1 /*
2  * Licensed to the Apache Software Foundation (ASF) under one or more
3  * contributor license agreements.  See the NOTICE file distributed with
4  * this work for additional information regarding copyright ownership.
5  * The ASF licenses this file to You under the Apache License, Version 2.0
6  * (the "License"); you may not use this file except in compliance with
7  * the License.  You may obtain a copy of the License at
8  *
9  *    http://www.apache.org/licenses/LICENSE-2.0
10  *
11  * Unless required by applicable law or agreed to in writing, software
12  * distributed under the License is distributed on an "AS IS" BASIS,
13  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14  * See the License for the specific language governing permissions and
15  * limitations under the License.
16  */
17 
18 package org.apache.spark.examples.mllib;
19 
20 // $example on$
21 import java.util.LinkedList;
22 // $example off$
23 
24 import org.apache.spark.SparkConf;
25 import org.apache.spark.SparkContext;
26 // $example on$
27 import org.apache.spark.api.java.JavaRDD;
28 import org.apache.spark.api.java.JavaSparkContext;
29 import org.apache.spark.mllib.linalg.Matrix;
30 import org.apache.spark.mllib.linalg.Vector;
31 import org.apache.spark.mllib.linalg.Vectors;
32 import org.apache.spark.mllib.linalg.distributed.RowMatrix;
33 // $example off$
34 
35 /**
36  * Example for compute principal components on a 'RowMatrix'.
37  */
38 public class JavaPCAExample {
main(String[] args)39   public static void main(String[] args) {
40     SparkConf conf = new SparkConf().setAppName("PCA Example");
41     SparkContext sc = new SparkContext(conf);
42 
43     // $example on$
44     double[][] array = {{1.12, 2.05, 3.12}, {5.56, 6.28, 8.94}, {10.2, 8.0, 20.5}};
45     LinkedList<Vector> rowsList = new LinkedList<>();
46     for (int i = 0; i < array.length; i++) {
47       Vector currentRow = Vectors.dense(array[i]);
48       rowsList.add(currentRow);
49     }
50     JavaRDD<Vector> rows = JavaSparkContext.fromSparkContext(sc).parallelize(rowsList);
51 
52     // Create a RowMatrix from JavaRDD<Vector>.
53     RowMatrix mat = new RowMatrix(rows.rdd());
54 
55     // Compute the top 3 principal components.
56     Matrix pc = mat.computePrincipalComponents(3);
57     RowMatrix projected = mat.multiply(pc);
58     // $example off$
59     Vector[] collectPartitions = (Vector[])projected.rows().collect();
60     System.out.println("Projected vector of principal component:");
61     for (Vector vector : collectPartitions) {
62       System.out.println("\t" + vector);
63     }
64   }
65 }
66