Get model snapshots API
editGet model snapshots API
editRetrieves information about model snapshots.
Request
editGET _ml/anomaly_detectors/<job_id>/model_snapshots
GET _ml/anomaly_detectors/<job_id>/model_snapshots/<snapshot_id>
Prerequisites
edit-
If the Elasticsearch security features are enabled, you must have
monitor_ml
,monitor
,manage_ml
, ormanage
cluster privileges to use this API. See Security privileges and Machine learning security privileges.
Path parameters
edit-
<job_id>
- (Required, string) Identifier for the anomaly detection job.
-
<snapshot_id>
-
(Optional, string) A numerical character string that uniquely identifies the model snapshot.
You can multiple snapshots for a single job in a single API request by using a comma-separated list of
<snapshot_id>
or a wildcard expression. You can get all snapshots for all calendars by using_all
, by specifying*
as the<snapshot_id>
, or by omitting the<snapshot_id>
.
Request body
edit-
desc
- (Optional, Boolean) If true, the results are sorted in descending order.
-
end
- (Optional, date) Returns snapshots with timestamps earlier than this time.
-
from
- (Optional, integer) Skips the specified number of snapshots.
-
size
- (Optional, integer) Specifies the maximum number of snapshots to obtain.
-
sort
- (Optional, string) Specifies the sort field for the requested snapshots. By default, the snapshots are sorted by their timestamp.
-
start
- (Optional, string) Returns snapshots with timestamps after this time.
Response body
editThe API returns an array of model snapshot objects, which have the following properties:
-
description
- (string) An optional description of the job.
-
job_id
- (string) A numerical character string that uniquely identifies the job that the snapshot was created for.
-
latest_record_time_stamp
- (date) The timestamp of the latest processed record.
-
latest_result_time_stamp
- (date) The timestamp of the latest bucket result.
-
min_version
- (string) The minimum version required to be able to restore the model snapshot.
-
model_size_stats
-
(object) Summary information describing the model.
Properties of
model_size_stats
-
bucket_allocation_failures_count
- (long) The number of buckets for which entities were not processed due to memory limit constraints.
-
categorized_doc_count
- (long) The number of documents that have had a field categorized.
-
categorization_status
-
(string) The status of categorization for this job. Contains one of the following values.
-
ok
: Categorization is performing acceptably well (or not being used at all). -
warn
: Categorization is detecting a distribution of categories that suggests the input data is inappropriate for categorization. Problems could be that there is only one category, more than 90% of categories are rare, the number of categories is greater than 50% of the number of categorized documents, there are no frequently matched categories, or more than 50% of categories are dead.
-
-
dead_category_count
- (long) The number of categories created by categorization that will never be assigned again because another category’s definition makes it a superset of the dead category. (Dead categories are a side effect of the way categorization has no prior training.)
-
failed_category_count
-
(long)
The number of times that categorization wanted to create a new category but
couldn’t because the job had hit its
model_memory_limit
. This count does not track which specific categories failed to be created. Therefore you cannot use this value to determine the number of unique categories that were missed. -
frequent_category_count
- (long) The number of categories that match more than 1% of categorized documents.
-
job_id
- (string) Identifier for the anomaly detection job.
-
log_time
-
(date) The timestamp that the
model_size_stats
were recorded, according to server-time. -
memory_status
-
(string) The status of the memory in relation to its
model_memory_limit
. Contains one of the following values.-
hard_limit
: The internal models require more space that the configured memory limit. Some incoming data could not be processed. -
ok
: The internal models stayed below the configured value. -
soft_limit
: The internal models require more than 60% of the configured memory limit and more aggressive pruning will be performed in order to try to reclaim space.
-
-
model_bytes
- (long) An approximation of the memory resources required for this analysis.
-
model_bytes_exceeded
- (long) The number of bytes over the high limit for memory usage at the last allocation failure.
-
model_bytes_memory_limit
- (long) The upper limit for memory usage, checked on increasing values.
-
rare_category_count
- (long) The number of categories that match just one categorized document.
-
result_type
-
(string) Internal. This value is always
model_size_stats
. -
timestamp
-
(date) The timestamp that the
model_size_stats
were recorded, according to the bucket timestamp of the data. -
total_by_field_count
- (long) The number of by field values analyzed. Note that these are counted separately for each detector and partition.
-
total_category_count
- (long) The number of categories created by categorization.
-
total_over_field_count
- (long) The number of over field values analyzed. Note that these are counted separately for each detector and partition.
-
total_partition_field_count
- (long) The number of partition field values analyzed.
-
-
retain
-
(Boolean)
If
true
, this snapshot will not be deleted during automatic cleanup of snapshots older thanmodel_snapshot_retention_days
. However, this snapshot will be deleted when the job is deleted. The default value isfalse
. -
snapshot_id
- (string) A numerical character string that uniquely identifies the model snapshot.
-
snapshot_doc_count
- (long) For internal use only.
-
timestamp
- (date) The creation timestamp for the snapshot.
Examples
editGET _ml/anomaly_detectors/high_sum_total_sales/model_snapshots { "start": "1575402236000" }
In this example, the API provides a single result:
{ "count" : 1, "model_snapshots" : [ { "job_id" : "high_sum_total_sales", "min_version" : "6.4.0", "timestamp" : 1575402237000, "description" : "State persisted due to job close at 2019-12-03T19:43:57+0000", "snapshot_id" : "1575402237", "snapshot_doc_count" : 1, "model_size_stats" : { "job_id" : "high_sum_total_sales", "result_type" : "model_size_stats", "model_bytes" : 1638816, "model_bytes_exceeded" : 0, "model_bytes_memory_limit" : 10485760, "total_by_field_count" : 3, "total_over_field_count" : 3320, "total_partition_field_count" : 2, "bucket_allocation_failures_count" : 0, "memory_status" : "ok", "categorized_doc_count" : 0, "total_category_count" : 0, "frequent_category_count" : 0, "rare_category_count" : 0, "dead_category_count" : 0, "categorization_status" : "ok", "log_time" : 1575402237000, "timestamp" : 1576965600000 }, "latest_record_time_stamp" : 1576971072000, "latest_result_time_stamp" : 1576965600000, "retain" : false } ] }