Interface AmazonMachineLearningAsync
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- All Superinterfaces:
AmazonMachineLearning
- All Known Implementing Classes:
AbstractAmazonMachineLearningAsync
,AmazonMachineLearningAsyncClient
public interface AmazonMachineLearningAsync extends AmazonMachineLearning
Interface for accessing Amazon Machine Learning asynchronously. Each asynchronous method will return a Java Future object representing the asynchronous operation; overloads which accept anAsyncHandler
can be used to receive notification when an asynchronous operation completes.Definition of the public APIs exposed by Amazon Machine Learning
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Method Summary
All Methods Instance Methods Abstract Methods Modifier and Type Method Description Future<CreateBatchPredictionResult>
createBatchPredictionAsync(CreateBatchPredictionRequest createBatchPredictionRequest)
Generates predictions for a group of observations.Future<CreateBatchPredictionResult>
createBatchPredictionAsync(CreateBatchPredictionRequest createBatchPredictionRequest, AsyncHandler<CreateBatchPredictionRequest,CreateBatchPredictionResult> asyncHandler)
Generates predictions for a group of observations.Future<CreateDataSourceFromRDSResult>
createDataSourceFromRDSAsync(CreateDataSourceFromRDSRequest createDataSourceFromRDSRequest)
Creates aDataSource
object from an Amazon Relational Database Service (Amazon RDS).Future<CreateDataSourceFromRDSResult>
createDataSourceFromRDSAsync(CreateDataSourceFromRDSRequest createDataSourceFromRDSRequest, AsyncHandler<CreateDataSourceFromRDSRequest,CreateDataSourceFromRDSResult> asyncHandler)
Creates aDataSource
object from an Amazon Relational Database Service (Amazon RDS).Future<CreateDataSourceFromRedshiftResult>
createDataSourceFromRedshiftAsync(CreateDataSourceFromRedshiftRequest createDataSourceFromRedshiftRequest)
Creates aDataSource
from Amazon Redshift.Future<CreateDataSourceFromRedshiftResult>
createDataSourceFromRedshiftAsync(CreateDataSourceFromRedshiftRequest createDataSourceFromRedshiftRequest, AsyncHandler<CreateDataSourceFromRedshiftRequest,CreateDataSourceFromRedshiftResult> asyncHandler)
Creates aDataSource
from Amazon Redshift.Future<CreateDataSourceFromS3Result>
createDataSourceFromS3Async(CreateDataSourceFromS3Request createDataSourceFromS3Request)
Creates aDataSource
object.Future<CreateDataSourceFromS3Result>
createDataSourceFromS3Async(CreateDataSourceFromS3Request createDataSourceFromS3Request, AsyncHandler<CreateDataSourceFromS3Request,CreateDataSourceFromS3Result> asyncHandler)
Creates aDataSource
object.Future<CreateEvaluationResult>
createEvaluationAsync(CreateEvaluationRequest createEvaluationRequest)
Creates a newEvaluation
of anMLModel
.Future<CreateEvaluationResult>
createEvaluationAsync(CreateEvaluationRequest createEvaluationRequest, AsyncHandler<CreateEvaluationRequest,CreateEvaluationResult> asyncHandler)
Creates a newEvaluation
of anMLModel
.Future<CreateMLModelResult>
createMLModelAsync(CreateMLModelRequest createMLModelRequest)
Creates a newMLModel
using the data files and the recipe as information sources.Future<CreateMLModelResult>
createMLModelAsync(CreateMLModelRequest createMLModelRequest, AsyncHandler<CreateMLModelRequest,CreateMLModelResult> asyncHandler)
Creates a newMLModel
using the data files and the recipe as information sources.Future<CreateRealtimeEndpointResult>
createRealtimeEndpointAsync(CreateRealtimeEndpointRequest createRealtimeEndpointRequest)
Creates a real-time endpoint for theMLModel
.Future<CreateRealtimeEndpointResult>
createRealtimeEndpointAsync(CreateRealtimeEndpointRequest createRealtimeEndpointRequest, AsyncHandler<CreateRealtimeEndpointRequest,CreateRealtimeEndpointResult> asyncHandler)
Creates a real-time endpoint for theMLModel
.Future<DeleteBatchPredictionResult>
deleteBatchPredictionAsync(DeleteBatchPredictionRequest deleteBatchPredictionRequest)
Assigns the DELETED status to aBatchPrediction
, rendering it unusable.Future<DeleteBatchPredictionResult>
deleteBatchPredictionAsync(DeleteBatchPredictionRequest deleteBatchPredictionRequest, AsyncHandler<DeleteBatchPredictionRequest,DeleteBatchPredictionResult> asyncHandler)
Assigns the DELETED status to aBatchPrediction
, rendering it unusable.Future<DeleteDataSourceResult>
deleteDataSourceAsync(DeleteDataSourceRequest deleteDataSourceRequest)
Assigns the DELETED status to aDataSource
, rendering it unusable.Future<DeleteDataSourceResult>
deleteDataSourceAsync(DeleteDataSourceRequest deleteDataSourceRequest, AsyncHandler<DeleteDataSourceRequest,DeleteDataSourceResult> asyncHandler)
Assigns the DELETED status to aDataSource
, rendering it unusable.Future<DeleteEvaluationResult>
deleteEvaluationAsync(DeleteEvaluationRequest deleteEvaluationRequest)
Assigns theDELETED
status to anEvaluation
, rendering it unusable.Future<DeleteEvaluationResult>
deleteEvaluationAsync(DeleteEvaluationRequest deleteEvaluationRequest, AsyncHandler<DeleteEvaluationRequest,DeleteEvaluationResult> asyncHandler)
Assigns theDELETED
status to anEvaluation
, rendering it unusable.Future<DeleteMLModelResult>
deleteMLModelAsync(DeleteMLModelRequest deleteMLModelRequest)
Assigns the DELETED status to anMLModel
, rendering it unusable.Future<DeleteMLModelResult>
deleteMLModelAsync(DeleteMLModelRequest deleteMLModelRequest, AsyncHandler<DeleteMLModelRequest,DeleteMLModelResult> asyncHandler)
Assigns the DELETED status to anMLModel
, rendering it unusable.Future<DeleteRealtimeEndpointResult>
deleteRealtimeEndpointAsync(DeleteRealtimeEndpointRequest deleteRealtimeEndpointRequest)
Deletes a real time endpoint of anMLModel
.Future<DeleteRealtimeEndpointResult>
deleteRealtimeEndpointAsync(DeleteRealtimeEndpointRequest deleteRealtimeEndpointRequest, AsyncHandler<DeleteRealtimeEndpointRequest,DeleteRealtimeEndpointResult> asyncHandler)
Deletes a real time endpoint of anMLModel
.Future<DescribeBatchPredictionsResult>
describeBatchPredictionsAsync()
Simplified method form for invoking the DescribeBatchPredictions operation.Future<DescribeBatchPredictionsResult>
describeBatchPredictionsAsync(AsyncHandler<DescribeBatchPredictionsRequest,DescribeBatchPredictionsResult> asyncHandler)
Simplified method form for invoking the DescribeBatchPredictions operation with an AsyncHandler.Future<DescribeBatchPredictionsResult>
describeBatchPredictionsAsync(DescribeBatchPredictionsRequest describeBatchPredictionsRequest)
Returns a list ofBatchPrediction
operations that match the search criteria in the request.Future<DescribeBatchPredictionsResult>
describeBatchPredictionsAsync(DescribeBatchPredictionsRequest describeBatchPredictionsRequest, AsyncHandler<DescribeBatchPredictionsRequest,DescribeBatchPredictionsResult> asyncHandler)
Returns a list ofBatchPrediction
operations that match the search criteria in the request.Future<DescribeDataSourcesResult>
describeDataSourcesAsync()
Simplified method form for invoking the DescribeDataSources operation.Future<DescribeDataSourcesResult>
describeDataSourcesAsync(AsyncHandler<DescribeDataSourcesRequest,DescribeDataSourcesResult> asyncHandler)
Simplified method form for invoking the DescribeDataSources operation with an AsyncHandler.Future<DescribeDataSourcesResult>
describeDataSourcesAsync(DescribeDataSourcesRequest describeDataSourcesRequest)
Returns a list ofDataSource
that match the search criteria in the request.Future<DescribeDataSourcesResult>
describeDataSourcesAsync(DescribeDataSourcesRequest describeDataSourcesRequest, AsyncHandler<DescribeDataSourcesRequest,DescribeDataSourcesResult> asyncHandler)
Returns a list ofDataSource
that match the search criteria in the request.Future<DescribeEvaluationsResult>
describeEvaluationsAsync()
Simplified method form for invoking the DescribeEvaluations operation.Future<DescribeEvaluationsResult>
describeEvaluationsAsync(AsyncHandler<DescribeEvaluationsRequest,DescribeEvaluationsResult> asyncHandler)
Simplified method form for invoking the DescribeEvaluations operation with an AsyncHandler.Future<DescribeEvaluationsResult>
describeEvaluationsAsync(DescribeEvaluationsRequest describeEvaluationsRequest)
Returns a list ofDescribeEvaluations
that match the search criteria in the request.Future<DescribeEvaluationsResult>
describeEvaluationsAsync(DescribeEvaluationsRequest describeEvaluationsRequest, AsyncHandler<DescribeEvaluationsRequest,DescribeEvaluationsResult> asyncHandler)
Returns a list ofDescribeEvaluations
that match the search criteria in the request.Future<DescribeMLModelsResult>
describeMLModelsAsync()
Simplified method form for invoking the DescribeMLModels operation.Future<DescribeMLModelsResult>
describeMLModelsAsync(AsyncHandler<DescribeMLModelsRequest,DescribeMLModelsResult> asyncHandler)
Simplified method form for invoking the DescribeMLModels operation with an AsyncHandler.Future<DescribeMLModelsResult>
describeMLModelsAsync(DescribeMLModelsRequest describeMLModelsRequest)
Returns a list ofMLModel
that match the search criteria in the request.Future<DescribeMLModelsResult>
describeMLModelsAsync(DescribeMLModelsRequest describeMLModelsRequest, AsyncHandler<DescribeMLModelsRequest,DescribeMLModelsResult> asyncHandler)
Returns a list ofMLModel
that match the search criteria in the request.Future<GetBatchPredictionResult>
getBatchPredictionAsync(GetBatchPredictionRequest getBatchPredictionRequest)
Returns aBatchPrediction
that includes detailed metadata, status, and data file information for aBatch Prediction
request.Future<GetBatchPredictionResult>
getBatchPredictionAsync(GetBatchPredictionRequest getBatchPredictionRequest, AsyncHandler<GetBatchPredictionRequest,GetBatchPredictionResult> asyncHandler)
Returns aBatchPrediction
that includes detailed metadata, status, and data file information for aBatch Prediction
request.Future<GetDataSourceResult>
getDataSourceAsync(GetDataSourceRequest getDataSourceRequest)
Returns aDataSource
that includes metadata and data file information, as well as the current status of theDataSource
.Future<GetDataSourceResult>
getDataSourceAsync(GetDataSourceRequest getDataSourceRequest, AsyncHandler<GetDataSourceRequest,GetDataSourceResult> asyncHandler)
Returns aDataSource
that includes metadata and data file information, as well as the current status of theDataSource
.Future<GetEvaluationResult>
getEvaluationAsync(GetEvaluationRequest getEvaluationRequest)
Returns anEvaluation
that includes metadata as well as the current status of theEvaluation
.Future<GetEvaluationResult>
getEvaluationAsync(GetEvaluationRequest getEvaluationRequest, AsyncHandler<GetEvaluationRequest,GetEvaluationResult> asyncHandler)
Returns anEvaluation
that includes metadata as well as the current status of theEvaluation
.Future<GetMLModelResult>
getMLModelAsync(GetMLModelRequest getMLModelRequest)
Returns anMLModel
that includes detailed metadata, and data source information as well as the current status of theMLModel
.Future<GetMLModelResult>
getMLModelAsync(GetMLModelRequest getMLModelRequest, AsyncHandler<GetMLModelRequest,GetMLModelResult> asyncHandler)
Returns anMLModel
that includes detailed metadata, and data source information as well as the current status of theMLModel
.Future<PredictResult>
predictAsync(PredictRequest predictRequest)
Generates a prediction for the observation using the specifiedML Model
.Future<PredictResult>
predictAsync(PredictRequest predictRequest, AsyncHandler<PredictRequest,PredictResult> asyncHandler)
Generates a prediction for the observation using the specifiedML Model
.Future<UpdateBatchPredictionResult>
updateBatchPredictionAsync(UpdateBatchPredictionRequest updateBatchPredictionRequest)
Updates theBatchPredictionName
of aBatchPrediction
.Future<UpdateBatchPredictionResult>
updateBatchPredictionAsync(UpdateBatchPredictionRequest updateBatchPredictionRequest, AsyncHandler<UpdateBatchPredictionRequest,UpdateBatchPredictionResult> asyncHandler)
Updates theBatchPredictionName
of aBatchPrediction
.Future<UpdateDataSourceResult>
updateDataSourceAsync(UpdateDataSourceRequest updateDataSourceRequest)
Updates theDataSourceName
of aDataSource
.Future<UpdateDataSourceResult>
updateDataSourceAsync(UpdateDataSourceRequest updateDataSourceRequest, AsyncHandler<UpdateDataSourceRequest,UpdateDataSourceResult> asyncHandler)
Updates theDataSourceName
of aDataSource
.Future<UpdateEvaluationResult>
updateEvaluationAsync(UpdateEvaluationRequest updateEvaluationRequest)
Updates theEvaluationName
of anEvaluation
.Future<UpdateEvaluationResult>
updateEvaluationAsync(UpdateEvaluationRequest updateEvaluationRequest, AsyncHandler<UpdateEvaluationRequest,UpdateEvaluationResult> asyncHandler)
Updates theEvaluationName
of anEvaluation
.Future<UpdateMLModelResult>
updateMLModelAsync(UpdateMLModelRequest updateMLModelRequest)
Updates theMLModelName
and theScoreThreshold
of anMLModel
.Future<UpdateMLModelResult>
updateMLModelAsync(UpdateMLModelRequest updateMLModelRequest, AsyncHandler<UpdateMLModelRequest,UpdateMLModelResult> asyncHandler)
Updates theMLModelName
and theScoreThreshold
of anMLModel
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Methods inherited from interface com.amazonaws.services.machinelearning.AmazonMachineLearning
createBatchPrediction, createDataSourceFromRDS, createDataSourceFromRedshift, createDataSourceFromS3, createEvaluation, createMLModel, createRealtimeEndpoint, deleteBatchPrediction, deleteDataSource, deleteEvaluation, deleteMLModel, deleteRealtimeEndpoint, describeBatchPredictions, describeBatchPredictions, describeDataSources, describeDataSources, describeEvaluations, describeEvaluations, describeMLModels, describeMLModels, getBatchPrediction, getCachedResponseMetadata, getDataSource, getEvaluation, getMLModel, predict, setEndpoint, setRegion, shutdown, updateBatchPrediction, updateDataSource, updateEvaluation, updateMLModel
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Method Detail
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createBatchPredictionAsync
Future<CreateBatchPredictionResult> createBatchPredictionAsync(CreateBatchPredictionRequest createBatchPredictionRequest)
Generates predictions for a group of observations. The observations to process exist in one or more data files referenced by a
DataSource
. This operation creates a newBatchPrediction
, and uses anMLModel
and the data files referenced by theDataSource
as information sources.CreateBatchPrediction
is an asynchronous operation. In response toCreateBatchPrediction
, Amazon Machine Learning (Amazon ML) immediately returns and sets theBatchPrediction
status toPENDING
. After theBatchPrediction
completes, Amazon ML sets the status toCOMPLETED
.You can poll for status updates by using the GetBatchPrediction operation and checking the
Status
parameter of the result. After theCOMPLETED
status appears, the results are available in the location specified by theOutputUri
parameter.- Parameters:
createBatchPredictionRequest
-- Returns:
- A Java Future containing the result of the CreateBatchPrediction operation returned by the service.
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createBatchPredictionAsync
Future<CreateBatchPredictionResult> createBatchPredictionAsync(CreateBatchPredictionRequest createBatchPredictionRequest, AsyncHandler<CreateBatchPredictionRequest,CreateBatchPredictionResult> asyncHandler)
Generates predictions for a group of observations. The observations to process exist in one or more data files referenced by a
DataSource
. This operation creates a newBatchPrediction
, and uses anMLModel
and the data files referenced by theDataSource
as information sources.CreateBatchPrediction
is an asynchronous operation. In response toCreateBatchPrediction
, Amazon Machine Learning (Amazon ML) immediately returns and sets theBatchPrediction
status toPENDING
. After theBatchPrediction
completes, Amazon ML sets the status toCOMPLETED
.You can poll for status updates by using the GetBatchPrediction operation and checking the
Status
parameter of the result. After theCOMPLETED
status appears, the results are available in the location specified by theOutputUri
parameter.- Parameters:
createBatchPredictionRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the CreateBatchPrediction operation returned by the service.
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createDataSourceFromRDSAsync
Future<CreateDataSourceFromRDSResult> createDataSourceFromRDSAsync(CreateDataSourceFromRDSRequest createDataSourceFromRDSRequest)
Creates a
DataSource
object from an Amazon Relational Database Service (Amazon RDS). ADataSource
references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.CreateDataSourceFromRDS
is an asynchronous operation. In response toCreateDataSourceFromRDS
, Amazon Machine Learning (Amazon ML) immediately returns and sets theDataSource
status toPENDING
. After theDataSource
is created and ready for use, Amazon ML sets theStatus
parameter toCOMPLETED
.DataSource
inCOMPLETED
orPENDING
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 toFAILED
and includes an error message in theMessage
attribute of the GetDataSource operation response.- Parameters:
createDataSourceFromRDSRequest
-- Returns:
- A Java Future containing the result of the CreateDataSourceFromRDS operation returned by the service.
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createDataSourceFromRDSAsync
Future<CreateDataSourceFromRDSResult> createDataSourceFromRDSAsync(CreateDataSourceFromRDSRequest createDataSourceFromRDSRequest, AsyncHandler<CreateDataSourceFromRDSRequest,CreateDataSourceFromRDSResult> asyncHandler)
Creates a
DataSource
object from an Amazon Relational Database Service (Amazon RDS). ADataSource
references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.CreateDataSourceFromRDS
is an asynchronous operation. In response toCreateDataSourceFromRDS
, Amazon Machine Learning (Amazon ML) immediately returns and sets theDataSource
status toPENDING
. After theDataSource
is created and ready for use, Amazon ML sets theStatus
parameter toCOMPLETED
.DataSource
inCOMPLETED
orPENDING
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 toFAILED
and includes an error message in theMessage
attribute of the GetDataSource operation response.- Parameters:
createDataSourceFromRDSRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the CreateDataSourceFromRDS operation returned by the service.
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createDataSourceFromRedshiftAsync
Future<CreateDataSourceFromRedshiftResult> createDataSourceFromRedshiftAsync(CreateDataSourceFromRedshiftRequest createDataSourceFromRedshiftRequest)
Creates a
DataSource
from Amazon Redshift. ADataSource
references data that can be used to perform either CreateMLModel, CreateEvaluation or CreateBatchPrediction operations.CreateDataSourceFromRedshift
is an asynchronous operation. In response toCreateDataSourceFromRedshift
, Amazon Machine Learning (Amazon ML) immediately returns and sets theDataSource
status toPENDING
. After theDataSource
is created and ready for use, Amazon ML sets theStatus
parameter toCOMPLETED
.DataSource
inCOMPLETED
orPENDING
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 toFAILED
and includes an error message in theMessage
attribute of the GetDataSource operation response.The observations should exist in the database hosted on an Amazon Redshift cluster and should be specified by a
SelectSqlQuery
. Amazon ML executes Unload command in Amazon Redshift to transfer the result set ofSelectSqlQuery
toS3StagingLocation.
After the
DataSource
is created, it's ready for use in evaluations and batch predictions. If you plan to use theDataSource
to train anMLModel
, theDataSource
requires another item -- a recipe. A recipe describes the observation variables that participate in training anMLModel
. 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.- Parameters:
createDataSourceFromRedshiftRequest
-- Returns:
- A Java Future containing the result of the CreateDataSourceFromRedshift operation returned by the service.
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createDataSourceFromRedshiftAsync
Future<CreateDataSourceFromRedshiftResult> createDataSourceFromRedshiftAsync(CreateDataSourceFromRedshiftRequest createDataSourceFromRedshiftRequest, AsyncHandler<CreateDataSourceFromRedshiftRequest,CreateDataSourceFromRedshiftResult> asyncHandler)
Creates a
DataSource
from Amazon Redshift. ADataSource
references data that can be used to perform either CreateMLModel, CreateEvaluation or CreateBatchPrediction operations.CreateDataSourceFromRedshift
is an asynchronous operation. In response toCreateDataSourceFromRedshift
, Amazon Machine Learning (Amazon ML) immediately returns and sets theDataSource
status toPENDING
. After theDataSource
is created and ready for use, Amazon ML sets theStatus
parameter toCOMPLETED
.DataSource
inCOMPLETED
orPENDING
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 toFAILED
and includes an error message in theMessage
attribute of the GetDataSource operation response.The observations should exist in the database hosted on an Amazon Redshift cluster and should be specified by a
SelectSqlQuery
. Amazon ML executes Unload command in Amazon Redshift to transfer the result set ofSelectSqlQuery
toS3StagingLocation.
After the
DataSource
is created, it's ready for use in evaluations and batch predictions. If you plan to use theDataSource
to train anMLModel
, theDataSource
requires another item -- a recipe. A recipe describes the observation variables that participate in training anMLModel
. 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.- Parameters:
createDataSourceFromRedshiftRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the CreateDataSourceFromRedshift operation returned by the service.
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createDataSourceFromS3Async
Future<CreateDataSourceFromS3Result> createDataSourceFromS3Async(CreateDataSourceFromS3Request createDataSourceFromS3Request)
Creates a
DataSource
object. ADataSource
references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.CreateDataSourceFromS3
is an asynchronous operation. In response toCreateDataSourceFromS3
, Amazon Machine Learning (Amazon ML) immediately returns and sets theDataSource
status toPENDING
. After theDataSource
is created and ready for use, Amazon ML sets theStatus
parameter toCOMPLETED
.DataSource
inCOMPLETED
orPENDING
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 toFAILED
and includes an error message in theMessage
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 theDataSource
.After the
DataSource
has been created, it's ready to use in evaluations and batch predictions. If you plan to use theDataSource
to train anMLModel
, theDataSource
requires another item: a recipe. A recipe describes the observation variables that participate in training anMLModel
. 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.- Parameters:
createDataSourceFromS3Request
-- Returns:
- A Java Future containing the result of the CreateDataSourceFromS3 operation returned by the service.
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createDataSourceFromS3Async
Future<CreateDataSourceFromS3Result> createDataSourceFromS3Async(CreateDataSourceFromS3Request createDataSourceFromS3Request, AsyncHandler<CreateDataSourceFromS3Request,CreateDataSourceFromS3Result> asyncHandler)
Creates a
DataSource
object. ADataSource
references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.CreateDataSourceFromS3
is an asynchronous operation. In response toCreateDataSourceFromS3
, Amazon Machine Learning (Amazon ML) immediately returns and sets theDataSource
status toPENDING
. After theDataSource
is created and ready for use, Amazon ML sets theStatus
parameter toCOMPLETED
.DataSource
inCOMPLETED
orPENDING
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 toFAILED
and includes an error message in theMessage
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 theDataSource
.After the
DataSource
has been created, it's ready to use in evaluations and batch predictions. If you plan to use theDataSource
to train anMLModel
, theDataSource
requires another item: a recipe. A recipe describes the observation variables that participate in training anMLModel
. 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.- Parameters:
createDataSourceFromS3Request
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the CreateDataSourceFromS3 operation returned by the service.
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createEvaluationAsync
Future<CreateEvaluationResult> createEvaluationAsync(CreateEvaluationRequest createEvaluationRequest)
Creates a new
Evaluation
of anMLModel
. AnMLModel
is evaluated on a set of observations associated to aDataSource
. Like aDataSource
for anMLModel
, theDataSource
for anEvaluation
contains values for the Target Variable. TheEvaluation
compares the predicted result for each observation to the actual outcome and provides a summary so that you know how effective theMLModel
functions on the test data. Evaluation generates a relevant performance metric such as BinaryAUC, RegressionRMSE or MulticlassAvgFScore based on the correspondingMLModelType
:BINARY
,REGRESSION
orMULTICLASS
.CreateEvaluation
is an asynchronous operation. In response toCreateEvaluation
, Amazon Machine Learning (Amazon ML) immediately returns and sets the evaluation status toPENDING
. After theEvaluation
is created and ready for use, Amazon ML sets the status toCOMPLETED
.You can use the GetEvaluation operation to check progress of the evaluation during the creation operation.
- Parameters:
createEvaluationRequest
-- Returns:
- A Java Future containing the result of the CreateEvaluation operation returned by the service.
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createEvaluationAsync
Future<CreateEvaluationResult> createEvaluationAsync(CreateEvaluationRequest createEvaluationRequest, AsyncHandler<CreateEvaluationRequest,CreateEvaluationResult> asyncHandler)
Creates a new
Evaluation
of anMLModel
. AnMLModel
is evaluated on a set of observations associated to aDataSource
. Like aDataSource
for anMLModel
, theDataSource
for anEvaluation
contains values for the Target Variable. TheEvaluation
compares the predicted result for each observation to the actual outcome and provides a summary so that you know how effective theMLModel
functions on the test data. Evaluation generates a relevant performance metric such as BinaryAUC, RegressionRMSE or MulticlassAvgFScore based on the correspondingMLModelType
:BINARY
,REGRESSION
orMULTICLASS
.CreateEvaluation
is an asynchronous operation. In response toCreateEvaluation
, Amazon Machine Learning (Amazon ML) immediately returns and sets the evaluation status toPENDING
. After theEvaluation
is created and ready for use, Amazon ML sets the status toCOMPLETED
.You can use the GetEvaluation operation to check progress of the evaluation during the creation operation.
- Parameters:
createEvaluationRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the CreateEvaluation operation returned by the service.
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createMLModelAsync
Future<CreateMLModelResult> createMLModelAsync(CreateMLModelRequest createMLModelRequest)
Creates a new
MLModel
using the data files and the recipe as information sources.An
MLModel
is nearly immutable. Users can only update theMLModelName
and theScoreThreshold
in anMLModel
without creating a newMLModel
.CreateMLModel
is an asynchronous operation. In response toCreateMLModel
, Amazon Machine Learning (Amazon ML) immediately returns and sets theMLModel
status toPENDING
. After theMLModel
is created and ready for use, Amazon ML sets the status toCOMPLETED
.You can use the GetMLModel operation to check progress of the
MLModel
during the creation operation.CreateMLModel requires a
DataSource
with computed statistics, which can be created by settingComputeStatistics
totrue
in CreateDataSourceFromRDS, CreateDataSourceFromS3, or CreateDataSourceFromRedshift operations.- Parameters:
createMLModelRequest
-- Returns:
- A Java Future containing the result of the CreateMLModel operation returned by the service.
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createMLModelAsync
Future<CreateMLModelResult> createMLModelAsync(CreateMLModelRequest createMLModelRequest, AsyncHandler<CreateMLModelRequest,CreateMLModelResult> asyncHandler)
Creates a new
MLModel
using the data files and the recipe as information sources.An
MLModel
is nearly immutable. Users can only update theMLModelName
and theScoreThreshold
in anMLModel
without creating a newMLModel
.CreateMLModel
is an asynchronous operation. In response toCreateMLModel
, Amazon Machine Learning (Amazon ML) immediately returns and sets theMLModel
status toPENDING
. After theMLModel
is created and ready for use, Amazon ML sets the status toCOMPLETED
.You can use the GetMLModel operation to check progress of the
MLModel
during the creation operation.CreateMLModel requires a
DataSource
with computed statistics, which can be created by settingComputeStatistics
totrue
in CreateDataSourceFromRDS, CreateDataSourceFromS3, or CreateDataSourceFromRedshift operations.- Parameters:
createMLModelRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the CreateMLModel operation returned by the service.
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createRealtimeEndpointAsync
Future<CreateRealtimeEndpointResult> createRealtimeEndpointAsync(CreateRealtimeEndpointRequest createRealtimeEndpointRequest)
Creates a real-time endpoint for the
MLModel
. The endpoint contains the URI of theMLModel
; that is, the location to send real-time prediction requests for the specifiedMLModel
.- Parameters:
createRealtimeEndpointRequest
-- Returns:
- A Java Future containing the result of the CreateRealtimeEndpoint operation returned by the service.
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createRealtimeEndpointAsync
Future<CreateRealtimeEndpointResult> createRealtimeEndpointAsync(CreateRealtimeEndpointRequest createRealtimeEndpointRequest, AsyncHandler<CreateRealtimeEndpointRequest,CreateRealtimeEndpointResult> asyncHandler)
Creates a real-time endpoint for the
MLModel
. The endpoint contains the URI of theMLModel
; that is, the location to send real-time prediction requests for the specifiedMLModel
.- Parameters:
createRealtimeEndpointRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the CreateRealtimeEndpoint operation returned by the service.
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deleteBatchPredictionAsync
Future<DeleteBatchPredictionResult> deleteBatchPredictionAsync(DeleteBatchPredictionRequest deleteBatchPredictionRequest)
Assigns the DELETED status to a
BatchPrediction
, rendering it unusable.After using the
DeleteBatchPrediction
operation, you can use the GetBatchPrediction operation to verify that the status of theBatchPrediction
changed to DELETED.Caution: The result of the
DeleteBatchPrediction
operation is irreversible.- Parameters:
deleteBatchPredictionRequest
-- Returns:
- A Java Future containing the result of the DeleteBatchPrediction operation returned by the service.
-
deleteBatchPredictionAsync
Future<DeleteBatchPredictionResult> deleteBatchPredictionAsync(DeleteBatchPredictionRequest deleteBatchPredictionRequest, AsyncHandler<DeleteBatchPredictionRequest,DeleteBatchPredictionResult> asyncHandler)
Assigns the DELETED status to a
BatchPrediction
, rendering it unusable.After using the
DeleteBatchPrediction
operation, you can use the GetBatchPrediction operation to verify that the status of theBatchPrediction
changed to DELETED.Caution: The result of the
DeleteBatchPrediction
operation is irreversible.- Parameters:
deleteBatchPredictionRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the DeleteBatchPrediction operation returned by the service.
-
deleteDataSourceAsync
Future<DeleteDataSourceResult> deleteDataSourceAsync(DeleteDataSourceRequest deleteDataSourceRequest)
Assigns the DELETED status to a
DataSource
, rendering it unusable.After using the
DeleteDataSource
operation, you can use the GetDataSource operation to verify that the status of theDataSource
changed to DELETED.Caution: The results of the
DeleteDataSource
operation are irreversible.- Parameters:
deleteDataSourceRequest
-- Returns:
- A Java Future containing the result of the DeleteDataSource operation returned by the service.
-
deleteDataSourceAsync
Future<DeleteDataSourceResult> deleteDataSourceAsync(DeleteDataSourceRequest deleteDataSourceRequest, AsyncHandler<DeleteDataSourceRequest,DeleteDataSourceResult> asyncHandler)
Assigns the DELETED status to a
DataSource
, rendering it unusable.After using the
DeleteDataSource
operation, you can use the GetDataSource operation to verify that the status of theDataSource
changed to DELETED.Caution: The results of the
DeleteDataSource
operation are irreversible.- Parameters:
deleteDataSourceRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the DeleteDataSource operation returned by the service.
-
deleteEvaluationAsync
Future<DeleteEvaluationResult> deleteEvaluationAsync(DeleteEvaluationRequest deleteEvaluationRequest)
Assigns the
DELETED
status to anEvaluation
, rendering it unusable.After invoking the
DeleteEvaluation
operation, you can use the GetEvaluation operation to verify that the status of theEvaluation
changed toDELETED
.Caution: The results of the
DeleteEvaluation
operation are irreversible.- Parameters:
deleteEvaluationRequest
-- Returns:
- A Java Future containing the result of the DeleteEvaluation operation returned by the service.
-
deleteEvaluationAsync
Future<DeleteEvaluationResult> deleteEvaluationAsync(DeleteEvaluationRequest deleteEvaluationRequest, AsyncHandler<DeleteEvaluationRequest,DeleteEvaluationResult> asyncHandler)
Assigns the
DELETED
status to anEvaluation
, rendering it unusable.After invoking the
DeleteEvaluation
operation, you can use the GetEvaluation operation to verify that the status of theEvaluation
changed toDELETED
.Caution: The results of the
DeleteEvaluation
operation are irreversible.- Parameters:
deleteEvaluationRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the DeleteEvaluation operation returned by the service.
-
deleteMLModelAsync
Future<DeleteMLModelResult> deleteMLModelAsync(DeleteMLModelRequest deleteMLModelRequest)
Assigns the DELETED status to an
MLModel
, rendering it unusable.After using the
DeleteMLModel
operation, you can use the GetMLModel operation to verify that the status of theMLModel
changed to DELETED.Caution: The result of the
DeleteMLModel
operation is irreversible.- Parameters:
deleteMLModelRequest
-- Returns:
- A Java Future containing the result of the DeleteMLModel operation returned by the service.
-
deleteMLModelAsync
Future<DeleteMLModelResult> deleteMLModelAsync(DeleteMLModelRequest deleteMLModelRequest, AsyncHandler<DeleteMLModelRequest,DeleteMLModelResult> asyncHandler)
Assigns the DELETED status to an
MLModel
, rendering it unusable.After using the
DeleteMLModel
operation, you can use the GetMLModel operation to verify that the status of theMLModel
changed to DELETED.Caution: The result of the
DeleteMLModel
operation is irreversible.- Parameters:
deleteMLModelRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the DeleteMLModel operation returned by the service.
-
deleteRealtimeEndpointAsync
Future<DeleteRealtimeEndpointResult> deleteRealtimeEndpointAsync(DeleteRealtimeEndpointRequest deleteRealtimeEndpointRequest)
Deletes a real time endpoint of an
MLModel
.- Parameters:
deleteRealtimeEndpointRequest
-- Returns:
- A Java Future containing the result of the DeleteRealtimeEndpoint operation returned by the service.
-
deleteRealtimeEndpointAsync
Future<DeleteRealtimeEndpointResult> deleteRealtimeEndpointAsync(DeleteRealtimeEndpointRequest deleteRealtimeEndpointRequest, AsyncHandler<DeleteRealtimeEndpointRequest,DeleteRealtimeEndpointResult> asyncHandler)
Deletes a real time endpoint of an
MLModel
.- Parameters:
deleteRealtimeEndpointRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the DeleteRealtimeEndpoint operation returned by the service.
-
describeBatchPredictionsAsync
Future<DescribeBatchPredictionsResult> describeBatchPredictionsAsync(DescribeBatchPredictionsRequest describeBatchPredictionsRequest)
Returns a list of
BatchPrediction
operations that match the search criteria in the request.- Parameters:
describeBatchPredictionsRequest
-- Returns:
- A Java Future containing the result of the DescribeBatchPredictions operation returned by the service.
-
describeBatchPredictionsAsync
Future<DescribeBatchPredictionsResult> describeBatchPredictionsAsync(DescribeBatchPredictionsRequest describeBatchPredictionsRequest, AsyncHandler<DescribeBatchPredictionsRequest,DescribeBatchPredictionsResult> asyncHandler)
Returns a list of
BatchPrediction
operations that match the search criteria in the request.- Parameters:
describeBatchPredictionsRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the DescribeBatchPredictions operation returned by the service.
-
describeBatchPredictionsAsync
Future<DescribeBatchPredictionsResult> describeBatchPredictionsAsync()
Simplified method form for invoking the DescribeBatchPredictions operation.
-
describeBatchPredictionsAsync
Future<DescribeBatchPredictionsResult> describeBatchPredictionsAsync(AsyncHandler<DescribeBatchPredictionsRequest,DescribeBatchPredictionsResult> asyncHandler)
Simplified method form for invoking the DescribeBatchPredictions operation with an AsyncHandler.
-
describeDataSourcesAsync
Future<DescribeDataSourcesResult> describeDataSourcesAsync(DescribeDataSourcesRequest describeDataSourcesRequest)
Returns a list of
DataSource
that match the search criteria in the request.- Parameters:
describeDataSourcesRequest
-- Returns:
- A Java Future containing the result of the DescribeDataSources operation returned by the service.
-
describeDataSourcesAsync
Future<DescribeDataSourcesResult> describeDataSourcesAsync(DescribeDataSourcesRequest describeDataSourcesRequest, AsyncHandler<DescribeDataSourcesRequest,DescribeDataSourcesResult> asyncHandler)
Returns a list of
DataSource
that match the search criteria in the request.- Parameters:
describeDataSourcesRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the DescribeDataSources operation returned by the service.
-
describeDataSourcesAsync
Future<DescribeDataSourcesResult> describeDataSourcesAsync()
Simplified method form for invoking the DescribeDataSources operation.
-
describeDataSourcesAsync
Future<DescribeDataSourcesResult> describeDataSourcesAsync(AsyncHandler<DescribeDataSourcesRequest,DescribeDataSourcesResult> asyncHandler)
Simplified method form for invoking the DescribeDataSources operation with an AsyncHandler.
-
describeEvaluationsAsync
Future<DescribeEvaluationsResult> describeEvaluationsAsync(DescribeEvaluationsRequest describeEvaluationsRequest)
Returns a list of
DescribeEvaluations
that match the search criteria in the request.- Parameters:
describeEvaluationsRequest
-- Returns:
- A Java Future containing the result of the DescribeEvaluations operation returned by the service.
-
describeEvaluationsAsync
Future<DescribeEvaluationsResult> describeEvaluationsAsync(DescribeEvaluationsRequest describeEvaluationsRequest, AsyncHandler<DescribeEvaluationsRequest,DescribeEvaluationsResult> asyncHandler)
Returns a list of
DescribeEvaluations
that match the search criteria in the request.- Parameters:
describeEvaluationsRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the DescribeEvaluations operation returned by the service.
-
describeEvaluationsAsync
Future<DescribeEvaluationsResult> describeEvaluationsAsync()
Simplified method form for invoking the DescribeEvaluations operation.
-
describeEvaluationsAsync
Future<DescribeEvaluationsResult> describeEvaluationsAsync(AsyncHandler<DescribeEvaluationsRequest,DescribeEvaluationsResult> asyncHandler)
Simplified method form for invoking the DescribeEvaluations operation with an AsyncHandler.
-
describeMLModelsAsync
Future<DescribeMLModelsResult> describeMLModelsAsync(DescribeMLModelsRequest describeMLModelsRequest)
Returns a list of
MLModel
that match the search criteria in the request.- Parameters:
describeMLModelsRequest
-- Returns:
- A Java Future containing the result of the DescribeMLModels operation returned by the service.
-
describeMLModelsAsync
Future<DescribeMLModelsResult> describeMLModelsAsync(DescribeMLModelsRequest describeMLModelsRequest, AsyncHandler<DescribeMLModelsRequest,DescribeMLModelsResult> asyncHandler)
Returns a list of
MLModel
that match the search criteria in the request.- Parameters:
describeMLModelsRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the DescribeMLModels operation returned by the service.
-
describeMLModelsAsync
Future<DescribeMLModelsResult> describeMLModelsAsync()
Simplified method form for invoking the DescribeMLModels operation.
-
describeMLModelsAsync
Future<DescribeMLModelsResult> describeMLModelsAsync(AsyncHandler<DescribeMLModelsRequest,DescribeMLModelsResult> asyncHandler)
Simplified method form for invoking the DescribeMLModels operation with an AsyncHandler.
-
getBatchPredictionAsync
Future<GetBatchPredictionResult> getBatchPredictionAsync(GetBatchPredictionRequest getBatchPredictionRequest)
Returns a
BatchPrediction
that includes detailed metadata, status, and data file information for aBatch Prediction
request.- Parameters:
getBatchPredictionRequest
-- Returns:
- A Java Future containing the result of the GetBatchPrediction operation returned by the service.
-
getBatchPredictionAsync
Future<GetBatchPredictionResult> getBatchPredictionAsync(GetBatchPredictionRequest getBatchPredictionRequest, AsyncHandler<GetBatchPredictionRequest,GetBatchPredictionResult> asyncHandler)
Returns a
BatchPrediction
that includes detailed metadata, status, and data file information for aBatch Prediction
request.- Parameters:
getBatchPredictionRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the GetBatchPrediction operation returned by the service.
-
getDataSourceAsync
Future<GetDataSourceResult> getDataSourceAsync(GetDataSourceRequest getDataSourceRequest)
Returns a
DataSource
that includes metadata and data file information, as well as the current status of theDataSource
.GetDataSource
provides results in normal or verbose format. The verbose format adds the schema description and the list of files pointed to by the DataSource to the normal format.- Parameters:
getDataSourceRequest
-- Returns:
- A Java Future containing the result of the GetDataSource operation returned by the service.
-
getDataSourceAsync
Future<GetDataSourceResult> getDataSourceAsync(GetDataSourceRequest getDataSourceRequest, AsyncHandler<GetDataSourceRequest,GetDataSourceResult> asyncHandler)
Returns a
DataSource
that includes metadata and data file information, as well as the current status of theDataSource
.GetDataSource
provides results in normal or verbose format. The verbose format adds the schema description and the list of files pointed to by the DataSource to the normal format.- Parameters:
getDataSourceRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the GetDataSource operation returned by the service.
-
getEvaluationAsync
Future<GetEvaluationResult> getEvaluationAsync(GetEvaluationRequest getEvaluationRequest)
Returns an
Evaluation
that includes metadata as well as the current status of theEvaluation
.- Parameters:
getEvaluationRequest
-- Returns:
- A Java Future containing the result of the GetEvaluation operation returned by the service.
-
getEvaluationAsync
Future<GetEvaluationResult> getEvaluationAsync(GetEvaluationRequest getEvaluationRequest, AsyncHandler<GetEvaluationRequest,GetEvaluationResult> asyncHandler)
Returns an
Evaluation
that includes metadata as well as the current status of theEvaluation
.- Parameters:
getEvaluationRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the GetEvaluation operation returned by the service.
-
getMLModelAsync
Future<GetMLModelResult> getMLModelAsync(GetMLModelRequest getMLModelRequest)
Returns an
MLModel
that includes detailed metadata, and data source information as well as the current status of theMLModel
.GetMLModel
provides results in normal or verbose format.- Parameters:
getMLModelRequest
-- Returns:
- A Java Future containing the result of the GetMLModel operation returned by the service.
-
getMLModelAsync
Future<GetMLModelResult> getMLModelAsync(GetMLModelRequest getMLModelRequest, AsyncHandler<GetMLModelRequest,GetMLModelResult> asyncHandler)
Returns an
MLModel
that includes detailed metadata, and data source information as well as the current status of theMLModel
.GetMLModel
provides results in normal or verbose format.- Parameters:
getMLModelRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the GetMLModel operation returned by the service.
-
predictAsync
Future<PredictResult> predictAsync(PredictRequest predictRequest)
Generates a prediction for the observation using the specified
ML Model
.Note Not all response parameters will be populated. Whether a response parameter is populated depends on the type of model requested.
- Parameters:
predictRequest
-- Returns:
- A Java Future containing the result of the Predict operation returned by the service.
-
predictAsync
Future<PredictResult> predictAsync(PredictRequest predictRequest, AsyncHandler<PredictRequest,PredictResult> asyncHandler)
Generates a prediction for the observation using the specified
ML Model
.Note Not all response parameters will be populated. Whether a response parameter is populated depends on the type of model requested.
- Parameters:
predictRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the Predict operation returned by the service.
-
updateBatchPredictionAsync
Future<UpdateBatchPredictionResult> updateBatchPredictionAsync(UpdateBatchPredictionRequest updateBatchPredictionRequest)
Updates the
BatchPredictionName
of aBatchPrediction
.You can use the GetBatchPrediction operation to view the contents of the updated data element.
- Parameters:
updateBatchPredictionRequest
-- Returns:
- A Java Future containing the result of the UpdateBatchPrediction operation returned by the service.
-
updateBatchPredictionAsync
Future<UpdateBatchPredictionResult> updateBatchPredictionAsync(UpdateBatchPredictionRequest updateBatchPredictionRequest, AsyncHandler<UpdateBatchPredictionRequest,UpdateBatchPredictionResult> asyncHandler)
Updates the
BatchPredictionName
of aBatchPrediction
.You can use the GetBatchPrediction operation to view the contents of the updated data element.
- Parameters:
updateBatchPredictionRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the UpdateBatchPrediction operation returned by the service.
-
updateDataSourceAsync
Future<UpdateDataSourceResult> updateDataSourceAsync(UpdateDataSourceRequest updateDataSourceRequest)
Updates the
DataSourceName
of aDataSource
.You can use the GetDataSource operation to view the contents of the updated data element.
- Parameters:
updateDataSourceRequest
-- Returns:
- A Java Future containing the result of the UpdateDataSource operation returned by the service.
-
updateDataSourceAsync
Future<UpdateDataSourceResult> updateDataSourceAsync(UpdateDataSourceRequest updateDataSourceRequest, AsyncHandler<UpdateDataSourceRequest,UpdateDataSourceResult> asyncHandler)
Updates the
DataSourceName
of aDataSource
.You can use the GetDataSource operation to view the contents of the updated data element.
- Parameters:
updateDataSourceRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the UpdateDataSource operation returned by the service.
-
updateEvaluationAsync
Future<UpdateEvaluationResult> updateEvaluationAsync(UpdateEvaluationRequest updateEvaluationRequest)
Updates the
EvaluationName
of anEvaluation
.You can use the GetEvaluation operation to view the contents of the updated data element.
- Parameters:
updateEvaluationRequest
-- Returns:
- A Java Future containing the result of the UpdateEvaluation operation returned by the service.
-
updateEvaluationAsync
Future<UpdateEvaluationResult> updateEvaluationAsync(UpdateEvaluationRequest updateEvaluationRequest, AsyncHandler<UpdateEvaluationRequest,UpdateEvaluationResult> asyncHandler)
Updates the
EvaluationName
of anEvaluation
.You can use the GetEvaluation operation to view the contents of the updated data element.
- Parameters:
updateEvaluationRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the UpdateEvaluation operation returned by the service.
-
updateMLModelAsync
Future<UpdateMLModelResult> updateMLModelAsync(UpdateMLModelRequest updateMLModelRequest)
Updates the
MLModelName
and theScoreThreshold
of anMLModel
.You can use the GetMLModel operation to view the contents of the updated data element.
- Parameters:
updateMLModelRequest
-- Returns:
- A Java Future containing the result of the UpdateMLModel operation returned by the service.
-
updateMLModelAsync
Future<UpdateMLModelResult> updateMLModelAsync(UpdateMLModelRequest updateMLModelRequest, AsyncHandler<UpdateMLModelRequest,UpdateMLModelResult> asyncHandler)
Updates the
MLModelName
and theScoreThreshold
of anMLModel
.You can use the GetMLModel operation to view the contents of the updated data element.
- Parameters:
updateMLModelRequest
-asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.- Returns:
- A Java Future containing the result of the UpdateMLModel operation returned by the service.
-
-