[
https://issues.apache.org/jira/browse/SPARK-13313?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15146731#comment-15146731
]
Petar Zecevic commented on SPARK-13313:
---------------------------------------
Yes, you need articles.tsv and links.tsv from this archive:
http://snap.stanford.edu/data/wikispeedia/wikispeedia_paths-and-graph.tar.gz
Then parse the data, assign IDs to article names and create the graph:
val articles = sc.textFile("articles.tsv", 6).filter(line => line.trim() != ""
&& !line.startsWith("#")).zipWithIndex().cache()
val links = sc.textFile("links.tsv", 6).filter(line => line.trim() != "" &&
!line.startsWith("#"))
val linkIndexes = links.map(x => { val spl = x.split("\t"); (spl(0), spl(1))
}).join(articles).map(x => x._2).join(articles).map(x => x._2)
val wikigraph = Graph.fromEdgeTuples(linkIndexes, 0)
Then get strongly connected components:
val wikiSCC = wikigraph.stronglyConnectedComponents(100)
wikiSCC graph contains 519 SCCs, but there should be much more. The largest SCC
in wikiSCC has 4051 vertices and that's obviously wrong.
The change in line 89, which I mentioned, seems to solve this problem, but then
other issues arise (stack overflow etc) and I don't have time to investigate
further. I hope someone will look into this.
> Strongly connected components doesn't find all strongly connected components
> ----------------------------------------------------------------------------
>
> Key: SPARK-13313
> URL: https://issues.apache.org/jira/browse/SPARK-13313
> Project: Spark
> Issue Type: Bug
> Components: GraphX
> Affects Versions: 1.6.0
> Reporter: Petar Zecevic
>
> Strongly connected components algorithm doesn't find all strongly connected
> components. I was using Wikispeedia dataset
> (http://snap.stanford.edu/data/wikispeedia.html) and the algorithm found 519
> SCCs and one of them had 4051 vertices, which in reality don't have any edges
> between them.
> I think the problem could be on line 89 of StronglyConnectedComponents.scala
> file where EdgeDirection.In should be changed to EdgeDirection.Out. I believe
> the second Pregel call should use Out edge direction, the same as the first
> call because the direction is reversed in the provided sendMsg function
> (message is sent to source vertex and not destination vertex).
> If that is changed (line 89), the algorithm starts finding much more SCCs,
> but eventually stack overflow exception occurs. I believe graph objects that
> are changed through iterations should not be cached, but checkpointed.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
