39 lines
1.2 KiB
Scala
39 lines
1.2 KiB
Scala
package eu.dnetlib.graph
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import eu.dnetlib.ConnectedComponent
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import eu.dnetlib.pace.model.MapDocument
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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, MapDocument)], edges: RDD[Edge[String]], maxIterations: Int): RDD[ConnectedComponent] = {
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val graph: Graph[MapDocument, 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().map[ConnectedComponent](cc => asConnectedComponent(cc))
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(connectedComponents)
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}
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def asConnectedComponent(group: (VertexId, Iterable[MapDocument])): ConnectedComponent = {
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val docs = group._2.toSet[MapDocument]
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val connectedComponent = new ConnectedComponent(JavaConversions.setAsJavaSet[MapDocument](docs));
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connectedComponent
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}
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} |