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/*
* Copyright 2010-2016 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 com.amazonaws.*;
import com.amazonaws.regions.*;
import com.amazonaws.services.machinelearning.model.*;
/**
* Interface for accessing AmazonMachineLearning.
*
* Definition of the public APIs exposed by Amazon Machine Learning
*
*/
public interface AmazonMachineLearning {
/**
* Overrides the default endpoint for this client ("https://machinelearning.us-east-1.amazonaws.com/").
* Callers can use this method to control which AWS region they want to work with.
*
* Callers can pass in just the endpoint (ex: "machinelearning.us-east-1.amazonaws.com/") or a full
* URL, including the protocol (ex: "https://machinelearning.us-east-1.amazonaws.com/"). If the
* protocol is not specified here, the default protocol from this client's
* {@link ClientConfiguration} will be used, which by default is HTTPS.
*
* For more information on using AWS regions with the AWS SDK for Java, and
* a complete list of all available endpoints for all AWS services, see:
*
* http://developer.amazonwebservices.com/connect/entry.jspa?externalID=3912
*
* This method is not threadsafe. An endpoint should be configured when the
* client is created and before any service requests are made. Changing it
* afterwards creates inevitable race conditions for any service requests in
* transit or retrying.
*
* @param endpoint
* The endpoint (ex: "machinelearning.us-east-1.amazonaws.com/") or a full URL,
* including the protocol (ex: "https://machinelearning.us-east-1.amazonaws.com/") of
* the region specific AWS endpoint this client will communicate
* with.
*
* @throws IllegalArgumentException
* If any problems are detected with the specified endpoint.
*/
public void setEndpoint(String endpoint) throws java.lang.IllegalArgumentException;
/**
* An alternative to {@link AmazonMachineLearning#setEndpoint(String)}, sets the
* regional endpoint for this client's service calls. Callers can use this
* method to control which AWS region they want to work with.
*
* By default, all service endpoints in all regions use the https protocol.
* To use http instead, specify it in the {@link ClientConfiguration}
* supplied at construction.
*
* This method is not threadsafe. A region should be configured when the
* client is created and before any service requests are made. Changing it
* afterwards creates inevitable race conditions for any service requests in
* transit or retrying.
*
* @param region
* The region this client will communicate with. See
* {@link Region#getRegion(com.amazonaws.regions.Regions)} for
* accessing a given region.
* @throws java.lang.IllegalArgumentException
* If the given region is null, or if this service isn't
* available in the given region. See
* {@link Region#isServiceSupported(String)}
* @see Region#getRegion(com.amazonaws.regions.Regions)
* @see Region#createClient(Class, com.amazonaws.auth.AWSCredentialsProvider, ClientConfiguration)
*/
public void setRegion(Region region) throws java.lang.IllegalArgumentException;
/**
*
* 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.
*
*
* @param getMLModelRequest Container for the necessary parameters to
* execute the GetMLModel service method on AmazonMachineLearning.
*
* @return The response from the GetMLModel service method, as returned
* by AmazonMachineLearning.
*
* @throws InvalidInputException
* @throws InternalServerException
* @throws ResourceNotFoundException
*
* @throws AmazonClientException
* If any internal errors are encountered inside the client while
* attempting to make the request or handle the response. For example
* if a network connection is not available.
* @throws AmazonServiceException
* If an error response is returned by AmazonMachineLearning indicating
* either a problem with the data in the request, or a server side issue.
*/
public GetMLModelResult getMLModel(GetMLModelRequest getMLModelRequest)
throws AmazonServiceException, AmazonClientException;
/**
*
* Generates a prediction for the observation using the specified
* ML Model .
*
*
* NOTE: Note Not all response parameters will be populated.
* Whether a response parameter is populated depends on the type of model
* requested.
*
*
* @param predictRequest Container for the necessary parameters to
* execute the Predict service method on AmazonMachineLearning.
*
* @return The response from the Predict service method, as returned by
* AmazonMachineLearning.
*
* @throws InvalidInputException
* @throws InternalServerException
* @throws ResourceNotFoundException
* @throws LimitExceededException
* @throws PredictorNotMountedException
*
* @throws AmazonClientException
* If any internal errors are encountered inside the client while
* attempting to make the request or handle the response. For example
* if a network connection is not available.
* @throws AmazonServiceException
* If an error response is returned by AmazonMachineLearning indicating
* either a problem with the data in the request, or a server side issue.
*/
public PredictResult predict(PredictRequest predictRequest)
throws AmazonServiceException, AmazonClientException;
/**
* Shuts down this client object, releasing any resources that might be held
* open. This is an optional method, and callers are not expected to call
* it, but can if they want to explicitly release any open resources. Once a
* client has been shutdown, it should not be used to make any more
* requests.
*/
public void shutdown();
/**
* Returns additional metadata for a previously executed successful request, typically used for
* debugging issues where a service isn't acting as expected. This data isn't considered part
* of the result data returned by an operation, so it's available through this separate,
* diagnostic interface.
*
* Response metadata is only cached for a limited period of time, so if you need to access
* this extra diagnostic information for an executed request, you should use this method
* to retrieve it as soon as possible after executing a request.
*
* @param request
* The originally executed request.
*
* @return The response metadata for the specified request, or null if none
* is available.
*/
public ResponseMetadata getCachedResponseMetadata(AmazonWebServiceRequest request);
}