[ML] Add functional tests for analytics UI: classification jobs (#56912)

* add classification functional tests

* remove unneeded testing tag

* update jobId and description per suggestion

Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>

x-pack/legacy/plugins/ml/public/application/data_frame_analytics/pages/analytics_exploration/components/classification_exploration/evaluate_panel.tsx

@@ -218,7 +218,10 @@ export const EvaluatePanel: FC<Props> = ({ jobConfig, jobStatus, searchQuery })
   }
 
   return (
-    <EuiPanel style={{ width: `${panelWidth}px` }}>
+    <EuiPanel
+      data-test-subj="mlDFAnalyticsClassificationExplorationEvaluatePanel"
+      style={{ width: `${panelWidth}px` }}
+    >
       <EuiFlexGroup direction="column" gutterSize="s">
         <EuiFlexItem>
           <EuiFlexGroup alignItems="center" justifyContent="spaceBetween">
@@ -337,6 +340,7 @@ export const EvaluatePanel: FC<Props> = ({ jobConfig, jobStatus, searchQuery })
                         </EuiFlexItem>
                         <EuiFlexItem grow={false} style={{ width: '90%' }}>
                           <EuiDataGrid
+                            data-test-subj="mlDFAnalyticsClassificationExplorationConfusionMatrix"
                             aria-label="Classification confusion matrix"
                             columns={columns}
                             columnVisibility={{ visibleColumns, setVisibleColumns }}

x-pack/legacy/plugins/ml/public/application/data_frame_analytics/pages/analytics_exploration/components/classification_exploration/results_table.tsx

@@ -401,7 +401,11 @@ export const ResultsTable: FC<Props> = React.memo(
         : searchError;
 
     return (
-      <EuiPanel grow={false} id="mlDataFrameAnalyticsTableResultsPanel">
+      <EuiPanel
+        grow={false}
+        id="mlDataFrameAnalyticsTableResultsPanel"
+        data-test-subj="mlDFAnalyticsClassificationExplorationTablePanel"
+      >
         <EuiFlexGroup alignItems="center" justifyContent="spaceBetween" responsive={false}>
           <EuiFlexItem grow={false}>
             <EuiFlexGroup gutterSize="s">

x-pack/test/functional/apps/machine_learning/data_frame_analytics/classification_creation.ts

@@ -0,0 +1,174 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License;
+ * you may not use this file except in compliance with the Elastic License.
+ */
+import expect from '@kbn/expect';
+
+import { FtrProviderContext } from '../../../ftr_provider_context';
+
+export default function({ getService }: FtrProviderContext) {
+  const esArchiver = getService('esArchiver');
+  const ml = getService('ml');
+
+  describe('classification creation', function() {
+    this.tags(['smoke']);
+    before(async () => {
+      await esArchiver.load('ml/bm_classification');
+    });
+
+    after(async () => {
+      await ml.api.cleanMlIndices();
+      await esArchiver.unload('ml/bm_classification');
+    });
+
+    const testDataList = [
+      {
+        suiteTitle: 'bank marketing',
+        jobType: 'classification',
+        jobId: `bm_1_${Date.now()}`,
+        jobDescription:
+          "Classification job based on 'bank-marketing' dataset with dependentVariable 'y' and trainingPercent '20'",
+        source: 'bank-marketing*',
+        get destinationIndex(): string {
+          return `dest_${this.jobId}`;
+        },
+        dependentVariable: 'y',
+        trainingPercent: '20',
+        modelMemory: '105mb',
+        createIndexPattern: true,
+        expected: {
+          row: {
+            type: 'classification',
+            status: 'stopped',
+            progress: '100',
+          },
+        },
+      },
+    ];
+    for (const testData of testDataList) {
+      describe(`${testData.suiteTitle}`, function() {
+        after(async () => {
+          await ml.api.deleteIndices(testData.destinationIndex);
+        });
+
+        it('loads the data frame analytics page', async () => {
+          await ml.navigation.navigateToMl();
+          await ml.navigation.navigateToDataFrameAnalytics();
+        });
+
+        it('loads the job creation flyout', async () => {
+          await ml.dataFrameAnalytics.startAnalyticsCreation();
+        });
+
+        it('selects the job type', async () => {
+          await ml.dataFrameAnalyticsCreation.assertJobTypeSelectExists();
+          await ml.dataFrameAnalyticsCreation.selectJobType(testData.jobType);
+        });
+
+        it('inputs the job id', async () => {
+          await ml.dataFrameAnalyticsCreation.assertJobIdInputExists();
+          await ml.dataFrameAnalyticsCreation.setJobId(testData.jobId);
+        });
+
+        it('inputs the job description', async () => {
+          await ml.dataFrameAnalyticsCreation.assertJobDescriptionInputExists();
+          await ml.dataFrameAnalyticsCreation.setJobDescription(testData.jobDescription);
+        });
+
+        it('selects the source index', async () => {
+          await ml.dataFrameAnalyticsCreation.assertSourceIndexInputExists();
+          await ml.dataFrameAnalyticsCreation.selectSourceIndex(testData.source);
+        });
+
+        it('inputs the destination index', async () => {
+          await ml.dataFrameAnalyticsCreation.assertDestIndexInputExists();
+          await ml.dataFrameAnalyticsCreation.setDestIndex(testData.destinationIndex);
+        });
+
+        it('inputs the dependent variable', async () => {
+          await ml.dataFrameAnalyticsCreation.assertDependentVariableInputExists();
+          await ml.dataFrameAnalyticsCreation.selectDependentVariable(testData.dependentVariable);
+        });
+
+        it('inputs the training percent', async () => {
+          await ml.dataFrameAnalyticsCreation.assertTrainingPercentInputExists();
+          await ml.dataFrameAnalyticsCreation.setTrainingPercent(testData.trainingPercent);
+        });
+
+        it('inputs the model memory limit', async () => {
+          await ml.dataFrameAnalyticsCreation.assertModelMemoryInputExists();
+          await ml.dataFrameAnalyticsCreation.setModelMemory(testData.modelMemory);
+        });
+
+        it('sets the create index pattern switch', async () => {
+          await ml.dataFrameAnalyticsCreation.assertCreateIndexPatternSwitchExists();
+          await ml.dataFrameAnalyticsCreation.setCreateIndexPatternSwitchState(
+            testData.createIndexPattern
+          );
+        });
+
+        it('creates the analytics job', async () => {
+          await ml.dataFrameAnalyticsCreation.assertCreateButtonExists();
+          await ml.dataFrameAnalyticsCreation.createAnalyticsJob();
+        });
+
+        it('starts the analytics job', async () => {
+          await ml.dataFrameAnalyticsCreation.assertStartButtonExists();
+          await ml.dataFrameAnalyticsCreation.startAnalyticsJob();
+        });
+
+        it('closes the create job flyout', async () => {
+          await ml.dataFrameAnalyticsCreation.assertCloseButtonExists();
+          await ml.dataFrameAnalyticsCreation.closeCreateAnalyticsJobFlyout();
+        });
+
+        it('finishes analytics processing', async () => {
+          await ml.dataFrameAnalytics.waitForAnalyticsCompletion(testData.jobId);
+        });
+
+        it('displays the analytics table', async () => {
+          await ml.dataFrameAnalytics.assertAnalyticsTableExists();
+        });
+
+        it('displays the stats bar', async () => {
+          await ml.dataFrameAnalytics.assertAnalyticsStatsBarExists();
+        });
+
+        it('displays the created job in the analytics table', async () => {
+          await ml.dataFrameAnalyticsTable.refreshAnalyticsTable();
+          await ml.dataFrameAnalyticsTable.filterWithSearchString(testData.jobId);
+          const rows = await ml.dataFrameAnalyticsTable.parseAnalyticsTable();
+          const filteredRows = rows.filter(row => row.id === testData.jobId);
+          expect(filteredRows).to.have.length(
+            1,
+            `Filtered analytics table should have 1 row for job id '${testData.jobId}' (got matching items '${filteredRows}')`
+          );
+        });
+
+        it('displays details for the created job in the analytics table', async () => {
+          await ml.dataFrameAnalyticsTable.assertAnalyticsRowFields(testData.jobId, {
+            id: testData.jobId,
+            description: testData.jobDescription,
+            sourceIndex: testData.source,
+            destinationIndex: testData.destinationIndex,
+            type: testData.expected.row.type,
+            status: testData.expected.row.status,
+            progress: testData.expected.row.progress,
+          });
+        });
+
+        it('creates the destination index and writes results to it', async () => {
+          await ml.api.assertIndicesExist(testData.destinationIndex);
+          await ml.api.assertIndicesNotEmpty(testData.destinationIndex);
+        });
+
+        it('displays the results view for created job', async () => {
+          await ml.dataFrameAnalyticsTable.openResultsView();
+          await ml.dataFrameAnalytics.assertClassificationEvaluatePanelElementsExists();
+          await ml.dataFrameAnalytics.assertClassificationTablePanelExists();
+        });
+      });
+    }
+  });
+}

x-pack/test/functional/apps/machine_learning/data_frame_analytics/index.ts

@@ -11,5 +11,6 @@ export default function({ loadTestFile }: FtrProviderContext) {
 
     loadTestFile(require.resolve('./outlier_detection_creation'));
     loadTestFile(require.resolve('./regression_creation'));
+    loadTestFile(require.resolve('./classification_creation'));
   });
 }

x-pack/test/functional/apps/machine_learning/data_frame_analytics/regression_creation.ts

@@ -11,7 +11,7 @@ export default function({ getService }: FtrProviderContext) {
   const esArchiver = getService('esArchiver');
   const ml = getService('ml');
 
-  describe('outlier detection creation', function() {
+  describe('regression creation', function() {
     this.tags(['smoke']);
     before(async () => {
       await esArchiver.load('ml/egs_regression');

x-pack/test/functional/services/machine_learning/data_frame_analytics.ts

@@ -44,6 +44,15 @@ export function MachineLearningDataFrameAnalyticsProvider(
       await testSubjects.existOrFail('mlDFAnalyticsRegressionExplorationTablePanel');
     },
 
+    async assertClassificationEvaluatePanelElementsExists() {
+      await testSubjects.existOrFail('mlDFAnalyticsClassificationExplorationEvaluatePanel');
+      await testSubjects.existOrFail('mlDFAnalyticsClassificationExplorationConfusionMatrix');
+    },
+
+    async assertClassificationTablePanelExists() {
+      await testSubjects.existOrFail('mlDFAnalyticsClassificationExplorationTablePanel');
+    },
+
     async assertOutlierTablePanelExists() {
       await testSubjects.existOrFail('mlDFAnalyticsOutlierExplorationTablePanel');
     },