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) |
Safe Haskell | None |
Language | Haskell2010 |
Creates a DataSource
object. A DataSource
references data that can
be used to perform CreateMLModel, CreateEvaluation, or
CreateBatchPrediction operations.
CreateDataSourceFromS3
is an asynchronous operation. In response to
CreateDataSourceFromS3
, 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 observation data used in a DataSource
should be ready to use; that
is, it should have a consistent structure, and missing data values
should be kept to a minimum. The observation data must reside in one or
more CSV files in an Amazon Simple Storage Service (Amazon S3) bucket,
along with a schema that describes the data items by name and type. The
same schema must be used for all of the data files referenced by the
DataSource
.
After the DataSource
has been created, it's ready to 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 CreateDataSourceFromS3.
- createDataSourceFromS3 :: Text -> S3DataSpec -> CreateDataSourceFromS3
- data CreateDataSourceFromS3
- cdsfsDataSourceName :: Lens' CreateDataSourceFromS3 (Maybe Text)
- cdsfsComputeStatistics :: Lens' CreateDataSourceFromS3 (Maybe Bool)
- cdsfsDataSourceId :: Lens' CreateDataSourceFromS3 Text
- cdsfsDataSpec :: Lens' CreateDataSourceFromS3 S3DataSpec
- createDataSourceFromS3Response :: Int -> CreateDataSourceFromS3Response
- data CreateDataSourceFromS3Response
- cdsfsrsDataSourceId :: Lens' CreateDataSourceFromS3Response (Maybe Text)
- cdsfsrsResponseStatus :: Lens' CreateDataSourceFromS3Response Int
Creating a Request
Creates a value of CreateDataSourceFromS3
with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
data CreateDataSourceFromS3 Source
See: createDataSourceFromS3
smart constructor.
Request Lenses
cdsfsDataSourceName :: Lens' CreateDataSourceFromS3 (Maybe Text) Source
A user-supplied name or description of the DataSource
.
cdsfsComputeStatistics :: Lens' CreateDataSourceFromS3 (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 an MLModel
training. This parameter
must be set to true
if the ''DataSource'' needs to be used for
MLModel
training
cdsfsDataSourceId :: Lens' CreateDataSourceFromS3 Text Source
A user-supplied identifier that uniquely identifies the DataSource
.
cdsfsDataSpec :: Lens' CreateDataSourceFromS3 S3DataSpec Source
The data specification of a DataSource
:
- DataLocationS3 - Amazon Simple Storage Service (Amazon S3) location of the observation data.
- DataSchemaLocationS3 - 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}}"'
Destructuring the Response
createDataSourceFromS3Response Source
Creates a value of CreateDataSourceFromS3Response
with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
data CreateDataSourceFromS3Response Source
Represents the output of a CreateDataSourceFromS3 operation, and is an acknowledgement that Amazon ML received the request.
The CreateDataSourceFromS3 operation is asynchronous. You can poll for
updates by using the GetBatchPrediction operation and checking the
Status
parameter.
See: createDataSourceFromS3Response
smart constructor.
Response Lenses
cdsfsrsDataSourceId :: Lens' CreateDataSourceFromS3Response (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.
cdsfsrsResponseStatus :: Lens' CreateDataSourceFromS3Response Int Source
The response status code.