Subgraph Extraction#

The Subgraph Extraction algorithm is the most straight-forward of the community algorithms. It extracts of a portion of a graph and returns a Graph object for follow-on analytics. For example, many of the community detection analytics simply return a list of vertices in a cluster. In order to run follow-on processing against a cluster, all the edges within that cluster are also needed. In fact it is more a tool than an analysis algorithm. Given a set of node ids, subgraph returns a graph object containing all the edges where both ends are in the node list.

When to use Subgraph Extraction#

  • when there are known nodes of interest and their related edges need to be analyzed further

  • When a data set is “too large” for analysis or display.

  • when previous analysis has revealed a community and a graph object containing that community is needed.

When not to use Subgraph Extraction#

  • For discovery or analysis, subgraph extraction can prune data that might otherwise reveal graph structure

  • To extract a community, subgraph extraction pulls out ALL edges, so it neither cleans nor promotes edges.

  • To extract all nodes within n-hops of a node. cuGraph alsow supplies this related function but subgraph extraction does not do this.

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