大数据学习之自定义输入 13

一：自定义输出

需求：将多个小文件合并为SequenceFile（存储了多个小文件）

存储格式：文件路径+文件的内容

c:/a.txt i am hunter henshuai 

c:/b.txt i love delireba

inputFormat(自定义加上路径)

代码编写：

1：自定义FileInputFormat编写

package it.dawn.YARNPra.自定义.inputformate;

import java.io.IOException;

import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.BytesWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.InputSplit;
import org.apache.hadoop.mapreduce.JobContext;
import org.apache.hadoop.mapreduce.RecordReader;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;

/**
 * @author Dawn
 * @date 2019年5月9日22:58:19
 * @version 1.0
 * 自定义输入，自己编写框架
 * 需求？
 * 将多个小文件合并为SequenceFile（存储了多个小文件）
 * 	存储格式：文件路径+文件的内容
 * 	c:/a.txt i am hunter henshuai 
 * 	c:/b.txt i love delireba
 * 
 * 	inputFormat(自定义加上路径)
 */


//1.创建自定义inputformat 
//为什么是用NullWritable, BytesWritable，
//因为，这里的key我们暂时处理为空。到后面Map输出阶段的时候，我们再讲输出类型改成Text 和BytesWritable
public class FuncFileInputFormat extends FileInputFormat<NullWritable, BytesWritable>{


	@Override
	protected boolean isSplitable(JobContext context,Path filename) {
		//不切原来的文件
		return false;
	}
	
	@Override
	public RecordReader<NullWritable, BytesWritable> createRecordReader(InputSplit split, TaskAttemptContext context)
			throws IOException, InterruptedException {
		
		FuncRecordReader RecordReader=new FuncRecordReader();
		return RecordReader;
	}

}

　　

2：自定义RecordReader类编写

package it.dawn.YARNPra.自定义.inputformate;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.BytesWritable;
import org.apache.hadoop.io.IOUtils;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.InputSplit;
import org.apache.hadoop.mapreduce.RecordReader;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
import org.apache.hadoop.mapreduce.lib.input.FileSplit;

/**
 * @author Dawn
 * @date 2019年5月9日23:12:03
 * @version 1.0
 * 
 */
//2.编写RecordReader 
public class FuncRecordReader extends RecordReader<NullWritable, BytesWritable>{

	boolean isProcess = false;
	FileSplit split;
	Configuration conf;
	BytesWritable value = new BytesWritable();
	
	@Override
	public void initialize(InputSplit split, TaskAttemptContext context)  {
		//初始化切片
		this.split=(FileSplit) split;
		//初始化配置信息
		conf=context.getConfiguration();
		
	}

	@Override
	public boolean nextKeyValue() throws IOException, InterruptedException {
		
		if(!isProcess) {
			//1.根据切片的长度来创建缓冲区
			byte[] buf= new byte[(int)split.getLength()];
			FSDataInputStream fis = null;
			FileSystem fs = null;
			
			try {
				//2.获取路径
				Path path=split.getPath();
				
				//3.根据路径获取文件系统
				fs=path.getFileSystem(conf);
				
				//4：拿到输入流
				fis=fs.open(path);
				
				//5：数据拷贝
				IOUtils.readFully(fis, buf, 0, buf.length);
				
				//6.拷贝缓存到最终的输出
				value.set(buf, 0, buf.length);
			}catch (IOException e) {
				e.printStackTrace();
			}finally {
				IOUtils.closeStream(fis);
				IOUtils.closeStream(fs);
			}
			
			isProcess=true;
			
			return true;
		}
		return false;
	}

	@Override
	public NullWritable getCurrentKey() throws IOException, InterruptedException {
		// TODO Auto-generated method stub
		return NullWritable.get();
	}

	@Override
	public BytesWritable getCurrentValue() throws IOException, InterruptedException {
		// TODO Auto-generated method stub
		return value;
	}

	@Override
	public float getProgress() throws IOException, InterruptedException {
		// TODO Auto-generated method stub
		return 0;
	}

	@Override
	public void close() throws IOException {
		// TODO Auto-generated method stub
		
	}

}

　　

3：编写MR

map:

package it.dawn.YARNPra.自定义.inputformate;

import java.io.IOException;

import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.BytesWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.input.FileSplit;

/**
 * @author Dawn
 * @date 2019年5月9日23:25:29
 * @version 1.0
 * 
 */
public class SequenceFileMapper extends Mapper<NullWritable, BytesWritable, Text, BytesWritable>{

	Text k=new Text();
	
	@Override
	protected void setup(Context context)
			throws IOException, InterruptedException {
		//1拿到切片信息
		FileSplit split=(FileSplit) context.getInputSplit();
		
		//2路径
		Path path=split.getPath();
		
		//3.即带路径又带名称
		k.set(path.toString());
	}
	
	
	@Override
	protected void map(NullWritable key, BytesWritable value,Context context)
			throws IOException, InterruptedException {
		context.write(k, value);
	}


}

　　

Reducer:

package it.dawn.YARNPra.自定义.inputformate;

import java.io.IOException;

import org.apache.hadoop.io.BytesWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

public class SequenceFileReducer extends Reducer<Text, BytesWritable, Text, BytesWritable>{

	@Override
	protected void reduce(Text key, Iterable<BytesWritable> value,
			Context context) throws IOException, InterruptedException {
		for(BytesWritable v:value) {
			context.write(key, v);
		}
	}
	

}

　　

driver:

package it.dawn.YARNPra.自定义.inputformate;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.BytesWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat;

/**
 * @author Dawn
 * @date 2019年5月9日23:32:39
 * @version 1.0
 * 
 */
public class SequenceDriver {
	public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
		// 1.获取job信息
		Configuration conf = new Configuration();
		Job job = Job.getInstance(conf);

		// 2.获取jar包
		job.setJarByClass(SequenceDriver.class);

		// 3.获取自定义的mapper与reducer类
		job.setMapperClass(SequenceFileMapper.class);
		job.setReducerClass(SequenceFileReducer.class);
		
		//设置自定义读取方式
		job.setInputFormatClass(FuncFileInputFormat.class);
		//设置默认的输出方式
		job.setOutputFormatClass(SequenceFileOutputFormat.class);

		// 4.设置map输出的数据类型
		job.setMapOutputKeyClass(Text.class);
		job.setMapOutputValueClass(BytesWritable.class);

		// 5.设置reduce输出的数据类型（最终的数据类型）
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(BytesWritable.class);

		// 6.设置输入存在的路径与处理后的结果路径
		FileInputFormat.setInputPaths(job, new Path("f:/temp/inputSelf/*.txt"));
		FileOutputFormat.setOutputPath(job, new Path("f:/temp/inputSelfout1"));

		// 7.提交任务
		boolean rs = job.waitForCompletion(true);
		System.out.println(rs ? 0 : 1);

	}

}

　　

运行结果截图：

输入：

输出（将就看吧！输出格式是BytesWriteble字节的输出，看起来不是很好）：