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[DOCS] Adds new dynamic machine learning settings (#34094)

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Lisa Cawley 2018-09-28 09:41:14 -07:00 committed by GitHub
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docs/reference/settings/ml-settings.asciidoc
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@ -1,15 +1,22 @@
[role="xpack"] [role="xpack"]
[[ml-settings]] [[ml-settings]]
=== Machine Learning Settings in Elasticsearch === Machine learning settings in Elasticsearch
++++ ++++
<titleabbrev>Machine Learning Settings</titleabbrev> <titleabbrev>Machine learning settings</titleabbrev>
++++ ++++
You do not need to configure any settings to use {ml}. It is enabled by default. You do not need to configure any settings to use {ml}. It is enabled by default.
All of these settings can be added to the `elasticsearch.yml` configuration file.
The dynamic settings can also be updated across a cluster with the
<<cluster-update-settings,cluster update settings API>>.
TIP: Dynamic settings take precedence over settings in the `elasticsearch.yml`
file.
[float] [float]
[[general-ml-settings]] [[general-ml-settings]]
==== General Machine Learning Settings ==== General machine learning settings
`node.ml`:: `node.ml`::
Set to `true` (default) to identify the node as a _machine learning node_. + Set to `true` (default) to identify the node as a _machine learning node_. +
@ -37,12 +44,6 @@ 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.max_open_jobs`::
The maximum number of jobs that can run on a node. Defaults to `20`.
The maximum number of jobs is also constrained by memory usage, so fewer
jobs than specified by this setting will run on a node if the estimated
memory use of the jobs would be higher than allowed.
`xpack.ml.max_machine_memory_percent`:: `xpack.ml.max_machine_memory_percent`::
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
@ -57,8 +58,26 @@ that is greater than this setting value, an error occurs. Existing jobs are not
affected when you update this setting. For more information about the affected when you update this setting. For more information about the
`model_memory_limit` property, see <<ml-apilimits>>. `model_memory_limit` property, see <<ml-apilimits>>.
`xpack.ml.max_open_jobs`::
The maximum number of jobs that can run on a node. Defaults to `20`.
The maximum number of jobs is also constrained by memory usage, so fewer
jobs than specified by this setting will run on a node if the estimated
memory use of the jobs would be higher than allowed.
`xpack.ml.node_concurrent_job_allocations`:: `xpack.ml.node_concurrent_job_allocations`::
The maximum number of jobs that can concurrently be in the `opening` state on The maximum number of jobs that can concurrently be in the `opening` state on
each node. Typically, jobs spend a small amount of time in this state before each node. Typically, jobs spend a small amount of time in this state before
they move to `open` state. Jobs that must restore large models when they are they move to `open` state. Jobs that must restore large models when they are
opening spend more time in the `opening` state. Defaults to `2`. opening spend more time in the `opening` state. Defaults to `2`.
[float]
[[advanced-ml-settings]]
==== Advanced machine learning settings
These settings are for advanced use cases; the default values are generally
sufficient:
`xpack.ml.max_anomaly_records`:: (<<cluster-update-settings,Dynamic>>)
The maximum number of records that are output per bucket. The default value is
`500`.