59 lines
2.6 KiB
Plaintext
59 lines
2.6 KiB
Plaintext
[role="xpack"]
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[[ml-settings]]
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=== Machine Learning Settings in Elasticsearch
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++++
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<titleabbrev>Machine Learning Settings</titleabbrev>
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++++
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You do not need to configure any settings to use {ml}. It is enabled by default.
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[float]
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[[general-ml-settings]]
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==== General Machine Learning Settings
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`node.ml`::
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Set to `true` (default) to identify the node as a _machine learning node_. +
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+
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If set to `false` in `elasticsearch.yml`, the node cannot run jobs. If set to
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`true` but `xpack.ml.enabled` is set to `false`, the `node.ml` setting is
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ignored and the node cannot run jobs. If you want to run jobs, there must be at
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least one machine learning node in your cluster. +
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+
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IMPORTANT: On dedicated coordinating nodes or dedicated master nodes, disable
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the `node.ml` role.
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`xpack.ml.enabled`::
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Set to `true` (default) to enable {ml} on the node. +
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+
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If set to `false` in `elasticsearch.yml`, the {ml} APIs are disabled on the node.
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Therefore the node cannot open jobs, start {dfeeds}, or receive transport (internal)
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communication requests related to {ml} APIs. It also affects all {kib} instances
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that connect to this {es} instance; you do not need to disable {ml} in those
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`kibana.yml` files. For more information about disabling {ml} in specific {kib}
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instances, see
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{kibana-ref}/ml-settings-kb.html[{kib} Machine Learning Settings].
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+
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IMPORTANT: If you want to use {ml} features in your cluster, you must have
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`xpack.ml.enabled` set to `true` on all master-eligible nodes. This is the
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default behavior.
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`xpack.ml.max_open_jobs`::
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The maximum number of jobs that can run on a node. Defaults to `20`.
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The maximum number of jobs is also constrained by memory usage, so fewer
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jobs than specified by this setting will run on a node if the estimated
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memory use of the jobs would be higher than allowed.
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`xpack.ml.max_machine_memory_percent`::
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The maximum percentage of the machine's memory that {ml} may use for running
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analytics processes. (These processes are separate to the {es} JVM.) Defaults to
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`30` percent. The limit is based on the total memory of the machine, not current
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free memory. Jobs will not be allocated to a node if doing so would cause the
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estimated memory use of {ml} jobs to exceed the limit.
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`xpack.ml.max_model_memory_limit`::
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The maximum `model_memory_limit` property value that can be set for any job on
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this node. If you try to create a job with a `model_memory_limit` property value
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that is greater than this setting value, an error occurs. Existing jobs are not
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affected when you update this setting. For more information about the
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`model_memory_limit` property, see <<ml-apilimits>>.
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