一、集群的规划
Zookeeper集群：
Hadoop集群： 二、准备工作
1、安装JDK 三、配置Zookeeper（在192.168.176.131安装）在主节点（bigdata112）上配置ZooKeeper （*）配置/training/zookeeper-3.4.6/conf/zoo.cfg文件 dataDir=/training/zookeeper-3.4.6/tmp server.1=bigdata112:2888:3888 server.2=bigdata113:2888:3888 server.3=bigdata114:2888:3888
（*）在/training/zookeeper-3.4.6/tmp目录下创建一个myid的空文件 （*）将配置好的zookeeper拷贝到其他节点，同时修改各自的myid文件
scp -r /training/zookeeper-3.4.6/ bigdata113:/training
scp -r /training/zookeeper-3.4.6/ bigdata114:/training
（*）分别修改113和114上/training/zookeeper-3.4.6/tmp/myid为2和3 四、安装Hadoop集群（在bigdata112上安装）
1、修改hadoo-env.sh 2、修改core-site.xml
<configuration>
<!-- 指定hdfs的nameservice为ns1 -->
<property>
<name>fs.defaultFS</name>
<value>hdfs://ns1</value>
</property>
<!-- 指定hadoop临时目录 -->
<property>
<name>hadoop.tmp.dir</name>
<value>/training/hadoop-2.7.3/tmp</value>
</property>
<!-- 指定zookeeper地址 -->
<property>
<name>ha.zookeeper.quorum</name>
<value>bigdata112:2181,bigdata113:2181,bigdata114:2181</value>
</property>
</configuration>
3、修改hdfs-site.xml（配置这个nameservice中有几个namenode）
<property>
<name>dfs.replication</name>
<value>2</value>
</property>
<property>
<name>dfs.webhdfs.enabled</name>
<value>true</value>
</property>
<configuration>
<!--指定hdfs的nameservice为ns1，需要和core-site.xml中的保持一致 -->
<property>
<name>dfs.nameservices</name>
<value>ns1</value>
</property>
<!-- ns1下面有两个NameNode，分别是nn1，nn2 -->
<property>
<name>dfs.ha.namenodes.ns1</name>
<value>nn1,nn2</value>
</property>
<!-- nn1的RPC通信地址 -->
<property>
<name>dfs.namenode.rpc-address.ns1.nn1</name>
<value>bigdata112:9000</value>
</property>
<!-- nn1的http通信地址 -->
<property>
<name>dfs.namenode.http-address.ns1.nn1</name>
<value>bigdata112:50070</value>
</property>
<!-- nn2的RPC通信地址 -->
<property>
<name>dfs.namenode.rpc-address.ns1.nn2</name>
<value>bigdata113:9000</value>
</property>
<!-- nn2的http通信地址 -->
<property>
<name>dfs.namenode.http-address.ns1.nn2</name>
<value>bigdata113:50070</value>
</property>
<!-- 指定NameNode的日志在JournalNode上的存放位置 -->
<property>
<name>dfs.namenode.shared.edits.dir</name>
<value>qjournal://bigdata112:8485;bigdata113:8485;/ns1</value>
</property>
<!-- 指定JournalNode在本地磁盘存放数据的位置 -->
<property>
<name>dfs.journalnode.edits.dir</name>
<value>/training/hadoop-2.7.3/journal</value>
</property>
<!-- 开启NameNode失败自动切换 -->
<property>
<name>dfs.ha.automatic-failover.enabled</name>
<value>true</value>
</property>
<!-- 配置失败自动切换实现方式 -->
<property>
<name>dfs.client.failover.proxy.provider.ns1</name>
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
<!-- 配置隔离机制方法，多个机制用换行分割，即每个机制暂用一行-->
<property>
<name>dfs.ha.fencing.methods</name>
<value>
sshfence
shell(/bin/true)
</value>
</property>
<!-- 使用sshfence隔离机制时需要ssh免登陆 -->
<property>
<name>dfs.ha.fencing.ssh.private-key-files</name>
<value>/root/.ssh/id_rsa</value>
</property>
<!-- 配置sshfence隔离机制超时时间 -->
<property>
<name>dfs.ha.fencing.ssh.connect-timeout</name>
<value>30000</value>
</property>
</configuration>
4、修改mapred-site.xml
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
</configuration>
5、修改yarn-site.xml
<configuration>
<!-- 开启RM高可靠 -->
<property>
<name>yarn.resourcemanager.ha.enabled</name>
<value>true</value>
</property>
<!-- 指定RM的cluster id -->
<property>
<name>yarn.resourcemanager.cluster-id</name>
<value>yrc</value>
</property>
<!-- 指定RM的名字 -->
<property>
<name>yarn.resourcemanager.ha.rm-ids</name>
<value>rm1,rm2</value>
</property>
<!-- 分别指定RM的地址 -->
<property>
<name>yarn.resourcemanager.hostname.rm1</name>
<value>bigdata112</value>
</property>
<property>
<name>yarn.resourcemanager.hostname.rm2</name>
<value>bigdata113</value>
</property>
<!-- 指定zk集群地址 -->
<property>
<name>yarn.resourcemanager.zk-address</name>
<value>bigdata112:2181,bigdata113:2181,bigdata114:2181</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
</configuration>
6、修改slaves
bigdata14
bigdata15
7、将配置好的hadoop拷贝到其他节点
scp -r /training/hadoop-2.7.3/ root@bigdata113:/training/
scp -r /training/hadoop-2.7.3/ root@bigdata114:/training/
scp -r /training/hadoop-2.7.3/ root@bigdata115:/training/
五、启动Zookeeper集群进到zk的安装目录的bin目录下：
启动
./zkServer.sh start
查看状态
./zkServer.sh status
六、在bigdata112和bigdata113上启动journalnodehadoop-daemon.sh start journalnode 七、格式化HDFS（在bigdata112上执行）
2.将112上这台的/training/hadoop-2.7.3/tmp/dfs拷贝到bigdata13的/training/hadoop-2.7.3/tmp/dfs下 scp -r /training/hadoop-2.7.3/tmp/dfs/* root@bigdata113:/training/hadoop-2.7.3/tmp/dfs/ 3.格式化zookeeper hdfs zkfc -formatZK 日志： 17/07/13 00:34:33 INFO ha.ActiveStandbyElector: Successfully created /hadoop-ha/ns1 in ZK. 八、在bigdata12上启动Hadoop集群
start-all.sh
日志：
Starting namenodes on [bigdata12 bigdata13]
bigdata12: starting namenode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-namenode-hadoop113.out
bigdata13: starting namenode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-namenode-hadoop112.out
bigdata14: starting datanode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-datanode-hadoop115.out
bigdata15: starting datanode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-datanode-hadoop114.out
bigdata13: starting zkfc, logging to /root/training/hadoop-2.7.3/logs/hadoop-root-zkfc-bigdata13.out
bigdata12: starting zkfc, logging to /root/training/hadoop-2.7.3/logs/hadoop-root-zkfc-bigdata12.out
bigdata113上的ResourceManager需要单独启动
命令：yarn-daemon.sh start resourcemanager
九、问题延伸
1、隔离机制和隔离级别
（*）关系型数据库：如果不考虑事务隔离级别，造成脏读、不可重复读、幻读
（*）HDFS的HA：如果不考虑隔离机制（隔离级别），造成脑裂的问题
2、什么是脑裂的问题？
脑裂的问题，针对的是数据节点（DataNode）
由于某种原因，造成了整个HDFS中存在多个active的NameDode，这时候DataNode就不知道谁是真正的NameNode。
(责任编辑：IT) |