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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.Binarizer;
import org.apache.spark.sql.DataFrame;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.RowFactory;
import org.apache.spark.sql.types.DataTypes;
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 JavaBinarizerExample {
public static void main(String[] args) {
SparkConf conf = new SparkConf().setAppName("JavaBinarizerExample");
JavaSparkContext jsc = new JavaSparkContext(conf);
SQLContext jsql = new SQLContext(jsc);
// $example on$
JavaRDD jrdd = jsc.parallelize(Arrays.asList(
RowFactory.create(0, 0.1),
RowFactory.create(1, 0.8),
RowFactory.create(2, 0.2)
));
StructType schema = new StructType(new StructField[]{
new StructField("label", DataTypes.DoubleType, false, Metadata.empty()),
new StructField("feature", DataTypes.DoubleType, false, Metadata.empty())
});
DataFrame continuousDataFrame = jsql.createDataFrame(jrdd, schema);
Binarizer binarizer = new Binarizer()
.setInputCol("feature")
.setOutputCol("binarized_feature")
.setThreshold(0.5);
DataFrame binarizedDataFrame = binarizer.transform(continuousDataFrame);
DataFrame binarizedFeatures = binarizedDataFrame.select("binarized_feature");
for (Row r : binarizedFeatures.collect()) {
Double binarized_value = r.getDouble(0);
System.out.println(binarized_value);
}
// $example off$
jsc.stop();
}
}
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