homebrew code and the method
used by Wikipedia, assign different values to these vertices. Our
own code has been compared against the PageRank implementation in
the NetworkX package and it agrees.
It looks like bug #1 is due to the Spark implementation of PageRank
not emitting output
Hi,
Colleagues and I have found that the PageRank implementation bundled
with Spark is incorrect in several ways. The code in question is in
Apache Spark 1.2 distribution's examples directory, called
SparkPageRank.scala.
Consider the example graph presented in the colorful figure
homebrew code and the method
used by Wikipedia, assign different values to these vertices. Our
own code has been compared against the PageRank implementation in
the NetworkX package and it agrees.
It looks like bug #1 is due to the Spark implementation of PageRank
not emitting output
(and spark). Had a look at the code and don't see that it
is, but could be missing something,
Thanks
Karen
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At 2014-11-15 18:01:22 -0700, tom85 tom.manha...@gmail.com wrote:
This line: val newPR = oldPR + (1.0 - resetProb) * msgSum
makes no sense to me. Should it not be:
val newPR = resetProb/graph.vertices.count() + (1.0 - resetProb) * msgSum
?
This is an unusual version of PageRank where the
Hi,
I wonder if the pagerank implementation is correct. More specifically, I
look at the following function from PageRank.scala
https://github.com/apache/spark/blob/master/graphx/src/main/scala/org/apache/spark/graphx/lib/PageRank.scala
, which is given to Pregel:
def vertexProgram(id
