Different num supersteps

[Martin Neumann]

Hej,

I have modified the connected component example to fit my input data. I
expect it to be deterministic.

But when I run it multiple times it takes a different number of Super
steps. This only happens on the complete dataset and not on my small test
dataset.
 (So I cannot check the output for correctness in a simple way)

Has anyone an Idea how this could happen?

cheers Martin




In case its useful here the computation class:

@Override
    public void compute(Vertex<Text, Text, NullWritable> vertex,
            Iterable<Text> inmessage) throws IOException {
        boolean changed = false;

// first superstep && setup
        if (getSuperstep() == 0) {
            //initialize value
            vertex.setValue(vertex.getId());
            //cheating by checking the neighbors ID's (cuts down 1
iteration)
            for (Edge<Text, NullWritable> e : vertex.getEdges()) {
                Text candidate = e.getTargetVertexId();
                if (candidate.compareTo(vertex.getValue()) < 0) {
                    changed = true;
                    vertex.setValue(candidate);
                }
            }
        }

        // other superstep
        else {
            // read all messages and compare with own state
            for (Text message : inmessage) {
                if (message.compareTo(vertex.getValue()) < 0) {
                    changed = true;
                    vertex.setValue(message);
                }
            }
        }

        // if state has changed send a message to all neighbors
        if (changed && getSuperstep() < limiter) {
            sendMessageToAllEdges(vertex, vertex.getValue());
        }

        vertex.voteToHalt();
    }