hub algorithm degree
Runs the degree algorithm on a model and saves the results for each entity to a model property.
Centrality algorithms measure the importance and significance of individual entities and relationships. When you run centrality algorithms, the value returned by an algorithm indicates the importance of an element. The degree algorithm reflects the number of relationships on an entity. The Degree Centrality algorithm can help find important or popular entities in a graph database.
Usage
hub algorithm degree --m model --d direction --wp weightProperty --lvsignificantLowValues --op outputProperty --w waitForCompleteRequired | Argument | Description |
---|---|---|
Yes | --m model |
Specifies the model. |
No | --d direction | Specifies the direction to apply to the algorithm where direction is one of the following:
|
No | --wp weightProperty |
Specifies a relationship property to use to measure how unfavorable a relationship is. By default, a higher value indicates a negative association. The default setting is null. |
No | --lv significantLowValues | If a relationship property is used as weight, this specifies whether a lower value is considered better than a higher value.
|
No | --op outputProperty |
Specifies the output property name to be something other than the algorithm name. The default is Degree. |
No | --w waitForComplete |
Specifies whether to wait for jobs to complete in a synchronous mode.
|
Example
The following will run the degree algorithm on the 911 model.
hub algorithm degree --m 911