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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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