| Copyright | (c) 2013-2023 Brendan Hay |
|---|---|
| License | Mozilla Public License, v. 2.0. |
| Maintainer | Brendan Hay |
| Stability | auto-generated |
| Portability | non-portable (GHC extensions) |
| Safe Haskell | Safe-Inferred |
| Language | Haskell2010 |
Amazonka.MachineLearning.CreateDataSourceFromRedshift
Description
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.
Synopsis
- data CreateDataSourceFromRedshift = CreateDataSourceFromRedshift' {}
- newCreateDataSourceFromRedshift :: Text -> RedshiftDataSpec -> Text -> CreateDataSourceFromRedshift
- createDataSourceFromRedshift_computeStatistics :: Lens' CreateDataSourceFromRedshift (Maybe Bool)
- createDataSourceFromRedshift_dataSourceName :: Lens' CreateDataSourceFromRedshift (Maybe Text)
- createDataSourceFromRedshift_dataSourceId :: Lens' CreateDataSourceFromRedshift Text
- createDataSourceFromRedshift_dataSpec :: Lens' CreateDataSourceFromRedshift RedshiftDataSpec
- createDataSourceFromRedshift_roleARN :: Lens' CreateDataSourceFromRedshift Text
- data CreateDataSourceFromRedshiftResponse = CreateDataSourceFromRedshiftResponse' {
- dataSourceId :: Maybe Text
- httpStatus :: Int
- newCreateDataSourceFromRedshiftResponse :: Int -> CreateDataSourceFromRedshiftResponse
- createDataSourceFromRedshiftResponse_dataSourceId :: Lens' CreateDataSourceFromRedshiftResponse (Maybe Text)
- createDataSourceFromRedshiftResponse_httpStatus :: Lens' CreateDataSourceFromRedshiftResponse Int
Creating a Request
data CreateDataSourceFromRedshift Source #
See: newCreateDataSourceFromRedshift smart constructor.
Constructors
| CreateDataSourceFromRedshift' | |
Fields
| |
Instances
newCreateDataSourceFromRedshift Source #
Arguments
| :: Text | |
| -> RedshiftDataSpec | |
| -> Text | |
| -> CreateDataSourceFromRedshift |
Create a value of CreateDataSourceFromRedshift with all optional fields omitted.
Use generic-lens or optics to modify other optional fields.
The following record fields are available, with the corresponding lenses provided for backwards compatibility:
CreateDataSourceFromRedshift, createDataSourceFromRedshift_computeStatistics - 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.
$sel:dataSourceName:CreateDataSourceFromRedshift', createDataSourceFromRedshift_dataSourceName - A user-supplied name or description of the DataSource.
CreateDataSourceFromRedshift, createDataSourceFromRedshift_dataSourceId - A user-supplied ID that uniquely identifies the DataSource.
$sel:dataSpec:CreateDataSourceFromRedshift', createDataSourceFromRedshift_dataSpec - 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
SelectSqlQueryquery 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
DataSchemaUriis specified. DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the
DataSource.Sample -
"{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"
CreateDataSourceFromRedshift, createDataSourceFromRedshift_roleARN - 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
SelectSqlQueryquery on an Amazon Redshift cluster - An Amazon S3 bucket policy to grant Amazon ML read/write
permissions on the
S3StagingLocation
Request Lenses
createDataSourceFromRedshift_computeStatistics :: 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.
createDataSourceFromRedshift_dataSourceName :: Lens' CreateDataSourceFromRedshift (Maybe Text) Source #
A user-supplied name or description of the DataSource.
createDataSourceFromRedshift_dataSourceId :: Lens' CreateDataSourceFromRedshift Text Source #
A user-supplied ID that uniquely identifies the DataSource.
createDataSourceFromRedshift_dataSpec :: Lens' CreateDataSourceFromRedshift RedshiftDataSpec Source #
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
SelectSqlQueryquery 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
DataSchemaUriis specified. DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the
DataSource.Sample -
"{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"
createDataSourceFromRedshift_roleARN :: 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
SelectSqlQueryquery on an Amazon Redshift cluster - An Amazon S3 bucket policy to grant Amazon ML read/write
permissions on the
S3StagingLocation
Destructuring the Response
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: newCreateDataSourceFromRedshiftResponse smart constructor.
Constructors
| CreateDataSourceFromRedshiftResponse' | |
Fields
| |
Instances
newCreateDataSourceFromRedshiftResponse Source #
Arguments
| :: Int | |
| -> CreateDataSourceFromRedshiftResponse |
Create a value of CreateDataSourceFromRedshiftResponse with all optional fields omitted.
Use generic-lens or optics to modify other optional fields.
The following record fields are available, with the corresponding lenses provided for backwards compatibility:
CreateDataSourceFromRedshift, createDataSourceFromRedshiftResponse_dataSourceId - A user-supplied ID that uniquely identifies the datasource. This value
should be identical to the value of the DataSourceID in the request.
$sel:httpStatus:CreateDataSourceFromRedshiftResponse', createDataSourceFromRedshiftResponse_httpStatus - The response's http status code.
Response Lenses
createDataSourceFromRedshiftResponse_dataSourceId :: 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.
createDataSourceFromRedshiftResponse_httpStatus :: Lens' CreateDataSourceFromRedshiftResponse Int Source #
The response's http status code.