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Wrong error message returned on delete trained model when model already deleted #105420

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maxhniebergall opened this issue Feb 12, 2024 · 2 comments · May be fixed by #107188
Open

Wrong error message returned on delete trained model when model already deleted #105420

maxhniebergall opened this issue Feb 12, 2024 · 2 comments · May be fixed by #107188
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>bug low-risk An open issue or test failure that is a low risk to future releases :ml Machine learning Team:ML Meta label for the ML team

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@maxhniebergall
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Elasticsearch Version

8.13

Installed Plugins

No response

Java Version

bundled

OS Version

23.3.0 Darwin Kernel Version 23.3.0 arm64 (M1 mac)

Problem Description

Calling DELETE _ml/trained_models/ when that model ID is referenced by an ingest processor / pipeline returns the error

  "error" : {
    "root_cause" : [
      {
        "type" : "status_exception",
        "reason" : "Cannot delete model [.elser_model_2] as it is still referenced by ingest processors; use force to delete the model"
      }
    ],

even when the model has already been force deleted.

Steps to Reproduce

PUT ELSER
(there should be a builtin pipeline referencing ELSER)
DELETE ELSER
(you should receive the error message)

Logs (if relevant)

No response

@maxhniebergall maxhniebergall added >bug needs:triage Requires assignment of a team area label :ml Machine learning low-risk An open issue or test failure that is a low risk to future releases and removed needs:triage Requires assignment of a team area label labels Feb 12, 2024
@elasticsearchmachine elasticsearchmachine added the Team:ML Meta label for the ML team label Feb 12, 2024
@elasticsearchmachine
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Pinging @elastic/ml-core (Team:ML)

@batcity
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batcity commented Apr 9, 2024

@maxhniebergall FYI I've added a PR to fix this issue: #107188. I'd appreciate it if you could take a look when you get a chance, thanks!

@maxhniebergall maxhniebergall removed their assignment May 15, 2024
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Labels
>bug low-risk An open issue or test failure that is a low risk to future releases :ml Machine learning Team:ML Meta label for the ML team
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3 participants