content: /*
   * Licensed to the Apache Software Foundation (ASF) under one or more
   * contributor license agreements.  See the NOTICE file distributed with
   * this work for additional information regarding copyright ownership.
   * The ASF licenses this file to You 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 org.apache.spark.mllib.regression;
  
  import java.util.Arrays;
  import java.util.List;
  
  import scala.Tuple2;
  
  import org.junit.After;
  import org.junit.Before;
  import org.junit.Test;
  
  import org.apache.spark.SparkConf;
  import org.apache.spark.mllib.linalg.Vector;
  import org.apache.spark.mllib.linalg.Vectors;
  import org.apache.spark.streaming.Duration;
  import org.apache.spark.streaming.api.java.JavaDStream;
  import org.apache.spark.streaming.api.java.JavaPairDStream;
  import org.apache.spark.streaming.api.java.JavaStreamingContext;
  import static org.apache.spark.streaming.JavaTestUtils.*;
  
  public class JavaStreamingLinearRegressionSuite {
  
    protected transient JavaStreamingContext ssc;
  
    @Before
    public void setUp() {
      SparkConf conf = new SparkConf()
        .setMaster("local[2]")
        .setAppName("test")
        .set("spark.streaming.clock", "org.apache.spark.util.ManualClock");
      ssc = new JavaStreamingContext(conf, new Duration(1000));
      ssc.checkpoint("checkpoint");
    }
  
    @After
    public void tearDown() {
      ssc.stop();
      ssc = null;
    }
  
    @Test
    @SuppressWarnings("unchecked")
    public void javaAPI() {
      List<LabeledPoint> trainingBatch = Arrays.asList(
        new LabeledPoint(1.0, Vectors.dense(1.0)),
        new LabeledPoint(0.0, Vectors.dense(0.0)));
      JavaDStream<LabeledPoint> training =
        attachTestInputStream(ssc, Arrays.asList(trainingBatch, trainingBatch), 2);
      List<Tuple2<Integer, Vector>> testBatch = Arrays.asList(
        new Tuple2<>(10, Vectors.dense(1.0)),
        new Tuple2<>(11, Vectors.dense(0.0)));
      JavaPairDStream<Integer, Vector> test = JavaPairDStream.fromJavaDStream(
        attachTestInputStream(ssc, Arrays.asList(testBatch, testBatch), 2));
      StreamingLinearRegressionWithSGD slr = new StreamingLinearRegressionWithSGD()
        .setNumIterations(2)
        .setInitialWeights(Vectors.dense(0.0));
      slr.trainOn(training);
      JavaPairDStream<Integer, Double> prediction = slr.predictOnValues(test);
      attachTestOutputStream(prediction.count());
      runStreams(ssc, 2, 2);
    }
  }
  