Java tutorial
/* * Cloud9: A MapReduce Library for Hadoop * * Licensed 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 mapreduce; import java.io.IOException; import java.util.Iterator; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.conf.Configured; import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.IntWritable; import org.apache.hadoop.io.LongWritable; 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.MapReduceBase; import org.apache.hadoop.mapred.Mapper; import org.apache.hadoop.mapred.OutputCollector; import org.apache.hadoop.mapred.Reducer; import org.apache.hadoop.mapred.Reporter; import org.apache.hadoop.mapred.Partitioner; import org.apache.hadoop.util.Tool; import org.apache.hadoop.util.ToolRunner; import org.apache.log4j.Logger; /** * <p> * Simple word count demo. This Hadoop Tool counts words in flat text file, and * takes the following command-line arguments: * </p> * * <ul> * <li>[input-path] input path</li> * <li>[output-path] output path</li> * <li>[num-mappers] number of mappers</li> * <li>[num-reducers] number of reducers</li> * </ul> * * @author Jimmy Lin * @author Marc Sloan */ public class BigramCount extends Configured implements Tool { private static final Logger sLogger = Logger.getLogger(BigramCount.class); /** * Mapper: emits (token, 1) for every pair occurrence * */ private static class MyMapper extends MapReduceBase implements Mapper<LongWritable, Text, WordPair, IntWritable> { /** * Store an IntWritable with a value of 1, which will be mapped * to each word found in the test */ private final static IntWritable one = new IntWritable(1); /** * reuse objects to save overhead of object creation */ private Text word = new Text(); /** * Mapping function. This takes the text input, converts it into a String which is split into * words, then each of the words is mapped to the OutputCollector with a count of * one. * * @param key Input key, not used in this example * @param value A line of input Text taken from the data * @param output Map from each word (Text) to its count (IntWritable) */ /*Whitespace characters*/ private String pattern = ","; /*New instance of WordPair to hold a two word sequence */ private WordPair twoWordSeq = new WordPair(); private WordPair indicator = new WordPair(); public void map(LongWritable key, Text value, OutputCollector<WordPair, IntWritable> output, Reporter reporter) throws IOException { /*Get Tokens*/ String[] tokens = value.toString().split(pattern); indicator.setWord("**"); indicator.setNeighbor(""); output.collect(indicator, one); for (int i = 0; i < tokens.length; i++) { /*Set Left Word*/ twoWordSeq.setWord(tokens[i]); /* This is to make sure our String array of the tokens does not fall out of bounds*/ int end = i + 1; if (!(end == tokens.length)) { /* Set right word */ twoWordSeq.setNeighbor(tokens[end]); if ((twoWordSeq.getWord().toString().isEmpty() || twoWordSeq.getNeighbor().toString().isEmpty())) { continue; } /*emit the two word seq and int 1 */ output.collect(twoWordSeq, new IntWritable(1)); } } } } /** * Reducer: sums up all the counts * */ private static class MyReducer extends MapReduceBase implements Reducer<WordPair, IntWritable, WordPair, IntWritable> { /** * Stores the sum of counts for a word */ private final static IntWritable SumValue = new IntWritable(); /** * @param key The Text word * @param values An iterator over the values associated with this word * @param output Map from each word (Text) to its count (IntWritable) * @param reporter Used to report progress */ private IntWritable totalCount = new IntWritable(); public void reduce(WordPair key, Iterator<IntWritable> values, OutputCollector<WordPair, IntWritable> output, Reporter reporter) throws IOException { totalCount.set(getTotalCount(values)); output.collect(key, totalCount); } } /*To partition mappings of same keys to the same reducers, using the modulo operation*/ private static class MyPartitioner extends MapReduceBase implements Partitioner<WordPair, IntWritable> { @Override public int getPartition(WordPair key, IntWritable arg1, int numReduceTasks) { return Math.abs(key.getWord().hashCode()) % numReduceTasks; } } private static int getTotalCount(Iterator<IntWritable> values) { int count = 0; while (values.hasNext()) { count += values.next().get(); } return count; } /** * Creates an instance of this tool. */ public BigramCount() { } /** * Prints argument options * @return */ private static int printUsage() { System.out.println("usage: [input-path] [output-path] [num-mappers] [num-reducers]"); ToolRunner.printGenericCommandUsage(System.out); return -1; } /** * Runs this tool. */ public int run(String[] args) throws Exception { if (args.length != 2) { printUsage(); return -1; } String inputPath = args[0]; String outputPath = args[1]; int mapTasks = 1;//Integer.parseInt(args[2]); int reduceTasks = 1;//Integer.parseInt(args[3]); sLogger.info("Tool: BigramCount"); sLogger.info(" - input path: " + inputPath); sLogger.info(" - output path: " + outputPath); sLogger.info(" - number of mappers: " + mapTasks); sLogger.info(" - number of reducers: " + reduceTasks); JobConf conf = new JobConf(BigramCount.class); conf.setJobName("BigramCount"); conf.setNumMapTasks(mapTasks); conf.setNumReduceTasks(reduceTasks); FileInputFormat.setInputPaths(conf, new Path(inputPath)); FileOutputFormat.setOutputPath(conf, new Path(outputPath)); FileOutputFormat.setCompressOutput(conf, false); /** * Note that these must match the Class arguments given in the mapper */ conf.setOutputKeyClass(WordPair.class); conf.setOutputValueClass(IntWritable.class); conf.setMapperClass(MyMapper.class); conf.setPartitionerClass(MyPartitioner.class); conf.setCombinerClass(MyReducer.class); conf.setReducerClass(MyReducer.class); // Delete the output directory if it exists already Path outputDir = new Path(outputPath); FileSystem.get(outputDir.toUri(), conf).delete(outputDir, true); long startTime = System.currentTimeMillis(); JobClient.runJob(conf); sLogger.info("Job Finished in " + (System.currentTimeMillis() - startTime) / 1000.0 + " seconds"); return 0; } /** * Dispatches command-line arguments to the tool via the * <code>ToolRunner</code>. */ public static void main(String[] args) throws Exception { int res = ToolRunner.run(new Configuration(), new BigramCount(), args); System.exit(res); } }