Sha256: 021df534f849b0e1c191a8d87fa4b87e58a61463e9cee81b83183456e638f7b2
Contents?: true
Size: 1.88 KB
Versions: 7
Compression:
Stored size: 1.88 KB
Contents
module Elasticsearch
module XPack
module API
module MachineLearning
module Actions
# Retrieve job results for one or more influencers
#
# @option arguments [String] :job_id [TODO] (*Required*)
# @option arguments [Hash] :body Influencer selection criteria
# @option arguments [Boolean] :exclude_interim Exclude interim results
# @option arguments [Int] :from skips a number of influencers
# @option arguments [Int] :size specifies a max number of influencers to get
# @option arguments [String] :start start timestamp for the requested influencers
# @option arguments [String] :end end timestamp for the requested influencers
# @option arguments [Double] :influencer_score influencer score threshold for the requested influencers
# @option arguments [String] :sort sort field for the requested influencers
# @option arguments [Boolean] :desc whether the results should be sorted in decending order
#
# @see http://www.elastic.co/guide/en/elasticsearch/reference/current/ml-get-influencer.html
#
def get_influencers(arguments={})
raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id]
valid_params = [
:exclude_interim,
:from,
:size,
:start,
:end,
:influencer_score,
:sort,
:desc ]
method = Elasticsearch::API::HTTP_GET
path = "_xpack/ml/anomaly_detectors/#{arguments[:job_id]}/results/influencers"
params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, valid_params
body = arguments[:body]
perform_request(method, path, params, body).body
end
end
end
end
end
end
Version data entries
7 entries across 7 versions & 1 rubygems