MapReduce实验——数据清洗

package mapreduce;

import java.io.IOException;
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 CleanResult {
    public static void main(String[] args) throws IOException,ClassNotFoundException,InterruptedException{
        Job job = Job.getInstance();
        job.setJobName("CleanResult");
        job.setJarByClass(WordCount.class);
        job.setMapperClass(doMapper.class);
        job.setReducerClass(doReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        Path in = new Path("hdfs://192.168.12.128:9000/mapreduce/in/result.txt");
        Path out = new Path("hdfs://192.168.12.128:9000/mapreduce/out/clean");
        FileInputFormat.addInputPath(job,in);
        FileOutputFormat.setOutputPath(job,out);
        System.exit(job.waitForCompletion(true) ? 0:1);
    }
    public static class doMapper extends Mapper<Object,Text,Text,IntWritable>{
        public static Text word = new Text();
        public static final IntWritable id = new IntWritable();
        @Override
        protected void map(Object key,Text value,Context context) throws IOException,InterruptedException{
            String[] data = value.toString().split(",");
            String[] time = data[1].split(":");
            data[1] = "2016-11-10 " + time[1] + ":" + time[2] + ":"  + time[3].split(" ")[0];
            String traffic = "";
            for(int i=0;i<data[3].length();i++){
                if(data[3].charAt(i) >= 48 && data[3].charAt(i)<=57) {
                    traffic += data[3].charAt(i);
                }
            }
            data[3] = traffic;
            String newValue = data[0];
            for(int i=1;i<5;i++)
                newValue += "\t" + data[i];
            id.set(Integer.parseInt(data[5]));
            word.set(newValue);
            context.write(word, id);
        }
    }
    
    public static class doReducer extends Reducer<Text,IntWritable,Text,IntWritable>{
        private IntWritable result = new IntWritable();
        @Override
        protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
             System.out.println("key:" + key);
                for(IntWritable value:values){
                    result.set(value.get());
                }
                System.out.println("value:" + result);
                context.write(key, result);
        }
        
    }

}

load data inpath ‘/mapreduce/out/clean/part-r-00000‘ into table data;