[DOCS] Expanded conceptual information about datafeeds (elastic/x-pack-elasticsearch#3849)
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[float]
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[[ml-dfeeds]]
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=== {dfeeds-cap}
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Jobs can analyze either a one-off batch of data or continuously in real time.
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{dfeeds-cap} retrieve data from {es} for analysis. Alternatively you can
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{ref}/ml-post-data.html[POST data] from any source directly to an API.
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Machine learning jobs can analyze data that is stored in {es} or data that is
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sent from some other source via an API. _{dfeeds-cap}_ retrieve data from {es}
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for analysis, which is the simpler and more common scenario.
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If you create jobs in {kib}, you must use {dfeeds}. When you create a job, you
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select an index pattern and {kib} configures the {dfeed} for you under the
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covers. If you use {ml} APIs instead, you can create a {dfeed} by using the
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{ref}/ml-put-datafeed.html[create {dfeeds} API] after you create a job. You can
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associate only one {dfeed} with each job.
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For a description of all the {dfeed} properties, see
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{ref}/ml-datafeed-resource.html[Datafeed Resources].
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To start retrieving data from {es}, you must start the {dfeed}. When you start
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it, you can optionally specify start and end times. If you do not specify an
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end time, the {dfeed} runs continuously. You can start and stop {dfeeds} in
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{kib} or use the {ref}/ml-start-datafeed.html[start {dfeeds}] and
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{ref}/ml-stop-datafeed.html[stop {dfeeds}] APIs. A {dfeed} can be started and
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stopped multiple times throughout its lifecycle.
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[IMPORTANT]
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--
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When {security} is enabled, a {dfeed} stores the roles of the user who created
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or updated the {dfeed} at that time. This means that if those roles are updated,
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the {dfeed} subsequently runs with the new permissions that are associated with
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the roles. However, if the user’s roles are adjusted after creating or updating
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the {dfeed}, the {dfeed} continues to run with the permissions that were
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associated with the original roles.
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One way to update the roles that are stored within the {dfeed} without changing
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any other settings is to submit an empty JSON document ({}) to the
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{ref}/ml-update-datafeed.html[update {dfeed} API].
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--
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If the data that you want to analyze is not stored in {es}, you cannot use
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{dfeeds}. You can however send batches of data directly to the job by using the
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{ref}/ml-post-data.html[post data to jobs API].
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@ -163,14 +163,11 @@ For more information, see {ref}/ml-datafeed-resource.html[Datafeed Resources].
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When {security} is enabled, a {dfeed} stores the roles of the user who created
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or updated the {dfeed} **at that time**. This means that if those roles are
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updated then the {dfeed} will subsequently run with the new permissions associated
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with the roles. However, if the user's roles are adjusted after creating or
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updating the {dfeed} then the {dfeed} will continue to run with the permissions
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associated with the original roles.
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A way to update the roles stored within the {dfeed} without changing any other
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settings is to submit an empty JSON document (`{}`) to the
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{ref}/ml-update-datafeed.html[update {dfeed} API].
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updated then the {dfeed} subsequently runs with the new permissions that are
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associated with the roles. However, if the user's roles are adjusted after
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creating or updating the {dfeed}, the {dfeed} continues to run with the
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permissions that were associated with the original roles. For more information,
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see <<ml-dfeeds>>.
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[float]
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=== Forecasts cannot be created for population jobs
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@ -5,6 +5,7 @@ include::analyzing.asciidoc[]
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include::forecasting.asciidoc[]
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include::buckets.asciidoc[]
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include::calendars.asciidoc[]
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include::datafeeds.asciidoc[]
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[[ml-concepts]]
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=== Basic Machine Learning Terms
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@ -16,5 +17,4 @@ There are a few concepts that are core to {ml} in {xpack}. Understanding these
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concepts from the outset will tremendously help ease the learning process.
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include::jobs.asciidoc[]
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include::datafeeds.asciidoc[]
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include::architecture.asciidoc[]
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