Module: Elasticsearch::XPack::API::MachineLearning::Actions
- Included in:
- MachineLearningClient
- Defined in:
- lib/elasticsearch/xpack/api/namespace/machine_learning.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/info.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/put_job.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/forecast.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_jobs.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/open_job.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/validate.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/close_job.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/flush_job.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/post_data.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/reset_job.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/delete_job.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/put_filter.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/update_job.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_buckets.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_filters.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_records.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/put_calendar.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/put_datafeed.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/delete_filter.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_calendars.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_datafeeds.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_job_stats.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/stop_datafeed.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/update_filter.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_categories.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/start_datafeed.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/delete_calendar.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/delete_datafeed.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/delete_forecast.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_influencers.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/params_registry.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/update_datafeed.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/preview_datafeed.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/put_calendar_job.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/set_upgrade_mode.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/put_trained_model.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/validate_detector.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_datafeed_stats.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_trained_models.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/delete_calendar_job.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/delete_expired_data.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/evaluate_data_frame.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/find_file_structure.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_calendar_events.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_model_snapshots.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_overall_buckets.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/delete_trained_model.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/post_calendar_events.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/upgrade_job_snapshot.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/delete_calendar_event.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/delete_model_snapshot.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/estimate_memory_usage.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/estimate_model_memory.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/revert_model_snapshot.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/update_model_snapshot.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/put_trained_model_alias.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_data_frame_analytics.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_trained_models_stats.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/put_data_frame_analytics.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/stop_data_frame_analytics.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/delete_trained_model_alias.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/start_data_frame_analytics.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/delete_data_frame_analytics.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/update_data_frame_analytics.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/explain_data_frame_analytics.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/preview_data_frame_analytics.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/stop_trained_model_deployment.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_data_frame_analytics_stats.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/infer_trained_model_deployment.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/start_trained_model_deployment.rb,
lib/elasticsearch/xpack/api/actions/machine_learning/get_model_snapshot_upgrade_stats.rb
Defined Under Namespace
Modules: ParamsRegistry
Instance Method Summary collapse
-
#close_job(arguments = {}) ⇒ Object
Closes one or more anomaly detection jobs.
-
#delete_calendar(arguments = {}) ⇒ Object
Deletes a calendar.
-
#delete_calendar_event(arguments = {}) ⇒ Object
Deletes scheduled events from a calendar.
-
#delete_calendar_job(arguments = {}) ⇒ Object
Deletes anomaly detection jobs from a calendar.
-
#delete_data_frame_analytics(arguments = {}) ⇒ Object
Deletes an existing data frame analytics job.
-
#delete_datafeed(arguments = {}) ⇒ Object
Deletes an existing datafeed.
-
#delete_expired_data(arguments = {}) ⇒ Object
Deletes expired and unused machine learning data.
-
#delete_filter(arguments = {}) ⇒ Object
Deletes a filter.
-
#delete_forecast(arguments = {}) ⇒ Object
Deletes forecasts from a machine learning job.
-
#delete_job(arguments = {}) ⇒ Object
Deletes an existing anomaly detection job.
-
#delete_model_snapshot(arguments = {}) ⇒ Object
Deletes an existing model snapshot.
-
#delete_trained_model(arguments = {}) ⇒ Object
Deletes an existing trained inference model that is currently not referenced by an ingest pipeline.
-
#delete_trained_model_alias(arguments = {}) ⇒ Object
Deletes a model alias that refers to the trained model.
- #estimate_memory_usage(arguments = {}) ⇒ Object
-
#estimate_model_memory(arguments = {}) ⇒ Object
Estimates the model memory.
-
#evaluate_data_frame(arguments = {}) ⇒ Object
Evaluates the data frame analytics for an annotated index.
-
#explain_data_frame_analytics(arguments = {}) ⇒ Object
Explains a data frame analytics config.
-
#find_file_structure(arguments = {}) ⇒ Object
Finds the structure of a text file.
-
#flush_job(arguments = {}) ⇒ Object
Forces any buffered data to be processed by the job.
-
#forecast(arguments = {}) ⇒ Object
Predicts the future behavior of a time series by using its historical behavior.
-
#get_buckets(arguments = {}) ⇒ Object
Retrieves anomaly detection job results for one or more buckets.
-
#get_calendar_events(arguments = {}) ⇒ Object
Retrieves information about the scheduled events in calendars.
-
#get_calendars(arguments = {}) ⇒ Object
Retrieves configuration information for calendars.
-
#get_categories(arguments = {}) ⇒ Object
Retrieves anomaly detection job results for one or more categories.
-
#get_data_frame_analytics(arguments = {}) ⇒ Object
Retrieves configuration information for data frame analytics jobs.
-
#get_data_frame_analytics_stats(arguments = {}) ⇒ Object
Retrieves usage information for data frame analytics jobs.
-
#get_datafeed_stats(arguments = {}) ⇒ Object
Retrieves usage information for datafeeds.
-
#get_datafeeds(arguments = {}) ⇒ Object
Retrieves configuration information for datafeeds.
-
#get_filters(arguments = {}) ⇒ Object
Retrieves filters.
-
#get_influencers(arguments = {}) ⇒ Object
Retrieves anomaly detection job results for one or more influencers.
-
#get_job_stats(arguments = {}) ⇒ Object
Retrieves usage information for anomaly detection jobs.
-
#get_jobs(arguments = {}) ⇒ Object
Retrieves configuration information for anomaly detection jobs.
-
#get_model_snapshot_upgrade_stats(arguments = {}) ⇒ Object
Gets stats for anomaly detection job model snapshot upgrades that are in progress.
-
#get_model_snapshots(arguments = {}) ⇒ Object
Retrieves information about model snapshots.
-
#get_overall_buckets(arguments = {}) ⇒ Object
Retrieves overall bucket results that summarize the bucket results of multiple anomaly detection jobs.
-
#get_records(arguments = {}) ⇒ Object
Retrieves anomaly records for an anomaly detection job.
-
#get_trained_models(arguments = {}) ⇒ Object
Retrieves configuration information for a trained inference model.
-
#get_trained_models_stats(arguments = {}) ⇒ Object
Retrieves usage information for trained inference models.
-
#infer_trained_model_deployment(arguments = {}) ⇒ Object
Evaluate a trained model.
-
#info(arguments = {}) ⇒ Object
Returns defaults and limits used by machine learning.
-
#open_job(arguments = {}) ⇒ Object
Opens one or more anomaly detection jobs.
-
#post_calendar_events(arguments = {}) ⇒ Object
Posts scheduled events in a calendar.
-
#post_data(arguments = {}) ⇒ Object
Sends data to an anomaly detection job for analysis.
-
#preview_data_frame_analytics(arguments = {}) ⇒ Object
Previews that will be analyzed given a data frame analytics config.
-
#preview_datafeed(arguments = {}) ⇒ Object
Previews a datafeed.
-
#put_calendar(arguments = {}) ⇒ Object
Instantiates a calendar.
-
#put_calendar_job(arguments = {}) ⇒ Object
Adds an anomaly detection job to a calendar.
-
#put_data_frame_analytics(arguments = {}) ⇒ Object
Instantiates a data frame analytics job.
-
#put_datafeed(arguments = {}) ⇒ Object
Instantiates a datafeed.
-
#put_filter(arguments = {}) ⇒ Object
Instantiates a filter.
-
#put_job(arguments = {}) ⇒ Object
Instantiates an anomaly detection job.
-
#put_trained_model(arguments = {}) ⇒ Object
Creates an inference trained model.
-
#put_trained_model_alias(arguments = {}) ⇒ Object
Creates a new model alias (or reassigns an existing one) to refer to the trained model.
-
#reset_job(arguments = {}) ⇒ Object
Resets an existing anomaly detection job.
-
#revert_model_snapshot(arguments = {}) ⇒ Object
Reverts to a specific snapshot.
-
#set_upgrade_mode(arguments = {}) ⇒ Object
Sets a cluster wide upgrade_mode setting that prepares machine learning indices for an upgrade.
-
#start_data_frame_analytics(arguments = {}) ⇒ Object
Starts a data frame analytics job.
-
#start_datafeed(arguments = {}) ⇒ Object
Starts one or more datafeeds.
-
#start_trained_model_deployment(arguments = {}) ⇒ Object
Start a trained model deployment.
-
#stop_data_frame_analytics(arguments = {}) ⇒ Object
Stops one or more data frame analytics jobs.
-
#stop_datafeed(arguments = {}) ⇒ Object
Stops one or more datafeeds.
-
#stop_trained_model_deployment(arguments = {}) ⇒ Object
Stop a trained model deployment.
-
#update_data_frame_analytics(arguments = {}) ⇒ Object
Updates certain properties of a data frame analytics job.
-
#update_datafeed(arguments = {}) ⇒ Object
Updates certain properties of a datafeed.
-
#update_filter(arguments = {}) ⇒ Object
Updates the description of a filter, adds items, or removes items.
-
#update_job(arguments = {}) ⇒ Object
Updates certain properties of an anomaly detection job.
-
#update_model_snapshot(arguments = {}) ⇒ Object
Updates certain properties of a snapshot.
-
#upgrade_job_snapshot(arguments = {}) ⇒ Object
Upgrades a given job snapshot to the current major version.
-
#validate(arguments = {}) ⇒ Object
Validates an anomaly detection job.
-
#validate_detector(arguments = {}) ⇒ Object
Validates an anomaly detection detector.
Instance Method Details
#close_job(arguments = {}) ⇒ Object
Closes one or more anomaly detection jobs. A job can be opened and closed multiple times throughout its lifecycle.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/close_job.rb', line 35 def close_job(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = Elasticsearch::API::HTTP_POST path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/_close" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#delete_calendar(arguments = {}) ⇒ Object
Deletes a calendar.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/delete_calendar.rb', line 30 def delete_calendar(arguments = {}) raise ArgumentError, "Required argument 'calendar_id' missing" unless arguments[:calendar_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _calendar_id = arguments.delete(:calendar_id) method = Elasticsearch::API::HTTP_DELETE path = "_ml/calendars/#{Elasticsearch::API::Utils.__listify(_calendar_id)}" params = {} body = nil perform_request(method, path, params, body, headers).body end |
#delete_calendar_event(arguments = {}) ⇒ Object
Deletes scheduled events from a calendar.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/delete_calendar_event.rb', line 31 def delete_calendar_event(arguments = {}) raise ArgumentError, "Required argument 'calendar_id' missing" unless arguments[:calendar_id] raise ArgumentError, "Required argument 'event_id' missing" unless arguments[:event_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _calendar_id = arguments.delete(:calendar_id) _event_id = arguments.delete(:event_id) method = Elasticsearch::API::HTTP_DELETE path = "_ml/calendars/#{Elasticsearch::API::Utils.__listify(_calendar_id)}/events/#{Elasticsearch::API::Utils.__listify(_event_id)}" params = {} body = nil perform_request(method, path, params, body, headers).body end |
#delete_calendar_job(arguments = {}) ⇒ Object
Deletes anomaly detection jobs from a calendar.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/delete_calendar_job.rb', line 31 def delete_calendar_job(arguments = {}) raise ArgumentError, "Required argument 'calendar_id' missing" unless arguments[:calendar_id] raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _calendar_id = arguments.delete(:calendar_id) _job_id = arguments.delete(:job_id) method = Elasticsearch::API::HTTP_DELETE path = "_ml/calendars/#{Elasticsearch::API::Utils.__listify(_calendar_id)}/jobs/#{Elasticsearch::API::Utils.__listify(_job_id)}" params = {} body = nil perform_request(method, path, params, body, headers).body end |
#delete_data_frame_analytics(arguments = {}) ⇒ Object
Deletes an existing data frame analytics job.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/delete_data_frame_analytics.rb', line 32 def delete_data_frame_analytics(arguments = {}) raise ArgumentError, "Required argument 'id' missing" unless arguments[:id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _id = arguments.delete(:id) method = Elasticsearch::API::HTTP_DELETE path = "_ml/data_frame/analytics/#{Elasticsearch::API::Utils.__listify(_id)}" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#delete_datafeed(arguments = {}) ⇒ Object
Deletes an existing datafeed.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/delete_datafeed.rb', line 31 def delete_datafeed(arguments = {}) raise ArgumentError, "Required argument 'datafeed_id' missing" unless arguments[:datafeed_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _datafeed_id = arguments.delete(:datafeed_id) method = Elasticsearch::API::HTTP_DELETE path = "_ml/datafeeds/#{Elasticsearch::API::Utils.__listify(_datafeed_id)}" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#delete_expired_data(arguments = {}) ⇒ Object
Deletes expired and unused machine learning data.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/delete_expired_data.rb', line 33 def delete_expired_data(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = Elasticsearch::API::HTTP_DELETE path = if _job_id "_ml/_delete_expired_data/#{Elasticsearch::API::Utils.__listify(_job_id)}" else "_ml/_delete_expired_data" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#delete_filter(arguments = {}) ⇒ Object
Deletes a filter.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/delete_filter.rb', line 30 def delete_filter(arguments = {}) raise ArgumentError, "Required argument 'filter_id' missing" unless arguments[:filter_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _filter_id = arguments.delete(:filter_id) method = Elasticsearch::API::HTTP_DELETE path = "_ml/filters/#{Elasticsearch::API::Utils.__listify(_filter_id)}" params = {} body = nil perform_request(method, path, params, body, headers).body end |
#delete_forecast(arguments = {}) ⇒ Object
Deletes forecasts from a machine learning job.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/delete_forecast.rb', line 33 def delete_forecast(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _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/#{Elasticsearch::API::Utils.__listify(_job_id)}/_forecast/#{Elasticsearch::API::Utils.__listify(_forecast_id)}" else "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/_forecast" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#delete_job(arguments = {}) ⇒ Object
Deletes an existing anomaly detection job.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/delete_job.rb', line 32 def delete_job(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = Elasticsearch::API::HTTP_DELETE path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#delete_model_snapshot(arguments = {}) ⇒ Object
Deletes an existing model snapshot.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/delete_model_snapshot.rb', line 31 def delete_model_snapshot(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] raise ArgumentError, "Required argument 'snapshot_id' missing" unless arguments[:snapshot_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) _snapshot_id = arguments.delete(:snapshot_id) method = Elasticsearch::API::HTTP_DELETE path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/model_snapshots/#{Elasticsearch::API::Utils.__listify(_snapshot_id)}" params = {} body = nil perform_request(method, path, params, body, headers).body end |
#delete_trained_model(arguments = {}) ⇒ Object
Deletes an existing trained inference model that is currently not referenced by an ingest pipeline.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/delete_trained_model.rb', line 30 def delete_trained_model(arguments = {}) raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _model_id = arguments.delete(:model_id) method = Elasticsearch::API::HTTP_DELETE path = "_ml/trained_models/#{Elasticsearch::API::Utils.__listify(_model_id)}" params = {} body = nil perform_request(method, path, params, body, headers).body end |
#delete_trained_model_alias(arguments = {}) ⇒ Object
Deletes a model alias that refers to the trained model
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/delete_trained_model_alias.rb', line 31 def delete_trained_model_alias(arguments = {}) raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id] raise ArgumentError, "Required argument 'model_alias' missing" unless arguments[:model_alias] headers = arguments.delete(:headers) || {} arguments = arguments.clone _model_alias = arguments.delete(:model_alias) _model_id = arguments.delete(:model_id) method = Elasticsearch::API::HTTP_DELETE path = "_ml/trained_models/#{Elasticsearch::API::Utils.__listify(_model_id)}/model_aliases/#{Elasticsearch::API::Utils.__listify(_model_alias)}" params = {} body = nil perform_request(method, path, params, body, headers).body end |
#estimate_memory_usage(arguments = {}) ⇒ Object
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/estimate_memory_usage.rb', line 29 def estimate_memory_usage(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] arguments = arguments.clone method = Elasticsearch::API::HTTP_POST path = "_ml/data_frame/analytics/_estimate_memory_usage" params = {} body = arguments[:body] perform_request(method, path, params, body).body end |
#estimate_model_memory(arguments = {}) ⇒ Object
Estimates the model memory
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/estimate_model_memory.rb', line 30 def estimate_model_memory(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] headers = arguments.delete(:headers) || {} arguments = arguments.clone method = Elasticsearch::API::HTTP_POST path = "_ml/anomaly_detectors/_estimate_model_memory" params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#evaluate_data_frame(arguments = {}) ⇒ Object
Evaluates the data frame analytics for an annotated index.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/evaluate_data_frame.rb', line 30 def evaluate_data_frame(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] headers = arguments.delete(:headers) || {} arguments = arguments.clone method = Elasticsearch::API::HTTP_POST path = "_ml/data_frame/_evaluate" params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#explain_data_frame_analytics(arguments = {}) ⇒ Object
Explains a data frame analytics config.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/explain_data_frame_analytics.rb', line 31 def explain_data_frame_analytics(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone _id = arguments.delete(:id) method = if arguments[:body] Elasticsearch::API::HTTP_POST else Elasticsearch::API::HTTP_GET end path = if _id "_ml/data_frame/analytics/#{Elasticsearch::API::Utils.__listify(_id)}/_explain" else "_ml/data_frame/analytics/_explain" end params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#find_file_structure(arguments = {}) ⇒ Object
Finds the structure of a text file. The text file must contain data that is suitable to be ingested into Elasticsearch. This functionality is Experimental and may be changed or removed completely in a future release. Elastic will take a best effort approach to fix any issues, but experimental features are not subject to the support SLA of official GA features.
*Deprecation notice*: This endpoint has changed to _text_structure/find_structure, please use that API instead Deprecated since version 7.12.0
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/find_file_structure.rb', line 53 def find_file_structure(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] headers = arguments.delete(:headers) || {} arguments = arguments.clone method = Elasticsearch::API::HTTP_POST path = "_ml/find_file_structure" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = Elasticsearch::API::Utils.__bulkify(arguments.delete(:body)) perform_request(method, path, params, body, headers).body end |
#flush_job(arguments = {}) ⇒ Object
Forces any buffered data to be processed by the job.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/flush_job.rb', line 36 def flush_job(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = Elasticsearch::API::HTTP_POST path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/_flush" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#forecast(arguments = {}) ⇒ Object
Predicts the future behavior of a time series by using its historical behavior.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/forecast.rb', line 34 def forecast(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = Elasticsearch::API::HTTP_POST path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/_forecast" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#get_buckets(arguments = {}) ⇒ Object
Retrieves anomaly detection job results for one or more buckets.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_buckets.rb', line 41 def get_buckets(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) = arguments.delete(:timestamp) method = if arguments[:body] Elasticsearch::API::HTTP_POST else Elasticsearch::API::HTTP_GET end path = if _job_id && "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/results/buckets/#{Elasticsearch::API::Utils.__listify()}" else "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/results/buckets" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#get_calendar_events(arguments = {}) ⇒ Object
Retrieves information about the scheduled events in calendars.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_calendar_events.rb', line 35 def get_calendar_events(arguments = {}) raise ArgumentError, "Required argument 'calendar_id' missing" unless arguments[:calendar_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _calendar_id = arguments.delete(:calendar_id) method = Elasticsearch::API::HTTP_GET path = "_ml/calendars/#{Elasticsearch::API::Utils.__listify(_calendar_id)}/events" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#get_calendars(arguments = {}) ⇒ Object
Retrieves configuration information for calendars.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_calendars.rb', line 33 def get_calendars(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone _calendar_id = arguments.delete(:calendar_id) method = if arguments[:body] Elasticsearch::API::HTTP_POST else Elasticsearch::API::HTTP_GET end path = if _calendar_id "_ml/calendars/#{Elasticsearch::API::Utils.__listify(_calendar_id)}" else "_ml/calendars" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#get_categories(arguments = {}) ⇒ Object
Retrieves anomaly detection job results for one or more categories.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_categories.rb', line 35 def get_categories(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) _category_id = arguments.delete(:category_id) method = if arguments[:body] Elasticsearch::API::HTTP_POST else Elasticsearch::API::HTTP_GET end path = if _job_id && _category_id "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/results/categories/#{Elasticsearch::API::Utils.__listify(_category_id)}" else "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/results/categories" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#get_data_frame_analytics(arguments = {}) ⇒ Object
Retrieves configuration information for data frame analytics jobs.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_data_frame_analytics.rb', line 34 def get_data_frame_analytics(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone _id = arguments.delete(:id) method = Elasticsearch::API::HTTP_GET path = if _id "_ml/data_frame/analytics/#{Elasticsearch::API::Utils.__listify(_id)}" else "_ml/data_frame/analytics" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#get_data_frame_analytics_stats(arguments = {}) ⇒ Object
Retrieves usage information for data frame analytics jobs.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_data_frame_analytics_stats.rb', line 34 def get_data_frame_analytics_stats(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone _id = arguments.delete(:id) method = Elasticsearch::API::HTTP_GET path = if _id "_ml/data_frame/analytics/#{Elasticsearch::API::Utils.__listify(_id)}/_stats" else "_ml/data_frame/analytics/_stats" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#get_datafeed_stats(arguments = {}) ⇒ Object
Retrieves usage information for datafeeds.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_datafeed_stats.rb', line 32 def get_datafeed_stats(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone _datafeed_id = arguments.delete(:datafeed_id) method = Elasticsearch::API::HTTP_GET path = if _datafeed_id "_ml/datafeeds/#{Elasticsearch::API::Utils.__listify(_datafeed_id)}/_stats" else "_ml/datafeeds/_stats" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#get_datafeeds(arguments = {}) ⇒ Object
Retrieves configuration information for datafeeds.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_datafeeds.rb', line 33 def get_datafeeds(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone _datafeed_id = arguments.delete(:datafeed_id) method = Elasticsearch::API::HTTP_GET path = if _datafeed_id "_ml/datafeeds/#{Elasticsearch::API::Utils.__listify(_datafeed_id)}" else "_ml/datafeeds" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#get_filters(arguments = {}) ⇒ Object
Retrieves filters.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_filters.rb', line 32 def get_filters(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone _filter_id = arguments.delete(:filter_id) method = Elasticsearch::API::HTTP_GET path = if _filter_id "_ml/filters/#{Elasticsearch::API::Utils.__listify(_filter_id)}" else "_ml/filters" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#get_influencers(arguments = {}) ⇒ Object
Retrieves anomaly detection job results for one or more influencers.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_influencers.rb', line 39 def get_influencers(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = if arguments[:body] Elasticsearch::API::HTTP_POST else Elasticsearch::API::HTTP_GET end path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/results/influencers" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#get_job_stats(arguments = {}) ⇒ Object
Retrieves usage information for anomaly detection jobs.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_job_stats.rb', line 32 def get_job_stats(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = Elasticsearch::API::HTTP_GET path = if _job_id "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/_stats" else "_ml/anomaly_detectors/_stats" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#get_jobs(arguments = {}) ⇒ Object
Retrieves configuration information for anomaly detection jobs.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_jobs.rb', line 33 def get_jobs(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = Elasticsearch::API::HTTP_GET path = if _job_id "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}" else "_ml/anomaly_detectors" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#get_model_snapshot_upgrade_stats(arguments = {}) ⇒ Object
Gets stats for anomaly detection job model snapshot upgrades that are in progress.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_model_snapshot_upgrade_stats.rb', line 32 def get_model_snapshot_upgrade_stats(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] raise ArgumentError, "Required argument 'snapshot_id' missing" unless arguments[:snapshot_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) _snapshot_id = arguments.delete(:snapshot_id) method = Elasticsearch::API::HTTP_GET path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/model_snapshots/#{Elasticsearch::API::Utils.__listify(_snapshot_id)}/_upgrade/_stats" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#get_model_snapshots(arguments = {}) ⇒ Object
Retrieves information about model snapshots.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_model_snapshots.rb', line 38 def get_model_snapshots(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) _snapshot_id = arguments.delete(:snapshot_id) method = if arguments[:body] Elasticsearch::API::HTTP_POST else Elasticsearch::API::HTTP_GET end path = if _job_id && _snapshot_id "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/model_snapshots/#{Elasticsearch::API::Utils.__listify(_snapshot_id)}" else "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/model_snapshots" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#get_overall_buckets(arguments = {}) ⇒ Object
Retrieves overall bucket results that summarize the bucket results of multiple anomaly detection jobs.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_overall_buckets.rb', line 39 def get_overall_buckets(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = if arguments[:body] Elasticsearch::API::HTTP_POST else Elasticsearch::API::HTTP_GET end path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/results/overall_buckets" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#get_records(arguments = {}) ⇒ Object
Retrieves anomaly records for an anomaly detection job.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_records.rb', line 39 def get_records(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = if arguments[:body] Elasticsearch::API::HTTP_POST else Elasticsearch::API::HTTP_GET end path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/results/records" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#get_trained_models(arguments = {}) ⇒ Object
Retrieves configuration information for a trained inference model.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_trained_models.rb', line 38 def get_trained_models(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone _model_id = arguments.delete(:model_id) method = Elasticsearch::API::HTTP_GET path = if _model_id "_ml/trained_models/#{Elasticsearch::API::Utils.__listify(_model_id)}" else "_ml/trained_models" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#get_trained_models_stats(arguments = {}) ⇒ Object
Retrieves usage information for trained inference models.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/get_trained_models_stats.rb', line 33 def get_trained_models_stats(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone _model_id = arguments.delete(:model_id) method = Elasticsearch::API::HTTP_GET path = if _model_id "_ml/trained_models/#{Elasticsearch::API::Utils.__listify(_model_id)}/_stats" else "_ml/trained_models/_stats" end params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#infer_trained_model_deployment(arguments = {}) ⇒ Object
Evaluate a trained model. This functionality is Experimental and may be changed or removed completely in a future release. Elastic will take a best effort approach to fix any issues, but experimental features are not subject to the support SLA of official GA features.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/infer_trained_model_deployment.rb', line 35 def infer_trained_model_deployment(arguments = {}) raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _model_id = arguments.delete(:model_id) method = Elasticsearch::API::HTTP_POST path = "_ml/trained_models/#{Elasticsearch::API::Utils.__listify(_model_id)}/deployment/_infer" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#info(arguments = {}) ⇒ Object
Returns defaults and limits used by machine learning.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/info.rb', line 29 def info(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone method = Elasticsearch::API::HTTP_GET path = "_ml/info" params = {} body = nil perform_request(method, path, params, body, headers).body end |
#open_job(arguments = {}) ⇒ Object
Opens one or more anomaly detection jobs.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/open_job.rb', line 31 def open_job(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = Elasticsearch::API::HTTP_POST path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/_open" params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#post_calendar_events(arguments = {}) ⇒ Object
Posts scheduled events in a calendar.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/post_calendar_events.rb', line 31 def post_calendar_events(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] raise ArgumentError, "Required argument 'calendar_id' missing" unless arguments[:calendar_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _calendar_id = arguments.delete(:calendar_id) method = Elasticsearch::API::HTTP_POST path = "_ml/calendars/#{Elasticsearch::API::Utils.__listify(_calendar_id)}/events" params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#post_data(arguments = {}) ⇒ Object
Sends data to an anomaly detection job for analysis.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/post_data.rb', line 33 def post_data(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = Elasticsearch::API::HTTP_POST path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/_data" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#preview_data_frame_analytics(arguments = {}) ⇒ Object
Previews that will be analyzed given a data frame analytics config.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/preview_data_frame_analytics.rb', line 31 def preview_data_frame_analytics(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone _id = arguments.delete(:id) method = if arguments[:body] Elasticsearch::API::HTTP_POST else Elasticsearch::API::HTTP_GET end path = if _id "_ml/data_frame/analytics/#{Elasticsearch::API::Utils.__listify(_id)}/_preview" else "_ml/data_frame/analytics/_preview" end params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#preview_datafeed(arguments = {}) ⇒ Object
Previews a datafeed.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/preview_datafeed.rb', line 31 def preview_datafeed(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone _datafeed_id = arguments.delete(:datafeed_id) method = if arguments[:body] Elasticsearch::API::HTTP_POST else Elasticsearch::API::HTTP_GET end path = if _datafeed_id "_ml/datafeeds/#{Elasticsearch::API::Utils.__listify(_datafeed_id)}/_preview" else "_ml/datafeeds/_preview" end params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#put_calendar(arguments = {}) ⇒ Object
Instantiates a calendar.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/put_calendar.rb', line 31 def put_calendar(arguments = {}) raise ArgumentError, "Required argument 'calendar_id' missing" unless arguments[:calendar_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _calendar_id = arguments.delete(:calendar_id) method = Elasticsearch::API::HTTP_PUT path = "_ml/calendars/#{Elasticsearch::API::Utils.__listify(_calendar_id)}" params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#put_calendar_job(arguments = {}) ⇒ Object
Adds an anomaly detection job to a calendar.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/put_calendar_job.rb', line 31 def put_calendar_job(arguments = {}) raise ArgumentError, "Required argument 'calendar_id' missing" unless arguments[:calendar_id] raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _calendar_id = arguments.delete(:calendar_id) _job_id = arguments.delete(:job_id) method = Elasticsearch::API::HTTP_PUT path = "_ml/calendars/#{Elasticsearch::API::Utils.__listify(_calendar_id)}/jobs/#{Elasticsearch::API::Utils.__listify(_job_id)}" params = {} body = nil perform_request(method, path, params, body, headers).body end |
#put_data_frame_analytics(arguments = {}) ⇒ Object
Instantiates a data frame analytics job.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/put_data_frame_analytics.rb', line 31 def put_data_frame_analytics(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] raise ArgumentError, "Required argument 'id' missing" unless arguments[:id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _id = arguments.delete(:id) method = Elasticsearch::API::HTTP_PUT path = "_ml/data_frame/analytics/#{Elasticsearch::API::Utils.__listify(_id)}" params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#put_datafeed(arguments = {}) ⇒ Object
Instantiates a datafeed.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/put_datafeed.rb', line 35 def put_datafeed(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] raise ArgumentError, "Required argument 'datafeed_id' missing" unless arguments[:datafeed_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _datafeed_id = arguments.delete(:datafeed_id) method = Elasticsearch::API::HTTP_PUT path = "_ml/datafeeds/#{Elasticsearch::API::Utils.__listify(_datafeed_id)}" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#put_filter(arguments = {}) ⇒ Object
Instantiates a filter.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/put_filter.rb', line 31 def put_filter(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] raise ArgumentError, "Required argument 'filter_id' missing" unless arguments[:filter_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _filter_id = arguments.delete(:filter_id) method = Elasticsearch::API::HTTP_PUT path = "_ml/filters/#{Elasticsearch::API::Utils.__listify(_filter_id)}" params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#put_job(arguments = {}) ⇒ Object
Instantiates an anomaly detection job.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/put_job.rb', line 35 def put_job(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = Elasticsearch::API::HTTP_PUT path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#put_trained_model(arguments = {}) ⇒ Object
Creates an inference trained model.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/put_trained_model.rb', line 32 def put_trained_model(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _model_id = arguments.delete(:model_id) method = Elasticsearch::API::HTTP_PUT path = "_ml/trained_models/#{Elasticsearch::API::Utils.__listify(_model_id)}" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#put_trained_model_alias(arguments = {}) ⇒ Object
Creates a new model alias (or reassigns an existing one) to refer to the trained model
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/put_trained_model_alias.rb', line 32 def put_trained_model_alias(arguments = {}) raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id] raise ArgumentError, "Required argument 'model_alias' missing" unless arguments[:model_alias] headers = arguments.delete(:headers) || {} arguments = arguments.clone _model_alias = arguments.delete(:model_alias) _model_id = arguments.delete(:model_id) method = Elasticsearch::API::HTTP_PUT path = "_ml/trained_models/#{Elasticsearch::API::Utils.__listify(_model_id)}/model_aliases/#{Elasticsearch::API::Utils.__listify(_model_alias)}" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#reset_job(arguments = {}) ⇒ Object
Resets an existing anomaly detection job.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/reset_job.rb', line 31 def reset_job(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = Elasticsearch::API::HTTP_POST path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/_reset" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#revert_model_snapshot(arguments = {}) ⇒ Object
Reverts to a specific snapshot.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/revert_model_snapshot.rb', line 33 def revert_model_snapshot(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] raise ArgumentError, "Required argument 'snapshot_id' missing" unless arguments[:snapshot_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) _snapshot_id = arguments.delete(:snapshot_id) method = Elasticsearch::API::HTTP_POST path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/model_snapshots/#{Elasticsearch::API::Utils.__listify(_snapshot_id)}/_revert" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#set_upgrade_mode(arguments = {}) ⇒ Object
Sets a cluster wide upgrade_mode setting that prepares machine learning indices for an upgrade.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/set_upgrade_mode.rb', line 31 def set_upgrade_mode(arguments = {}) headers = arguments.delete(:headers) || {} arguments = arguments.clone method = Elasticsearch::API::HTTP_POST path = "_ml/set_upgrade_mode" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#start_data_frame_analytics(arguments = {}) ⇒ Object
Starts a data frame analytics job.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/start_data_frame_analytics.rb', line 32 def start_data_frame_analytics(arguments = {}) raise ArgumentError, "Required argument 'id' missing" unless arguments[:id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _id = arguments.delete(:id) method = Elasticsearch::API::HTTP_POST path = "_ml/data_frame/analytics/#{Elasticsearch::API::Utils.__listify(_id)}/_start" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#start_datafeed(arguments = {}) ⇒ Object
Starts one or more datafeeds.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/start_datafeed.rb', line 34 def start_datafeed(arguments = {}) raise ArgumentError, "Required argument 'datafeed_id' missing" unless arguments[:datafeed_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _datafeed_id = arguments.delete(:datafeed_id) method = Elasticsearch::API::HTTP_POST path = "_ml/datafeeds/#{Elasticsearch::API::Utils.__listify(_datafeed_id)}/_start" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#start_trained_model_deployment(arguments = {}) ⇒ Object
Start a trained model deployment. This functionality is Experimental and may be changed or removed completely in a future release. Elastic will take a best effort approach to fix any issues, but experimental features are not subject to the support SLA of official GA features.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/start_trained_model_deployment.rb', line 35 def start_trained_model_deployment(arguments = {}) raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _model_id = arguments.delete(:model_id) method = Elasticsearch::API::HTTP_POST path = "_ml/trained_models/#{Elasticsearch::API::Utils.__listify(_model_id)}/deployment/_start" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#stop_data_frame_analytics(arguments = {}) ⇒ Object
Stops one or more data frame analytics jobs.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/stop_data_frame_analytics.rb', line 34 def stop_data_frame_analytics(arguments = {}) raise ArgumentError, "Required argument 'id' missing" unless arguments[:id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _id = arguments.delete(:id) method = Elasticsearch::API::HTTP_POST path = "_ml/data_frame/analytics/#{Elasticsearch::API::Utils.__listify(_id)}/_stop" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#stop_datafeed(arguments = {}) ⇒ Object
Stops one or more datafeeds.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/stop_datafeed.rb', line 35 def stop_datafeed(arguments = {}) raise ArgumentError, "Required argument 'datafeed_id' missing" unless arguments[:datafeed_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _datafeed_id = arguments.delete(:datafeed_id) method = Elasticsearch::API::HTTP_POST path = "_ml/datafeeds/#{Elasticsearch::API::Utils.__listify(_datafeed_id)}/_stop" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#stop_trained_model_deployment(arguments = {}) ⇒ Object
Stop a trained model deployment. This functionality is Experimental and may be changed or removed completely in a future release. Elastic will take a best effort approach to fix any issues, but experimental features are not subject to the support SLA of official GA features.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/stop_trained_model_deployment.rb', line 34 def stop_trained_model_deployment(arguments = {}) raise ArgumentError, "Required argument 'model_id' missing" unless arguments[:model_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _model_id = arguments.delete(:model_id) method = Elasticsearch::API::HTTP_POST path = "_ml/trained_models/#{Elasticsearch::API::Utils.__listify(_model_id)}/deployment/_stop" params = {} body = nil perform_request(method, path, params, body, headers).body end |
#update_data_frame_analytics(arguments = {}) ⇒ Object
Updates certain properties of a data frame analytics job.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/update_data_frame_analytics.rb', line 31 def update_data_frame_analytics(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] raise ArgumentError, "Required argument 'id' missing" unless arguments[:id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _id = arguments.delete(:id) method = Elasticsearch::API::HTTP_POST path = "_ml/data_frame/analytics/#{Elasticsearch::API::Utils.__listify(_id)}/_update" params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#update_datafeed(arguments = {}) ⇒ Object
Updates certain properties of a datafeed.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/update_datafeed.rb', line 35 def update_datafeed(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] raise ArgumentError, "Required argument 'datafeed_id' missing" unless arguments[:datafeed_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _datafeed_id = arguments.delete(:datafeed_id) method = Elasticsearch::API::HTTP_POST path = "_ml/datafeeds/#{Elasticsearch::API::Utils.__listify(_datafeed_id)}/_update" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#update_filter(arguments = {}) ⇒ Object
Updates the description of a filter, adds items, or removes items.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/update_filter.rb', line 31 def update_filter(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] raise ArgumentError, "Required argument 'filter_id' missing" unless arguments[:filter_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _filter_id = arguments.delete(:filter_id) method = Elasticsearch::API::HTTP_POST path = "_ml/filters/#{Elasticsearch::API::Utils.__listify(_filter_id)}/_update" params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#update_job(arguments = {}) ⇒ Object
Updates certain properties of an anomaly detection job.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/update_job.rb', line 31 def update_job(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) method = Elasticsearch::API::HTTP_POST path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/_update" params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#update_model_snapshot(arguments = {}) ⇒ Object
Updates certain properties of a snapshot.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/update_model_snapshot.rb', line 32 def update_model_snapshot(arguments = {}) 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] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) _snapshot_id = arguments.delete(:snapshot_id) method = Elasticsearch::API::HTTP_POST path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/model_snapshots/#{Elasticsearch::API::Utils.__listify(_snapshot_id)}/_update" params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#upgrade_job_snapshot(arguments = {}) ⇒ Object
Upgrades a given job snapshot to the current major version.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/upgrade_job_snapshot.rb', line 33 def upgrade_job_snapshot(arguments = {}) raise ArgumentError, "Required argument 'job_id' missing" unless arguments[:job_id] raise ArgumentError, "Required argument 'snapshot_id' missing" unless arguments[:snapshot_id] headers = arguments.delete(:headers) || {} arguments = arguments.clone _job_id = arguments.delete(:job_id) _snapshot_id = arguments.delete(:snapshot_id) method = Elasticsearch::API::HTTP_POST path = "_ml/anomaly_detectors/#{Elasticsearch::API::Utils.__listify(_job_id)}/model_snapshots/#{Elasticsearch::API::Utils.__listify(_snapshot_id)}/_upgrade" params = Elasticsearch::API::Utils.__validate_and_extract_params arguments, ParamsRegistry.get(__method__) body = nil perform_request(method, path, params, body, headers).body end |
#validate(arguments = {}) ⇒ Object
Validates an anomaly detection job.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/validate.rb', line 30 def validate(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] headers = arguments.delete(:headers) || {} arguments = arguments.clone method = Elasticsearch::API::HTTP_POST path = "_ml/anomaly_detectors/_validate" params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |
#validate_detector(arguments = {}) ⇒ Object
Validates an anomaly detection detector.
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# File 'lib/elasticsearch/xpack/api/actions/machine_learning/validate_detector.rb', line 30 def validate_detector(arguments = {}) raise ArgumentError, "Required argument 'body' missing" unless arguments[:body] headers = arguments.delete(:headers) || {} arguments = arguments.clone method = Elasticsearch::API::HTTP_POST path = "_ml/anomaly_detectors/_validate/detector" params = {} body = arguments[:body] perform_request(method, path, params, body, headers).body end |