一、集群的规划

Zookeeper集群:
192.168.176.131 (bigdata112)
192.168.176.132 (bigdata113)
192.168.176.135 (bigdata114)

Hadoop集群:
192.168.176.131 (bigdata112) NameNode1 ResourceManager1 Journalnode
192.168.176.132 (bigdata113) NameNode2 ResourceManager2 Journalnode
192.168.176.135 (bigdata114) DataNode1 NodeManager1
192.168.176.136 (bigdata115) DataNode2 NodeManager2

二、准备工作

1、安装JDK
2、配置环境变量
3、配置免密码登录
4、配置主机名

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
echo 1 > /training/zookeeper-3.4.6/tmp/myid

(*)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
export JAVA_HOME=/training/jdk1.8.0_144

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journalnode

hadoop-daemon.sh start journalnode

七、格式化HDFS(在bigdata112上执行)

  1. 格式化HDFS
    hdfs namenode -format

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。