Class: Aws::LookoutEquipment::Client

Inherits:
Seahorse::Client::Base
  • Object
show all
Includes:
ClientStubs
Defined in:
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](/sdk-for-ruby/v3/developer-guide/setup-config.html).

See #initialize for a full list of supported configuration options.

Class Attribute Summary collapse

API Operations collapse

Class Method Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(options) ⇒ Client

Returns a new instance of Client.

Parameters:

  • options (Hash)

Options Hash (options):

  • :plugins (Array<Seahorse::Client::Plugin>) — default: []] —

    A list of plugins to apply to the client. Each plugin is either a class name or an instance of a plugin class.

  • :credentials (required, Aws::CredentialProvider) —

    Your AWS credentials. This can be an instance of any one of the following classes:

    • ‘Aws::Credentials` - Used for configuring static, non-refreshing credentials.

    • ‘Aws::SharedCredentials` - Used for loading static credentials from a shared file, such as `~/.aws/config`.

    • ‘Aws::AssumeRoleCredentials` - Used when you need to assume a role.

    • ‘Aws::AssumeRoleWebIdentityCredentials` - Used when you need to assume a role after providing credentials via the web.

    • ‘Aws::SSOCredentials` - Used for loading credentials from AWS SSO using an access token generated from `aws login`.

    • ‘Aws::ProcessCredentials` - Used for loading credentials from a process that outputs to stdout.

    • ‘Aws::InstanceProfileCredentials` - Used for loading credentials from an EC2 IMDS on an EC2 instance.

    • ‘Aws::ECSCredentials` - Used for loading credentials from instances running in ECS.

    • ‘Aws::CognitoIdentityCredentials` - Used for loading credentials from the Cognito Identity service.

    When ‘:credentials` are not configured directly, the following locations will be searched for credentials:

    • ‘Aws.config`

    • The ‘:access_key_id`, `:secret_access_key`, `:session_token`, and `:account_id` options.

    • ENV, ENV, ENV, and ENV

    • ‘~/.aws/credentials`

    • ‘~/.aws/config`

    • EC2/ECS IMDS instance profile - When used by default, the timeouts are very aggressive. Construct and pass an instance of ‘Aws::InstanceProfileCredentials` or `Aws::ECSCredentials` to enable retries and extended timeouts. Instance profile credential fetching can be disabled by setting ENV to true.

  • :region (required, String) —

    The AWS region to connect to. The configured ‘:region` is used to determine the service `:endpoint`. When not passed, a default `:region` is searched for in the following locations:

  • :access_key_id (String)
  • :account_id (String)
  • :active_endpoint_cache (Boolean) — default: false —

    When set to ‘true`, a thread polling for endpoints will be running in the background every 60 secs (default). Defaults to `false`.

  • :adaptive_retry_wait_to_fill (Boolean) — default: true —

    Used only in ‘adaptive` retry mode. When true, the request will sleep until there is sufficent client side capacity to retry the request. When false, the request will raise a `RetryCapacityNotAvailableError` and will not retry instead of sleeping.

  • :client_side_monitoring (Boolean) — default: false —

    When ‘true`, client-side metrics will be collected for all API requests from this client.

  • :client_side_monitoring_client_id (String) — default: "" —

    Allows you to provide an identifier for this client which will be attached to all generated client side metrics. Defaults to an empty string.

  • :client_side_monitoring_host (String) — default: "127.0.0.1" —

    Allows you to specify the DNS hostname or IPv4 or IPv6 address that the client side monitoring agent is running on, where client metrics will be published via UDP.

  • :client_side_monitoring_port (Integer) — default: 31000 —

    Required for publishing client metrics. The port that the client side monitoring agent is running on, where client metrics will be published via UDP.

  • :client_side_monitoring_publisher (Aws::ClientSideMonitoring::Publisher) — default: Aws::ClientSideMonitoring::Publisher —

    Allows you to provide a custom client-side monitoring publisher class. By default, will use the Client Side Monitoring Agent Publisher.

  • :convert_params (Boolean) — default: true —

    When ‘true`, an attempt is made to coerce request parameters into the required types.

  • :correct_clock_skew (Boolean) — default: true —

    Used only in ‘standard` and adaptive retry modes. Specifies whether to apply a clock skew correction and retry requests with skewed client clocks.

  • :defaults_mode (String) — default: "legacy" —

    See DefaultsModeConfiguration for a list of the accepted modes and the configuration defaults that are included.

  • :disable_host_prefix_injection (Boolean) — default: false —

    Set to true to disable SDK automatically adding host prefix to default service endpoint when available.

  • :disable_request_compression (Boolean) — default: false —

    When set to ‘true’ the request body will not be compressed for supported operations.

  • :endpoint (String, URI::HTTPS, URI::HTTP) —

    Normally you should not configure the ‘:endpoint` option directly. This is normally constructed from the `:region` option. Configuring `:endpoint` is normally reserved for connecting to test or custom endpoints. The endpoint should be a URI formatted like:

    'http://example.com'
'https://example.com'
'http://example.com:123'
  • :endpoint_cache_max_entries (Integer) — default: 1000 —

    Used for the maximum size limit of the LRU cache storing endpoints data for endpoint discovery enabled operations. Defaults to 1000.

  • :endpoint_cache_max_threads (Integer) — default: 10 —

    Used for the maximum threads in use for polling endpoints to be cached, defaults to 10.

  • :endpoint_cache_poll_interval (Integer) — default: 60 —

    When :endpoint_discovery and :active_endpoint_cache is enabled, Use this option to config the time interval in seconds for making requests fetching endpoints information. Defaults to 60 sec.

  • :endpoint_discovery (Boolean) — default: false —

    When set to ‘true`, endpoint discovery will be enabled for operations when available.

  • :ignore_configured_endpoint_urls (Boolean) —

    Setting to true disables use of endpoint URLs provided via environment variables and the shared configuration file.

  • :log_formatter (Aws::Log::Formatter) — default: Aws::Log::Formatter.default —

    The log formatter.

  • :log_level (Symbol) — default: :info —

    The log level to send messages to the ‘:logger` at.

  • :logger (Logger) —

    The Logger instance to send log messages to. If this option is not set, logging will be disabled.

  • :max_attempts (Integer) — default: 3 —

    An integer representing the maximum number attempts that will be made for a single request, including the initial attempt. For example, setting this value to 5 will result in a request being retried up to 4 times. Used in ‘standard` and `adaptive` retry modes.

  • :profile (String) — default: "default" —

    Used when loading credentials from the shared credentials file at HOME/.aws/credentials. When not specified, ‘default’ is used.

  • :request_min_compression_size_bytes (Integer) — default: 10240 —

    The minimum size in bytes that triggers compression for request bodies. The value must be non-negative integer value between 0 and 10485780 bytes inclusive.

  • :retry_backoff (Proc) —

    A proc or lambda used for backoff. Defaults to 2**retries * retry_base_delay. This option is only used in the ‘legacy` retry mode.

  • :retry_base_delay (Float) — default: 0.3 —

    The base delay in seconds used by the default backoff function. This option is only used in the ‘legacy` retry mode.

  • :retry_jitter (Symbol) — default: :none —

    A delay randomiser function used by the default backoff function. Some predefined functions can be referenced by name - :none, :equal, :full, otherwise a Proc that takes and returns a number. This option is only used in the ‘legacy` retry mode.

    @see www.awsarchitectureblog.com/2015/03/backoff.html

  • :retry_limit (Integer) — default: 3 —

    The maximum number of times to retry failed requests. Only ~ 500 level server errors and certain ~ 400 level client errors are retried. Generally, these are throttling errors, data checksum errors, networking errors, timeout errors, auth errors, endpoint discovery, and errors from expired credentials. This option is only used in the ‘legacy` retry mode.

  • :retry_max_delay (Integer) — default: 0 —

    The maximum number of seconds to delay between retries (0 for no limit) used by the default backoff function. This option is only used in the ‘legacy` retry mode.

  • :retry_mode (String) — default: "legacy" —

    Specifies which retry algorithm to use. Values are:

    • ‘legacy` - The pre-existing retry behavior. This is default value if no retry mode is provided.

    • ‘standard` - A standardized set of retry rules across the AWS SDKs. This includes support for retry quotas, which limit the number of unsuccessful retries a client can make.

    • ‘adaptive` - An experimental retry mode that includes all the functionality of `standard` mode along with automatic client side throttling. This is a provisional mode that may change behavior in the future.

  • :sdk_ua_app_id (String) —

    A unique and opaque application ID that is appended to the User-Agent header as app/sdk_ua_app_id. It should have a maximum length of 50. This variable is sourced from environment variable AWS_SDK_UA_APP_ID or the shared config profile attribute sdk_ua_app_id.

  • :secret_access_key (String)
  • :session_token (String)
  • :sigv4a_signing_region_set (Array) —

    A list of regions that should be signed with SigV4a signing. When not passed, a default ‘:sigv4a_signing_region_set` is searched for in the following locations:

  • :simple_json (Boolean) — default: false —

    Disables request parameter conversion, validation, and formatting. Also disables response data type conversions. The request parameters hash must be formatted exactly as the API expects.This option is useful when you want to ensure the highest level of performance by avoiding overhead of walking request parameters and response data structures.

  • :stub_responses (Boolean) — default: false —

    Causes the client to return stubbed responses. By default fake responses are generated and returned. You can specify the response data to return or errors to raise by calling ClientStubs#stub_responses. See ClientStubs for more information.

    ** Please note ** When response stubbing is enabled, no HTTP requests are made, and retries are disabled.

  • :telemetry_provider (Aws::Telemetry::TelemetryProviderBase) — default: Aws::Telemetry::NoOpTelemetryProvider —

    Allows you to provide a telemetry provider, which is used to emit telemetry data. By default, uses ‘NoOpTelemetryProvider` which will not record or emit any telemetry data. The SDK supports the following telemetry providers:

    • OpenTelemetry (OTel) - To use the OTel provider, install and require the

    ‘opentelemetry-sdk` gem and then, pass in an instance of a `Aws::Telemetry::OTelProvider` for telemetry provider.

  • :token_provider (Aws::TokenProvider) —

    A Bearer Token Provider. This can be an instance of any one of the following classes:

    • ‘Aws::StaticTokenProvider` - Used for configuring static, non-refreshing tokens.

    • ‘Aws::SSOTokenProvider` - Used for loading tokens from AWS SSO using an access token generated from `aws login`.

    When ‘:token_provider` is not configured directly, the `Aws::TokenProviderChain` will be used to search for tokens configured for your profile in shared configuration files.

  • :use_dualstack_endpoint (Boolean) —

    When set to ‘true`, dualstack enabled endpoints (with `.aws` TLD) will be used if available.

  • :use_fips_endpoint (Boolean) —

    When set to ‘true`, fips compatible endpoints will be used if available. When a `fips` region is used, the region is normalized and this config is set to `true`.

  • :validate_params (Boolean) — default: true —

    When ‘true`, request parameters are validated before sending the request.

  • :endpoint_provider (Aws::LookoutEquipment::EndpointProvider) —

    The endpoint provider used to resolve endpoints. Any object that responds to ‘#resolve_endpoint(parameters)` where `parameters` is a Struct similar to `Aws::LookoutEquipment::EndpointParameters`.

  • :http_continue_timeout (Float) — default: 1 —

    The number of seconds to wait for a 100-continue response before sending the request body. This option has no effect unless the request has “Expect” header set to “100-continue”. Defaults to ‘nil` which disables this behaviour. This value can safely be set per request on the session.

  • :http_idle_timeout (Float) — default: 5 —

    The number of seconds a connection is allowed to sit idle before it is considered stale. Stale connections are closed and removed from the pool before making a request.

  • :http_open_timeout (Float) — default: 15 —

    The default number of seconds to wait for response data. This value can safely be set per-request on the session.

  • :http_proxy (URI::HTTP, String) —

    A proxy to send requests through. Formatted like ‘proxy.com:123’.

  • :http_read_timeout (Float) — default: 60 —

    The default number of seconds to wait for response data. This value can safely be set per-request on the session.

  • :http_wire_trace (Boolean) — default: false —

    When ‘true`, HTTP debug output will be sent to the `:logger`.

  • :on_chunk_received (Proc) —

    When a Proc object is provided, it will be used as callback when each chunk of the response body is received. It provides three arguments: the chunk, the number of bytes received, and the total number of bytes in the response (or nil if the server did not send a ‘content-length`).

  • :on_chunk_sent (Proc) —

    When a Proc object is provided, it will be used as callback when each chunk of the request body is sent. It provides three arguments: the chunk, the number of bytes read from the body, and the total number of bytes in the body.

  • :raise_response_errors (Boolean) — default: true —

    When ‘true`, response errors are raised.

  • :ssl_ca_bundle (String) —

    Full path to the SSL certificate authority bundle file that should be used when verifying peer certificates. If you do not pass ‘:ssl_ca_bundle` or `:ssl_ca_directory` the the system default will be used if available.

  • :ssl_ca_directory (String) —

    Full path of the directory that contains the unbundled SSL certificate authority files for verifying peer certificates. If you do not pass ‘:ssl_ca_bundle` or `:ssl_ca_directory` the the system default will be used if available.

  • :ssl_ca_store (String) —

    Sets the X509::Store to verify peer certificate.

  • :ssl_cert (OpenSSL::X509::Certificate) —

    Sets a client certificate when creating http connections.

  • :ssl_key (OpenSSL::PKey) —

    Sets a client key when creating http connections.

  • :ssl_timeout (Float) —

    Sets the SSL timeout in seconds

  • :ssl_verify_peer (Boolean) — default: true —

    When ‘true`, SSL peer certificates are verified when establishing a connection.



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 451

def initialize(*args)
  super
end

Class Attribute Details

.identifier ⇒ Object (readonly)

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future. 



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 3379

def identifier
  @identifier
end

Class Method Details

.errors_module ⇒ Object

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future. 



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 3382

def errors_module
  Errors
end

Instance Method Details

#build_request(operation_name, params = {}) ⇒ Object

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.

Parameters:

  • params ({}) (defaults to: {}) 


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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 3352

def build_request(operation_name, params = {})
  handlers = @handlers.for(operation_name)
  tracer = config.telemetry_provider.tracer_provider.tracer(
    Aws::Telemetry.module_to_tracer_name('Aws::LookoutEquipment')
  )
  context = Seahorse::Client::RequestContext.new(
    operation_name: operation_name,
    operation: config.api.operation(operation_name),
    client: self,
    params: params,
    config: config,
    tracer: tracer
  )
  context[:gem_name] = 'aws-sdk-lookoutequipment'
  context[:gem_version] = '1.42.0'
  Seahorse::Client::Request.new(handlers, context)
end

#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. 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.

Examples:

Request syntax with placeholder values


resp = client.create_dataset({
  dataset_name: "DatasetName", # required
  dataset_schema: {
    inline_data_schema: "InlineDataSchema",
  },
  server_side_kms_key_id: "NameOrArn",
  client_token: "IdempotenceToken", # required
  tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
})

Response structure


resp.dataset_name #=> String
resp.dataset_arn #=> String
resp.status #=> String, one of "CREATED", "INGESTION_IN_PROGRESS", "ACTIVE", "IMPORT_IN_PROGRESS"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :dataset_name (required, String) —

    The name of the dataset being created.

  • :dataset_schema (Types::DatasetSchema) —

    A JSON description of the data that is in each time series dataset, including names, column names, and data types.

  • :server_side_kms_key_id (String) —

    Provides the identifier of the KMS key used to encrypt dataset data by Amazon Lookout for Equipment.

  • :client_token (required, String) —

    A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

    **A suitable default value is auto-generated.** You should normally not need to pass this option.**

  • :tags (Array<Types::Tag>) —

    Any tags associated with the ingested data described in the dataset.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 517

def create_dataset(params = {}, options = {})
  req = build_request(:create_dataset, params)
  req.send_request(options)
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.

Examples:

Request syntax with placeholder values


resp = client.create_inference_scheduler({
  model_name: "ModelName", # required
  inference_scheduler_name: "InferenceSchedulerName", # required
  data_delay_offset_in_minutes: 1,
  data_upload_frequency: "PT5M", # required, accepts PT5M, PT10M, PT15M, PT30M, PT1H
  data_input_configuration: { # required
    s3_input_configuration: {
      bucket: "S3Bucket", # required
      prefix: "S3Prefix",
    },
    input_time_zone_offset: "TimeZoneOffset",
    inference_input_name_configuration: {
      timestamp_format: "FileNameTimestampFormat",
      component_timestamp_delimiter: "ComponentTimestampDelimiter",
    },
  },
  data_output_configuration: { # required
    s3_output_configuration: { # required
      bucket: "S3Bucket", # required
      prefix: "S3Prefix",
    },
    kms_key_id: "NameOrArn",
  },
  role_arn: "IamRoleArn", # required
  server_side_kms_key_id: "NameOrArn",
  client_token: "IdempotenceToken", # required
  tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
})

Response structure


resp.inference_scheduler_arn #=> String
resp.inference_scheduler_name #=> String
resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
resp.model_quality #=> String, one of "QUALITY_THRESHOLD_MET", "CANNOT_DETERMINE_QUALITY", "POOR_QUALITY_DETECTED"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    The name of the previously trained machine learning model being used to create the inference scheduler.

  • :inference_scheduler_name (required, String) —

    The name of the inference scheduler being created.

  • :data_delay_offset_in_minutes (Integer) —

    The interval (in minutes) of planned delay at the start of each inference segment. For example, if inference is set to run every ten minutes, the delay is set to five minutes and the time is 09:08. The inference scheduler will wake up at the configured interval (which, without a delay configured, would be 09:10) plus the additional five minute delay time (so 09:15) to check your Amazon S3 bucket. The delay provides a buffer for you to upload data at the same frequency, so that you don’t have to stop and restart the scheduler when uploading new data.

    For more information, see [Understanding the inference process].

    [1]: docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-inference-process.html

  • :data_upload_frequency (required, String) —

    How often data is uploaded to the source Amazon S3 bucket for the input data. The value chosen is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment runs inference on your data.

    For more information, see [Understanding the inference process].

    [1]: docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-inference-process.html

  • :data_input_configuration (required, Types::InferenceInputConfiguration) —

    Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location.

  • :data_output_configuration (required, Types::InferenceOutputConfiguration) —

    Specifies configuration information for the output results for the inference scheduler, including the S3 location for the output.

  • :role_arn (required, String) —

    The Amazon Resource Name (ARN) of a role with permission to access the data source being used for the inference.

  • :server_side_kms_key_id (String) —

    Provides the identifier of the KMS key used to encrypt inference scheduler data by Amazon Lookout for Equipment.

  • :client_token (required, String) —

    A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

    **A suitable default value is auto-generated.** You should normally not need to pass this option.**

  • :tags (Array<Types::Tag>) —

    Any tags associated with the inference scheduler.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 649

def create_inference_scheduler(params = {}, options = {})
  req = build_request(:create_inference_scheduler, params)
  req.send_request(options)
end

#create_label(params = {}) ⇒ Types::CreateLabelResponse

Creates a label for an event.

Examples:

Request syntax with placeholder values


resp = client.create_label({
  label_group_name: "LabelGroupName", # required
  start_time: Time.now, # required
  end_time: Time.now, # required
  rating: "ANOMALY", # required, accepts ANOMALY, NO_ANOMALY, NEUTRAL
  fault_code: "FaultCode",
  notes: "Comments",
  equipment: "Equipment",
  client_token: "IdempotenceToken", # required
})

Response structure


resp.label_id #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :label_group_name (required, String) —

    The name of a group of labels.

    Data in this field will be retained for service usage. Follow best practices for the security of your data.

  • :start_time (required, Time, DateTime, Date, Integer, String) —

    The start time of the labeled event.

  • :end_time (required, Time, DateTime, Date, Integer, String) —

    The end time of the labeled event.

  • :rating (required, String) —

    Indicates whether a labeled event represents an anomaly.

  • :fault_code (String) —

    Provides additional information about the label. The fault code must be defined in the FaultCodes attribute of the label group.

    Data in this field will be retained for service usage. Follow best practices for the security of your data.

  • :notes (String) —

    Metadata providing additional information about the label.

    Data in this field will be retained for service usage. Follow best practices for the security of your data.

  • :equipment (String) —

    Indicates that a label pertains to a particular piece of equipment.

    Data in this field will be retained for service usage. Follow best practices for the security of your data.

  • :client_token (required, String) —

    A unique identifier for the request to create a label. If you do not set the client request token, Lookout for Equipment generates one.

    **A suitable default value is auto-generated.** You should normally not need to pass this option.**

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 722

def create_label(params = {}, options = {})
  req = build_request(:create_label, params)
  req.send_request(options)
end

#create_label_group(params = {}) ⇒ Types::CreateLabelGroupResponse

Creates a group of labels.

Examples:

Request syntax with placeholder values


resp = client.create_label_group({
  label_group_name: "LabelGroupName", # required
  fault_codes: ["FaultCode"],
  client_token: "IdempotenceToken", # required
  tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
})

Response structure


resp.label_group_name #=> String
resp.label_group_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :label_group_name (required, String) —

    Names a group of labels.

    Data in this field will be retained for service usage. Follow best practices for the security of your data.

  • :fault_codes (Array<String>) —

    The acceptable fault codes (indicating the type of anomaly associated with the label) that can be used with this label group.

    Data in this field will be retained for service usage. Follow best practices for the security of your data.

  • :client_token (required, String) —

    A unique identifier for the request to create a label group. If you do not set the client request token, Lookout for Equipment generates one.

    **A suitable default value is auto-generated.** You should normally not need to pass this option.**

  • :tags (Array<Types::Tag>) —

    Tags that provide metadata about the label group you are creating.

    Data in this field will be retained for service usage. Follow best practices for the security of your data.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 783

def create_label_group(params = {}, options = {})
  req = build_request(:create_label_group, params)
  req.send_request(options)
end

#create_model(params = {}) ⇒ Types::CreateModelResponse

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.

Examples:

Request syntax with placeholder values


resp = client.create_model({
  model_name: "ModelName", # required
  dataset_name: "DatasetIdentifier", # required
  dataset_schema: {
    inline_data_schema: "InlineDataSchema",
  },
  labels_input_configuration: {
    s3_input_configuration: {
      bucket: "S3Bucket", # required
      prefix: "S3Prefix",
    },
    label_group_name: "LabelGroupName",
  },
  client_token: "IdempotenceToken", # required
  training_data_start_time: Time.now,
  training_data_end_time: Time.now,
  evaluation_data_start_time: Time.now,
  evaluation_data_end_time: Time.now,
  role_arn: "IamRoleArn",
  data_pre_processing_configuration: {
    target_sampling_rate: "PT1S", # accepts PT1S, PT5S, PT10S, PT15S, PT30S, PT1M, PT5M, PT10M, PT15M, PT30M, PT1H
  },
  server_side_kms_key_id: "NameOrArn",
  tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
  off_condition: "OffCondition",
  model_diagnostics_output_configuration: {
    s3_output_configuration: { # required
      bucket: "S3Bucket", # required
      prefix: "S3Prefix",
    },
    kms_key_id: "NameOrArn",
  },
})

Response structure


resp.model_arn #=> String
resp.status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    The name for the machine learning model to be created.

  • :dataset_name (required, String) —

    The name of the dataset for the machine learning model being created.

  • :dataset_schema (Types::DatasetSchema) —

    The data schema for the machine learning model being created.

  • :labels_input_configuration (Types::LabelsInputConfiguration) —

    The input configuration for the labels being used for the machine learning model that’s being created.

  • :client_token (required, String) —

    A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

    **A suitable default value is auto-generated.** You should normally not need to pass this option.**

  • :training_data_start_time (Time, DateTime, Date, Integer, String) —

    Indicates the time reference in the dataset that should be used to begin the subset of training data for the machine learning model.

  • :training_data_end_time (Time, DateTime, Date, Integer, String) —

    Indicates the time reference in the dataset that should be used to end the subset of training data for the machine learning model.

  • :evaluation_data_start_time (Time, DateTime, Date, Integer, String) —

    Indicates the time reference in the dataset that should be used to begin the subset of evaluation data for the machine learning model.

  • :evaluation_data_end_time (Time, DateTime, Date, Integer, String) —

    Indicates the time reference in the dataset that should be used to end the subset of evaluation data for the machine learning model.

  • :role_arn (String) —

    The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the machine learning model.

  • :data_pre_processing_configuration (Types::DataPreProcessingConfiguration) —

    The configuration is the ‘TargetSamplingRate`, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the `TargetSamplingRate` is 1 minute.

    When providing a value for the ‘TargetSamplingRate`, you must attach the prefix “PT” to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H

  • :server_side_kms_key_id (String) —

    Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.

  • :tags (Array<Types::Tag>) —

    Any tags associated with the machine learning model being created.

  • :off_condition (String) —

    Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.

  • :model_diagnostics_output_configuration (Types::ModelDiagnosticsOutputConfiguration) —

    The Amazon S3 location where you want Amazon Lookout for Equipment to save the pointwise model diagnostics. You must also specify the ‘RoleArn` request parameter.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 926

def create_model(params = {}, options = {})
  req = build_request(:create_model, params)
  req.send_request(options)
end

#create_retraining_scheduler(params = {}) ⇒ Types::CreateRetrainingSchedulerResponse

Creates a retraining scheduler on the specified model.

Examples:

Example: Creates a retraining scheduler with manual promote mode


resp = client.create_retraining_scheduler({
  client_token: "sample-client-token", 
  lookback_window: "P360D", 
  model_name: "sample-model", 
  promote_mode: "MANUAL", 
  retraining_frequency: "P1M", 
})

resp.to_h outputs the following:
{
  model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", 
  model_name: "sample-model", 
  status: "PENDING", 
}

Example: Creates a retraining scheduler with a specific start date


resp = client.create_retraining_scheduler({
  client_token: "sample-client-token", 
  lookback_window: "P360D", 
  model_name: "sample-model", 
  retraining_frequency: "P1M", 
  retraining_start_date: Time.parse("2024-01-01T00:00:00Z"), 
})

resp.to_h outputs the following:
{
  model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", 
  model_name: "sample-model", 
  status: "PENDING", 
}

Request syntax with placeholder values


resp = client.create_retraining_scheduler({
  model_name: "ModelName", # required
  retraining_start_date: Time.now,
  retraining_frequency: "RetrainingFrequency", # required
  lookback_window: "LookbackWindow", # required
  promote_mode: "MANAGED", # accepts MANAGED, MANUAL
  client_token: "IdempotenceToken", # required
})

Response structure


resp.model_name #=> String
resp.model_arn #=> String
resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    The name of the model to add the retraining scheduler to.

  • :retraining_start_date (Time, DateTime, Date, Integer, String) —

    The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day.

  • :retraining_frequency (required, String) —

    This parameter uses the [ISO 8601] standard to set the frequency at which you want retraining to occur in terms of Years, Months, and/or Days (note: other parameters like Time are not currently supported). The minimum value is 30 days (P30D) and the maximum value is 1 year (P1Y). For example, the following values are valid:

    • P3M15D – Every 3 months and 15 days

    • P2M – Every 2 months

    • P150D – Every 150 days

    [1]: en.wikipedia.org/wiki/ISO_8601#Durations

  • :lookback_window (required, String) —

    The number of past days of data that will be used for retraining.

  • :promote_mode (String) —

    Indicates how the service will use new models. In ‘MANAGED` mode, new models will automatically be used for inference if they have better performance than the current model. In `MANUAL` mode, the new models will not be used [until they are manually activated].

    [1]: docs.aws.amazon.com/lookout-for-equipment/latest/ug/versioning-model.html#model-activation

  • :client_token (required, String) —

    A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

    **A suitable default value is auto-generated.** You should normally not need to pass this option.**

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1039

def create_retraining_scheduler(params = {}, options = {})
  req = build_request(:create_retraining_scheduler, params)
  req.send_request(options)
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.

Examples:

Request syntax with placeholder values


resp = client.delete_dataset({
  dataset_name: "DatasetIdentifier", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :dataset_name (required, String) —

    The name of the dataset to be deleted.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1066

def delete_dataset(params = {}, options = {})
  req = build_request(:delete_dataset, params)
  req.send_request(options)
end

#delete_inference_scheduler(params = {}) ⇒ Struct

Deletes an inference scheduler that has been set up. Prior inference results will not be deleted.

Examples:

Request syntax with placeholder values


resp = client.delete_inference_scheduler({
  inference_scheduler_name: "InferenceSchedulerIdentifier", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :inference_scheduler_name (required, String) —

    The name of the inference scheduler to be deleted.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1089

def delete_inference_scheduler(params = {}, options = {})
  req = build_request(:delete_inference_scheduler, params)
  req.send_request(options)
end

#delete_label(params = {}) ⇒ Struct

Deletes a label.

Examples:

Request syntax with placeholder values


resp = client.delete_label({
  label_group_name: "LabelGroupName", # required
  label_id: "LabelId", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :label_group_name (required, String) —

    The name of the label group that contains the label that you want to delete. Data in this field will be retained for service usage. Follow best practices for the security of your data.

  • :label_id (required, String) —

    The ID of the label that you want to delete.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1117

def delete_label(params = {}, options = {})
  req = build_request(:delete_label, params)
  req.send_request(options)
end

#delete_label_group(params = {}) ⇒ Struct

Deletes a group of labels.

Examples:

Request syntax with placeholder values


resp = client.delete_label_group({
  label_group_name: "LabelGroupName", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :label_group_name (required, String) —

    The name of the label group that you want to delete. Data in this field will be retained for service usage. Follow best practices for the security of your data.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1141

def delete_label_group(params = {}, options = {})
  req = build_request(:delete_label_group, params)
  req.send_request(options)
end

#delete_model(params = {}) ⇒ Struct

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.

Examples:

Request syntax with placeholder values


resp = client.delete_model({
  model_name: "ModelName", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    The name of the machine learning model to be deleted.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1165

def delete_model(params = {}, options = {})
  req = build_request(:delete_model, params)
  req.send_request(options)
end

#delete_resource_policy(params = {}) ⇒ Struct

Deletes the resource policy attached to the resource.

Examples:

Request syntax with placeholder values


resp = client.delete_resource_policy({
  resource_arn: "ResourceArn", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    The Amazon Resource Name (ARN) of the resource for which the resource policy should be deleted.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1188

def delete_resource_policy(params = {}, options = {})
  req = build_request(:delete_resource_policy, params)
  req.send_request(options)
end

#delete_retraining_scheduler(params = {}) ⇒ Struct

Deletes a retraining scheduler from a model. The retraining scheduler must be in the ‘STOPPED` status.

Examples:

Example: Deletes a retraining scheduler


resp = client.delete_retraining_scheduler({
  model_name: "sample-model", 
})

Request syntax with placeholder values


resp = client.delete_retraining_scheduler({
  model_name: "ModelName", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    The name of the model whose retraining scheduler you want to delete.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1218

def delete_retraining_scheduler(params = {}, options = {})
  req = build_request(:delete_retraining_scheduler, params)
  req.send_request(options)
end

#describe_data_ingestion_job(params = {}) ⇒ Types::DescribeDataIngestionJobResponse

Provides information on a specific data ingestion job such as creation time, dataset ARN, and status.

Examples:

Request syntax with placeholder values


resp = client.describe_data_ingestion_job({
  job_id: "IngestionJobId", # required
})

Response structure


resp.job_id #=> String
resp.dataset_arn #=> String
resp.ingestion_input_configuration.s3_input_configuration.bucket #=> String
resp.ingestion_input_configuration.s3_input_configuration.prefix #=> String
resp.ingestion_input_configuration.s3_input_configuration.key_pattern #=> String
resp.role_arn #=> String
resp.created_at #=> Time
resp.status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS"
resp.failed_reason #=> String
resp.data_quality_summary.insufficient_sensor_data.missing_complete_sensor_data.affected_sensor_count #=> Integer
resp.data_quality_summary.insufficient_sensor_data.sensors_with_short_date_range.affected_sensor_count #=> Integer
resp.data_quality_summary.missing_sensor_data.affected_sensor_count #=> Integer
resp.data_quality_summary.missing_sensor_data.total_number_of_missing_values #=> Integer
resp.data_quality_summary.invalid_sensor_data.affected_sensor_count #=> Integer
resp.data_quality_summary.invalid_sensor_data.total_number_of_invalid_values #=> Integer
resp.data_quality_summary.unsupported_timestamps.total_number_of_unsupported_timestamps #=> Integer
resp.data_quality_summary.duplicate_timestamps.total_number_of_duplicate_timestamps #=> Integer
resp.ingested_files_summary.total_number_of_files #=> Integer
resp.ingested_files_summary.ingested_number_of_files #=> Integer
resp.ingested_files_summary.discarded_files #=> Array
resp.ingested_files_summary.discarded_files[0].bucket #=> String
resp.ingested_files_summary.discarded_files[0].key #=> String
resp.status_detail #=> String
resp.ingested_data_size #=> Integer
resp.data_start_time #=> Time
resp.data_end_time #=> Time
resp.source_dataset_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :job_id (required, String) —

    The job ID of the data ingestion job.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1286

def describe_data_ingestion_job(params = {}, options = {})
  req = build_request(:describe_data_ingestion_job, params)
  req.send_request(options)
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.

Examples:

Request syntax with placeholder values


resp = client.describe_dataset({
  dataset_name: "DatasetIdentifier", # required
})

Response structure


resp.dataset_name #=> String
resp.dataset_arn #=> String
resp.created_at #=> Time
resp.last_updated_at #=> Time
resp.status #=> String, one of "CREATED", "INGESTION_IN_PROGRESS", "ACTIVE", "IMPORT_IN_PROGRESS"
resp.schema #=> String
resp.server_side_kms_key_id #=> String
resp.ingestion_input_configuration.s3_input_configuration.bucket #=> String
resp.ingestion_input_configuration.s3_input_configuration.prefix #=> String
resp.ingestion_input_configuration.s3_input_configuration.key_pattern #=> String
resp.data_quality_summary.insufficient_sensor_data.missing_complete_sensor_data.affected_sensor_count #=> Integer
resp.data_quality_summary.insufficient_sensor_data.sensors_with_short_date_range.affected_sensor_count #=> Integer
resp.data_quality_summary.missing_sensor_data.affected_sensor_count #=> Integer
resp.data_quality_summary.missing_sensor_data.total_number_of_missing_values #=> Integer
resp.data_quality_summary.invalid_sensor_data.affected_sensor_count #=> Integer
resp.data_quality_summary.invalid_sensor_data.total_number_of_invalid_values #=> Integer
resp.data_quality_summary.unsupported_timestamps.total_number_of_unsupported_timestamps #=> Integer
resp.data_quality_summary.duplicate_timestamps.total_number_of_duplicate_timestamps #=> Integer
resp.ingested_files_summary.total_number_of_files #=> Integer
resp.ingested_files_summary.ingested_number_of_files #=> Integer
resp.ingested_files_summary.discarded_files #=> Array
resp.ingested_files_summary.discarded_files[0].bucket #=> String
resp.ingested_files_summary.discarded_files[0].key #=> String
resp.role_arn #=> String
resp.data_start_time #=> Time
resp.data_end_time #=> Time
resp.source_dataset_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :dataset_name (required, String) —

    The name of the dataset to be described.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1354

def describe_dataset(params = {}, options = {})
  req = build_request(:describe_dataset, params)
  req.send_request(options)
end

#describe_inference_scheduler(params = {}) ⇒ Types::DescribeInferenceSchedulerResponse

Specifies information about the inference scheduler being used, including name, model, status, and associated metadata

Examples:

Request syntax with placeholder values


resp = client.describe_inference_scheduler({
  inference_scheduler_name: "InferenceSchedulerIdentifier", # required
})

Response structure


resp.model_arn #=> String
resp.model_name #=> String
resp.inference_scheduler_name #=> String
resp.inference_scheduler_arn #=> String
resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
resp.data_delay_offset_in_minutes #=> Integer
resp.data_upload_frequency #=> String, one of "PT5M", "PT10M", "PT15M", "PT30M", "PT1H"
resp.created_at #=> Time
resp.updated_at #=> Time
resp.data_input_configuration.s3_input_configuration.bucket #=> String
resp.data_input_configuration.s3_input_configuration.prefix #=> String
resp.data_input_configuration.input_time_zone_offset #=> String
resp.data_input_configuration.inference_input_name_configuration.timestamp_format #=> String
resp.data_input_configuration.inference_input_name_configuration.component_timestamp_delimiter #=> String
resp.data_output_configuration.s3_output_configuration.bucket #=> String
resp.data_output_configuration.s3_output_configuration.prefix #=> String
resp.data_output_configuration.kms_key_id #=> String
resp.role_arn #=> String
resp.server_side_kms_key_id #=> String
resp.latest_inference_result #=> String, one of "ANOMALOUS", "NORMAL"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :inference_scheduler_name (required, String) —

    The name of the inference scheduler being described.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1415

def describe_inference_scheduler(params = {}, options = {})
  req = build_request(:describe_inference_scheduler, params)
  req.send_request(options)
end

#describe_label(params = {}) ⇒ Types::DescribeLabelResponse

Returns the name of the label.

Examples:

Request syntax with placeholder values


resp = client.describe_label({
  label_group_name: "LabelGroupName", # required
  label_id: "LabelId", # required
})

Response structure


resp.label_group_name #=> String
resp.label_group_arn #=> String
resp.label_id #=> String
resp.start_time #=> Time
resp.end_time #=> Time
resp.rating #=> String, one of "ANOMALY", "NO_ANOMALY", "NEUTRAL"
resp.fault_code #=> String
resp.notes #=> String
resp.equipment #=> String
resp.created_at #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :label_group_name (required, String) —

    Returns the name of the group containing the label.

  • :label_id (required, String) —

    Returns the ID of the label.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1465

def describe_label(params = {}, options = {})
  req = build_request(:describe_label, params)
  req.send_request(options)
end

#describe_label_group(params = {}) ⇒ Types::DescribeLabelGroupResponse

Returns information about the label group.

Examples:

Request syntax with placeholder values


resp = client.describe_label_group({
  label_group_name: "LabelGroupName", # required
})

Response structure


resp.label_group_name #=> String
resp.label_group_arn #=> String
resp.fault_codes #=> Array
resp.fault_codes[0] #=> String
resp.created_at #=> Time
resp.updated_at #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :label_group_name (required, String) —

    Returns the name of the label group.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1502

def describe_label_group(params = {}, options = {})
  req = build_request(:describe_label_group, params)
  req.send_request(options)
end

#describe_model(params = {}) ⇒ Types::DescribeModelResponse

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.

Examples:

Request syntax with placeholder values


resp = client.describe_model({
  model_name: "ModelName", # required
})

Response structure


resp.model_name #=> String
resp.model_arn #=> String
resp.dataset_name #=> String
resp.dataset_arn #=> String
resp.schema #=> String
resp.labels_input_configuration.s3_input_configuration.bucket #=> String
resp.labels_input_configuration.s3_input_configuration.prefix #=> String
resp.labels_input_configuration.label_group_name #=> String
resp.training_data_start_time #=> Time
resp.training_data_end_time #=> Time
resp.evaluation_data_start_time #=> Time
resp.evaluation_data_end_time #=> Time
resp.role_arn #=> String
resp.data_pre_processing_configuration.target_sampling_rate #=> String, one of "PT1S", "PT5S", "PT10S", "PT15S", "PT30S", "PT1M", "PT5M", "PT10M", "PT15M", "PT30M", "PT1H"
resp.status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS"
resp.training_execution_start_time #=> Time
resp.training_execution_end_time #=> Time
resp.failed_reason #=> String
resp.model_metrics #=> String
resp.last_updated_time #=> Time
resp.created_at #=> Time
resp.server_side_kms_key_id #=> String
resp.off_condition #=> String
resp.source_model_version_arn #=> String
resp.import_job_start_time #=> Time
resp.import_job_end_time #=> Time
resp.active_model_version #=> Integer
resp.active_model_version_arn #=> String
resp.model_version_activated_at #=> Time
resp.previous_active_model_version #=> Integer
resp.previous_active_model_version_arn #=> String
resp.previous_model_version_activated_at #=> Time
resp.prior_model_metrics #=> String
resp.latest_scheduled_retraining_failed_reason #=> String
resp.latest_scheduled_retraining_status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS", "CANCELED"
resp.latest_scheduled_retraining_model_version #=> Integer
resp.latest_scheduled_retraining_start_time #=> Time
resp.latest_scheduled_retraining_available_data_in_days #=> Integer
resp.next_scheduled_retraining_start_date #=> Time
resp.accumulated_inference_data_start_time #=> Time
resp.accumulated_inference_data_end_time #=> Time
resp.retraining_scheduler_status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
resp.model_diagnostics_output_configuration.s3_output_configuration.bucket #=> String
resp.model_diagnostics_output_configuration.s3_output_configuration.prefix #=> String
resp.model_diagnostics_output_configuration.kms_key_id #=> String
resp.model_quality #=> String, one of "QUALITY_THRESHOLD_MET", "CANNOT_DETERMINE_QUALITY", "POOR_QUALITY_DETECTED"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    The name of the machine learning model to be described.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1618

def describe_model(params = {}, options = {})
  req = build_request(:describe_model, params)
  req.send_request(options)
end

#describe_model_version(params = {}) ⇒ Types::DescribeModelVersionResponse

Retrieves information about a specific machine learning model version.

Examples:

Request syntax with placeholder values


resp = client.describe_model_version({
  model_name: "ModelName", # required
  model_version: 1, # required
})

Response structure


resp.model_name #=> String
resp.model_arn #=> String
resp.model_version #=> Integer
resp.model_version_arn #=> String
resp.status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS", "CANCELED"
resp.source_type #=> String, one of "TRAINING", "RETRAINING", "IMPORT"
resp.dataset_name #=> String
resp.dataset_arn #=> String
resp.schema #=> String
resp.labels_input_configuration.s3_input_configuration.bucket #=> String
resp.labels_input_configuration.s3_input_configuration.prefix #=> String
resp.labels_input_configuration.label_group_name #=> String
resp.training_data_start_time #=> Time
resp.training_data_end_time #=> Time
resp.evaluation_data_start_time #=> Time
resp.evaluation_data_end_time #=> Time
resp.role_arn #=> String
resp.data_pre_processing_configuration.target_sampling_rate #=> String, one of "PT1S", "PT5S", "PT10S", "PT15S", "PT30S", "PT1M", "PT5M", "PT10M", "PT15M", "PT30M", "PT1H"
resp.training_execution_start_time #=> Time
resp.training_execution_end_time #=> Time
resp.failed_reason #=> String
resp.model_metrics #=> String
resp.last_updated_time #=> Time
resp.created_at #=> Time
resp.server_side_kms_key_id #=> String
resp.off_condition #=> String
resp.source_model_version_arn #=> String
resp.import_job_start_time #=> Time
resp.import_job_end_time #=> Time
resp.imported_data_size_in_bytes #=> Integer
resp.prior_model_metrics #=> String
resp.retraining_available_data_in_days #=> Integer
resp.auto_promotion_result #=> String, one of "MODEL_PROMOTED", "MODEL_NOT_PROMOTED", "RETRAINING_INTERNAL_ERROR", "RETRAINING_CUSTOMER_ERROR", "RETRAINING_CANCELLED"
resp.auto_promotion_result_reason #=> String
resp.model_diagnostics_output_configuration.s3_output_configuration.bucket #=> String
resp.model_diagnostics_output_configuration.s3_output_configuration.prefix #=> String
resp.model_diagnostics_output_configuration.kms_key_id #=> String
resp.model_diagnostics_results_object.bucket #=> String
resp.model_diagnostics_results_object.key #=> String
resp.model_quality #=> String, one of "QUALITY_THRESHOLD_MET", "CANNOT_DETERMINE_QUALITY", "POOR_QUALITY_DETECTED"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    The name of the machine learning model that this version belongs to.

  • :model_version (required, Integer) —

    The version of the machine learning model.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1723

def describe_model_version(params = {}, options = {})
  req = build_request(:describe_model_version, params)
  req.send_request(options)
end

#describe_resource_policy(params = {}) ⇒ Types::DescribeResourcePolicyResponse

Provides the details of a resource policy attached to a resource.

Examples:

Request syntax with placeholder values


resp = client.describe_resource_policy({
  resource_arn: "ResourceArn", # required
})

Response structure


resp.policy_revision_id #=> String
resp.resource_policy #=> String
resp.creation_time #=> Time
resp.last_modified_time #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    The Amazon Resource Name (ARN) of the resource that is associated with the resource policy.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1758

def describe_resource_policy(params = {}, options = {})
  req = build_request(:describe_resource_policy, params)
  req.send_request(options)
end

#describe_retraining_scheduler(params = {}) ⇒ Types::DescribeRetrainingSchedulerResponse

Provides a description of the retraining scheduler, including information such as the model name and retraining parameters.

Examples:

Example: Describes a retraining scheduler


resp = client.describe_retraining_scheduler({
  model_name: "sample-model", 
})

resp.to_h outputs the following:
{
  created_at: Time.parse("2023-10-01T15:00:00Z"), 
  lookback_window: "P360D", 
  model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", 
  model_name: "sample-model", 
  promote_mode: "MANAGED", 
  retraining_frequency: "P1M", 
  retraining_start_date: Time.parse("2023-11-01T00:00:00Z"), 
  status: "RUNNING", 
  updated_at: Time.parse("2023-10-01T15:00:00Z"), 
}

Request syntax with placeholder values


resp = client.describe_retraining_scheduler({
  model_name: "ModelName", # required
})

Response structure


resp.model_name #=> String
resp.model_arn #=> String
resp.retraining_start_date #=> Time
resp.retraining_frequency #=> String
resp.lookback_window #=> String
resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
resp.promote_mode #=> String, one of "MANAGED", "MANUAL"
resp.created_at #=> Time
resp.updated_at #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    The name of the model that the retraining scheduler is attached to.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1823

def describe_retraining_scheduler(params = {}, options = {})
  req = build_request(:describe_retraining_scheduler, params)
  req.send_request(options)
end

#import_dataset(params = {}) ⇒ Types::ImportDatasetResponse

Imports a dataset.

Examples:

Request syntax with placeholder values


resp = client.import_dataset({
  source_dataset_arn: "DatasetArn", # required
  dataset_name: "DatasetName",
  client_token: "IdempotenceToken", # required
  server_side_kms_key_id: "NameOrArn",
  tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
})

Response structure


resp.dataset_name #=> String
resp.dataset_arn #=> String
resp.status #=> String, one of "CREATED", "INGESTION_IN_PROGRESS", "ACTIVE", "IMPORT_IN_PROGRESS"
resp.job_id #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :source_dataset_arn (required, String) —

    The Amazon Resource Name (ARN) of the dataset to import.

  • :dataset_name (String) —

    The name of the machine learning dataset to be created. If the dataset already exists, Amazon Lookout for Equipment overwrites the existing dataset. If you don’t specify this field, it is filled with the name of the source dataset.

  • :client_token (required, String) —

    A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

    **A suitable default value is auto-generated.** You should normally not need to pass this option.**

  • :server_side_kms_key_id (String) —

    Provides the identifier of the KMS key key used to encrypt model data by Amazon Lookout for Equipment.

  • :tags (Array<Types::Tag>) —

    Any tags associated with the dataset to be created.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1886

def import_dataset(params = {}, options = {})
  req = build_request(:import_dataset, params)
  req.send_request(options)
end

#import_model_version(params = {}) ⇒ Types::ImportModelVersionResponse

Imports a model that has been trained successfully.

Examples:

Request syntax with placeholder values


resp = client.import_model_version({
  source_model_version_arn: "ModelVersionArn", # required
  model_name: "ModelName",
  dataset_name: "DatasetIdentifier", # required
  labels_input_configuration: {
    s3_input_configuration: {
      bucket: "S3Bucket", # required
      prefix: "S3Prefix",
    },
    label_group_name: "LabelGroupName",
  },
  client_token: "IdempotenceToken", # required
  role_arn: "IamRoleArn",
  server_side_kms_key_id: "NameOrArn",
  tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
  inference_data_import_strategy: "NO_IMPORT", # accepts NO_IMPORT, ADD_WHEN_EMPTY, OVERWRITE
})

Response structure


resp.model_name #=> String
resp.model_arn #=> String
resp.model_version_arn #=> String
resp.model_version #=> Integer
resp.status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS", "CANCELED"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :source_model_version_arn (required, String) —

    The Amazon Resource Name (ARN) of the model version to import.

  • :model_name (String) —

    The name for the machine learning model to be created. If the model already exists, Amazon Lookout for Equipment creates a new version. If you do not specify this field, it is filled with the name of the source model.

  • :dataset_name (required, String) —

    The name of the dataset for the machine learning model being imported.

  • :labels_input_configuration (Types::LabelsInputConfiguration) —

    Contains the configuration information for the S3 location being used to hold label data.

  • :client_token (required, String) —

    A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

    **A suitable default value is auto-generated.** You should normally not need to pass this option.**

  • :role_arn (String) —

    The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the machine learning model.

  • :server_side_kms_key_id (String) —

    Provides the identifier of the KMS key key used to encrypt model data by Amazon Lookout for Equipment.

  • :tags (Array<Types::Tag>) —

    The tags associated with the machine learning model to be created.

  • :inference_data_import_strategy (String) —

    Indicates how to import the accumulated inference data when a model version is imported. The possible values are as follows:

    • NO_IMPORT – Don’t import the data.

    • ADD_WHEN_EMPTY – Only import the data from the source model if there is no existing data in the target model.

    • OVERWRITE – Import the data from the source model and overwrite the existing data in the target model.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 1984

def import_model_version(params = {}, options = {})
  req = build_request(:import_model_version, params)
  req.send_request(options)
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.

Examples:

Request syntax with placeholder values


resp = client.list_data_ingestion_jobs({
  dataset_name: "DatasetName",
  next_token: "NextToken",
  max_results: 1,
  status: "IN_PROGRESS", # accepts IN_PROGRESS, SUCCESS, FAILED, IMPORT_IN_PROGRESS
})

Response structure


resp.next_token #=> String
resp.data_ingestion_job_summaries #=> Array
resp.data_ingestion_job_summaries[0].job_id #=> String
resp.data_ingestion_job_summaries[0].dataset_name #=> String
resp.data_ingestion_job_summaries[0].dataset_arn #=> String
resp.data_ingestion_job_summaries[0].ingestion_input_configuration.s3_input_configuration.bucket #=> String
resp.data_ingestion_job_summaries[0].ingestion_input_configuration.s3_input_configuration.prefix #=> String
resp.data_ingestion_job_summaries[0].ingestion_input_configuration.s3_input_configuration.key_pattern #=> String
resp.data_ingestion_job_summaries[0].status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :dataset_name (String) —

    The name of the dataset being used for the data ingestion job.

  • :next_token (String) —

    An opaque pagination token indicating where to continue the listing of data ingestion jobs.

  • :max_results (Integer) —

    Specifies the maximum number of data ingestion jobs to list.

  • :status (String) —

    Indicates the status of the data ingestion job.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2037

def list_data_ingestion_jobs(params = {}, options = {})
  req = build_request(:list_data_ingestion_jobs, params)
  req.send_request(options)
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.

Examples:

Request syntax with placeholder values


resp = client.list_datasets({
  next_token: "NextToken",
  max_results: 1,
  dataset_name_begins_with: "DatasetName",
})

Response structure


resp.next_token #=> String
resp.dataset_summaries #=> Array
resp.dataset_summaries[0].dataset_name #=> String
resp.dataset_summaries[0].dataset_arn #=> String
resp.dataset_summaries[0].status #=> String, one of "CREATED", "INGESTION_IN_PROGRESS", "ACTIVE", "IMPORT_IN_PROGRESS"
resp.dataset_summaries[0].created_at #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    An opaque pagination token indicating where to continue the listing of datasets.

  • :max_results (Integer) —

    Specifies the maximum number of datasets to list.

  • :dataset_name_begins_with (String) —

    The beginning of the name of the datasets to be listed.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2083

def list_datasets(params = {}, options = {})
  req = build_request(:list_datasets, params)
  req.send_request(options)
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.

Examples:

Request syntax with placeholder values


resp = client.list_inference_events({
  next_token: "NextToken",
  max_results: 1,
  inference_scheduler_name: "InferenceSchedulerIdentifier", # required
  interval_start_time: Time.now, # required
  interval_end_time: Time.now, # required
})

Response structure


resp.next_token #=> String
resp.inference_event_summaries #=> Array
resp.inference_event_summaries[0].inference_scheduler_arn #=> String
resp.inference_event_summaries[0].inference_scheduler_name #=> String
resp.inference_event_summaries[0].event_start_time #=> Time
resp.inference_event_summaries[0].event_end_time #=> Time
resp.inference_event_summaries[0].diagnostics #=> String
resp.inference_event_summaries[0].event_duration_in_seconds #=> Integer

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    An opaque pagination token indicating where to continue the listing of inference events.

  • :max_results (Integer) —

    Specifies the maximum number of inference events to list.

  • :inference_scheduler_name (required, String) —

    The name of the inference scheduler for the inference events listed.

  • :interval_start_time (required, Time, DateTime, Date, Integer, String) —

    Lookout for Equipment will return all the inference events with an end time equal to or greater than the start time given.

  • :interval_end_time (required, Time, DateTime, Date, Integer, String) —

    Returns all the inference events with an end start time equal to or greater than less than the end time given.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2141

def list_inference_events(params = {}, options = {})
  req = build_request(:list_inference_events, params)
  req.send_request(options)
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.

Examples:

Request syntax with placeholder values


resp = client.list_inference_executions({
  next_token: "NextToken",
  max_results: 1,
  inference_scheduler_name: "InferenceSchedulerIdentifier", # required
  data_start_time_after: Time.now,
  data_end_time_before: Time.now,
  status: "IN_PROGRESS", # accepts IN_PROGRESS, SUCCESS, FAILED
})

Response structure


resp.next_token #=> String
resp.inference_execution_summaries #=> Array
resp.inference_execution_summaries[0].model_name #=> String
resp.inference_execution_summaries[0].model_arn #=> String
resp.inference_execution_summaries[0].inference_scheduler_name #=> String
resp.inference_execution_summaries[0].inference_scheduler_arn #=> String
resp.inference_execution_summaries[0].scheduled_start_time #=> Time
resp.inference_execution_summaries[0].data_start_time #=> Time
resp.inference_execution_summaries[0].data_end_time #=> Time
resp.inference_execution_summaries[0].data_input_configuration.s3_input_configuration.bucket #=> String
resp.inference_execution_summaries[0].data_input_configuration.s3_input_configuration.prefix #=> String
resp.inference_execution_summaries[0].data_input_configuration.input_time_zone_offset #=> String
resp.inference_execution_summaries[0].data_input_configuration.inference_input_name_configuration.timestamp_format #=> String
resp.inference_execution_summaries[0].data_input_configuration.inference_input_name_configuration.component_timestamp_delimiter #=> String
resp.inference_execution_summaries[0].data_output_configuration.s3_output_configuration.bucket #=> String
resp.inference_execution_summaries[0].data_output_configuration.s3_output_configuration.prefix #=> String
resp.inference_execution_summaries[0].data_output_configuration.kms_key_id #=> String
resp.inference_execution_summaries[0].customer_result_object.bucket #=> String
resp.inference_execution_summaries[0].customer_result_object.key #=> String
resp.inference_execution_summaries[0].status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED"
resp.inference_execution_summaries[0].failed_reason #=> String
resp.inference_execution_summaries[0].model_version #=> Integer
resp.inference_execution_summaries[0].model_version_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    An opaque pagination token indicating where to continue the listing of inference executions.

  • :max_results (Integer) —

    Specifies the maximum number of inference executions to list.

  • :inference_scheduler_name (required, String) —

    The name of the inference scheduler for the inference execution listed.

  • :data_start_time_after (Time, DateTime, Date, Integer, String) —

    The time reference in the inferenced dataset after which Amazon Lookout for Equipment started the inference execution.

  • :data_end_time_before (Time, DateTime, Date, Integer, String) —

    The time reference in the inferenced dataset before which Amazon Lookout for Equipment stopped the inference execution.

  • :status (String) —

    The status of the inference execution.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2219

def list_inference_executions(params = {}, options = {})
  req = build_request(:list_inference_executions, params)
  req.send_request(options)
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.

Examples:

Request syntax with placeholder values


resp = client.list_inference_schedulers({
  next_token: "NextToken",
  max_results: 1,
  inference_scheduler_name_begins_with: "InferenceSchedulerIdentifier",
  model_name: "ModelName",
  status: "PENDING", # accepts PENDING, RUNNING, STOPPING, STOPPED
})

Response structure


resp.next_token #=> String
resp.inference_scheduler_summaries #=> Array
resp.inference_scheduler_summaries[0].model_name #=> String
resp.inference_scheduler_summaries[0].model_arn #=> String
resp.inference_scheduler_summaries[0].inference_scheduler_name #=> String
resp.inference_scheduler_summaries[0].inference_scheduler_arn #=> String
resp.inference_scheduler_summaries[0].status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
resp.inference_scheduler_summaries[0].data_delay_offset_in_minutes #=> Integer
resp.inference_scheduler_summaries[0].data_upload_frequency #=> String, one of "PT5M", "PT10M", "PT15M", "PT30M", "PT1H"
resp.inference_scheduler_summaries[0].latest_inference_result #=> String, one of "ANOMALOUS", "NORMAL"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    An opaque pagination token indicating where to continue the listing of inference schedulers.

  • :max_results (Integer) —

    Specifies the maximum number of inference schedulers to list.

  • :inference_scheduler_name_begins_with (String) —

    The beginning of the name of the inference schedulers to be listed.

  • :model_name (String) —

    The name of the machine learning model used by the inference scheduler to be listed.

  • :status (String) —

    Specifies the current status of the inference schedulers.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2278

def list_inference_schedulers(params = {}, options = {})
  req = build_request(:list_inference_schedulers, params)
  req.send_request(options)
end

#list_label_groups(params = {}) ⇒ Types::ListLabelGroupsResponse

Returns a list of the label groups.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_label_groups({
  label_group_name_begins_with: "LabelGroupName",
  next_token: "NextToken",
  max_results: 1,
})

Response structure


resp.next_token #=> String
resp.label_group_summaries #=> Array
resp.label_group_summaries[0].label_group_name #=> String
resp.label_group_summaries[0].label_group_arn #=> String
resp.label_group_summaries[0].created_at #=> Time
resp.label_group_summaries[0].updated_at #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :label_group_name_begins_with (String) —

    The beginning of the name of the label groups to be listed.

  • :next_token (String) —

    An opaque pagination token indicating where to continue the listing of label groups.

  • :max_results (Integer) —

    Specifies the maximum number of label groups to list.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2323

def list_label_groups(params = {}, options = {})
  req = build_request(:list_label_groups, params)
  req.send_request(options)
end

#list_labels(params = {}) ⇒ Types::ListLabelsResponse

Provides a list of labels.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_labels({
  label_group_name: "LabelGroupName", # required
  interval_start_time: Time.now,
  interval_end_time: Time.now,
  fault_code: "FaultCode",
  equipment: "Equipment",
  next_token: "NextToken",
  max_results: 1,
})

Response structure


resp.next_token #=> String
resp.label_summaries #=> Array
resp.label_summaries[0].label_group_name #=> String
resp.label_summaries[0].label_id #=> String
resp.label_summaries[0].label_group_arn #=> String
resp.label_summaries[0].start_time #=> Time
resp.label_summaries[0].end_time #=> Time
resp.label_summaries[0].rating #=> String, one of "ANOMALY", "NO_ANOMALY", "NEUTRAL"
resp.label_summaries[0].fault_code #=> String
resp.label_summaries[0].equipment #=> String
resp.label_summaries[0].created_at #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :label_group_name (required, String) —

    Returns the name of the label group.

  • :interval_start_time (Time, DateTime, Date, Integer, String) —

    Returns all the labels with a end time equal to or later than the start time given.

  • :interval_end_time (Time, DateTime, Date, Integer, String) —

    Returns all labels with a start time earlier than the end time given.

  • :fault_code (String) —

    Returns labels with a particular fault code.

  • :equipment (String) —

    Lists the labels that pertain to a particular piece of equipment.

  • :next_token (String) —

    An opaque pagination token indicating where to continue the listing of label groups.

  • :max_results (Integer) —

    Specifies the maximum number of labels to list.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2390

def list_labels(params = {}, options = {})
  req = build_request(:list_labels, params)
  req.send_request(options)
end

#list_model_versions(params = {}) ⇒ Types::ListModelVersionsResponse

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.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_model_versions({
  model_name: "ModelName", # required
  next_token: "NextToken",
  max_results: 1,
  status: "IN_PROGRESS", # accepts IN_PROGRESS, SUCCESS, FAILED, IMPORT_IN_PROGRESS, CANCELED
  source_type: "TRAINING", # accepts TRAINING, RETRAINING, IMPORT
  created_at_end_time: Time.now,
  created_at_start_time: Time.now,
  max_model_version: 1,
  min_model_version: 1,
})

Response structure


resp.next_token #=> String
resp.model_version_summaries #=> Array
resp.model_version_summaries[0].model_name #=> String
resp.model_version_summaries[0].model_arn #=> String
resp.model_version_summaries[0].model_version #=> Integer
resp.model_version_summaries[0].model_version_arn #=> String
resp.model_version_summaries[0].created_at #=> Time
resp.model_version_summaries[0].status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS", "CANCELED"
resp.model_version_summaries[0].source_type #=> String, one of "TRAINING", "RETRAINING", "IMPORT"
resp.model_version_summaries[0].model_quality #=> String, one of "QUALITY_THRESHOLD_MET", "CANNOT_DETERMINE_QUALITY", "POOR_QUALITY_DETECTED"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    Then name of the machine learning model for which the model versions are to be listed.

  • :next_token (String) —

    If the total number of results exceeds the limit that the response can display, the response returns an opaque pagination token indicating where to continue the listing of machine learning model versions. Use this token in the ‘NextToken` field in the request to list the next page of results.

  • :max_results (Integer) —

    Specifies the maximum number of machine learning model versions to list.

  • :status (String) —

    Filter the results based on the current status of the model version.

  • :source_type (String) —

    Filter the results based on the way the model version was generated.

  • :created_at_end_time (Time, DateTime, Date, Integer, String) —

    Filter results to return all the model versions created before this time.

  • :created_at_start_time (Time, DateTime, Date, Integer, String) —

    Filter results to return all the model versions created after this time.

  • :max_model_version (Integer) —

    Specifies the highest version of the model to return in the list.

  • :min_model_version (Integer) —

    Specifies the lowest version of the model to return in the list.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2472

def list_model_versions(params = {}, options = {})
  req = build_request(:list_model_versions, params)
  req.send_request(options)
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.

Examples:

Request syntax with placeholder values


resp = client.list_models({
  next_token: "NextToken",
  max_results: 1,
  status: "IN_PROGRESS", # accepts IN_PROGRESS, SUCCESS, FAILED, IMPORT_IN_PROGRESS
  model_name_begins_with: "ModelName",
  dataset_name_begins_with: "DatasetName",
})

Response structure


resp.next_token #=> String
resp.model_summaries #=> Array
resp.model_summaries[0].model_name #=> String
resp.model_summaries[0].model_arn #=> String
resp.model_summaries[0].dataset_name #=> String
resp.model_summaries[0].dataset_arn #=> String
resp.model_summaries[0].status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS"
resp.model_summaries[0].created_at #=> Time
resp.model_summaries[0].active_model_version #=> Integer
resp.model_summaries[0].active_model_version_arn #=> String
resp.model_summaries[0].latest_scheduled_retraining_status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS", "CANCELED"
resp.model_summaries[0].latest_scheduled_retraining_model_version #=> Integer
resp.model_summaries[0].latest_scheduled_retraining_start_time #=> Time
resp.model_summaries[0].next_scheduled_retraining_start_date #=> Time
resp.model_summaries[0].retraining_scheduler_status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
resp.model_summaries[0].model_diagnostics_output_configuration.s3_output_configuration.bucket #=> String
resp.model_summaries[0].model_diagnostics_output_configuration.s3_output_configuration.prefix #=> String
resp.model_summaries[0].model_diagnostics_output_configuration.kms_key_id #=> String
resp.model_summaries[0].model_quality #=> String, one of "QUALITY_THRESHOLD_MET", "CANNOT_DETERMINE_QUALITY", "POOR_QUALITY_DETECTED"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    An opaque pagination token indicating where to continue the listing of machine learning models.

  • :max_results (Integer) —

    Specifies the maximum number of machine learning models to list.

  • :status (String) —

    The status of the machine learning model.

  • :model_name_begins_with (String) —

    The beginning of the name of the machine learning models being listed.

  • :dataset_name_begins_with (String) —

    The beginning of the name of the dataset of the machine learning models to be listed.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2540

def list_models(params = {}, options = {})
  req = build_request(:list_models, params)
  req.send_request(options)
end

#list_retraining_schedulers(params = {}) ⇒ Types::ListRetrainingSchedulersResponse

Lists all retraining schedulers in your account, filtering by model name prefix and status.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Example: Listing retraining schedulers


resp = client.list_retraining_schedulers({
  max_results: 50, 
})

resp.to_h outputs the following:
{
  retraining_scheduler_summaries: [
    {
      lookback_window: "P180D", 
      model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model-1/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", 
      model_name: "sample-model-1", 
      retraining_frequency: "P1M", 
      retraining_start_date: Time.parse("2023-06-01T00:00:00Z"), 
      status: "RUNNING", 
    }, 
    {
      lookback_window: "P180D", 
      model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model-2/a1b2c3d4-5678-90ab-cdef-EXAMPLE22222", 
      model_name: "sample-model-2", 
      retraining_frequency: "P30D", 
      retraining_start_date: Time.parse("2023-08-15T00:00:00Z"), 
      status: "RUNNING", 
    }, 
    {
      lookback_window: "P360D", 
      model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model-3/a1b2c3d4-5678-90ab-cdef-EXAMPLE33333", 
      model_name: "sample-model-3", 
      retraining_frequency: "P1M", 
      retraining_start_date: Time.parse("2023-09-01T00:00:00Z"), 
      status: "STOPPED", 
    }, 
  ], 
}

Request syntax with placeholder values


resp = client.list_retraining_schedulers({
  model_name_begins_with: "ModelName",
  status: "PENDING", # accepts PENDING, RUNNING, STOPPING, STOPPED
  next_token: "NextToken",
  max_results: 1,
})

Response structure


resp.retraining_scheduler_summaries #=> Array
resp.retraining_scheduler_summaries[0].model_name #=> String
resp.retraining_scheduler_summaries[0].model_arn #=> String
resp.retraining_scheduler_summaries[0].status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
resp.retraining_scheduler_summaries[0].retraining_start_date #=> Time
resp.retraining_scheduler_summaries[0].retraining_frequency #=> String
resp.retraining_scheduler_summaries[0].lookback_window #=> String
resp.next_token #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name_begins_with (String) —

    Specify this field to only list retraining schedulers whose machine learning models begin with the value you specify.

  • :status (String) —

    Specify this field to only list retraining schedulers whose status matches the value you specify.

  • :next_token (String) —

    If the number of results exceeds the maximum, a pagination token is returned. Use the token in the request to show the next page of retraining schedulers.

  • :max_results (Integer) —

    Specifies the maximum number of retraining schedulers to list.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2632

def list_retraining_schedulers(params = {}, options = {})
  req = build_request(:list_retraining_schedulers, params)
  req.send_request(options)
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.

Examples:

Request syntax with placeholder values


resp = client.list_sensor_statistics({
  dataset_name: "DatasetName", # required
  ingestion_job_id: "IngestionJobId",
  max_results: 1,
  next_token: "NextToken",
})

Response structure


resp.sensor_statistics_summaries #=> Array
resp.sensor_statistics_summaries[0].component_name #=> String
resp.sensor_statistics_summaries[0].sensor_name #=> String
resp.sensor_statistics_summaries[0].data_exists #=> Boolean
resp.sensor_statistics_summaries[0].missing_values.count #=> Integer
resp.sensor_statistics_summaries[0].missing_values.percentage #=> Float
resp.sensor_statistics_summaries[0].invalid_values.count #=> Integer
resp.sensor_statistics_summaries[0].invalid_values.percentage #=> Float
resp.sensor_statistics_summaries[0].invalid_date_entries.count #=> Integer
resp.sensor_statistics_summaries[0].invalid_date_entries.percentage #=> Float
resp.sensor_statistics_summaries[0].duplicate_timestamps.count #=> Integer
resp.sensor_statistics_summaries[0].duplicate_timestamps.percentage #=> Float
resp.sensor_statistics_summaries[0].categorical_values.status #=> String, one of "POTENTIAL_ISSUE_DETECTED", "NO_ISSUE_DETECTED"
resp.sensor_statistics_summaries[0].categorical_values.number_of_category #=> Integer
resp.sensor_statistics_summaries[0].multiple_operating_modes.status #=> String, one of "POTENTIAL_ISSUE_DETECTED", "NO_ISSUE_DETECTED"
resp.sensor_statistics_summaries[0].large_timestamp_gaps.status #=> String, one of "POTENTIAL_ISSUE_DETECTED", "NO_ISSUE_DETECTED"
resp.sensor_statistics_summaries[0].large_timestamp_gaps.number_of_large_timestamp_gaps #=> Integer
resp.sensor_statistics_summaries[0].large_timestamp_gaps.max_timestamp_gap_in_days #=> Integer
resp.sensor_statistics_summaries[0].monotonic_values.status #=> String, one of "POTENTIAL_ISSUE_DETECTED", "NO_ISSUE_DETECTED"
resp.sensor_statistics_summaries[0].monotonic_values.monotonicity #=> String, one of "DECREASING", "INCREASING", "STATIC"
resp.sensor_statistics_summaries[0].data_start_time #=> Time
resp.sensor_statistics_summaries[0].data_end_time #=> Time
resp.next_token #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :dataset_name (required, String) —

    The name of the dataset associated with the list of Sensor Statistics.

  • :ingestion_job_id (String) —

    The ingestion job id associated with the list of Sensor Statistics. To get sensor statistics for a particular ingestion job id, both dataset name and ingestion job id must be submitted as inputs.

  • :max_results (Integer) —

    Specifies the maximum number of sensors for which to retrieve statistics.

  • :next_token (String) —

    An opaque pagination token indicating where to continue the listing of sensor statistics.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2703

def list_sensor_statistics(params = {}, options = {})
  req = build_request(:list_sensor_statistics, params)
  req.send_request(options)
end

#list_tags_for_resource(params = {}) ⇒ Types::ListTagsForResourceResponse

Lists all the tags for a specified resource, including key and value.

Examples:

Request syntax with placeholder values


resp = client.list_tags_for_resource({
  resource_arn: "AmazonResourceArn", # required
})

Response structure


resp.tags #=> Array
resp.tags[0].key #=> String
resp.tags[0].value #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    The Amazon Resource Name (ARN) of the resource (such as the dataset or model) that is the focus of the ‘ListTagsForResource` operation.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2734

def list_tags_for_resource(params = {}, options = {})
  req = build_request(:list_tags_for_resource, params)
  req.send_request(options)
end

#put_resource_policy(params = {}) ⇒ Types::PutResourcePolicyResponse

Creates a resource control policy for a given resource.

Examples:

Request syntax with placeholder values


resp = client.put_resource_policy({
  resource_arn: "ResourceArn", # required
  resource_policy: "Policy", # required
  policy_revision_id: "PolicyRevisionId",
  client_token: "IdempotenceToken", # required
})

Response structure


resp.resource_arn #=> String
resp.policy_revision_id #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    The Amazon Resource Name (ARN) of the resource for which the policy is being created.

  • :resource_policy (required, String) —

    The JSON-formatted resource policy to create.

  • :policy_revision_id (String) —

    A unique identifier for a revision of the resource policy.

  • :client_token (required, String) —

    A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

    **A suitable default value is auto-generated.** You should normally not need to pass this option.**

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2781

def put_resource_policy(params = {}, options = {})
  req = build_request(:put_resource_policy, params)
  req.send_request(options)
end

#start_data_ingestion_job(params = {}) ⇒ Types::StartDataIngestionJobResponse

Starts a data ingestion job. Amazon Lookout for Equipment returns the job status.

Examples:

Request syntax with placeholder values


resp = client.start_data_ingestion_job({
  dataset_name: "DatasetIdentifier", # required
  ingestion_input_configuration: { # required
    s3_input_configuration: { # required
      bucket: "S3Bucket", # required
      prefix: "S3Prefix",
      key_pattern: "KeyPattern",
    },
  },
  role_arn: "IamRoleArn", # required
  client_token: "IdempotenceToken", # required
})

Response structure


resp.job_id #=> String
resp.status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :dataset_name (required, String) —

    The name of the dataset being used by the data ingestion job.

  • :ingestion_input_configuration (required, Types::IngestionInputConfiguration) —

    Specifies information for the input data for the data ingestion job, including dataset S3 location.

  • :role_arn (required, String) —

    The Amazon Resource Name (ARN) of a role with permission to access the data source for the data ingestion job.

  • :client_token (required, String) —

    A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

    **A suitable default value is auto-generated.** You should normally not need to pass this option.**

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2836

def start_data_ingestion_job(params = {}, options = {})
  req = build_request(:start_data_ingestion_job, params)
  req.send_request(options)
end

#start_inference_scheduler(params = {}) ⇒ Types::StartInferenceSchedulerResponse

Starts an inference scheduler.

Examples:

Request syntax with placeholder values


resp = client.start_inference_scheduler({
  inference_scheduler_name: "InferenceSchedulerIdentifier", # required
})

Response structure


resp.model_arn #=> String
resp.model_name #=> String
resp.inference_scheduler_name #=> String
resp.inference_scheduler_arn #=> String
resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :inference_scheduler_name (required, String) —

    The name of the inference scheduler to be started.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2872

def start_inference_scheduler(params = {}, options = {})
  req = build_request(:start_inference_scheduler, params)
  req.send_request(options)
end

#start_retraining_scheduler(params = {}) ⇒ Types::StartRetrainingSchedulerResponse

Starts a retraining scheduler.

Examples:

Example: Starts a retraining scheduler


resp = client.start_retraining_scheduler({
  model_name: "sample-model", 
})

resp.to_h outputs the following:
{
  model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", 
  model_name: "sample-model", 
  status: "PENDING", 
}

Request syntax with placeholder values


resp = client.start_retraining_scheduler({
  model_name: "ModelName", # required
})

Response structure


resp.model_name #=> String
resp.model_arn #=> String
resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    The name of the model whose retraining scheduler you want to start.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2918

def start_retraining_scheduler(params = {}, options = {})
  req = build_request(:start_retraining_scheduler, params)
  req.send_request(options)
end

#stop_inference_scheduler(params = {}) ⇒ Types::StopInferenceSchedulerResponse

Stops an inference scheduler.

Examples:

Request syntax with placeholder values


resp = client.stop_inference_scheduler({
  inference_scheduler_name: "InferenceSchedulerIdentifier", # required
})

Response structure


resp.model_arn #=> String
resp.model_name #=> String
resp.inference_scheduler_name #=> String
resp.inference_scheduler_arn #=> String
resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :inference_scheduler_name (required, String) —

    The name of the inference scheduler to be stopped.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 2954

def stop_inference_scheduler(params = {}, options = {})
  req = build_request(:stop_inference_scheduler, params)
  req.send_request(options)
end

#stop_retraining_scheduler(params = {}) ⇒ Types::StopRetrainingSchedulerResponse

Stops a retraining scheduler.

Examples:

Example: Stops a retraining scheduler


resp = client.stop_retraining_scheduler({
  model_name: "sample-model", 
})

resp.to_h outputs the following:
{
  model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", 
  model_name: "sample-model", 
  status: "STOPPING", 
}

Request syntax with placeholder values


resp = client.stop_retraining_scheduler({
  model_name: "ModelName", # required
})

Response structure


resp.model_name #=> String
resp.model_arn #=> String
resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    The name of the model whose retraining scheduler you want to stop.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 3000

def stop_retraining_scheduler(params = {}, options = {})
  req = build_request(:stop_retraining_scheduler, params)
  req.send_request(options)
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.

Examples:

Request syntax with placeholder values


resp = client.tag_resource({
  resource_arn: "AmazonResourceArn", # required
  tags: [ # required
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    The Amazon Resource Name (ARN) of the specific resource to which the tag should be associated.

  • :tags (required, Array<Types::Tag>) —

    The tag or tags to be associated with a specific resource. Both the tag key and value are specified.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 3038

def tag_resource(params = {}, options = {})
  req = build_request(:tag_resource, params)
  req.send_request(options)
end

#untag_resource(params = {}) ⇒ Struct

Removes a specific tag from a given resource. The tag is specified by its key.

Examples:

Request syntax with placeholder values


resp = client.untag_resource({
  resource_arn: "AmazonResourceArn", # required
  tag_keys: ["TagKey"], # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    The Amazon Resource Name (ARN) of the resource to which the tag is currently associated.

  • :tag_keys (required, Array<String>) —

    Specifies the key of the tag to be removed from a specified resource.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 3066

def untag_resource(params = {}, options = {})
  req = build_request(:untag_resource, params)
  req.send_request(options)
end

#update_active_model_version(params = {}) ⇒ Types::UpdateActiveModelVersionResponse

Sets the active model version for a given machine learning model.

Examples:

Request syntax with placeholder values


resp = client.update_active_model_version({
  model_name: "ModelName", # required
  model_version: 1, # required
})

Response structure


resp.model_name #=> String
resp.model_arn #=> String
resp.current_active_version #=> Integer
resp.previous_active_version #=> Integer
resp.current_active_version_arn #=> String
resp.previous_active_version_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    The name of the machine learning model for which the active model version is being set.

  • :model_version (required, Integer) —

    The version of the machine learning model for which the active model version is being set.

Returns:

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 3110

def update_active_model_version(params = {}, options = {})
  req = build_request(:update_active_model_version, params)
  req.send_request(options)
end

#update_inference_scheduler(params = {}) ⇒ Struct

Updates an inference scheduler.

Examples:

Request syntax with placeholder values


resp = client.update_inference_scheduler({
  inference_scheduler_name: "InferenceSchedulerIdentifier", # required
  data_delay_offset_in_minutes: 1,
  data_upload_frequency: "PT5M", # accepts PT5M, PT10M, PT15M, PT30M, PT1H
  data_input_configuration: {
    s3_input_configuration: {
      bucket: "S3Bucket", # required
      prefix: "S3Prefix",
    },
    input_time_zone_offset: "TimeZoneOffset",
    inference_input_name_configuration: {
      timestamp_format: "FileNameTimestampFormat",
      component_timestamp_delimiter: "ComponentTimestampDelimiter",
    },
  },
  data_output_configuration: {
    s3_output_configuration: { # required
      bucket: "S3Bucket", # required
      prefix: "S3Prefix",
    },
    kms_key_id: "NameOrArn",
  },
  role_arn: "IamRoleArn",
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :inference_scheduler_name (required, String) —

    The name of the inference scheduler to be updated.

  • :data_delay_offset_in_minutes (Integer) —

    A period of time (in minutes) by which inference on the data is delayed after the data starts. For instance, if you select an offset delay time of five minutes, inference will not begin on the data until the first data measurement after the five minute mark. For example, if five minutes is selected, the inference scheduler will wake up at the configured frequency with the additional five minute delay time to check the customer S3 bucket. The customer can upload data at the same frequency and they don’t need to stop and restart the scheduler when uploading new data.

  • :data_upload_frequency (String) —

    How often data is uploaded to the source S3 bucket for the input data. The value chosen is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment starts a scheduled inference on your data. In this example, it starts once every 5 minutes.

  • :data_input_configuration (Types::InferenceInputConfiguration) —

    Specifies information for the input data for the inference scheduler, including delimiter, format, and dataset location.

  • :data_output_configuration (Types::InferenceOutputConfiguration) —

    Specifies information for the output results from the inference scheduler, including the output S3 location.

  • :role_arn (String) —

    The Amazon Resource Name (ARN) of a role with permission to access the data source for the inference scheduler.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 3185

def update_inference_scheduler(params = {}, options = {})
  req = build_request(:update_inference_scheduler, params)
  req.send_request(options)
end

#update_label_group(params = {}) ⇒ Struct

Updates the label group.

Examples:

Request syntax with placeholder values


resp = client.update_label_group({
  label_group_name: "LabelGroupName", # required
  fault_codes: ["FaultCode"],
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :label_group_name (required, String) —

    The name of the label group to be updated.

  • :fault_codes (Array<String>) —

    Updates the code indicating the type of anomaly associated with the label.

    Data in this field will be retained for service usage. Follow best practices for the security of your data.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 3215

def update_label_group(params = {}, options = {})
  req = build_request(:update_label_group, params)
  req.send_request(options)
end

#update_model(params = {}) ⇒ Struct

Updates a model in the account.

Examples:

Example: Updates a model


resp = client.update_model({
  labels_input_configuration: {
    label_group_name: "sample-label-group", 
  }, 
  model_name: "sample-model", 
})

Request syntax with placeholder values


resp = client.update_model({
  model_name: "ModelName", # required
  labels_input_configuration: {
    s3_input_configuration: {
      bucket: "S3Bucket", # required
      prefix: "S3Prefix",
    },
    label_group_name: "LabelGroupName",
  },
  role_arn: "IamRoleArn",
  model_diagnostics_output_configuration: {
    s3_output_configuration: { # required
      bucket: "S3Bucket", # required
      prefix: "S3Prefix",
    },
    kms_key_id: "NameOrArn",
  },
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    The name of the model to update.

  • :labels_input_configuration (Types::LabelsInputConfiguration) —

    Contains the configuration information for the S3 location being used to hold label data.

  • :role_arn (String) —

    The ARN of the model to update.

  • :model_diagnostics_output_configuration (Types::ModelDiagnosticsOutputConfiguration) —

    The Amazon S3 location where you want Amazon Lookout for Equipment to save the pointwise model diagnostics for the model. You must also specify the ‘RoleArn` request parameter.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 3274

def update_model(params = {}, options = {})
  req = build_request(:update_model, params)
  req.send_request(options)
end

#update_retraining_scheduler(params = {}) ⇒ Struct

Updates a retraining scheduler.

Examples:

Example: Updates a retraining scheduler


resp = client.update_retraining_scheduler({
  model_name: "sample-model", 
  retraining_frequency: "P1Y", 
  retraining_start_date: Time.parse("2024-01-01T00:00:00Z"), 
})

Request syntax with placeholder values


resp = client.update_retraining_scheduler({
  model_name: "ModelName", # required
  retraining_start_date: Time.now,
  retraining_frequency: "RetrainingFrequency",
  lookback_window: "LookbackWindow",
  promote_mode: "MANAGED", # accepts MANAGED, MANUAL
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    The name of the model whose retraining scheduler you want to update.

  • :retraining_start_date (Time, DateTime, Date, Integer, String) —

    The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day.

  • :retraining_frequency (String) —

    This parameter uses the [ISO 8601] standard to set the frequency at which you want retraining to occur in terms of Years, Months, and/or Days (note: other parameters like Time are not currently supported). The minimum value is 30 days (P30D) and the maximum value is 1 year (P1Y). For example, the following values are valid:

    • P3M15D – Every 3 months and 15 days

    • P2M – Every 2 months

    • P150D – Every 150 days

    [1]: en.wikipedia.org/wiki/ISO_8601#Durations

  • :lookback_window (String) —

    The number of past days of data that will be used for retraining.

  • :promote_mode (String) —

    Indicates how the service will use new models. In ‘MANAGED` mode, new models will automatically be used for inference if they have better performance than the current model. In `MANUAL` mode, the new models will not be used [until they are manually activated].

    [1]: docs.aws.amazon.com/lookout-for-equipment/latest/ug/versioning-model.html#model-activation

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 3343

def update_retraining_scheduler(params = {}, options = {})
  req = build_request(:update_retraining_scheduler, params)
  req.send_request(options)
end

#waiter_names ⇒ Object

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.

Deprecated. 


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# File 'lib/aws-sdk-lookoutequipment/client.rb', line 3372

def waiter_names
  []
end