案例一

分析

准备数据

hello--a.txt 1
hello--b.txt 2
hello--c.txt 1
allen--b.txt 2
jerry--a.txt 2
allen--a.txt 1
jerry--c.txt 2

代码

package com.index;
import com.folwsum.FlowSumSort;
import org.apache.hadoop.conf.Configuration;
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.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import java.io.IOException;
public class IndexStepTwo {
    public static class IndexStepTwoMapper extends Mapper<LongWritable, Text, Text, Text> {
        Text k = new Text();
        Text v = new Text();
        @Override
        protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
            String line = value.toString();
            String[] fields = line.split(" ");
            String word_file = fields[0];
            String count = fields[1];
            String[] split = word_file.split("--");
            String word = split[0];
            String file = split[1];
            k.set(word);
            v.set(file+"--"+count);
            context.write(k, v);    // k hello  v a.txt--1
        }
    }
    public static class IndexStepTwoReduce extends Reducer<Text, Text, Text, Text> {
        Text v = new Text();
        @Override
        protected void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
            StringBuffer sBuffer = new StringBuffer();
            for (Text value : values) {
                //拼接下格式
                sBuffer.append(value.toString()).append(" ");
            }
            v.set(sBuffer.toString());
            context.write(key, v);
        }
    }
    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Configuration conf = new Configuration();
        Job job = Job.getInstance();
        job.setJarByClass(IndexStepTwo.class);
        //告诉程序，我们的程序所用的mapper类和reducer类是什么
        job.setMapperClass(IndexStepTwoMapper.class);
        job.setReducerClass(IndexStepTwoReduce.class);
        //告诉框架，我们程序输出的数据类型
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(Text.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);
        //这里可以进行combiner组件的设置
        job.setCombinerClass(IndexStepTwoReduce.class);
        //告诉框架，我们程序使用的数据读取组件 结果输出所用的组件是什么
        //TextInputFormat是mapreduce程序中内置的一种读取数据组件  准确的说 叫做 读取文本文件的输入组件
        job.setInputFormatClass(TextInputFormat.class);
        job.setOutputFormatClass(TextOutputFormat.class);
        //告诉框架，我们要处理的数据文件在那个路劲下
        FileInputFormat.setInputPaths(job, new Path("/Users/jdxia/Desktop/website/hdfs/index/input/"));
        //如果有这个文件夹就删除
        Path out = new Path("/Users/jdxia/Desktop/website/hdfs/index/output/");
        FileSystem fileSystem = FileSystem.get(conf);
        if (fileSystem.exists(out)) {
            fileSystem.delete(out, true);
        }
        //告诉框架，我们的处理结果要输出到什么地方
        FileOutputFormat.setOutputPath(job, out);
        boolean res = job.waitForCompletion(true);
        System.exit(res ? 0 : 1);
    }
}

结果展示

里面的crc是个校验文件

allen    a.txt--1 b.txt--2  
hello    c.txt--1 b.txt--2 a.txt--1  
jerry    c.txt--2 a.txt--2

案例二

代码前提

如果准备的数据是这样

那就要把他先变成这样

hello--a.txt 1
hello--b.txt 2
hello--c.txt 1
allen--b.txt 2
jerry--a.txt 2
allen--a.txt 1
jerry--c.txt 2

代码

public class IndexStepOne {
    public static class IndexStepOneMapper extends Mapper<LongWritable, Text, Text, IntWritable>{
        Text k = new Text();
        IntWritable v = new IntWritable(1);
        @Override
        protected void map(LongWritable key, Text value,Context context) throws IOException, InterruptedException {
            String line = value.toString();
            String[] words = line.split(" ");
            FileSplit Split = (FileSplit)context.getInputSplit();
            String filename = Split.getPath().getName();
            //输出key :单词--文件名  value:1
            for(String word : words){
                k.set(word +"--"+ filename);    
                context.write(k, v);
            }
        }
    }
    public static class IndexStepOneReducer extends Reducer<Text, IntWritable, Text, IntWritable>{
        IntWritable v = new IntWritable();
        @Override
        protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
            int count = 0;
            for(IntWritable value : values){
                count += value.get();
            }
            v.set(count);
            context.write(key, v);
        }
    }
    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
        Job job = Job.getInstance(conf);
        job.setJarByClass(IndexStepOne.class);
        //告诉程序，我们的程序所用的mapper类和reducer类是什么
        job.setMapperClass(IndexStepOneMapper.class);
        job.setReducerClass(IndexStepOneReducer.class);
        //告诉框架，我们程序输出的数据类型
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        //这里可以进行combiner组件的设置
        job.setCombinerClass(IndexStepOneReducer.class);
        //告诉框架，我们程序使用的数据读取组件 结果输出所用的组件是什么
        //TextInputFormat是mapreduce程序中内置的一种读取数据组件  准确的说 叫做 读取文本文件的输入组件
        job.setInputFormatClass(TextInputFormat.class);
        job.setOutputFormatClass(TextOutputFormat.class);
        //告诉框架，我们要处理的数据文件在那个路劲下
        FileInputFormat.setInputPaths(job, new Path("D:/index/input"));
        //告诉框架，我们的处理结果要输出到什么地方
        FileOutputFormat.setOutputPath(job, new Path("D:/index/output-1"));
        boolean res = job.waitForCompletion(true);
        System.exit(res?0:1);        
    }
}