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https://issues.apache.org/jira/browse/SPARK-11496?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15471257#comment-15471257
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Apache Spark commented on SPARK-11496:
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User 'moustaki' has created a pull request for this issue:
https://github.com/apache/spark/pull/14998
> Parallel implementation of personalized pagerank
> ------------------------------------------------
>
> Key: SPARK-11496
> URL: https://issues.apache.org/jira/browse/SPARK-11496
> Project: Spark
> Issue Type: New Feature
> Components: GraphX
> Affects Versions: 2.1.0
> Reporter: Yves Raimond
> Assignee: Yves Raimond
> Priority: Minor
>
> The current implementation of personalized pagerank only supports one source
> node. Most applications of personalized pagerank require to run the
> propagation for multiple source nodes. However code such as:
> {code}
> sourceVertices.map { sourceVertex =>
> graph.staticPersonalizedPageRank(sourceVertex, 10) }
> {code}
> Will be very slow, as it needs to run 10 iterations * sourceVertices.size
> propagation steps.
> It would be good to offer an alternative API that runs personalized pagerank
> over a list of source vertices in parallel, so that it only needs to run 10
> propagation steps in the example above.
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