[API] Adds machine_learning.clear_trained_model_deployment_cache

Author: picandocodigo

elasticsearch-api/lib/elasticsearch/api/actions/machine_learning/clear_trained_model_deployment_cache.rb

@@ -0,0 +1,57 @@
+# Licensed to Elasticsearch B.V. under one or more contributor
+# license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright
+# ownership. Elasticsearch B.V. licenses this file to you under
+# the Apache License, Version 2.0 (the "License"); you may
+# not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+#
+# Auto generated from build hash f284cc16f4d4b4289bc679aa1529bb504190fe80
+# @see https://github.com/elastic/elasticsearch/tree/main/rest-api-spec
+#
+module Elasticsearch
+  module API
+    module MachineLearning
+      module Actions
+        # Clear the cached results from 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.
+        #
+        # @option arguments [String] :model_id The unique identifier of the trained model. (*Required*)
+        # @option arguments [Hash] :headers Custom HTTP headers
+        #
+        # @see https://www.elastic.co/guide/en/elasticsearch/reference/current/clear-trained-model-deployment-cache.html
+        #
+        def clear_trained_model_deployment_cache(arguments = {})
+          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)
+          )
+        end
+      end
+    end
+  end
+end

elasticsearch-api/spec/unit_tests_platinum/unit/machine_learning/clear_trained_model_deployment_cache_test.rb

@@ -0,0 +1,40 @@
+# Licensed to Elasticsearch B.V. under one or more contributor
+# license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright
+# ownership. Elasticsearch B.V. licenses this file to you under
+# the Apache License, Version 2.0 (the "License"); you may
+# not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+require 'test_helper'
+
+module Elasticsearch
+  module Test
+    class MachineLearningClearTrainedModelDeploymentCacheTest < Minitest::Test
+      context 'Machine Learning: Clear trained model deployment cache' do
+        subject { FakeClient.new }
+
+        should 'perform correct request' do
+          subject.expects(:perform_request).with do |method, url, params, body|
+            assert_equal('POST', method)
+            assert_equal('_ml/trained_models/model/deployment/cache/_clear', url)
+            assert_equal({}, params)
+            assert_nil(body)
+            true
+          end.returns(FakeResponse.new)
+
+          subject.ml.clear_trained_model_deployment_cache(model_id: 'model')
+        end
+      end
+    end
+  end
+end