hadoop jar 提示 Not a valid JAR

解决Hadoop环境下运行WordCount程序的问题

最新推荐文章于 2022-02-20 18:30:21 发布

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本文解决了一个在Hadoop环境下使用WordCount程序时出现的错误：使用了错误的JAR包路径，导致执行失败。通过更正输入和输出目录参数，成功解决了问题并实现了程序在Hadoop集群上的正确运行。

. 编译 WordCount.java
2. 打成 WordCount.jar包上传的hdfs。。
3. hadoop jar WordCount.jar ***.**.MainClass /**/input /***/output

问题一直提示 Not a valid JAR: /usr/***/***/wordcount.jar

问题是：执行jar包的时候应该是用本地jar包，而不是hdfs上的，所以写出hdfs路径是不对的

下面是代码

package com.gilang.hadoop.wordcount;

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

import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileInputFormat;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.Mapper;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.TextInputFormat;
import org.apache.hadoop.mapred.TextOutputFormat;

public class WordCount {

	public static class Map extends MapReduceBase implements
			Mapper<LongWritable, Text, Text, IntWritable> {
		private final static IntWritable one = new IntWritable(1);
		private Text word = new Text();

		public void map(LongWritable key, Text value,
				OutputCollector<Text, IntWritable> output, Reporter reporter)
				throws IOException {
			String line = value.toString();
			StringTokenizer tokenizer = new StringTokenizer(line);
			while (tokenizer.hasMoreTokens()) {
				word.set(tokenizer.nextToken());
				output.collect(word, one);
			}
		}
	}

	public static class Reduce extends MapReduceBase implements
			Reducer<Text, IntWritable, Text, IntWritable> {
		public void reduce(Text key, Iterator<IntWritable> values,
				OutputCollector<Text, IntWritable> output, Reporter reporter)
				throws IOException {
			
			int sum = 0;
			while (values.hasNext()) {
				sum += values.next().get();
			}
			output.collect(key, new IntWritable(sum));
		}
	}

	public static void main(String[] args) throws Exception {
		
		System.out.println("-------------------------"+args.length);
		/*if (args.length != 2) {
			System.err
					.println("Usage: WordCount <input path> <output path>");
			System.exit(-1);
		}*/
		System.out.println("-------------------------");
		JobConf conf = new JobConf(WordCount.class);
		conf.setJobName("wordcount");

		conf.setOutputKeyClass(Text.class);
		conf.setOutputValueClass(IntWritable.class);
		
		conf.setMapperClass(Map.class);
		conf.setCombinerClass(Reduce.class);
		conf.setReducerClass(Reduce.class);
		
		conf.setInputFormat(TextInputFormat.class);
		conf.setOutputFormat(TextOutputFormat.class);
		
		System.out.println(args[0]+"|"+args[1]+"|"+args[2]);
		FileInputFormat.setInputPaths(conf, new Path(args[1]));
		FileOutputFormat.setOutputPath(conf, new Path(args[2]));
		
		JobClient.runJob(conf);
	}

}

当时在后面的两个输入目录参数和输出目录的参数上犯错了，，确定好args下标的位置

输出目录也就是我的那个 wordcount 目录下不能有 output目录，MapReduce 会抛文件已存在异常

我执行的命令: ./hadoop jar /home/long/Desktop/wordcount.jar com.gilang.hadoop.wordcount.WordCount /user/hadoop/wordcount/input /user/hadoop/wordcount/output