[Hadoop培训笔记]03-MapReduce集群的安装与部署

注：开源力量Hadoop Development网络培训，链接：http://new.osforce.cn/course/52  个人笔记，不具参考性。

说明：
1）实验采用的是hadoop1.x，hadoop2.x的代码做一个分析
2）学习hadoop的基础知识；java基础；Linux操作基础

MapRedcue集群环境搭建
MapReduce WordCount运行
Hadoop Eclipse插件

bin目录下执行：./start-mapred.sh，启动jobtracker和tasktracker
问题：启动后使用jps命令，看不到上述tracker在运行。
原因：通过logs目录里的hadoop-michaelchen-tasktracker-mars.clustertech.com.log，查看后发现这么一条：Can not start task tracker because java.lang.IllegalArgumentException: Does not contain a valid host:port authority: local
解决方法：没有配置 mapred-site.xml，配置如下。再次启动，使用jps可以看到jobtracker和tasktracker

<property> <name>mapred.job.tracker</name> <value>localhost:9101</value> </property>

bin目录下创建 vim a.txt，里面写一些单词作为输入文件。

  1 hello world  2 hello java  3 java c++

然后将a.txt放入一个创建的input目录里，让hadoop example中的wordcount程序执行，从input目录里获取数据，结果放到output目录里

./hadoop fs -mkdir /input./hadoop fs -put a.txt /input./hadoop jar ../hadoop-examples-1.2.1.jar wordcount /input /output

执行的过程比较有趣，所以也贴到这里

13/12/04 12:23:07 INFO input.FileInputFormat: Total input paths to process : 113/12/04 12:23:07 INFO util.NativeCodeLoader: Loaded the native-hadoop library13/12/04 12:23:07 WARN snappy.LoadSnappy: Snappy native library not loaded13/12/04 12:23:08 INFO mapred.JobClient: Running job: job_201312041206_000113/12/04 12:23:09 INFO mapred.JobClient:  map 0% reduce 0%13/12/04 12:23:22 INFO mapred.JobClient:  map 100% reduce 0%13/12/04 12:23:34 INFO mapred.JobClient:  map 100% reduce 100%13/12/04 12:23:38 INFO mapred.JobClient: Job complete: job_201312041206_000113/12/04 12:23:38 INFO mapred.JobClient: Counters: 2913/12/04 12:23:38 INFO mapred.JobClient:   Job Counters13/12/04 12:23:38 INFO mapred.JobClient:     Launched reduce tasks=113/12/04 12:23:38 INFO mapred.JobClient:     SLOTS_MILLIS_MAPS=1419913/12/04 12:23:38 INFO mapred.JobClient:     Total time spent by all reduces waiting after reserving slots (ms)=013/12/04 12:23:38 INFO mapred.JobClient:     Total time spent by all maps waiting after reserving slots (ms)=013/12/04 12:23:38 INFO mapred.JobClient:     Launched map tasks=113/12/04 12:23:38 INFO mapred.JobClient:     Data-local map tasks=113/12/04 12:23:38 INFO mapred.JobClient:     SLOTS_MILLIS_REDUCES=1216813/12/04 12:23:38 INFO mapred.JobClient:   File Output Format Counters13/12/04 12:23:38 INFO mapred.JobClient:     Bytes Written=2913/12/04 12:23:38 INFO mapred.JobClient:   FileSystemCounters13/12/04 12:23:38 INFO mapred.JobClient:     FILE_BYTES_READ=5113/12/04 12:23:38 INFO mapred.JobClient:     HDFS_BYTES_READ=13413/12/04 12:23:38 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=11731313/12/04 12:23:38 INFO mapred.JobClient:     HDFS_BYTES_WRITTEN=2913/12/04 12:23:38 INFO mapred.JobClient:   File Input Format Counters13/12/04 12:23:38 INFO mapred.JobClient:     Bytes Read=3213/12/04 12:23:38 INFO mapred.JobClient:   Map-Reduce Framework13/12/04 12:23:38 INFO mapred.JobClient:     Map output materialized bytes=5113/12/04 12:23:38 INFO mapred.JobClient:     Map input records=313/12/04 12:23:38 INFO mapred.JobClient:     Reduce shuffle bytes=5113/12/04 12:23:38 INFO mapred.JobClient:     Spilled Records=813/12/04 12:23:38 INFO mapred.JobClient:     Map output bytes=5613/12/04 12:23:38 INFO mapred.JobClient:     Total committed heap usage (bytes)=18114150413/12/04 12:23:38 INFO mapred.JobClient:     CPU time spent (ms)=540013/12/04 12:23:38 INFO mapred.JobClient:     Combine input records=613/12/04 12:23:38 INFO mapred.JobClient:     SPLIT_RAW_BYTES=10213/12/04 12:23:38 INFO mapred.JobClient:     Reduce input records=413/12/04 12:23:38 INFO mapred.JobClient:     Reduce input groups=413/12/04 12:23:38 INFO mapred.JobClient:     Combine output records=413/12/04 12:23:38 INFO mapred.JobClient:     Physical memory (bytes) snapshot=17591500813/12/04 12:23:38 INFO mapred.JobClient:     Reduce output records=413/12/04 12:23:38 INFO mapred.JobClient:     Virtual memory (bytes) snapshot=78720614413/12/04 12:23:38 INFO mapred.JobClient:     Map output records=6

看看创建了什么文件，使用命令 ./hadoop fs -lsr /

drwxr-xr-x   - michaelchen supergroup          0 2013-12-04 12:20 /input-rw-r--r--   1 michaelchen supergroup         32 2013-12-04 12:20 /input/a.txtdrwxr-xr-x   - michaelchen supergroup          0 2013-12-04 12:23 /output-rw-r--r--   1 michaelchen supergroup          0 2013-12-04 12:23 /output/_SUCCESSdrwxr-xr-x   - michaelchen supergroup          0 2013-12-04 12:23 /output/_logsdrwxr-xr-x   - michaelchen supergroup          0 2013-12-04 12:23 /output/_logs/history-rw-r--r--   1 michaelchen supergroup      13815 2013-12-04 12:23 /output/_logs/history/job_201312041206_0001_1386130987951_michaelchen_word+count-rw-r--r--   1 michaelchen supergroup      49533 2013-12-04 12:23 /output/_logs/history/job_201312041206_0001_conf.xml-rw-r--r--   1 michaelchen supergroup         29 2013-12-04 12:23 /output/part-r-00000drwxr-xr-x   - michaelchen supergroup          0 2013-12-04 10:26 /systemdrwxr-xr-x   - michaelchen supergroup          0 2013-12-04 12:17 /tmpdrwxr-xr-x   - michaelchen supergroup          0 2013-12-04 12:17 /tmp/hadoop-michaelchendrwxr-xr-x   - michaelchen supergroup          0 2013-12-04 12:23 /tmp/hadoop-michaelchen/mapreddrwxr-xr-x   - michaelchen supergroup          0 2013-12-04 12:23 /tmp/hadoop-michaelchen/mapred/stagingdrwxr-xr-x   - michaelchen supergroup          0 2013-12-04 12:23 /tmp/hadoop-michaelchen/mapred/staging/michaelchendrwx------   - michaelchen supergroup          0 2013-12-04 12:23 /tmp/hadoop-michaelchen/mapred/staging/michaelchen/.stagingdrwx------   - michaelchen supergroup          0 2013-12-04 12:23 /tmp/hadoop-michaelchen/mapred/system-rw-------   1 michaelchen supergroup          4 2013-12-04 12:17 /tmp/hadoop-michaelchen/mapred/system/jobtracker.infodrwxr-xr-x   - michaelchen supergroup          0 2013-12-04 10:33 /userdrwxr-xr-x   - michaelchen supergroup          0 2013-12-04 10:33 /user/michaelchendrwxr-xr-x   - michaelchen supergroup          0 2013-12-04 10:33 /user/michaelchen/archiveDirdrwxr-xr-x   - michaelchen supergroup          0 2013-12-04 10:33 /user/michaelchen/archiveDir/pack.har-rw-r--r--   1 michaelchen supergroup          0 2013-12-04 10:33 /user/michaelchen/archiveDir/pack.har/_SUCCESS-rw-r--r--   5 michaelchen supergroup         72 2013-12-04 10:33 /user/michaelchen/archiveDir/pack.har/_index-rw-r--r--   5 michaelchen supergroup         22 2013-12-04 10:33 /user/michaelchen/archiveDir/pack.har/_masterindex-rw-r--r--   1 michaelchen supergroup      15147 2013-12-04 10:33 /user/michaelchen/archiveDir/pack.har/part-0drwxr-xr-x   - michaelchen supergroup          0 2013-12-04 10:31 /xwchen-rw-r--r--   1 michaelchen supergroup      15147 2013-12-04 10:31 /xwchen/hadoop

分析后的结果放在这里，使用命令查看：./hadoop fs -cat /output/part-r-00000

c++     1hello   2java    2world   1

Hadoop Eclipse插件

1）hadoop自0.20.x版本后不再提供现成的hadoop-eclipse插件，而是给出了源码自行编译
2）编译采用的是ant+ivy
3）URL：http://wiki.apache.org/hadoop/EclipsePlugin

编译的整个过程很是容易出问题，建议参考此链接：http://www.srccodes.com/p/article/30/build-hadoop-eclipse-plugin-jar-from-source-code-and-install-that-plugin-in-eclipse-ide

链接中注意版本号可能会有更改。

不过我编译的hadoop plugin的插件还是在eclipse中无法使用，最后用的网上下载的。。。
无法使用是出现在eclipse菜单里，show-others里编辑mapreduce路径，点new，弹不出窗口，泪奔啊～～

WordCount里用的相关Jar包依赖如下：

输入参数：hdfs://192.168.56.101:9100/input /output

注意output之前不能存在，否则报错。

其他参考视频。在1.2.1中编译成功，运行成功。

试题中的一些笔记：

• hadoop对于小文件的处理方式：Archive、CombinedInputFormat、SequenceFile、MapFile
• Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks.
• Borg（来自Google），YARN（来自Apache，属于Hadoop下面的一个分支，开源），Mesos（来自Twitter，开源），Torca（来自腾讯搜搜），Corona（来自Facebook，开源）一类系统被称为资源统一管理系统或者资源统一调度系统，它们是大数据时代的必然产物。
• SecondaryNamenode的作用是合并fsimage和editlogs
• Apache Tez由Hortonworks开发
• 关系型数据库与HDFS之间相互数据迁移的工具是sqoop
• hadoop2.x采用maven构建源代码