Closeness Arguments - Aster Analytics

Teradata AsterĀ® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Published
September 2017
Language
English (United States)
Last Update
2018-04-17
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dita:id
B700-1022
lifecycle
previous
Product Category
Software
TargetKey
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).
Directed
[Optional] Specifies whether the graph is directed. Default: 'true'.
EdgeWeight
[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).
MaxDistance
[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.
GroupSize
[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.

SampleRate
[Optional] Specifies the sample rate (the percentage of source vertices to sample), a numeric value in the range (0, 1]. Default: 1.
Accumulate
[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.