图算法实现 - 单源最短路径

import scala.reflect.ClassTag
import org.apache.spark.graphx._
/**
 * Computes shortest paths to the given set of landmark vertices, returning a graph where each
 * vertex attribute is a map containing the shortest-path distance to each reachable landmark.
 */
object ShortestPaths {
  /** Stores a map from the vertex id of a landmark to the distance to that landmark. */
  type SPMap = Map[VertexId, Int]
  private def makeMap(x: (VertexId, Int)*) = Map(x: _*)
  private def incrementMap(spmap: SPMap): SPMap = spmap.map { case (v, d) => v -> (d + 1) }
  private def addMaps(spmap1: SPMap, spmap2: SPMap): SPMap =
    (spmap1.keySet ++ spmap2.keySet).map {
      k => k -> math.min(spmap1.getOrElse(k, Int.MaxValue), spmap2.getOrElse(k, Int.MaxValue))
    }.toMap
  /**
   * Computes shortest paths to the given set of landmark vertices.
   *
   * @tparam ED the edge attribute type (not used in the computation)
   *
   * @param graph the graph for which to compute the shortest paths
   * @param landmarks the list of landmark vertex ids. Shortest paths will be computed to each
   * landmark.
   *
   * @return a graph where each vertex attribute is a map containing the shortest-path distance to
   * each reachable landmark vertex.
   */
  def run[VD, ED: ClassTag](graph: Graph[VD, ED], landmarks: Seq[VertexId]): Graph[SPMap, ED] = {
    val spGraph = graph.mapVertices { (vid, attr) =>
      if (landmarks.contains(vid)) makeMap(vid -> 0) else makeMap()
    }
    val initialMessage = makeMap()
    def vertexProgram(id: VertexId, attr: SPMap, msg: SPMap): SPMap = {
      addMaps(attr, msg)
    }
    def sendMessage(edge: EdgeTriplet[SPMap, _]): Iterator[(VertexId, SPMap)] = {
      val newAttr = incrementMap(edge.dstAttr)
      if (edge.srcAttr != addMaps(newAttr, edge.srcAttr)) Iterator((edge.srcId, newAttr))
      else Iterator.empty
    }
    Pregel(spGraph, initialMessage)(vertexProgram, sendMessage, addMaps)
  }
}