AmazonMachineLearningAsyncClient (AWS SDK for Java

java.lang.Object
- com.amazonaws.AmazonWebServiceClient
- - com.amazonaws.services.machinelearning.AmazonMachineLearningClient
  - - com.amazonaws.services.machinelearning.AmazonMachineLearningAsyncClient

All Implemented Interfaces:

AmazonMachineLearning, AmazonMachineLearningAsync
```
@ThreadSafe
public class AmazonMachineLearningAsyncClient
extends AmazonMachineLearningClient
implements AmazonMachineLearningAsync
```
Interface for accessing Amazon Machine Learning asynchronously. Each asynchronous method will return a Java Future object representing the asynchronous operation; overloads which accept an AsyncHandler can be used to receive notification when an asynchronous operation completes.
Definition of the public APIs exposed by Amazon Machine Learning

Field Summary
- Fields inherited from class com.amazonaws.AmazonWebServiceClient
  LOGGING_AWS_REQUEST_METRIC

Constructor Summary

Constructors
Constructor and Description
`AmazonMachineLearningAsyncClient()` Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning.
`AmazonMachineLearningAsyncClient(AWSCredentials awsCredentials)` Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning using the specified AWS account credentials.
`AmazonMachineLearningAsyncClient(AWSCredentials awsCredentials, ClientConfiguration clientConfiguration, ExecutorService executorService)` Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning using the specified AWS account credentials, executor service, and client configuration options.
`AmazonMachineLearningAsyncClient(AWSCredentials awsCredentials, ExecutorService executorService)` Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning using the specified AWS account credentials and executor service.
`AmazonMachineLearningAsyncClient(AWSCredentialsProvider awsCredentialsProvider)` Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning using the specified AWS account credentials provider.
`AmazonMachineLearningAsyncClient(AWSCredentialsProvider awsCredentialsProvider, ClientConfiguration clientConfiguration)` Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning using the provided AWS account credentials provider and client configuration options.
`AmazonMachineLearningAsyncClient(AWSCredentialsProvider awsCredentialsProvider, ClientConfiguration clientConfiguration, ExecutorService executorService)` Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning using the specified AWS account credentials provider, executor service, and client configuration options.
`AmazonMachineLearningAsyncClient(AWSCredentialsProvider awsCredentialsProvider, ExecutorService executorService)` Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning using the specified AWS account credentials provider and executor service.
`AmazonMachineLearningAsyncClient(ClientConfiguration clientConfiguration)` Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning.

Method Summary

Methods
Modifier and Type	Method and Description
`Future<CreateBatchPredictionResult>`	`createBatchPredictionAsync(CreateBatchPredictionRequest request)` Generates predictions for a group of observations.
`Future<CreateBatchPredictionResult>`	`createBatchPredictionAsync(CreateBatchPredictionRequest request, AsyncHandler<CreateBatchPredictionRequest,CreateBatchPredictionResult> asyncHandler)` Generates predictions for a group of observations.
`Future<CreateDataSourceFromRDSResult>`	`createDataSourceFromRDSAsync(CreateDataSourceFromRDSRequest request)` Creates a `DataSource` object from an Amazon Relational Database Service (Amazon RDS).
`Future<CreateDataSourceFromRDSResult>`	`createDataSourceFromRDSAsync(CreateDataSourceFromRDSRequest request, AsyncHandler<CreateDataSourceFromRDSRequest,CreateDataSourceFromRDSResult> asyncHandler)` Creates a `DataSource` object from an Amazon Relational Database Service (Amazon RDS).
`Future<CreateDataSourceFromRedshiftResult>`	`createDataSourceFromRedshiftAsync(CreateDataSourceFromRedshiftRequest request)` Creates a `DataSource` from Amazon Redshift.
`Future<CreateDataSourceFromRedshiftResult>`	`createDataSourceFromRedshiftAsync(CreateDataSourceFromRedshiftRequest request, AsyncHandler<CreateDataSourceFromRedshiftRequest,CreateDataSourceFromRedshiftResult> asyncHandler)` Creates a `DataSource` from Amazon Redshift.
`Future<CreateDataSourceFromS3Result>`	`createDataSourceFromS3Async(CreateDataSourceFromS3Request request)` Creates a `DataSource` object.
`Future<CreateDataSourceFromS3Result>`	`createDataSourceFromS3Async(CreateDataSourceFromS3Request request, AsyncHandler<CreateDataSourceFromS3Request,CreateDataSourceFromS3Result> asyncHandler)` Creates a `DataSource` object.
`Future<CreateEvaluationResult>`	`createEvaluationAsync(CreateEvaluationRequest request)` Creates a new `Evaluation` of an `MLModel`.
`Future<CreateEvaluationResult>`	`createEvaluationAsync(CreateEvaluationRequest request, AsyncHandler<CreateEvaluationRequest,CreateEvaluationResult> asyncHandler)` Creates a new `Evaluation` of an `MLModel`.
`Future<CreateMLModelResult>`	`createMLModelAsync(CreateMLModelRequest request)` Creates a new `MLModel` using the data files and the recipe as information sources.
`Future<CreateMLModelResult>`	`createMLModelAsync(CreateMLModelRequest request, AsyncHandler<CreateMLModelRequest,CreateMLModelResult> asyncHandler)` Creates a new `MLModel` using the data files and the recipe as information sources.
`Future<CreateRealtimeEndpointResult>`	`createRealtimeEndpointAsync(CreateRealtimeEndpointRequest request)` Creates a real-time endpoint for the `MLModel`.
`Future<CreateRealtimeEndpointResult>`	`createRealtimeEndpointAsync(CreateRealtimeEndpointRequest request, AsyncHandler<CreateRealtimeEndpointRequest,CreateRealtimeEndpointResult> asyncHandler)` Creates a real-time endpoint for the `MLModel`.
`Future<DeleteBatchPredictionResult>`	`deleteBatchPredictionAsync(DeleteBatchPredictionRequest request)` Assigns the DELETED status to a `BatchPrediction`, rendering it unusable.
`Future<DeleteBatchPredictionResult>`	`deleteBatchPredictionAsync(DeleteBatchPredictionRequest request, AsyncHandler<DeleteBatchPredictionRequest,DeleteBatchPredictionResult> asyncHandler)` Assigns the DELETED status to a `BatchPrediction`, rendering it unusable.
`Future<DeleteDataSourceResult>`	`deleteDataSourceAsync(DeleteDataSourceRequest request)` Assigns the DELETED status to a `DataSource`, rendering it unusable.
`Future<DeleteDataSourceResult>`	`deleteDataSourceAsync(DeleteDataSourceRequest request, AsyncHandler<DeleteDataSourceRequest,DeleteDataSourceResult> asyncHandler)` Assigns the DELETED status to a `DataSource`, rendering it unusable.
`Future<DeleteEvaluationResult>`	`deleteEvaluationAsync(DeleteEvaluationRequest request)` Assigns the `DELETED` status to an `Evaluation`, rendering it unusable.
`Future<DeleteEvaluationResult>`	`deleteEvaluationAsync(DeleteEvaluationRequest request, AsyncHandler<DeleteEvaluationRequest,DeleteEvaluationResult> asyncHandler)` Assigns the `DELETED` status to an `Evaluation`, rendering it unusable.
`Future<DeleteMLModelResult>`	`deleteMLModelAsync(DeleteMLModelRequest request)` Assigns the DELETED status to an `MLModel`, rendering it unusable.
`Future<DeleteMLModelResult>`	`deleteMLModelAsync(DeleteMLModelRequest request, AsyncHandler<DeleteMLModelRequest,DeleteMLModelResult> asyncHandler)` Assigns the DELETED status to an `MLModel`, rendering it unusable.
`Future<DeleteRealtimeEndpointResult>`	`deleteRealtimeEndpointAsync(DeleteRealtimeEndpointRequest request)` Deletes a real time endpoint of an `MLModel`.
`Future<DeleteRealtimeEndpointResult>`	`deleteRealtimeEndpointAsync(DeleteRealtimeEndpointRequest request, AsyncHandler<DeleteRealtimeEndpointRequest,DeleteRealtimeEndpointResult> asyncHandler)` Deletes a real time endpoint of an `MLModel`.
`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 request)` Returns a list of `BatchPrediction` operations that match the search criteria in the request.
`Future<DescribeBatchPredictionsResult>`	`describeBatchPredictionsAsync(DescribeBatchPredictionsRequest request, AsyncHandler<DescribeBatchPredictionsRequest,DescribeBatchPredictionsResult> asyncHandler)` Returns a list of `BatchPrediction` 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 request)` Returns a list of `DataSource` that match the search criteria in the request.
`Future<DescribeDataSourcesResult>`	`describeDataSourcesAsync(DescribeDataSourcesRequest request, AsyncHandler<DescribeDataSourcesRequest,DescribeDataSourcesResult> asyncHandler)` Returns a list of `DataSource` 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 request)` Returns a list of `DescribeEvaluations` that match the search criteria in the request.
`Future<DescribeEvaluationsResult>`	`describeEvaluationsAsync(DescribeEvaluationsRequest request, AsyncHandler<DescribeEvaluationsRequest,DescribeEvaluationsResult> asyncHandler)` Returns a list of `DescribeEvaluations` 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 request)` Returns a list of `MLModel` that match the search criteria in the request.
`Future<DescribeMLModelsResult>`	`describeMLModelsAsync(DescribeMLModelsRequest request, AsyncHandler<DescribeMLModelsRequest,DescribeMLModelsResult> asyncHandler)` Returns a list of `MLModel` that match the search criteria in the request.
`Future<GetBatchPredictionResult>`	`getBatchPredictionAsync(GetBatchPredictionRequest request)` Returns a `BatchPrediction` that includes detailed metadata, status, and data file information for a `Batch Prediction` request.
`Future<GetBatchPredictionResult>`	`getBatchPredictionAsync(GetBatchPredictionRequest request, AsyncHandler<GetBatchPredictionRequest,GetBatchPredictionResult> asyncHandler)` Returns a `BatchPrediction` that includes detailed metadata, status, and data file information for a `Batch Prediction` request.
`Future<GetDataSourceResult>`	`getDataSourceAsync(GetDataSourceRequest request)` Returns a `DataSource` that includes metadata and data file information, as well as the current status of the `DataSource` .
`Future<GetDataSourceResult>`	`getDataSourceAsync(GetDataSourceRequest request, AsyncHandler<GetDataSourceRequest,GetDataSourceResult> asyncHandler)` Returns a `DataSource` that includes metadata and data file information, as well as the current status of the `DataSource` .
`Future<GetEvaluationResult>`	`getEvaluationAsync(GetEvaluationRequest request)` Returns an `Evaluation` that includes metadata as well as the current status of the `Evaluation`.
`Future<GetEvaluationResult>`	`getEvaluationAsync(GetEvaluationRequest request, AsyncHandler<GetEvaluationRequest,GetEvaluationResult> asyncHandler)` Returns an `Evaluation` that includes metadata as well as the current status of the `Evaluation`.
`ExecutorService`	`getExecutorService()` Returns the executor service used by this client to execute async requests.
`Future<GetMLModelResult>`	`getMLModelAsync(GetMLModelRequest request)` Returns an `MLModel` that includes detailed metadata, and data source information as well as the current status of the `MLModel`.
`Future<GetMLModelResult>`	`getMLModelAsync(GetMLModelRequest request, AsyncHandler<GetMLModelRequest,GetMLModelResult> asyncHandler)` Returns an `MLModel` that includes detailed metadata, and data source information as well as the current status of the `MLModel`.
`Future<PredictResult>`	`predictAsync(PredictRequest request)` Generates a prediction for the observation using the specified `ML Model`.
`Future<PredictResult>`	`predictAsync(PredictRequest request, AsyncHandler<PredictRequest,PredictResult> asyncHandler)` Generates a prediction for the observation using the specified `ML Model`.
`void`	`shutdown()` Shuts down the client, releasing all managed resources.
`Future<UpdateBatchPredictionResult>`	`updateBatchPredictionAsync(UpdateBatchPredictionRequest request)` Updates the `BatchPredictionName` of a `BatchPrediction`.
`Future<UpdateBatchPredictionResult>`	`updateBatchPredictionAsync(UpdateBatchPredictionRequest request, AsyncHandler<UpdateBatchPredictionRequest,UpdateBatchPredictionResult> asyncHandler)` Updates the `BatchPredictionName` of a `BatchPrediction`.
`Future<UpdateDataSourceResult>`	`updateDataSourceAsync(UpdateDataSourceRequest request)` Updates the `DataSourceName` of a `DataSource`.
`Future<UpdateDataSourceResult>`	`updateDataSourceAsync(UpdateDataSourceRequest request, AsyncHandler<UpdateDataSourceRequest,UpdateDataSourceResult> asyncHandler)` Updates the `DataSourceName` of a `DataSource`.
`Future<UpdateEvaluationResult>`	`updateEvaluationAsync(UpdateEvaluationRequest request)` Updates the `EvaluationName` of an `Evaluation`.
`Future<UpdateEvaluationResult>`	`updateEvaluationAsync(UpdateEvaluationRequest request, AsyncHandler<UpdateEvaluationRequest,UpdateEvaluationResult> asyncHandler)` Updates the `EvaluationName` of an `Evaluation`.
`Future<UpdateMLModelResult>`	`updateMLModelAsync(UpdateMLModelRequest request)` Updates the `MLModelName` and the `ScoreThreshold` of an `MLModel`.
`Future<UpdateMLModelResult>`	`updateMLModelAsync(UpdateMLModelRequest request, AsyncHandler<UpdateMLModelRequest,UpdateMLModelResult> asyncHandler)` Updates the `MLModelName` and the `ScoreThreshold` of an `MLModel`.

Methods inherited from class com.amazonaws.AmazonWebServiceClient
addRequestHandler, addRequestHandler, configureRegion, getRequestMetricsCollector, getServiceName, getSignerByURI, getSignerRegionOverride, getTimeOffset, removeRequestHandler, removeRequestHandler, setEndpoint, setEndpoint, setRegion, setServiceNameIntern, setSignerRegionOverride, setTimeOffset, withEndpoint, withRegion, withRegion, withTimeOffset

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - AmazonMachineLearningAsyncClient
```
public AmazonMachineLearningAsyncClient()
```
    Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning. A credentials provider chain will be used that searches for credentials in this order:
    - Environment Variables - AWS_ACCESS_KEY_ID and AWS_SECRET_KEY
    - Java System Properties - aws.accessKeyId and aws.secretKey
    - Credential profiles file at the default location (~/.aws/credentials) shared by all AWS SDKs and the AWS CLI
    - Instance profile credentials delivered through the Amazon EC2 metadata service
    Asynchronous methods are delegated to a fixed-size thread pool containing 50 threads (to match the default maximum number of concurrent connections to the service).
    See Also:
    DefaultAWSCredentialsProviderChain, Executors.newFixedThreadPool(int)
  - AmazonMachineLearningAsyncClient
```
public AmazonMachineLearningAsyncClient(ClientConfiguration clientConfiguration)
```
    Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning. A credentials provider chain will be used that searches for credentials in this order:
    - Environment Variables - AWS_ACCESS_KEY_ID and AWS_SECRET_KEY
    - Java System Properties - aws.accessKeyId and aws.secretKey
    - Credential profiles file at the default location (~/.aws/credentials) shared by all AWS SDKs and the AWS CLI
    - Instance profile credentials delivered through the Amazon EC2 metadata service
    Asynchronous methods are delegated to a fixed-size thread pool containing a number of threads equal to the maximum number of concurrent connections configured via ClientConfiguration.getMaxConnections().
    Parameters:
    clientConfiguration - The client configuration options controlling how this client connects to Amazon Machine Learning (ex: proxy settings, retry counts, etc).
    See Also:
    DefaultAWSCredentialsProviderChain, Executors.newFixedThreadPool(int)
  - AmazonMachineLearningAsyncClient
```
public AmazonMachineLearningAsyncClient(AWSCredentials awsCredentials)
```
    Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning using the specified AWS account credentials.
    Asynchronous methods are delegated to a fixed-size thread pool containing 50 threads (to match the default maximum number of concurrent connections to the service).
    
    Parameters:
    awsCredentials - The AWS credentials (access key ID and secret key) to use when authenticating with AWS services.
    See Also:
    Executors.newFixedThreadPool(int)
  - AmazonMachineLearningAsyncClient
```
public AmazonMachineLearningAsyncClient(AWSCredentials awsCredentials,
                                ExecutorService executorService)
```
    Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning using the specified AWS account credentials and executor service. Default client settings will be used.
    
    Parameters:
    awsCredentials - The AWS credentials (access key ID and secret key) to use when authenticating with AWS services.
    executorService - The executor service by which all asynchronous requests will be executed.
  - AmazonMachineLearningAsyncClient
```
public AmazonMachineLearningAsyncClient(AWSCredentials awsCredentials,
                                ClientConfiguration clientConfiguration,
                                ExecutorService executorService)
```
    Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning using the specified AWS account credentials, executor service, and client configuration options.
    
    Parameters:
    awsCredentials - The AWS credentials (access key ID and secret key) to use when authenticating with AWS services.
    clientConfiguration - Client configuration options (ex: max retry limit, proxy settings, etc).
    executorService - The executor service by which all asynchronous requests will be executed.
  - AmazonMachineLearningAsyncClient
```
public AmazonMachineLearningAsyncClient(AWSCredentialsProvider awsCredentialsProvider)
```
    Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning using the specified AWS account credentials provider. Default client settings will be used.
    Asynchronous methods are delegated to a fixed-size thread pool containing 50 threads (to match the default maximum number of concurrent connections to the service).
    
    Parameters:
    awsCredentialsProvider - The AWS credentials provider which will provide credentials to authenticate requests with AWS services.
    See Also:
    Executors.newFixedThreadPool(int)
  - AmazonMachineLearningAsyncClient
```
public AmazonMachineLearningAsyncClient(AWSCredentialsProvider awsCredentialsProvider,
                                ClientConfiguration clientConfiguration)
```
    Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning using the provided AWS account credentials provider and client configuration options.
    Asynchronous methods are delegated to a fixed-size thread pool containing a number of threads equal to the maximum number of concurrent connections configured via ClientConfiguration.getMaxConnections().
    
    Parameters:
    awsCredentialsProvider - The AWS credentials provider which will provide credentials to authenticate requests with AWS services.
    clientConfiguration - Client configuration options (ex: max retry limit, proxy settings, etc).
    See Also:
    DefaultAWSCredentialsProviderChain, Executors.newFixedThreadPool(int)
  - AmazonMachineLearningAsyncClient
```
public AmazonMachineLearningAsyncClient(AWSCredentialsProvider awsCredentialsProvider,
                                ExecutorService executorService)
```
    Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning using the specified AWS account credentials provider and executor service. Default client settings will be used.
    
    Parameters:
    awsCredentialsProvider - The AWS credentials provider which will provide credentials to authenticate requests with AWS services.
    executorService - The executor service by which all asynchronous requests will be executed.
  - AmazonMachineLearningAsyncClient
```
public AmazonMachineLearningAsyncClient(AWSCredentialsProvider awsCredentialsProvider,
                                ClientConfiguration clientConfiguration,
                                ExecutorService executorService)
```
    Constructs a new asynchronous client to invoke service methods on Amazon Machine Learning using the specified AWS account credentials provider, executor service, and client configuration options.
    
    Parameters:
    awsCredentialsProvider - The AWS credentials provider which will provide credentials to authenticate requests with AWS services.
    clientConfiguration - Client configuration options (ex: max retry limit, proxy settings, etc).
    executorService - The executor service by which all asynchronous requests will be executed.
- Method Detail
  - getExecutorService
```
public ExecutorService getExecutorService()
```
    Returns the executor service used by this client to execute async requests.
    
    Returns:
    The executor service used by this client to execute async requests.
  - createBatchPredictionAsync
```
public Future<CreateBatchPredictionResult> createBatchPredictionAsync(CreateBatchPredictionRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    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 new BatchPrediction, and uses an MLModel and the data files referenced by the DataSource as information sources.
    
    CreateBatchPrediction is an asynchronous operation. In response to CreateBatchPrediction, Amazon Machine Learning (Amazon ML) immediately returns and sets the BatchPrediction status to PENDING. After the BatchPrediction completes, Amazon ML sets the status to COMPLETED.
    
    You can poll for status updates by using the GetBatchPrediction operation and checking the Status parameter of the result. After the COMPLETED status appears, the results are available in the location specified by the OutputUri parameter.
    
    Specified by:
    
    createBatchPredictionAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the CreateBatchPrediction operation returned by the service.
  - createBatchPredictionAsync
```
public Future<CreateBatchPredictionResult> createBatchPredictionAsync(CreateBatchPredictionRequest request,
                                                             AsyncHandler<CreateBatchPredictionRequest,CreateBatchPredictionResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    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 new BatchPrediction, and uses an MLModel and the data files referenced by the DataSource as information sources.
    
    CreateBatchPrediction is an asynchronous operation. In response to CreateBatchPrediction, Amazon Machine Learning (Amazon ML) immediately returns and sets the BatchPrediction status to PENDING. After the BatchPrediction completes, Amazon ML sets the status to COMPLETED.
    
    You can poll for status updates by using the GetBatchPrediction operation and checking the Status parameter of the result. After the COMPLETED status appears, the results are available in the location specified by the OutputUri parameter.
    
    Specified by:
    
    createBatchPredictionAsync in interface AmazonMachineLearningAsync
    
    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.
  - createDataSourceFromRDSAsync
```
public Future<CreateDataSourceFromRDSResult> createDataSourceFromRDSAsync(CreateDataSourceFromRDSRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Creates a DataSource object from an Amazon Relational Database Service (Amazon RDS). A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
    
    CreateDataSourceFromRDS is an asynchronous operation. In response to CreateDataSourceFromRDS, Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING. After the DataSource is created and ready for use, Amazon ML sets the Status parameter to COMPLETED. DataSource in COMPLETED or PENDING status can only be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
    
    If Amazon ML cannot accept the input source, it sets the Status parameter to FAILED and includes an error message in the Message attribute of the GetDataSource operation response.
    
    Specified by:
    
    createDataSourceFromRDSAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the CreateDataSourceFromRDS operation returned by the service.
  - createDataSourceFromRDSAsync
```
public Future<CreateDataSourceFromRDSResult> createDataSourceFromRDSAsync(CreateDataSourceFromRDSRequest request,
                                                                 AsyncHandler<CreateDataSourceFromRDSRequest,CreateDataSourceFromRDSResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Creates a DataSource object from an Amazon Relational Database Service (Amazon RDS). A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
    
    CreateDataSourceFromRDS is an asynchronous operation. In response to CreateDataSourceFromRDS, Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING. After the DataSource is created and ready for use, Amazon ML sets the Status parameter to COMPLETED. DataSource in COMPLETED or PENDING status can only be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
    
    If Amazon ML cannot accept the input source, it sets the Status parameter to FAILED and includes an error message in the Message attribute of the GetDataSource operation response.
    
    Specified by:
    
    createDataSourceFromRDSAsync in interface AmazonMachineLearningAsync
    
    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.
  - createDataSourceFromRedshiftAsync
```
public Future<CreateDataSourceFromRedshiftResult> createDataSourceFromRedshiftAsync(CreateDataSourceFromRedshiftRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Creates a DataSource from Amazon Redshift. A DataSource references data that can be used to perform either CreateMLModel, CreateEvaluation or CreateBatchPrediction operations.
    
    CreateDataSourceFromRedshift is an asynchronous operation. In response to CreateDataSourceFromRedshift, Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING. After the DataSource is created and ready for use, Amazon ML sets the Status parameter to COMPLETED. DataSource in COMPLETED or PENDING status can only be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
    
    If Amazon ML cannot accept the input source, it sets the Status parameter to FAILED and includes an error message in the Message attribute of the GetDataSource operation response.
    
    The 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 of SelectSqlQuery to S3StagingLocation.
    
    After the DataSource is created, it's ready for use in evaluations and batch predictions. If you plan to use the DataSource to train an MLModel, the DataSource requires another item -- a recipe. A recipe describes the observation variables that participate in training an MLModel. A recipe describes how each input variable will be used in training. Will the variable be included or excluded from training? Will the variable be manipulated, for example, combined with another variable or split apart into word combinations? The recipe provides answers to these questions. For more information, see the Amazon Machine Learning Developer Guide.
    
    Specified by:
    
    createDataSourceFromRedshiftAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the CreateDataSourceFromRedshift operation returned by the service.
  - createDataSourceFromRedshiftAsync
```
public Future<CreateDataSourceFromRedshiftResult> createDataSourceFromRedshiftAsync(CreateDataSourceFromRedshiftRequest request,
                                                                           AsyncHandler<CreateDataSourceFromRedshiftRequest,CreateDataSourceFromRedshiftResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Creates a DataSource from Amazon Redshift. A DataSource references data that can be used to perform either CreateMLModel, CreateEvaluation or CreateBatchPrediction operations.
    
    CreateDataSourceFromRedshift is an asynchronous operation. In response to CreateDataSourceFromRedshift, Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING. After the DataSource is created and ready for use, Amazon ML sets the Status parameter to COMPLETED. DataSource in COMPLETED or PENDING status can only be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
    
    If Amazon ML cannot accept the input source, it sets the Status parameter to FAILED and includes an error message in the Message attribute of the GetDataSource operation response.
    
    The 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 of SelectSqlQuery to S3StagingLocation.
    
    After the DataSource is created, it's ready for use in evaluations and batch predictions. If you plan to use the DataSource to train an MLModel, the DataSource requires another item -- a recipe. A recipe describes the observation variables that participate in training an MLModel. A recipe describes how each input variable will be used in training. Will the variable be included or excluded from training? Will the variable be manipulated, for example, combined with another variable or split apart into word combinations? The recipe provides answers to these questions. For more information, see the Amazon Machine Learning Developer Guide.
    
    Specified by:
    
    createDataSourceFromRedshiftAsync in interface AmazonMachineLearningAsync
    
    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.
  - createDataSourceFromS3Async
```
public Future<CreateDataSourceFromS3Result> createDataSourceFromS3Async(CreateDataSourceFromS3Request request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Creates a DataSource object. A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
    
    CreateDataSourceFromS3 is an asynchronous operation. In response to CreateDataSourceFromS3, Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING. After the DataSource is created and ready for use, Amazon ML sets the Status parameter to COMPLETED. DataSource in COMPLETED or PENDING status can only be used to perform CreateMLModel, CreateEvaluation or CreateBatchPrediction operations.
    
    If Amazon ML cannot accept the input source, it sets the Status parameter to FAILED and includes an error message in the Message attribute of the GetDataSource operation response.
    
    The observation data used in a DataSource should be ready to use; that is, it should have a consistent structure, and missing data values should be kept to a minimum. The observation data must reside in one or more CSV files in an Amazon Simple Storage Service (Amazon S3) bucket, along with a schema that describes the data items by name and type. The same schema must be used for all of the data files referenced by the DataSource.
    
    After the DataSource has been created, it's ready to use in evaluations and batch predictions. If you plan to use the DataSource to train an MLModel, the DataSource requires another item: a recipe. A recipe describes the observation variables that participate in training an MLModel. A recipe describes how each input variable will be used in training. Will the variable be included or excluded from training? Will the variable be manipulated, for example, combined with another variable, or split apart into word combinations? The recipe provides answers to these questions. For more information, see the Amazon Machine Learning Developer Guide.
    
    Specified by:
    
    createDataSourceFromS3Async in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the CreateDataSourceFromS3 operation returned by the service.
  - createDataSourceFromS3Async
```
public Future<CreateDataSourceFromS3Result> createDataSourceFromS3Async(CreateDataSourceFromS3Request request,
                                                               AsyncHandler<CreateDataSourceFromS3Request,CreateDataSourceFromS3Result> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Creates a DataSource object. A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
    
    CreateDataSourceFromS3 is an asynchronous operation. In response to CreateDataSourceFromS3, Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING. After the DataSource is created and ready for use, Amazon ML sets the Status parameter to COMPLETED. DataSource in COMPLETED or PENDING status can only be used to perform CreateMLModel, CreateEvaluation or CreateBatchPrediction operations.
    
    If Amazon ML cannot accept the input source, it sets the Status parameter to FAILED and includes an error message in the Message attribute of the GetDataSource operation response.
    
    The observation data used in a DataSource should be ready to use; that is, it should have a consistent structure, and missing data values should be kept to a minimum. The observation data must reside in one or more CSV files in an Amazon Simple Storage Service (Amazon S3) bucket, along with a schema that describes the data items by name and type. The same schema must be used for all of the data files referenced by the DataSource.
    
    After the DataSource has been created, it's ready to use in evaluations and batch predictions. If you plan to use the DataSource to train an MLModel, the DataSource requires another item: a recipe. A recipe describes the observation variables that participate in training an MLModel. A recipe describes how each input variable will be used in training. Will the variable be included or excluded from training? Will the variable be manipulated, for example, combined with another variable, or split apart into word combinations? The recipe provides answers to these questions. For more information, see the Amazon Machine Learning Developer Guide.
    
    Specified by:
    
    createDataSourceFromS3Async in interface AmazonMachineLearningAsync
    
    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.
  - createEvaluationAsync
```
public Future<CreateEvaluationResult> createEvaluationAsync(CreateEvaluationRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Creates a new Evaluation of an MLModel. An MLModel is evaluated on a set of observations associated to a DataSource. Like a DataSource for an MLModel, the DataSource for an Evaluation contains values for the Target Variable. The Evaluation compares the predicted result for each observation to the actual outcome and provides a summary so that you know how effective the MLModel functions on the test data. Evaluation generates a relevant performance metric such as BinaryAUC, RegressionRMSE or MulticlassAvgFScore based on the corresponding MLModelType: BINARY, REGRESSION or MULTICLASS.
    
    CreateEvaluation is an asynchronous operation. In response to CreateEvaluation, Amazon Machine Learning (Amazon ML) immediately returns and sets the evaluation status to PENDING. After the Evaluation is created and ready for use, Amazon ML sets the status to COMPLETED.
    
    You can use the GetEvaluation operation to check progress of the evaluation during the creation operation.
    
    Specified by:
    
    createEvaluationAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the CreateEvaluation operation returned by the service.
  - createEvaluationAsync
```
public Future<CreateEvaluationResult> createEvaluationAsync(CreateEvaluationRequest request,
                                                   AsyncHandler<CreateEvaluationRequest,CreateEvaluationResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Creates a new Evaluation of an MLModel. An MLModel is evaluated on a set of observations associated to a DataSource. Like a DataSource for an MLModel, the DataSource for an Evaluation contains values for the Target Variable. The Evaluation compares the predicted result for each observation to the actual outcome and provides a summary so that you know how effective the MLModel functions on the test data. Evaluation generates a relevant performance metric such as BinaryAUC, RegressionRMSE or MulticlassAvgFScore based on the corresponding MLModelType: BINARY, REGRESSION or MULTICLASS.
    
    CreateEvaluation is an asynchronous operation. In response to CreateEvaluation, Amazon Machine Learning (Amazon ML) immediately returns and sets the evaluation status to PENDING. After the Evaluation is created and ready for use, Amazon ML sets the status to COMPLETED.
    
    You can use the GetEvaluation operation to check progress of the evaluation during the creation operation.
    
    Specified by:
    
    createEvaluationAsync in interface AmazonMachineLearningAsync
    
    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.
  - createMLModelAsync
```
public Future<CreateMLModelResult> createMLModelAsync(CreateMLModelRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Creates a new MLModel using the data files and the recipe as information sources.
    
    An MLModel is nearly immutable. Users can only update the MLModelName and the ScoreThreshold in an MLModel without creating a new MLModel.
    
    CreateMLModel is an asynchronous operation. In response to CreateMLModel, Amazon Machine Learning (Amazon ML) immediately returns and sets the MLModel status to PENDING. After the MLModel is created and ready for use, Amazon ML sets the status to COMPLETED.
    
    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 setting ComputeStatistics to true in CreateDataSourceFromRDS, CreateDataSourceFromS3, or CreateDataSourceFromRedshift operations.
    
    Specified by:
    
    createMLModelAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the CreateMLModel operation returned by the service.
  - createMLModelAsync
```
public Future<CreateMLModelResult> createMLModelAsync(CreateMLModelRequest request,
                                             AsyncHandler<CreateMLModelRequest,CreateMLModelResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Creates a new MLModel using the data files and the recipe as information sources.
    
    An MLModel is nearly immutable. Users can only update the MLModelName and the ScoreThreshold in an MLModel without creating a new MLModel.
    
    CreateMLModel is an asynchronous operation. In response to CreateMLModel, Amazon Machine Learning (Amazon ML) immediately returns and sets the MLModel status to PENDING. After the MLModel is created and ready for use, Amazon ML sets the status to COMPLETED.
    
    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 setting ComputeStatistics to true in CreateDataSourceFromRDS, CreateDataSourceFromS3, or CreateDataSourceFromRedshift operations.
    
    Specified by:
    
    createMLModelAsync in interface AmazonMachineLearningAsync
    
    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.
  - createRealtimeEndpointAsync
```
public Future<CreateRealtimeEndpointResult> createRealtimeEndpointAsync(CreateRealtimeEndpointRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Creates a real-time endpoint for the MLModel. The endpoint contains the URI of the MLModel; that is, the location to send real-time prediction requests for the specified MLModel .
    
    Specified by:
    
    createRealtimeEndpointAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the CreateRealtimeEndpoint operation returned by the service.
  - createRealtimeEndpointAsync
```
public Future<CreateRealtimeEndpointResult> createRealtimeEndpointAsync(CreateRealtimeEndpointRequest request,
                                                               AsyncHandler<CreateRealtimeEndpointRequest,CreateRealtimeEndpointResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Creates a real-time endpoint for the MLModel. The endpoint contains the URI of the MLModel; that is, the location to send real-time prediction requests for the specified MLModel .
    
    Specified by:
    
    createRealtimeEndpointAsync in interface AmazonMachineLearningAsync
    
    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.
  - deleteBatchPredictionAsync
```
public Future<DeleteBatchPredictionResult> deleteBatchPredictionAsync(DeleteBatchPredictionRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    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 the BatchPrediction changed to DELETED.
    
    Caution: The result of the DeleteBatchPrediction operation is irreversible.
    
    Specified by:
    
    deleteBatchPredictionAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the DeleteBatchPrediction operation returned by the service.
  - deleteBatchPredictionAsync
```
public Future<DeleteBatchPredictionResult> deleteBatchPredictionAsync(DeleteBatchPredictionRequest request,
                                                             AsyncHandler<DeleteBatchPredictionRequest,DeleteBatchPredictionResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    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 the BatchPrediction changed to DELETED.
    
    Caution: The result of the DeleteBatchPrediction operation is irreversible.
    
    Specified by:
    
    deleteBatchPredictionAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<DeleteDataSourceResult> deleteDataSourceAsync(DeleteDataSourceRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    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 the DataSource changed to DELETED.
    
    Caution: The results of the DeleteDataSource operation are irreversible.
    
    Specified by:
    
    deleteDataSourceAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the DeleteDataSource operation returned by the service.
  - deleteDataSourceAsync
```
public Future<DeleteDataSourceResult> deleteDataSourceAsync(DeleteDataSourceRequest request,
                                                   AsyncHandler<DeleteDataSourceRequest,DeleteDataSourceResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    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 the DataSource changed to DELETED.
    
    Caution: The results of the DeleteDataSource operation are irreversible.
    
    Specified by:
    
    deleteDataSourceAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<DeleteEvaluationResult> deleteEvaluationAsync(DeleteEvaluationRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Assigns the DELETED status to an Evaluation, rendering it unusable.
    
    After invoking the DeleteEvaluation operation, you can use the GetEvaluation operation to verify that the status of the Evaluation changed to DELETED.
    
    Caution: The results of the DeleteEvaluation operation are irreversible.
    
    Specified by:
    
    deleteEvaluationAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the DeleteEvaluation operation returned by the service.
  - deleteEvaluationAsync
```
public Future<DeleteEvaluationResult> deleteEvaluationAsync(DeleteEvaluationRequest request,
                                                   AsyncHandler<DeleteEvaluationRequest,DeleteEvaluationResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Assigns the DELETED status to an Evaluation, rendering it unusable.
    
    After invoking the DeleteEvaluation operation, you can use the GetEvaluation operation to verify that the status of the Evaluation changed to DELETED.
    
    Caution: The results of the DeleteEvaluation operation are irreversible.
    
    Specified by:
    
    deleteEvaluationAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<DeleteMLModelResult> deleteMLModelAsync(DeleteMLModelRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    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 the MLModel changed to DELETED.
    
    Caution: The result of the DeleteMLModel operation is irreversible.
    
    Specified by:
    
    deleteMLModelAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the DeleteMLModel operation returned by the service.
  - deleteMLModelAsync
```
public Future<DeleteMLModelResult> deleteMLModelAsync(DeleteMLModelRequest request,
                                             AsyncHandler<DeleteMLModelRequest,DeleteMLModelResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    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 the MLModel changed to DELETED.
    
    Caution: The result of the DeleteMLModel operation is irreversible.
    
    Specified by:
    
    deleteMLModelAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<DeleteRealtimeEndpointResult> deleteRealtimeEndpointAsync(DeleteRealtimeEndpointRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Deletes a real time endpoint of an MLModel.
    
    Specified by:
    
    deleteRealtimeEndpointAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the DeleteRealtimeEndpoint operation returned by the service.
  - deleteRealtimeEndpointAsync
```
public Future<DeleteRealtimeEndpointResult> deleteRealtimeEndpointAsync(DeleteRealtimeEndpointRequest request,
                                                               AsyncHandler<DeleteRealtimeEndpointRequest,DeleteRealtimeEndpointResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Deletes a real time endpoint of an MLModel.
    
    Specified by:
    
    deleteRealtimeEndpointAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<DescribeBatchPredictionsResult> describeBatchPredictionsAsync(DescribeBatchPredictionsRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns a list of BatchPrediction operations that match the search criteria in the request.
    
    Specified by:
    
    describeBatchPredictionsAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the DescribeBatchPredictions operation returned by the service.
  - describeBatchPredictionsAsync
```
public Future<DescribeBatchPredictionsResult> describeBatchPredictionsAsync(DescribeBatchPredictionsRequest request,
                                                                   AsyncHandler<DescribeBatchPredictionsRequest,DescribeBatchPredictionsResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns a list of BatchPrediction operations that match the search criteria in the request.
    
    Specified by:
    
    describeBatchPredictionsAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<DescribeBatchPredictionsResult> describeBatchPredictionsAsync()
```
    Simplified method form for invoking the DescribeBatchPredictions operation.
    
    Specified by:
    
    describeBatchPredictionsAsync in interface AmazonMachineLearningAsync
    
    See Also:
    describeBatchPredictionsAsync(DescribeBatchPredictionsRequest)
  - describeBatchPredictionsAsync
```
public Future<DescribeBatchPredictionsResult> describeBatchPredictionsAsync(AsyncHandler<DescribeBatchPredictionsRequest,DescribeBatchPredictionsResult> asyncHandler)
```
    Simplified method form for invoking the DescribeBatchPredictions operation with an AsyncHandler.
    
    Specified by:
    
    describeBatchPredictionsAsync in interface AmazonMachineLearningAsync
    
    See Also:
    describeBatchPredictionsAsync(DescribeBatchPredictionsRequest, com.amazonaws.handlers.AsyncHandler)
  - describeDataSourcesAsync
```
public Future<DescribeDataSourcesResult> describeDataSourcesAsync(DescribeDataSourcesRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns a list of DataSource that match the search criteria in the request.
    
    Specified by:
    
    describeDataSourcesAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the DescribeDataSources operation returned by the service.
  - describeDataSourcesAsync
```
public Future<DescribeDataSourcesResult> describeDataSourcesAsync(DescribeDataSourcesRequest request,
                                                         AsyncHandler<DescribeDataSourcesRequest,DescribeDataSourcesResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns a list of DataSource that match the search criteria in the request.
    
    Specified by:
    
    describeDataSourcesAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<DescribeDataSourcesResult> describeDataSourcesAsync()
```
    Simplified method form for invoking the DescribeDataSources operation.
    
    Specified by:
    
    describeDataSourcesAsync in interface AmazonMachineLearningAsync
    
    See Also:
    describeDataSourcesAsync(DescribeDataSourcesRequest)
  - describeDataSourcesAsync
```
public Future<DescribeDataSourcesResult> describeDataSourcesAsync(AsyncHandler<DescribeDataSourcesRequest,DescribeDataSourcesResult> asyncHandler)
```
    Simplified method form for invoking the DescribeDataSources operation with an AsyncHandler.
    
    Specified by:
    
    describeDataSourcesAsync in interface AmazonMachineLearningAsync
    
    See Also:
    describeDataSourcesAsync(DescribeDataSourcesRequest, com.amazonaws.handlers.AsyncHandler)
  - describeEvaluationsAsync
```
public Future<DescribeEvaluationsResult> describeEvaluationsAsync(DescribeEvaluationsRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns a list of DescribeEvaluations that match the search criteria in the request.
    
    Specified by:
    
    describeEvaluationsAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the DescribeEvaluations operation returned by the service.
  - describeEvaluationsAsync
```
public Future<DescribeEvaluationsResult> describeEvaluationsAsync(DescribeEvaluationsRequest request,
                                                         AsyncHandler<DescribeEvaluationsRequest,DescribeEvaluationsResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns a list of DescribeEvaluations that match the search criteria in the request.
    
    Specified by:
    
    describeEvaluationsAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<DescribeEvaluationsResult> describeEvaluationsAsync()
```
    Simplified method form for invoking the DescribeEvaluations operation.
    
    Specified by:
    
    describeEvaluationsAsync in interface AmazonMachineLearningAsync
    
    See Also:
    describeEvaluationsAsync(DescribeEvaluationsRequest)
  - describeEvaluationsAsync
```
public Future<DescribeEvaluationsResult> describeEvaluationsAsync(AsyncHandler<DescribeEvaluationsRequest,DescribeEvaluationsResult> asyncHandler)
```
    Simplified method form for invoking the DescribeEvaluations operation with an AsyncHandler.
    
    Specified by:
    
    describeEvaluationsAsync in interface AmazonMachineLearningAsync
    
    See Also:
    describeEvaluationsAsync(DescribeEvaluationsRequest, com.amazonaws.handlers.AsyncHandler)
  - describeMLModelsAsync
```
public Future<DescribeMLModelsResult> describeMLModelsAsync(DescribeMLModelsRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns a list of MLModel that match the search criteria in the request.
    
    Specified by:
    
    describeMLModelsAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the DescribeMLModels operation returned by the service.
  - describeMLModelsAsync
```
public Future<DescribeMLModelsResult> describeMLModelsAsync(DescribeMLModelsRequest request,
                                                   AsyncHandler<DescribeMLModelsRequest,DescribeMLModelsResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns a list of MLModel that match the search criteria in the request.
    
    Specified by:
    
    describeMLModelsAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<DescribeMLModelsResult> describeMLModelsAsync()
```
    Simplified method form for invoking the DescribeMLModels operation.
    
    Specified by:
    
    describeMLModelsAsync in interface AmazonMachineLearningAsync
    
    See Also:
    describeMLModelsAsync(DescribeMLModelsRequest)
  - describeMLModelsAsync
```
public Future<DescribeMLModelsResult> describeMLModelsAsync(AsyncHandler<DescribeMLModelsRequest,DescribeMLModelsResult> asyncHandler)
```
    Simplified method form for invoking the DescribeMLModels operation with an AsyncHandler.
    
    Specified by:
    
    describeMLModelsAsync in interface AmazonMachineLearningAsync
    
    See Also:
    describeMLModelsAsync(DescribeMLModelsRequest, com.amazonaws.handlers.AsyncHandler)
  - getBatchPredictionAsync
```
public Future<GetBatchPredictionResult> getBatchPredictionAsync(GetBatchPredictionRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns a BatchPrediction that includes detailed metadata, status, and data file information for a Batch Prediction request.
    
    Specified by:
    
    getBatchPredictionAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the GetBatchPrediction operation returned by the service.
  - getBatchPredictionAsync
```
public Future<GetBatchPredictionResult> getBatchPredictionAsync(GetBatchPredictionRequest request,
                                                       AsyncHandler<GetBatchPredictionRequest,GetBatchPredictionResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns a BatchPrediction that includes detailed metadata, status, and data file information for a Batch Prediction request.
    
    Specified by:
    
    getBatchPredictionAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<GetDataSourceResult> getDataSourceAsync(GetDataSourceRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns a DataSource that includes metadata and data file information, as well as the current status of the DataSource .
    
    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.
    
    Specified by:
    
    getDataSourceAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the GetDataSource operation returned by the service.
  - getDataSourceAsync
```
public Future<GetDataSourceResult> getDataSourceAsync(GetDataSourceRequest request,
                                             AsyncHandler<GetDataSourceRequest,GetDataSourceResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns a DataSource that includes metadata and data file information, as well as the current status of the DataSource .
    
    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.
    
    Specified by:
    
    getDataSourceAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<GetEvaluationResult> getEvaluationAsync(GetEvaluationRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns an Evaluation that includes metadata as well as the current status of the Evaluation.
    
    Specified by:
    
    getEvaluationAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the GetEvaluation operation returned by the service.
  - getEvaluationAsync
```
public Future<GetEvaluationResult> getEvaluationAsync(GetEvaluationRequest request,
                                             AsyncHandler<GetEvaluationRequest,GetEvaluationResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns an Evaluation that includes metadata as well as the current status of the Evaluation.
    
    Specified by:
    
    getEvaluationAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<GetMLModelResult> getMLModelAsync(GetMLModelRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns an MLModel that includes detailed metadata, and data source information as well as the current status of the MLModel.
    
    GetMLModel provides results in normal or verbose format.
    
    Specified by:
    
    getMLModelAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the GetMLModel operation returned by the service.
  - getMLModelAsync
```
public Future<GetMLModelResult> getMLModelAsync(GetMLModelRequest request,
                                       AsyncHandler<GetMLModelRequest,GetMLModelResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Returns an MLModel that includes detailed metadata, and data source information as well as the current status of the MLModel.
    
    GetMLModel provides results in normal or verbose format.
    
    Specified by:
    
    getMLModelAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<PredictResult> predictAsync(PredictRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    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.
    
    Specified by:
    
    predictAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the Predict operation returned by the service.
  - predictAsync
```
public Future<PredictResult> predictAsync(PredictRequest request,
                                 AsyncHandler<PredictRequest,PredictResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    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.
    
    Specified by:
    
    predictAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<UpdateBatchPredictionResult> updateBatchPredictionAsync(UpdateBatchPredictionRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Updates the BatchPredictionName of a BatchPrediction.
    
    You can use the GetBatchPrediction operation to view the contents of the updated data element.
    
    Specified by:
    
    updateBatchPredictionAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the UpdateBatchPrediction operation returned by the service.
  - updateBatchPredictionAsync
```
public Future<UpdateBatchPredictionResult> updateBatchPredictionAsync(UpdateBatchPredictionRequest request,
                                                             AsyncHandler<UpdateBatchPredictionRequest,UpdateBatchPredictionResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Updates the BatchPredictionName of a BatchPrediction.
    
    You can use the GetBatchPrediction operation to view the contents of the updated data element.
    
    Specified by:
    
    updateBatchPredictionAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<UpdateDataSourceResult> updateDataSourceAsync(UpdateDataSourceRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Updates the DataSourceName of a DataSource.
    
    You can use the GetDataSource operation to view the contents of the updated data element.
    
    Specified by:
    
    updateDataSourceAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the UpdateDataSource operation returned by the service.
  - updateDataSourceAsync
```
public Future<UpdateDataSourceResult> updateDataSourceAsync(UpdateDataSourceRequest request,
                                                   AsyncHandler<UpdateDataSourceRequest,UpdateDataSourceResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Updates the DataSourceName of a DataSource.
    
    You can use the GetDataSource operation to view the contents of the updated data element.
    
    Specified by:
    
    updateDataSourceAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<UpdateEvaluationResult> updateEvaluationAsync(UpdateEvaluationRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Updates the EvaluationName of an Evaluation.
    
    You can use the GetEvaluation operation to view the contents of the updated data element.
    
    Specified by:
    
    updateEvaluationAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the UpdateEvaluation operation returned by the service.
  - updateEvaluationAsync
```
public Future<UpdateEvaluationResult> updateEvaluationAsync(UpdateEvaluationRequest request,
                                                   AsyncHandler<UpdateEvaluationRequest,UpdateEvaluationResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Updates the EvaluationName of an Evaluation.
    
    You can use the GetEvaluation operation to view the contents of the updated data element.
    
    Specified by:
    
    updateEvaluationAsync in interface AmazonMachineLearningAsync
    
    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
```
public Future<UpdateMLModelResult> updateMLModelAsync(UpdateMLModelRequest request)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Updates the MLModelName and the ScoreThreshold of an MLModel.
    
    You can use the GetMLModel operation to view the contents of the updated data element.
    
    Specified by:
    
    updateMLModelAsync in interface AmazonMachineLearningAsync
    
    Returns:
    A Java Future containing the result of the UpdateMLModel operation returned by the service.
  - updateMLModelAsync
```
public Future<UpdateMLModelResult> updateMLModelAsync(UpdateMLModelRequest request,
                                             AsyncHandler<UpdateMLModelRequest,UpdateMLModelResult> asyncHandler)
```
    Description copied from interface: AmazonMachineLearningAsync
    
    Updates the MLModelName and the ScoreThreshold of an MLModel.
    
    You can use the GetMLModel operation to view the contents of the updated data element.
    
    Specified by:
    
    updateMLModelAsync in interface AmazonMachineLearningAsync
    
    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.
  - shutdown
```
public void shutdown()
```
    Shuts down the client, releasing all managed resources. This includes forcibly terminating all pending asynchronous service calls. Clients who wish to give pending asynchronous service calls time to complete should call getExecutorService().shutdown() followed by getExecutorService().awaitTermination() prior to calling this method.
    
    Specified by:
    
    shutdown in interface AmazonMachineLearning
    
    Overrides:
    
    shutdown in class AmazonWebServiceClient

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Class AmazonMachineLearningAsyncClient

Field Summary

Fields inherited from class com.amazonaws.AmazonWebServiceClient

Constructor Summary

Method Summary

Methods inherited from class com.amazonaws.services.machinelearning.AmazonMachineLearningClient

Methods inherited from class com.amazonaws.AmazonWebServiceClient

Methods inherited from class java.lang.Object

Methods inherited from interface com.amazonaws.services.machinelearning.AmazonMachineLearning

Constructor Detail

AmazonMachineLearningAsyncClient

AmazonMachineLearningAsyncClient

AmazonMachineLearningAsyncClient

AmazonMachineLearningAsyncClient

AmazonMachineLearningAsyncClient

AmazonMachineLearningAsyncClient

AmazonMachineLearningAsyncClient

AmazonMachineLearningAsyncClient

AmazonMachineLearningAsyncClient

Method Detail

getExecutorService

createBatchPredictionAsync

createBatchPredictionAsync

createDataSourceFromRDSAsync

createDataSourceFromRDSAsync

createDataSourceFromRedshiftAsync

createDataSourceFromRedshiftAsync

createDataSourceFromS3Async

createDataSourceFromS3Async

createEvaluationAsync

createEvaluationAsync

createMLModelAsync

createMLModelAsync

createRealtimeEndpointAsync

createRealtimeEndpointAsync

deleteBatchPredictionAsync

deleteBatchPredictionAsync

deleteDataSourceAsync

deleteDataSourceAsync

deleteEvaluationAsync

deleteEvaluationAsync

deleteMLModelAsync

deleteMLModelAsync

deleteRealtimeEndpointAsync

deleteRealtimeEndpointAsync

describeBatchPredictionsAsync

describeBatchPredictionsAsync

describeBatchPredictionsAsync

describeBatchPredictionsAsync

describeDataSourcesAsync

describeDataSourcesAsync

describeDataSourcesAsync

describeDataSourcesAsync

describeEvaluationsAsync

describeEvaluationsAsync

describeEvaluationsAsync

describeEvaluationsAsync

describeMLModelsAsync

describeMLModelsAsync

describeMLModelsAsync

describeMLModelsAsync

getBatchPredictionAsync

getBatchPredictionAsync

getDataSourceAsync

getDataSourceAsync

getEvaluationAsync

getEvaluationAsync

getMLModelAsync

getMLModelAsync

predictAsync

predictAsync

updateBatchPredictionAsync

updateBatchPredictionAsync

updateDataSourceAsync

updateDataSourceAsync

updateEvaluationAsync

updateEvaluationAsync

updateMLModelAsync

updateMLModelAsync