概述
环境：hadoop 3.3.6
jdk : 1.8
linux 环境：
[root@hadoop01 soft]# uname -a
Linux hadoop01 3.10.0-693.el7.x86_64 #1 SMP Tue Aug 22 21:09:27 UTC 2017 x86_64 x86_64 x86_64 GNU/Linux
相关文章链接如下：
| 文章名称 | 链接 |
|---|---|
| hadoop安装基础环境安装一 | 地址 |
| hadoop一主三从安装 | 地址 |
官网文档(单节点安装)
官网文档速递
安装需要的包：hadoop-3.3.6.tar.gz zookeeper-3.4.14.tar.gz
HA 各组件机器分配如下：
| hostname | ip | 组件 |
|---|---|---|
| hadoop01 | 10.xx.3x.142 | NN RM |
| hadoop02 | 10.xx.3x.143 | NN |
| hadoop03 | 10.xx.3x.144 | NM DN |
| hadoop04 | 10.xx.3x.145 | NM DN |
注意：原来的这些机器 hadoop01 与其它机器做了免密，jdk 还是原有的配置， 需要做 hadoop02 与其它机器做免密。
免密请参考 hadoop安装基础环境安装一
实践
一主两从
解压
# 解压
[root@hadoop01 soft]# tar -zxvf hadoop-3.3.6.tar.gz
[root@hadoop01 soft]# ls
hadoop-3.3.6 hadoop-3.3.6.tar.gz zookeeper-3.4.14.tar.gz
配置文件
hadoop-env.sh
[root@hadoop01 hadoop]# pwd
/data/hadoop/soft/hadoop-3.3.6/etc/hadoop
[root@hadoop01 hadoop]# vi hadoop-env.sh
export JAVA_HOME=/data/soft/jdk1.8
core-site.xml
# 创建存储 hadoop_repo
mkdir -p /data/hadoop/hadoop_repo
[root@hadoop01 hadoop]# vi core-site.xml
加入下面的配置内容
<property>
<name>fs.defaultFS</name>
<value>hdfs://hadoop01:9000</value>
</property>
<!-- 是 hadoop文件系统依赖的基本配置,比如跑MapReduce时生成的临时路径本质上其实就是生成在它的下面 -->
<property>
<name>hadoop.tmp.dir</name>
<value>/data/hadoop/hadoop_repo</value>
</property>
<!-- 删除文件存在时间 -->
<property>
<name>fs.trash.interval</name>
<value>1440</value>
</property>
<property>
<name>hadoop.proxyuser.root.hosts</name>
<value>*</value>
</property>
<property>
<name>hadoop.proxyuser.root.groups</name>
<value>*</value>
</property>
hdfs-site.xml
因为只有两个 DN 所以分片设置为 2
[root@hadoop01 hadoop]# vi hdfs-site.xml
<property>
<name>dfs.replication</name>
<value>2</value>
</property>
yarn-site.xml
[root@hadoop01 hadoop]# vi yarn-site.xml
yarn-resourcemanager.webapp.address hadoop01:37856 可以定制对外访问地址 8088易容易被挖矿
<property>
<name>yarn.nodemanager.aux-services</name>
<value>spark_shuffle,mapreduce_shuffle</value>
</property>
<property>
<name>yarn.nodemanager.aux-services.spark_shuffle.class</name>
<value>org.apache.spark.network.yarn.YarnShuffleService</value>
</property>
<property>
<name>yarn.nodemanager.env-whitelist</name>
<value>JAVA_HOME,HADOOP_COMMON_HOME,HADOOP_HDFS_HOME,HADOOP_CONF_DIR,CLASSPATH_PREPEND_DISTCACHE,HADOOP_YARN_HOME,HADOOP_MAPRED_HOME</value>
</property>
<property>
<name>yarn.resourcemanager.hostname</name>
<value>hadoop01</value>
</property>
<property>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>
<property>
<name>yarn.log.server.url</name>
<value>http://hadoop01:19888/jobhistory/logs/</value>
</property>
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>10240</value>
<description>该节点上YARN可使用的物理内存总量</description>
</property>
<property>
<name>yarn.nodemanager.resource.cpu-vcores</name>
<value>8</value>
<description>表示集群中每个节点可被分配的虚拟CPU个数</description>
</property>
<property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>1024</value>
<description>每个容器container请求被分配的最小内存</description>
</property>
<property>
<name>yarn.scheduler.maximum-allocation-mb</name>
<value>8096</value>
<description>每个容器container请求被分配的最大内存,不能给太大</description>
</property>
<property>
<name>yarn.scheduler.minimum-allocation-vcores</name>
<value>1</value>
<description>每个容器container请求被分配的最少虚拟CPU个数</description>
</property>
<property>
<name>yarn.scheduler.maximum-allocation-vcores</name>
<value>4</value>
<description>每个容器container请求被分配的最多虚拟CPU个数</description>
</property>
mapred-site.xml
[root@hadoop01 hadoop]# vi mapred-site.xml
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
workers
[root@hadoop01 hadoop]# vi workers
[root@hadoop01 hadoop]# cat workers
hadoop03
hadoop04
分发
# 每个节点都要创建
mkdir -p /data/hadoop/soft
scp -rq /data/hadoop/soft/hadoop-3.3.6 hadoop02:/data/hadoop/soft/hadoop-3.3.6
scp -rq /data/hadoop/soft/hadoop-3.3.6 hadoop03:/data/hadoop/soft/hadoop-3.3.6
scp -rq /data/hadoop/soft/hadoop-3.3.6 hadoop04:/data/hadoop/soft/hadoop-3.3.6
分发时，注意检查一下配置是否生效
环境变量
根据自己本机环境变量配置
vi /etc/profile 或 ~.bash_profile
格式化
[root@hadoop01 bin]# pwd
/data/hadoop/soft/hadoop-3.3.6/bin
./hdfs namenode -format
2024-01-11 11:32:53,304 INFO common.Storage: Storage directory /data/hadoop/hadoop_repo/dfs/name has been successfully formatted.
启动 hdfs
[root@hadoop01 sbin]# pwd
/data/hadoop/soft/hadoop-3.3.6/sbin
# 报错，忘记配置 用户了
[root@hadoop01 sbin]# ./start-dfs.sh
Starting namenodes on [hadoop01]
ERROR: Attempting to operate on hdfs namenode as root
ERROR: but there is no HDFS_NAMENODE_USER defined. Aborting operation.
Starting datanodes
ERROR: Attempting to operate on hdfs datanode as root
ERROR: but there is no HDFS_DATANODE_USER defined. Aborting operation.
Starting secondary namenodes [hadoop01]
ERROR: Attempting to operate on hdfs secondarynamenode as root
ERROR: but there is no HDFS_SECONDARYNAMENODE_USER defined. Aborting operation.
2024-01-11 11:35:01,599 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
[root@hadoop01 sbin]# vi start-dfs.sh
[root@hadoop01 sbin]# vi stop-dfs.sh
[root@hadoop01 sbin]# vi start-yarn.sh
[root@hadoop01 sbin]# vi stop-yarn.sh
# 重新分发
// start-dfs.sh，stop-dfs.sh，start-yarn.sh，stop-yarn.sh 写在最前面
HDFS_ZKFC_USER=root
HDFS_JOURNALNODE_USER=root
export HDFS_NAMENODE_USER=root
export HDFS_DATANODE_USER=root
export HDFS_SECONDARYNAMENODE_USER=root
export YARN_RESOURCEMANAGER_USER=root
export YARN_NODEMANAGER_USER=root
启动后的结果
[root@hadoop01 sbin]# ./start-dfs.sh
Starting namenodes on [hadoop01]
上一次登录：四 1月 11 13:08:21 CST 2024从 10.35.232.75pts/2 上
/etc/profile: line 62: hadoop: command not found
Starting datanodes
上一次登录：四 1月 11 13:08:54 CST 2024pts/0 上
/etc/profile: line 62: hadoop: command not found
hadoop04: WARNING: /data/hadoop/soft/hadoop-3.3.6/logs does not exist. Creating.
hadoop03: WARNING: /data/hadoop/soft/hadoop-3.3.6/logs does not exist. Creating.
Starting secondary namenodes [hadoop01]
上一次登录：四 1月 11 13:08:56 CST 2024pts/0 上
/etc/profile: line 62: hadoop: command not found
2024-01-11 13:09:03,358 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
[root@hadoop01 sbin]# jps
12433 NameNode
2422 nacos-server.jar
12823 SecondaryNameNode
19911 Jps
[root@hadoop02 ~]# jps
21780 Jps
[root@hadoop02 ~]#
[root@hadoop03 ~]# jps
12853 DataNode
13033 Jps
[root@hadoop04 ~]# jps
5771 DataNode
5951 Jps
启动 yarn
[root@hadoop01 sbin]# ./start-dfs.sh
Starting namenodes on [hadoop01]
上一次登录：四 1月 11 13:39:35 CST 2024从 10.35.232.75pts/2 上
/etc/profile: line 62: hadoop: command not found
Starting datanodes
上一次登录：四 1月 11 13:49:32 CST 2024pts/0 上
/etc/profile: line 62: hadoop: command not found
Starting secondary namenodes [hadoop01]
上一次登录：四 1月 11 13:49:34 CST 2024pts/0 上
/etc/profile: line 62: hadoop: command not found
2024-01-11 13:49:41,008 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
[root@hadoop01 sbin]# ./start-yarn.sh
Starting resourcemanager
上一次登录：四 1月 11 13:49:37 CST 2024pts/0 上
/etc/profile: line 62: hadoop: command not found
Starting nodemanagers
上一次登录：四 1月 11 13:50:01 CST 2024pts/0 上
/etc/profile: line 62: hadoop: command not found
[root@hadoop01 sbin]#
[root@hadoop03 lib]# jps
16288 Jps
16007 NodeManager
15372 DataNode
[root@hadoop04 lib]# jps
9348 DataNode
10343 Jps
9995 NodeManager
http://10.xx.3x.142:9870
http://10.xx.3x.142:8088
验证
[root@hadoop02 ~]# hdfs dfs -mkdir /test
[root@hadoop02 ~]#
bug
hadoop一主三从安装 中就有这个问题
注意：这问题是因为生产上用的是 spark
按步就搬解决。记住重新分发一下。
zookeeper
在此只部署单机，生产上部署集群
[root@hadoop01 soft]# tar -zxvf zookeeper-3.4.14.tar.gz
[root@hadoop01 soft]# ls
hadoop-3.3.6 hadoop-3.3.6.tar.gz zookeeper-3.4.14 zookeeper-3.4.14.tar.gz
[root@hadoop01 zookeeper-3.4.14]# cd conf/
[root@hadoop01 conf]# ls
configuration.xsl log4j.properties zoo_sample.cfg
[root@hadoop01 conf]# mv zoo_sample.cfg zoo.cfg
[root@hadoop01 conf]# vi zoo.cfg
[root@hadoop01 conf]#
dataDir=/data/hadoop/zk_repo
[root@hadoop01 bin]# pwd
/data/hadoop/soft/zookeeper-3.4.14/bin
[root@hadoop01 bin]# ./zkServer.sh start
ZooKeeper JMX enabled by default
Using config: /data/hadoop/soft/zookeeper-3.4.14/bin/../conf/zoo.cfg
Starting zookeeper ... STARTED
HA
core-site.xml
<property>
<name>fs.defaultFS</name>
<value>hdfs://mycluster</value>
</property>
<!-- 是 hadoop文件系统依赖的基本配置,比如跑MapReduce时生成的临时路径本质上其实就是生成在它的下面 -->
<property>
<name>hadoop.tmp.dir</name>
<value>/data/hadoop/hadoop_repo</value>
</property>
<!-- 删除文件存在时间 -->
<property>
<name>fs.trash.interval</name>
<value>1440</value>
</property>
<property>
<name>hadoop.proxyuser.root.hosts</name>
<value>*</value>
</property>
<property>
<name>hadoop.proxyuser.root.groups</name>
<value>*</value>
</property>
<property>
<name>ha.zookeeper.quorum</name>
<value>hadoop01:2181</value>
</property>
hdfs-site.xml
注意 ： 三个journal节点都需要创建. (mkdir -p 执行启动命令)
<property>
<name>dfs.replication</name>
<value>2</value>
</property>
<! -- 上面已有 -->
<property>
<name>dfs.nameservices</name>
<value>mycluster</value>
</property>
<property>
<name>dfs.ha.namenodes.mycluster</name>
<value>nn1,nn2</value>
</property>
<property>
<name>dfs.namenode.rpc-address.mycluster.nn1</name>
<value>hadoop01:8020</value>
</property>
<property>
<name>dfs.namenode.rpc-address.mycluster.nn2</name>
<value>hadoop02:8020</value>
</property>
<property>
<name>dfs.namenode.http-address.mycluster.nn1</name>
<value>hadoop01:9870</value>
</property>
<property>
<name>dfs.namenode.http-address.mycluster.nn2</name>
<value>hadoop02:9870</value>
</property>
<property>
<name>dfs.namenode.shared.edits.dir</name>
<value>qjournal://hadoop01:8485;hadoop02:8485;hadoop03:8485/mycluster</value>
</property>
<property>
<name>dfs.journalnode.edits.dir</name>
<value>/data/hadoop/journal</value>
</property>
<property>
<name>dfs.ha.automatic-failover.enabled</name>
<value>true</value>
</property>
<property>
<name>dfs.client.failover.proxy.provider.mycluster</name>
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
<property>
<name>dfs.ha.nn.not-become-active-in-safemode</name>
<value>true</value>
</property>
<property>
<name>dfs.ha.fencing.methods</name>
<value>sshfence</value>
</property>
<property>
<name>dfs.ha.fencing.ssh.private-key-files</name>
<value>/root/.ssh/id_rsa</value>
</property>
<property>
<name>dfs.ha.fencing.ssh.connect-timeout</name>
<value>30000</value>
</property>
[root@hadoop01 hadoop]# mkdir journal
[root@hadoop01 hadoop]# cd journal/
[root@hadoop01 journal]# ls
[root@hadoop01 journal]# pwd
/data/hadoop/journal
mkdir -p /data/hadoop/journal
改为配置分发
# 除了修改了的机器，其它的都删除，重新分发
cd /data/hadoop/soft/ && rm -rf hadoop-3.3.6/
scp -rq /data/hadoop/soft/hadoop-3.3.6 hadoop02:/data/hadoop/soft/hadoop-3.3.6
scp -rq /data/hadoop/soft/hadoop-3.3.6 hadoop03:/data/hadoop/soft/hadoop-3.3.6
scp -rq /data/hadoop/soft/hadoop-3.3.6 hadoop04:/data/hadoop/soft/hadoop-3.3.6
cd /data/hadoop/soft/hadoop-3.3.6/etc/hadoop && cat hdfs-site.xml
执行
# 三个 journal 节点依次执行并检查
[root@hadoop01 bin]# pwd
/data/hadoop/soft/hadoop-3.3.6/bin
[root@hadoop01 bin]# ./hdfs --daemon start journalnode
cd /data/hadoop/soft/hadoop-3.3.6/bin && ./hdfs --daemon start journalnode
[root@hadoop03 bin]# jps
10393 Jps
10175 JournalNode
# hadoop01上重新格式化
./hdfs namenode -format
# namenode 启动
cd /data/hadoop/soft/hadoop-3.3.6/bin && ./hdfs --daemon start namenode
[root@hadoop01 bin]# ./hdfs --daemon start namenode
[root@hadoop01 bin]# jps
24352 NameNode
20529 QuorumPeerMain
24515 Jps
2422 nacos-server.jar
32683 JournalNode
# namenode 备用节点上执行
[root@hadoop02 bin]# ./hdfs namenode -bootstrapStandby
2024-01-11 15:08:25,601 INFO common.Storage: Storage directory /data/hadoop/hadoop_repo/dfs/name has been successfully formatted.
# 回到 hadoop01节点上 zkfc -formatZK
[root@hadoop01 bin]# ./hdfs zkfc -formatZK
2024-01-11 15:10:29,614 INFO ha.ActiveStandbyElector: Session connected.
2024-01-11 15:10:29,629 INFO ha.ActiveStandbyElector: Successfully created /hadoop-ha/mycluster in ZK.
## 启动 hdfs
[root@hadoop01 sbin]# ./start-dfs.sh
Starting namenodes on [hadoop01 hadoop02]
上一次登录：四 1月 11 15:38:41 CST 2024pts/0 上
/etc/profile: line 62: hadoop: command not found
hadoop02: namenode is running as process 1949. Stop it first and ensure /tmp/hadoop-root-namenode.pid file is empty before retry.
hadoop01: namenode is running as process 10787. Stop it first and ensure /tmp/hadoop-root-namenode.pid file is empty before retry.
Starting datanodes
上一次登录：四 1月 11 15:45:44 CST 2024pts/0 上
/etc/profile: line 62: hadoop: command not found
Starting journal nodes [hadoop03 hadoop02 hadoop01]
上一次登录：四 1月 11 15:45:44 CST 2024pts/0 上
/etc/profile: line 62: hadoop: command not found
hadoop03: journalnode is running as process 2861. Stop it first and ensure /tmp/hadoop-root-journalnode.pid file is empty before retry.
hadoop01: journalnode is running as process 11453. Stop it first and ensure /tmp/hadoop-root-journalnode.pid file is empty before retry.
hadoop02: journalnode is running as process 2263. Stop it first and ensure /tmp/hadoop-root-journalnode.pid file is empty before retry.
2024-01-11 15:45:48,859 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Starting ZK Failover Controllers on NN hosts [hadoop01 hadoop02]
上一次登录：四 1月 11 15:45:48 CST 2024pts/0 上
/etc/profile: line 62: hadoop: command not found
hadoop02: zkfc is running as process 2518. Stop it first and ensure /tmp/hadoop-root-zkfc.pid file is empty before retry.
hadoop01: zkfc is running as process 11880. Stop it first and ensure /tmp/hadoop-root-zkfc.pid file is empty before retry.
[root@hadoop01 sbin]# jps
20529 QuorumPeerMain
3681 Jps
10787 NameNode
11880 DFSZKFailoverController
11453 JournalNode
[root@hadoop01 sbin]#
[root@hadoop02 hadoop_repo]# jps
2518 DFSZKFailoverController
2263 JournalNode
1949 NameNode
18126 Jps
[root@hadoop03 hadoop]# jps
10263 DataNode
12170 Jps
2861 JournalNode
[root@hadoop04 hadoop]# jps
30245 DataNode
32366 Jps
验证 HA
验证：直接 kill 掉 active 所在节点的 NameNode ，观察
备用节点是否自动转正。
[root@hadoop02 sbin]# jps
11411 DFSZKFailoverController
6342 JournalNode
11896 Jps
10649 NameNode
[root@hadoop02 sbin]# kill 10649
[root@hadoop02 sbin]# jps
11411 DFSZKFailoverController
6342 JournalNode
19782 Jps
文章来源：https://www.toymoban.com/news/detail-785939.html
结束
hadoop HA-QJM 至此就结束了，如有疑问，欢迎评论区留言。文章来源地址https://www.toymoban.com/news/detail-785939.html
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