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* [ML] adding new _preview endpoint for data frame analytics (#69453) This commit adds a new `_preview` endpoint for data frame analytics. This allows users to see the data on which their model will be trained. This is especially useful in the arrival of custom feature processors. The API design is a similar to datafeed `_preview` and data frame analytics `_explain`.
107 lines
2.3 KiB
Text
107 lines
2.3 KiB
Text
[role="xpack"]
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[testenv="platinum"]
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[[preview-dfanalytics]]
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= Preview {dfanalytics} API
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[subs="attributes"]
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++++
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<titleabbrev>Preview {dfanalytics}</titleabbrev>
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++++
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Previews the features used by a {dataframe-analytics-config}.
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beta::[]
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[[ml-preview-dfanalytics-request]]
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== {api-request-title}
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`GET _ml/data_frame/analytics/_preview` +
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`POST _ml/data_frame/analytics/_preview` +
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`GET _ml/data_frame/analytics/<data_frame_analytics_id>/_preview` +
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`POST _ml/data_frame/analytics/<data_frame_analytics_id>/_preview`
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[[ml-preview-dfanalytics-prereq]]
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== {api-prereq-title}
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If the {es} {security-features} are enabled, you must have the following
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privileges:
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* cluster: `monitor_ml`
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For more information, see <<security-privileges>> and {ml-docs-setup-privileges}.
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[[ml-preview-dfanalytics-desc]]
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== {api-description-title}
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This API provides preview of the extracted features for a {dataframe-analytics-config}
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that either exists already or one that has not been created yet.
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[[ml-preview-dfanalytics-path-params]]
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== {api-path-parms-title}
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`<data_frame_analytics_id>`::
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(Optional, string)
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include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=job-id-data-frame-analytics]
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[[ml-preview-dfanalytics-request-body]]
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== {api-request-body-title}
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`config`::
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(Optional, object)
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A {dataframe-analytics-config} as described in <<put-dfanalytics>>.
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Note that `id` and `dest` don't need to be provided in the context of this API.
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[role="child_attributes"]
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[[ml-preview-dfanalytics-results]]
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== {api-response-body-title}
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The API returns a response that contains the following:
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`feature_values`::
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(array)
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An array of objects that contain feature name and value pairs. The features have
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been processed and indicate what will be sent to the model for training.
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[[ml-preview-dfanalytics-example]]
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== {api-examples-title}
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[source,console]
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--------------------------------------------------
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POST _ml/data_frame/analytics/_preview
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{
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"config": {
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"source": {
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"index": "houses_sold_last_10_yrs"
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},
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"analysis": {
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"regression": {
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"dependent_variable": "price"
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}
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}
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}
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}
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--------------------------------------------------
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// TEST[skip:TBD]
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The API returns the following results:
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[source,console-result]
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----
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{
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"feature_values": [
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{
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"number_of_bedrooms": "1",
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"postcode": "29655",
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"price": "140.4"
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},
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...
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]
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}
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----
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