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https://issues.apache.org/jira/browse/MAHOUT-742?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13063408#comment-13063408
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Sebastian Schelter commented on MAHOUT-742:
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I'd like to note here that this issue only covers the most straight-forward
approach to computing pagerank in Map/Reduce and the code assumes that the
pagerank vector and any row from the transition matrix fit into memory.
There are more efficient ways to compute pagerank as described in
http://portal.acm.org/citation.cfm?id=1830263 and blockwise matrix-vector
mulitplication is necessary if the vectors don't fit into memory anymore.
Nevertheless we should be very happy to have this contribution and I think it
offers a good starting point for further improvements.
> Pagerank implementation in Map/Reduce
> -------------------------------------
>
> Key: MAHOUT-742
> URL: https://issues.apache.org/jira/browse/MAHOUT-742
> Project: Mahout
> Issue Type: New Feature
> Components: Graph
> Affects Versions: 0.6
> Reporter: Christoph Nagel
> Assignee: Sebastian Schelter
> Fix For: 0.6
>
> Attachments: MAHOUT-742.patch
>
>
> Hi,
> my name is Christoph Nagel. I'm student on technical university Berlin and
> participating on the course of Isabel Drost and Sebastian Schelter.
> My work is to implement the pagerank-algorithm, where the pagerank-vector
> fits in memory.
> For the computation I used the naive algorithm shown in the book 'Mining of
> Massive Datasets' from Rajaraman & Ullman
> (http://www-scf.usc.edu/~csci572/2012Spring/UllmanMiningMassiveDataSets.pdf).
> Matrix- and vector-multiplication are done with mahout methods.
> Most work is the transformation the input graph, which has to consists of a
> nodes- and edges file.
> Format of nodes file: <node>\n
> Format of edges file: <startNode>\t<endNode>\n
> Therefore I created the following classes:
> * LineIndexer: assigns each line an index
> * EdgesToIndex: indexes the nodes of the edges
> * EdgesIndexToTransitionMatrix: creates the transition matrix
> * Pagerank: computes PR from transition matrix
> * JoinNodesWithPagerank: creates the joined output
> * PagerankExampleJob: does the complete job
> Each class has a test (not PagerankExampleJob) and I took the example of the
> book for evaluating.
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