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hadoop处理不同的输入文件,文件关联

2014-04-11 00:00来源:中国存储网
导读:类型一: 一一对应file1:a 1b 2c 3file2:1 !2 @3 #file1和file2进行关联,想要的结果:a !b @3 #思路:1、标记不同输入文件2、将file1的key、value颠倒 ;file1和file2的key相同,file1的v

类型一: 一一对应

file1:

a  1
b  2
c  3

 

file2:

1 !
2 @
3 #

file1和file2进行关联,想要的结果:

a  !

b  @

3  #

 

思路:

1、标记不同输入文件

2、将file1的key、value颠倒 ;file1和file2的key相同,file1的value做key,file2的value做value ,输出。

程序:

 

package smiple;

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.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.InputSplit;
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.FileSplit;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

public class FileJoin {

	public static class MyMap extends Mapper<LongWritable , Text, Text, Text> {

		public void map(LongWritable key, Text value, Context context)throws IOException, InterruptedException {
//			String line = value.toString();
			String line=new String(value.getBytes(),0,value.getLength(),"GBK");
			StringTokenizer tokenizer = new StringTokenizer(line);
			String keystr = tokenizer.nextToken();
			String valuestr = tokenizer.nextToken();
			
			//获取文件名
			InputSplit inputSplit = context.getInputSplit();
			String fileName = ((FileSplit) inputSplit).getPath().getName();
			
			
			if("file1".equals(fileName)){//加标记
				context.write(new Text(valuestr),new Text("file1_"+keystr));
			}else if("file2".equals(fileName)){
				context.write(new Text(keystr), new Text("file2_"+valuestr));
			}
			
		}
	}

	public static class MyReduce extends Reducer<Text, Text, Text, Text> {

		public void reduce(Text key, Iterable<Text> values,Context context) throws IOException, InterruptedException {
			Text resultKey = new Text("key0");
			Text resultValue = new Text("value0");
			for (Text val : values) {
				if("file1_".equals(val.toString().substring(0, 6))){
					resultKey = new Text(val.toString().substring(6));
				}else if("file2_".equals(val.toString().substring(0, 6))){
					resultValue = new Text(val.toString().substring(6));
				}
			}
			System.out.println(resultKey.toString()+"   " + resultValue.toString());
			context.write(resultKey, resultValue);
		}
	}

	public static void main(String[] args) throws Exception {
		Configuration conf = new Configuration();
		String[] ioArgs = new String[] { "hdfs://ip:port/mr/join/in","hdfs://ip:port/mr/join/out" };
		String[] otherArgs = new GenericOptionsParser(conf, ioArgs).getRemainingArgs();

		if (otherArgs.length != 2) {
			System.err.println("Usage: Data Sort <in> <out>");
			System.exit(2);
		}
		Job job = new Job(conf, "file join ");

		job.setJarByClass(Sort.class);

		// 设置Map和Reduce处理类
		job.setMapperClass(MyMap.class);
		job.setReducerClass(MyReduce.class);

		// 设置输出类型
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(Text.class);

		// 设置输入和输出目录
		FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
		FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));

		System.exit(job.waitForCompletion(true) ? 0 : 1);

	}

}

 

结果:

 

hadoop处理不同的输入文件,文件关联

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