bigdata-02-hadoop2.8.4-resourceHA安装

时间 2020-06-17

标签 bigdata hadoop2.8.4 hadoop resourceha 安装栏目大数据繁體版

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1, 电脑环境准备

1), 关闭selinux

vim /etc/selinux/config SELINUX=disabled

2), 时间同步

yum -y install chrony

修改时间服务器配置, 并重启java

vim  /etc/chrony.conf [root@dock hadoop]# cat /etc/chrony.conf | grep -v ^$ | grep -v ^# server 0.centos.pool.ntp.org iburst server 1.centos.pool.ntp.org iburst server 2.centos.pool.ntp.org iburst server 3.centos.pool.ntp.org iburst driftfile /var/lib/chrony/drift makestep 1.0 3 rtcsync allow 192.168.199.0/16 local stratum 10 logdir /var/log/chrony

修改须要同步的服务器配置, 并重启node

vim /etc/chrony.conf [root@node1 ~]# cat /etc/chrony.conf | grep -v ^$ | grep -v ^# server 192.168.199.131 iburst driftfile /var/lib/chrony/drift makestep 1.0 3 rtcsync logdir /var/log/chrony

执行时间同步linux

systemctl restart chronyd [root@node2 ~]# chronyc sources -v 210 Number of sources = 1 .-- Source mode  '^' = server, '=' = peer, '#' = local clock. / .- Source state '*' = current synced, '+' = combined , '-' = not combined, | /   '?' = unreachable, 'x' = time may be in error, '~' = time too variable. ||                                                 .- xxxx [ yyyy ] +/- zzzz ||      Reachability register (octal) -.           |  xxxx = adjusted offset, ||      Log2(Polling interval) --.      |          |  yyyy = measured offset, ||                                \     |          |  zzzz = estimated error. ||                                 |    | \ MS Name/IP address Stratum Poll Reach LastRx Last sample ===============================================================================
^* dock                          3   6   177     4  -1590ns[  +62us] +/-   13ms

查看时间同步: apache

[root@node3 ~]# timedatectl Local time: Wed 2018-03-21 08:16:02 EDT Universal time: Wed 2018-03-21 12:16:02 UTC RTC time: Wed 2018-03-21 12:16:02 Time zone: America/New_York (EDT, -0400) NTP enabled: yes NTP synchronized: yes RTC in local TZ: no DST active: yes Last DST change: DST began at Sun 2018-03-11 01:59:59 EST Sun 2018-03-11 03:00:00 EDT Next DST change: DST ends (the clock jumps one hour backwards) at Sun 2018-11-04 01:59:59 EDT Sun 2018-11-04 01:00:00 EST

3), 修改hostname, 不少集群都须要执行这一个

hostname node1, hostname node2 hostname node3

4), jdk 版本

java -version 1.8.0_161编程

5), 设置免密登录

ssh-keygen -t dsa -P '' -f ~/.ssh/id_dsa

发送到namenode, 设置bootstrap

非root用户, 记得修改authorized 权限为。600vim

cat ~/.ssh/id_dsa.pub >> ~/.ssh/authorized_keys

2, zookeeper 安装

参照其余博客..centos

3, hadoop安装

zkFc-用来作HA的备份和切换的, 作active, standby的状态管理的, 监控namenode进程, 记录信息到zookeeper中服务器

journalNode--复制fsimage和edtis的框架

1), 修改环境变量

export HADOOP_HOME=/usr/local/hadoop-2.7.5 export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin

2), 修改hadoop-env.sh

cd {HADOOP_HOME}/etc/hadoop export JAVA_HOME=/usr/local/jdk/jdk1.8.0_161

3), 配置core_site.xml

<configuration>
    <property>
　　　　　<--! 指定hdfs的nameservice -->
        <name>fs.defaultFS</name>
        <value>hdfs://hdfscluster</value>
    </property>
    <property>
　　　　<!-- 指定hadoop临时目录 -->
        <name>hadoop.tmp.dir</name>
        <value>/usr/local/hadoop-2.8.4/tmp</value>
    </property>

    <property>
　　　　<!-- 指定zookeeper地址 -->
        <name>ha.zookeeper.quorum</name>
        <value>node1:2181,node2:2181,node3:2181</value>
    </property>
</configuration>

4), 修改 hdfs-site.xml

<configuration>
    <!--指定hdfs的nameservice为ns1，须要和core-site.xml中的保持一致 -->
    <property>
        <name>dfs.nameservices</name>
        <value>hdfscluster</value>
    </property>
    <!-- ns1下面有两个NameNode，分别是nn1，nn2 -->
    <property>
        <name>dfs.ha.namenodes.hdfscluster</name>
        <value>nn1,nn2</value>
    </property>
    <!-- nn1的RPC通讯地址 -->
    <property>
        <name>dfs.namenode.rpc-address.hdfscluster.nn1</name>
        <value>192.168.199.182:8020</value>
    </property>
    <!-- nn1的http通讯地址 -->
    <property>
        <name>dfs.namenode.http-address.hdfscluster.nn1</name>
        <value>192.168.199.182:50070</value>
    </property>
    <!-- nn2的RPC通讯地址 -->
    <property>
        <name>dfs.namenode.rpc-address.hdfscluster.nn2</name>
        <value>192.168.199.247:8020</value>
    </property>
    <!-- nn2的http通讯地址 -->
    <property>
        <name>dfs.namenode.http-address.hdfscluster.nn2</name>
        <value>192.168.199.247:50070</value>
    </property>
    <!-- 指定NameNode的元数据在JournalNode上的存放位置 -->
    <property>
        <name>dfs.namenode.shared.edits.dir</name>
        <value>qjournal://node1:8485;node2:8485;node3:8485/hdfscluster</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>/usr/local/hadoop-2.8.4/journaldata</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.hdfscluster</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，即每一个机制暂用一行-->

<property>
        <name>dfs.ha.fencing.methods</name>
        <value>sshfence</value>
    </property>

<!-- 使用sshfence隔离机制时须要ssh免登录 -->
    <property>
        <name>dfs.ha.fencing.ssh.private-key-files</name>
        <value>/root/.ssh/id_dsa</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>

备注: 若是集群成功后, 但建立目录显示: ipc.Client: Retrying connect to serve, 就更改成

5), 添加 slaves

vim slaves node1 node2 node3

4, 配置yarn

1), 修改mapred-site.xml.template 为 mapred-site.xml

<configuration>  
    <!-- 指定mr框架为yarn方式 -->  
    <property>  
        <name>mapreduce.framework.name</name>  
        <value>yarn</value>  
    </property>  
</configuration>

2), 配置 yarn-site.xml

<configuration>

<!-- Site specific YARN configuration properties -->
<!-- 开启RM高可用 -->
    <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>yarncluster</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>node1</value>
    </property>
    <property>
       <name>yarn.resourcemanager.hostname.rm2</name>
       <value>node2</value>
    </property>
    <!-- 指定zk集群地址 -->
    <property>
       <name>yarn.resourcemanager.zk-address</name>
       <value>node1:2181,node2:2181,node3:2181</value>
    </property>
    <property>
       <name>yarn.nodemanager.aux-services</name>
       <value>mapreduce_shuffle</value>
    </property>
</configuration>

5, 格式化namenode

1), 3台机器启动 journalenode

hadoop-daemon.sh start journalnode

2), 格式化namenode, 并启动

hdfs namenode -format hadoop-daemon.sh start namenode

3), 在另外一个namenode上拷贝, 或者手动拷贝

hdfs namenode -bootstrapStandby

4), 启动第二个namenode

hadoop-daemon.sh start namenode

5), 在activeNameNode上格式化zookeeper

hdfs zkfc -formatZK

6), 启动

start-dfs.sh

此时可经过 node1:50070 访问 hadoop

6, 启动yarn

1), 在nameNode上执行

start-yarn.sh

2), 启动 resourcenamenager

yarn-HA, 不须要记录状态, 因此很是简单

yarn-daemon.sh start resourcemanager

此时可经过 node1:8088 进行访问

之后启动时, 先启动3台zookeeper, 而后 start-dfs.sh 便可以了

7, 进行测试

1, 建立输入, 输出目录

hadoop fs -mkdir -p /data/wordcount hadoop fs -mkdir -p /output

2, 上传文件

hadoop fs -put README.txt /data/wordcount

3, 执行样例

hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.5.jar wordcount /data/wordcount /output/wordcount

4, 查看分片文件

hadoop fs -text /output/wordcount/part-r-00000

HA编程的时候应该注意:

1, 代码访问hdfs的时候,

FileSystem.get(new URI("hfs://hdfscluster/", conf), conf, "root);

须要将配置文件

hdfs-site.xml, core-site.xml, yarn-site.xml, mapred-site.xml 放在resources下,

在 new Configuration() 的时候, 会自动加载resources中的配置文件