elasticsearch-js/docs/reference/api/MlJobConfig.md

MlJobConfig [interface-MlJobConfig]

Name	Type	Description
allow_lazy_open	boolean	Advanced configuration option. Specifies whether this job can open when there is insufficient machine learning node capacity for it to be immediately assigned to a node.
analysis_config	MlAnalysisConfig	The analysis configuration, which specifies how to analyze the data. After you create a job, you cannot change the analysis configuration; all the properties are informational.
analysis_limits	MlAnalysisLimits	Limits can be applied for the resources required to hold the mathematical models in memory. These limits are approximate and can be set per job. They do not control the memory used by other processes, for example the Elasticsearch Java processes.
background_persist_interval	Duration	Advanced configuration option. The time between each periodic persistence of the model. The default value is a randomized value between 3 to 4 hours, which avoids all jobs persisting at exactly the same time. The smallest allowed value is 1 hour.
custom_settings	MlCustomSettings	Advanced configuration option. Contains custom metadata about the job.
daily_model_snapshot_retention_after_days	long	Advanced configuration option, which affects the automatic removal of old model snapshots for this job. It specifies a period of time (in days) after which only the first snapshot per day is retained. This period is relative to the timestamp of the most recent snapshot for this job.
data_description	MlDataDescription	The data description defines the format of the input data when you send data to the job by using the post data API. Note that when configure a datafeed, these properties are automatically set.
datafeed_config	MlDatafeedConfig	The datafeed, which retrieves data from Elasticsearch for analysis by the job. You can associate only one datafeed with each anomaly detection job.
description	string	A description of the job.
groups	string[]	A list of job groups. A job can belong to no groups or many.
job_id	Id	Identifier for the anomaly detection job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters.
job_type	string	Reserved for future use, currently set to anomaly_detector.
model_plot_config	MlModelPlotConfig	This advanced configuration option stores model information along with the results. It provides a more detailed view into anomaly detection. Model plot provides a simplified and indicative view of the model and its bounds.
model_snapshot_retention_days	long	Advanced configuration option, which affects the automatic removal of old model snapshots for this job. It specifies the maximum period of time (in days) that snapshots are retained. This period is relative to the timestamp of the most recent snapshot for this job. The default value is 10, which means snapshots ten days older than the newest snapshot are deleted.
renormalization_window_days	long	Advanced configuration option. The period over which adjustments to the score are applied, as new data is seen. The default value is the longer of 30 days or 100 bucket_spans.
results_index_name	IndexName	A text string that affects the name of the machine learning results index. The default value is shared, which generates an index named .ml-anomalies-shared.
results_retention_days	long	Advanced configuration option. The period of time (in days) that results are retained. Age is calculated relative to the timestamp of the latest bucket result. If this property has a non-null value, once per day at 00:30 (server time), results that are the specified number of days older than the latest bucket result are deleted from Elasticsearch. The default value is null, which means all results are retained. Annotations generated by the system also count as results for retention purposes; they are deleted after the same number of days as results. Annotations added by users are retained forever.