WordCount

package cmd;

import java.net.URI;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
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;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

public class WordCountApp extends Configured implements Tool{
    static String INPUT_PATH = "";
    static String OUT_PATH = "";
    
    @Override
    public int run(String[] arg0) throws Exception {
        INPUT_PATH = arg0[0];
        OUT_PATH = arg0[1];
        
        Configuration conf = new Configuration();
        final FileSystem fileSystem = FileSystem.get(new URI(INPUT_PATH), conf);
        final Path outPath = new Path(OUT_PATH);
        if(fileSystem.exists(outPath)){
            fileSystem.delete(outPath, true);
        }
        
        final Job job = new Job(conf , WordCountApp.class.getSimpleName());
        //打包运行必须执行的秘密方法
        job.setJarByClass(WordCountApp.class);
        
        //1.1指定读取的文件位于哪里
        FileInputFormat.setInputPaths(job, INPUT_PATH);
        //指定如何对输入文件进行格式化，把输入文件每一行解析成键值对
        //job.setInputFormatClass(TextInputFormat.class);
        
        //1.2 指定自定义的map类
        job.setMapperClass(MyMapper.class);
        //map输出的<k,v>类型。如果<k3,v3>的类型与<k2,v2>类型一致，则可以省略
        //job.setMapOutputKeyClass(Text.class);
        //job.setMapOutputValueClass(LongWritable.class);
        
        //1.3 分区
        //job.setPartitionerClass(HashPartitioner.class);
        //有一个reduce任务运行
        //job.setNumReduceTasks(1);
        
        //1.4 TODO 排序、分组
        
        //1.5 TODO 规约
        
        //2.2 指定自定义reduce类
        job.setReducerClass(MyReducer.class);
        //指定reduce的输出类型
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(LongWritable.class);
        
        //2.3 指定写出到哪里
        FileOutputFormat.setOutputPath(job, outPath);
        //指定输出文件的格式化类
        //job.setOutputFormatClass(TextOutputFormat.class);
        
        //把job提交给JobTracker运行
        job.waitForCompletion(true);
        return 0;
    }
    
    public static void main(String[] args) throws Exception {
        ToolRunner.run(new WordCountApp(), args);
    }
    
    /**
     * KEYIN    即k1        表示行的偏移量
     * VALUEIN    即v1        表示行文本内容
     * KEYOUT    即k2        表示行中出现的单词
     * VALUEOUT    即v2        表示行中出现的单词的次数，固定值1
     */
    static class MyMapper extends Mapper<LongWritable, Text, Text, LongWritable>{
        protected void map(LongWritable k1, Text v1, Context context) throws java.io.IOException ,InterruptedException {
            final String[] splited = v1.toString().split("\t");
            for (String word : splited) {
                context.write(new Text(word), new LongWritable(1));
            }
        };
    }
    
    /**
     * KEYIN    即k2        表示行中出现的单词
     * VALUEIN    即v2        表示行中出现的单词的次数
     * KEYOUT    即k3        表示文本中出现的不同单词
     * VALUEOUT    即v3        表示文本中出现的不同单词的总次数
     *
     */
    static class MyReducer extends Reducer<Text, LongWritable, Text, LongWritable>{
        protected void reduce(Text k2, java.lang.Iterable<LongWritable> v2s, Context ctx) throws java.io.IOException ,InterruptedException {
            long times = 0L;
            for (LongWritable count : v2s) {
                times += count.get();
            }
            ctx.write(k2, new LongWritable(times));
        };
    }

        
}