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 com.google.common.collect.Lists; import org.apache.spark.api.java.JavaRDD; import org.apache.spark.ml.attribute.Attribute; import org.apache.spark.ml.attribute.AttributeGroup; import org.apache.spark.ml.attribute.NumericAttribute; import org.apache.spark.ml.feature.VectorSlicer; 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.*; // $example off$ public class JavaVectorSlicerExample { public static void main(String[] args) { SparkConf conf = new SparkConf().setAppName("JavaVectorSlicerExample"); JavaSparkContext jsc = new JavaSparkContext(conf); SQLContext jsql = new SQLContext(jsc); // $example on$ Attribute[] attrs = new Attribute[] { NumericAttribute.defaultAttr().withName("f1"), NumericAttribute.defaultAttr().withName("f2"), NumericAttribute.defaultAttr().withName("f3") }; AttributeGroup group = new AttributeGroup("userFeatures", attrs); JavaRDD<Row> jrdd = jsc.parallelize(Lists.newArrayList( RowFactory.create(Vectors.sparse(3, new int[] { 0, 1 }, new double[] { -2.0, 2.3 })), RowFactory.create(Vectors.dense(-2.0, 2.3, 0.0)))); DataFrame dataset = jsql.createDataFrame(jrdd, (new StructType()).add(group.toStructField())); VectorSlicer vectorSlicer = new VectorSlicer().setInputCol("userFeatures").setOutputCol("features"); vectorSlicer.setIndices(new int[] { 1 }).setNames(new String[] { "f3" }); // or slicer.setIndices(new int[]{1, 2}), or slicer.setNames(new String[]{"f2", "f3"}) DataFrame output = vectorSlicer.transform(dataset); System.out.println(output.select("userFeatures", "features").first()); // $example off$ jsc.stop(); } }