/**
* Copyright 2013-2015 Pierre Merienne
*
* 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.
*/
package com.github.pmerienne.trident.ml.nlp;
import static org.junit.Assert.assertEquals;
import org.junit.Test;
import com.github.pmerienne.trident.ml.nlp.ClassifyTextQuery;
import com.github.pmerienne.trident.ml.nlp.KLDClassifier;
import com.github.pmerienne.trident.ml.nlp.TextClassifierUpdater;
import com.github.pmerienne.trident.ml.preprocessing.TextInstanceCreator;
import com.github.pmerienne.trident.ml.testing.ReutersBatchSpout;
import storm.trident.TridentState;
import storm.trident.TridentTopology;
import storm.trident.testing.MemoryMapState;
import backtype.storm.Config;
import backtype.storm.LocalCluster;
import backtype.storm.LocalDRPC;
import backtype.storm.tuple.Fields;
public class KLDClassifierTridentIntegration {
@Test
public void testInTopology() throws InterruptedException {
// Start local cluster
LocalCluster cluster = new LocalCluster();
LocalDRPC localDRPC = new LocalDRPC();
try {
// Build topology
TridentTopology toppology = new TridentTopology();
// "Training" stream
TridentState classifierState = toppology.newStream("reutersData", new ReutersBatchSpout())
// Transform raw data to text instance
.each(new Fields("label", "text"), new TextInstanceCreator<Integer>(), new Fields("instance"))
// Update text classifier
.partitionPersist(new MemoryMapState.Factory(), new Fields("instance"), new TextClassifierUpdater<Integer>("newsClassifier", new KLDClassifier(9)));
// Classification stream
toppology.newDRPCStream("classify", localDRPC)
// Convert DRPC args to text instance
.each(new Fields("args"), new TextInstanceCreator<Integer>(false), new Fields("instance"))
// Query classifier with text instance
.stateQuery(classifierState, new Fields("instance"), new ClassifyTextQuery<Integer>("newsClassifier"), new Fields("prediction")).project(new Fields("prediction"));
cluster.submitTopology(this.getClass().getSimpleName(), new Config(), toppology.build());
Thread.sleep(4000);
// Query with DRPC
for (Integer realClass : ReutersBatchSpout.REUTEURS_EVAL_SAMPLES.keySet()) {
Integer prediction = extractPrediction(localDRPC.execute("classify", ReutersBatchSpout.REUTEURS_EVAL_SAMPLES.get(realClass)));
assertEquals(realClass, prediction);
}
} finally {
cluster.shutdown();
localDRPC.shutdown();
}
}
protected static Integer extractPrediction(String drpcResult) {
return Integer.parseInt(drpcResult.replaceAll("\\[", "").replaceAll("\\]", ""));
}
}