ubuntu 安装 hadoop（单机版）

时间:2015-10-20 15:44 来源:linux.it.net.cn 作者:IT

网上虽然有很多类似的文章，但大部分都有部分细节讲清楚，导致本小哥装了好久才装上。

为此，遂起心想整理下一份尽可能清晰的安装步骤来，遂成此文。

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Hadoop是MapReduce的开源实现，现在介绍它的单机模式安装方法。

实验平台：Ubuntu 9.04，Hadoop0.20，JDK1.6

1，我是在deskTop版本的Ubuntu下安装的所以，需要先安装ssh server。这个很好找，直接到到新立得里搜索ssh，第一个就是。
2，安装sun jdk6，切忌一定要是java6及其以上版本。先到更新管理器里把canonical的源加进去。
之后sudo apt-get update.
3, sudo apt-get sun-java6-jdk
4, sudo update-java-alternatives -s java-6-sun
5,增加一个用户组用户，用于hadoop运行及访问。

sudo addgroup hadoop

sudo adduser --ingroup hadoop hadoop

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6,生成SSH证书，配置SSH加密key

user@ubuntu:~$ su - hadoop

hadoop@ubuntu:~$ ssh-keygen -t rsa -P ""

Generating public/private rsa key pair.

Enter file in which to save the key (/home/hadoop/.ssh/id_rsa):

Created directory '/home/hadoop/.ssh'.

Your identification has been saved in /home/hadoop/.ssh/id_rsa.

Your public key has been saved in /home/hadoop/.ssh/id_rsa.pub.

The key fingerprint is:

9b:82:ea:58:b4:e0:35:d7:ff:19:66:a6:ef:ae:0e:d2 hadoop@ubuntu

The key's randomart image is:

[...snipp...]

hadoop@ubuntu:~$

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hadoop@ubuntu:~$ cat $HOME/.ssh/id_rsa.pub >> $HOME/.ssh/authorized_keys

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配置完成，测试一下：

hadoop@ubuntu:~$ ssh localhost

The authenticity of host 'localhost (::1)' can't be established.

RSA key fingerprint is d7:87:25:47:ae:02:00:eb:1d:75:4f:bb:44:f9:36:26.

Are you sure you want to continue connecting (yes/no)? yes

Warning: Permanently added 'localhost' (RSA) to the list of known hosts.

Linux ubuntu 2.6.32-22-generic #33-Ubuntu SMP Wed Apr 28 13:27:30 UTC 2010 i686 GNU/Linux

Ubuntu 10.04 LTS

[...snipp...]

hadoop@ubuntu:~$

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>> 下面就是安装Hadoop了。
首先是：下载，解压缩，分配权限。

?请至下载 Hadoop 0.20，并解开压缩文件到 /opt 路径。
?$ tar zxvf hadoop-0.20.0.tar.gz
?$ sudo mv hadoop-0.20.0 /opt/
?$ sudo chown -R hadoop:hadoop /opt/hadoop-0.20.0
?$ sudo ln -sf /opt/hadoop-0.20.0 /opt/hadoop

》》设定 hadoop-env.sh

?进入 hadoop 目录，做进一步的设定。我们需要修改两个档案，第一个是 hadoop-env.sh，需要设定 JAVA_HOME, HADOOP_HOME, PATH 三个环境变量。
/opt$ cd hadoop/
/opt/hadoop$ cat >> conf/hadoop-env.sh << EOF
贴上以下信息
export JAVA_HOME=/usr/lib/jvm/java-6-sun[注意，这里要改成自己的JAVA_HOME地址]
export HADOOP_HOME=/opt/hadoop
export PATH=$PATH:/opt/hadoop/bin
EOF
ook，现在安装完毕。

》》设定 hadoop配置文件

?編輯 /opt/hadoop/conf/core-site.xml
<configuration>
  <property>
    <name>fs.default.name</name>
    <value>hdfs://localhost:9000</value>
  </property>
  <property>
    <name>hadoop.tmp.dir</name>
    <value>/tmp/hadoop/hadoop-${user.name}</value>
  </property>
</configuration>
?編輯 /opt/hadoop/conf/hdfs-site.xml
<configuration>
  <property>
    <name>dfs.replication</name>
    <value>1</value>
  </property>
</configuration>
?編輯 /opt/hadoop/conf/mapred-site.xml
<configuration>
  <property>
    <name>mapred.job.tracker</name>
    <value>localhost:9001</value>
  </property>
</configuration>

》》格式化HDFS

?以上我们已经设定好 Hadoop 单机测试的环境，接着让我们来启动 Hadoop 相关服务，格式化 namenode， secondarynamenode, tasktracker
?$ cd /opt/hadoop
?$ source /opt/hadoop/conf/hadoop-env.sh
?$ hadoop namenode -format

执行画面如：
09/03/23 20:19:47 INFO dfs.NameNode: STARTUP_MSG:
/************************************************************
STARTUP_MSG: Starting NameNode
STARTUP_MSG:   host = /localhost
STARTUP_MSG:   args = [-format]
STARTUP_MSG:   version = 0.20.3
STARTUP_MSG:   build = https://svn.apache.org/repos/asf/hadoop/core/branches/branch-0.20 -r 736250; compiled by 'ndaley' on Thu Jan 22 23:12:08 UTC 2009
************************************************************/
09/03/23 20:19:47 INFO fs.FSNamesystem: fsOwner=hadooper,hadooper
09/03/23 20:19:47 INFO fs.FSNamesystem: supergroup=supergroup
09/03/23 20:19:47 INFO fs.FSNamesystem: isPermissionEnabled=true
09/03/23 20:19:47 INFO dfs.Storage: Image file of size 82 saved in 0 seconds.
09/03/23 20:19:47 INFO dfs.Storage: Storage directory /tmp/hadoop-hadooper/dfs/name has been successfully formatted.
09/03/23 20:19:47 INFO dfs.NameNode: SHUTDOWN_MSG:
/************************************************************
SHUTDOWN_MSG: Shutting down NameNode at /localhost
************************************************************/

》》启动Hadoop

?接着用 start-all.sh 来启动所有服务，包含 namenode, datanode,
/opt/hadoop$ bin/start-all.sh
执行画面如：
starting namenode, logging to /opt/hadoop/logs/hadoop-hadooper-namenode-vPro.out
localhost: starting datanode, logging to /opt/hadoop/logs/hadoop-hadooper-datanode-vPro.out
localhost: starting secondarynamenode, logging to /opt/hadoop/logs/hadoop-hadooper-secondarynamenode-vPro.out
starting jobtracker, logging to /opt/hadoop/logs/hadoop-hadooper-jobtracker-vPro.out

也可以通过jps命令:

若安装成功，当输入jps命令时，将会有如下画面：

4706 JobTracker

4582 SecondaryNameNode

4278 NameNode

4413 DataNode

4853 TaskTracker

4889 Jps

》》停止服务的脚本是：

hadoop@ubuntu:~$ /bin/stop-all.sh

上面的内容主要参考：http://bbs.chinacloud.cn/archiver/showtopic-589.aspx and

http://www.hadoopor.com/thread-2674-1-1.html

下面是运行hadoop自带wordcount的步骤（主要转自：http://nlslzf.iteye.com/blog/810948）

》》准备执行wordcount任务的数据

a.在hdfs 中建立一个input 目录

/opt/hadoop$ mkdir input

b.先在本地磁盘建立两个输入文件file01 和file02:

/opt/hadoop$ echo “Hello World Bye World” > file01

/opt/hadoop$ echo “Hello World Bye World” > file02

c. 将file01 和file02 拷贝到hdfs 中：

(1)cp file01 ./input

(2)cp file02 ./input

然后，将本地目录input上传到HDFS文件系统上，执行如下命令：
[root@localhost hadoop-0.19.2]# bin/hadoop fs -put input/ input[很关键的一步]

》》执行wordcount：

在hadoop所在目录里有几个jar文件，其中hadoop-0.19.2-examples.jar就是我们需要的，它里面含有wordcount，咱们使用命

下面的hadoop-0.19.2-examples.jar 注意改成自己版本对应的jar

（4）启动wordcount任务
执行如下命令行：
[root@localhost hadoop-0.19.2]# bin/hadoop jar hadoop-0.19.2-examples.jar wordcount input output
元数据目录为input，输出数据目录为output。
任务执行信息如下所示：
10/08/01 19:06:15 INFO mapred.FileInputFormat: Total input paths to process : 4
10/08/01 19:06:15 INFO mapred.JobClient: Running job: job_201008011904_0002
10/08/01 19:06:16 INFO mapred.JobClient: map 0% reduce 0%
10/08/01 19:06:22 INFO mapred.JobClient: map 20% reduce 0%
10/08/01 19:06:24 INFO mapred.JobClient: map 40% reduce 0%
10/08/01 19:06:25 INFO mapred.JobClient: map 60% reduce 0%
10/08/01 19:06:27 INFO mapred.JobClient: map 80% reduce 0%
10/08/01 19:06:28 INFO mapred.JobClient: map 100% reduce 0%
10/08/01 19:06:38 INFO mapred.JobClient: map 100% reduce 26%
10/08/01 19:06:40 INFO mapred.JobClient: map 100% reduce 100%
10/08/01 19:06:41 INFO mapred.JobClient: Job complete: job_201008011904_0002
10/08/01 19:06:41 INFO mapred.JobClient: Counters: 16
10/08/01 19:06:41 INFO mapred.JobClient:   File Systems
10/08/01 19:06:41 INFO mapred.JobClient:     HDFS bytes read=301489
10/08/01 19:06:41 INFO mapred.JobClient:     HDFS bytes written=113098
10/08/01 19:06:41 INFO mapred.JobClient:     Local bytes read=174004
10/08/01 19:06:41 INFO mapred.JobClient:     Local bytes written=348172
10/08/01 19:06:41 INFO mapred.JobClient:   Job Counters
10/08/01 19:06:41 INFO mapred.JobClient:     Launched reduce tasks=1
10/08/01 19:06:41 INFO mapred.JobClient:     Launched map tasks=5
10/08/01 19:06:41 INFO mapred.JobClient:     Data-local map tasks=5
10/08/01 19:06:41 INFO mapred.JobClient:   Map-Reduce Framework
10/08/01 19:06:41 INFO mapred.JobClient:     Reduce input groups=8997
10/08/01 19:06:41 INFO mapred.JobClient:     Combine output records=10860
10/08/01 19:06:41 INFO mapred.JobClient:     Map input records=7363
10/08/01 19:06:41 INFO mapred.JobClient:     Reduce output records=8997
10/08/01 19:06:41 INFO mapred.JobClient:     Map output bytes=434077
10/08/01 19:06:41 INFO mapred.JobClient:     Map input bytes=299871
10/08/01 19:06:41 INFO mapred.JobClient:     Combine input records=39193
10/08/01 19:06:41 INFO mapred.JobClient:     Map output records=39193
10/08/01 19:06:41 INFO mapred.JobClient:     Reduce input records=10860
（5）查看任务执行结果
可以通过如下命令行：
bin/hadoop fs -cat output/*
执行结果，截取部分显示如下所示：
vijayarenu      20
violations.     1
virtual 3
vis-a-vis       1
visible 1
visit   1
volume 1
volume, 1
volumes 2
volumes.        1
w.r.t   2
wait    9
waiting 6
waiting.        1
waits   3
want    1
warning 7
warning,        1
warnings        12
warnings.       3
warranties      1
warranty        1
warranty,       1
（6）终止Hadoop相关后台进程
执行如下命令行：
[root@localhost hadoop-0.19.2]# bin/stop-all.sh
执行信息如下所示：
stopping jobtracker
localhost: stopping tasktracker
stopping namenode
localhost: stopping datanode
localhost: stopping secondarynamenode
已经将上面列出的5个进程jobtracker、tasktracker、namenode、datanode、secondarynamenode

上文主要参见：http://blog.csdn.net/yangchao228/article/details/6646977 和 http://nlslzf.iteye.com/blog/810948

(责任编辑：IT)