@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public interface AmazonLookoutEquipmentAsync extends AmazonLookoutEquipment
AsyncHandler can be used to receive
notification when an asynchronous operation completes.
Note: Do not directly implement this interface, new methods are added to it regularly. Extend from
AbstractAmazonLookoutEquipmentAsync instead.
Amazon Lookout for Equipment is a machine learning service that uses advanced analytics to identify anomalies in machines from sensor data for use in predictive maintenance.
ENDPOINT_PREFIX| Modifier and Type | Method and Description |
|---|---|
Future<CreateDatasetResult> |
createDatasetAsync(CreateDatasetRequest createDatasetRequest)
Creates a container for a collection of data being ingested for analysis.
|
Future<CreateDatasetResult> |
createDatasetAsync(CreateDatasetRequest createDatasetRequest,
AsyncHandler<CreateDatasetRequest,CreateDatasetResult> asyncHandler)
Creates a container for a collection of data being ingested for analysis.
|
Future<CreateInferenceSchedulerResult> |
createInferenceSchedulerAsync(CreateInferenceSchedulerRequest createInferenceSchedulerRequest)
Creates a scheduled inference.
|
Future<CreateInferenceSchedulerResult> |
createInferenceSchedulerAsync(CreateInferenceSchedulerRequest createInferenceSchedulerRequest,
AsyncHandler<CreateInferenceSchedulerRequest,CreateInferenceSchedulerResult> asyncHandler)
Creates a scheduled inference.
|
Future<CreateModelResult> |
createModelAsync(CreateModelRequest createModelRequest)
Creates an ML model for data inference.
|
Future<CreateModelResult> |
createModelAsync(CreateModelRequest createModelRequest,
AsyncHandler<CreateModelRequest,CreateModelResult> asyncHandler)
Creates an ML model for data inference.
|
Future<DeleteDatasetResult> |
deleteDatasetAsync(DeleteDatasetRequest deleteDatasetRequest)
Deletes a dataset and associated artifacts.
|
Future<DeleteDatasetResult> |
deleteDatasetAsync(DeleteDatasetRequest deleteDatasetRequest,
AsyncHandler<DeleteDatasetRequest,DeleteDatasetResult> asyncHandler)
Deletes a dataset and associated artifacts.
|
Future<DeleteInferenceSchedulerResult> |
deleteInferenceSchedulerAsync(DeleteInferenceSchedulerRequest deleteInferenceSchedulerRequest)
Deletes an inference scheduler that has been set up.
|
Future<DeleteInferenceSchedulerResult> |
deleteInferenceSchedulerAsync(DeleteInferenceSchedulerRequest deleteInferenceSchedulerRequest,
AsyncHandler<DeleteInferenceSchedulerRequest,DeleteInferenceSchedulerResult> asyncHandler)
Deletes an inference scheduler that has been set up.
|
Future<DeleteModelResult> |
deleteModelAsync(DeleteModelRequest deleteModelRequest)
Deletes an ML model currently available for Amazon Lookout for Equipment.
|
Future<DeleteModelResult> |
deleteModelAsync(DeleteModelRequest deleteModelRequest,
AsyncHandler<DeleteModelRequest,DeleteModelResult> asyncHandler)
Deletes an ML model currently available for Amazon Lookout for Equipment.
|
Future<DescribeDataIngestionJobResult> |
describeDataIngestionJobAsync(DescribeDataIngestionJobRequest describeDataIngestionJobRequest)
Provides information on a specific data ingestion job such as creation time, dataset ARN, status, and so on.
|
Future<DescribeDataIngestionJobResult> |
describeDataIngestionJobAsync(DescribeDataIngestionJobRequest describeDataIngestionJobRequest,
AsyncHandler<DescribeDataIngestionJobRequest,DescribeDataIngestionJobResult> asyncHandler)
Provides information on a specific data ingestion job such as creation time, dataset ARN, status, and so on.
|
Future<DescribeDatasetResult> |
describeDatasetAsync(DescribeDatasetRequest describeDatasetRequest)
Provides a JSON description of the data that is in each time series dataset, including names, column names, and
data types.
|
Future<DescribeDatasetResult> |
describeDatasetAsync(DescribeDatasetRequest describeDatasetRequest,
AsyncHandler<DescribeDatasetRequest,DescribeDatasetResult> asyncHandler)
Provides a JSON description of the data that is in each time series dataset, including names, column names, and
data types.
|
Future<DescribeInferenceSchedulerResult> |
describeInferenceSchedulerAsync(DescribeInferenceSchedulerRequest describeInferenceSchedulerRequest)
Specifies information about the inference scheduler being used, including name, model, status, and associated
metadata
|
Future<DescribeInferenceSchedulerResult> |
describeInferenceSchedulerAsync(DescribeInferenceSchedulerRequest describeInferenceSchedulerRequest,
AsyncHandler<DescribeInferenceSchedulerRequest,DescribeInferenceSchedulerResult> asyncHandler)
Specifies information about the inference scheduler being used, including name, model, status, and associated
metadata
|
Future<DescribeModelResult> |
describeModelAsync(DescribeModelRequest describeModelRequest)
Provides a JSON containing the overall information about a specific ML model, including model name and ARN,
dataset, training and evaluation information, status, and so on.
|
Future<DescribeModelResult> |
describeModelAsync(DescribeModelRequest describeModelRequest,
AsyncHandler<DescribeModelRequest,DescribeModelResult> asyncHandler)
Provides a JSON containing the overall information about a specific ML model, including model name and ARN,
dataset, training and evaluation information, status, and so on.
|
Future<ListDataIngestionJobsResult> |
listDataIngestionJobsAsync(ListDataIngestionJobsRequest listDataIngestionJobsRequest)
Provides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data,
status, and so on.
|
Future<ListDataIngestionJobsResult> |
listDataIngestionJobsAsync(ListDataIngestionJobsRequest listDataIngestionJobsRequest,
AsyncHandler<ListDataIngestionJobsRequest,ListDataIngestionJobsResult> asyncHandler)
Provides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data,
status, and so on.
|
Future<ListDatasetsResult> |
listDatasetsAsync(ListDatasetsRequest listDatasetsRequest)
Lists all datasets currently available in your account, filtering on the dataset name.
|
Future<ListDatasetsResult> |
listDatasetsAsync(ListDatasetsRequest listDatasetsRequest,
AsyncHandler<ListDatasetsRequest,ListDatasetsResult> asyncHandler)
Lists all datasets currently available in your account, filtering on the dataset name.
|
Future<ListInferenceExecutionsResult> |
listInferenceExecutionsAsync(ListInferenceExecutionsRequest listInferenceExecutionsRequest)
Lists all inference executions that have been performed by the specified inference scheduler.
|
Future<ListInferenceExecutionsResult> |
listInferenceExecutionsAsync(ListInferenceExecutionsRequest listInferenceExecutionsRequest,
AsyncHandler<ListInferenceExecutionsRequest,ListInferenceExecutionsResult> asyncHandler)
Lists all inference executions that have been performed by the specified inference scheduler.
|
Future<ListInferenceSchedulersResult> |
listInferenceSchedulersAsync(ListInferenceSchedulersRequest listInferenceSchedulersRequest)
Retrieves a list of all inference schedulers currently available for your account.
|
Future<ListInferenceSchedulersResult> |
listInferenceSchedulersAsync(ListInferenceSchedulersRequest listInferenceSchedulersRequest,
AsyncHandler<ListInferenceSchedulersRequest,ListInferenceSchedulersResult> asyncHandler)
Retrieves a list of all inference schedulers currently available for your account.
|
Future<ListModelsResult> |
listModelsAsync(ListModelsRequest listModelsRequest)
Generates a list of all models in the account, including model name and ARN, dataset, and status.
|
Future<ListModelsResult> |
listModelsAsync(ListModelsRequest listModelsRequest,
AsyncHandler<ListModelsRequest,ListModelsResult> asyncHandler)
Generates a list of all models in the account, including model name and ARN, dataset, and status.
|
Future<ListTagsForResourceResult> |
listTagsForResourceAsync(ListTagsForResourceRequest listTagsForResourceRequest)
Lists all the tags for a specified resource, including key and value.
|
Future<ListTagsForResourceResult> |
listTagsForResourceAsync(ListTagsForResourceRequest listTagsForResourceRequest,
AsyncHandler<ListTagsForResourceRequest,ListTagsForResourceResult> asyncHandler)
Lists all the tags for a specified resource, including key and value.
|
Future<StartDataIngestionJobResult> |
startDataIngestionJobAsync(StartDataIngestionJobRequest startDataIngestionJobRequest)
Starts a data ingestion job.
|
Future<StartDataIngestionJobResult> |
startDataIngestionJobAsync(StartDataIngestionJobRequest startDataIngestionJobRequest,
AsyncHandler<StartDataIngestionJobRequest,StartDataIngestionJobResult> asyncHandler)
Starts a data ingestion job.
|
Future<StartInferenceSchedulerResult> |
startInferenceSchedulerAsync(StartInferenceSchedulerRequest startInferenceSchedulerRequest)
Starts an inference scheduler.
|
Future<StartInferenceSchedulerResult> |
startInferenceSchedulerAsync(StartInferenceSchedulerRequest startInferenceSchedulerRequest,
AsyncHandler<StartInferenceSchedulerRequest,StartInferenceSchedulerResult> asyncHandler)
Starts an inference scheduler.
|
Future<StopInferenceSchedulerResult> |
stopInferenceSchedulerAsync(StopInferenceSchedulerRequest stopInferenceSchedulerRequest)
Stops an inference scheduler.
|
Future<StopInferenceSchedulerResult> |
stopInferenceSchedulerAsync(StopInferenceSchedulerRequest stopInferenceSchedulerRequest,
AsyncHandler<StopInferenceSchedulerRequest,StopInferenceSchedulerResult> asyncHandler)
Stops an inference scheduler.
|
Future<TagResourceResult> |
tagResourceAsync(TagResourceRequest tagResourceRequest)
Associates a given tag to a resource in your account.
|
Future<TagResourceResult> |
tagResourceAsync(TagResourceRequest tagResourceRequest,
AsyncHandler<TagResourceRequest,TagResourceResult> asyncHandler)
Associates a given tag to a resource in your account.
|
Future<UntagResourceResult> |
untagResourceAsync(UntagResourceRequest untagResourceRequest)
Removes a specific tag from a given resource.
|
Future<UntagResourceResult> |
untagResourceAsync(UntagResourceRequest untagResourceRequest,
AsyncHandler<UntagResourceRequest,UntagResourceResult> asyncHandler)
Removes a specific tag from a given resource.
|
Future<UpdateInferenceSchedulerResult> |
updateInferenceSchedulerAsync(UpdateInferenceSchedulerRequest updateInferenceSchedulerRequest)
Updates an inference scheduler.
|
Future<UpdateInferenceSchedulerResult> |
updateInferenceSchedulerAsync(UpdateInferenceSchedulerRequest updateInferenceSchedulerRequest,
AsyncHandler<UpdateInferenceSchedulerRequest,UpdateInferenceSchedulerResult> asyncHandler)
Updates an inference scheduler.
|
createDataset, createInferenceScheduler, createModel, deleteDataset, deleteInferenceScheduler, deleteModel, describeDataIngestionJob, describeDataset, describeInferenceScheduler, describeModel, getCachedResponseMetadata, listDataIngestionJobs, listDatasets, listInferenceExecutions, listInferenceSchedulers, listModels, listTagsForResource, shutdown, startDataIngestionJob, startInferenceScheduler, stopInferenceScheduler, tagResource, untagResource, updateInferenceSchedulerFuture<CreateDatasetResult> createDatasetAsync(CreateDatasetRequest createDatasetRequest)
Creates a container for a collection of data being ingested for analysis. The dataset contains the metadata describing where the data is and what the data actually looks like. In other words, it contains the location of the data source, the data schema, and other information. A dataset also contains any tags associated with the ingested data.
createDatasetRequest - Future<CreateDatasetResult> createDatasetAsync(CreateDatasetRequest createDatasetRequest, AsyncHandler<CreateDatasetRequest,CreateDatasetResult> asyncHandler)
Creates a container for a collection of data being ingested for analysis. The dataset contains the metadata describing where the data is and what the data actually looks like. In other words, it contains the location of the data source, the data schema, and other information. A dataset also contains any tags associated with the ingested data.
createDatasetRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<CreateInferenceSchedulerResult> createInferenceSchedulerAsync(CreateInferenceSchedulerRequest createInferenceSchedulerRequest)
Creates a scheduled inference. Scheduling an inference is setting up a continuous real-time inference plan to analyze new measurement data. When setting up the schedule, you provide an S3 bucket location for the input data, assign it a delimiter between separate entries in the data, set an offset delay if desired, and set the frequency of inferencing. You must also provide an S3 bucket location for the output data.
createInferenceSchedulerRequest - Future<CreateInferenceSchedulerResult> createInferenceSchedulerAsync(CreateInferenceSchedulerRequest createInferenceSchedulerRequest, AsyncHandler<CreateInferenceSchedulerRequest,CreateInferenceSchedulerResult> asyncHandler)
Creates a scheduled inference. Scheduling an inference is setting up a continuous real-time inference plan to analyze new measurement data. When setting up the schedule, you provide an S3 bucket location for the input data, assign it a delimiter between separate entries in the data, set an offset delay if desired, and set the frequency of inferencing. You must also provide an S3 bucket location for the output data.
createInferenceSchedulerRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<CreateModelResult> createModelAsync(CreateModelRequest createModelRequest)
Creates an ML model for data inference.
A machine-learning (ML) model is a mathematical model that finds patterns in your data. In Amazon Lookout for Equipment, the model learns the patterns of normal behavior and detects abnormal behavior that could be potential equipment failure (or maintenance events). The models are made by analyzing normal data and abnormalities in machine behavior that have already occurred.
Your model is trained using a portion of the data from your dataset and uses that data to learn patterns of normal behavior and abnormal patterns that lead to equipment failure. Another portion of the data is used to evaluate the model's accuracy.
createModelRequest - Future<CreateModelResult> createModelAsync(CreateModelRequest createModelRequest, AsyncHandler<CreateModelRequest,CreateModelResult> asyncHandler)
Creates an ML model for data inference.
A machine-learning (ML) model is a mathematical model that finds patterns in your data. In Amazon Lookout for Equipment, the model learns the patterns of normal behavior and detects abnormal behavior that could be potential equipment failure (or maintenance events). The models are made by analyzing normal data and abnormalities in machine behavior that have already occurred.
Your model is trained using a portion of the data from your dataset and uses that data to learn patterns of normal behavior and abnormal patterns that lead to equipment failure. Another portion of the data is used to evaluate the model's accuracy.
createModelRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<DeleteDatasetResult> deleteDatasetAsync(DeleteDatasetRequest deleteDatasetRequest)
Deletes a dataset and associated artifacts. The operation will check to see if any inference scheduler or data ingestion job is currently using the dataset, and if there isn't, the dataset, its metadata, and any associated data stored in S3 will be deleted. This does not affect any models that used this dataset for training and evaluation, but does prevent it from being used in the future.
deleteDatasetRequest - Future<DeleteDatasetResult> deleteDatasetAsync(DeleteDatasetRequest deleteDatasetRequest, AsyncHandler<DeleteDatasetRequest,DeleteDatasetResult> asyncHandler)
Deletes a dataset and associated artifacts. The operation will check to see if any inference scheduler or data ingestion job is currently using the dataset, and if there isn't, the dataset, its metadata, and any associated data stored in S3 will be deleted. This does not affect any models that used this dataset for training and evaluation, but does prevent it from being used in the future.
deleteDatasetRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<DeleteInferenceSchedulerResult> deleteInferenceSchedulerAsync(DeleteInferenceSchedulerRequest deleteInferenceSchedulerRequest)
Deletes an inference scheduler that has been set up. Already processed output results are not affected.
deleteInferenceSchedulerRequest - Future<DeleteInferenceSchedulerResult> deleteInferenceSchedulerAsync(DeleteInferenceSchedulerRequest deleteInferenceSchedulerRequest, AsyncHandler<DeleteInferenceSchedulerRequest,DeleteInferenceSchedulerResult> asyncHandler)
Deletes an inference scheduler that has been set up. Already processed output results are not affected.
deleteInferenceSchedulerRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<DeleteModelResult> deleteModelAsync(DeleteModelRequest deleteModelRequest)
Deletes an ML model currently available for Amazon Lookout for Equipment. This will prevent it from being used with an inference scheduler, even one that is already set up.
deleteModelRequest - Future<DeleteModelResult> deleteModelAsync(DeleteModelRequest deleteModelRequest, AsyncHandler<DeleteModelRequest,DeleteModelResult> asyncHandler)
Deletes an ML model currently available for Amazon Lookout for Equipment. This will prevent it from being used with an inference scheduler, even one that is already set up.
deleteModelRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<DescribeDataIngestionJobResult> describeDataIngestionJobAsync(DescribeDataIngestionJobRequest describeDataIngestionJobRequest)
Provides information on a specific data ingestion job such as creation time, dataset ARN, status, and so on.
describeDataIngestionJobRequest - Future<DescribeDataIngestionJobResult> describeDataIngestionJobAsync(DescribeDataIngestionJobRequest describeDataIngestionJobRequest, AsyncHandler<DescribeDataIngestionJobRequest,DescribeDataIngestionJobResult> asyncHandler)
Provides information on a specific data ingestion job such as creation time, dataset ARN, status, and so on.
describeDataIngestionJobRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<DescribeDatasetResult> describeDatasetAsync(DescribeDatasetRequest describeDatasetRequest)
Provides a JSON description of the data that is in each time series dataset, including names, column names, and data types.
describeDatasetRequest - Future<DescribeDatasetResult> describeDatasetAsync(DescribeDatasetRequest describeDatasetRequest, AsyncHandler<DescribeDatasetRequest,DescribeDatasetResult> asyncHandler)
Provides a JSON description of the data that is in each time series dataset, including names, column names, and data types.
describeDatasetRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<DescribeInferenceSchedulerResult> describeInferenceSchedulerAsync(DescribeInferenceSchedulerRequest describeInferenceSchedulerRequest)
Specifies information about the inference scheduler being used, including name, model, status, and associated metadata
describeInferenceSchedulerRequest - Future<DescribeInferenceSchedulerResult> describeInferenceSchedulerAsync(DescribeInferenceSchedulerRequest describeInferenceSchedulerRequest, AsyncHandler<DescribeInferenceSchedulerRequest,DescribeInferenceSchedulerResult> asyncHandler)
Specifies information about the inference scheduler being used, including name, model, status, and associated metadata
describeInferenceSchedulerRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<DescribeModelResult> describeModelAsync(DescribeModelRequest describeModelRequest)
Provides a JSON containing the overall information about a specific ML model, including model name and ARN, dataset, training and evaluation information, status, and so on.
describeModelRequest - Future<DescribeModelResult> describeModelAsync(DescribeModelRequest describeModelRequest, AsyncHandler<DescribeModelRequest,DescribeModelResult> asyncHandler)
Provides a JSON containing the overall information about a specific ML model, including model name and ARN, dataset, training and evaluation information, status, and so on.
describeModelRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<ListDataIngestionJobsResult> listDataIngestionJobsAsync(ListDataIngestionJobsRequest listDataIngestionJobsRequest)
Provides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data, status, and so on.
listDataIngestionJobsRequest - Future<ListDataIngestionJobsResult> listDataIngestionJobsAsync(ListDataIngestionJobsRequest listDataIngestionJobsRequest, AsyncHandler<ListDataIngestionJobsRequest,ListDataIngestionJobsResult> asyncHandler)
Provides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data, status, and so on.
listDataIngestionJobsRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<ListDatasetsResult> listDatasetsAsync(ListDatasetsRequest listDatasetsRequest)
Lists all datasets currently available in your account, filtering on the dataset name.
listDatasetsRequest - Future<ListDatasetsResult> listDatasetsAsync(ListDatasetsRequest listDatasetsRequest, AsyncHandler<ListDatasetsRequest,ListDatasetsResult> asyncHandler)
Lists all datasets currently available in your account, filtering on the dataset name.
listDatasetsRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<ListInferenceExecutionsResult> listInferenceExecutionsAsync(ListInferenceExecutionsRequest listInferenceExecutionsRequest)
Lists all inference executions that have been performed by the specified inference scheduler.
listInferenceExecutionsRequest - Future<ListInferenceExecutionsResult> listInferenceExecutionsAsync(ListInferenceExecutionsRequest listInferenceExecutionsRequest, AsyncHandler<ListInferenceExecutionsRequest,ListInferenceExecutionsResult> asyncHandler)
Lists all inference executions that have been performed by the specified inference scheduler.
listInferenceExecutionsRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<ListInferenceSchedulersResult> listInferenceSchedulersAsync(ListInferenceSchedulersRequest listInferenceSchedulersRequest)
Retrieves a list of all inference schedulers currently available for your account.
listInferenceSchedulersRequest - Future<ListInferenceSchedulersResult> listInferenceSchedulersAsync(ListInferenceSchedulersRequest listInferenceSchedulersRequest, AsyncHandler<ListInferenceSchedulersRequest,ListInferenceSchedulersResult> asyncHandler)
Retrieves a list of all inference schedulers currently available for your account.
listInferenceSchedulersRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<ListModelsResult> listModelsAsync(ListModelsRequest listModelsRequest)
Generates a list of all models in the account, including model name and ARN, dataset, and status.
listModelsRequest - Future<ListModelsResult> listModelsAsync(ListModelsRequest listModelsRequest, AsyncHandler<ListModelsRequest,ListModelsResult> asyncHandler)
Generates a list of all models in the account, including model name and ARN, dataset, and status.
listModelsRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<ListTagsForResourceResult> listTagsForResourceAsync(ListTagsForResourceRequest listTagsForResourceRequest)
Lists all the tags for a specified resource, including key and value.
listTagsForResourceRequest - Future<ListTagsForResourceResult> listTagsForResourceAsync(ListTagsForResourceRequest listTagsForResourceRequest, AsyncHandler<ListTagsForResourceRequest,ListTagsForResourceResult> asyncHandler)
Lists all the tags for a specified resource, including key and value.
listTagsForResourceRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<StartDataIngestionJobResult> startDataIngestionJobAsync(StartDataIngestionJobRequest startDataIngestionJobRequest)
Starts a data ingestion job. Amazon Lookout for Equipment returns the job status.
startDataIngestionJobRequest - Future<StartDataIngestionJobResult> startDataIngestionJobAsync(StartDataIngestionJobRequest startDataIngestionJobRequest, AsyncHandler<StartDataIngestionJobRequest,StartDataIngestionJobResult> asyncHandler)
Starts a data ingestion job. Amazon Lookout for Equipment returns the job status.
startDataIngestionJobRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<StartInferenceSchedulerResult> startInferenceSchedulerAsync(StartInferenceSchedulerRequest startInferenceSchedulerRequest)
Starts an inference scheduler.
startInferenceSchedulerRequest - Future<StartInferenceSchedulerResult> startInferenceSchedulerAsync(StartInferenceSchedulerRequest startInferenceSchedulerRequest, AsyncHandler<StartInferenceSchedulerRequest,StartInferenceSchedulerResult> asyncHandler)
Starts an inference scheduler.
startInferenceSchedulerRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<StopInferenceSchedulerResult> stopInferenceSchedulerAsync(StopInferenceSchedulerRequest stopInferenceSchedulerRequest)
Stops an inference scheduler.
stopInferenceSchedulerRequest - Future<StopInferenceSchedulerResult> stopInferenceSchedulerAsync(StopInferenceSchedulerRequest stopInferenceSchedulerRequest, AsyncHandler<StopInferenceSchedulerRequest,StopInferenceSchedulerResult> asyncHandler)
Stops an inference scheduler.
stopInferenceSchedulerRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<TagResourceResult> tagResourceAsync(TagResourceRequest tagResourceRequest)
Associates a given tag to a resource in your account. A tag is a key-value pair which can be added to an Amazon Lookout for Equipment resource as metadata. Tags can be used for organizing your resources as well as helping you to search and filter by tag. Multiple tags can be added to a resource, either when you create it, or later. Up to 50 tags can be associated with each resource.
tagResourceRequest - Future<TagResourceResult> tagResourceAsync(TagResourceRequest tagResourceRequest, AsyncHandler<TagResourceRequest,TagResourceResult> asyncHandler)
Associates a given tag to a resource in your account. A tag is a key-value pair which can be added to an Amazon Lookout for Equipment resource as metadata. Tags can be used for organizing your resources as well as helping you to search and filter by tag. Multiple tags can be added to a resource, either when you create it, or later. Up to 50 tags can be associated with each resource.
tagResourceRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<UntagResourceResult> untagResourceAsync(UntagResourceRequest untagResourceRequest)
Removes a specific tag from a given resource. The tag is specified by its key.
untagResourceRequest - Future<UntagResourceResult> untagResourceAsync(UntagResourceRequest untagResourceRequest, AsyncHandler<UntagResourceRequest,UntagResourceResult> asyncHandler)
Removes a specific tag from a given resource. The tag is specified by its key.
untagResourceRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Future<UpdateInferenceSchedulerResult> updateInferenceSchedulerAsync(UpdateInferenceSchedulerRequest updateInferenceSchedulerRequest)
Updates an inference scheduler.
updateInferenceSchedulerRequest - Future<UpdateInferenceSchedulerResult> updateInferenceSchedulerAsync(UpdateInferenceSchedulerRequest updateInferenceSchedulerRequest, AsyncHandler<UpdateInferenceSchedulerRequest,UpdateInferenceSchedulerResult> asyncHandler)
Updates an inference scheduler.
updateInferenceSchedulerRequest - asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.