hadoop-2.3.0-cdh5.1.0完全分布式集群配置及HA配置的示例分析
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一、安装前准备: 操作系统:CentOS 6.5 64位操作系统 环境:jdk1.7.0_45以上,本次采用jdk-7u55-linux-x64.tar.gz master01 10.10.2.57 namenode 节点 master02 10.10.2.58 namenode 节点 slave01:10.10.2.173 datanode 节点 slave02:10.10.2.59 datanode 节点 slave03: 10.10.2.60 datanode 节点 注:Hadoop2.0以上采用的是jdk环境是1.7,Linux自带的jdk卸载掉,重新安装 下载地址:http://www.oracle.com/technetwork/java/javase/downloads/index.html 软件版本:hadoop-2.3.0-cdh6.1.0.tar.gz, zookeeper-3.4.5-cdh6.1.0.tar.gz 下载地址:http://archive.cloudera.com/cdh6/cdh/5/ 开始安装: 二、jdk安装 1、检查是否自带jdk rpm -qa | grep jdk java-1.6.0-openjdk-1.6.0.0-1.45.1.11.1.el6.i686 2、卸载自带jdk yum -y remove java-1.6.0-openjdk-1.6.0.0-1.45.1.11.1.el6.i686 3、安装jdk-7u55-linux-x64.tar.gz 在usr/目录下创建文件夹java,在java文件夹下运行tar –zxvf jdk-7u55-linux-x64.tar.gz 解压到java目录下 [root@master01 java]# ls jdk1.7.0_55 三、配置环境变量 远行vi /etc/profile # /etc/profile # System wide environment and startup programs, for login setup # Functions and aliases go in /etc/bashrc export JAVA_HOME=/usr/java/jdk1.7.0_55 export JRE_HOME=/usr/java/jdk1.7.0_55/jre export CLASSPATH=/usr/java/jdk1.7.0_55/lib export PATH=$JAVA_HOME/bin: $PATH 保存修改,运行source /etc/profile 重新加载环境变量 运行java -version [root@master01 java]# java -version java version "1.7.0_55" Java(TM) SE Runtime Environment (build 1.7.0_55-b13) Java HotSpot(TM) 64-Bit Server VM (build 24.55-b03, mixed mode) Jdk配置成功 四、系统配置 预先准备5台机器,并配置IP 关闭防火墙 chkconfig iptables off(永久性关闭) 配置主机名和hosts文件 [root@master01 java]# vi /etc/hosts 127.0.0.1 localhost localhost.localdomain localhost4 localhost4.localdomain4 ::1 localhost localhost.localdomain localhost6 localhost6.localdomain6 10.10.2.57 master01 10.10.2.58 master02 10.10.2.173 slave01 10.10.2.59 slave02 10.10.2.60 slave03 按照不同机器IP配置不同的主机名 3、SSH无密码验证配置 因为Hadoop运行过程需要远程管理Hadoop的守护进程,NameNode节点需要通过SSH(Secure Shell)链接各个DataNode节点,停止或启动他们的进程,所以SSH必须是没有密码的,所以我们要把NameNode节点和DataNode节点配制成无秘密通信,同理DataNode也需要配置无密码链接NameNode节点。 在每一台机器上配置: vi /etc/ssh/sshd_config打开 RSAAuthentication yes # 启用 RSA 认证,PubkeyAuthentication yes # 启用公钥私钥配对认证方式 Master01:运行:ssh-keygen –t rsa –P '' 不输入密码直接enter 默认存放在 /root/.ssh目录下, cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys [root@master01 .ssh]# ls authorized_keys id_rsa id_rsa.pub known_hosts slave01执行相同的操作,然后将master01 /root/.ssh/目录下的id_rsa.pub放到 slave01 相同目录下的authorized_keys这样slave01就持有了master01的公钥 然后直接ssh slave01测试是否可以无密码连接到slave01上,然后将slave01 上的id_rsa.pub 追加到master01的authorized_keys中,测试ssh master01 是否可以直接连上slave01. [root@master01 ~]# ssh slave01 Last login: Tue Aug 19 14:28:15 2014 from master01 [root@slave01 ~]# Master01-master02 Master01-slave01 Master01-slave02 Master01-slave03 Master02-slave01 Master02-slave02 Master02-slave03 执行相同的操作。 五、安装Hadoop 建立文件目录 /usr/local/cloud 创建文件夹data,存放数据、日志文件,haooop原文件,zookeeper原文件 [root@slave01 cloud]# ls data hadoop tar zookeeper 5.1、配置hadoop-env.sh 进入到/usr/local/cloud/hadoop/etc/hadoop目录下 配置vi hadoop-env.sh hadoop运行环境加载 export JAVA_HOME=/usr/java/jdk1.7.0_55 5.2、配置core-site.xmlhadoop.tmp.dir /usr/local/cloud/data/hadoop/tmp fs.defaultFS hdfs://zzg (2)hdfs-site.xml配置 ha.zookeeper.quorum master01:2181,slave01:2181,slave02:2181 dfs.namenode.name.dir /usr/local/cloud/data/hadoop/dfs/nn dfs.datanode.data.dir /usr/local/cloud/data/hadoop/dfs/dn dfs.replication 3 dfs.webhdfs.enabled true dfs.permissions false dfs.permissions.enabled false dfs.nameservices zzg dfs.ha.namenodes.zzg nn1,nn2 dfs.namenode.rpc-address.zzg.nn1 master01:9000 dfs.namenode.rpc-address.zzg.nn2 master02:9000 dfs.namenode.http-address.zzg.nn1 master01:50070 dfs.namenode.http-address.zzg.nn2 master02:50070 dfs.namenode.servicerpc-address.zzg.nn1 master01:53310 dfs.namenode.servicerpc-address.zzg.nn2 master02:53310 dfs.namenode.shared.edits.dir qjournal://master01:8485;slave01:8485;slave02:8485/zzg dfs.journalnode.edits.dir /usr/local/cloud/data/hadoop/ha/journal dfs.client.failover.proxy.provider.zzg org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider dfs.ha.automatic-failover.enabled true ha.zookeeper.quorum master01:2181,slave01:2181,slave02:2181 dfs.ha.fencing.methods sshfence 5.3 配置maped-site.xml dfs.ha.fencing.ssh.private-key-files /root/.ssh/id_rsa 5.4配置yarn HA 配置yarn-en.sh java环境 # some Java parameters export JAVA_HOME=/usr/java/jdk1.7.0_55 5.5配置yarn-site.xml mapreduce.framework.name yarn yarn.resourcemanager.connect.retry-interval.ms 2000 yarn.resourcemanager.ha.enabled true yarn.resourcemanager.ha.automatic-failover.enabled true yarn.resourcemanager.ha.rm-ids rm1,rm2 yarn.resourcemanager.ha.id rm1 If we want to launch more than one RM in single node, we need this configuration yarn.resourcemanager.recovery.enabled true yarn.resourcemanager.zk-state-store.address localhost:2181 yarn.resourcemanager.store.class org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore yarn.resourcemanager.zk-address localhost:2181 yarn.resourcemanager.cluster-id yarn-cluster yarn.app.mapreduce.am.scheduler.connection.wait.interval-ms 5000 yarn.resourcemanager.address.rm1 master01:23140 yarn.resourcemanager.scheduler.address.rm1 master01:23130 yarn.resourcemanager.webapp.address.rm1 master01:23188 yarn.resourcemanager.resource-tracker.address.rm1 master01:23125 yarn.resourcemanager.admin.address.rm1 master01:23141 yarn.resourcemanager.ha.admin.address.rm1 master01:23142 yarn.resourcemanager.address.rm2 master02:23140 yarn.resourcemanager.scheduler.address.rm2 master02:23130 yarn.resourcemanager.webapp.address.rm2 master02:23188 yarn.resourcemanager.resource-tracker.address.rm2 master02:23125 yarn.resourcemanager.admin.address.rm2 master02:23141 yarn.resourcemanager.ha.admin.address.rm2 master02:23142 Address where the localizer IPC is. yarn.nodemanager.localizer.address 0.0.0.0:23344 NM Webapp address. yarn.nodemanager.webapp.address 0.0.0.0:23999 yarn.nodemanager.aux-services mapreduce_shuffle yarn.nodemanager.aux-services.mapreduce.shuffle.class org.apache.hadoop.mapred.ShuffleHandler yarn.nodemanager.local-dirs /usr/local/cloud/data/hadoop/yarn/local yarn.nodemanager.log-dirs /usr/local/cloud/data/logs/hadoop mapreduce.shuffle.port 23080 六、配置zookeeper集群 在zookeeper目录下建立data目录 和logs目录, 配置zoo.cnf dataDir=/usr/local/cloud/zookeeper/data dataLogDir=/usr/local/cloud/zookeeper/logs # the port at which the clients will connect clientPort=2181 server.1=master01:2888:3888 server.2=master02:2888:3888 server.3=slave01:2888:3888 server.4=slave02:2888:3888 server.5=slave03:2888:3888 在data目录下创建myid文件,并在对应的机器上填写数字,如上配置master01 server01 的myid写入1, master02 中的data的myid写入2,依次在其他机子上执行相同操作。 在各个机器下zookeeper目录下的bin目录下执行zkServer.sh start命令 再运行zkServer.sh status如果出现leader 或fllower 则说明集群配置正确。 到此各个配置文件配置完毕 七、启动Hadoop集群严格按照以下顺序执行(第一次) (1)各个节点启动zookeeper,在zookeeper/bin/zkServer.sh start (2) 在hadoop/bin/hdfs zkfc –formatZK 进行格式化创建命名空间 (3)在配置了journalnode的节点启动,master01,slave01,slave02 在hadoop/sbin/hadoop-daemon.sh journalnode (4)在主namenode节点执行格式化 ./bin/hadoop namenode -format zzg 主机器上启动namenode hadoop/sbin/ hadoop-daemon.sh start namenode (5)将主namenode节点格式化的目录拷贝到从主namenode节点上 hadoop/bin/hdfs namenode –bootstrapStandby hadoop/sbin/hadoop-daemon.sh start namenode (6) 在两个namenode节点都执行以下命令 ./sbin/hadoop-daemon.sh start zkfc (7) 在所有datanode节点都执行以下命令启动datanode ./sbin/hadoop-daemon.sh start datanode (8)在主namenode节点启动yarn,运行yarn-start.sh命令 jps可以看到 namenode节点 [root@master01 ~]# jps 38972 JournalNode 38758 NameNode 39166 DFSZKFailoverController 37473 QuorumPeerMain 39778 ResourceManager 42620 Jps datanode节点 [root@slave01 ~]# jps 33440 DataNode 35277 Jps 32681 QuorumPeerMain 33568 JournalNode 34231 NodeManager yarn.client.failover-proxy-provider org.apache.hadoop.yarn.client.ConfiguredRMFailoverProxyProvider
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