@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class AbstractAmazonLookoutEquipment extends Object implements AmazonLookoutEquipment
AmazonLookoutEquipment. Convenient method forms pass through to the corresponding
overload that takes a request object, which throws an UnsupportedOperationException.ENDPOINT_PREFIX| Modifier and Type | Method and Description |
|---|---|
CreateDatasetResult |
createDataset(CreateDatasetRequest request)
Creates a container for a collection of data being ingested for analysis.
|
CreateInferenceSchedulerResult |
createInferenceScheduler(CreateInferenceSchedulerRequest request)
Creates a scheduled inference.
|
CreateLabelResult |
createLabel(CreateLabelRequest request)
Creates a label for an event.
|
CreateLabelGroupResult |
createLabelGroup(CreateLabelGroupRequest request)
Creates a group of labels.
|
CreateModelResult |
createModel(CreateModelRequest request)
Creates a machine learning model for data inference.
|
CreateRetrainingSchedulerResult |
createRetrainingScheduler(CreateRetrainingSchedulerRequest request)
Creates a retraining scheduler on the specified model.
|
DeleteDatasetResult |
deleteDataset(DeleteDatasetRequest request)
Deletes a dataset and associated artifacts.
|
DeleteInferenceSchedulerResult |
deleteInferenceScheduler(DeleteInferenceSchedulerRequest request)
Deletes an inference scheduler that has been set up.
|
DeleteLabelResult |
deleteLabel(DeleteLabelRequest request)
Deletes a label.
|
DeleteLabelGroupResult |
deleteLabelGroup(DeleteLabelGroupRequest request)
Deletes a group of labels.
|
DeleteModelResult |
deleteModel(DeleteModelRequest request)
Deletes a machine learning model currently available for Amazon Lookout for Equipment.
|
DeleteResourcePolicyResult |
deleteResourcePolicy(DeleteResourcePolicyRequest request)
Deletes the resource policy attached to the resource.
|
DeleteRetrainingSchedulerResult |
deleteRetrainingScheduler(DeleteRetrainingSchedulerRequest request)
Deletes a retraining scheduler from a model.
|
DescribeDataIngestionJobResult |
describeDataIngestionJob(DescribeDataIngestionJobRequest request)
Provides information on a specific data ingestion job such as creation time, dataset ARN, and status.
|
DescribeDatasetResult |
describeDataset(DescribeDatasetRequest request)
Provides a JSON description of the data in each time series dataset, including names, column names, and data
types.
|
DescribeInferenceSchedulerResult |
describeInferenceScheduler(DescribeInferenceSchedulerRequest request)
Specifies information about the inference scheduler being used, including name, model, status, and associated
metadata
|
DescribeLabelResult |
describeLabel(DescribeLabelRequest request)
Returns the name of the label.
|
DescribeLabelGroupResult |
describeLabelGroup(DescribeLabelGroupRequest request)
Returns information about the label group.
|
DescribeModelResult |
describeModel(DescribeModelRequest request)
Provides a JSON containing the overall information about a specific machine learning model, including model name
and ARN, dataset, training and evaluation information, status, and so on.
|
DescribeModelVersionResult |
describeModelVersion(DescribeModelVersionRequest request)
Retrieves information about a specific machine learning model version.
|
DescribeResourcePolicyResult |
describeResourcePolicy(DescribeResourcePolicyRequest request)
Provides the details of a resource policy attached to a resource.
|
DescribeRetrainingSchedulerResult |
describeRetrainingScheduler(DescribeRetrainingSchedulerRequest request)
Provides a description of the retraining scheduler, including information such as the model name and retraining
parameters.
|
ResponseMetadata |
getCachedResponseMetadata(AmazonWebServiceRequest request)
Returns additional metadata for a previously executed successful request, typically used for debugging issues
where a service isn't acting as expected.
|
ImportDatasetResult |
importDataset(ImportDatasetRequest request)
Imports a dataset.
|
ImportModelVersionResult |
importModelVersion(ImportModelVersionRequest request)
Imports a model that has been trained successfully.
|
ListDataIngestionJobsResult |
listDataIngestionJobs(ListDataIngestionJobsRequest request)
Provides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data,
status, and so on.
|
ListDatasetsResult |
listDatasets(ListDatasetsRequest request)
Lists all datasets currently available in your account, filtering on the dataset name.
|
ListInferenceEventsResult |
listInferenceEvents(ListInferenceEventsRequest request)
Lists all inference events that have been found for the specified inference scheduler.
|
ListInferenceExecutionsResult |
listInferenceExecutions(ListInferenceExecutionsRequest request)
Lists all inference executions that have been performed by the specified inference scheduler.
|
ListInferenceSchedulersResult |
listInferenceSchedulers(ListInferenceSchedulersRequest request)
Retrieves a list of all inference schedulers currently available for your account.
|
ListLabelGroupsResult |
listLabelGroups(ListLabelGroupsRequest request)
Returns a list of the label groups.
|
ListLabelsResult |
listLabels(ListLabelsRequest request)
Provides a list of labels.
|
ListModelsResult |
listModels(ListModelsRequest request)
Generates a list of all models in the account, including model name and ARN, dataset, and status.
|
ListModelVersionsResult |
listModelVersions(ListModelVersionsRequest request)
Generates a list of all model versions for a given model, including the model version, model version ARN, and
status.
|
ListRetrainingSchedulersResult |
listRetrainingSchedulers(ListRetrainingSchedulersRequest request)
Lists all retraining schedulers in your account, filtering by model name prefix and status.
|
ListSensorStatisticsResult |
listSensorStatistics(ListSensorStatisticsRequest request)
Lists statistics about the data collected for each of the sensors that have been successfully ingested in the
particular dataset.
|
ListTagsForResourceResult |
listTagsForResource(ListTagsForResourceRequest request)
Lists all the tags for a specified resource, including key and value.
|
PutResourcePolicyResult |
putResourcePolicy(PutResourcePolicyRequest request)
Creates a resource control policy for a given resource.
|
void |
shutdown()
Shuts down this client object, releasing any resources that might be held open.
|
StartDataIngestionJobResult |
startDataIngestionJob(StartDataIngestionJobRequest request)
Starts a data ingestion job.
|
StartInferenceSchedulerResult |
startInferenceScheduler(StartInferenceSchedulerRequest request)
Starts an inference scheduler.
|
StartRetrainingSchedulerResult |
startRetrainingScheduler(StartRetrainingSchedulerRequest request)
Starts a retraining scheduler.
|
StopInferenceSchedulerResult |
stopInferenceScheduler(StopInferenceSchedulerRequest request)
Stops an inference scheduler.
|
StopRetrainingSchedulerResult |
stopRetrainingScheduler(StopRetrainingSchedulerRequest request)
Stops a retraining scheduler.
|
TagResourceResult |
tagResource(TagResourceRequest request)
Associates a given tag to a resource in your account.
|
UntagResourceResult |
untagResource(UntagResourceRequest request)
Removes a specific tag from a given resource.
|
UpdateActiveModelVersionResult |
updateActiveModelVersion(UpdateActiveModelVersionRequest request)
Sets the active model version for a given machine learning model.
|
UpdateInferenceSchedulerResult |
updateInferenceScheduler(UpdateInferenceSchedulerRequest request)
Updates an inference scheduler.
|
UpdateLabelGroupResult |
updateLabelGroup(UpdateLabelGroupRequest request)
Updates the label group.
|
UpdateModelResult |
updateModel(UpdateModelRequest request)
Updates a model in the account.
|
UpdateRetrainingSchedulerResult |
updateRetrainingScheduler(UpdateRetrainingSchedulerRequest request)
Updates a retraining scheduler.
|
public CreateDatasetResult createDataset(CreateDatasetRequest request)
AmazonLookoutEquipmentCreates 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. For example, 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.
createDataset in interface AmazonLookoutEquipmentpublic CreateInferenceSchedulerResult createInferenceScheduler(CreateInferenceSchedulerRequest request)
AmazonLookoutEquipmentCreates 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.
createInferenceScheduler in interface AmazonLookoutEquipmentpublic CreateLabelResult createLabel(CreateLabelRequest request)
AmazonLookoutEquipmentCreates a label for an event.
createLabel in interface AmazonLookoutEquipmentpublic CreateLabelGroupResult createLabelGroup(CreateLabelGroupRequest request)
AmazonLookoutEquipmentCreates a group of labels.
createLabelGroup in interface AmazonLookoutEquipmentpublic CreateModelResult createModel(CreateModelRequest request)
AmazonLookoutEquipmentCreates a machine learning 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.
createModel in interface AmazonLookoutEquipmentpublic CreateRetrainingSchedulerResult createRetrainingScheduler(CreateRetrainingSchedulerRequest request)
AmazonLookoutEquipmentCreates a retraining scheduler on the specified model.
createRetrainingScheduler in interface AmazonLookoutEquipmentpublic DeleteDatasetResult deleteDataset(DeleteDatasetRequest request)
AmazonLookoutEquipmentDeletes 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.
deleteDataset in interface AmazonLookoutEquipmentpublic DeleteInferenceSchedulerResult deleteInferenceScheduler(DeleteInferenceSchedulerRequest request)
AmazonLookoutEquipmentDeletes an inference scheduler that has been set up. Prior inference results will not be deleted.
deleteInferenceScheduler in interface AmazonLookoutEquipmentpublic DeleteLabelResult deleteLabel(DeleteLabelRequest request)
AmazonLookoutEquipmentDeletes a label.
deleteLabel in interface AmazonLookoutEquipmentpublic DeleteLabelGroupResult deleteLabelGroup(DeleteLabelGroupRequest request)
AmazonLookoutEquipmentDeletes a group of labels.
deleteLabelGroup in interface AmazonLookoutEquipmentpublic DeleteModelResult deleteModel(DeleteModelRequest request)
AmazonLookoutEquipmentDeletes a machine learning 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.
deleteModel in interface AmazonLookoutEquipmentpublic DeleteResourcePolicyResult deleteResourcePolicy(DeleteResourcePolicyRequest request)
AmazonLookoutEquipmentDeletes the resource policy attached to the resource.
deleteResourcePolicy in interface AmazonLookoutEquipmentpublic DeleteRetrainingSchedulerResult deleteRetrainingScheduler(DeleteRetrainingSchedulerRequest request)
AmazonLookoutEquipment
Deletes a retraining scheduler from a model. The retraining scheduler must be in the STOPPED status.
deleteRetrainingScheduler in interface AmazonLookoutEquipmentpublic DescribeDataIngestionJobResult describeDataIngestionJob(DescribeDataIngestionJobRequest request)
AmazonLookoutEquipmentProvides information on a specific data ingestion job such as creation time, dataset ARN, and status.
describeDataIngestionJob in interface AmazonLookoutEquipmentpublic DescribeDatasetResult describeDataset(DescribeDatasetRequest request)
AmazonLookoutEquipmentProvides a JSON description of the data in each time series dataset, including names, column names, and data types.
describeDataset in interface AmazonLookoutEquipmentpublic DescribeInferenceSchedulerResult describeInferenceScheduler(DescribeInferenceSchedulerRequest request)
AmazonLookoutEquipmentSpecifies information about the inference scheduler being used, including name, model, status, and associated metadata
describeInferenceScheduler in interface AmazonLookoutEquipmentpublic DescribeLabelResult describeLabel(DescribeLabelRequest request)
AmazonLookoutEquipmentReturns the name of the label.
describeLabel in interface AmazonLookoutEquipmentpublic DescribeLabelGroupResult describeLabelGroup(DescribeLabelGroupRequest request)
AmazonLookoutEquipmentReturns information about the label group.
describeLabelGroup in interface AmazonLookoutEquipmentpublic DescribeModelResult describeModel(DescribeModelRequest request)
AmazonLookoutEquipmentProvides a JSON containing the overall information about a specific machine learning model, including model name and ARN, dataset, training and evaluation information, status, and so on.
describeModel in interface AmazonLookoutEquipmentpublic DescribeModelVersionResult describeModelVersion(DescribeModelVersionRequest request)
AmazonLookoutEquipmentRetrieves information about a specific machine learning model version.
describeModelVersion in interface AmazonLookoutEquipmentpublic DescribeResourcePolicyResult describeResourcePolicy(DescribeResourcePolicyRequest request)
AmazonLookoutEquipmentProvides the details of a resource policy attached to a resource.
describeResourcePolicy in interface AmazonLookoutEquipmentpublic DescribeRetrainingSchedulerResult describeRetrainingScheduler(DescribeRetrainingSchedulerRequest request)
AmazonLookoutEquipmentProvides a description of the retraining scheduler, including information such as the model name and retraining parameters.
describeRetrainingScheduler in interface AmazonLookoutEquipmentpublic ImportDatasetResult importDataset(ImportDatasetRequest request)
AmazonLookoutEquipmentImports a dataset.
importDataset in interface AmazonLookoutEquipmentpublic ImportModelVersionResult importModelVersion(ImportModelVersionRequest request)
AmazonLookoutEquipmentImports a model that has been trained successfully.
importModelVersion in interface AmazonLookoutEquipmentpublic ListDataIngestionJobsResult listDataIngestionJobs(ListDataIngestionJobsRequest request)
AmazonLookoutEquipmentProvides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data, status, and so on.
listDataIngestionJobs in interface AmazonLookoutEquipmentpublic ListDatasetsResult listDatasets(ListDatasetsRequest request)
AmazonLookoutEquipmentLists all datasets currently available in your account, filtering on the dataset name.
listDatasets in interface AmazonLookoutEquipmentpublic ListInferenceEventsResult listInferenceEvents(ListInferenceEventsRequest request)
AmazonLookoutEquipmentLists all inference events that have been found for the specified inference scheduler.
listInferenceEvents in interface AmazonLookoutEquipmentpublic ListInferenceExecutionsResult listInferenceExecutions(ListInferenceExecutionsRequest request)
AmazonLookoutEquipmentLists all inference executions that have been performed by the specified inference scheduler.
listInferenceExecutions in interface AmazonLookoutEquipmentpublic ListInferenceSchedulersResult listInferenceSchedulers(ListInferenceSchedulersRequest request)
AmazonLookoutEquipmentRetrieves a list of all inference schedulers currently available for your account.
listInferenceSchedulers in interface AmazonLookoutEquipmentpublic ListLabelGroupsResult listLabelGroups(ListLabelGroupsRequest request)
AmazonLookoutEquipmentReturns a list of the label groups.
listLabelGroups in interface AmazonLookoutEquipmentpublic ListLabelsResult listLabels(ListLabelsRequest request)
AmazonLookoutEquipmentProvides a list of labels.
listLabels in interface AmazonLookoutEquipmentpublic ListModelVersionsResult listModelVersions(ListModelVersionsRequest request)
AmazonLookoutEquipment
Generates a list of all model versions for a given model, including the model version, model version ARN, and
status. To list a subset of versions, use the MaxModelVersion and MinModelVersion
fields.
listModelVersions in interface AmazonLookoutEquipmentpublic ListModelsResult listModels(ListModelsRequest request)
AmazonLookoutEquipmentGenerates a list of all models in the account, including model name and ARN, dataset, and status.
listModels in interface AmazonLookoutEquipmentpublic ListRetrainingSchedulersResult listRetrainingSchedulers(ListRetrainingSchedulersRequest request)
AmazonLookoutEquipmentLists all retraining schedulers in your account, filtering by model name prefix and status.
listRetrainingSchedulers in interface AmazonLookoutEquipmentpublic ListSensorStatisticsResult listSensorStatistics(ListSensorStatisticsRequest request)
AmazonLookoutEquipmentLists statistics about the data collected for each of the sensors that have been successfully ingested in the particular dataset. Can also be used to retreive Sensor Statistics for a previous ingestion job.
listSensorStatistics in interface AmazonLookoutEquipmentpublic ListTagsForResourceResult listTagsForResource(ListTagsForResourceRequest request)
AmazonLookoutEquipmentLists all the tags for a specified resource, including key and value.
listTagsForResource in interface AmazonLookoutEquipmentpublic PutResourcePolicyResult putResourcePolicy(PutResourcePolicyRequest request)
AmazonLookoutEquipmentCreates a resource control policy for a given resource.
putResourcePolicy in interface AmazonLookoutEquipmentpublic StartDataIngestionJobResult startDataIngestionJob(StartDataIngestionJobRequest request)
AmazonLookoutEquipmentStarts a data ingestion job. Amazon Lookout for Equipment returns the job status.
startDataIngestionJob in interface AmazonLookoutEquipmentpublic StartInferenceSchedulerResult startInferenceScheduler(StartInferenceSchedulerRequest request)
AmazonLookoutEquipmentStarts an inference scheduler.
startInferenceScheduler in interface AmazonLookoutEquipmentpublic StartRetrainingSchedulerResult startRetrainingScheduler(StartRetrainingSchedulerRequest request)
AmazonLookoutEquipmentStarts a retraining scheduler.
startRetrainingScheduler in interface AmazonLookoutEquipmentpublic StopInferenceSchedulerResult stopInferenceScheduler(StopInferenceSchedulerRequest request)
AmazonLookoutEquipmentStops an inference scheduler.
stopInferenceScheduler in interface AmazonLookoutEquipmentpublic StopRetrainingSchedulerResult stopRetrainingScheduler(StopRetrainingSchedulerRequest request)
AmazonLookoutEquipmentStops a retraining scheduler.
stopRetrainingScheduler in interface AmazonLookoutEquipmentpublic TagResourceResult tagResource(TagResourceRequest request)
AmazonLookoutEquipmentAssociates 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.
tagResource in interface AmazonLookoutEquipmentpublic UntagResourceResult untagResource(UntagResourceRequest request)
AmazonLookoutEquipmentRemoves a specific tag from a given resource. The tag is specified by its key.
untagResource in interface AmazonLookoutEquipmentpublic UpdateActiveModelVersionResult updateActiveModelVersion(UpdateActiveModelVersionRequest request)
AmazonLookoutEquipmentSets the active model version for a given machine learning model.
updateActiveModelVersion in interface AmazonLookoutEquipmentpublic UpdateInferenceSchedulerResult updateInferenceScheduler(UpdateInferenceSchedulerRequest request)
AmazonLookoutEquipmentUpdates an inference scheduler.
updateInferenceScheduler in interface AmazonLookoutEquipmentpublic UpdateLabelGroupResult updateLabelGroup(UpdateLabelGroupRequest request)
AmazonLookoutEquipmentUpdates the label group.
updateLabelGroup in interface AmazonLookoutEquipmentpublic UpdateModelResult updateModel(UpdateModelRequest request)
AmazonLookoutEquipmentUpdates a model in the account.
updateModel in interface AmazonLookoutEquipmentpublic UpdateRetrainingSchedulerResult updateRetrainingScheduler(UpdateRetrainingSchedulerRequest request)
AmazonLookoutEquipmentUpdates a retraining scheduler.
updateRetrainingScheduler in interface AmazonLookoutEquipmentpublic void shutdown()
AmazonLookoutEquipmentshutdown in interface AmazonLookoutEquipmentpublic ResponseMetadata getCachedResponseMetadata(AmazonWebServiceRequest request)
AmazonLookoutEquipmentResponse metadata is only cached for a limited period of time, so if you need to access this extra diagnostic information for an executed request, you should use this method to retrieve it as soon as possible after executing a request.
getCachedResponseMetadata in interface AmazonLookoutEquipmentrequest - The originally executed request.