MapReduce案例七：小文件合并

目录

• 一、数据样例
• 二、需求
• 三、分析
• 四、代码实现

一、数据样例

• 文件一：one.txt

pangtouyu yinain yutang chaojidan
pikaqiu Dalen study let me happy

• 文件二：two.txt

longlong fanfan
mazong kailun yuhang yixin
longlong fanfan
mazong kailun yuhang yixin

• 文件三：three.txt

shuaige changmo zhenqiang
dongli lingu xuanxuan

二、需求

• 无论hdfs还是mapreduce，对于小文件都有损效率，实践中，又难免面临处理大量小文件的场景，此时，就需要有相应解决方案。将多个小文件合并成一个文件SequenceFile，SequenceFile里面存储着多个文件，存储的形式为文件路径+名称为key，文件内容为value。

三、分析

• 小文件的优化无非以下几种方式：
  （1）在数据采集的时候，就将小文件或小批数据合成大文件再上传HDFS
  （2）在业务处理之前，在HDFS上使用mapreduce程序对小文件进行合并
  （3）在mapreduce处理时，可采用CombineTextInputFormat提高效率

• 本节采用自定义InputFormat的方式，处理输入小文件的问题。
  （1）自定义一个类继承FileInputFormat
  （2）改写RecordReader，实现一次读取一个完整文件封装为KV
  （3）在输出时使用SequenceFileOutPutFormat输出合并文件

四、代码实现

• 1、创建 WholeRecordReader 类：

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;

public class WholeRecordReader extends RecordReader<NullWritable, BytesWritable>{

	private Configuration configuration;
	private FileSplit split;
	
	private boolean processed = false;
	private BytesWritable value = new BytesWritable();
	
	@Override
	public void initialize(InputSplit split, TaskAttemptContext context) throws IOException, InterruptedException {
		
		this.split = (FileSplit)split;
		configuration = context.getConfiguration();
	}

	@Override
	public boolean nextKeyValue() throws IOException, InterruptedException {
		
		if (!processed) {
			// 1 定义缓存区
			byte[] contents = new byte[(int)split.getLength()];
			
			FileSystem fs = null;
			FSDataInputStream fis = null;
			
			try {
				// 2 获取文件系统
				Path path = split.getPath();
				fs = path.getFileSystem(configuration);
				
				// 3 读取数据
				fis = fs.open(path);
				
				// 4 读取文件内容
				IOUtils.readFully(fis, contents, 0, contents.length);
				
				// 5 输出文件内容
				value.set(contents, 0, contents.length);
			} catch (Exception e) {
				
			}finally {
				IOUtils.closeStream(fis);
			}
			
			processed = true;
			
			return true;
		}
		
		return false;
	}

	@Override
	public NullWritable getCurrentKey() throws IOException, InterruptedException {
		return NullWritable.get();
	}

	@Override
	public BytesWritable getCurrentValue() throws IOException, InterruptedException {
		return value;
	}

	@Override
	public float getProgress() throws IOException, InterruptedException {
		return processed? 1:0;
	}

	@Override
	public void close() throws IOException {
	}
}

• 2、创建 WholeFileInputformat 类：

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;

// 定义类继承FileInputFormat
public class WholeFileInputformat extends FileInputFormat<NullWritable, BytesWritable>{
	
	@Override
	protected boolean isSplitable(JobContext context, Path filename) {
		return false;
	}

	@Override
	public RecordReader<NullWritable, BytesWritable> createRecordReader(InputSplit split, TaskAttemptContext context)
			throws IOException, InterruptedException {
		
		WholeRecordReader recordReader = new WholeRecordReader();
		recordReader.initialize(split, context);
		
		return recordReader;
	}
}

• 3、创建 SequenceFileMapper 类：

import java.io.IOException;
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;

public class SequenceFileMapper extends Mapper<NullWritable, BytesWritable, Text, BytesWritable>{
	
	Text k = new Text();
	
	@Override
	protected void setup(Mapper<NullWritable, BytesWritable, Text, BytesWritable>.Context context)
			throws IOException, InterruptedException {
		// 1 获取文件切片信息
		FileSplit inputSplit = (FileSplit) context.getInputSplit();
		// 2 获取切片名称
		String name = inputSplit.getPath().toString();
		// 3 设置key的输出
		k.set(name);
	}
	
	@Override
	protected void map(NullWritable key, BytesWritable value,
			Context context)
			throws IOException, InterruptedException {

		context.write(k, value);
	}
}

• 4、创建 SequenceFileReducer 类：

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> values, Context context)
			throws IOException, InterruptedException {

		context.write(key, values.iterator().next());
	}
}

• 5、创建 SequenceFileDriver 类：

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;

public class SequenceFileDriver {

	public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
		
		args = new String[] { "e:/input/inputinputformat", "e:/output1" };
		Configuration conf = new Configuration();

		Job job = Job.getInstance(conf);
		job.setJarByClass(SequenceFileDriver.class);
		job.setMapperClass(SequenceFileMapper.class);
		job.setReducerClass(SequenceFileReducer.class);

        // 设置输入的inputFormat
		job.setInputFormatClass(WholeFileInputformat.class);
        // 设置输出的outputFormat
		job.setOutputFormatClass(SequenceFileOutputFormat.class);

		job.setMapOutputKeyClass(Text.class);
		job.setMapOutputValueClass(BytesWritable.class);
		
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(BytesWritable.class);

		FileInputFormat.setInputPaths(job, new Path(args[0]));
		FileOutputFormat.setOutputPath(job, new Path(args[1]));

		job.waitForCompletion(true);
	}
}

• 结果图：