRedshift Text Source

A user-supplied ID that uniquely identifies the DataSource.

cdsfrDataSpec :: Lens' CreateDataSourceFromRedshift RedshiftDataSpec Source

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 - ' "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"'

cdsfrRoleARN :: Lens' CreateDataSourceFromRedshift Text Source

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

Destructuring the Response

createDataSourceFromRedshiftResponse Source

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:

data CreateDataSourceFromRedshiftResponse Source

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.

Response Lenses

cdsfrrsDataSourceId :: Lens' CreateDataSourceFromRedshiftResponse (Maybe Text) Source

A user-supplied ID that uniquely identifies the datasource. This value should be identical to the value of the DataSourceID in the request.