[
https://issues.apache.org/jira/browse/FLINK-3768?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15245621#comment-15245621
]
Greg Hogan commented on FLINK-3768:
-----------------------------------
Yes, same objective but different implementations. This implementation counts
triangles. [FLINK-1528] was storing each edge list in a {{HashSet}} then
performing the {{Graph.reduceOnNeighbors}} join to test whether each 2-hop
vertex is also a neighbor (double counting triangles, which is accounted for in
the computation of the clustering coefficient). Listing triangles is
significantly faster than broadcasting edge lists to all neighbors which is
quadratic in vertex degree.
> Clustering Coefficient
> ----------------------
>
> Key: FLINK-3768
> URL: https://issues.apache.org/jira/browse/FLINK-3768
> Project: Flink
> Issue Type: New Feature
> Components: Gelly
> Affects Versions: 1.1.0
> Reporter: Greg Hogan
> Assignee: Greg Hogan
> Fix For: 1.1.0
>
>
> The local clustering coefficient measures the connectedness of each vertex's
> neighborhood. Values range from 0.0 (no edges between neighbors) to 1.0
> (neighborhood is a clique).
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
