Hadoop2.6.5高可用集群搭建
软件环境:
linux系统: CentOS6.7
Hadoop版本: 2.6.5
zookeeper版本: 3.4.8主机配置:
一共m1, m2, m3这五部机, 每部主机的用户名都为centos
192.168.179.201: m1
192.168.179.202: m2
192.168.179.203: m3
m1: Zookeeper, Namenode, DataNode, ResourceManager, NodeManager, Master, Worker
m2: Zookeeper, Namenode, DataNode, ResourceManager, NodeManager, Worker
m3: Zookeeper, DataNode, NodeManager, Worker前期准备
1.配置主机IP:
sudo vi /etc/sysconfig/network-scripts/ifcfg-eth02.配置主机名:
sudo vi /etc/sysconfig/network3.配置主机名和IP的映射关系:
sudo vi /etc/hosts4.关闭防火墙
(1)临时关闭:
service iptables stopservice iptables status(2)开机时自动关闭:
chkconfig iptables offchkconfig iptables --list
搭建步骤：
一.安装配置Zookeeper集群（在m3.m4,m5三部主机上）
1.解压
tar -zxvf zookeeper-3.4.8.tar.gz -C /home/hadoop/soft/zookeeper2.配置环境变量
vi /etc/profile## Zookeeper
export ZK_HOME=/home/centos/soft/zookeeper
export CLASSPATH=$CLASSPATH:$ZK_HOME/lib
export PATH=$PATH:$ZK_HOME/sbin:$ZK_HOME/binsource /etc/profile3.修改配置
(1)配置zoo.cfg文件
cd /home/centos/soft/zookeeper/conf/cp zoo_sample.cfg zoo.cfgvi zoo.cfg
## 修改dataDir此项配置
dataDir=/home/centos/soft/zookeeper/tmp
## 添加以下三项配置
server.1=m3:2888:3888
server.2=m4:2888:3888
server.3=m5:2888:3888(2)创建tmp目录
mkdir /home/centos/soft/zookeeper/tmp(3)编辑myid文件
touch /home/centos/soft/zookeeper/tmp/myidecho 1 > /home/centos/soft/zookeeper/tmp/myid ## 在m3主机上myid=14.配置zookeeper日志存放位置
- 编辑
zkEnv.sh文件
vi /home/centos/soft/zookeeper/bin/zkEnv.sh
# 编辑下列该项配置
if [ "x${ZOO_LOG_DIR}" = "x" ]
then
ZOO_LOG_DIR="/home/centos/soft/zookeeper/logs" ## 修改此项
fi
(5)创建logs目录
mkdir /home/centos/soft/zookeeper/logs5. 拷贝到其他主机并修改myid
(1)拷贝到其他主机
scp -r /home/centos/soft/zookeeper/ m4:/home/centos/soft/
scp -r /home/centos/soft/zookeeper/ m5:/home/centos/soft/(2)修改myid
echo 2 > /home/centos/soft/zookeeper/tmp/myid ## m4主机
echo 3 > /home/centos/soft/zookeeper/tmp/myid ## m5主机
二.安装配置hadoop集群
1.解压
tar -zxvf hadoop-2.6.5.tar.gz -C /home/centos/soft/hadoop2.将Hadoop配置进环境变量
vi /etc/profile## Java
export JAVA_HOME=/home/centos/soft/jdk
export CLASSPATH=$CLASSPATH:$JAVA_HOME/lib
export PATH=$PATH:$JAVA_HOME/bin
## Hadoop
export HADOOP_USER_NAME=centos
export HADOOP_HOME=/home/centos/soft/hadoop
export CLASSPATH=$CLASSPATH:$HADOOP_HOME/lib
export PATH=$PATH:$HADOOP_HOME/binsource /etc/profile3.编辑hadoop-env.sh文件
1.编辑hadoop-env.sh文件
export JAVA_HOME=/home/centos/soft/jdk2.编辑core-site.xml文件
<configuration>
<property>
<name>fs.defaultFSname>
<value>hdfs://ns1value>
property>
<property>
<name>hadoop.tmp.dirname>
<value>/home/centos/soft/hadoop/tmpvalue>
property>
<property>
<name>ha.zookeeper.quorumname>
<value>m3:2181,m4:2181,m5:2181value>
property>
<property>
<name>hadoop.proxyuser.centos.hostsname>
<value>*value>
property>
<property>
<name>hadoop.proxyuser.centos.groupsname>
<value>*value>
property>
configuration>3.编辑hdfs-site.xml文件
<configuration>
<property>
<name>dfs.nameservicesname>
<value>ns1value>
property>
<property>
<name>dfs.ha.namenodes.ns1name>
<value>nn1,nn2value>
property>
<property>
<name>dfs.namenode.rpc-address.ns1.nn1name>
<value>m1:9000value>
property>
<property>
<name>dfs.namenode.http-address.ns1.nn1name>
<value>m1:50070value>
property>
<property>
<name>dfs.namenode.rpc-address.ns1.nn2name>
<value>m2:9000value>
property>
<property>
<name>dfs.namenode.http-address.ns1.nn2name>
<value>m2:50070value>
property>
<property>
<name>dfs.namenode.shared.edits.dirname>
<value>qjournal://m3:8485;m4:8485;m5:8485/ns1value>
property>
<property>
<name>dfs.journalnode.edits.dirname>
<value>/home/centos/soft/hadoop/journalvalue>
property>
<property>
<name>dfs.namenode.name.dirname>
<value>/home/centos/soft/hadoop/tmp/dfs/namevalue>
property>
<property>
<name>dfs.datanode.data.dirname>
<value>/home/centos/soft/hadoop/tmp/dfs/datavalue>
property>
<property>
<name>dfs.replicationname>
<value>1value>
property>
<property>
<name>dfs.ha.automatic-failover.enabledname>
<value>truevalue>
property>
<property>
<name>dfs.webhdfs.enabledname>
<value>truevalue>
property>
<property>
<name>dfs.client.failover.proxy.provider.ns1name>
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvidervalue>
property>
<property>
<name>dfs.ha.fencing.methodsname>
<value>
sshfence
shell(/bin/true)
value>
property>
<property>
<name>dfs.ha.fencing.ssh.private-key-filesname>
<value>/home/centos/.ssh/id_rsavalue>
property>
<property>
<name>dfs.ha.fencing.ssh.connect-timeoutname>
<value>30000value>
property>
<property>
<name>dfs.permissionsname>
<value>falsevalue>
property>
<property>
<name>heartbeat.recheck.intervalname>
<value>2000value>
property>
<property>
<name>dfs.heartbeat.intervalname>
<value>1value>
property>
<property>
<name>dfs.blockreport.intervalMsecname>
<value>3600000value>
<description>Determines block reporting interval in milliseconds.description>
property>
configuration>4.编辑mapred-site.xml文件
<configuration>
<property>
<name>mapreduce.framework.namename>
<value>yarnvalue>
property>
<property>
<name>mapreduce.jobhistory.addressname>
<value>0.0.0.0:10020value>
<description>MapReduce JobHistory Server IPC host:portdescription>
property>
<property>
<name>mapreduce.jobhistory.webapp.addressname>
<value>0.0.0.0:19888value>
<description>MapReduce JobHistory Server Web UI host:portdescription>
property>
<property>
<name>mapreduce.task.io.sort.mbname>
<value>1value>
property>
<property>
<name>yarn.app.mapreduce.am.staging-dirname>
<value>/uservalue>
property>
<property>
<name>mapreduce.jobhistory.intermediate-done-dirname>
<value>/user/history/done_intermediatevalue>
property>
<property>
<name>mapreduce.jobhistory.done-dirname>
<value>/user/historyvalue>
property>
configuration> 5.编辑yarn-site.xml文件
<configuration>
<property>
<name>yarn.resourcemanager.ha.enabledname>
<value>truevalue>
property>
<property>
<name>yarn.resourcemanager.cluster-idname>
<value>yrcvalue>
property>
<property>
<name>yarn.resourcemanager.ha.rm-idsname>
<value>rm1,rm2value>
property>
<property>
<name>yarn.resourcemanager.hostname.rm1name>
<value>m1value>
property>
<property>
<name>yarn.resourcemanager.hostname.rm2name>
<value>m2value>
property>
<property>
<name>yarn.resourcemanager.zk-addressname>
<value>m3:2181,m4:2181,m5:2181value>
property>
<property>
<name>yarn.nodemanager.aux-servicesname>
<value>mapreduce_shuffle,spark_shufflevalue>
property>
<property>
<name>yarn.nodemanager.resource.memory-mbname>
<value>2048value>
property>
<property>
<name>yarn.scheduler.maximum-allocation-mbname>
<value>4096value>
property>
<property>
<name>yarn.nodemanager.log-dirsname>
<value>/home/centos/soft/hadoop/logsvalue>
property>
<property>
<name>yarn.resourcemanager.scheduler.classname>
<value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairSchedulervalue>
property>
<property>
<name>yarn.nodemanager.aux-services.spark_shuffle.classname>
<value>org.apache.spark.network.yarn.YarnShuffleServicevalue>
property>
<property>
<name>yarn.nodemanager.pmem-check-enabledname>
<value>falsevalue>
<description>是否启动一个线程检查每个任务正使用的物理内存量，如果任务超出分配值，则直接将其杀掉，默认是truedescription>
property>
<property>
<name>yarn.nodemanager.vmem-check-enabledname>
<value>falsevalue>
<description>是否启动一个线程检查每个任务正使用的物理内存量，如果任务超出分配值，则直接将其杀掉，默认是truedescription>
property>
<property>
<name>spark.shuffle.service.portname>
<value>7337value>
property>
configuration>6.编辑slaves文件
编辑slaves文件, slaves是指定子节点的位置, 在HDFS上为DataNode的节点位置, 在YARN上为NodeManager的节点位置, 以你的实际情况而定
m3
m4
m5
三.初始化Hadoop
1. 配置主机之间免密码登陆
(1)在m1上生产一对密匙
ssh-keygen -t rsa(2)将公钥拷贝到其他节点，包括本主机
ssh-coyp-id 127.0.0.1
ssh-coyp-id localhost
ssh-coyp-id m1
ssh-coyp-id m2
ssh-coyp-id m3(3)在其他主机上重复(1)(2)的操作
2.将配置好的hadoop拷贝到其他节点
scp -r /home/centos/soft/hadoop m2:/home/centos/soft/
scp -r /home/centos/soft/hadoop m3:/home/centos/soft/
scp -r /home/centos/soft/hadoop m4:/home/centos/soft/
scp -r /home/centos/soft/hadoop m5:/home/centos/soft/注意：严格按照下面的步骤
3.启动zookeeper集群（分别在m3、m4、m5上启动zk)
- 启动zookeeper服务
cd /home/centos/soft/zookeeper-3.4.5/bin/./zkServer.sh start- 查看状态：一个leader，两个follower
./zkServer.sh status4.启动journalnode (分别在m3、m4、m5主机上执行, 必须在HDFS格式化前执行, 不然会报错)
(1)启动JournalNode服务
cd /home/centos/soft/hadoopsbin/hadoop-daemon.sh start journalnode(2)运行jps命令检验，m3、m4、m5上多了JournalNode进程
jps5.格式化HDFS(在m1上执行即可)
(1)在m1上执行命令:
hdfs namenode -format(2)格式化后会在根据core-site.xml中的hadoop.tmp.dir配置生成个文件，这里我配置的是/home/centos/soft/hadoop/tmp，然后将m1主机上的/home/centos/soft/hadoop下的tmp目录拷贝到m2主机上的/home/centos/soft/hadoop目录下
scp -r /home/centos/soft/hadoop/tmp/ m2:/home/centos/soft/hadoop/6.格式化ZK(在m1上执行)
hdfs zkfc -formatZK7.启动HDFS(在m1上执行)
sbin/start-dfs.sh8.启动YARN(在m1,m2上执行)
sbin/start-yarn.sh至此，Hadoop-2.6.5配置完毕!!!
四.检验Hadoop集群搭建成功
0.在Windows下编辑hosts文件, 配置主机名与IP的映射(此步骤可跳过)**
C:\Windows\System32\drivers\etc\hosts
192.168.179.201 m1
192.168.179.202 m2
192.168.179.203 m3
192.168.179.204 m4
192.168.179.205 m51.可以统计浏览器访问:
http://m1:50070
NameNode 'm1:9000' (active)
http://m2:50070
NameNode 'm2:9000' (standby)2.验证HDFS HA
(1)首先向hdfs上传一个文件
hadoop fs -put /etc/profile /profile(2)查看是否已上传到HDFS上
hadoop fs -ls /(3)然后再kill掉active的NameNode
kill -9 of NN> (4)通过浏览器访问：http://m2:50070
NameNode 'm2:9000' (active) ## 主机m2上的NameNode变成了active(5)执行命令：
hadoop fs -ls / ## 看之前在m1上传的文件是否还存在！！！(6)手动在m1上启动挂掉的NameNode
sbin/hadoop-daemon.sh start namenode(7)通过浏览器访问：http://m1:50070
NameNode 'm1:9000' (standby)3.验证YARN：
- 用浏览器访问: http://m1:8088, 查看是否有NodeManager服务在运行
- 运行一下hadoop提供的demo中的WordCount程序, 在linux上执行以下命令
hadoop jar /home/centos/soft/hadoop/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.5.jar wordcount InputParameter OutputParameter在http://m1:8088 上是否有application在运行,若有则YARN没问题
OK，大功告成！！！