【2】搭建HA高可用hadoop-2.3（安装zookeeper）
【3】搭建HA高可用hadoop-2.3（部署配置hadoop--cdh5.1.0）
【4】搭建HA高可用hadoop-2.3（部署配置HBase）
安装部署hadoop
(1)安装hadoop
master1、master2、slave1、slave2、slave3
#cd /opt/ #tar xf hadoop-2.3.0-cdh5.1.0.tar.gz
#ln -s ln -s hadoop-2.3.0-cdh5.1.0 hadoop
(2)添加hadoop环境变量
master1、master2、slave1、slave2、slave3
#cat >> /etc/profile <<EOFexport HADOOP_HOME=/opt/hadoopexport PATH=$PATH:$HADOOP_HOME/binEOF#source /etc/profile
(3)配置hadoop
|
主要配置文件 (hadoop-2.3.0-cdh5.1.0 /etc/hadoop/) |
格式 | 作用 |
| hadoop-env.sh | bash脚本 | hadoop需要的环境变量 |
| core-site.xml | xml | hadoop的core的配置项 |
| hdfs-site.xml | xml | hdfs的守护进程配置，包括namenode、datanode |
| slaves | 纯文本 | datanode的节点列表（每行一个） |
| mapred-env.sh | bash脚本 | mapreduce需要的环境变量 |
| mapre-site.xml | xml | mapreduce的守护进程配置 |
| yarn-env.sh | bash脚本 | yarn需要的环境变量 |
| yarn-site.xml | xml | yarn的配置项 |
以下1-8的配置，所有机器都相同，可先配置一台，将配置统一copy到另外几台机器。
master1、master2、slave1、slave2、slave3
1:配置hadoop-env.sh
cat >> hadoop-env.sh <<EOFexport JAVA_HOME=/usr/java/jdk1.8.0_60export HADOOP_HOME=/opt/hadoop-2.3.0-cdh5.1.0EOF
2:配置core-site.xml
#mkdir -p /data/hadoop/tmp#vim core-site.xml<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="configuration.xsl"?><configuration> <property> <!--填写hdfs集群名，因为是HA，两个namenode--> <name>fs.defaultFS</name> <value>hdfs://mycluster</value> </property> <property> <!-- hadoop很多路径都依赖他，namenode节点该目录不可以删除，否则要重新格式化--> <name>hadoop.tmp.dir</name> <value>/data/hadoop/tmp</value> </property> <property> <!--zookeeper集群的地址--> <name>ha.zookeeper.quorum</name> <value>master1:2181,master2:2181,slave1:2181,slave2:2181,slave3:2181</value> </property></configuration>
3:配置hdfs-site.xml
#mkdir -p /data/hadoop/dfs/{namenode,datanode}#mkdir -p /data/hadoop/ha/journal#vim hdfs-site.xml<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="configuration.xsl"?><!--hdfs-site.xml--><configuration> <property> <!--设置为true，否则一些命令无法使用如：webhdfs的LISTSTATUS--> <name>dfs.webhdfs.enabled</name> <value>true</value> </property> <property> <!--数据三副本--> <name>dfs.replication</name> <value>3</value> </property> <property> <!--namenode的数据目录，存储集群元数据--> <name>dfs.namenode.name.dir</name> <value>file:/data/hadoop/dfs/namenode</value> </property> <property> <!--datenode的数据目录--> <name>dfs.datanode.data.dir</name> <value>file:/data/hadoop/dfs/datanode</value> </property> <property> <!--可选，关闭权限带来一些不必要的麻烦--> <name>dfs.permissions</name> <value>false</value> </property> <property> <!--可选，关闭权限带来一些不必要的麻烦--> <name>dfs.permissions.enabled</name> <value>false</value> </property> <!--HA配置--> <property> <!--设置集群的逻辑名--> <name>dfs.nameservices</name> <value>mycluster</value> </property> <property> <!--hdfs集群中的namenode节点逻辑名--> <name>dfs.ha.namenodes.mycluster</name> <value>namenode1,namenode2</value> </property> <property> <!--hdfs namenode逻辑名中RPC配置，rpc简单理解为序列化文件上传输出文件要用到--> <name>dfs.namenode.rpc-address.mycluster.namenode1</name> <value>master1:9000</value> </property> <property> <!--hdfs namenode逻辑名中RPC配置，rpc简单理解为序列化文件上传输出文件要用到--> <name>dfs.namenode.rpc-address.mycluster.namenode2</name> <value>master2:9000</value> </property> <property> <!--配置hadoop页面访问端口--> <name>dfs.namenode.http-address.mycluster.namenode1</name> <value>master1:50070</value> </property> <property> <name>dfs.namenode.http-address.mycluster.namenode2</name> <value>master2:50070</value> </property> <property> <!--建立与namenode的通信--> <name>dfs.namenode.servicerpc-address.mycluster.namenode1</name> <value>master1:53310</value> </property> <property> <name>dfs.namenode.servicerpc-address.mycluster.namenode2</name> <value>master2:53310</value> </property> <property> <!--journalnode 共享文件集群--> <name>dfs.namenode.shared.edits.dir</name> <value>qjournal://master1:8485;master2:8485;slave1:8485;slave2:8485;slave3:8485/mycluster</value> </property> <property> <!--journalnode对namenode的进行共享设置--> <name>dfs.journalnode.edits.dir</name> <value>/data/hadoop/ha/journal</value> </property> <property> <!--设置故障处理类--> <name>dfs.client.failover.proxy.provider.mycluster</name> <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value> </property> <property> <!--开启自动切换，namenode1 stanby后nn2或active--> <name>dfs.ha.automatic-failover.enabled</name> <value>true</value> </property> <property> <!--zookeeper集群的地址--> <name>ha.zookeeper.quorum</name> <value>master1:2181,master2:2181,slave1:2181,slave2:2181,slave3:2181</value> </property> <property> <!--使用ssh方式进行故障切换--> <name>dfs.ha.fencing.methods</name> <value>sshfence</value> </property> <property> <!--ssh通信密码通信位置--> <name>dfs.ha.fencing.ssh.private-key-files</name> <value>/root/.ssh/id_rsa</value> </property></configuration>
4:配置mapred-env.sh
cat >> mapred-env.sh <<EOF#heqinqin configureexport JAVA_HOME=/usr/java/jdk1.8.0_60EOF
5:配置mapred-site.xml
<?xml version="1.0"?><?xml-stylesheet type="text/xsl" href="configuration.xsl"?><configuration> <name>mapreduce.framework.name</name> <value>yarn<value></configuration>
6:配置yarn-env.sh
cat >> yarn-env.sh <<EOF#heqinqin configureexport JAVA_HOME=/usr/java/jdk1.8.0_60EOF
7:配置yarn-site.xml
#mkdir -p /data/hadoop/yarn/local#mkdir -p /data/hadoop/logs#chown -R hadoop /data/hadoop#vim yarn-site.xml<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="configuration.xsl"?><!--####################yarn-site.xml#########################--><configuration> <property> <!--rm失联后重新链接的时间--> <name>yarn.resourcemanager.connect.retry-interval.ms</name> <value>2000</value> </property> <property> <!--开启resource manager HA,默认为false--> <name>yarn.resourcemanager.ha.enabled</name> <value>true</value> </property> <property> <!--开启故障自动切换--> <name>yarn.resourcemanager.ha.automatic-failover.enabled</name> <value>true</value> </property> <property> <!--配置resource manager --> <name>yarn.resourcemanager.ha.rm-ids</name> <value>rm1,rm2</value> </property> <property> <name>yarn.resourcemanager.ha.id</name> <value>rm1</value> <description>If we want to launch more than one RM in single node, we need this configuration</description> </property> <property> <!--开启自动恢复功能--> <name>yarn.resourcemanager.recovery.enabled</name> <value>true</value> </property> <property> <!--配置与zookeeper的连接地址--> <name>yarn.resourcemanager.zk-state-store.address</name> <value>localhost:2181</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>localhost:2181</value> </property> <property> <name>yarn.resourcemanager.cluster-id</name> <value>yarncluster</value> </property> <property> <!--schelduler失联等待连接时间--> <name>yarn.app.mapreduce.am.scheduler.connection.wait.interval-ms</name> <value>5000</value> </property><!--配置resourcemanager--> <!--配置rm1--> <property> <!--配置应用管理端口--> <name>yarn.resourcemanager.address.rm1</name> <value>master1:8032</value> </property> <property> <!--scheduler调度器组建的ipc端口--> <name>yarn.resourcemanager.scheduler.address.rm1</name> <value>master1:8030</value> </property> <property> <!--http服务端口--> <name>yarn.resourcemanager.webapp.address.rm1</name> <value>master1:8088</value> </property> <property> <!--IPC端口--> <name>yarn.resourcemanager.resource-tracker.address.rm1</name> <value>master1:8031</value> </property> <property> <!--IPC端口--> <name>yarn.resourcemanager.admin.address.rm1</name> <value>master1:8033</value> </property> <property> <name>yarn.resourcemanager.ha.admin.address.rm1</name> <value>master1:8035</value> </property> <!--配置rm2--> <property> <!--application 管理端口--> <name>yarn.resourcemanager.address.rm2</name> <value>master2:8032</value> </property> <property> <!--scheduler调度器端口--> <name>yarn.resourcemanager.scheduler.address.rm2</name> <value>master2:8030</value> </property> <property> <!--http服务端口--> <name>yarn.resourcemanager.webapp.address.rm2</name> <value>master2:8088</value> </property> <property> <!--ipc端口--> <name>yarn.resourcemanager.resource-tracker.address.rm2</name> <value>master2:8031</value> </property> <property> <!--ipc端口--> <name>yarn.resourcemanager.admin.address.rm2</name> <value>master2:8033</value> </property> <property> <name>yarn.resourcemanager.ha.admin.address.rm2</name> <value>master2:8035</value> </property><!--配置nodemanager--> <property> <!--配置localizer ipc端口--> <description>Address where the localizer IPC is.</description> <name>yarn.nodemanager.localizer.address</name> <value>0.0.0.0:8040</value> </property> <property> <!--nodemanager http访问端口--> <description>NM Webapp address.</description> <name>yarn.nodemanager.webapp.address</name> <value>0.0.0.0:8042</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.nodemanager.local-dirs</name> <value>/data/hadoop/yarn/local</value> </property> <property> <name>yarn.nodemanager.log-dirs</name> <value>/data/hadoop/logs</value> </property> <property> <name>mapreduce.shuffle.port</name> <value>8050</value> </property><!--故障处理类--> <property> <name>yarn.client.failover-proxy-provider</name> <value>org.apache.hadoop.yarn.client.ConfiguredRMFailoverProxyProvider</value> </property></configuration>
8:配置slaves
cat >> slaves <<EOFslave1slave2slave3EOF
配置完毕
启动集群
(1)格式化命名空间
master1
#/opt/hadoop/bin/hdfs zkfc -formatZK
(2)启动journalnode
master1、master2、slave1、slave2、slave3 （集群内随意算则奇数台机器作为journalnode，三台也可以）
#/opt/hadoop/sbin/hadoop-daemon.sh start journalnode
(3)master1节点格式化，并启动namenode
master1
格式化namenode的目录
#/opt/hadoop/bin/hadoop namenode -format mycluster
启动namenode
#/opt/hadoop/sbin/hadoop-daemon.sh start namenode
(4)master2节点同步master1的格式化目录，并启动namenode
master2
从master1将格式化的目录同步过来
#/opt/hadoop/bin/hdfs namenode -bootstrapStandby
启动namenode
#/opt/hadoop/sbin/hadoop-daemon.sh start namenode
(5)master节点启动zkfs
master1、master2
#/opt/hadoop/sbin/hadoop-daemon.sh start zkfc
(6)slave节点启动datanode
slave1、slave2、slave3
#/opt/hadoop/sbin/hadoop-daemon.sh start datanode
(7)master节点启动yarn
master1
#/opt/hadoop/sbin/start-yarn.sh
(8)master节点启动historyserver
master1
./mr-jobhistory-daemon.sh start historyserver
集群已启动。在各服务器执行jps查看，两个master上各一个namenode，形成namenode高可用，实现故障自动切换。
【2】搭建HA高可用hadoop-2.3（安装zookeeper）
【3】搭建HA高可用hadoop-2.3（部署配置hadoop--cdh5.1.0）
【4】搭建HA高可用hadoop-2.3（部署配置HBase）
本文出自 “酱酱酱子” 博客，请务必保留此出处http://heqin.blog.51cto.com/8931355/1789069