module Elasticsearch::API::MachineLearning::Actions
Public Instance Methods
Source
# 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
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.
@option arguments [String] :model_id The unique identifier of the trained model. (Required) @option arguments [Hash] :headers Custom HTTP headers
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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
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.
@option arguments [String] :job_id 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) @option arguments [Boolean] :allow_no_match 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.
@option arguments [Boolean] :force 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.
@option arguments [Time] :timeout Controls the time to wait until a job has closed. Server default: 30m. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-close-job
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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 a calendar. Remove all scheduled events from a calendar, then delete it.
@option arguments [String] :calendar_id A string that uniquely identifies a calendar. (Required) @option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-delete-calendar
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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 events from a calendar.
@option arguments [String] :calendar_id A string that uniquely identifies a calendar. (Required) @option arguments [String] :event_id Identifier for the scheduled event.
You can obtain this identifier by using the get calendar events API. (*Required*)
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-delete-calendar-event
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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 anomaly jobs from a calendar.
@option arguments [String] :calendar_id A string that uniquely identifies a calendar. (Required) @option arguments [String, Array] :job_id 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*)
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-delete-calendar-job
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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 a data frame analytics job.
@option arguments [String] :id Identifier for the data frame analytics job. (Required) @option arguments [Boolean] :force If true
, it deletes a job that is not stopped; this method is quicker than stopping and deleting the job. @option arguments [Time] :timeout The time to wait for the job to be deleted. Server default: 1m. @option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-delete-data-frame-analytics
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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 a datafeed.
@option arguments [String] :datafeed_id 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*)
@option arguments [Boolean] :force Use to forcefully delete a started datafeed; this method is quicker than
stopping and deleting the datafeed.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-delete-datafeed
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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 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>+.
@option arguments [String] :job_id Identifier for an anomaly detection job. It can be a job identifier, a
group name, or a wildcard expression.
@option arguments [Float] :requests_per_second The desired requests per second for the deletion processes. The default
behavior is no throttling.
@option arguments [Time] :timeout How long can the underlying delete processes run until they are canceled. Server default: 8h. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-delete-expired-data
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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 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.
@option arguments [String] :filter_id A string that uniquely identifies a filter. (Required) @option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-delete-filter
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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 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.
@option arguments [String] :job_id Identifier for the anomaly detection job. (Required) @option arguments [String] :forecast_id 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.
@option arguments [Boolean] :allow_no_forecasts 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.
@option arguments [Time] :timeout 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.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-delete-forecast
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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 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.
@option arguments [String] :job_id Identifier for the anomaly detection job. (Required) @option arguments [Boolean] :force Use to forcefully delete an opened job; this method is quicker than
closing and deleting the job.
@option arguments [Boolean] :delete_user_annotations Specifies whether annotations that have been added by the
user should be deleted along with any auto-generated annotations when the job is reset.
@option arguments [Boolean] :wait_for_completion Specifies whether the request should return immediately or wait until the
job deletion completes. Server default: true.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-delete-job
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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 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
.
@option arguments [String] :job_id Identifier for the anomaly detection job. (Required) @option arguments [String] :snapshot_id Identifier for the model snapshot. (Required) @option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-delete-model-snapshot
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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 an unreferenced trained model. The request deletes a trained inference model that is not referenced by an ingest pipeline.
@option arguments [String] :model_id The unique identifier of the trained model. (Required) @option arguments [Boolean] :force Forcefully deletes a trained model that is referenced by ingest pipelines or has a started deployment. @option arguments [Time] :timeout 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. @option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-delete-trained-model
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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
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.
@option arguments [String] :model_alias The model alias to delete. (Required) @option arguments [String] :model_id The trained model ID to which the model alias refers. (Required) @option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-delete-trained-model-alias
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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
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.
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-estimate-model-memory
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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
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.
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-evaluate-data-frame
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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
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.
@option arguments [String] :id 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.
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-explain-data-frame-analytics
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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
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.
@option arguments [String] :job_id Identifier for the anomaly detection job. (Required) @option arguments [String, Time] :advance_time Specifies to advance to a particular time value. Results are generated
and the model is updated for data from the specified time interval.
@option arguments [Boolean] :calc_interim If true, calculates the interim results for the most recent bucket or all
buckets within the latency period.
@option arguments [String, Time] :end When used in conjunction with calc_interim
and start
, specifies the
range of buckets on which to calculate interim results.
@option arguments [String, Time] :skip_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.
@option arguments [String, Time] :start When used in conjunction with calc_interim
, specifies the range of
buckets on which to calculate interim results.
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-flush-job
Source
# 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
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.
@option arguments [String] :job_id Identifier for the anomaly detection job. The job must be open when you
create a forecast; otherwise, an error occurs. (*Required*)
@option arguments [Time] :duration 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.
@option arguments [Time] :expires_in 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.
@option arguments [String] :max_model_memory 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.
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-forecast
Source
# 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 anomaly detection job results for buckets. The API
presents a chronological view of the records, grouped by bucket.
@option arguments [String] :job_id Identifier for the anomaly detection job. (Required) @option arguments [String, Time] :timestamp The timestamp of a single bucket result. If you do not specify this
parameter, the API returns information about all buckets.
@option arguments [Float] :anomaly_score Returns buckets with anomaly scores greater or equal than this value. Server default: 0. @option arguments [Boolean] :desc If true
, the buckets are sorted in descending order. @option arguments [String, Time] :end Returns buckets with timestamps earlier than this time. -1
means it is
unset and results are not limited to specific timestamps. Server default: -1.
@option arguments [Boolean] :exclude_interim If true
, the output excludes interim results. @option arguments [Boolean] :expand If true, the output includes anomaly records. @option arguments [Integer] :from Skips the specified number of buckets. Server default: 0. @option arguments [Integer] :size Specifies the maximum number of buckets to obtain. Server default: 100. @option arguments [String] :sort Specifies the sort field for the requested buckets. Server default: timestamp. @option arguments [String, Time] :start Returns buckets with timestamps after this time. -1
means it is unset
and results are not limited to specific timestamps. Server default: -1.
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-buckets
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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 info about events in calendars.
@option arguments [String] :calendar_id 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) @option arguments [String, Time] :end Specifies to get events with timestamps earlier than this time. @option arguments [Integer] :from Skips the specified number of events. Server default: 0. @option arguments [String] :job_id 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 +*+. @option arguments [Integer] :size Specifies the maximum number of events to obtain. Server default: 100. @option arguments [String, Time] :start Specifies to get events with timestamps after this time. @option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-calendar-events
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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 calendar configuration info.
@option arguments [String] :calendar_id 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. @option arguments [Integer] :from Skips the specified number of calendars. This parameter is supported only when you omit the calendar identifier. Server default: 0. @option arguments [Integer] :size Specifies the maximum number of calendars to obtain. This parameter is supported only when you omit the calendar identifier. Server default: 10000. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-calendars
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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 anomaly detection job results for categories.
@option arguments [String] :job_id Identifier for the anomaly detection job. (Required) @option arguments [String] :category_id 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.
@option arguments [Integer] :from Skips the specified number of categories. Server default: 0. @option arguments [String] :partition_field_value Only return categories for the specified partition. @option arguments [Integer] :size Specifies the maximum number of categories to obtain. Server default: 100. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-categories
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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 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.
@option arguments [String] :id 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.
@option arguments [Boolean] :allow_no_match 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.
@option arguments [Integer] :from Skips the specified number of data frame analytics jobs. Server default: 0. @option arguments [Integer] :size Specifies the maximum number of data frame analytics jobs to obtain. Server default: 100. @option arguments [Boolean] :exclude_generated 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.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-data-frame-analytics
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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 data frame analytics job stats.
@option arguments [String] :id 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.
@option arguments [Boolean] :allow_no_match 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.
@option arguments [Integer] :from Skips the specified number of data frame analytics jobs. Server default: 0. @option arguments [Integer] :size Specifies the maximum number of data frame analytics jobs to obtain. Server default: 100. @option arguments [Boolean] :verbose Defines whether the stats response should be verbose. @option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-data-frame-analytics-stats
Source
# 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 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.
@option arguments [String, Array] :datafeed_id 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.
@option arguments [Boolean] :allow_no_match 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.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-datafeed-stats
Source
# 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 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.
@option arguments [String, Array] :datafeed_id 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.
@option arguments [Boolean] :allow_no_match 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.
@option arguments [Boolean] :exclude_generated 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.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-datafeeds
Source
# 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 filters. You can get a single filter or all filters.
@option arguments [String, Array] :filter_id A string that uniquely identifies a filter. @option arguments [Integer] :from Skips the specified number of filters. Server default: 0. @option arguments [Integer] :size Specifies the maximum number of filters to obtain. Server default: 100. @option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-filters
Source
# 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 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.
@option arguments [String] :job_id Identifier for the anomaly detection job. (Required) @option arguments [Boolean] :desc If true, the results are sorted in descending order. @option arguments [String, Time] :end 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.
@option arguments [Boolean] :exclude_interim If true, the output excludes interim results. By default, interim results
are included.
@option arguments [Float] :influencer_score Returns influencers with anomaly scores greater than or equal to this
value. Server default: 0.
@option arguments [Integer] :from Skips the specified number of influencers. Server default: 0. @option arguments [Integer] :size Specifies the maximum number of influencers to obtain. Server default: 100. @option arguments [String] :sort Specifies the sort field for the requested influencers. By default, the
influencers are sorted by the +influencer_score+ value.
@option arguments [String, Time] :start 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.
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-influencers
Source
# 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 anomaly detection job stats.
@option arguments [String] :job_id 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.
@option arguments [Boolean] :allow_no_match 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.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-job-stats
Source
# 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 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>+.
@option arguments [String, Array] :job_id 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.
@option arguments [Boolean] :allow_no_match 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.
@option arguments [Boolean] :exclude_generated 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.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-jobs
Source
# 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 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.
@option arguments [String] :node_id The names of particular nodes in the cluster to target. For example, +nodeId1,nodeId2+ or
+ml:true+
@option arguments [Time] :master_timeout 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.
@option arguments [Time] :timeout 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.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-memory-stats
Source
# 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 anomaly detection job model snapshot upgrade usage info.
@option arguments [String] :job_id Identifier for the anomaly detection job. (Required) @option arguments [String] :snapshot_id 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*)
@option arguments [Boolean] :allow_no_match 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.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-model-snapshot-upgrade-stats
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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 model snapshots info.
@option arguments [String] :job_id Identifier for the anomaly detection job. (Required) @option arguments [String] :snapshot_id 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.
@option arguments [Boolean] :desc If true, the results are sorted in descending order. @option arguments [String, Time] :end Returns snapshots with timestamps earlier than this time. @option arguments [Integer] :from Skips the specified number of snapshots. Server default: 0. @option arguments [Integer] :size Specifies the maximum number of snapshots to obtain. Server default: 100. @option arguments [String] :sort Specifies the sort field for the requested snapshots. By default, the
snapshots are sorted by their timestamp.
@option arguments [String, Time] :start Returns snapshots with timestamps after this time. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-model-snapshots
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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 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.
@option arguments [String] :job_id 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*)
@option arguments [Boolean] :allow_no_match 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.
@option arguments [Time] :bucket_span 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.
@option arguments [String, Time] :end Returns overall buckets with timestamps earlier than this time. @option arguments [Boolean] :exclude_interim If true
, the output excludes interim results. @option arguments [Double, String] :overall_score Returns overall buckets with overall scores greater than or equal to this
value.
@option arguments [String, Time] :start Returns overall buckets with timestamps after this time. @option arguments [Integer] :top_n The number of top anomaly detection job bucket scores to be used in the
+overall_score+ calculation. Server default: 1.
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-overall-buckets
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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 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.
@option arguments [String] :job_id Identifier for the anomaly detection job. (Required) @option arguments [Boolean] :desc If true, the results are sorted in descending order. @option arguments [String, Time] :end Returns records with timestamps earlier than this time. The default value
means results are not limited to specific timestamps. Server default: -1.
@option arguments [Boolean] :exclude_interim If true
, the output excludes interim results. @option arguments [Integer] :from Skips the specified number of records. Server default: 0. @option arguments [Float] :record_score Returns records with anomaly scores greater or equal than this value. Server default: 0. @option arguments [Integer] :size Specifies the maximum number of records to obtain. Server default: 100. @option arguments [String] :sort Specifies the sort field for the requested records. Server default: record_score. @option arguments [String, Time] :start Returns records with timestamps after this time. The default value means
results are not limited to specific timestamps. Server default: -1.
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-records
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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 model configuration info.
@option arguments [String, Array] :model_id 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.
@option arguments [Boolean] :allow_no_match 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.
@option arguments [Boolean] :decompress_definition Specifies whether the included model definition should be returned as a
JSON map (true) or in a custom compressed format (false). Server default: true.
@option arguments [Boolean] :exclude_generated 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.
@option arguments [Integer] :from Skips the specified number of models. Server default: 0. @option arguments [String] :include A comma delimited string of optional fields to include in the response
body.
@option arguments [Integer] :size Specifies the maximum number of models to obtain. Server default: 100. @option arguments [String] :tags 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.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-trained-models
Source
# 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
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.
@option arguments [String, Array] :model_id The unique identifier of the trained model or a model alias. It can be a
comma-separated list or a wildcard expression.
@option arguments [Boolean] :allow_no_match 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.
@option arguments [Integer] :from Skips the specified number of models. Server default: 0. @option arguments [Integer] :size Specifies the maximum number of models to obtain. Server default: 100. @option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-get-trained-models-stats
Source
# 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
Evaluate a trained model.
@option arguments [String] :model_id The unique identifier of the trained model. (Required) @option arguments [Time] :timeout Controls the amount of time to wait for inference results. Server default: 10s. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-infer-trained-model
Source
# 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
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.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-info
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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
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.
@option arguments [String] :job_id Identifier for the anomaly detection job. (Required) @option arguments [Time] :timeout Controls the time to wait until a job has opened. Server default: 30m. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-open-job
Source
# 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
Add scheduled events to the calendar.
@option arguments [String] :calendar_id A string that uniquely identifies a calendar. (Required) @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-post-calendar-events
Source
# 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
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.
@option arguments [String] :job_id Identifier for the anomaly detection job. The job must have a state of open to receive and process the data. (Required) @option arguments [String, Time] :reset_end Specifies the end of the bucket resetting range. @option arguments [String, Time] :reset_start Specifies the start of the bucket resetting range. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body data
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-post-data
Source
# 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 features used by data frame analytics. Preview the extracted features used by a data frame analytics config.
@option arguments [String] :id Identifier for the data frame analytics job. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-preview-data-frame-analytics
Source
# 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
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.
@option arguments [String] :datafeed_id 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.
@option arguments [String, Time] :start The start time from where the datafeed preview should begin @option arguments [String, Time] :end The end time when the datafeed preview should stop @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-preview-datafeed
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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
Create a calendar.
@option arguments [String] :calendar_id A string that uniquely identifies a calendar. (Required) @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-put-calendar
Source
# 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
Add anomaly detection job to calendar.
@option arguments [String] :calendar_id A string that uniquely identifies a calendar. (Required) @option arguments [String, Array] :job_id 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) @option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-put-calendar-job
Source
# 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
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.
@option arguments [String] :id 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*)
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-put-data-frame-analytics
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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
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:+{“match_all”: {“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.
@option arguments [String] :datafeed_id 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*)
@option arguments [Boolean] :allow_no_indices 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.
@option arguments [String, Array<String>] :expand_wildcards 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.
@option arguments [Boolean] :ignore_throttled If true, concrete, expanded, or aliased indices are ignored when frozen. Server default: true. @option arguments [Boolean] :ignore_unavailable If true, unavailable indices (missing or closed) are ignored. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-put-datafeed
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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
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.
@option arguments [String] :filter_id A string that uniquely identifies a filter. (Required) @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-put-filter
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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
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}}+.
@option arguments [String] :job_id 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) @option arguments [Boolean] :allow_no_indices 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.
@option arguments [String, Array<String>] :expand_wildcards 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.
@option arguments [Boolean] :ignore_throttled If true
, concrete, expanded or aliased indices are ignored when frozen. Server default: true. @option arguments [Boolean] :ignore_unavailable If true
, unavailable indices (missing or closed) are ignored. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-put-job
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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
Create a trained model. Enable you to supply a trained model that is not created by data frame analytics.
@option arguments [String] :model_id The unique identifier of the trained model. (Required) @option arguments [Boolean] :defer_definition_decompression If set to true
and a compressed_definition
is provided,
the request defers definition decompression and skips relevant validations.
@option arguments [Boolean] :wait_for_completion Whether to wait for all child operations (e.g. model download)
to complete.
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-put-trained-model
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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
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.
@option arguments [String] :model_alias The alias to create or update. This value cannot end in numbers. (Required) @option arguments [String] :model_id The identifier for the trained model that the alias refers to. (Required) @option arguments [Boolean] :reassign 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.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-put-trained-model-alias
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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
Create part of a trained model definition.
@option arguments [String] :model_id The unique identifier of the trained model. (Required) @option arguments [Integer] :part 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*)
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
Source
# 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
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.
@option arguments [String] :model_id The unique identifier of the trained model. (Required) @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-put-trained-model-vocabulary
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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
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.
@option arguments [String] :job_id The ID of the job to reset. (Required) @option arguments [Boolean] :wait_for_completion Should this request wait until the operation has completed before
returning. Server default: true.
@option arguments [Boolean] :delete_user_annotations Specifies whether annotations that have been added by the
user should be deleted along with any auto-generated annotations when the job is reset.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-reset-job
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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
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.
@option arguments [String] :job_id Identifier for the anomaly detection job. (Required) @option arguments [String] :snapshot_id 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*)
@option arguments [Boolean] :delete_intervening_results 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.
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-revert-model-snapshot
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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
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
.
@option arguments [Boolean] :enabled When true
, it enables upgrade_mode
which temporarily halts all job
and datafeed tasks and prohibits new job and datafeed tasks from starting.
@option arguments [Time] :timeout The time to wait for the request to be completed. Server default: 30s. @option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-set-upgrade-mode
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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 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.
@option arguments [String] :id 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*)
@option arguments [Time] :timeout Controls the amount of time to wait until the data frame analytics job
starts. Server default: 20s.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-start-data-frame-analytics
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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 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.
@option arguments [String] :datafeed_id 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*)
@option arguments [String, Time] :end 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 +2017-01-22T06:00:00+00:00+ - 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.
@option arguments [String, Time] :start 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.
@option arguments [Time] :timeout Specifies the amount of time to wait until a datafeed starts. Server default: 20s. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-start-datafeed
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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
Start a trained model deployment. It allocates the model to every machine learning node.
@option arguments [String] :model_id The unique identifier of the trained model. Currently, only PyTorch models are supported. (Required) @option arguments [Integer, String] :cache_size 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.
@option arguments [String] :deployment_id A unique identifier for the deployment of the model. @option arguments [Integer] :number_of_allocations 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.
@option arguments [String] :priority The deployment priority. @option arguments [Integer] :queue_capacity 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.
@option arguments [Integer] :threads_per_allocation 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.
@option arguments [Time] :timeout Specifies the amount of time to wait for the model to deploy. Server default: 20s. @option arguments [String] :wait_for Specifies the allocation status to wait for before returning. Server default: started. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-start-trained-model-deployment
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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 data frame analytics jobs. A data frame analytics job can be started and stopped multiple times throughout its lifecycle.
@option arguments [String] :id 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*)
@option arguments [Boolean] :allow_no_match 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.
@option arguments [Boolean] :force If true, the data frame analytics job is stopped forcefully. @option arguments [Time] :timeout Controls the amount of time to wait until the data frame analytics job
stops. Defaults to 20 seconds. Server default: 20s.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-stop-data-frame-analytics
Source
# 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 datafeeds. A datafeed that is stopped ceases to retrieve data from Elasticsearch
. A datafeed can be started and stopped multiple times throughout its lifecycle.
@option arguments [String] :datafeed_id 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*)
@option arguments [Boolean] :allow_no_match 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.
@option arguments [Boolean] :force If true
, the datafeed is stopped forcefully. @option arguments [Time] :timeout Specifies the amount of time to wait until a datafeed stops. Server default: 20s. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-stop-datafeed
Source
# 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
Stop a trained model deployment.
@option arguments [String] :model_id The unique identifier of the trained model. (Required) @option arguments [Boolean] :allow_no_match 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.
@option arguments [Boolean] :force Forcefully stops the deployment, even if it is used by ingest pipelines. You can’t use these pipelines until you
restart the model deployment.
@option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-stop-trained-model-deployment
Source
# 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 a data frame analytics job.
@option arguments [String] :id 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*)
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-update-data-frame-analytics
Source
# 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 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.
@option arguments [String] :datafeed_id 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*)
@option arguments [Boolean] :allow_no_indices 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.
@option arguments [String, Array<String>] :expand_wildcards 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.
@option arguments [Boolean] :ignore_throttled If true
, concrete, expanded or aliased indices are ignored when frozen. Server default: true. @option arguments [Boolean] :ignore_unavailable If true
, unavailable indices (missing or closed) are ignored. @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-update-datafeed
Source
# 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 a filter. Updates the description of a filter, adds items, or removes items from the list.
@option arguments [String] :filter_id A string that uniquely identifies a filter. (Required) @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-update-filter
Source
# 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 an anomaly detection job. Updates certain properties of an anomaly detection job.
@option arguments [String] :job_id Identifier for the job. (Required) @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-update-job
Source
# 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 a snapshot. Updates certain properties of a snapshot.
@option arguments [String] :job_id Identifier for the anomaly detection job. (Required) @option arguments [String] :snapshot_id Identifier for the model snapshot. (Required) @option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-update-model-snapshot
Source
# 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
Update a trained model deployment.
@option arguments [String] :model_id The unique identifier of the trained model. Currently, only PyTorch models are supported. (Required) @option arguments [Integer] :number_of_allocations 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.
@option arguments [Hash] :headers Custom HTTP headers @option arguments [Hash] :body request body
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-update-trained-model-deployment
Source
# 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
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.
@option arguments [String] :job_id Identifier for the anomaly detection job. (Required) @option arguments [String] :snapshot_id A numerical character string that uniquely identifies the model snapshot. (Required) @option arguments [Boolean] :wait_for_completion 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.
@option arguments [Time] :timeout Controls the time to wait for the request to complete. Server default: 30m. @option arguments [Hash] :headers Custom HTTP headers
@see www.elastic.co/docs/api/doc/elasticsearch/v9/operation/operation-ml-upgrade-job-snapshot