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.examples.mllib;
  
  
  import org.apache.spark.api.java.function.VoidFunction;
  import org.apache.spark.api.java.JavaRDD;
  import org.apache.spark.api.java.function.Function;
  // $example on$
  import org.apache.spark.mllib.stat.test.BinarySample;
  import org.apache.spark.mllib.stat.test.StreamingTest;
  import org.apache.spark.mllib.stat.test.StreamingTestResult;
  // $example off$
  import org.apache.spark.SparkConf;
  import org.apache.spark.streaming.Duration;
  import org.apache.spark.streaming.Seconds;
  import org.apache.spark.streaming.api.java.JavaDStream;
  import org.apache.spark.streaming.api.java.JavaStreamingContext;
  import org.apache.spark.util.Utils;
  
  
  /**
   * Perform streaming testing using Welch's 2-sample t-test on a stream of data, where the data
   * stream arrives as text files in a directory. Stops when the two groups are statistically
   * significant (p-value < 0.05) or after a user-specified timeout in number of batches is exceeded.
   *
   * The rows of the text files must be in the form `Boolean, Double`. For example:
   *   false, -3.92
   *   true, 99.32
   *
   * Usage:
   *   JavaStreamingTestExample <dataDir> <batchDuration> <numBatchesTimeout>
   *
   * To run on your local machine using the directory `dataDir` with 5 seconds between each batch and
   * a timeout after 100 insignificant batches, call:
   *    $ bin/run-example mllib.JavaStreamingTestExample dataDir 5 100
   *
   * As you add text files to `dataDir` the significance test wil continually update every
   * `batchDuration` seconds until the test becomes significant (p-value < 0.05) or the number of
   * batches processed exceeds `numBatchesTimeout`.
   */
  public class JavaStreamingTestExample {
  
    private static int timeoutCounter = 0;
  
    public static void main(String[] args) throws Exception {
      if (args.length != 3) {
        System.err.println("Usage: JavaStreamingTestExample " +
          "<dataDir> <batchDuration> <numBatchesTimeout>");
          System.exit(1);
      }
  
      String dataDir = args[0];
      Duration batchDuration = Seconds.apply(Long.parseLong(args[1]));
      int numBatchesTimeout = Integer.parseInt(args[2]);
  
      SparkConf conf = new SparkConf().setMaster("local").setAppName("StreamingTestExample");
      JavaStreamingContext ssc = new JavaStreamingContext(conf, batchDuration);
  
      ssc.checkpoint(Utils.createTempDir(System.getProperty("java.io.tmpdir"), "spark").toString());
  
      // $example on$
      JavaDStream<BinarySample> data = ssc.textFileStream(dataDir).map(
        new Function<String, BinarySample>() {
          @Override
          public BinarySample call(String line) {
            String[] ts = line.split(",");
            boolean label = Boolean.parseBoolean(ts[0]);
            double value = Double.parseDouble(ts[1]);
            return new BinarySample(label, value);
          }
        });
  
      StreamingTest streamingTest = new StreamingTest()
        .setPeacePeriod(0)
        .setWindowSize(0)
        .setTestMethod("welch");
  
      JavaDStream<StreamingTestResult> out = streamingTest.registerStream(data);
      out.print();
      // $example off$
  
      // Stop processing if test becomes significant or we time out
      timeoutCounter = numBatchesTimeout;
  
      out.foreachRDD(new VoidFunction<JavaRDD<StreamingTestResult>>() {
        @Override
        public void call(JavaRDD<StreamingTestResult> rdd) {
          timeoutCounter -= 1;
  
          boolean anySignificant = !rdd.filter(new Function<StreamingTestResult, Boolean>() {
            @Override
            public Boolean call(StreamingTestResult v) {
              return v.pValue() < 0.05;
            }
          }).isEmpty();
  
          if (timeoutCounter <= 0 || anySignificant) {
            rdd.context().stop();
          }
        }
      });
  
      ssc.start();
      ssc.awaitTermination();
    }
  }
  