/*
* Hivemall: Hive scalable Machine Learning Library
*
* Copyright (C) 2013-2014
* National Institute of Advanced Industrial Science and Technology (AIST)
* Registration Number: H25PRO-1520
*
* This library is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation.
*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with this library; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*/
package hivemall.knn.lsh;
import hivemall.knn.lsh.MinHashesUDF;
import java.util.Arrays;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.junit.Test;
import org.junit.Assert;
public class MinHashUDFTest {
@Test
public void testEvaluate() throws HiveException {
MinHashesUDF minhash = new MinHashesUDF();
Assert.assertEquals(5, minhash.evaluate(Arrays.asList(1, 2, 3, 4)).size());
Assert.assertEquals(9, minhash.evaluate(Arrays.asList(1, 2, 3, 4), 9, 2).size());
Assert.assertEquals(minhash.evaluate(Arrays.asList(1, 2, 3, 4)), minhash.evaluate(Arrays.asList(1, 2, 3, 4), 5, 2));
Assert.assertEquals(minhash.evaluate(Arrays.asList(1, 2, 3, 4)), minhash.evaluate(Arrays.asList("1", "2", "3", "4"), true));
Assert.assertEquals(minhash.evaluate(Arrays.asList(1, 2, 3, 4)), minhash.evaluate(Arrays.asList("1:1.0", "2:1.0", "3:1.0", "4:1.0"), false));
}
}