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From "Takeshi Yamamuro (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-15880) PREGEL Based Semi-Clustering Algorithm Implementation using Spark GraphX API
Date Thu, 19 Jan 2017 15:54:26 GMT

    [ https://issues.apache.org/jira/browse/SPARK-15880?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15830137#comment-15830137
] 

Takeshi Yamamuro commented on SPARK-15880:
------------------------------------------

I also think we do not have a strong reason to implement this on spark. Since activities to
support new features in this component is too inactive, maintenance costs are relatively high
as compared to gains we get from the implementation.

> PREGEL Based Semi-Clustering Algorithm Implementation using Spark GraphX API
> ----------------------------------------------------------------------------
>
>                 Key: SPARK-15880
>                 URL: https://issues.apache.org/jira/browse/SPARK-15880
>             Project: Spark
>          Issue Type: New Feature
>          Components: GraphX
>            Reporter: R J
>            Priority: Minor
>         Attachments: pregel_paper.pdf
>
>   Original Estimate: 672h
>  Remaining Estimate: 672h
>
> The main concept of Semi-Clustering algorithm on top of social graphs are:
>  - Vertices in a social graph typically represent people, and edges represent connections
between them.
>  - Edges may be based on explicit actions (e.g., adding a friend in a social networking
site), or may be inferred from people’s behaviour (e.g., email conversations or co-publication).
>  - Edges may have weights, to represent the interactions frequency or strength.
>  - A semi-cluster in a social graph is a group of people who interact frequently with
each other and less frequently with others.
>  - What distinguishes it from ordinary clustering is that, a vertex may belong to more
than one semi-cluster.



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