Copyright	(c) 2013-2021 Brendan Hay
License	Mozilla Public License, v. 2.0.
Maintainer	Brendan Hay <brendan.g.hay+amazonka@gmail.com>
Stability	auto-generated
Portability	non-portable (GHC extensions)
Safe Haskell	None

Amazonka.MachineLearning.CreateDataSourceFromS3

Contents

Creating a Request
Request Lenses
Destructuring the Response
Response Lenses

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 has been created and is ready for use, Amazon ML sets the Status parameter to COMPLETED. DataSource in the COMPLETED or PENDING state 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 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) location, 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 also needs 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.

Synopsis

Creating a Request

data CreateDataSourceFromS3 Source #

See: newCreateDataSourceFromS3 smart constructor.

Constructors

CreateDataSourceFromS3'

Fields

dataSourceName :: Maybe Text
A user-supplied name or description of the DataSource.
computeStatistics :: Maybe Bool
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.
dataSourceId :: Text
A user-supplied identifier that uniquely identifies the DataSource.
dataSpec :: S3DataSpec
The data specification of a DataSource:
- DataLocationS3 - The Amazon S3 location of the observation data.
- DataSchemaLocationS3 - The 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 that represents the splitting and rearrangement requirements for the Datasource.
  Sample - "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"

Instances

Instances details

Eq CreateDataSourceFromS3 Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Methods (==) :: CreateDataSourceFromS3 -> CreateDataSourceFromS3 -> Bool # (/=) :: CreateDataSourceFromS3 -> CreateDataSourceFromS3 -> Bool #
Read CreateDataSourceFromS3 Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Methods readsPrec :: Int -> ReadS CreateDataSourceFromS3 # readList :: ReadS [CreateDataSourceFromS3] # readPrec :: ReadPrec CreateDataSourceFromS3 # readListPrec :: ReadPrec [CreateDataSourceFromS3] #
Show CreateDataSourceFromS3 Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Methods showsPrec :: Int -> CreateDataSourceFromS3 -> ShowS # show :: CreateDataSourceFromS3 -> String # showList :: [CreateDataSourceFromS3] -> ShowS #
Generic CreateDataSourceFromS3 Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Associated Types type Rep CreateDataSourceFromS3 :: Type -> Type # Methods from :: CreateDataSourceFromS3 -> Rep CreateDataSourceFromS3 x # to :: Rep CreateDataSourceFromS3 x -> CreateDataSourceFromS3 #
NFData CreateDataSourceFromS3 Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Methods rnf :: CreateDataSourceFromS3 -> () #
Hashable CreateDataSourceFromS3 Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Methods hashWithSalt :: Int -> CreateDataSourceFromS3 -> Int # hash :: CreateDataSourceFromS3 -> Int #
ToJSON CreateDataSourceFromS3 Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Methods toJSON :: CreateDataSourceFromS3 -> Value # toEncoding :: CreateDataSourceFromS3 -> Encoding # toJSONList :: [CreateDataSourceFromS3] -> Value # toEncodingList :: [CreateDataSourceFromS3] -> Encoding #
AWSRequest CreateDataSourceFromS3 Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Associated Types type AWSResponse CreateDataSourceFromS3 # Methods request :: CreateDataSourceFromS3 -> Request CreateDataSourceFromS3 # response :: MonadResource m => Logger -> Service -> Proxy CreateDataSourceFromS3 -> ClientResponse ClientBody -> m (Either Error (ClientResponse (AWSResponse CreateDataSourceFromS3))) #
ToHeaders CreateDataSourceFromS3 Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Methods toHeaders :: CreateDataSourceFromS3 -> [Header] #
ToPath CreateDataSourceFromS3 Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Methods toPath :: CreateDataSourceFromS3 -> ByteString #
ToQuery CreateDataSourceFromS3 Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Methods toQuery :: CreateDataSourceFromS3 -> QueryString #
type Rep CreateDataSourceFromS3 Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 type Rep CreateDataSourceFromS3 = D1 ('MetaData "CreateDataSourceFromS3" "Amazonka.MachineLearning.CreateDataSourceFromS3" "libZSservicesZSamazonka-mlZSamazonka-ml" 'False) (C1 ('MetaCons "CreateDataSourceFromS3'" 'PrefixI 'True) ((S1 ('MetaSel ('Just "dataSourceName") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: S1 ('MetaSel ('Just "computeStatistics") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Bool))) :: (S1 ('MetaSel ('Just "dataSourceId") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text) :*: S1 ('MetaSel ('Just "dataSpec") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 S3DataSpec))))
type AWSResponse CreateDataSourceFromS3 Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 type AWSResponse CreateDataSourceFromS3 = CreateDataSourceFromS3Response

newCreateDataSourceFromS3 Source #

Arguments

:: Text	`$sel:dataSourceId:CreateDataSourceFromS3'`
-> S3DataSpec	`$sel:dataSpec:CreateDataSourceFromS3'`
-> CreateDataSourceFromS3

Create a value of CreateDataSourceFromS3 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:

$sel:dataSourceName:CreateDataSourceFromS3', createDataSourceFromS3_dataSourceName - A user-supplied name or description of the DataSource.

$sel:computeStatistics:CreateDataSourceFromS3', createDataSourceFromS3_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:dataSourceId:CreateDataSourceFromS3', createDataSourceFromS3_dataSourceId - A user-supplied identifier that uniquely identifies the DataSource.

$sel:dataSpec:CreateDataSourceFromS3', createDataSourceFromS3_dataSpec - The data specification of a DataSource:

DataLocationS3 - The Amazon S3 location of the observation data.
DataSchemaLocationS3 - The 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 that represents the splitting and rearrangement requirements for the Datasource.
Sample - "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"

Request Lenses

createDataSourceFromS3_dataSourceName :: Lens' CreateDataSourceFromS3 (Maybe Text) Source #

A user-supplied name or description of the DataSource.

createDataSourceFromS3_computeStatistics :: 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 MLModel training. This parameter must be set to true if the @DataSource needs to be used for MLModel@ training.

createDataSourceFromS3_dataSourceId :: Lens' CreateDataSourceFromS3 Text Source #

A user-supplied identifier that uniquely identifies the DataSource.

createDataSourceFromS3_dataSpec :: Lens' CreateDataSourceFromS3 S3DataSpec Source #

The data specification of a DataSource:

DataLocationS3 - The Amazon S3 location of the observation data.
DataSchemaLocationS3 - The 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 that represents the splitting and rearrangement requirements for the Datasource.
Sample - "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"

Destructuring the Response

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: newCreateDataSourceFromS3Response smart constructor.

Constructors

CreateDataSourceFromS3Response'
Fields dataSourceId :: Maybe Text A user-supplied ID that uniquely identifies the `DataSource`. This value should be identical to the value of the `DataSourceID` in the request. httpStatus :: Int The response's http status code.

Instances

Instances details

Eq CreateDataSourceFromS3Response Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Methods (==) :: CreateDataSourceFromS3Response -> CreateDataSourceFromS3Response -> Bool # (/=) :: CreateDataSourceFromS3Response -> CreateDataSourceFromS3Response -> Bool #
Read CreateDataSourceFromS3Response Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Methods readsPrec :: Int -> ReadS CreateDataSourceFromS3Response # readList :: ReadS [CreateDataSourceFromS3Response] # readPrec :: ReadPrec CreateDataSourceFromS3Response # readListPrec :: ReadPrec [CreateDataSourceFromS3Response] #
Show CreateDataSourceFromS3Response Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Methods showsPrec :: Int -> CreateDataSourceFromS3Response -> ShowS # show :: CreateDataSourceFromS3Response -> String # showList :: [CreateDataSourceFromS3Response] -> ShowS #
Generic CreateDataSourceFromS3Response Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Associated Types type Rep CreateDataSourceFromS3Response :: Type -> Type # Methods from :: CreateDataSourceFromS3Response -> Rep CreateDataSourceFromS3Response x # to :: Rep CreateDataSourceFromS3Response x -> CreateDataSourceFromS3Response #
NFData CreateDataSourceFromS3Response Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 Methods rnf :: CreateDataSourceFromS3Response -> () #
type Rep CreateDataSourceFromS3Response Source #
Instance details Defined in Amazonka.MachineLearning.CreateDataSourceFromS3 type Rep CreateDataSourceFromS3Response = D1 ('MetaData "CreateDataSourceFromS3Response" "Amazonka.MachineLearning.CreateDataSourceFromS3" "libZSservicesZSamazonka-mlZSamazonka-ml" 'False) (C1 ('MetaCons "CreateDataSourceFromS3Response'" 'PrefixI 'True) (S1 ('MetaSel ('Just "dataSourceId") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :*: S1 ('MetaSel ('Just "httpStatus") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Int)))

newCreateDataSourceFromS3Response Source #

Arguments

:: Int	`$sel:httpStatus:CreateDataSourceFromS3Response'`
-> CreateDataSourceFromS3Response

Create a value of CreateDataSourceFromS3Response 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:

$sel:dataSourceId:CreateDataSourceFromS3', createDataSourceFromS3Response_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:CreateDataSourceFromS3Response', createDataSourceFromS3Response_httpStatus - The response's http status code.

Response Lenses

createDataSourceFromS3Response_dataSourceId :: 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.

createDataSourceFromS3Response_httpStatus :: Lens' CreateDataSourceFromS3Response Int Source #

The response's http status code.