MapReduce：如果值不超过阈值，则筛选出键值对

Question

Using MapReduce, how do you modify the following word count code such that it will only output words above a certain count threshold? (eg I want add some kind of filtering of key-value pairs.)

Input:

ant bee cat
bee cat dog
cat dog

Output: let say count threshold is 2 or more

cat 3
dog 2

---

Following code is from: http://hadoop.apache.org/docs/r1.2.1/mapred_tutorial.html#Source+Code

public static class Map1 extends MapReduceBase implements Mapper<LongWritable, Text, Text, IntWritable> {
  private final static IntWritable one = new IntWritable(1);
  private Text word = new Text();

  public void map(LongWritable key, Text value, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException {
    String line = value.toString();
    StringTokenizer tokenizer = new StringTokenizer(line);
    while (tokenizer.hasMoreTokens()) {
      word.set(tokenizer.nextToken());
      output.collect(word, one);
    }
  }
}

public static class Reduce1 extends MapReduceBase implements Reducer<Text, IntWritable, Text, IntWritable> {
  public void reduce(Text key, Iterator<IntWritable> values, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException {
    int sum = 0;
    while (values.hasNext()) {
      sum += values.next().get();
    }
    output.collect(key, new IntWritable(sum));
  }
}

---

EDIT: RE: about inputs/testcase

Input file ("example.dat") and a simple test case ("testcase") is found here: https://github.com/csiu/tokens/tree/master/other/SO-26695749

---

EDIT:

The problem wasn't the code. It was due to some strange behavior between the org.apache.hadoop.mapred package. ( Is it better to use the mapred or the mapreduce package to create a Hadoop Job? ).

Point: use org.apache.hadoop.mapreduce instead

Answer 1

Try adding an if statement before collecting the output in reduce.

if(sum >= 2)
    output.collect(key, new IntWritable(sum));

Answer 2

You can just do the filtering in the Reduce1 class:

if (sum>=2) {
    output.collect(key. new IntWritable(sum));
}