[ML] DF Analytics functional tests: re-enable regression, classificat…

…ion, and outlier creation (elastic#71006) * update mml test. re-enable reg, class, and outlier creation tests * remove unnecessary second argument
alvarezmelissa87 · Jul 8, 2020 · 2d2de40 · 2d2de40
1 parent eff820b
commit 2d2de40
Show file tree

Hide file tree

Showing 4 changed files with 20 additions and 12 deletions.
diff --git a/x-pack/test/functional/apps/ml/data_frame_analytics/classification_creation.ts b/x-pack/test/functional/apps/ml/data_frame_analytics/classification_creation.ts
@@ -10,8 +10,8 @@ import { FtrProviderContext } from '../../../ftr_provider_context';
 export default function ({ getService }: FtrProviderContext) {
   const esArchiver = getService('esArchiver');
   const ml = getService('ml');
-  // flaky test https://github.com/elastic/kibana/issues/70455
-  describe.skip('classification creation', function () {
+
+  describe('classification creation', function () {
     before(async () => {
       await esArchiver.loadIfNeeded('ml/bm_classification');
       await ml.testResources.createIndexPatternIfNeeded('ft_bank_marketing', '@timestamp');
@@ -96,9 +96,9 @@ export default function ({ getService }: FtrProviderContext) {
           await ml.dataFrameAnalyticsCreation.continueToAdditionalOptionsStep();
         });
 
-        it('inputs the model memory limit', async () => {
+        it('accepts the suggested model memory limit', async () => {
           await ml.dataFrameAnalyticsCreation.assertModelMemoryInputExists();
-          await ml.dataFrameAnalyticsCreation.setModelMemory(testData.modelMemory);
+          await ml.dataFrameAnalyticsCreation.assertModelMemoryInputPopulated();
         });
 
         it('continues to the details step', async () => {

diff --git a/x-pack/test/functional/apps/ml/data_frame_analytics/outlier_detection_creation.ts b/x-pack/test/functional/apps/ml/data_frame_analytics/outlier_detection_creation.ts
@@ -11,8 +11,7 @@ export default function ({ getService }: FtrProviderContext) {
   const esArchiver = getService('esArchiver');
   const ml = getService('ml');
 
-  // Flaky: https://github.com/elastic/kibana/issues/70906
-  describe.skip('outlier detection creation', function () {
+  describe('outlier detection creation', function () {
     before(async () => {
       await esArchiver.loadIfNeeded('ml/ihp_outlier');
       await ml.testResources.createIndexPatternIfNeeded('ft_ihp_outlier', '@timestamp');
@@ -93,9 +92,9 @@ export default function ({ getService }: FtrProviderContext) {
           await ml.dataFrameAnalyticsCreation.continueToAdditionalOptionsStep();
         });
 
-        it('inputs the model memory limit', async () => {
+        it('accepts the suggested model memory limit', async () => {
           await ml.dataFrameAnalyticsCreation.assertModelMemoryInputExists();
-          await ml.dataFrameAnalyticsCreation.setModelMemory(testData.modelMemory);
+          await ml.dataFrameAnalyticsCreation.assertModelMemoryInputPopulated();
         });
 
         it('continues to the details step', async () => {

diff --git a/x-pack/test/functional/apps/ml/data_frame_analytics/regression_creation.ts b/x-pack/test/functional/apps/ml/data_frame_analytics/regression_creation.ts
@@ -10,8 +10,8 @@ import { FtrProviderContext } from '../../../ftr_provider_context';
 export default function ({ getService }: FtrProviderContext) {
   const esArchiver = getService('esArchiver');
   const ml = getService('ml');
-  // flaky test https://github.com/elastic/kibana/issues/70455
-  describe.skip('regression creation', function () {
+
+  describe('regression creation', function () {
     before(async () => {
       await esArchiver.loadIfNeeded('ml/egs_regression');
       await ml.testResources.createIndexPatternIfNeeded('ft_egs_regression', '@timestamp');
@@ -96,9 +96,9 @@ export default function ({ getService }: FtrProviderContext) {
           await ml.dataFrameAnalyticsCreation.continueToAdditionalOptionsStep();
         });
 
-        it('inputs the model memory limit', async () => {
+        it('accepts the suggested model memory limit', async () => {
           await ml.dataFrameAnalyticsCreation.assertModelMemoryInputExists();
-          await ml.dataFrameAnalyticsCreation.setModelMemory(testData.modelMemory);
+          await ml.dataFrameAnalyticsCreation.assertModelMemoryInputPopulated();
         });
 
         it('continues to the details step', async () => {

diff --git a/x-pack/test/functional/services/ml/data_frame_analytics_creation.ts b/x-pack/test/functional/services/ml/data_frame_analytics_creation.ts
@@ -306,6 +306,15 @@ export function MachineLearningDataFrameAnalyticsCreationProvider(
       );
     },
 
+    async assertModelMemoryInputPopulated() {
+      const actualModelMemory = await testSubjects.getAttribute(
+        'mlAnalyticsCreateJobWizardModelMemoryInput',
+        'value'
+      );
+
+      expect(actualModelMemory).not.to.be('');
+    },
+
     async assertPredictionFieldNameValue(expectedValue: string) {
       const actualPredictedFieldName = await testSubjects.getAttribute(
         'mlAnalyticsCreateJobWizardPredictionFieldNameInput',