From ae5666b09b4c7efeacd0e191bb5a7334cd67ed5a Mon Sep 17 00:00:00 2001
From: Kibana Machine <42973632+kibanamachine@users.noreply.github.com>
Date: Mon, 20 Feb 2023 05:51:20 -0500
Subject: [PATCH] [8.7] [ML] Fixing ML saved object cache (#151122) (#151589)

# Backport

This will backport the following commits from `main` to `8.7`:
- [[ML] Fixing ML saved object cache
(#151122)](https://github.com/elastic/kibana/pull/151122)

<!--- Backport version: 8.9.7 -->

### Questions ?
Please refer to the [Backport tool
documentation](https://github.com/sqren/backport)

<!--BACKPORT [{"author":{"name":"James
Gowdy","email":"jgowdy@elastic.co"},"sourceCommit":{"committedDate":"2023-02-20T09:41:14Z","message":"[ML]
Fixing ML saved object cache (#151122)\n\nPR
https://github.com/elastic/kibana/pull/146155 introduced a cache
of\r\nthe ML saved objects to the `mlSavedObjectService` to
improve\r\nperformance.\r\n\r\nThis can cause a problem for the module
`setup` function when called\r\nmore than once from an external plugin
in a single request.\r\nA single instance of the `mlSavedObjectService`
is used per request and\r\nso for each `setup` call the same cache is
used. Any saved objects\r\ncreated, updated or removed in the first
`setup` call are missing from\r\nthe cache in subsequent
calls.\r\n\r\nThis means any jobs being created in the second call to
`setup` cannot\r\nbe opened as do not exist in the cache.\r\n\r\nThis PR
clears the cache after every write action to the saved object\r\nclient
causing it to be repopulated the next time it is
read.","sha":"f6bb0f4fccab76791ef292ebd90df581c3fbdac6","branchLabelMapping":{"^v8.8.0$":"main","^v(\\d+).(\\d+).\\d+$":"$1.$2"}},"sourcePullRequest":{"labels":["bug","non-issue",":ml","Feature:Anomaly
Detection","release_note:skip","v8.7.0","v8.8.0"],"number":151122,"url":"https://github.com/elastic/kibana/pull/151122","mergeCommit":{"message":"[ML]
Fixing ML saved object cache (#151122)\n\nPR
https://github.com/elastic/kibana/pull/146155 introduced a cache
of\r\nthe ML saved objects to the `mlSavedObjectService` to
improve\r\nperformance.\r\n\r\nThis can cause a problem for the module
`setup` function when called\r\nmore than once from an external plugin
in a single request.\r\nA single instance of the `mlSavedObjectService`
is used per request and\r\nso for each `setup` call the same cache is
used. Any saved objects\r\ncreated, updated or removed in the first
`setup` call are missing from\r\nthe cache in subsequent
calls.\r\n\r\nThis means any jobs being created in the second call to
`setup` cannot\r\nbe opened as do not exist in the cache.\r\n\r\nThis PR
clears the cache after every write action to the saved object\r\nclient
causing it to be repopulated the next time it is
read.","sha":"f6bb0f4fccab76791ef292ebd90df581c3fbdac6"}},"sourceBranch":"main","suggestedTargetBranches":["8.7"],"targetPullRequestStates":[{"branch":"8.7","label":"v8.7.0","labelRegex":"^v(\\d+).(\\d+).\\d+$","isSourceBranch":false,"state":"NOT_CREATED"},{"branch":"main","label":"v8.8.0","labelRegex":"^v8.8.0$","isSourceBranch":true,"state":"MERGED","url":"https://github.com/elastic/kibana/pull/151122","number":151122,"mergeCommit":{"message":"[ML]
Fixing ML saved object cache (#151122)\n\nPR
https://github.com/elastic/kibana/pull/146155 introduced a cache
of\r\nthe ML saved objects to the `mlSavedObjectService` to
improve\r\nperformance.\r\n\r\nThis can cause a problem for the module
`setup` function when called\r\nmore than once from an external plugin
in a single request.\r\nA single instance of the `mlSavedObjectService`
is used per request and\r\nso for each `setup` call the same cache is
used. Any saved objects\r\ncreated, updated or removed in the first
`setup` call are missing from\r\nthe cache in subsequent
calls.\r\n\r\nThis means any jobs being created in the second call to
`setup` cannot\r\nbe opened as do not exist in the cache.\r\n\r\nThis PR
clears the cache after every write action to the saved object\r\nclient
causing it to be repopulated the next time it is
read.","sha":"f6bb0f4fccab76791ef292ebd90df581c3fbdac6"}}]}] BACKPORT-->

Co-authored-by: James Gowdy <jgowdy@elastic.co>
---
 .../ml/server/saved_objects/service.ts        | 28 +++++++++++++++++--
 1 file changed, 26 insertions(+), 2 deletions(-)

diff --git a/x-pack/plugins/ml/server/saved_objects/service.ts b/x-pack/plugins/ml/server/saved_objects/service.ts
index 1c31b6d0d088d..d05972a1368ee 100644
--- a/x-pack/plugins/ml/server/saved_objects/service.ts
+++ b/x-pack/plugins/ml/server/saved_objects/service.ts
@@ -63,6 +63,12 @@ export function mlSavedObjectServiceFactory(
     (options: SavedObjectsFindOptions) => JSON.stringify(options)
   );
 
+  function _clearSavedObjectsClientCache() {
+    if (_savedObjectsClientFindMemo.cache.clear) {
+      _savedObjectsClientFindMemo.cache.clear();
+    }
+  }
+
   async function _getJobObjects(
     jobType?: JobType,
     jobId?: string,
@@ -118,6 +124,7 @@ export function mlSavedObjectServiceFactory(
         } else {
           // the saved object has no spaces, this is unexpected, attempt a normal delete
           await savedObjectsClient.delete(ML_JOB_SAVED_OBJECT_TYPE, id, { force: true });
+          _clearSavedObjectsClientCache();
         }
       }
     } catch (error) {
@@ -128,11 +135,12 @@ export function mlSavedObjectServiceFactory(
     await savedObjectsClient.create<JobObject>(ML_JOB_SAVED_OBJECT_TYPE, job, {
       id,
     });
+    _clearSavedObjectsClientCache();
   }
 
   async function _bulkCreateJobs(jobs: Array<{ job: JobObject; namespaces: string[] }>) {
     await isMlReady();
-    return await savedObjectsClient.bulkCreate<JobObject>(
+    const results = await savedObjectsClient.bulkCreate<JobObject>(
       jobs.map((j) => ({
         type: ML_JOB_SAVED_OBJECT_TYPE,
         id: _jobSavedObjectId(j.job),
@@ -140,6 +148,8 @@ export function mlSavedObjectServiceFactory(
         initialNamespaces: j.namespaces,
       }))
     );
+    _clearSavedObjectsClientCache();
+    return results;
   }
 
   function _jobSavedObjectId(job: JobObject) {
@@ -154,6 +164,7 @@ export function mlSavedObjectServiceFactory(
     }
 
     await savedObjectsClient.delete(ML_JOB_SAVED_OBJECT_TYPE, job.id, { force: true });
+    _clearSavedObjectsClientCache();
   }
 
   async function _forceDeleteJob(jobType: JobType, jobId: string, namespace: string) {
@@ -169,6 +180,7 @@ export function mlSavedObjectServiceFactory(
       namespace: namespace === '*' ? undefined : namespace,
       force: true,
     });
+    _clearSavedObjectsClientCache();
   }
 
   async function createAnomalyDetectionJob(jobId: string, datafeedId?: string) {
@@ -250,6 +262,7 @@ export function mlSavedObjectServiceFactory(
     const jobObject = job.attributes;
     jobObject.datafeed_id = datafeedId;
     await savedObjectsClient.update<JobObject>(ML_JOB_SAVED_OBJECT_TYPE, job.id, jobObject);
+    _clearSavedObjectsClientCache();
   }
 
   async function deleteDatafeed(datafeedId: string) {
@@ -262,6 +275,7 @@ export function mlSavedObjectServiceFactory(
     const jobObject = job.attributes;
     jobObject.datafeed_id = null;
     await savedObjectsClient.update<JobObject>(ML_JOB_SAVED_OBJECT_TYPE, job.id, jobObject);
+    _clearSavedObjectsClientCache();
   }
 
   async function _getIds(jobType: JobType, idType: keyof JobObject) {
@@ -372,6 +386,8 @@ export function mlSavedObjectServiceFactory(
         spacesToAdd,
         spacesToRemove
       );
+      _clearSavedObjectsClientCache();
+
       updateResult.objects.forEach(({ id: objectId, error }) => {
         const jobId = jobObjectIdMap.get(objectId)!;
         if (error) {
@@ -492,6 +508,7 @@ export function mlSavedObjectServiceFactory(
           await savedObjectsClient.delete(ML_TRAINED_MODEL_SAVED_OBJECT_TYPE, modelId, {
             force: true,
           });
+          _clearSavedObjectsClientCache();
         }
       }
     } catch (error) {
@@ -518,6 +535,7 @@ export function mlSavedObjectServiceFactory(
         ...(initialNamespaces ? { initialNamespaces } : {}),
       }
     );
+    _clearSavedObjectsClientCache();
   }
 
   async function _bulkCreateTrainedModel(models: TrainedModelObject[], namespaceFallback?: string) {
@@ -528,7 +546,7 @@ export function mlSavedObjectServiceFactory(
       return acc;
     }, {} as Record<string, string[] | undefined>);
 
-    return await savedObjectsClient.bulkCreate<TrainedModelObject>(
+    const results = await savedObjectsClient.bulkCreate<TrainedModelObject>(
       models.map((m) => {
         let initialNamespaces = m.job && namespacesPerJob[m.job.job_id];
         if (!initialNamespaces?.length && namespaceFallback) {
@@ -546,6 +564,8 @@ export function mlSavedObjectServiceFactory(
         };
       })
     );
+    _clearSavedObjectsClientCache();
+    return results;
   }
 
   async function getAllTrainedModelObjectsForAllSpaces(modelIds?: string[]) {
@@ -577,6 +597,7 @@ export function mlSavedObjectServiceFactory(
     }
 
     await savedObjectsClient.delete(ML_TRAINED_MODEL_SAVED_OBJECT_TYPE, model.id, { force: true });
+    _clearSavedObjectsClientCache();
   }
 
   async function _forceDeleteTrainedModel(modelId: string, namespace: string) {
@@ -586,6 +607,7 @@ export function mlSavedObjectServiceFactory(
       namespace: namespace === '*' ? undefined : namespace,
       force: true,
     });
+    _clearSavedObjectsClientCache();
   }
 
   async function filterTrainedModelsForSpace<T>(list: T[], field: keyof T): Promise<T[]> {
@@ -729,6 +751,8 @@ export function mlSavedObjectServiceFactory(
         spacesToAdd,
         spacesToRemove
       );
+      _clearSavedObjectsClientCache();
+
       updateResult.objects.forEach(({ id: objectId, error }) => {
         const model = trainedModelObjectIdMap.get(objectId)!;
         if (error) {