1.打开eclipse之后,建立wordcount项目

package wordcount;
import java.io.IOException;  
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.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 {  
    public static class TokenizerMapper 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, Context context)  
                throws IOException, InterruptedException {  
            StringTokenizer itr = new StringTokenizer(value.toString());  
            while (itr.hasMoreTokens()) {  
                word.set(itr.nextToken());  
                context.write(word, one);  
            }  
        }  
    }  
    public static class IntSumReducer extends Reducer<Text, IntWritable, Text, IntWritable> {  
        private IntWritable result = new IntWritable();  
        public void reduce(Text key, Iterable<IntWritable> values, Context context)  
                throws IOException, InterruptedException {  
            int sum = 0;  
            for (IntWritable val : values) {  
                sum += val.get();  
            }  
            result.set(sum);  
            context.write(key, result);  
        }  
    }  
    public static void main(String[] args) throws Exception {  
        Configuration conf = new Configuration();  
        if (args.length != 2) {  
            System.err.println("Usage: wordcount  ");  
            System.exit(2);  
        }  
        Job job = new Job(conf, "word count");  
        job.setJarByClass(WordCount.class);  
        job.setMapperClass(TokenizerMapper.class);  
        job.setReducerClass(IntSumReducer.class);  
        job.setMapOutputKeyClass(Text.class);  
        job.setMapOutputValueClass(IntWritable.class);  
        job.setOutputKeyClass(Text.class);  
        job.setOutputValueClass(IntWritable.class);  
        FileInputFormat.addInputPath(job, new Path(args[0]));  
        FileOutputFormat.setOutputPath(job, new Path(args[1]));  
        System.exit(job.waitForCompletion(true) ? 0 : 1);  
    }  
}  

2.配置hadoop路径。

把需要运行的文件放进input文件夹,如何在eclipse上的run configuration上配置需要运行的文件路径和运行结果路径,中间用一个空格隔开,如何点击apply-run,开始跑。

 mac上eclipse上运行word count_mapreduce

3.用终端查看结果

JIAS-MacBook-Pro:output jia$ cat part-r-00000 
do    2
excuse    1
fine    1
hello    2
how    1
me    1
thank    2
you    3