/* * 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.ml; import org.apache.spark.sql.SparkSession; // $example on$ import java.util.Arrays; import org.apache.spark.ml.feature.VectorAssembler; import org.apache.spark.ml.linalg.VectorUDT; import org.apache.spark.ml.linalg.Vectors; import org.apache.spark.sql.Dataset; import org.apache.spark.sql.Row; import org.apache.spark.sql.RowFactory; import org.apache.spark.sql.types.*; import static org.apache.spark.sql.types.DataTypes.*; // $example off$ public class JavaVectorAssemblerExample { public static void main(String[] args) { SparkSession spark = SparkSession .builder() .appName("JavaVectorAssemblerExample") .getOrCreate(); // $example on$ StructType schema = createStructType(new StructField[]{ createStructField("id", IntegerType, false), createStructField("hour", IntegerType, false), createStructField("mobile", DoubleType, false), createStructField("userFeatures", new VectorUDT(), false), createStructField("clicked", DoubleType, false) }); Row row = RowFactory.create(0, 18, 1.0, Vectors.dense(0.0, 10.0, 0.5), 1.0); Dataset<Row> dataset = spark.createDataFrame(Arrays.asList(row), schema); VectorAssembler assembler = new VectorAssembler() .setInputCols(new String[]{"hour", "mobile", "userFeatures"}) .setOutputCol("features"); Dataset<Row> output = assembler.transform(dataset); System.out.println("Assembled columns 'hour', 'mobile', 'userFeatures' to vector column " + "'features'"); output.select("features", "clicked").show(false); // $example off$ spark.stop(); } }