I think this is a separate issue with how the EdgeRDDImpl partitions
edges. If you can merge this change in and rebuild, it should work:
https://github.com/apache/spark/pull/4136/files
If you can't, I just called the Graph.partitonBy() method right after
construction my graph but before perfo
Just curious, is this set to be merged at some point?
On Thu Jan 22 2015 at 4:34:46 PM Ankur Dave wrote:
> At 2015-01-22 02:06:37 -0800, NicolasC wrote:
> > I try to execute a simple program that runs the ShortestPaths algorithm
> > (org.apache.spark.graphx.lib.ShortestPaths) on a small grid gr
Found a problem in the spark-shell, but can't confirm that it's related to
open issues on Spark's JIRA page. I was wondering if anyone could help
identify if this is an issue or if it's already being addressed.
Test: (in spark-shell)
case class Person(name: String, age: Int)
val peopleList = Lis
Found a problem in the spark-shell, but can't confirm that it's related to
open issues on Spark's JIRA page. I was wondering if anyone could help
identify if this is an issue or if it's already being addressed.
Test: (in spark-shell)
case class Person(name: String, age: Int)
val peopleList = Lis
I'm trying to implement a graph algorithm that does a form of path
searching. Once a certain criteria is met on any path in the graph, I
wanted to halt the rest of the iterations. But I can't see how to do that
with the Pregel API, since any vertex isn't able to know the state of other
arbitrary
I'm trying to implement a graph algorithm that does a form of path
searching. Once a certain criteria is met on any path in the graph, I
wanted to halt the rest of the iterations. But I can't see how to do that
with the Pregel API, since any vertex isn't able to know the state of other
arbitrary
t user and product.
> > If we don't have any data trained on a user, there is no way to predict
> how he would like a product.
> > That filtering takes a lot of work though. I can share some code on that
> too if you like.
> >
> > Best,
> > Burak
> >
&
I have a few questions regarding a collaborative filtering model, and was
hoping for some recommendations (no pun intended...)
*Setup*
I have a csv file with user/movie/ratings named unimaginatively
'movies.csv'. Here are the contents:
0,0,5
0,1,5
0,2,0
0,3,0
1,0,5
1,3,0
2,1,4
2,2,0
3,0,0
3,1,0
