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| -rw-r--r-- | docs/graphx-programming-guide.md | 5 |
1 files changed, 2 insertions, 3 deletions
diff --git a/docs/graphx-programming-guide.md b/docs/graphx-programming-guide.md index c82c3d7358..c6505d21f1 100644 --- a/docs/graphx-programming-guide.md +++ b/docs/graphx-programming-guide.md @@ -543,7 +543,6 @@ val maxOutDegree: (VertexID, Int) = graph.outDegrees.reduce(max) val maxDegrees: (VertexID, Int) = graph.degrees.reduce(max) {% endhighlight %} - ### Collecting Neighbors In some cases it may be easier to express computation by collecting neighboring vertices and their @@ -562,8 +561,8 @@ def collectNeighbors(edgeDirection: EdgeDirection): VertexRDD[ Array[(VertexID, # Pregel API <a name="pregel"></a> -Graphs are inherently recursive data-structures as properties of a vertices depend on properties of -their neighbors which intern depend on properties of the neighbors of their neighbors. As a +Graphs are inherently recursive data-structures as properties of vertices depend on properties of +their neighbors which intern depend on properties of *their* neighbors. As a consequence many important graph algorithms iteratively recompute the properties of each vertex until a fixed-point condition is reached. A range of graph-parallel abstractions have been proposed to express these iterative algorithms. GraphX exposes a Pregel operator which is a fusion of |