More cleanup.

graphx/src/main/scala/org/apache/spark/graphx/Edge.scala

@@ -37,7 +37,7 @@ case class Edge[@specialized(Char, Int, Boolean, Byte, Long, Float, Double) ED]
     if (vid == srcId) EdgeDirection.Out else { assert(vid == dstId); EdgeDirection.In }
 }
 
-object Edge {
+private[graphx] object Edge {
   def lexicographicOrdering[ED] = new Ordering[Edge[ED]] {
     override def compare(a: Edge[ED], b: Edge[ED]): Int =
       (if (a.srcId != b.srcId) a.srcId - b.srcId else a.dstId - b.dstId).toInt

graphx/src/main/scala/org/apache/spark/graphx/EdgeDirection.scala

@@ -26,6 +26,9 @@ class EdgeDirection private (private val name: String) extends Serializable {
 }
 
 
+/**
+ * A set of [[EdgeDirection]]s.
+ */
 object EdgeDirection {
   /** Edges arriving at a vertex. */
   final val In = new EdgeDirection("In")

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

@@ -14,13 +14,11 @@ object ConnectedComponents {
    * @tparam ED the edge attribute type (preserved in the computation)
    *
    * @param graph the graph for which to compute the connected components
-   * @param undirected compute reachability ignoring edge direction.
    *
    * @return a graph with vertex attributes containing the smallest vertex in each
    *         connected component
    */
-  def run[VD: ClassTag, ED: ClassTag](graph: Graph[VD, ED]):
-    Graph[VertexID, ED] = {
+  def run[VD: ClassTag, ED: ClassTag](graph: Graph[VD, ED]): Graph[VertexID, ED] = {
     val ccGraph = graph.mapVertices { case (vid, _) => vid }
     def sendMessage(edge: EdgeTriplet[VertexID, ED]) = {
       if (edge.srcAttr < edge.dstAttr) {

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

@@ -9,11 +9,11 @@ import org.apache.spark.graphx._
  *
  * The algorithm is relatively straightforward and can be computed in three steps:
  *
- * 1) Compute the set of neighbors for each vertex
- * 2) For each edge compute the intersection of the sets and send the
- *    count to both vertices.
- * 3) Compute the sum at each vertex and divide by two since each
- *    triangle is counted twice.
+ * <ul>
+ * <li>Compute the set of neighbors for each vertex
+ * <li>For each edge compute the intersection of the sets and send the count to both vertices.
+ * <li> Compute the sum at each vertex and divide by two since each triangle is counted twice.
+ * </ul>
  *
  * Note that the input graph should have its edges in canonical direction
  * (i.e. the `sourceId` less than `destId`). Also the graph must have been partitioned