首先确保Hadoop已正确安装及运行。

将WordCount.java拷贝出来

$ cp ./src/examples/org/apache/hadoop/examples/WordCount.java /home/hadoop/

在当前目录下创建一个存放WordCount.class的文件夹

$ mkdir class

编译WordCount.java

$ javac -classpath /usr/local/hadoop/hadoop-core-0.20.203.0.jar:/usr/local/hadoop/lib/commons-cli-1.2.jar WordCount.java -d class

编译完成后class文件夹下会出现一个org文件夹

$ ls class

org

对编译好的class打包

$ cd class

$ jar cvf WordCount.jar *

已添加清单

正在添加: org/(输入 = 0) (输出 = 0)(存储了 0%)

正在添加: org/apache/(输入 = 0) (输出 = 0)(存储了 0%)

正在添加: org/apache/hadoop/(输入 = 0) (输出 = 0)(存储了 0%)

正在添加: org/apache/hadoop/examples/(输入 = 0) (输出 = 0)(存储了 0%)

正在添加: org/apache/hadoop/examples/WordCount$TokenizerMapper.class(输入 = 1790) (输出 = 765)(压缩了 57%)

正在添加: org/apache/hadoop/examples/WordCount$IntSumReducer.class(输入 = 1793) (输出 = 746)(压缩了 58%)

正在添加: org/apache/hadoop/examples/WordCount.class(输入 = 1911) (输出 = 996)(压缩了 47%)

至此java文件的编译工作已经完成

准备测试文件，启动Hadoop。

由于运行Hadoop时指定的输入文件只能是HDFS文件系统里的文件，所以我们必须将要测试的文件从本地文件系统拷贝到HDFS文件系统中。

$ hadoop fs -mkdir input

$ hadoop fs -ls

Found 1 items

drwxr-xr-x   - hadoop supergroup          0 2014-03-26 10:39 /user/hadoop/input

$ hadoop fs -put file input

$ hadoop fs -ls input

Found 1 items

-rw-r--r--   2 hadoop supergroup         75 2014-03-26 10:40 /user/hadoop/input/file

运行程序

$ cd class

$ ls

org  WordCount.jar

$ hadoop jar WordCount.jar org.apache.hadoop.examples.WordCount input output

14/03/26 10:57:39 INFO input.FileInputFormat: Total input paths to process : 1

14/03/26 10:57:40 INFO mapred.JobClient: Running job: job_201403261015_0001

14/03/26 10:57:41 INFO mapred.JobClient:  map 0% reduce 0%

14/03/26 10:57:54 INFO mapred.JobClient:  map 100% reduce 0%

14/03/26 10:58:06 INFO mapred.JobClient:  map 100% reduce 100%

14/03/26 10:58:11 INFO mapred.JobClient: Job complete: job_201403261015_0001

14/03/26 10:58:11 INFO mapred.JobClient: Counters: 25

14/03/26 10:58:11 INFO mapred.JobClient:   Job Counters

14/03/26 10:58:11 INFO mapred.JobClient:     Launched reduce tasks=1

14/03/26 10:58:11 INFO mapred.JobClient:     SLOTS_MILLIS_MAPS=12321

14/03/26 10:58:11 INFO mapred.JobClient:     Total time spent by all reduces waiting after reserving slots (ms)=0

14/03/26 10:58:11 INFO mapred.JobClient:     Total time spent by all maps waiting after reserving slots (ms)=0

14/03/26 10:58:11 INFO mapred.JobClient:     Launched map tasks=1

14/03/26 10:58:11 INFO mapred.JobClient:     Data-local map tasks=1

14/03/26 10:58:11 INFO mapred.JobClient:     SLOTS_MILLIS_REDUCES=10303

14/03/26 10:58:11 INFO mapred.JobClient:   File Output Format Counters

14/03/26 10:58:11 INFO mapred.JobClient:     Bytes Written=51

14/03/26 10:58:11 INFO mapred.JobClient:   FileSystemCounters

14/03/26 10:58:11 INFO mapred.JobClient:     FILE_BYTES_READ=85

14/03/26 10:58:11 INFO mapred.JobClient:     HDFS_BYTES_READ=184

14/03/26 10:58:11 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=42541

14/03/26 10:58:11 INFO mapred.JobClient:     HDFS_BYTES_WRITTEN=51

14/03/26 10:58:11 INFO mapred.JobClient:   File Input Format Counters

14/03/26 10:58:11 INFO mapred.JobClient:     Bytes Read=75

14/03/26 10:58:11 INFO mapred.JobClient:   Map-Reduce Framework

14/03/26 10:58:11 INFO mapred.JobClient:     Reduce input groups=7

14/03/26 10:58:11 INFO mapred.JobClient:     Map output materialized bytes=85

14/03/26 10:58:11 INFO mapred.JobClient:     Combine output records=7

14/03/26 10:58:11 INFO mapred.JobClient:     Map input records=1

14/03/26 10:58:11 INFO mapred.JobClient:     Reduce shuffle bytes=0

14/03/26 10:58:11 INFO mapred.JobClient:     Reduce output records=7

14/03/26 10:58:11 INFO mapred.JobClient:     Spilled Records=14

14/03/26 10:58:11 INFO mapred.JobClient:     Map output bytes=131

14/03/26 10:58:11 INFO mapred.JobClient:     Combine input records=14

14/03/26 10:58:11 INFO mapred.JobClient:     Map output records=14

14/03/26 10:58:11 INFO mapred.JobClient:     SPLIT_RAW_BYTES=109

14/03/26 10:58:11 INFO mapred.JobClient:     Reduce input records=7

查看结果

$ hadoop fs -ls

Found 2 items

drwxr-xr-x   - hadoop supergroup          0 2014-03-26 10:40 /user/hadoop/input

drwxr-xr-x   - hadoop supergroup          0 2014-03-26 10:58 /user/hadoop/output

可以发现hadoop中多了一个output文件，查看output中的文件信息

$ hadoop fs -ls output

Found 3 items

-rw-r--r--   2 hadoop supergroup          0 2014-03-26 11:04 /user/hadoop/output/_SUCCESS

drwxr-xr-x   - hadoop supergroup          0 2014-03-26 11:04 /user/hadoop/output/_logs

-rw-r--r--   2 hadoop supergroup         65 2014-03-26 11:04 /user/hadoop/output/part-r-00000

查看运行结果

$ hadoop fs -cat output/part-r-00000

Bye	3

Hello	3

Word	1

World	3

bye	1

hello	2

world	1

至此，Hadoop下WordCount示例运行结束。

如果还想运行一遍就需要把output文件夹删除，否则会报异常，如下

14/03/26 11:41:30 INFO mapred.JobClient: Cleaning up the staging area hdfs://localhost:9000/tmp/hadoop-hadoop/mapred/staging/hadoop/.staging/job_201403261015_0003

Exception in thread "main" org.apache.hadoop.mapred.FileAlreadyExistsException: Output directory output already exists

	at org.apache.hadoop.mapreduce.lib.output.FileOutputFormat.checkOutputSpecs(FileOutputFormat.java:134)

	at org.apache.hadoop.mapred.JobClient$2.run(JobClient.java:830)

	at org.apache.hadoop.mapred.JobClient$2.run(JobClient.java:791)

	at java.security.AccessController.doPrivileged(Native Method)

	at javax.security.auth.Subject.doAs(Subject.java:415)

	at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1059)

	at org.apache.hadoop.mapred.JobClient.submitJobInternal(JobClient.java:791)

	at org.apache.hadoop.mapreduce.Job.submit(Job.java:465)

	at org.apache.hadoop.mapreduce.Job.waitForCompletion(Job.java:494)

	at org.apache.hadoop.examples.WordCount.main(WordCount.java:67)

	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)

	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)

	at java.lang.reflect.Method.invoke(Method.java:601)

	at org.apache.hadoop.util.RunJar.main(RunJar.java:156)

删除output文件夹操作如下

$ hadoop fs -rmr output

Deleted hdfs://localhost:9000/user/hadoop/output

也可以直接运行Hadoop示例中已经编译过的jar文件

$ hadoop jar /usr/local/hadoop/hadoop-examples-0.20.203.0.jar wordcount input output

14/03/28 17:02:33 INFO input.FileInputFormat: Total input paths to process : 2

14/03/28 17:02:33 INFO mapred.JobClient: Running job: job_201403281439_0004

14/03/28 17:02:34 INFO mapred.JobClient:  map 0% reduce 0%

14/03/28 17:02:49 INFO mapred.JobClient:  map 100% reduce 0%

14/03/28 17:03:01 INFO mapred.JobClient:  map 100% reduce 100%

14/03/28 17:03:06 INFO mapred.JobClient: Job complete: job_201403281439_0004

14/03/28 17:03:06 INFO mapred.JobClient: Counters: 25

14/03/28 17:03:06 INFO mapred.JobClient:   Job Counters

14/03/28 17:03:06 INFO mapred.JobClient:     Launched reduce tasks=1

14/03/28 17:03:06 INFO mapred.JobClient:     SLOTS_MILLIS_MAPS=17219

14/03/28 17:03:06 INFO mapred.JobClient:     Total time spent by all reduces waiting after reserving slots (ms)=0

14/03/28 17:03:06 INFO mapred.JobClient:     Total time spent by all maps waiting after reserving slots (ms)=0

14/03/28 17:03:06 INFO mapred.JobClient:     Launched map tasks=2

14/03/28 17:03:06 INFO mapred.JobClient:     Data-local map tasks=2

14/03/28 17:03:06 INFO mapred.JobClient:     SLOTS_MILLIS_REDUCES=10398

14/03/28 17:03:06 INFO mapred.JobClient:   File Output Format Counters

14/03/28 17:03:06 INFO mapred.JobClient:     Bytes Written=65

14/03/28 17:03:06 INFO mapred.JobClient:   FileSystemCounters

14/03/28 17:03:06 INFO mapred.JobClient:     FILE_BYTES_READ=131

14/03/28 17:03:06 INFO mapred.JobClient:     HDFS_BYTES_READ=343

14/03/28 17:03:06 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=63840

14/03/28 17:03:06 INFO mapred.JobClient:     HDFS_BYTES_WRITTEN=65

14/03/28 17:03:06 INFO mapred.JobClient:   File Input Format Counters

14/03/28 17:03:06 INFO mapred.JobClient:     Bytes Read=124

14/03/28 17:03:06 INFO mapred.JobClient:   Map-Reduce Framework

14/03/28 17:03:06 INFO mapred.JobClient:     Reduce input groups=9

14/03/28 17:03:06 INFO mapred.JobClient:     Map output materialized bytes=137

14/03/28 17:03:06 INFO mapred.JobClient:     Combine output records=11

14/03/28 17:03:06 INFO mapred.JobClient:     Map input records=2

14/03/28 17:03:06 INFO mapred.JobClient:     Reduce shuffle bytes=85

14/03/28 17:03:06 INFO mapred.JobClient:     Reduce output records=9

14/03/28 17:03:06 INFO mapred.JobClient:     Spilled Records=22

14/03/28 17:03:06 INFO mapred.JobClient:     Map output bytes=216

14/03/28 17:03:06 INFO mapred.JobClient:     Combine input records=23

14/03/28 17:03:06 INFO mapred.JobClient:     Map output records=23

14/03/28 17:03:06 INFO mapred.JobClient:     SPLIT_RAW_BYTES=219

14/03/28 17:03:06 INFO mapred.JobClient:     Reduce input records=11

参考资料：http://www.cnblogs.com/aukle/p/3214984.html

http://blog.csdn.net/turkeyzhou/article/details/8121601

http://www.cnblogs.com/xia520pi/archive/2012/05/16/2504205.html

最新文章

  1. html
  2. mysqldump: Error: Binlogging on server not active
  3. C#使用 DirectX SDK 9做视频播放器 并在视频画线添加文字 VMR9
  4. Spring1：Spring简介、环境搭建、源码下载及导入MyEclipse
  5. linux查看java jdk安装路径和设置环境变量
  6. 用Photoshop处理图片使背景透明
  7. C++学习20 虚基类详解
  8. nagios为监控图像添加图片
  9. 原生JS取代一些JQuery方法
  10. Array--Good parts
  11. Linux(CentOs)下安装Phantomjs + Casperjs
  12. HDU-4115 Eliminate the Conflict 2sat
  13. <%@ include file=” ”%> ——最简洁易懂的解释
  14. 生成二维码的js以及调用打印插件
  15. 把玩爬虫框架Gecco
  16. Spring获取bean的步骤
  17. nginx比apache处理静态文件速度快，但是nginx处理大量并发的php请求时，容易出现502错误，频率大概是多少
  18. 日志系统的 ELK 的搭建
  19. setDaemon 守护线程
  20. Html5 手机端网页

热门文章

  1. TV
  2. material-dialogs
  3. sed命令查找<media/msm_cam_sensor.h>替换为"len_msm_cam_sensor.h"
  4. 空间的配置和释放 std::alloc
  5. LibSVM学习（四）——逐步深入LibSVM 转
  6. Java_InvokeAll_又返回值_多个线程同时执行，取消超时线程
  7. Laravel 5.1中 Redis 的安装配置及基本使用教程
  8. linux下使用find xargs grep查找文件及文件内容
  9. 有符号的范围,-128~+127详解（zt）
  10. Old Calculator