[DOCS] Makes the naming convention of the DFA response objects coherent (#53172)
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István Zoltán Szabó
parent
af0b1c2860
commit
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@ -143,7 +143,8 @@ of a node to run the job.
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end::assignment-explanation-anomaly-jobs[]
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tag::assignment-explanation-datafeeds[]
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For started {dfeeds} only, contains messages relating to the selection of a node.
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For started {dfeeds} only, contains messages relating to the selection of a
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node.
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end::assignment-explanation-datafeeds[]
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tag::assignment-explanation-dfanalytics[]
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@ -318,10 +319,10 @@ add them here as
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end::char-filter[]
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tag::chunking-config[]
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{dfeeds-cap} might be required to search over long time periods, for several months
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or years. This search is split into time chunks in order to ensure the load
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on {es} is managed. Chunking configuration controls how the size of these time
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chunks are calculated and is an advanced configuration option.
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{dfeeds-cap} might be required to search over long time periods, for several
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months or years. This search is split into time chunks in order to ensure the
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load on {es} is managed. Chunking configuration controls how the size of these
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time chunks are calculated and is an advanced configuration option.
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A chunking configuration object has the following properties:
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`chunking_config`.`mode`:::
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@ -380,7 +381,8 @@ end::custom-rules-scope-filter-type[]
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tag::custom-rules-conditions[]
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An optional array of numeric conditions when the rule applies. A rule must
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either have a non-empty scope or at least one condition. Multiple conditions are
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combined together with a logical `AND`. A condition has the following properties:
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combined together with a logical `AND`. A condition has the following
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properties:
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end::custom-rules-conditions[]
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tag::custom-rules-conditions-applies-to[]
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@ -392,7 +394,8 @@ end::custom-rules-conditions-applies-to[]
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tag::custom-rules-conditions-operator[]
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Specifies the condition operator. The available options are `gt` (greater than),
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`gte` (greater than or equals), `lt` (less than) and `lte` (less than or equals).
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`gte` (greater than or equals), `lt` (less than) and `lte` (less than or
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equals).
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end::custom-rules-conditions-operator[]
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tag::custom-rules-conditions-value[]
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@ -431,47 +434,6 @@ tag::data-frame-analytics[]
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An array of {dfanalytics-job} resources, which are sorted by the `id` value in
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ascending order.
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`id`:::
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(string) The unique identifier of the {dfanalytics-job}.
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`source`:::
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(object) The configuration of how the analysis data is sourced. It has an
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`index` parameter and optionally a `query` and a `_source`.
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`index`::::
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(array) Index or indices on which to perform the analysis. It can be a single
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index or index pattern as well as an array of indices or patterns.
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`query`::::
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(object) The query that has been specified for the {dfanalytics-job}. The {es}
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query domain-specific language (<<query-dsl,DSL>>). This value corresponds to
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the query object in an {es} search POST body. By default, this property has the
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following value: `{"match_all": {}}`.
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`_source`::::
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(object) Contains the specified `includes` and/or `excludes` patterns that
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select which fields are present in the destination. Fields that are excluded
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cannot be included in the analysis.
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`includes`:::::
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(array) An array of strings that defines the fields that are included in the
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destination.
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`excludes`:::::
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(array) An array of strings that defines the fields that are excluded from the
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destination.
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`dest`:::
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(string) The destination configuration of the analysis.
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`index`::::
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(string) The _destination index_ that stores the results of the
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{dfanalytics-job}.
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`results_field`::::
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(string) The name of the field that stores the results of the analysis. Defaults
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to `ml`.
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`analysis`:::
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(object) The type of analysis that is performed on the `source`.
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@ -479,49 +441,84 @@ to `ml`.
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(object) Contains `includes` and/or `excludes` patterns that select which fields
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are included in the analysis.
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`includes`::::
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(Optional, array) An array of strings that defines the fields that are included
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in the analysis.
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`excludes`::::
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`analyzed_fields`.`excludes`:::
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(Optional, array) An array of strings that defines the fields that are excluded
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from the analysis.
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`analyzed_fields`.`includes`:::
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(Optional, array) An array of strings that defines the fields that are included
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in the analysis.
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`dest`:::
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(string) The destination configuration of the analysis.
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`dest`.`index`:::
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(string) The _destination index_ that stores the results of the
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{dfanalytics-job}.
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`dest`.`results_field`:::
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(string) The name of the field that stores the results of the analysis. Defaults
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to `ml`.
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`id`:::
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(string) The unique identifier of the {dfanalytics-job}.
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`model_memory_limit`:::
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(string) The `model_memory_limit` that has been set to the {dfanalytics-job}.
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`source`:::
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(object) The configuration of how the analysis data is sourced. It has an
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`index` parameter and optionally a `query` and a `_source`.
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`source`.`index`:::
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(array) Index or indices on which to perform the analysis. It can be a single
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index or index pattern as well as an array of indices or patterns.
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`source`.`query`:::
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(object) The query that has been specified for the {dfanalytics-job}. The {es}
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query domain-specific language (<<query-dsl,DSL>>). This value corresponds to
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the query object in an {es} search POST body. By default, this property has the
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following value: `{"match_all": {}}`.
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`source`.`_source`:::
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(object) Contains the specified `includes` and/or `excludes` patterns that
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select which fields are present in the destination. Fields that are excluded
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cannot be included in the analysis.
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`source`.`_source`.`excludes`:::
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(array) An array of strings that defines the fields that are excluded from the
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destination.
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`source`.`_source`.`includes`:::
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(array) An array of strings that defines the fields that are included in the
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destination.
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end::data-frame-analytics[]
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tag::data-frame-analytics-stats[]
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An array of statistics objects for {dfanalytics-jobs}, which are
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sorted by the `id` value in ascending order.
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`assignment_explanation`:::
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(string)
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For running jobs only, contains messages relating to the selection of a node to
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run the job.
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`id`:::
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(string) The unique identifier of the {dfanalytics-job}.
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`state`:::
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(string) Current state of the {dfanalytics-job}.
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`progress`:::
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(array) The progress report of the {dfanalytics-job} by phase.
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`phase`::::
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(string) Defines the phase of the {dfanalytics-job}. Possible phases:
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`reindexing`, `loading_data`, `analyzing`, and `writing_results`.
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`progress_percent`::::
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(integer) The progress that the {dfanalytics-job} has made expressed in
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percentage.
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(string)
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The unique identifier of the {dfanalytics-job}.
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`memory_usage`:::
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(Optional, Object) An object describing memory usage of the analytics.
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It will be present only after the job has started and memory usage has
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been reported.
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(Optional, object)
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An object describing memory usage of the analytics. It is present only after the
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job is started and memory usage is reported.
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`timestamp`::::
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(date) The timestamp when memory usage was calculated.
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`memory_usage`.`peak_usage_bytes`:::
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(long)
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The number of bytes used at the highest peak of memory usage.
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`peak_usage_bytes`::::
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(long) The number of bytes used at the highest peak of memory usage.
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`memory_usage`.`timestamp`:::
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(date)
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The timestamp when memory usage was calculated.
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`node`:::
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(object)
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@ -549,10 +546,19 @@ The node name.
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(string)
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The host and port where transport HTTP connections are accepted.
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`assignment_explanation`:::
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(string)
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For running jobs only, contains messages relating to the selection of a node to
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run the job.
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`progress`:::
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(array) The progress report of the {dfanalytics-job} by phase.
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`progress`.`phase`:::
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(string) Defines the phase of the {dfanalytics-job}. Possible phases:
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`reindexing`, `loading_data`, `analyzing`, and `writing_results`.
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`progress`.`progress_percent`:::
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(integer) The progress that the {dfanalytics-job} has made expressed in
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percentage.
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`state`:::
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(string) Current state of the {dfanalytics-job}.
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end::data-frame-analytics-stats[]
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tag::datafeed-id[]
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@ -585,10 +591,10 @@ window. For example: `{"enabled": true, "check_window": "1h"}`.
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+
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--
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The {dfeed} can optionally search over indices that have already been read in
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an effort to determine whether any data has subsequently been added to the index.
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If missing data is found, it is a good indication that the `query_delay` option
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is set too low and the data is being indexed after the {dfeed} has passed that
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moment in time. See
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an effort to determine whether any data has subsequently been added to the
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index. If missing data is found, it is a good indication that the `query_delay`
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option is set too low and the data is being indexed after the {dfeed} has passed
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that moment in time. See
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{ml-docs}/ml-delayed-data-detection.html[Working with delayed data].
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This check runs only on real-time {dfeeds}.
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@ -811,7 +817,8 @@ A comma separated list of influencer field names. Typically these can be the by,
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over, or partition fields that are used in the detector configuration. You might
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also want to use a field name that is not specifically named in a detector, but
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is available as part of the input data. When you use multiple detectors, the use
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of influencers is recommended as it aggregates results for each influencer entity.
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of influencers is recommended as it aggregates results for each influencer
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entity.
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end::influencers[]
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tag::input-bytes[]
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@ -937,9 +944,10 @@ tag::max-empty-searches[]
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If a real-time {dfeed} has never seen any data (including during any initial
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training period) then it will automatically stop itself and close its associated
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job after this many real-time searches that return no documents. In other words,
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it will stop after `frequency` times `max_empty_searches` of real-time operation.
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If not set then a {dfeed} with no end time that sees no data will remain started
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until it is explicitly stopped. By default this setting is not set.
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it will stop after `frequency` times `max_empty_searches` of real-time
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operation. If not set then a {dfeed} with no end time that sees no data will
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remain started until it is explicitly stopped. By default this setting is not
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set.
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end::max-empty-searches[]
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tag::maximum-number-trees[]
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@ -1091,10 +1099,10 @@ Only the specified `terms` can be viewed when using the Single Metric Viewer.
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end::model-plot-config-terms[]
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tag::model-snapshot-retention-days[]
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Advanced configuration option. The period of time (in days) that model snapshots are retained.
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Age is calculated relative to the timestamp of the newest model snapshot.
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The default value is `1`, which means snapshots that are one day (twenty-four hours)
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older than the newest snapshot are deleted.
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Advanced configuration option. The period of time (in days) that model snapshots
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are retained. Age is calculated relative to the timestamp of the newest model
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snapshot. The default value is `1`, which means snapshots that are one day
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(twenty-four hours) older than the newest snapshot are deleted.
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end::model-snapshot-retention-days[]
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tag::model-timestamp[]
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@ -1249,10 +1257,10 @@ is `shared`, which generates an index named `.ml-anomalies-shared`.
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end::results-index-name[]
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tag::results-retention-days[]
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Advanced configuration option. The period of time (in days) that results are retained.
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Age is calculated relative to the timestamp of the latest bucket result.
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If this property has a non-null value, once per day at 00:30 (server time),
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results that are the specified number of days older than the latest
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Advanced configuration option. The period of time (in days) that results are
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retained. Age is calculated relative to the timestamp of the latest bucket
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result. If this property has a non-null value, once per day at 00:30 (server
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time), results that are the specified number of days older than the latest
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bucket result are deleted from {es}. The default value is null, which means all
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results are retained.
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end::results-retention-days[]
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@ -1352,11 +1360,11 @@ job must be opened before it can accept further data.
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* `closing`: The job close action is in progress and has not yet completed. A
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closing job cannot accept further data.
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* `failed`: The job did not finish successfully due to an error. This situation
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can occur due to invalid input data, a fatal error occurring during the analysis,
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or an external interaction such as the process being killed by the Linux out of
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memory (OOM) killer. If the job had irrevocably failed, it must be force closed
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and then deleted. If the {dfeed} can be corrected, the job can be closed and
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then re-opened.
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can occur due to invalid input data, a fatal error occurring during the
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analysis, or an external interaction such as the process being killed by the
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Linux out of memory (OOM) killer. If the job had irrevocably failed, it must be
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force closed and then deleted. If the {dfeed} can be corrected, the job can be
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closed and then re-opened.
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* `opened`: The job is available to receive and process data.
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* `opening`: The job open action is in progress and has not yet completed.
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--
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