Java tutorial
/** * 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.classifier.cbayes; import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.DefaultStringifier; import org.apache.hadoop.io.DoubleWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapred.FileInputFormat; import org.apache.hadoop.mapred.FileOutputFormat; import org.apache.hadoop.mapred.JobClient; import org.apache.hadoop.mapred.JobConf; import org.apache.hadoop.mapred.SequenceFileInputFormat; import org.apache.hadoop.mapred.SequenceFileOutputFormat; import org.apache.hadoop.util.GenericsUtil; import org.apache.mahout.classifier.bayes.io.SequenceFileModelReader; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import java.io.IOException; import java.util.Map; /** Create and run the Bayes Trainer. */ public class CBayesThetaNormalizerDriver { private static final Logger log = LoggerFactory.getLogger(CBayesThetaNormalizerDriver.class); private CBayesThetaNormalizerDriver() { } /** * Takes in two arguments: <ol> <li>The input {@link org.apache.hadoop.fs.Path} where the input documents live</li> * <li>The output {@link org.apache.hadoop.fs.Path} where to write the {@link org.apache.mahout.common.Model} as a * {@link org.apache.hadoop.io.SequenceFile}</li> </ol> * * @param args The args */ public static void main(String[] args) throws IOException { String input = args[0]; String output = args[1]; runJob(input, output); } /** * Run the job * * @param input the input pathname String * @param output the output pathname String */ public static void runJob(String input, String output) throws IOException { JobClient client = new JobClient(); JobConf conf = new JobConf(CBayesThetaNormalizerDriver.class); conf.setOutputKeyClass(Text.class); conf.setOutputValueClass(DoubleWritable.class); FileInputFormat.addInputPath(conf, new Path(output + "/trainer-weights/Sigma_j")); FileInputFormat.addInputPath(conf, new Path(output + "/trainer-tfIdf/trainer-tfIdf")); Path outPath = new Path(output + "/trainer-thetaNormalizer"); FileOutputFormat.setOutputPath(conf, outPath); conf.setNumMapTasks(100); //conf.setNumReduceTasks(1); conf.setMapperClass(CBayesThetaNormalizerMapper.class); conf.setInputFormat(SequenceFileInputFormat.class); conf.setCombinerClass(CBayesThetaNormalizerReducer.class); conf.setReducerClass(CBayesThetaNormalizerReducer.class); conf.setOutputFormat(SequenceFileOutputFormat.class); conf.set("io.serializations", "org.apache.hadoop.io.serializer.JavaSerialization,org.apache.hadoop.io.serializer.WritableSerialization"); // Dont ever forget this. People should keep track of how hadoop conf parameters and make or break a piece of code FileSystem dfs = FileSystem.get(outPath.toUri(), conf); if (dfs.exists(outPath)) { dfs.delete(outPath, true); } Path Sigma_kFiles = new Path(output + "/trainer-weights/Sigma_k/*"); Map<String, Double> labelWeightSum = SequenceFileModelReader.readLabelSums(dfs, Sigma_kFiles, conf); DefaultStringifier<Map<String, Double>> mapStringifier = new DefaultStringifier<Map<String, Double>>(conf, GenericsUtil.getClass(labelWeightSum)); String labelWeightSumString = mapStringifier.toString(labelWeightSum); log.info("Sigma_k for Each Label"); Map<String, Double> c = mapStringifier.fromString(labelWeightSumString); log.info("{}", c); conf.set("cnaivebayes.sigma_k", labelWeightSumString); Path sigma_kSigma_jFile = new Path(output + "/trainer-weights/Sigma_kSigma_j/*"); double sigma_jSigma_k = SequenceFileModelReader.readSigma_jSigma_k(dfs, sigma_kSigma_jFile, conf); DefaultStringifier<Double> stringifier = new DefaultStringifier<Double>(conf, Double.class); String sigma_jSigma_kString = stringifier.toString(sigma_jSigma_k); log.info("Sigma_kSigma_j for each Label and for each Features"); double retSigma_jSigma_k = stringifier.fromString(sigma_jSigma_kString); log.info("{}", retSigma_jSigma_k); conf.set("cnaivebayes.sigma_jSigma_k", sigma_jSigma_kString); Path vocabCountFile = new Path(output + "/trainer-tfIdf/trainer-vocabCount/*"); double vocabCount = SequenceFileModelReader.readVocabCount(dfs, vocabCountFile, conf); String vocabCountString = stringifier.toString(vocabCount); log.info("Vocabulary Count"); conf.set("cnaivebayes.vocabCount", vocabCountString); double retvocabCount = stringifier.fromString(vocabCountString); log.info("{}", retvocabCount); client.setConf(conf); JobClient.runJob(conf); } }