88 lines
2.7 KiB
Plaintext
88 lines
2.7 KiB
Plaintext
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[role="xpack"]
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[testenv="platinum"]
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[[ml-estimate-model-memory]]
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=== Estimate {anomaly-jobs} model memory API
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++++
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<titleabbrev>Estimate model memory</titleabbrev>
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++++
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Estimates the model memory an {anomaly-job} is likely to need based on analysis
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configuration details and cardinality estimates for the fields it references.
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[[ml-estimate-model-memory-request]]
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==== {api-request-title}
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`POST _ml/anomaly_detectors/_estimate_model_memory`
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[[ml-estimate-model-memory-prereqs]]
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==== {api-prereq-title}
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* If the {es} {security-features} are enabled, you must have `manage_ml` or
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`manage` cluster privileges to use this API. See
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<<security-privileges>>.
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[[ml-estimate-model-memory-request-body]]
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==== {api-request-body-title}
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`analysis_config`::
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(Required, object) For a list of the properties that you can specify in the
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`analysis_config` component of the body of this API, see <<put-analysisconfig>>.
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`max_bucket_cardinality`::
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(Optional, object) Estimates of the highest cardinality in a single bucket
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that will be observed for influencer fields over the time period that the job
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analyzes data. To produce a good answer, values must be provided for
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all influencer fields. It does not matter if values are provided for fields
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that are not listed as `influencers`. If there are no `influencers` then
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`max_bucket_cardinality` can be omitted from the request.
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`overall_cardinality`::
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(Optional, object) Estimates of the cardinality that will be observed for
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fields over the whole time period that the job analyzes data. To produce
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a good answer, values must be provided for fields referenced in the
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`by_field_name`, `over_field_name` and `partition_field_name` of any
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detectors. It does not matter if values are provided for other fields.
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If no detectors have a `by_field_name`, `over_field_name` or
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`partition_field_name` then `overall_cardinality` can be omitted
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from the request.
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[[ml-estimate-model-memory-example]]
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==== {api-examples-title}
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[source,console]
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--------------------------------------------------
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POST _ml/anomaly_detectors/_estimate_model_memory
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{
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"analysis_config": {
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"bucket_span": "5m",
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"detectors": [
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{
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"function": "sum",
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"field_name": "bytes",
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"by_field_name": "status",
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"partition_field_name": "app"
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}
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],
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"influencers": [ "source_ip", "dest_ip" ]
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},
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"overall_cardinality": {
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"status": 10,
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"app": 50
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},
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"max_bucket_cardinality": {
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"source_ip": 300,
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"dest_ip": 30
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}
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}
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--------------------------------------------------
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// TEST[skip:needs-licence]
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The estimate returns the following result:
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[source,console-result]
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----
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{
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"model_memory_estimate": "45mb"
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}
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----
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