[ML] Anomaly detection wizards: adds functional test for geo wizard (#150942)

## Summary

Adds functional tests for the geo wizard in anomaly detection

[Flaky test runner
build](https://buildkite.com/elastic/kibana-flaky-test-suite-runner/builds/1913)


### Checklist

Delete any items that are not applicable to this PR.
- [x] [Unit or functional
tests](https://www.elastic.co/guide/en/kibana/master/development-tests.html)
were updated or added to match the most common scenarios

---------

Co-authored-by: Kibana Machine <42973632+kibanamachine@users.noreply.github.com>
Co-authored-by: Robert Oskamp <traeluki@gmail.com>

x-pack/plugins/ml/public/application/jobs/new_job/pages/components/pick_fields_step/components/split_field/split_field.tsx

@@ -62,7 +62,7 @@ export const SplitFieldSelector: FC = () => {
         changeHandler={setSplitField}
         selectedField={splitField}
         isClearable={true}
-        testSubject="mlMultiMetricSplitFieldSelect"
+        testSubject="mlSplitFieldSelect"
       />
     </Description>
   );

x-pack/test/functional/apps/ml/anomaly_detection_jobs/geo_job.ts

@@ -0,0 +1,354 @@
+/*
+ * 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 { FtrProviderContext } from '../../../ftr_provider_context';
+
+export default function ({ getService }: FtrProviderContext) {
+  const esArchiver = getService('esArchiver');
+  const ml = getService('ml');
+
+  const jobId = `ec_geo_1_${Date.now()}`;
+  const jobIdClone = `${jobId}_clone`;
+  const jobDescription = 'Create geo job based on the ecommerce sample dataset with 15m bucketspan';
+  const jobGroups = ['automated', 'ecommerce', 'geo'];
+  const jobGroupsClone = [...jobGroups, 'clone'];
+  const geoField = 'geoip.location';
+  const splitField = 'customer_gender';
+  const detectors = [
+    {
+      identifier: 'Lat long(geoip.location)',
+      frontCardTitle: "Men's Clothing",
+      function: 'lat_long',
+      field_name: geoField,
+      numberOfBackCards: 5,
+      splitField,
+    },
+  ];
+  const bucketSpan = '15m';
+  const memoryLimit = '8mb';
+
+  function getExpectedRow(expectedJobId: string, expectedJobGroups: string[]) {
+    return {
+      id: expectedJobId,
+      description: jobDescription,
+      jobGroups: [...new Set(expectedJobGroups)].sort(),
+      recordCount: '4,675',
+      memoryStatus: 'ok',
+      jobState: 'closed',
+      datafeedState: 'stopped',
+      latestTimestamp: '2019-07-12 23:45:36',
+    };
+  }
+
+  function getExpectedCounts(expectedJobId: string) {
+    return {
+      job_id: expectedJobId,
+      processed_record_count: '4,675',
+      processed_field_count: '9,350',
+      input_bytes: '504.1 KB',
+      input_field_count: '9,350',
+      invalid_date_count: '0',
+      missing_field_count: '0',
+      out_of_order_timestamp_count: '0',
+      empty_bucket_count: '492',
+      sparse_bucket_count: '0',
+      bucket_count: '2,975',
+      earliest_record_timestamp: '2019-06-12 00:04:19',
+      latest_record_timestamp: '2019-07-12 23:45:36',
+      input_record_count: '4,675',
+      latest_bucket_timestamp: '2019-07-12 23:45:00',
+    };
+  }
+
+  function getExpectedModelSizeStats(expectedJobId: string) {
+    return {
+      job_id: expectedJobId,
+      result_type: 'model_size_stats',
+      model_bytes_exceeded: '0.0 B',
+      total_by_field_count: '4',
+      total_over_field_count: '0',
+      total_partition_field_count: '3',
+      bucket_allocation_failures_count: '0',
+      memory_status: 'ok',
+      timestamp: '2019-07-12 23:30:00',
+    };
+  }
+
+  const calendarId = `wizard-test-calendar_${Date.now()}`;
+
+  describe('geo', function () {
+    this.tags(['ml']);
+    before(async () => {
+      await esArchiver.loadIfNeeded('x-pack/test/functional/es_archives/ml/ecommerce');
+      await ml.testResources.createIndexPatternIfNeeded('ft_ecommerce', 'order_date');
+      await ml.testResources.setKibanaTimeZoneToUTC();
+
+      await ml.api.createCalendar(calendarId);
+      await ml.securityUI.loginAsMlPowerUser();
+    });
+
+    after(async () => {
+      await ml.api.cleanMlIndices();
+      await ml.testResources.deleteIndexPatternByTitle('ft_ecommerce');
+    });
+
+    it('job creation loads the geo wizard for the source data', async () => {
+      await ml.testExecution.logTestStep('job creation loads the job management page');
+      await ml.navigation.navigateToMl();
+      await ml.navigation.navigateToJobManagement();
+
+      await ml.testExecution.logTestStep('job creation loads the new job source selection page');
+      await ml.jobManagement.navigateToNewJobSourceSelection();
+
+      await ml.testExecution.logTestStep('job creation loads the job type selection page');
+      await ml.jobSourceSelection.selectSourceForAnomalyDetectionJob('ft_ecommerce');
+
+      await ml.testExecution.logTestStep('job creation loads the geo job wizard page');
+      await ml.jobTypeSelection.selectGeoJob();
+    });
+
+    it('job creation navigates through the geo wizard and sets all needed fields', async () => {
+      await ml.testExecution.logTestStep('job creation displays the time range step');
+      await ml.jobWizardCommon.assertTimeRangeSectionExists();
+
+      await ml.testExecution.logTestStep('job creation sets the time range');
+      await ml.jobWizardCommon.clickUseFullDataButton(
+        'Jun 12, 2019 @ 00:04:19.000',
+        'Jul 12, 2019 @ 23:45:36.000'
+      );
+
+      await ml.testExecution.logTestStep('job creation displays the event rate chart');
+      await ml.jobWizardCommon.assertEventRateChartExists();
+      await ml.jobWizardCommon.assertEventRateChartHasData();
+
+      await ml.testExecution.logTestStep('job creation displays the pick fields step');
+      await ml.jobWizardCommon.advanceToPickFieldsSection();
+
+      await ml.testExecution.logTestStep('job creation selects the geo field');
+      await ml.jobWizardGeo.assertGeoFieldInputExists();
+      await ml.jobWizardGeo.selectGeoField(geoField);
+
+      await ml.testExecution.logTestStep('job creation displays detector preview');
+
+      await ml.jobWizardGeo.assertDetectorPreviewExists(detectors[0].identifier);
+
+      await ml.testExecution.logTestStep(
+        'job creation inputs the split field and displays split cards'
+      );
+
+      await ml.jobWizardMultiMetric.assertSplitFieldInputExists();
+      await ml.jobWizardMultiMetric.selectSplitField(splitField);
+
+      await ml.jobWizardMultiMetric.assertDetectorSplitExists(splitField);
+      await ml.jobWizardMultiMetric.assertDetectorSplitFrontCardTitle('FEMALE');
+      await ml.jobWizardMultiMetric.assertDetectorSplitNumberOfBackCards(1);
+
+      await ml.testExecution.logTestStep('job creation displays the influencer field');
+      await ml.jobWizardCommon.assertInfluencerInputExists();
+      await ml.jobWizardCommon.assertInfluencerSelection([splitField]);
+
+      await ml.testExecution.logTestStep('job creation inputs the bucket span');
+      await ml.jobWizardCommon.assertBucketSpanInputExists();
+      await ml.jobWizardCommon.setBucketSpan(bucketSpan);
+
+      await ml.testExecution.logTestStep('job creation displays the job details step');
+      await ml.jobWizardCommon.advanceToJobDetailsSection();
+
+      await ml.testExecution.logTestStep('job creation inputs the job id');
+      await ml.jobWizardCommon.assertJobIdInputExists();
+      await ml.jobWizardCommon.setJobId(jobId);
+
+      await ml.testExecution.logTestStep('job creation inputs the job description');
+      await ml.jobWizardCommon.assertJobDescriptionInputExists();
+      await ml.jobWizardCommon.setJobDescription(jobDescription);
+
+      await ml.testExecution.logTestStep('job creation inputs job groups');
+      await ml.jobWizardCommon.assertJobGroupInputExists();
+      for (const jobGroup of jobGroups) {
+        await ml.jobWizardCommon.addJobGroup(jobGroup);
+      }
+      await ml.jobWizardCommon.assertJobGroupSelection(jobGroups);
+
+      await ml.testExecution.logTestStep('job creation opens the additional settings section');
+      await ml.jobWizardCommon.ensureAdditionalSettingsSectionOpen();
+
+      await ml.testExecution.logTestStep('job creation adds a new custom url');
+      await ml.jobWizardCommon.addCustomUrl({ label: 'check-kibana-dashboard' });
+
+      await ml.testExecution.logTestStep('job creation assigns calendars');
+      await ml.jobWizardCommon.addCalendar(calendarId);
+
+      await ml.testExecution.logTestStep('job creation opens the advanced section');
+      await ml.jobWizardCommon.ensureAdvancedSectionOpen();
+
+      await ml.testExecution.logTestStep('job creation displays the model plot switch');
+      await ml.jobWizardCommon.assertModelPlotSwitchExists();
+
+      await ml.testExecution.logTestStep('job creation enables the dedicated index switch');
+      await ml.jobWizardCommon.assertDedicatedIndexSwitchExists();
+      await ml.jobWizardCommon.activateDedicatedIndexSwitch();
+
+      await ml.testExecution.logTestStep('job creation inputs the model memory limit');
+      await ml.jobWizardCommon.assertModelMemoryLimitInputExists();
+      await ml.jobWizardCommon.setModelMemoryLimit(memoryLimit);
+
+      await ml.testExecution.logTestStep('job creation displays the validation step');
+      await ml.jobWizardCommon.advanceToValidationSection();
+
+      await ml.testExecution.logTestStep('job creation displays the summary step');
+      await ml.jobWizardCommon.advanceToSummarySection();
+    });
+
+    it('job creation runs the job and displays it correctly in the job list', async () => {
+      await ml.testExecution.logTestStep('job creation creates the job and finishes processing');
+      await ml.jobWizardCommon.assertCreateJobButtonExists();
+      await ml.jobWizardCommon.createJobAndWaitForCompletion();
+
+      await ml.testExecution.logTestStep('job creation displays the created job in the job list');
+      await ml.navigation.navigateToMl();
+      await ml.navigation.navigateToJobManagement();
+
+      await ml.jobTable.filterWithSearchString(jobId, 1);
+
+      await ml.testExecution.logTestStep(
+        'job creation displays details for the created job in the job list'
+      );
+      await ml.jobTable.assertJobRowFields(jobId, getExpectedRow(jobId, jobGroups));
+
+      await ml.jobTable.assertJobRowDetailsCounts(
+        jobId,
+        getExpectedCounts(jobId),
+        getExpectedModelSizeStats(jobId)
+      );
+
+      await ml.testExecution.logTestStep('job creation has detector results');
+      for (let i = 0; i < detectors.length; i++) {
+        await ml.api.assertDetectorResultsExist(jobId, i);
+      }
+    });
+
+    it('job cloning opens the existing job in the geo wizard', async () => {
+      await ml.testExecution.logTestStep(
+        'job cloning clicks the clone action and loads the geo wizard'
+      );
+      await ml.jobTable.clickCloneJobAction(jobId);
+      await ml.jobTypeSelection.assertGeoJobWizardOpen();
+    });
+
+    it('job cloning navigates through the geo wizard, checks and sets all needed fields', async () => {
+      await ml.testExecution.logTestStep('job cloning displays the time range step');
+      await ml.jobWizardCommon.assertTimeRangeSectionExists();
+
+      await ml.testExecution.logTestStep('job cloning sets the time range');
+      await ml.jobWizardCommon.clickUseFullDataButton(
+        'Jun 12, 2019 @ 00:04:19.000',
+        'Jul 12, 2019 @ 23:45:36.000'
+      );
+
+      await ml.testExecution.logTestStep('job cloning displays the event rate chart');
+      await ml.jobWizardCommon.assertEventRateChartExists();
+      await ml.jobWizardCommon.assertEventRateChartHasData();
+
+      await ml.testExecution.logTestStep('job cloning displays the pick fields step');
+      await ml.jobWizardCommon.advanceToPickFieldsSection();
+
+      await ml.testExecution.logTestStep('job cloning pre-fills the geo field');
+      await ml.jobWizardGeo.assertGeoFieldInputExists();
+      await ml.jobWizardGeo.assertGeoFieldSelection([geoField]);
+
+      await ml.testExecution.logTestStep(
+        'job cloning displays the detector preview with pre-filled geo field'
+      );
+      await ml.jobWizardGeo.assertDetectorPreviewExists(detectors[0].identifier);
+
+      await ml.testExecution.logTestStep('job cloning pre-fills influencers');
+      await ml.jobWizardCommon.assertInfluencerInputExists();
+      await ml.jobWizardCommon.assertInfluencerSelection([splitField]);
+
+      await ml.testExecution.logTestStep('job cloning pre-fills the bucket span');
+      await ml.jobWizardCommon.assertBucketSpanInputExists();
+      await ml.jobWizardCommon.assertBucketSpanValue(bucketSpan);
+
+      await ml.testExecution.logTestStep('job cloning displays the job details step');
+      await ml.jobWizardCommon.advanceToJobDetailsSection();
+
+      await ml.testExecution.logTestStep('job cloning does not pre-fill the job id');
+      await ml.jobWizardCommon.assertJobIdInputExists();
+      await ml.jobWizardCommon.assertJobIdValue('');
+
+      await ml.testExecution.logTestStep('job cloning inputs the clone job id');
+      await ml.jobWizardCommon.setJobId(jobIdClone);
+
+      await ml.testExecution.logTestStep('job cloning pre-fills the job description');
+      await ml.jobWizardCommon.assertJobDescriptionInputExists();
+      await ml.jobWizardCommon.assertJobDescriptionValue(jobDescription);
+
+      await ml.testExecution.logTestStep('job cloning pre-fills job groups');
+      await ml.jobWizardCommon.assertJobGroupInputExists();
+      await ml.jobWizardCommon.assertJobGroupSelection(jobGroups);
+
+      await ml.testExecution.logTestStep('job cloning inputs the clone job group');
+      await ml.jobWizardCommon.assertJobGroupInputExists();
+      await ml.jobWizardCommon.addJobGroup('clone');
+      await ml.jobWizardCommon.assertJobGroupSelection(jobGroupsClone);
+
+      await ml.testExecution.logTestStep('job cloning opens the additional settings section');
+      await ml.jobWizardCommon.ensureAdditionalSettingsSectionOpen();
+
+      await ml.testExecution.logTestStep('job cloning persists custom urls');
+      await ml.customUrls.assertCustomUrlLabel(0, 'check-kibana-dashboard');
+
+      await ml.testExecution.logTestStep('job cloning persists assigned calendars');
+      await ml.jobWizardCommon.assertCalendarsSelection([calendarId]);
+
+      await ml.testExecution.logTestStep('job cloning opens the advanced section');
+      await ml.jobWizardCommon.ensureAdvancedSectionOpen();
+
+      await ml.testExecution.logTestStep('job cloning pre-fills the model plot switch');
+      await ml.jobWizardCommon.assertModelPlotSwitchExists();
+      await ml.jobWizardCommon.assertModelPlotSwitchCheckedState(false);
+
+      await ml.testExecution.logTestStep('job cloning pre-fills the dedicated index switch');
+      await ml.jobWizardCommon.assertDedicatedIndexSwitchExists();
+      await ml.jobWizardCommon.assertDedicatedIndexSwitchCheckedState(true);
+
+      await ml.testExecution.logTestStep('job cloning displays the validation step');
+      await ml.jobWizardCommon.advanceToValidationSection();
+
+      await ml.testExecution.logTestStep('job cloning displays the summary step');
+      await ml.jobWizardCommon.advanceToSummarySection();
+    });
+
+    it('job cloning runs the clone job and displays it correctly in the job list', async () => {
+      await ml.testExecution.logTestStep('job cloning creates the job and finishes processing');
+      await ml.jobWizardCommon.assertCreateJobButtonExists();
+      await ml.jobWizardCommon.createJobAndWaitForCompletion();
+
+      await ml.testExecution.logTestStep('job cloning displays the created job in the job list');
+      await ml.navigation.navigateToMl();
+      await ml.navigation.navigateToJobManagement();
+
+      await ml.jobTable.filterWithSearchString(jobIdClone, 1);
+
+      await ml.testExecution.logTestStep(
+        'job cloning displays details for the created job in the job list'
+      );
+      await ml.jobTable.assertJobRowFields(jobIdClone, getExpectedRow(jobIdClone, jobGroupsClone));
+
+      await ml.jobTable.assertJobRowDetailsCounts(
+        jobIdClone,
+        getExpectedCounts(jobIdClone),
+        getExpectedModelSizeStats(jobIdClone)
+      );
+
+      await ml.testExecution.logTestStep('job cloning has detector results');
+      for (let i = 0; i < detectors.length; i++) {
+        await ml.api.assertDetectorResultsExist(jobId, i);
+      }
+    });
+  });
+}

x-pack/test/functional/apps/ml/anomaly_detection_jobs/index.ts

@@ -43,6 +43,7 @@ export default function ({ getService, loadTestFile }: FtrProviderContext) {
       loadTestFile(require.resolve('./single_metric_job_without_datafeed_start'));
       loadTestFile(require.resolve('./multi_metric_job'));
       loadTestFile(require.resolve('./population_job'));
+      loadTestFile(require.resolve('./geo_job'));
       loadTestFile(require.resolve('./saved_search_job'));
       loadTestFile(require.resolve('./advanced_job'));
       loadTestFile(require.resolve('./categorization_job'));

x-pack/test/functional/services/ml/index.ts

@@ -36,6 +36,7 @@ import { MachineLearningJobWizardCommonProvider } from './job_wizard_common';
 import { MachineLearningJobWizardCategorizationProvider } from './job_wizard_categorization';
 import { MachineLearningJobWizardMultiMetricProvider } from './job_wizard_multi_metric';
 import { MachineLearningJobWizardPopulationProvider } from './job_wizard_population';
+import { MachineLearningJobWizardGeoProvider } from './job_wizard_geo';
 import { MachineLearningLensVisualizationsProvider } from './lens_visualizations';
 import { MachineLearningNavigationProvider } from './navigation';
 import { MachineLearningOverviewPageProvider } from './overview_page';
@@ -115,6 +116,7 @@ export function MachineLearningProvider(context: FtrProviderContext) {
   const jobWizardCommon = MachineLearningJobWizardCommonProvider(context, commonUI, customUrls);
   const jobWizardMultiMetric = MachineLearningJobWizardMultiMetricProvider(context);
   const jobWizardPopulation = MachineLearningJobWizardPopulationProvider(context);
+  const jobWizardGeo = MachineLearningJobWizardGeoProvider(context);
   const lensVisualizations = MachineLearningLensVisualizationsProvider(context, commonUI);
   const navigation = MachineLearningNavigationProvider(context);
   const overviewPage = MachineLearningOverviewPageProvider(context);
@@ -174,6 +176,7 @@ export function MachineLearningProvider(context: FtrProviderContext) {
     jobWizardCommon,
     jobWizardMultiMetric,
     jobWizardPopulation,
+    jobWizardGeo,
     lensVisualizations,
     mlNodesPanel,
     navigation,

x-pack/test/functional/services/ml/job_type_selection.ts

@@ -34,10 +34,19 @@ export function MachineLearningJobTypeSelectionProvider({ getService }: FtrProvi
       await this.assertPopulationJobWizardOpen();
     },
 
+    async selectGeoJob() {
+      await testSubjects.clickWhenNotDisabledWithoutRetry('mlJobTypeLinkGeoJob');
+      await this.assertGeoJobWizardOpen();
+    },
+
     async assertPopulationJobWizardOpen() {
       await testSubjects.existOrFail('mlPageJobWizard population');
     },
 
+    async assertGeoJobWizardOpen() {
+      await testSubjects.existOrFail('mlPageJobWizard geo');
+    },
+
     async selectAdvancedJob() {
       await testSubjects.clickWhenNotDisabledWithoutRetry('mlJobTypeLinkAdvancedJob');
       await this.assertAdvancedJobWizardOpen();

x-pack/test/functional/services/ml/job_wizard_geo.ts

@@ -0,0 +1,52 @@
+/*
+ * 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 { FtrProviderContext } from '../../ftr_provider_context';
+
+export function MachineLearningJobWizardGeoProvider({ getService }: FtrProviderContext) {
+  const comboBox = getService('comboBox');
+  const testSubjects = getService('testSubjects');
+
+  return {
+    async assertGeoFieldInputExists() {
+      await testSubjects.existOrFail('mlGeoFieldNameSelect > comboBoxInput');
+    },
+
+    async assertGeoFieldSelection(expectedIdentifier: string[]) {
+      const comboBoxSelectedOptions = await comboBox.getComboBoxSelectedOptions(
+        'mlGeoFieldNameSelect > comboBoxInput'
+      );
+      expect(comboBoxSelectedOptions).to.eql(
+        expectedIdentifier,
+        `Expected geo field selection to be '${expectedIdentifier}' (got '${comboBoxSelectedOptions}')`
+      );
+    },
+
+    async selectGeoField(identifier: string) {
+      await comboBox.set('mlGeoFieldNameSelect > comboBoxInput', identifier);
+      await this.assertGeoFieldSelection([identifier]);
+    },
+
+    async assertSplitCardWithMapExampleExists() {
+      await testSubjects.existOrFail('mlGeoJobWizardMap');
+    },
+
+    async assertDetectorPreviewExists(detectorDescription: string) {
+      await testSubjects.existOrFail('mlGeoMap > mlDetectorTitle');
+      const actualDetectorTitle = await testSubjects.getVisibleText('mlGeoMap > mlDetectorTitle');
+      expect(actualDetectorTitle).to.eql(
+        detectorDescription,
+        `Expected detector title to be '${detectorDescription}' (got '${actualDetectorTitle}')`
+      );
+
+      await testSubjects.existOrFail('mlGeoJobWizardMap');
+      await testSubjects.existOrFail('mlEmbeddedMapContent');
+    },
+  };
+}

x-pack/test/functional/services/ml/job_wizard_multi_metric.ts

@@ -15,12 +15,12 @@ export function MachineLearningJobWizardMultiMetricProvider({ getService }: FtrP
 
   return {
     async assertSplitFieldInputExists() {
-      await testSubjects.existOrFail('mlMultiMetricSplitFieldSelect > comboBoxInput');
+      await testSubjects.existOrFail('mlSplitFieldSelect > comboBoxInput');
     },
 
     async assertSplitFieldSelection(expectedIdentifier: string[]) {
       const comboBoxSelectedOptions = await comboBox.getComboBoxSelectedOptions(
-        'mlMultiMetricSplitFieldSelect > comboBoxInput'
+        'mlSplitFieldSelect > comboBoxInput'
       );
       expect(comboBoxSelectedOptions).to.eql(
         expectedIdentifier,
@@ -29,12 +29,12 @@ export function MachineLearningJobWizardMultiMetricProvider({ getService }: FtrP
     },
 
     async selectSplitField(identifier: string) {
-      await comboBox.set('mlMultiMetricSplitFieldSelect > comboBoxInput', identifier);
+      await comboBox.set('mlSplitFieldSelect > comboBoxInput', identifier);
       await this.assertSplitFieldSelection([identifier]);
     },
 
     async scrollSplitFieldIntoView() {
-      await testSubjects.scrollIntoView('mlMultiMetricSplitFieldSelect');
+      await testSubjects.scrollIntoView('mlSplitFieldSelect');
     },
 
     async assertDetectorSplitExists(splitField: string) {