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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.math.hadoop.similarity;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
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.hadoop.util.ToolRunner;
import org.apache.mahout.common.AbstractJob;
import org.apache.mahout.common.ClassUtils;
import org.apache.mahout.common.HadoopUtil;
import org.apache.mahout.common.StringTuple;
import org.apache.mahout.common.commandline.DefaultOptionCreator;
import org.apache.mahout.common.distance.DistanceMeasure;
import org.apache.mahout.common.distance.SquaredEuclideanDistanceMeasure;
import org.apache.mahout.math.VectorWritable;
import com.google.common.base.Preconditions;
import java.io.IOException;
/**
* This class does a Map-side join between seed vectors (the map side can also be a Cluster) and a list of other vectors
* and emits the a tuple of seed id, other id, distance. It is a more generic version of KMean's mapper
*/
public class VectorDistanceSimilarityJob extends AbstractJob {
public static final String SEEDS = "seeds";
public static final String SEEDS_PATH_KEY = "seedsPath";
public static final String DISTANCE_MEASURE_KEY = "vectorDistSim.measure";
public static final String OUT_TYPE_KEY = "outType";
public static final String MAX_DISTANCE = "maxDistance";
public static void main(String[] args) throws Exception {
ToolRunner.run(new Configuration(), new VectorDistanceSimilarityJob(), args);
}
@Override
public int run(String[] args) throws Exception {
addInputOption();
addOutputOption();
addOption(DefaultOptionCreator.distanceMeasureOption().create());
addOption(SEEDS, "s", "The set of vectors to compute distances against. Must fit in memory on the mapper");
addOption(MAX_DISTANCE, "mx", "set an upper-bound on distance (double) such that any pair of vectors with a"
+ " distance greater than this value is ignored in the output. Ignored for non pairwise output!");
addOption(DefaultOptionCreator.overwriteOption().create());
addOption(OUT_TYPE_KEY, "ot", "[pw|v] -- Define the output style: pairwise, the default, (pw) or vector (v). "
+ "Pairwise is a tuple of , vector is >.",
"pw");
if (parseArguments(args) == null) {
return -1;
}
Path input = getInputPath();
Path output = getOutputPath();
Path seeds = new Path(getOption(SEEDS));
String measureClass = getOption(DefaultOptionCreator.DISTANCE_MEASURE_OPTION);
if (measureClass == null) {
measureClass = SquaredEuclideanDistanceMeasure.class.getName();
}
if (hasOption(DefaultOptionCreator.OVERWRITE_OPTION)) {
HadoopUtil.delete(getConf(), output);
}
DistanceMeasure measure = ClassUtils.instantiateAs(measureClass, DistanceMeasure.class);
String outType = getOption(OUT_TYPE_KEY, "pw");
Double maxDistance = null;
if ("pw".equals(outType)) {
String maxDistanceArg = getOption(MAX_DISTANCE);
if (maxDistanceArg != null) {
maxDistance = Double.parseDouble(maxDistanceArg);
Preconditions.checkArgument(maxDistance > 0.0d, "value for " + MAX_DISTANCE + " must be greater than zero");
}
}
run(getConf(), input, seeds, output, measure, outType, maxDistance);
return 0;
}
public static void run(Configuration conf,
Path input,
Path seeds,
Path output,
DistanceMeasure measure, String outType)
throws IOException, ClassNotFoundException, InterruptedException {
run(conf, input, seeds, output, measure, outType, null);
}
public static void run(Configuration conf,
Path input,
Path seeds,
Path output,
DistanceMeasure measure, String outType, Double maxDistance)
throws IOException, ClassNotFoundException, InterruptedException {
if (maxDistance != null) {
conf.set(MAX_DISTANCE, String.valueOf(maxDistance));
}
conf.set(DISTANCE_MEASURE_KEY, measure.getClass().getName());
conf.set(SEEDS_PATH_KEY, seeds.toString());
Job job = new Job(conf, "Vector Distance Similarity: seeds: " + seeds + " input: " + input);
job.setInputFormatClass(SequenceFileInputFormat.class);
job.setOutputFormatClass(SequenceFileOutputFormat.class);
if ("pw".equalsIgnoreCase(outType)) {
job.setMapOutputKeyClass(StringTuple.class);
job.setOutputKeyClass(StringTuple.class);
job.setMapOutputValueClass(DoubleWritable.class);
job.setOutputValueClass(DoubleWritable.class);
job.setMapperClass(VectorDistanceMapper.class);
} else if ("v".equalsIgnoreCase(outType)) {
job.setMapOutputKeyClass(Text.class);
job.setOutputKeyClass(Text.class);
job.setMapOutputValueClass(VectorWritable.class);
job.setOutputValueClass(VectorWritable.class);
job.setMapperClass(VectorDistanceInvertedMapper.class);
} else {
throw new IllegalArgumentException("Invalid outType specified: " + outType);
}
job.setNumReduceTasks(0);
FileInputFormat.addInputPath(job, input);
FileOutputFormat.setOutputPath(job, output);
job.setJarByClass(VectorDistanceSimilarityJob.class);
HadoopUtil.delete(conf, output);
if (!job.waitForCompletion(true)) {
throw new IllegalStateException("VectorDistance Similarity failed processing " + seeds);
}
}
}