Java tutorial
/* * 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 com.sdw.dream.spark.examples.ml; import org.apache.spark.SparkConf; import org.apache.spark.api.java.JavaSparkContext; import org.apache.spark.sql.SQLContext; // $example on$ import java.util.Arrays; import org.apache.spark.api.java.JavaRDD; import org.apache.spark.ml.feature.PCA; import org.apache.spark.ml.feature.PCAModel; import org.apache.spark.mllib.linalg.VectorUDT; import org.apache.spark.mllib.linalg.Vectors; import org.apache.spark.sql.DataFrame; import org.apache.spark.sql.Row; import org.apache.spark.sql.RowFactory; import org.apache.spark.sql.types.Metadata; import org.apache.spark.sql.types.StructField; import org.apache.spark.sql.types.StructType; // $example off$ public class JavaPCAExample { public static void main(String[] args) { SparkConf conf = new SparkConf().setAppName("JavaPCAExample"); JavaSparkContext jsc = new JavaSparkContext(conf); SQLContext jsql = new SQLContext(jsc); // $example on$ JavaRDD<Row> data = jsc.parallelize( Arrays.asList(RowFactory.create(Vectors.sparse(5, new int[] { 1, 3 }, new double[] { 1.0, 7.0 })), RowFactory.create(Vectors.dense(2.0, 0.0, 3.0, 4.0, 5.0)), RowFactory.create(Vectors.dense(4.0, 0.0, 0.0, 6.0, 7.0)))); StructType schema = new StructType( new StructField[] { new StructField("features", new VectorUDT(), false, Metadata.empty()), }); DataFrame df = jsql.createDataFrame(data, schema); PCAModel pca = new PCA().setInputCol("features").setOutputCol("pcaFeatures").setK(3).fit(df); DataFrame result = pca.transform(df).select("pcaFeatures"); result.show(); // $example off$ jsc.stop(); } }