Method: Elasticsearch::API::MachineLearning::Actions#forecast

Defined in:
lib/elasticsearch/api/actions/machine_learning/forecast.rb

#forecast(arguments = {}) ⇒ Object

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

Parameters:

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

    a customizable set of options

Options Hash (arguments):

  • :job_id (String) —

    The ID of the job to forecast for

  • :duration (Time) —

    The duration of the forecast

  • :expires_in (Time) —

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

  • :max_model_memory (String) —

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

  • :headers (Hash) —

    Custom HTTP headers

  • :body (Hash) —

    Query parameters can be specified in the body

Raises:

  • (ArgumentError)

See Also:


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

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

  defined_params = [:job_id].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