hadoop集群测试（单词计数）

Hadoop集群安装好后，可以测试hadoop的基本功能。hadoop自带了一个jar包（hadoop-examples-0.20.205.0.jar，不同版本最后不同）中wordcount程序可以测试统计单词的个数，先来体验一下再说。

[hadoop@master ~]$ mkdir input#先创建一个输入目录[hadoop@master ~]$ cd input/[hadoop@master input]$ echo "hello world">text1.txt#将要输入的文件放到该目录[hadoop@master input]$ echo "hello hadoop">text2.txt[hadoop@master input]$ lstext1.txt  text2.txt[hadoop@master input]$ cat text1.txt hello world[hadoop@master input]$ cat text2.txt hello hadoop[hadoop@master input]$ cd ..[hadoop@master ~]$ lsinput  log  公共的  模板  视频  图片  文档  下载  新文件~  音乐  桌面[hadoop@master ~]$ /usr/bin/hadoop dfs -put ./input in#将input目录中的两个文件放到hdfs中[hadoop@master ~]$ /usr/bin/hadoop dfs -ls ./in/*#查看hdfs中的两个文件-rw-r--r--   2 hadoop supergroup         12 2012-09-13 16:16 /user/hadoop/in/text1.txt-rw-r--r--   2 hadoop supergroup         13 2012-09-13 16:16 /user/hadoop/in/text2.txt#运行hadoop自带的一个jar包中的wordcount程序，这个程序统计单词的出现次数#程序的输入是in这个目录中的两个文件，结果输出到out目录[hadoop@master ~]$ /usr/bin/hadoop jar /usr/hadoop-examples-0.20.205.0.jar wordcount in out12/09/13 16:20:32 INFO input.FileInputFormat: Total input paths to process : 212/09/13 16:20:36 INFO mapred.JobClient: Running job: job_201209131425_000112/09/13 16:20:37 INFO mapred.JobClient:  map 0% reduce 0%12/09/13 16:23:38 INFO mapred.JobClient:  map 50% reduce 0%12/09/13 16:24:31 INFO mapred.JobClient:  map 100% reduce 16%12/09/13 16:24:40 INFO mapred.JobClient:  map 100% reduce 100%12/09/13 16:24:45 INFO mapred.JobClient: Job complete: job_201209131425_000112/09/13 16:24:45 INFO mapred.JobClient: Counters: 2912/09/13 16:24:45 INFO mapred.JobClient:   Job Counters 12/09/13 16:24:45 INFO mapred.JobClient:     Launched reduce tasks=112/09/13 16:24:45 INFO mapred.JobClient:     SLOTS_MILLIS_MAPS=23020512/09/13 16:24:45 INFO mapred.JobClient:     Total time spent by all reduces waiting after reserving slots (ms)=012/09/13 16:24:45 INFO mapred.JobClient:     Total time spent by all maps waiting after reserving slots (ms)=012/09/13 16:24:45 INFO mapred.JobClient:     Launched map tasks=312/09/13 16:24:45 INFO mapred.JobClient:     Data-local map tasks=312/09/13 16:24:45 INFO mapred.JobClient:     SLOTS_MILLIS_REDUCES=5866712/09/13 16:24:45 INFO mapred.JobClient:   File Output Format Counters 12/09/13 16:24:45 INFO mapred.JobClient:     Bytes Written=2512/09/13 16:24:45 INFO mapred.JobClient:   FileSystemCounters12/09/13 16:24:45 INFO mapred.JobClient:     FILE_BYTES_READ=5512/09/13 16:24:45 INFO mapred.JobClient:     HDFS_BYTES_READ=24112/09/13 16:24:45 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=6435412/09/13 16:24:45 INFO mapred.JobClient:     HDFS_BYTES_WRITTEN=2512/09/13 16:24:45 INFO mapred.JobClient:   File Input Format Counters 12/09/13 16:24:45 INFO mapred.JobClient:     Bytes Read=2512/09/13 16:24:45 INFO mapred.JobClient:   Map-Reduce Framework12/09/13 16:24:45 INFO mapred.JobClient:     Map output materialized bytes=6112/09/13 16:24:45 INFO mapred.JobClient:     Map input records=212/09/13 16:24:45 INFO mapred.JobClient:     Reduce shuffle bytes=6112/09/13 16:24:45 INFO mapred.JobClient:     Spilled Records=812/09/13 16:24:45 INFO mapred.JobClient:     Map output bytes=4112/09/13 16:24:45 INFO mapred.JobClient:     CPU time spent (ms)=1384012/09/13 16:24:45 INFO mapred.JobClient:     Total committed heap usage (bytes)=31936102412/09/13 16:24:45 INFO mapred.JobClient:     Combine input records=412/09/13 16:24:45 INFO mapred.JobClient:     SPLIT_RAW_BYTES=21612/09/13 16:24:45 INFO mapred.JobClient:     Reduce input records=412/09/13 16:24:45 INFO mapred.JobClient:     Reduce input groups=312/09/13 16:24:45 INFO mapred.JobClient:     Combine output records=412/09/13 16:24:45 INFO mapred.JobClient:     Physical memory (bytes) snapshot=32993280012/09/13 16:24:45 INFO mapred.JobClient:     Reduce output records=312/09/13 16:24:45 INFO mapred.JobClient:     Virtual memory (bytes) snapshot=113326080012/09/13 16:24:45 INFO mapred.JobClient:     Map output records=4#运行完成后，可以看到多了一个out目录，注意hdfs中没有当前目录的概念，也不能使用cd命令[hadoop@master ~]$ /usr/bin/hadoop dfs -lsFound 2 itemsdrwxr-xr-x   - hadoop supergroup          0 2012-09-13 16:16 /user/hadoop/indrwxr-xr-x   - hadoop supergroup          0 2012-09-13 16:24 /user/hadoop/out[hadoop@master ~]$ /usr/bin/hadoop dfs -ls ./out#进入到out目录Found 3 items-rw-r--r--   2 hadoop supergroup          0 2012-09-13 16:24 /user/hadoop/out/_SUCCESSdrwxr-xr-x   - hadoop supergroup          0 2012-09-13 16:20 /user/hadoop/out/_logs-rw-r--r--   2 hadoop supergroup         25 2012-09-13 16:24 /user/hadoop/out/part-r-00000[hadoop@master ~]$ /usr/bin/hadoop dfs -cat ./out/part-r-00000#查看结果hadoop1hello2world1[hadoop@master ~]$ 

对于一个需要时间很长的作业，我们可以通过浏览器查看作业的运行状态，通过访问master节点的50030端口（http://masterip:50030）可以查看master节点jobTracker的运行状态，访问master节点的50070端口可以查看集群dfs的信息。

截图如下：

JobTracker运行截图

dfs使用情况截图