[ML] Adding job overrides to the module setup endpoint

[jgowdyelastic]

Adds the ability to supply the /api/ml/modules/setup/{moduleId} endpoint with job and datafeed overrides in the form or partial job and datafeed configurations.
e.g. this will apply model_memory_limit: 13mb to all jobs in the module.

"jobOverrides": {
  "analysis_limits": {
     "model_memory_limit": "13mb"
  }
}

The overrides can be a single object or array of objects. If the object contains a job_id or datafeed_id, the overrides contained in that object will only be applied to the matching job or datafeed in the module.
If no id is specified, the overrides in the object will be applied to all jobs or datafeeds in the module.

The below example will set the bucket_span to 15m in all jobs and the model_memory_limit to 13mb for the job visitor_rate_ecs
It will also set the scroll_size to 1001 for all datafeeds and the frequency to 30m for the datafeed for the job visitor_rate_ecs
Rather than using the job_id in the datafeed, you could also have used:
"datafeed_id": "datafeed-visitor_rate_ecs"

{
  "jobOverrides":[{
    "job_id": "visitor_rate_ecs",
    "analysis_limits": {
      "model_memory_limit": "13mb"
    }
  }, {
    "analysis_config" : {
      "bucket_span": "15m"
    }
  }],
  "datafeedOverrides": [{
    "scroll_size": 1001
  }, {
    "job_id": "visitor_rate_ecs",
    "frequency": "30m"
  }]
}

These overrides are applied before any of the existing overridable options (e.g. useDedicatedIndex, groups, indexPatternName etc) and so can be overridden themselves.
In the below example, the match_all query will be used over the query passed in via the datafeedOverrides

{
  "query": {"bool":{"must":[{"match_all":{}}]}}
  "datafeedOverrides": {
    "query": {}
  }
}

Functional tests are needed for this change, which will be added in a follow up PR.

cc @weltenwort

Fixes #42409

Checklist

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• Unit or functional tests were updated or added to match the most common scenarios
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[elasticmachine]

Pinging @elastic/ml-ui

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[jgowdyelastic]

retest

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[alvarezmelissa87]

LGTM overall 👍 - just added a couple of small comments

[walterra]

LGTM

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[peteharverson]

LGTM