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https://issues.apache.org/jira/browse/HAMA-594?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13631295#comment-13631295
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Rishabh Garg commented on HAMA-594:
-----------------------------------
Thankyou for your reply. I have gone through the paper properly now and was
successful in understanding the algorithm involved. Just trying to get
practical experience with Hama and Hadoop. Would you like me to implement the
sample code you had put around a year ago ?
i.e.
@Override
public void compute(Iterator<SCMessage> messages) throws IOException {
if (this.getSuperstepCount() == 0) {
// In superstep 0, V enters itself in that list as a semi-cluster of
// size 1 and score 1, and publishes itself to all of its neighbors.
}
// In subsequent supersteps, V circulates over the received semi-clusters
SCMessage clusters = null;
while ((clusters = messages.next()) != null) {
for (SemiCluster c : clusters.getClusters()) {
// If a semi-cluster c does not already contain V, V is added to c to
// form c’.
}
}
// The semi-clusters are sorted by their scores and the
// best ones are sent to V’s neighbors.
// Vertex V updates its list of semi-clusters with the
// semi-clusters that contain V.
boolean updated = updateLocalClusters(clusters);
if (!updated) {
// The algorithm terminates either when the semi-
// clusters stop changing or the user may provide a
// limit.
// At that point, the list of best semi-cluster
// candidates for each vertex may be aggregated
// into a global list of best semi-clusters.
voteToHalt();
} else {
// The semi-clusters are sorted by their scores and the best ones are
// sent to V’s neighbors.
}
}
}
> Implementation of a Semi-Clustering algorithm, described in Pregel paper.
> -------------------------------------------------------------------------
>
> Key: HAMA-594
> URL: https://issues.apache.org/jira/browse/HAMA-594
> Project: Hama
> Issue Type: New Feature
> Components: examples, graph
> Reporter: Edward J. Yoon
> Labels: gsoc, gsoc2013, mentor
>
> {quote}
> 5.4 Semi-Clustering
> Pregel has been used for several different versions of clus-tering. One
> version, semi-clustering, arises in social graphs. Vertices in a social graph
> typically represent people, and edges represent connections between them.
> ....
> {quote}
> This issue implements Semi-Clustering algorithm, described in Pregel paper,
> using Hama graph APIs.
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