【Hadoop】5.MapReduce框架原理-自定义InputFormat

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说明

自定义InputFormat一般应用于hadoop自带的InputFormat类型不能满足某个应用场景中，需要我们自定义来解决

自定义步骤

自定义Inputformat步骤如下：

1. 自定义一个类继承InputFormat
2. 改写RecordReader，实现一次读取一个完成的文件封装为KV
3. 在输出时使用SequenceFileOutPutFormat输出合并文件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里面存储着很多小文件，存储的形式为文件路径+名称为key，文件内容为value）。

示例操作

步骤：

1. 自定义一个类继承FileInputFormat
   a. 重写isSpliable()方法，返回false 设置为文件不可分割
   b. 重写createRecordReader()，创建自定义的RecordReader对象，并初始化
2. 改写RecordReader，实现一次读取一个完整的文件封装成为KV
   a. 采用IO流一次读取一个文件输出到value中，因为设置了不可分割所以整个文件都封装到了value中
   b. 获取文件路径信息+名称作为key
3. 设置Driver
   a.

代码：

CustomerInputFormate自定义InputFormat

package com.xing.MapReduce.InputFormatSequenceFile;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;/***  自定义InputFormat*/
public class CustomerInputFormate extends FileInputFormat<Text,BytesWritable> {/***  新建自定义的RecordReader* @param inputSplit* @param taskAttemptContext* @return* @throws IOException* @throws InterruptedException*/public RecordReader<Text, BytesWritable> createRecordReader(InputSplit inputSplit, TaskAttemptContext taskAttemptContext) throws IOException, InterruptedException {CustomerRecordReader reader = new CustomerRecordReader();reader.initialize(inputSplit,taskAttemptContext );return reader;}/***  设置为不可分割* @param context* @param filename* @return*/@Overrideprotected boolean isSplitable(JobContext context, Path filename) {return false;}
}

CustomerRecordReader 自定义RecordReader

package com.xing.MapReduce.InputFormatSequenceFile;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.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RecordReader*/
public class CustomerRecordReader extends RecordReader<Text, BytesWritable> {// 分片信息FileSplit split;Configuration configuration;Text k = new Text();BytesWritable v = new BytesWritable();boolean isProgress = true;//初始化方法public void initialize(InputSplit inputSplit, TaskAttemptContext taskAttemptContext) throws IOException, InterruptedException {this.split = (FileSplit) inputSplit;this.configuration = taskAttemptContext.getConfiguration();}//核心业务处理(对key和value的封装)public boolean nextKeyValue() throws IOException, InterruptedException {if (isProgress){//1. 获取fsPath path = split.getPath();System.out.println("@@@@@@@@@@@@@@@@"+split.getLength());System.out.println("$$$$$$$$$$$$$$$$"+split);FileSystem fileSystem = path.getFileSystem(configuration);//2. 获取输入流FSDataInputStream fis = fileSystem.open(path);//3. 拷贝byte[] bytes = new byte[(int) split.getLength()];IOUtils.readFully(fis, bytes,0 ,bytes.length);//4. 填充k-vv.set(bytes,0 ,bytes.length);k.set(path.toString());//5. 收尾IOUtils.closeStream(fis);isProgress = false;return true;}return false;}// 获取kay值public Text getCurrentKey() throws IOException, InterruptedException {return k;}// 获取value值public BytesWritable getCurrentValue() throws IOException, InterruptedException {return v;}public float getProgress() throws IOException, InterruptedException {return 0;}public void close() throws IOException {}
}

SequenceFileMapper

package com.xing.MapReduce.InputFormatSequenceFile;import org.apache.hadoop.io.BytesWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;import java.io.IOException;public class SequenceFileMapper extends Mapper<Text,BytesWritable,Text,BytesWritable> {@Overrideprotected void map(Text key, BytesWritable value, Context context) throws IOException, InterruptedException {// 直接输出 这里的key就是文件路径信息 value就是文本内容context.write(key,value );}}

SequenceFileReducer

package com.xing.MapReduce.InputFormatSequenceFile;import org.apache.hadoop.io.BytesWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;import java.io.IOException;public class SequenceFileReducer extends Reducer<Text,BytesWritable,Text,BytesWritable> {@Overrideprotected void reduce(Text key, Iterable<BytesWritable> values, Context context) throws IOException, InterruptedException {// 就是简单的输出内容for (BytesWritable value : values) {context.write(key,value);}}
}

SequenceFileDriver

package com.xing.MapReduce.InputFormatSequenceFile;import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
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;import java.io.IOException;public class SequenceFileDriver {public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {// 获取configuration和FileSystemConfiguration configuration = new Configuration();FileSystem fs = FileSystem.get(configuration);// 设置job的名字和jar包Job job = Job.getInstance(configuration);job.setJobName("SequenceFileDriver");job.setJarByClass(SequenceFileDriver.class);// 设置job的mapper和reduce的处理类名job.setMapperClass(SequenceFileMapper.class);job.setReducerClass(SequenceFileReducer.class);// 设置输入类型和输出类型job.setInputFormatClass(CustomerInputFormate.class);job.setOutputFormatClass(SequenceFileOutputFormat.class);// 设置输出的key和输出的value类型job.setOutputKeyClass(Text.class);job.setOutputValueClass(BytesWritable.class);// 判断输出地址是否存在if (fs.exists(new Path("E:\\hdfs\\output1"))){fs.delete(new Path("E:\\hdfs\\output1"),true );}// 设置输入和输出的文件路径FileInputFormat.setInputPaths(job,new Path("E:\\hdfs\\input"));FileOutputFormat.setOutputPath(job,new Path("E:\\hdfs\\output1"));// 返回结果boolean b = job.waitForCompletion(true);System.exit(b ? 0 : -1);}
}

输入和输出

输入：

输出：

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