examples/ml/JavaDCTExample.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.examples.ml;
0019
0020 import org.apache.spark.sql.Dataset;
0021 import org.apache.spark.sql.SparkSession;
0022
0023 // $example on$
0024 import java.util.Arrays;
0025 import java.util.List;
0026
0027 import org.apache.spark.ml.feature.DCT;
0028 import org.apache.spark.ml.linalg.VectorUDT;
0029 import org.apache.spark.ml.linalg.Vectors;
0030 import org.apache.spark.sql.Row;
0031 import org.apache.spark.sql.RowFactory;
0032 import org.apache.spark.sql.types.Metadata;
0033 import org.apache.spark.sql.types.StructField;
0034 import org.apache.spark.sql.types.StructType;
0035 // $example off$
0036
0037 public class JavaDCTExample {
0038   public static void main(String[] args) {
0039     SparkSession spark = SparkSession
0040       .builder()
0041       .appName("JavaDCTExample")
0042       .getOrCreate();
0043
0044     // $example on$
0045     List<Row> data = Arrays.asList(
0046       RowFactory.create(Vectors.dense(0.0, 1.0, -2.0, 3.0)),
0047       RowFactory.create(Vectors.dense(-1.0, 2.0, 4.0, -7.0)),
0048       RowFactory.create(Vectors.dense(14.0, -2.0, -5.0, 1.0))
0049     );
0050     StructType schema = new StructType(new StructField[]{
0051       new StructField("features", new VectorUDT(), false, Metadata.empty()),
0052     });
0053     Dataset<Row> df = spark.createDataFrame(data, schema);
0054
0055     DCT dct = new DCT()
0056       .setInputCol("features")
0057       .setOutputCol("featuresDCT")
0058       .setInverse(false);
0059
0060     Dataset<Row> dctDf = dct.transform(df);
0061
0062     dctDf.select("featuresDCT").show(false);
0063     // $example off$
0064
0065     spark.stop();
0066   }
0067 }
0068