bigdata-02-hadoop2.8.4-resourceHA安装

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

vim  /etc/chrony.conf

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

修改需要同步的服务器配置, 并重启

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
rtcsync
logdir /var/log/chrony

执行时间同步

systemctl restart chronyd

[root@node2 ~]# chronyc sources -v
 Number of sources = 

  .-- 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                                       -1590ns[  +62us] +/-   13ms

查看时间同步:

[root@node3 ~]# timedatectl
      Local time: Wed -- :: EDT
  Universal time: Wed -- :: UTC
        RTC time: Wed -- ::
       Time zone: America/New_York (EDT, -)
     NTP enabled: yes
NTP synchronized: yes
 RTC in local TZ: no
      DST active: yes
 Last DST change: DST began at
                  Sun -- :: EST
                  Sun -- :: EDT
 Next DST change: DST ends (the clock jumps one hour backwards) at
                  Sun -- :: EDT
                  Sun -- :: EST

3), 修改hostname, 很多集群都需要执行这一个

hostname node1,

hostname node2

hostname node3

4), jdk 版本

java  -version   1.8.0_161

5), 设置免密登陆

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

发送到namenode, 设置

非root用户, 记得修改authorized 权限为。600

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

2, zookeeper 安装

参照其他博客..

3, hadoop安装

zkFc-用来做HA的备份和切换的, 做active, standby的状态管理的, 监控namenode进程, 记录信息到zookeeper中

journalNode--复制fsimage和edtis的

1), 修改环境变量

export HADOOP_HOME=/usr/local/hadoop-2.7.
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..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:,node2:,node3:</value>
    </property>
</configuration>

4), 修改 hdfs-site.xml

<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>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通信地址 -->
    <property>
        <name>dfs.namenode.rpc-address.hdfscluster.nn1</name>
        <value>192.168.199.182:</value>
    </property>
    <!-- nn1的http通信地址 -->
    <property>
        <name>dfs.namenode.http-address.hdfscluster.nn1</name>
        <value>192.168.199.182:</value>
    </property>
    <!-- nn2的RPC通信地址 -->
    <property>
        <name>dfs.namenode.rpc-address.hdfscluster.nn2</name>
        <value>192.168.199.247:</value>
    </property>
    <!-- nn2的http通信地址 -->
    <property>
        <name>dfs.namenode.http-address.hdfscluster.nn2</name>
        <value>192.168.199.247:</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隔离机制时需要ssh免登陆 -->
    <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></value>
    </property>
</configuration>

备注: 如果集群成功后, 但创建目录显示: ipc.Client: Retrying connect to serve, 就更改为

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:,node2:,node3:</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

此时可通过  node1:50070 访问 hadoop

6, 启动yarn

1), 在nameNode上执行

start-yarn.sh

2), 启动 resourcenamenager

yarn-HA, 不需要记录状态, 所以非常简单

yarn-daemon.sh start resourcemanager

此时可通过  node1:8088 进行访问

以后启动时, 先启动3台zookeeper, 然后 start-dfs.sh 即可以了

7, 进行测试

1, 创建输入, 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..jar wordcount /data/wordcount /output/wordcount

4, 查看分片文件

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

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);

需要将配置文件

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