/** * 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 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 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(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 <seed, other, distance>, vector is <other, <Vector of size the number of seeds>>.", "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); if (getConf() == null) { setConf(new Configuration()); } String outType = getOption(OUT_TYPE_KEY); if (outType == null) { outType = "pw"; } run(getConf(), input, seeds, output, measure, outType); return 0; } public static void run(Configuration conf, Path input, Path seeds, Path output, DistanceMeasure measure, String outType) throws IOException, ClassNotFoundException, InterruptedException { 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); } } }