forked from D-Net/dnet-hadoop
37 lines
1.1 KiB
Scala
37 lines
1.1 KiB
Scala
package eu.dnetlib.dhp.dedup.graph
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import org.apache.spark.graphx._
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import org.apache.spark.rdd.RDD
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import scala.collection.JavaConversions;
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object GraphProcessor {
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def findCCs(vertexes: RDD[(VertexId, String)], edges: RDD[Edge[String]], maxIterations: Int): RDD[ConnectedComponent] = {
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val graph: Graph[String, String] = Graph(vertexes, edges).partitionBy(PartitionStrategy.RandomVertexCut) //TODO remember to remove partitionby
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val cc = graph.connectedComponents(maxIterations).vertices
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val joinResult = vertexes.leftOuterJoin(cc).map {
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case (id, (openaireId, cc)) => {
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if (cc.isEmpty) {
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(id, openaireId)
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}
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else {
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(cc.get, openaireId)
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}
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}
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}
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val connectedComponents = joinResult.groupByKey()
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.map[ConnectedComponent](cc => asConnectedComponent(cc))
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connectedComponents
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}
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def asConnectedComponent(group: (VertexId, Iterable[String])): ConnectedComponent = {
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val docs = group._2.toSet[String]
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val connectedComponent = new ConnectedComponent(JavaConversions.setAsJavaSet[String](docs));
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connectedComponent
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}
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} |