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[ML] Add accessibility test for population and advanced job wizards #146052

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merged 2 commits into from
Nov 23, 2022
Merged

[ML] Add accessibility test for population and advanced job wizards #146052

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8b2c8aa
Add accessibility test for population and advanced job wizards
qn895 Nov 22, 2022
bd66ea8
Merge branch 'main' into ml-accessibility-tests
kibanamachine Nov 23, 2022
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272 changes: 272 additions & 0 deletions x-pack/test/accessibility/apps/ml.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,17 @@

import { FtrProviderContext } from '../ftr_provider_context';

interface Detector {
identifier: string;
function: string;
field?: string;
byField?: string;
overField?: string;
partitionField?: string;
excludeFrequent?: string;
description?: string;
}

export default function ({ getService }: FtrProviderContext) {
const a11y = getService('a11y');
const ml = getService('ml');
Expand Down Expand Up @@ -95,6 +106,114 @@ export default function ({ getService }: FtrProviderContext) {
'../../functional/apps/ml/data_visualizer/files_to_import/artificial_server_log'
);

const advancedJobTestData = {
suiteTitle: 'with multiple metric detectors and custom datafeed settings',
jobSource: ecIndexPattern,
jobId: `ec_advanced_1_${Date.now()}`,
get jobIdClone(): string {
return `${this.jobId}_clone`;
},
jobDescription: `Create advanced job from ${ecIndexPattern} dataset with multiple metric detectors and custom datafeed settings`,
jobGroups: ['automated', 'ecommerce', 'advanced'],
get jobGroupsClone(): string[] {
return [...this.jobGroups, 'clone'];
},
pickFieldsConfig: {
detectors: [
{
identifier: 'high_count',
function: 'high_count',
description: 'high_count detector without split',
} as Detector,
{
identifier: 'mean("products.base_price") by "category.keyword"',
function: 'mean',
field: 'products.base_price',
byField: 'category.keyword',
} as Detector,
{
identifier: 'sum("products.discount_amount") over customer_id',
function: 'sum',
field: 'products.discount_amount',
overField: 'customer_id',
} as Detector,
{
identifier: 'median(total_quantity) partition_field_name=customer_gender',
function: 'median',
field: 'total_quantity',
partitionField: 'customer_gender',
} as Detector,
{
identifier:
'max(total_quantity) by "geoip.continent_name" over customer_id partition_field_name=customer_gender',
function: 'max',
field: 'total_quantity',
byField: 'geoip.continent_name',
overField: 'customer_id',
partitionField: 'customer_gender',
} as Detector,
],
influencers: [
'customer_id',
'category.keyword',
'geoip.continent_name',
'customer_gender',
],
bucketSpan: '1h',
memoryLimit: '10mb',
},
datafeedConfig: {
queryDelay: '55s',
frequency: '350s',
scrollSize: '999',
},
};
const populationJobTestData = {
suiteTitle: 'population job',
jobSource: ecIndexPattern,
jobId: `ec_population_1_${Date.now()}`,
get jobIdClone(): string {
return `${this.jobId}_clone`;
},
jobDescription:
'Create population job based on the ecommerce sample dataset with 2h bucketspan over customer_id' +
' - detectors: (Mean(products.base_price) by customer_gender), (Mean(products.quantity) by category.leyword)',
jobGroups: ['automated', 'ecommerce', 'population'],
get jobGroupsClone(): string[] {
return [...this.jobGroups, 'clone'];
},
populationField: 'customer_id',
pickFieldsConfig: {
detectors: [
{
identifier: 'Mean(products.base_price)',
splitField: 'customer_gender',
frontCardTitle: 'FEMALE',
numberOfBackCards: 1,
},
{
identifier: 'Mean(products.quantity)',
splitField: 'category.keyword',
frontCardTitle: "Men's Clothing",
numberOfBackCards: 5,
},
],
influencers: [
'customer_id',
'category.keyword',
'geoip.continent_name',
'customer_gender',
],
bucketSpan: '2h',
memoryLimit: '8mb',
},
datafeedConfig: {
queryDelay: '55s',
frequency: '350s',
scrollSize: '999',
},
};

before(async () => {
await esArchiver.loadIfNeeded('x-pack/test/functional/es_archives/ml/farequote');
await esArchiver.loadIfNeeded('x-pack/test/functional/es_archives/ml/ihp_outlier');
Expand Down Expand Up @@ -267,6 +386,159 @@ export default function ({ getService }: FtrProviderContext) {
await a11y.testAppSnapshot();
});

it('anomaly detection create advanced job open wizard', async () => {
await ml.navigation.navigateToMl();
await ml.navigation.navigateToJobManagement();

await ml.jobManagement.navigateToNewJobSourceSelection();

await ml.jobSourceSelection.selectSourceForAnomalyDetectionJob(
advancedJobTestData.jobSource
);

await ml.jobTypeSelection.selectAdvancedJob();
await a11y.testAppSnapshot();
});

it('anomaly detection create advanced job pick fields step', async () => {
await ml.jobWizardCommon.advanceToPickFieldsSection();
await a11y.testAppSnapshot();

for (const detector of advancedJobTestData.pickFieldsConfig.detectors) {
await ml.jobWizardAdvanced.openCreateDetectorModal();
await a11y.testAppSnapshot();

await ml.jobWizardAdvanced.selectDetectorFunction(detector.function);
if (detector.hasOwnProperty('field')) {
await ml.jobWizardAdvanced.selectDetectorField(detector.field!);
}
if (detector.hasOwnProperty('byField')) {
await ml.jobWizardAdvanced.selectDetectorByField(detector.byField!);
}
if (detector.hasOwnProperty('overField')) {
await ml.jobWizardAdvanced.selectDetectorOverField(detector.overField!);
}
if (detector.hasOwnProperty('partitionField')) {
await ml.jobWizardAdvanced.selectDetectorPartitionField(detector.partitionField!);
}
if (detector.hasOwnProperty('excludeFrequent')) {
await ml.jobWizardAdvanced.selectDetectorExcludeFrequent(detector.excludeFrequent!);
}
if (detector.hasOwnProperty('description')) {
await ml.jobWizardAdvanced.setDetectorDescription(detector.description!);
}

await ml.jobWizardAdvanced.confirmAddDetectorModal();
}

await ml.testExecution.logTestStep('job creation inputs the bucket span');
await ml.jobWizardCommon.setBucketSpan(advancedJobTestData.pickFieldsConfig.bucketSpan);

await ml.testExecution.logTestStep('job creation inputs influencers');
for (const influencer of advancedJobTestData.pickFieldsConfig.influencers) {
await ml.jobWizardCommon.addInfluencer(influencer);
}

await ml.testExecution.logTestStep('job creation inputs the model memory limit');
await ml.jobWizardCommon.setModelMemoryLimit(
advancedJobTestData.pickFieldsConfig.memoryLimit,
{
withAdvancedSection: false,
}
);
await a11y.testAppSnapshot();
});

it('anomaly detection create advanced job job details step', async () => {
await ml.jobWizardCommon.advanceToJobDetailsSection();
await ml.jobWizardCommon.setJobId(advancedJobTestData.jobId);
await ml.jobWizardCommon.setJobDescription(advancedJobTestData.jobDescription);
for (const jobGroup of advancedJobTestData.jobGroups) {
await ml.jobWizardCommon.addJobGroup(jobGroup);
}
await ml.jobWizardCommon.ensureAdditionalSettingsSectionOpen();
await ml.jobWizardCommon.addCustomUrl({ label: 'check-kibana-dashboard' });
await ml.jobWizardCommon.addCalendar(calendarId);
await a11y.testAppSnapshot();
});

it('anomaly detection create advanced job validation step', async () => {
await ml.jobWizardCommon.advanceToValidationSection();
await a11y.testAppSnapshot();
});

it('anomaly detection create advanced job job summary step', async () => {
await ml.jobWizardCommon.advanceToSummarySection();
await a11y.testAppSnapshot();
});

it('anomaly detection create population job open wizard', async () => {
await ml.navigation.navigateToJobManagement();
await ml.jobManagement.navigateToNewJobSourceSelection();

await ml.jobSourceSelection.selectSourceForAnomalyDetectionJob(ecIndexPattern);

await ml.testExecution.logTestStep('job creation loads the population job wizard page');
await ml.jobTypeSelection.selectPopulationJob();
await a11y.testAppSnapshot();
});

it('anomaly detection create population job pick fields step', async () => {
await ml.jobWizardCommon.advanceToPickFieldsSection();
await ml.jobWizardPopulation.selectPopulationField(populationJobTestData.populationField);
for (const [
index,
detector,
] of populationJobTestData.pickFieldsConfig.detectors.entries()) {
await ml.jobWizardCommon.selectAggAndField(detector.identifier, false);
await ml.jobWizardCommon.assertDetectorPreviewExists(
detector.identifier,
index,
'SCATTER'
);
}

for (const [
index,
detector,
] of populationJobTestData.pickFieldsConfig.detectors.entries()) {
await ml.jobWizardPopulation.assertDetectorSplitFieldInputExists(index);
await ml.jobWizardPopulation.selectDetectorSplitField(index, detector.splitField);
}
await ml.jobWizardCommon.setBucketSpan(populationJobTestData.pickFieldsConfig.bucketSpan);
await a11y.testAppSnapshot();
});

it('anomaly detection create population job details step', async () => {
await ml.jobWizardCommon.advanceToJobDetailsSection();

await ml.jobWizardCommon.setJobId(populationJobTestData.jobId);
await ml.jobWizardCommon.setJobDescription(populationJobTestData.jobDescription);
for (const jobGroup of populationJobTestData.jobGroups) {
await ml.jobWizardCommon.addJobGroup(jobGroup);
}
await ml.jobWizardCommon.ensureAdditionalSettingsSectionOpen();
await ml.jobWizardCommon.addCustomUrl({ label: 'check-kibana-dashboard' });
await ml.jobWizardCommon.addCalendar(calendarId);

await ml.testExecution.logTestStep('job creation inputs the model memory limit');
await ml.jobWizardCommon.setModelMemoryLimit(
populationJobTestData.pickFieldsConfig.memoryLimit
);

await a11y.testAppSnapshot();
});

it('anomaly detection create population job validation step', async () => {
await ml.jobWizardCommon.advanceToValidationSection();
await a11y.testAppSnapshot();
});

it('anomaly detection create population job summary step', async () => {
await ml.jobWizardCommon.advanceToSummarySection();
await a11y.testAppSnapshot();
});

it('anomaly detection Single Metric Viewer page', async () => {
await ml.navigation.navigateToMl();
await ml.navigation.navigateToAnomalyDetection();
Expand Down