7.00.02 - Modularity 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 key of the target vertex of an edge. The key consists of the names of one or more edges table columns.
[Optional] Legacy argument that determined whether the graph was directed. The default value was 'true'. The function ignores this argument, treating all graphs as undirected.
[Optional] Specifies the name of the edges table column that contains edge weights. Each edge_weight is a positive value. Default behavior: The weight of each edge is 1 (that is, the graph is unweighted).

This argument determines how the function treats duplicate edges (that is, edges with the same source and destination, which might have different weights). For a weighted graph, the function treats duplicate edges as a single edge whose weight is the sum of the weights of the duplicate edges. For an unweighted graph, the function uses only one of the duplicate edges.

[Optional] Specifies the name of the column that represents the community association of the vertices. Use this argument if you know some vertex communities.
[Optional] Specifies hierarchical-level information for the communities. For details, see Resolution. Default: 1.0. If you specify a list of resolution values, the function incrementally finds the communities for each value and for the default value.

Each resolution must be a distinct DOUBLE PRECISION value in the range [0.0, 1000000.0]. The value 0.0 puts each node in its own community of size 1. You can specify a maximum of 500 resolution values.

[Optional] Specifies the name of the table that the function generates to output the weights of the edges between the communities at different resolution levels. If a table named community_edge_table exists, the function overwrites the existing table. If you omit this argument, the function does not create this table.
[Optional] Specifies the seed to use to create a random number during modularity computation. The seed must be a positive BIGINT value. The function multiplies seed by the hash code of vertex_key to generate a unique seed for each vertex. Default: 1.

The function also uses seed for these purposes:

  • To break ties between different vertices during community formation
  • To determine when to stop community formation

    If seed is 1 (default value), community formation continues until the change in modularity score drops below a threshold value. The threshold value is set in the function code; you cannot change it.

    If seed is set to any other value, community formation continues until the change in modularity score between iterations is 0. This deeper analysis of the graph can improve community formation, but can also increase execution time.

[Optional] Specifies the names of the vertices columns to copy to the community vertex table. Default behavior: The function copies the vertex_key columns to the output vertex table for each vertex, changing the column names to id, id_1, id_2, and so on.