基于ZooKeeper实现HDFS的HA.png
1、集群的规划
-
Zookeeper集群：
192.168.157.112 （bigdata112）
192.168.157.113 （bigdata113）
192.168.157.114 （bigdata114） -
Hadoop集群：
192.168.157.112 （bigdata112） NameNode1 ResourceManager1 Journalnode1
192.168.157.113 （bigdata113） NameNode2 ResourceManager2 Journalnode2
192.168.157.114 （bigdata114） DataNode1 NodeManager1
192.168.157.115 （bigdata115） DataNode2 NodeManager2
2、准备工作
- 安装JDK
- 配置环境变量
- 配置免密码登录
- 配置主机名
3、配置Zookeeper（在bigdata112安装）
- 在主节点（bigdata112）上配置ZooKeeper
-
配置/root/training/zookeeper-3.4.6/conf/zoo.cfg文件
dataDir=/root/training/zookeeper-3.4.6/tmp server.1=bigdata112:2888:3888 server.2=bigdata113:2888:3888 server.3=bigdata114:2888:3888 -
在/root/training/zookeeper-3.4.6/tmp目录下创建一个myid的空文件
echo 1 > /root/training/zookeeper-3.4.6/tmp/myid -
将配置好的zookeeper拷贝到其他节点，同时修改各自的myid文件
scp -r /root/training/zookeeper-3.4.6/ bigdata113:/root/training
scp -r /root/training/zookeeper-3.4.6/ bigdata114:/root/training -
在113/114上修改myid
- 113：
echo 2 > /root/training/zookeeper-3.4.6/tmp/myid - 114：
echo 3 > /root/training/zookeeper-3.4.6/tmp/myid
- 113：
-
4、安装Hadoop集群（在bigdata112上安装）
-
4.1、修改hadoo-env.sh
export JAVA_HOME=/root/training/jdk1.8.0_181 -
4.2、修改core-site.xml
<configuration> <!-- 指定hdfs的nameservice为ns1 --> <property> <name>fs.defaultFS</name> <value>hdfs://ns1</value> </property> <!-- 指定hadoop临时目录 --> <property> <name>hadoop.tmp.dir</name> <value>/root/training/hadoop-2.7.3/tmp</value> </property> <!-- 指定zookeeper地址 --> <property> <name>ha.zookeeper.quorum</name> <value>bigdata112:2181,bigdata113:2181,bigdata114:2181</value> </property> </configuration> -
4.3、修改hdfs-site.xml（配置这个nameservice中有几个namenode）
<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>ns1</value> </property> <!-- ns1下面有两个NameNode，分别是nn1，nn2 --> <property> <name>dfs.ha.namenodes.ns1</name> <value>nn1,nn2</value> </property> <!-- nn1的RPC通信地址 --> <property> <name>dfs.namenode.rpc-address.ns1.nn1</name> <value>bigdata112:9000</value> </property> <!-- nn1的http通信地址 --> <property> <name>dfs.namenode.http-address.ns1.nn1</name> <value>bigdata112:50070</value> </property> <!-- nn2的RPC通信地址 --> <property> <name>dfs.namenode.rpc-address.ns1.nn2</name> <value>bigdata113:9000</value> </property> <!-- nn2的http通信地址 --> <property> <name>dfs.namenode.http-address.ns1.nn2</name> <value>bigdata113:50070</value> </property> <!-- 指定NameNode的日志在JournalNode上的存放位置 --> <property> <name>dfs.namenode.shared.edits.dir</name> <value>qjournal://bigdata112:8485;bigdata113:8485;/ns1</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>/root/training/hadoop-2.7.3/journal</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.ns1</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 shell(/bin/true) </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_rsa</value> </property> <!-- 配置sshfence隔离机制超时时间 --> <property> <name>dfs.ha.fencing.ssh.connect-timeout</name> <value>30000</value> </property> </configuration> -
4.4、修改mapred-site.xml
<configuration> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> </configuration> -
4.5、修改yarn-site.xml
<configuration> <!-- 开启RM高可靠 --> <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>yrc</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>bigdata112</value> </property> <property> <name>yarn.resourcemanager.hostname.rm2</name> <value>bigdata113</value> </property> <!-- 指定zk集群地址 --> <property> <name>yarn.resourcemanager.zk-address</name> <value>bigdata112:2181,bigdata113:2181,bigdata114:2181</value> </property> <property> <name>yarn.nodemanager.aux-services</name> <value>mapreduce_shuffle</value> </property> </configuration> -
4.6、修改slaves
bigdata114 bigdata115 -
4.7、将配置好的hadoop拷贝到其他节点
scp -r /root/training/hadoop-2.7.3/ root@bigdata113:/root/training/
scp -r /root/training/hadoop-2.7.3/ root@bigdata114:/root/training/
scp -r /root/training/hadoop-2.7.3/ root@bigdata115:/root/training/
5、启动Zookeeper集群
- 在112/113/114上执行
zkServer.sh start - 查看是否执行成功：
jps
6、在bigdata112和bigdata13上启动journalnode
- 在112/113上执行
hadoop-daemon.sh start journalnode - 查看是否执行成功：
jps
7、格式化HDFS（在bigdata112上执行）
- 7.1. hdfs namenode -format
- 7.2. 将/root/training/hadoop-2.7.3/tmp拷贝到bigdata113的/root/training/hadoop-2.7.3/tmp下
8、格式化zookeeper
hdfs zkfc -formatZK
日志：
17/07/13 00:34:33 INFO ha.ActiveStandbyElector: Successfully created /hadoop-ha/ns1 in ZK.
9、在bigdata112上启动Hadoop集群
start-all.sh
日志：
Starting namenodes on [bigdata112 bigdata113]
bigdata112: starting namenode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-namenode-hadoop113.out
bigdata113: starting namenode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-namenode-hadoop112.out
bigdata114: starting datanode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-datanode-hadoop115.out
bigdata115: starting datanode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-datanode-hadoop114.out
bigdata113: starting zkfc, logging to /root/training/hadoop-2.7.3/logs/hadoop-root-zkfc-bigdata13.out
bigdata112: starting zkfc, logging to /root/training/hadoop-2.7.3/logs/hadoop-root-zkfc-bigdata12.out
- bigdata113上的ResourceManager需要单独启动
yarn-daemon.sh start resourcemanager
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