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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,
* 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 org.apache.spark.ml.feature;
import java.util.Arrays;
import org.junit.After;
import org.junit.Assert;
import org.junit.Before;
import org.junit.Test;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.mllib.linalg.Vector;
import org.apache.spark.mllib.linalg.VectorUDT;
import org.apache.spark.mllib.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.SQLContext;
import org.apache.spark.sql.types.*;
import static org.apache.spark.sql.types.DataTypes.*;
public class JavaVectorAssemblerSuite {
private transient JavaSparkContext jsc;
private transient SQLContext sqlContext;
@Before
public void setUp() {
jsc = new JavaSparkContext("local", "JavaVectorAssemblerSuite");
sqlContext = new SQLContext(jsc);
}
@After
public void tearDown() {
jsc.stop();
jsc = null;
}
@Test
public void testVectorAssembler() {
StructType schema = createStructType(new StructField[] {
createStructField("id", IntegerType, false),
createStructField("x", DoubleType, false),
createStructField("y", new VectorUDT(), false),
createStructField("name", StringType, false),
createStructField("z", new VectorUDT(), false),
createStructField("n", LongType, false)
});
Row row = RowFactory.create(
0, 0.0, Vectors.dense(1.0, 2.0), "a",
Vectors.sparse(2, new int[] {1}, new double[] {3.0}), 10L);
Dataset<Row> dataset = sqlContext.createDataFrame(Arrays.asList(row), schema);
VectorAssembler assembler = new VectorAssembler()
.setInputCols(new String[] {"x", "y", "z", "n"})
.setOutputCol("features");
Dataset<Row> output = assembler.transform(dataset);
Assert.assertEquals(
Vectors.sparse(6, new int[] {1, 2, 4, 5}, new double[] {1.0, 2.0, 3.0, 10.0}),
output.select("features").first().<Vector>getAs(0));
}
}
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