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 scala.Tuple3;
  
  import com.google.common.collect.Lists;
  
  import org.apache.spark.SparkConf;
  import org.apache.spark.api.java.JavaRDD;
  import org.apache.spark.api.java.JavaSparkContext;
  // $example on$
  import org.apache.spark.mllib.clustering.PowerIterationClustering;
  import org.apache.spark.mllib.clustering.PowerIterationClusteringModel;
  // $example off$
  
  /**
   * Java example for graph clustering using power iteration clustering (PIC).
   */
  public class JavaPowerIterationClusteringExample {
    public static void main(String[] args) {
      SparkConf sparkConf = new SparkConf().setAppName("JavaPowerIterationClusteringExample");
      JavaSparkContext sc = new JavaSparkContext(sparkConf);
  
      @SuppressWarnings("unchecked")
      // $example on$
      JavaRDD<Tuple3<Long, Long, Double>> similarities = sc.parallelize(Lists.newArrayList(
        new Tuple3<>(0L, 1L, 0.9),
        new Tuple3<>(1L, 2L, 0.9),
        new Tuple3<>(2L, 3L, 0.9),
        new Tuple3<>(3L, 4L, 0.1),
        new Tuple3<>(4L, 5L, 0.9)));
  
      PowerIterationClustering pic = new PowerIterationClustering()
        .setK(2)
        .setMaxIterations(10);
      PowerIterationClusteringModel model = pic.run(similarities);
  
      for (PowerIterationClustering.Assignment a: model.assignments().toJavaRDD().collect()) {
        System.out.println(a.id() + " -> " + a.cluster());
      }
      // $example off$
  
      sc.stop();
    }
  }
  