map reduce word count例子不起作用

时间:2011-03-26 01:26:42

标签: mapreduce word-count

我尝试自己实现单词计数示例,这是我对mapper的实现:

public static class Map extends Mapper<LongWritable, Text, Text, IntWritable> {

    public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        Text word = new Text();     
        String line = value.toString();
        StringTokenizer tokenizer = new StringTokenizer(line);
        while (tokenizer.hasMoreTokens()) {
            word.set(tokenizer.nextToken());
            context.write(word, new IntWritable(1));
        }
    }
}

和reducer:

public static class Reduce extends Reducer<Text, IntWritable, Text, IntWritable> {
    public void reduce(Text key, Iterator<IntWritable> values, Context context) throws IOException, InterruptedException {
        int sum = 0;
        while (values.hasNext())
            sum += values.next().get();
    context.write(key, new IntWritable(sum));
    }
}

但是我执行此代码的输出看起来只是mapper的输出,例如,如果输入是“hello world hello”,输出将是

hello 1
hello 1
world 1

我还在映射和缩减之间使用组合器。任何人都可以解释一下这段代码有什么问题吗?

非常感谢!

2 个答案:

答案 0 :(得分:3)

用这个替换你的reduce方法:

        @Override
        protected void reduce(Text key, java.lang.Iterable<IntWritable> values, org.apache.hadoop.mapreduce.Reducer<Text, IntWritable, Text, IntWritable>.Context context) throws IOException,
                InterruptedException {
            int sum = 0;
            for (IntWritable value : values) {
                sum += value.get();
            }
            context.write(key, new IntWritable(sum));
        }

所以底线是你没有覆盖正确的方法。 @Override可以帮助解决这类错误。

还要确保将Reduce.class设置为reduce类而不是Reducer.class!

) HTH 约翰内斯

答案 1 :(得分:0)

如果你不想使用reduce方法的args而不是替代解决方案,那么:

@Override
protected void reduce(Object key, Iterable values, Context context) throws 
IOException, InterruptedException {

 int sum = 0;
 Iterable<IntWritable> v = values;
 Iterator<IntWritable> itr = v.iterator();

 while(itr.hasNext()){
    sum += itr.next().get();
 }

 context.write(key, new IntWritable(sum));
}