集群环境规划

将整个 ha 搭建完成后,集群将形成以下模样

1.配置 core-site.xml

    
    
        fs.defaultFS
        hdfs://mycluster
    
    
    
        hadoop.tmp.dir
        /opt/ha/hadoop-3.3.1/data
    
    
     
        hadoop.http.staticuser.user            
        hadoop 
    
    
    
        ha.zookeeper.quorum
        hadoop101:2181,hadoop102:2181,hadoop103:2181
    
    
    
        ipc.client.connect.max.retries
        20
    
    
    
        ipc.client.connect.retry.interval
        5000
    

2.配置 hdfs-site.xml

    
    
        dfs.namenode.name.dir
        file://${hadoop.tmp.dir}/name
    
    
    
        dfs.datanode.data.dir
        file://${hadoop.tmp.dir}/data
    
    
    
        dfs.journalnode.edits.dir
        ${hadoop.tmp.dir}/jn
    
    
    
        dfs.nameservices
        mycluster
    
    
    
        dfs.ha.namenodes.mycluster
        nn1,nn2,nn3
    
    
    
        dfs.namenode.rpc-address.mycluster.nn1
        hadoop101:8020
    
    
        dfs.namenode.rpc-address.mycluster.nn2
        hadoop102:8020
    
    
        dfs.namenode.rpc-address.mycluster.nn3
        hadoop103:8020
    
    
    
        dfs.namenode.http-address.mycluster.nn1
        hadoop101:9870
    
    
        dfs.namenode.http-address.mycluster.nn2
        hadoop102:9870
    
    
        dfs.namenode.http-address.mycluster.nn3
        hadoop103:9870
    
    
    
        dfs.namenode.shared.edits.dir
        qjournal://hadoop101:8485;hadoop102:8485;hadoop103:8485/mycluster
    
    
    
        dfs.client.failover.proxy.provider.mycluster
        org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider
    
    
    
        dfs.ha.fencing.methods
        sshfence
    
    
    
        dfs.ha.fencing.ssh.private-key-files
        /home/usr1/.ssh/id_rsa
    
    
    
        dfs.ha.automatic-failover.enabled
        true
    

3.配置 yarn-site.xml

    
        yarn.nodemanager.aux-services
        mapreduce_shuffle
    
    
    
        yarn.resourcemanager.ha.enabled
        true
    
    
    
        yarn.resourcemanager.cluster-id
        cluster-yarn1
    
    
    
        yarn.resourcemanager.ha.rm-ids
        rm1,rm2,rm3
    
    
    
    
        yarn.resourcemanager.hostname.rm1
        hadoop101
    
    
    
        yarn.resourcemanager.webapp.address.rm1
        hadoop101:8088
    
    
    
        yarn.resourcemanager.address.rm1
        hadoop101:8032
    
    
    
        yarn.resourcemanager.scheduler.address.rm1
        hadoop101:8030
    
    
    
        yarn.resourcemanager.resource-tracker.address.rm1
        hadoop101:8031
    
    
    
    
        yarn.resourcemanager.hostname.rm2
        hadoop102
    
    
        yarn.resourcemanager.webapp.address.rm2
        hadoop102:8088
    
    
        yarn.resourcemanager.address.rm2
        hadoop102:8032
    
    
        yarn.resourcemanager.scheduler.address.rm2
        hadoop102:8030
    
    
        yarn.resourcemanager.resource-tracker.address.rm2
        hadoop102:8031
    
    
    
    
        yarn.resourcemanager.hostname.rm3
        hadoop103
    
    
    
        yarn.resourcemanager.webapp.address.rm3
        hadoop103:8088
    
    
    
        yarn.resourcemanager.address.rm3
        hadoop103:8032
    
    
    
        yarn.resourcemanager.scheduler.address.rm3
        hadoop103:8030
    
    
    
        yarn.resourcemanager.resource-tracker.address.rm3
        hadoop103:8031
    
    
    
        yarn.resourcemanager.zk-address
        hadoop101:2181,hadoop102:2181,hadoop103:2181
    
    
    
        yarn.resourcemanager.recovery.enabled
        true
    
    
    
        yarn.resourcemanager.store.class
        org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore
    
    
    
        yarn.nodemanager.env-whitelist
        JAVA_HOME,HADOOP_COMMON_HOME,HADOOP_HDFS_HOME,HADOOP_CONF_DIR,CLAS
SPATH_PREPEND_DISTCACHE,HADOOP_YARN_HOME,HADOOP_MAPRED_HOME
    

4.配置mapred-site.xml

    
    
        mapreduce.framework.name
        yarn
    

最后配置works

hadoop101
hadoop102
hadoop103

分发配置好的 hadoop 环境到其他节点

5.启动 HDFS-HA 集群

前提先启动zookeeper集群

1) 初始化 HA 在 Zookeeper 中状态：

[hadoop@hadoop101 ~]$ hdfs zkfc -formatZK  

2) 在各个 JournalNode 节点上，输入以下命令启动 journalnode 服务

[hadoop@hadoop101 ~]$ hdfs --daemon start journalnode
[hadoop@hadoop102 ~]$ hdfs --daemon start journalnode
[hadoop@hadoop103 ~]$ hdfs --daemon start journalnode

3）在[nn1]上，对其进行格式化， 并启动

[hadoop@hadoop101 ~]$ hdfs namenode -format
[hadoop@hadoop101 ~]$ hdfs --daemon start namenode

4）在[nn2]和[nn3]上，同步 nn1 的元数据信息

[hadoop@hadoop102 ~]$ hdfs namenode -bootstrapStandby
[hadoop@hadoop103 ~]$ hdfs namenode -bootstrapStandby

5）启动[nn2]和[nn3]

[hadoop@hadoop102 ~]$ hdfs --daemon start namenode
[hadoop@hadoop103 ~]$ hdfs --daemon start namenode  

6) 启动 HDFS 服务：

[hadoop@hadoop101 ~]$ start-dfs.sh  

7) 启动 YARN

[hadoop@hadoop101 ~]$ start-yarn.sh

8）查看hdfs是否 Active

[hadoop@hadoop101 ~]$ hdfs haadmin -getServiceState nn1  

• ? 也可以去 zkCli.sh 客户端查看 Namenode 选举锁节点内容，去到zookeeper目录下：

[hadoop@hadoop101 zookeeper-3.5.7]$ bin/zkCli.sh

[zk: localhost:2181(CONNECTED) 0] get -s /hadoop-ha/mycluster/ActiveStandbyElectorLock

	myclusternn2	hadoop102 ?>(?>
cZxid = 0xd00000004
ctime = Tue Feb 15 20:18:04 CST 2022
mZxid = 0xd00000004
mtime = Tue Feb 15 20:18:04 CST 2022
pZxid = 0xd00000004
cversion = 0
dataVersion = 0
aclVersion = 0
ephemeralOwner = 0x200002da9ac0000
dataLength = 33
numChildren = 0

9) 查看yarn服务状态

[hadoop@hadoop101 ~]$ yarn rmadmin -getServiceState rm1

• 可以去 zkCli.sh 客户端查看 ResourceManager 选举锁节点内容：

[hadoop@hadoop101 zookeeper-3.5.7]$ bin/zkCli.sh

[zk: localhost:2181(CONNECTED) 0] get -s /yarn-leader-election/cluster-yarn1/ActiveStandbyElectorLock

cluster-yarn1rm3
cZxid = 0xe0000012c
ctime = Tue Feb 15 22:19:03 CST 2022
mZxid = 0xe0000012c
mtime = Tue Feb 15 22:19:03 CST 2022
pZxid = 0xe0000012c
cversion = 0
dataVersion = 0
aclVersion = 0
ephemeralOwner = 0x20000014a5e0012
dataLength = 20
numChildren = 0