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https://issues.apache.org/jira/browse/GIRAPH-26?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13431437#comment-13431437
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Eli Reisman commented on GIRAPH-26:
-----------------------------------
Sounds great. New word on high is, for apps keep the constant defs in your IO
or vertex class rather than GiraphJob and then just eliminate the run() method
and that sort of stuff. If this is all old news for the new patch, then
disregard. Really looking forward to the patch.
You mentioned that it generates random edge weight data as well as edges
themselves. I wonder, are these just Random() values or are they generated with
a particular distribution such as the way your edges are generated? if they are
just straight up random, could we have configs for those too? Like someone
might want to do shortest paths without negative edge weights, some might have
other value needs for their algorithm tests (values all greater than 100 or
less than 1000 etc.) Just curious not a big deal.
> Improve PseudoRandomVertexInputFormat to create a more realistic synthetic
> graph (e.g. power-law distributed vertex-cardinality).
> ---------------------------------------------------------------------------------------------------------------------------------
>
> Key: GIRAPH-26
> URL: https://issues.apache.org/jira/browse/GIRAPH-26
> Project: Giraph
> Issue Type: Test
> Components: benchmark
> Affects Versions: 0.2.0
> Reporter: Jake Mannix
> Assignee: Sean Choi
> Priority: Minor
> Fix For: 0.2.0
>
> Attachments: GIRAPH-26-1.patch
>
>
> The PageRankBenchmark class, to be a proper benchmark, should run over graphs
> which look more like data seen in the wild, and web link graphs, social
> network graphs, and text corpora (represented as a bipartite graph) all have
> power-law distributions, so benchmarking a synthetic graph which looks more
> like this would be a nice test which would stress cases of uneven
> split-distribution and bottlenecks of subclusters of the graph of heavily
> connected vertices.
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