[ML] API integration tests for job validation (#66265)

* [ML] TS refactoring

* [ML] fix page overflow

* [ML] tests

* [ML] fix typing issues and unit tests

* [ML] remove string conversion

* [ML] indexOf checks

* [ML] fix tooltip overflow

* [ML] fix i18n

* [ML] fix unit tests

* [ML] use MlJobAggregation

* [ML] use enums

* Revert "[ML] fix tooltip overflow"

This reverts commit 103c36b

* Revert "[ML] fix page overflow"

This reverts commit 3c86922

x-pack/plugins/ml/common/types/data_recognizer.ts

@@ -8,7 +8,7 @@ export interface JobStat {
   id: string;
   earliestTimestampMs: number;
   latestTimestampMs: number;
-  latestResultsTimestampMs: number;
+  latestResultsTimestampMs: number | undefined;
 }
 
 export interface JobExistResult {

x-pack/plugins/ml/common/util/anomaly_utils.ts

@@ -29,7 +29,7 @@ export enum ENTITY_FIELD_TYPE {
 export interface EntityField {
   fieldName: string;
   fieldValue: string | number | undefined;
-  fieldType: ENTITY_FIELD_TYPE;
+  fieldType?: ENTITY_FIELD_TYPE;
 }
 
 // List of function descriptions for which actual values from record level results should be displayed.

x-pack/plugins/ml/common/util/job_utils.test.js → x-pack/plugins/ml/common/util/job_utils.test.ts

@@ -15,11 +15,11 @@ import {
   isJobVersionGte,
   mlFunctionToESAggregation,
   isJobIdValid,
-  ML_MEDIAN_PERCENTS,
   prefixDatafeedId,
   getSafeAggregationName,
   getLatestDataOrBucketTimestamp,
 } from './job_utils';
+import { CombinedJob, Job } from '../types/anomaly_detection_jobs';
 
 describe('ML - job utils', () => {
   describe('calculateDatafeedFrequencyDefaultSeconds', () => {
@@ -51,7 +51,7 @@ describe('ML - job utils', () => {
 
   describe('isTimeSeriesViewJob', () => {
     test('returns true when job has a single detector with a metric function', () => {
-      const job = {
+      const job = ({
         analysis_config: {
           detectors: [
             {
@@ -61,13 +61,13 @@ describe('ML - job utils', () => {
             },
           ],
         },
-      };
+      } as unknown) as CombinedJob;
 
       expect(isTimeSeriesViewJob(job)).toBe(true);
     });
 
     test('returns true when job has at least one detector with a metric function', () => {
-      const job = {
+      const job = ({
         analysis_config: {
           detectors: [
             {
@@ -83,13 +83,13 @@ describe('ML - job utils', () => {
             },
           ],
         },
-      };
+      } as unknown) as CombinedJob;
 
       expect(isTimeSeriesViewJob(job)).toBe(true);
     });
 
     test('returns false when job does not have at least one detector with a metric function', () => {
-      const job = {
+      const job = ({
         analysis_config: {
           detectors: [
             {
@@ -105,13 +105,13 @@ describe('ML - job utils', () => {
             },
           ],
         },
-      };
+      } as unknown) as CombinedJob;
 
       expect(isTimeSeriesViewJob(job)).toBe(false);
     });
 
     test('returns false when job has a single count by category detector', () => {
-      const job = {
+      const job = ({
         analysis_config: {
           detectors: [
             {
@@ -121,14 +121,14 @@ describe('ML - job utils', () => {
             },
           ],
         },
-      };
+      } as unknown) as CombinedJob;
 
       expect(isTimeSeriesViewJob(job)).toBe(false);
     });
   });
 
   describe('isTimeSeriesViewDetector', () => {
-    const job = {
+    const job = ({
       analysis_config: {
         detectors: [
           {
@@ -168,7 +168,7 @@ describe('ML - job utils', () => {
           },
         },
       },
-    };
+    } as unknown) as CombinedJob;
 
     test('returns true for a detector with a metric function', () => {
       expect(isTimeSeriesViewDetector(job, 0)).toBe(true);
@@ -192,7 +192,7 @@ describe('ML - job utils', () => {
   });
 
   describe('isSourceDataChartableForDetector', () => {
-    const job = {
+    const job = ({
       analysis_config: {
         detectors: [
           { function: 'count' }, // 0
@@ -251,7 +251,7 @@ describe('ML - job utils', () => {
           },
         },
       },
-    };
+    } as unknown) as CombinedJob;
 
     test('returns true for expected detectors', () => {
       expect(isSourceDataChartableForDetector(job, 0)).toBe(true);
@@ -299,13 +299,13 @@ describe('ML - job utils', () => {
   });
 
   describe('isModelPlotChartableForDetector', () => {
-    const job1 = {
+    const job1 = ({
       analysis_config: {
         detectors: [{ function: 'count' }],
       },
-    };
+    } as unknown) as Job;
 
-    const job2 = {
+    const job2 = ({
       analysis_config: {
         detectors: [
           { function: 'count' },
@@ -319,7 +319,7 @@ describe('ML - job utils', () => {
       model_plot_config: {
         enabled: true,
       },
-    };
+    } as unknown) as Job;
 
     test('returns false when model plot is not enabled', () => {
       expect(isModelPlotChartableForDetector(job1, 0)).toBe(false);
@@ -339,7 +339,7 @@ describe('ML - job utils', () => {
   });
 
   describe('getPartitioningFieldNames', () => {
-    const job = {
+    const job = ({
       analysis_config: {
         detectors: [
           {
@@ -367,7 +367,7 @@ describe('ML - job utils', () => {
           },
         ],
       },
-    };
+    } as unknown) as CombinedJob;
 
     test('returns empty array for a detector with no partitioning fields', () => {
       const resp = getPartitioningFieldNames(job, 0);
@@ -392,7 +392,7 @@ describe('ML - job utils', () => {
 
   describe('isModelPlotEnabled', () => {
     test('returns true for a job in which model plot has been enabled', () => {
-      const job = {
+      const job = ({
         analysis_config: {
           detectors: [
             {
@@ -405,13 +405,13 @@ describe('ML - job utils', () => {
         model_plot_config: {
           enabled: true,
         },
-      };
+      } as unknown) as Job;
 
       expect(isModelPlotEnabled(job, 0)).toBe(true);
     });
 
     test('returns expected values for a job in which model plot has been enabled with terms', () => {
-      const job = {
+      const job = ({
         analysis_config: {
           detectors: [
             {
@@ -426,7 +426,7 @@ describe('ML - job utils', () => {
           enabled: true,
           terms: 'US,AAL',
         },
-      };
+      } as unknown) as Job;
 
       expect(
         isModelPlotEnabled(job, 0, [
@@ -450,7 +450,7 @@ describe('ML - job utils', () => {
     });
 
     test('returns true for jobs in which model plot has not been enabled', () => {
-      const job1 = {
+      const job1 = ({
         analysis_config: {
           detectors: [
             {
@@ -463,18 +463,18 @@ describe('ML - job utils', () => {
         model_plot_config: {
           enabled: false,
         },
-      };
-      const job2 = {};
+      } as unknown) as CombinedJob;
+      const job2 = ({} as unknown) as CombinedJob;
 
       expect(isModelPlotEnabled(job1, 0)).toBe(false);
       expect(isModelPlotEnabled(job2, 0)).toBe(false);
     });
   });
 
   describe('isJobVersionGte', () => {
-    const job = {
+    const job = ({
       job_version: '6.1.1',
-    };
+    } as unknown) as CombinedJob;
 
     test('returns true for later job version', () => {
       expect(isJobVersionGte(job, '6.1.0')).toBe(true);
@@ -548,12 +548,6 @@ describe('ML - job utils', () => {
     });
   });
 
-  describe('ML_MEDIAN_PERCENTS', () => {
-    test("is '50.0'", () => {
-      expect(ML_MEDIAN_PERCENTS).toBe('50.0');
-    });
-  });
-
   describe('prefixDatafeedId', () => {
     test('returns datafeed-prefix-job from datafeed-job"', () => {
       expect(prefixDatafeedId('datafeed-job', 'prefix-')).toBe('datafeed-prefix-job');