mllib/clustering/JavaStreamingKMeansSuite.java

0001 /*
0002  * Licensed to the Apache Software Foundation (ASF) under one or more
0003  * contributor license agreements.  See the NOTICE file distributed with
0004  * this work for additional information regarding copyright ownership.
0005  * The ASF licenses this file to You under the Apache License, Version 2.0
0006  * (the "License"); you may not use this file except in compliance with
0007  * the License.  You may obtain a copy of the License at
0008  *
0009  *    http://www.apache.org/licenses/LICENSE-2.0
0010  *
0011  * Unless required by applicable law or agreed to in writing, software
0012  * distributed under the License is distributed on an "AS IS" BASIS,
0013  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
0014  * See the License for the specific language governing permissions and
0015  * limitations under the License.
0016  */
0017
0018 package org.apache.spark.mllib.clustering;
0019
0020 import java.util.Arrays;
0021 import java.util.List;
0022
0023 import scala.Tuple2;
0024
0025 import org.junit.After;
0026 import org.junit.Before;
0027 import org.junit.Test;
0028
0029 import org.apache.spark.SparkConf;
0030 import org.apache.spark.mllib.linalg.Vector;
0031 import org.apache.spark.mllib.linalg.Vectors;
0032 import org.apache.spark.streaming.Duration;
0033 import org.apache.spark.streaming.api.java.JavaDStream;
0034 import org.apache.spark.streaming.api.java.JavaPairDStream;
0035 import org.apache.spark.streaming.api.java.JavaStreamingContext;
0036 import static org.apache.spark.streaming.JavaTestUtils.*;
0037
0038 public class JavaStreamingKMeansSuite {
0039
0040   protected transient JavaStreamingContext ssc;
0041
0042   @Before
0043   public void setUp() {
0044     SparkConf conf = new SparkConf()
0045       .setMaster("local[2]")
0046       .setAppName("test")
0047       .set("spark.streaming.clock", "org.apache.spark.util.ManualClock");
0048     ssc = new JavaStreamingContext(conf, new Duration(1000));
0049     ssc.checkpoint("checkpoint");
0050   }
0051
0052   @After
0053   public void tearDown() {
0054     ssc.stop();
0055     ssc = null;
0056   }
0057
0058   @Test
0059   @SuppressWarnings("unchecked")
0060   public void javaAPI() {
0061     List<Vector> trainingBatch = Arrays.asList(
0062       Vectors.dense(1.0),
0063       Vectors.dense(0.0));
0064     JavaDStream<Vector> training =
0065       attachTestInputStream(ssc, Arrays.asList(trainingBatch, trainingBatch), 2);
0066     List<Tuple2<Integer, Vector>> testBatch = Arrays.asList(
0067       new Tuple2<>(10, Vectors.dense(1.0)),
0068       new Tuple2<>(11, Vectors.dense(0.0)));
0069     JavaPairDStream<Integer, Vector> test = JavaPairDStream.fromJavaDStream(
0070       attachTestInputStream(ssc, Arrays.asList(testBatch, testBatch), 2));
0071     StreamingKMeans skmeans = new StreamingKMeans()
0072       .setK(1)
0073       .setDecayFactor(1.0)
0074       .setInitialCenters(new Vector[]{Vectors.dense(1.0)}, new double[]{0.0});
0075     skmeans.trainOn(training);
0076     JavaPairDStream<Integer, Integer> prediction = skmeans.predictOnValues(test);
0077     attachTestOutputStream(prediction.count());
0078     runStreams(ssc, 2, 2);
0079   }
0080 }