Java examples for Big Data:Hadoop
inverted Index in hadoop
import java.io.IOException; import java.util.*; import org.apache.hadoop.fs.Path; import org.apache.hadoop.classification.InterfaceAudience.Private; import org.apache.hadoop.conf.*; import org.apache.hadoop.io.*; import org.apache.hadoop.mapred.*; import org.apache.hadoop.util.*; public class inverted_Index { public static class Map extends MapReduceBase implements Mapper<LongWritable, Text, Text, Text> { //private final static LongWritable one = new LongWritable(location); private Text word = new Text(); public void map(LongWritable key, Text value, OutputCollector<Text, Text> output, Reporter reporter) throws IOException { FileSplit fs = (FileSplit) reporter.getInputSplit(); String fileName = fs.getPath().getName(); String line = value.toString(); StringTokenizer tokenizer = new StringTokenizer(line); while (tokenizer.hasMoreTokens()) { word.set(tokenizer.nextToken()); output.collect(word, new Text(fileName)); }//from ww w . j av a 2 s . c o m } } public static class Reduce extends MapReduceBase implements Reducer<Text, Text, Text, Text> { public void reduce(Text key, Iterator<Text> values, OutputCollector<Text, Text> output, Reporter reporter) throws IOException { String fileSet = new String(); while (values.hasNext()) { String fileString = values.toString(); fileSet = fileSet + fileString; } output.collect(key, new Text(fileSet)); } } public static void main(String[] args) throws Exception { JobConf conf = new JobConf(inverted_Index.class); conf.setJobName("inverted_Index"); conf.setOutputKeyClass(Text.class); conf.setOutputValueClass(Text.class); conf.setMapperClass(Map.class); conf.setCombinerClass(Reduce.class); conf.setReducerClass(Reduce.class); conf.setInputFormat(TextInputFormat.class); conf.setOutputFormat(TextOutputFormat.class); FileInputFormat.setInputPaths(conf, new Path(args[0])); FileOutputFormat.setOutputPath(conf, new Path(args[1])); JobClient.runJob(conf); } }