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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-2909) Gelly Graph Generators
Date Fri, 08 Apr 2016 13:59:25 GMT

    [ https://issues.apache.org/jira/browse/FLINK-2909?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15232216#comment-15232216
] 

ASF GitHub Bot commented on FLINK-2909:
---------------------------------------

Github user vasia commented on the pull request:

    https://github.com/apache/flink/pull/1807#issuecomment-207442760
  
    Really amazing job @greghogan! I left a few suggestions on improving the docs / usage
of the generators. Otherwise, I think it's good to merge. This will be a great addition to
Gelly :) Do you have any idea on how the generators scale?


> Gelly Graph Generators
> ----------------------
>
>                 Key: FLINK-2909
>                 URL: https://issues.apache.org/jira/browse/FLINK-2909
>             Project: Flink
>          Issue Type: New Feature
>          Components: Gelly
>    Affects Versions: 1.0.0
>            Reporter: Greg Hogan
>            Assignee: Greg Hogan
>
> Include a selection of graph generators in Gelly. Generated graphs will be useful for
performing scalability, stress, and regression testing as well as benchmarking and comparing
algorithms, for both Flink users and developers. Generated data is infinitely scalable yet
described by a few simple parameters and can often substitute for user data or sharing large
files when reporting issues.
> There are at multiple categories of graphs as documented by [NetworkX|https://networkx.github.io/documentation/latest/reference/generators.html]
and elsewhere.
> Graphs may be a well-defined, i.e. the [Chvátal graph|https://en.wikipedia.org/wiki/Chv%C3%A1tal_graph].
These may be sufficiently small to populate locally.
> Graphs may be scalable, i.e. complete and star graphs. These should use Flink's distributed
parallelism.
> Graphs may be stochastic, i.e. [RMat graphs|http://snap.stanford.edu/class/cs224w-readings/chakrabarti04rmat.pdf]
. A key consideration is that the graphs should source randomness from a seedable PRNG and
generate the same Graph regardless of parallelism.



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