[ML] AIOps: Refactors function argument structure for Log Rate Analysis.

[walterra]

Summary

Part of #178613.

Refactors the function argument structure of code used on Kibana server for Log Rate Analysis from individual arguments to single objects that contain all options. The options structure looks like this:

{
  // "meta" args like dependencies, general callbacks etc. on the outer most level
  esClient,
  abortSignal,
  ...
  // within "arguments" we pass in actual options that are necessary for the logic of the function
  arguments: {
    start,
    end,
    query,
    fields,
    ...
  }
}

The main benefit is that code where these functions are used become easier to read. Instead of the strict order of args that sometimes included undefined or just a value where it's hard to guess for which argument it's used for, this enforces to have the names of options show up in the consuming code. Here's an example:

Before:

await fetchHistogramsForFields(
                client,
                requestBody.index,
                histogramQuery,
                [
                  {
                    fieldName: requestBody.timeFieldName,
                    type: KBN_FIELD_TYPES.DATE,
                    interval: overallTimeSeries.interval,
                    min: overallTimeSeries.stats[0],
                    max: overallTimeSeries.stats[1],
                  },
                ],
                -1,
                undefined,
                abortSignal,
                stateHandler.sampleProbability(),
                RANDOM_SAMPLER_SEED
              )

After:

                (await fetchHistogramsForFields({
                  esClient,
                  abortSignal,
                  arguments: {
                    indexPattern: requestBody.index,
                    query: histogramQuery,
                    fields: [
                      {
                        fieldName: requestBody.timeFieldName,
                        type: KBN_FIELD_TYPES.DATE,
                        interval: overallTimeSeries.interval,
                        min: overallTimeSeries.stats[0],
                        max: overallTimeSeries.stats[1],
                      },
                    ],
                    samplerShardSize: -1,
                    randomSamplerProbability: stateHandler.sampleProbability(),
                    randomSamplerSeed: RANDOM_SAMPLER_SEED,
                  },
                })) as [NumericChartData]

Checklist

• Unit or functional tests were updated or added to match the most common scenarios
• This was checked for breaking API changes and was labeled appropriately

[elasticmachine]

Pinging @elastic/ml-ui (:ml)

[elasticmachine]

💛 Build succeeded, but was flaky

• Buildkite Build
• Commit: 1526118

Failed CI Steps

• Jest Tests #2

Test Failures

• [job] [logs] Jest Tests #2 / useSetupTechnology should not update agent policy and selected policy tab when setup technology matches the current one

Metrics [docs]

Any counts in public APIs

Total count of every any typed public API. Target amount is 0. Run node scripts/build_api_docs --plugin [yourplugin] --stats any for more detailed information.

id	before	after	diff
@kbn/ml-agg-utils	2	1	-1

Unknown metric groups

API count

id	before	after	diff
@kbn/ml-agg-utils	102	90	-12

History

• 💛 Build #219907 was flaky be4457b
• 💔 Build #219841 failed 7d10eb69105e49eda7e5f30306688bdc8bd5ecdf

cc @walterra

[peteharverson]

Code LGTM - a nice refactor to make the code easier to read.

[alvarezmelissa87]

LGTM ⚡