From 7bec588ae61e2e6d18bb92ed2cbce252fcce401c Mon Sep 17 00:00:00 2001 From: Pete Harverson Date: Mon, 2 Mar 2020 11:31:17 +0000 Subject: [PATCH 1/3] [ML] Add support for date_nanos time field in anomaly job wizard --- .../server/models/job_validation/messages.js | 2 +- .../job_validation/validate_time_range.js | 80 -------------- .../job_validation/validate_time_range.ts | 104 ++++++++++++++++++ 3 files changed, 105 insertions(+), 81 deletions(-) delete mode 100644 x-pack/plugins/ml/server/models/job_validation/validate_time_range.js create mode 100644 x-pack/plugins/ml/server/models/job_validation/validate_time_range.ts diff --git a/x-pack/plugins/ml/server/models/job_validation/messages.js b/x-pack/plugins/ml/server/models/job_validation/messages.js index 33931f03facc3..55315d4586d3c 100644 --- a/x-pack/plugins/ml/server/models/job_validation/messages.js +++ b/x-pack/plugins/ml/server/models/job_validation/messages.js @@ -495,7 +495,7 @@ export const getMessages = () => { time_field_invalid: { status: 'ERROR', text: i18n.translate('xpack.ml.models.jobValidation.messages.timeFieldInvalidMessage', { - defaultMessage: `{timeField} cannot be used as the time-field because it's not a valid field of type 'date'.`, + defaultMessage: `{timeField} cannot be used as the time field because it's not a valid field of type 'date'.`, values: { timeField: `'{{timeField}}'`, }, diff --git a/x-pack/plugins/ml/server/models/job_validation/validate_time_range.js b/x-pack/plugins/ml/server/models/job_validation/validate_time_range.js deleted file mode 100644 index e6a92b45649b0..0000000000000 --- a/x-pack/plugins/ml/server/models/job_validation/validate_time_range.js +++ /dev/null @@ -1,80 +0,0 @@ -/* - * 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 _ from 'lodash'; - -import { ES_FIELD_TYPES } from '../../../../../../src/plugins/data/server'; -import { parseInterval } from '../../../../../legacy/plugins/ml/common/util/parse_interval'; -import { validateJobObject } from './validate_job_object'; - -const BUCKET_SPAN_COMPARE_FACTOR = 25; -const MIN_TIME_SPAN_MS = 7200000; -const MIN_TIME_SPAN_READABLE = '2 hours'; - -export async function isValidTimeField(callWithRequest, job) { - const index = job.datafeed_config.indices.join(','); - const timeField = job.data_description.time_field; - - // check if time_field is of type 'date' - const fieldCaps = await callWithRequest('fieldCaps', { - index, - fields: [timeField], - }); - // get the field's type with the following notation - // because a nested field could contain dots and confuse _.get - const fieldType = _.get(fieldCaps, `fields['${timeField}'].date.type`); - return fieldType === ES_FIELD_TYPES.DATE; -} - -export async function validateTimeRange(callWithRequest, job, duration) { - const messages = []; - - validateJobObject(job); - - // check if time_field is of type 'date' - if (!(await isValidTimeField(callWithRequest, job))) { - messages.push({ - id: 'time_field_invalid', - timeField: job.data_description.time_field, - }); - // if the time field is invalid, skip all other checks - return Promise.resolve(messages); - } - - // if there is no duration, do not run the estimate test - if ( - typeof duration === 'undefined' || - typeof duration.start === 'undefined' || - typeof duration.end === 'undefined' - ) { - return Promise.resolve(messages); - } - - // check if time range is after the Unix epoch start - if (duration.start < 0 || duration.end < 0) { - messages.push({ id: 'time_range_before_epoch' }); - } - - // check for minimum time range (25 buckets or 2 hours, whichever is longer) - const bucketSpan = parseInterval(job.analysis_config.bucket_span).valueOf(); - const minTimeSpanBasedOnBucketSpan = bucketSpan * BUCKET_SPAN_COMPARE_FACTOR; - const timeSpan = duration.end - duration.start; - const minRequiredTimeSpan = Math.max(MIN_TIME_SPAN_MS, minTimeSpanBasedOnBucketSpan); - - if (minRequiredTimeSpan > timeSpan) { - messages.push({ - id: 'time_range_short', - minTimeSpanReadable: MIN_TIME_SPAN_READABLE, - bucketSpanCompareFactor: BUCKET_SPAN_COMPARE_FACTOR, - }); - } - - if (messages.length === 0) { - messages.push({ id: 'success_time_range' }); - } - - return messages; -} diff --git a/x-pack/plugins/ml/server/models/job_validation/validate_time_range.ts b/x-pack/plugins/ml/server/models/job_validation/validate_time_range.ts new file mode 100644 index 0000000000000..8008388bbd435 --- /dev/null +++ b/x-pack/plugins/ml/server/models/job_validation/validate_time_range.ts @@ -0,0 +1,104 @@ +/* + * 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 { ES_FIELD_TYPES } from '../../../../../../src/plugins/data/server'; +import { parseInterval } from '../../../../../legacy/plugins/ml/common/util/parse_interval'; +import { CombinedJob } from '../../../../../legacy/plugins/ml/public/application/jobs/new_job/common/job_creator/configs'; +import { callWithRequestType } from '../../../../../legacy/plugins/ml/common/types/kibana'; +// @ts-ignore +import { validateJobObject } from './validate_job_object'; + +interface ValidateTimeRangeMessage { + id: string; + timeField?: string; + minTimeSpanReadable?: string; + bucketSpanCompareFactor?: number; +} + +interface TimeRange { + start: number; + end: number; +} + +const BUCKET_SPAN_COMPARE_FACTOR = 25; +const MIN_TIME_SPAN_MS = 7200000; +const MIN_TIME_SPAN_READABLE = '2 hours'; + +export async function isValidTimeField(callWithRequest: callWithRequestType, job: CombinedJob) { + const index = job.datafeed_config.indices.join(','); + const timeField = job.data_description.time_field; + + // check if time_field is of type 'date' or 'date_nanos' + const fieldCaps = await callWithRequest('fieldCaps', { + index, + fields: [timeField], + }); + + let fieldType = fieldCaps.fields[timeField]?.date?.type; + if (fieldType === undefined) { + fieldType = fieldCaps.fields[timeField]?.date_nanos?.type; + } + return fieldType === ES_FIELD_TYPES.DATE || fieldType === ES_FIELD_TYPES.DATE_NANOS; +} + +export async function validateTimeRange( + callWithRequest: callWithRequestType, + job: CombinedJob, + timeRange: TimeRange | undefined +) { + const messages: ValidateTimeRangeMessage[] = []; + + validateJobObject(job); + + // check if time_field is a date type + if (!(await isValidTimeField(callWithRequest, job))) { + messages.push({ + id: 'time_field_invalid', + timeField: job.data_description.time_field, + }); + // if the time field is invalid, skip all other checks + return Promise.resolve(messages); + } + + // if there is no duration, do not run the estimate test + if ( + typeof timeRange === 'undefined' || + typeof timeRange.start === 'undefined' || + typeof timeRange.end === 'undefined' + ) { + return Promise.resolve(messages); + } + + // check if time range is after the Unix epoch start + if (timeRange.start < 0 || timeRange.end < 0) { + messages.push({ id: 'time_range_before_epoch' }); + } + + // check for minimum time range (25 buckets or 2 hours, whichever is longer) + const interval = parseInterval(job.analysis_config.bucket_span); + if (interval === null) { + messages.push({ id: 'bucket_span_invalid' }); + } else { + const bucketSpan: number = interval.asMilliseconds(); + const minTimeSpanBasedOnBucketSpan = bucketSpan * BUCKET_SPAN_COMPARE_FACTOR; + const timeSpan = timeRange.end - timeRange.start; + const minRequiredTimeSpan = Math.max(MIN_TIME_SPAN_MS, minTimeSpanBasedOnBucketSpan); + + if (minRequiredTimeSpan > timeSpan) { + messages.push({ + id: 'time_range_short', + minTimeSpanReadable: MIN_TIME_SPAN_READABLE, + bucketSpanCompareFactor: BUCKET_SPAN_COMPARE_FACTOR, + }); + } + } + + if (messages.length === 0) { + messages.push({ id: 'success_time_range' }); + } + + return messages; +} From 00ce82faccfdbc1c5b5f151dde7d232849dda63f Mon Sep 17 00:00:00 2001 From: Pete Harverson Date: Tue, 3 Mar 2020 17:11:47 +0000 Subject: [PATCH 2/3] [ML] Edits following review --- .../ml/server/models/job_validation/messages.js | 2 +- .../models/job_validation/validate_time_range.ts | 14 +++++++------- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/x-pack/plugins/ml/server/models/job_validation/messages.js b/x-pack/plugins/ml/server/models/job_validation/messages.js index 55315d4586d3c..105d642560cc7 100644 --- a/x-pack/plugins/ml/server/models/job_validation/messages.js +++ b/x-pack/plugins/ml/server/models/job_validation/messages.js @@ -495,7 +495,7 @@ export const getMessages = () => { time_field_invalid: { status: 'ERROR', text: i18n.translate('xpack.ml.models.jobValidation.messages.timeFieldInvalidMessage', { - defaultMessage: `{timeField} cannot be used as the time field because it's not a valid field of type 'date'.`, + defaultMessage: `{timeField} cannot be used as the time field because it is not a field of type 'date' or 'date_nanos'.`, values: { timeField: `'{{timeField}}'`, }, diff --git a/x-pack/plugins/ml/server/models/job_validation/validate_time_range.ts b/x-pack/plugins/ml/server/models/job_validation/validate_time_range.ts index 8008388bbd435..551b5ab9173a4 100644 --- a/x-pack/plugins/ml/server/models/job_validation/validate_time_range.ts +++ b/x-pack/plugins/ml/server/models/job_validation/validate_time_range.ts @@ -4,10 +4,10 @@ * you may not use this file except in compliance with the Elastic License. */ +import { APICaller } from 'src/core/server'; import { ES_FIELD_TYPES } from '../../../../../../src/plugins/data/server'; import { parseInterval } from '../../../../../legacy/plugins/ml/common/util/parse_interval'; import { CombinedJob } from '../../../../../legacy/plugins/ml/public/application/jobs/new_job/common/job_creator/configs'; -import { callWithRequestType } from '../../../../../legacy/plugins/ml/common/types/kibana'; // @ts-ignore import { validateJobObject } from './validate_job_object'; @@ -27,12 +27,12 @@ const BUCKET_SPAN_COMPARE_FACTOR = 25; const MIN_TIME_SPAN_MS = 7200000; const MIN_TIME_SPAN_READABLE = '2 hours'; -export async function isValidTimeField(callWithRequest: callWithRequestType, job: CombinedJob) { +export async function isValidTimeField(callAsCurrentUser: APICaller, job: CombinedJob) { const index = job.datafeed_config.indices.join(','); const timeField = job.data_description.time_field; // check if time_field is of type 'date' or 'date_nanos' - const fieldCaps = await callWithRequest('fieldCaps', { + const fieldCaps = await callAsCurrentUser('fieldCaps', { index, fields: [timeField], }); @@ -45,7 +45,7 @@ export async function isValidTimeField(callWithRequest: callWithRequestType, job } export async function validateTimeRange( - callWithRequest: callWithRequestType, + callAsCurrentUser: APICaller, job: CombinedJob, timeRange: TimeRange | undefined ) { @@ -54,13 +54,13 @@ export async function validateTimeRange( validateJobObject(job); // check if time_field is a date type - if (!(await isValidTimeField(callWithRequest, job))) { + if (!(await isValidTimeField(callAsCurrentUser, job))) { messages.push({ id: 'time_field_invalid', timeField: job.data_description.time_field, }); // if the time field is invalid, skip all other checks - return Promise.resolve(messages); + return messages; } // if there is no duration, do not run the estimate test @@ -69,7 +69,7 @@ export async function validateTimeRange( typeof timeRange.start === 'undefined' || typeof timeRange.end === 'undefined' ) { - return Promise.resolve(messages); + return messages; } // check if time range is after the Unix epoch start From 15fa7cf42300c8c676f9fa30f6889838b5f949b5 Mon Sep 17 00:00:00 2001 From: Pete Harverson Date: Wed, 4 Mar 2020 16:51:09 +0000 Subject: [PATCH 3/3] [ML] Add functional test for creating job off date_nanos data --- .../anomaly_detection/date_nanos_job.ts | 440 +++++ .../anomaly_detection/index.ts | 1 + .../ml/event_rate_nanos/data.json.gz | Bin 0 -> 1656445 bytes .../ml/event_rate_nanos/mappings.json | 1477 +++++++++++++++++ 4 files changed, 1918 insertions(+) create mode 100644 x-pack/test/functional/apps/machine_learning/anomaly_detection/date_nanos_job.ts create mode 100644 x-pack/test/functional/es_archives/ml/event_rate_nanos/data.json.gz create mode 100644 x-pack/test/functional/es_archives/ml/event_rate_nanos/mappings.json diff --git a/x-pack/test/functional/apps/machine_learning/anomaly_detection/date_nanos_job.ts b/x-pack/test/functional/apps/machine_learning/anomaly_detection/date_nanos_job.ts new file mode 100644 index 0000000000000..2a9824f46778d --- /dev/null +++ b/x-pack/test/functional/apps/machine_learning/anomaly_detection/date_nanos_job.ts @@ -0,0 +1,440 @@ +/* + * 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'; + +interface Detector { + identifier: string; + function: string; + field?: string; + byField?: string; + overField?: string; + partitionField?: string; + excludeFrequent?: string; + description?: string; +} + +interface DatafeedConfig { + queryDelay?: string; + frequency?: string; + scrollSize?: string; +} + +interface PickFieldsConfig { + detectors: Detector[]; + influencers: string[]; + bucketSpan: string; + memoryLimit: string; + summaryCountField?: string; +} + +// type guards +// Detector +const isDetectorWithField = (arg: any): arg is Required> => { + return arg.hasOwnProperty('field'); +}; +const isDetectorWithByField = (arg: any): arg is Required> => { + return arg.hasOwnProperty('byField'); +}; +const isDetectorWithOverField = (arg: any): arg is Required> => { + return arg.hasOwnProperty('overField'); +}; +const isDetectorWithPartitionField = ( + arg: any +): arg is Required> => { + return arg.hasOwnProperty('partitionField'); +}; +const isDetectorWithExcludeFrequent = ( + arg: any +): arg is Required> => { + return arg.hasOwnProperty('excludeFrequent'); +}; +const isDetectorWithDescription = (arg: any): arg is Required> => { + return arg.hasOwnProperty('description'); +}; + +// DatafeedConfig +const isDatafeedConfigWithQueryDelay = ( + arg: any +): arg is Required> => { + return arg.hasOwnProperty('queryDelay'); +}; +const isDatafeedConfigWithFrequency = ( + arg: any +): arg is Required> => { + return arg.hasOwnProperty('frequency'); +}; +const isDatafeedConfigWithScrollSize = ( + arg: any +): arg is Required> => { + return arg.hasOwnProperty('scrollSize'); +}; + +// PickFieldsConfig +const isPickFieldsConfigWithSummaryCountField = ( + arg: any +): arg is Required> => { + return arg.hasOwnProperty('summaryCountField'); +}; + +// eslint-disable-next-line import/no-default-export +export default function({ getService }: FtrProviderContext) { + const esArchiver = getService('esArchiver'); + const ml = getService('ml'); + + const defaultValues = { + datafeedQuery: `{ + "bool": { + "must": [ + { + "match_all": {} + } + ] + } +}`, + queryDelay: '60s', + frequency: '450s', + scrollSize: '1000', + }; + + const testDataList = [ + { + suiteTitle: 'with count detector and model plot disabled', + jobSource: 'event_rate_gen_trend_nanos', + jobId: `event_rate_nanos_count_1_${Date.now()}`, + jobDescription: + 'Create advanced job based on the event rate dataset with a date_nanos time field, 30m bucketspan and count', + jobGroups: ['automated', 'event-rate', 'date-nanos'], + pickFieldsConfig: { + detectors: [ + { + identifier: 'count', + function: 'count', + description: 'event rate', + } as Detector, + ], + summaryCountField: 'count', + influencers: [], + bucketSpan: '30m', + memoryLimit: '10mb', + } as PickFieldsConfig, + datafeedConfig: {} as DatafeedConfig, + expected: { + wizard: { + timeField: '@timestamp', + }, + row: { + recordCount: '105,120', + memoryStatus: 'ok', + jobState: 'closed', + datafeedState: 'stopped', + latestTimestamp: '2016-01-01 00:00:00', + }, + counts: { + processed_record_count: '105,120', + processed_field_count: '105,120', + input_bytes: '4.2 MB', + input_field_count: '105,120', + invalid_date_count: '0', + missing_field_count: '0', + out_of_order_timestamp_count: '0', + empty_bucket_count: '0', + sparse_bucket_count: '0', + bucket_count: '17,520', + earliest_record_timestamp: '2015-01-01 00:10:00', + latest_record_timestamp: '2016-01-01 00:00:00', + input_record_count: '105,120', + latest_bucket_timestamp: '2016-01-01 00:00:00', + }, + modelSizeStats: { + result_type: 'model_size_stats', + model_bytes_exceeded: '0.0 B', + model_bytes_memory_limit: '10.0 MB', + total_by_field_count: '3', + total_over_field_count: '0', + total_partition_field_count: '2', + bucket_allocation_failures_count: '0', + memory_status: 'ok', + timestamp: '2015-12-31 23:30:00', + }, + }, + }, + ]; + + describe('job on data set with date_nanos time field', function() { + this.tags(['smoke', 'mlqa']); + before(async () => { + await esArchiver.load('ml/event_rate_nanos'); + await ml.securityUI.loginAsMlPowerUser(); + }); + + after(async () => { + await esArchiver.unload('ml/event_rate_nanos'); + await ml.api.cleanMlIndices(); + }); + + for (const testData of testDataList) { + describe(`${testData.suiteTitle}`, function() { + it('job creation loads the job management page', async () => { + await ml.navigation.navigateToMl(); + await ml.navigation.navigateToJobManagement(); + }); + + it('job creation loads the new job source selection page', async () => { + await ml.jobManagement.navigateToNewJobSourceSelection(); + }); + + it('job creation loads the job type selection page', async () => { + await ml.jobSourceSelection.selectSourceForAnomalyDetectionJob(testData.jobSource); + }); + + it('job creation loads the advanced job wizard page', async () => { + await ml.jobTypeSelection.selectAdvancedJob(); + }); + + it('job creation displays the configure datafeed step', async () => { + await ml.jobWizardCommon.assertConfigureDatafeedSectionExists(); + }); + + it('job creation pre-fills the datafeed query editor', async () => { + await ml.jobWizardAdvanced.assertDatafeedQueryEditorExists(); + await ml.jobWizardAdvanced.assertDatafeedQueryEditorValue(defaultValues.datafeedQuery); + }); + + it('job creation inputs the query delay', async () => { + await ml.jobWizardAdvanced.assertQueryDelayInputExists(); + await ml.jobWizardAdvanced.assertQueryDelayValue(defaultValues.queryDelay); + if (isDatafeedConfigWithQueryDelay(testData.datafeedConfig)) { + await ml.jobWizardAdvanced.setQueryDelay(testData.datafeedConfig.queryDelay); + } + }); + + it('job creation inputs the frequency', async () => { + await ml.jobWizardAdvanced.assertFrequencyInputExists(); + await ml.jobWizardAdvanced.assertFrequencyValue(defaultValues.frequency); + if (isDatafeedConfigWithFrequency(testData.datafeedConfig)) { + await ml.jobWizardAdvanced.setFrequency(testData.datafeedConfig.frequency); + } + }); + + it('job creation inputs the scroll size', async () => { + await ml.jobWizardAdvanced.assertScrollSizeInputExists(); + await ml.jobWizardAdvanced.assertScrollSizeValue(defaultValues.scrollSize); + if (isDatafeedConfigWithScrollSize(testData.datafeedConfig)) { + await ml.jobWizardAdvanced.setScrollSize(testData.datafeedConfig.scrollSize); + } + }); + + it('job creation pre-fills the time field', async () => { + await ml.jobWizardAdvanced.assertTimeFieldInputExists(); + await ml.jobWizardAdvanced.assertTimeFieldSelection([testData.expected.wizard.timeField]); + }); + + it('job creation displays the pick fields step', async () => { + await ml.jobWizardCommon.advanceToPickFieldsSection(); + }); + + it('job creation selects the summary count field', async () => { + await ml.jobWizardAdvanced.assertSummaryCountFieldInputExists(); + if (isPickFieldsConfigWithSummaryCountField(testData.pickFieldsConfig)) { + await ml.jobWizardAdvanced.selectSummaryCountField( + testData.pickFieldsConfig.summaryCountField + ); + } else { + await ml.jobWizardAdvanced.assertSummaryCountFieldSelection([]); + } + }); + + it('job creation adds detectors', async () => { + for (const detector of testData.pickFieldsConfig.detectors) { + await ml.jobWizardAdvanced.openCreateDetectorModal(); + await ml.jobWizardAdvanced.assertDetectorFunctionInputExists(); + await ml.jobWizardAdvanced.assertDetectorFunctionSelection([]); + await ml.jobWizardAdvanced.assertDetectorFieldInputExists(); + await ml.jobWizardAdvanced.assertDetectorFieldSelection([]); + await ml.jobWizardAdvanced.assertDetectorByFieldInputExists(); + await ml.jobWizardAdvanced.assertDetectorByFieldSelection([]); + await ml.jobWizardAdvanced.assertDetectorOverFieldInputExists(); + await ml.jobWizardAdvanced.assertDetectorOverFieldSelection([]); + await ml.jobWizardAdvanced.assertDetectorPartitionFieldInputExists(); + await ml.jobWizardAdvanced.assertDetectorPartitionFieldSelection([]); + await ml.jobWizardAdvanced.assertDetectorExcludeFrequentInputExists(); + await ml.jobWizardAdvanced.assertDetectorExcludeFrequentSelection([]); + await ml.jobWizardAdvanced.assertDetectorDescriptionInputExists(); + await ml.jobWizardAdvanced.assertDetectorDescriptionValue(''); + + await ml.jobWizardAdvanced.selectDetectorFunction(detector.function); + if (isDetectorWithField(detector)) { + await ml.jobWizardAdvanced.selectDetectorField(detector.field); + } + if (isDetectorWithByField(detector)) { + await ml.jobWizardAdvanced.selectDetectorByField(detector.byField); + } + if (isDetectorWithOverField(detector)) { + await ml.jobWizardAdvanced.selectDetectorOverField(detector.overField); + } + if (isDetectorWithPartitionField(detector)) { + await ml.jobWizardAdvanced.selectDetectorPartitionField(detector.partitionField); + } + if (isDetectorWithExcludeFrequent(detector)) { + await ml.jobWizardAdvanced.selectDetectorExcludeFrequent(detector.excludeFrequent); + } + if (isDetectorWithDescription(detector)) { + await ml.jobWizardAdvanced.setDetectorDescription(detector.description); + } + + await ml.jobWizardAdvanced.confirmAddDetectorModal(); + } + }); + + it('job creation displays detector entries', async () => { + for (const [index, detector] of testData.pickFieldsConfig.detectors.entries()) { + await ml.jobWizardAdvanced.assertDetectorEntryExists( + index, + detector.identifier, + isDetectorWithDescription(detector) ? detector.description : undefined + ); + } + }); + + it('job creation inputs the bucket span', async () => { + await ml.jobWizardCommon.assertBucketSpanInputExists(); + await ml.jobWizardCommon.setBucketSpan(testData.pickFieldsConfig.bucketSpan); + }); + + it('job creation inputs influencers', async () => { + await ml.jobWizardCommon.assertInfluencerInputExists(); + await ml.jobWizardCommon.assertInfluencerSelection([]); + for (const influencer of testData.pickFieldsConfig.influencers) { + await ml.jobWizardCommon.addInfluencer(influencer); + } + }); + + it('job creation inputs the model memory limit', async () => { + await ml.jobWizardCommon.assertModelMemoryLimitInputExists({ + withAdvancedSection: false, + }); + await ml.jobWizardCommon.setModelMemoryLimit(testData.pickFieldsConfig.memoryLimit, { + withAdvancedSection: false, + }); + }); + + it('job creation displays the job details step', async () => { + await ml.jobWizardCommon.advanceToJobDetailsSection(); + }); + + it('job creation inputs the job id', async () => { + await ml.jobWizardCommon.assertJobIdInputExists(); + await ml.jobWizardCommon.setJobId(testData.jobId); + }); + + it('job creation inputs the job description', async () => { + await ml.jobWizardCommon.assertJobDescriptionInputExists(); + await ml.jobWizardCommon.setJobDescription(testData.jobDescription); + }); + + it('job creation inputs job groups', async () => { + await ml.jobWizardCommon.assertJobGroupInputExists(); + for (const jobGroup of testData.jobGroups) { + await ml.jobWizardCommon.addJobGroup(jobGroup); + } + await ml.jobWizardCommon.assertJobGroupSelection(testData.jobGroups); + }); + + it('job creation opens the additional settings section', async () => { + await ml.jobWizardCommon.ensureAdditionalSettingsSectionOpen(); + }); + + it('job creation displays the model plot switch', async () => { + await ml.jobWizardCommon.assertModelPlotSwitchExists({ withAdvancedSection: false }); + }); + + it('job creation enables the dedicated index switch', async () => { + await ml.jobWizardCommon.assertDedicatedIndexSwitchExists({ withAdvancedSection: false }); + await ml.jobWizardCommon.activateDedicatedIndexSwitch({ withAdvancedSection: false }); + }); + + it('job creation displays the validation step', async () => { + await ml.jobWizardCommon.advanceToValidationSection(); + }); + + it('job creation displays the summary step', async () => { + await ml.jobWizardCommon.advanceToSummarySection(); + }); + + it('job creation creates the job and finishes processing', async () => { + await ml.jobWizardCommon.assertCreateJobButtonExists(); + await ml.jobWizardAdvanced.createJob(); + await ml.jobManagement.assertStartDatafeedModalExists(); + await ml.jobManagement.confirmStartDatafeedModal(); + await ml.jobManagement.waitForJobCompletion(testData.jobId); + }); + + it('job creation displays the created job in the job list', async () => { + await ml.jobTable.refreshJobList(); + await ml.jobTable.filterWithSearchString(testData.jobId); + const rows = await ml.jobTable.parseJobTable(); + expect(rows.filter(row => row.id === testData.jobId)).to.have.length(1); + }); + + it('job creation displays details for the created job in the job list', async () => { + await ml.jobTable.assertJobRowFields(testData.jobId, { + id: testData.jobId, + description: testData.jobDescription, + jobGroups: [...new Set(testData.jobGroups)].sort(), + recordCount: testData.expected.row.recordCount, + memoryStatus: testData.expected.row.memoryStatus, + jobState: testData.expected.row.jobState, + datafeedState: testData.expected.row.datafeedState, + latestTimestamp: testData.expected.row.latestTimestamp, + }); + + await ml.jobTable.assertJobRowDetailsCounts( + testData.jobId, + { + job_id: testData.jobId, + processed_record_count: testData.expected.counts.processed_record_count, + processed_field_count: testData.expected.counts.processed_field_count, + input_bytes: testData.expected.counts.input_bytes, + input_field_count: testData.expected.counts.input_field_count, + invalid_date_count: testData.expected.counts.invalid_date_count, + missing_field_count: testData.expected.counts.missing_field_count, + out_of_order_timestamp_count: testData.expected.counts.out_of_order_timestamp_count, + empty_bucket_count: testData.expected.counts.empty_bucket_count, + sparse_bucket_count: testData.expected.counts.sparse_bucket_count, + bucket_count: testData.expected.counts.bucket_count, + earliest_record_timestamp: testData.expected.counts.earliest_record_timestamp, + latest_record_timestamp: testData.expected.counts.latest_record_timestamp, + input_record_count: testData.expected.counts.input_record_count, + latest_bucket_timestamp: testData.expected.counts.latest_bucket_timestamp, + }, + { + job_id: testData.jobId, + result_type: testData.expected.modelSizeStats.result_type, + model_bytes_exceeded: testData.expected.modelSizeStats.model_bytes_exceeded, + model_bytes_memory_limit: testData.expected.modelSizeStats.model_bytes_memory_limit, + total_by_field_count: testData.expected.modelSizeStats.total_by_field_count, + total_over_field_count: testData.expected.modelSizeStats.total_over_field_count, + total_partition_field_count: + testData.expected.modelSizeStats.total_partition_field_count, + bucket_allocation_failures_count: + testData.expected.modelSizeStats.bucket_allocation_failures_count, + memory_status: testData.expected.modelSizeStats.memory_status, + timestamp: testData.expected.modelSizeStats.timestamp, + } + ); + }); + + it('job creation has detector results', async () => { + for (let i = 0; i < testData.pickFieldsConfig.detectors.length; i++) { + await ml.api.assertDetectorResultsExist(testData.jobId, i); + } + }); + }); + } + }); +} diff --git a/x-pack/test/functional/apps/machine_learning/anomaly_detection/index.ts b/x-pack/test/functional/apps/machine_learning/anomaly_detection/index.ts index 28e8b221cff4e..402c67589e285 100644 --- a/x-pack/test/functional/apps/machine_learning/anomaly_detection/index.ts +++ b/x-pack/test/functional/apps/machine_learning/anomaly_detection/index.ts @@ -17,5 +17,6 @@ export default function({ loadTestFile }: FtrProviderContext) { loadTestFile(require.resolve('./single_metric_viewer')); loadTestFile(require.resolve('./anomaly_explorer')); loadTestFile(require.resolve('./categorization_job')); + loadTestFile(require.resolve('./date_nanos_job')); }); } diff --git a/x-pack/test/functional/es_archives/ml/event_rate_nanos/data.json.gz b/x-pack/test/functional/es_archives/ml/event_rate_nanos/data.json.gz new file mode 100644 index 0000000000000000000000000000000000000000..838b8d1872c0aa3532f092bce96d24200800d397 GIT binary patch literal 1656445 zcmXtgc_38n`+mDrZz`2ng-=BiQg(w;NkS-;EEz45J-cC+N~IEtB+JaCEGcW2$u^S~ zD$9_49c4Kf3=T8KnDKkgyx-rS&z$2~@8`a+>$>klE_&m}`U5U5tJdDQ8g%ujXP}?& zs&6E-I2WD#hg{ySlN~xzX$o$^8gZnb#X1k8<|aR0Pm)nQDU7hV_&aCA0o9|Qv-VW~ z?2O%ezsdOd&Y#=@3H0*J+hQXZ5^nxyl$>E0cIEAghf!4}f7ypWQm`bkAV)E{wZc+k z50IUQtc@ZBWL~{;wgmgjRFJT)m!gZmJx3FyCxj|yyN9|k4fV_6vEliqZdO98Sf~}7 zOv7mi$5NC0FiiS#JxgsRlr#MOXKHb!noBAD?y80Bg>mBO)61s^CGV^#Y*Tee^yAVq zg-%=y&Cu|}%9;yrV5V?-MeJ*eeq-8FD^qS+P$NbZ7)@3c*H{@+6C{s6%i4DpDlm%b 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"sendUsageFrom": { + "ignore_above": 256, + "type": "keyword" + }, + "userHasSeenNotice": { + "type": "boolean" + } + } + }, + "timelion-sheet": { + "properties": { + "description": { + "type": "text" + }, + "hits": { + "type": "integer" + }, + "kibanaSavedObjectMeta": { + "properties": { + "searchSourceJSON": { + "type": "text" + } + } + }, + "timelion_chart_height": { + "type": "integer" + }, + "timelion_columns": { + "type": "integer" + }, + "timelion_interval": { + "type": "keyword" + }, + "timelion_other_interval": { + "type": "keyword" + }, + "timelion_rows": { + "type": "integer" + }, + "timelion_sheet": { + "type": "text" + }, + "title": { + "type": "text" + }, + "version": { + "type": "integer" + } + } + }, + "tsvb-validation-telemetry": { + "properties": { + "failedRequests": { + "type": "long" + } + } + }, + "type": { + "type": "keyword" + }, + "ui-metric": { + "properties": { + "count": { + "type": "integer" + } + } + }, + "updated_at": { + "type": "date" + }, + "upgrade-assistant-reindex-operation": { + "dynamic": "true", + "properties": { + "indexName": { + "type": "keyword" + }, + "status": { + "type": "integer" + } + } + }, + "upgrade-assistant-telemetry": { + "properties": { + "features": { + "properties": { + "deprecation_logging": { + "properties": { + "enabled": { + "null_value": true, + "type": "boolean" + } + } + } + } + }, + "ui_open": { + "properties": { + "cluster": { + "null_value": 0, + "type": "long" + }, + "indices": { + "null_value": 0, + "type": "long" + }, + "overview": { + "null_value": 0, + "type": "long" + } + } + }, + "ui_reindex": { + "properties": { + "close": { + "null_value": 0, + "type": "long" + }, + "open": { + "null_value": 0, + "type": "long" + }, + "start": { + "null_value": 0, + "type": "long" + }, + "stop": { + "null_value": 0, + "type": "long" + } + } + } + } + }, + "url": { + "properties": { + "accessCount": { + "type": "long" + }, + "accessDate": { + "type": "date" + }, + "createDate": { + "type": "date" 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