1.1 - 8.10 - Betweenness Syntax Elements - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Teradata Vantage
Release Number
October 2019
Content Type
Programming Reference
Publication ID
English (United States)
Specify the target key (the names of the Edges table columns that identify the target vertex). If you specify targets_table, then the function uses only the vertices in targets_table as targets (which must be a subset of those that this syntax element specifies).
[Optional] Specify whether the graph is directed.
Default: 'true'
[Optional] Specify the name of the Edges table column that contains edge weights. The weights are positive values.
Default behavior: The weight of each edge is 1 (that is, the graph is unweighted).
[Optional] Specify the maximum distance (an integer) between the source and target vertices. A negative max_distance specifies an infinite distance. If vertices are separated by more than max_distance, the function does not output them.
Default: 10
[Optional] Specify the number of source vertices that execute a SNSP algorithm in parallel. If group_size exceeds the number of source vertices in each partition, s, then s is the group size.
Default behavior: The function calculates the optimal group size based on various cluster and query characteristics.

Running a group of vertices on each vworker, in parallel, uses less memory than running all vertices on each vworker.

[Optional] Specify the sample rate (the percentage of source vertices to sample), a DOUBLE PRECISION value in the range (0.0, 1.0]. The number of source vertices that the function uses to create betweenness is approximately sample_rate*n, where n is the number of vertices in the graph.
[Optional] Specify the names of the Vertices table columns to copy to the output table. These columns enable you to identify the different betweenness scores in the output table.