Module: Elasticsearch::API::MachineLearning::Actions

Included in:
MachineLearningClient
Defined in:
lib/elasticsearch/api/namespace/machine_learning.rb,
lib/elasticsearch/api/actions/machine_learning/info.rb,
lib/elasticsearch/api/actions/machine_learning/put_job.rb,
lib/elasticsearch/api/actions/machine_learning/forecast.rb,
lib/elasticsearch/api/actions/machine_learning/get_jobs.rb,
lib/elasticsearch/api/actions/machine_learning/open_job.rb,
lib/elasticsearch/api/actions/machine_learning/validate.rb,
lib/elasticsearch/api/actions/machine_learning/close_job.rb,
lib/elasticsearch/api/actions/machine_learning/flush_job.rb,
lib/elasticsearch/api/actions/machine_learning/post_data.rb,
lib/elasticsearch/api/actions/machine_learning/reset_job.rb,
lib/elasticsearch/api/actions/machine_learning/delete_job.rb,
lib/elasticsearch/api/actions/machine_learning/put_filter.rb,
lib/elasticsearch/api/actions/machine_learning/update_job.rb,
lib/elasticsearch/api/actions/machine_learning/get_buckets.rb,
lib/elasticsearch/api/actions/machine_learning/get_filters.rb,
lib/elasticsearch/api/actions/machine_learning/get_records.rb,
lib/elasticsearch/api/actions/machine_learning/put_calendar.rb,
lib/elasticsearch/api/actions/machine_learning/put_datafeed.rb,
lib/elasticsearch/api/actions/machine_learning/delete_filter.rb,
lib/elasticsearch/api/actions/machine_learning/get_calendars.rb,
lib/elasticsearch/api/actions/machine_learning/get_datafeeds.rb,
lib/elasticsearch/api/actions/machine_learning/get_job_stats.rb,
lib/elasticsearch/api/actions/machine_learning/stop_datafeed.rb,
lib/elasticsearch/api/actions/machine_learning/update_filter.rb,
lib/elasticsearch/api/actions/machine_learning/get_categories.rb,
lib/elasticsearch/api/actions/machine_learning/start_datafeed.rb,
lib/elasticsearch/api/actions/machine_learning/delete_calendar.rb,
lib/elasticsearch/api/actions/machine_learning/delete_datafeed.rb,
lib/elasticsearch/api/actions/machine_learning/delete_forecast.rb,
lib/elasticsearch/api/actions/machine_learning/get_influencers.rb,
lib/elasticsearch/api/actions/machine_learning/update_datafeed.rb,
lib/elasticsearch/api/actions/machine_learning/get_memory_stats.rb,
lib/elasticsearch/api/actions/machine_learning/preview_datafeed.rb,
lib/elasticsearch/api/actions/machine_learning/put_calendar_job.rb,
lib/elasticsearch/api/actions/machine_learning/set_upgrade_mode.rb,
lib/elasticsearch/api/actions/machine_learning/put_trained_model.rb,
lib/elasticsearch/api/actions/machine_learning/validate_detector.rb,
lib/elasticsearch/api/actions/machine_learning/get_datafeed_stats.rb,
lib/elasticsearch/api/actions/machine_learning/get_trained_models.rb,
lib/elasticsearch/api/actions/machine_learning/delete_calendar_job.rb,
lib/elasticsearch/api/actions/machine_learning/delete_expired_data.rb,
lib/elasticsearch/api/actions/machine_learning/evaluate_data_frame.rb,
lib/elasticsearch/api/actions/machine_learning/get_calendar_events.rb,
lib/elasticsearch/api/actions/machine_learning/get_model_snapshots.rb,
lib/elasticsearch/api/actions/machine_learning/get_overall_buckets.rb,
lib/elasticsearch/api/actions/machine_learning/infer_trained_model.rb,
lib/elasticsearch/api/actions/machine_learning/delete_trained_model.rb,
lib/elasticsearch/api/actions/machine_learning/post_calendar_events.rb,
lib/elasticsearch/api/actions/machine_learning/upgrade_job_snapshot.rb,
lib/elasticsearch/api/actions/machine_learning/delete_calendar_event.rb,
lib/elasticsearch/api/actions/machine_learning/delete_model_snapshot.rb,
lib/elasticsearch/api/actions/machine_learning/estimate_model_memory.rb,
lib/elasticsearch/api/actions/machine_learning/revert_model_snapshot.rb,
lib/elasticsearch/api/actions/machine_learning/update_model_snapshot.rb,
lib/elasticsearch/api/actions/machine_learning/put_trained_model_alias.rb,
lib/elasticsearch/api/actions/machine_learning/get_data_frame_analytics.rb,
lib/elasticsearch/api/actions/machine_learning/get_trained_models_stats.rb,
lib/elasticsearch/api/actions/machine_learning/put_data_frame_analytics.rb,
lib/elasticsearch/api/actions/machine_learning/stop_data_frame_analytics.rb,
lib/elasticsearch/api/actions/machine_learning/delete_trained_model_alias.rb,
lib/elasticsearch/api/actions/machine_learning/start_data_frame_analytics.rb,
lib/elasticsearch/api/actions/machine_learning/delete_data_frame_analytics.rb,
lib/elasticsearch/api/actions/machine_learning/update_data_frame_analytics.rb,
lib/elasticsearch/api/actions/machine_learning/explain_data_frame_analytics.rb,
lib/elasticsearch/api/actions/machine_learning/preview_data_frame_analytics.rb,
lib/elasticsearch/api/actions/machine_learning/put_trained_model_vocabulary.rb,
lib/elasticsearch/api/actions/machine_learning/stop_trained_model_deployment.rb,
lib/elasticsearch/api/actions/machine_learning/get_data_frame_analytics_stats.rb,
lib/elasticsearch/api/actions/machine_learning/start_trained_model_deployment.rb,
lib/elasticsearch/api/actions/machine_learning/update_trained_model_deployment.rb,
lib/elasticsearch/api/actions/machine_learning/get_model_snapshot_upgrade_stats.rb,
lib/elasticsearch/api/actions/machine_learning/put_trained_model_definition_part.rb,
lib/elasticsearch/api/actions/machine_learning/clear_trained_model_deployment_cache.rb more...

Instance Method Summary collapse

Instance Method Details

#clear_trained_model_deployment_cache(arguments = {}) ⇒ Object

Clear the cached results from a trained model deployment

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The unique identifier of the trained model. (Required)

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/clear_trained_model_deployment_cache.rb', line 32

def clear_trained_model_deployment_cache(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.clear_trained_model_deployment_cache" }

  defined_params = [:model_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _model_id = arguments.delete(:model_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/trained_models/#{Utils.__listify(_model_id)}/deployment/cache/_clear"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#close_job(arguments = {}) ⇒ Object

Closes one or more anomaly detection jobs. A job can be opened and closed multiple times throughout its lifecycle.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The name of the job to close

  • :allow_no_match (Boolean) —

    Whether to ignore if a wildcard expression matches no jobs. (This includes ‘_all` string or when no jobs have been specified)

  • :force (Boolean) —

    True if the job should be forcefully closed

  • :timeout (Time) —

    Controls the time to wait until a job has closed. Default to 30 minutes

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The URL params optionally sent in the body

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/close_job.rb', line 36

def close_job(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.close_job" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/_close"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#delete_calendar(arguments = {}) ⇒ Object

Deletes a calendar.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    The ID of the calendar to delete

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/delete_calendar.rb', line 32

def delete_calendar(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.delete_calendar" }

  defined_params = [:calendar_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'calendar_id' missing" unless arguments[:calendar_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _calendar_id = arguments.delete(:calendar_id)

  method = Elasticsearch::API::HTTP_DELETE
  path   = "_ml/calendars/#{Utils.__listify(_calendar_id)}"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#delete_calendar_event(arguments = {}) ⇒ Object

Deletes scheduled events from a calendar.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    The ID of the calendar to modify

  • :event_id (String) —

    The ID of the event to remove from the calendar

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/delete_calendar_event.rb', line 33

def delete_calendar_event(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.delete_calendar_event" }

  defined_params = [:calendar_id, :event_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'calendar_id' missing" unless arguments[:calendar_id]
  raise ArgumentError, "Required argument 'event_id' missing" unless arguments[:event_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _calendar_id = arguments.delete(:calendar_id)

  _event_id = arguments.delete(:event_id)

  method = Elasticsearch::API::HTTP_DELETE
  path   = "_ml/calendars/#{Utils.__listify(_calendar_id)}/events/#{Utils.__listify(_event_id)}"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#delete_calendar_job(arguments = {}) ⇒ Object

Deletes anomaly detection jobs from a calendar.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    The ID of the calendar to modify

  • :job_id (String) —

    The ID of the job to remove from the calendar

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/delete_calendar_job.rb', line 33

def delete_calendar_job(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.delete_calendar_job" }

  defined_params = [:calendar_id, :job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'calendar_id' missing" unless arguments[:calendar_id]
  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _calendar_id = arguments.delete(:calendar_id)

  _job_id = arguments.delete(:job_id)

  method = Elasticsearch::API::HTTP_DELETE
  path   = "_ml/calendars/#{Utils.__listify(_calendar_id)}/jobs/#{Utils.__listify(_job_id)}"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#delete_data_frame_analytics(arguments = {}) ⇒ Object

Deletes an existing data frame analytics job.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    The ID of the data frame analytics to delete

  • :force (Boolean) —

    True if the job should be forcefully deleted

  • :timeout (Time) —

    Controls the time to wait until a job is deleted. Defaults to 1 minute

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/delete_data_frame_analytics.rb', line 34

def delete_data_frame_analytics(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.delete_data_frame_analytics" }

  defined_params = [:id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'id' missing" unless arguments[:id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _id = arguments.delete(:id)

  method = Elasticsearch::API::HTTP_DELETE
  path   = "_ml/data_frame/analytics/#{Utils.__listify(_id)}"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#delete_datafeed(arguments = {}) ⇒ Object

Deletes an existing datafeed.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String) —

    The ID of the datafeed to delete

  • :force (Boolean) —

    True if the datafeed should be forcefully deleted

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/delete_datafeed.rb', line 33

def delete_datafeed(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.delete_datafeed" }

  defined_params = [:datafeed_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'datafeed_id' missing" unless arguments[:datafeed_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _datafeed_id = arguments.delete(:datafeed_id)

  method = Elasticsearch::API::HTTP_DELETE
  path   = "_ml/datafeeds/#{Utils.__listify(_datafeed_id)}"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#delete_expired_data(arguments = {}) ⇒ Object

Deletes expired and unused machine learning data.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job(s) to perform expired data hygiene for

  • :requests_per_second (Number) —

    The desired requests per second for the deletion processes.

  • :timeout (Time) —

    How long can the underlying delete processes run until they are canceled

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    deleting expired data parameters

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/delete_expired_data.rb', line 35

def delete_expired_data(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.delete_expired_data" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  method = Elasticsearch::API::HTTP_DELETE
  path   = if _job_id
             "_ml/_delete_expired_data/#{Utils.__listify(_job_id)}"
           else
             "_ml/_delete_expired_data"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#delete_filter(arguments = {}) ⇒ Object

Deletes a filter.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :filter_id (String) —

    The ID of the filter to delete

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/delete_filter.rb', line 32

def delete_filter(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.delete_filter" }

  defined_params = [:filter_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'filter_id' missing" unless arguments[:filter_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _filter_id = arguments.delete(:filter_id)

  method = Elasticsearch::API::HTTP_DELETE
  path   = "_ml/filters/#{Utils.__listify(_filter_id)}"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#delete_forecast(arguments = {}) ⇒ Object

Deletes forecasts from a machine learning job.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job from which to delete forecasts

  • :forecast_id (String) —

    The ID of the forecast to delete, can be comma delimited list. Leaving blank implies ‘_all`

  • :allow_no_forecasts (Boolean) —

    Whether to ignore if ‘_all` matches no forecasts

  • :timeout (Time) —

    Controls the time to wait until the forecast(s) are deleted. Default to 30 seconds

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/delete_forecast.rb', line 35

def delete_forecast(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.delete_forecast" }

  defined_params = [:job_id, :forecast_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _job_id = arguments.delete(:job_id)

  _forecast_id = arguments.delete(:forecast_id)

  method = Elasticsearch::API::HTTP_DELETE
  path   = if _job_id && _forecast_id
             "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/_forecast/#{Utils.__listify(_forecast_id)}"
           else
             "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/_forecast"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#delete_job(arguments = {}) ⇒ Object

Deletes an existing anomaly detection job.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job to delete

  • :force (Boolean) —

    True if the job should be forcefully deleted

  • :wait_for_completion (Boolean) —

    Should this request wait until the operation has completed before returning

  • :delete_user_annotations (Boolean) —

    Should annotations added by the user be deleted

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/delete_job.rb', line 35

def delete_job(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.delete_job" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _job_id = arguments.delete(:job_id)

  method = Elasticsearch::API::HTTP_DELETE
  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#delete_model_snapshot(arguments = {}) ⇒ Object

Deletes an existing model snapshot.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job to fetch

  • :snapshot_id (String) —

    The ID of the snapshot to delete

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/delete_model_snapshot.rb', line 33

def delete_model_snapshot(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.delete_model_snapshot" }

  defined_params = [:job_id, :snapshot_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]
  raise ArgumentError, "Required argument 'snapshot_id' missing" unless arguments[:snapshot_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _job_id = arguments.delete(:job_id)

  _snapshot_id = arguments.delete(:snapshot_id)

  method = Elasticsearch::API::HTTP_DELETE
  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/model_snapshots/#{Utils.__listify(_snapshot_id)}"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#delete_trained_model(arguments = {}) ⇒ Object

Deletes an existing trained inference model that is currently not referenced by an ingest pipeline.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The ID of the trained model to delete

  • :timeout (Time) —

    Controls the amount of time to wait for the model to be deleted.

  • :force (Boolean) —

    True if the model should be forcefully deleted

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/delete_trained_model.rb', line 34

def delete_trained_model(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.delete_trained_model" }

  defined_params = [:model_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _model_id = arguments.delete(:model_id)

  method = Elasticsearch::API::HTTP_DELETE
  path   = "_ml/trained_models/#{Utils.__listify(_model_id)}"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#delete_trained_model_alias(arguments = {}) ⇒ Object

Deletes a model alias that refers to the trained model

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :model_alias (String) —

    The trained model alias to delete

  • :model_id (String) —

    The trained model where the model alias is assigned

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/delete_trained_model_alias.rb', line 33

def delete_trained_model_alias(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.delete_trained_model_alias" }

  defined_params = [:model_id, :model_alias].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id]
  raise ArgumentError, "Required argument 'model_alias' missing" unless arguments[:model_alias]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _model_alias = arguments.delete(:model_alias)

  _model_id = arguments.delete(:model_id)

  method = Elasticsearch::API::HTTP_DELETE
  path   = "_ml/trained_models/#{Utils.__listify(_model_id)}/model_aliases/#{Utils.__listify(_model_alias)}"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#estimate_model_memory(arguments = {}) ⇒ Object

Estimates the model memory

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The analysis config, plus cardinality estimates for fields it references (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/estimate_model_memory.rb', line 32

def estimate_model_memory(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.estimate_model_memory" }

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body   = arguments.delete(:body)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/anomaly_detectors/_estimate_model_memory"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#evaluate_data_frame(arguments = {}) ⇒ Object

Evaluates the data frame analytics for an annotated index.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The evaluation definition (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/evaluate_data_frame.rb', line 32

def evaluate_data_frame(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.evaluate_data_frame" }

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body   = arguments.delete(:body)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/data_frame/_evaluate"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#explain_data_frame_analytics(arguments = {}) ⇒ Object

Explains a data frame analytics config.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    The ID of the data frame analytics to explain

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The data frame analytics config to explain

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/explain_data_frame_analytics.rb', line 33

def explain_data_frame_analytics(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.explain_data_frame_analytics" }

  defined_params = [:id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _id = arguments.delete(:id)

  method = if body
             Elasticsearch::API::HTTP_POST
           else
             Elasticsearch::API::HTTP_GET
           end

  path   = if _id
             "_ml/data_frame/analytics/#{Utils.__listify(_id)}/_explain"
           else
             "_ml/data_frame/analytics/_explain"
           end
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#flush_job(arguments = {}) ⇒ Object

Forces any buffered data to be processed by the job.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The name of the job to flush

  • :calc_interim (Boolean) —

    Calculates interim results for the most recent bucket or all buckets within the latency period

  • :start (String) —

    When used in conjunction with calc_interim, specifies the range of buckets on which to calculate interim results

  • :end (String) —

    When used in conjunction with calc_interim, specifies the range of buckets on which to calculate interim results

  • :advance_time (String) —

    Advances time to the given value generating results and updating the model for the advanced interval

  • :skip_time (String) —

    Skips time to the given value without generating results or updating the model for the skipped interval

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    Flush parameters

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/flush_job.rb', line 38

def flush_job(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.flush_job" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/_flush"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#forecast(arguments = {}) ⇒ Object

Predicts the future behavior of a time series by using its historical behavior.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job to forecast for

  • :duration (Time) —

    The duration of the forecast

  • :expires_in (Time) —

    The time interval after which the forecast expires. Expired forecasts will be deleted at the first opportunity.

  • :max_model_memory (String) —

    The max memory able to be used by the forecast. Default is 20mb.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    Query parameters can be specified in the body

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/forecast.rb', line 36

def forecast(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.forecast" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/_forecast"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_buckets(arguments = {}) ⇒ Object

Retrieves anomaly detection job results for one or more buckets.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    ID of the job to get bucket results from

  • :timestamp (String) —

    The timestamp of the desired single bucket result

  • :expand (Boolean) —

    Include anomaly records

  • :exclude_interim (Boolean) —

    Exclude interim results

  • :from (Integer) —

    skips a number of buckets

  • :size (Integer) —

    specifies a max number of buckets to get

  • :start (String) —

    Start time filter for buckets

  • :end (String) —

    End time filter for buckets

  • :anomaly_score (Double) —

    Filter for the most anomalous buckets

  • :sort (String) —

    Sort buckets by a particular field

  • :desc (Boolean) —

    Set the sort direction

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    Bucket selection details if not provided in URI

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_buckets.rb', line 43

def get_buckets(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_buckets" }

  defined_params = [:job_id, :timestamp].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  _timestamp = arguments.delete(:timestamp)

  method = if body
             Elasticsearch::API::HTTP_POST
           else
             Elasticsearch::API::HTTP_GET
           end

  path   = if _job_id && _timestamp
             "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/results/buckets/#{Utils.__listify(_timestamp)}"
           else
             "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/results/buckets"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_calendar_events(arguments = {}) ⇒ Object

Retrieves information about the scheduled events in calendars.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    The ID of the calendar containing the events

  • :job_id (String) —

    Get events for the job. When this option is used calendar_id must be ‘_all’

  • :start (String) —

    Get events after this time

  • :end (Date) —

    Get events before this time

  • :from (Integer) —

    Skips a number of events

  • :size (Integer) —

    Specifies a max number of events to get

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_calendar_events.rb', line 37

def get_calendar_events(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_calendar_events" }

  defined_params = [:calendar_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'calendar_id' missing" unless arguments[:calendar_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _calendar_id = arguments.delete(:calendar_id)

  method = Elasticsearch::API::HTTP_GET
  path   = "_ml/calendars/#{Utils.__listify(_calendar_id)}/events"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_calendars(arguments = {}) ⇒ Object

Retrieves configuration information for calendars.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    The ID of the calendar to fetch

  • :from (Integer) —

    skips a number of calendars

  • :size (Integer) —

    specifies a max number of calendars to get

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The from and size parameters optionally sent in the body

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_calendars.rb', line 35

def get_calendars(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_calendars" }

  defined_params = [:calendar_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _calendar_id = arguments.delete(:calendar_id)

  method = if body
             Elasticsearch::API::HTTP_POST
           else
             Elasticsearch::API::HTTP_GET
           end

  path   = if _calendar_id
             "_ml/calendars/#{Utils.__listify(_calendar_id)}"
           else
             "_ml/calendars"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_categories(arguments = {}) ⇒ Object

Retrieves anomaly detection job results for one or more categories.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The name of the job

  • :category_id (Long) —

    The identifier of the category definition of interest

  • :from (Integer) —

    skips a number of categories

  • :size (Integer) —

    specifies a max number of categories to get

  • :partition_field_value (String) —

    Specifies the partition to retrieve categories for. This is optional, and should never be used for jobs where per-partition categorization is disabled.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    Category selection details if not provided in URI

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_categories.rb', line 37

def get_categories(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_categories" }

  defined_params = [:job_id, :category_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  _category_id = arguments.delete(:category_id)

  method = if body
             Elasticsearch::API::HTTP_POST
           else
             Elasticsearch::API::HTTP_GET
           end

  path   = if _job_id && _category_id
             "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/results/categories/#{Utils.__listify(_category_id)}"
           else
             "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/results/categories"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_data_frame_analytics(arguments = {}) ⇒ Object

Retrieves configuration information for data frame analytics jobs.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    The ID of the data frame analytics to fetch

  • :allow_no_match (Boolean) —

    Whether to ignore if a wildcard expression matches no data frame analytics. (This includes ‘_all` string or when no data frame analytics have been specified)

  • :from (Integer) —

    skips a number of analytics

  • :size (Integer) —

    specifies a max number of analytics to get

  • :exclude_generated (Boolean) —

    Omits fields that are illegal to set on data frame analytics PUT

  • :headers (Hash) —

    Custom HTTP headers

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_data_frame_analytics.rb', line 36

def get_data_frame_analytics(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_data_frame_analytics" }

  defined_params = [:id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _id = arguments.delete(:id)

  method = Elasticsearch::API::HTTP_GET
  path   = if _id
             "_ml/data_frame/analytics/#{Utils.__listify(_id)}"
           else
             "_ml/data_frame/analytics"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_data_frame_analytics_stats(arguments = {}) ⇒ Object

Retrieves usage information for data frame analytics jobs.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    The ID of the data frame analytics stats to fetch

  • :allow_no_match (Boolean) —

    Whether to ignore if a wildcard expression matches no data frame analytics. (This includes ‘_all` string or when no data frame analytics have been specified)

  • :from (Integer) —

    skips a number of analytics

  • :size (Integer) —

    specifies a max number of analytics to get

  • :verbose (Boolean) —

    whether the stats response should be verbose

  • :headers (Hash) —

    Custom HTTP headers

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_data_frame_analytics_stats.rb', line 36

def get_data_frame_analytics_stats(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_data_frame_analytics_stats" }

  defined_params = [:id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _id = arguments.delete(:id)

  method = Elasticsearch::API::HTTP_GET
  path   = if _id
             "_ml/data_frame/analytics/#{Utils.__listify(_id)}/_stats"
           else
             "_ml/data_frame/analytics/_stats"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_datafeed_stats(arguments = {}) ⇒ Object

Retrieves usage information for datafeeds.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String) —

    The ID of the datafeeds stats to fetch

  • :allow_no_match (Boolean) —

    Whether to ignore if a wildcard expression matches no datafeeds. (This includes ‘_all` string or when no datafeeds have been specified)

  • :headers (Hash) —

    Custom HTTP headers

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_datafeed_stats.rb', line 33

def get_datafeed_stats(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_datafeed_stats" }

  defined_params = [:datafeed_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _datafeed_id = arguments.delete(:datafeed_id)

  method = Elasticsearch::API::HTTP_GET
  path   = if _datafeed_id
             "_ml/datafeeds/#{Utils.__listify(_datafeed_id)}/_stats"
           else
             "_ml/datafeeds/_stats"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_datafeeds(arguments = {}) ⇒ Object

Retrieves configuration information for datafeeds.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String) —

    The ID of the datafeeds to fetch

  • :allow_no_match (Boolean) —

    Whether to ignore if a wildcard expression matches no datafeeds. (This includes ‘_all` string or when no datafeeds have been specified)

  • :exclude_generated (Boolean) —

    Omits fields that are illegal to set on datafeed PUT

  • :headers (Hash) —

    Custom HTTP headers

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_datafeeds.rb', line 34

def get_datafeeds(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_datafeeds" }

  defined_params = [:datafeed_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _datafeed_id = arguments.delete(:datafeed_id)

  method = Elasticsearch::API::HTTP_GET
  path   = if _datafeed_id
             "_ml/datafeeds/#{Utils.__listify(_datafeed_id)}"
           else
             "_ml/datafeeds"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_filters(arguments = {}) ⇒ Object

Retrieves filters.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :filter_id (String) —

    The ID of the filter to fetch

  • :from (Integer) —

    skips a number of filters

  • :size (Integer) —

    specifies a max number of filters to get

  • :headers (Hash) —

    Custom HTTP headers

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_filters.rb', line 34

def get_filters(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_filters" }

  defined_params = [:filter_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _filter_id = arguments.delete(:filter_id)

  method = Elasticsearch::API::HTTP_GET
  path   = if _filter_id
             "_ml/filters/#{Utils.__listify(_filter_id)}"
           else
             "_ml/filters"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_influencers(arguments = {}) ⇒ Object

Retrieves anomaly detection job results for one or more influencers.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job

  • :exclude_interim (Boolean) —

    Exclude interim results

  • :from (Integer) —

    skips a number of influencers

  • :size (Integer) —

    specifies a max number of influencers to get

  • :start (String) —

    start timestamp for the requested influencers

  • :end (String) —

    end timestamp for the requested influencers

  • :influencer_score (Double) —

    influencer score threshold for the requested influencers

  • :sort (String) —

    sort field for the requested influencers

  • :desc (Boolean) —

    whether the results should be sorted in decending order

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    Influencer selection criteria

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_influencers.rb', line 41

def get_influencers(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_influencers" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  method = if body
             Elasticsearch::API::HTTP_POST
           else
             Elasticsearch::API::HTTP_GET
           end

  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/results/influencers"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_job_stats(arguments = {}) ⇒ Object

Retrieves usage information for anomaly detection jobs.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the jobs stats to fetch

  • :allow_no_match (Boolean) —

    Whether to ignore if a wildcard expression matches no jobs. (This includes ‘_all` string or when no jobs have been specified)

  • :headers (Hash) —

    Custom HTTP headers

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_job_stats.rb', line 33

def get_job_stats(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_job_stats" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _job_id = arguments.delete(:job_id)

  method = Elasticsearch::API::HTTP_GET
  path   = if _job_id
             "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/_stats"
           else
             "_ml/anomaly_detectors/_stats"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_jobs(arguments = {}) ⇒ Object

Retrieves configuration information for anomaly detection jobs.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the jobs to fetch

  • :allow_no_match (Boolean) —

    Whether to ignore if a wildcard expression matches no jobs. (This includes ‘_all` string or when no jobs have been specified)

  • :exclude_generated (Boolean) —

    Omits fields that are illegal to set on job PUT

  • :headers (Hash) —

    Custom HTTP headers

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_jobs.rb', line 34

def get_jobs(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_jobs" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _job_id = arguments.delete(:job_id)

  method = Elasticsearch::API::HTTP_GET
  path   = if _job_id
             "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}"
           else
             "_ml/anomaly_detectors"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_memory_stats(arguments = {}) ⇒ Object

Returns information on how ML is using memory.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :node_id (String) —

    Specifies the node or nodes to retrieve stats for.

  • :master_timeout (Time) —

    Explicit operation timeout for connection to master node

  • :timeout (Time) —

    Explicit operation timeout

  • :headers (Hash) —

    Custom HTTP headers

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_memory_stats.rb', line 34

def get_memory_stats(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_memory_stats" }

  defined_params = [:node_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _node_id = arguments.delete(:node_id)

  method = Elasticsearch::API::HTTP_GET
  path   = if _node_id
             "_ml/memory/#{Utils.__listify(_node_id)}/_stats"
           else
             "_ml/memory/_stats"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_model_snapshot_upgrade_stats(arguments = {}) ⇒ Object

Gets stats for anomaly detection job model snapshot upgrades that are in progress.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job. May be a wildcard, comma separated list or ‘_all`.

  • :snapshot_id (String) —

    The ID of the snapshot. May be a wildcard, comma separated list or ‘_all`.

  • :allow_no_match (Boolean) —

    Whether to ignore if a wildcard expression matches no jobs or no snapshots. (This includes the ‘_all` string.)

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_model_snapshot_upgrade_stats.rb', line 34

def get_model_snapshot_upgrade_stats(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_model_snapshot_upgrade_stats" }

  defined_params = [:job_id, :snapshot_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]
  raise ArgumentError, "Required argument 'snapshot_id' missing" unless arguments[:snapshot_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _job_id = arguments.delete(:job_id)

  _snapshot_id = arguments.delete(:snapshot_id)

  method = Elasticsearch::API::HTTP_GET
  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/model_snapshots/#{Utils.__listify(_snapshot_id)}/_upgrade/_stats"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_model_snapshots(arguments = {}) ⇒ Object

Retrieves information about model snapshots.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job to fetch

  • :snapshot_id (String) —

    The ID of the snapshot to fetch

  • :from (Integer) —

    Skips a number of documents

  • :size (Integer) —

    The default number of documents returned in queries as a string.

  • :start (Date) —

    The filter ‘start’ query parameter

  • :end (Date) —

    The filter ‘end’ query parameter

  • :sort (String) —

    Name of the field to sort on

  • :desc (Boolean) —

    True if the results should be sorted in descending order

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    Model snapshot selection criteria

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_model_snapshots.rb', line 40

def get_model_snapshots(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_model_snapshots" }

  defined_params = [:job_id, :snapshot_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  _snapshot_id = arguments.delete(:snapshot_id)

  method = if body
             Elasticsearch::API::HTTP_POST
           else
             Elasticsearch::API::HTTP_GET
           end

  path   = if _job_id && _snapshot_id
             "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/model_snapshots/#{Utils.__listify(_snapshot_id)}"
           else
             "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/model_snapshots"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_overall_buckets(arguments = {}) ⇒ Object

Retrieves overall bucket results that summarize the bucket results of multiple anomaly detection jobs.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The job IDs for which to calculate overall bucket results

  • :top_n (Integer) —

    The number of top job bucket scores to be used in the overall_score calculation

  • :bucket_span (String) —

    The span of the overall buckets. Defaults to the longest job bucket_span

  • :overall_score (Double) —

    Returns overall buckets with overall scores higher than this value

  • :exclude_interim (Boolean) —

    If true overall buckets that include interim buckets will be excluded

  • :start (String) —

    Returns overall buckets with timestamps after this time

  • :end (String) —

    Returns overall buckets with timestamps earlier than this time

  • :allow_no_match (Boolean) —

    Whether to ignore if a wildcard expression matches no jobs. (This includes ‘_all` string or when no jobs have been specified)

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    Overall bucket selection details if not provided in URI

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_overall_buckets.rb', line 40

def get_overall_buckets(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_overall_buckets" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  method = if body
             Elasticsearch::API::HTTP_POST
           else
             Elasticsearch::API::HTTP_GET
           end

  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/results/overall_buckets"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_records(arguments = {}) ⇒ Object

Retrieves anomaly records for an anomaly detection job.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job

  • :exclude_interim (Boolean) —

    Exclude interim results

  • :from (Integer) —

    skips a number of records

  • :size (Integer) —

    specifies a max number of records to get

  • :start (String) —

    Start time filter for records

  • :end (String) —

    End time filter for records

  • :record_score (Double) —

    Returns records with anomaly scores greater or equal than this value

  • :sort (String) —

    Sort records by a particular field

  • :desc (Boolean) —

    Set the sort direction

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    Record selection criteria

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_records.rb', line 41

def get_records(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_records" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  method = if body
             Elasticsearch::API::HTTP_POST
           else
             Elasticsearch::API::HTTP_GET
           end

  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/results/records"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_trained_models(arguments = {}) ⇒ Object

Retrieves configuration information for a trained inference model.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The ID of the trained models to fetch

  • :allow_no_match (Boolean) —

    Whether to ignore if a wildcard expression matches no trained models. (This includes ‘_all` string or when no trained models have been specified)

  • :include (String) —

    A comma-separate list of fields to optionally include. Valid options are ‘definition’ and ‘total_feature_importance’. Default is none.

  • :include_model_definition (Boolean) —

    Should the full model definition be included in the results. These definitions can be large. So be cautious when including them. Defaults to false. Deprecated

  • :decompress_definition (Boolean) —

    Should the model definition be decompressed into valid JSON or returned in a custom compressed format. Defaults to true.

  • :from (Integer) —

    skips a number of trained models

  • :size (Integer) —

    specifies a max number of trained models to get

  • :tags (List) —

    A comma-separated list of tags that the model must have.

  • :exclude_generated (Boolean) —

    Omits fields that are illegal to set on model PUT

  • :headers (Hash) —

    Custom HTTP headers

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_trained_models.rb', line 40

def get_trained_models(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_trained_models" }

  defined_params = [:model_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _model_id = arguments.delete(:model_id)

  method = Elasticsearch::API::HTTP_GET
  path   = if _model_id
             "_ml/trained_models/#{Utils.__listify(_model_id)}"
           else
             "_ml/trained_models"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#get_trained_models_stats(arguments = {}) ⇒ Object

Retrieves usage information for trained inference models.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The ID of the trained models stats to fetch

  • :allow_no_match (Boolean) —

    Whether to ignore if a wildcard expression matches no trained models. (This includes ‘_all` string or when no trained models have been specified)

  • :from (Integer) —

    skips a number of trained models

  • :size (Integer) —

    specifies a max number of trained models to get

  • :headers (Hash) —

    Custom HTTP headers

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/get_trained_models_stats.rb', line 35

def get_trained_models_stats(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.get_trained_models_stats" }

  defined_params = [:model_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _model_id = arguments.delete(:model_id)

  method = Elasticsearch::API::HTTP_GET
  path   = if _model_id
             "_ml/trained_models/#{Utils.__listify(_model_id)}/_stats"
           else
             "_ml/trained_models/_stats"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#infer_trained_model(arguments = {}) ⇒ Object

Evaluate a trained model.

*Deprecation notice*: /_ml/trained_models/model_id/deployment/_infer is deprecated. Use /_ml/trained_models/model_id/_infer instead Deprecated since version 8.3.0

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The unique identifier of the trained model. (Required)

  • :timeout (Time) —

    Controls the amount of time to wait for inference results.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The docs to apply inference on and inference configuration overrides (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/infer_trained_model.rb', line 39

def infer_trained_model(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.infer_trained_model" }

  defined_params = [:model_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _model_id = arguments.delete(:model_id)

  method = Elasticsearch::API::HTTP_POST
  path   = if _model_id
             "_ml/trained_models/#{Utils.__listify(_model_id)}/deployment/_infer"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#info(arguments = {}) ⇒ Object

Returns defaults and limits used by machine learning.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :headers (Hash) —

    Custom HTTP headers

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/info.rb', line 31

def info(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.info" }

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body   = nil

  method = Elasticsearch::API::HTTP_GET
  path   = "_ml/info"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#open_job(arguments = {}) ⇒ Object

Opens one or more anomaly detection jobs.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job to open

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    Query parameters can be specified in the body

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/open_job.rb', line 33

def open_job(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.open_job" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/_open"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#post_calendar_events(arguments = {}) ⇒ Object

Posts scheduled events in a calendar.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    The ID of the calendar to modify

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    A list of events (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/post_calendar_events.rb', line 33

def post_calendar_events(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.post_calendar_events" }

  defined_params = [:calendar_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'calendar_id' missing" unless arguments[:calendar_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _calendar_id = arguments.delete(:calendar_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/calendars/#{Utils.__listify(_calendar_id)}/events"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#post_data(arguments = {}) ⇒ Object

Sends data to an anomaly detection job for analysis.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The name of the job receiving the data

  • :reset_start (String) —

    Optional parameter to specify the start of the bucket resetting range

  • :reset_end (String) —

    Optional parameter to specify the end of the bucket resetting range

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The data to process (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/post_data.rb', line 35

def post_data(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.post_data" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/_data"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#preview_data_frame_analytics(arguments = {}) ⇒ Object

Previews that will be analyzed given a data frame analytics config.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    The ID of the data frame analytics to preview

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The data frame analytics config to preview

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/preview_data_frame_analytics.rb', line 33

def preview_data_frame_analytics(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.preview_data_frame_analytics" }

  defined_params = [:id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _id = arguments.delete(:id)

  method = if body
             Elasticsearch::API::HTTP_POST
           else
             Elasticsearch::API::HTTP_GET
           end

  path   = if _id
             "_ml/data_frame/analytics/#{Utils.__listify(_id)}/_preview"
           else
             "_ml/data_frame/analytics/_preview"
           end
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#preview_datafeed(arguments = {}) ⇒ Object

Previews a datafeed.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String) —

    The ID of the datafeed to preview

  • :start (String) —

    The start time from where the datafeed preview should begin

  • :end (String) —

    The end time when the datafeed preview should stop

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The datafeed config and job config with which to execute the preview

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/preview_datafeed.rb', line 35

def preview_datafeed(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.preview_datafeed" }

  defined_params = [:datafeed_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _datafeed_id = arguments.delete(:datafeed_id)

  method = if body
             Elasticsearch::API::HTTP_POST
           else
             Elasticsearch::API::HTTP_GET
           end

  path   = if _datafeed_id
             "_ml/datafeeds/#{Utils.__listify(_datafeed_id)}/_preview"
           else
             "_ml/datafeeds/_preview"
           end
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#put_calendar(arguments = {}) ⇒ Object

Instantiates a calendar.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    The ID of the calendar to create

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The calendar details

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/put_calendar.rb', line 33

def put_calendar(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.put_calendar" }

  defined_params = [:calendar_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'calendar_id' missing" unless arguments[:calendar_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _calendar_id = arguments.delete(:calendar_id)

  method = Elasticsearch::API::HTTP_PUT
  path   = "_ml/calendars/#{Utils.__listify(_calendar_id)}"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#put_calendar_job(arguments = {}) ⇒ Object

Adds an anomaly detection job to a calendar.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    The ID of the calendar to modify

  • :job_id (String) —

    The ID of the job to add to the calendar

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/put_calendar_job.rb', line 33

def put_calendar_job(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.put_calendar_job" }

  defined_params = [:calendar_id, :job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'calendar_id' missing" unless arguments[:calendar_id]
  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _calendar_id = arguments.delete(:calendar_id)

  _job_id = arguments.delete(:job_id)

  method = Elasticsearch::API::HTTP_PUT
  path   = "_ml/calendars/#{Utils.__listify(_calendar_id)}/jobs/#{Utils.__listify(_job_id)}"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#put_data_frame_analytics(arguments = {}) ⇒ Object

Instantiates a data frame analytics job.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    The ID of the data frame analytics to create

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The data frame analytics configuration (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/put_data_frame_analytics.rb', line 33

def put_data_frame_analytics(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.put_data_frame_analytics" }

  defined_params = [:id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'id' missing" unless arguments[:id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _id = arguments.delete(:id)

  method = Elasticsearch::API::HTTP_PUT
  path   = "_ml/data_frame/analytics/#{Utils.__listify(_id)}"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#put_datafeed(arguments = {}) ⇒ Object

Instantiates a datafeed.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String) —

    The ID of the datafeed to create

  • :ignore_unavailable (Boolean) —

    Ignore unavailable indexes (default: false)

  • :allow_no_indices (Boolean) —

    Ignore if the source indices expressions resolves to no concrete indices (default: true)

  • :ignore_throttled (Boolean) —

    Ignore indices that are marked as throttled (default: true)

  • :expand_wildcards (String) —

    Whether source index expressions should get expanded to open or closed indices (default: open) (options: open, closed, hidden, none, all)

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The datafeed config (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/put_datafeed.rb', line 37

def put_datafeed(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.put_datafeed" }

  defined_params = [:datafeed_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'datafeed_id' missing" unless arguments[:datafeed_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _datafeed_id = arguments.delete(:datafeed_id)

  method = Elasticsearch::API::HTTP_PUT
  path   = "_ml/datafeeds/#{Utils.__listify(_datafeed_id)}"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#put_filter(arguments = {}) ⇒ Object

Instantiates a filter.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :filter_id (String) —

    The ID of the filter to create

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The filter details (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/put_filter.rb', line 33

def put_filter(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.put_filter" }

  defined_params = [:filter_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'filter_id' missing" unless arguments[:filter_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _filter_id = arguments.delete(:filter_id)

  method = Elasticsearch::API::HTTP_PUT
  path   = "_ml/filters/#{Utils.__listify(_filter_id)}"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#put_job(arguments = {}) ⇒ Object

Instantiates an anomaly detection job.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job to create

  • :ignore_unavailable (Boolean) —

    Ignore unavailable indexes (default: false). Only set if datafeed_config is provided.

  • :allow_no_indices (Boolean) —

    Ignore if the source indices expressions resolves to no concrete indices (default: true). Only set if datafeed_config is provided.

  • :ignore_throttled (Boolean) —

    Ignore indices that are marked as throttled (default: true). Only set if datafeed_config is provided.

  • :expand_wildcards (String) —

    Whether source index expressions should get expanded to open or closed indices (default: open). Only set if datafeed_config is provided. (options: open, closed, hidden, none, all)

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The job (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/put_job.rb', line 37

def put_job(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.put_job" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  method = Elasticsearch::API::HTTP_PUT
  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#put_trained_model(arguments = {}) ⇒ Object

Creates an inference trained model.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The ID of the trained models to store

  • :defer_definition_decompression (Boolean) —

    If set to ‘true` and a `compressed_definition` is provided, the request defers definition decompression and skips relevant validations.

  • :wait_for_completion (Boolean) —

    Whether to wait for all child operations(e.g. model download) to complete, before returning or not. Default to false

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The trained model configuration (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/put_trained_model.rb', line 35

def put_trained_model(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.put_trained_model" }

  defined_params = [:model_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _model_id = arguments.delete(:model_id)

  method = Elasticsearch::API::HTTP_PUT
  path   = "_ml/trained_models/#{Utils.__listify(_model_id)}"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#put_trained_model_alias(arguments = {}) ⇒ Object

Creates a new model alias (or reassigns an existing one) to refer to the trained model

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :model_alias (String) —

    The trained model alias to update

  • :model_id (String) —

    The trained model where the model alias should be assigned

  • :reassign (Boolean) —

    If the model_alias already exists and points to a separate model_id, this parameter must be true. Defaults to false.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/put_trained_model_alias.rb', line 34

def put_trained_model_alias(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.put_trained_model_alias" }

  defined_params = [:model_id, :model_alias].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id]
  raise ArgumentError, "Required argument 'model_alias' missing" unless arguments[:model_alias]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _model_alias = arguments.delete(:model_alias)

  _model_id = arguments.delete(:model_id)

  method = Elasticsearch::API::HTTP_PUT
  path   = "_ml/trained_models/#{Utils.__listify(_model_id)}/model_aliases/#{Utils.__listify(_model_alias)}"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#put_trained_model_definition_part(arguments = {}) ⇒ Object

Creates part of a trained model definition

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The ID of the trained model for this definition part

  • :part (Integer) —

    The part number

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The trained model definition part (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/put_trained_model_definition_part.rb', line 34

def put_trained_model_definition_part(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.put_trained_model_definition_part" }

  defined_params = [:model_id, :part].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id]
  raise ArgumentError, "Required argument 'part' missing" unless arguments[:part]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _model_id = arguments.delete(:model_id)

  _part = arguments.delete(:part)

  method = Elasticsearch::API::HTTP_PUT
  path   = "_ml/trained_models/#{Utils.__listify(_model_id)}/definition/#{Utils.__listify(_part)}"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#put_trained_model_vocabulary(arguments = {}) ⇒ Object

Creates a trained model vocabulary

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The ID of the trained model for this vocabulary

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The trained model vocabulary (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/put_trained_model_vocabulary.rb', line 33

def put_trained_model_vocabulary(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.put_trained_model_vocabulary" }

  defined_params = [:model_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _model_id = arguments.delete(:model_id)

  method = Elasticsearch::API::HTTP_PUT
  path   = "_ml/trained_models/#{Utils.__listify(_model_id)}/vocabulary"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#reset_job(arguments = {}) ⇒ Object

Resets an existing anomaly detection job.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job to reset

  • :wait_for_completion (Boolean) —

    Should this request wait until the operation has completed before returning

  • :delete_user_annotations (Boolean) —

    Should annotations added by the user be deleted

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/reset_job.rb', line 34

def reset_job(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.reset_job" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _job_id = arguments.delete(:job_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/_reset"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#revert_model_snapshot(arguments = {}) ⇒ Object

Reverts to a specific snapshot.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job to fetch

  • :snapshot_id (String) —

    The ID of the snapshot to revert to

  • :delete_intervening_results (Boolean) —

    Should we reset the results back to the time of the snapshot?

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    Reversion options

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/revert_model_snapshot.rb', line 35

def revert_model_snapshot(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.revert_model_snapshot" }

  defined_params = [:job_id, :snapshot_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]
  raise ArgumentError, "Required argument 'snapshot_id' missing" unless arguments[:snapshot_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  _snapshot_id = arguments.delete(:snapshot_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/model_snapshots/#{Utils.__listify(_snapshot_id)}/_revert"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#set_upgrade_mode(arguments = {}) ⇒ Object

Sets a cluster wide upgrade_mode setting that prepares machine learning indices for an upgrade.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :enabled (Boolean) —

    Whether to enable upgrade_mode ML setting or not. Defaults to false.

  • :timeout (Time) —

    Controls the time to wait before action times out. Defaults to 30 seconds

  • :headers (Hash) —

    Custom HTTP headers

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/set_upgrade_mode.rb', line 33

def set_upgrade_mode(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.set_upgrade_mode" }

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body   = nil

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/set_upgrade_mode"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#start_data_frame_analytics(arguments = {}) ⇒ Object

Starts a data frame analytics job.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    The ID of the data frame analytics to start

  • :timeout (Time) —

    Controls the time to wait until the task has started. Defaults to 20 seconds

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The start data frame analytics parameters

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/start_data_frame_analytics.rb', line 34

def start_data_frame_analytics(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.start_data_frame_analytics" }

  defined_params = [:id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'id' missing" unless arguments[:id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _id = arguments.delete(:id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/data_frame/analytics/#{Utils.__listify(_id)}/_start"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#start_datafeed(arguments = {}) ⇒ Object

Starts one or more datafeeds.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String) —

    The ID of the datafeed to start

  • :start (String) —

    The start time from where the datafeed should begin

  • :end (String) —

    The end time when the datafeed should stop. When not set, the datafeed continues in real time

  • :timeout (Time) —

    Controls the time to wait until a datafeed has started. Default to 20 seconds

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The start datafeed parameters

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/start_datafeed.rb', line 36

def start_datafeed(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.start_datafeed" }

  defined_params = [:datafeed_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'datafeed_id' missing" unless arguments[:datafeed_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _datafeed_id = arguments.delete(:datafeed_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/datafeeds/#{Utils.__listify(_datafeed_id)}/_start"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#start_trained_model_deployment(arguments = {}) ⇒ Object

Start a trained model deployment.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The unique identifier of the trained model. (Required)

  • :cache_size (String) —

    A byte-size value for configuring the inference cache size. For example, 20mb.

  • :deployment_id (String) —

    The Id of the new deployment. Defaults to the model_id if not set.

  • :number_of_allocations (Integer) —

    The total number of allocations this model is assigned across machine learning nodes.

  • :threads_per_allocation (Integer) —

    The number of threads used by each model allocation during inference.

  • :priority (String) —

    The deployment priority.

  • :queue_capacity (Integer) —

    Controls how many inference requests are allowed in the queue at a time.

  • :timeout (Time) —

    Controls the amount of time to wait for the model to deploy.

  • :wait_for (String) —

    The allocation status for which to wait (options: starting, started, fully_allocated)

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/start_trained_model_deployment.rb', line 40

def start_trained_model_deployment(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.start_trained_model_deployment" }

  defined_params = [:model_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _model_id = arguments.delete(:model_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/trained_models/#{Utils.__listify(_model_id)}/deployment/_start"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#stop_data_frame_analytics(arguments = {}) ⇒ Object

Stops one or more data frame analytics jobs.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    The ID of the data frame analytics to stop

  • :allow_no_match (Boolean) —

    Whether to ignore if a wildcard expression matches no data frame analytics. (This includes ‘_all` string or when no data frame analytics have been specified)

  • :force (Boolean) —

    True if the data frame analytics should be forcefully stopped

  • :timeout (Time) —

    Controls the time to wait until the task has stopped. Defaults to 20 seconds

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The stop data frame analytics parameters

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/stop_data_frame_analytics.rb', line 36

def stop_data_frame_analytics(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.stop_data_frame_analytics" }

  defined_params = [:id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'id' missing" unless arguments[:id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _id = arguments.delete(:id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/data_frame/analytics/#{Utils.__listify(_id)}/_stop"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#stop_datafeed(arguments = {}) ⇒ Object

Stops one or more datafeeds.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String) —

    The ID of the datafeed to stop

  • :allow_no_match (Boolean) —

    Whether to ignore if a wildcard expression matches no datafeeds. (This includes ‘_all` string or when no datafeeds have been specified)

  • :allow_no_datafeeds (Boolean) —

    Whether to ignore if a wildcard expression matches no datafeeds. (This includes ‘_all` string or when no datafeeds have been specified) Deprecated

  • :force (Boolean) —

    True if the datafeed should be forcefully stopped.

  • :timeout (Time) —

    Controls the time to wait until a datafeed has stopped. Default to 20 seconds

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The URL params optionally sent in the body

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/stop_datafeed.rb', line 37

def stop_datafeed(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.stop_datafeed" }

  defined_params = [:datafeed_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'datafeed_id' missing" unless arguments[:datafeed_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _datafeed_id = arguments.delete(:datafeed_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/datafeeds/#{Utils.__listify(_datafeed_id)}/_stop"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#stop_trained_model_deployment(arguments = {}) ⇒ Object

Stop a trained model deployment.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The unique identifier of the trained model. (Required)

  • :allow_no_match (Boolean) —

    Whether to ignore if a wildcard expression matches no deployments. (This includes ‘_all` string or when no deployments have been specified)

  • :force (Boolean) —

    True if the deployment should be forcefully stopped

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The stop deployment parameters

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/stop_trained_model_deployment.rb', line 35

def stop_trained_model_deployment(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.stop_trained_model_deployment" }

  defined_params = [:model_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _model_id = arguments.delete(:model_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/trained_models/#{Utils.__listify(_model_id)}/deployment/_stop"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#update_data_frame_analytics(arguments = {}) ⇒ Object

Updates certain properties of a data frame analytics job.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    The ID of the data frame analytics to update

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The data frame analytics settings to update (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/update_data_frame_analytics.rb', line 33

def update_data_frame_analytics(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.update_data_frame_analytics" }

  defined_params = [:id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'id' missing" unless arguments[:id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _id = arguments.delete(:id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/data_frame/analytics/#{Utils.__listify(_id)}/_update"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#update_datafeed(arguments = {}) ⇒ Object

Updates certain properties of a datafeed.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String) —

    The ID of the datafeed to update

  • :ignore_unavailable (Boolean) —

    Ignore unavailable indexes (default: false)

  • :allow_no_indices (Boolean) —

    Ignore if the source indices expressions resolves to no concrete indices (default: true)

  • :ignore_throttled (Boolean) —

    Ignore indices that are marked as throttled (default: true)

  • :expand_wildcards (String) —

    Whether source index expressions should get expanded to open or closed indices (default: open) (options: open, closed, hidden, none, all)

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The datafeed update settings (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/update_datafeed.rb', line 37

def update_datafeed(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.update_datafeed" }

  defined_params = [:datafeed_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'datafeed_id' missing" unless arguments[:datafeed_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _datafeed_id = arguments.delete(:datafeed_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/datafeeds/#{Utils.__listify(_datafeed_id)}/_update"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#update_filter(arguments = {}) ⇒ Object

Updates the description of a filter, adds items, or removes items.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :filter_id (String) —

    The ID of the filter to update

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The filter update (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/update_filter.rb', line 33

def update_filter(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.update_filter" }

  defined_params = [:filter_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'filter_id' missing" unless arguments[:filter_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _filter_id = arguments.delete(:filter_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/filters/#{Utils.__listify(_filter_id)}/_update"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#update_job(arguments = {}) ⇒ Object

Updates certain properties of an anomaly detection job.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job to create

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The job update settings (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/update_job.rb', line 33

def update_job(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.update_job" }

  defined_params = [:job_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/_update"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#update_model_snapshot(arguments = {}) ⇒ Object

Updates certain properties of a snapshot.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job to fetch

  • :snapshot_id (String) —

    The ID of the snapshot to update

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The model snapshot properties to update (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/update_model_snapshot.rb', line 34

def update_model_snapshot(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.update_model_snapshot" }

  defined_params = [:job_id, :snapshot_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]
  raise ArgumentError, "Required argument 'snapshot_id' missing" unless arguments[:snapshot_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _job_id = arguments.delete(:job_id)

  _snapshot_id = arguments.delete(:snapshot_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/model_snapshots/#{Utils.__listify(_snapshot_id)}/_update"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#update_trained_model_deployment(arguments = {}) ⇒ Object

Updates certain properties of trained model deployment. This functionality is in Beta and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The unique identifier of the trained model.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The updated trained model deployment settings (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/update_trained_model_deployment.rb', line 37

def update_trained_model_deployment(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.update_trained_model_deployment" }

  defined_params = [:model_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]
  raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = arguments.delete(:body)

  _model_id = arguments.delete(:model_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/trained_models/#{Utils.__listify(_model_id)}/deployment/_update"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#upgrade_job_snapshot(arguments = {}) ⇒ Object

Upgrades a given job snapshot to the current major version.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job

  • :snapshot_id (String) —

    The ID of the snapshot

  • :timeout (Time) —

    How long should the API wait for the job to be opened and the old snapshot to be loaded.

  • :wait_for_completion (Boolean) —

    Should the request wait until the task is complete before responding to the caller. Default is false.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/upgrade_job_snapshot.rb', line 35

def upgrade_job_snapshot(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.upgrade_job_snapshot" }

  defined_params = [:job_id, :snapshot_id].inject({}) do |set_variables, variable|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
    set_variables
  end
  request_opts[:defined_params] = defined_params unless defined_params.empty?

  raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]
  raise ArgumentError, "Required argument 'snapshot_id' missing" unless arguments[:snapshot_id]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body = nil

  _job_id = arguments.delete(:job_id)

  _snapshot_id = arguments.delete(:snapshot_id)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/anomaly_detectors/#{Utils.__listify(_job_id)}/model_snapshots/#{Utils.__listify(_snapshot_id)}/_upgrade"
  params = Utils.process_params(arguments)

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#validate(arguments = {}) ⇒ Object

Validates an anomaly detection job.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The job config (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/validate.rb', line 32

def validate(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.validate" }

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body   = arguments.delete(:body)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/anomaly_detectors/_validate"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end

#validate_detector(arguments = {}) ⇒ Object

Validates an anomaly detection detector.

Parameters:

  • arguments (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (arguments):

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    The detector (Required)

Raises:

  • (ArgumentError)

See Also:

[View source]

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# File 'lib/elasticsearch/api/actions/machine_learning/validate_detector.rb', line 32

def validate_detector(arguments = {})
  request_opts = { endpoint: arguments[:endpoint] || "ml.validate_detector" }

  raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]

  arguments = arguments.clone
  headers = arguments.delete(:headers) || {}

  body   = arguments.delete(:body)

  method = Elasticsearch::API::HTTP_POST
  path   = "_ml/anomaly_detectors/_validate/detector"
  params = {}

  Elasticsearch::API::Response.new(
    perform_request(method, path, params, body, headers, request_opts)
  )
end