Retrieves job results for one or more buckets.
GET _ml/anomaly_detectors/<job_id>/results/buckets
GET _ml/anomaly_detectors/<job_id>/results/buckets/<timestamp>
job_id
timestamp
anomaly_score
desc
end
exclude_interim
expand
page
from
size
sort
timestamp field.
start
The API returns the following information:
buckets
You must have monitor_ml, monitor, manage_ml, or manage cluster
privileges to use this API. You also need read index privilege on the index
that stores the results. The machine_learning_admin and machine_learning_user
roles provide these privileges. For more information, see
Security Privileges and
Built-in Roles.
The following example gets bucket information for the it-ops-kpi job:
GET _ml/anomaly_detectors/it-ops-kpi/results/buckets
{
"anomaly_score": 80,
"start": "1454530200001"
}In this example, the API returns a single result that matches the specified score and time constraints:
{
"count": 1,
"buckets": [
{
"job_id": "it-ops-kpi",
"timestamp": 1454943900000,
"anomaly_score": 94.1706,
"bucket_span": 300,
"initial_anomaly_score": 94.1706,
"event_count": 153,
"is_interim": false,
"bucket_influencers": [
{
"job_id": "it-ops-kpi",
"result_type": "bucket_influencer",
"influencer_field_name": "bucket_time",
"initial_anomaly_score": 94.1706,
"anomaly_score": 94.1706,
"raw_anomaly_score": 2.32119,
"probability": 0.00000575042,
"timestamp": 1454943900000,
"bucket_span": 300,
"is_interim": false
}
],
"processing_time_ms": 2,
"partition_scores": [],
"result_type": "bucket"
}
]
}