Model Snapshot Resourcesedit

Model snapshots are saved to disk periodically. By default, this is occurs approximately every 3 hours to 4 hours and is configurable with the background_persist_interval property.

By default, model snapshots are retained for one day (twenty-four hours). You can change this behavior by updating the model_snapshot_retention_days for the job. When choosing a new value, consider the following:

  • Persistence enables resilience in the event of a system failure.
  • Persistence enables snapshots to be reverted.
  • The time taken to persist a job is proportional to the size of the model in memory.

A model snapshot resource has 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.
min_version
(string) The minimum version required to be able to restore the model snapshot.
latest_record_time_stamp
(date) The timestamp of the latest processed record.
latest_result_time_stamp
(date) The timestamp of the latest bucket result.
model_size_stats
(object) Summary information describing the model. See Model Size Statistics.
retain
(boolean) If true, this snapshot will not be deleted during automatic cleanup of snapshots older than model_snapshot_retention_days. However, this snapshot will be deleted when the job is deleted. The default value is false.
snapshot_id
(string) A numerical character string that uniquely identifies the model snapshot. For example: "1491852978".
snapshot_doc_count
(long) For internal use only.
timestamp
(date) The creation timestamp for the snapshot.
Note

All of these properties are informational with the exception of description and retain.

Model Size Statisticsedit

The model_size_stats object has the following properties:

bucket_allocation_failures_count
(long) The number of buckets for which entities were not processed due to memory limit constraints.
job_id
(string) A numerical character string that uniquely identifies the 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.

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.
hard_limit
The internal models require more space that the configured memory limit. Some incoming data could not be processed.
model_bytes
(long) An approximation of the memory resources required for this analysis.
result_type
(string) Internal. This value is always set to "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_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.
Note

All of these properties are informational; you cannot change their values.