myeclipse 安裝hadoop插件及開發MapReduce

windows上安裝 hadoop （不使用Cygwin）

ubuntu上安裝 hadoop

工具及軟件

1. myeclipse 10.8

2. hadoop2.6.0 插件點我下載

1. 將插件放入myeclipse的目錄MyEclipse\MyEclipse 10\dropins

2. 如有必要，刪除configuration目錄下的org.eclipse.update文件夾

3. 第一次啓動eclpse後，會讓我們設定一個工作目錄，即以後建的項目都在這個工作目錄下。

進入後，在菜單window->Rreferences下打開設置：

點擊browse選擇hadoop目錄，然後點OK

4. 打開myeclipse在window>>show view >>會出現MapReduce Tools>>Map/Reduce Locations 打開

配置hadoop運行環境

在eclipse下配置hadoop location的時候。hadoop端口號應該與conf文件夾下的core-site.xml以及mapred-site.xml保持一致，前者對應dfs master，後者對應map-red master

在配置完後，在Project Explorer中就可以瀏覽到DFS中的文件

編寫第一個MR程序(統計單詞數量)

在eclipse菜單下 new Project 可以看到，裏面增加了Map/Reduce選項：

新建一個Map/Reduce

新建一個類 WordCount.java

代碼如下

import java.io.IOException;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
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 org.apache.hadoop.util.GenericOptionsParser;

public class WordCount {

	public static class TokenizerMapper extends
			Mapper<Object, Text, Text, IntWritable> {
		private final static IntWritable one = new IntWritable(1);
		private Text word = new Text();

		public void map(Object key, Text value, Context context)
				throws IOException, InterruptedException {
			System.out.println("key=" + key.toString());
			System.out.println("Value=" + value.toString());
			StringTokenizer itr = new StringTokenizer(value.toString());
			while (itr.hasMoreTokens()) {
				word.set(itr.nextToken());
				context.write(word, one);
			}
		}
	}

	public static class IntSumReducer extends
			Reducer<Text, IntWritable, Text, IntWritable> {
		private IntWritable result = new IntWritable();

		public void reduce(Text key, Iterable<IntWritable> values,
				Context context) throws IOException, InterruptedException {
			int sum = 0;
			for (IntWritable val : values) {
				sum += val.get();
			}
			result.set(sum);
			context.write(key, result);
		}
	}

	public static void main(String[] args) throws Exception {
		Configuration conf = new Configuration();
		System.out.println("url:" + conf.get("fs.default.name"));
		String[] otherArgs = new GenericOptionsParser(conf, args)
				.getRemainingArgs();
		if (otherArgs.length != 2) {
			System.err.println("Usage: wordcount <in> <out>");
			System.exit(2);
		}
		Job job = new Job(conf, "word count");
		job.setJarByClass(WordCount.class);
		job.setMapperClass(TokenizerMapper.class);
		job.setCombinerClass(IntSumReducer.class);
		job.setReducerClass(IntSumReducer.class);
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(IntWritable.class);
		FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
		FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
		System.exit(job.waitForCompletion(true) ? 0 : 1);
	}

}

接下來直接在 myeclipse中運行。 Run on Hadoop

如果報錯如

(null) entry in command string: null chmod 0700

需要把 hadoop\bin 下的hadoop.dll拷貝到 c:\windows\system32目錄中

以上的WordCount運行還需要設置運行時參數，輸入文件夾和輸出文件夾

Run Configuration

首先創建 wcin 目錄並且上傳多個 .txt 的碎文件到 wcin目錄下

F:\study\hadoop\hadoop-2.6.5\sbin>hadoop fs -mkdir hdfs://localhost:9002/wcin

F:\study\hadoop\hadoop-2.6.5\sbin>hadoop fs -put c:\a.txt hdfs://localhost:9002/
wcin/wc.txt

wcout目錄不用創建了，運行輸出後自動創建

看圖結果