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 ronchy; import java.io.IOException; import java.util.Iterator; import java.util.StringTokenizer; 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.DoubleWritable; 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.mapreduce.lib.output.SequenceFileOutputFormat; 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); private static class MyMapper extends MapReduceBase implements Mapper<LongWritable, Text, Text, Text> { private Text word = new Text(); public void map(LongWritable key, Text value, OutputCollector<Text, Text> output, Reporter reporter) throws IOException { //Convert input word into String and tokenize to find words String line = ((Text) value).toString(); String[] data = line.split(","); double score = Double.parseDouble(data[1]); String out1 = score + "," + data[2] + "," + data[3]; word.set(data[0]); //output.collect(word, new DoubleWritable(score)); output.collect(word, new Text(out1)); } } /** * Reducer: sums up all the counts * */ private static class MyReducer extends MapReduceBase implements Reducer<Text, Text, Text, Text> { //private final static DoubleWritable SumValue = new DoubleWritable(); public void reduce(Text key, Iterator<Text> values, OutputCollector<Text, Text> output, Reporter reporter) throws IOException { // sum up values double positive_sum = 0.0; double negative_sum = 0.0; Text out = new Text(); int total_cn = 0; int positive_cn = 0; int negative_cn = 0; int neutral_cn = 0; double positive_retweet_sum = 0; double negative_retweet_sum = 0; double neutral_retweet_sum = 0; double positive_favorite_sum = 0; double negative_favorite_sum = 0; double neutral_favorite_sum = 0; while (values.hasNext()) { String str1 = values.next().toString(); String data[] = str1.split(","); double num = Double.parseDouble(data[0]); if (num > 0.0) { positive_sum += num; positive_retweet_sum += Double.parseDouble(data[1]); positive_favorite_sum += Double.parseDouble(data[2]); positive_cn++; } else if (num < 0.0) { negative_sum += num; negative_retweet_sum += Double.parseDouble(data[1]); negative_favorite_sum += Double.parseDouble(data[2]); negative_cn++; } else if (num == 0.0) { neutral_retweet_sum += Double.parseDouble(data[1]); neutral_favorite_sum += Double.parseDouble(data[2]); neutral_cn++; } total_cn++; } String str = ("" + positive_sum + "," + positive_cn + "," + positive_retweet_sum + "," + positive_favorite_sum + "," + negative_sum + "," + negative_cn + "," + negative_retweet_sum + "," + negative_favorite_sum + "," + neutral_cn + "," + neutral_retweet_sum + "," + neutral_favorite_sum + "," + total_cn + ""); output.collect(key, new Text(str)); } } /** * 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 != 4) { printUsage(); return -1; } String inputPath = args[0]; String outputPath = args[1]; int mapTasks = Integer.parseInt(args[2]); int reduceTasks = 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(Text.class); conf.setOutputValueClass(Text.class); conf.setMapOutputKeyClass(Text.class); conf.setMapOutputValueClass(Text.class); conf.setMapperClass(MyMapper.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); } }