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[ML] Frustrating experience creating DFA job when xpack.ml.max_model_memory_limit is set #60486

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droberts195 opened this issue Mar 18, 2020 · 3 comments
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Feature:Data Frame Analytics ML data frame analytics features :ml v7.8.0

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@droberts195
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droberts195 commented Mar 18, 2020

When xpack.ml.max_model_memory_limit is set it is possible that a particular data frame analytics job is impossible for the cluster to create and run successfully. But I can imagine that the way this manifests itself in the UI will cause immense frustration.

In the following example xpack.ml.max_model_memory_limit was set to 410mb.

After creating the initial config and clicking "Create" you get an error like this:

Screenshot 2020-03-18 at 10 57 22

The obvious reaction will then be to edit the model memory limit to bring it down to the maximum permitted:

Screenshot 2020-03-18 at 10 57 46

This works, and you can create the job, but then when you try to start it you get this error:

Screenshot 2020-03-18 at 10 58 04

Given that the backend code is so defensive about stopping you running a job that has a model memory limit less than the estimated requirement it would be better if the UI was also stricter, and broke the bad news that you cannot do what you want to at an earlier stage.

@droberts195 droberts195 added :ml Feature:Data Frame Analytics ML data frame analytics features labels Mar 18, 2020
@elasticmachine
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Pinging @elastic/ml-ui (:ml)

@droberts195
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#60496 is related to this, because if we make the UI refuse job creation at an earlier stage based on the latest model memory estimate it has then we need to make sure that that estimate reflects all the changes made to the config.

@alvarezmelissa87
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Closing this off as we haven't been able to reproduce it on latest master and the related fix (#62850) has gone in.

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Feature:Data Frame Analytics ML data frame analytics features :ml v7.8.0
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