[DOCS] Split ML overview topics (elastic/x-pack-elasticsearch#3262)

Original commit: elastic/x-pack-elasticsearch@793e25ff62

docs/en/ml/architecture.asciidoc

@@ -0,0 +1,9 @@
+[float]
+[[ml-nodes]]
+=== Machine learning nodes
+
+A {ml} node is a node that has `xpack.ml.enabled` and `node.ml` set to `true`,
+which is the default behavior. If you set `node.ml` to `false`, the node can
+service API requests but it cannot run jobs. If you want to use {xpackml}
+features, there must be at least one {ml} node in your cluster. For more
+information about this setting, see <<xpack-settings>>.

docs/en/ml/buckets.asciidoc

@@ -0,0 +1,12 @@
+[float]
+[[ml-buckets]]
+=== Buckets
+
+The {xpackml} features use the concept of a bucket to divide the time
+series into batches for processing. The _bucket span_ is part of the
+configuration information for a job. It defines the time interval that is used
+to summarize and model the data. This is typically between 5 minutes to 1 hour
+and it depends on your data characteristics. When you set the bucket span,
+take into account the granularity at which you want to analyze, the frequency
+of the input data, the typical duration of the anomalies, and the frequency at
+which alerting is required.

docs/en/ml/datafeeds.asciidoc

@@ -0,0 +1,7 @@
+[float]
+[[ml-dfeeds]]
+=== {dfeeds-cap}
+
+Jobs can analyze either a one-off batch of data or continuously in real time.
+{dfeeds-cap} retrieve data from {es} for analysis. Alternatively you can
+{ref}/ml-post-data.html[POST data] from any source directly to an API.

docs/en/ml/jobs.asciidoc

@@ -0,0 +1,24 @@
+[float]
+[[ml-jobs]]
+=== Jobs
+
+Machine learning jobs contain the configuration information and metadata
+necessary to perform an analytics task. For a list of the properties associated
+with a job, see {ref}/ml-job-resource.html[Job Resources].
+
+[float]
+[[ml-detectors]]
+=== Detectors
+
+As part of the configuration information that is associated with a job,
+detectors define the type of analysis that needs to be done. They also specify
+which fields to analyze. You can have more than one detector in a job, which
+is more efficient than running multiple jobs against the same data. For a list
+of the properties associated with detectors, see
+{ref}/ml-job-resource.html#ml-detectorconfig[Detector Configuration Objects].
+
+[float]
+[[ml-function-overview]]
+=== Analytical functions
+
+See <<ml-functions>>.

docs/en/ml/overview.asciidoc

@@ -4,58 +4,7 @@
 There are a few concepts that are core to {ml} in {xpack}. Understanding these
 concepts from the outset will tremendously help ease the learning process.
 
-[float]
-[[ml-jobs]]
-=== Jobs
-
-Machine learning jobs contain the configuration information and metadata
-necessary to perform an analytics task. For a list of the properties associated
-with a job, see {ref}/ml-job-resource.html[Job Resources].
-
-[float]
-[[ml-dfeeds]]
-=== {dfeeds-cap}
-
-Jobs can analyze either a one-off batch of data or continuously in real time.
-{dfeeds-cap} retrieve data from {es} for analysis. Alternatively you can
-{ref}/ml-post-data.html[POST data] from any source directly to an API.
-
-[float]
-[[ml-detectors]]
-=== Detectors
-
-As part of the configuration information that is associated with a job,
-detectors define the type of analysis that needs to be done. They also specify
-which fields to analyze. You can have more than one detector in a job, which
-is more efficient than running multiple jobs against the same data. For a list
-of the properties associated with detectors, see
-{ref}/ml-job-resource.html#ml-detectorconfig[Detector Configuration Objects].
-
-[float]
-[[ml-buckets]]
-=== Buckets
-
-The {xpackml} features use the concept of a bucket to divide the time
-series into batches for processing. The _bucket span_ is part of the
-configuration information for a job. It defines the time interval that is used
-to summarize and model the data. This is typically between 5 minutes to 1 hour
-and it depends on your data characteristics. When you set the bucket span,
-take into account the granularity at which you want to analyze, the frequency
-of the input data, the typical duration of the anomalies, and the frequency at
-which alerting is required.
-
-[float]
-[[ml-nodes]]
-=== Machine learning nodes
-
-A {ml} node is a node that has `xpack.ml.enabled` and `node.ml` set to `true`,
-which is the default behavior. If you set `node.ml` to `false`, the node can
-service API requests but it cannot run jobs. If you want to use {xpackml}
-features, there must be at least one {ml} node in your cluster. For more
-information about this setting, see <<xpack-settings>>.
-
-[float]
-[[ml-function-overview]]
-=== Analytical functions
-
-See <<ml-functions>>.
+include::jobs.asciidoc[]
+include::datafeeds.asciidoc[]
+include::buckets.asciidoc[]
+include::architecture.asciidoc[]