Post data to jobs APIedit
Sends data to an anomaly detection job for analysis.
Requestedit
POST _ml/anomaly_detectors/<job_id>/_data
Prerequisitesedit
-
If the Elasticsearch security features are enabled, you must have
manage_mlormanagecluster privileges to use this API. See Security privileges.
Descriptionedit
The job must have a state of open to receive and process the data.
The data that you send to the job must use the JSON format. Multiple JSON
documents can be sent, either adjacent with no separator in between them or
whitespace separated. Newline delimited JSON (NDJSON) is a possible whitespace
separated format, and for this the Content-Type header should be set to
application/x-ndjson.
Upload sizes are limited to the Elasticsearch HTTP receive buffer size (default 100 Mb). If your data is larger, split it into multiple chunks and upload each one separately in sequential time order. When running in real time, it is generally recommended that you perform many small uploads, rather than queueing data to upload larger files.
When uploading data, check the job data counts for progress. The following documents will not be processed:
- Documents not in chronological order and outside the latency window
- Records with an invalid timestamp
For each job, data can only be accepted from a single connection at a time. It is not currently possible to post data to multiple jobs using wildcards or a comma-separated list.
Path parametersedit
-
<job_id> - (Required, string) Identifier for the anomaly detection job.
Query parametersedit
-
reset_start - (Optional, string) Specifies the start of the bucket resetting range.
-
reset_end - (Optional, string) Specifies the end of the bucket resetting range.
Request bodyedit
A sequence of one or more JSON documents containing the data to be analyzed. Only whitespace characters are permitted in between the documents.
Examplesedit
The following example posts data from the it_ops_new_kpi.json file to the
it_ops_new_kpi job:
$ curl -s -H "Content-type: application/json" -X POST http:\/\/localhost:9200/_ml/anomaly_detectors/it_ops_new_kpi/_data --data-binary @it_ops_new_kpi.json
When the data is sent, you receive information about the operational progress of the job. For example:
{
"job_id":"it_ops_new_kpi",
"processed_record_count":21435,
"processed_field_count":64305,
"input_bytes":2589063,
"input_field_count":85740,
"invalid_date_count":0,
"missing_field_count":0,
"out_of_order_timestamp_count":0,
"empty_bucket_count":16,
"sparse_bucket_count":0,
"bucket_count":2165,
"earliest_record_timestamp":1454020569000,
"latest_record_timestamp":1455318669000,
"last_data_time":1491952300658,
"latest_empty_bucket_timestamp":1454541600000,
"input_record_count":21435
}
For more information about these properties, see Response body.