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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.mahout.clustering.spectral;
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat;
import org.apache.mahout.math.VectorWritable;
/**
* Given a DistributedRowMatrix, this job normalizes each row to unit
* vector length. If the input is a matrix U, and the output is a matrix
* W, the job follows:
*
* {@code v_ij = u_ij / sqrt(sum_j(u_ij * u_ij))}
*/
public final class UnitVectorizerJob {
private UnitVectorizerJob() {
}
public static void runJob(Path input, Path output)
throws IOException, InterruptedException, ClassNotFoundException {
Configuration conf = new Configuration();
Job job = new Job(conf, "UnitVectorizerJob");
job.setInputFormatClass(SequenceFileInputFormat.class);
job.setOutputKeyClass(IntWritable.class);
job.setOutputValueClass(VectorWritable.class);
job.setOutputFormatClass(SequenceFileOutputFormat.class);
job.setMapperClass(UnitVectorizerMapper.class);
job.setNumReduceTasks(0);
FileInputFormat.addInputPath(job, input);
FileOutputFormat.setOutputPath(job, output);
job.setJarByClass(UnitVectorizerJob.class);
boolean succeeded = job.waitForCompletion(true);
if (!succeeded) {
throw new IllegalStateException("Job failed!");
}
}
public static class UnitVectorizerMapper
extends Mapper {
@Override
protected void map(IntWritable row, VectorWritable vector, Context context)
throws IOException, InterruptedException {
context.write(row, new VectorWritable(vector.get().normalize(2)));
}
}
}
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