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

Defined in:
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/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/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

Instance Method Summary collapse

Instance Method Details

#clear_trained_model_deployment_cache(arguments = {}) ⇒ Object

Clear trained model deployment cache. Cache will be cleared on all nodes where the trained model is assigned. A trained model deployment may have an inference cache enabled. As requests are handled by each allocated node, their responses may be cached on that individual node. Calling this API clears the caches without restarting the 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:



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

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

  defined_params = [:model_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Close anomaly detection jobs. A job can be opened and closed multiple times throughout its lifecycle. A closed job cannot receive data or perform analysis operations, but you can still explore and navigate results. When you close a job, it runs housekeeping tasks such as pruning the model history, flushing buffers, calculating final results and persisting the model snapshots. Depending upon the size of the job, it could take several minutes to close and the equivalent time to re-open. After it is closed, the job has a minimal overhead on the cluster except for maintaining its meta data. Therefore it is a best practice to close jobs that are no longer required to process data. If you close an anomaly detection job whose datafeed is running, the request first tries to stop the datafeed. This behavior is equivalent to calling stop datafeed API with the same timeout and force parameters as the close job request. When a datafeed that has a specified end date stops, it automatically closes its associated job.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. It can be a job identifier, a group name, or a wildcard expression. You can close multiple anomaly detection jobs in a single API request by using a group name, a comma-separated list of jobs, or a wildcard expression. You can close all jobs by using _all or by specifying * as the job identifier. (Required)

  • :allow_no_match (Boolean) —

    Specifies what to do when the request: contains wildcard expressions and there are no jobs that match; contains the _all string or no identifiers and there are no matches; or contains wildcard expressions and there are only partial matches. By default, it returns an empty jobs array when there are no matches and the subset of results when there are partial matches. If false, the request returns a 404 status code when there are no matches or only partial matches. Server default: true.

  • :force (Boolean) —

    Use to close a failed job, or to forcefully close a job which has not responded to its initial close request; the request returns without performing the associated actions such as flushing buffers and persisting the model snapshots. If you want the job to be in a consistent state after the close job API returns, do not set to true. This parameter should be used only in situations where the job has already failed or where you are not interested in results the job might have recently produced or might produce in the future.

  • :timeout (Time) —

    Controls the time to wait until a job has closed. Server default: 30m.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/close_job.rb', line 42

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Delete a calendar. Remove all scheduled events from a calendar, then delete it.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    A string that uniquely identifies a calendar. (Required)

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:calendar_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Delete events from a calendar.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    A string that uniquely identifies a calendar. (Required)

  • :event_id (String) —

    Identifier for the scheduled event. You can obtain this identifier by using the get calendar events API. (Required)

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:calendar_id, :event_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Delete anomaly jobs from a calendar.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    A string that uniquely identifies a calendar. (Required)

  • :job_id (String, Array) —

    An identifier for the anomaly detection jobs. It can be a job identifier, a group name, or a comma-separated list of jobs or groups. (Required)

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:calendar_id, :job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Delete a data frame analytics job.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    Identifier for the data frame analytics job. (Required)

  • :force (Boolean) —

    If true, it deletes a job that is not stopped; this method is quicker than stopping and deleting the job.

  • :timeout (Time) —

    The time to wait for the job to be deleted. Server default: 1m.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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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].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Delete a datafeed.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String) —

    A numerical character string that uniquely identifies the datafeed. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters. (Required)

  • :force (Boolean) —

    Use to forcefully delete a started datafeed; this method is quicker than stopping and deleting the datafeed.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:datafeed_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Delete expired ML data. Delete all job results, model snapshots and forecast data that have exceeded their retention days period. Machine learning state documents that are not associated with any job are also deleted. You can limit the request to a single or set of anomaly detection jobs by using a job identifier, a group name, a comma-separated list of jobs, or a wildcard expression. You can delete expired data for all anomaly detection jobs by using _all, by specifying * as the <job_id>, or by omitting the <job_id>.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for an anomaly detection job. It can be a job identifier, a group name, or a wildcard expression.

  • :requests_per_second (Float) —

    The desired requests per second for the deletion processes. The default behavior is no throttling.

  • :timeout (Time) —

    How long can the underlying delete processes run until they are canceled. Server default: 8h.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/delete_expired_data.rb', line 45

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Delete a filter. If an anomaly detection job references the filter, you cannot delete the filter. You must update or delete the job before you can delete the filter.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :filter_id (String) —

    A string that uniquely identifies a filter. (Required)

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:filter_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Delete forecasts from a job. By default, forecasts are retained for 14 days. You can specify a different retention period with the expires_in parameter in the forecast jobs API. The delete forecast API enables you to delete one or more forecasts before they expire.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. (Required)

  • :forecast_id (String) —

    A comma-separated list of forecast identifiers. If you do not specify this optional parameter or if you specify _all or * the API deletes all forecasts from the job.

  • :allow_no_forecasts (Boolean) —

    Specifies whether an error occurs when there are no forecasts. In particular, if this parameter is set to false and there are no forecasts associated with the job, attempts to delete all forecasts return an error. Server default: true.

  • :timeout (Time) —

    Specifies the period of time to wait for the completion of the delete operation. When this period of time elapses, the API fails and returns an error. Server default: 30s.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/delete_forecast.rb', line 46

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

  defined_params = [:job_id, :forecast_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Delete an anomaly detection job. All job configuration, model state and results are deleted. It is not currently possible to delete multiple jobs using wildcards or a comma separated list. If you delete a job that has a datafeed, the request first tries to delete the datafeed. This behavior is equivalent to calling the delete datafeed API with the same timeout and force parameters as the delete job request.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. (Required)

  • :force (Boolean) —

    Use to forcefully delete an opened job; this method is quicker than closing and deleting the job.

  • :delete_user_annotations (Boolean) —

    Specifies whether annotations that have been added by the user should be deleted along with any auto-generated annotations when the job is reset.

  • :wait_for_completion (Boolean) —

    Specifies whether the request should return immediately or wait until the job deletion completes. Server default: true.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/delete_job.rb', line 45

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Delete a model snapshot. You cannot delete the active model snapshot. To delete that snapshot, first revert to a different one. To identify the active model snapshot, refer to the model_snapshot_id in the results from the get jobs API.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. (Required)

  • :snapshot_id (String) —

    Identifier for the model snapshot. (Required)

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:job_id, :snapshot_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Delete an unreferenced trained model. The request deletes a trained inference model that is not referenced by an ingest pipeline.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The unique identifier of the trained model. (Required)

  • :force (Boolean) —

    Forcefully deletes a trained model that is referenced by ingest pipelines or has a started deployment.

  • :timeout (Time) —

    Period to wait for a response. If no response is received before the timeout expires, the request fails and returns an error. Server default: 30s.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:model_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Delete a trained model alias. This API deletes an existing model alias that refers to a trained model. If the model alias is missing or refers to a model other than the one identified by the model_id, this API returns an error.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :model_alias (String) —

    The model alias to delete. (Required)

  • :model_id (String) —

    The trained model ID to which the model alias refers. (Required)

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:model_id, :model_alias].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Estimate job model memory usage. Make an estimation of the memory usage for an anomaly detection job model. The estimate is based on analysis configuration details for the job and cardinality estimates for the fields it references.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

Evaluate data frame analytics. The API packages together commonly used evaluation metrics for various types of machine learning features. This has been designed for use on indexes created by data frame analytics. Evaluation requires both a ground truth field and an analytics result field to be present.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

Explain data frame analytics config. This API provides explanations for a data frame analytics config that either exists already or one that has not been created yet. The following explanations are provided:

  • which fields are included or not in the analysis and why,

  • how much memory is estimated to be required. The estimate can be used when deciding the appropriate value for model_memory_limit setting later on.

If you have object fields or fields that are excluded via source filtering, they are not included in the explanation.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    Identifier for the data frame analytics job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

See Also:



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

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

  defined_params = [:id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Force buffered data to be processed. The flush jobs API is only applicable when sending data for analysis using the post data API. Depending on the content of the buffer, then it might additionally calculate new results. Both flush and close operations are similar, however the flush is more efficient if you are expecting to send more data for analysis. When flushing, the job remains open and is available to continue analyzing data. A close operation additionally prunes and persists the model state to disk and the job must be opened again before analyzing further data.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. (Required)

  • :advance_time (String, Time) —

    Specifies to advance to a particular time value. Results are generated and the model is updated for data from the specified time interval.

  • :calc_interim (Boolean) —

    If true, calculates the interim results for the most recent bucket or all buckets within the latency period.

  • :end (String, Time) —

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

  • :skip_time (String, Time) —

    Specifies to skip to a particular time value. Results are not generated and the model is not updated for data from the specified time interval.

  • :start (String, Time) —

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

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/flush_job.rb', line 51

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Predict future behavior of a time series. Forecasts are not supported for jobs that perform population analysis; an error occurs if you try to create a forecast for a job that has an over_field_name in its configuration. Forcasts predict future behavior based on historical data.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. The job must be open when you create a forecast; otherwise, an error occurs. (Required)

  • :duration (Time) —

    A period of time that indicates how far into the future to forecast. For example, 30d corresponds to 30 days. The forecast starts at the last record that was processed. Server default: 1d.

  • :expires_in (Time) —

    The period of time that forecast results are retained. After a forecast expires, the results are deleted. If set to a value of 0, the forecast is never automatically deleted. Server default: 14d.

  • :max_model_memory (String) —

    The maximum memory the forecast can use. If the forecast needs to use more than the provided amount, it will spool to disk. Default is 20mb, maximum is 500mb and minimum is 1mb. If set to 40% or more of the job’s configured memory limit, it is automatically reduced to below that amount. Server default: 20mb.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/forecast.rb', line 49

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get anomaly detection job results for buckets. The API presents a chronological view of the records, grouped by bucket.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. (Required)

  • :timestamp (String, Time) —

    The timestamp of a single bucket result. If you do not specify this parameter, the API returns information about all buckets.

  • :anomaly_score (Float) —

    Returns buckets with anomaly scores greater or equal than this value. Server default: 0.

  • :desc (Boolean) —

    If true, the buckets are sorted in descending order.

  • :end (String, Time) —

    Returns buckets with timestamps earlier than this time. -1 means it is unset and results are not limited to specific timestamps. Server default: -1.

  • :exclude_interim (Boolean) —

    If true, the output excludes interim results.

  • :expand (Boolean) —

    If true, the output includes anomaly records.

  • :from (Integer) —

    Skips the specified number of buckets. Server default: 0.

  • :size (Integer) —

    Specifies the maximum number of buckets to obtain. Server default: 100.

  • :sort (String) —

    Specifies the sort field for the requested buckets. Server default: timestamp.

  • :start (String, Time) —

    Returns buckets with timestamps after this time. -1 means it is unset and results are not limited to specific timestamps. Server default: -1.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/get_buckets.rb', line 47

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

  defined_params = [:job_id, :timestamp].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get info about events in calendars.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    A string that uniquely identifies a calendar. You can get information for multiple calendars by using a comma-separated list of ids or a wildcard expression. You can get information for all calendars by using _all or * or by omitting the calendar identifier. (Required)

  • :end (String, Time) —

    Specifies to get events with timestamps earlier than this time.

  • :from (Integer) —

    Skips the specified number of events. Server default: 0.

  • :job_id (String) —

    Specifies to get events for a specific anomaly detection job identifier or job group. It must be used with a calendar identifier of _all or *.

  • :size (Integer) —

    Specifies the maximum number of events to obtain. Server default: 100.

  • :start (String, Time) —

    Specifies to get events with timestamps after this time.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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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].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get calendar configuration info.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    A string that uniquely identifies a calendar. You can get information for multiple calendars by using a comma-separated list of ids or a wildcard expression. You can get information for all calendars by using _all or * or by omitting the calendar identifier.

  • :from (Integer) —

    Skips the specified number of calendars. This parameter is supported only when you omit the calendar identifier. Server default: 0.

  • :size (Integer) —

    Specifies the maximum number of calendars to obtain. This parameter is supported only when you omit the calendar identifier. Server default: 10000.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

See Also:



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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].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get anomaly detection job results for categories.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. (Required)

  • :category_id (String) —

    Identifier for the category, which is unique in the job. If you specify neither the category ID nor the partition_field_value, the API returns information about all categories. If you specify only the partition_field_value, it returns information about all categories for the specified partition.

  • :from (Integer) —

    Skips the specified number of categories. Server default: 0.

  • :partition_field_value (String) —

    Only return categories for the specified partition.

  • :size (Integer) —

    Specifies the maximum number of categories to obtain. Server default: 100.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:job_id, :category_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get data frame analytics job configuration info. You can get information for multiple data frame analytics jobs in a single API request by using a comma-separated list of data frame analytics jobs or a wildcard expression.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    Identifier for the data frame analytics job. If you do not specify this option, the API returns information for the first hundred data frame analytics jobs.

  • :allow_no_match (Boolean) —

    Specifies what to do when the request:

    • Contains wildcard expressions and there are no data frame analytics

    jobs that match.

    • Contains the _all string or no identifiers and there are no matches.

    • Contains wildcard expressions and there are only partial matches.

    The default value returns an empty data_frame_analytics array when there are no matches and the subset of results when there are partial matches. If this parameter is false, the request returns a 404 status code when there are no matches or only partial matches. Server default: true.

  • :from (Integer) —

    Skips the specified number of data frame analytics jobs. Server default: 0.

  • :size (Integer) —

    Specifies the maximum number of data frame analytics jobs to obtain. Server default: 100.

  • :exclude_generated (Boolean) —

    Indicates if certain fields should be removed from the configuration on retrieval. This allows the configuration to be in an acceptable format to be retrieved and then added to another cluster.

  • :headers (Hash) —

    Custom HTTP headers

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/get_data_frame_analytics.rb', line 51

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

  defined_params = [:id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get data frame analytics job stats.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    Identifier for the data frame analytics job. If you do not specify this option, the API returns information for the first hundred data frame analytics jobs.

  • :allow_no_match (Boolean) —

    Specifies what to do when the request:

    • Contains wildcard expressions and there are no data frame analytics

    jobs that match.

    • Contains the _all string or no identifiers and there are no matches.

    • Contains wildcard expressions and there are only partial matches.

    The default value returns an empty data_frame_analytics array when there are no matches and the subset of results when there are partial matches. If this parameter is false, the request returns a 404 status code when there are no matches or only partial matches. Server default: true.

  • :from (Integer) —

    Skips the specified number of data frame analytics jobs. Server default: 0.

  • :size (Integer) —

    Specifies the maximum number of data frame analytics jobs to obtain. Server default: 100.

  • :verbose (Boolean) —

    Defines whether the stats response should be verbose.

  • :headers (Hash) —

    Custom HTTP headers

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/get_data_frame_analytics_stats.rb', line 46

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

  defined_params = [:id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get datafeed stats. You can get statistics for multiple datafeeds in a single API request by using a comma-separated list of datafeeds or a wildcard expression. You can get statistics for all datafeeds by using _all, by specifying * as the <feed_id>, or by omitting the <feed_id>. If the datafeed is stopped, the only information you receive is the datafeed_id and the state. This API returns a maximum of 10,000 datafeeds.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String, Array) —

    Identifier for the datafeed. It can be a datafeed identifier or a wildcard expression. If you do not specify one of these options, the API returns information about all datafeeds.

  • :allow_no_match (Boolean) —

    Specifies what to do when the request:

    • Contains wildcard expressions and there are no datafeeds that match.

    • Contains the _all string or no identifiers and there are no matches.

    • Contains wildcard expressions and there are only partial matches.

    The default value is true, which returns an empty datafeeds array when there are no matches and the subset of results when there are partial matches. If this parameter is false, the request returns a 404 status code when there are no matches or only partial matches.

  • :headers (Hash) —

    Custom HTTP headers

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/get_datafeed_stats.rb', line 48

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

  defined_params = [:datafeed_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get datafeeds configuration info. You can get information for multiple datafeeds in a single API request by using a comma-separated list of datafeeds or a wildcard expression. You can get information for all datafeeds by using _all, by specifying * as the <feed_id>, or by omitting the <feed_id>. This API returns a maximum of 10,000 datafeeds.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String, Array) —

    Identifier for the datafeed. It can be a datafeed identifier or a wildcard expression. If you do not specify one of these options, the API returns information about all datafeeds.

  • :allow_no_match (Boolean) —

    Specifies what to do when the request:

    • Contains wildcard expressions and there are no datafeeds that match.

    • Contains the _all string or no identifiers and there are no matches.

    • Contains wildcard expressions and there are only partial matches.

    The default value is true, which returns an empty datafeeds array when there are no matches and the subset of results when there are partial matches. If this parameter is false, the request returns a 404 status code when there are no matches or only partial matches.

  • :exclude_generated (Boolean) —

    Indicates if certain fields should be removed from the configuration on retrieval. This allows the configuration to be in an acceptable format to be retrieved and then added to another cluster.

  • :headers (Hash) —

    Custom HTTP headers

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/get_datafeeds.rb', line 50

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

  defined_params = [:datafeed_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get filters. You can get a single filter or all filters.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :filter_id (String, Array) —

    A string that uniquely identifies a filter.

  • :from (Integer) —

    Skips the specified number of filters. Server default: 0.

  • :size (Integer) —

    Specifies the maximum number of filters to obtain. Server default: 100.

  • :headers (Hash) —

    Custom HTTP headers

See Also:



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

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

  defined_params = [:filter_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get anomaly detection job results for influencers. Influencers are the entities that have contributed to, or are to blame for, the anomalies. Influencer results are available only if an influencer_field_name is specified in the job configuration.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. (Required)

  • :desc (Boolean) —

    If true, the results are sorted in descending order.

  • :end (String, Time) —

    Returns influencers with timestamps earlier than this time. The default value means it is unset and results are not limited to specific timestamps. Server default: -1.

  • :exclude_interim (Boolean) —

    If true, the output excludes interim results. By default, interim results are included.

  • :influencer_score (Float) —

    Returns influencers with anomaly scores greater than or equal to this value. Server default: 0.

  • :from (Integer) —

    Skips the specified number of influencers. Server default: 0.

  • :size (Integer) —

    Specifies the maximum number of influencers to obtain. Server default: 100.

  • :sort (String) —

    Specifies the sort field for the requested influencers. By default, the influencers are sorted by the influencer_score value.

  • :start (String, Time) —

    Returns influencers with timestamps after this time. The default value means it is unset and results are not limited to specific timestamps. Server default: -1.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/get_influencers.rb', line 50

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get anomaly detection job stats.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. It can be a job identifier, a group name, a comma-separated list of jobs, or a wildcard expression. If you do not specify one of these options, the API returns information for all anomaly detection jobs.

  • :allow_no_match (Boolean) —

    Specifies what to do when the request:

    • Contains wildcard expressions and there are no jobs that match.

    • Contains the _all string or no identifiers and there are no matches.

    • Contains wildcard expressions and there are only partial matches.

    If true, the API returns an empty jobs array when there are no matches and the subset of results when there are partial matches. If false, the API returns a 404 status code when there are no matches or only partial matches. Server default: true.

  • :headers (Hash) —

    Custom HTTP headers

See Also:



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

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get anomaly detection jobs configuration info. You can get information for multiple anomaly detection jobs in a single API request by using a group name, a comma-separated list of jobs, or a wildcard expression. You can get information for all anomaly detection jobs by using _all, by specifying * as the <job_id>, or by omitting the <job_id>.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String, Array) —

    Identifier for the anomaly detection job. It can be a job identifier, a group name, or a wildcard expression. If you do not specify one of these options, the API returns information for all anomaly detection jobs.

  • :allow_no_match (Boolean) —

    Specifies what to do when the request:

    • Contains wildcard expressions and there are no jobs that match.

    • Contains the _all string or no identifiers and there are no matches.

    • Contains wildcard expressions and there are only partial matches.

    The default value is true, which returns an empty jobs array when there are no matches and the subset of results when there are partial matches. If this parameter is false, the request returns a 404 status code when there are no matches or only partial matches. Server default: true.

  • :exclude_generated (Boolean) —

    Indicates if certain fields should be removed from the configuration on retrieval. This allows the configuration to be in an acceptable format to be retrieved and then added to another cluster.

  • :headers (Hash) —

    Custom HTTP headers

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/get_jobs.rb', line 49

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get machine learning memory usage info. Get information about how machine learning jobs and trained models are using memory, on each node, both within the JVM heap, and natively, outside of the JVM.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :node_id (String) —

    The names of particular nodes in the cluster to target. For example, nodeId1,nodeId2 or ml:true

  • :master_timeout (Time) —

    Period to wait for a connection to the master node. If no response is received before the timeout expires, the request fails and returns an error. Server default: 30s.

  • :timeout (Time) —

    Period to wait for a response. If no response is received before the timeout expires, the request fails and returns an error. Server default: 30s.

  • :headers (Hash) —

    Custom HTTP headers

See Also:



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

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

  defined_params = [:node_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get anomaly detection job model snapshot upgrade usage info.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. (Required)

  • :snapshot_id (String) —

    A numerical character string that uniquely identifies the model snapshot. You can get information for multiple snapshots by using a comma-separated list or a wildcard expression. You can get all snapshots by using _all, by specifying * as the snapshot ID, or by omitting the snapshot ID. (Required)

  • :allow_no_match (Boolean) —

    Specifies what to do when the request:

    • Contains wildcard expressions and there are no jobs that match.

    • Contains the _all string or no identifiers and there are no matches.

    • Contains wildcard expressions and there are only partial matches.

    The default value is true, which returns an empty jobs array when there are no matches and the subset of results when there are partial matches. If this parameter is false, the request returns a 404 status code when there are no matches or only partial matches.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/get_model_snapshot_upgrade_stats.rb', line 42

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

  defined_params = [:job_id, :snapshot_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get model snapshots info.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. (Required)

  • :snapshot_id (String) —

    A numerical character string that uniquely identifies the model snapshot. You can get information for multiple snapshots by using a comma-separated list or a wildcard expression. You can get all snapshots by using _all, by specifying * as the snapshot ID, or by omitting the snapshot ID.

  • :desc (Boolean) —

    If true, the results are sorted in descending order.

  • :end (String, Time) —

    Returns snapshots with timestamps earlier than this time.

  • :from (Integer) —

    Skips the specified number of snapshots. Server default: 0.

  • :size (Integer) —

    Specifies the maximum number of snapshots to obtain. Server default: 100.

  • :sort (String) —

    Specifies the sort field for the requested snapshots. By default, the snapshots are sorted by their timestamp.

  • :start (String, Time) —

    Returns snapshots with timestamps after this time.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:job_id, :snapshot_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get overall bucket results. Retrievs overall bucket results that summarize the bucket results of multiple anomaly detection jobs. The overall_score is calculated by combining the scores of all the buckets within the overall bucket span. First, the maximum anomaly_score per anomaly detection job in the overall bucket is calculated. Then the top_n of those scores are averaged to result in the overall_score. This means that you can fine-tune the overall_score so that it is more or less sensitive to the number of jobs that detect an anomaly at the same time. For example, if you set top_n to 1, the overall_score is the maximum bucket score in the overall bucket. Alternatively, if you set top_n to the number of jobs, the overall_score is high only when all jobs detect anomalies in that overall bucket. If you set the bucket_span parameter (to a value greater than its default), the overall_score is the maximum overall_score of the overall buckets that have a span equal to the jobs’ largest bucket span.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. It can be a job identifier, a group name, a comma-separated list of jobs or groups, or a wildcard expression.You can summarize the bucket results for all anomaly detection jobs by using _all or by specifying * as the <job_id>. (Required)

  • :allow_no_match (Boolean) —

    Specifies what to do when the request:

    • Contains wildcard expressions and there are no jobs that match.

    • Contains the _all string or no identifiers and there are no matches.

    • Contains wildcard expressions and there are only partial matches.

    If true, the request returns an empty jobs array when there are no matches and the subset of results when there are partial matches. If this parameter is false, the request returns a 404 status code when there are no matches or only partial matches. Server default: true.

  • :bucket_span (Time) —

    The span of the overall buckets. Must be greater or equal to the largest bucket span of the specified anomaly detection jobs, which is the default value.By default, an overall bucket has a span equal to the largest bucket span of the specified anomaly detection jobs. To override that behavior, use the optional bucket_span parameter.

  • :end (String, Time) —

    Returns overall buckets with timestamps earlier than this time.

  • :exclude_interim (Boolean) —

    If true, the output excludes interim results.

  • :overall_score (Double, String) —

    Returns overall buckets with overall scores greater than or equal to this value.

  • :start (String, Time) —

    Returns overall buckets with timestamps after this time.

  • :top_n (Integer) —

    The number of top anomaly detection job bucket scores to be used in the overall_score calculation. Server default: 1.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/get_overall_buckets.rb', line 72

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get anomaly records for an anomaly detection job. Records contain the detailed analytical results. They describe the anomalous activity that has been identified in the input data based on the detector configuration. There can be many anomaly records depending on the characteristics and size of the input data. In practice, there are often too many to be able to manually process them. The machine learning features therefore perform a sophisticated aggregation of the anomaly records into buckets. The number of record results depends on the number of anomalies found in each bucket, which relates to the number of time series being modeled and the number of detectors.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. (Required)

  • :desc (Boolean) —

    If true, the results are sorted in descending order.

  • :end (String, Time) —

    Returns records with timestamps earlier than this time. The default value means results are not limited to specific timestamps. Server default: -1.

  • :exclude_interim (Boolean) —

    If true, the output excludes interim results.

  • :from (Integer) —

    Skips the specified number of records. Server default: 0.

  • :record_score (Float) —

    Returns records with anomaly scores greater or equal than this value. Server default: 0.

  • :size (Integer) —

    Specifies the maximum number of records to obtain. Server default: 100.

  • :sort (String) —

    Specifies the sort field for the requested records. Server default: record_score.

  • :start (String, Time) —

    Returns records with timestamps after this time. The default value means results are not limited to specific timestamps. Server default: -1.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/get_records.rb', line 53

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get trained model configuration info.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :model_id (String, Array) —

    The unique identifier of the trained model or a model alias.You can get information for multiple trained models in a single API request by using a comma-separated list of model IDs or a wildcard expression.

  • :allow_no_match (Boolean) —

    Specifies what to do when the request:

    • Contains wildcard expressions and there are no models that match.

    • Contains the _all string or no identifiers and there are no matches.

    • Contains wildcard expressions and there are only partial matches.

    If true, it returns an empty array when there are no matches and the subset of results when there are partial matches. Server default: true.

  • :decompress_definition (Boolean) —

    Specifies whether the included model definition should be returned as a JSON map (true) or in a custom compressed format (false). Server default: true.

  • :exclude_generated (Boolean) —

    Indicates if certain fields should be removed from the configuration on retrieval. This allows the configuration to be in an acceptable format to be retrieved and then added to another cluster.

  • :from (Integer) —

    Skips the specified number of models. Server default: 0.

  • :include (String) —

    A comma delimited string of optional fields to include in the response body.

  • :size (Integer) —

    Specifies the maximum number of models to obtain. Server default: 100.

  • :tags (String) —

    A comma delimited string of tags. A trained model can have many tags, or none. When supplied, only trained models that contain all the supplied tags are returned.

  • :headers (Hash) —

    Custom HTTP headers

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/get_trained_models.rb', line 52

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

  defined_params = [:model_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Get trained models usage info. You can get usage information for multiple trained models in a single API request by using a comma-separated list of model IDs or a wildcard expression.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :model_id (String, Array) —

    The unique identifier of the trained model or a model alias. It can be a comma-separated list or a wildcard expression.

  • :allow_no_match (Boolean) —

    Specifies what to do when the request:

    • Contains wildcard expressions and there are no models that match.

    • Contains the _all string or no identifiers and there are no matches.

    • Contains wildcard expressions and there are only partial matches.

    If true, it returns an empty array when there are no matches and the subset of results when there are partial matches. Server default: true.

  • :from (Integer) —

    Skips the specified number of models. Server default: 0.

  • :size (Integer) —

    Specifies the maximum number of models to obtain. Server default: 100.

  • :headers (Hash) —

    Custom HTTP headers

See Also:



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

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

  defined_params = [:model_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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.

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. Server default: 10s.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:model_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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)}/_infer"
  params = Utils.process_params(arguments)

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

#info(arguments = {}) ⇒ Object

Get machine learning information. Get defaults and limits used by machine learning. This endpoint is designed to be used by a user interface that needs to fully understand machine learning configurations where some options are not specified, meaning that the defaults should be used. This endpoint may be used to find out what those defaults are. It also provides information about the maximum size of machine learning jobs that could run in the current cluster configuration.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :headers (Hash) —

    Custom HTTP headers

See Also:



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

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

Open anomaly detection jobs. An anomaly detection job must be opened to be ready to receive and analyze data. It can be opened and closed multiple times throughout its lifecycle. When you open a new job, it starts with an empty model. When you open an existing job, the most recent model state is automatically loaded. The job is ready to resume its analysis from where it left off, once new data is received.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. (Required)

  • :timeout (Time) —

    Controls the time to wait until a job has opened. Server default: 30m.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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 = Utils.process_params(arguments)

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

#post_calendar_events(arguments = {}) ⇒ Object

Add scheduled events to the calendar.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    A string that uniquely identifies a calendar. (Required)

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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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].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Send data to an anomaly detection job for analysis. IMPORTANT: For each job, data can be accepted from only a single connection at a time. It is not currently possible to post data to multiple jobs using wildcards or a comma-separated list.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. The job must have a state of open to receive and process the data. (Required)

  • :reset_end (String, Time) —

    Specifies the end of the bucket resetting range.

  • :reset_start (String, Time) —

    Specifies the start of the bucket resetting range.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    data

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Preview features used by data frame analytics. Preview the extracted features used by a data frame analytics config.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    Identifier for the data frame analytics job.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

See Also:



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

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

  defined_params = [:id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Preview a datafeed. This API returns the first “page” of search results from a datafeed. You can preview an existing datafeed or provide configuration details for a datafeed and anomaly detection job in the API. The preview shows the structure of the data that will be passed to the anomaly detection engine. IMPORTANT: When Elasticsearch security features are enabled, the preview uses the credentials of the user that called the API. However, when the datafeed starts it uses the roles of the last user that created or updated the datafeed. To get a preview that accurately reflects the behavior of the datafeed, use the appropriate credentials. You can also use secondary authorization headers to supply the credentials.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String) —

    A numerical character string that uniquely identifies the datafeed. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters. NOTE: If you use this path parameter, you cannot provide datafeed or anomaly detection job configuration details in the request body.

  • :start (String, Time) —

    The start time from where the datafeed preview should begin

  • :end (String, Time) —

    The end time when the datafeed preview should stop

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/preview_datafeed.rb', line 46

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

  defined_params = [:datafeed_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Create a calendar.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    A string that uniquely identifies a calendar. (Required)

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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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].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Add anomaly detection job to calendar.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :calendar_id (String) —

    A string that uniquely identifies a calendar. (Required)

  • :job_id (String, Array) —

    An identifier for the anomaly detection jobs. It can be a job identifier, a group name, or a comma-separated list of jobs or groups. (Required)

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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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].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Create a data frame analytics job. This API creates a data frame analytics job that performs an analysis on the source indices and stores the outcome in a destination index. By default, the query used in the source configuration is {“match_all”: {}}. If the destination index does not exist, it is created automatically when you start the job. If you supply only a subset of the regression or classification parameters, hyperparameter optimization occurs. It determines a value for each of the undefined parameters.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    Identifier for the data frame analytics job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters. (Required)

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Create a datafeed. Datafeeds retrieve data from Elasticsearch for analysis by an anomaly detection job. You can associate only one datafeed with each anomaly detection job. The datafeed contains a query that runs at a defined interval (frequency). If you are concerned about delayed data, you can add a delay (+query_delay’) at each interval. By default, the datafeed uses the following query:+{“boost”: 1}+. When Elasticsearch security features are enabled, your datafeed remembers which roles the user who created it had at the time of creation and runs the query using those same roles. If you provide secondary authorization headers, those credentials are used instead. You must use Kibana, this API, or the create anomaly detection jobs API to create a datafeed. Do not add a datafeed directly to the+.ml-config+index. Do not give users+write+privileges on the+.ml-config` index.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String) —

    A numerical character string that uniquely identifies the datafeed. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters. (Required)

  • :allow_no_indices (Boolean) —

    If true, wildcard indices expressions that resolve into no concrete indices are ignored. This includes the _all string or when no indices are specified. Server default: true.

  • :expand_wildcards (String, Array<String>) —

    Type of index that wildcard patterns can match. If the request can target data streams, this argument determines whether wildcard expressions match hidden data streams. Supports comma-separated values. Server default: open.

  • :ignore_throttled (Boolean) —

    If true, concrete, expanded, or aliased indices are ignored when frozen. Server default: true.

  • :ignore_unavailable (Boolean) —

    If true, unavailable indices (missing or closed) are ignored.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/put_datafeed.rb', line 51

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

  defined_params = [:datafeed_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Create a filter. A filter contains a list of strings. It can be used by one or more anomaly detection jobs. Specifically, filters are referenced in the custom_rules property of detector configuration objects.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :filter_id (String) —

    A string that uniquely identifies a filter. (Required)

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:filter_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Create an anomaly detection job. If you include a datafeed_config, you must have read index privileges on the source index. If you include a datafeed_config but do not provide a query, the datafeed uses {“match_all”: {“boost”: 1}}.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The identifier for the anomaly detection job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters. (Required)

  • :allow_no_indices (Boolean) —

    If true, wildcard indices expressions that resolve into no concrete indices are ignored. This includes the _all string or when no indices are specified. Server default: true.

  • :expand_wildcards (String, Array<String>) —

    Type of index that wildcard patterns can match. If the request can target data streams, this argument determines whether wildcard expressions match hidden data streams. Supports comma-separated values. Valid values are:

    • all: Match any data stream or index, including hidden ones.

    • closed: Match closed, non-hidden indices. Also matches any non-hidden data stream. Data streams cannot be closed.

    • hidden: Match hidden data streams and hidden indices. Must be combined with open, closed, or both.

    • none: Wildcard patterns are not accepted.

    • open: Match open, non-hidden indices. Also matches any non-hidden data stream. Server default: open.

  • :ignore_throttled (Boolean) —

    If true, concrete, expanded or aliased indices are ignored when frozen. Server default: true.

  • :ignore_unavailable (Boolean) —

    If true, unavailable indices (missing or closed) are ignored.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/put_job.rb', line 46

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Create a trained model. Enable you to supply a trained model that is not created by data frame analytics.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The unique identifier of the trained model. (Required)

  • :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.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:model_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Create or update a trained model alias. A trained model alias is a logical name used to reference a single trained model. You can use aliases instead of trained model identifiers to make it easier to reference your models. For example, you can use aliases in inference aggregations and processors. An alias must be unique and refer to only a single trained model. However, you can have multiple aliases for each trained model. If you use this API to update an alias such that it references a different trained model ID and the model uses a different type of data frame analytics, an error occurs. For example, this situation occurs if you have a trained model for regression analysis and a trained model for classification analysis; you cannot reassign an alias from one type of trained model to another. If you use this API to update an alias and there are very few input fields in common between the old and new trained models for the model alias, the API returns a warning.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :model_alias (String) —

    The alias to create or update. This value cannot end in numbers. (Required)

  • :model_id (String) —

    The identifier for the trained model that the alias refers to. (Required)

  • :reassign (Boolean) —

    Specifies whether the alias gets reassigned to the specified trained model if it is already assigned to a different model. If the alias is already assigned and this parameter is false, the API returns an error.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/put_trained_model_alias.rb', line 52

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

  defined_params = [:model_id, :model_alias].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Create part of a trained model definition.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The unique identifier of the trained model. (Required)

  • :part (Integer) —

    The definition part number. When the definition is loaded for inference the definition parts are streamed in the order of their part number. The first part must be 0 and the final part must be total_parts - 1. (Required)

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:model_id, :part].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Create a trained model vocabulary. This API is supported only for natural language processing (NLP) models. The vocabulary is stored in the index as described in inference_config.*.vocabulary of the trained model definition.

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

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:model_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Reset an anomaly detection job. All model state and results are deleted. The job is ready to start over as if it had just been created. It is not currently possible to reset multiple jobs using wildcards or a comma separated list.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job to reset. (Required)

  • :wait_for_completion (Boolean) —

    Should this request wait until the operation has completed before returning. Server default: true.

  • :delete_user_annotations (Boolean) —

    Specifies whether annotations that have been added by the user should be deleted along with any auto-generated annotations when the job is reset.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Revert to a snapshot. The machine learning features react quickly to anomalous input, learning new behaviors in data. Highly anomalous input increases the variance in the models whilst the system learns whether this is a new step-change in behavior or a one-off event. In the case where this anomalous input is known to be a one-off, then it might be appropriate to reset the model state to a time before this event. For example, you might consider reverting to a saved snapshot after Black Friday or a critical system failure.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. (Required)

  • :snapshot_id (String) —

    You can specify empty as the <snapshot_id>. Reverting to the empty snapshot means the anomaly detection job starts learning a new model from scratch when it is started. (Required)

  • :delete_intervening_results (Boolean) —

    If true, deletes the results in the time period between the latest results and the time of the reverted snapshot. It also resets the model to accept records for this time period. If you choose not to delete intervening results when reverting a snapshot, the job will not accept input data that is older than the current time. If you want to resend data, then delete the intervening results.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/revert_model_snapshot.rb', line 49

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

  defined_params = [:job_id, :snapshot_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Set upgrade_mode for ML indices. Sets a cluster wide upgrade_mode setting that prepares machine learning indices for an upgrade. When upgrading your cluster, in some circumstances you must restart your nodes and reindex your machine learning indices. In those circumstances, there must be no machine learning jobs running. You can close the machine learning jobs, do the upgrade, then open all the jobs again. Alternatively, you can use this API to temporarily halt tasks associated with the jobs and datafeeds and prevent new jobs from opening. You can also use this API during upgrades that do not require you to reindex your machine learning indices, though stopping jobs is not a requirement in that case. You can see the current value for the upgrade_mode setting by using the get machine learning info API.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :enabled (Boolean) —

    When true, it enables upgrade_mode which temporarily halts all job and datafeed tasks and prohibits new job and datafeed tasks from starting.

  • :timeout (Time) —

    The time to wait for the request to be completed. Server default: 30s.

  • :headers (Hash) —

    Custom HTTP headers

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/set_upgrade_mode.rb', line 47

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

Start a data frame analytics job. A data frame analytics job can be started and stopped multiple times throughout its lifecycle. If the destination index does not exist, it is created automatically the first time you start the data frame analytics job. The index.number_of_shards and index.number_of_replicas settings for the destination index are copied from the source index. If there are multiple source indices, the destination index copies the highest setting values. The mappings for the destination index are also copied from the source indices. If there are any mapping conflicts, the job fails to start. If the destination index exists, it is used as is. You can therefore set up the destination index in advance with custom settings and mappings.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    Identifier for the data frame analytics job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters. (Required)

  • :timeout (Time) —

    Controls the amount of time to wait until the data frame analytics job starts. Server default: 20s.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/start_data_frame_analytics.rb', line 47

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

  defined_params = [:id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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_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

Start datafeeds. A datafeed must be started in order to retrieve data from Elasticsearch. A datafeed can be started and stopped multiple times throughout its lifecycle. Before you can start a datafeed, the anomaly detection job must be open. Otherwise, an error occurs. If you restart a stopped datafeed, it continues processing input data from the next millisecond after it was stopped. If new data was indexed for that exact millisecond between stopping and starting, it will be ignored. When Elasticsearch security features are enabled, your datafeed remembers which roles the last user to create or update it had at the time of creation or update and runs the query using those same roles. If you provided secondary authorization headers when you created or updated the datafeed, those credentials are used instead.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String) —

    A numerical character string that uniquely identifies the datafeed. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters. (Required)

  • :end (String, Time) —

    The time that the datafeed should end, which can be specified by using one of the following formats:

    • ISO 8601 format with milliseconds, for example 2017-01-22T06:00:00.000Z

    • ISO 8601 format without milliseconds, for example 2017-01-22T06:00:0000:00+

    • Milliseconds since the epoch, for example 1485061200000

    Date-time arguments using either of the ISO 8601 formats must have a time zone designator, where Z is accepted as an abbreviation for UTC time. When a URL is expected (for example, in browsers), the +++ used in time zone designators must be encoded as %2B. The end time value is exclusive. If you do not specify an end time, the datafeed runs continuously.

  • :start (String, Time) —

    The time that the datafeed should begin, which can be specified by using the same formats as the end parameter. This value is inclusive. If you do not specify a start time and the datafeed is associated with a new anomaly detection job, the analysis starts from the earliest time for which data is available. If you restart a stopped datafeed and specify a start value that is earlier than the timestamp of the latest processed record, the datafeed continues from 1 millisecond after the timestamp of the latest processed record.

  • :timeout (Time) —

    Specifies the amount of time to wait until a datafeed starts. Server default: 20s.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/start_datafeed.rb', line 59

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

  defined_params = [:datafeed_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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. It allocates the model to every machine learning node.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :model_id (String) —

    The unique identifier of the trained model. Currently, only PyTorch models are supported. (Required)

  • :cache_size (Integer, String) —

    The inference cache size (in memory outside the JVM heap) per node for the model. The default value is the same size as the model_size_bytes. To disable the cache, 0b can be provided.

  • :deployment_id (String) —

    A unique identifier for the deployment of the model.

  • :number_of_allocations (Integer) —

    The number of model allocations on each node where the model is deployed. All allocations on a node share the same copy of the model in memory but use a separate set of threads to evaluate the model. Increasing this value generally increases the throughput. If this setting is greater than the number of hardware threads it will automatically be changed to a value less than the number of hardware threads. If adaptive_allocations is enabled, do not set this value, because it’s automatically set. Server default: 1.

  • :priority (String) —

    The deployment priority.

  • :queue_capacity (Integer) —

    Specifies the number of inference requests that are allowed in the queue. After the number of requests exceeds this value, new requests are rejected with a 429 error. Server default: 1024.

  • :threads_per_allocation (Integer) —

    Sets the number of threads used by each model allocation during inference. This generally increases the inference speed. The inference process is a compute-bound process; any number greater than the number of available hardware threads on the machine does not increase the inference speed. If this setting is greater than the number of hardware threads it will automatically be changed to a value less than the number of hardware threads. Server default: 1.

  • :timeout (Time) —

    Specifies the amount of time to wait for the model to deploy. Server default: 20s.

  • :wait_for (String) —

    Specifies the allocation status to wait for before returning. Server default: started.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/start_trained_model_deployment.rb', line 55

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

  defined_params = [:model_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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/_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

Stop data frame analytics jobs. A data frame analytics job can be started and stopped multiple times throughout its lifecycle.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    Identifier for the data frame analytics job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters. (Required)

  • :allow_no_match (Boolean) —

    Specifies what to do when the request:

    • Contains wildcard expressions and there are no data frame analytics

    jobs that match.

    • Contains the _all string or no identifiers and there are no matches.

    • Contains wildcard expressions and there are only partial matches.

    The default value is true, which returns an empty data_frame_analytics array when there are no matches and the subset of results when there are partial matches. If this parameter is false, the request returns a 404 status code when there are no matches or only partial matches. Server default: true.

  • :force (Boolean) —

    If true, the data frame analytics job is stopped forcefully.

  • :timeout (Time) —

    Controls the amount of time to wait until the data frame analytics job stops. Defaults to 20 seconds. Server default: 20s.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/stop_data_frame_analytics.rb', line 48

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

  defined_params = [:id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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_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

Stop datafeeds. A datafeed that is stopped ceases to retrieve data from Elasticsearch. A datafeed can be started and stopped multiple times throughout its lifecycle.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String) —

    Identifier for the datafeed. You can stop multiple datafeeds in a single API request by using a comma-separated list of datafeeds or a wildcard expression. You can close all datafeeds by using _all or by specifying * as the identifier. (Required)

  • :allow_no_match (Boolean) —

    Specifies what to do when the request:

    • Contains wildcard expressions and there are no datafeeds that match.

    • Contains the _all string or no identifiers and there are no matches.

    • Contains wildcard expressions and there are only partial matches.

    If true, the API returns an empty datafeeds array when there are no matches and the subset of results when there are partial matches. If false, the API returns a 404 status code when there are no matches or only partial matches. Server default: true.

  • :force (Boolean) —

    If true, the datafeed is stopped forcefully.

  • :timeout (Time) —

    Specifies the amount of time to wait until a datafeed stops. Server default: 20s.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/stop_datafeed.rb', line 46

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

  defined_params = [:datafeed_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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) —

    Specifies what to do when the request: contains wildcard expressions and there are no deployments that match; contains the _all string or no identifiers and there are no matches; or contains wildcard expressions and there are only partial matches. By default, it returns an empty array when there are no matches and the subset of results when there are partial matches. If false, the request returns a 404 status code when there are no matches or only partial matches. Server default: true.

  • :force (Boolean) —

    Forcefully stops the deployment, even if it is used by ingest pipelines. You can’t use these pipelines until you restart the model deployment.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:model_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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/_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

Update a data frame analytics job.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :id (String) —

    Identifier for the data frame analytics job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters. (Required)

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Update a datafeed. You must stop and start the datafeed for the changes to be applied. When Elasticsearch security features are enabled, your datafeed remembers which roles the user who updated it had at the time of the update and runs the query using those same roles. If you provide secondary authorization headers, those credentials are used instead.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :datafeed_id (String) —

    A numerical character string that uniquely identifies the datafeed. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters. (Required)

  • :allow_no_indices (Boolean) —

    If true, wildcard indices expressions that resolve into no concrete indices are ignored. This includes the _all string or when no indices are specified. Server default: true.

  • :expand_wildcards (String, Array<String>) —

    Type of index that wildcard patterns can match. If the request can target data streams, this argument determines whether wildcard expressions match hidden data streams. Supports comma-separated values. Valid values are:

    • all: Match any data stream or index, including hidden ones.

    • closed: Match closed, non-hidden indices. Also matches any non-hidden data stream. Data streams cannot be closed.

    • hidden: Match hidden data streams and hidden indices. Must be combined with open, closed, or both.

    • none: Wildcard patterns are not accepted.

    • open: Match open, non-hidden indices. Also matches any non-hidden data stream. Server default: open.

  • :ignore_throttled (Boolean) —

    If true, concrete, expanded or aliased indices are ignored when frozen. Server default: true.

  • :ignore_unavailable (Boolean) —

    If true, unavailable indices (missing or closed) are ignored.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/update_datafeed.rb', line 50

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

  defined_params = [:datafeed_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

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

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :filter_id (String) —

    A string that uniquely identifies a filter. (Required)

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:filter_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Update an anomaly detection job. Updates certain properties of an anomaly detection job.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the job. (Required)

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:job_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Update a snapshot. Updates certain properties of a snapshot.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. (Required)

  • :snapshot_id (String) —

    Identifier for the model snapshot. (Required)

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:job_id, :snapshot_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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

Update 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. Currently, only PyTorch models are supported. (Required)

  • :number_of_allocations (Integer) —

    The number of model allocations on each node where the model is deployed. All allocations on a node share the same copy of the model in memory but use a separate set of threads to evaluate the model. Increasing this value generally increases the throughput. If this setting is greater than the number of hardware threads it will automatically be changed to a value less than the number of hardware threads. Server default: 1.

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    request body

Raises:

  • (ArgumentError)

See Also:



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

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

  defined_params = [:model_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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/_update"
  params = Utils.process_params(arguments)

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

#upgrade_job_snapshot(arguments = {}) ⇒ Object

Upgrade a snapshot. Upgrade an anomaly detection model snapshot to the latest major version. Over time, older snapshot formats are deprecated and removed. Anomaly detection jobs support only snapshots that are from the current or previous major version. This API provides a means to upgrade a snapshot to the current major version. This aids in preparing the cluster for an upgrade to the next major version. Only one snapshot per anomaly detection job can be upgraded at a time and the upgraded snapshot cannot be the current snapshot of the anomaly detection job.

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    Identifier for the anomaly detection job. (Required)

  • :snapshot_id (String) —

    A numerical character string that uniquely identifies the model snapshot. (Required)

  • :wait_for_completion (Boolean) —

    When true, the API won’t respond until the upgrade is complete. Otherwise, it responds as soon as the upgrade task is assigned to a node.

  • :timeout (Time) —

    Controls the time to wait for the request to complete. Server default: 30m.

  • :headers (Hash) —

    Custom HTTP headers

Raises:

  • (ArgumentError)

See Also:



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# File 'lib/elasticsearch/api/actions/machine_learning/upgrade_job_snapshot.rb', line 45

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

  defined_params = [:job_id, :snapshot_id].each_with_object({}) do |variable, set_variables|
    set_variables[variable] = arguments[variable] if arguments.key?(variable)
  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