[hadoop]Windows下eclipse导入hadoop源码，编译WordCount，打包jar

lgyx

　　hadoop版本为hadoop1.2.1
　　eclipse版本为eclipse-standard-kepler-SR2-win32-x86_64
　　WordCount.java为hadoop-1.2.1\src\examples\org\apache\hadoop\examples\WordCount.java





1 /**
2  *  Licensed under the Apache License, Version 2.0 (the "License");
3  *  you may not use this file except in compliance with the License.
4  *  You may obtain a copy of the License at
5  *
6  *      http://www.apache.org/licenses/LICENSE-2.0
7  *
8  *  Unless required by applicable law or agreed to in writing, software
9  *  distributed under the License is distributed on an "AS IS" BASIS,
10  *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
11  *  See the License for the specific language governing permissions and
12  *  limitations under the License.
13  */
14
15
16 package org.apache.hadoop.examples;
17
18 import java.io.IOException;
19 import java.util.StringTokenizer;
20
21 import org.apache.hadoop.conf.Configuration;
22 import org.apache.hadoop.fs.Path;
23 import org.apache.hadoop.io.IntWritable;
24 import org.apache.hadoop.io.Text;
25 import org.apache.hadoop.mapreduce.Job;
26 import org.apache.hadoop.mapreduce.Mapper;
27 import org.apache.hadoop.mapreduce.Reducer;
28 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
29 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
30 import org.apache.hadoop.util.GenericOptionsParser;
31
32 public class WordCount {
33
34   public static class TokenizerMapper
35        extends Mapper{
36     
37     private final static IntWritable one = new IntWritable(1);
38     private Text word = new Text();
39      
40     public void map(Object key, Text value, Context context
41                     ) throws IOException, InterruptedException {
42       StringTokenizer itr = new StringTokenizer(value.toString());
43       while (itr.hasMoreTokens()) {
44         word.set(itr.nextToken());
45         context.write(word, one);
46       }
47     }
48   }
49   
50   public static class IntSumReducer
51        extends Reducer {
52     private IntWritable result = new IntWritable();
53
54     public void reduce(Text key, Iterable values,
55                        Context context
56                        ) throws IOException, InterruptedException {
57       int sum = 0;
58       for (IntWritable val : values) {
59         sum += val.get();
60       }
61       result.set(sum);
62       context.write(key, result);
63     }
64   }
65
66   public static void main(String[] args) throws Exception {
67     Configuration conf = new Configuration();
68     String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
69     if (otherArgs.length != 2) {
70       System.err.println("Usage: wordcount  ");
71       System.exit(2);
72     }
73     Job job = new Job(conf, "word count");
74     job.setJarByClass(WordCount.class);
75     job.setMapperClass(TokenizerMapper.class);
76     job.setCombinerClass(IntSumReducer.class);
77     job.setReducerClass(IntSumReducer.class);
78     job.setOutputKeyClass(Text.class);
79     job.setOutputValueClass(IntWritable.class);
80     FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
81     FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
82     System.exit(job.waitForCompletion(true) ? 0 : 1);
83   }
84 }
View Code　　
　　在eclipse中新建java project，project名为WordCount
　　在project中新建class，类名为WordCount
　　再将上述代码覆盖eclipse中的WordCount.java
　　并将页首的package改了wordcount,改后的源码如下





1 package wordcount;
2
3 import java.io.IOException;
4 import java.util.StringTokenizer;
5
6 import org.apache.hadoop.conf.Configuration;
7 import org.apache.hadoop.fs.Path;
8 import org.apache.hadoop.io.IntWritable;
9 import org.apache.hadoop.io.Text;
10 import org.apache.hadoop.mapreduce.Job;
11 import org.apache.hadoop.mapreduce.Mapper;
12 import org.apache.hadoop.mapreduce.Reducer;
13 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
14 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
15 import org.apache.hadoop.util.GenericOptionsParser;
16
17 public class WordCount {
18
19   public static class TokenizerMapper
20        extends Mapper{
21     
22     private final static IntWritable one = new IntWritable(1);
23     private Text word = new Text();
24      
25     public void map(Object key, Text value, Context context
26                     ) throws IOException, InterruptedException {
27       StringTokenizer itr = new StringTokenizer(value.toString());
28       while (itr.hasMoreTokens()) {
29         word.set(itr.nextToken());
30         context.write(word, one);
31       }
32     }
33   }
34   
35   public static class IntSumReducer
36        extends Reducer {
37     private IntWritable result = new IntWritable();
38
39     public void reduce(Text key, Iterable values,
40                        Context context
41                        ) throws IOException, InterruptedException {
42       int sum = 0;
43       for (IntWritable val : values) {
44         sum += val.get();
45       }
46       result.set(sum);
47       context.write(key, result);
48     }
49   }
50
51   public static void main(String[] args) throws Exception {
52     Configuration conf = new Configuration();
53     String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
54     if (otherArgs.length != 2) {
55       System.err.println("Usage: wordcount  ");
56       System.exit(2);
57     }
58     Job job = new Job(conf, "word count");
59     job.setJarByClass(WordCount.class);
60     job.setMapperClass(TokenizerMapper.class);
61     job.setCombinerClass(IntSumReducer.class);
62     job.setReducerClass(IntSumReducer.class);
63     job.setOutputKeyClass(Text.class);
64     job.setOutputValueClass(IntWritable.class);
65     FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
66     FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
67     System.exit(job.waitForCompletion(true) ? 0 : 1);
68   
69   }
70 }
View Code　　



1 import org.apache.hadoop.conf.Configuration;
2 import org.apache.hadoop.fs.Path;
3 import org.apache.hadoop.io.IntWritable;
4 import org.apache.hadoop.io.Text;
5 import org.apache.hadoop.mapreduce.Job;
6 import org.apache.hadoop.mapreduce.Mapper;
7 import org.apache.hadoop.mapreduce.Reducer;
8 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
9 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
10 import org.apache.hadoop.util.GenericOptionsParser;
　　可以看到源码import了好几个hadoop自定义类，非JDK环境自带的类，所以需要把这些依赖包导入eclipse中，不然编译器如何能找到这些类呢，得明确让编译器知道这些类所在位置。
　　这时候编译并运行一下，会发现有如下错误



Exception in thread "main" java.lang.Error: Unresolved compilation problems:
The import org.apache.commons cannot be resolved
The import org.apache.commons cannot be resolved
The import org.codehaus cannot be resolved
The import org.codehaus cannot be resolved
Log cannot be resolved to a type
LogFactory cannot be resolved
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
Log cannot be resolved to a type
JsonFactory cannot be resolved to a type
JsonFactory cannot be resolved to a type
JsonGenerator cannot be resolved to a type
at org.apache.hadoop.conf.Configuration.(Configuration.java:60)
at wordcount.WordCount.main(WordCount.java:52)
　　原因是缺少依赖的jar库文件，再把缺少的jar库文件添加入库即可。
　　使用Add External JARs添加hadoop1.2.1\lib目录下所有jar文件。

　　再一次编译并运行，成功

　　 最后打包成为jar文件
　　file->export
　　

　　其中，WordCount.jar不是强求与类名相同，可以改为其他，譬如CountWord.jar,关系不大，然后点击Finish即可。
　　之后就可以在hadoop上运行了。运行WordCount详解可以参考Hadoop集群（第6期）_WordCount运行详解



1 hadoop jar WordCount.jar WordCount input output
　　注意上述代码中是没有



1 package org.apache.hadoop.examples;
　　倘若使用了package，那么jar文件中就有层次的，不再如hadoop jar WordCount.jar WordCount input output就可以运行了，需要详细指出WordCount（这个是主类的类名），运行命令改为



hadoop jar WordCount.jar org.apache.hadoop.examples.WordCount input output
　　关于这里打包的内容，在[hadoop]命令行编译并运行hadoop例子WordCount有讲述

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