Eclipse实现Hadoop WordCount

最新推荐文章于 2023-04-17 22:10:31 发布

原创最新推荐文章于 2023-04-17 22:10:31 发布 · 1k 阅读

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#hadoop #eclipse #wordcount

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本文指导如何在Eclipse中配置Hadoop环境，包括安装hadoop-eclipse-plugin，设置Hadoop路径，创建Map/Reduce项目，编写WordCount程序，并解释如何验证配置是否正确。

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首先，安装eclipse，下载 hadoop-eclipse-plugin， https://github.com/winghc/hadoop2x-eclipse-plugin，将下载好的jar包放到eclipse安装目录的plugin文件夹里面，重启eclipse

其次，在mac下eclipse的preference在菜单栏Eclipse->偏好设置（preference），打开选择Hadoop Map/Reduce，browse选择hadoop的安装目录，点击ok

第三，在菜单栏选择window->open perspective->others->Map/Reduce，在eclipse右下找到Map/Reduce Location，右键new hadoop location，name为MapReduce Location，DFS Master Port为9000

第四，创建 Map/Reduce Project，命名为WordCount，其他设置默认，New class 名称为WordCount，package为org.apache.hadoop.examples

第五，将之前（Hadoop系列之前的文章）配置好的core-site.xml、hdfs-site.xml、log4j.properties放到src文件夹下

第六，编辑代码如下

public class WordCount {
	
	public static class TokenizerMapper 
	extends Mapper<Object, Text, Text, IntWritable>{
	
		//like java's Integer
		private final static IntWritable one = new IntWritable(1);
		//like java's String
		private Text word = new Text();
		public void map(Object key, Text value, Context context
				) throws IOException, InterruptedException {
			//whether has fengefu(token) or not
			StringTokenizer itr = new StringTokenizer(value.toString());
			while (itr.hasMoreTokens()) {
				word.set(itr.nextToken());
				//record when the word appears in pair
				 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) {
	   //add up all the only word that appear. When it appears, there is a "one"
     sum += val.get();
   }
   result.set(sum);
   context.write(key, result);
 }
}

public static void main(String[] args) throws Exception {
 Configuration conf = new Configuration();
 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);
}
}

第七，选择菜单栏run configurations，在Arguments中输入args[0],args[1]的路径，如果有建立好hadoop的路径（如之前文章所述，可以直接写input output），当然也可以写自己的路径。

当然也可以在终端用bin/hadoop fs -ls 查看路径是否存在，文件是否存在