EshwarSR commented on a change in pull request #24230: [SPARK-27295][GraphX]
Provision to provide the initial scores for source nodes while running
Personalized Page Rank
URL: https://github.com/apache/spark/pull/24230#discussion_r270094583
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File path: graphx/src/main/scala/org/apache/spark/graphx/lib/PageRank.scala
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@@ -196,11 +196,45 @@ object PageRank extends Logging {
require(sources.nonEmpty, s"The list of sources must be non-empty," +
s" but got ${sources.mkString("[", ",", "]")}")
+ val sourcesWithScores = sources zip Array.fill(sources.size)(1.0)
+ runParallelPersonalizedPageRank(graph, numIter, resetProb,
sourcesWithScores)
+ }
+
+ /**
+ * Run Personalized PageRank for a fixed number of iterations, for a
+ * set of starting nodes in parallel. Returns a graph with vertex attributes
+ * containing the pagerank relative to all starting nodes (as a sparse
vector) and
+ * edge attributes the normalized edge weight
+ *
+ * @tparam VD The original vertex attribute (not used)
+ * @tparam ED The original edge attribute (not used)
+ *
+ * @param graph The graph on which to compute personalized pagerank
+ * @param numIter The number of iterations to run
+ * @param resetProb The random reset probability
+ * @param sources The list of (source, initial score) to compute
personalized pagerank from
+ * @return the graph with vertex attributes
+ * containing the pagerank relative to all starting nodes (as a
sparse vector
+ * indexed by the position of nodes in the sources list) and
+ * edge attributes the normalized edge weight
+ */
+ def runParallelPersonalizedPageRank[VD: ClassTag, ED: ClassTag](
+ graph: Graph[VD, ED],
+ numIter: Int,
+ resetProb: Double = 0.15,
+ sources: Array[(VertexId, Double)]): Graph[Vector, Double] = {
+ require(numIter > 0, s"Number of iterations must be greater than 0," +
+ s" but got ${numIter}")
+ require(resetProb >= 0 && resetProb <= 1, s"Random reset probability must
belong" +
+ s" to [0, 1], but got ${resetProb}")
+ require(sources.nonEmpty, s"The list of sources must be non-empty," +
+ s" but got ${sources.mkString("[", ",", "]")}")
+
val zero = Vectors.sparse(sources.size, List()).asBreeze
- // map of vid -> vector where for each vid, the _position of vid in
source_ is set to 1.0
+ // map of vid -> vector where for each vid, the _position of vid in
source_ is set to provided score
val sourcesInitMap = sources.zipWithIndex.map { case (vid, i) =>
Review comment:
Done
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