mirror of
https://github.com/elastic/kibana.git
synced 2025-04-23 09:19:04 -04:00
[ML] Add accessibility test for population and advanced job wizards (#146052)
This commit is contained in:
Quynh Nguyen (Quinn)
GitHub
parent
cf0cde26a0
commit
83bf248540
1 changed files with 272 additions and 0 deletions
|
|
@ -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');
|
||||
|
|
@ -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');
|
||||
|
|
@ -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();
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue