[ML] Use constant metric, revert code removal, update function descri…

…ption type signature

x-pack/plugins/ml/public/application/components/anomalies_table/anomaly_details.js

@@ -38,6 +38,7 @@ import {
 import { MULTI_BUCKET_IMPACT } from '../../../../common/constants/multi_bucket_impact';
 import { formatValue } from '../../formatters/format_value';
 import { MAX_CHARS } from './anomalies_table_constants';
+import { ML_JOB_AGGREGATION } from '../../../../common/constants/aggregation_types';
 
 const TIME_FIELD_NAME = 'timestamp';
 
@@ -130,7 +131,8 @@ function getDetailsItems(anomaly, examples, filter) {
     title: i18n.translate('xpack.ml.anomaliesTable.anomalyDetails.functionTitle', {
       defaultMessage: 'function',
     }),
-    description: source.function !== 'metric' ? source.function : source.function_description,
+    description:
+      source.function !== ML_JOB_AGGREGATION.METRIC ? source.function : source.function_description,
   });
 
   if (source.field_name !== undefined) {

x-pack/plugins/ml/public/application/explorer/explorer_charts/explorer_chart_config_builder.js

@@ -14,6 +14,7 @@ import { getEntityFieldList } from '../../../../common/util/anomaly_utils';
 import { buildConfigFromDetector } from '../../util/chart_config_builder';
 import { mlJobService } from '../../services/job_service';
 import { mlFunctionToESAggregation } from '../../../../common/util/job_utils';
+import { ML_JOB_AGGREGATION } from '../../../../common/constants/aggregation_types';
 
 // Builds the chart configuration for the provided anomaly record, returning
 // an object with properties used for the display (series function and field, aggregation interval etc),
@@ -49,7 +50,7 @@ export function buildConfig(record) {
   // define the metric series to be plotted.
   config.entityFields = getEntityFieldList(record);
 
-  if (record.function === 'metric') {
+  if (record.function === ML_JOB_AGGREGATION.METRIC) {
     config.metricFunction = mlFunctionToESAggregation(record.function_description);
   }
 

x-pack/plugins/ml/public/application/services/ml_api_service/results.ts

@@ -26,7 +26,7 @@ export const resultsApiProvider = (httpService: HttpService) => ({
     maxRecords: number,
     maxExamples?: number,
     influencersFilterQuery?: any,
-    functionDescription?: string | undefined
+    functionDescription?: string
   ) {
     const body = JSON.stringify({
       jobIds,

x-pack/plugins/ml/public/application/services/results_service/result_service_rx.ts

@@ -351,7 +351,7 @@ export function resultsServiceRxProvider(mlApiServices: MlApiServices) {
       earliestMs: number | null,
       latestMs: number | null,
       maxResults: number | undefined,
-      functionDescription?: string | undefined
+      functionDescription?: string
     ): Observable<RecordsForCriteria> {
       const obj: RecordsForCriteria = { success: true, records: [] };
 

x-pack/plugins/ml/public/application/timeseriesexplorer/get_function_description.ts

@@ -10,6 +10,7 @@ import { ToastNotificationService } from '../services/toast_notification_service
 import { getControlsForDetector } from './get_controls_for_detector';
 import { getCriteriaFields } from './get_criteria_fields';
 import { CombinedJob } from '../../../common/types/anomaly_detection_jobs';
+import { ML_JOB_AGGREGATION } from '../../../common/constants/aggregation_types';
 
 /**
  * Get the function description from the record with the highest anomaly score
@@ -30,7 +31,11 @@ export const getFunctionDescription = async (
 ) => {
   // if the detector's function is metric, fetch the highest scoring anomaly record
   // and set to plot the function_description (avg/min/max) of that record by default
-  if (selectedJob?.analysis_config?.detectors[selectedDetectorIndex]?.function !== 'metric') return;
+  if (
+    selectedJob?.analysis_config?.detectors[selectedDetectorIndex]?.function !==
+    ML_JOB_AGGREGATION.METRIC
+  )
+    return;
 
   const entityControls = getControlsForDetector(
     selectedDetectorIndex,

x-pack/plugins/ml/public/application/timeseriesexplorer/timeseriesexplorer.js

@@ -428,9 +428,11 @@ export class TimeSeriesExplorer extends React.Component {
 
     const { loadCounter: currentLoadCounter, functionDescription } = this.state;
 
-    const functionToPlotByIfMetric = aggregationTypeTransform.toES(functionDescription);
-
     const currentSelectedJob = mlJobService.getJob(selectedJobId);
+    if (currentSelectedJob === undefined) {
+      return;
+    }
+    const functionToPlotByIfMetric = aggregationTypeTransform.toES(functionDescription);
 
     this.contextChartSelectedInitCallDone = false;
 

x-pack/plugins/ml/public/application/timeseriesexplorer/timeseriesexplorer_utils/get_focus_data.ts

@@ -53,7 +53,7 @@ export function getFocusData(
   nonBlankEntities: any[],
   searchBounds: any,
   selectedJob: Job,
-  functionDescription: string | undefined
+  functionDescription?: string | undefined
 ): Observable<FocusData> {
   const esFunctionToPlotIfMetric =
     functionDescription !== undefined

x-pack/plugins/ml/public/application/timeseriesexplorer/timeseriesexplorer_utils/timeseriesexplorer_utils.js

@@ -19,6 +19,7 @@ import { parseInterval } from '../../../../common/util/parse_interval';
 import { getBoundsRoundedToInterval, getTimeBucketsFromCache } from '../../util/time_buckets';
 
 import { CHARTS_POINT_TARGET, TIME_FIELD_NAME } from '../timeseriesexplorer_constants';
+import { ML_JOB_AGGREGATION } from '../../../../common/constants/aggregation_types';
 
 // create new job objects based on standard job config objects
 // new job objects just contain job id, bucket span in seconds and a selected flag.
@@ -143,7 +144,11 @@ export function processDataForFocusAnomalies(
     // Look for a chart point with the same time as the record.
     // If none found, find closest time in chartData set.
     const recordTime = record[TIME_FIELD_NAME];
-    if (record.function === 'metric' && record.function_description !== functionDescription) return;
+    if (
+      record.function === ML_JOB_AGGREGATION.METRIC &&
+      record.function_description !== functionDescription
+    )
+      return;
 
     const chartPoint = findChartPointForAnomalyTime(chartData, recordTime, aggregationInterval);
     if (chartPoint !== undefined) {
@@ -163,7 +168,7 @@ export function processDataForFocusAnomalies(
             chartPoint.value = record.actual;
           }
 
-          if (record.function === 'metric') {
+          if (record.function === ML_JOB_AGGREGATION.METRIC) {
             chartPoint.value = Array.isArray(record.actual) ? record.actual[0] : record.actual;
           }
 

x-pack/plugins/ml/server/models/results_service/results_service.ts

@@ -55,7 +55,7 @@ export function resultsServiceProvider(mlClient: MlClient) {
     maxRecords: number = ANOMALIES_TABLE_DEFAULT_QUERY_SIZE,
     maxExamples: number = DEFAULT_MAX_EXAMPLES,
     influencersFilterQuery?: any,
-    functionDescription?: string | undefined
+    functionDescription?: string
   ) {
     // Build the query to return the matching anomaly record results.
     // Add criteria for the time range, record score, plus any specified job IDs.