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Strongly connected component algorithm #112

Merged
merged 2 commits into from
Dec 19, 2013
Merged

Strongly connected component algorithm #112

merged 2 commits into from
Dec 19, 2013

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amatsukawa
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A SCC implementation in GraphX based on graph coloring. SCC of a vertex is the intersection of a vertex's successor and predecessors in the graph.

  1. Each vertex starts with its vertex id as its "color".
  2. Propagate the color forward from each vertex, accept a neighbor's color if it's smaller than yours. At convergence, vertices with the same color represents all nodes that are visitable from the root of that color.
  3. Reverse the graph.
  4. Start at all roots, walk the graph. Visit a neighbor if it has the same color as you. All nodes visited belongs to the SCC identified by the root color.

Closes #24

@AmplabJenkins
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All automated tests passed.
Refer to this link for build results: https://amplab.cs.berkeley.edu/jenkins/job/GraphXPullRequestBuilder/5684/

@ankurdave
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Cool, thanks!

ankurdave added a commit that referenced this pull request Dec 19, 2013
Strongly connected component algorithm
@ankurdave ankurdave merged commit da301b5 into amplab:master Dec 19, 2013
pwendell added a commit that referenced this pull request Mar 21, 2014
Author: Patrick Wendell <[email protected]>

Closes #112 from pwendell/pyspark-take and squashes the following commits:

daae80e [Patrick Wendell] SPARK-1019: pyspark RDD take() throws an NPE
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Add a strongly connected components example
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