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[ML][Inference] document new settings (#49309) (#49336) 

* [ML][Inference] document new settings

* [DOCS] Minor edits
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Benjamin Trent 2019-11-19 16:43:19 -05:00 committed by GitHub
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docs/reference/settings/ml-settings.asciidoc
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@ -50,6 +50,25 @@ IMPORTANT: If you want to use {ml} features in your cluster, you must have
`xpack.ml.enabled` set to `true` on all master-eligible nodes. This is the `xpack.ml.enabled` set to `true` on all master-eligible nodes. This is the
default behavior. default behavior.
`xpack.ml.inference_model.cache_size`::
The maximum inference cache size allowed. The inference cache exists in the JVM
heap on each ingest node. The cache affords faster processing times for the
`inference` processor. The value can be a static byte sized value (i.e. "2gb")
or a percentage of total allocated heap. The default is "40%".
`xpack.ml.inference_model.time_to_live`::
The time to live (TTL) for models in the inference model cache. The TTL is
calculated from last access. The `inference` processor attempts to load the
model from cache. If the `inference` processor does not receive any documents
for the duration of the TTL, the referenced model is flagged for eviction from
the cache. If a document is processed later, the model is again loaded into the
cache. Defaults to `5m`.
`xpack.ml.max_inference_processors` (<<cluster-update-settings,Dynamic>>)::
The total number of `inference` type processors allowed across all ingest
pipelines. Once the limit is reached, adding an `inference` processor to
a pipeline is disallowed. Defaults to `50`.
`xpack.ml.max_machine_memory_percent` (<<cluster-update-settings,Dynamic>>):: `xpack.ml.max_machine_memory_percent` (<<cluster-update-settings,Dynamic>>)::
The maximum percentage of the machine's memory that {ml} may use for running The maximum percentage of the machine's memory that {ml} may use for running
analytics processes. (These processes are separate to the {es} JVM.) Defaults to analytics processes. (These processes are separate to the {es} JVM.) Defaults to