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Elastic Docs ›Elasticsearch Guide [6.8] ›X-Pack APIs ›Definitions

Model snapshot resources

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Model snapshot resources

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Model snapshots are saved to disk periodically. By default, this 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.
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

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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.

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

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