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/*
* Copyright 2014-2019 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 software.amazon.awssdk.services.machinelearning;
import java.util.function.Consumer;
import software.amazon.awssdk.annotations.Generated;
import software.amazon.awssdk.awscore.exception.AwsServiceException;
import software.amazon.awssdk.core.SdkClient;
import software.amazon.awssdk.core.exception.SdkClientException;
import software.amazon.awssdk.regions.ServiceMetadata;
import software.amazon.awssdk.services.machinelearning.model.AddTagsRequest;
import software.amazon.awssdk.services.machinelearning.model.AddTagsResponse;
import software.amazon.awssdk.services.machinelearning.model.CreateBatchPredictionRequest;
import software.amazon.awssdk.services.machinelearning.model.CreateBatchPredictionResponse;
import software.amazon.awssdk.services.machinelearning.model.CreateDataSourceFromRdsRequest;
import software.amazon.awssdk.services.machinelearning.model.CreateDataSourceFromRdsResponse;
import software.amazon.awssdk.services.machinelearning.model.CreateDataSourceFromRedshiftRequest;
import software.amazon.awssdk.services.machinelearning.model.CreateDataSourceFromRedshiftResponse;
import software.amazon.awssdk.services.machinelearning.model.CreateDataSourceFromS3Request;
import software.amazon.awssdk.services.machinelearning.model.CreateDataSourceFromS3Response;
import software.amazon.awssdk.services.machinelearning.model.CreateEvaluationRequest;
import software.amazon.awssdk.services.machinelearning.model.CreateEvaluationResponse;
import software.amazon.awssdk.services.machinelearning.model.CreateMlModelRequest;
import software.amazon.awssdk.services.machinelearning.model.CreateMlModelResponse;
import software.amazon.awssdk.services.machinelearning.model.CreateRealtimeEndpointRequest;
import software.amazon.awssdk.services.machinelearning.model.CreateRealtimeEndpointResponse;
import software.amazon.awssdk.services.machinelearning.model.DeleteBatchPredictionRequest;
import software.amazon.awssdk.services.machinelearning.model.DeleteBatchPredictionResponse;
import software.amazon.awssdk.services.machinelearning.model.DeleteDataSourceRequest;
import software.amazon.awssdk.services.machinelearning.model.DeleteDataSourceResponse;
import software.amazon.awssdk.services.machinelearning.model.DeleteEvaluationRequest;
import software.amazon.awssdk.services.machinelearning.model.DeleteEvaluationResponse;
import software.amazon.awssdk.services.machinelearning.model.DeleteMlModelRequest;
import software.amazon.awssdk.services.machinelearning.model.DeleteMlModelResponse;
import software.amazon.awssdk.services.machinelearning.model.DeleteRealtimeEndpointRequest;
import software.amazon.awssdk.services.machinelearning.model.DeleteRealtimeEndpointResponse;
import software.amazon.awssdk.services.machinelearning.model.DeleteTagsRequest;
import software.amazon.awssdk.services.machinelearning.model.DeleteTagsResponse;
import software.amazon.awssdk.services.machinelearning.model.DescribeBatchPredictionsRequest;
import software.amazon.awssdk.services.machinelearning.model.DescribeBatchPredictionsResponse;
import software.amazon.awssdk.services.machinelearning.model.DescribeDataSourcesRequest;
import software.amazon.awssdk.services.machinelearning.model.DescribeDataSourcesResponse;
import software.amazon.awssdk.services.machinelearning.model.DescribeEvaluationsRequest;
import software.amazon.awssdk.services.machinelearning.model.DescribeEvaluationsResponse;
import software.amazon.awssdk.services.machinelearning.model.DescribeMlModelsRequest;
import software.amazon.awssdk.services.machinelearning.model.DescribeMlModelsResponse;
import software.amazon.awssdk.services.machinelearning.model.DescribeTagsRequest;
import software.amazon.awssdk.services.machinelearning.model.DescribeTagsResponse;
import software.amazon.awssdk.services.machinelearning.model.GetBatchPredictionRequest;
import software.amazon.awssdk.services.machinelearning.model.GetBatchPredictionResponse;
import software.amazon.awssdk.services.machinelearning.model.GetDataSourceRequest;
import software.amazon.awssdk.services.machinelearning.model.GetDataSourceResponse;
import software.amazon.awssdk.services.machinelearning.model.GetEvaluationRequest;
import software.amazon.awssdk.services.machinelearning.model.GetEvaluationResponse;
import software.amazon.awssdk.services.machinelearning.model.GetMlModelRequest;
import software.amazon.awssdk.services.machinelearning.model.GetMlModelResponse;
import software.amazon.awssdk.services.machinelearning.model.IdempotentParameterMismatchException;
import software.amazon.awssdk.services.machinelearning.model.InternalServerException;
import software.amazon.awssdk.services.machinelearning.model.InvalidInputException;
import software.amazon.awssdk.services.machinelearning.model.InvalidTagException;
import software.amazon.awssdk.services.machinelearning.model.LimitExceededException;
import software.amazon.awssdk.services.machinelearning.model.MachineLearningException;
import software.amazon.awssdk.services.machinelearning.model.PredictRequest;
import software.amazon.awssdk.services.machinelearning.model.PredictResponse;
import software.amazon.awssdk.services.machinelearning.model.PredictorNotMountedException;
import software.amazon.awssdk.services.machinelearning.model.ResourceNotFoundException;
import software.amazon.awssdk.services.machinelearning.model.TagLimitExceededException;
import software.amazon.awssdk.services.machinelearning.model.UpdateBatchPredictionRequest;
import software.amazon.awssdk.services.machinelearning.model.UpdateBatchPredictionResponse;
import software.amazon.awssdk.services.machinelearning.model.UpdateDataSourceRequest;
import software.amazon.awssdk.services.machinelearning.model.UpdateDataSourceResponse;
import software.amazon.awssdk.services.machinelearning.model.UpdateEvaluationRequest;
import software.amazon.awssdk.services.machinelearning.model.UpdateEvaluationResponse;
import software.amazon.awssdk.services.machinelearning.model.UpdateMlModelRequest;
import software.amazon.awssdk.services.machinelearning.model.UpdateMlModelResponse;
import software.amazon.awssdk.services.machinelearning.paginators.DescribeBatchPredictionsIterable;
import software.amazon.awssdk.services.machinelearning.paginators.DescribeDataSourcesIterable;
import software.amazon.awssdk.services.machinelearning.paginators.DescribeEvaluationsIterable;
import software.amazon.awssdk.services.machinelearning.paginators.DescribeMLModelsIterable;
/**
* Service client for accessing Amazon Machine Learning. This can be created using the static {@link #builder()} method.
*
* Definition of the public APIs exposed by Amazon Machine Learning
*/
@Generated("software.amazon.awssdk:codegen")
public interface MachineLearningClient extends SdkClient {
String SERVICE_NAME = "machinelearning";
/**
* Create a {@link MachineLearningClient} with the region loaded from the
* {@link software.amazon.awssdk.regions.providers.DefaultAwsRegionProviderChain} and credentials loaded from the
* {@link software.amazon.awssdk.auth.credentials.DefaultCredentialsProvider}.
*/
static MachineLearningClient create() {
return builder().build();
}
/**
* Create a builder that can be used to configure and create a {@link MachineLearningClient}.
*/
static MachineLearningClientBuilder builder() {
return new DefaultMachineLearningClientBuilder();
}
/**
*
* 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, AddTags updates the tag's
* value.
*
*
* @param addTagsRequest
* @return Result of the AddTags operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InvalidTagException
* @throws TagLimitExceededException
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.AddTags
*/
default AddTagsResponse addTags(AddTagsRequest addTagsRequest) throws InvalidInputException, InvalidTagException,
TagLimitExceededException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* 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, AddTags updates the tag's
* value.
*
*
*
* This is a convenience which creates an instance of the {@link AddTagsRequest.Builder} avoiding the need to create
* one manually via {@link AddTagsRequest#builder()}
*
*
* @param addTagsRequest
* A {@link Consumer} that will call methods on {@link AddTagsInput.Builder} to create a request.
* @return Result of the AddTags operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InvalidTagException
* @throws TagLimitExceededException
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.AddTags
*/
default AddTagsResponse addTags(Consumer addTagsRequest) throws InvalidInputException,
InvalidTagException, TagLimitExceededException, ResourceNotFoundException, InternalServerException,
AwsServiceException, SdkClientException, MachineLearningException {
return addTags(AddTagsRequest.builder().applyMutation(addTagsRequest).build());
}
/**
*
* 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.
*
*
* @param createBatchPredictionRequest
* @return Result of the CreateBatchPrediction operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws IdempotentParameterMismatchException
* A second request to use or change an object was not allowed. This can result from retrying a request
* using a parameter that was not present in the original request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.CreateBatchPrediction
*/
default CreateBatchPredictionResponse createBatchPrediction(CreateBatchPredictionRequest createBatchPredictionRequest)
throws InvalidInputException, InternalServerException, IdempotentParameterMismatchException, AwsServiceException,
SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* 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.
*
*
*
* This is a convenience which creates an instance of the {@link CreateBatchPredictionRequest.Builder} avoiding the
* need to create one manually via {@link CreateBatchPredictionRequest#builder()}
*
*
* @param createBatchPredictionRequest
* A {@link Consumer} that will call methods on {@link CreateBatchPredictionInput.Builder} to create a
* request.
* @return Result of the CreateBatchPrediction operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws IdempotentParameterMismatchException
* A second request to use or change an object was not allowed. This can result from retrying a request
* using a parameter that was not present in the original request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.CreateBatchPrediction
*/
default CreateBatchPredictionResponse createBatchPrediction(
Consumer createBatchPredictionRequest) throws InvalidInputException,
InternalServerException, IdempotentParameterMismatchException, AwsServiceException, SdkClientException,
MachineLearningException {
return createBatchPrediction(CreateBatchPredictionRequest.builder().applyMutation(createBatchPredictionRequest).build());
}
/**
*
* 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
* the COMPLETED or PENDING state can be used only 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.
*
*
* @param createDataSourceFromRdsRequest
* @return Result of the CreateDataSourceFromRDS operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws IdempotentParameterMismatchException
* A second request to use or change an object was not allowed. This can result from retrying a request
* using a parameter that was not present in the original request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.CreateDataSourceFromRDS
*/
default CreateDataSourceFromRdsResponse createDataSourceFromRDS(CreateDataSourceFromRdsRequest createDataSourceFromRdsRequest)
throws InvalidInputException, InternalServerException, IdempotentParameterMismatchException, AwsServiceException,
SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* 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
* the COMPLETED or PENDING state can be used only 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.
*
*
*
* This is a convenience which creates an instance of the {@link CreateDataSourceFromRdsRequest.Builder} avoiding
* the need to create one manually via {@link CreateDataSourceFromRdsRequest#builder()}
*
*
* @param createDataSourceFromRdsRequest
* A {@link Consumer} that will call methods on {@link CreateDataSourceFromRDSInput.Builder} to create a
* request.
* @return Result of the CreateDataSourceFromRDS operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws IdempotentParameterMismatchException
* A second request to use or change an object was not allowed. This can result from retrying a request
* using a parameter that was not present in the original request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.CreateDataSourceFromRDS
*/
default CreateDataSourceFromRdsResponse createDataSourceFromRDS(
Consumer createDataSourceFromRdsRequest) throws InvalidInputException,
InternalServerException, IdempotentParameterMismatchException, AwsServiceException, SdkClientException,
MachineLearningException {
return createDataSourceFromRDS(CreateDataSourceFromRdsRequest.builder().applyMutation(createDataSourceFromRdsRequest)
.build());
}
/**
*
* Creates a DataSource from a database hosted on an Amazon Redshift cluster. 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 states can be used to perform only CreateMLModel,
* CreateEvaluation, or CreateBatchPrediction operations.
*
*
* If Amazon ML can't 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 be contained in the database hosted on an Amazon Redshift cluster and should be specified
* by a SelectSqlQuery query. Amazon ML executes an Unload command in Amazon Redshift to
* transfer the result set of the SelectSqlQuery query to S3StagingLocation.
*
*
* After the DataSource has been created, it's ready for use in evaluations and batch predictions. If
* you plan to use the DataSource to train an MLModel, the DataSource also
* requires a recipe. A recipe describes how each input variable will be used in training an MLModel.
* 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.
*
*
*
* 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 GetDataSource for an existing
* datasource and copy the values to a CreateDataSource call. Change the settings that you want to
* change and make sure that all required fields have the appropriate values.
*
*
*
* @param createDataSourceFromRedshiftRequest
* @return Result of the CreateDataSourceFromRedshift operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws IdempotentParameterMismatchException
* A second request to use or change an object was not allowed. This can result from retrying a request
* using a parameter that was not present in the original request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.CreateDataSourceFromRedshift
*/
default CreateDataSourceFromRedshiftResponse createDataSourceFromRedshift(
CreateDataSourceFromRedshiftRequest createDataSourceFromRedshiftRequest) throws InvalidInputException,
InternalServerException, IdempotentParameterMismatchException, AwsServiceException, SdkClientException,
MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Creates a DataSource from a database hosted on an Amazon Redshift cluster. 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 states can be used to perform only CreateMLModel,
* CreateEvaluation, or CreateBatchPrediction operations.
*
*
* If Amazon ML can't 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 be contained in the database hosted on an Amazon Redshift cluster and should be specified
* by a SelectSqlQuery query. Amazon ML executes an Unload command in Amazon Redshift to
* transfer the result set of the SelectSqlQuery query to S3StagingLocation.
*
*
* After the DataSource has been created, it's ready for use in evaluations and batch predictions. If
* you plan to use the DataSource to train an MLModel, the DataSource also
* requires a recipe. A recipe describes how each input variable will be used in training an MLModel.
* 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.
*
*
*
* 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 GetDataSource for an existing
* datasource and copy the values to a CreateDataSource call. Change the settings that you want to
* change and make sure that all required fields have the appropriate values.
*
*
*
* This is a convenience which creates an instance of the {@link CreateDataSourceFromRedshiftRequest.Builder}
* avoiding the need to create one manually via {@link CreateDataSourceFromRedshiftRequest#builder()}
*
*
* @param createDataSourceFromRedshiftRequest
* A {@link Consumer} that will call methods on {@link CreateDataSourceFromRedshiftInput.Builder} to create a
* request.
* @return Result of the CreateDataSourceFromRedshift operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws IdempotentParameterMismatchException
* A second request to use or change an object was not allowed. This can result from retrying a request
* using a parameter that was not present in the original request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.CreateDataSourceFromRedshift
*/
default CreateDataSourceFromRedshiftResponse createDataSourceFromRedshift(
Consumer createDataSourceFromRedshiftRequest)
throws InvalidInputException, InternalServerException, IdempotentParameterMismatchException, AwsServiceException,
SdkClientException, MachineLearningException {
return createDataSourceFromRedshift(CreateDataSourceFromRedshiftRequest.builder()
.applyMutation(createDataSourceFromRedshiftRequest).build());
}
/**
*
* 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 has been created and is
* ready for use, Amazon ML sets the Status parameter to COMPLETED.
* DataSource in the COMPLETED or PENDING state can be used to perform only
* CreateMLModel, CreateEvaluation or CreateBatchPrediction operations.
*
*
* If Amazon ML can't 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) 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 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 also
* needs a recipe. A recipe describes how each input variable will be used in training an MLModel. 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.
*
*
* @param createDataSourceFromS3Request
* @return Result of the CreateDataSourceFromS3 operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws IdempotentParameterMismatchException
* A second request to use or change an object was not allowed. This can result from retrying a request
* using a parameter that was not present in the original request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.CreateDataSourceFromS3
*/
default CreateDataSourceFromS3Response createDataSourceFromS3(CreateDataSourceFromS3Request createDataSourceFromS3Request)
throws InvalidInputException, InternalServerException, IdempotentParameterMismatchException, AwsServiceException,
SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* 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 has been created and is
* ready for use, Amazon ML sets the Status parameter to COMPLETED.
* DataSource in the COMPLETED or PENDING state can be used to perform only
* CreateMLModel, CreateEvaluation or CreateBatchPrediction operations.
*
*
* If Amazon ML can't 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) 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 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 also
* needs a recipe. A recipe describes how each input variable will be used in training an MLModel. 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.
*
*
*
* This is a convenience which creates an instance of the {@link CreateDataSourceFromS3Request.Builder} avoiding the
* need to create one manually via {@link CreateDataSourceFromS3Request#builder()}
*
*
* @param createDataSourceFromS3Request
* A {@link Consumer} that will call methods on {@link CreateDataSourceFromS3Input.Builder} to create a
* request.
* @return Result of the CreateDataSourceFromS3 operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws IdempotentParameterMismatchException
* A second request to use or change an object was not allowed. This can result from retrying a request
* using a parameter that was not present in the original request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.CreateDataSourceFromS3
*/
default CreateDataSourceFromS3Response createDataSourceFromS3(
Consumer createDataSourceFromS3Request) throws InvalidInputException,
InternalServerException, IdempotentParameterMismatchException, AwsServiceException, SdkClientException,
MachineLearningException {
return createDataSourceFromS3(CreateDataSourceFromS3Request.builder().applyMutation(createDataSourceFromS3Request)
.build());
}
/**
*
* 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.
*
*
* @param createEvaluationRequest
* @return Result of the CreateEvaluation operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws IdempotentParameterMismatchException
* A second request to use or change an object was not allowed. This can result from retrying a request
* using a parameter that was not present in the original request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.CreateEvaluation
*/
default CreateEvaluationResponse createEvaluation(CreateEvaluationRequest createEvaluationRequest)
throws InvalidInputException, InternalServerException, IdempotentParameterMismatchException, AwsServiceException,
SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* 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.
*
*
*
* This is a convenience which creates an instance of the {@link CreateEvaluationRequest.Builder} avoiding the need
* to create one manually via {@link CreateEvaluationRequest#builder()}
*
*
* @param createEvaluationRequest
* A {@link Consumer} that will call methods on {@link CreateEvaluationInput.Builder} to create a request.
* @return Result of the CreateEvaluation operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws IdempotentParameterMismatchException
* A second request to use or change an object was not allowed. This can result from retrying a request
* using a parameter that was not present in the original request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.CreateEvaluation
*/
default CreateEvaluationResponse createEvaluation(Consumer createEvaluationRequest)
throws InvalidInputException, InternalServerException, IdempotentParameterMismatchException, AwsServiceException,
SdkClientException, MachineLearningException {
return createEvaluation(CreateEvaluationRequest.builder().applyMutation(createEvaluationRequest).build());
}
/**
*
* Creates a new MLModel using the DataSource and the recipe as information sources.
*
*
* An MLModel is nearly immutable. Users can update only 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 has been created and ready is for use, Amazon ML sets the status to
* COMPLETED.
*
*
* You can use the GetMLModel operation to check the 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.
*
*
* @param createMlModelRequest
* @return Result of the CreateMLModel operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws IdempotentParameterMismatchException
* A second request to use or change an object was not allowed. This can result from retrying a request
* using a parameter that was not present in the original request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.CreateMLModel
*/
default CreateMlModelResponse createMLModel(CreateMlModelRequest createMlModelRequest) throws InvalidInputException,
InternalServerException, IdempotentParameterMismatchException, AwsServiceException, SdkClientException,
MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Creates a new MLModel using the DataSource and the recipe as information sources.
*
*
* An MLModel is nearly immutable. Users can update only 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 has been created and ready is for use, Amazon ML sets the status to
* COMPLETED.
*
*
* You can use the GetMLModel operation to check the 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.
*
*
*
* This is a convenience which creates an instance of the {@link CreateMlModelRequest.Builder} avoiding the need to
* create one manually via {@link CreateMlModelRequest#builder()}
*
*
* @param createMlModelRequest
* A {@link Consumer} that will call methods on {@link CreateMLModelInput.Builder} to create a request.
* @return Result of the CreateMLModel operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws IdempotentParameterMismatchException
* A second request to use or change an object was not allowed. This can result from retrying a request
* using a parameter that was not present in the original request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.CreateMLModel
*/
default CreateMlModelResponse createMLModel(Consumer createMlModelRequest)
throws InvalidInputException, InternalServerException, IdempotentParameterMismatchException, AwsServiceException,
SdkClientException, MachineLearningException {
return createMLModel(CreateMlModelRequest.builder().applyMutation(createMlModelRequest).build());
}
/**
*
* 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.
*
*
* @param createRealtimeEndpointRequest
* @return Result of the CreateRealtimeEndpoint operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.CreateRealtimeEndpoint
*/
default CreateRealtimeEndpointResponse createRealtimeEndpoint(CreateRealtimeEndpointRequest createRealtimeEndpointRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* 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.
*
*
*
* This is a convenience which creates an instance of the {@link CreateRealtimeEndpointRequest.Builder} avoiding the
* need to create one manually via {@link CreateRealtimeEndpointRequest#builder()}
*
*
* @param createRealtimeEndpointRequest
* A {@link Consumer} that will call methods on {@link CreateRealtimeEndpointInput.Builder} to create a
* request.
* @return Result of the CreateRealtimeEndpoint operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.CreateRealtimeEndpoint
*/
default CreateRealtimeEndpointResponse createRealtimeEndpoint(
Consumer createRealtimeEndpointRequest) throws InvalidInputException,
ResourceNotFoundException, InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
return createRealtimeEndpoint(CreateRealtimeEndpointRequest.builder().applyMutation(createRealtimeEndpointRequest)
.build());
}
/**
*
* 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.
*
*
* @param deleteBatchPredictionRequest
* @return Result of the DeleteBatchPrediction operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DeleteBatchPrediction
*/
default DeleteBatchPredictionResponse deleteBatchPrediction(DeleteBatchPredictionRequest deleteBatchPredictionRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* 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.
*
*
*
* This is a convenience which creates an instance of the {@link DeleteBatchPredictionRequest.Builder} avoiding the
* need to create one manually via {@link DeleteBatchPredictionRequest#builder()}
*
*
* @param deleteBatchPredictionRequest
* A {@link Consumer} that will call methods on {@link DeleteBatchPredictionInput.Builder} to create a
* request.
* @return Result of the DeleteBatchPrediction operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DeleteBatchPrediction
*/
default DeleteBatchPredictionResponse deleteBatchPrediction(
Consumer deleteBatchPredictionRequest) throws InvalidInputException,
ResourceNotFoundException, InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
return deleteBatchPrediction(DeleteBatchPredictionRequest.builder().applyMutation(deleteBatchPredictionRequest).build());
}
/**
*
* 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.
*
*
* @param deleteDataSourceRequest
* @return Result of the DeleteDataSource operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DeleteDataSource
*/
default DeleteDataSourceResponse deleteDataSource(DeleteDataSourceRequest deleteDataSourceRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* 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.
*
*
*
* This is a convenience which creates an instance of the {@link DeleteDataSourceRequest.Builder} avoiding the need
* to create one manually via {@link DeleteDataSourceRequest#builder()}
*
*
* @param deleteDataSourceRequest
* A {@link Consumer} that will call methods on {@link DeleteDataSourceInput.Builder} to create a request.
* @return Result of the DeleteDataSource operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DeleteDataSource
*/
default DeleteDataSourceResponse deleteDataSource(Consumer deleteDataSourceRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
return deleteDataSource(DeleteDataSourceRequest.builder().applyMutation(deleteDataSourceRequest).build());
}
/**
*
* 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.
*
*
* 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.
*
*
*
* This is a convenience which creates an instance of the {@link DeleteEvaluationRequest.Builder} avoiding the need
* to create one manually via {@link DeleteEvaluationRequest#builder()}
*
*
* @param deleteEvaluationRequest
* A {@link Consumer} that will call methods on {@link DeleteEvaluationInput.Builder} to create a request.
* @return Result of the DeleteEvaluation operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DeleteEvaluation
*/
default DeleteEvaluationResponse deleteEvaluation(Consumer deleteEvaluationRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
return deleteEvaluation(DeleteEvaluationRequest.builder().applyMutation(deleteEvaluationRequest).build());
}
/**
*
* 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.
*
*
* @param deleteMlModelRequest
* @return Result of the DeleteMLModel operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DeleteMLModel
*/
default DeleteMlModelResponse deleteMLModel(DeleteMlModelRequest deleteMlModelRequest) throws InvalidInputException,
ResourceNotFoundException, InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* 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.
*
*
*
* This is a convenience which creates an instance of the {@link DeleteMlModelRequest.Builder} avoiding the need to
* create one manually via {@link DeleteMlModelRequest#builder()}
*
*
* @param deleteMlModelRequest
* A {@link Consumer} that will call methods on {@link DeleteMLModelInput.Builder} to create a request.
* @return Result of the DeleteMLModel operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DeleteMLModel
*/
default DeleteMlModelResponse deleteMLModel(Consumer deleteMlModelRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
return deleteMLModel(DeleteMlModelRequest.builder().applyMutation(deleteMlModelRequest).build());
}
/**
*
* Deletes a real time endpoint of an MLModel.
*
*
* @param deleteRealtimeEndpointRequest
* @return Result of the DeleteRealtimeEndpoint operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DeleteRealtimeEndpoint
*/
default DeleteRealtimeEndpointResponse deleteRealtimeEndpoint(DeleteRealtimeEndpointRequest deleteRealtimeEndpointRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Deletes a real time endpoint of an MLModel.
*
*
*
* This is a convenience which creates an instance of the {@link DeleteRealtimeEndpointRequest.Builder} avoiding the
* need to create one manually via {@link DeleteRealtimeEndpointRequest#builder()}
*
*
* @param deleteRealtimeEndpointRequest
* A {@link Consumer} that will call methods on {@link DeleteRealtimeEndpointInput.Builder} to create a
* request.
* @return Result of the DeleteRealtimeEndpoint operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DeleteRealtimeEndpoint
*/
default DeleteRealtimeEndpointResponse deleteRealtimeEndpoint(
Consumer deleteRealtimeEndpointRequest) throws InvalidInputException,
ResourceNotFoundException, InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
return deleteRealtimeEndpoint(DeleteRealtimeEndpointRequest.builder().applyMutation(deleteRealtimeEndpointRequest)
.build());
}
/**
*
* Deletes the specified tags associated with an ML object. After this operation is complete, you can't recover
* deleted tags.
*
*
* If you specify a tag that doesn't exist, Amazon ML ignores it.
*
*
* @param deleteTagsRequest
* @return Result of the DeleteTags operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InvalidTagException
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DeleteTags
*/
default DeleteTagsResponse deleteTags(DeleteTagsRequest deleteTagsRequest) throws InvalidInputException, InvalidTagException,
ResourceNotFoundException, InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Deletes the specified tags associated with an ML object. After this operation is complete, you can't recover
* deleted tags.
*
*
* If you specify a tag that doesn't exist, Amazon ML ignores it.
*
*
*
* This is a convenience which creates an instance of the {@link DeleteTagsRequest.Builder} avoiding the need to
* create one manually via {@link DeleteTagsRequest#builder()}
*
*
* @param deleteTagsRequest
* A {@link Consumer} that will call methods on {@link DeleteTagsInput.Builder} to create a request.
* @return Result of the DeleteTags operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InvalidTagException
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DeleteTags
*/
default DeleteTagsResponse deleteTags(Consumer deleteTagsRequest) throws InvalidInputException,
InvalidTagException, ResourceNotFoundException, InternalServerException, AwsServiceException, SdkClientException,
MachineLearningException {
return deleteTags(DeleteTagsRequest.builder().applyMutation(deleteTagsRequest).build());
}
/**
*
* Returns a list of BatchPrediction operations that match the search criteria in the request.
*
*
* @return Result of the DescribeBatchPredictions operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeBatchPredictions
* @see #describeBatchPredictions(DescribeBatchPredictionsRequest)
*/
default DescribeBatchPredictionsResponse describeBatchPredictions() throws InvalidInputException, InternalServerException,
AwsServiceException, SdkClientException, MachineLearningException {
return describeBatchPredictions(DescribeBatchPredictionsRequest.builder().build());
}
/**
*
* Returns a list of BatchPrediction operations that match the search criteria in the request.
*
*
* @param describeBatchPredictionsRequest
* @return Result of the DescribeBatchPredictions operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeBatchPredictions
*/
default DescribeBatchPredictionsResponse describeBatchPredictions(
DescribeBatchPredictionsRequest describeBatchPredictionsRequest) throws InvalidInputException,
InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Returns a list of BatchPrediction operations that match the search criteria in the request.
*
*
*
* This is a convenience which creates an instance of the {@link DescribeBatchPredictionsRequest.Builder} avoiding
* the need to create one manually via {@link DescribeBatchPredictionsRequest#builder()}
*
*
* @param describeBatchPredictionsRequest
* A {@link Consumer} that will call methods on {@link DescribeBatchPredictionsInput.Builder} to create a
* request.
* @return Result of the DescribeBatchPredictions operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeBatchPredictions
*/
default DescribeBatchPredictionsResponse describeBatchPredictions(
Consumer describeBatchPredictionsRequest) throws InvalidInputException,
InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
return describeBatchPredictions(DescribeBatchPredictionsRequest.builder().applyMutation(describeBatchPredictionsRequest)
.build());
}
/**
*
* Returns a list of BatchPrediction operations that match the search criteria in the request.
*
*
*
* This is a variant of
* {@link #describeBatchPredictions(software.amazon.awssdk.services.machinelearning.model.DescribeBatchPredictionsRequest)}
* operation. The return type is a custom iterable that can be used to iterate through all the pages. SDK will
* internally handle making service calls for you.
*
*
* When this operation is called, a custom iterable is returned but no service calls are made yet. So there is no
* guarantee that the request is valid. As you iterate through the iterable, SDK will start lazily loading response
* pages by making service calls until there are no pages left or your iteration stops. If there are errors in your
* request, you will see the failures only after you start iterating through the iterable.
*
*
*
* The following are few ways to iterate through the response pages:
*
* 1) Using a Stream
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeBatchPredictionsIterable responses = client.describeBatchPredictionsPaginator(request);
* responses.stream().forEach(....);
* }
*
*
* 2) Using For loop
*
*
* {
* @code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeBatchPredictionsIterable responses = client
* .describeBatchPredictionsPaginator(request);
* for (software.amazon.awssdk.services.machinelearning.model.DescribeBatchPredictionsResponse response : responses) {
* // do something;
* }
* }
*
*
* 3) Use iterator directly
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeBatchPredictionsIterable responses = client.describeBatchPredictionsPaginator(request);
* responses.iterator().forEachRemaining(....);
* }
*
*
* Note: If you prefer to have control on service calls, use the
* {@link #describeBatchPredictions(software.amazon.awssdk.services.machinelearning.model.DescribeBatchPredictionsRequest)}
* operation.
*
*
* @return A custom iterable that can be used to iterate through all the response pages.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeBatchPredictions
* @see #describeBatchPredictionsPaginator(DescribeBatchPredictionsRequest)
*/
default DescribeBatchPredictionsIterable describeBatchPredictionsPaginator() throws InvalidInputException,
InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
return describeBatchPredictionsPaginator(DescribeBatchPredictionsRequest.builder().build());
}
/**
*
* Returns a list of BatchPrediction operations that match the search criteria in the request.
*
*
*
* This is a variant of
* {@link #describeBatchPredictions(software.amazon.awssdk.services.machinelearning.model.DescribeBatchPredictionsRequest)}
* operation. The return type is a custom iterable that can be used to iterate through all the pages. SDK will
* internally handle making service calls for you.
*
*
* When this operation is called, a custom iterable is returned but no service calls are made yet. So there is no
* guarantee that the request is valid. As you iterate through the iterable, SDK will start lazily loading response
* pages by making service calls until there are no pages left or your iteration stops. If there are errors in your
* request, you will see the failures only after you start iterating through the iterable.
*
*
*
* The following are few ways to iterate through the response pages:
*
* 1) Using a Stream
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeBatchPredictionsIterable responses = client.describeBatchPredictionsPaginator(request);
* responses.stream().forEach(....);
* }
*
*
* 2) Using For loop
*
*
* {
* @code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeBatchPredictionsIterable responses = client
* .describeBatchPredictionsPaginator(request);
* for (software.amazon.awssdk.services.machinelearning.model.DescribeBatchPredictionsResponse response : responses) {
* // do something;
* }
* }
*
*
* 3) Use iterator directly
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeBatchPredictionsIterable responses = client.describeBatchPredictionsPaginator(request);
* responses.iterator().forEachRemaining(....);
* }
*
*
* Note: If you prefer to have control on service calls, use the
* {@link #describeBatchPredictions(software.amazon.awssdk.services.machinelearning.model.DescribeBatchPredictionsRequest)}
* operation.
*
*
* @param describeBatchPredictionsRequest
* @return A custom iterable that can be used to iterate through all the response pages.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeBatchPredictions
*/
default DescribeBatchPredictionsIterable describeBatchPredictionsPaginator(
DescribeBatchPredictionsRequest describeBatchPredictionsRequest) throws InvalidInputException,
InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Returns a list of BatchPrediction operations that match the search criteria in the request.
*
*
*
* This is a variant of
* {@link #describeBatchPredictions(software.amazon.awssdk.services.machinelearning.model.DescribeBatchPredictionsRequest)}
* operation. The return type is a custom iterable that can be used to iterate through all the pages. SDK will
* internally handle making service calls for you.
*
*
* When this operation is called, a custom iterable is returned but no service calls are made yet. So there is no
* guarantee that the request is valid. As you iterate through the iterable, SDK will start lazily loading response
* pages by making service calls until there are no pages left or your iteration stops. If there are errors in your
* request, you will see the failures only after you start iterating through the iterable.
*
*
*
* The following are few ways to iterate through the response pages:
*
* 1) Using a Stream
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeBatchPredictionsIterable responses = client.describeBatchPredictionsPaginator(request);
* responses.stream().forEach(....);
* }
*
*
* 2) Using For loop
*
*
* {
* @code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeBatchPredictionsIterable responses = client
* .describeBatchPredictionsPaginator(request);
* for (software.amazon.awssdk.services.machinelearning.model.DescribeBatchPredictionsResponse response : responses) {
* // do something;
* }
* }
*
*
* 3) Use iterator directly
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeBatchPredictionsIterable responses = client.describeBatchPredictionsPaginator(request);
* responses.iterator().forEachRemaining(....);
* }
*
*
* Note: If you prefer to have control on service calls, use the
* {@link #describeBatchPredictions(software.amazon.awssdk.services.machinelearning.model.DescribeBatchPredictionsRequest)}
* operation.
*
*
* This is a convenience which creates an instance of the {@link DescribeBatchPredictionsRequest.Builder} avoiding
* the need to create one manually via {@link DescribeBatchPredictionsRequest#builder()}
*
*
* @param describeBatchPredictionsRequest
* A {@link Consumer} that will call methods on {@link DescribeBatchPredictionsInput.Builder} to create a
* request.
* @return A custom iterable that can be used to iterate through all the response pages.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeBatchPredictions
*/
default DescribeBatchPredictionsIterable describeBatchPredictionsPaginator(
Consumer describeBatchPredictionsRequest) throws InvalidInputException,
InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
return describeBatchPredictionsPaginator(DescribeBatchPredictionsRequest.builder()
.applyMutation(describeBatchPredictionsRequest).build());
}
/**
*
* Returns a list of DataSource that match the search criteria in the request.
*
*
* @return Result of the DescribeDataSources operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeDataSources
* @see #describeDataSources(DescribeDataSourcesRequest)
*/
default DescribeDataSourcesResponse describeDataSources() throws InvalidInputException, InternalServerException,
AwsServiceException, SdkClientException, MachineLearningException {
return describeDataSources(DescribeDataSourcesRequest.builder().build());
}
/**
*
* Returns a list of DataSource that match the search criteria in the request.
*
*
* @param describeDataSourcesRequest
* @return Result of the DescribeDataSources operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeDataSources
*/
default DescribeDataSourcesResponse describeDataSources(DescribeDataSourcesRequest describeDataSourcesRequest)
throws InvalidInputException, InternalServerException, AwsServiceException, SdkClientException,
MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Returns a list of DataSource that match the search criteria in the request.
*
*
*
* This is a convenience which creates an instance of the {@link DescribeDataSourcesRequest.Builder} avoiding the
* need to create one manually via {@link DescribeDataSourcesRequest#builder()}
*
*
* @param describeDataSourcesRequest
* A {@link Consumer} that will call methods on {@link DescribeDataSourcesInput.Builder} to create a request.
* @return Result of the DescribeDataSources operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeDataSources
*/
default DescribeDataSourcesResponse describeDataSources(
Consumer describeDataSourcesRequest) throws InvalidInputException,
InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
return describeDataSources(DescribeDataSourcesRequest.builder().applyMutation(describeDataSourcesRequest).build());
}
/**
*
* Returns a list of DataSource that match the search criteria in the request.
*
*
*
* This is a variant of
* {@link #describeDataSources(software.amazon.awssdk.services.machinelearning.model.DescribeDataSourcesRequest)}
* operation. The return type is a custom iterable that can be used to iterate through all the pages. SDK will
* internally handle making service calls for you.
*
*
* When this operation is called, a custom iterable is returned but no service calls are made yet. So there is no
* guarantee that the request is valid. As you iterate through the iterable, SDK will start lazily loading response
* pages by making service calls until there are no pages left or your iteration stops. If there are errors in your
* request, you will see the failures only after you start iterating through the iterable.
*
*
*
* The following are few ways to iterate through the response pages:
*
* 1) Using a Stream
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeDataSourcesIterable responses = client.describeDataSourcesPaginator(request);
* responses.stream().forEach(....);
* }
*
*
* 2) Using For loop
*
*
* {
* @code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeDataSourcesIterable responses = client
* .describeDataSourcesPaginator(request);
* for (software.amazon.awssdk.services.machinelearning.model.DescribeDataSourcesResponse response : responses) {
* // do something;
* }
* }
*
*
* 3) Use iterator directly
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeDataSourcesIterable responses = client.describeDataSourcesPaginator(request);
* responses.iterator().forEachRemaining(....);
* }
*
*
* Note: If you prefer to have control on service calls, use the
* {@link #describeDataSources(software.amazon.awssdk.services.machinelearning.model.DescribeDataSourcesRequest)}
* operation.
*
*
* @return A custom iterable that can be used to iterate through all the response pages.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeDataSources
* @see #describeDataSourcesPaginator(DescribeDataSourcesRequest)
*/
default DescribeDataSourcesIterable describeDataSourcesPaginator() throws InvalidInputException, InternalServerException,
AwsServiceException, SdkClientException, MachineLearningException {
return describeDataSourcesPaginator(DescribeDataSourcesRequest.builder().build());
}
/**
*
* Returns a list of DataSource that match the search criteria in the request.
*
*
*
* This is a variant of
* {@link #describeDataSources(software.amazon.awssdk.services.machinelearning.model.DescribeDataSourcesRequest)}
* operation. The return type is a custom iterable that can be used to iterate through all the pages. SDK will
* internally handle making service calls for you.
*
*
* When this operation is called, a custom iterable is returned but no service calls are made yet. So there is no
* guarantee that the request is valid. As you iterate through the iterable, SDK will start lazily loading response
* pages by making service calls until there are no pages left or your iteration stops. If there are errors in your
* request, you will see the failures only after you start iterating through the iterable.
*
*
*
* The following are few ways to iterate through the response pages:
*
* 1) Using a Stream
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeDataSourcesIterable responses = client.describeDataSourcesPaginator(request);
* responses.stream().forEach(....);
* }
*
*
* 2) Using For loop
*
*
* {
* @code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeDataSourcesIterable responses = client
* .describeDataSourcesPaginator(request);
* for (software.amazon.awssdk.services.machinelearning.model.DescribeDataSourcesResponse response : responses) {
* // do something;
* }
* }
*
*
* 3) Use iterator directly
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeDataSourcesIterable responses = client.describeDataSourcesPaginator(request);
* responses.iterator().forEachRemaining(....);
* }
*
*
* Note: If you prefer to have control on service calls, use the
* {@link #describeDataSources(software.amazon.awssdk.services.machinelearning.model.DescribeDataSourcesRequest)}
* operation.
*
*
* @param describeDataSourcesRequest
* @return A custom iterable that can be used to iterate through all the response pages.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeDataSources
*/
default DescribeDataSourcesIterable describeDataSourcesPaginator(DescribeDataSourcesRequest describeDataSourcesRequest)
throws InvalidInputException, InternalServerException, AwsServiceException, SdkClientException,
MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Returns a list of DataSource that match the search criteria in the request.
*
*
*
* This is a variant of
* {@link #describeDataSources(software.amazon.awssdk.services.machinelearning.model.DescribeDataSourcesRequest)}
* operation. The return type is a custom iterable that can be used to iterate through all the pages. SDK will
* internally handle making service calls for you.
*
*
* When this operation is called, a custom iterable is returned but no service calls are made yet. So there is no
* guarantee that the request is valid. As you iterate through the iterable, SDK will start lazily loading response
* pages by making service calls until there are no pages left or your iteration stops. If there are errors in your
* request, you will see the failures only after you start iterating through the iterable.
*
*
*
* The following are few ways to iterate through the response pages:
*
* 1) Using a Stream
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeDataSourcesIterable responses = client.describeDataSourcesPaginator(request);
* responses.stream().forEach(....);
* }
*
*
* 2) Using For loop
*
*
* {
* @code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeDataSourcesIterable responses = client
* .describeDataSourcesPaginator(request);
* for (software.amazon.awssdk.services.machinelearning.model.DescribeDataSourcesResponse response : responses) {
* // do something;
* }
* }
*
*
* 3) Use iterator directly
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeDataSourcesIterable responses = client.describeDataSourcesPaginator(request);
* responses.iterator().forEachRemaining(....);
* }
*
*
* Note: If you prefer to have control on service calls, use the
* {@link #describeDataSources(software.amazon.awssdk.services.machinelearning.model.DescribeDataSourcesRequest)}
* operation.
*
*
* This is a convenience which creates an instance of the {@link DescribeDataSourcesRequest.Builder} avoiding the
* need to create one manually via {@link DescribeDataSourcesRequest#builder()}
*
*
* @param describeDataSourcesRequest
* A {@link Consumer} that will call methods on {@link DescribeDataSourcesInput.Builder} to create a request.
* @return A custom iterable that can be used to iterate through all the response pages.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeDataSources
*/
default DescribeDataSourcesIterable describeDataSourcesPaginator(
Consumer describeDataSourcesRequest) throws InvalidInputException,
InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
return describeDataSourcesPaginator(DescribeDataSourcesRequest.builder().applyMutation(describeDataSourcesRequest)
.build());
}
/**
*
* Returns a list of DescribeEvaluations that match the search criteria in the request.
*
*
* @return Result of the DescribeEvaluations operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeEvaluations
* @see #describeEvaluations(DescribeEvaluationsRequest)
*/
default DescribeEvaluationsResponse describeEvaluations() throws InvalidInputException, InternalServerException,
AwsServiceException, SdkClientException, MachineLearningException {
return describeEvaluations(DescribeEvaluationsRequest.builder().build());
}
/**
*
* Returns a list of DescribeEvaluations that match the search criteria in the request.
*
*
* @param describeEvaluationsRequest
* @return Result of the DescribeEvaluations operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeEvaluations
*/
default DescribeEvaluationsResponse describeEvaluations(DescribeEvaluationsRequest describeEvaluationsRequest)
throws InvalidInputException, InternalServerException, AwsServiceException, SdkClientException,
MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Returns a list of DescribeEvaluations that match the search criteria in the request.
*
*
*
* This is a convenience which creates an instance of the {@link DescribeEvaluationsRequest.Builder} avoiding the
* need to create one manually via {@link DescribeEvaluationsRequest#builder()}
*
*
* @param describeEvaluationsRequest
* A {@link Consumer} that will call methods on {@link DescribeEvaluationsInput.Builder} to create a request.
* @return Result of the DescribeEvaluations operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeEvaluations
*/
default DescribeEvaluationsResponse describeEvaluations(
Consumer describeEvaluationsRequest) throws InvalidInputException,
InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
return describeEvaluations(DescribeEvaluationsRequest.builder().applyMutation(describeEvaluationsRequest).build());
}
/**
*
* Returns a list of DescribeEvaluations that match the search criteria in the request.
*
*
*
* This is a variant of
* {@link #describeEvaluations(software.amazon.awssdk.services.machinelearning.model.DescribeEvaluationsRequest)}
* operation. The return type is a custom iterable that can be used to iterate through all the pages. SDK will
* internally handle making service calls for you.
*
*
* When this operation is called, a custom iterable is returned but no service calls are made yet. So there is no
* guarantee that the request is valid. As you iterate through the iterable, SDK will start lazily loading response
* pages by making service calls until there are no pages left or your iteration stops. If there are errors in your
* request, you will see the failures only after you start iterating through the iterable.
*
*
*
* The following are few ways to iterate through the response pages:
*
* 1) Using a Stream
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeEvaluationsIterable responses = client.describeEvaluationsPaginator(request);
* responses.stream().forEach(....);
* }
*
*
* 2) Using For loop
*
*
* {
* @code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeEvaluationsIterable responses = client
* .describeEvaluationsPaginator(request);
* for (software.amazon.awssdk.services.machinelearning.model.DescribeEvaluationsResponse response : responses) {
* // do something;
* }
* }
*
*
* 3) Use iterator directly
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeEvaluationsIterable responses = client.describeEvaluationsPaginator(request);
* responses.iterator().forEachRemaining(....);
* }
*
*
* Note: If you prefer to have control on service calls, use the
* {@link #describeEvaluations(software.amazon.awssdk.services.machinelearning.model.DescribeEvaluationsRequest)}
* operation.
*
*
* @return A custom iterable that can be used to iterate through all the response pages.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeEvaluations
* @see #describeEvaluationsPaginator(DescribeEvaluationsRequest)
*/
default DescribeEvaluationsIterable describeEvaluationsPaginator() throws InvalidInputException, InternalServerException,
AwsServiceException, SdkClientException, MachineLearningException {
return describeEvaluationsPaginator(DescribeEvaluationsRequest.builder().build());
}
/**
*
* Returns a list of DescribeEvaluations that match the search criteria in the request.
*
*
*
* This is a variant of
* {@link #describeEvaluations(software.amazon.awssdk.services.machinelearning.model.DescribeEvaluationsRequest)}
* operation. The return type is a custom iterable that can be used to iterate through all the pages. SDK will
* internally handle making service calls for you.
*
*
* When this operation is called, a custom iterable is returned but no service calls are made yet. So there is no
* guarantee that the request is valid. As you iterate through the iterable, SDK will start lazily loading response
* pages by making service calls until there are no pages left or your iteration stops. If there are errors in your
* request, you will see the failures only after you start iterating through the iterable.
*
*
*
* The following are few ways to iterate through the response pages:
*
* 1) Using a Stream
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeEvaluationsIterable responses = client.describeEvaluationsPaginator(request);
* responses.stream().forEach(....);
* }
*
*
* 2) Using For loop
*
*
* {
* @code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeEvaluationsIterable responses = client
* .describeEvaluationsPaginator(request);
* for (software.amazon.awssdk.services.machinelearning.model.DescribeEvaluationsResponse response : responses) {
* // do something;
* }
* }
*
*
* 3) Use iterator directly
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeEvaluationsIterable responses = client.describeEvaluationsPaginator(request);
* responses.iterator().forEachRemaining(....);
* }
*
*
* Note: If you prefer to have control on service calls, use the
* {@link #describeEvaluations(software.amazon.awssdk.services.machinelearning.model.DescribeEvaluationsRequest)}
* operation.
*
*
* @param describeEvaluationsRequest
* @return A custom iterable that can be used to iterate through all the response pages.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeEvaluations
*/
default DescribeEvaluationsIterable describeEvaluationsPaginator(DescribeEvaluationsRequest describeEvaluationsRequest)
throws InvalidInputException, InternalServerException, AwsServiceException, SdkClientException,
MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Returns a list of DescribeEvaluations that match the search criteria in the request.
*
*
*
* This is a variant of
* {@link #describeEvaluations(software.amazon.awssdk.services.machinelearning.model.DescribeEvaluationsRequest)}
* operation. The return type is a custom iterable that can be used to iterate through all the pages. SDK will
* internally handle making service calls for you.
*
*
* When this operation is called, a custom iterable is returned but no service calls are made yet. So there is no
* guarantee that the request is valid. As you iterate through the iterable, SDK will start lazily loading response
* pages by making service calls until there are no pages left or your iteration stops. If there are errors in your
* request, you will see the failures only after you start iterating through the iterable.
*
*
*
* The following are few ways to iterate through the response pages:
*
* 1) Using a Stream
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeEvaluationsIterable responses = client.describeEvaluationsPaginator(request);
* responses.stream().forEach(....);
* }
*
*
* 2) Using For loop
*
*
* {
* @code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeEvaluationsIterable responses = client
* .describeEvaluationsPaginator(request);
* for (software.amazon.awssdk.services.machinelearning.model.DescribeEvaluationsResponse response : responses) {
* // do something;
* }
* }
*
*
* 3) Use iterator directly
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeEvaluationsIterable responses = client.describeEvaluationsPaginator(request);
* responses.iterator().forEachRemaining(....);
* }
*
*
* Note: If you prefer to have control on service calls, use the
* {@link #describeEvaluations(software.amazon.awssdk.services.machinelearning.model.DescribeEvaluationsRequest)}
* operation.
*
*
* This is a convenience which creates an instance of the {@link DescribeEvaluationsRequest.Builder} avoiding the
* need to create one manually via {@link DescribeEvaluationsRequest#builder()}
*
*
* @param describeEvaluationsRequest
* A {@link Consumer} that will call methods on {@link DescribeEvaluationsInput.Builder} to create a request.
* @return A custom iterable that can be used to iterate through all the response pages.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeEvaluations
*/
default DescribeEvaluationsIterable describeEvaluationsPaginator(
Consumer describeEvaluationsRequest) throws InvalidInputException,
InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
return describeEvaluationsPaginator(DescribeEvaluationsRequest.builder().applyMutation(describeEvaluationsRequest)
.build());
}
/**
*
* Returns a list of MLModel that match the search criteria in the request.
*
*
* @return Result of the DescribeMLModels operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeMLModels
* @see #describeMLModels(DescribeMlModelsRequest)
*/
default DescribeMlModelsResponse describeMLModels() throws InvalidInputException, InternalServerException,
AwsServiceException, SdkClientException, MachineLearningException {
return describeMLModels(DescribeMlModelsRequest.builder().build());
}
/**
*
* Returns a list of MLModel that match the search criteria in the request.
*
*
* @param describeMlModelsRequest
* @return Result of the DescribeMLModels operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeMLModels
*/
default DescribeMlModelsResponse describeMLModels(DescribeMlModelsRequest describeMlModelsRequest)
throws InvalidInputException, InternalServerException, AwsServiceException, SdkClientException,
MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Returns a list of MLModel that match the search criteria in the request.
*
*
*
* This is a convenience which creates an instance of the {@link DescribeMlModelsRequest.Builder} avoiding the need
* to create one manually via {@link DescribeMlModelsRequest#builder()}
*
*
* @param describeMlModelsRequest
* A {@link Consumer} that will call methods on {@link DescribeMLModelsInput.Builder} to create a request.
* @return Result of the DescribeMLModels operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeMLModels
*/
default DescribeMlModelsResponse describeMLModels(Consumer describeMlModelsRequest)
throws InvalidInputException, InternalServerException, AwsServiceException, SdkClientException,
MachineLearningException {
return describeMLModels(DescribeMlModelsRequest.builder().applyMutation(describeMlModelsRequest).build());
}
/**
*
* Returns a list of MLModel that match the search criteria in the request.
*
*
*
* This is a variant of
* {@link #describeMLModels(software.amazon.awssdk.services.machinelearning.model.DescribeMlModelsRequest)}
* operation. The return type is a custom iterable that can be used to iterate through all the pages. SDK will
* internally handle making service calls for you.
*
*
* When this operation is called, a custom iterable is returned but no service calls are made yet. So there is no
* guarantee that the request is valid. As you iterate through the iterable, SDK will start lazily loading response
* pages by making service calls until there are no pages left or your iteration stops. If there are errors in your
* request, you will see the failures only after you start iterating through the iterable.
*
*
*
* The following are few ways to iterate through the response pages:
*
* 1) Using a Stream
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeMLModelsIterable responses = client.describeMLModelsPaginator(request);
* responses.stream().forEach(....);
* }
*
*
* 2) Using For loop
*
*
* {
* @code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeMLModelsIterable responses = client
* .describeMLModelsPaginator(request);
* for (software.amazon.awssdk.services.machinelearning.model.DescribeMlModelsResponse response : responses) {
* // do something;
* }
* }
*
*
* 3) Use iterator directly
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeMLModelsIterable responses = client.describeMLModelsPaginator(request);
* responses.iterator().forEachRemaining(....);
* }
*
*
* Note: If you prefer to have control on service calls, use the
* {@link #describeMLModels(software.amazon.awssdk.services.machinelearning.model.DescribeMlModelsRequest)}
* operation.
*
*
* @return A custom iterable that can be used to iterate through all the response pages.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeMLModels
* @see #describeMLModelsPaginator(DescribeMlModelsRequest)
*/
default DescribeMLModelsIterable describeMLModelsPaginator() throws InvalidInputException, InternalServerException,
AwsServiceException, SdkClientException, MachineLearningException {
return describeMLModelsPaginator(DescribeMlModelsRequest.builder().build());
}
/**
*
* Returns a list of MLModel that match the search criteria in the request.
*
*
*
* This is a variant of
* {@link #describeMLModels(software.amazon.awssdk.services.machinelearning.model.DescribeMlModelsRequest)}
* operation. The return type is a custom iterable that can be used to iterate through all the pages. SDK will
* internally handle making service calls for you.
*
*
* When this operation is called, a custom iterable is returned but no service calls are made yet. So there is no
* guarantee that the request is valid. As you iterate through the iterable, SDK will start lazily loading response
* pages by making service calls until there are no pages left or your iteration stops. If there are errors in your
* request, you will see the failures only after you start iterating through the iterable.
*
*
*
* The following are few ways to iterate through the response pages:
*
* 1) Using a Stream
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeMLModelsIterable responses = client.describeMLModelsPaginator(request);
* responses.stream().forEach(....);
* }
*
*
* 2) Using For loop
*
*
* {
* @code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeMLModelsIterable responses = client
* .describeMLModelsPaginator(request);
* for (software.amazon.awssdk.services.machinelearning.model.DescribeMlModelsResponse response : responses) {
* // do something;
* }
* }
*
*
* 3) Use iterator directly
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeMLModelsIterable responses = client.describeMLModelsPaginator(request);
* responses.iterator().forEachRemaining(....);
* }
*
*
* Note: If you prefer to have control on service calls, use the
* {@link #describeMLModels(software.amazon.awssdk.services.machinelearning.model.DescribeMlModelsRequest)}
* operation.
*
*
* @param describeMlModelsRequest
* @return A custom iterable that can be used to iterate through all the response pages.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeMLModels
*/
default DescribeMLModelsIterable describeMLModelsPaginator(DescribeMlModelsRequest describeMlModelsRequest)
throws InvalidInputException, InternalServerException, AwsServiceException, SdkClientException,
MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Returns a list of MLModel that match the search criteria in the request.
*
*
*
* This is a variant of
* {@link #describeMLModels(software.amazon.awssdk.services.machinelearning.model.DescribeMlModelsRequest)}
* operation. The return type is a custom iterable that can be used to iterate through all the pages. SDK will
* internally handle making service calls for you.
*
*
* When this operation is called, a custom iterable is returned but no service calls are made yet. So there is no
* guarantee that the request is valid. As you iterate through the iterable, SDK will start lazily loading response
* pages by making service calls until there are no pages left or your iteration stops. If there are errors in your
* request, you will see the failures only after you start iterating through the iterable.
*
*
*
* The following are few ways to iterate through the response pages:
*
* 1) Using a Stream
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeMLModelsIterable responses = client.describeMLModelsPaginator(request);
* responses.stream().forEach(....);
* }
*
*
* 2) Using For loop
*
*
* {
* @code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeMLModelsIterable responses = client
* .describeMLModelsPaginator(request);
* for (software.amazon.awssdk.services.machinelearning.model.DescribeMlModelsResponse response : responses) {
* // do something;
* }
* }
*
*
* 3) Use iterator directly
*
*
* {@code
* software.amazon.awssdk.services.machinelearning.paginators.DescribeMLModelsIterable responses = client.describeMLModelsPaginator(request);
* responses.iterator().forEachRemaining(....);
* }
*
*
* Note: If you prefer to have control on service calls, use the
* {@link #describeMLModels(software.amazon.awssdk.services.machinelearning.model.DescribeMlModelsRequest)}
* operation.
*
*
* This is a convenience which creates an instance of the {@link DescribeMlModelsRequest.Builder} avoiding the need
* to create one manually via {@link DescribeMlModelsRequest#builder()}
*
*
* @param describeMlModelsRequest
* A {@link Consumer} that will call methods on {@link DescribeMLModelsInput.Builder} to create a request.
* @return A custom iterable that can be used to iterate through all the response pages.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeMLModels
*/
default DescribeMLModelsIterable describeMLModelsPaginator(Consumer describeMlModelsRequest)
throws InvalidInputException, InternalServerException, AwsServiceException, SdkClientException,
MachineLearningException {
return describeMLModelsPaginator(DescribeMlModelsRequest.builder().applyMutation(describeMlModelsRequest).build());
}
/**
*
* Describes one or more of the tags for your Amazon ML object.
*
*
* @param describeTagsRequest
* @return Result of the DescribeTags operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeTags
*/
default DescribeTagsResponse describeTags(DescribeTagsRequest describeTagsRequest) throws InvalidInputException,
ResourceNotFoundException, InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Describes one or more of the tags for your Amazon ML object.
*
*
*
* This is a convenience which creates an instance of the {@link DescribeTagsRequest.Builder} avoiding the need to
* create one manually via {@link DescribeTagsRequest#builder()}
*
*
* @param describeTagsRequest
* A {@link Consumer} that will call methods on {@link DescribeTagsInput.Builder} to create a request.
* @return Result of the DescribeTags operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.DescribeTags
*/
default DescribeTagsResponse describeTags(Consumer describeTagsRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
return describeTags(DescribeTagsRequest.builder().applyMutation(describeTagsRequest).build());
}
/**
*
* Returns a BatchPrediction that includes detailed metadata, status, and data file information for a
* Batch Prediction request.
*
*
* @param getBatchPredictionRequest
* @return Result of the GetBatchPrediction operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.GetBatchPrediction
*/
default GetBatchPredictionResponse getBatchPrediction(GetBatchPredictionRequest getBatchPredictionRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Returns a BatchPrediction that includes detailed metadata, status, and data file information for a
* Batch Prediction request.
*
*
*
* This is a convenience which creates an instance of the {@link GetBatchPredictionRequest.Builder} avoiding the
* need to create one manually via {@link GetBatchPredictionRequest#builder()}
*
*
* @param getBatchPredictionRequest
* A {@link Consumer} that will call methods on {@link GetBatchPredictionInput.Builder} to create a request.
* @return Result of the GetBatchPrediction operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.GetBatchPrediction
*/
default GetBatchPredictionResponse getBatchPrediction(Consumer getBatchPredictionRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
return getBatchPrediction(GetBatchPredictionRequest.builder().applyMutation(getBatchPredictionRequest).build());
}
/**
*
* 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.
*
*
* @param getDataSourceRequest
* @return Result of the GetDataSource operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.GetDataSource
*/
default GetDataSourceResponse getDataSource(GetDataSourceRequest getDataSourceRequest) throws InvalidInputException,
ResourceNotFoundException, InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* 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.
*
*
*
* This is a convenience which creates an instance of the {@link GetDataSourceRequest.Builder} avoiding the need to
* create one manually via {@link GetDataSourceRequest#builder()}
*
*
* @param getDataSourceRequest
* A {@link Consumer} that will call methods on {@link GetDataSourceInput.Builder} to create a request.
* @return Result of the GetDataSource operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.GetDataSource
*/
default GetDataSourceResponse getDataSource(Consumer getDataSourceRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
return getDataSource(GetDataSourceRequest.builder().applyMutation(getDataSourceRequest).build());
}
/**
*
* Returns an Evaluation that includes metadata as well as the current status of the
* Evaluation.
*
*
* @param getEvaluationRequest
* @return Result of the GetEvaluation operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.GetEvaluation
*/
default GetEvaluationResponse getEvaluation(GetEvaluationRequest getEvaluationRequest) throws InvalidInputException,
ResourceNotFoundException, InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Returns an Evaluation that includes metadata as well as the current status of the
* Evaluation.
*
*
*
* This is a convenience which creates an instance of the {@link GetEvaluationRequest.Builder} avoiding the need to
* create one manually via {@link GetEvaluationRequest#builder()}
*
*
* @param getEvaluationRequest
* A {@link Consumer} that will call methods on {@link GetEvaluationInput.Builder} to create a request.
* @return Result of the GetEvaluation operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.GetEvaluation
*/
default GetEvaluationResponse getEvaluation(Consumer getEvaluationRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
return getEvaluation(GetEvaluationRequest.builder().applyMutation(getEvaluationRequest).build());
}
/**
*
* Returns an MLModel that includes detailed metadata, data source information, and the current status
* of the MLModel.
*
*
* GetMLModel provides results in normal or verbose format.
*
*
* @param getMlModelRequest
* @return Result of the GetMLModel operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.GetMLModel
*/
default GetMlModelResponse getMLModel(GetMlModelRequest getMlModelRequest) throws InvalidInputException,
ResourceNotFoundException, InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Returns an MLModel that includes detailed metadata, data source information, and the current status
* of the MLModel.
*
*
* GetMLModel provides results in normal or verbose format.
*
*
*
* This is a convenience which creates an instance of the {@link GetMlModelRequest.Builder} avoiding the need to
* create one manually via {@link GetMlModelRequest#builder()}
*
*
* @param getMlModelRequest
* A {@link Consumer} that will call methods on {@link GetMLModelInput.Builder} to create a request.
* @return Result of the GetMLModel operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.GetMLModel
*/
default GetMlModelResponse getMLModel(Consumer getMlModelRequest) throws InvalidInputException,
ResourceNotFoundException, InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
return getMLModel(GetMlModelRequest.builder().applyMutation(getMlModelRequest).build());
}
/**
*
* 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.
*
* DataSource.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws PredictorNotMountedException
* The exception is thrown when a predict request is made to an unmounted MLModel.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.Predict
*/
default PredictResponse predict(PredictRequest predictRequest) throws InvalidInputException, ResourceNotFoundException,
LimitExceededException, InternalServerException, PredictorNotMountedException, AwsServiceException,
SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* 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.
*
*
*
* This is a convenience which creates an instance of the {@link PredictRequest.Builder} avoiding the need to create
* one manually via {@link PredictRequest#builder()}
*
*
* @param predictRequest
* A {@link Consumer} that will call methods on {@link PredictInput.Builder} to create a request.
* @return Result of the Predict operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws LimitExceededException
* The subscriber exceeded the maximum number of operations. This exception can occur when listing objects
* such as DataSource.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws PredictorNotMountedException
* The exception is thrown when a predict request is made to an unmounted MLModel.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.Predict
*/
default PredictResponse predict(Consumer predictRequest) throws InvalidInputException,
ResourceNotFoundException, LimitExceededException, InternalServerException, PredictorNotMountedException,
AwsServiceException, SdkClientException, MachineLearningException {
return predict(PredictRequest.builder().applyMutation(predictRequest).build());
}
/**
*
* Updates the BatchPredictionName of a BatchPrediction.
*
*
* You can use the GetBatchPrediction operation to view the contents of the updated data element.
*
*
* @param updateBatchPredictionRequest
* @return Result of the UpdateBatchPrediction operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.UpdateBatchPrediction
*/
default UpdateBatchPredictionResponse updateBatchPrediction(UpdateBatchPredictionRequest updateBatchPredictionRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Updates the BatchPredictionName of a BatchPrediction.
*
*
* You can use the GetBatchPrediction operation to view the contents of the updated data element.
*
*
*
* This is a convenience which creates an instance of the {@link UpdateBatchPredictionRequest.Builder} avoiding the
* need to create one manually via {@link UpdateBatchPredictionRequest#builder()}
*
*
* @param updateBatchPredictionRequest
* A {@link Consumer} that will call methods on {@link UpdateBatchPredictionInput.Builder} to create a
* request.
* @return Result of the UpdateBatchPrediction operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.UpdateBatchPrediction
*/
default UpdateBatchPredictionResponse updateBatchPrediction(
Consumer updateBatchPredictionRequest) throws InvalidInputException,
ResourceNotFoundException, InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
return updateBatchPrediction(UpdateBatchPredictionRequest.builder().applyMutation(updateBatchPredictionRequest).build());
}
/**
*
* Updates the DataSourceName of a DataSource.
*
*
* You can use the GetDataSource operation to view the contents of the updated data element.
*
*
* @param updateDataSourceRequest
* @return Result of the UpdateDataSource operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.UpdateDataSource
*/
default UpdateDataSourceResponse updateDataSource(UpdateDataSourceRequest updateDataSourceRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Updates the DataSourceName of a DataSource.
*
*
* You can use the GetDataSource operation to view the contents of the updated data element.
*
*
*
* This is a convenience which creates an instance of the {@link UpdateDataSourceRequest.Builder} avoiding the need
* to create one manually via {@link UpdateDataSourceRequest#builder()}
*
*
* @param updateDataSourceRequest
* A {@link Consumer} that will call methods on {@link UpdateDataSourceInput.Builder} to create a request.
* @return Result of the UpdateDataSource operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.UpdateDataSource
*/
default UpdateDataSourceResponse updateDataSource(Consumer updateDataSourceRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
return updateDataSource(UpdateDataSourceRequest.builder().applyMutation(updateDataSourceRequest).build());
}
/**
*
* Updates the EvaluationName of an Evaluation.
*
*
* You can use the GetEvaluation operation to view the contents of the updated data element.
*
*
* @param updateEvaluationRequest
* @return Result of the UpdateEvaluation operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.UpdateEvaluation
*/
default UpdateEvaluationResponse updateEvaluation(UpdateEvaluationRequest updateEvaluationRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Updates the EvaluationName of an Evaluation.
*
*
* You can use the GetEvaluation operation to view the contents of the updated data element.
*
*
*
* This is a convenience which creates an instance of the {@link UpdateEvaluationRequest.Builder} avoiding the need
* to create one manually via {@link UpdateEvaluationRequest#builder()}
*
*
* @param updateEvaluationRequest
* A {@link Consumer} that will call methods on {@link UpdateEvaluationInput.Builder} to create a request.
* @return Result of the UpdateEvaluation operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.UpdateEvaluation
*/
default UpdateEvaluationResponse updateEvaluation(Consumer updateEvaluationRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
return updateEvaluation(UpdateEvaluationRequest.builder().applyMutation(updateEvaluationRequest).build());
}
/**
*
* Updates the MLModelName and the ScoreThreshold of an MLModel.
*
*
* You can use the GetMLModel operation to view the contents of the updated data element.
*
*
* @param updateMlModelRequest
* @return Result of the UpdateMLModel operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.UpdateMLModel
*/
default UpdateMlModelResponse updateMLModel(UpdateMlModelRequest updateMlModelRequest) throws InvalidInputException,
ResourceNotFoundException, InternalServerException, AwsServiceException, SdkClientException, MachineLearningException {
throw new UnsupportedOperationException();
}
/**
*
* Updates the MLModelName and the ScoreThreshold of an MLModel.
*
*
* You can use the GetMLModel operation to view the contents of the updated data element.
*
*
*
* This is a convenience which creates an instance of the {@link UpdateMlModelRequest.Builder} avoiding the need to
* create one manually via {@link UpdateMlModelRequest#builder()}
*
*
* @param updateMlModelRequest
* A {@link Consumer} that will call methods on {@link UpdateMLModelInput.Builder} to create a request.
* @return Result of the UpdateMLModel operation returned by the service.
* @throws InvalidInputException
* An error on the client occurred. Typically, the cause is an invalid input value.
* @throws ResourceNotFoundException
* A specified resource cannot be located.
* @throws InternalServerException
* An error on the server occurred when trying to process a request.
* @throws SdkException
* Base class for all exceptions that can be thrown by the SDK (both service and client). Can be used for
* catch all scenarios.
* @throws SdkClientException
* If any client side error occurs such as an IO related failure, failure to get credentials, etc.
* @throws MachineLearningException
* Base class for all service exceptions. Unknown exceptions will be thrown as an instance of this type.
* @sample MachineLearningClient.UpdateMLModel
*/
default UpdateMlModelResponse updateMLModel(Consumer updateMlModelRequest)
throws InvalidInputException, ResourceNotFoundException, InternalServerException, AwsServiceException,
SdkClientException, MachineLearningException {
return updateMLModel(UpdateMlModelRequest.builder().applyMutation(updateMlModelRequest).build());
}
static ServiceMetadata serviceMetadata() {
return ServiceMetadata.of("machinelearning");
}
}