amazonka-ml-1.4.1: Amazon Machine Learning SDK.

Copyright(c) 2013-2016 Brendan Hay
LicenseMozilla Public License, v. 2.0.
MaintainerBrendan Hay <brendan.g.hay@gmail.com>
Stabilityauto-generated
Portabilitynon-portable (GHC extensions)
Safe HaskellNone
LanguageHaskell2010

Network.AWS.MachineLearning.CreateDataSourceFromS3

Contents

Description

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.

Synopsis

Creating a Request

createDataSourceFromS3 Source #

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.

Instances

Eq CreateDataSourceFromS3 Source # 
Data CreateDataSourceFromS3 Source # 

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> CreateDataSourceFromS3 -> c CreateDataSourceFromS3 #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c CreateDataSourceFromS3 #

toConstr :: CreateDataSourceFromS3 -> Constr #

dataTypeOf :: CreateDataSourceFromS3 -> DataType #

dataCast1 :: Typeable (* -> *) t => (forall d. Data d => c (t d)) -> Maybe (c CreateDataSourceFromS3) #

dataCast2 :: Typeable (* -> * -> *) t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c CreateDataSourceFromS3) #

gmapT :: (forall b. Data b => b -> b) -> CreateDataSourceFromS3 -> CreateDataSourceFromS3 #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> CreateDataSourceFromS3 -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> CreateDataSourceFromS3 -> r #

gmapQ :: (forall d. Data d => d -> u) -> CreateDataSourceFromS3 -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> CreateDataSourceFromS3 -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> CreateDataSourceFromS3 -> m CreateDataSourceFromS3 #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> CreateDataSourceFromS3 -> m CreateDataSourceFromS3 #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> CreateDataSourceFromS3 -> m CreateDataSourceFromS3 #

Read CreateDataSourceFromS3 Source # 
Show CreateDataSourceFromS3 Source # 
Generic CreateDataSourceFromS3 Source # 
Hashable CreateDataSourceFromS3 Source # 
ToJSON CreateDataSourceFromS3 Source # 
NFData CreateDataSourceFromS3 Source # 

Methods

rnf :: CreateDataSourceFromS3 -> () #

AWSRequest CreateDataSourceFromS3 Source # 
ToQuery CreateDataSourceFromS3 Source # 
ToPath CreateDataSourceFromS3 Source # 
ToHeaders CreateDataSourceFromS3 Source # 
type Rep CreateDataSourceFromS3 Source # 
type Rep CreateDataSourceFromS3 = D1 (MetaData "CreateDataSourceFromS3" "Network.AWS.MachineLearning.CreateDataSourceFromS3" "amazonka-ml-1.4.1-5jDp9fGygLI17rP35njtq9" False) (C1 (MetaCons "CreateDataSourceFromS3'" PrefixI True) ((:*:) ((:*:) (S1 (MetaSel (Just Symbol "_cdsfsDataSourceName") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))) (S1 (MetaSel (Just Symbol "_cdsfsComputeStatistics") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bool)))) ((:*:) (S1 (MetaSel (Just Symbol "_cdsfsDataSourceId") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 Text)) (S1 (MetaSel (Just Symbol "_cdsfsDataSpec") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 S3DataSpec)))))
type Rs CreateDataSourceFromS3 Source # 

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.

Instances

Eq CreateDataSourceFromS3Response Source # 
Data CreateDataSourceFromS3Response Source # 

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> CreateDataSourceFromS3Response -> c CreateDataSourceFromS3Response #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c CreateDataSourceFromS3Response #

toConstr :: CreateDataSourceFromS3Response -> Constr #

dataTypeOf :: CreateDataSourceFromS3Response -> DataType #

dataCast1 :: Typeable (* -> *) t => (forall d. Data d => c (t d)) -> Maybe (c CreateDataSourceFromS3Response) #

dataCast2 :: Typeable (* -> * -> *) t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c CreateDataSourceFromS3Response) #

gmapT :: (forall b. Data b => b -> b) -> CreateDataSourceFromS3Response -> CreateDataSourceFromS3Response #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> CreateDataSourceFromS3Response -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> CreateDataSourceFromS3Response -> r #

gmapQ :: (forall d. Data d => d -> u) -> CreateDataSourceFromS3Response -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> CreateDataSourceFromS3Response -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> CreateDataSourceFromS3Response -> m CreateDataSourceFromS3Response #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> CreateDataSourceFromS3Response -> m CreateDataSourceFromS3Response #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> CreateDataSourceFromS3Response -> m CreateDataSourceFromS3Response #

Read CreateDataSourceFromS3Response Source # 
Show CreateDataSourceFromS3Response Source # 
Generic CreateDataSourceFromS3Response Source # 
NFData CreateDataSourceFromS3Response Source # 
type Rep CreateDataSourceFromS3Response Source # 
type Rep CreateDataSourceFromS3Response = D1 (MetaData "CreateDataSourceFromS3Response" "Network.AWS.MachineLearning.CreateDataSourceFromS3" "amazonka-ml-1.4.1-5jDp9fGygLI17rP35njtq9" False) (C1 (MetaCons "CreateDataSourceFromS3Response'" PrefixI True) ((:*:) (S1 (MetaSel (Just Symbol "_cdsfsrsDataSourceId") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))) (S1 (MetaSel (Just Symbol "_cdsfsrsResponseStatus") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 Int))))

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.