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SnappyData distributed data store and execution engine
/*
* 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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* See the License for the specific language governing permissions and
* limitations under the License.
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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 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 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();
}
}
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