[ML] Api tests for ml/saved_objects/remove_item_from_current_space

x-pack/test/api_integration/apis/ml/saved_objects/index.ts

@@ -18,5 +18,6 @@ export default function ({ loadTestFile }: FtrProviderContext) {
     loadTestFile(require.resolve('./sync_jobs'));
     loadTestFile(require.resolve('./sync_trained_models'));
     loadTestFile(require.resolve('./update_jobs_spaces'));
+    loadTestFile(require.resolve('./remove_from_current_space'));
   });
 }

x-pack/test/api_integration/apis/ml/saved_objects/remove_from_current_space.ts

@@ -0,0 +1,137 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+import expect from '@kbn/expect';
+import { MlSavedObjectType } from '@kbn/ml-plugin/common/types/saved_objects';
+import { FtrProviderContext } from '../../../ftr_provider_context';
+import { USER } from '../../../../functional/services/ml/security_common';
+import { COMMON_REQUEST_HEADERS } from '../../../../functional/services/ml/common_api';
+
+export default ({ getService }: FtrProviderContext) => {
+  const esArchiver = getService('esArchiver');
+  const ml = getService('ml');
+  const spacesService = getService('spaces');
+  const supertest = getService('supertestWithoutAuth');
+
+  const adJobId = 'fq_single';
+  const dfaJobId = 'ihp_od';
+  const trainedModelId = 'trained_model';
+  const idSpace1 = 'space1';
+  const idSpace2 = 'space2';
+  const defaultSpaceId = 'default';
+
+  async function runRequest(
+    requestBody: {
+      ids: string[];
+      mlSavedObjectType: MlSavedObjectType;
+    },
+    space: string,
+    expectedStatusCode: number,
+    user: USER
+  ) {
+    const { body, status } = await supertest
+      .post(`/s/${space}/api/ml/saved_objects/remove_item_from_current_space`)
+      .auth(user, ml.securityCommon.getPasswordForUser(user))
+      .set(COMMON_REQUEST_HEADERS)
+      .send(requestBody);
+    ml.api.assertResponseStatusCode(expectedStatusCode, status, body);
+
+    return body;
+  }
+
+  describe('POST saved_objects/remove_item_from_current_space', () => {
+    before(async () => {
+      await ml.testResources.setKibanaTimeZoneToUTC();
+      await esArchiver.loadIfNeeded('x-pack/test/functional/es_archives/ml/ihp_outlier');
+
+      // create spaces
+      await spacesService.create({ id: idSpace1, name: 'space_one', disabledFeatures: [] });
+      await spacesService.create({ id: idSpace2, name: 'space_two', disabledFeatures: [] });
+
+      // create anomaly detection job
+      await ml.api.createAnomalyDetectionJob(ml.commonConfig.getADFqSingleMetricJobConfig(adJobId));
+      // create data frame analytics job
+      await ml.api.createDataFrameAnalyticsJob(
+        ml.commonConfig.getDFAIhpOutlierDetectionJobConfig(dfaJobId)
+      );
+      // Create trained model
+      const trainedModelConfig = ml.api.createTestTrainedModelConfig(trainedModelId, 'regression');
+      await ml.api.createTrainedModel(trainedModelId, trainedModelConfig.body);
+
+      // reassign spaces for all items
+      await ml.api.updateJobSpaces(adJobId, 'anomaly-detector', [idSpace1, idSpace2], []);
+      await ml.api.updateJobSpaces(dfaJobId, 'data-frame-analytics', [idSpace1, idSpace2], []);
+      await ml.api.updateTrainedModelSpaces(trainedModelId, [idSpace1, idSpace2], []);
+    });
+
+    after(async () => {
+      await ml.api.cleanMlIndices();
+      await ml.testResources.cleanMLSavedObjects();
+      await spacesService.delete(idSpace1);
+      await spacesService.delete(idSpace2);
+    });
+
+    it('should remove AD job from current space', async () => {
+      await ml.api.assertJobSpaces(adJobId, 'anomaly-detector', [
+        defaultSpaceId,
+        idSpace1,
+        idSpace2,
+      ]);
+      const mlSavedObjectType = 'anomaly-detector';
+      const body = await runRequest(
+        {
+          ids: [adJobId],
+          mlSavedObjectType,
+        },
+        idSpace1,
+        200,
+        USER.ML_POWERUSER
+      );
+
+      expect(body).to.eql({ [adJobId]: { success: true, type: mlSavedObjectType } });
+      await ml.api.assertJobSpaces(adJobId, mlSavedObjectType, [defaultSpaceId, idSpace2]);
+    });
+
+    it('should remove DFA job from current space', async () => {
+      await ml.api.assertJobSpaces(dfaJobId, 'data-frame-analytics', [
+        defaultSpaceId,
+        idSpace1,
+        idSpace2,
+      ]);
+      const mlSavedObjectType = 'data-frame-analytics';
+      const body = await runRequest(
+        {
+          ids: [dfaJobId],
+          mlSavedObjectType,
+        },
+        idSpace2,
+        200,
+        USER.ML_POWERUSER
+      );
+
+      expect(body).to.eql({ [dfaJobId]: { success: true, type: mlSavedObjectType } });
+      await ml.api.assertJobSpaces(dfaJobId, mlSavedObjectType, [defaultSpaceId, idSpace1]);
+    });
+
+    it('should remove trained model from current space', async () => {
+      await ml.api.assertTrainedModelSpaces(trainedModelId, [defaultSpaceId, idSpace1, idSpace2]);
+      const mlSavedObjectType = 'trained-model';
+      const body = await runRequest(
+        {
+          ids: [trainedModelId],
+          mlSavedObjectType,
+        },
+        idSpace2,
+        200,
+        USER.ML_POWERUSER
+      );
+
+      expect(body).to.eql({ [trainedModelId]: { success: true, type: mlSavedObjectType } });
+      await ml.api.assertTrainedModelSpaces(trainedModelId, [defaultSpaceId, idSpace1]);
+    });
+  });
+};