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MOMO User Analysis

1. 介绍

通过3台CentOS 7 虚拟机模拟Hadoop环境，部署Hadoop，Hive。其中Hive通过MySQL作为Metastore的后端数据库。通过DataGrip的远程连接的方式对进行数据的ETL，最后使用TabLeau对数据进行简单的可视化分析。

Hadoop and Hive note

Tableau Dash Board：

image-20230322105430291

附录A. Hadoop的部署

1. 配置IP地址与网关&导入虚拟机

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  • 修改VMware的IP与网关

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  • 修改Windows网络适配器的IP与网关

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  • 在VMware虚拟机配置局域网，导入3台CentOS虚拟机，虚线部分为虚拟机部分

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  • Windows设置host映射：C:\Windows\System32\drivers\etc

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  • Linux服务器设置host映射 vim /etc/hosts

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2. XShell 连接虚拟机&配置基本环境

  • Xshell新建会话

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  • SSH免密登录（只需配置node1到node1、node2、node3）

    #node1生成公钥私钥 (一路回车)
ssh-keygen

#node1配置免密登录到node1 node2 node3
ssh-copy-id node1
ssh-copy-id node2
ssh-copy-id node3

  • 集群同步时间 ntpdate [ntp5.aliyun.com](http://ntp5.aliyun.com/)

  • 关闭服务器防火墙：

    firewall-cmd --state	#查看防火墙状态
systemctl stop firewalld.service  #停止firewalld服务
systemctl disable firewalld.service  #开机禁用firewalld服务

  • 创建文件夹export/data, export/sever, export/software

  • 安装配置JDK 1.8 /export/server

    #解压安装包
tar zxvf jdk-8u65-linux-x64.tar.gz

#配置环境变量
vim /etc/profile

export JAVA_HOME=/export/server/jdk1.8.0_241
export PATH=$PATH:$JAVA_HOME/bin
export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar

source /etc/profile

#验证是否安装成功
java -version

  • 上传Hadoop安装包到node1 /export/server

    hadoop-3.3.0-Centos7-64-with-snappy.tar.gz

tar zxvf hadoop-3.3.0-Centos7-64-with-snappy.tar.gz

  • 修改配置文件(配置文件路径 hadoop-3.3.0/etc/hadoop)

    • hadoop-env.sh

      #文件最后添加
export JAVA_HOME=/export/server/jdk1.8.0_241

export HDFS_NAMENODE_USER=root
export HDFS_DATANODE_USER=root
export HDFS_SECONDARYNAMENODE_USER=root
export YARN_RESOURCEMANAGER_USER=root
export YARN_NODEMANAGER_USER=root

    • core-site.xml

      <!-- 设置默认使用的文件系统 Hadoop支持file、HDFS、GFS、ali|Amazon云等文件系统 -->
<property>
    <name>fs.defaultFS</name>
    <value>hdfs://node1:8020</value>
</property>

<!-- 设置Hadoop本地保存数据路径 -->
<property>
    <name>hadoop.tmp.dir</name>
    <value>/export/data/hadoop-3.3.0</value>
</property>

<!-- 设置HDFS web UI用户身份 -->
<property>
    <name>hadoop.http.staticuser.user</name>
    <value>root</value>
</property>

<!-- 整合hive 用户代理设置 -->
<property>
    <name>hadoop.proxyuser.root.hosts</name>
    <value>*</value>
</property>

<property>
    <name>hadoop.proxyuser.root.groups</name>
    <value>*</value>
</property>

<!-- 文件系统垃圾桶保存时间 -->
<property>
    <name>fs.trash.interval</name>
    <value>1440</value>
</property>

    • hdfs-site.xml

      <!-- 设置SNN进程运行机器位置信息 -->
<property>
    <name>dfs.namenode.secondary.http-address</name>
    <value>node2:9868</value>
</property>

    • mapred-site.xml

      <!-- 设置MR程序默认运行模式： yarn集群模式 local本地模式 -->
<property>
  <name>mapreduce.framework.name</name>
  <value>yarn</value>
</property>

<!-- MR程序历史服务地址 -->
<property>
  <name>mapreduce.jobhistory.address</name>
  <value>node1:10020</value>
</property>

<!-- MR程序历史服务器web端地址 -->
<property>
  <name>mapreduce.jobhistory.webapp.address</name>
  <value>node1:19888</value>
</property>

<property>
  <name>yarn.app.mapreduce.am.env</name>
  <value>HADOOP_MAPRED_HOME=${HADOOP_HOME}</value>
</property>

<property>
  <name>mapreduce.map.env</name>
  <value>HADOOP_MAPRED_HOME=${HADOOP_HOME}</value>
</property>

<property>
  <name>mapreduce.reduce.env</name>
  <value>HADOOP_MAPRED_HOME=${HADOOP_HOME}</value>
</property>

    • yarn-site.xml

      <!-- 设置YARN集群主角色运行机器位置 -->
<property>
	<name>yarn.resourcemanager.hostname</name>
	<value>node1</value>
</property>

<property>
    <name>yarn.nodemanager.aux-services</name>
    <value>mapreduce_shuffle</value>
</property>

<!-- 是否将对容器实施物理内存限制 -->
<property>
    <name>yarn.nodemanager.pmem-check-enabled</name>
    <value>false</value>
</property>

<!-- 是否将对容器实施虚拟内存限制。 -->
<property>
    <name>yarn.nodemanager.vmem-check-enabled</name>
    <value>false</value>
</property>

<!-- 开启日志聚集 -->
<property>
  <name>yarn.log-aggregation-enable</name>
  <value>true</value>
</property>

<!-- 设置yarn历史服务器地址 -->
<property>
    <name>yarn.log.server.url</name>
    <value><http://node1:19888/jobhistory/logs></value>
</property>

<!-- 历史日志保存的时间 7天 -->
<property>
  <name>yarn.log-aggregation.retain-seconds</name>
  <value>604800</value>
</property>

    • workers

      node1.itcast.cn
node2.itcast.cn
node3.itcast.cn

  • 分发同步hadoop安装包

    cd /export/server

scp -r hadoop-3.3.0 root@node2:$PWD
scp -r hadoop-3.3.0 root@node3:$PWD

  • 将hadoop添加到环境变量（3台机器）

    vim /etc/profile

export HADOOP_HOME=/export/server/hadoop-3.3.0
export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin

source /etc/profile

#scp给其他两台机器

  • Hadoop集群启动

    • （==首次启动==）格式化namenode

      hdfs namenode -format

    • 脚本一键启动

      # 单独启动HDFS集群
start-dfs.sh
# 单独启动YARN集群
start-yarn.sh
# 启动Hadoop集群（包含上面两个）
start-all.sh

    • Web UI页面

附件B. Hive部署

Mysql安装

  • 卸载Centos7自带的mariadb

    [root@node3 ~]# rpm -qa|grep mariadb
mariadb-libs-5.5.64-1.el7.x86_64

[root@node3 ~]# rpm -e mariadb-libs-5.5.64-1.el7.x86_64 --nodeps
[root@node3 ~]# rpm -qa|grep mariadb
[root@node3 ~]#

  • 安装mysql

    mkdir /export/software/mysql

#上传mysql-5.7.29-1.el7.x86_64.rpm-bundle.tar 到上述文件夹下  解压
tar xvf mysql-5.7.29-1.el7.x86_64.rpm-bundle.tar

#执行安装
yum -y install libaio

[root@node3 mysql]# rpm -ivh mysql-community-common-5.7.29-1.el7.x86_64.rpm mysql-community-libs-5.7.29-1.el7.x86_64.rpm mysql-community-client-5.7.29-1.el7.x86_64.rpm mysql-community-server-5.7.29-1.el7.x86_64.rpm

warning: mysql-community-common-5.7.29-1.el7.x86_64.rpm: Header V3 DSA/SHA1 Signature, key ID 5072e1f5: NOKEY
Preparing...                          ################################# [100%]
Updating / installing...
   1:mysql-community-common-5.7.29-1.e################################# [ 25%]
   2:mysql-community-libs-5.7.29-1.el7################################# [ 50%]
   3:mysql-community-client-5.7.29-1.e################################# [ 75%]
   4:mysql-community-server-5.7.29-1.e################                  ( 49%)

  • mysql初始化设置

    #初始化
mysqld --initialize

#更改所属组
chown mysql:mysql /var/lib/mysql -R

#启动mysql
systemctl start mysqld.service

#查看生成的临时root密码
cat  /var/log/mysqld.log

[Note] A temporary password is generated for root@localhost: o+TU+KDOm004

  • 修改root密码 授权远程访问 设置开机自启动

    [root@node2 ~]# mysql -u root -p
Enter password:     #这里输入在日志中生成的临时密码
Welcome to the MySQL monitor.  Commands end with ; or \g.
Your MySQL connection id is 3
Server version: 5.7.29

Copyright (c) 2000, 2020, Oracle and/or its affiliates. All rights reserved.

Oracle is a registered trademark of Oracle Corporation and/or its
affiliates. Other names may be trademarks of their respective
owners.

Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.

mysql>

#更新root密码  设置为hadoop
mysql> alter user user() identified by "hadoop";
Query OK, 0 rows affected (0.00 sec)

#授权
mysql> use mysql;

mysql> GRANT ALL PRIVILEGES ON *.* TO 'root'@'%' IDENTIFIED BY 'hadoop' WITH GRANT OPTION;

mysql> FLUSH PRIVILEGES;

#mysql的启动和关闭 状态查看 （这几个命令必须记住）
systemctl stop mysqld
systemctl status mysqld
systemctl start mysqld

#建议设置为开机自启动服务
[root@node2 ~]# systemctl enable  mysqld
Created symlink from /etc/systemd/system/multi-user.target.wants/mysqld.service to /usr/lib/systemd/system/mysqld.service.

#查看是否已经设置自启动成功
[root@node2 ~]# systemctl list-unit-files | grep mysqld
mysqld.service                                enabled

  • Centos7 干净卸载mysql 5.7

    #关闭mysql服务
systemctl stop mysqld.service

#查找安装mysql的rpm包
[root@node3 ~]# rpm -qa | grep -i mysql
mysql-community-libs-5.7.29-1.el7.x86_64
mysql-community-common-5.7.29-1.el7.x86_64
mysql-community-client-5.7.29-1.el7.x86_64
mysql-community-server-5.7.29-1.el7.x86_64

#卸载
[root@node3 ~]# yum remove mysql-community-libs-5.7.29-1.el7.x86_64 mysql-community-common-5.7.29-1.el7.x86_64 mysql-community-client-5.7.29-1.el7.x86_64 mysql-community-server-5.7.29-1.el7.x86_64

#查看是否卸载干净
rpm -qa | grep -i mysql

#查找mysql相关目录 删除
[root@node1 ~]# find / -name mysql
/var/lib/mysql
/var/lib/mysql/mysql
/usr/share/mysql

[root@node1 ~]# rm -rf /var/lib/mysql
[root@node1 ~]# rm -rf /var/lib/mysql/mysql
[root@node1 ~]# rm -rf /usr/share/mysql

#删除默认配置 日志
rm -rf /etc/my.cnf
rm -rf /var/log/mysqld.log

Hive的安装（安装一台）

  • 上传安装包 解压

    tar zxvf apache-hive-3.1.2-bin.tar.gz

  • 解决Hive与Hadoop之间guava版本差异

    cd /export/server/apache-hive-3.1.2-bin/
rm -rf lib/guava-19.0.jar
cp /export/server/hadoop-3.3.0/share/hadoop/common/lib/guava-27.0-jre.jar ./lib/

  • 修改配置文件

    • hive-env.sh

      cd /export/server/apache-hive-3.1.2-bin/conf
mv hive-env.sh.template hive-env.sh

vim hive-env.sh
export HADOOP_HOME=/export/server/hadoop-3.3.0
export HIVE_CONF_DIR=/export/server/apache-hive-3.1.2-bin/conf
export HIVE_AUX_JARS_PATH=/export/server/apache-hive-3.1.2-bin/lib

    • hive-site.xml

      vim hive-site.xml

      <configuration>
<!-- 存储元数据mysql相关配置 -->
<property>
    <name>javax.jdo.option.ConnectionURL</name>
    <value>jdbc:mysql://node1:3306/hive3?createDatabaseIfNotExist=true&amp;useSSL=false&amp;useUnicode=true&amp;characterEncoding=UTF-8</value>
</property>

<property>
    <name>javax.jdo.option.ConnectionDriverName</name>
    <value>com.mysql.jdbc.Driver</value>
</property>

<property>
    <name>javax.jdo.option.ConnectionUserName</name>
    <value>root</value>
</property>

<property>
    <name>javax.jdo.option.ConnectionPassword</name>
    <value>hadoop</value>
</property>

<!-- H2S运行绑定host -->
<property>
    <name>hive.server2.thrift.bind.host</name>
    <value>node1</value>
</property>

<!-- 远程模式部署metastore metastore地址 -->
<property>
    <name>hive.metastore.uris</name>
    <value>thrift://node1:9083</value>
</property>

<!-- 关闭元数据存储授权  -->
<property>
    <name>hive.metastore.event.db.notification.api.auth</name>
    <value>false</value>
</property>
</configuration>

  • 上传mysql jdbc驱动到hive安装包lib下

    mysql-connector-java-5.1.32.jar

  • 初始化元数据

    cd /export/server/apache-hive-3.1.2-bin/

bin/schematool -initSchema -dbType mysql -verbos
#初始化成功会在mysql中创建74张表

  • 在hdfs创建hive存储目录（如存在则不用操作）

    hadoop fs -mkdir /tmp
hadoop fs -mkdir -p /user/hive/warehouse
hadoop fs -chmod g+w /tmp
hadoop fs -chmod g+w /user/hive/warehouse

  • ==启动hive==

  • 1、启动metastore服务

    #前台启动  关闭ctrl+c
/export/server/apache-hive-3.1.2-bin/bin/hive --service metastore

#前台启动开启debug日志
/export/server/apache-hive-3.1.2-bin/bin/hive --service metastore --hiveconf hive.root.logger=DEBUG,console

#后台启动 进程挂起  关闭使用jps+ kill -9
nohup /export/server/apache-hive-3.1.2-bin/bin/hive --service metastore &

  • 2、启动hiveserver2服务

      nohup /export/server/apache-hive-3.1.2-bin/bin/hive --service hiveserver2 &

  #注意 启动hiveserver2需要一定的时间  不要启动之后立即beeline连接 可能连接不上

  • 3、beeline客户端连接

    /export/server/apache-hive-3.1.2-bin/bin/beeline

beeline> ! connect jdbc:hive2://node1:10000
beeline> root
beeline> 直接回车