[ML] Anomaly Detection: Fix validation error when no data in index. (#86114)

For cardinality checks, an empty index of the fields checks not returning any results would block the user from moving to the next step in the Anomaly Detection job wizard.
This PR fixes it by adding more fine grained checks and only returning warning-level messages for the above cases. A warning-level message will allow the user to continue to the next step in the wizard.
This commit is contained in:
Walter Rafelsberger 2020-12-17 18:58:37 +01:00 committed by GitHub
parent 7bac741a1e
commit 755dc7e8ee
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7 changed files with 206 additions and 83 deletions

View file

@ -90,6 +90,38 @@ export const getMessages = once(() => {
url:
'https://www.elastic.co/guide/en/machine-learning/{{version}}/ml-configuring-aggregation.html',
},
cardinality_no_results: {
status: VALIDATION_STATUS.WARNING,
heading: i18n.translate(
'xpack.ml.models.jobValidation.messages.cardinalityNoResultsHeading',
{
defaultMessage: 'Field cardinality',
}
),
text: i18n.translate('xpack.ml.models.jobValidation.messages.cardinalityNoResultsMessage', {
defaultMessage: `Cardinality checks could not be run. The query to validate fields didn't return any documents.`,
}),
},
cardinality_field_not_exists: {
status: VALIDATION_STATUS.WARNING,
heading: i18n.translate(
'xpack.ml.models.jobValidation.messages.cardinalityFieldNotExistsHeading',
{
defaultMessage: 'Field cardinality',
}
),
text: i18n.translate(
'xpack.ml.models.jobValidation.messages.cardinalityFieldNotExistsMessage',
{
defaultMessage: `Cardinality checks could not be run for field {fieldName}. The query to validate the field didn't return any documents.`,
values: {
fieldName: '"{{fieldName}}"',
},
}
),
url:
'https://www.elastic.co/guide/en/machine-learning/{{version}}/ml-configuring-aggregation.html',
},
cardinality_by_field: {
status: VALIDATION_STATUS.WARNING,
text: i18n.translate('xpack.ml.models.jobValidation.messages.cardinalityByFieldMessage', {

View file

@ -208,60 +208,103 @@ export class ValidateJobUI extends Component {
const duration = typeof getDuration === 'function' ? getDuration() : undefined;
const fields = this.props.fields;
// Run job validation only if a job config has been passed on and the duration makes sense to run it.
// Otherwise we skip the call and display a generic warning, but let the user move on to the next wizard step.
if (typeof job === 'object') {
let shouldShowLoadingIndicator = true;
if (typeof duration === 'object' && duration.start !== null && duration.end !== null) {
let shouldShowLoadingIndicator = true;
this.props.ml
.validateJob({ duration, fields, job })
.then((messages) => {
shouldShowLoadingIndicator = false;
this.setState({
...this.state,
ui: {
...this.state.ui,
iconType: statusToEuiIconType(getMostSevereMessageStatus(messages)),
isLoading: false,
isModalVisible: true,
},
data: {
messages,
success: true,
},
title: job.job_id,
});
if (typeof this.props.setIsValid === 'function') {
this.props.setIsValid(
messages.some((m) => m.status === VALIDATION_STATUS.ERROR) === false
this.props.ml
.validateJob({ duration, fields, job })
.then((messages) => {
shouldShowLoadingIndicator = false;
const messagesContainError = messages.some((m) => m.status === VALIDATION_STATUS.ERROR);
if (messagesContainError) {
messages.push({
id: 'job_validation_includes_error',
text: i18n.translate('xpack.ml.validateJob.jobValidationIncludesErrorText', {
defaultMessage:
'Job validation has failed, but you can still continue and create the job. Please be aware the job may encounter problems when running.',
}),
status: VALIDATION_STATUS.WARNING,
});
}
this.setState({
...this.state,
ui: {
...this.state.ui,
iconType: statusToEuiIconType(getMostSevereMessageStatus(messages)),
isLoading: false,
isModalVisible: true,
},
data: {
messages,
success: true,
},
title: job.job_id,
});
if (typeof this.props.setIsValid === 'function') {
this.props.setIsValid(!messagesContainError);
}
})
.catch((error) => {
const { toasts } = this.props.kibana.services.notifications;
const toastNotificationService = toastNotificationServiceProvider(toasts);
toastNotificationService.displayErrorToast(
error,
i18n.translate('xpack.ml.jobService.validateJobErrorTitle', {
defaultMessage: 'Job Validation Error',
})
);
}
})
.catch((error) => {
const { toasts } = this.props.kibana.services.notifications;
const toastNotificationService = toastNotificationServiceProvider(toasts);
toastNotificationService.displayErrorToast(
error,
i18n.translate('xpack.ml.jobService.validateJobErrorTitle', {
defaultMessage: 'Job Validation Error',
})
);
});
// wait for 250ms before triggering the loading indicator
// to avoid flickering when there's a loading time below
// 250ms for the job validation data
const delay = 250;
setTimeout(() => {
if (shouldShowLoadingIndicator) {
this.setState({
...this.state,
ui: {
...this.state.ui,
isLoading: true,
isModalVisible: false,
},
});
// wait for 250ms before triggering the loading indicator
// to avoid flickering when there's a loading time below
// 250ms for the job validation data
const delay = 250;
setTimeout(() => {
if (shouldShowLoadingIndicator) {
this.setState({
...this.state,
ui: {
...this.state.ui,
isLoading: true,
isModalVisible: false,
},
});
}
}, delay);
} else {
this.setState({
...this.state,
ui: {
...this.state.ui,
iconType: statusToEuiIconType(VALIDATION_STATUS.WARNING),
isLoading: false,
isModalVisible: true,
},
data: {
messages: [
{
id: 'job_validation_skipped',
text: i18n.translate('xpack.ml.validateJob.jobValidationSkippedText', {
defaultMessage:
'Job validation could not be run because of insufficient sample data. Please be aware the job may encounter problems when running.',
}),
status: VALIDATION_STATUS.WARNING,
},
],
success: true,
},
title: job.job_id,
});
if (typeof this.props.setIsValid === 'function') {
this.props.setIsValid(true);
}
}, delay);
}
}
};

View file

@ -27,6 +27,7 @@ const job = {
};
const getJobConfig = () => job;
const getDuration = () => ({ start: 0, end: 1 });
function prepareTest(messages) {
const p = Promise.resolve(messages);
@ -40,7 +41,9 @@ function prepareTest(messages) {
},
};
const component = <ValidateJob getJobConfig={getJobConfig} ml={ml} kibana={kibana} />;
const component = (
<ValidateJob getDuration={getDuration} getJobConfig={getJobConfig} ml={ml} kibana={kibana} />
);
const wrapper = shallowWithIntl(component);

View file

@ -4,7 +4,7 @@
* you may not use this file except in compliance with the Elastic License.
*/
import React, { Fragment, FC, useContext, useState, useEffect } from 'react';
import React, { Fragment, FC, useContext, useEffect } from 'react';
import { WizardNav } from '../wizard_nav';
import { WIZARD_STEPS, StepProps } from '../step_types';
import { JobCreatorContext } from '../job_creator_context';
@ -21,7 +21,6 @@ const idFilterList = [
export const ValidationStep: FC<StepProps> = ({ setCurrentStep, isCurrentStep }) => {
const { jobCreator, jobCreatorUpdate, jobValidator } = useContext(JobCreatorContext);
const [nextActive, setNextActive] = useState(false);
if (jobCreator.type === JOB_TYPE.ADVANCED) {
// for advanced jobs, ignore time range warning as the
@ -50,13 +49,8 @@ export const ValidationStep: FC<StepProps> = ({ setCurrentStep, isCurrentStep })
}, []);
// keep a record of the advanced validation in the jobValidator
// and disable the next button if any advanced checks have failed.
// note, it is not currently possible to get to a state where any of the
// advanced validation checks return an error because they are all
// caught in previous basic checks
function setIsValid(valid: boolean) {
jobValidator.advancedValid = valid;
setNextActive(valid);
}
return (
@ -74,7 +68,7 @@ export const ValidationStep: FC<StepProps> = ({ setCurrentStep, isCurrentStep })
<WizardNav
previous={() => setCurrentStep(WIZARD_STEPS.JOB_DETAILS)}
next={() => setCurrentStep(WIZARD_STEPS.SUMMARY)}
nextActive={nextActive}
nextActive={true}
/>
</Fragment>
)}

View file

@ -12,7 +12,7 @@ import type { MlClient } from '../../lib/ml_client';
const callAs = {
fieldCaps: () => Promise.resolve({ body: { fields: [] } }),
search: () => Promise.resolve({ body: { hits: { total: { value: 0, relation: 'eq' } } } }),
search: () => Promise.resolve({ body: { hits: { total: { value: 1, relation: 'eq' } } } }),
};
const mlClusterClient = ({

View file

@ -189,6 +189,38 @@ describe('ML - validateCardinality', () => {
);
});
it('cardinality no results', () => {
const job = getJobConfig('partition_field_name');
const mockCardinality = cloneDeep(mockResponses);
mockCardinality.search.hits.total.value = 0;
mockCardinality.search.aggregations.airline_count.doc_count = 0;
return validateCardinality(
mlClusterClientFactory(mockCardinality),
(job as unknown) as CombinedJob
).then((messages) => {
const ids = messages.map((m) => m.id);
expect(ids).toStrictEqual(['cardinality_no_results']);
});
});
it('cardinality field not exists', () => {
const job = getJobConfig('partition_field_name');
const mockCardinality = cloneDeep(mockResponses);
mockCardinality.search.hits.total.value = 1;
mockCardinality.search.aggregations.airline_count.doc_count = 0;
return validateCardinality(
mlClusterClientFactory(mockCardinality),
(job as unknown) as CombinedJob
).then((messages) => {
const ids = messages.map((m) => m.id);
expect(ids).toStrictEqual(['cardinality_field_not_exists']);
});
});
it('fields not aggregatable', () => {
const job = getJobConfig('partition_field_name');
job.analysis_config.detectors.push({

View file

@ -132,35 +132,54 @@ const validateFactory = (client: IScopedClusterClient, job: CombinedJob): Valida
datafeedConfig
);
uniqueFieldNames.forEach((uniqueFieldName) => {
const field = stats.aggregatableExistsFields.find(
(fieldData) => fieldData.fieldName === uniqueFieldName
);
if (field !== undefined && typeof field === 'object' && field.stats) {
modelPlotCardinality +=
modelPlotConfigFieldCount > 0 ? modelPlotConfigFieldCount : field.stats.cardinality!;
if (stats.totalCount === 0) {
messages.push({
id: 'cardinality_no_results',
});
} else {
uniqueFieldNames.forEach((uniqueFieldName) => {
const aggregatableNotExistsField = stats.aggregatableNotExistsFields.find(
(fieldData) => fieldData.fieldName === uniqueFieldName
);
if (isInvalid(field.stats.cardinality!)) {
if (aggregatableNotExistsField !== undefined) {
messages.push({
id: messageId || (`cardinality_${type}_field` as MessageId),
id: 'cardinality_field_not_exists',
fieldName: uniqueFieldName,
});
} else {
const field = stats.aggregatableExistsFields.find(
(fieldData) => fieldData.fieldName === uniqueFieldName
);
if (field !== undefined && typeof field === 'object' && field.stats) {
modelPlotCardinality +=
modelPlotConfigFieldCount > 0
? modelPlotConfigFieldCount
: field.stats.cardinality!;
if (isInvalid(field.stats.cardinality!)) {
messages.push({
id: messageId || (`cardinality_${type}_field` as MessageId),
fieldName: uniqueFieldName,
});
}
} else {
// only report uniqueFieldName as not aggregatable if it's not part
// of a valid categorization configuration and if it's not a scripted field or runtime mapping.
if (
!isValidCategorizationConfig(job, uniqueFieldName) &&
!isScriptField(job, uniqueFieldName) &&
!isRuntimeMapping(job, uniqueFieldName)
) {
messages.push({
id: 'field_not_aggregatable',
fieldName: uniqueFieldName,
});
}
}
}
} else {
// only report uniqueFieldName as not aggregatable if it's not part
// of a valid categorization configuration and if it's not a scripted field or runtime mapping.
if (
!isValidCategorizationConfig(job, uniqueFieldName) &&
!isScriptField(job, uniqueFieldName) &&
!isRuntimeMapping(job, uniqueFieldName)
) {
messages.push({
id: 'field_not_aggregatable',
fieldName: uniqueFieldName,
});
}
}
});
});
}
} catch (e) {
// checkAggregatableFieldsExist may return an error if 'fielddata' is
// disabled for text fields (which is the default). If there was only