Linux下编译java并生成jar包

下面是WordCount.java类
  1. package com.ll;
  3. import java.io.IOException;
  4. import java.util.Iterator;
  5. import java.util.StringTokenizer;
  7. import org.apache.hadoop.fs.Path;
  8. import org.apache.hadoop.io.IntWritable;
  9. import org.apache.hadoop.io.LongWritable;
  10. import org.apache.hadoop.io.Text;
  11. import org.apache.hadoop.mapred.FileInputFormat;
  12. import org.apache.hadoop.mapred.FileOutputFormat;
  13. import org.apache.hadoop.mapred.JobClient;
  14. import org.apache.hadoop.mapred.JobConf;
  15. import org.apache.hadoop.mapred.MapReduceBase;
  16. import org.apache.hadoop.mapred.Mapper;
  17. import org.apache.hadoop.mapred.OutputCollector;
  18. import org.apache.hadoop.mapred.Reducer;
  19. import org.apache.hadoop.mapred.Reporter;
  20. import org.apache.hadoop.mapred.TextInputFormat;
  21. import org.apache.hadoop.mapred.TextOutputFormat;
  23. public class WordCount {
  25. 	public static class Map extends MapReduceBase implements
  26. 			Mapper<LongWritable, Text, Text, IntWritable> {
  27. 		private final static IntWritable one = new IntWritable(1);
  28. 		private Text word = new Text();
  30. 		public void map(LongWritable key, Text value,
  31. 				OutputCollector<Text, IntWritable> output, Reporter reporter)
  32. 				throws IOException {
  33. 			String line = value.toString();
  34. 			StringTokenizer tokenizer = new StringTokenizer(line);
  35. 			while (tokenizer.hasMoreTokens()) {
  36. 				word.set(tokenizer.nextToken());
  37. 				output.collect(word, one);
  38. 			}
  39. 		}
  40. 	}
  42. 	public static class Reduce extends MapReduceBase implements
  43. 			Reducer<Text, IntWritable, Text, IntWritable> {
  44. 		public void reduce(Text key, Iterator<IntWritable> values,
  45. 				OutputCollector<Text, IntWritable> output, Reporter reporter)
  46. 				throws IOException {
  47. 			int sum = 0;
  48. 			while (values.hasNext()) {
  49. 				sum += values.next().get();
  50. 			}
  51. 			output.collect(key, new IntWritable(sum));
  52. 		}
  53. 	}
  55. 	public static void main(String[] args) throws Exception {
  56. 		JobConf conf = new JobConf(WordCount.class);
  57. 		conf.setJobName("wordcount");
  59. 		conf.setOutputKeyClass(Text.class);
  60. 		conf.setOutputValueClass(IntWritable.class);
  62. 		conf.setMapperClass(Map.class);
  63. 		conf.setCombinerClass(Reduce.class);
  64. 		conf.setReducerClass(Reduce.class);
  66. 		conf.setInputFormat(TextInputFormat.class);
  67. 		conf.setOutputFormat(TextOutputFormat.class);
  69. 		FileInputFormat.setInputPaths(conf, new Path(args[0]));
  70. 		FileOutputFormat.setOutputPath(conf, new Path(args[1]));
  72. 		JobClient.runJob(conf);
  73. 	}
  74. }
使用Linux命令行编译java代码，并生成jar包
  1. mkdir wordcount_classes 
  2. javac -classpath ${HADOOP_HOME}/hadoop-${HADOOP_VERSION}-core.jar -d wordcount_classes/ WordCount.java 
  3. jar -cvf /usr/joe/wordcount121.jar -C wordcount_classes/ .
说明：
  • javac ：用于编译java--->class文件；
  • -classpath：后面指定依赖的jara包存储的位置；
  • -d：指定输出目录；







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原文地址：https://www.cnblogs.com/ssslinppp/p/5942729.html