/*
* Copyright 2012-2017 Amazon.com, Inc. or its affiliates. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with
* the License. A copy of the License is located at
*
* http://aws.amazon.com/apache2.0
*
* or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
* CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions
* and limitations under the License.
*/
package com.amazonaws.services.machinelearning;
import javax.annotation.Generated;
import com.amazonaws.services.machinelearning.model.*;
/**
* Interface for accessing Amazon Machine Learning asynchronously. Each asynchronous method will return a Java Future
* object representing the asynchronous operation; overloads which accept an {@code AsyncHandler} can be used to receive
* notification when an asynchronous operation completes.
* <p>
* <b>Note:</b> Do not directly implement this interface, new methods are added to it regularly. Extend from
* {@link com.amazonaws.services.machinelearning.AbstractAmazonMachineLearningAsync} instead.
* </p>
* <p>
* Definition of the public APIs exposed by Amazon Machine Learning
*/
@Generated("com.amazonaws:aws-java-sdk-code-generator")
public interface AmazonMachineLearningAsync extends AmazonMachineLearning {
/**
* <p>
* Adds one or more tags to an object, up to a limit of 10. Each tag consists of a key and an optional value. If you
* add a tag using a key that is already associated with the ML object, <code>AddTags</code> updates the tag's
* value.
* </p>
*
* @param addTagsRequest
* @return A Java Future containing the result of the AddTags operation returned by the service.
* @sample AmazonMachineLearningAsync.AddTags
*/
java.util.concurrent.Future<AddTagsResult> addTagsAsync(AddTagsRequest addTagsRequest);
/**
* <p>
* Adds one or more tags to an object, up to a limit of 10. Each tag consists of a key and an optional value. If you
* add a tag using a key that is already associated with the ML object, <code>AddTags</code> updates the tag's
* value.
* </p>
*
* @param addTagsRequest
* @param 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.
* @return A Java Future containing the result of the AddTags operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.AddTags
*/
java.util.concurrent.Future<AddTagsResult> addTagsAsync(AddTagsRequest addTagsRequest,
com.amazonaws.handlers.AsyncHandler<AddTagsRequest, AddTagsResult> asyncHandler);
/**
* <p>
* Generates predictions for a group of observations. The observations to process exist in one or more data files
* referenced by a <code>DataSource</code>. This operation creates a new <code>BatchPrediction</code>, and uses an
* <code>MLModel</code> and the data files referenced by the <code>DataSource</code> as information sources.
* </p>
* <p>
* <code>CreateBatchPrediction</code> is an asynchronous operation. In response to
* <code>CreateBatchPrediction</code>, Amazon Machine Learning (Amazon ML) immediately returns and sets the
* <code>BatchPrediction</code> status to <code>PENDING</code>. After the <code>BatchPrediction</code> completes,
* Amazon ML sets the status to <code>COMPLETED</code>.
* </p>
* <p>
* You can poll for status updates by using the <a>GetBatchPrediction</a> operation and checking the
* <code>Status</code> parameter of the result. After the <code>COMPLETED</code> status appears, the results are
* available in the location specified by the <code>OutputUri</code> parameter.
* </p>
*
* @param createBatchPredictionRequest
* @return A Java Future containing the result of the CreateBatchPrediction operation returned by the service.
* @sample AmazonMachineLearningAsync.CreateBatchPrediction
*/
java.util.concurrent.Future<CreateBatchPredictionResult> createBatchPredictionAsync(CreateBatchPredictionRequest createBatchPredictionRequest);
/**
* <p>
* Generates predictions for a group of observations. The observations to process exist in one or more data files
* referenced by a <code>DataSource</code>. This operation creates a new <code>BatchPrediction</code>, and uses an
* <code>MLModel</code> and the data files referenced by the <code>DataSource</code> as information sources.
* </p>
* <p>
* <code>CreateBatchPrediction</code> is an asynchronous operation. In response to
* <code>CreateBatchPrediction</code>, Amazon Machine Learning (Amazon ML) immediately returns and sets the
* <code>BatchPrediction</code> status to <code>PENDING</code>. After the <code>BatchPrediction</code> completes,
* Amazon ML sets the status to <code>COMPLETED</code>.
* </p>
* <p>
* You can poll for status updates by using the <a>GetBatchPrediction</a> operation and checking the
* <code>Status</code> parameter of the result. After the <code>COMPLETED</code> status appears, the results are
* available in the location specified by the <code>OutputUri</code> parameter.
* </p>
*
* @param createBatchPredictionRequest
* @param 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.
* @return A Java Future containing the result of the CreateBatchPrediction operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.CreateBatchPrediction
*/
java.util.concurrent.Future<CreateBatchPredictionResult> createBatchPredictionAsync(CreateBatchPredictionRequest createBatchPredictionRequest,
com.amazonaws.handlers.AsyncHandler<CreateBatchPredictionRequest, CreateBatchPredictionResult> asyncHandler);
/**
* <p>
* Creates a <code>DataSource</code> object from an <a href="http://aws.amazon.com/rds/"> Amazon Relational Database
* Service</a> (Amazon RDS). A <code>DataSource</code> references data that can be used to perform
* <code>CreateMLModel</code>, <code>CreateEvaluation</code>, or <code>CreateBatchPrediction</code> operations.
* </p>
* <p>
* <code>CreateDataSourceFromRDS</code> is an asynchronous operation. In response to
* <code>CreateDataSourceFromRDS</code>, Amazon Machine Learning (Amazon ML) immediately returns and sets the
* <code>DataSource</code> status to <code>PENDING</code>. After the <code>DataSource</code> is created and ready
* for use, Amazon ML sets the <code>Status</code> parameter to <code>COMPLETED</code>. <code>DataSource</code> in
* the <code>COMPLETED</code> or <code>PENDING</code> state can be used only to perform
* <code>>CreateMLModel</code>>, <code>CreateEvaluation</code>, or <code>CreateBatchPrediction</code>
* operations.
* </p>
* <p>
* If Amazon ML cannot accept the input source, it sets the <code>Status</code> parameter to <code>FAILED</code> and
* includes an error message in the <code>Message</code> attribute of the <code>GetDataSource</code> operation
* response.
* </p>
*
* @param createDataSourceFromRDSRequest
* @return A Java Future containing the result of the CreateDataSourceFromRDS operation returned by the service.
* @sample AmazonMachineLearningAsync.CreateDataSourceFromRDS
*/
java.util.concurrent.Future<CreateDataSourceFromRDSResult> createDataSourceFromRDSAsync(CreateDataSourceFromRDSRequest createDataSourceFromRDSRequest);
/**
* <p>
* Creates a <code>DataSource</code> object from an <a href="http://aws.amazon.com/rds/"> Amazon Relational Database
* Service</a> (Amazon RDS). A <code>DataSource</code> references data that can be used to perform
* <code>CreateMLModel</code>, <code>CreateEvaluation</code>, or <code>CreateBatchPrediction</code> operations.
* </p>
* <p>
* <code>CreateDataSourceFromRDS</code> is an asynchronous operation. In response to
* <code>CreateDataSourceFromRDS</code>, Amazon Machine Learning (Amazon ML) immediately returns and sets the
* <code>DataSource</code> status to <code>PENDING</code>. After the <code>DataSource</code> is created and ready
* for use, Amazon ML sets the <code>Status</code> parameter to <code>COMPLETED</code>. <code>DataSource</code> in
* the <code>COMPLETED</code> or <code>PENDING</code> state can be used only to perform
* <code>>CreateMLModel</code>>, <code>CreateEvaluation</code>, or <code>CreateBatchPrediction</code>
* operations.
* </p>
* <p>
* If Amazon ML cannot accept the input source, it sets the <code>Status</code> parameter to <code>FAILED</code> and
* includes an error message in the <code>Message</code> attribute of the <code>GetDataSource</code> operation
* response.
* </p>
*
* @param createDataSourceFromRDSRequest
* @param 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.
* @return A Java Future containing the result of the CreateDataSourceFromRDS operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.CreateDataSourceFromRDS
*/
java.util.concurrent.Future<CreateDataSourceFromRDSResult> createDataSourceFromRDSAsync(CreateDataSourceFromRDSRequest createDataSourceFromRDSRequest,
com.amazonaws.handlers.AsyncHandler<CreateDataSourceFromRDSRequest, CreateDataSourceFromRDSResult> asyncHandler);
/**
* <p>
* Creates a <code>DataSource</code> from a database hosted on an Amazon Redshift cluster. A <code>DataSource</code>
* references data that can be used to perform either <code>CreateMLModel</code>, <code>CreateEvaluation</code>, or
* <code>CreateBatchPrediction</code> operations.
* </p>
* <p>
* <code>CreateDataSourceFromRedshift</code> is an asynchronous operation. In response to
* <code>CreateDataSourceFromRedshift</code>, Amazon Machine Learning (Amazon ML) immediately returns and sets the
* <code>DataSource</code> status to <code>PENDING</code>. After the <code>DataSource</code> is created and ready
* for use, Amazon ML sets the <code>Status</code> parameter to <code>COMPLETED</code>. <code>DataSource</code> in
* <code>COMPLETED</code> or <code>PENDING</code> states can be used to perform only <code>CreateMLModel</code>,
* <code>CreateEvaluation</code>, or <code>CreateBatchPrediction</code> operations.
* </p>
* <p>
* If Amazon ML can't accept the input source, it sets the <code>Status</code> parameter to <code>FAILED</code> and
* includes an error message in the <code>Message</code> attribute of the <code>GetDataSource</code> operation
* response.
* </p>
* <p>
* The observations should be contained in the database hosted on an Amazon Redshift cluster and should be specified
* by a <code>SelectSqlQuery</code> query. Amazon ML executes an <code>Unload</code> command in Amazon Redshift to
* transfer the result set of the <code>SelectSqlQuery</code> query to <code>S3StagingLocation</code>.
* </p>
* <p>
* After the <code>DataSource</code> has been created, it's ready for use in evaluations and batch predictions. If
* you plan to use the <code>DataSource</code> to train an <code>MLModel</code>, the <code>DataSource</code> also
* requires a recipe. A recipe describes how each input variable will be used in training an <code>MLModel</code>.
* Will the variable be included or excluded from training? Will the variable be manipulated; for example, will it
* be combined with another variable or will it be split apart into word combinations? The recipe provides answers
* to these questions.
* </p>
* <?oxy_insert_start author="laurama" timestamp="20160406T153842-0700">
* <p>
* You can't change an existing datasource, but you can copy and modify the settings from an existing Amazon
* Redshift datasource to create a new datasource. To do so, call <code>GetDataSource</code> for an existing
* datasource and copy the values to a <code>CreateDataSource</code> call. Change the settings that you want to
* change and make sure that all required fields have the appropriate values.
* </p>
* <?oxy_insert_end>
*
* @param createDataSourceFromRedshiftRequest
* @return A Java Future containing the result of the CreateDataSourceFromRedshift operation returned by the
* service.
* @sample AmazonMachineLearningAsync.CreateDataSourceFromRedshift
*/
java.util.concurrent.Future<CreateDataSourceFromRedshiftResult> createDataSourceFromRedshiftAsync(
CreateDataSourceFromRedshiftRequest createDataSourceFromRedshiftRequest);
/**
* <p>
* Creates a <code>DataSource</code> from a database hosted on an Amazon Redshift cluster. A <code>DataSource</code>
* references data that can be used to perform either <code>CreateMLModel</code>, <code>CreateEvaluation</code>, or
* <code>CreateBatchPrediction</code> operations.
* </p>
* <p>
* <code>CreateDataSourceFromRedshift</code> is an asynchronous operation. In response to
* <code>CreateDataSourceFromRedshift</code>, Amazon Machine Learning (Amazon ML) immediately returns and sets the
* <code>DataSource</code> status to <code>PENDING</code>. After the <code>DataSource</code> is created and ready
* for use, Amazon ML sets the <code>Status</code> parameter to <code>COMPLETED</code>. <code>DataSource</code> in
* <code>COMPLETED</code> or <code>PENDING</code> states can be used to perform only <code>CreateMLModel</code>,
* <code>CreateEvaluation</code>, or <code>CreateBatchPrediction</code> operations.
* </p>
* <p>
* If Amazon ML can't accept the input source, it sets the <code>Status</code> parameter to <code>FAILED</code> and
* includes an error message in the <code>Message</code> attribute of the <code>GetDataSource</code> operation
* response.
* </p>
* <p>
* The observations should be contained in the database hosted on an Amazon Redshift cluster and should be specified
* by a <code>SelectSqlQuery</code> query. Amazon ML executes an <code>Unload</code> command in Amazon Redshift to
* transfer the result set of the <code>SelectSqlQuery</code> query to <code>S3StagingLocation</code>.
* </p>
* <p>
* After the <code>DataSource</code> has been created, it's ready for use in evaluations and batch predictions. If
* you plan to use the <code>DataSource</code> to train an <code>MLModel</code>, the <code>DataSource</code> also
* requires a recipe. A recipe describes how each input variable will be used in training an <code>MLModel</code>.
* Will the variable be included or excluded from training? Will the variable be manipulated; for example, will it
* be combined with another variable or will it be split apart into word combinations? The recipe provides answers
* to these questions.
* </p>
* <?oxy_insert_start author="laurama" timestamp="20160406T153842-0700">
* <p>
* You can't change an existing datasource, but you can copy and modify the settings from an existing Amazon
* Redshift datasource to create a new datasource. To do so, call <code>GetDataSource</code> for an existing
* datasource and copy the values to a <code>CreateDataSource</code> call. Change the settings that you want to
* change and make sure that all required fields have the appropriate values.
* </p>
* <?oxy_insert_end>
*
* @param createDataSourceFromRedshiftRequest
* @param 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.
* @return A Java Future containing the result of the CreateDataSourceFromRedshift operation returned by the
* service.
* @sample AmazonMachineLearningAsyncHandler.CreateDataSourceFromRedshift
*/
java.util.concurrent.Future<CreateDataSourceFromRedshiftResult> createDataSourceFromRedshiftAsync(
CreateDataSourceFromRedshiftRequest createDataSourceFromRedshiftRequest,
com.amazonaws.handlers.AsyncHandler<CreateDataSourceFromRedshiftRequest, CreateDataSourceFromRedshiftResult> asyncHandler);
/**
* <p>
* Creates a <code>DataSource</code> object. A <code>DataSource</code> references data that can be used to perform
* <code>CreateMLModel</code>, <code>CreateEvaluation</code>, or <code>CreateBatchPrediction</code> operations.
* </p>
* <p>
* <code>CreateDataSourceFromS3</code> is an asynchronous operation. In response to
* <code>CreateDataSourceFromS3</code>, Amazon Machine Learning (Amazon ML) immediately returns and sets the
* <code>DataSource</code> status to <code>PENDING</code>. After the <code>DataSource</code> has been created and is
* ready for use, Amazon ML sets the <code>Status</code> parameter to <code>COMPLETED</code>.
* <code>DataSource</code> in the <code>COMPLETED</code> or <code>PENDING</code> state can be used to perform only
* <code>CreateMLModel</code>, <code>CreateEvaluation</code> or <code>CreateBatchPrediction</code> operations.
* </p>
* <p>
* If Amazon ML can't accept the input source, it sets the <code>Status</code> parameter to <code>FAILED</code> and
* includes an error message in the <code>Message</code> attribute of the <code>GetDataSource</code> operation
* response.
* </p>
* <p>
* The observation data used in a <code>DataSource</code> should be ready to use; that is, it should have a
* consistent structure, and missing data values should be kept to a minimum. The observation data must reside in
* one or more .csv files in an Amazon Simple Storage Service (Amazon S3) location, along with a schema that
* describes the data items by name and type. The same schema must be used for all of the data files referenced by
* the <code>DataSource</code>.
* </p>
* <p>
* After the <code>DataSource</code> has been created, it's ready to use in evaluations and batch predictions. If
* you plan to use the <code>DataSource</code> to train an <code>MLModel</code>, the <code>DataSource</code> also
* needs a recipe. A recipe describes how each input variable will be used in training an <code>MLModel</code>. Will
* the variable be included or excluded from training? Will the variable be manipulated; for example, will it be
* combined with another variable or will it be split apart into word combinations? The recipe provides answers to
* these questions.
* </p>
*
* @param createDataSourceFromS3Request
* @return A Java Future containing the result of the CreateDataSourceFromS3 operation returned by the service.
* @sample AmazonMachineLearningAsync.CreateDataSourceFromS3
*/
java.util.concurrent.Future<CreateDataSourceFromS3Result> createDataSourceFromS3Async(CreateDataSourceFromS3Request createDataSourceFromS3Request);
/**
* <p>
* Creates a <code>DataSource</code> object. A <code>DataSource</code> references data that can be used to perform
* <code>CreateMLModel</code>, <code>CreateEvaluation</code>, or <code>CreateBatchPrediction</code> operations.
* </p>
* <p>
* <code>CreateDataSourceFromS3</code> is an asynchronous operation. In response to
* <code>CreateDataSourceFromS3</code>, Amazon Machine Learning (Amazon ML) immediately returns and sets the
* <code>DataSource</code> status to <code>PENDING</code>. After the <code>DataSource</code> has been created and is
* ready for use, Amazon ML sets the <code>Status</code> parameter to <code>COMPLETED</code>.
* <code>DataSource</code> in the <code>COMPLETED</code> or <code>PENDING</code> state can be used to perform only
* <code>CreateMLModel</code>, <code>CreateEvaluation</code> or <code>CreateBatchPrediction</code> operations.
* </p>
* <p>
* If Amazon ML can't accept the input source, it sets the <code>Status</code> parameter to <code>FAILED</code> and
* includes an error message in the <code>Message</code> attribute of the <code>GetDataSource</code> operation
* response.
* </p>
* <p>
* The observation data used in a <code>DataSource</code> should be ready to use; that is, it should have a
* consistent structure, and missing data values should be kept to a minimum. The observation data must reside in
* one or more .csv files in an Amazon Simple Storage Service (Amazon S3) location, along with a schema that
* describes the data items by name and type. The same schema must be used for all of the data files referenced by
* the <code>DataSource</code>.
* </p>
* <p>
* After the <code>DataSource</code> has been created, it's ready to use in evaluations and batch predictions. If
* you plan to use the <code>DataSource</code> to train an <code>MLModel</code>, the <code>DataSource</code> also
* needs a recipe. A recipe describes how each input variable will be used in training an <code>MLModel</code>. Will
* the variable be included or excluded from training? Will the variable be manipulated; for example, will it be
* combined with another variable or will it be split apart into word combinations? The recipe provides answers to
* these questions.
* </p>
*
* @param createDataSourceFromS3Request
* @param 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.
* @return A Java Future containing the result of the CreateDataSourceFromS3 operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.CreateDataSourceFromS3
*/
java.util.concurrent.Future<CreateDataSourceFromS3Result> createDataSourceFromS3Async(CreateDataSourceFromS3Request createDataSourceFromS3Request,
com.amazonaws.handlers.AsyncHandler<CreateDataSourceFromS3Request, CreateDataSourceFromS3Result> asyncHandler);
/**
* <p>
* Creates a new <code>Evaluation</code> of an <code>MLModel</code>. An <code>MLModel</code> is evaluated on a set
* of observations associated to a <code>DataSource</code>. Like a <code>DataSource</code> for an
* <code>MLModel</code>, the <code>DataSource</code> for an <code>Evaluation</code> contains values for the
* <code>Target Variable</code>. The <code>Evaluation</code> compares the predicted result for each observation to
* the actual outcome and provides a summary so that you know how effective the <code>MLModel</code> functions on
* the test data. Evaluation generates a relevant performance metric, such as BinaryAUC, RegressionRMSE or
* MulticlassAvgFScore based on the corresponding <code>MLModelType</code>: <code>BINARY</code>,
* <code>REGRESSION</code> or <code>MULTICLASS</code>.
* </p>
* <p>
* <code>CreateEvaluation</code> is an asynchronous operation. In response to <code>CreateEvaluation</code>, Amazon
* Machine Learning (Amazon ML) immediately returns and sets the evaluation status to <code>PENDING</code>. After
* the <code>Evaluation</code> is created and ready for use, Amazon ML sets the status to <code>COMPLETED</code>.
* </p>
* <p>
* You can use the <code>GetEvaluation</code> operation to check progress of the evaluation during the creation
* operation.
* </p>
*
* @param createEvaluationRequest
* @return A Java Future containing the result of the CreateEvaluation operation returned by the service.
* @sample AmazonMachineLearningAsync.CreateEvaluation
*/
java.util.concurrent.Future<CreateEvaluationResult> createEvaluationAsync(CreateEvaluationRequest createEvaluationRequest);
/**
* <p>
* Creates a new <code>Evaluation</code> of an <code>MLModel</code>. An <code>MLModel</code> is evaluated on a set
* of observations associated to a <code>DataSource</code>. Like a <code>DataSource</code> for an
* <code>MLModel</code>, the <code>DataSource</code> for an <code>Evaluation</code> contains values for the
* <code>Target Variable</code>. The <code>Evaluation</code> compares the predicted result for each observation to
* the actual outcome and provides a summary so that you know how effective the <code>MLModel</code> functions on
* the test data. Evaluation generates a relevant performance metric, such as BinaryAUC, RegressionRMSE or
* MulticlassAvgFScore based on the corresponding <code>MLModelType</code>: <code>BINARY</code>,
* <code>REGRESSION</code> or <code>MULTICLASS</code>.
* </p>
* <p>
* <code>CreateEvaluation</code> is an asynchronous operation. In response to <code>CreateEvaluation</code>, Amazon
* Machine Learning (Amazon ML) immediately returns and sets the evaluation status to <code>PENDING</code>. After
* the <code>Evaluation</code> is created and ready for use, Amazon ML sets the status to <code>COMPLETED</code>.
* </p>
* <p>
* You can use the <code>GetEvaluation</code> operation to check progress of the evaluation during the creation
* operation.
* </p>
*
* @param createEvaluationRequest
* @param 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.
* @return A Java Future containing the result of the CreateEvaluation operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.CreateEvaluation
*/
java.util.concurrent.Future<CreateEvaluationResult> createEvaluationAsync(CreateEvaluationRequest createEvaluationRequest,
com.amazonaws.handlers.AsyncHandler<CreateEvaluationRequest, CreateEvaluationResult> asyncHandler);
/**
* <p>
* Creates a new <code>MLModel</code> using the <code>DataSource</code> and the recipe as information sources.
* </p>
* <p>
* An <code>MLModel</code> is nearly immutable. Users can update only the <code>MLModelName</code> and the
* <code>ScoreThreshold</code> in an <code>MLModel</code> without creating a new <code>MLModel</code>.
* </p>
* <p>
* <code>CreateMLModel</code> is an asynchronous operation. In response to <code>CreateMLModel</code>, Amazon
* Machine Learning (Amazon ML) immediately returns and sets the <code>MLModel</code> status to <code>PENDING</code>
* . After the <code>MLModel</code> has been created and ready is for use, Amazon ML sets the status to
* <code>COMPLETED</code>.
* </p>
* <p>
* You can use the <code>GetMLModel</code> operation to check the progress of the <code>MLModel</code> during the
* creation operation.
* </p>
* <p>
* <code>CreateMLModel</code> requires a <code>DataSource</code> with computed statistics, which can be created by
* setting <code>ComputeStatistics</code> to <code>true</code> in <code>CreateDataSourceFromRDS</code>,
* <code>CreateDataSourceFromS3</code>, or <code>CreateDataSourceFromRedshift</code> operations.
* </p>
*
* @param createMLModelRequest
* @return A Java Future containing the result of the CreateMLModel operation returned by the service.
* @sample AmazonMachineLearningAsync.CreateMLModel
*/
java.util.concurrent.Future<CreateMLModelResult> createMLModelAsync(CreateMLModelRequest createMLModelRequest);
/**
* <p>
* Creates a new <code>MLModel</code> using the <code>DataSource</code> and the recipe as information sources.
* </p>
* <p>
* An <code>MLModel</code> is nearly immutable. Users can update only the <code>MLModelName</code> and the
* <code>ScoreThreshold</code> in an <code>MLModel</code> without creating a new <code>MLModel</code>.
* </p>
* <p>
* <code>CreateMLModel</code> is an asynchronous operation. In response to <code>CreateMLModel</code>, Amazon
* Machine Learning (Amazon ML) immediately returns and sets the <code>MLModel</code> status to <code>PENDING</code>
* . After the <code>MLModel</code> has been created and ready is for use, Amazon ML sets the status to
* <code>COMPLETED</code>.
* </p>
* <p>
* You can use the <code>GetMLModel</code> operation to check the progress of the <code>MLModel</code> during the
* creation operation.
* </p>
* <p>
* <code>CreateMLModel</code> requires a <code>DataSource</code> with computed statistics, which can be created by
* setting <code>ComputeStatistics</code> to <code>true</code> in <code>CreateDataSourceFromRDS</code>,
* <code>CreateDataSourceFromS3</code>, or <code>CreateDataSourceFromRedshift</code> operations.
* </p>
*
* @param createMLModelRequest
* @param 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.
* @return A Java Future containing the result of the CreateMLModel operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.CreateMLModel
*/
java.util.concurrent.Future<CreateMLModelResult> createMLModelAsync(CreateMLModelRequest createMLModelRequest,
com.amazonaws.handlers.AsyncHandler<CreateMLModelRequest, CreateMLModelResult> asyncHandler);
/**
* <p>
* Creates a real-time endpoint for the <code>MLModel</code>. The endpoint contains the URI of the
* <code>MLModel</code>; that is, the location to send real-time prediction requests for the specified
* <code>MLModel</code>.
* </p>
*
* @param createRealtimeEndpointRequest
* @return A Java Future containing the result of the CreateRealtimeEndpoint operation returned by the service.
* @sample AmazonMachineLearningAsync.CreateRealtimeEndpoint
*/
java.util.concurrent.Future<CreateRealtimeEndpointResult> createRealtimeEndpointAsync(CreateRealtimeEndpointRequest createRealtimeEndpointRequest);
/**
* <p>
* Creates a real-time endpoint for the <code>MLModel</code>. The endpoint contains the URI of the
* <code>MLModel</code>; that is, the location to send real-time prediction requests for the specified
* <code>MLModel</code>.
* </p>
*
* @param createRealtimeEndpointRequest
* @param 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.
* @return A Java Future containing the result of the CreateRealtimeEndpoint operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.CreateRealtimeEndpoint
*/
java.util.concurrent.Future<CreateRealtimeEndpointResult> createRealtimeEndpointAsync(CreateRealtimeEndpointRequest createRealtimeEndpointRequest,
com.amazonaws.handlers.AsyncHandler<CreateRealtimeEndpointRequest, CreateRealtimeEndpointResult> asyncHandler);
/**
* <p>
* Assigns the DELETED status to a <code>BatchPrediction</code>, rendering it unusable.
* </p>
* <p>
* After using the <code>DeleteBatchPrediction</code> operation, you can use the <a>GetBatchPrediction</a> operation
* to verify that the status of the <code>BatchPrediction</code> changed to DELETED.
* </p>
* <p>
* <b>Caution:</b> The result of the <code>DeleteBatchPrediction</code> operation is irreversible.
* </p>
*
* @param deleteBatchPredictionRequest
* @return A Java Future containing the result of the DeleteBatchPrediction operation returned by the service.
* @sample AmazonMachineLearningAsync.DeleteBatchPrediction
*/
java.util.concurrent.Future<DeleteBatchPredictionResult> deleteBatchPredictionAsync(DeleteBatchPredictionRequest deleteBatchPredictionRequest);
/**
* <p>
* Assigns the DELETED status to a <code>BatchPrediction</code>, rendering it unusable.
* </p>
* <p>
* After using the <code>DeleteBatchPrediction</code> operation, you can use the <a>GetBatchPrediction</a> operation
* to verify that the status of the <code>BatchPrediction</code> changed to DELETED.
* </p>
* <p>
* <b>Caution:</b> The result of the <code>DeleteBatchPrediction</code> operation is irreversible.
* </p>
*
* @param deleteBatchPredictionRequest
* @param 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.
* @return A Java Future containing the result of the DeleteBatchPrediction operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.DeleteBatchPrediction
*/
java.util.concurrent.Future<DeleteBatchPredictionResult> deleteBatchPredictionAsync(DeleteBatchPredictionRequest deleteBatchPredictionRequest,
com.amazonaws.handlers.AsyncHandler<DeleteBatchPredictionRequest, DeleteBatchPredictionResult> asyncHandler);
/**
* <p>
* Assigns the DELETED status to a <code>DataSource</code>, rendering it unusable.
* </p>
* <p>
* After using the <code>DeleteDataSource</code> operation, you can use the <a>GetDataSource</a> operation to verify
* that the status of the <code>DataSource</code> changed to DELETED.
* </p>
* <p>
* <b>Caution:</b> The results of the <code>DeleteDataSource</code> operation are irreversible.
* </p>
*
* @param deleteDataSourceRequest
* @return A Java Future containing the result of the DeleteDataSource operation returned by the service.
* @sample AmazonMachineLearningAsync.DeleteDataSource
*/
java.util.concurrent.Future<DeleteDataSourceResult> deleteDataSourceAsync(DeleteDataSourceRequest deleteDataSourceRequest);
/**
* <p>
* Assigns the DELETED status to a <code>DataSource</code>, rendering it unusable.
* </p>
* <p>
* After using the <code>DeleteDataSource</code> operation, you can use the <a>GetDataSource</a> operation to verify
* that the status of the <code>DataSource</code> changed to DELETED.
* </p>
* <p>
* <b>Caution:</b> The results of the <code>DeleteDataSource</code> operation are irreversible.
* </p>
*
* @param deleteDataSourceRequest
* @param 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.
* @return A Java Future containing the result of the DeleteDataSource operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.DeleteDataSource
*/
java.util.concurrent.Future<DeleteDataSourceResult> deleteDataSourceAsync(DeleteDataSourceRequest deleteDataSourceRequest,
com.amazonaws.handlers.AsyncHandler<DeleteDataSourceRequest, DeleteDataSourceResult> asyncHandler);
/**
* <p>
* Assigns the <code>DELETED</code> status to an <code>Evaluation</code>, rendering it unusable.
* </p>
* <p>
* After invoking the <code>DeleteEvaluation</code> operation, you can use the <code>GetEvaluation</code> operation
* to verify that the status of the <code>Evaluation</code> changed to <code>DELETED</code>.
* </p>
* <caution><title>Caution</title>
* <p>
* The results of the <code>DeleteEvaluation</code> operation are irreversible.
* </p>
* </caution>
*
* @param deleteEvaluationRequest
* @return A Java Future containing the result of the DeleteEvaluation operation returned by the service.
* @sample AmazonMachineLearningAsync.DeleteEvaluation
*/
java.util.concurrent.Future<DeleteEvaluationResult> deleteEvaluationAsync(DeleteEvaluationRequest deleteEvaluationRequest);
/**
* <p>
* Assigns the <code>DELETED</code> status to an <code>Evaluation</code>, rendering it unusable.
* </p>
* <p>
* After invoking the <code>DeleteEvaluation</code> operation, you can use the <code>GetEvaluation</code> operation
* to verify that the status of the <code>Evaluation</code> changed to <code>DELETED</code>.
* </p>
* <caution><title>Caution</title>
* <p>
* The results of the <code>DeleteEvaluation</code> operation are irreversible.
* </p>
* </caution>
*
* @param deleteEvaluationRequest
* @param 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.
* @return A Java Future containing the result of the DeleteEvaluation operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.DeleteEvaluation
*/
java.util.concurrent.Future<DeleteEvaluationResult> deleteEvaluationAsync(DeleteEvaluationRequest deleteEvaluationRequest,
com.amazonaws.handlers.AsyncHandler<DeleteEvaluationRequest, DeleteEvaluationResult> asyncHandler);
/**
* <p>
* Assigns the <code>DELETED</code> status to an <code>MLModel</code>, rendering it unusable.
* </p>
* <p>
* After using the <code>DeleteMLModel</code> operation, you can use the <code>GetMLModel</code> operation to verify
* that the status of the <code>MLModel</code> changed to DELETED.
* </p>
* <p>
* <b>Caution:</b> The result of the <code>DeleteMLModel</code> operation is irreversible.
* </p>
*
* @param deleteMLModelRequest
* @return A Java Future containing the result of the DeleteMLModel operation returned by the service.
* @sample AmazonMachineLearningAsync.DeleteMLModel
*/
java.util.concurrent.Future<DeleteMLModelResult> deleteMLModelAsync(DeleteMLModelRequest deleteMLModelRequest);
/**
* <p>
* Assigns the <code>DELETED</code> status to an <code>MLModel</code>, rendering it unusable.
* </p>
* <p>
* After using the <code>DeleteMLModel</code> operation, you can use the <code>GetMLModel</code> operation to verify
* that the status of the <code>MLModel</code> changed to DELETED.
* </p>
* <p>
* <b>Caution:</b> The result of the <code>DeleteMLModel</code> operation is irreversible.
* </p>
*
* @param deleteMLModelRequest
* @param 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.
* @return A Java Future containing the result of the DeleteMLModel operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.DeleteMLModel
*/
java.util.concurrent.Future<DeleteMLModelResult> deleteMLModelAsync(DeleteMLModelRequest deleteMLModelRequest,
com.amazonaws.handlers.AsyncHandler<DeleteMLModelRequest, DeleteMLModelResult> asyncHandler);
/**
* <p>
* Deletes a real time endpoint of an <code>MLModel</code>.
* </p>
*
* @param deleteRealtimeEndpointRequest
* @return A Java Future containing the result of the DeleteRealtimeEndpoint operation returned by the service.
* @sample AmazonMachineLearningAsync.DeleteRealtimeEndpoint
*/
java.util.concurrent.Future<DeleteRealtimeEndpointResult> deleteRealtimeEndpointAsync(DeleteRealtimeEndpointRequest deleteRealtimeEndpointRequest);
/**
* <p>
* Deletes a real time endpoint of an <code>MLModel</code>.
* </p>
*
* @param deleteRealtimeEndpointRequest
* @param 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.
* @return A Java Future containing the result of the DeleteRealtimeEndpoint operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.DeleteRealtimeEndpoint
*/
java.util.concurrent.Future<DeleteRealtimeEndpointResult> deleteRealtimeEndpointAsync(DeleteRealtimeEndpointRequest deleteRealtimeEndpointRequest,
com.amazonaws.handlers.AsyncHandler<DeleteRealtimeEndpointRequest, DeleteRealtimeEndpointResult> asyncHandler);
/**
* <p>
* Deletes the specified tags associated with an ML object. After this operation is complete, you can't recover
* deleted tags.
* </p>
* <p>
* If you specify a tag that doesn't exist, Amazon ML ignores it.
* </p>
*
* @param deleteTagsRequest
* @return A Java Future containing the result of the DeleteTags operation returned by the service.
* @sample AmazonMachineLearningAsync.DeleteTags
*/
java.util.concurrent.Future<DeleteTagsResult> deleteTagsAsync(DeleteTagsRequest deleteTagsRequest);
/**
* <p>
* Deletes the specified tags associated with an ML object. After this operation is complete, you can't recover
* deleted tags.
* </p>
* <p>
* If you specify a tag that doesn't exist, Amazon ML ignores it.
* </p>
*
* @param deleteTagsRequest
* @param 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.
* @return A Java Future containing the result of the DeleteTags operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.DeleteTags
*/
java.util.concurrent.Future<DeleteTagsResult> deleteTagsAsync(DeleteTagsRequest deleteTagsRequest,
com.amazonaws.handlers.AsyncHandler<DeleteTagsRequest, DeleteTagsResult> asyncHandler);
/**
* <p>
* Returns a list of <code>BatchPrediction</code> operations that match the search criteria in the request.
* </p>
*
* @param describeBatchPredictionsRequest
* @return A Java Future containing the result of the DescribeBatchPredictions operation returned by the service.
* @sample AmazonMachineLearningAsync.DescribeBatchPredictions
*/
java.util.concurrent.Future<DescribeBatchPredictionsResult> describeBatchPredictionsAsync(DescribeBatchPredictionsRequest describeBatchPredictionsRequest);
/**
* <p>
* Returns a list of <code>BatchPrediction</code> operations that match the search criteria in the request.
* </p>
*
* @param describeBatchPredictionsRequest
* @param 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.
* @return A Java Future containing the result of the DescribeBatchPredictions operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.DescribeBatchPredictions
*/
java.util.concurrent.Future<DescribeBatchPredictionsResult> describeBatchPredictionsAsync(DescribeBatchPredictionsRequest describeBatchPredictionsRequest,
com.amazonaws.handlers.AsyncHandler<DescribeBatchPredictionsRequest, DescribeBatchPredictionsResult> asyncHandler);
/**
* Simplified method form for invoking the DescribeBatchPredictions operation.
*
* @see #describeBatchPredictionsAsync(DescribeBatchPredictionsRequest)
*/
java.util.concurrent.Future<DescribeBatchPredictionsResult> describeBatchPredictionsAsync();
/**
* Simplified method form for invoking the DescribeBatchPredictions operation with an AsyncHandler.
*
* @see #describeBatchPredictionsAsync(DescribeBatchPredictionsRequest, com.amazonaws.handlers.AsyncHandler)
*/
java.util.concurrent.Future<DescribeBatchPredictionsResult> describeBatchPredictionsAsync(
com.amazonaws.handlers.AsyncHandler<DescribeBatchPredictionsRequest, DescribeBatchPredictionsResult> asyncHandler);
/**
* <p>
* Returns a list of <code>DataSource</code> that match the search criteria in the request.
* </p>
*
* @param describeDataSourcesRequest
* @return A Java Future containing the result of the DescribeDataSources operation returned by the service.
* @sample AmazonMachineLearningAsync.DescribeDataSources
*/
java.util.concurrent.Future<DescribeDataSourcesResult> describeDataSourcesAsync(DescribeDataSourcesRequest describeDataSourcesRequest);
/**
* <p>
* Returns a list of <code>DataSource</code> that match the search criteria in the request.
* </p>
*
* @param describeDataSourcesRequest
* @param 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.
* @return A Java Future containing the result of the DescribeDataSources operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.DescribeDataSources
*/
java.util.concurrent.Future<DescribeDataSourcesResult> describeDataSourcesAsync(DescribeDataSourcesRequest describeDataSourcesRequest,
com.amazonaws.handlers.AsyncHandler<DescribeDataSourcesRequest, DescribeDataSourcesResult> asyncHandler);
/**
* Simplified method form for invoking the DescribeDataSources operation.
*
* @see #describeDataSourcesAsync(DescribeDataSourcesRequest)
*/
java.util.concurrent.Future<DescribeDataSourcesResult> describeDataSourcesAsync();
/**
* Simplified method form for invoking the DescribeDataSources operation with an AsyncHandler.
*
* @see #describeDataSourcesAsync(DescribeDataSourcesRequest, com.amazonaws.handlers.AsyncHandler)
*/
java.util.concurrent.Future<DescribeDataSourcesResult> describeDataSourcesAsync(
com.amazonaws.handlers.AsyncHandler<DescribeDataSourcesRequest, DescribeDataSourcesResult> asyncHandler);
/**
* <p>
* Returns a list of <code>DescribeEvaluations</code> that match the search criteria in the request.
* </p>
*
* @param describeEvaluationsRequest
* @return A Java Future containing the result of the DescribeEvaluations operation returned by the service.
* @sample AmazonMachineLearningAsync.DescribeEvaluations
*/
java.util.concurrent.Future<DescribeEvaluationsResult> describeEvaluationsAsync(DescribeEvaluationsRequest describeEvaluationsRequest);
/**
* <p>
* Returns a list of <code>DescribeEvaluations</code> that match the search criteria in the request.
* </p>
*
* @param describeEvaluationsRequest
* @param 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.
* @return A Java Future containing the result of the DescribeEvaluations operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.DescribeEvaluations
*/
java.util.concurrent.Future<DescribeEvaluationsResult> describeEvaluationsAsync(DescribeEvaluationsRequest describeEvaluationsRequest,
com.amazonaws.handlers.AsyncHandler<DescribeEvaluationsRequest, DescribeEvaluationsResult> asyncHandler);
/**
* Simplified method form for invoking the DescribeEvaluations operation.
*
* @see #describeEvaluationsAsync(DescribeEvaluationsRequest)
*/
java.util.concurrent.Future<DescribeEvaluationsResult> describeEvaluationsAsync();
/**
* Simplified method form for invoking the DescribeEvaluations operation with an AsyncHandler.
*
* @see #describeEvaluationsAsync(DescribeEvaluationsRequest, com.amazonaws.handlers.AsyncHandler)
*/
java.util.concurrent.Future<DescribeEvaluationsResult> describeEvaluationsAsync(
com.amazonaws.handlers.AsyncHandler<DescribeEvaluationsRequest, DescribeEvaluationsResult> asyncHandler);
/**
* <p>
* Returns a list of <code>MLModel</code> that match the search criteria in the request.
* </p>
*
* @param describeMLModelsRequest
* @return A Java Future containing the result of the DescribeMLModels operation returned by the service.
* @sample AmazonMachineLearningAsync.DescribeMLModels
*/
java.util.concurrent.Future<DescribeMLModelsResult> describeMLModelsAsync(DescribeMLModelsRequest describeMLModelsRequest);
/**
* <p>
* Returns a list of <code>MLModel</code> that match the search criteria in the request.
* </p>
*
* @param describeMLModelsRequest
* @param 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.
* @return A Java Future containing the result of the DescribeMLModels operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.DescribeMLModels
*/
java.util.concurrent.Future<DescribeMLModelsResult> describeMLModelsAsync(DescribeMLModelsRequest describeMLModelsRequest,
com.amazonaws.handlers.AsyncHandler<DescribeMLModelsRequest, DescribeMLModelsResult> asyncHandler);
/**
* Simplified method form for invoking the DescribeMLModels operation.
*
* @see #describeMLModelsAsync(DescribeMLModelsRequest)
*/
java.util.concurrent.Future<DescribeMLModelsResult> describeMLModelsAsync();
/**
* Simplified method form for invoking the DescribeMLModels operation with an AsyncHandler.
*
* @see #describeMLModelsAsync(DescribeMLModelsRequest, com.amazonaws.handlers.AsyncHandler)
*/
java.util.concurrent.Future<DescribeMLModelsResult> describeMLModelsAsync(
com.amazonaws.handlers.AsyncHandler<DescribeMLModelsRequest, DescribeMLModelsResult> asyncHandler);
/**
* <p>
* Describes one or more of the tags for your Amazon ML object.
* </p>
*
* @param describeTagsRequest
* @return A Java Future containing the result of the DescribeTags operation returned by the service.
* @sample AmazonMachineLearningAsync.DescribeTags
*/
java.util.concurrent.Future<DescribeTagsResult> describeTagsAsync(DescribeTagsRequest describeTagsRequest);
/**
* <p>
* Describes one or more of the tags for your Amazon ML object.
* </p>
*
* @param describeTagsRequest
* @param 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.
* @return A Java Future containing the result of the DescribeTags operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.DescribeTags
*/
java.util.concurrent.Future<DescribeTagsResult> describeTagsAsync(DescribeTagsRequest describeTagsRequest,
com.amazonaws.handlers.AsyncHandler<DescribeTagsRequest, DescribeTagsResult> asyncHandler);
/**
* <p>
* Returns a <code>BatchPrediction</code> that includes detailed metadata, status, and data file information for a
* <code>Batch Prediction</code> request.
* </p>
*
* @param getBatchPredictionRequest
* @return A Java Future containing the result of the GetBatchPrediction operation returned by the service.
* @sample AmazonMachineLearningAsync.GetBatchPrediction
*/
java.util.concurrent.Future<GetBatchPredictionResult> getBatchPredictionAsync(GetBatchPredictionRequest getBatchPredictionRequest);
/**
* <p>
* Returns a <code>BatchPrediction</code> that includes detailed metadata, status, and data file information for a
* <code>Batch Prediction</code> request.
* </p>
*
* @param getBatchPredictionRequest
* @param 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.
* @return A Java Future containing the result of the GetBatchPrediction operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.GetBatchPrediction
*/
java.util.concurrent.Future<GetBatchPredictionResult> getBatchPredictionAsync(GetBatchPredictionRequest getBatchPredictionRequest,
com.amazonaws.handlers.AsyncHandler<GetBatchPredictionRequest, GetBatchPredictionResult> asyncHandler);
/**
* <p>
* Returns a <code>DataSource</code> that includes metadata and data file information, as well as the current status
* of the <code>DataSource</code>.
* </p>
* <p>
* <code>GetDataSource</code> 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.
* </p>
*
* @param getDataSourceRequest
* @return A Java Future containing the result of the GetDataSource operation returned by the service.
* @sample AmazonMachineLearningAsync.GetDataSource
*/
java.util.concurrent.Future<GetDataSourceResult> getDataSourceAsync(GetDataSourceRequest getDataSourceRequest);
/**
* <p>
* Returns a <code>DataSource</code> that includes metadata and data file information, as well as the current status
* of the <code>DataSource</code>.
* </p>
* <p>
* <code>GetDataSource</code> 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.
* </p>
*
* @param getDataSourceRequest
* @param 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.
* @return A Java Future containing the result of the GetDataSource operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.GetDataSource
*/
java.util.concurrent.Future<GetDataSourceResult> getDataSourceAsync(GetDataSourceRequest getDataSourceRequest,
com.amazonaws.handlers.AsyncHandler<GetDataSourceRequest, GetDataSourceResult> asyncHandler);
/**
* <p>
* Returns an <code>Evaluation</code> that includes metadata as well as the current status of the
* <code>Evaluation</code>.
* </p>
*
* @param getEvaluationRequest
* @return A Java Future containing the result of the GetEvaluation operation returned by the service.
* @sample AmazonMachineLearningAsync.GetEvaluation
*/
java.util.concurrent.Future<GetEvaluationResult> getEvaluationAsync(GetEvaluationRequest getEvaluationRequest);
/**
* <p>
* Returns an <code>Evaluation</code> that includes metadata as well as the current status of the
* <code>Evaluation</code>.
* </p>
*
* @param getEvaluationRequest
* @param 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.
* @return A Java Future containing the result of the GetEvaluation operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.GetEvaluation
*/
java.util.concurrent.Future<GetEvaluationResult> getEvaluationAsync(GetEvaluationRequest getEvaluationRequest,
com.amazonaws.handlers.AsyncHandler<GetEvaluationRequest, GetEvaluationResult> asyncHandler);
/**
* <p>
* Returns an <code>MLModel</code> that includes detailed metadata, data source information, and the current status
* of the <code>MLModel</code>.
* </p>
* <p>
* <code>GetMLModel</code> provides results in normal or verbose format.
* </p>
*
* @param getMLModelRequest
* @return A Java Future containing the result of the GetMLModel operation returned by the service.
* @sample AmazonMachineLearningAsync.GetMLModel
*/
java.util.concurrent.Future<GetMLModelResult> getMLModelAsync(GetMLModelRequest getMLModelRequest);
/**
* <p>
* Returns an <code>MLModel</code> that includes detailed metadata, data source information, and the current status
* of the <code>MLModel</code>.
* </p>
* <p>
* <code>GetMLModel</code> provides results in normal or verbose format.
* </p>
*
* @param getMLModelRequest
* @param 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.
* @return A Java Future containing the result of the GetMLModel operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.GetMLModel
*/
java.util.concurrent.Future<GetMLModelResult> getMLModelAsync(GetMLModelRequest getMLModelRequest,
com.amazonaws.handlers.AsyncHandler<GetMLModelRequest, GetMLModelResult> asyncHandler);
/**
* <p>
* Generates a prediction for the observation using the specified <code>ML Model</code>.
* </p>
* <note><title>Note</title>
* <p>
* Not all response parameters will be populated. Whether a response parameter is populated depends on the type of
* model requested.
* </p>
* </note>
*
* @param predictRequest
* @return A Java Future containing the result of the Predict operation returned by the service.
* @sample AmazonMachineLearningAsync.Predict
*/
java.util.concurrent.Future<PredictResult> predictAsync(PredictRequest predictRequest);
/**
* <p>
* Generates a prediction for the observation using the specified <code>ML Model</code>.
* </p>
* <note><title>Note</title>
* <p>
* Not all response parameters will be populated. Whether a response parameter is populated depends on the type of
* model requested.
* </p>
* </note>
*
* @param predictRequest
* @param 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.
* @return A Java Future containing the result of the Predict operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.Predict
*/
java.util.concurrent.Future<PredictResult> predictAsync(PredictRequest predictRequest,
com.amazonaws.handlers.AsyncHandler<PredictRequest, PredictResult> asyncHandler);
/**
* <p>
* Updates the <code>BatchPredictionName</code> of a <code>BatchPrediction</code>.
* </p>
* <p>
* You can use the <code>GetBatchPrediction</code> operation to view the contents of the updated data element.
* </p>
*
* @param updateBatchPredictionRequest
* @return A Java Future containing the result of the UpdateBatchPrediction operation returned by the service.
* @sample AmazonMachineLearningAsync.UpdateBatchPrediction
*/
java.util.concurrent.Future<UpdateBatchPredictionResult> updateBatchPredictionAsync(UpdateBatchPredictionRequest updateBatchPredictionRequest);
/**
* <p>
* Updates the <code>BatchPredictionName</code> of a <code>BatchPrediction</code>.
* </p>
* <p>
* You can use the <code>GetBatchPrediction</code> operation to view the contents of the updated data element.
* </p>
*
* @param updateBatchPredictionRequest
* @param 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.
* @return A Java Future containing the result of the UpdateBatchPrediction operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.UpdateBatchPrediction
*/
java.util.concurrent.Future<UpdateBatchPredictionResult> updateBatchPredictionAsync(UpdateBatchPredictionRequest updateBatchPredictionRequest,
com.amazonaws.handlers.AsyncHandler<UpdateBatchPredictionRequest, UpdateBatchPredictionResult> asyncHandler);
/**
* <p>
* Updates the <code>DataSourceName</code> of a <code>DataSource</code>.
* </p>
* <p>
* You can use the <code>GetDataSource</code> operation to view the contents of the updated data element.
* </p>
*
* @param updateDataSourceRequest
* @return A Java Future containing the result of the UpdateDataSource operation returned by the service.
* @sample AmazonMachineLearningAsync.UpdateDataSource
*/
java.util.concurrent.Future<UpdateDataSourceResult> updateDataSourceAsync(UpdateDataSourceRequest updateDataSourceRequest);
/**
* <p>
* Updates the <code>DataSourceName</code> of a <code>DataSource</code>.
* </p>
* <p>
* You can use the <code>GetDataSource</code> operation to view the contents of the updated data element.
* </p>
*
* @param updateDataSourceRequest
* @param 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.
* @return A Java Future containing the result of the UpdateDataSource operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.UpdateDataSource
*/
java.util.concurrent.Future<UpdateDataSourceResult> updateDataSourceAsync(UpdateDataSourceRequest updateDataSourceRequest,
com.amazonaws.handlers.AsyncHandler<UpdateDataSourceRequest, UpdateDataSourceResult> asyncHandler);
/**
* <p>
* Updates the <code>EvaluationName</code> of an <code>Evaluation</code>.
* </p>
* <p>
* You can use the <code>GetEvaluation</code> operation to view the contents of the updated data element.
* </p>
*
* @param updateEvaluationRequest
* @return A Java Future containing the result of the UpdateEvaluation operation returned by the service.
* @sample AmazonMachineLearningAsync.UpdateEvaluation
*/
java.util.concurrent.Future<UpdateEvaluationResult> updateEvaluationAsync(UpdateEvaluationRequest updateEvaluationRequest);
/**
* <p>
* Updates the <code>EvaluationName</code> of an <code>Evaluation</code>.
* </p>
* <p>
* You can use the <code>GetEvaluation</code> operation to view the contents of the updated data element.
* </p>
*
* @param updateEvaluationRequest
* @param 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.
* @return A Java Future containing the result of the UpdateEvaluation operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.UpdateEvaluation
*/
java.util.concurrent.Future<UpdateEvaluationResult> updateEvaluationAsync(UpdateEvaluationRequest updateEvaluationRequest,
com.amazonaws.handlers.AsyncHandler<UpdateEvaluationRequest, UpdateEvaluationResult> asyncHandler);
/**
* <p>
* Updates the <code>MLModelName</code> and the <code>ScoreThreshold</code> of an <code>MLModel</code>.
* </p>
* <p>
* You can use the <code>GetMLModel</code> operation to view the contents of the updated data element.
* </p>
*
* @param updateMLModelRequest
* @return A Java Future containing the result of the UpdateMLModel operation returned by the service.
* @sample AmazonMachineLearningAsync.UpdateMLModel
*/
java.util.concurrent.Future<UpdateMLModelResult> updateMLModelAsync(UpdateMLModelRequest updateMLModelRequest);
/**
* <p>
* Updates the <code>MLModelName</code> and the <code>ScoreThreshold</code> of an <code>MLModel</code>.
* </p>
* <p>
* You can use the <code>GetMLModel</code> operation to view the contents of the updated data element.
* </p>
*
* @param updateMLModelRequest
* @param 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.
* @return A Java Future containing the result of the UpdateMLModel operation returned by the service.
* @sample AmazonMachineLearningAsyncHandler.UpdateMLModel
*/
java.util.concurrent.Future<UpdateMLModelResult> updateMLModelAsync(UpdateMLModelRequest updateMLModelRequest,
com.amazonaws.handlers.AsyncHandler<UpdateMLModelRequest, UpdateMLModelResult> asyncHandler);
}