【ambari-部署】Ambari2.6.2 HDP2.6.5 大数据集群搭建

喜欢ヅ旅行 2021-12-10 15:09 371阅读 0赞

转自： [https://blog.csdn.net/weixin\_33923762/article/details/90932169][https_blog.csdn.net_weixin_33923762_article_details_90932169]

hadoop 集群 master无法免密登录slave2： [https://blog.csdn.net/weixin\_37600848/article/details/83418515][https_blog.csdn.net_weixin_37600848_article_details_83418515]

Ambari,hadoop的配置,管理和监控项目入门： [https://blog.csdn.net/wuliusir/article/details/50754859][https_blog.csdn.net_wuliusir_article_details_50754859]

Ambari2.6.2集成Kerberos： [https://blog.51cto.com/784687488/2332072?source=dra][https_blog.51cto.com_784687488_2332072_source_dra]

Flink流处理之迭代API分析： [https://blog.csdn.net/yanghua\_kobe/article/details/53456674][https_blog.csdn.net_yanghua_kobe_article_details_53456674]

Ambari架构源码解析： [https://blog.csdn.net/chengyuqiang/article/details/60963480][https_blog.csdn.net_chengyuqiang_article_details_60963480]

[ambari rest api (三)][ambari rest api]： [https://www.cnblogs.com/itboys/p/7004148.html][ambari rest api]

Flink Rest API使用：  [https://blog.csdn.net/qq\_27710549/article/details/80500857][https_blog.csdn.net_qq_27710549_article_details_80500857]

[HUE配置文件hue.ini 的zookeeper模块详解（图文详解）（分HA集群）][HUE_hue.ini _zookeeper_HA]： [https://www.cnblogs.com/zlslch/p/6817538.html][HUE_hue.ini _zookeeper_HA]

Flink 通过 REST API 获取实时 task metric 汇总统计信息： [https://blog.csdn.net/yuchuanchen/article/details/88406438][https_blog.csdn.net_yuchuanchen_article_details_88406438]

CDH 和ambari之间的比较： [https://blog.csdn.net/qq\_32649581/article/details/90899363][https_blog.csdn.net_qq_32649581_article_details_90899363]

docker安装centos7搭建集群: [https://blog.csdn.net/kk25114/article/details/88639383][https_blog.csdn.net_kk25114_article_details_88639383]

hadoop集群上部署flink环境: [https://blog.csdn.net/weixin\_40626699/article/details/89139591][https_blog.csdn.net_weixin_40626699_article_details_89139591]

[大数据基础之Ambari（3）通过Ambari部署Airflow][Ambari_3_Ambari_Airflow]: [https://www.cnblogs.com/barneywill/p/10284804.html][Ambari_3_Ambari_Airflow]

Hadoop建设工具Ambari的安装部署及完整使用（一）——介绍: [https://blog.csdn.net/balabalayi/article/details/64904822][https_blog.csdn.net_balabalayi_article_details_64904822]

flink实战--REST API与metrics监控:  [https://blog.csdn.net/aA518189/article/details/88952910][https_blog.csdn.net_aA518189_article_details_88952910]

Flink架构、原理与部署测试及从kafka到flink到hbase:  [https://blog.csdn.net/qq\_38799155/article/details/80808818][https_blog.csdn.net_qq_38799155_article_details_80808818]

分布式集群离线配置:  [https://blog.csdn.net/m0\_37614660/article/details/88987862][https_blog.csdn.net_m0_37614660_article_details_88987862]

Ubuntu 16.04安装Hadoop及Spark:  [https://blog.csdn.net/u011596455/article/details/53115410][https_blog.csdn.net_u011596455_article_details_53115410]

Ambari部署Hadoop环境&安装ZooKeeper :  [https://my.oschina.net/qiangzigege/blog/534176][https_my.oschina.net_qiangzigege_blog_534176]

随笔分类 - ELK(Elasticsearch/Logstash/Kibana)集群搭建:  [https://www.cnblogs.com/zlslch/category/972313.html][https_www.cnblogs.com_zlslch_category_972313.html]

比较完整的hadoop集群组件的安装教程; [https://blog.csdn.net/u010199356/article/details/87538403][https_blog.csdn.net_u010199356_article_details_87538403]

本地调试opentsdb的环境搭建： [https://blog.csdn.net/weixin\_34242819/article/details/88281740][https_blog.csdn.net_weixin_34242819_article_details_88281740]

原文链接：[http://www.jianshu.com/p/abcb22a47652][https_blog.csdn.net_weixin_33923762_article_details_90932169]

Ambari 2.6.2 中  
HDFS-2.7.3 YARN-2.7.3 HIVE-1.2.1 HBASE-1.1.2 ZOOKEEPER-3.4.6 SPARK-2.3.0

> 注：本文基于root用户操作

# 一、安装环境准备 #

> 操作系统 centos7.5  
> hdc-data1：192.168.163.51  
> hdc-data2：192.168.163.52  
> hdc-data3：192.168.163.53  
> 【安装环境准备每台集群机器一样的操作，或者使用scp远程拷贝】

### 1、主机名IP映射配置 ###

FQDN：(Fully Qualified Domain Name)全限定域名：同时带有主机名和域名的名称。（通过符号“.”）  
例如：主机名是bigserver,域名是mycompany.com,那么FQDN就是bigserver.mycompany.com。

1.  `vi /etc/hosts`
2.  `#添加如下地址映射及FQDN（ambari注册时需要）`
3.  `192.168.163.51 hdc-data1 hdc-data1.hadoop`
4.  `192.168.163.52 hdc-data2 hdc-data2.hadoop`
5.  `192.168.163.53 hdc-data3 hdc-data3.hadoop`

### 2、SSH免密登录配置 ###

1.  `ssh-keygen`
2.  `ssh-copy-id -i ~/.ssh/id_rsa.pub root@hdc-data1`
3.  `ssh-copy-id -i ~/.ssh/id_rsa.pub root@hdc-data2`
4.  `ssh-copy-id -i ~/.ssh/id_rsa.pub root@hdc-data3`

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### 3、关闭及禁止防火墙 ###

1.  `systemctl stop firewalld.service`
2.  `systemctl disable firewalld.service`

### 4、关闭SELinux ###

> SELinux(Security-Enhanced Linux) 是美国国家安全局（NSA）对于强制访问控制的实现，是 Linux历史上最杰出的新安全子系统。NSA是在Linux社区的帮助下开发了一种访问控制体系，在这种访问控制体系的限制下，进程只能访问那些在他的任务中所需要文件。

1.  `vi /etc/sysconfig/selinux`
2.  `#修改以下内容`
3.  `SELINUX=disabled`

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### 5、开启NTP服务 ###

1.  `yum install -y ntp`
2.  `systemctl enable ntpd`
3.  `systemctl start ntpd`

### 6、安装JDK ###

> 下载地址：[https://www.oracle.com/technetwork/cn/java/javase/downloads/jdk8-downloads-2133151-zhs.html][https_www.oracle.com_technetwork_cn_java_javase_downloads_jdk8-downloads-2133151-zhs.html]

通过文件传输上传到服务器，这里不可用wget直接下载。

1.  `mkdir -p /opt/java`
2.  `tar -zxvf jdk-8u181-linux-x64.tar.gz -C /opt/java/`
3.  `vi /etc/profile`
4.   
5.  `export JAVA_HOME=/opt/java/jdk1.8.0_181`
6.  `export JRE_HOME=$JAVA_HOME/jre`
7.  `export CLASSPATH=.:$JAVA_HOME/lib:$JAVA_HOME/jre/lib`
8.  `export PATH=$PATH:$JAVA_HOME/bin`

远程分发到其他服务器

1.  `scp -r /opt/java/jdk1.8.0_181/ root@hdc-data2:/opt/java/`
2.  `scp -r /opt/java/jdk1.8.0_181/ root@hdc-data3:/opt/java/`
3.   
4.  `scp /etc/profile root@hdc-data2:/etc/`
5.  `scp /etc/profile root@hdc-data3:/etc/`
6.   
7.  `source /etc/profile`

# 二、Ambari安装 #

### 1、制作Ambari本地yum源 ###

选取一台机器即可，在此选择hdc-data1。

> [https://docs.hortonworks.com/HDPDocuments/Ambari-2.6.2.0/bk\_ambari-installation/content/ch\_obtaining-public-repos.html][https_docs.hortonworks.com_HDPDocuments_Ambari-2.6.2.0_bk_ambari-installation_content_ch_obtaining-public-repos.html]
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需要下载资源安装包如下：

1.  `wget http://public-repo-1.hortonworks.com/ambari/centos7/2.x/updates/2.6.2.0/ambari-2.6.2.0-centos7.tar.gz`
2.  `wget http://public-repo-1.hortonworks.com/HDP/centos7/2.x/updates/2.6.5.0/HDP-2.6.5.0-centos7-rpm.tar.gz`
3.  `wget http://public-repo-1.hortonworks.com/HDP-UTILS-1.1.0.22/repos/centos7/HDP-UTILS-1.1.0.22-centos7.tar.gz`
4.  `wget http://public-repo-1.hortonworks.com/HDP-GPL/centos7/2.x/updates/2.6.5.0/HDP-GPL-2.6.5.0-centos7-gpl.tar.gz`

1.1 安装 Apache HTTP 服务器

1.  `yum install httpd -y`
2.  `#开启服务并设置开机自启动`
3.  `systemctl start httpd.service`
4.  `systemctl enable httpd.service`

1.2 安装制作yum源工具

yum install yum-utils createrepo

1.3 创建http服务器

http根目录默认是即/var/www/html/

1.  `mkdir -p /var/www/html/ambari`
2.  `#cd /var/www/html/ambari`
3.  `#将下载好的安装包上传并解压`
4.  `tar xvf HDP-2.6.5.0-centos7-rpm.tar.gz -C /var/www/html/ambari`
5.  `tar xvf ambari-2.6.2.0-centos7.tar.gz -C /var/www/html/ambari`
6.  `tar xvf HDP-UTILS-1.1.0.22-centos7.tar.gz -C /var/www/html/ambari`
7.  `tar xvf HDP-GPL-2.6.5.0-centos7-gpl.tar.gz -C /var/www/html/ambari`
8.   
9.  `# 删除压缩包`
10. `rm -rf ambari-2.6.2.0-centos7.tar.gz`
11. `rm -rf HDP-2.6.5.0-centos7-rpm.tar.gz`
12. `rm -rf HDP-UTILS-1.1.0.22-centos7.tar.gz`
13. `rm -rf HDP-GPL-2.6.5.0-centos7-gpl.tar.gz`

验证

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1.4 配置ambari、HDP、HDP-UTILS的本地源

1.  `#yum install wget -y`
2.  `cd /etc/yum.repos.d/`
3.  `wget http://public-repo-1.hortonworks.com/ambari/centos7/2.x/updates/2.6.2.0/ambari.repo`
4.  `wget http://public-repo-1.hortonworks.com/HDP/centos7/2.x/updates/2.6.5.0/hdp.repo`
5.  `wget http://public-repo-1.hortonworks.com/HDP-GPL/centos7/2.x/updates/2.6.5.0/hdp.gpl.repo`

编辑ambari.repo，修改baseurl和gpgkey

1.  `[root@hdc-data1 yum.repos.d]# vi ambari.repo`
2.   
3.  `#VERSION_NUMBER=2.6.2.0-155`
4.  `[ambari-2.6.2.0]`
5.  `name=ambari Version - ambari-2.6.2.0`
6.  `#baseurl=http://public-repo-1.hortonworks.com/ambari/centos7/2.x/updates/2.6.2.0`
7.  `baseurl=http://192.168.163.51/ambari/ambari/centos7/2.6.2.0-155`
8.  `gpgcheck=1`
9.  `#gpgkey=http://public-repo-1.hortonworks.com/ambari/centos7/2.x/updates/2.6.2.0/RPM-GPG-KEY/RPM-GPG-KEY-Jenkins`
10. `gpgkey=http://192.168.163.51/ambari/ambari/centos7/2.6.2.0-155/RPM-GPG-KEY/RPM-GPG-KEY-Jenkins`
11. `enabled=1`
12. `priority=1`

编辑hdp.repo，修改baseurl和gpgkey

1.  `[root@hdc-data1 yum.repos.d]# vi hdp.repo`
2.   
3.  `#VERSION_NUMBER=2.6.5.0-292`
4.  `[HDP-2.6.5.0]`
5.  `name=HDP Version - HDP-2.6.5.0`
6.  `#baseurl=http://public-repo-1.hortonworks.com/HDP/centos7/2.x/updates/2.6.5.0`
7.  `baseurl=http://192.168.163.51/ambari/HDP/centos7/2.6.5.0-292`
8.  `gpgcheck=1`
9.  `#gpgkey=http://public-repo-1.hortonworks.com/HDP/centos7/2.x/updates/2.6.5.0/RPM-GPG-KEY/RPM-GPG-KEY-Jenkins`
10. `gpgkey=http://192.168.163.51/ambari/HDP/centos7/2.6.5.0-292/RPM-GPG-KEY/RPM-GPG-KEY-Jenkins`
11. `enabled=1`
12. `priority=1`
13.  
14.  
15. `[HDP-UTILS-1.1.0.22]`
16. `name=HDP-UTILS Version - HDP-UTILS-1.1.0.22`
17. `#baseurl=http://public-repo-1.hortonworks.com/HDP-UTILS-1.1.0.22/repos/centos7`
18. `baseurl=http://192.168.163.51/ambari/HDP-UTILS/centos7/1.1.0.22`
19. `gpgcheck=1`
20. `#gpgkey=http://public-repo-1.hortonworks.com/HDP/centos7/2.x/updates/2.6.5.0/RPM-GPG-KEY/RPM-GPG-KEY-Jenkins`
21. `gpgkey=http://192.168.163.51/ambari/HDP-UTILS/centos7/1.1.0.22/RPM-GPG-KEY/RPM-GPG-KEY-Jenkins`
22. `enabled=1`
23. `priority=1`

编辑hdp.gpl.repo，修改baseurl和gpgkey

1.  `[root@hdc-data1 yum.repos.d]# vi hdp.gpl.repo`
2.   
3.  `#VERSION_NUMBER=2.6.5.0-292`
4.  `[HDP-GPL-2.6.5.0]`
5.  `name=HDP-GPL Version - HDP-GPL-2.6.5.0`
6.  `#baseurl=http://public-repo-1.hortonworks.com/HDP-GPL/centos7/2.x/updates/2.6.5.0`
7.  `baseurl=http://192.168.163.51/ambari/HDP-GPL/centos7/2.6.5.0-292`
8.  `gpgcheck=1`
9.  `#gpgkey=http://public-repo-1.hortonworks.com/HDP-GPL/centos7/2.x/updates/2.6.5.0/RPM-GPG-KEY/RPM-GPG-KEY-Jenkins`
10. `gpgkey=http://192.168.163.51/ambari/HDP-GPL/centos7/2.6.5.0-292/RPM-GPG-KEY/RPM-GPG-KEY-Jenkins`
11. `enabled=1`
12. `priority=1`
13.

分发到其他机器

1.  `scp /etc/yum.repos.d/ambari.repo root@hdc-data2:/etc/yum.repos.d/`
2.  `scp /etc/yum.repos.d/ambari.repo root@hdc-data3:/etc/yum.repos.d/`
3.  `scp /etc/yum.repos.d/hdp.repo root@hdc-data2:/etc/yum.repos.d/`
4.  `scp /etc/yum.repos.d/hdp.repo root@hdc-data3:/etc/yum.repos.d/`
5.  `scp /etc/yum.repos.d/hdp.gpl.repo root@hdc-data2:/etc/yum.repos.d/`
6.  `scp /etc/yum.repos.d/hdp.gpl.repo root@hdc-data3:/etc/yum.repos.d/`

每台机器yum配置

1.  `yum clean all`
2.  `yum makecache`
3.  `yum list`

### 2、安装Mysql数据库 ###

> Ambari安装会将安装等信息写入数据库，建议使用MariaDB数据库，也可以不安装而使用默认数据库PostgreSQL

2.1 安装及初始化设置

1.  `[root@hdc-data1 ~]# yum install mariadb-server`
2.  `[root@hdc-data1 ~]# systemctl start mariadb`
3.  `[root@hdc-data1 ~]# systemctl enable mariadb`
4.  `[root@hdc-data1 ~]# mysql_secure_installation`
5.   
6.  `#首先是设置密码，会提示先输入密码`
7.  `Enter current password for root (enter for none):<–初次运行直接回车`
8.  `#设置密码`
9.  `Set root password? [Y/n] <– 是否设置root用户密码，输入y并回车或直接回车`
10. `New password: <– 设置root用户的密码`
11. `Re-enter new password: <– 再输入一次你设置的密码`
12. `#其他配置`
13. `Remove anonymous users? [Y/n] <– 是否删除匿名用户，回车`
14. `Disallow root login remotely? [Y/n] <–是否禁止root远程登录,回车,`
15. `Remove test database and access to it? [Y/n] <– 是否删除test数据库，回车`
16. `Reload privilege tables now? [Y/n] <– 是否重新加载权限表，回车`

> **【可选】修改mysql端口**（生产环境安全考虑）  
> 查看端口
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2.2 安装完成后创建ambari数据库及用户

1.  `#进入mysql shell`
2.  `mysql -uroot -p`

1.  `create database ambari character set utf8 ;`
2.  `CREATE USER 'ambari'@'%'IDENTIFIED BY 'ambari123';`
3.  `GRANT ALL PRIVILEGES ON *.* TO 'ambari'@'%';`
4.  `FLUSH PRIVILEGES;`

如果要安装Hive，创建Hive数据库和用户

1.  `create database hive character set utf8 ;`
2.  `CREATE USER 'hive'@'%'IDENTIFIED BY 'hive123';`
3.  `GRANT ALL PRIVILEGES ON *.* TO 'hive'@'%';`
4.  `FLUSH PRIVILEGES;`

如果要安装Oozie，创建Oozie数据库和用户

1.  `create database oozie character set utf8 ;`
2.  `CREATE USER 'oozie'@'%'IDENTIFIED BY 'oozie123';`
3.  `GRANT ALL PRIVILEGES ON *.* TO 'oozie'@'%';`
4.  `FLUSH PRIVILEGES;`

### 3、安装 ambari ###

yum install ambari-server

### 4、下载mysql驱动 ###

> [http://central.maven.org/maven2/mysql/mysql-connector-java/5.1.40/][http_central.maven.org_maven2_mysql_mysql-connector-java_5.1.40]  
> 将mysql-connector-Java.jar复制到/usr/share/java目录下

1.  `mkdir /usr/share/java`
2.  `cp mysql-connector-java-5.1.40.jar /usr/share/java/mysql-connector-java.jar`

将mysql-connector-java.jar复制到/var/lib/ambari-server/resources目录下

cp mysql-connector-java-5.1.40.jar /var/lib/ambari-server/resources/mysql-jdbc-driver.jar

### 5、编辑/etc/ambari-server/conf/ambari.properties，添加如下内容 ###

1.  `server.jdbc.driver.path=/usr/share/java/mysql-connector-java.jar`
2.  `#【可选】修改默认8080端口`
3.  `#client.api.port=18080`

### 6、ambaria初始化 ###

1.  `#设置mysql驱动`
2.  `ambari-server setup --jdbc-db=mysql --jdbc-driver=/usr/share/java/mysql-connector-java.jar`
3.  `ambari-server setup`

完整初始化如下：

1.  `[root@hdc-data1 ~]# ambari-server setup`
2.  `Using python /usr/bin/python`
3.  `Setup ambari-server`
4.  `Checking SELinux...`
5.  `SELinux status is 'disabled'`
6.  `Customize user account for ambari-server daemon [y/n] (n)? y`
7.  `Enter user account for ambari-server daemon (root):`
8.  `Adjusting ambari-server permissions and ownership...`
9.  `Checking firewall status...`
10. `Checking JDK...`
11. `[1] Oracle JDK 1.8 + Java Cryptography Extension (JCE) Policy Files 8`
12. `[2] Oracle JDK 1.7 + Java Cryptography Extension (JCE) Policy Files 7`
13. `[3] Custom JDK`
14. `==============================================================================`
15. `Enter choice (1): 3`
16. `WARNING: JDK must be installed on all hosts and JAVA_HOME must be valid on all hosts.`
17. `WARNING: JCE Policy files are required for configuring Kerberos security. If you plan to use Kerberos,please make sure JCE Unlimited Strength Jurisdiction Policy Files are valid on all hosts.`
18. `Path to JAVA_HOME: /opt/java/jdk1.8.0_181`
19. `Validating JDK on Ambari Server...done.`
20. `Checking GPL software agreement...`
21. `GPL License for LZO: https://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html`
22. `Enable Ambari Server to download and install GPL Licensed LZO packages [y/n] (n)? y`
23. `Completing setup...`
24. `Configuring database...`
25. `Enter advanced database configuration [y/n] (n)? y`
26. `Configuring database...`
27. `==============================================================================`
28. `Choose one of the following options:`
29. `[1] - PostgreSQL (Embedded)`
30. `[2] - Oracle`
31. `[3] - MySQL / MariaDB`
32. `[4] - PostgreSQL`
33. `[5] - Microsoft SQL Server (Tech Preview)`
34. `[6] - SQL Anywhere`
35. `[7] - BDB`
36. `==============================================================================`
37. `Enter choice (1): 3`
38. `Hostname (localhost):`
39. `Port (3306):`
40. `Database name (ambari):`
41. `Username (ambari):`
42. `Enter Database Password (bigdata):`
43. `Re-enter password:`
44. `Configuring ambari database...`
45. `Configuring remote database connection properties...`
46. `WARNING: Before starting Ambari Server, you must run the following DDL against the database to create the schema: /var/lib/ambari-server/resources/Ambari-DDL-MySQL-CREATE.sql`
47. `Proceed with configuring remote database connection properties [y/n] (y)? y`
48. `Extracting system views...`
49. `.....ambari-admin-2.6.2.0.155.jar`
50. `......`
51. `Adjusting ambari-server permissions and ownership...`
52. `Ambari Server 'setup' completed successfully.`

> 说明：  
> 1：提示是否自定义设置。输入：y 或 按回车继续  
> 2：ambari-server 账号。使用root（推荐）用户直接回车 若使用ambari用户输入：ambari  
> 3：设置JDK,输入数字3，选客户端安装jdk，如果服务器可以访问外网，则可以选1，自动下载jdk1.8，默认下载的安装目录是/usr/java/default  
> 4：如果上面选择3自定义JDK,则需要设置JAVA\_HOME  
> 5：输入：y 或 按回车继续  
> 6：输入“y“，进行数据库的高级配置  
> 7：输入“3“，选择mysql/mariadb数据库  
> 8：设置数据库的配置参数：host,port,database,username,password。根据实际情况输入，如果和括号内相同，则可以直接回车。若端口改6033则输入port:6033。  
> 9：输入：y 或 按回车继续  
> （若设置更改，可以再次执行`ambari-server setup`进行设置）

### 7、将Ambari数据库脚本导入到数据库 ###

1.  `#用Ambari用户（上面设置的用户）登录mysql`
2.  `mysql -u ambari -p`
3.  `use ambari;`
4.  `source /var/lib/ambari-server/resources/Ambari-DDL-MySQL-CREATE.sql`

> ![14788851-fa6158d1a5d982ca.png][]
> 
> image.png

### 8、启动Ambari ###

ambari-server start

>  
> 
> ![14788851-62cc7ceabfa6b0ed.png][]
> 
> image.png
> 
>   
> 浏览器访问： [http://hdc-data1:8080/][http_hdc-data1_8080] 默认登录用户：admin，密码：admin
> 
>

### 9、WEBUI配置 ###

> ![14788851-603463fdf82f4b6a.png][]
> 
> image.png
> 
>  
> 
>  
> 
> 创建集群名称
> 
> ![14788851-40b71b7fcaa84d20.png][]
> 
> image.png
> 
>  
> 
>  
> 
> 选择HDP版本和选择本地仓库
> 
> ![14788851-a86a2a36ca46f76e.png][]
> 
> image.png
> 
>   
> 配置HDP的Repository
> 
> ![14788851-e5a87037f420c065.png][]
> 
> image.png
> 
>   
> 输入集群节点host(FQDN)和Ambari节点SSH的私钥
> 
> ![14788851-fc32b66ad45c1744.png][]
> 
> image.png
> 
>  
> 
>  
> 
> 等待ambari-agents注册
> 
> ![14788851-d3338cedcaf1f3d3.png][]
> 
> image.png
> 
>   
> 若报错
> 
> ![14788851-021966852ede6088.png][]
> 
> image.png
> 
>  
> 
> ![14788851-c609abd44f5d7a13.png][]
> 
> image.png

【遇到问题 Confirm Hosts】  
注册ambari-agents时failed  
NetUtil.py:96 - EOF occurred in violation of protocol (\_ssl.c:579)  
SSLError: Failed to connect. Please check openssl library versions.  
解决：如下第三个方案，/etc/ambari-agent/conf/ambari-agent.ini文件只有执行该步骤进行注册才生成。修改后点击“Retry Failed”按钮，等待注册成功进入下一步。

1.  `# 1、yum upgrade openssl 已是最新本版，未解决`
2.  `# 2、vi /etc/python/cert-verification.cfg 修改 verify=disable，未解决`
3.  `[https]`
4.  `#verify=platform_default`
5.  `verify=disable`
6.  `# 3、最后解决方案 在ambari-agent的配置文件/etc/ambari-agent/conf/ambari-agent.ini`
7.  `在 ［security］标签下面增加一项`
8.  `[security]`
9.  `force_https_protocol=PROTOCOL_TLSv1_2`

> ![14788851-cffc2d69f3ac75e4.png][]
> 
> image.png

>  
> 
>  
> 
> 选择安装组件，（最小化安装HDFS+YARN+MAPREDUCE2+Ambari Metrics+SmartSense+ZooKeeper+Hbase）不必要的组件可以暂时不安装节省安装时间，后续可以再添加安装组件
> 
> ![14788851-c6502ee15880113a.png][]
> 
> image.png
> 
>  
> 
> ![14788851-42b561a11604e549.png][]
> 
> image.png
> 
>  
> 
>  
> 
> 实际部署时需按规划设计进行分配（注意：Hbase HA 的话在Hbase Master 点击后面的小绿色+号，添加standby master）：
> 
> ![14788851-d1b8343393ccd3c2.png][]
> 
> image.png
> 
>   
> 工作节点角色分配(生产环境全勾了)
> 
> ![14788851-2f13405acf5ce462.png][]
> 
> image.png
> 
>   
> 组件配置信息修改  
> 通常数据目录修改到/data/目录下，有红色信息提示的组件表示要输入相应的账号密码。以下示例，可根据自己的实际情况配置。
> 
>  
> 
> HDFS
> 
> ![14788851-ea93e394b866a268.png][]
> 
> image.png
> 
>  
> 
> ![14788851-a31fd1e7653cd863.png][]
> 
> image.png
> 
>   
> HIVE,若数据库端口修改按实际填写
> 
> ![14788851-5fb664a68f0b358c.png][]
> 
> image.png
> 
>   
> Oozie
> 
> ![14788851-ed7399362578a50c.png][]
> 
> image.png
> 
>   
> Zookeeper
> 
> ![14788851-dab75015068d127f.png][]
> 
> image.png
> 
>  
> 
> ![14788851-23ef9d3f9fbd2e48.png][]
> 
> image.png
> 
>  
> 
> ![14788851-ded441f657ca8309.png][]
> 
> image.png
> 
>  
> 
> ![14788851-7345766924e0c76a.png][]
> 
> image.png

暂时修改了以下属性，具体配置信息可根据实际情况后续相应修改

<table> 
 <thead> 
  <tr> 
   <th>端口属性</th> 
   <th>修改值</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>dfs.namenode.http-address</td> 
   <td>server1.hadoop:5070 （def:50070）</td> 
  </tr> 
  <tr> 
   <td>yarn.resourcemanager.webapp.address</td> 
   <td>server2.hadoop:8888 （def:8088）</td> 
  </tr> 
  <tr> 
   <td>yarn.resourcemanager.webapp.https.address</td> 
   <td>server2.hadoop:8890(def:8090)</td> 
  </tr> 
  <tr> 
   <td>mapreduce.jobhistory.webapp.address</td> 
   <td>server2.hadoop:18888 (def:19888)</td> 
  </tr> 
 </tbody> 
</table>

<table> 
 <thead> 
  <tr> 
   <th>属性</th> 
   <th>修改值</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td><strong>HDFS</strong></td> 
   <td>&nbsp;</td> 
  </tr> 
  <tr> 
   <td>NameNode</td> 
   <td>/data/hadoop/hdfs/namenode</td> 
  </tr> 
  <tr> 
   <td>DataNode</td> 
   <td>/data/hadoop/hdfs/data</td> 
  </tr> 
  <tr> 
   <td>SecondaryNameNode Checkpoint directories</td> 
   <td>/data/hadoop/hdfs/namesecondary</td> 
  </tr> 
  <tr> 
   <td>Hadoop PID Dir Prefix</td> 
   <td>/data/var/run/hadoop</td> 
  </tr> 
  <tr> 
   <td>Hadoop Log Dir Prefix</td> 
   <td>/data/var/log/hadoop</td> 
  </tr> 
  <tr> 
   <td>dfs.journalnode.edits.dir</td> 
   <td>/data/hadoop/hdfs/journalnode</td> 
  </tr> 
  <tr> 
   <td><strong>Yarn</strong></td> 
   <td>&nbsp;</td> 
  </tr> 
  <tr> 
   <td>yarn.nodemanager.local-dirs</td> 
   <td>/data/hadoop/yarn/local</td> 
  </tr> 
  <tr> 
   <td>yarn.nodemanager.log-dirs</td> 
   <td>/data/hadoop/yarn/log</td> 
  </tr> 
  <tr> 
   <td>yarn.timeline-service.leveldb-state-store.path</td> 
   <td>/data/hadoop/yarn/timeline</td> 
  </tr> 
  <tr> 
   <td>yarn.timeline-service.leveldb-timeline-store.path</td> 
   <td>/data/hadoop/yarn/timeline</td> 
  </tr> 
  <tr> 
   <td>YARN Log Dir Prefix</td> 
   <td>/data/var/log/hadoop-yarn</td> 
  </tr> 
  <tr> 
   <td>YARN PID Dir Prefix</td> 
   <td>/data/var/run/hadoop-yarn</td> 
  </tr> 
  <tr> 
   <td><strong>Mapreduce</strong></td> 
   <td>&nbsp;</td> 
  </tr> 
  <tr> 
   <td>Mapreduce Log Dir Prefix</td> 
   <td>/data/var/log/hadoop-mapreduce</td> 
  </tr> 
  <tr> 
   <td>Mapreduce PID Dir Prefix</td> 
   <td>/data/var/run/hadoop-mapreduce</td> 
  </tr> 
  <tr> 
   <td>mapreduce.jobhistory.recovery.store.leveldb.path</td> 
   <td>/data/hadoop/mapreduce/jhs</td> 
  </tr> 
  <tr> 
   <td><strong>Hive</strong></td> 
   <td>&nbsp;</td> 
  </tr> 
  <tr> 
   <td>Hive Log Dir</td> 
   <td>/data/var/log/hive</td> 
  </tr> 
  <tr> 
   <td>Hive PID Dir</td> 
   <td>/data/var/run/hive</td> 
  </tr> 
  <tr> 
   <td><strong>HBase</strong></td> 
   <td>&nbsp;</td> 
  </tr> 
  <tr> 
   <td>HBase Log Dir Prefix</td> 
   <td>/data/var/log/hbase</td> 
  </tr> 
  <tr> 
   <td>HBase PID Dir</td> 
   <td>/data/var/run/hbase</td> 
  </tr> 
  <tr> 
   <td><strong>Oozie</strong></td> 
   <td>&nbsp;</td> 
  </tr> 
  <tr> 
   <td>Oozie Data Dir</td> 
   <td>/data/hadoop/oozie/data</td> 
  </tr> 
  <tr> 
   <td>Oozie Log Dir</td> 
   <td>/data/var/log/oozie</td> 
  </tr> 
  <tr> 
   <td>Oozie PID Dir</td> 
   <td>/data/var/run/oozie</td> 
  </tr> 
  <tr> 
   <td><strong>zookeeper</strong></td> 
   <td>&nbsp;</td> 
  </tr> 
  <tr> 
   <td>ZooKeeper directory</td> 
   <td>/data/hadoop/zookeeper</td> 
  </tr> 
  <tr> 
   <td>ZooKeeper Log Dir</td> 
   <td>/data/var/log/zookeeper</td> 
  </tr> 
  <tr> 
   <td>ZooKeeper PID Dir</td> 
   <td>/data/var/run/zookeeper</td> 
  </tr> 
  <tr> 
   <td><strong>ambari-infra</strong></td> 
   <td>&nbsp;</td> 
  </tr> 
  <tr> 
   <td>Metrics Collector log dir</td> 
   <td>/data/var/log/ambari-metrics-collector</td> 
  </tr> 
  <tr> 
   <td>Metrics Collector pid dir</td> 
   <td>/data/var/run/ambari-metrics-collector</td> 
  </tr> 
  <tr> 
   <td>Metrics Monitor log dir</td> 
   <td>/data/var/log/ambari-metrics-monitor</td> 
  </tr> 
  <tr> 
   <td>Metrics Monitor pid dir</td> 
   <td>/data/var/run/ambari-metrics-monitor</td> 
  </tr> 
  <tr> 
   <td>Aggregator checkpoint directory</td> 
   <td>/data/var/lib/ambari-metrics-collector/checkpoint</td> 
  </tr> 
  <tr> 
   <td>Metrics Grafana data dir</td> 
   <td>/data/var/lib/ambari-metrics-grafana</td> 
  </tr> 
  <tr> 
   <td>Metrics Grafana log dir</td> 
   <td>/data/var/log/ambari-metrics-grafana</td> 
  </tr> 
  <tr> 
   <td>Metrics Grafana pid dir</td> 
   <td>/data/var/run/ambari-metrics-grafana</td> 
  </tr> 
  <tr> 
   <td>hbase_log_dir</td> 
   <td>/data/var/log/ambari-metrics-collector</td> 
  </tr> 
  <tr> 
   <td>hbase_pid_dir</td> 
   <td>/data/var/run/ambari-metrics-collector/</td> 
  </tr> 
  <tr> 
   <td>hbase.tmp.dir</td> 
   <td>/data/var/lib/ambari-metrics-collector/hbase-tmp</td> 
  </tr> 
  <tr> 
   <td>&nbsp;</td> 
   <td>&nbsp;</td> 
  </tr> 
  <tr> 
   <td><strong>ambari-infra</strong></td> 
   <td>&nbsp;</td> 
  </tr> 
  <tr> 
   <td>Infra Solr Client log dir</td> 
   <td>/data/var/log/ambari-infra-solr-client</td> 
  </tr> 
  <tr> 
   <td>Infra Solr log dir</td> 
   <td>/data/var/log/ambari-infra-solr</td> 
  </tr> 
  <tr> 
   <td>Infra Solr pid dir</td> 
   <td>/data/var/run/ambari-infra-solr</td> 
  </tr> 
  <tr> 
   <td><strong>spark</strong></td> 
   <td>&nbsp;</td> 
  </tr> 
  <tr> 
   <td>livy2_log_dir</td> 
   <td>/data/var/log/livy2</td> 
  </tr> 
  <tr> 
   <td>livy2_pid_dir</td> 
   <td>/data/var/run/livy2</td> 
  </tr> 
  <tr> 
   <td>spark_log_dir</td> 
   <td>/data/var/log/spark2</td> 
  </tr> 
  <tr> 
   <td>spark_pid_dir</td> 
   <td>/data/var/run/spark2</td> 
  </tr> 
 </tbody> 
</table>

>  
> 
>  
> 
> 等待安装完成
> 
> ![14788851-db0b65a325a24e25.png][]
> 
> image.png
> 
>  
> 
>  
> 
> 直到所有节点成功安装完成才能进行下一步操作
> 
> ![14788851-1a4af7591ac2684e.png][]
> 
> image.png

最终结果界面类似如下：

![14788851-7e426022f28bee53.png][]

image.png

**安装完成！**

# 三、后续操作 #

操作前最好先将集群打个快照备份

### 1、HDFS启用HA(高可用) ###

参考[http://www.louisvv.com/archives/1490.html][http_www.louisvv.com_archives_1490.html]

> **step1：**关闭hbase、hive相关服务
> 
> ![14788851-fd808d62609f68f6.png][]
> 
> image.png
> 
>   
> **step2:**在HDFS选择Enable NameNode HA
> 
> ![14788851-7594c85a3bfbc74e.png][]
> 
> image.png
> 
>   
> **step3:**输入namenode ha serverid
> 
> ![14788851-3ab4867f8d01f9c3.png][]
> 
> image.png
> 
>   
> **step4:**默认，进入下一步
> 
> ![14788851-a0a7225f722573ce.png][]
> 
> image.png
> 
>   
> **step5:**预览，直接进入下一步
> 
> ![14788851-302a9814487016f4.png][]
> 
> image.png
> 
>   
> **step6:**创建checkpoint，根据提示执行下列命令
> 
> ![14788851-4bb7dafd98a232d7.png][]
> 
> image.png
> 
>   
> 根据提示在server1执行下列两条命令
> 
> ![14788851-bc131acf85539fe0.png][]
> 
> image.png
> 
>   
> 命令执行完成方可进入下一步
> 
> ![14788851-f3f2473859896bf1.png][]
> 
> image.png
> 
>   
> **step7:**等待配置进程完成
> 
> ![14788851-1b974da6f29ccb47.png][]
> 
> image.png
> 
>   
> **step8:**Journalnode初始化
> 
> ![14788851-e6ee70e03939dcfa.png][]
> 
> image.png
> 
>   
> **需要在原NameNode节点执行下列命令**
> 
>

sudo su hdfs -l -c 'hdfs namenode -initializeSharedEdits'

>  
> 
> ![14788851-a5b0667e6d53bd34.png][]
> 
> image.png
> 
>   
> **step9:** 启动组件，进入下一步
> 
> ![14788851-950f0720ab45150a.png][]
> 
> image.png
> 
>   
> **step10:**初始化元数据，
> 
>

sudo su hdfs -l -c 'hdfs zkfc -formatZK'

>  
> 
> ![14788851-79b905212c14d592.png][]
> 
> image.png
> 
>   
> **注意**在 **新添加的NameNode节点**上操作
> 
>

sudo su hdfs -l -c 'hdfs namenode -bootstrapStandby'

>  
> 
> ![14788851-e1273fb94b1e7ab5.png][]
> 
> image.png
> 
>  
> 
> ![14788851-9ec96a9c23a63069.png][]
> 
> image.png
> 
>   
> **step11:**等待所有服务重启，完成
> 
> ![14788851-6daae242c9def7bb.png][]
> 
> image.png
> 
>  
> 
> ![14788851-d51071f720d81856.png][]
> 
> image.png

[https_blog.csdn.net_weixin_33923762_article_details_90932169]: https://blog.csdn.net/weixin_33923762/article/details/90932169
[https_blog.csdn.net_weixin_37600848_article_details_83418515]: https://blog.csdn.net/weixin_37600848/article/details/83418515
[https_blog.csdn.net_wuliusir_article_details_50754859]: https://blog.csdn.net/wuliusir/article/details/50754859
[https_blog.51cto.com_784687488_2332072_source_dra]: https://blog.51cto.com/784687488/2332072?source=dra
[https_blog.csdn.net_yanghua_kobe_article_details_53456674]: https://blog.csdn.net/yanghua_kobe/article/details/53456674
[https_blog.csdn.net_chengyuqiang_article_details_60963480]: https://blog.csdn.net/chengyuqiang/article/details/60963480
[ambari rest api]: https://www.cnblogs.com/itboys/p/7004148.html
[https_blog.csdn.net_qq_27710549_article_details_80500857]: https://blog.csdn.net/qq_27710549/article/details/80500857
[HUE_hue.ini _zookeeper_HA]: https://www.cnblogs.com/zlslch/p/6817538.html
[https_blog.csdn.net_yuchuanchen_article_details_88406438]: https://blog.csdn.net/yuchuanchen/article/details/88406438
[https_blog.csdn.net_qq_32649581_article_details_90899363]: https://blog.csdn.net/qq_32649581/article/details/90899363
[https_blog.csdn.net_kk25114_article_details_88639383]: https://blog.csdn.net/kk25114/article/details/88639383
[https_blog.csdn.net_weixin_40626699_article_details_89139591]: https://blog.csdn.net/weixin_40626699/article/details/89139591
[Ambari_3_Ambari_Airflow]: https://www.cnblogs.com/barneywill/p/10284804.html
[https_blog.csdn.net_balabalayi_article_details_64904822]: https://blog.csdn.net/balabalayi/article/details/64904822
[https_blog.csdn.net_aA518189_article_details_88952910]: https://blog.csdn.net/aA518189/article/details/88952910
[https_blog.csdn.net_qq_38799155_article_details_80808818]: https://blog.csdn.net/qq_38799155/article/details/80808818
[https_blog.csdn.net_m0_37614660_article_details_88987862]: https://blog.csdn.net/m0_37614660/article/details/88987862
[https_blog.csdn.net_u011596455_article_details_53115410]: https://blog.csdn.net/u011596455/article/details/53115410
[https_my.oschina.net_qiangzigege_blog_534176]: https://my.oschina.net/qiangzigege/blog/534176
[https_www.cnblogs.com_zlslch_category_972313.html]: https://www.cnblogs.com/zlslch/category/972313.html
[https_blog.csdn.net_u010199356_article_details_87538403]: https://blog.csdn.net/u010199356/article/details/87538403
[https_blog.csdn.net_weixin_34242819_article_details_88281740]: https://blog.csdn.net/weixin_34242819/article/details/88281740
[14788851-6a262f27bc06d496.png]: /images/20211210/39764dd6fedd440d9be7189d48f978c4.png
[14788851-fa6f6a6afd7e8a76.png]: /images/20211210/4ebe82a72a4a410d9253cc6145e9fbfa.png
[https_www.oracle.com_technetwork_cn_java_javase_downloads_jdk8-downloads-2133151-zhs.html]: https://links.jianshu.com/go?to=https%3A%2F%2Fwww.oracle.com%2Ftechnetwork%2Fcn%2Fjava%2Fjavase%2Fdownloads%2Fjdk8-downloads-2133151-zhs.html
[https_docs.hortonworks.com_HDPDocuments_Ambari-2.6.2.0_bk_ambari-installation_content_ch_obtaining-public-repos.html]: https://links.jianshu.com/go?to=https%3A%2F%2Fdocs.hortonworks.com%2FHDPDocuments%2FAmbari-2.6.2.0%2Fbk_ambari-installation%2Fcontent%2Fch_obtaining-public-repos.html
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