7.00.02 - Closeness Arguments - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2

Aster Analytics
Release Number
September 2017
Content Type
Programming Reference
User Guide
Publication ID
English (United States)
Last Update
Specifies 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 argument specifies).
[Optional] Specifies whether the graph is directed. Default: 'true'.
[Optional] Specifies 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] Specifies 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] Specifies the number of source vertices that run 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 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] Specifies the sample rate (the percentage of source vertices to sample), a numeric value in the range (0, 1]. Default: 1.
[Optional] Specifies the names of the vertices table columns to copy to the output table. These columns enable you to identify the different closeness scores in the output table.