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@@ -11,33 +11,35 @@ POST _ml/set_upgrade_mode?enabled=false
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// TEARDOWN
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////////////
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-If your {ml} indices were created earlier than the previous major version, they
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-must be reindexed. In those circumstances, there must be no machine learning
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-jobs running during the upgrade.
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-
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-In all other circumstances, there is no requirement to close your {ml} jobs.
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-There are, however, advantages to doing so. If you choose to leave your jobs
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-running during the upgrade, they are affected when you stop the {ml} nodes. The
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-jobs move to another {ml} node and restore the model states. This scenario has
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-the least disruption to the active {ml} jobs but incurs the highest load on the
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-cluster.
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-
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-To close all {ml} jobs before you upgrade, see
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-{stack-ov}/stopping-ml.html[Stopping {ml}]. This method persists the model
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-state at the moment of closure, which means that when you open your jobs after
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-the upgrade, they use the exact same model. This scenario takes the most time,
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-however, especially if you have many jobs or jobs with large model states.
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-
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-To temporarily halt the tasks associated with your {ml} jobs and {dfeeds} and
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-prevent new jobs from opening, use the <<ml-set-upgrade-mode,set upgrade mode API>>:
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+If your {ml} indices were created before {prev-major-version}, you must
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+<<reindex-upgrade,reindex the indices>>.
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+If your {ml} indices were created in {prev-major-version}, you can:
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+
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+* Leave your {ml} jobs running during the upgrade. When you shut down a
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+{ml} node, its jobs automatically move to another node and restore the model
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+states. This option enables your jobs to continue running during the upgrade but
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+it puts increased load on the cluster.
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+
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+* Temporarily halt the tasks associated with your {ml} jobs and {dfeeds} and
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+prevent new jobs from opening by using the
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+<<ml-set-upgrade-mode,set upgrade mode API>>:
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++
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+--
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[source,js]
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--------------------------------------------------
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POST _ml/set_upgrade_mode?enabled=true
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--------------------------------------------------
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// CONSOLE
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-This method does not persist the absolute latest model state, rather it uses the
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-last model state that was automatically saved. By halting the tasks, you avoid
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-incurring the cost of managing active jobs during the upgrade and it's quicker
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-than stopping {dfeeds} and closing jobs.
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+When you disable upgrade mode, the jobs resume using the last model
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+state that was automatically saved. This option avoids the overhead of managing
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+active jobs during the upgrade and is faster than explicitly stopping {dfeeds}
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+and closing jobs.
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+--
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+
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+* {stack-ov}/stopping-ml.html[Stop all {dfeeds} and close all jobs]. This option
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+saves the model state at the time of closure. When you reopen the jobs after the
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+upgrade, they use the exact same model. However, saving the latest model state
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+takes longer than using upgrade mode, especially if you have a lot of jobs or
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+jobs with large model states.
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