Hadoop 2.5.1集群安装配置
本文的安装只涉及了hadoop-common、hadoop-hdfs、hadoop-mapreduce和hadoop-yarn，并不包含HBase、Hive和Pig等。
http://blog.csdn.net/aquester/article/details/24621005
1. 规划
1.1. 机器列表
|
NameNode |
SecondaryNameNode |
DataNodes |
|
172.16.0.100 |
172.16.0.101 |
172.16.0.110 |
|
172.16.0.111 |
||
|
172.16.0.112 |
1.2. 主机名
|
机器IP |
主机名 |
|
172.16.0.100 |
NameNode |
|
172.16.0.101 |
SecondaryNameNode |
|
172.16.0.110 |
DataNode110 |
|
172.16.0.111 |
DataNode111 |
|
172.16.0.112 |
DataNode112 |
2.设定IP与主机名
# rm -rf /etc/udev/rules.d/*.rules
# vi /etc/sysconfig/network-scripts/ifcfg-eth0
DEVICE=eth0
TYPE=Ethernet
ONBOOT=yes
NM_CONTROLLED=yes
BOOTPROTO=static
NETMASK=255.255.0.0
GATEWAY=192.168.0.6
IPADDR=192.168.1.20
DNS1=192.168.0.3
DNS2=192.168.0.6
DEFROUTE=yes
PEERDNS=yes
PEERROUTES=yes
IPV4_FAILURE_FATAL=yes
IPV6INIT=no
NAME="System eth0"
# vi /etc/sysconfig/network
NETWORKING=yes
HOSTNAME=NameNode.smartmap
# vi /etc/hosts
127.0.0.1 localhost localhost.localdomain localhost4 localhost4.localdomain4
192.168.1.20 NameNode NameNode.smartmap
192.168.1.50 SecondaryNameNode SecondaryNameNode.smartmap
192.168.1.70 DataNode110 DataNode110.smartmap
192.168.1.90 DataNode111 DataNode111.smartmap
::1 localhost localhost.localdomain localhost6 localhost6.localdomain6
3.免密码登录
3.1. 免密码登录范围
要求能通过免登录包括使用IP和主机名都能免密码登录：
1) NameNode能免密码登录所有的DataNode
2) SecondaryNameNode能免密码登录所有的DataNode
3) NameNode能免密码登录自己
4) SecondaryNameNode能免密码登录自己
5) NameNode能免密码登录SecondaryNameNode
6) SecondaryNameNode能免密码登录NameNode
7) DataNode能免密码登录自己
8) DataNode不需要配置免密码登录NameNode、SecondaryNameNode和其它DataNode。
3.2. 软件安装
# yum install openssh-clients (NameNode、SecondaryNameNode和其它DataNode均执行)
# yum install wget
3.3. SSH配置
vi /etc/ssh/sshd_config (NameNode、SecondaryNameNode和其它DataNode均执行)
RSAAuthentication yes
PubkeyAuthentication yes
AuthorizedKeysFile .ssh/authorized_keys
service sshd restart
3.4. SSH无密码配置
# ssh-keygen -t rsa (NameNode、SecondaryNameNode和其它DataNode均执行)
看到图形输出，表示密钥生成成功，目录下多出两个文件
私钥文件：id_raa
公钥文件：id_rsa.pub
将公钥文件id_rsa.pub内容放到authorized_keys文件中：
# cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys (NameNode、SecondaryNameNode均执行)
将公钥文件authorized_keys分发到各dataNode节点：
(NameNode、SecondaryNameNode均执行)
# scp authorized_keys root@SecondaryNameNode:/root/.ssh/
# scp authorized_keys root@DataNode110:/root/.ssh/
# scp authorized_keys root@DataNode111:/root/.ssh/
# scp authorized_keys root@DataNode112:/root/.ssh/
3.5. SSH无密码登录验证
验证ssh无密码登录：
(NameNode均执行)
# ssh root@localhost
# ssh root@SecondaryNameNode
# ssh root@DataNode110
# ssh root@DataNode111
# ssh root@DataNode112
(SecondaryNameNode均执行)
# ssh root@localhost
# ssh root@NameNode
# ssh root@DataNode110
# ssh root@DataNode111
# ssh root@DataNode112
(DataNode110均执行)
# ssh root@localhost
(DataNode111均执行)
# ssh root@localhost
(DataNode111均执行)
# ssh root@localhost
4.JDK安装与环境变量配置
(以下内容NameNode、SecondaryNameNode和其它DataNode均执行)
4.1. JDK下载
jdk-7u72-linux-x64.tar.gz
# scp jdk-7u72-linux-x64.tar.gz root@192.168.1.50:/opt/
4.2.卸载系统自带的开源JDK
# rpm -qa |grep java
# rpm –e java
4.3.把安装文件拷贝到用户目录
例如：
/opt/java目录下
4.4.解压文件
# tar -xzvf jdk-7u72-linux-x64.tar.gz
解压后，在/opt/java目录下就会生成一个新的目录 jdk1.7.0_72，该目录下存放的是解压后的文件。
至此，安装工作基本完成，下面是要进行环境变量的设置。
注意：如果你下载的文件是rpm 格式的话，可以通过下面的命令来安装：
rpm -ivh jdk-7u72-linux-x64.rpm
4.5.环境变量设置
修改.profile文件 （推荐此种方式，这样其他程序也可以友好的使用JDK了）
# vi /etc/profile
在文件中找到export PATH USER LOGNAME MAIL HOSTNAME HISTSIZE INPUTRC，改为下面的形式：
export JAVA_HOME=/opt/java/jdk1.7.0_72
export PATH=$PATH:$JAVA_HOME/bin:$JAVA_HOME/jre/bin
export CLASSPATH=.:$JAVA_HOME/lib:$JAVA_HOME/jre/lib
4.6.让环境变量生效
执行配置文件令其立刻生效
# source /etc/profile
之后执行以下命令验证是否安装成功
# java -version
如果出现下面的信息，则表示安装成功
java version "1.7.0_72"
Java(TM) SE Runtime Environment (build 1.7.0_72-b14)
Java HotSpot(TM) 64-Bit Server VM (build 24.72-b04, mixed mode)
5.Hadoop安装与配置
5.1.Hadoop下载
# wget http://mirrors.hust.edu.cn/apache/hadoop/common/stable/hadoop-2.5.1.tar.gz
# scp hadoop-2.5.1.tar.gz root@192.168.1.50:/opt/
5.2.解压文件
# tar -zxvf hadoop-2.5.1.tar.gz
5.3.配置
# cd /opt/hadoop-2.5.1/etc/hadoop
cp /opt/hadoop/hadoop-2.5.1/share/doc/hadoop/hadoop-project-dist/hadoop-common/core-default.xml /opt/hadoop/hadoop-2.5.1/etc/hadoop/core-site.xml
cp /opt/hadoop/hadoop-2.5.1/share/doc/hadoop/hadoop-project-dist/hadoop-hdfs/hdfs-default.xml /opt/hadoop/hadoop-2.5.1/etc/hadoop/hdfs-site.xml
cp /opt/hadoop/hadoop-2.5.1/share/doc/hadoop/hadoop-yarn/hadoop-yarn-common/yarn-default.xml /opt/hadoop/hadoop-2.5.1/etc/hadoop/yarn-site.xml
cp /opt/hadoop/hadoop-2.5.1/share/doc/hadoop/hadoop-mapreduce-client/hadoop-mapreduce-client-core/mapred-default.xml /opt/hadoop/hadoop-2.5.1/etc/hadoop/mapred-site.xml
# mkdir -p /opt/hadoop/tmp/dfs/name
# mkdir -p /opt/hadoop/tmp/dfs/data
# mkdir -p /opt/hadoop/tmp/dfs/namesecondary
5.3.1.core-site.xml
# vi core-site.xml
<configuration>
<property>
<name>hadoop.tmp.dir</name>
<value>/opt/hadoop/tmp</value>
<description>Abase for other temporary directories.</description>
</property>
<property>
<name>fs.defaultFS</name>
<value>hdfs://192.168.1.20:9000</value>
</property>
<property>
<name>io.file.buffer.size</name>
<value>4096</value>
</property>
</configuration>
|
属性名 |
属性值 |
涉及范围 |
|
fs.defaultFS |
hdfs://192.168.1.20:9000 |
所有节点 |
|
hadoop.tmp.dir |
/opt/hadoop/tmp |
所有节点 |
|
fs.default.name |
hdfs://192.168.1.20:9000 |
|
5.3.2.hdfs-site.xml
# vi hdfs-site.xml
<configuration>
<property>
<name>dfs.namenode.http-address</name>
<value>192.168.1.20:50070</value>
</property>
<property>
<name>dfs.namenode.http-bind-host</name>
<value>192.168.1.20</value>
</property>
<property>
<name>dfs.namenode.secondary.http-address</name>
<value>192.168.1.50:50090</value>
</property>
<property>
<name>dfs.replication</name>
<value>2</value>
</property>
<property>
<name>dfs.webhdfs.enabled</name>
<value>true</value>
</property>
</configuration>
|
属性名 |
属性值 |
涉及范围 |
|
dfs.namenode.http-address |
192.168.1.20:50070 |
所有节点 |
|
dfs.namenode.http-bind-host |
192.168.1.20 |
所有节点 |
|
dfs.namenode.secondary.http-address |
192.168.1.50:50090 |
NameNode、SecondaryNameNode |
|
dfs.replication |
2 |
|
2.3.3.mapred-site.xml
# vi mapred-site.xml
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>mapreduce.jobtracker.http.address</name>
<value>192.168.1.20:50030</value>
</property>
<property>
<name>mapreduce.jobhistory.address</name>
<value>192.168.1.20:10020</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>192.168.1.20:19888</value>
</property>
<property>
<name>mapreduce.jobhistory.admin.address</name>
<value>192.168.1.20:10033</value>
</property>
</configuration>
|
属性名 |
属性值 |
涉及范围 |
|
mapreduce.framework.name |
yarn |
所有节点 |
|
mapreduce.jobtracker.http.address |
192.168.1.20:50030 |
|
2.3.4.yarn-site.xml
# vi yarn-site.xml
<configuration>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.resourcemanager.hostname</name>
<value>192.168.1.20</value>
</property>
</configuration>
|
属性名 |
属性值 |
涉及范围 |
|
192.168.1.20 |
所有节点 |
|
|
yarn.nodemanager.aux-services |
mapreduce_shuffle |
所有节点 |
|
|
|
|
5.3.5.slaves
# vi slaves
DataNode110
DataNode111
5.3.5.secondaryNamenodes
# vi master
SecondaryNameNode
5.3.6.修改JAVA_HOME
分别在文件hadoop-env.sh和yarn-env.sh中添加JAVA_HOME配置
# vi hadoop-env.sh
export JAVA_HOME=/opt/java/jdk1.7.0_72
export HADOOP_HOME=/opt/hadoop/hadoop-2.5.1
export HADOOP_COMMON_LIB_NATIVE_DIR=${HADOOP_HOME}/lib/native
export HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib/native"
# vi yarn-env.sh
export JAVA_HOME=/opt/java/jdk1.7.0_72
export HADOOP_HOME=/opt/hadoop/hadoop-2.5.1
export HADOOP_COMMON_LIB_NATIVE_DIR=${HADOOP_HOME}/lib/native
export HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib/native"
5.4.环境变量设置
修改.profile文件 （推荐此种方式，这样其他程序也可以友好的使用JDK了）
# vi /etc/profile
在文件中找到export PATH USER LOGNAME MAIL HOSTNAME HISTSIZE INPUTRC，改为下面的形式：
export JAVA_HOME=/opt/java/jdk1.7.0_72
export JRE_HOME=$JAVA_HOME/jre
export PATH=$JAVA_HOME/bin:$JRE_HOME/bin:$PATH
export CLASSPATH=.:$JAVA_HOME/lib:$JAVA_HOME/jre/lib:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
export HADOOP_HOME=/opt/hadoop/hadoop-2.5.1
export HADOOP_COMMON_HOME=$HADOOP_HOME
export HADOOP_HDFS_HOME=$HADOOP_HOME
export HADOOP_MAPRED_HOME=$HADOOP_HOME
export HADOOP_YARN_HOME=$HADOOP_HOME
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
export CLASSPATH=$HADOOP_HOME/lib:$CLASSPATH
export PATH=$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH
export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native
export HADOOP_OPTS="-Djava.library.path=/opt/hadoop/hadoop-2.5.1/lib/native"
5.4.1.让环境变量生效
执行配置文件令其立刻生效
# source /etc/profile
5.5.启动HDFS
5.5.1.格式化NameNode
# hdfs namenode -format
5.5.1.启动HDFS
. /opt/hadoop/hadoop-2.5.1/sbin/start-dfs.sh
5.5.1.启动YARN
. /opt/hadoop/hadoop-2.5.1/sbin/start-yarn.sh
设置logger级别，看下具体原因
export HADOOP_ROOT_LOGGER=DEBUG,console
windows->show view->other-> MapReduce Tools->Map/Reduce Locations
hadoop-2.5.1-src.tar.gz\hadoop-2.5.1-src\hadoop-mapreduce-project\hadoop-mapreduce-examples\src\main\java\org\apache\hadoop\examples - TAR+GZIP archive, unpacked size 82,752,131 bytes
