Sub partition in Machine Learning


Is it possible to make sub partitions in Machine Learning ?
domain and event are fields in every document.
I created a categorization ml job, with partition_field = domain, but this is not enough, I must split it by domain and event, and since its a categorization job, I already have by_field_name = mlcategory, so I guess the only way to achieve this is to concatenate domain and event and partition on it ?

this is the job config:

  "job_id": "test_ml",
  "description": "",
  "groups": [],
  "analysis_config": {
    "bucket_span": "15m",
    "detectors": [
        "function": "count",
        "by_field_name": "mlcategory",
        "partition_field_name": "domain"
    "influencers": [
    "categorization_field_name": "error"
  "data_description": {
    "time_field": "date_time"
  "analysis_limits": {
    "model_memory_limit": "139MB"
  "results_index_name": "test_ml"


Correct, since mlcategory is taking up the by_field_name, it is taking away your ability to double-split.

You'd need to create a scripted_field in your datafeed's query that was the concatenation of domain and event and then partition on this new domain_event field

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