Fix style errors; generalize ShortestPath type signature

graphx/src/main/scala/org/apache/spark/graphx/lib/ShortestPaths.scala

@@ -18,48 +18,44 @@
 package org.apache.spark.graphx.lib
 
 import org.apache.spark.graphx._
+import scala.reflect.ClassTag
 
 object ShortestPaths {
   type SPMap = Map[VertexId, Int] // map of landmarks -> minimum distance to landmark
   def SPMap(x: (VertexId, Int)*) = Map(x: _*)
   def increment(spmap: SPMap): SPMap = spmap.map { case (v, d) => v -> (d + 1) }
   def plus(spmap1: SPMap, spmap2: SPMap): SPMap =
-    (spmap1.keySet ++ spmap2.keySet).map{
-      k => k -> scala.math.min(spmap1.getOrElse(k, Int.MaxValue), spmap2.getOrElse(k, Int.MaxValue))
+    (spmap1.keySet ++ spmap2.keySet).map {
+      k => k -> math.min(spmap1.getOrElse(k, Int.MaxValue), spmap2.getOrElse(k, Int.MaxValue))
     }.toMap
 
   /**
    * Compute the shortest paths to each landmark for each vertex and
    * return an RDD with the map of landmarks to their shortest-path
    * lengths.
    *
-   * @tparam VD the shortest paths map for the vertex
-   * @tparam ED the incremented shortest-paths map of the originating
-   * vertex (discarded in the computation)
+   * @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
    *
    * @return a graph with vertex attributes containing a map of the
    * shortest paths to each landmark
    */
-  def run[VD, ED](graph: Graph[VD, ED], landmarks: Seq[VertexId])
-    (implicit m1: Manifest[VD], m2: Manifest[ED]): Graph[SPMap, SPMap] = {
-
+  def run[ED: ClassTag](graph: Graph[_, ED], landmarks: Seq[VertexId]): Graph[SPMap, ED] = {
     val spGraph = graph
-      .mapVertices{ (vid, attr) =>
+      .mapVertices { (vid, attr) =>
         if (landmarks.contains(vid)) SPMap(vid -> 0)
         else SPMap()
       }
-      .mapTriplets{ edge => edge.srcAttr }
 
     val initialMessage = SPMap()
 
     def vertexProgram(id: VertexId, attr: SPMap, msg: SPMap): SPMap = {
       plus(attr, msg)
     }
 
-    def sendMessage(edge: EdgeTriplet[SPMap, SPMap]): Iterator[(VertexId, SPMap)] = {
+    def sendMessage(edge: EdgeTriplet[SPMap, _]): Iterator[(VertexId, SPMap)] = {
       val newAttr = increment(edge.srcAttr)
       if (edge.dstAttr != plus(newAttr, edge.dstAttr)) Iterator((edge.dstId, newAttr))
       else Iterator.empty

graphx/src/test/scala/org/apache/spark/graphx/lib/ShortestPathsSuite.scala

@@ -30,13 +30,18 @@ class ShortestPathsSuite extends FunSuite with LocalSparkContext {
 
   test("Shortest Path Computations") {
     withSpark { sc =>
-      val shortestPaths = Set((1,Map(1 -> 0, 4 -> 2)), (2,Map(1 -> 1, 4 -> 2)), (3,Map(1 -> 2, 4 -> 1)),
-                              (4,Map(1 -> 2, 4 -> 0)), (5,Map(1 -> 1, 4 -> 1)), (6,Map(1 -> 3, 4 -> 1)))
-      val edgeSeq = Seq((1, 2), (1, 5), (2, 3), (2, 5), (3, 4), (4, 5), (4, 6)).flatMap{ case e => Seq(e, e.swap) }
+      val shortestPaths = Set(
+        (1, Map(1 -> 0, 4 -> 2)), (2, Map(1 -> 1, 4 -> 2)), (3, Map(1 -> 2, 4 -> 1)),
+        (4, Map(1 -> 2, 4 -> 0)), (5, Map(1 -> 1, 4 -> 1)), (6, Map(1 -> 3, 4 -> 1)))
+      val edgeSeq = Seq((1, 2), (1, 5), (2, 3), (2, 5), (3, 4), (4, 5), (4, 6)).flatMap {
+        case e => Seq(e, e.swap)
+      }
       val edges = sc.parallelize(edgeSeq).map { case (v1, v2) => (v1.toLong, v2.toLong) }
       val graph = Graph.fromEdgeTuples(edges, 1)
       val landmarks = Seq(1, 4).map(_.toLong)
-      val results = ShortestPaths.run(graph, landmarks).vertices.collect.map { case (v, spMap) => (v, spMap.mapValues(_.get)) }
+      val results = ShortestPaths.run(graph, landmarks).vertices.collect.map {
+        case (v, spMap) => (v, spMap.mapValues(_.get))
+      }
       assert(results.toSet === shortestPaths)
     }
   }