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Martin Junghanns commented on FLINK-2905: ----------------------------------------- Hi, I agree with you that Option 3 is the most intuitive one. But as it is just a deduction from Option 2, I thought about two basic cases for intersection. Let's focus on the edges: E(G1): {code} 1, 3, 13 {code} E(G2): {code} 1, 3, 13 1, 3, 14 {code} Call 1 {{G' = G1.intersect(G2, considerEdgeValues = true)}} E(G') {code} 1, 3, 13 // G1 1, 3, 13 // G2 {code} Call 2 {{G' = G1.intersect(G2, considerEdgeValues = false)}} E(G') {code} 1, 3, 13 // G1 1, 3, 13 // G2 1, 3, 14 // G2 {code} If users are interested in Option 3, they can call {{E(G').distinct()}}. So imho, those two calls are the most basic ones and leave more specific analytics to the user (e.g. distinct, edge aggregation, ...). Wdyt? > Add intersect method to Graph class > ----------------------------------- > > Key: FLINK-2905 > URL: https://issues.apache.org/jira/browse/FLINK-2905 > Project: Flink > Issue Type: New Feature > Components: Gelly > Affects Versions: 0.10 > Reporter: Martin Junghanns > Assignee: Martin Junghanns > Priority: Minor > > Currently, the Gelly Graph supports the set operations > {{Graph.union(otherGraph)}} and {{Graph.difference(otherGraph)}}. It would be > nice to have a {{Graph.intersect(otherGraph)}} method, where the resulting > graph contains all vertices and edges contained in both input graphs. -- This message was sent by Atlassian JIRA (v6.3.4#6332)