hadoop+zookeeper+hbase分布式安装

前期服务器配置##

  1. 修改/etc/hosts文件，添加以下信息（如果正常IP）
    119.23.163.113 master
    120.79.116.198 slave1
    120.79.116.23 slave2
    如果安全组内的IP，通过ip a方式查询内部IP并添加到/etc/hosts；

  2. 确认三个服务器之间可以互相ping通

  3. 给三个机器生成密钥文件

    1. 三台机器上执行以下命令
      ssh-keygen
    2. 生成公共密钥，先在master服务器上生成，之后复制到其他两个服务器
      1. 以下为正常免密方式
      • touch /root/.ssh/authorized_keys
      • cat /root/.ssh/id_rsa.pub >> /root/.ssh/authorized_keys
      • vim /root/.ssh/authorized_keys
        • 将其他两个机器的/root/.ssh/id_rsa.pub的内容复制到authorized_keys文件中
      • chmod 600 /root/.ssh/authorized_keys
      • chmod 700 /root/.ssh/
      1. 以下为公司内安全组方式的互相免密方式
      • ssh-copy-id -i ~/.ssh/id_rsa.pub $ip

  4. 解压hadoopzookeeperhbase包

  5. 重命名解压后的文件名
    mv hadoop-2.6.0-cdh5.6.0/ hadoop/
    mv hbase-1.0.0-cdh5.6.0/ hbase
    mv zookeeper-3.4.5-cdh5.6.0/ zookeeper

  6. 安装Java环境

    1. 解压包
    2. 配置/etc/profile
      export JAVA_HOME=/opt/cdh/jdk1.8.0_144
      export CLASSPATH=$:CLASSPATH:$JAVA_HOME/lib/
      export PATH=$PATH:$JAVA_HOME/bin
    3. 使生效 source /etc/profile
    4. 验证 java -version

hadoop分布式部署##

  1. 进入配置文件目录cd hadoop/etc/hadoop/,修改配置文件
    1. vim core-site.xml
	<property>
	    <name>hadoop.tmp.dir</name>
	    <value>/opt/cdh/hadoop-env/tmp</value>
	    <description>Abase for other temporary directories.</description>
	</property>
	<property>
	    <name>fs.default.name</name>
	    <value>hdfs://master:9000</value>
	</property>

2. vim hadoop-env.sh

export JAVA_HOME=/opt/cdh/jdk1.8.0_144

3. vim hdfs-site.xml

<property>
   <name>dfs.name.dir</name>
   <value>/opt/cdh/hadoop-env/dfs/name</value>
   <description>Path on the local filesystem where theNameNode stores the namespace and transactions logs persistently.</description>
</property>
<property>
   <name>dfs.data.dir</name>
   <value>/opt/cdh/hadoop-env/dfs/data</value>
   <description>Comma separated list of paths on the localfilesystem of a DataNode where it should store its blocks.</description>
</property>
<property>
   <name>dfs.replication</name>
   <value>2</value>
</property>
<property>
      <name>dfs.permissions</name>
      <value>true</value>
      <description>need not permissions</description>
</property>

4. cp mapred-site.xml.template mapred-site.xml  
   vim mapred-site.xml

	<property>
	    <name>mapred.job.tracker</name>
	    <value>master:49001</value>
	</property>
	<property>
	    <name>mapred.local.dir</name>
	    <value>/opt/cdh/hadoop-env/var</value>
	</property>
	<property>
	    <name>mapreduce.framework.name</name>
	    <value>yarn</value>
	</property>

5. vim slaves

	slave1
	slave2

6. vim yarn-site.xml

   <property>
        <name>yarn.resourcemanager.hostname</name>
        <value>master</value>
   </property>
   <property>
        <description>The address of the applications manager interface in the RM.</description>
        <name>yarn.resourcemanager.address</name>
        <value>${yarn.resourcemanager.hostname}:8032</value>
   </property>
   <property>
        <description>The address of the scheduler interface.</description>
        <name>yarn.resourcemanager.scheduler.address</name>
        <value>${yarn.resourcemanager.hostname}:8030</value>
   </property>
   <property>
        <description>The http address of the RM web application.</description>
        <name>yarn.resourcemanager.webapp.address</name>
        <value>${yarn.resourcemanager.hostname}:8088</value>
   </property>
   <property>
        <description>The https adddress of the RM web application.</description>
        <name>yarn.resourcemanager.webapp.https.address</name>
        <value>${yarn.resourcemanager.hostname}:8090</value>
   </property>
   <property>
        <name>yarn.resourcemanager.resource-tracker.address</name>
        <value>${yarn.resourcemanager.hostname}:8031</value>
   </property>
   <property>
        <description>The address of the RM admin interface.</description>
        <name>yarn.resourcemanager.admin.address</name>
        <value>${yarn.resourcemanager.hostname}:8033</value>
   </property>
   <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
   </property>
   <property>
        <name>yarn.scheduler.maximum-allocation-mb</name>
        <value>8182</value>
        <discription>每个节点可用内存,单位MB,默认8182MB</discription>
   </property>
   <property>
        <name>yarn.nodemanager.vmem-pmem-ratio</name>
        <value>2.1</value>
   </property>
   <property>
        <name>yarn.nodemanager.resource.memory-mb</name>
        <value>8182</value>
   </property>

zookeeper部署##

  1. 进入zookeeper配置目录cd /opt/cdh/zookeeper/conf
    • cp zoo_sample.cfg zoo.cfg
    • vim zoo.cfg
dataDir=/opt/cdh/zookeeper-env
dataLogDir=/opt/cdh/zookeeper-env/logs

server.1=master:2888:3888
server.2=slave1:2888:3888
server.3=slave2:2888:3888

2.. 配置各服务器zookeeperID
+ 进入每个服务器的dataDir,每个服务器ID不一样比如以下是echo 1，其他的就是echo 2或者echo 3
cd /opt/cdh/zookeeper-env
echo 1 > myid

hbase部署##

  1. 进入hbase配置目录cd /opt/cdh/hbase/conf
    1. vim hbase-env.sh
	export JAVA_HOME=/opt/cdh/jdk1.8.0_144
	export HBASE_CLASSPATH=/opt/cdh/hbase/conf 
	export HBASE_MANAGES_ZK=false        #此配置信息，设置由hbase自己管理zookeeper，不需要单独的zookeeper。
	export HBASE_HOME=/opt/cdh/hbase
	export HADOOP_HOME=/opt/cdh/hadoop 
	export HBASE_LOG_DIR=/opt/cdh/hbase-env/logs    #Hbase日志目录

2. vim hbase-site.xml

   <property>
     <name>hbase.rootdir</name>
     <value>hdfs://master:9000/hbase</value>
    </property>
    <property>
     <name>hbase.cluster.distributed</name>
     <value>true</value>
    </property>
    <property>
    <name>hbase.master</name>
    <value>master:60000</value>
    </property>
    <property>
     <name>hbase.zookeeper.quorum</name>
     <value>slave1,slave2</value>
    </property>

3. vim regionservers

	slave1
	slave2

启动集群##

  1. 启动hadoop，只在master上启动
    1. /opt/cdh/hadoop/bin/hadoop namenode -format
    2. /opt/cdh/hadoop/sbin/start-all.sh
  2. 启动zookeeper，现在slave服务器启动，再启动master上的zookeeper
    1. /opt/cdh/zookeeper/bin/zkServer.sh start
  3. 启动hbase，只在master启动
    1. /opt/cdh/hbase/bin/start-hbase.sh
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原文地址：https://www.cnblogs.com/fengzzi/p/10033008.html