org.apache.spark.examples.ml.JavaVectorSlicerExample Maven / Gradle / Ivy
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* http://www.apache.org/licenses/LICENSE-2.0
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package org.apache.spark.examples.ml;
import org.apache.spark.sql.SparkSession;
// $example on$
import java.util.Arrays;
import java.util.List;
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.ml.linalg.Vectors;
import org.apache.spark.sql.Dataset;
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) {
SparkSession spark = SparkSession
.builder()
.appName("JavaVectorSlicerExample")
.getOrCreate();
// $example on$
Attribute[] attrs = {
NumericAttribute.defaultAttr().withName("f1"),
NumericAttribute.defaultAttr().withName("f2"),
NumericAttribute.defaultAttr().withName("f3")
};
AttributeGroup group = new AttributeGroup("userFeatures", attrs);
List data = Arrays.asList(
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))
);
Dataset dataset =
spark.createDataFrame(data, (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"})
Dataset output = vectorSlicer.transform(dataset);
output.show(false);
// $example off$
spark.stop();
}
}
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