Get overall buckets API
editGet overall buckets API
editRetrieves overall bucket results that summarize the bucket results of multiple anomaly detection jobs.
Request
editGET _ml/anomaly_detectors/<job_id>/results/overall_buckets
GET _ml/anomaly_detectors/<job_id>,<job_id>/results/overall_buckets
GET _ml/anomaly_detectors/_all/results/overall_buckets
Prerequisites
edit-
You must have
monitor_ml
,monitor
,manage_ml
, ormanage
cluster privileges to use this API. You also needread
index privilege on the index that stores the results. Themachine_learning_admin
andmachine_learning_user
roles provide these privileges. For more information, see Security privileges and Built-in roles.
Description
editYou can summarize the bucket results for all anomaly detection jobs by using _all
or
by specifying *
as the <job_id>
.
By default, an overall bucket has a span equal to the largest bucket span of the
specified anomaly detection jobs. To override that behavior, use the optional
bucket_span
parameter. To learn more about the concept of buckets, see
Buckets.
The overall_score
is calculated by combining the scores of all the buckets
within the overall bucket span. First, the maximum anomaly_score
per
anomaly detection job in the overall bucket is calculated. Then the top_n
of those
scores are averaged to result in the overall_score
. This means that you can
fine-tune the overall_score
so that it is more or less sensitive to the number
of jobs that detect an anomaly at the same time. For example, if you set top_n
to 1
, the overall_score
is the maximum bucket score in the overall bucket.
Alternatively, if you set top_n
to the number of jobs, the overall_score
is
high only when all jobs detect anomalies in that overall bucket. If you set
the bucket_span
parameter (to a value greater than its default), the
overall_score
is the maximum overall_score
of the overall buckets that have
a span equal to the jobs' largest bucket span.
Path parameters
edit-
<job_id>
- (Required, string) Identifier for the anomaly detection job. It can be a job identifier, a group name, a comma-separated list of jobs or groups, or a wildcard expression.
Request body
edit-
allow_no_jobs
-
(Optional, boolean) If
false
and thejob_id
does not match any anomaly detection jobs, an error occurs. The default value istrue
. -
bucket_span
- (Optional, string) The span of the overall buckets. Must be greater or equal to the largest bucket span of the specified anomaly detection jobs, which is the default value.
-
end
- (string) Returns overall buckets with timestamps earlier than this time.
-
exclude_interim
-
(boolean) If
true
, the output excludes interim overall buckets. Overall buckets are interim if any of the job buckets within the overall bucket interval are interim. By default, interim results are included. -
overall_score
- (double) Returns overall buckets with overall scores greater or equal than this value.
-
start
- (string) Returns overall buckets with timestamps after this time.
-
top_n
-
(Optional, integer) The number of top anomaly detection job bucket scores to be used
in the
overall_score
calculation. The default value is1
.
Response body
editThe API returns the following information:
-
overall_buckets
- (array) An array of overall bucket objects. For more information, see Overall Buckets.
Examples
editThe following example gets overall buckets for anomaly detection jobs with IDs matching
job-*
:
GET _ml/anomaly_detectors/job-*/results/overall_buckets { "overall_score": 80, "start": "1403532000000" }
In this example, the API returns a single result that matches the specified
score and time constraints. The overall_score
is the max job score as
top_n
defaults to 1 when not specified:
{ "count": 1, "overall_buckets": [ { "timestamp" : 1403532000000, "bucket_span" : 3600, "overall_score" : 80.0, "jobs" : [ { "job_id" : "job-1", "max_anomaly_score" : 30.0 }, { "job_id" : "job-2", "max_anomaly_score" : 10.0 }, { "job_id" : "job-3", "max_anomaly_score" : 80.0 } ], "is_interim" : false, "result_type" : "overall_bucket" } ] }
The next example is similar but this time top_n
is set to 2
:
GET _ml/anomaly_detectors/job-*/results/overall_buckets { "top_n": 2, "overall_score": 50.0, "start": "1403532000000" }
Note how the overall_score
is now the average of the top 2 job scores:
{ "count": 1, "overall_buckets": [ { "timestamp" : 1403532000000, "bucket_span" : 3600, "overall_score" : 55.0, "jobs" : [ { "job_id" : "job-1", "max_anomaly_score" : 30.0 }, { "job_id" : "job-2", "max_anomaly_score" : 10.0 }, { "job_id" : "job-3", "max_anomaly_score" : 80.0 } ], "is_interim" : false, "result_type" : "overall_bucket" } ] }