amazonka-ml-1.3.3: Amazon Machine Learning SDK.

Copyright(c) 2013-2015 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.Types

Contents

Description

 

Synopsis

Service Configuration

machineLearning :: Service Source

API version '2014-12-12' of the Amazon Machine Learning SDK configuration.

Errors

_InternalServerException :: AsError a => Getting (First ServiceError) a ServiceError Source

An error on the server occurred when trying to process a request.

_InvalidInputException :: AsError a => Getting (First ServiceError) a ServiceError Source

An error on the client occurred. Typically, the cause is an invalid input value.

_IdempotentParameterMismatchException :: AsError a => Getting (First ServiceError) a ServiceError Source

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.

_PredictorNotMountedException :: AsError a => Getting (First ServiceError) a ServiceError Source

The exception is thrown when a predict request is made to an unmounted MLModel.

_ResourceNotFoundException :: AsError a => Getting (First ServiceError) a ServiceError Source

A specified resource cannot be located.

_LimitExceededException :: AsError a => Getting (First ServiceError) a ServiceError Source

The subscriber exceeded the maximum number of operations. This exception can occur when listing objects such as DataSource.

Algorithm

data Algorithm Source

The function used to train a MLModel. Training choices supported by Amazon ML include the following:

  • SGD - Stochastic Gradient Descent.
  • RandomForest - Random forest of decision trees.

Constructors

SGD 

BatchPredictionFilterVariable

data BatchPredictionFilterVariable Source

A list of the variables to use in searching or filtering BatchPrediction.

  • CreatedAt - Sets the search criteria to BatchPrediction creation date.
  • Status - Sets the search criteria to BatchPrediction status.
  • Name - Sets the search criteria to the contents of BatchPrediction ____ Name.
  • IAMUser - Sets the search criteria to the user account that invoked the BatchPrediction creation.
  • MLModelId - Sets the search criteria to the MLModel used in the BatchPrediction.
  • DataSourceId - Sets the search criteria to the DataSource used in the BatchPrediction.
  • DataURI - Sets the search criteria to the data file(s) used in the BatchPrediction. The URL can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.

DataSourceFilterVariable

data DataSourceFilterVariable Source

A list of the variables to use in searching or filtering DataSource.

  • CreatedAt - Sets the search criteria to DataSource creation date.
  • Status - Sets the search criteria to DataSource status.
  • Name - Sets the search criteria to the contents of DataSource ____ Name.
  • DataUri - Sets the search criteria to the URI of data files used to create the DataSource. The URI can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.
  • IAMUser - Sets the search criteria to the user account that invoked the DataSource creation.

Note

The variable names should match the variable names in the DataSource.

DetailsAttributes

EntityStatus

EvaluationFilterVariable

data EvaluationFilterVariable Source

A list of the variables to use in searching or filtering Evaluation.

  • CreatedAt - Sets the search criteria to Evaluation creation date.
  • Status - Sets the search criteria to Evaluation status.
  • Name - Sets the search criteria to the contents of Evaluation ____ Name.
  • IAMUser - Sets the search criteria to the user account that invoked an evaluation.
  • MLModelId - Sets the search criteria to the Predictor that was evaluated.
  • DataSourceId - Sets the search criteria to the DataSource used in evaluation.
  • DataUri - Sets the search criteria to the data file(s) used in evaluation. The URL can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.

MLModelFilterVariable

MLModelType

RealtimeEndpointStatus

SortOrder

data SortOrder Source

The sort order specified in a listing condition. Possible values include the following:

  • asc - Present the information in ascending order (from A-Z).
  • dsc - Present the information in descending order (from Z-A).

Constructors

Asc 
Dsc 

BatchPrediction

data BatchPrediction Source

Represents the output of GetBatchPrediction operation.

The content consists of the detailed metadata, the status, and the data file information of a Batch Prediction.

See: batchPrediction smart constructor.

batchPrediction :: BatchPrediction Source

Creates a value of BatchPrediction with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

bpStatus :: Lens' BatchPrediction (Maybe EntityStatus) Source

The status of the BatchPrediction. This element can have one of the following values:

  • PENDING - Amazon Machine Learning (Amazon ML) submitted a request to generate predictions for a batch of observations.
  • INPROGRESS - The process is underway.
  • FAILED - The request to peform a batch prediction did not run to completion. It is not usable.
  • COMPLETED - The batch prediction process completed successfully.
  • DELETED - The BatchPrediction is marked as deleted. It is not usable.

bpLastUpdatedAt :: Lens' BatchPrediction (Maybe UTCTime) Source

The time of the most recent edit to the BatchPrediction. The time is expressed in epoch time.

bpCreatedAt :: Lens' BatchPrediction (Maybe UTCTime) Source

The time that the BatchPrediction was created. The time is expressed in epoch time.

bpInputDataLocationS3 :: Lens' BatchPrediction (Maybe Text) Source

The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

bpMLModelId :: Lens' BatchPrediction (Maybe Text) Source

The ID of the MLModel that generated predictions for the BatchPrediction request.

bpBatchPredictionDataSourceId :: Lens' BatchPrediction (Maybe Text) Source

The ID of the DataSource that points to the group of observations to predict.

bpBatchPredictionId :: Lens' BatchPrediction (Maybe Text) Source

The ID assigned to the BatchPrediction at creation. This value should be identical to the value of the BatchPredictionID in the request.

bpCreatedByIAMUser :: Lens' BatchPrediction (Maybe Text) Source

The AWS user account that invoked the BatchPrediction. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

bpName :: Lens' BatchPrediction (Maybe Text) Source

A user-supplied name or description of the BatchPrediction.

bpMessage :: Lens' BatchPrediction (Maybe Text) Source

A description of the most recent details about processing the batch prediction request.

bpOutputURI :: Lens' BatchPrediction (Maybe Text) Source

The location of an Amazon S3 bucket or directory to receive the operation results. The following substrings are not allowed in the s3 key portion of the "outputURI" field: ':', '//', '/./', '/../'.

DataSource

data DataSource Source

Represents the output of the GetDataSource operation.

The content consists of the detailed metadata and data file information and the current status of the DataSource.

See: dataSource smart constructor.

dsStatus :: Lens' DataSource (Maybe EntityStatus) Source

The current status of the DataSource. This element can have one of the following values:

  • PENDING - Amazon Machine Learning (Amazon ML) submitted a request to create a DataSource.
  • INPROGRESS - The creation process is underway.
  • FAILED - The request to create a DataSource did not run to completion. It is not usable.
  • COMPLETED - The creation process completed successfully.
  • DELETED - The DataSource is marked as deleted. It is not usable.

dsNumberOfFiles :: Lens' DataSource (Maybe Integer) Source

The number of data files referenced by the DataSource.

dsLastUpdatedAt :: Lens' DataSource (Maybe UTCTime) Source

The time of the most recent edit to the BatchPrediction. The time is expressed in epoch time.

dsCreatedAt :: Lens' DataSource (Maybe UTCTime) Source

The time that the DataSource was created. The time is expressed in epoch time.

dsDataSourceId :: Lens' DataSource (Maybe Text) Source

The ID that is assigned to the DataSource during creation.

dsDataSizeInBytes :: Lens' DataSource (Maybe Integer) Source

The total number of observations contained in the data files that the DataSource references.

dsCreatedByIAMUser :: Lens' DataSource (Maybe Text) Source

The AWS user account from which the DataSource was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

dsName :: Lens' DataSource (Maybe Text) Source

A user-supplied name or description of the DataSource.

dsDataLocationS3 :: Lens' DataSource (Maybe Text) Source

The location and name of the data in Amazon Simple Storage Service (Amazon S3) that is used by a DataSource.

dsComputeStatistics :: Lens' DataSource (Maybe Bool) Source

The parameter is true if statistics need to be generated from the observation data.

dsMessage :: Lens' DataSource (Maybe Text) Source

A description of the most recent details about creating the DataSource.

dsDataRearrangement :: Lens' DataSource (Maybe Text) Source

A JSON string that represents the splitting requirement of a Datasource.

dsRoleARN :: Lens' DataSource (Maybe Text) Source

Undocumented member.

Evaluation

data Evaluation Source

Represents the output of GetEvaluation operation.

The content consists of the detailed metadata and data file information and the current status of the Evaluation.

See: evaluation smart constructor.

evaluation :: Evaluation Source

Creates a value of Evaluation with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

eStatus :: Lens' Evaluation (Maybe EntityStatus) Source

The status of the evaluation. This element can have one of the following values:

  • PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an MLModel.
  • INPROGRESS - The evaluation is underway.
  • FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
  • COMPLETED - The evaluation process completed successfully.
  • DELETED - The Evaluation is marked as deleted. It is not usable.

ePerformanceMetrics :: Lens' Evaluation (Maybe PerformanceMetrics) Source

Measurements of how well the MLModel performed, using observations referenced by the DataSource. One of the following metrics is returned, based on the type of the MLModel:

  • BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.
  • RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.
  • MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.

For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.

eLastUpdatedAt :: Lens' Evaluation (Maybe UTCTime) Source

The time of the most recent edit to the Evaluation. The time is expressed in epoch time.

eCreatedAt :: Lens' Evaluation (Maybe UTCTime) Source

The time that the Evaluation was created. The time is expressed in epoch time.

eInputDataLocationS3 :: Lens' Evaluation (Maybe Text) Source

The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.

eMLModelId :: Lens' Evaluation (Maybe Text) Source

The ID of the MLModel that is the focus of the evaluation.

eCreatedByIAMUser :: Lens' Evaluation (Maybe Text) Source

The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

eName :: Lens' Evaluation (Maybe Text) Source

A user-supplied name or description of the Evaluation.

eEvaluationId :: Lens' Evaluation (Maybe Text) Source

The ID that is assigned to the Evaluation at creation.

eMessage :: Lens' Evaluation (Maybe Text) Source

A description of the most recent details about evaluating the MLModel.

eEvaluationDataSourceId :: Lens' Evaluation (Maybe Text) Source

The ID of the DataSource that is used to evaluate the MLModel.

MLModel

data MLModel Source

Represents the output of a GetMLModel operation.

The content consists of the detailed metadata and the current status of the MLModel.

See: mLModel smart constructor.

mlmStatus :: Lens' MLModel (Maybe EntityStatus) Source

The current status of an MLModel. This element can have one of the following values:

  • PENDING - Amazon Machine Learning (Amazon ML) submitted a request to create an MLModel.
  • INPROGRESS - The creation process is underway.
  • FAILED - The request to create an MLModel did not run to completion. It is not usable.
  • COMPLETED - The creation process completed successfully.
  • DELETED - The MLModel is marked as deleted. It is not usable.

mlmLastUpdatedAt :: Lens' MLModel (Maybe UTCTime) Source

The time of the most recent edit to the MLModel. The time is expressed in epoch time.

mlmTrainingParameters :: Lens' MLModel (HashMap Text Text) Source

A list of the training parameters in the MLModel. The list is implemented as a map of key/value pairs.

The following is the current set of training parameters:

  • 'sgd.l1RegularizationAmount' - Coefficient regularization L1 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to zero, resulting in a sparse feature set. If you use this parameter, specify a small value, such as 1.0E-04 or 1.0E-08.

    The value is a double that ranges from 0 to MAX_DOUBLE. The default is not to use L1 normalization. The parameter cannot be used when L2 is specified. Use this parameter sparingly.

  • 'sgd.l2RegularizationAmount' - Coefficient regularization L2 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to small, nonzero values. If you use this parameter, specify a small value, such as 1.0E-04 or 1.0E-08.

    The valus is a double that ranges from 0 to MAX_DOUBLE. The default is not to use L2 normalization. This cannot be used when L1 is specified. Use this parameter sparingly.

  • 'sgd.maxPasses' - Number of times that the training process traverses the observations to build the MLModel. The value is an integer that ranges from 1 to 10000. The default value is 10.
  • 'sgd.maxMLModelSizeInBytes' - Maximum allowed size of the model. Depending on the input data, the model size might affect performance.

    The value is an integer that ranges from 100000 to 2147483648. The default value is 33554432.

mlmScoreThresholdLastUpdatedAt :: Lens' MLModel (Maybe UTCTime) Source

The time of the most recent edit to the ScoreThreshold. The time is expressed in epoch time.

mlmCreatedAt :: Lens' MLModel (Maybe UTCTime) Source

The time that the MLModel was created. The time is expressed in epoch time.

mlmInputDataLocationS3 :: Lens' MLModel (Maybe Text) Source

The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

mlmMLModelId :: Lens' MLModel (Maybe Text) Source

The ID assigned to the MLModel at creation.

mlmSizeInBytes :: Lens' MLModel (Maybe Integer) Source

Undocumented member.

mlmAlgorithm :: Lens' MLModel (Maybe Algorithm) Source

The algorithm used to train the MLModel. The following algorithm is supported:

  • SGD -- Stochastic gradient descent. The goal of SGD is to minimize the gradient of the loss function.

mlmCreatedByIAMUser :: Lens' MLModel (Maybe Text) Source

The AWS user account from which the MLModel was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

mlmName :: Lens' MLModel (Maybe Text) Source

A user-supplied name or description of the MLModel.

mlmTrainingDataSourceId :: Lens' MLModel (Maybe Text) Source

The ID of the training DataSource. The CreateMLModel operation uses the TrainingDataSourceId.

mlmMessage :: Lens' MLModel (Maybe Text) Source

A description of the most recent details about accessing the MLModel.

mlmMLModelType :: Lens' MLModel (Maybe MLModelType) Source

Identifies the MLModel category. The following are the available types:

  • REGRESSION - Produces a numeric result. For example, "What listing price should a house have?".
  • BINARY - Produces one of two possible results. For example, "Is this a child-friendly web site?".
  • MULTICLASS - Produces more than two possible results. For example, "Is this a HIGH, LOW or MEDIUM risk trade?".

PerformanceMetrics

data PerformanceMetrics Source

Measurements of how well the MLModel performed on known observations. One of the following metrics is returned, based on the type of the MLModel:

  • BinaryAUC: The binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.
  • RegressionRMSE: The regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.
  • MulticlassAvgFScore: The multiclass MLModel uses the F1 score technique to measure performance.

For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.

See: performanceMetrics smart constructor.

performanceMetrics :: PerformanceMetrics Source

Creates a value of PerformanceMetrics with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

Prediction

data Prediction Source

The output from a Predict operation:

  • Details - Contains the following attributes: DetailsAttributes.PREDICTIVE_MODEL_TYPE - REGRESSION | BINARY | MULTICLASS DetailsAttributes.ALGORITHM - SGD
  • PredictedLabel - Present for either a BINARY or MULTICLASS MLModel request.
  • PredictedScores - Contains the raw classification score corresponding to each label.
  • PredictedValue - Present for a REGRESSION MLModel request.

See: prediction smart constructor.

prediction :: Prediction Source

Creates a value of Prediction with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

pPredictedValue :: Lens' Prediction (Maybe Double) Source

The prediction value for REGRESSION MLModel.

pPredictedLabel :: Lens' Prediction (Maybe Text) Source

The prediction label for either a BINARY or MULTICLASS MLModel.

RDSDataSpec

data RDSDataSpec Source

The data specification of an Amazon Relational Database Service (Amazon RDS) DataSource.

See: rdsDataSpec smart constructor.

rdsdsDataSchemaURI :: Lens' RDSDataSpec (Maybe Text) Source

The Amazon S3 location of the DataSchema.

rdsdsDataSchema :: Lens' RDSDataSpec (Maybe Text) Source

A JSON string that represents the schema for an Amazon RDS DataSource. The DataSchema defines the structure of the observation data in the data file(s) referenced in the DataSource.

A DataSchema is not required if you specify a DataSchemaUri

Define your DataSchema as a series of key-value pairs. attributes and excludedVariableNames have an array of key-value pairs for their value. Use the following format to define your DataSchema.

{ "version": "1.0",

"recordAnnotationFieldName": "F1",

"recordWeightFieldName": "F2",

"targetFieldName": "F3",

"dataFormat": "CSV",

"dataFileContainsHeader": true,

"attributes": [

{ "fieldName": "F1", "fieldType": "TEXT" }, { "fieldName": "F2", "fieldType": "NUMERIC" }, { "fieldName": "F3", "fieldType": "CATEGORICAL" }, { "fieldName": "F4", "fieldType": "NUMERIC" }, { "fieldName": "F5", "fieldType": "CATEGORICAL" }, { "fieldName": "F6", "fieldType": "TEXT" }, { "fieldName": "F7", "fieldType": "WEIGHTED_INT_SEQUENCE" }, { "fieldName": "F8", "fieldType": "WEIGHTED_STRING_SEQUENCE" } ],

"excludedVariableNames": [ "F6" ] }

rdsdsDataRearrangement :: Lens' RDSDataSpec (Maybe Text) Source

DataRearrangement - A JSON string that represents the splitting requirement of a DataSource.

Sample - ' "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"'

rdsdsDatabaseInformation :: Lens' RDSDataSpec RDSDatabase Source

Describes the DatabaseName and InstanceIdentifier of an an Amazon RDS database.

rdsdsSelectSqlQuery :: Lens' RDSDataSpec Text Source

The query that is used to retrieve the observation data for the DataSource.

rdsdsDatabaseCredentials :: Lens' RDSDataSpec RDSDatabaseCredentials Source

The AWS Identity and Access Management (IAM) credentials that are used connect to the Amazon RDS database.

rdsdsS3StagingLocation :: Lens' RDSDataSpec Text Source

The Amazon S3 location for staging Amazon RDS data. The data retrieved from Amazon RDS using SelectSqlQuery is stored in this location.

rdsdsResourceRole :: Lens' RDSDataSpec Text Source

The role (DataPipelineDefaultResourceRole) assumed by an Amazon Elastic Compute Cloud (Amazon EC2) instance to carry out the copy operation from Amazon RDS to an Amazon S3 task. For more information, see Role templates for data pipelines.

rdsdsServiceRole :: Lens' RDSDataSpec Text Source

The role (DataPipelineDefaultRole) assumed by AWS Data Pipeline service to monitor the progress of the copy task from Amazon RDS to Amazon S3. For more information, see Role templates for data pipelines.

rdsdsSubnetId :: Lens' RDSDataSpec Text Source

The subnet ID to be used to access a VPC-based RDS DB instance. This attribute is used by Data Pipeline to carry out the copy task from Amazon RDS to Amazon S3.

rdsdsSecurityGroupIds :: Lens' RDSDataSpec [Text] Source

The security group IDs to be used to access a VPC-based RDS DB instance. Ensure that there are appropriate ingress rules set up to allow access to the RDS DB instance. This attribute is used by Data Pipeline to carry out the copy operation from Amazon RDS to an Amazon S3 task.

RDSDatabase

rdsDatabase Source

Creates a value of RDSDatabase with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

rdsdInstanceIdentifier :: Lens' RDSDatabase Text Source

The ID of an RDS DB instance.

RDSDatabaseCredentials

rdsDatabaseCredentials Source

Creates a value of RDSDatabaseCredentials with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

RDSMetadata

data RDSMetadata Source

The datasource details that are specific to Amazon RDS.

See: rdsMetadata smart constructor.

rdsMetadata :: RDSMetadata Source

Creates a value of RDSMetadata with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

rmSelectSqlQuery :: Lens' RDSMetadata (Maybe Text) Source

The SQL query that is supplied during CreateDataSourceFromRDS. Returns only if Verbose is true in GetDataSourceInput.

rmDataPipelineId :: Lens' RDSMetadata (Maybe Text) Source

The ID of the Data Pipeline instance that is used to carry to copy data from Amazon RDS to Amazon S3. You can use the ID to find details about the instance in the Data Pipeline console.

rmDatabase :: Lens' RDSMetadata (Maybe RDSDatabase) Source

The database details required to connect to an Amazon RDS.

rmResourceRole :: Lens' RDSMetadata (Maybe Text) Source

The role (DataPipelineDefaultResourceRole) assumed by an Amazon EC2 instance to carry out the copy task from Amazon RDS to Amazon S3. For more information, see Role templates for data pipelines.

rmServiceRole :: Lens' RDSMetadata (Maybe Text) Source

The role (DataPipelineDefaultRole) assumed by the Data Pipeline service to monitor the progress of the copy task from Amazon RDS to Amazon S3. For more information, see Role templates for data pipelines.

RealtimeEndpointInfo

realtimeEndpointInfo :: RealtimeEndpointInfo Source

Creates a value of RealtimeEndpointInfo with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

reiCreatedAt :: Lens' RealtimeEndpointInfo (Maybe UTCTime) Source

The time that the request to create the real-time endpoint for the MLModel was received. The time is expressed in epoch time.

reiEndpointURL :: Lens' RealtimeEndpointInfo (Maybe Text) Source

The URI that specifies where to send real-time prediction requests for the MLModel.

Note

The application must wait until the real-time endpoint is ready before using this URI.

reiEndpointStatus :: Lens' RealtimeEndpointInfo (Maybe RealtimeEndpointStatus) Source

The current status of the real-time endpoint for the MLModel. This element can have one of the following values:

  • NONE - Endpoint does not exist or was previously deleted.
  • READY - Endpoint is ready to be used for real-time predictions.
  • UPDATING - Updating/creating the endpoint.

reiPeakRequestsPerSecond :: Lens' RealtimeEndpointInfo (Maybe Int) Source

The maximum processing rate for the real-time endpoint for MLModel, measured in incoming requests per second.

RedshiftDataSpec

rDataSchemaURI :: Lens' RedshiftDataSpec (Maybe Text) Source

Describes the schema location for an Amazon Redshift DataSource.

rDataSchema :: Lens' RedshiftDataSpec (Maybe Text) Source

A JSON string that represents the schema for an Amazon Redshift DataSource. The DataSchema defines the structure of the observation data in the data file(s) referenced in the DataSource.

A DataSchema is not required if you specify a DataSchemaUri.

Define your DataSchema as a series of key-value pairs. attributes and excludedVariableNames have an array of key-value pairs for their value. Use the following format to define your DataSchema.

{ "version": "1.0",

"recordAnnotationFieldName": "F1",

"recordWeightFieldName": "F2",

"targetFieldName": "F3",

"dataFormat": "CSV",

"dataFileContainsHeader": true,

"attributes": [

{ "fieldName": "F1", "fieldType": "TEXT" }, { "fieldName": "F2", "fieldType": "NUMERIC" }, { "fieldName": "F3", "fieldType": "CATEGORICAL" }, { "fieldName": "F4", "fieldType": "NUMERIC" }, { "fieldName": "F5", "fieldType": "CATEGORICAL" }, { "fieldName": "F6", "fieldType": "TEXT" }, { "fieldName": "F7", "fieldType": "WEIGHTED_INT_SEQUENCE" }, { "fieldName": "F8", "fieldType": "WEIGHTED_STRING_SEQUENCE" } ],

"excludedVariableNames": [ "F6" ] }

rDataRearrangement :: Lens' RedshiftDataSpec (Maybe Text) Source

Describes the splitting specifications for a DataSource.

rDatabaseInformation :: Lens' RedshiftDataSpec RedshiftDatabase Source

Describes the DatabaseName and ClusterIdentifier for an Amazon Redshift DataSource.

rSelectSqlQuery :: Lens' RedshiftDataSpec Text Source

Describes the SQL Query to execute on an Amazon Redshift database for an Amazon Redshift DataSource.

rDatabaseCredentials :: Lens' RedshiftDataSpec RedshiftDatabaseCredentials Source

Describes AWS Identity and Access Management (IAM) credentials that are used connect to the Amazon Redshift database.

rS3StagingLocation :: Lens' RedshiftDataSpec Text Source

Describes an Amazon S3 location to store the result set of the SelectSqlQuery query.

RedshiftDatabase

redshiftDatabase Source

Creates a value of RedshiftDatabase with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

RedshiftDatabaseCredentials

redshiftDatabaseCredentials Source

Creates a value of RedshiftDatabaseCredentials with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

RedshiftMetadata

redshiftMetadata :: RedshiftMetadata Source

Creates a value of RedshiftMetadata with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

redSelectSqlQuery :: Lens' RedshiftMetadata (Maybe Text) Source

The SQL query that is specified during CreateDataSourceFromRedshift. Returns only if Verbose is true in GetDataSourceInput.

S3DataSpec

s3DataSpec Source

Creates a value of S3DataSpec with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

sdsDataSchema :: Lens' S3DataSpec (Maybe Text) Source

A JSON string that represents the schema for an Amazon S3 DataSource. The DataSchema defines the structure of the observation data in the data file(s) referenced in the DataSource.

Define your DataSchema as a series of key-value pairs. attributes and excludedVariableNames have an array of key-value pairs for their value. Use the following format to define your DataSchema.

{ "version": "1.0",

"recordAnnotationFieldName": "F1",

"recordWeightFieldName": "F2",

"targetFieldName": "F3",

"dataFormat": "CSV",

"dataFileContainsHeader": true,

"attributes": [

{ "fieldName": "F1", "fieldType": "TEXT" }, { "fieldName": "F2", "fieldType": "NUMERIC" }, { "fieldName": "F3", "fieldType": "CATEGORICAL" }, { "fieldName": "F4", "fieldType": "NUMERIC" }, { "fieldName": "F5", "fieldType": "CATEGORICAL" }, { "fieldName": "F6", "fieldType": "TEXT" }, { "fieldName": "F7", "fieldType": "WEIGHTED_INT_SEQUENCE" }, { "fieldName": "F8", "fieldType": "WEIGHTED_STRING_SEQUENCE" } ],

"excludedVariableNames": [ "F6" ] }

sdsDataSchemaLocationS3 :: Lens' S3DataSpec (Maybe Text) Source

Describes the schema Location in Amazon S3.

sdsDataRearrangement :: Lens' S3DataSpec (Maybe Text) Source

Describes the splitting requirement of a Datasource.

sdsDataLocationS3 :: Lens' S3DataSpec Text Source

The location of the data file(s) used by a DataSource. The URI specifies a data file or an Amazon Simple Storage Service (Amazon S3) directory or bucket containing data files.