2.1.8 hadoop体系之离线计算-hdfs分布式文件系统-HA(高可用)-Hadoop集群环境搭建
作者：互联网
目录
4. 复制hadoop01上的NameNode的元数据到hadoop02
5. 在NameNode节点(hadoop01或hadoop02)格式化zkfc
8. 最后单独启动hadoop01的历史任务服务器和hadoop02的ResourceManager
1.准备工作
jdk1.8 、hadoop2.7.7 、zookeeper3.5.7
三台节点安装 psmisc
sudo yum -y install psmisc2.安装工作
2.1、集群规划
2.2、集群配置
先创建好所需目录
[xiaokang@hadoop01 ~]$ mkdir -p /opt/software/hadoop-2.7.7/tmp
[xiaokang@hadoop01 ~]$ mkdir -p /opt/software/hadoop-2.7.7/dfs/journalnode_data
[xiaokang@hadoop01 ~]$ mkdir -p /opt/software/hadoop-2.7.7/dfs/edits
[xiaokang@hadoop01 ~]$ mkdir -p /opt/software/hadoop-2.7.7/dfs/datanode_data
[xiaokang@hadoop01 ~]$ mkdir -p /opt/software/hadoop-2.7.7/dfs/namenode_data
1. hadoop-env.sh
export JAVA_HOME=/opt/moudle/jdk1.8.0_191
export HADOOP_CONF_DIR=/opt/software/hadoop-2.7.7/etc/hadoop
2. core-site.xml
<configuration>
<property>
<!--指定hadoop集群在zookeeper上注册的节点名-->
<name>fs.defaultFS</name>
<value>hdfs://hacluster</value>
</property>
<property>
<!--用来指定hadoop运行时产生文件的存放目录-->
<name>hadoop.tmp.dir</name>
<value>file:///opt/software/hadoop-2.7.7/tmp</value>
</property>
<property>
<!--设置缓存大小，默认4kb-->
<name>io.file.buffer.size</name>
<value>4096</value>
</property>
<property>
<!--指定zookeeper的存放地址 -->
<name>ha.zookeeper.quorum</name>
<value>hadoop01:2181,hadoop02:2181,hadoop03:2181</value>
</property>
</configuration>
3. hdfs-site.xml
<configuration>
<property>
<!--数据块默认大小128M-->
<name>dfs.block.size</name>
<value>134217728</value>
</property>
<property>
<!--副本数量，不配置的话默认为3-->
<name>dfs.replication</name>
<value>3</value>
</property>
<property>
<!--namenode节点数据（元数据）的存放位置-->
<name>dfs.name.dir</name>
<value>file:///opt/software/hadoop-2.7.7/dfs/namenode_data</value>
</property>
<property>
<!--datanode节点数据（元数据）的存放位置-->
<name>dfs.data.dir</name>
<value>file:///opt/software/hadoop-2.7.7/dfs/datanode_data</value>
</property>
<property>
<name>dfs.webhdfs.enabled</name>
<value>true</value>
</property>
<property>
<name>dfs.datanode.max.transfer.threads</name>
<value>4096</value>
</property>
<property>
<!--指定hadoop集群在zookeeper上注册的节点名-->
<name>dfs.nameservices</name>
<value>hacluster</value>
</property>
<property>
<!-- hacluster集群下有两个namenode，分别为nn1,nn2 -->
<name>dfs.ha.namenodes.hacluster</name>
<value>nn1,nn2</value>
</property>
<!-- nn1的rpc、servicepc和http通信 -->
<property>
<name>dfs.namenode.rpc-address.hacluster.nn1</name>
<value>hadoop01:9000</value>
</property>
<property>
<name>dfs.namenode.servicepc-address.hacluster.nn1</name>
<value>hadoop01:53310</value>
</property>
<property>
<name>dfs.namenode.http-address.hacluster.nn1</name>
<value>hadoop01:50070</value>
</property>
<!-- nn2的rpc、servicepc和http通信 -->
<property>
<name>dfs.namenode.rpc-address.hacluster.nn2</name>
<value>hadoop02:9000</value>
</property>
<property>
<name>dfs.namenode.servicepc-address.hacluster.nn2</name>
<value>hadoop02:53310</value>
</property>
<property>
<name>dfs.namenode.http-address.hacluster.nn2</name>
<value>hadoop02:50070</value>
</property>
<property>
<!-- 指定namenode的元数据在JournalNode上存放的位置 -->
<name>dfs.namenode.shared.edits.dir</name>
<value>qjournal://hadoop01:8485;hadoop02:8485;hadoop03:8485/hacluster</value>
</property>
<property>
<!-- 指定JournalNode在本地磁盘存放数据的位置 -->
<name>dfs.journalnode.edits.dir</name>
<value>/opt/software/hadoop-2.7.7/dfs/journalnode_data</value>
</property>
<property>
<!-- namenode操作日志的存放位置 -->
<name>dfs.namenode.edits.dir</name>
<value>/opt/software/hadoop-2.7.7/dfs/edits</value>
</property>
<property>
<!-- 开启namenode故障转移自动切换 -->
<name>dfs.ha.automatic-failover.enabled</name>
<value>true</value>
</property>
<property>
<!-- 配置失败自动切换实现方式 -->
<name>dfs.client.failover.proxy.provider.hacluster</name>
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
<property>
<!-- 配置隔离机制 -->
<name>dfs.ha.fencing.methods</name>
<value>sshfence</value>
</property>
<property>
<!-- 使用隔离机制需要SSH免密登录 -->
<name>dfs.ha.fencing.ssh.private-key-files</name>
<value>/home/xiaokang/.ssh/id_rsa</value>
</property>
<property>
<!--hdfs文件操作权限,false为不验证-->
<name>dfs.permissions</name>
<value>false</value>
</property>
</configuration>
4. mapred-site.xml
<configuration>
<property>
<!--指定mapreduce运行在yarn上-->
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<!--配置任务历史服务器地址-->
<name>mapreduce.jobhistory.address</name>
<value>hadoop01:10020</value>
</property>
<property>
<!--配置任务历史服务器web-UI地址-->
<name>mapreduce.jobhistory.webapp.address</name>
<value>hadoop01:19888</value>
</property>
<property>
<!--开启uber模式-->
<name>mapreduce.job.ubertask.enable</name>
<value>true</value>
</property>
</configuration>
5. yarn-site.xml
<configuration>
<property>
<!-- 开启Yarn高可用 -->
<name>yarn.resourcemanager.ha.enabled</name>
<value>true</value>
</property>
<property>
<!-- 指定Yarn集群在zookeeper上注册的节点名 -->
<name>yarn.resourcemanager.cluster-id</name>
<value>hayarn</value>
</property>
<property>
<!-- 指定两个ResourceManager的名称 -->
<name>yarn.resourcemanager.ha.rm-ids</name>
<value>rm1,rm2</value>
</property>
<property>
<!-- 指定rm1的主机 -->
<name>yarn.resourcemanager.hostname.rm1</name>
<value>hadoop02</value>
</property>
<property>
<!-- 指定rm2的主机 -->
<name>yarn.resourcemanager.hostname.rm2</name>
<value>hadoop03</value>
</property>
<property>
<!-- 配置zookeeper的地址 -->
<name>yarn.resourcemanager.zk-address</name>
<value>hadoop01:2181,hadoop02:2181,hadoop03:2181</value>
</property>
<property>
<!-- 开启Yarn恢复机制 -->
<name>yarn.resourcemanager.recovery.enabled</name>
<value>true</value>
</property>
<property>
<!-- 配置执行ResourceManager恢复机制实现类 -->
<name>yarn.resourcemanager.store.class</name>
<value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
</property>
<property>
<!--指定主resourcemanager的地址-->
<name>yarn.resourcemanager.hostname</name>
<value>hadoop03</value>
</property>
<property>
<!--NodeManager获取数据的方式-->
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<!--开启日志聚集功能-->
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>
<property>
<!--配置日志保留7天-->
<name>yarn.log-aggregation.retain-seconds</name>
<value>604800</value>
</property>
</configuration>
6. slaves
hadoop01
hadoop02
hadoop03
将 Hadoop 安装包分发到其他两台服务器，分发后建议在这两台服务器上也配置一下 Hadoop 的环境变量。
# 将安装包分发到hadoop02
[xiaokang@hadoop01 ~]$ scp -r /opt/software/hadoop-2.7.7/ xiaokang@hadoop02:/opt/software/
# 将安装包分发到hadoop03
[xiaokang@hadoop01 hadoop]$ scp -r /opt/software/hadoop-2.7.7/ xiaokang@hadoop03:/opt/software/
2.3、启动集群（初始化工作）
1. 启动3个Zookeeper
[xiaokang@hadoop01 ~]$ zkServer.sh start
[xiaokang@hadoop02 ~]$ zkServer.sh start
[xiaokang@hadoop03 ~]$ zkServer.sh start
2. 启动3个JournalNode
[xiaokang@hadoop01 ~]$ hadoop-daemon.sh start journalnode
[xiaokang@hadoop02 ~]$ hadoop-daemon.sh start journalnode
[xiaokang@hadoop03 ~]$ hadoop-daemon.sh start journalnode
3. 格式化NameNode
【仅hadoop01】
[xiaokang@hadoop01 ~]$ hdfs namenode -format
4. 复制hadoop01上的NameNode的元数据到hadoop02
[xiaokang@hadoop01 ~]$ scp -r /opt/software/hadoop-2.7.7/dfs/namenode_data/current/ xiaokang@hadoop02:/opt/software/hadoop-2.7.7/dfs/namenode_data/
5. 在NameNode节点(hadoop01或hadoop02)格式化zkfc
【二者选其一即可】
[xiaokang@hadoop01 ~]$ hdfs zkfc -formatZK
或
[xiaokang@hadoop02 ~]$ hdfs zkfc -formatZK
6. 在hadoop01上启动HDFS相关服务
[xiaokang@hadoop01 ~]$ start-dfs.sh
Starting namenodes on [hadoop01 hadoop02]
hadoop02: starting namenode, logging to /opt/software/hadoop-2.7.7/logs/hadoop-xiaokang-namenode-hadoop02.out
hadoop01: starting namenode, logging to /opt/software/hadoop-2.7.7/logs/hadoop-xiaokang-namenode-hadoop01.out
hadoop03: starting datanode, logging to /opt/software/hadoop-2.7.7/logs/hadoop-xiaokang-datanode-hadoop03.out
hadoop02: starting datanode, logging to /opt/software/hadoop-2.7.7/logs/hadoop-xiaokang-datanode-hadoop02.out
hadoop01: starting datanode, logging to /opt/software/hadoop-2.7.7/logs/hadoop-xiaokang-datanode-hadoop01.out
Starting journal nodes [hadoop01 hadoop02 hadoop03]
hadoop02: journalnode running as process 7546. Stop it first.
hadoop01: journalnode running as process 7827. Stop it first.
hadoop03: journalnode running as process 7781. Stop it first.
Starting ZK Failover Controllers on NN hosts [hadoop01 hadoop02]
hadoop01: starting zkfc, logging to /opt/software/hadoop-2.7.7/logs/hadoop-xiaokang-zkfc-hadoop01.out
hadoop02: starting zkfc, logging to /opt/software/hadoop-2.7.7/logs/hadoop-xiaokang-zkfc-hadoop02.out
7. 在hadoop03上启动YARN相关服务
[xiaokang@hadoop03 ~]$ start-yarn.sh
8. 最后单独启动hadoop01的历史任务服务器和hadoop02的ResourceManager
[xiaokang@hadoop01 ~]$ mr-jobhistory-daemon.sh start historyserver
[xiaokang@hadoop02 ~]$ yarn-daemon.sh start resourcemanager
2.4、查看集群
1. jps进程查看
[xiaokang@hadoop01 ~]$ jps
8227 QuorumPeerMain
8916 DataNode
8663 JournalNode
8791 NameNode
9035 DFSZKFailoverController
11048 JobHistoryServer
9147 NodeManager
9260 Jps
[xiaokang@hadoop02 ~]$ jps
7538 QuorumPeerMain
8214 NodeManager
7802 JournalNode
8010 DataNode
8122 DFSZKFailoverController
8346 ResourceManager
8395 Jps
7916 NameNode
[xiaokang@hadoop03 ~]$ jps
8897 Jps
8343 DataNode
8472 ResourceManager
8249 JournalNode
7994 QuorumPeerMain
8575 NodeManager
【查看NameNode的状态】
[xiaokang@hadoop01 ~]$ hdfs haadmin -getServiceState nn1
active
[xiaokang@hadoop01 ~]$ hdfs haadmin -getServiceState nn2
standby
【查看ResourceManager的状态】
[xiaokang@hadoop03 ~]$ yarn rmadmin -getServiceState rm1
standby
[xiaokang@hadoop03 ~]$ yarn rmadmin -getServiceState rm2
active
2. WebUI查看
HDFS 和 YARN 的端口号分别为 50070 和 8088，界面应该如下：
此时 hadoop01 上的 NameNode 处于可用状态：
而 hadoop02 上的 NameNode 则处于备用状态：
hadoop03 上的 ResourceManager 处于可用状态：
hadoop02 上的 ResourceManager 则处于备用状态：
同时界面上也有 Journal Manager 的相关信息：
2.5、代码测试HA
/**
* 测试HA集群
*
* @author xiaokang
*/
public class TestHDFS {
public static void main(String[] args) throws IOException, InterruptedException {
Configuration conf = new Configuration();
conf.set("fs.defaultFS", "hdfs://hacluster");
conf.set("dfs.nameservices", "hacluster");
conf.set("dfs.ha.namenodes.hacluster", "nn1,nn2");
conf.set("dfs.namenode.rpc-address.hacluster.nn1", "192.168.239.161:9000");
conf.set("dfs.namenode.rpc-address.hacluster.nn2", "192.168.239.162:9000");
conf.set("dfs.client.failover.proxy.provider.hacluster", "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider");
FileSystem fs = FileSystem.get(URI.create("hdfs://hacluster"), conf, "xiaokang");
fs.mkdirs(new Path(args[0]));
System.out.println("ok-微信公众号：小康新鲜事儿");
}
}
[xiaokang@hadoop01 ~]$ hadoop jar Zookeeper-API-1.0.jar TestHDFS /xiaokang
#杀掉active的NameNode之后，再次创建一个文件夹
[xiaokang@hadoop02 logs]$ kill -9 8277
[xiaokang@hadoop01 ~]$ hadoop jar Zookeeper-API-1.0.jar TestHDFS /xiaokang1
2.6、集群二次启动
上面的集群初次启动涉及到一些必要初始化操作，所以过程略显繁琐。但是集群一旦搭建好后，想要再次启用它是比较方便的，步骤如下（首选需要确保 ZooKeeper 集群已经启动）：
在 hadoop01 启动 HDFS，此时会启动所有与 HDFS 高可用相关的服务，包括 NameNode、DataNode 、 JournalNode和DFSZKFailoverController：
[xiaokang@hadoop01 ~]$ start-dfs.sh
在 hadoop03 启动 YARN：
[xiaokang@hadoop03 ~]$ start-yarn.sh
这个时候 hadoop02 上的 ResourceManager 服务通常还是没有启动的，需要手动启动：
[xiaokang@hadoop02 ~]$ yarn-daemon.sh start resourcemanager
标签：opt,hdfs,hadoop02,hadoop01,离线,hadoop,dfs,xiaokang 来源： https://blog.csdn.net/Suyebiubiu/article/details/111531926