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From Krishna Sankar <ksanka...@gmail.com>
Subject Re: [GRAPHX] Graph Algorithms and Spark
Date Thu, 21 Apr 2016 19:32:09 GMT
Hi,

   1. Yep, GraphX is stable and would be a good choice for you to implement
   algorithms. For a quick intro you can refer to our Strata MLlib tutorial
   GraphX slides http://goo.gl/Ffq2Az
   2. GraphX has implemented algorithms like PageRank &
   ConnectedComponents[1]
   3. It also has primitives to develop the kind of algorithms that you are
   talking about
   4. For you to implement interesting algorithms, the main APIs of
   interest would be the pregel API and the aggregateMessages API[2]. Am sure
   you will also use the map*, subgraph and the join APIs.

Cheers
<k/>
[1]
http://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.graphx.GraphOps
[2]
http://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.graphx.Graph

On Thu, Apr 21, 2016 at 11:47 AM, tgensol <thibaut.gensollen@gmail.com>
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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