HadoopHA高可用配置文件修改&启动步骤说明

Love The Way You Lie 2023-10-08 15:18 6阅读 0赞

### HadoopHA高可用配置文件修改&启动步骤说明 ###

###### core-site.xml的配置 ######

<property>
    	<name>fs.defaultFS</name>
    	<value>hdfs://myns1/</value>
    </property>
    
    <property>
    	<name>hadoop.tmp.dir</name>
    	<value>/opt/soft/hadoop/data</value>
    </property>
    
    <property>
    	<name>ha.zookeeper.quorum</name>
    	<value>mymaster:2181,myslave1:2181,myslave2:2181</value>
    </property>
    
    <property>
    	<name>hadoop.proxyuser.bigdata.hosts</name>
    	<value>*</value>
    </property>
    <property>
    	<name>hadoop.proxyuser.bigdata.groups</name>
    	<value>*</value>
    </property>

###### hdfs-site.xml的配置 ######

<property>
    	<name>fs.replication</name>
    	<value>2</value>
    </property>
    
    <property>
    	<name>dfs.nameservices</name>
    	<value>myns1</value>
    </property>
    
    <property>
    	<name>dfs.ha.namenodes.myns1</name>
    	<value>nn1,nn2</value>
    </property>
    
    
    <property>
    	<name>dfs.namenode.rpc-address.myns1.nn1</name>
    	<value>mymaster:9000</value>
    </property>
    
    <property>
    	<name>dfs.namenode.http-address.myns1.nn1</name>
    	<value>mymaster:50070</value>
    </property>
    
    
    <property>
    	<name>dfs.namenode.rpc-address.myns1.nn2</name>
    	<value>myslave1:9000</value>
    </property>
    
    <property>
    	<name>dfs.namenode.http-address.myns1.nn2</name>
    	<value>myslave1:50070</value>
    </property>
    
    
    <property>
    	<name>dfs.namenode.shared.edits.dir</name>
    	<value>qjournal://mymaster:8485;myslave1:8485;myslave2:8485/myns1</value>
    </property>
    
    <property>
    	<name>dfs.journalnode.edits.dir</name>
    	<value>/opt/soft/hadoop/journaldata</value>
    </property>
    
    
    <property>
    	<name>dfs.ha.automatic-failover.enabled</name>
    	<value>true</value>
    </property>
    
    
    
    <property>
    	<name>dfs.client.failover.proxy.provider.myns1</name>
    	<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
    </property>
    
    
    <property>
    	<name>dfs.ha.fencing.methods</name>
    	<value>
    		sshfence
    		shell(/bin/true)
    	</value>
    </property>
    
    
    <property>
    	<name>dfs.ha.fencing.ssh.private-key-files</name>
    	<value>/home/账户名/.ssh/id_rsa</value>
    	
    </property>
    
    
    <property>
    	<name>dfs.ha.fencing.ssh.connect-timeout</name>
    	<value>30000</value>
    </property>
    
    
    <property>
    	<name>dfs.webhdfs.enabled</name>
    	<value>true</value>
    </property>

###### yarn-site.xml配置 ######

<property>
    	<name>yarn.resourcemanager.ha.enabled</name>
    	<value>true</value>
    </property>
    
    
    <property>
    	<name>yarn.resourcemanager.cluster-id</name>
    	<value>yrc</value>
    </property>
    
    
    <property>
    	<name>yarn.resourcemanager.ha.rm-ids</name>
    	<value>rm1,rm2</value>
    </property>
    
    
    <property>
    	<name>yarn.resourcemanager.hostname.rm1</name>
    	<value>mymaster</value>
    </property>
    <property>
    	<name>yarn.resourcemanager.hostname.rm2</name>
    	<value>myslave1</value>
    </property>
    
    
    <property>
    	<name>yarn.resourcemanager.zk-address</name>
    	<value>mymaster:2181,myslave1:2181,myslave2:2181</value>
    </property>
    
    
    <property>
    	<name>yarn.nodemanager.aux-services</name>
    	<value>mapreduce_shuffle</value>
    </property>
    
    
    <property>
    	<name>yarn.log-aggregation.retain-seconds</name>
    	<value>86400</value>
    </property>
    
    <property>
    	<name>yarn.resourcemanager.recovery.enabled</name>
    	<value>true</value>
    </property>
    
    
    <property>
    	<name>yarn.resourcemanager.store.class</name>
    	<value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
    </property>

###### mapred-site.xml配置 ######

<property>
    	<name>mapreduce.framework.name</name>
    	<value>yarn</value>
    </property>
    
    
    <property>
    	<name>mapreduce.jobhistory.address</name>
    	<value>mymaster:10020</value>
    </property>
    
    
    <property>
    	<name>mapreduce.jobhistory.webapp.address</name>
    	<value>mymaster:19888</value>
    </property>

###### slaves配置 ######

将集群datanode节点机器名放在这里，换行即可，如：
    mymaster
    myslave1
    myslave2

###### hadoop-env.sh ######

export JAVA_HOME=/opt/jdk

##### mapred-env.sh #####

# Licensed to the Apache Software Foundation (ASF) under one or more
    # contributor license agreements.  See the NOTICE file distributed with
    # this work for additional information regarding copyright ownership.
    # The ASF licenses this file to You under the Apache License, Version 2.0
    # (the "License"); you may not use this file except in compliance with
    # the License.  You may obtain a copy of the License at
    #
    #     http://www.apache.org/licenses/LICENSE-2.0
    #
    # Unless required by applicable law or agreed to in writing, software
    # distributed under the License is distributed on an "AS IS" BASIS,
    # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    # See the License for the specific language governing permissions and
    # limitations under the License.
    
    # export JAVA_HOME=/home/y/libexec/jdk1.6.0/
    
    export HADOOP_JOB_HISTORYSERVER_HEAPSIZE=1000
    export JAVA_HOME=/opt/jdk
    export HADOOP_MAPRED_ROOT_LOGGER=INFO,RFA
    
    #export HADOOP_JOB_HISTORYSERVER_OPTS=
    #export HADOOP_MAPRED_LOG_DIR="" # Where log files are stored.  $HADOOP_MAPRED_HOME/logs by default.
    #export HADOOP_JHS_LOGGER=INFO,RFA # Hadoop JobSummary logger.
    #export HADOOP_MAPRED_PID_DIR= # The pid files are stored. /tmp by default.
    #export HADOOP_MAPRED_IDENT_STRING= #A string representing this instance of hadoop. $USER by default
    #export HADOOP_MAPRED_NICENESS= #The scheduling priority for daemons. Defaults to 0.

###### HadoopHA启动步骤 ######

1、分别每个机器上启动zookeeper集群（jps看到QuorumPeerMain进程）
        bin/zkServer.sh start
    2、每个机器上启动 journalnode(最好是奇数台机器)
       (hadoop-daemon.sh start journalnode)
       启动完毕后jps能看到JournalNode进程
    3、在一个namenode节点上进行格式化
       （格式化成功后在配置的data目录下，有个dfs，里面有name和data，因为没有启动集群，data是空的因为格式化后暂时没有内容）
       （name中存储元数据，data存真数据）
       （name下有current，下面有4个文件，就是元数据信息<fsimage.....,seen_txid,VERSION>）
    4、注意，在格式化后namenode的机器上找到存放数据的data目录，然后拷贝到另外一个备份的data目录下，保持初始元数据一致。
         下面是例子，具体目录自己决定。
         scp -r data hadoop02:/opt/temp
         scp -r data hadoop03:/opt/temp
    5、在第任何一个namenode上执行zkfc -formatZK操作(#格式化zookeeper)，命令如下：
       hdfs zkfc -formatZK
    6、start-dfs.sh
    7、start-yarn.sh
    8、测试
       1）分别在每个机器上jps查看状态
       2）分别访问两个namenode机器上的50070界面，查看状态是否一个是Active，另外一个是Standby
       3）也可以测试访问一下yarn集群
       4）高可用测试，测试主备切换
       （将active状态的namenode进程干掉，kill -9 xxxxid）
       （可以再使用单节点启动方式启动namenode：hadoop-daemon.sh start namenode）
    
    
    在另外一台resourceManager机器上单独启动resourceManager进程：
    yarn-daemon.sh start resourcemanager
    
    
     yarn高可用测试和hadoop一样，访问的端口是8088
    
    
    
    启动历史服务器
    mr-jobhistory-daemon.sh start historyserver
    
    yarn-daemon.sh start nodemanager
    yarn-daemon.sh start resourcemanager
    
    然后两台机器分别启动resourcemanager即可
    
    命令方式查看hadoop状态：hdfs haadmin -getServiceState nn2
    命令方式查看yarn状态：yarn rmadmin -getServiceState rm1