Class: Aws::LookoutEquipment::Client
- Inherits:
-
Seahorse::Client::Base
- Object
- Seahorse::Client::Base
- Aws::LookoutEquipment::Client
- Includes:
- ClientStubs
- Defined in:
- gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb
Overview
An API client for LookoutEquipment. To construct a client, you need to configure a :region
and :credentials
.
client = Aws::LookoutEquipment::Client.new(
region: region_name,
credentials: credentials,
# ...
)
For details on configuring region and credentials see the developer guide.
See #initialize for a full list of supported configuration options.
Instance Attribute Summary
Attributes inherited from Seahorse::Client::Base
API Operations collapse
-
#create_dataset(params = {}) ⇒ Types::CreateDatasetResponse
Creates a container for a collection of data being ingested for analysis.
-
#create_inference_scheduler(params = {}) ⇒ Types::CreateInferenceSchedulerResponse
Creates a scheduled inference.
-
#create_model(params = {}) ⇒ Types::CreateModelResponse
Creates an ML model for data inference.
-
#delete_dataset(params = {}) ⇒ Struct
Deletes a dataset and associated artifacts.
-
#delete_inference_scheduler(params = {}) ⇒ Struct
Deletes an inference scheduler that has been set up.
-
#delete_model(params = {}) ⇒ Struct
Deletes an ML model currently available for Amazon Lookout for Equipment.
-
#describe_data_ingestion_job(params = {}) ⇒ Types::DescribeDataIngestionJobResponse
Provides information on a specific data ingestion job such as creation time, dataset ARN, and status.
-
#describe_dataset(params = {}) ⇒ Types::DescribeDatasetResponse
Provides a JSON description of the data in each time series dataset, including names, column names, and data types.
-
#describe_inference_scheduler(params = {}) ⇒ Types::DescribeInferenceSchedulerResponse
Specifies information about the inference scheduler being used, including name, model, status, and associated metadata.
-
#describe_model(params = {}) ⇒ Types::DescribeModelResponse
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.
-
#list_data_ingestion_jobs(params = {}) ⇒ Types::ListDataIngestionJobsResponse
Provides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data, status, and so on.
-
#list_datasets(params = {}) ⇒ Types::ListDatasetsResponse
Lists all datasets currently available in your account, filtering on the dataset name.
-
#list_inference_events(params = {}) ⇒ Types::ListInferenceEventsResponse
Lists all inference events that have been found for the specified inference scheduler.
-
#list_inference_executions(params = {}) ⇒ Types::ListInferenceExecutionsResponse
Lists all inference executions that have been performed by the specified inference scheduler.
-
#list_inference_schedulers(params = {}) ⇒ Types::ListInferenceSchedulersResponse
Retrieves a list of all inference schedulers currently available for your account.
-
#list_models(params = {}) ⇒ Types::ListModelsResponse
Generates a list of all models in the account, including model name and ARN, dataset, and status.
-
#list_sensor_statistics(params = {}) ⇒ Types::ListSensorStatisticsResponse
Lists statistics about the data collected for each of the sensors that have been successfully ingested in the particular dataset.
-
#list_tags_for_resource(params = {}) ⇒ Types::ListTagsForResourceResponse
Lists all the tags for a specified resource, including key and value.
-
#start_data_ingestion_job(params = {}) ⇒ Types::StartDataIngestionJobResponse
Starts a data ingestion job.
-
#start_inference_scheduler(params = {}) ⇒ Types::StartInferenceSchedulerResponse
Starts an inference scheduler.
-
#stop_inference_scheduler(params = {}) ⇒ Types::StopInferenceSchedulerResponse
Stops an inference scheduler.
-
#tag_resource(params = {}) ⇒ Struct
Associates a given tag to a resource in your account.
-
#untag_resource(params = {}) ⇒ Struct
Removes a specific tag from a given resource.
-
#update_inference_scheduler(params = {}) ⇒ Struct
Updates an inference scheduler.
Instance Method Summary collapse
-
#initialize(options) ⇒ Client
constructor
A new instance of Client.
Methods included from ClientStubs
#api_requests, #stub_data, #stub_responses
Methods inherited from Seahorse::Client::Base
add_plugin, api, clear_plugins, define, new, #operation_names, plugins, remove_plugin, set_api, set_plugins
Methods included from Seahorse::Client::HandlerBuilder
#handle, #handle_request, #handle_response
Constructor Details
#initialize(options) ⇒ Client
Returns a new instance of Client.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 358 def initialize(*args) super end |
Instance Method Details
#create_dataset(params = {}) ⇒ Types::CreateDatasetResponse
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.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 425 def create_dataset(params = {}, = {}) req = build_request(:create_dataset, params) req.send_request() end |
#create_inference_scheduler(params = {}) ⇒ Types::CreateInferenceSchedulerResponse
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.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 544 def create_inference_scheduler(params = {}, = {}) req = build_request(:create_inference_scheduler, params) req.send_request() end |
#create_model(params = {}) ⇒ Types::CreateModelResponse
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.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 674 def create_model(params = {}, = {}) req = build_request(:create_model, params) req.send_request() end |
#delete_dataset(params = {}) ⇒ Struct
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.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 701 def delete_dataset(params = {}, = {}) req = build_request(:delete_dataset, params) req.send_request() end |
#delete_inference_scheduler(params = {}) ⇒ Struct
Deletes an inference scheduler that has been set up. Already processed output results are not affected.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 724 def delete_inference_scheduler(params = {}, = {}) req = build_request(:delete_inference_scheduler, params) req.send_request() end |
#delete_model(params = {}) ⇒ Struct
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.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 748 def delete_model(params = {}, = {}) req = build_request(:delete_model, params) req.send_request() end |
#describe_data_ingestion_job(params = {}) ⇒ Types::DescribeDataIngestionJobResponse
Provides information on a specific data ingestion job such as creation time, dataset ARN, and status.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 814 def describe_data_ingestion_job(params = {}, = {}) req = build_request(:describe_data_ingestion_job, params) req.send_request() end |
#describe_dataset(params = {}) ⇒ Types::DescribeDatasetResponse
Provides a JSON description of the data in each time series dataset, including names, column names, and data types.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 880 def describe_dataset(params = {}, = {}) req = build_request(:describe_dataset, params) req.send_request() end |
#describe_inference_scheduler(params = {}) ⇒ Types::DescribeInferenceSchedulerResponse
Specifies information about the inference scheduler being used, including name, model, status, and associated metadata
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 939 def describe_inference_scheduler(params = {}, = {}) req = build_request(:describe_inference_scheduler, params) req.send_request() end |
#describe_model(params = {}) ⇒ Types::DescribeModelResponse
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.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1010 def describe_model(params = {}, = {}) req = build_request(:describe_model, params) req.send_request() end |
#list_data_ingestion_jobs(params = {}) ⇒ Types::ListDataIngestionJobsResponse
Provides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data, status, and so on.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1063 def list_data_ingestion_jobs(params = {}, = {}) req = build_request(:list_data_ingestion_jobs, params) req.send_request() end |
#list_datasets(params = {}) ⇒ Types::ListDatasetsResponse
Lists all datasets currently available in your account, filtering on the dataset name.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1109 def list_datasets(params = {}, = {}) req = build_request(:list_datasets, params) req.send_request() end |
#list_inference_events(params = {}) ⇒ Types::ListInferenceEventsResponse
Lists all inference events that have been found for the specified inference scheduler.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1167 def list_inference_events(params = {}, = {}) req = build_request(:list_inference_events, params) req.send_request() end |
#list_inference_executions(params = {}) ⇒ Types::ListInferenceExecutionsResponse
Lists all inference executions that have been performed by the specified inference scheduler.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1243 def list_inference_executions(params = {}, = {}) req = build_request(:list_inference_executions, params) req.send_request() end |
#list_inference_schedulers(params = {}) ⇒ Types::ListInferenceSchedulersResponse
Retrieves a list of all inference schedulers currently available for your account.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1296 def list_inference_schedulers(params = {}, = {}) req = build_request(:list_inference_schedulers, params) req.send_request() end |
#list_models(params = {}) ⇒ Types::ListModelsResponse
Generates a list of all models in the account, including model name and ARN, dataset, and status.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1353 def list_models(params = {}, = {}) req = build_request(:list_models, params) req.send_request() end |
#list_sensor_statistics(params = {}) ⇒ Types::ListSensorStatisticsResponse
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.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1424 def list_sensor_statistics(params = {}, = {}) req = build_request(:list_sensor_statistics, params) req.send_request() end |
#list_tags_for_resource(params = {}) ⇒ Types::ListTagsForResourceResponse
Lists all the tags for a specified resource, including key and value.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1455 def (params = {}, = {}) req = build_request(:list_tags_for_resource, params) req.send_request() end |
#start_data_ingestion_job(params = {}) ⇒ Types::StartDataIngestionJobResponse
Starts a data ingestion job. Amazon Lookout for Equipment returns the job status.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1510 def start_data_ingestion_job(params = {}, = {}) req = build_request(:start_data_ingestion_job, params) req.send_request() end |
#start_inference_scheduler(params = {}) ⇒ Types::StartInferenceSchedulerResponse
Starts an inference scheduler.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1546 def start_inference_scheduler(params = {}, = {}) req = build_request(:start_inference_scheduler, params) req.send_request() end |
#stop_inference_scheduler(params = {}) ⇒ Types::StopInferenceSchedulerResponse
Stops an inference scheduler.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1582 def stop_inference_scheduler(params = {}, = {}) req = build_request(:stop_inference_scheduler, params) req.send_request() end |
#tag_resource(params = {}) ⇒ Struct
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.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1620 def tag_resource(params = {}, = {}) req = build_request(:tag_resource, params) req.send_request() end |
#untag_resource(params = {}) ⇒ Struct
Removes a specific tag from a given resource. The tag is specified by its key.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1648 def untag_resource(params = {}, = {}) req = build_request(:untag_resource, params) req.send_request() end |
#update_inference_scheduler(params = {}) ⇒ Struct
Updates an inference scheduler.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1723 def update_inference_scheduler(params = {}, = {}) req = build_request(:update_inference_scheduler, params) req.send_request() end |