= 用Hadoop 0.18 改成 Hadoop 0.20 程式易出現的問題 =

 == 前言 ==
 * 下面程式碼雖然看起來跑wordcount , 但出來的結果卻是跑 helloword 

{{{
#!java

import java.io.IOException;
import java.util.Iterator;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
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.OutputCollector;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class wordcount {
	static public class wcmapper extends
			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);
			}
		}
	}

	static public class wcreducer extends
			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));
		}
	}

	public static void main(String[] args) throws Exception {

		Configuration conf = new Configuration();

		Job job = new Job(conf, "wordcount");

		job.setJarByClass(wordcount.class);

		FileInputFormat.setInputPaths(job, "/user/shunfa/input");
		FileOutputFormat.setOutputPath(job, new Path(
				"/user/shunfa/output-wordcount11"));

		job.setMapperClass(wcmapper.class);
		job.setReducerClass(wcreducer.class);
		job.waitForCompletion(true);
	}
}

}}}

輸入檔內容為
{{{
#!text

i am little cat
you are small dog
haha
}}}

 * 預期結果

{{{
am 1
are 1
cat 1
....
}}}

 * 執行結果：

{{{
0   i am little cat
12    you are small dog
32  haha
...
}}}

 * 解決方法提示

已經用 org.apache.hadoop.mapreduce.Mapper;  org.apache.hadoop.mapreduce.Reducer;  來實做的map() 與 reduce () 的 function， 

implement 時不可用 '''''map(LongWritable key, Text value,  OutputCollector<Text, IntWritable> output, Reporter reporter) '''''，

應改成 '''map(LongWritable key, Text value,  Context context)  ''' 來實做