Centos 6.5 hadoop 2.2.0 全分布式安装

hadoop 2.2.0 cluster setup

环境：

操作系统:Centos 6.5

jdk:jdk1.7.0_51

hadoop版本:2.2.0

hostname    ip

master 192.168.1.180

slave1 192.168.1.181

slave2 192.168.1.182

slave3 192.168.1.183

一、前期系统环境配置

设置主机名

临时生效修改主机名，重启失效

[lxj@master ~]$ hostnamemaster

永久生效修改主机名,需重启.

[lxj@master ~]$ vim/etc/sysconfig/network

NETWORKING=yes

HOSTNAME=master

2.设置ip

[lxj@master ~]$ vim/etc/sysconfig/network-scripts/ifcfg-eth0

DEVICE=eth0

TYPE=Ethernet

UUID=390e4922-0d95-4c34-9dde-897fb8acef0f

ONBOOT=yes

NM_CONTROLLED=yes

BOOTPROTO=none

HWADDR=08:00:27:1C:57:24

IPADDR=192.168.1.180

PREFIX=24

GATEWAY=192.168.1.1

DNS1=192.168.1.1

DOMAIN=114.114.114.114

DEFROUTE=yes

IPV4_FAILURE_FATAL=yes

IPV6INIT=no

NAME="Systemeth0"

LAST_CONNECT=1393996666

3.host 映射

[lxj@master ~]$ vim/etc/hosts

127.0.0.1   localhost

192.168.1.180 master

192.168.1.181 slave1

192.168.1.182 slave2

192.168.1.183 slave3

其他节点hosts改成这样。

4.关闭防火墙

开机启动关闭

[lxj@master ~]$ sudoservice iptables stop

[lxj@master ~]$ sudochkconfig iptables off

5.ssh 无密码登录，master 需要启动slave节点的相关进程

[lxj@master ~]$ssh-keygen -t rsa -P '' -f ~/.ssh/id_rsa

[lxj@master ~]$ cat~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys

测试是否能无密码登录了

[lxj@master ~]$ sshlocalhost

如果以上操作完成后 还需要输入密码 请做一下操作

/home/用户名/.ssh 目录权限 700

/home/用户名/.ssh/authorized_keys 文件权限 600

[lxj@master ~]$ chmod 700/home/lxj/.ssh

[lxj@master ~]$ chmod 600/home/lxj/.ssh/authorized_keys

6.拷贝公钥到其他slave节点

由于master主机公钥已写入authorized_keys授权文件，所以只要拷贝授权文件到其他slave节点即可

注意节点.ssh目录和authorized_keys文件权限也分别要是700,600。

[lxj@master ~]$ scp/home/lxj/.ssh/authorized_keys lxj@slave1:/home/lxj/.ssh/

[lxj@master ~]$ scp/home/lxj/.ssh/authorized_keys lxj@slave2:/home/lxj/.ssh/

[lxj@master ~]$ scp/home/lxj/.ssh/authorized_keys lxj@slave3:/home/lxj/.ssh/

测试是否可以无密码登录slave节点了

[lxj@master ~]$ sshslave1

[lxj@master ~]$ exit

[lxj@master ~]$ sshslave2

[lxj@master ~]$ exit

[lxj@master ~]$ sshslave3

可以的话，这样master无密码登录其他slave节点就配配置好了！

二、hadoop
配置文件

先设置下环境变量

JAVA_HOME=/home/lxj/jdk1.7.0_51

CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar

HADOOP_HOME=/home/lxj/hadoop-2.2.0

HADOOP_MAPRED_HOME=$HADOOP_HOME

HADOOP_COMMON_HOME=$HADOOP_HOME

HADOOP_HDFS_HOME=$HADOOP_HOME

YARN_HOME=$HADOOP_HOME

HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop

YARN_CONF_DIR=$HADOOP_HOME/etc/hadoop

PATH=$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH

export JAVA_HOME CLASSPATHHADOOP_HOME HADOOP_MAPRED_HOME HADOOP_COMMON_HOME HADOOP_HDFS_HOME YARN_HOMEHADOOP_CONF_DIR YARN_CONF_DIR  PATH

主要需修改的配置文件

我们先在master机器上修改这些配置文件，然后传到各个节点hadoop 目录在~/hadoop-2.2.0

hadoop-env.sh、core-site.xml、hdfs-site.xml、mapred-site.xml、yarn-env.sh、yarn-site.xml、masters、slaves

以上配置文件，如果没有则自己新建

节点信息

NameNode: master,slave1

SecondaryNameNode: master,slave1

DataNode:slave1,slave2,slave3

三、master
机器配置

1.hadoop-env.sh 修改JAVA_HOME

[lxj@master ~]$  cd ~/hadoop-2.2.0/etc/hadoop

[lxj@master hadoop]$ vimhadoop-env.sh

# The onlyrequired environment variable is JAVA_HOME. All others are

#optional.  When running a distributedconfiguration it is best to

# setJAVA_HOME in this file, so that it is correctly defined on

# remotenodes.

# The javaimplementation to use.

export
JAVA_HOME=/home/lxj/jdk-1.7.0_15

2.core-site.xml

<?xmlversion="1.0" encoding="UTF-8"?>

<?xml-stylesheettype="text/xsl" href="configuration.xsl"?>

<configuration>

<property>

<name>fs.default.name</name>

<value>hdfs://master:9000</value>

</property>

<property>

<name>hadoop.tmp.dir</name>

<value>/home/lxj/hadoop/tmp</value>

</property>

</configuration>

3.hdfs-site.xml

<?xmlversion="1.0" encoding="UTF-8"?>

<?xml-stylesheettype="text/xsl" href="configuration.xsl"?>

<!--Put site-specific property overrides in this file. -->

<configuration>

<property>

<name>dfs.namenode.secondary.http-address</name>

<value>master:50090</value>

</property>

<property>

<name>fs.checkpoint.period</name>

</value>

</property>

<property>

<name>fs.checkpoint.size</name>

</value>

</property>

<property>

<name>dfs.namenode.name.dir</name>

<value>file:/home/lxj/hadoop/hdfs/namenode</value>

</property>

<property>

<name>dfs.datanode.data.dir</name>

<value>file:/home/lxj/hadoop/hdfs/datanode</value>

</property>

<property>

<name>dfs.permissions</name>

<value>false</value>

</property>

<property>

<name>dfs.replication</name>

</value>

</property>

<property>

<name>dfs.webhdfs.enabled</name>

<value>true</value>

</property>

</configuration>

4.mapred-site.xml

<?xmlversion="1.0"?>

<?xml-stylesheettype="text/xsl" href="configuration.xsl"?>

<configuration>

<property>

<name>mapreduce.framework.name</name>

<value>yarn</value>

</property>

<property>

<name>mapred.job.tracker</name>

<value>master:9001</value>

</property>

<property>

<name>mapreduce.jobhistory.address</name>

<value>master:10020</value>

</property>

<property>

<name>mapreduce.jobhistory.webapp.address</name>

<value>master:19888</value>

</property>

</configuration>

5.yarn-env.sh 修改JAVA_HOME

# someJava parameters

export
JAVA_HOME=/home/lxj/jdk1.7.0_51

if["$JAVA_HOME" !=""];then

#echo "run java in$JAVA_HOME"

JAVA_HOME=$JAVA_HOME

fi

6.yarn-site.xml

<?xmlversion="1.0"?>

<configuration>

<property>

<name>yarn.nodemanager.aux-services</name>

<value>mapreduce_shuffle</value>

</property>

<property>

<name>yarn.nodemanager.aux-servicex.mapreduce.shuffle.class</name>

<value>org.apache.hadoop.mapred.ShuffleHandler</value>

</property>

<property>

<name>yarn.resourcemanager.address</name>

<value>master:8032</value>

</property>

<property>

<name>yarn.resourcemanager.scheduler.address</name>

<value>master:8030</value>

</property>

<property>

<name>yarn.resourcemanager.resource-tracker.address</name>

<value>master:8031</value>

</property>

<property>

<name>yarn.resourcemanager.admin.address</name>

<value>master:8033</value>

</property>

<property>

<name>yarn.resourcemanager.webapp.address</name>

<value>master:8088</value>

</property>

</configuration>

7.masters 添加master主机 多个换行写

master

8.slaves 添加slave节点 当加入master时，master即当作NameNode又当作DataNode节点

slave1

slave2

slave3

四、slave
节点配置

其他节点各拷贝一份。

[lxj@master ~]$ scp -r~/hadoop-2.2.0 lxj@slave1:/home/lxj/

[lxj@master ~]$ scp -r~/hadoop-2.2.0 lxj@slave2:/home/lxj/

[lxj@master ~]$ scp -r~/hadoop-2.2.0 lxj@slave3:/home/lxj/

slave节点的hadoop路径需和master的路径一样，当然系统环境需要保持一致。

只要将master主机的配置好的文件拷贝到各个节点即可。

五、 hadoop
启动

1.格式化一个新的分布式文件系统

需要在master和slave1都要执行

[lxj@master ~]$ hdfsnamenode -format

2.启动hdfs和yarn 只需在master执行

[lxj@master ~]$start-dfs.sh

[lxj@master ~]$start-yarn.sh

[lxj@master ~]$mr-jobhistory-daemon.sh start historyserver

或者

[lxj@mater ~]$start-all.sh

start-all.sh已废弃，不推荐使用！

3.测试

master 进程

[lxj@master ~]$ jps

11597 JobHistoryServer

4529 Jps

4460 ResourceManager

4293 NameNode

4377 SecondaryNameNode

slaves进程

[lxj@master ~]$ jps

1941 DataNode

2176 Jps

2046 NodeManager

创建输入目录和文件

[lxj@master ~]$ hdfs dfs-mkdir /input

[lxj@master ~]$ vim./test

hello hadoop test

拷贝文件到hdfs文系统，运行wordcount程序计算输入文件的单词出现次数

[lxj@master ~]$ hdfs dfs-copyFromLocal ./test /input

[lxj@master ~]$ hadoopjar/home/lxj/hadoop-2.2.0/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.2.0.jarwordcount /input/ /out

[lxj@master ~]$ hdfs dfs-cat /out/*

hadoop  1

hello   1

test    1

搞了下ha federationqjm 配置，没起来，还是从基础配置开始吧，以后在扩展。

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