hadoop-2.7.1基于QMJ高可用安装配置
1.修改主机名及hosts文件
10.205.22.185 nn1 (主)作用namenode,resourcemanager,datanode,JournalNode,zk,zkfc(hive,sqoop可选)
10.205.22.186 nn2 (备)作用namenode,resourcemanager,datanode,JournalNode,zk,zkfc
10.205.22.187 dn1 作用datanode,JournalNode,zk
1.1配置ssh免密码登录
主节点能免密码登录各个从节点
ssh nn1
ssh nn2
ssh dn1
2. 安装jdk1.8和zookeeper(可根据需求决定是否安装hive,sqoop)
2.1修改profile文件,配置环境变量
export JAVA_HOME=/usr/java/jdk1..0_65
export JRE_HOME=/usr/java/jdk1..0_65/jre
export HADOOP_HOME=/app/hadoop-2.7.
export HIVE_HOME=/app/hive
export SQOOP_HOME=/app/sqoop
export ZOOKEEPER_HOME=/app/zookeeper-3.4.
export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$ZOOKEEPER_HOME/bin:$HIVE_HOME/bin:$SQOOP_HOME/bin:$MAVEN_HOME/bin
export CLASSPATH=.:$JAVA_HOME/lib:$JRE_HOME/lib
ulimit -SHn
2.2 修改zookeeper配置文件zoo.cfg
添加:
dataDir=/home/zookeeper
server.= nn1::
server.= nn2::
server.= dn1::
2.3 修改zookeeper的ID号
/home/zookeeper/myid
1 #nn1服务器myid修改为1
2 #nn2服务器myid修改为2
3 #nn3服务器myid修改为3
3.安装hadoop-2.7.1,修改配置文件
创建相应的目录
mkdir -p /home/hadoop/tmp
mkdir -p /home/hadoop/hdfs/data
mkdir -p /home/hadoop/journal
mkdir -p /home/hadoop/name
修改slaves文件
nn1
nn2
dn1
修改hadoop-env.sh文件
export JAVA_HOME=/usr/java/jdk1..0_65
export HADOOP_LOG_DIR=/home/hadoop/log/hadoop
修改hadoop日志记录文件log4j.properties
hadoop.log.dir=/home/hadoop/log/hadoop
定义yarn日志yarn-env.sh
YARN_LOG_DIR="/home/hadoop/log/yarn"
3.1配置hdfs-site.xml
<configuration>
<property>
<name>dfs.nameservices</name>
<value>masters</value>
</property>
<property>
<name>dfs.ha.namenodes.masters</name>
<value>nn1,nn2</value>
</property>
<property>
<name>dfs.namenode.rpc-address.masters.nn1</name>
<value>nn1:9000</value>
</property>
<property>
<name>dfs.namenode.http-address.masters.nn1</name>
<value>nn1:50070</value>
</property>
<property>
<name>dfs.namenode.rpc-address.masters.nn2</name>
<value>nn2:9000</value>
</property>
<property>
<name>dfs.namenode.http-address.masters.nn2</name>
<value>nn2:50070</value>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>file:/home/hadoop/hdfs/data</value>
</property>
<property>
<name>dfs.replication</name>
<value>2</value>
</property>
<property>
<name>dfs.namenode.name.dir</name>
<value>file:/home/hadoop/name</value>
</property>
<property>
<name>dfs.namenode.shared.edits.dir</name>
<value>qjournal://nn1:8485;nn2:8485;dn1:8485/masters</value>
</property>
<property>
<name>dfs.journalnode.edits.dir</name>
<value>/home/hadoop/journal</value>
</property>
<property>
<name>dfs.ha.automatic-failover.enabled</name>
<value>true</value>
</property>
<property>
<name>dfs.client.failover.proxy.provider.masters</name>
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
<property>
<name>dfs.ha.fencing.methods</name>
<value>sshfence</value>
</property>
<property>
<name>dfs.ha.fencing.ssh.private-key-files</name>
<value>/root/.ssh/id_rsa</value>
</property>
<property>
<name>dfs.ha.fencing.ssh.connect-timeout</name>
<value>30000</value>
</property>
</configuration>
3.2配置core-site.xml文件
<configuration>
<property>
<name>fs.defaultFS</name>
<value>hdfs://masters</value>
</property>
<property>
<name>hadoop.tmp.dir</name>
<value>/home/hadoop/tmp</value>
</property>
<property>
<name>ha.zookeeper.quorum</name>
<value>nn1:2181,nn2:2181,dn1:2181</value>
</property> <property>
<name>io.compression.codecs</name>
<value>org.apache.hadoop.io.compress.GzipCodec,org.apache.hadoop.io.compress.DefaultCodec,com.hadoop.compression.lzo.LzoCodec,com.hadoop.compression.lzo.LzopCodec,org.apache.hadoop.io.compress.BZip2Codec</value>
</property>
<property>
<name>io.compression.codec.lzo.class</name>
<value>com.hadoop.compression.lzo.LzoCodec</value>
</property>
</configuration>
3.3配置yarn-site.xml文件
<configuration>
<property>
<name>yarn.resourcemanager.ha.enabled</name>
<value>true</value>
</property>
<property>
<name>yarn.resourcemanager.cluster-id</name>
<value>rm-cluster</value>
</property>
<property>
<name>yarn.resourcemanager.ha.rm-ids</name>
<value>rm1,rm2</value>
</property>
<property>
<name>yarn.resourcemanager.ha.automatic-failover.enabled</name>
<value>true</value>
</property>
<property>
<name>yarn.resourcemanager.ha.automatic-failover.embedded</name>
<value>true</value>
</property>
<property>
<name>yarn.resourcemanager.hostname.rm1</name>
<value>nn1</value>
</property>
<property>
<name>yarn.resourcemanager.hostname.rm2</name>
<value>nn2</value>
</property>
<property>
<name>yarn.resourcemanager.store.class</name>
<value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
</property>
<property>
<name>yarn.resourcemanager.zk-address</name>
<value>nn1:,nn2:,dn1:</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address.rm1</name>
<value>nn1:</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address.rm2</name>
<value>nn2:</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address.rm1</name>
<value>nn1:</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address.rm2</name>
<value>nn2:</value>
</property>
<property>
<name>yarn.resourcemanager.address.rm1</name>
<value>nn1:</value>
</property>
<property>
<name>yarn.resourcemanager.address.rm2</name>
<value>nn2:</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address.rm1</name>
<value>nn1:</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address.rm2</name>
<value>nn2:</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address.rm1</name>
<value>nn1:</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address.rm2</name>
<value>nn2:</value>
</property>
<property>
<name>yarn.nodemanager.log-dirs</name>
<value>/home/hadoop/log/mapred</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
<property>
<name>yarn.client.failover-proxy-provider</name>
<value>org.apache.hadoop.yarn.client.ConfiguredRMFailoverProxyProvider</value>
</property>
</configuration>
3.4配置mapred-site.xml文件
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>mapreduce.jobhistory.address</name>
<value>nn1:10020</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>nn2:19888</value>
</property> <property>
<name>mapred.compress.map.output</name>
<value>true</value>
</property>
<property>
<name>mapred.map.output.compression.codec</name>
<value>com.hadoop.compression.lzo.LzoCodec</value>
</property>
<property>
<name>mapred.child.env</name>
<value>LD_LIBRARY_PATH=/usr/local/lzo/lib</value>
</property>
</configuration>
3.5同步hadoop到各个节点,并配置上述相关文件
4.启动服务
4.1在各个节点启动zookeeper,查看状态
zkServer.sh start
zkServer.sh status
在主节点格式化zookeeper
hdfs zkfc -formatZK
4.2在三个journalnode节点启日志程序
hadoop-daemon.sh start journalnode
4.3在主namenode节点格式化hadoop
hadoop namenode -format
4.4在主namenode节点启动namenode进程
hadoop-daemon.sh start namenode
4.5在备namenode节点执行命令,把备namenode节点的目录格式化并把元数据从主namenode节点同步过来
hdfs namenode -bootstrapStandby
hadoop-daemon.sh start namenode 启动namenode
yarn-daemon.sh start resourcemanager 启动resourcemanager
4.6启动其他相关服务
start-dfs.sh
start-yarn.sh
4.7 查看高可用状态
hdfs haadmin -getServiceState nn1/nn2 查看namenode
yarn rmadmin -getServiceState rm1/rm2 查看resourcemanager
4.8登录web查看状态
http://nn1:50070
http://nn1:8088
hadoop-2.7.1基于QMJ高可用安装配置的更多相关文章
- Centos7之pacemaker高可用安装配置详解
		
申明: centos7的pacemaker与6使用的方法不一致,即使用centos6.x的方法在centos7.x上面配置pacemaker不能成功. 因此openstack 上面的centos7.1 ...
 - Centos7 pcs pacemaker高可用安装配置详解
 - hadoop高可用安装和原理详解
		
本篇主要从hdfs的namenode和resourcemanager的高可用进行安装和原理的阐述. 一.HA安装 1.基本环境准备 1.1.1.centos7虚拟机安装,详情见VMware安装Cent ...
 - 实现基于Keepalived高可用集群网站架构的多种方法
		
实现基于Keepalived高可用集群网站架构 随着业务的发展,网站的访问量越来越大,网站访问量已经从原来的1000QPS,变为3000QPS,目前业务已经通过集群LVS架构可做到随时拓展,后端节点已 ...
 - hadoop 2.7.1 高可用安装部署
		
hadoop集群规划 目标:创建2个NameNode,做高可用,一个NameNode挂掉,另一个能够启动:一个运行Yarn,3台DataNode,3台Zookeeper集群,做高可用. 在hadoop ...
 - Kubernetes全栈架构师(二进制高可用安装k8s集群部署篇)--学习笔记
		
目录 二进制高可用基本配置 二进制系统和内核升级 二进制基本组件安装 二进制生成证书详解 二进制高可用及etcd配置 二进制K8s组件配置 二进制使用Bootstrapping自动颁发证书 二进制No ...
 - Kubernetes全栈架构师(二进制高可用安装k8s集群扩展篇)--学习笔记
		
目录 二进制Metrics&Dashboard安装 二进制高可用集群可用性验证 生产环境k8s集群关键性配置 Bootstrapping: Kubelet启动过程 Bootstrapping: ...
 - openstack pike 集群高可用  安装 部署   目录汇总
		
# openstack pike 集群高可用 安装部署#安装环境 centos 7 史上最详细的openstack pike版 部署文档欢迎经验分享,欢迎笔记分享欢迎留言,或加QQ群663105353 ...
 - openstack高可用haproxy配置
		
#openstack高可用haproxy配置openstack pike 部署 目录汇总 http://www.cnblogs.com/elvi/p/7613861.html #openstack高可 ...
 
随机推荐
- 20145305 《Java程序设计》实验五
			
实验内容 1.掌握Socket程序的编写: 2.掌握密码技术的使用: 3.设计安全传输系统. 实验步骤 基于Java Socket实现安全传输 基于TCP实现客户端和服务器,结对编程一人负责客户端,一 ...
 - Nginx+Tomcat+Keepalived+Memcache 负载均衡动静分离技术
			
一.概述 Nginx 作负载均衡器的优点许多,简单概括为: ①实现了可弹性化的架构,在压力增大的时候可以临时添加Tomcat服务器添加到这个架构里面去; ②upstream具有负载均衡能力,可以自动判 ...
 - maven项目导入报错
			
极大可能是仓库设置问题
 - Count the Colors(线段树染色)
			
Count the Colors Time Limit:2000MS Memory Limit:65536KB 64bit IO Format:%lld & %llu Submit ...
 - How to make 9-patch image downloaded from the Network
			
Probably everyone, who is in touch with the Android world dealt with 9-patch term. It is an image in ...
 - ansible高级用法
			
将多个符合正则的文件拷贝到目标机器 - name: Copy copy: src={{ item }} dest=/root/.sshkeys mode=0600 owner=root group=r ...
 - CVU介绍
			
ORA.CVU New resource (Cluster Verification Utility) is added in 11.2.0.2 Unlike the previous resour ...
 - UIApplication及UIWindow
			
*:first-child { margin-top: 0 !important; } body > *:last-child { margin-bottom: 0 !important; } ...
 - HDU 4121 Xiangqi   我老了?
			
Xiangqi Time Limit: 2000/1000 MS (Java/Others) Memory Limit: 32768/32768 K (Java/Others)Total Sub ...
 - CODESOFT 2015中的条形码对象该如何创建
			
CODESOFT条码设计软件提供了大量适应行业要求的符号,以及创建二维条形码的选项.用户可以通过条形码对话框选择符号.定义其属性以及输入要编码的消息.下面小编带大家具体学习下如何在CODESOFT ...