@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)
AmazonLookoutEquipment
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. 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 AmazonLookoutEquipment
public CreateInferenceSchedulerResult createInferenceScheduler(CreateInferenceSchedulerRequest request)
AmazonLookoutEquipment
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.
createInferenceScheduler
in interface AmazonLookoutEquipment
public CreateLabelResult createLabel(CreateLabelRequest request)
AmazonLookoutEquipment
Creates a label for an event.
createLabel
in interface AmazonLookoutEquipment
public CreateLabelGroupResult createLabelGroup(CreateLabelGroupRequest request)
AmazonLookoutEquipment
Creates a group of labels.
createLabelGroup
in interface AmazonLookoutEquipment
public CreateModelResult createModel(CreateModelRequest request)
AmazonLookoutEquipment
Creates 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 AmazonLookoutEquipment
public CreateRetrainingSchedulerResult createRetrainingScheduler(CreateRetrainingSchedulerRequest request)
AmazonLookoutEquipment
Creates a retraining scheduler on the specified model.
createRetrainingScheduler
in interface AmazonLookoutEquipment
public DeleteDatasetResult deleteDataset(DeleteDatasetRequest request)
AmazonLookoutEquipment
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.
deleteDataset
in interface AmazonLookoutEquipment
public DeleteInferenceSchedulerResult deleteInferenceScheduler(DeleteInferenceSchedulerRequest request)
AmazonLookoutEquipment
Deletes an inference scheduler that has been set up. Prior inference results will not be deleted.
deleteInferenceScheduler
in interface AmazonLookoutEquipment
public DeleteLabelResult deleteLabel(DeleteLabelRequest request)
AmazonLookoutEquipment
Deletes a label.
deleteLabel
in interface AmazonLookoutEquipment
public DeleteLabelGroupResult deleteLabelGroup(DeleteLabelGroupRequest request)
AmazonLookoutEquipment
Deletes a group of labels.
deleteLabelGroup
in interface AmazonLookoutEquipment
public DeleteModelResult deleteModel(DeleteModelRequest request)
AmazonLookoutEquipment
Deletes 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 AmazonLookoutEquipment
public DeleteResourcePolicyResult deleteResourcePolicy(DeleteResourcePolicyRequest request)
AmazonLookoutEquipment
Deletes the resource policy attached to the resource.
deleteResourcePolicy
in interface AmazonLookoutEquipment
public DeleteRetrainingSchedulerResult deleteRetrainingScheduler(DeleteRetrainingSchedulerRequest request)
AmazonLookoutEquipment
Deletes a retraining scheduler from a model. The retraining scheduler must be in the STOPPED
status.
deleteRetrainingScheduler
in interface AmazonLookoutEquipment
public DescribeDataIngestionJobResult describeDataIngestionJob(DescribeDataIngestionJobRequest request)
AmazonLookoutEquipment
Provides information on a specific data ingestion job such as creation time, dataset ARN, and status.
describeDataIngestionJob
in interface AmazonLookoutEquipment
public DescribeDatasetResult describeDataset(DescribeDatasetRequest request)
AmazonLookoutEquipment
Provides a JSON description of the data in each time series dataset, including names, column names, and data types.
describeDataset
in interface AmazonLookoutEquipment
public DescribeInferenceSchedulerResult describeInferenceScheduler(DescribeInferenceSchedulerRequest request)
AmazonLookoutEquipment
Specifies information about the inference scheduler being used, including name, model, status, and associated metadata
describeInferenceScheduler
in interface AmazonLookoutEquipment
public DescribeLabelResult describeLabel(DescribeLabelRequest request)
AmazonLookoutEquipment
Returns the name of the label.
describeLabel
in interface AmazonLookoutEquipment
public DescribeLabelGroupResult describeLabelGroup(DescribeLabelGroupRequest request)
AmazonLookoutEquipment
Returns information about the label group.
describeLabelGroup
in interface AmazonLookoutEquipment
public DescribeModelResult describeModel(DescribeModelRequest request)
AmazonLookoutEquipment
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.
describeModel
in interface AmazonLookoutEquipment
public DescribeModelVersionResult describeModelVersion(DescribeModelVersionRequest request)
AmazonLookoutEquipment
Retrieves information about a specific machine learning model version.
describeModelVersion
in interface AmazonLookoutEquipment
public DescribeResourcePolicyResult describeResourcePolicy(DescribeResourcePolicyRequest request)
AmazonLookoutEquipment
Provides the details of a resource policy attached to a resource.
describeResourcePolicy
in interface AmazonLookoutEquipment
public DescribeRetrainingSchedulerResult describeRetrainingScheduler(DescribeRetrainingSchedulerRequest request)
AmazonLookoutEquipment
Provides a description of the retraining scheduler, including information such as the model name and retraining parameters.
describeRetrainingScheduler
in interface AmazonLookoutEquipment
public ImportDatasetResult importDataset(ImportDatasetRequest request)
AmazonLookoutEquipment
Imports a dataset.
importDataset
in interface AmazonLookoutEquipment
public ImportModelVersionResult importModelVersion(ImportModelVersionRequest request)
AmazonLookoutEquipment
Imports a model that has been trained successfully.
importModelVersion
in interface AmazonLookoutEquipment
public ListDataIngestionJobsResult listDataIngestionJobs(ListDataIngestionJobsRequest request)
AmazonLookoutEquipment
Provides 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 AmazonLookoutEquipment
public ListDatasetsResult listDatasets(ListDatasetsRequest request)
AmazonLookoutEquipment
Lists all datasets currently available in your account, filtering on the dataset name.
listDatasets
in interface AmazonLookoutEquipment
public ListInferenceEventsResult listInferenceEvents(ListInferenceEventsRequest request)
AmazonLookoutEquipment
Lists all inference events that have been found for the specified inference scheduler.
listInferenceEvents
in interface AmazonLookoutEquipment
public ListInferenceExecutionsResult listInferenceExecutions(ListInferenceExecutionsRequest request)
AmazonLookoutEquipment
Lists all inference executions that have been performed by the specified inference scheduler.
listInferenceExecutions
in interface AmazonLookoutEquipment
public ListInferenceSchedulersResult listInferenceSchedulers(ListInferenceSchedulersRequest request)
AmazonLookoutEquipment
Retrieves a list of all inference schedulers currently available for your account.
listInferenceSchedulers
in interface AmazonLookoutEquipment
public ListLabelGroupsResult listLabelGroups(ListLabelGroupsRequest request)
AmazonLookoutEquipment
Returns a list of the label groups.
listLabelGroups
in interface AmazonLookoutEquipment
public ListLabelsResult listLabels(ListLabelsRequest request)
AmazonLookoutEquipment
Provides a list of labels.
listLabels
in interface AmazonLookoutEquipment
public 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 AmazonLookoutEquipment
public ListModelsResult listModels(ListModelsRequest request)
AmazonLookoutEquipment
Generates a list of all models in the account, including model name and ARN, dataset, and status.
listModels
in interface AmazonLookoutEquipment
public ListRetrainingSchedulersResult listRetrainingSchedulers(ListRetrainingSchedulersRequest request)
AmazonLookoutEquipment
Lists all retraining schedulers in your account, filtering by model name prefix and status.
listRetrainingSchedulers
in interface AmazonLookoutEquipment
public ListSensorStatisticsResult listSensorStatistics(ListSensorStatisticsRequest request)
AmazonLookoutEquipment
Lists 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 AmazonLookoutEquipment
public ListTagsForResourceResult listTagsForResource(ListTagsForResourceRequest request)
AmazonLookoutEquipment
Lists all the tags for a specified resource, including key and value.
listTagsForResource
in interface AmazonLookoutEquipment
public PutResourcePolicyResult putResourcePolicy(PutResourcePolicyRequest request)
AmazonLookoutEquipment
Creates a resource control policy for a given resource.
putResourcePolicy
in interface AmazonLookoutEquipment
public StartDataIngestionJobResult startDataIngestionJob(StartDataIngestionJobRequest request)
AmazonLookoutEquipment
Starts a data ingestion job. Amazon Lookout for Equipment returns the job status.
startDataIngestionJob
in interface AmazonLookoutEquipment
public StartInferenceSchedulerResult startInferenceScheduler(StartInferenceSchedulerRequest request)
AmazonLookoutEquipment
Starts an inference scheduler.
startInferenceScheduler
in interface AmazonLookoutEquipment
public StartRetrainingSchedulerResult startRetrainingScheduler(StartRetrainingSchedulerRequest request)
AmazonLookoutEquipment
Starts a retraining scheduler.
startRetrainingScheduler
in interface AmazonLookoutEquipment
public StopInferenceSchedulerResult stopInferenceScheduler(StopInferenceSchedulerRequest request)
AmazonLookoutEquipment
Stops an inference scheduler.
stopInferenceScheduler
in interface AmazonLookoutEquipment
public StopRetrainingSchedulerResult stopRetrainingScheduler(StopRetrainingSchedulerRequest request)
AmazonLookoutEquipment
Stops a retraining scheduler.
stopRetrainingScheduler
in interface AmazonLookoutEquipment
public TagResourceResult tagResource(TagResourceRequest request)
AmazonLookoutEquipment
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.
tagResource
in interface AmazonLookoutEquipment
public UntagResourceResult untagResource(UntagResourceRequest request)
AmazonLookoutEquipment
Removes a specific tag from a given resource. The tag is specified by its key.
untagResource
in interface AmazonLookoutEquipment
public UpdateActiveModelVersionResult updateActiveModelVersion(UpdateActiveModelVersionRequest request)
AmazonLookoutEquipment
Sets the active model version for a given machine learning model.
updateActiveModelVersion
in interface AmazonLookoutEquipment
public UpdateInferenceSchedulerResult updateInferenceScheduler(UpdateInferenceSchedulerRequest request)
AmazonLookoutEquipment
Updates an inference scheduler.
updateInferenceScheduler
in interface AmazonLookoutEquipment
public UpdateLabelGroupResult updateLabelGroup(UpdateLabelGroupRequest request)
AmazonLookoutEquipment
Updates the label group.
updateLabelGroup
in interface AmazonLookoutEquipment
public UpdateModelResult updateModel(UpdateModelRequest request)
AmazonLookoutEquipment
Updates a model in the account.
updateModel
in interface AmazonLookoutEquipment
public UpdateRetrainingSchedulerResult updateRetrainingScheduler(UpdateRetrainingSchedulerRequest request)
AmazonLookoutEquipment
Updates a retraining scheduler.
updateRetrainingScheduler
in interface AmazonLookoutEquipment
public void shutdown()
AmazonLookoutEquipment
shutdown
in interface AmazonLookoutEquipment
public ResponseMetadata getCachedResponseMetadata(AmazonWebServiceRequest request)
AmazonLookoutEquipment
Response metadata is only cached for a limited period of time, so if you need to access this extra diagnostic information for an executed request, you should use this method to retrieve it as soon as possible after executing a request.
getCachedResponseMetadata
in interface AmazonLookoutEquipment
request
- The originally executed request.