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.
All of these properties are informational with the exception of
description and retain.
Model Size Statistics
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_statswere 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_statswere 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.
All of these properties are informational; you cannot change their values.