2019-02-15 12:29:45 -05:00
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[testenv="platinum"]
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2019-02-20 15:03:41 -05:00
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////////////
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Take us out of upgrade mode after running any snippets on this page.
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2019-09-05 10:11:25 -04:00
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[source,console]
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2019-02-20 15:03:41 -05:00
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--------------------------------------------------
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POST _ml/set_upgrade_mode?enabled=false
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--------------------------------------------------
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// TEARDOWN
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////////////
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2019-03-25 13:23:10 -04:00
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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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2019-02-15 12:29:45 -05:00
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2019-03-25 13:23:10 -04:00
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If your {ml} indices were created in {prev-major-version}, you can:
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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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* 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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2019-09-05 10:11:25 -04:00
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[source,console]
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2019-02-15 12:29:45 -05:00
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--------------------------------------------------
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POST _ml/set_upgrade_mode?enabled=true
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--------------------------------------------------
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2019-04-23 10:57:17 -04:00
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+
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2019-03-25 13:23:10 -04:00
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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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* {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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