Updates an existing data frame analytics job.
Requires the following privileges:
machine_learning_adminbuilt-in role grants this privilege)
The data frame analytics job remembers which roles the user who updated it had at the time of the update. When you start the job, it performs the analysis using those same roles. If you provide secondary authorization headers, those credentials are used instead.
This API updates an existing data frame analytics job that performs an analysis on the source indices and stores the outcome in a destination index.
- (Required, string) Identifier for the data frame analytics job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters.
Specifies whether this job can start when there is insufficient machine learning node
capacity for it to be immediately assigned to a node. The default is
false; if a machine learning node with capacity to run the job cannot immediately be found, the API returns an error. However, this is also subject to the cluster-wide
xpack.ml.max_lazy_ml_nodessetting. See Advanced machine learning settings. If this option is set to
true, the API does not return an error and the job waits in the
startingstate until sufficient machine learning node capacity is available.
- (Optional, string) A description of the job.
The maximum number of threads to be used by the analysis.
The default value is
1. Using more threads may decrease the time necessary to complete the analysis at the cost of using more CPU. Note that the process may use additional threads for operational functionality other than the analysis itself.
The approximate maximum amount of memory resources that are permitted for
analytical processing. The default value for data frame analytics jobs is
1gb. If you specify a value for the
xpack.ml.max_model_memory_limitsetting, an error occurs when you try to create jobs that have
model_memory_limitvalues greater than that setting value. For more information, see Machine learning settings.