How to use

VertexMetrics

in

org.apache.flink.graph.library.metric.directed

@Override
public GlobalClusteringCoefficient<K, VV, EV> run(Graph<K, VV, EV> input)
    throws Exception {
  super.run(input);
  triangleCount = new Count<>();
  DataSet<TriangleListing.Result<K>> triangles = input
    .run(new TriangleListing<K, VV, EV>()
      .setSortTriangleVertices(false)
      .setParallelism(parallelism));
  triangleCount.run(triangles);
  vertexMetrics = new VertexMetrics<K, VV, EV>()
    .setParallelism(parallelism);
  input.run(vertexMetrics);
  return this;
}

@Override
public Result getResult() {
  // each triangle must be counted from each of the three vertices
  // as each triplet is counted in this manner
  long numberOfTriangles = 3 * triangleCount.getResult();
  return new Result(vertexMetrics.getResult().getNumberOfTriplets(), numberOfTriangles);
}

@Override
public DataSet plan(Graph<K, VV, EV> graph) throws Exception {
  switch (order.getValue()) {
    case DIRECTED:
      vertexMetrics = graph
        .run(new org.apache.flink.graph.library.metric.directed.VertexMetrics<K, VV, EV>()
          .setParallelism(parallelism.getValue().intValue()));
      edgeMetrics = graph
        .run(new org.apache.flink.graph.library.metric.directed.EdgeMetrics<K, VV, EV>()
          .setParallelism(parallelism.getValue().intValue()));
      break;
    case UNDIRECTED:
      vertexMetrics = graph
        .run(new org.apache.flink.graph.library.metric.undirected.VertexMetrics<K, VV, EV>()
          .setParallelism(parallelism.getValue().intValue()));
      edgeMetrics = graph
        .run(new org.apache.flink.graph.library.metric.undirected.EdgeMetrics<K, VV, EV>()
          .setParallelism(parallelism.getValue().intValue()));
      break;
  }
  return null;
}

@Override
public GlobalClusteringCoefficient<K, VV, EV> run(Graph<K, VV, EV> input)
    throws Exception {
  super.run(input);
  triangleCount = new Count<>();
  DataSet<TriangleListing.Result<K>> triangles = input
    .run(new TriangleListing<K, VV, EV>()
      .setSortTriangleVertices(false)
      .setParallelism(parallelism));
  triangleCount.run(triangles);
  vertexMetrics = new VertexMetrics<K, VV, EV>()
    .setParallelism(parallelism);
  input.run(vertexMetrics);
  return this;
}

@Override
public GlobalClusteringCoefficient<K, VV, EV> run(Graph<K, VV, EV> input)
    throws Exception {
  super.run(input);
  triangleCount = new Count<>();
  DataSet<TriangleListing.Result<K>> triangles = input
    .run(new TriangleListing<K, VV, EV>()
      .setSortTriangleVertices(false)
      .setLittleParallelism(littleParallelism));
  triangleCount.run(triangles);
  vertexMetrics = new VertexMetrics<K, VV, EV>()
    .setParallelism(littleParallelism);
  input.run(vertexMetrics);
  return this;
}

@Override
public GlobalClusteringCoefficient<K, VV, EV> run(Graph<K, VV, EV> input)
    throws Exception {
  super.run(input);
  triangleCount = new Count<>();
  DataSet<TriangleListing.Result<K>> triangles = input
    .run(new TriangleListing<K, VV, EV>()
      .setSortTriangleVertices(false)
      .setParallelism(parallelism));
  triangleCount.run(triangles);
  vertexMetrics = new VertexMetrics<K, VV, EV>()
    .setParallelism(parallelism);
  input.run(vertexMetrics);
  return this;
}