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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.
This is an asynchronous operation using the standard naming convention for .NET 4.5 or higher. For .NET 3.5 the operation is implemented as a pair of methods using the standard naming convention of BeginCreateDataSourceFromRedshift and EndCreateDataSourceFromRedshift.
Namespace: Amazon.MachineLearning
Assembly: AWSSDK.MachineLearning.dll
Version: 3.x.y.z
public abstract Task<CreateDataSourceFromRedshiftResponse> CreateDataSourceFromRedshiftAsync( CreateDataSourceFromRedshiftRequest request, CancellationToken cancellationToken )
Container for the necessary parameters to execute the CreateDataSourceFromRedshift service method.
A cancellation token that can be used by other objects or threads to receive notice of cancellation.
| Exception | Condition |
|---|---|
| IdempotentParameterMismatchException | A second request to use or change an object was not allowed. This can result from retrying a request using a parameter that was not present in the original request. |
| InternalServerException | An error on the server occurred when trying to process a request. |
| InvalidInputException | An error on the client occurred. Typically, the cause is an invalid input value. |
.NET Core App:
Supported in: 3.1
.NET Standard:
Supported in: 2.0
.NET Framework:
Supported in: 4.5