MapReduce自定义InputFormat和OutputFormat

一、自定义InputFormat

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 love Beijing 
        c:/b.txt I love China
        
        inputFormat(自定义加上路径)

1.Mapper类

package com.css.inputformat;

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;

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 {
        // 输出
        context.write(k, value);
    }
}

2.Reducer类

package com.css.inputformat;

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 {
        for (BytesWritable v : values) {
            context.write(key, v);
        }
    }
}

3.自定义InputFormat类

package com.css.inputformat;

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;

/**
 * 1.创建自定义Inputformat
 */
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;
    }
}

4.自定义RecordReader类

package com.css.inputformat;

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;

/**
 * 2.编写RecordReader
 */
public class FuncRecordReader extends RecordReader<NullWritable, BytesWritable>{

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

    @Override
    public boolean nextKeyValue() {
        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.拿到输出流
                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 (Exception e) {
                e.printStackTrace();
            } finally {
                IOUtils.closeStream(fis);
                IOUtils.closeStream(fs);
            }
            
            isProcess = 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 0;
    }

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

5.Driver类

package com.css.inputformat;

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 SequenceDriver {
    public static void main(String[] args) throws IllegalArgumentException, 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);
        
        // 4.设置自定义读取方式
        job.setInputFormatClass(FuncFileInputFormat.class);
        // 5.设置默认的输出方式
        job.setOutputFormatClass(SequenceFileOutputFormat.class);

        // 6.设置map输出的数据类型
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(BytesWritable.class);

        // 7.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);

        // 8.设置输入存在的路径与处理后的结果路径
        FileInputFormat.setInputPaths(job, new Path("c:/in1027/"));
        FileOutputFormat.setOutputPath(job, new Path("c:/out1027/"));

        // 9.提交任务
        boolean rs = job.waitForCompletion(true);
        System.out.println(rs ? 0 : 1);
    }
}

6.输入小文件

（1）a.txt
I love Beijing
（2）b.txt
I love China
（3）c.txt
Bejing is the capital of China

7.输出文件part-r-00000

SEQorg.apache.hadoop.io.Text"org.apache.hadoop.io.BytesWritable      嫜瑻z萶2
?擎?  (   file:/c:/in1027/a.txt   I love Beijing   &   file:/c:/in1027/b.txt   I love China   8   file:/c:/in1027/c.txt   Bejing is the capital of China

 

二、自定义OutputFormat

需求:过滤日志文件
    把包含main的放在一个文件中 d:/main.logs
    把不包含main的放在另外一个文件 d:/other.logs

1.Mapper类

package com.css.outputformat;

import java.io.IOException;

import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

public class FileMapper extends Mapper<LongWritable, Text, Text, NullWritable>{

    @Override
    protected void map(LongWritable key, Text value, Context context)
            throws IOException, InterruptedException {
        // 输出
        context.write(value, NullWritable.get());
    }
}

2.Reducer类

package com.css.outputformat;

import java.io.IOException;

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

public class FileReducer extends Reducer<Text, NullWritable, Text, NullWritable>{

    @Override
    protected void reduce(Text key, Iterable<NullWritable> values,
            Context context) throws IOException, InterruptedException {
        // 数据换行
        String k = key.toString() + "
";
        context.write(new Text(k), NullWritable.get());
    }
}

3.自定义OutputFormat类

package com.css.outputformat;

import java.io.IOException;

import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.RecordWriter;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class FuncFileOutputFormat extends FileOutputFormat<Text, NullWritable>{

    @Override
    public RecordWriter<Text, NullWritable> getRecordWriter(TaskAttemptContext job)
            throws IOException, InterruptedException {
        FileRecordWriter fileRecordWriter = new FileRecordWriter(job);
        return fileRecordWriter;
    }
}

4.自定义RecordWriter类

package com.css.outputformat;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataOutputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.RecordWriter;
import org.apache.hadoop.mapreduce.TaskAttemptContext;

public class FileRecordWriter extends RecordWriter<Text, NullWritable>{

    Configuration conf = null;
    FSDataOutputStream mainlog = null;
    FSDataOutputStream otherlog = null;
    
    // 1.定义数据输出路径
    public FileRecordWriter(TaskAttemptContext job) throws IOException{
        // 获取配置信息
        conf = job.getConfiguration();
        // 获取文件系统
        FileSystem fs = FileSystem.get(conf);
        // 定义输出路径
        mainlog = fs.create(new Path("c:/outputmain/main.logs")); // part-r-00000
        otherlog = fs.create(new Path("c:/outputother/other.logs"));
    }
    
    // 2.数据输出
    @Override
    public void write(Text key, NullWritable value) throws IOException, InterruptedException {
        // 判断的话根据key
        if (key.toString().contains("main")) {
            // 写出到文件
            mainlog.write(key.getBytes());
        }else {
            otherlog.write(key.getBytes());
        }
    }

    // 3.关闭资源
    @Override
    public void close(TaskAttemptContext context) throws IOException, InterruptedException {
        if (null != mainlog) {
            mainlog.close();
        }
        if (null != otherlog) {
            otherlog.close();
        }
    }
}

5.Driver类

package com.css.outputformat;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.NullWritable;
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;

public class FileDriver {
    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(FileDriver.class);
        // 3.获取自定义的mapper与reducer类
        job.setMapperClass(FileMapper.class);
        job.setReducerClass(FileReducer.class);
        // 4.设置map输出的数据类型
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(NullWritable.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(NullWritable.class);
        // 6.设置自定义outputFormat
        job.setOutputFormatClass(FuncFileOutputFormat.class);
        // 7.设置输入存在的路径与处理后的结果路径
        FileInputFormat.setInputPaths(job, new Path("c:/in1029/"));
        FileOutputFormat.setOutputPath(job, new Path("c:/out1029/"));
        // 8.提交任务
        boolean rs = job.waitForCompletion(true);
        System.out.println(rs ? 0 : 1);
    }
}

6.输入文件data.logs

http://www.baidu.com
http://taobao.com
http://jd.com
http://it.com
http://main.js
http://qq.com
http://main.com.cn

7.输出文件

（1）main.logs
http://main.com.cn
 http://main.js
 
（2）other.logs
http://it.com
 http://jd.com
 http://qq.com
 http://taobao.com
 http://www.baidu.com