[ML] Fix put job endpoint when payload contains datafeed (#134986)

* [ML] Fix put job endpoint when payload contains datafeed

* adding tests

x-pack/plugins/ml/server/routes/anomaly_detectors.ts

@@ -25,6 +25,7 @@ import {
   forceQuerySchema,
   jobResetQuerySchema,
 } from './schemas/anomaly_detectors_schema';
+import { getAuthorizationHeader } from '../lib/request_authorization';
 
 /**
  * Routes for the anomaly detectors
@@ -180,11 +181,14 @@ export function jobRoutes({ router, routeGuard }: RouteInitialization) {
     routeGuard.fullLicenseAPIGuard(async ({ mlClient, request, response }) => {
       try {
         const { jobId } = request.params;
-        const body = await mlClient.putJob({
+        const body = await mlClient.putJob(
+          {
             job_id: jobId,
             // @ts-expect-error job type custom_rules is incorrect
             body: request.body,
-        });
+          },
+          getAuthorizationHeader(request)
+        );
 
         return response.ok({
           body,

x-pack/plugins/ml/server/routes/schemas/anomaly_detectors_schema.ts

@@ -6,6 +6,7 @@
  */
 
 import { schema } from '@kbn/config-schema';
+import { datafeedConfigSchema } from './datafeeds_schema';
 
 const customRulesSchema = schema.maybe(
   schema.arrayOf(
@@ -121,7 +122,7 @@ export const anomalyDetectionJobSchema = {
   description: schema.maybe(schema.string()),
   established_model_memory: schema.maybe(schema.number()),
   finished_time: schema.maybe(schema.number()),
-  job_id: schema.string(),
+  job_id: schema.maybe(schema.string()),
   job_type: schema.maybe(schema.string()),
   job_version: schema.maybe(schema.string()),
   groups: schema.maybe(schema.arrayOf(schema.maybe(schema.string()))),
@@ -136,6 +137,7 @@ export const anomalyDetectionJobSchema = {
   results_index_name: schema.maybe(schema.string()),
   results_retention_days: schema.maybe(schema.number()),
   state: schema.maybe(schema.string()),
+  datafeed_config: schema.maybe(datafeedConfigSchema),
 };
 
 export const jobIdSchema = schema.object({

x-pack/test/api_integration/apis/ml/anomaly_detectors/create_with_datafeed.ts

@@ -0,0 +1,95 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+import expect from '@kbn/expect';
+
+import { FtrProviderContext } from '../../../ftr_provider_context';
+import { USER } from '../../../../functional/services/ml/security_common';
+import { COMMON_REQUEST_HEADERS } from '../../../../functional/services/ml/common_api';
+
+export default ({ getService }: FtrProviderContext) => {
+  const esArchiver = getService('esArchiver');
+  const supertest = getService('supertestWithoutAuth');
+  const ml = getService('ml');
+
+  const jobId = `fq_single_${Date.now()}`;
+
+  const testDataList = [
+    {
+      testTitle: 'ML Poweruser creates a single metric job with datafeed',
+      user: USER.ML_POWERUSER,
+      jobId: `${jobId}_1`,
+      requestBody: {
+        job_id: `${jobId}_1`,
+        description:
+          'Single metric job based on the farequote dataset with 30m bucketspan and mean(responsetime)',
+        groups: ['automated', 'farequote', 'single-metric'],
+        analysis_config: {
+          bucket_span: '30m',
+          detectors: [{ function: 'mean', field_name: 'responsetime' }],
+          influencers: [],
+          summary_count_field_name: 'doc_count',
+        },
+        data_description: { time_field: '@timestamp' },
+        analysis_limits: { model_memory_limit: '11MB' },
+        model_plot_config: { enabled: true },
+        datafeed_config: {
+          datafeed_id: `datafeed-${jobId}_1`,
+          indices: ['farequote-*'],
+          query: {
+            match_all: {},
+          },
+        },
+      },
+      expected: {
+        responseCode: 200,
+        responseBody: {
+          // skipping parts of the job config we're not going to check
+          // we're only interesting in the datafeed_config for this test
+          datafeed_config: {
+            job_id: `${jobId}_1`,
+            datafeed_id: `datafeed-${jobId}_1`,
+            indices: ['farequote-*'],
+            query: {
+              match_all: {},
+            },
+          },
+        },
+      },
+    },
+  ];
+
+  describe('PUT anomaly_detectors which contain a datafeed config', function () {
+    before(async () => {
+      await esArchiver.loadIfNeeded('x-pack/test/functional/es_archives/ml/farequote');
+      await ml.testResources.setKibanaTimeZoneToUTC();
+    });
+
+    after(async () => {
+      await ml.api.cleanMlIndices();
+    });
+
+    for (const testData of testDataList) {
+      it(`${testData.testTitle}`, async () => {
+        const { body, status } = await supertest
+          .put(`/api/ml/anomaly_detectors/${testData.jobId}`)
+          .auth(testData.user, ml.securityCommon.getPasswordForUser(testData.user))
+          .set(COMMON_REQUEST_HEADERS)
+          .send(testData.requestBody);
+        ml.api.assertResponseStatusCode(testData.expected.responseCode, status, body);
+
+        // Validate the important parts of the response.
+        const expectedResponse = testData.expected.responseBody;
+        expect(body.datafeed_config.datafeed_id).to.eql(
+          expectedResponse.datafeed_config.datafeed_id
+        );
+        expect(body.datafeed_config.job_id).to.eql(expectedResponse.datafeed_config.job_id);
+        expect(body.datafeed_config.indices).to.eql(expectedResponse.datafeed_config.indices);
+      });
+    }
+  });
+};

x-pack/test/api_integration/apis/ml/anomaly_detectors/index.ts

@@ -18,5 +18,6 @@ export default function ({ loadTestFile }: FtrProviderContext) {
     loadTestFile(require.resolve('./delete_with_spaces'));
     loadTestFile(require.resolve('./create_with_spaces'));
     loadTestFile(require.resolve('./forecast_with_spaces'));
+    loadTestFile(require.resolve('./create_with_datafeed'));
   });
 }