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SnappyData distributed data store and execution engine
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* 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,
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package org.apache.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.VectorAssembler;
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.*;
import static org.apache.spark.sql.types.DataTypes.*;
// $example off$
public class JavaVectorAssemblerExample {
public static void main(String[] args) {
SparkConf conf = new SparkConf().setAppName("JavaVectorAssemblerExample");
JavaSparkContext jsc = new JavaSparkContext(conf);
SQLContext sqlContext = new SQLContext(jsc);
// $example on$
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);
JavaRDD rdd = jsc.parallelize(Arrays.asList(row));
DataFrame dataset = sqlContext.createDataFrame(rdd, schema);
VectorAssembler assembler = new VectorAssembler()
.setInputCols(new String[]{"hour", "mobile", "userFeatures"})
.setOutputCol("features");
DataFrame output = assembler.transform(dataset);
System.out.println(output.select("features", "clicked").first());
// $example off$
jsc.stop();
}
}
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