What is GraphX:

 

-          It can be viewed as a kind of Distributed, Parallel, Graph Database

-          It can be viewed as Graph Data Structure (Data Structures 101 from 
your CS course)

-          It features some off the shelve algos for Graph Processing and 
Navigation  (Algos and Data Structures 101) and the implementation of these 
takes advantage of the distributed parallel nature of GrapphX

 

Any of the MLib algos can be applied to ANY data structure from time series to 
graph to matrix/tabular etc – it is up to your needs and imagination 

 

As an example – Clustering – you can apply it to Graph Data Structure BUT you 
may also leverage the Graph inherent connection/clustering properties and Graph 
algos taking advantage of that Instead of e.g. the run of the mill K-Means 
which is ok for te.g. time series, matrix etc data structures

 

From: Timothée Rebours [mailto:t.rebo...@gmail.com] 
Sent: Thursday, June 18, 2015 10:44 AM
To: Akhil Das
Cc: user@spark.apache.org
Subject: Re: Machine Learning on GraphX

 

Thanks for the quick answer.
I've already followed this tutorial but it doesn't use GraphX at all. My goal 
would be to work directly on the graph, and not extracting edges and vertices 
from the graph as standard RDDs and then work on that with the standard MLlib's 
ALS, which has no interest. That's why I tried with the other implementation, 
but it's not optimized at all.

I might have gone in the wrong direction with the ALS, but I'd like to see 
what's possible to do with MLlib on GraphX. Any idea ?

 

2015-06-18 11:19 GMT+02:00 Akhil Das <ak...@sigmoidanalytics.com>:

This might give you a good start 
http://ampcamp.berkeley.edu/big-data-mini-course/movie-recommendation-with-mllib.html
 its a bit old though.




Thanks

Best Regards

 

On Thu, Jun 18, 2015 at 2:33 PM, texol <t.rebo...@gmail.com> wrote:

Hi,

I'm new to GraphX and I'd like to use Machine Learning algorithms on top of
it. I wanted to write a simple program implementing MLlib's ALS on a
bipartite graph (a simple movie recommendation), but didn't succeed. I found
an implementation on Spark 1.1.x
(https://github.com/ankurdave/spark/blob/GraphXALS/graphx/src/main/scala/org/apache/spark/graphx/lib/ALS.scala)
of ALS on GraphX, but it is painfully slow compared to the standard
implementation, and uses the deprecated (in the current version)
PregelVertex class.
Do we expect a new implementation ? Is there a smarter solution to do so ?

Thanks,
Regards,
Timothée Rebours.




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