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//lcawley: Verified example output 2017-04-11
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[[ml-flush-job]]
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==== Flush Jobs
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The flush job API forces any buffered data to be processed by the job.
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2017-04-25 17:08:29 -04:00
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2017-04-04 18:26:39 -04:00
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===== Request
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`POST _xpack/ml/anomaly_detectors/<job_id>/_flush`
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===== Description
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The flush job API is only applicable when sending data for analysis using the
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<<ml-post-data,post data API>>. Depending on the content of the buffer, then it
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might additionally calculate new results.
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Both flush and close operations are similar, however the flush is more efficient
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if you are expecting to send more data for analysis. When flushing, the job
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remains open and is available to continue analyzing data. A close operation
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additionally prunes and persists the model state to disk and the job must be
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opened again before analyzing further data.
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===== Path Parameters
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`job_id` (required)::
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(string) Identifier for the job
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===== Query Parameters
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`advance_time`::
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(string) Specifies that no data prior to the date `advance_time` is expected.
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`end`::
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(string) When used in conjunction with `calc_interim`, specifies the range
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of buckets on which to calculate interim results.
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`calc_interim`::
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(boolean) If true, calculates the interim results for the most recent bucket
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or all buckets within the latency period.
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`start`::
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(string) When used in conjunction with `calc_interim`, specifies the range of
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buckets on which to calculate interim results.
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===== Authorization
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You must have `manage_ml`, or `manage` cluster privileges to use this API.
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For more information, see <<privileges-list-cluster>>.
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2017-04-06 10:56:46 -04:00
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===== Examples
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The following example flushes the `farequote` job:
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[source,js]
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--------------------------------------------------
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POST _xpack/ml/anomaly_detectors/farequote/_flush
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{
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"calc_interim": true
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}
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--------------------------------------------------
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// CONSOLE
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// TEST[skip:todo]
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When the operation succeeds, you receive the following results:
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[source,js]
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----
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{
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"flushed": true
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}
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----
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