hadoop 2.0安装及HA配置简述

一.单机模式

a、配置本机到本机的免密登录

b、解压hadoop压缩包，修改hadoop.env.sh中的JAVA_HOME

c、修改core-site.xml

<configuration>
  <property>
    <name>fs.defaultFS</name>
    <value>hdfs://192.168.110.222</value>
  </property>
</configuration>

d、修改hadfs-site.xml

<configuration>
  <property>
    <name>dfs.namenode.name.dir</name>
    <value>/root/softs/hadoop-2.7./namelog</value>
  </property>
  <property>
    <name>dfs.datanode.data.dir</name>
    <value>/root/softs/hadoop-2.7./datalog</value>
  </property>
</configuration>

e、格式化namenode，启动hfds

bin/hdfs namenode -format
sbin/start-dfs.sh

二.高可用配置

a.节点规划

hostname	ip	software	jps
hbase1	192.168.110.51	jdk/hadoop	namenode/resourcemanager/zkfc
hbase2	192.168.110.52	jdk/hadoop	namenode/resourcemanager/zkfc
hbase3	192.168.110.53	jdk/hadoop/zookeeper	datanode/nodemanager/journalnode/quorumpeermain
hbase4	192.168.110.54	jdk/hadoop/zookeeper	datanode/nodemanager/journalnode/quorumpeermain
hbase5	192.168.110.55	jdk/hadoop/zookeeper	datanode/nodemanager/journalnode/quorumpeermain

b.配置免密登录

c.hadoop主要配置文件

core-site.xml

<configuration>
        <property>
                <name>fs.defaultFS</name>
                <value>hdfs://myCluster</value>
        </property>
        <property>
        <name>io.file.buffer.size</name>
        <value></value>
        </property>
        <property>
                <name>fs.trash.interval</name>
                <value></value>
        </property>
        <property>
                <name>ha.zookeeper.quorum</name>
                <value>hbase3:,hbase4:,hbase5:</value>
        </property>
</configuration>

hdfs-site.xml

<property>
<name>dfs.namenode.name.dir</name>
<value>file:///root/apps/hadoop-2.7.7/namelogs</value>
</property>
<property>
<name>dfs.blocksize</name>
<value>256m</value>
</property>
<property>
<name>dfs.namenode.handler.count</name>
<value>100</value>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>file:///root/apps/hadoop-2.7.7/data</value>
</property>
<!-- the max number of files a datanode will serve at any one time -->
<property>
<name>dfs.datanode.max.transfer.threads</name>
<value>4096</value>
</property>
<property>
<name>dfs.webhdfs.enabled</name>
<value>true</value>
</property>
<property>
<name>dfs.nameservices</name>
<value>myCluster</value>
</property>
<property>
<name>dfs.ha.namenodes.myCluster</name>
<value>nn1,nn2</value>
</property>
<property>
<name>dfs.namenode.rpc-address.myCluster.nn1</name>
<value>192.168.169.11:8020</value>
</property>
<property>
<name>dfs.namenode.rpc-address.myCluster.nn2</name>
<value>192.168.169.12:8020</value>
</property>
<!-- 配置nn1,nn2的http通信端口 -->
<property>
<name>dfs.namenode.http-address.myCluster.nn1</name>
<value>192.168.169.11:50070</value>
</property>
<property>
<name>dfs.namenode.http-address.myCluster.nn2</name>
<value>192.168.169.12:50070</value>
</property>
<!-- 指定namenode元数据存储在journalnode中的路劲 -->
<property>
<name>dfs.namenode.shared.edits.dir</name>
<value>qjournal://192.168.169.13:8485;192.168.169.14:8485;192.168.169.15:8485/myCluster</value>
</property>
<!-- 指定journalnode日志文件存储的路劲 -->
<property>
<name>dfs.journalnode.edits.dir</name>
<value>/root/apps/hadoop-2.7.7/journallog</value>
</property>
<!-- 指定HDFS客户端连接active namenode的java类 -->
<property>
<name>dfs.client.failover.proxy.provider.myCluster</name>
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
<!-- 配置隔离机制为ssh -->
<property>
<name>dfs.ha.fencing.methods</name>
<value>sshfence</value>
</property>
<!-- 指定秘钥的位置 -->
<property>
<name>dfs.ha.fencing.ssh.private-key-files</name>
<value>/root/.ssh/id_rsa</value>
</property>
<!-- 开启自动故障转移 -->
<property>
<name>dfs.ha.automatic-failover.enabled</name>
<value>true</value>
</property>

mapred-site.xml

<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>mapreduce.map.memory.mb</name>
<value>1536</value>
</property>
<property>
<name>mapreduce.map.java.opts</name>
<value>-Xmx1024M</value>
</property>
<property>
<name>mapreduce.reduce.memory.mb</name>
<value>3072</value>
</property>
<property>
<name>mapreduce.reduce.java.opts</name>
<value>-Xmx2560M</value>
</property>
<property>
<name>mapreduce.task.io.sort.mb</name>
<value>512</value>
</property>
<property>
<name>mapreduce.task.io.sort.factor</name>
<value>100</value>
</property>
<property>
<name>mapreduce.reduce.shuffle.parallelcopies</name>
<value>50</value>
</property>
<property>
<name>mapreduce.jobhistory.address</name>
<value>hbase1:10020</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>hbase1:19888</value>
</property>
<!-- 开启uber模式（针对小作业的优化） -->
<property>
<name>mapreduce.job.ubertask.enable</name>
<value>true</value>
</property>
<!-- 配置启动uber模式的最大map数 -->
<property>
<name>mapreduce.job.ubertask.maxmaps</name>
<value>9</value>
</property>
<!-- 配置启动uber模式的最大reduce数 -->
<property>
<name>mapreduce.job.ubertask.maxreduces</name>
<value>1</value>
</property>

yarn-site.xml

<property>
<name>yarn.resourcemanager.ha.enabled</name>
<value>true</value>
</property>
<!-- 启用自动故障转移 -->
<property>
<name>yarn.resourcemanager.ha.automatic-failover.enabled</name>
<value>true</value>
</property>
<!-- 指定YARN HA的名称 -->
<property>
<name>yarn.resourcemanager.cluster-id</name>
<value>yarncluster</value>
</property>
<!-- 指定两个resourcemanager的名称 -->
<property>
<name>yarn.resourcemanager.ha.rm-ids</name>
<value>rm1,rm2</value>
</property>
<!-- 配置rm1，rm2的主机 -->
<property>
<name>yarn.resourcemanager.hostname.rm1</name>
<value>192.168.169.11</value>
</property>
<property>
<name>yarn.resourcemanager.hostname.rm2</name>
<value>192.168.169.12</value>
</property>
<!-- 配置YARN的http端口 -->
<property>
<name>yarn.resourcemanager.webapp.address.rm1</name>
<value>192.168.169.11:8088</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address.rm2</name>
<value>192.168.169.12:8088</value>
</property>
<!-- 配置zookeeper的地址 -->
<property>
<name>yarn.resourcemanager.zk-address</name>
<value>192.168.169.13:2181,192.168.169.14:2181,192.168.169.15:2181</value>
</property>
<!-- 配置zookeeper的存储位置 -->
<property>
<name>yarn.resourcemanager.zk-state-store.parent-path</name>
<value>/rmstore</value>
</property>
<!-- 开启yarn resourcemanager restart -->
<property>
<name>yarn.resourcemanager.recovery.enabled</name>
<value>true</value>
</property>
<!-- 配置resourcemanager的状态存储到zookeeper中 -->
<property>
<name>yarn.resourcemanager.store.class</name>
<value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
</property>
<!-- 开启yarn nodemanager restart -->
<property>
<name>yarn.nodemanager.recovery.enabled</name>
<value>true</value>
</property>
<!-- 配置nodemanager IPC的通信端口 -->
<property>
<name>yarn.nodemanager.address</name>
<value>0.0.0.0:45454</value>
</property>
<!-- 配置Web Application Proxy安全代理（防止yarn被攻击） -->
<property>
<name>yarn.web-proxy.address</name>
<value>192.168.169.12:8888</value>
</property>
<!-- 开启日志 -->
<property>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>

slaves

hbase3
hbase4
hbase5

d.集群初始化

　　// 启动zookeeper

　　// 格式化zkfc

　　// 启动journalnode

　　// 格式化hfds

　　// 将元数据目录拷贝到stangby节点

　　// 关闭journalnode

e.启动集群

《参考：https://blog.csdn.net/carl810224/article/details/52160418》