Get inference trained model statistics API
editGet inference trained model statistics API
editRetrieves usage information for trained inference models.
This functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features.
Request
editGET _ml/inference/_stats
GET _ml/inference/_all/_stats
GET _ml/inference/<model_id>/_stats
GET _ml/inference/<model_id>,<model_id_2>/_stats
GET _ml/inference/<model_id_pattern*>,<model_id_2>/_stats
Prerequisites
editRequired privileges which should be added to a custom role:
-
cluster:
monitor_ml
For more information, see Security privileges and Built-in roles.
Description
editYou can get usage information for multiple trained models in a single API request by using a comma-separated list of model IDs or a wildcard expression.
Path parameters
edit-
<model_id>
- (Optional, string) The unique identifier of the trained inference model.
Query parameters
edit-
allow_no_match
-
(Optional, boolean) Specifies what to do when the request:
- Contains wildcard expressions and there are no data frame analytics jobs that match.
-
Contains the
_all
string or no identifiers and there are no matches. - Contains wildcard expressions and there are only partial matches.
The default value is
true
, which returns an emptydata_frame_analytics
array when there are no matches and the subset of results when there are partial matches. If this parameter isfalse
, the request returns a404
status code when there are no matches or only partial matches. -
from
-
(Optional, integer)
Skips the specified number of data frame analytics jobs. The default value is
0
. -
size
-
(Optional, integer)
Specifies the maximum number of data frame analytics jobs to obtain. The default value
is
100
.
Response codes
edit-
404
(Missing resources) -
If
allow_no_match
isfalse
, this code indicates that there are no resources that match the request or only partial matches for the request.
Examples
editThe following example gets usage information for all the trained models:
GET _ml/inference/_stats
The API returns the following results:
{ "count": 2, "trained_model_stats": [ { "model_id": "flight-delay-prediction-1574775339910", "pipeline_count": 0 }, { "model_id": "regression-job-one-1574775307356", "pipeline_count": 1, "ingest": { "total": { "count": 178, "time_in_millis": 8, "current": 0, "failed": 0 }, "pipelines": { "flight-delay": { "count": 178, "time_in_millis": 8, "current": 0, "failed": 0, "processors": [ { "inference": { "type": "inference", "stats": { "count": 178, "time_in_millis": 7, "current": 0, "failed": 0 } } } ] } } } } ] }