blob: 8f3537a5e057027ca08759e64a47277995da5a88 [file] [log] [blame]
package org.apache.samoa.learners.clusterers.simple;
/*
* #%L
* SAMOA
* %%
* Copyright (C) 2014 - 2015 Apache Software Foundation
* %%
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* #L%
*/
/**
* License
*/
import com.google.common.collect.ImmutableSet;
import java.util.Set;
import org.apache.samoa.core.Processor;
import org.apache.samoa.instances.Instances;
import org.apache.samoa.learners.Learner;
import org.apache.samoa.learners.clusterers.*;
import org.apache.samoa.topology.ProcessingItem;
import org.apache.samoa.topology.Stream;
import org.apache.samoa.topology.TopologyBuilder;
import com.github.javacliparser.ClassOption;
import com.github.javacliparser.Configurable;
import com.github.javacliparser.IntOption;
/**
*
* Learner that contain a single learner.
*
*/
public final class DistributedClusterer implements Learner, Configurable {
private static final long serialVersionUID = 684111382631697031L;
private Stream resultStream;
private Instances dataset;
public ClassOption learnerOption = new ClassOption("learner", 'l', "Clusterer to use.", LocalClustererAdapter.class,
ClustreamClustererAdapter.class.getName());
public IntOption paralellismOption = new IntOption("paralellismOption", 'P',
"The paralellism level for concurrent processes", 2, 1, Integer.MAX_VALUE);
private TopologyBuilder builder;
// private ClusteringDistributorProcessor distributorP;
private LocalClustererProcessor learnerP;
// private Stream distributorToLocalStream;
private Stream localToGlobalStream;
// private int parallelism;
@Override
public void init(TopologyBuilder builder, Instances dataset, int parallelism) {
this.builder = builder;
this.dataset = dataset;
// this.parallelism = parallelism;
this.setLayout();
}
protected void setLayout() {
// Distributor
// distributorP = new ClusteringDistributorProcessor();
// this.builder.addProcessor(distributorP, parallelism);
// distributorToLocalStream = this.builder.createStream(distributorP);
// distributorP.setOutputStream(distributorToLocalStream);
// distributorToGlobalStream = this.builder.createStream(distributorP);
// Local Clustering
learnerP = new LocalClustererProcessor();
LocalClustererAdapter learner = (LocalClustererAdapter) this.learnerOption.getValue();
learner.setDataset(this.dataset);
learnerP.setLearner(learner);
builder.addProcessor(learnerP, this.paralellismOption.getValue());
localToGlobalStream = this.builder.createStream(learnerP);
learnerP.setOutputStream(localToGlobalStream);
// Global Clustering
LocalClustererProcessor globalClusteringCombinerP = new LocalClustererProcessor();
LocalClustererAdapter globalLearner = (LocalClustererAdapter) this.learnerOption.getValue();
globalLearner.setDataset(this.dataset);
globalClusteringCombinerP.setLearner(learner);
builder.addProcessor(globalClusteringCombinerP, 1);
builder.connectInputAllStream(localToGlobalStream, globalClusteringCombinerP);
// Output Stream
resultStream = this.builder.createStream(globalClusteringCombinerP);
globalClusteringCombinerP.setOutputStream(resultStream);
}
@Override
public Processor getInputProcessor() {
// return distributorP;
return learnerP;
}
@Override
public Set<Stream> getResultStreams() {
Set<Stream> streams = ImmutableSet.of(this.resultStream);
return streams;
}
}