MapReduce任务提交和切片源码+各种inputFormat以及自定义inputFormat+自定义inputFormat代码实现

1、MapReduce任务提交和切片源码

debug能力（怎样使用）：

 

2、各种inputFormat以及自定inputFormat 自定义inputFormat代码实现

 之后就是自定义的inputformat

无论HDFS还是MapReduce，在处理小文件时效率都非常低，但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。可以自定义InputFormat实现小文件的合并。

1．需求

将多个小文件合并成一个SequenceFile文件（SequenceFile文件是Hadoop用来存储二进制形式的key-value对的文件格式），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。

原文件：

 源代码如下：

package inputformat;

import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.BytesWritable;
import org.apache.hadoop.io.Text;
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;

import java.io.IOException;

public class TextInputFormat extends FileInputFormat<Text, BytesWritable> {
    //保证文件不被切片
    @Override
    protected boolean isSplitable(JobContext context, Path filename) {
        return super.isSplitable(context, filename);
    }

    public RecordReader<Text, BytesWritable> createRecordReader(InputSplit inputSplit, TaskAttemptContext taskAttemptContext) throws IOException, InterruptedException {
       return new WholeFileRecordReader();
    }
}

　　

package inputformat;

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

import javax.xml.soap.Text;
import java.io.IOException;

public class WcDriver {
    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Job job =Job.getInstance(new Configuration());
        job.setJarByClass(WcDriver.class);
        job. setMapOutputKeyClass(Text.class);
        job. setMapOutputValueClass (BytesWritable.class);
        job. setOutputKeyClass(Text .class);
        job. setOutputValueClass ( BytesWritable.class);
        job. setInputFormatClass (TextInputFormat.class);
        FileInputFormat. setInputPaths(job, new Path("d:\input" ));
        FileOutputFormat. setOutputPath(job, new Path("d:\loutput"));
        boolean b=job.waitForCompletion(true);
        System.exit(b?0:1);
    }
}

　　

package inputformat;

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.Text;
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;

import java.io.IOException;
//自定义RR，处理一个文件，把文件直接都成kv值

public class WholeFileRecordReader extends RecordReader<Text, BytesWritable>{
    private boolean notRead=true;
    private Text key=new Text();
    private BytesWritable value=new BytesWritable();
    private FSDataInputStream inputStream;
    private FileSplit fs;

    //进行初始化
    public void initialize(InputSplit inputSplit, TaskAttemptContext taskAttemptContext) throws IOException, InterruptedException {
        //四局属于套路。转换切片类型为文件切片
        fs=(FileSplit)inputSplit;
        //通过切片获取路径
        Path path=fs.getPath();
        //通过路径获取文件系统
        FileSystem fileSystem=path.getFileSystem(taskAttemptContext.getConfiguration());
        //开流
        inputStream=fileSystem.open(path);

    }
    //尝试读取下一组kv值如果读到了返回true反之亦然
    public boolean nextKeyValue() throws IOException, InterruptedException {
        if(notRead)
        {
            //具体读文件的过程
            //首先是读key
            key.set(fs.getPath().toString());
            //读value
            byte[] buf=new byte[(int)fs.getLength()];
            inputStream.read(buf);
            value.set(buf,0,buf.length);
            notRead=false;
            return true;
        }
        else
        {
            return false;
        }
    }
    //获取当前读到的key
    public Text getCurrentKey() throws IOException, InterruptedException {
        return key;
    }
    //获取当前读到的value
    public BytesWritable getCurrentValue() throws IOException, InterruptedException {
        return value;
    }
    //读取其进度
    public float getProgress() throws IOException, InterruptedException {
        return notRead?0:1;
    }
    //关闭资源
    public void close() throws IOException {
        IOUtils.closeStream(inputStream);
    }
}