重寫Writable介面

如下程式碼就是自定義mr資料型別，在wordcount類使用它。

WordCountWritable

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import org.apache.hadoop.io.Writable;


/**
 * 自定義wc的資料型別：
 * @author lyd
 */
public class WordCountWritable implements Writable{
	public String word;
	public int counter;
	
	public WordCountWritable(){
	}
	
	public WordCountWritable(String word, int counter) {
		this.word = word;
		this.counter = counter;
	}

	/**
	 * 寫
	 */
	@Override
	public void write(DataOutput out) throws IOException {
		out.writeUTF(word);
		out.writeInt(counter);
	}

	/**
	 * 讀
	 */
	@Override
	public void readFields(DataInput in) throws IOException {
		this.word = in.readUTF();
		this.counter = in.readInt();
	}

	/**
	 * @return the word
	 */
	public String getWord() {
		return word;
	}

	/**
	 * @param word the word to set
	 */
	public void setWord(String word) {
		this.word = word;
	}

	/**
	 * @return the counter
	 */
	public int getCounter() {
		return counter;
	}

	/**
	 * @param counter the counter to set
	 */
	public void setCounter(int counter) {
		this.counter = counter;
	}

	/* (non-Javadoc)
	 * @see java.lang.Object#toString()
	 */
	@Override
	public String toString() {
		return word + ":" + counter;
	}
}
 

WordCount

import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

import edu.qianfeng.mr.day01.WordCountWritable;

public class WordCount {
public static class MyMapper extends Mapper<LongWritable, Text, Text, IntWritable>{
	
	Text word = new Text();
	IntWritable one = new IntWritable(1);
	
	@Override
	protected void map(LongWritable key, Text value,Context context)
			throws IOException, InterruptedException {
		//獲取行資料
		String line = value.toString();
		//對資料進行拆分   [hello,qianfeng,hi,qianfeng] [hello,1603] [hi,hadoop,hi,spark]
		String []  words = line.split(" ");
		//迴圈陣列
		for (String s : words) {
			word.set(s);
			context.write(word, one);
		}
		
	}
}

/**
 * 自定義reducer類
 * @author lyd
 *
 */
public static class MyReducer extends Reducer<Text, IntWritable, WordCountWritable, NullWritable>{
	
	@Override
	protected void reduce(Text key, Iterable<IntWritable> value,Context context)
			throws IOException, InterruptedException {
		//定義一個計數器
		int counter = 0;
		//迴圈奇數
		for (IntWritable i : value) {
			counter += i.get();
		}
		//建立資料型別物件
		WordCountWritable wc = new WordCountWritable(key.toString(), counter);
		//reduce階段的最終輸出
		context.write(wc, null);
	}
}

/**
 * job的主入口
 * @param args
 */
public static void main(String[] args) {
	
	try {
		//獲取配置物件
		Configuration conf = new Configuration();
		//建立job
		Job job = new Job(conf, "wordcount");
		//為job設定執行主類
		job.setJarByClass(WordCount.class);
		
		//設定map階段的屬性
		job.setMapperClass(MyMapper.class);
		job.setMapOutputKeyClass(Text.class);
		job.setMapOutputValueClass(IntWritable.class);
		FileInputFormat.addInputPath(job, new Path(args[0]));
		
		
		//設定reduce階段的屬性
		job.setReducerClass(MyReducer.class);
		job.setOutputKeyClass(WordCountWritable.class);
		job.setOutputValueClass(NullWritable.class);
		FileOutputFormat.setOutputPath(job, new Path(args[1]));
		
		//提交執行作業job 並列印資訊
		int isok = job.waitForCompletion(true)?0:1;
		//退出job
		System.exit(isok);
		
	} catch (IOException | ClassNotFoundException | InterruptedException e) {
		e.printStackTrace();
	}
	}
}