/**
* 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.mahout.utils;
import java.util.List;
import com.google.common.collect.Lists;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.mahout.common.DummyRecordWriter;
import org.apache.mahout.common.MahoutTestCase;
import org.apache.mahout.math.DenseVector;
import org.apache.mahout.math.Vector;
import org.apache.mahout.math.VectorWritable;
import org.junit.Test;
/**
* Code stolen from TestAffinityMatrixJob. Like TAMJ, it tests the Mappers/Reducers but not test the job
*/
public class TestConcatenateVectorsJob extends MahoutTestCase {
private static final double [][] DATA_A = {
{0,1,2,3,4},
{},
{0,1,2,3,4}
};
private static final double [][] DATA_B = {
{},
{5,6,7},
{5,6,7}
};
@Test
public void testConcatenateVectorsReducer() throws Exception {
Configuration configuration = new Configuration();
configuration.set(ConcatenateVectorsJob.MATRIXA_DIMS, "5");
configuration.set(ConcatenateVectorsJob.MATRIXB_DIMS, "3");
// Yes, all of this generic rigmarole is needed, and woe betide he who changes it
ConcatenateVectorsReducer reducer = new ConcatenateVectorsReducer();
DummyRecordWriter<IntWritable, VectorWritable> recordWriter = new DummyRecordWriter<IntWritable, VectorWritable>();
Reducer<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context reduceContext =
DummyRecordWriter.build(reducer, configuration, recordWriter, IntWritable.class, VectorWritable.class);
reducer.setup(reduceContext);
for(int i = 0; i < 3; i++) {
double[] values = DATA_A[i];
List<VectorWritable> vwList = Lists.newArrayList();
if (values.length > 0) {
Vector v = new DenseVector(values);
VectorWritable vw = new VectorWritable();
vw.set(v);
vwList.add(vw);
}
values = DATA_B[i];
if (values.length > 0) {
Vector v = new DenseVector(values);
VectorWritable vw = new VectorWritable();
vw.set(v);
vwList.add(vw);
}
IntWritable row = new IntWritable(i);
reducer.reduce(row, vwList, reduceContext);
}
for (IntWritable row : recordWriter.getKeys()) {
List<VectorWritable> list = recordWriter.getValue(row);
Vector v = list.get(0).get();
assertEquals(8, v.size());
for (Vector.Element element : v.nonZeroes()) {
assertEquals(element.index(), v.get(element.index()), 0.001);
}
}
}
}