Get datafeeds API
editGet datafeeds API
editRetrieves configuration information for datafeeds.
Request
editGET _ml/datafeeds/<feed_id>
GET _ml/datafeeds/<feed_id>,<feed_id>
GET _ml/datafeeds/
GET _ml/datafeeds/_all
Prerequisites
editRequires the monitor_ml
cluster privilege. This privilege is included in the
machine_learning_user
built-in role.
Description
editThis API returns a maximum of 10,000 datafeeds.
Path parameters
edit-
<feed_id>
-
(Optional, string) Identifier for the datafeed. It can be a datafeed identifier or a wildcard expression.
You can get information for multiple datafeeds in a single API request by using a comma-separated list of datafeeds or a wildcard expression. You can get information for all datafeeds by using
_all
, by specifying*
as the datafeed identifier, or by omitting the identifier.
Query parameters
edit-
allow_no_match
-
(Optional, Boolean) Specifies what to do when the request:
- Contains wildcard expressions and there are no datafeeds 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 emptydatafeeds
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. -
exclude_generated
- (Optional, Boolean) Indicates if certain fields should be removed from the configuration on retrieval. This allows the configuration to be in an acceptable format to be retrieved and then added to another cluster. Default is false.
Response body
editThe API returns an array of datafeed resources. For the full list of properties, see create datafeeds API.
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
editresp = client.ml.get_datafeeds( datafeed_id="datafeed-high_sum_total_sales", ) print(resp)
response = client.ml.get_datafeeds( datafeed_id: 'datafeed-high_sum_total_sales' ) puts response
const response = await client.ml.getDatafeeds({ datafeed_id: "datafeed-high_sum_total_sales", }); console.log(response);
GET _ml/datafeeds/datafeed-high_sum_total_sales
The API returns the following results:
{ "count" : 1, "datafeeds" : [ { "datafeed_id" : "datafeed-high_sum_total_sales", "job_id" : "high_sum_total_sales", "authorization" : { "roles" : [ "superuser" ] }, "query_delay" : "93169ms", "chunking_config" : { "mode" : "auto" }, "indices_options" : { "expand_wildcards" : [ "open" ], "ignore_unavailable" : false, "allow_no_indices" : true, "ignore_throttled" : true }, "query" : { "bool" : { "filter" : [ { "term" : { "event.dataset" : "sample_ecommerce" } } ] } }, "indices" : [ "kibana_sample_data_ecommerce" ], "scroll_size" : 1000, "delayed_data_check_config" : { "enabled" : true } } ] }