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新版APIWordCount小例及如何导入jar包

作者:  发布日期:2014-08-16 21:08:46
  • WordCount:

    简单解析wordcount小例子的代码,对应于新版的API进行处理。
    import java.io.IOException;
    import java.util.StringTokenizer;
    import org.apache.hadoop.conf.Configuration;
    import org.apache.hadoop.examples.WordCount.TokenizerMapper;
    import org.apache.hadoop.fs.Path;
    import org.apache.hadoop.io.IntWritable;
    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 {
    
    	/**
    	 * @param 
    	 * @XD 2014-8-16
    	 */
    	public static class TokenzierMapper extends Mapper<Object,Text,Text,IntWritable>{
    		//对于切下的单词赋予出现频数1
    		private final static IntWritable one = new IntWritable(1);
    		
    		//存储切下的单词
    		private Text word = new Text();
    		
    		public void map(Object key,Text value,Context context) throws IOException, InterruptedException{
    			//StringTokenizer 对输入单词进行切分
    			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>{
    		//存取对应单词总频数
    		private IntWritable result = new IntWritable();
    		
    		public  void reduce(Text key,Iterable<IntWritable> values,Context context) throws IOException, InterruptedException{
    			//计算频数
    			int sum = 0;
    			for(IntWritable value:values){
    				sum+=value.get();
    			}
    			result.set(sum);
    			//写入输出
    			context.write(key, result);
    		}
    	}
    	public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
    		// TODO Auto-generated method stub
    		//初始化配置
    		Configuration conf = new Configuration();
    		Job job = new Job(conf,"word count");
    		job.setJarByClass(WordCount.class);
    		
    		//设置map,combine,reduce处理
    		job.setMapperClass(TokenizerMapper.class);
    		job.setReducerClass(IntSumReducer.class);
    		job.setCombinerClass(IntSumReducer.class);
    		
    		//设置输出格式处理类
    		job.setOutputKeyClass(Text.class);
    		job.setOutputValueClass(IntWritable.class);
    		
    		//设置输入输出路径
    		FileInputFormat.addInputPath(job, new Path(args[0]));
    		FileOutputFormat.setOutputPath(job, new Path(args[1]));
    		
    		job.waitForCompletion(true);
    		
    		System.out.println("任务名称: "+job.getJobName());
    		System.out.println("任务成功: "+(job.isSuccessful()?"Yes":"No"));
    		
    	}
    }
    

    在eclipse中实现此过程,需要先导入自己hadoop安装目录下面的jar包,eclipse导入jar如下:

    1.右击工程的根目录,点击Properties进入Properties。或者选中工程根目录,按Alt-Enter即可。

    2.在Properties页面中选中Java Build Path,选中Libraries标签,点击Add External JARs。

    3.找到需要添加的jar包,确定即可。


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