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From Robin East <>
Subject Re: [GRAPHX] Graph Algorithms and Spark
Date Thu, 21 Apr 2016 19:53:27 GMT

Aside from LDA, which is implemented in MLLib, GraphX has the following built-in algorithms:

PageRank/Personalised PageRank
Connected Components
Strongly Connected Components
Triangle Count
Shortest Paths
Label Propagation

It also implements a version of Pregel framework, a form of bulk-synchronous parallel processing
that is the foundation of most of the above algorithms. We cover other algorithms in our book
and if you search on google you will find a number of other examples.

Robin East
Spark GraphX in Action Michael Malak and Robin East
Manning Publications Co. <>

> On 21 Apr 2016, at 19:47, tgensol <> wrote:
> Hi there,
> I am working in a group of the University of Michigan, and we are trying to
> make (and find first) some Distributed graph algorithms. 
> I know spark, and I found GraphX. I read the docs, but I only found Latent
> Dirichlet Allocation algorithms working with GraphX, so I was wondering why
> ?
> Basically, the groupe wants to implement Minimal Spanning Tree, kNN,
> shortest path at first.
> So my askings are :
> Is graphX enough stable for developing this kind of algorithms on it ?
> Do you know some algorithms like these working on top of GraphX ? And if no,
> why do you think, nobody tried to do it ? Is this too hard ? Or just because
> nobody needs it ?
> Maybe, it is only my knowledge about GraphX which is weak, and it is not
> possible to make these algorithms with GraphX.
> Thanking you in advance,
> Best regards,
> Thibaut 
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