大数据开发相关组件部署及数据抽取

快来打我* 2024-04-28 07:44 7阅读 0赞

##  ##

> ![16df0128c2fc4761be10983e3e8c7ec5.png][]
> 
> 大抵是不用进厂了罢。

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![837b11390fd2464cb748a84aef98ffc4.png][]

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**目录**

一、大数据集群组件部署

1. 基础环境配置

2. hadoop集群部署

2.1 jdk的部署和安装

2.2 Hadoop集群配置

3.hive组件部署

3.1 MYSql数据库部署

3.2 Hive部署

4. spark组件部署

5. Flink组件部署

6. Flume组件部署

7. Zookeeper组件部署

8. Kafka组件部署

9. MaxWell组件部署

10. Redis组件部署

11. Hbase组件部署

12. Clickhouse组件部署

二、数据抽取

2.1 实时数据抽取

2.1.1 Maxwell数据抽取

2.1.2 端口日志数据抽取

2. 离线数据抽取

实时数据分析

4.1 Linux端环境准备

4.2 Windows端环境准备

4.3 实时数据分析代码开发

4.4 统计SKU商品的总额,将值存入Redis

🥇Summary

获取源码？私信？关注？点赞？收藏？WeChat?

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## 一、大数据集群组件部署 ##

### 1. 基础环境配置 ###

<table> 
 <thead> 
  <tr> 
   <th>主机名</th> 
   <th>IP地址</th> 
   <th>账号</th> 
   <th>密码</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>master</td> 
   <td>192.168.1.100</td> 
   <td>root</td> 
   <td>password</td> 
  </tr> 
  <tr> 
   <td>slave1</td> 
   <td>192.168.1.101</td> 
   <td>root</td> 
   <td>password</td> 
  </tr> 
  <tr> 
   <td>slave2</td> 
   <td>192.168.1.102</td> 
   <td>root</td> 
   <td>password</td> 
  </tr> 
 </tbody> 
</table>

修改三个节点的主机名：

[root@master ~]# hostnamectl set-hostname master

slave1:

[root@localhost ~]# hostnamectl set-hostname slave1
    [root@localhost ~]# bash
    [root@slave1 ~]#

slave2:

[root@localhost ~]# hostnamectl set-hostname slave2
    [root@localhost ~]# bash
    [root@slave2 ~]#

设置固定ip:

master:

命令：

[root@master ~]# vi /etc/sysconfig/network-scripts/ifcfg-ens33

文件内容：

TYPE=Ethernet
    PROXY_METHOD=none
    BROWSER_ONLY=no
    BOOTPROTO=static
    DEFROUTE=yes
    IPV4_FAILURE_FATAL=no
    IPV6INIT=yes
    IPV6_AUTOCONF=yes
    IPV6_DEFROUTE=yes
    IPV6_FAILURE_FATAL=no
    IPV6_ADDR_GEN_MODE=stable-privacy
    NAME=ens35
    DEVICE=ens35
    ONBOOT=yes
    IPADDR=192.168.1.100
    NETMASK=255.255.255.0
    GATEWAY=192.168.1.254
    
    DNS1=114.114.114.114
    DNS2=8.8.8.8

重启网卡：

[root@master ~]# systemctl restart network

查看ip:

[root@master ~]# ip a
    1: lo: <LOOPBACK,UP,LOWER_UP> mtu 65536 qdisc noqueue state UNKNOWN qlen 1
        link/loopback 00:00:00:00:00:00 brd 00:00:00:00:00:00
        inet 127.0.0.1/8 scope host lo
           valid_lft forever preferred_lft forever
        inet6 ::1/128 scope host 
           valid_lft forever preferred_lft forever
    2: ens35: <BROADCAST,MULTICAST,UP,LOWER_UP> mtu 1500 qdisc pfifo_fast state UP qlen 1000
        link/ether 00:0c:29:69:e9:e8 brd ff:ff:ff:ff:ff:ff
        inet 192.168.1.100/24 brd 192.168.1.255 scope global dynamic ens35
           valid_lft 1111sec preferred_lft 1111sec
        inet6 fe80::2859:3941:9736:7030/64 scope link 
           valid_lft forever preferred_lft forever
    3: virbr0: <NO-CARRIER,BROADCAST,MULTICAST,UP> mtu 1500 qdisc noqueue state DOWN qlen 1000
        link/ether 52:54:00:00:28:5e brd ff:ff:ff:ff:ff:ff
        inet 192.168.122.1/24 brd 192.168.122.255 scope global virbr0
           valid_lft forever preferred_lft forever
    4: virbr0-nic: <BROADCAST,MULTICAST> mtu 1500 qdisc pfifo_fast master virbr0 state DOWN qlen 1000
        link/ether 52:54:00:00:28:5e brd ff:ff:ff:ff:ff:ff
    [root@master ~]#

slave1:

命令：

[root@master ~]# vi /etc/sysconfig/network-scripts/ifcfg-ens33

文件内容：

TYPE=Ethernet
    PROXY_METHOD=none
    BROWSER_ONLY=no
    BOOTPROTO=static
    DEFROUTE=yes
    IPV4_FAILURE_FATAL=no
    IPV6INIT=yes
    IPV6_AUTOCONF=yes
    IPV6_DEFROUTE=yes
    IPV6_FAILURE_FATAL=no
    IPV6_ADDR_GEN_MODE=stable-privacy
    NAME=ens35
    DEVICE=ens35
    ONBOOT=yes
    IPADDR=192.168.1.101
    NETMASK=255.255.255.0
    GATEWAY=192.168.1.254
    DNS1=114.114.114.114
    DNS2=8.8.8.8

重启网卡：

[root@slave1 ~]# systemctl restart network

查看ip:

[root@slave1 ~]# ip a
    1: lo: <LOOPBACK,UP,LOWER_UP> mtu 65536 qdisc noqueue state UNKNOWN qlen 1
        link/loopback 00:00:00:00:00:00 brd 00:00:00:00:00:00
        inet 127.0.0.1/8 scope host lo
           valid_lft forever preferred_lft forever
        inet6 ::1/128 scope host 
           valid_lft forever preferred_lft forever
    2: ens35: <BROADCAST,MULTICAST,UP,LOWER_UP> mtu 1500 qdisc pfifo_fast state UP qlen 1000
        link/ether 00:0c:29:75:1f:92 brd ff:ff:ff:ff:ff:ff
        inet 192.168.1.101/24 brd 192.168.1.255 scope global dynamic ens35
           valid_lft 1507sec preferred_lft 1507sec
        inet6 fe80::f66b:758e:9c24:88b9/64 scope link 
           valid_lft forever preferred_lft forever
    3: virbr0: <NO-CARRIER,BROADCAST,MULTICAST,UP> mtu 1500 qdisc noqueue state DOWN qlen 1000
        link/ether 52:54:00:4b:05:cc brd ff:ff:ff:ff:ff:ff
        inet 192.168.122.1/24 brd 192.168.122.255 scope global virbr0
           valid_lft forever preferred_lft forever
    4: virbr0-nic: <BROADCAST,MULTICAST> mtu 1500 qdisc pfifo_fast master virbr0 state DOWN qlen 1000
        link/ether 52:54:00:4b:05:cc brd ff:ff:ff:ff:ff:ff
    [root@slave1 ~]#

slave2:

命令：

[root@master ~]# vi /etc/sysconfig/network-scripts/ifcfg-ens160

文件内容：

TYPE=Ethernet
    PROXY_METHOD=none
    BROWSER_ONLY=no
    BOOTPROTO=static
    DEFROUTE=yes
    IPV4_FAILURE_FATAL=no
    IPV6INIT=yes
    IPV6_AUTOCONF=yes
    IPV6_DEFROUTE=yes
    IPV6_FAILURE_FATAL=no
    IPV6_ADDR_GEN_MODE=stable-privacy
    NAME=ens35
    DEVICE=ens35
    ONBOOT=yes
    IPADDR=192.168.1.102
    NETMASK=255.255.255.0
    GATEWAY=192.168.1.254
    
    DNS1=114.114.114.114
    DNS2=8.8.8.8

重启网卡：

root@slave2 ~]# systemctl restart network

查看ip:

[root@slave2 ~]# ip a
    1: lo: <LOOPBACK,UP,LOWER_UP> mtu 65536 qdisc noqueue state UNKNOWN qlen 1
        link/loopback 00:00:00:00:00:00 brd 00:00:00:00:00:00
        inet 127.0.0.1/8 scope host lo
           valid_lft forever preferred_lft forever
        inet6 ::1/128 scope host 
           valid_lft forever preferred_lft forever
    2: ens35: <BROADCAST,MULTICAST,UP,LOWER_UP> mtu 1500 qdisc pfifo_fast state UP qlen 1000
        link/ether 00:0c:29:4b:92:6c brd ff:ff:ff:ff:ff:ff
        inet 192.168.1.102/24 brd 192.168.1.255 scope global dynamic ens35
           valid_lft 416sec preferred_lft 416sec
        inet6 fe80::2162:1337:a894:11ce/64 scope link 
           valid_lft forever preferred_lft forever
    3: virbr0: <NO-CARRIER,BROADCAST,MULTICAST,UP> mtu 1500 qdisc noqueue state DOWN qlen 1000
        link/ether 52:54:00:4b:05:cc brd ff:ff:ff:ff:ff:ff
        inet 192.168.122.1/24 brd 192.168.122.255 scope global virbr0
           valid_lft forever preferred_lft forever
    4: virbr0-nic: <BROADCAST,MULTICAST> mtu 1500 qdisc pfifo_fast master virbr0 state DOWN qlen 1000
        link/ether 52:54:00:4b:05:cc brd ff:ff:ff:ff:ff:ff
    [root@slave2 ~]#

在master节点的/etc/hosts内部做ip和主机名的映射：

命令：

[root@master ~]# vi /etc/hosts

内容：

192.168.1.100 master
    192.168.1.101 slave1
    192.168.1.102 slave2

将master的/etc/hosts配置文件拷贝到slave1和slave2的/etc目录下

[root@master ~]# scp /etc/hosts
    hosts        hosts.allow  hosts.deny   
    [root@master ~]# scp /etc/hosts slave1:/etc/
    The authenticity of host 'slave1 (192.168.1.101)' can't be established.
    ECDSA key fingerprint is SHA256:4lVQUkkZo5DlZodLDGbEP3NZKrLvXNW/qeIGRch1eNI.
    ECDSA key fingerprint is MD5:a4:e8:a1:a8:45:d1:69:f5:94:d3:9c:99:1f:7d:c2:d5.
    Are you sure you want to continue connecting (yes/no)? yes
    Warning: Permanently added 'slave1,192.168.1.101' (ECDSA) to the list of known hosts.
    root@slave1's password: 
    hosts                                             100%  221    64.7KB/s   00:00    
    [root@master ~]# scp /etc/hosts slave2:/etc/
    The authenticity of host 'slave2 (192.168.1.102)' can't be established.
    ECDSA key fingerprint is SHA256:4lVQUkkZo5DlZodLDGbEP3NZKrLvXNW/qeIGRch1eNI.
    ECDSA key fingerprint is MD5:a4:e8:a1:a8:45:d1:69:f5:94:d3:9c:99:1f:7d:c2:d5.
    Are you sure you want to continue connecting (yes/no)? yes
    Warning: Permanently added 'slave2,192.168.1.102' (ECDSA) to the list of known hosts.
    root@slave2's password: 
    hosts                                             100%  221   257.8KB/s   00:00    
    [root@master ~]#
    
    scp -r  
    复制目录
    scr 
    复制文件

在三个节点做免密登录：

master:

[root@master ~]# ssh-keygen -t rsa
    Generating public/private rsa key pair.
    Enter file in which to save the key (/root/.ssh/id_rsa): 
    Enter passphrase (empty for no passphrase): 
    Enter same passphrase again: 
    Your identification has been saved in /root/.ssh/id_rsa.
    Your public key has been saved in /root/.ssh/id_rsa.pub.
    The key fingerprint is:
    SHA256:s3RzKkZ7vcTmll5uQW0ldRuil5NGgC34K/qe33+OgkI root@master
    The key's randomart image is:
    +---[RSA 2048]----+
    |        . o..o oo|
    |       . o .o = =|
    |        . .. * +.|
    |         .  o o o|
    |        S + .. . |
    |       E * *  .  |
    |      o * + =... |
    |     . o.+.=o+o. |
    |      o+o. +*++. |
    +----[SHA256]-----+
    [root@master ~]# ssh-copy-id master
    /usr/bin/ssh-copy-id: INFO: Source of key(s) to be installed: "/root/.ssh/id_rsa.pub"
    The authenticity of host 'master (192.168.1.100)' can't be established.
    ECDSA key fingerprint is SHA256:2lG2/rO51PcX3P7MHU9/WjpTuuAVJS6yYZiLDA+gUZ4.
    ECDSA key fingerprint is MD5:c9:06:dc:69:31:20:01:4f:bb:26:db:2e:e0:da:92:94.
    Are you sure you want to continue connecting (yes/no)? yes
    /usr/bin/ssh-copy-id: INFO: attempting to log in with the new key(s), to filter out any that are already installed
    /usr/bin/ssh-copy-id: INFO: 1 key(s) remain to be installed -- if you are prompted now it is to install the new keys
    root@master's password: 
    
    Number of key(s) added: 1
    
    Now try logging into the machine, with:   "ssh 'master'"
    and check to make sure that only the key(s) you wanted were added.
    
    [root@master ~]# ssh-copy-id slave1
    /usr/bin/ssh-copy-id: INFO: Source of key(s) to be installed: "/root/.ssh/id_rsa.pub"
    /usr/bin/ssh-copy-id: INFO: attempting to log in with the new key(s), to filter out any that are already installed
    /usr/bin/ssh-copy-id: INFO: 1 key(s) remain to be installed -- if you are prompted now it is to install the new keys
    root@slave1's password: 
    
    Number of key(s) added: 1
    
    Now try logging into the machine, with:   "ssh 'slave1'"
    and check to make sure that only the key(s) you wanted were added.
    
    [root@master ~]# ssh-copy-id slave2
    /usr/bin/ssh-copy-id: INFO: Source of key(s) to be installed: "/root/.ssh/id_rsa.pub"
    /usr/bin/ssh-copy-id: INFO: attempting to log in with the new key(s), to filter out any that are already installed
    /usr/bin/ssh-copy-id: INFO: 1 key(s) remain to be installed -- if you are prompted now it is to install the new keys
    root@slave2's password: 
    
    Number of key(s) added: 1
    
    Now try logging into the machine, with:   "ssh 'slave2'"
    and check to make sure that only the key(s) you wanted were added.
    
    [root@master ~]#

slave1:

[root@slave1 ~]# ssh-keygen -t rsa
    Generating public/private rsa key pair.
    Enter file in which to save the key (/root/.ssh/id_rsa): 
    Enter passphrase (empty for no passphrase): 
    Enter same passphrase again: 
    Your identification has been saved in /root/.ssh/id_rsa.
    Your public key has been saved in /root/.ssh/id_rsa.pub.
    The key fingerprint is:
    SHA256:wXPBu3R+MWJQv7fnyGhgvCrsNyiHbzzzJzQB/kkMHn4 root@slave1
    The key's randomart image is:
    +---[RSA 2048]----+
    |         ....    |
    |      +.  o. .   |
    |     + =+ .o  .  |
    |      + E+o + o. |
    |       +S= = ..o.|
    |        = = . ...|
    |     + o o o . ..|
    |    o X + o .o o.|
    |     *o*o= .. o .|
    +----[SHA256]-----+
    [root@slave1 ~]# ssh-copy-id master
    /usr/bin/ssh-copy-id: INFO: Source of key(s) to be installed: "/root/.ssh/id_rsa.pub"
    The authenticity of host 'master (192.168.1.100)' can't be established.
    ECDSA key fingerprint is SHA256:2lG2/rO51PcX3P7MHU9/WjpTuuAVJS6yYZiLDA+gUZ4.
    ECDSA key fingerprint is MD5:c9:06:dc:69:31:20:01:4f:bb:26:db:2e:e0:da:92:94.
    Are you sure you want to continue connecting (yes/no)? yes
    /usr/bin/ssh-copy-id: INFO: attempting to log in with the new key(s), to filter out any that are already installed
    /usr/bin/ssh-copy-id: INFO: 1 key(s) remain to be installed -- if you are prompted now it is to install the new keys
    root@master's password: 
    
    Number of key(s) added: 1
    
    Now try logging into the machine, with:   "ssh 'master'"
    and check to make sure that only the key(s) you wanted were added.
    
    [root@slave1 ~]# ssh-copy-id slave1
    /usr/bin/ssh-copy-id: INFO: Source of key(s) to be installed: "/root/.ssh/id_rsa.pub"
    The authenticity of host 'slave1 (192.168.1.101)' can't be established.
    ECDSA key fingerprint is SHA256:4lVQUkkZo5DlZodLDGbEP3NZKrLvXNW/qeIGRch1eNI.
    ECDSA key fingerprint is MD5:a4:e8:a1:a8:45:d1:69:f5:94:d3:9c:99:1f:7d:c2:d5.
    Are you sure you want to continue connecting (yes/no)? yes
    /usr/bin/ssh-copy-id: INFO: attempting to log in with the new key(s), to filter out any that are already installed
    /usr/bin/ssh-copy-id: INFO: 1 key(s) remain to be installed -- if you are prompted now it is to install the new keys
    root@slave1's password: 
    
    Number of key(s) added: 1
    
    Now try logging into the machine, with:   "ssh 'slave1'"
    and check to make sure that only the key(s) you wanted were added.
    
    [root@slave1 ~]# ssh-copy-id slave2
    /usr/bin/ssh-copy-id: INFO: Source of key(s) to be installed: "/root/.ssh/id_rsa.pub"
    The authenticity of host 'slave2 (192.168.1.102)' can't be established.
    ECDSA key fingerprint is SHA256:4lVQUkkZo5DlZodLDGbEP3NZKrLvXNW/qeIGRch1eNI.
    ECDSA key fingerprint is MD5:a4:e8:a1:a8:45:d1:69:f5:94:d3:9c:99:1f:7d:c2:d5.
    Are you sure you want to continue connecting (yes/no)? yes
    /usr/bin/ssh-copy-id: INFO: attempting to log in with the new key(s), to filter out any that are already installed
    /usr/bin/ssh-copy-id: INFO: 1 key(s) remain to be installed -- if you are prompted now it is to install the new keys
    root@slave2's password: 
    
    Number of key(s) added: 1
    
    Now try logging into the machine, with:   "ssh 'slave2'"
    and check to make sure that only the key(s) you wanted were added.
    
    [root@slave1 ~]#

slave2:

[root@slave2 ~]# ssh-keygen -t rsa
    Generating public/private rsa key pair.
    Enter file in which to save the key (/root/.ssh/id_rsa): 
    Enter passphrase (empty for no passphrase): 
    Enter same passphrase again: 
    Your identification has been saved in /root/.ssh/id_rsa.
    Your public key has been saved in /root/.ssh/id_rsa.pub.
    The key fingerprint is:
    SHA256:RCXC1qIT61bJFnA1ycNG5ET4zaQEv6duUL7y7UvLq+4 root@slave2
    The key's randomart image is:
    +---[RSA 2048]----+
    |    .o+@Xo.      |
    |    ..**Oo.      |
    |     * B+*       |
    |    + =.+.o      |
    |   . + oS .      |
    |    o . .o       |
    |   .   ....      |
    |      ..o+ .     |
    |       *EoBo     |
    +----[SHA256]-----+
    [root@slave2 ~]# ssh-copy-id master
    /usr/bin/ssh-copy-id: INFO: Source of key(s) to be installed: "/root/.ssh/id_rsa.pub"
    The authenticity of host 'master (192.168.1.100)' can't be established.
    ECDSA key fingerprint is SHA256:2lG2/rO51PcX3P7MHU9/WjpTuuAVJS6yYZiLDA+gUZ4.
    ECDSA key fingerprint is MD5:c9:06:dc:69:31:20:01:4f:bb:26:db:2e:e0:da:92:94.
    Are you sure you want to continue connecting (yes/no)? yes
    /usr/bin/ssh-copy-id: INFO: attempting to log in with the new key(s), to filter out any that are already installed
    /usr/bin/ssh-copy-id: INFO: 1 key(s) remain to be installed -- if you are prompted now it is to install the new keys
    root@master's password: 
    
    Number of key(s) added: 1
    
    Now try logging into the machine, with:   "ssh 'master'"
    and check to make sure that only the key(s) you wanted were added.
    
    [root@slave2 ~]# ssh-copy-id slave1
    /usr/bin/ssh-copy-id: INFO: Source of key(s) to be installed: "/root/.ssh/id_rsa.pub"
    The authenticity of host 'slave1 (192.168.1.101)' can't be established.
    ECDSA key fingerprint is SHA256:4lVQUkkZo5DlZodLDGbEP3NZKrLvXNW/qeIGRch1eNI.
    ECDSA key fingerprint is MD5:a4:e8:a1:a8:45:d1:69:f5:94:d3:9c:99:1f:7d:c2:d5.
    Are you sure you want to continue connecting (yes/no)? yes
    /usr/bin/ssh-copy-id: INFO: attempting to log in with the new key(s), to filter out any that are already installed
    /usr/bin/ssh-copy-id: INFO: 1 key(s) remain to be installed -- if you are prompted now it is to install the new keys
    root@slave1's password: 
    
    Number of key(s) added: 1
    
    Now try logging into the machine, with:   "ssh 'slave1'"
    and check to make sure that only the key(s) you wanted were added.
    
    [root@slave2 ~]# ssh-copy-id slave2
    /usr/bin/ssh-copy-id: INFO: Source of key(s) to be installed: "/root/.ssh/id_rsa.pub"
    The authenticity of host 'slave2 (192.168.1.102)' can't be established.
    ECDSA key fingerprint is SHA256:4lVQUkkZo5DlZodLDGbEP3NZKrLvXNW/qeIGRch1eNI.
    ECDSA key fingerprint is MD5:a4:e8:a1:a8:45:d1:69:f5:94:d3:9c:99:1f:7d:c2:d5.
    Are you sure you want to continue connecting (yes/no)? yes
    /usr/bin/ssh-copy-id: INFO: attempting to log in with the new key(s), to filter out any that are already installed
    /usr/bin/ssh-copy-id: INFO: 1 key(s) remain to be installed -- if you are prompted now it is to install the new keys
    root@slave2's password: 
    
    Number of key(s) added: 1
    
    Now try logging into the machine, with:   "ssh 'slave2'"
    and check to make sure that only the key(s) you wanted were added.
    
    [root@slave2 ~]#

master:

关闭防火墙：

[root@master ~]# systemctl stop firewalld

禁止防火墙开机启动：

[root@master ~]# systemctl disable firewalld

slave1:

关闭防火墙：

[root@master ~]# systemctl stop firewalld

禁止防火墙开机启动：

[root@master ~]# systemctl disable firewalld

slave2:

关闭防火墙：

[root@master ~]# systemctl stop firewalld

禁止防火墙开机启动：

[root@master ~]# systemctl disable firewalld

### 2. hadoop集群部署 ###

#### 2.1 jdk的部署和安装 ####

创建要解压的路径：

[root@master softwares]# mkdir /opt/module
    [root@master softwares]# ls /opt/
    module  softwares
    [root@master softwares]#

解压jdk：

[root@master softwares]# tar -zxvf jdk-8u212-linux-x64.tar.gz -C /opt/module/

重命名jdk文件件

[root@master softwares]# ls /opt/module/
    jdk1.8.0_212
    [root@master softwares]# cd /opt/module/
    [root@master module]# ls
    jdk1.8.0_212
    [root@master module]# mv jdk1.8.0_212/ jdk
    [root@master module]# ls
    jdk
    [root@master module]#

修改环境变量配置：

[root@master module]# vi /etc/profile

修改内容：

# JAVA_HOME 
    export JAVA_HOME=/opt/module/jdk
    export PATH="$JAVA_HOME/bin:$PATH"

source使配置文件生效：

[root@master module]# source /etc/profile
    [root@master module]#

执行java -version 查看Java版本，能看到版本说明配置生效：

[root@master module]# java -version
    java version "1.8.0_212"
    Java(TM) SE Runtime Environment (build 1.8.0_212-b10)
    Java HotSpot(TM) 64-Bit Server VM (build 25.212-b10, mixed mode)
    [root@master module]#

在slave1和slave2节点创建module路径：

[root@slave1 ~]# mkdir /opt/module/
    [root@slave1 ~]# 
    [root@slave2 ~]# mkdir /opt/module

拷贝jdk和jdk的环境变量到slave1和slave2节点：

[root@master module]# scp -r /opt/module/jdk/ slave1:/opt/module/jdk
    [root@master module]# scp -r /opt/module/jdk/ slave2:/opt/module/jdk

在slave1和slave2节点配置环境变量：

[root@slave1 jdk]# vi /etc/profile
    [root@slave1 jdk]# source /etc/profile
    [root@slave1 jdk]# java -version
    java version "1.8.0_212"
    Java(TM) SE Runtime Environment (build 1.8.0_212-b10)
    Java HotSpot(TM) 64-Bit Server VM (build 25.212-b10, mixed mode)
    [root@slave1 jdk]# 
     [root@slave2 ~]# vi /etc/profile
    [root@slave2 ~]# source /etc/profile
    [root@slave2 ~]# java -version\
    > ;
    java version "1.8.0_212"
    Java(TM) SE Runtime Environment (build 1.8.0_212-b10)
    Java HotSpot(TM) 64-Bit Server VM (build 25.212-b10, mixed mode)
    [root@slave2 ~]#

#### 2.2 Hadoop集群配置 ####

1.  解压hadoop到/opt/module/路径下：
    
        [root@master softwares]# tar -zxvf /opt/softwares/hadoop-3.1.3.tar.gz -C /opt/module/
2.  修改文件名称，配置hadoop环境变量
    
        [root@master module]# mv hadoop-3.1.3/ hadoop
        [root@master module]# ls
        hadoop  jdk
        [root@master module]# vi /etc/profile
    
    配置内容：
    
        # HADOOP_HOME
        export HADOOP_HOME=/opt/module/hadoop
        export PATH="$HADOOP_HOME/bin:$PATH"
    
    source并查看hadoop版本：
    
        [root@master module]# hadoop version
        Hadoop 3.1.3
        Source code repository https://gitbox.apache.org/repos/asf/hadoop.git -r ba631c436b806728f8ec2f54ab1e289526c90579
        Compiled by ztang on 2019-09-12T02:47Z
        Compiled with protoc 2.5.0
        From source with checksum ec785077c385118ac91aadde5ec9799
        This command was run using /opt/module/hadoop/share/hadoop/common/hadoop-common-3.1.3.jar
        [root@master module]#
3.  配置hadoop相关配置文件：
    
    核心配置文件
    
    配置core-site.xml
    
        [root@master hadoop]# vi /opt/module/hadoop/etc/hadoop/core-site.xml
    
    文件内容：
    
        <configuration>
        
                <property>
                             <name>fs.defaultFS</name>
                             <value>hdfs://master:9000</value>
                </property>
        
                <property>
                            <name>hadoop.tmp.dir</name>
                            <value>/opt/module/hadoop/data</value>
                </property>
        </configuration>

HDFS配置文件：

配置hdfs-site.xml

[root@master hadoop]# vim /opt/module/hadoop/etc/hadoop/hdfs-site.xml

文件内容：

<configuration>
            
            <property>
                    <name>dfs.namenode.http-address</name>
                    <value>master:50070</value>
            </property>
            
            <property>
                    <name>dfs.replication</name>
                    <value>1</value>
            </property>
    </configuration>

YARN配置文件：

配置yarn-site.xml

[root@master hadoop]# vim /opt/module/hadoop/etc/hadoop/yarn-site.xml

配置内容：

<configuration>
    
    
    
            <property>
                    <name>yarn.nodemanager.aux-services</name>
                    <value>mapreduce_shuffle</value>
            </property>
    ‘
            <property>
                    <name>yarn.resourcemanager.hostname</name>
                    <value>master</value>
            </property>
    </configuration>

MAPREDUCE配置文件：

配置mapred-site.xml

[root@master hadoop]# vim /opt/module/hadoop/etc/hadoop/mapred-site.xml

配置内容：

<configuration>
    
        <property>
            <name>mapreduce.framework.name</name>
            <value>yarn</value>
        </property>
    
        <property>
            <name>mapreduce.jobhistory.address</name>
            <value>master:10020</value>
        </property>
    
        <property>
            <name>mapreduce.jobhistory.webapp.address</name>
            <value>master:19888</value>
        </property>
    </configuration>
    配置workers
    [root@master hadoop]# vim /opt/module/hadoop/etc/hadoop/workers

配置内容：

master
    slave1
    slave2

配置hadoop-env.sh

[root@master hadoop]# vi /opt/module/hadoop/etc/hadoop/hadoop-env.sh

配置内容：

export JAVA_HOME=/opt/module/jdk

配置mapred-env.sh

[root@master hadoop]# vi /opt/module/hadoop/etc/hadoop/mapred-env.sh

配置内容：

export JAVA_HOME=/opt/module/jdk

配置yarn-env.sh

[root@master hadoop]# vi /opt/module/hadoop/etc/hadoop/yarn-env.sh

配置内容：

export JAVA_HOME=/opt/module/jdk

将hadoop拷贝到slave1和slave2节点：

[root@master hadoop]# scp -r /opt/module/hadoop/ slave1:/opt/module/hadoop/
    [root@master hadoop]# scp -r /opt/module/hadoop/ slave2:/opt/module/hadoop/

格式化namenode:

[root@master hadoop]# hdfs namenode -format

`在/etc/profile下配置hadoop的HDFS用户和yarn的用户`：

[root@master hadoop]# vi /etc/profile

配置内容：

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

source /etc/profile使配置文件生效：

[root@master hadoop]# source /etc/profile

启动Hadoop集群：

[root@master hadoop]# pwd
    /opt/module/hadoop
    [root@master hadoop]# ./sbin/start-all.sh

jps查看hadoop进程是否启动：

[root@master hadoop]# jps
    7472 DataNode
    7297 NameNode
    7682 SecondaryNameNode
    7939 ResourceManager
    8467 Jps
    8091 NodeManager
    [root@master hadoop]#

slave1:

[root@slave1 hadoop]# jps
    5194 NodeManager
    5325 Jps
    5087 DataNode
    [root@slave1 hadoop]#

slave2:

[root@slave2 hadoop]# jps
    5065 NodeManager
    5196 Jps
    4958 DataNode
    [root@slave2 hadoop]#

### 3.hive组件部署 ###

#### 3.1 MYSql数据库部署 ####

安装包位置 /opt/softwares/mysql

账号：root

密码：123456

1.  卸载mariadb

[root@master hadoop]# rpm -qa | grep mariadb
    mariadb-libs-5.5.56-2.el7.x86_64
    [root@master hadoop]# rpm -e --nodeps mari
    mariadb-libs  marisa        
    [root@master hadoop]# rpm -e --nodeps mariadb-libs 
    [root@master hadoop]#

1.  通过rpm命令按顺序安装mysql:

安装包位置：

[root@master softwares]# cd Mysql/
    [root@master Mysql]# ls
    01_mysql-community-common-5.7.16-1.el7.x86_64.rpm
    02_mysql-community-libs-5.7.16-1.el7.x86_64.rpm
    03_mysql-community-libs-compat-5.7.16-1.el7.x86_64.rpm
    04_mysql-community-client-5.7.16-1.el7.x86_64.rpm
    05_mysql-community-server-5.7.16-1.el7.x86_64.rpm
    mysql-connector-java-5.1.27-bin.jar
    [root@master Mysql]# pwd
    /opt/softwares/Mysql
    [root@master Mysql]#

通过rpm命令按顺序安装mysql:

[root@master Mysql]# rpm -ivh 01_mysql-community-common-5.7.16-1.el7.x86_64.rpm 
    [root@master Mysql]# rpm -ivh 02_mysql-community-libs-5.7.16-1.el7.x86_64.rpm 
    [root@master Mysql]# rpm -ivh 03_mysql-community-libs-compat-5.7.16-1.el7.x86_64.rpm 
    [root@master Mysql]# rpm -ivh 04_mysql-community-client-5.7.16-1.el7.x86_64.rpm 
    [root@master Mysql]# rpm -ivh 05_mysql-community-server-5.7.16-1.el7.x86_64.rpm

查看是否安装成功：

[root@master Mysql]# rpm -qa | grep mysql
    mysql-community-server-5.7.16-1.el7.x86_64
    mysql-community-libs-5.7.16-1.el7.x86_64
    mysql-community-libs-compat-5.7.16-1.el7.x86_64
    mysql-community-client-5.7.16-1.el7.x86_64
    mysql-community-common-5.7.16-1.el7.x86_64
    [root@master Mysql]#

通过命令启动mysql:

[root@master Mysql]# service mysqld start
    Redirecting to /bin/systemctl start mysqld.service

查看临时密码并通过临时密码登录mysql：

[root@master Mysql]# grep 'temporary password' /var/log/mysqld.log 
    2022-11-14T13:46:27.335510Z 1 [Note] A temporary password is generated for root@localhost: 
    +N_r2eOrOvk*
    
    [root@master Mysql]# mysql -uroot -p+N_r2eOrOvk*
    mysql: [Warning] Using a password on the command line interface can be insecure.
    Welcome to the MySQL monitor.  Commands end with ; or \g.
    Your MySQL connection id is 2
    Server version: 5.7.16
    
    Copyright (c) 2000, 2016, 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>

mysql修改密码及开启远程访问：

mysql> set global validate_password_policy=0;
    Query OK, 0 rows affected (0.00 sec)
    
    mysql> set global validate_password_length=1;
    Query OK, 0 rows affected (0.00 sec)
    
    mysql> alter user 'root'@'localhost' identified by '123456';
    Query OK, 0 rows affected (0.00 sec)
    
    mysql> grant all privileges on *.* to 'root'@'%' identified by '123456'; 
    Query OK, 0 rows affected, 1 warning (0.00 sec)
    
    mysql> flush privileges;
    Query OK, 0 rows affected (0.00 sec)
    
    mysql> exit;

退出后使用自己设置的密码登录mysql测试：

[root@master Mysql]# mysql -uroot -p123456
    mysql: [Warning] Using a password on the command line interface can be insecure.
    Welcome to the MySQL monitor.  Commands end with ; or \g.
    Your MySQL connection id is 5
    Server version: 5.7.16 MySQL Community Server (GPL)
    
    Copyright (c) 2000, 2016, 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>

#### 3.2 Hive部署 ####

解压hive，并重命名为hive，将hive环境变量配置到/etc/profile:

[root@master Mysql]# tar -zxvf /opt/softwares/apache-hive-3.1.2-bin.tar.gz -C /opt/module/
    [root@master Mysql]# mv /opt/module/apache-hive-3.1.2-bin/ /opt/module/hive
    [root@master Mysql]# ls /opt/module/
    hadoop  hive  jdk
    [root@master Mysql]#vi /etc/profile
    [root@master Mysql]# source /etc/profile
    [root@master Mysql]#

环境变量配置内容：

# HIVE_HOME
    export HIVE_HOME=/opt/module/hive
    export PATH="$HIVE_HOME/bin:$PATH"

将Hive元数据配置到mysql:

将jdbc驱动拷贝到hive的lib目录下：

[root@master Mysql]# cp /opt/softwares/Mysql/mysql-connector-java-5.1.27-bin.jar /opt/module/hive/lib/
    [root@master Mysql]#

在hive相对路径下的conf目录下，配置hive-site.xml:

[root@master Mysql]# vi /opt/module/hive/conf/hive-site.xml

配置文件内容：

<?xml version="1.0"?>
    <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
    <configuration>
        <property>
            <name>javax.jdo.option.ConnectionURL</name>
            <value>jdbc:mysql://master:3306/metastore?useSSL=false</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>123456</value>
        </property>
    
        <property>
            <name>hive.metastore.warehouse.dir</name>
            <value>/user/hive/warehouse</value>
        </property>
    
        <property>
            <name>hive.metastore.schema.verification</name>
            <value>false</value>
        </property>
    
        <property>
        <name>hive.server2.thrift.port</name>
        <value>10000</value>
        </property>
    
        <property>
            <name>hive.server2.thrift.bind.host</name>
            <value>master</value>
        </property>
    
        <property>
            <name>hive.metastore.event.db.notification.api.auth</name>
            <value>false</value>
        </property>
        
        <property>
            <name>hive.cli.print.header</name>
            <value>true</value>
        </property>
    
        <property>
            <name>hive.cli.print.current.db</name>
            <value>true</value>
        </property>
    </configuration>

初始化元数据库：

登录Mysql，创建hive的元数据库：

[root@master Mysql]# mysql -uroot -p123456
    mysql: [Warning] Using a password on the command line interface can be insecure.
    Welcome to the MySQL monitor.  Commands end with ; or \g.
    Your MySQL connection id is 6
    Server version: 5.7.16 MySQL Community Server (GPL)
    
    Copyright (c) 2000, 2016, 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> create database metastore;
    Query OK, 1 row affected (0.00 sec)
    
    mysql> quit;
    Bye
    [root@master Mysql]#

初始化hive元数据库：

[root@master Mysql]# schematool --initSchema -dbType mysql -verbose

启动Hive客户端，查看数据库：

[root@master Mysql]# hive
    which: no hbase in (/opt/module/hadoop/bin:/opt/module/hive/bin:/opt/module/jdk/bin:/usr/local/python3/bin:/opt/module/hadoop/bin:/opt/module/jdk/bin:/usr/local/python3/bin:/opt/module/hadoop/bin:/opt/module/jdk/bin:/usr/local/python3/bin:/opt/module/jdk/bin:/usr/local/python3/bin:/usr/local/python3/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/root/bin)
    SLF4J: Class path contains multiple SLF4J bindings.
    SLF4J: Found binding in [jar:file:/opt/module/hive/lib/log4j-slf4j-impl-2.10.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
    SLF4J: Found binding in [jar:file:/opt/module/hadoop/share/hadoop/common/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
    SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
    SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
    Hive Session ID = 69642fdc-0c17-4637-8e11-3415e32bfd4d
    
    Logging initialized using configuration in jar:file:/opt/module/hive/lib/hive-common-3.1.2.jar!/hive-log4j2.properties Async: true
    Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.
    Hive Session ID = 1ee7f81d-bfad-4ab6-aa30-6c4c26976021
    hive (default)> show databases;
    OK
    database_name
    default
    Time taken: 0.543 seconds, Fetched: 1 row(s)
    hive (default)>

### 4. spark组件部署 ###

解压spark安装包，重命名spark并配置环境变量：

[root@master softwares]# tar -zxvf /opt/softwares/spark-3.1.3-bin-hadoop3.2.tgz -C /opt/module/
    [root@master softwares]# mv /opt/module/spark-3.1.3-bin-hadoop3.2/ /opt/module/spark
    [root@master softwares]# vi /etc/profile

环境变量配置内容：

# SPARK_HOME
    export SPARK_HOME=/opt/module/spark
    export PATH="$SPARK_HOME/bin:$PATH"

source 使环境变量生效：

[root@master softwares]# source /etc/profile

重命名workers。template 文件并配置计算节点：

[root@master conf]# mv workers.template workers
    [root@master conf]# vim workers

配置内容：

master
    slave1
    slave2

修改spark-env.sh文件：

[root@master conf]# cp spark-env.sh.template spark-env.sh
    [root@master conf]# vim spark-env.sh
    [root@master conf]#

添加如下内容：

export JAVA_HOME=/opt/module/jdk
    export HADOOP_HOME=/opt/module/hadoop
    export SPARK_MASTER_IP=master
    export SPARK_MASTER_PORT=7077
    export SPARK_DIST_CLASSPATH=$(/opt/module/hadoop/bin/hadoop classpath)
    export SPARK_YARN_USER_ENV="CLASSPATH=/opt/module/hadoop/etc/hadoop"
    export HADOOP_CONF_DIR=/opt/module/hadoop/etc/hadoop
    export YARN_CONF_DIR=/opt/module/hadoop/etc/hadoop

将spark拷贝到其他两个节点：

[root@master conf]# scp -r /opt/module/spark/ slave1:/opt/module/
    [root@master conf]# scp -r /opt/module/spark/ slave2:/opt/module/

启动spark集群并查看进程：

[root@master spark]# /opt/module/spark/sbin/start-all.sh 
    starting org.apache.spark.deploy.master.Master, logging to /opt/module/spark/logs/spark-root-org.apache.spark.deploy.master.Master-1-master.out
    master: starting org.apache.spark.deploy.worker.Worker, logging to /opt/module/spark/logs/spark-root-org.apache.spark.deploy.worker.Worker-1-master.out
    slave1: starting org.apache.spark.deploy.worker.Worker, logging to /opt/module/spark/logs/spark-root-org.apache.spark.deploy.worker.Worker-1-slave1.out
    slave2: starting org.apache.spark.deploy.worker.Worker, logging to /opt/module/spark/logs/spark-root-org.apache.spark.deploy.worker.Worker-1-slave2.out
    [root@master spark]# jps
    7472 DataNode
    7297 NameNode
    7682 SecondaryNameNode
    7939 ResourceManager
    11715 Master
    11909 Jps
    8091 NodeManager
    11854 Worker
    [root@master spark]#

运行SparkPI程序测试spark:

[root@master spark]# ./bin/spark-submit --class org.apache.spark.examples.SparkPi --master spark://master:7077 examples/jars/spark-examples_2.12-3.1.3.jar

结果：

2022-11-14 22:24:35,002 INFO scheduler.TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool 
    2022-11-14 22:24:35,010 INFO scheduler.DAGScheduler: ResultStage 0 (reduce at SparkPi.scala:38) finished in 2.131 s
    2022-11-14 22:24:35,013 INFO scheduler.DAGScheduler: Job 0 is finished. Cancelling potential speculative or zombie tasks for this job
    2022-11-14 22:24:35,013 INFO scheduler.TaskSchedulerImpl: Killing all running tasks in stage 0: Stage finished
    2022-11-14 22:24:35,014 INFO scheduler.DAGScheduler: Job 0 finished: reduce at SparkPi.scala:38, took 2.189453 s
    Pi is roughly 3.141475707378537
    2022-11-14 22:24:35,046 INFO server.AbstractConnector: Stopped Spark@4fbb001b{HTTP/1.1, (http/1.1)}{0.0.0.0:4040}
    2022-11-14 22:24:35,048 INFO ui.SparkUI: Stopped Spark web UI at http://master:4040
    2022-11-14 22:24:35,050 INFO cluster.StandaloneSchedulerBackend: Shutting down all executors
    2022-11-14 22:24:35,050 INFO cluster.CoarseGrainedSchedulerBackend$DriverEndpoint: Asking each executor to shut down
    2022-11-14 22:24:35,122 INFO spark.MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
    [root@master spark]#

### 5. Flink组件部署 ###

解压Flink修改flink名称并配置环境变量：

[root@master spark]# tar -zxvf /opt/softwares/flink-1.14.6-bin-scala_2.12.tgz -C /opt/module/
    [root@master spark]# mv /opt/module/flink-1.14.6/ /opt/module/flink/
    [root@master spark]# vi /etc/profile

配置内容：

# FLINK_HOME
    export FLINK_HOME=/opt/module/flink
    export PATH="$FLINK_HOME/bin:$PATH"

source /etc/profile配置文件：

[root@master spark]# source /etc/profile
    [root@master spark]#

修改flink-conf.yaml配置文件：

[root@master conf]# vim /opt/module/flink/conf/flink-conf.yaml

修改内容：

jobmanager.rpc.address: master

修改workers配置文件：

[root@master conf]# vim /opt/module/flink/conf/workers

修改内容：

master
    slave1
    slave2

将flink分发到slave1和slave2：

[root@master conf]# scp -r /opt/module/flink/ slave1:/opt/module/
    [root@master conf]# scp -r /opt/module/flink/ slave2:/opt/module/

启动flink集群并查看进程：

[root@master flink]# ./bin/start-cluster.sh 
    Starting cluster.
    Starting standalonesession daemon on host master.
    Starting taskexecutor daemon on host master.
    Starting taskexecutor daemon on host slave1.
    Starting taskexecutor daemon on host slave2.
    [root@master flink]# jps
    7472 DataNode
    7297 NameNode
    13617 TaskManagerRunner
    7682 SecondaryNameNode
    7939 ResourceManager
    11715 Master
    13732 Jps
    8091 NodeManager
    11854 Worker
    [root@master flink]#

提交测试jar包测试flink:

[root@master batch]# flink run -m master:8081 /opt/module/flink/examples/batch/WordCount.jar 
    注意：运行flink要关闭spark standalone集群

测试结果：

(under,1)
    (undiscover,1)
    (unworthy,1)
    (us,3)
    (we,4)
    (weary,1)
    (what,1)
    (when,2)
    (whether,1)
    (whips,1)
    (who,2)
    (whose,1)
    (will,1)
    (wish,1)
    (with,3)
    (would,2)
    (wrong,1)
    (you,1)
    [root@master batch]#

FLinkWeb端界面（[http://192.168.1.100:8081/\#/overview][http_192.168.1.100_8081_overview]）：

### 6. Flume组件部署 ###

解压flume修改文件名称并配置环境变量：

[root@master module]# tar -zxvf /opt/softwares/apache-flume-1.9.0-bin.tar.gz -C /opt/module/
    [root@master module]# mv /opt/module/apache-flume-1.9.0-bin/ /opt/module/flume
    [root@master batch]# vim /etc/profile

环境变量配置内容：

# FLUME_HOME
    export FLUME_HOME=/opt/module/flume
    export PATH="$FLUME_HOME/bin:$PATH"

source /etc/profile:

[root@master batch]# source /etc/profile
    [root@master batch]#

删除flume和hadoop冲突的jar包：

cd /opt/module/flume/lib
    [root@master lib]# rm -rf /opt/module/flume/lib/guava-11.0.2.jar

修改log4j配置文件：

[root@master lib]# vim /opt/module/flume/conf/log4j.properties

修改内容：

flume.log.dir=/opt/module/flume/logs

### 7. Zookeeper组件部署 ###

解压zookeeper修改文件名称并配置环境变量：

[root@master lib]# tar -zxvf /opt/softwares/apache-zookeeper-3.5.7-bin.tar.gz -C /opt/module/
    [root@master lib]# mv /opt/module/apache-zookeeper-3.5.7-bin/ /opt/module/zookeeper
    mv apache-zookeeper-3.5.7-bin/ zookeeper
    [root@master lib]# vim /etc/profile

环境变量修改内容：

# ZOOKEEPER_HOME
    export ZOOKEEPER_HOME=/opt/module/zookeeper
    export PATH="$ZOOKEEPER_HOME/bin:$PATH"

source /etc/profile使环境变量生效：

[root@master lib]# source /etc/profile
    [root@master lib]#

配置服务器编号：

在zookeeper目录下创建zkData

[root@master zookeeper]# mkdir zkData
    [root@master zookeeper]# cd zkData/
    [root@master zkData]# vim myid

myid文件内容：

配置zoo.cfg文件

重命名zoo\_sample.cfg为zoo.cfg，并修改zoo.cfg文件内容:

cd ../conf
    [root@master conf]# mv zoo_sample.cfg zoo.cfg
    [root@master conf]# vim zoo.cfg

修改内容：

dataDir=/opt/module/zookeeper/zkData
    
    
    # 设置zookeeper内部通信地址和选举端口
    server.2=master:2888:3888
    server.3=slave1:2888:3888
    server.4=slave2:2888:3888

将zookeeper拷贝到slave1和slave2:

[root@master conf]# scp -r /opt/module/zookeeper/ slave1:/opt/module/
    [root@master conf]# scp -r /opt/module/zookeeper/ slave2:/opt/module/

修改slave1和slave2上myid内容：

[root@slave1 module]# vim /opt/module/zookeeper/zkData/myid 
    3
    [root@slave2 hadoop]# vim /opt/module/zookeeper/zkData/myid 
    4

启动zookeeper集群：

[root@slave2 hadoop]# /opt/module/zookeeper/bin/zkServer.sh start
    ZooKeeper JMX enabled by default
    Using config: /opt/module/zookeeper/bin/../conf/zoo.cfg
    Starting zookeeper ... STARTED
    [root@slave2 hadoop]# 
    [root@slave1 module]# /opt/module/zookeeper/bin/zkServer.sh start
    ZooKeeper JMX enabled by default
    Using config: /opt/module/zookeeper/bin/../conf/zoo.cfg
    Starting zookeeper ... STARTED
    [root@slave1 module]# 
    [root@master conf]# /opt/module/zookeeper/bin/zkServer.sh start
    ZooKeeper JMX enabled by default
    Using config: /opt/module/zookeeper/bin/../conf/zoo.cfg
    Starting zookeeper ... STARTED
    [root@master conf]#

查看zookeeper进程状态 验证结果：

[root@master conf]# /opt/module/zookeeper/bin/zkServer.sh status
    ZooKeeper JMX enabled by default
    Using config: /opt/module/zookeeper/bin/../conf/zoo.cfg
    Client port found: 2181. Client address: localhost.
    Mode: follower
    [root@master conf]# 
    [root@slave1 module]# /opt/module/zookeeper/bin/zkServer.sh status
    ZooKeeper JMX enabled by default
    Using config: /opt/module/zookeeper/bin/../conf/zoo.cfg
    Client port found: 2181. Client address: localhost.
    Mode: follower
    [root@slave1 module]# 
    [root@slave2 hadoop]# /opt/module/zookeeper/bin/zkServer.sh status
    ZooKeeper JMX enabled by default
    Using config: /opt/module/zookeeper/bin/../conf/zoo.cfg
    Client port found: 2181. Client address: localhost.
    Mode: leader
    [root@slave2 hadoop]#

### 8. Kafka组件部署 ###

解压重命名kafka，并配置环境变量：

[root@master conf]# tar -zxvf /opt/softwares/kafka_2.12-3.0.0.tgz -C /opt/module/
    [root@master conf]# mv /opt/module/kafka_2.12-3.0.0/ /opt/module/kafka
    [root@master conf]# vim /etc/profile

配置内容：

# KAFKA_HOME
    export KAFKA_HOME=/opt/module/kafka
    export PATH="$KAFKA_HOME/bin:$PATH"

修改kafka的server.properties配置文件：

[root@master config]# vim /opt/module/kafka/config/server.properties

修改内容：

# 唯一值
    broker.id=0
    # kafka启动会自动创建
    log.dirs=/opt/module/kafka/logs
    # zk连接
    zookeeper.connect=master:2181,slave1:2181,slave2:2181/kafka

将kafka拷贝到slave1和slave2节点：

[root@master config]# scp -r /opt/module/kafka/ slave1:/opt/module/
    [root@master config]# scp -r /opt/module/kafka/ slave2:/opt/module/

修改slave1和slave2节点的broker.id值

[root@slave1 module]# vim /opt/module/kafka/config/server.properties
    broker.id=1
    [root@slave2 hadoop]# vim /opt/module/kafka/config/server.properties 
    broker.id=2

在三个节点启动kafka:

[root@master config]# /opt/module/kafka/bin/kafka-server-start.sh -daemon /opt/module/kafka/config/server.properties 
    [root@slave1 module]# /opt/module/kafka/bin/kafka-server-start.sh -daemon /opt/module/kafka/config/server.properties 
    [root@slave2 hadoop]# /opt/module/kafka/bin/kafka-server-start.sh -daemon /opt/module/kafka/config/server.properties 
    
    /opt/module/kafka/bin/kafka-server-start.sh -daemon /opt/kafka/config/server.properties

查看kafka进程：

[root@master config]# jps
    7472 DataNode
    7297 NameNode
    7682 SecondaryNameNode
    7939 ResourceManager
    15123 CliFrontend
    18035 QuorumPeerMain
    16388 StandaloneSessionClusterEntrypoint
    18725 Kafka
    16694 TaskManagerRunner
    14170 CliFrontend
    8091 NodeManager
    18813 Jps
    [root@master config]# 
    [root@slave1 module]# jps
    10032 Jps
    9383 QuorumPeerMain
    8841 TaskManagerRunner
    5194 NodeManager
    9963 Kafka
    5087 DataNode
    [root@slave1 module]# 
    [root@slave2 hadoop]# jps
    9202 QuorumPeerMain
    9874 Jps
    5065 NodeManager
    8681 TaskManagerRunner
    9804 Kafka
    4958 DataNode
    [root@slave2 hadoop]#

### 9. MaxWell组件部署 ###

解压重命名maxwell,并配置环境变量：

[root@master softwares]# tar -zxvf /opt/softwares/maxwell-1.29.2.tar.gz -C /opt/module/
    [root@master softwares]# mv /opt/module/maxwell-1.29.2/ /opt/module/maxwell/
    [root@master softwares]# vim /etc/profile

修改内容：

# MAXWELL_HOME
    export MAXWELL_HOME=/opt/module/maxwell
    export PATH="$MAXWELL_HOME/bin:$PATH"

修改MySQL相关配置：

启用MySQL Binlog,进行数据同步要先开启BinLog

修改MySQL配置文件/etc/my/cnf

[root@master ~]# vim /etc/my.cnf

修改内容：

#数据库id
    server-id = 1
    #启动binlog，该参数的值会作为binlog的文件名
    log-bin=mysql-bin
    #binlog类型，maxwell要求为row类型
    binlog_format=row
    #启用binlog的数据库，需根据实际情况作出修改
    binlog-do-db=ds_pub

在mysql中创建出数据库ds\_pub:

[root@master ~]# mysql -uroot -p123456
    mysql: [Warning] Using a password on the command line interface can be insecure.
    Welcome to the MySQL monitor.  Commands end with ; or \g.
    Your MySQL connection id is 30
    Server version: 5.7.16 MySQL Community Server (GPL)
    
    Copyright (c) 2000, 2016, 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> show databases;
    +--------------------+
    | Database           |
    +--------------------+
    | information_schema |
    | metastore          |
    | mysql              |
    | performance_schema |
    | sys                |
    +--------------------+
    5 rows in set (0.00 sec)
    
    mysql> create database ds_pub;
    Query OK, 1 row affected (0.00 sec)
    
    mysql> exit;
    Bye

重启mysql服务：

[root@master ~]# systemctl restart mysqld
    [root@master ~]#

在MySQL中创建Maxwell所需要的数据库和用户

[root@master ~]# mysql -uroot -p123456
    mysql: [Warning] Using a password on the command line interface can be insecure.
    Welcome to the MySQL monitor.  Commands end with ; or \g.
    Your MySQL connection id is 2
    Server version: 5.7.16-log MySQL Community Server (GPL)
    
    Copyright (c) 2000, 2016, 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> CREATE DATABASE maxwell;
    Query OK, 1 row affected (0.00 sec)
    
    mysql> set global validate_password_policy=0;
    Query OK, 0 rows affected (0.00 sec)
    
    mysql> set global validate_password_length=4;
    Query OK, 0 rows affected (0.00 sec)
    
    mysql> CREATE USER 'maxwell'@'%' IDENTIFIED BY 'maxwell';
    Query OK, 0 rows affected (0.01 sec)
    
    mysql> GRANT ALL ON maxwell.* TO 'maxwell'@'%';
    Query OK, 0 rows affected (0.00 sec)
    
    mysql> GRANT SELECT, REPLICATION CLIENT, REPLICATION SLAVE ON *.* TO 'maxwell'@'%';
    Query OK, 0 rows affected (0.00 sec)
    
    mysql> exit;
    Bye
    [root@master ~]#

\[root@master redis\]\# cd /opt/maxwell \[root@master maxwell\]\# ls bin config.properties.example lib log4j2.xml README.md config.md kinesis-producer-library.properties.example LICENSE quickstart.md \[root@master maxwell\]\# cp config.properties.example config.properties

### 10. Redis组件部署 ###

解压重命名redis,并配置环境变量：

[root@master softwares]# tar -zxvf redis-6.2.6.tar.gz -C /opt/module/
    [root@master softwares]# mv /opt/module/redis-6.2.6/ /opt/module/redis
    [root@master softwares]# cd /opt/module/
    [root@master module]# ls
    flink  flume  hadoop  hive  jdk  kafka  maxwell  redis  spark  zookeeper
    [root@master module]#

（1.）查看是否安装了gcc相关程序 命令：which gcc ![在这里插入图片描述][20200527215137201.png] （显示没有相关的文件） （2）安装gcc程序 命令：yum -y install gcc automake autoconf libtool make

查看gcc编译器版本:

[root@master redis]# gcc --version
    gcc (GCC) 4.8.5 20150623 (Red Hat 4.8.5-44)
    Copyright (C) 2015 Free Software Foundation, Inc.
    This is free software; see the source for copying conditions.  There is NO
    warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
    
    [root@master redis]#

进入redis目录,执行make命令:

[root@master redis]# cd /opt/module/redis/
    [root@master redis]# make
    [root@master redis]# make install

备份redis.conf 到/root目录

[root@master redis]# cp redis.conf /root/
    [root@master redis]#

设置Redis在后台启动:

[root@master ~]# vim redis.conf

修改内容:

bind 192.168.1.100 -::1
    
    # 设置为在后台启动
    daemonize yes 
    #pro

修改redis.conf 名称:

[root@master ~]# mv redis.conf my_redis.conf

后台启动redis

[root@master ~]# redis-server /root/my_redis.conf 
    [root@master ~]#

用客户端去访问redis:

[root@master ~]# redis-cli -h 192.168.1.100 -p 6379
    192.168.1.100:6379>

### 11. Hbase组件部署 ###

解压重命名hbase，并配置环境：

[root@master hbase]# tar -zxvf hbase-2.3.3-bin.tar.gz -C /opt/module/
    [root@master hbase]# mv hbase-2.3.3/ hbase
    [root@master module]# ls
    clickhouse  flink  flume  hadoop  hbase  hive  jdk  kafka  maxwell  Mysql  redis  spark  zookeeper

配置profile环境变量：

[root@master module]# vi /etc/profile
    #hbase_home
    export HBASE_HOME=/opt/module/hbase
    export PATH="HBASE_HOME/bin:$PATH"
    [root@master module]# source /etc/profile

修改hbase-env.sh配置文件：

[root@master conf]# vi hbase-env.sh
    
    export JAVA_HOME=/opt/module/jdk
    export HBASE_MANAGES_ZK=false

修改hbase-site.xml文件：

<configuration>
      
      <property>
        <name>hbase.cluster.distributed</name>
        <value>true</value>
      </property>
      <property>
        <name>hbase.tmp.dir</name>
        <value>./tmp</value>
      </property>
      <property>
        <name>hbase.unsafe.stream.capability.enforce</name>
        <value>false</value>
      </property>
      <property>
        <name>hbase.root.dir</name>
        <value>hdfs://master:9000/base</value>
      </property>
     <property>
        <name>hbase.zookeeper.quorum</name>
        <value>master,slave1,slave2</value>
      </property>
     <property>
        <name>hbase.zookeeper.property.clientPort</name>
        <value>2181</value>
      </property>
     <property>
        <name>hbase.master.maxclockskew</name>
        <value>30000</value>
      </property>
      <property>
        <name>hbase.zookeeper.property.dataDir</name>
        <value>/opt/mopdule/zookeeper</value>
      </property>
      <property>
        <name>zookeeper.session.timeout</name>
        <value>300000</value>
      </property>
    </configuration>

修改regionsservers文件：

[root@master conf]# vi regionservers
    
    master
    slave1
    slave2

启动hbase

[root@master hbase]# ./bin/start-hbase.sh

jps:在哪台服务器使用上述命令启动则那台服务器即为master节点，使用 jps命令查看启动情况

[root@master hbase]# jps
    2465 ResourceManager
    1844 NameNode
    5652 HRegionServer
    6308 Jps
    2792 NodeManager
    3144 Worker
    3001 Master
    2219 SecondaryNameNode
    3211 QuorumPeerMain
    5435 HMaster
    2015 DataNode
    3583 Kafka

### 12. Clickhouse组件部署 ###

rpm安装：

[root@master clickhouse]# rpm -ivh clickhouse-common-static-dbg-21.9.4.35-2.x86_64.rpm
    警告：clickhouse-common-static-dbg-21.9.4.35-2.x86_64.rpm: 头V4 RSA/SHA1 Signature, 密钥 ID e0c56bd4: NOKEY
    准备中...                          ################################# [100%]
    正在升级/安装...
       1:clickhouse-common-static-dbg-21.9################################# [100%]
    [root@master clickhouse]# rpm -ivh clickhouse-common-static-21.9.4.35-2.x86_64.rpm
    警告：clickhouse-common-static-21.9.4.35-2.x86_64.rpm: 头V4 RSA/SHA1 Signature, 密钥 ID e0c56bd4: NOKEY
    准备中...                          ################################# [100%]
    正在升级/安装...
       1:clickhouse-common-static-21.9.4.3################################# [100%]
    [root@master clickhouse]# rpm -ivh clickhouse-server-21.9.4.35-2.noarch.rpm
    警告：clickhouse-server-21.9.4.35-2.noarch.rpm: 头V4 RSA/SHA1 Signature, 密钥 ID e0c56bd4: NOKEY
    准备中...                          ################################# [100%]
    正在升级/安装...
       1:clickhouse-server-21.9.4.35-2    ################################# [100%]
    ClickHouse binary is already located at /usr/bin/clickhouse
    Symlink /usr/bin/clickhouse-server already exists but it points to /clickhouse. Will replace the old symlink to /usr/bin/clickhouse.
    Creating symlink /usr/bin/clickhouse-server to /usr/bin/clickhouse.
    Creating symlink /usr/bin/clickhouse-client to /usr/bin/clickhouse.
    Creating symlink /usr/bin/clickhouse-local to /usr/bin/clickhouse.
    Creating symlink /usr/bin/clickhouse-benchmark to /usr/bin/clickhouse.
    Symlink /usr/bin/clickhouse-copier already exists but it points to /clickhouse. Will replace the old symlink to /usr/bin/clickhouse.
    Creating symlink /usr/bin/clickhouse-copier to /usr/bin/clickhouse.
    Creating symlink /usr/bin/clickhouse-obfuscator to /usr/bin/clickhouse.
    Creating symlink /usr/bin/clickhouse-git-import to /usr/bin/clickhouse.
    Creating symlink /usr/bin/clickhouse-compressor to /usr/bin/clickhouse.
    Creating symlink /usr/bin/clickhouse-format to /usr/bin/clickhouse.
    Symlink /usr/bin/clickhouse-extract-from-config already exists but it points to /clickhouse. Will replace the old symlink to /usr/bin/clickhouse.
    Creating symlink /usr/bin/clickhouse-extract-from-config to /usr/bin/clickhouse.
    Creating clickhouse group if it does not exist.
     groupadd -r clickhouse
    Creating clickhouse user if it does not exist.
     useradd -r --shell /bin/false --home-dir /nonexistent -g clickhouse clickhouse
    Will set ulimits for clickhouse user in /etc/security/limits.d/clickhouse.conf.
    Creating config directory /etc/clickhouse-server/config.d that is used for tweaks of main server configuration.
    Creating config directory /etc/clickhouse-server/users.d that is used for tweaks of users configuration.
    Config file /etc/clickhouse-server/config.xml already exists, will keep it and extract path info from it.
    /etc/clickhouse-server/config.xml has /var/lib/clickhouse/ as data path.
    /etc/clickhouse-server/config.xml has /var/log/clickhouse-server/ as log path.
    Users config file /etc/clickhouse-server/users.xml already exists, will keep it and extract users info from it.
     chown --recursive clickhouse:clickhouse '/etc/clickhouse-server'
    Creating log directory /var/log/clickhouse-server/.
    Creating data directory /var/lib/clickhouse/.
    Creating pid directory /var/run/clickhouse-server.
     chown --recursive clickhouse:clickhouse '/var/log/clickhouse-server/'
     chown --recursive clickhouse:clickhouse '/var/run/clickhouse-server'
     chown clickhouse:clickhouse '/var/lib/clickhouse/'
     groupadd -r clickhouse-bridge
     useradd -r --shell /bin/false --home-dir /nonexistent -g clickhouse-bridge clickhouse-bridge
     chown --recursive clickhouse-bridge:clickhouse-bridge '/usr/bin/clickhouse-odbc-bridge'
     chown --recursive clickhouse-bridge:clickhouse-bridge '/usr/bin/clickhouse-library-bridge'
    Enter password for default user: 
    Password for default user is saved in file /etc/clickhouse-server/users.d/default-password.xml.
    Setting capabilities for clickhouse binary. This is optional.
    
    ClickHouse has been successfully installed.
    
    Start clickhouse-server with:
     sudo clickhouse start
    
    Start clickhouse-client with:
     clickhouse-client --password
    
    Created symlink from /etc/systemd/system/multi-user.target.wants/clickhouse-server.service to /etc/systemd/system/clickhouse-server.service.
    [root@master clickhouse]# ls
    clickhouse-client-21.9.4.35-2.noarch.rpm         clickhouse-common-static-dbg-21.9.4.35-2.x86_64.rpm
    clickhouse-common-static-21.9.4.35-2.x86_64.rpm  clickhouse-server-21.9.4.35-2.noarch.rpm
    [root@master clickhouse]# rpm -ivh clickhouse-client-21.9.4.35-2.noarch.rpm
    警告：clickhouse-client-21.9.4.35-2.noarch.rpm: 头V4 RSA/SHA1 Signature, 密钥 ID e0c56bd4: NOKEY
    准备中...                          ################################# [100%]
    正在升级/安装...
       1:clickhouse-client-21.9.4.35-2    ################################# [100%]
    [root@master clickhouse]#

修改配置文件：

[root@master module]# vi /etc/clickhouse-server/config.xml
    <log>/data/clickhouse/log/clickhouse-server/clickhouse-server.log</log>
    
    <errorlog>/data/clickhouse/log/clickhouse-server/clickhouse-server.err.log</errorlog>
    
    <path>/data/clickhouse/</path>
    
    
    <tmp_path>/data/clickhouse/tmp/</tmp_path>
    
    
    <user_files_path>/data/clickhouse/user_files/</user_files_path>

启动 ClickServer 前台启动：

clickhouse-server --config-file=/etc/clickhouse-server/config.xml
    查看启动后的进程：ps -aux | grep click

后台启动：

nohup clickhouse-server --config-file=/etc/clickhouse-server/config.xml >null 2>&1 &

使用 client 连接server

clickhouse-client

## 二、数据抽取 ##

### 2.1 实时数据抽取 ###

#### 2.1.1 Maxwell数据抽取 ####

修改Maxwell配置文件config.peoperties

[root@master ~]# cd /opt/module/maxwell/
    [root@master maxwell]# ls
    bin                                          LICENSE
    config.md                                    log4j2.xml
    config.properties.example                    quickstart.md
    kinesis-producer-library.properties.example  README.md
    lib
    [root@master maxwell]# cp config.properties.example config.properties
    [root@master maxwell]# vim config.properties

修改内容:

log_level=info
    
    producer=kafka
    kafka.bootstrap.servers=master:9092,slave1:9092
    kafka_topic=maxwell
    
    # mysql login info
    host=master
    user=maxwell
    password=maxwell
    jdbc_options=useSSL=false&serverTimezone=Asia/Shanghai

启动maxwell:

[root@master maxwell]# /opt/module/maxwell/bin/maxwell --config /opt/module/maxwell/config.properties --daemon
    Redirecting STDOUT to /opt/module/maxwell/bin/../logs/MaxwellDaemon.out
    Using kafka version: 1.0.0
    [root@master maxwell]#

在kafka中创建topic:

[root@master maxwell]# kafka-topics.sh --bootstrap-server master:9092 --partitions 1 --replication-factor 1 --create -topic maxwell
    Created topic maxwell.
    [root@master maxwell]#

启动kafka console consumer消费数据:

[root@master maxwell]# 
    [root@master conf]# kafka-console-consumer.sh --bootstrap-server master:9092 --topic maxwell

在mysql中执行source命令,往数据库中添加数据:

结果(kafka的console consumer消费到MySQL数据库中导入的数据)

{"database":"ds_pub","table":"base_province","type":"insert","ts":1668443406,"xid":1326,"xoffset":15,"data":{"id":17,"name":"辽宁","region_id":"3","area_code":"210000","iso_code":"CN-21"}}
    {"database":"ds_pub","table":"base_province","type":"insert","ts":1668443406,"xid":1326,"xoffset":16,"data":{"id":18,"name":"陕西","region_id":"7","area_code":"610000","iso_code":"CN-61"}}
    {"database":"ds_pub","table":"base_province","type":"insert","ts":1668443406,"xid":1326,"xoffset":17,"data":{"id":19,"name":"甘肃","region_id":"7","area_code":"620000","iso_code":"CN-62"}}
    {"database":"ds_pub","table":"base_province","type":"insert","ts":1668443406,"xid":1326,"xoffset":18,"data":{"id":20,"name":"青海","region_id":"7","area_code":"630000","iso_code":"CN-63"}}
    {"database":"ds_pub","table":"base_province","type":"insert","ts":1668443406,"xid":1326,"xoffset":19,"data":{"id":21,"name":"宁夏","region_id":"7","area_code":"640000","iso_code":"CN-64"}}
    {"database":"ds_pub","table":"base_province","type":"insert","ts":1668443406,"xid":1326,"xoffset":20,"data":{"id":22,"name":"新疆","region_id":"7","area_code":"650000","iso_code":"CN-65"}}
    {"database":"ds_pub","table":"base_province","type":"insert","ts":1668443406,"xid":1326,"xoffset":21,"data":{"id":23,"name":"河南","region_id":"4","area_code":"410000","iso_code":"CN-41"}}
    {"database":"ds_pub","table":"base_province","type":"insert","ts":1668443406,"xid":1326,"xoffset":22,"data":{"id":24,"name":"湖北","region_id":"4","area_code":"420000","iso_code":"CN-42"}}
    {"database":"ds_pub","table":"base_province","type":"insert","ts":1668443406,"xid":1326,"xoffset":23,"data":{"id":25,"name":"湖南","region_id":"4","area_code":"430000","iso_code":"CN-43"}}
    {"database":"ds_pub","table":"base_province","type":"insert","ts":1668443406,"xid":1326,"xoffset":24,"data":{"id":26,"name":"广东","region_id":"5","area_code":"440000","iso_code":"CN-44"}}

#### 2.1.2 端口日志数据抽取 ####

编写Flume.conf配置文件,配置要采集的端口

[root@master conf]# vim /opt/module/flume/conf/read_socket_write_kafka.conf(出现错误问题)
    
    [root@master ~]# cd /opt/flume/conf
    [root@master conf]# ls
    flume-conf.properties.template  flume-env.sh.template  read_socket_write_kafka.conf（出现错误问题）
    flume-env.ps1.template          log4j.properties       socket_to_kafka.conf
    [root@master conf]# vim socket_to_kafka.conf

文件内容:

# # 命名这个代理上的组件
    a1.sources = r1
    a1.sinks = k1
    a1.channels = c1
    #
    #描述/配置源
    a1.sources.r1.type = exec
    a1.sources.r1.command = nc master 26001
    #
    # # 描述接收器
    a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
    a1.sinks.k1.kafka.bootstrap.servers = master:9092
    a1.sinks.k1.kafka.topic = order
    a1.sinks.k1.kafka.producer.acks = 1
    a1.sinks.k1.kafka.acks = 1
    # 使用一个通道缓冲内存中的事件
    a1.channels.c1.type = memory
    a1.channels.c1.capacity = 1000
    a1.channels.c1.transactionCapacity = 100
    # 将source和sink绑定到通道
    a1.sources.r1.channels = c1
    a1.sinks.k1.channel = c1

启动flume采集端口日志: ------第二个master

[root@master conf]# flume-ng agent --name a1 --conf /opt/module/flume/conf/ --conf-file /opt/module/flume/conf/read_socket_write_kafka.conf -Dflume.root.logger=INFO,console
    
    flume-ng agent --name a1 --conf /opt/flume/conf/ --conf-file /opt/flume/conf/socket_to_kafka.conf-Dflume.root.logger=INFO,console

在kafka中创建topic: -----之前创建好

[root@master ~]# kafka-topics.sh --bootstrap-server master:9092 --partitions 1 --replication-factor 1 --create -topic order
    Created topic order.
    [root@master ~]#

开启kafka的console consumer:在命令行消费数据 -----第三个master可直接出现数据

[root@master ~]# kafka-console-consumer.sh --bootstrap-server master:9092,slave1:9092,slave2:9092 --from-beginning --topic order

开启日志端口脚本,往端口实时生成数据: - ----第一个master

[root@master ~]# cd /opt/data/
    [root@master data]# ls
    ds_pub.sql  order.sh  order.txt
    [root@master data]# ll -a
    total 304
    drwxr-xr-x  2 root root     57 Nov 15 00:53 .
    drwxr-xr-x. 5 root root     49 Nov 15 00:52 ..
    -rw-r--r--  1 root root 187698 Nov 15 00:53 ds_pub.sql
    -rw-r--r--  1 root root     72 Nov 15 00:52 order.sh
    -rw-r--r--  1 root root 115027 Nov 15 00:53 order.txt
    [root@master data]# chmod -R 777 /opt/data/
    [root@master data]# sh order.sh | nc -lk 26001

结果:

nc master 26001

D,"8815","3632","14","Dior迪奥口红唇膏送女友老婆礼物生日礼物 烈艳蓝金999+888两支装礼盒","http://kAXllAQEzJWHwiExxVmyJIABfXyzbKwedeofMqwh","496","2","2020-4-26 18:55:16","2402","56"
    I,
    D,"8816","3633","14","Dior迪奥口红唇膏送女友老婆礼物生日礼物 烈艳蓝金999+888两支装礼盒","http://kAXllAQEzJWHwiExxVmyJIABfXyzbKwedeofMqwh","496","1","2020-4-26 18:55:16","2401",
    I,
    D,"8817","3634","12","联想(Lenovo)拯救者Y7000 英特尔酷睿i7 2019新款 15.6英寸发烧游戏本笔记本电脑（i7-9750H 8GB 512GB SSD GTX1650 4G 高色域","http://kAXllAQEzJWHwiExxVmyJIABfXyzbKwedeofMqwh","6699","2","2020-4-26 18:55:16","2401",
    I,
    D,"8818","3635","4","小米Play 流光渐变AI双摄 4GB+64GB 梦幻蓝 全网通4G 双卡双待 小水滴全面屏拍照游戏智能手机","http://SXlkutIjYpDWWTEpNUiisnlsevOHVElrdngQLgyZ","1442","1","2020-4-26 18:55:16","2402","33"
    I,
    D,"8819","3636","3","小米（MI）电视 55英寸曲面4K智能WiFi网络液晶电视机4S L55M5-AQ 小米电视4S 55英寸 曲面","http://LzpblavcZQeYEbwbSjsnmsgAjtpudhDradqsRgdZ","3100","3","2020-4-26 18:55:16","2401",
    I,
    D,"8820","3637","15","迪奥（Dior）烈艳蓝金唇膏 口红 3.5g 999号 哑光-经典正红","http://kAXllAQEzJWHwiExxVmyJIABfXyzbKwedeofMqwh","252","2","2020-4-26 18:55:16","2401",

reboot new 重启

15日上9点30分完成 从10开始即可

### 2. 离线数据抽取 ###

教程参考：

hive(19-86)：[尚硅谷大数据Hive教程（基于hive3.x丨hive3.1.2）\_哔哩哔哩\_bilibili][Hive_hive3.x_hive3.1.2_bilibili]

sparkSQL(153-184):[尚硅谷大数据Spark教程从入门到精通\_哔哩哔哩\_bilibili][Spark_bilibili]

从mysql抽取数据到hive，使用的是spark，spark的开发工具是idea

在idea创建maven项目：

根据情况设置：maven的阿里云的源，加快maven的下载速度：

在idea项目中打开maven的settings.xml文件：

在settings.xml内部增加下面选项：

<mirror>
            <id>nexus-aliyun</id>
            <mirrorOf>central</mirrorOf>
            <name>Nexus aliyun</name>
            <url>http://maven.aliyun.com/nexus/content/groups/public</url>
        </mirror>

如果没有settings.xml文件，可以自己新建，并写入以下配置：

<mirrors>
        
         <mirror>
            <id>nexus-aliyun</id>
            <mirrorOf>central</mirrorOf>
            <name>Nexus aliyun</name>
            <url>http://maven.aliyun.com/nexus/content/groups/public</url>
        </mirror>
    
      </mirrors>

创建完成项目后，配置项目的pom文件：

<properties>
            <scala.version>2.12</scala.version>
            <mysqlconnect.version>5.1.47</mysqlconnect.version>
            <spark.version>3.1.1</spark.version>
            <hive.version>2.3.6</hive.version>
        </properties>
    
        <dependencies>
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-core_${scala.version}</artifactId>
                <version>${spark.version}</version>
            </dependency>
    
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-sql_${scala.version}</artifactId>
                <version>${spark.version}</version>
            </dependency>
    
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-hive_${scala.version}</artifactId>
                <version>${spark.version}</version>
            </dependency>
    
            <dependency>
                <groupId>mysql</groupId>
                <artifactId>mysql-connector-java</artifactId>
                <version>${mysqlconnect.version}</version>
            </dependency>
    
            <dependency>
                <groupId>org.apache.hive</groupId>
                <artifactId>hive-exec</artifactId>
                <version>2.3.7</version>
            </dependency>
    
        </dependencies>

将hive的hive-site.xml文件拷贝到项目的resources目录下：

如果hadoop的windos项目未配置，需要配置hadoop的windows相关内容：

参考：[Windows配置本地Hadoop运行环境 - 走看看][Windows_Hadoop_ -]

配置完成以后，开始spark项目相关编写：

在scala目录下创建edu.jl.ods package， 在edu.jl.ods中创建hello.scala文件，

在文件中选择scala版本，如果没有的话在idea的plugins下安装scala的插件：

在hello.scala中写入以下内容，测试scala环境是否能正常运行：

package edu.jl.ods
    
    object hello {
      def main(args: Array[String]): Unit = {
        println("hello")
      }
    }

运行结果：

如果scala版本有误，可以在项目的structure配置中重新选择scala版本：

spark读取MySQL数据库ds\_pub,表order\_info;

在edu.jl.ods中创建SparkReadMySQL：

在文件内写入以下代码：

package edu.jl.ods
    
    import org.apache.spark.sql.SparkSession
    
    import java.util.Properties
    
    object SparkReadMySQL {
    
      def main(args: Array[String]): Unit = {
    
        // 构建sparkSession
        val sparkSession: SparkSession = SparkSession.builder()
          .master("local[*]")
          .appName("SparkReadMySQL")
          .getOrCreate()
    
        // 设置连接mysql相关配置
        val MYSQLDBURL:String = "jdbc:mysql://192.168.1.100:3306/ds_pub?useUnicode=true&characterEncoding=utf-8&useSSL=false"
    
        val properties = new Properties()
        properties.setProperty("user","root")
        properties.setProperty("password","123456")
        properties.setProperty("driver","com.mysql.jdbc.Driver")
    
        sparkSession.read.jdbc(MYSQLDBURL,"order_info",properties).createTempView("order_info")
    
        val selectId = "select id,consignee from order_info"
    
        sparkSession.sql(selectId).show()
    
      }
    
    }

spark读取mysql并写入hive：

在edu.jl.ods中创建SparkReadMySQLToHive.scala：

package edu.jl.ods
    
    import org.apache.spark.sql.SparkSession
    
    import java.util.Properties
    
    object SparkReadMySQLtoHive {
    
      def main(args: Array[String]): Unit = {
    
        // 设置hadoop的用户名为root
        System.setProperty("HADOOP_USER_NAME","root")
    
        // 构建sparkSession
        val sparkSession: SparkSession = SparkSession.builder()
          .master("local[*]")
          .config("spark.sql.warehouse.dir", "hdfs://192.168.1.100:9000/user/hive/warehouse/")
          .appName("SparkReadMySQL")
          .enableHiveSupport()
          .getOrCreate()
    
        // 设置连接mysql相关配置
        val MYSQLDBURL: String = "jdbc:mysql://192.168.1.100:3306/ds_pub?useUnicode=true&characterEncoding=utf-8&useSSL=false"
    
        // MySQL properties配置
        val properties = new Properties()
        properties.setProperty("user", "root")
        properties.setProperty("password", "123456")
        properties.setProperty("driver", "com.mysql.jdbc.Driver")
    
        // spark 读取mysqljdbc配置 读取mysql的 order_info 这个表 并创建临时视图 order_info
        sparkSession.read.jdbc(MYSQLDBURL, "order_info", properties).createTempView("order_info")
    
        // 从视图order_info 中查询数据
        val selectId = "select * from order_info"
    
        // 在hive的ods库中创建order_info表
        val create_order_info: String =
          """create table ods.order_info(
            | id                  int,
            | consignee           string,
            | consignee_tel       string,
            | final_total_amount  string,
            | order_status        string,
            | user_id             string,
            | delivery_address    string,
            | order_comment       string,
            | out_trade_no        string,
            | trade_body          string,
            | create_time         date,
            | operate_time        date,
            | expire_time         date,
            | tracking_no         String,
            | parent_order_id     int,
            | img_url             string,
            | province_id         int,
            | benefit_reduce_amount string,
            | original_total_amount string,
            | feight_fee           string
            |) row format delimited fields terminated by ',' stored as textfile;
            |""".stripMargin
    
        // 将从order_info视图中查到的数据加载到 hive的ods库的order_info表中
        val loadDataToHive: String =
          """
            |insert overwrite ods.order_info
            |select * from order_info
            |""".stripMargin
    
        // 从hive的ods库的order_info 查询数据（验证数据是否写入到hive中了）
        val ods_order_info = "select * from ods.order_info"
    
        // 在sparkSession中执行上面的sql语句
    //    sparkSession.sql(create_order_info).show()
    //    sparkSession.sql("desc ods.order_info").show()
    
        sparkSession.sql(loadDataToHive)
    
        sparkSession.sql("select * from ods.order_info limit 5").show()
    
    //    sparkSession.sql(selectId).show()
    
        // sql运行完毕关闭sparkSession连接
        sparkSession.close()
    
      }
    
    }

写入hive的分区表，分区为昨天的日期：

在edu.jl.ods中创建SparkReadMySQLToHivePartitionTable.scala：

package edu.jl.ods
    
    import org.apache.spark.sql.SparkSession
    
    import java.util.Properties
    
    object SparkReadMySQLtoHivePartitionTable {
    
      def main(args: Array[String]): Unit = {
    
        // 设置hadoop的用户名为root
        System.setProperty("HADOOP_USER_NAME","root")
    
        // 构建sparkSession
        val sparkSession: SparkSession = SparkSession.builder()
          .master("local[*]")
          .config("spark.sql.warehouse.dir", "hdfs://192.168.1.100:9000/user/hive/warehouse/")
          .appName("SparkReadMySQL")
          .enableHiveSupport()
          .getOrCreate()
    
        // 设置连接mysql相关配置
        val MYSQLDBURL: String = "jdbc:mysql://192.168.1.100:3306/ds_pub?useUnicode=true&characterEncoding=utf-8&useSSL=false"
    
        // MySQL properties配置
        val properties = new Properties()
        properties.setProperty("user", "root")
        properties.setProperty("password", "123456")
        properties.setProperty("driver", "com.mysql.jdbc.Driver")
    
        // spark 读取mysqljdbc配置 读取mysql的 order_info 这个表 并创建临时视图 order_info
        sparkSession.read.jdbc(MYSQLDBURL, "order_info", properties).createTempView("order_info")
    
        // 从视图order_info 中查询数据
        val selectId = "select * from order_info"
    
        // 在hive的ods库中创建order_info表
        val create_order_info: String =
          """create table ods.order_info_par(
            | id                  int,
            | consignee           string,
            | consignee_tel       string,
            | final_total_amount  string,
            | order_status        string,
            | user_id             string,
            | delivery_address    string,
            | order_comment       string,
            | out_trade_no        string,
            | trade_body          string,
            | create_time         date,
            | operate_time        date,
            | expire_time         date,
            | tracking_no         String,
            | parent_order_id     int,
            | img_url             string,
            | province_id         int,
            | benefit_reduce_amount string,
            | original_total_amount string,
            | feight_fee           string
            |) partitioned by (etl_date string) row format delimited fields terminated by ',' stored as textfile;
            |""".stripMargin
    
        // 将从order_info视图中查到的数据加载到 hive的ods库的order_info_par表中
        val loadDataToHive: String =
          """
            |insert overwrite ods.order_info_par partition(etl_date="20221114")
            |select * from order_info
            |""".stripMargin
    
        // 从hive的ods库的order_info 查询数据（验证数据是否写入到hive中了）
        val ods_order_info = "select * from ods.order_info_par limit 5"
    
        // 在sparkSession中执行上面的sql语句
    //    sparkSession.sql(create_order_info).show()
    //    sparkSession.sql("desc ods.order_info").show()
    
        sparkSession.sql(loadDataToHive)
    
        sparkSession.sql(ods_order_info).show()
    
    //    sparkSession.sql(selectId).show()
    
        // sql运行完毕关闭sparkSession连接
        sparkSession.close()
    
      }
    
    }

结果查询分区表的分区情况：

hive (ods)> show partitions order_info_par;
    OK
    partition
    etl_date=20221114
    Time taken: 0.048 seconds, Fetched: 1 row(s)
    hive (ods)>

查看分区表的前五行数据：

hive (ods)> select * from order_info_par limit 5;
    OK
    order_info_par.id   order_info_par.consignee    order_info_par.consignee_tel    order_info_par.final_total_amount   order_info_par.order_status order_info_par.user_id  order_info_par.delivery_address order_info_par.order_comment    order_info_par.out_trade_no order_info_par.trade_body   order_info_par.create_time  order_info_par.operate_time order_info_par.expire_time  order_info_par.tracking_no  order_info_par.parent_order_id  order_info_par.img_url  order_info_par.province_id  order_info_par.benefit_reduce_amount    order_info_par.original_total_amount    order_info_par.feight_fee   order_info_par.etl_date
    3443    严致  13207871570 1449.00 1005    2790    第4大街第5号楼4单元464门 描述345855    214537477223728 小米Play 流光渐变AI双摄 4GB+64GB 梦幻蓝 全网通4G 双卡双待 小水滴全面屏拍照游戏智能手机等1件商品 2020-04-25  2020-04-26  2020-04-25  NULL    NULL    http://img.gmall.com/117814.jpg 20  0.00    1442.00 7.00    20221114
    3444    慕容亨 13028730359 17805.00    1005    2015    第9大街第26号楼3单元383门    描述948496    226551358533723 Apple iPhoneXSMax (A2104) 256GB 深空灰色 移动联通电信4G手机 双卡双待等2件商品   2020-04-25  2020-04-26  2020-04-25  NULL    NULL    http://img.gmall.com/353392.jpg 11  0.00    17800.00    5.00    20221114
    3445    姚兰凤 13080315675 16180.00    1005    8263    第5大街第1号楼7单元722门 描述148518    754426449478474 联想(Lenovo)拯救者Y7000 英特尔酷睿i7 2019新款 15.6英寸发烧游戏本笔记本电脑（i7-9750H 8GB 512GB SSD GTX1650 4G 高色域等3件商品   2020-04-25  2020-04-26  2020-04-25  NULLNULL    http://img.gmall.com/478856.jpg 26  3935.00 20097.00    18.00   20221114
    3446    柏锦黛 13487267342 4922.00 1005    7031    第17大街第40号楼2单元564门   描述779464    262955273144195 十月稻田 沁州黄小米 (黄小米 五谷杂粮 山西特产 真空装 大米伴侣 粥米搭档) 2.5kg等4件商品 2020-04-25  2020-04-26  2020-04-25  NULL    NULL    http://img.gmall.com/144444.jpg 30  0.00    4903.00 19.00   20221114
    3447    计娴瑾 13208002474 6665.00 1005    5903    第4大街第25号楼6单元338门    描述396659    689816418657611 荣耀10青春版 幻彩渐变 2400万AI自拍 全网通版4GB+64GB 渐变蓝 移动联通电信4G全面屏手机 双卡双待等3件商品 2020-04-25  2020-04-25  2020-04-25  NULL    NULL    http://img.gmall.com/793265.jpg 29  0.00    6660.00 5.00    20221114
    Time taken: 0.145 seconds, Fetched: 5 row(s)
    hive (ods)>

## 实时数据分析 ##

### 4.1 Linux端环境准备 ###

需要开启端口生成数据,在/opt/data目录下执行端口开启的命令:

[root@master data]# pwd
    /opt/data
    [root@master data]# sh order.sh | nc -lk 26001

如果端口被占用(Ncat: bind to :::26001: Address already in use. QUITTING.),需要通过netstat -ntlp命令查看占用端口的进程号,通过kill -9 加进程号的方式关闭对应进程:

[root@master data]# netstat -ntlp
    [root@master data]# kill -9 xxx

kill掉占用端口的进程后重新启动数据生成脚本:

[root@master data]# sh order.sh | nc -lk 26001

需要配置并启动flume:

[root@master ~]# flume-ng agent --name a1 --conf /opt/module/flume/conf/ --conf-file /opt/module/flume/conf/socket_to_kafka.conf -Dflume.root.logger=INFO,console

socket\_to\_kafka.conf配置内容:

# # 命名这个代理上的组件 
    a1.sources = r1
    a1.sinks = k1
    a1.channels = c1
    
    #描述/配置源 
    a1.sources.r1.type = exec
    a1.sources.r1.command = nc master 26001
    
    # # 描述接收器 
    a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
    a1.sinks.k1.kafka.bootstrap.servers = master:9092
    a1.sinks.k1.kafka.topic = order
    a1.sinks.k1.kafka.producer.acks = 1
    
    # a1.sinks.k1.type = logger
    
    # 使用一个通道缓冲内存中的事件 
    a1.channels.c1.type = memory
    a1.channels.c1.capacity = 1000
    a1.channels.c1.transactionCapacity = 100 
              
    # 将source和sink绑定到通道 
    a1.sources.r1.channels = c1
    a1.sinks.k1.channel = c1

如果flume 在后台仍然运行 可以通过jps查看进程号方式找到进程号 并kill -9 关闭

[root@master conf]# kill -9 12618
    [root@master conf]# jps
    10720 Kafka
    3315 NodeManager
    2901 SecondaryNameNode
    3157 ResourceManager
    11669 ConsoleConsumer
    3688 QuorumPeerMain
    8008 RunJar
    15080 Jps
    2489 NameNode
    2653 DataNode
    11279 ConsoleConsumer
    [1]+  Killed                  flume-ng agent --name a1 --conf /opt/module/flume/conf/ --conf-file /opt/module/flume/conf/socket_to_kafka.conf -Dflume.root.logger=INFO,console  (wd: ~)
    (wd now: /opt/module/flume/conf)
    [root@master conf]#

需要修改kafka配置,并重启kafka:

修改kafka/config/server.properties配置:

[root@master config]# vim /opt/module/kafka/config/server.properties

修改内容:

advertised.listeners=PLAINTEXT://192.168.1.100:9092

重启kafka:

[root@master config]# jps
    10720 Kafka
    15106 Application
    3315 NodeManager
    2901 SecondaryNameNode
    3157 ResourceManager
    11669 ConsoleConsumer
    3688 QuorumPeerMain
    8008 RunJar
    2489 NameNode
    15370 Jps
    2653 DataNode
    11279 ConsoleConsumer
    [root@master config]# kill -9 10720
    [root@master config]# /opt/module/kafka/bin/kafka-server-start.sh -daemon /opt/module/kafka/config/server.properties

注:三台linux都要执行上述操作;

在master节点开启kafka-console-consumer.sh接收数据,验证配置是否成功:

[root@master config]# kafka-console-consumer.sh --bootstrap-server master:9092,slave1:9092,slave2:9092 --topic order
    I,"3578","张娣","13586813843","26718","1005","8708","第12大街第14号楼3单元391门","描述732297","347956132393657","Apple iPhoneXSMax (A2104) 256GB 深空灰色 移动联通电信4G手机 双卡双待等3件商品","2020-4-26 18:55:01","2020-4-26 18:59:01","2020-4-26 19:10:01",,,"http://img.gmall.com/991685.jpg","21","0","26700","18"
    D,"8756","3573","1","荣耀10青春版 幻彩渐变 2400万AI自拍 全网通版4GB+64GB 渐变蓝 移动联通电信4G全面屏手机 双卡双待","http://AOvKmfRQEBRJJllwCwCuptVAOtBBcIjWeJRsmhbJ","2220","3","2020-4-26 18:55:01","2401",
    I,"3579","伏彩春","13316165573","7374","1005","1515","第16大街第14号楼7单元619门","描述349867","152178625166735","荣耀10 GT游戏加速 AIS手持夜景 6GB+64GB 幻影蓝全网通 移动联通电信等3件商品","2020-4-26 18:55:01","2020-4-26 19:03:49","2020-4-26 19:10:01",,,"http://img.gmall.com/648845.jpg","15","0","7356","18"

### 4.2 Windows端环境准备 ###

创建Flink实时数据分析的项目:

在项目中引入Flink开发所需的pom依赖:

<properties>
            <flink.version>1.14.0</flink.version>
            <scala.version>2.12</scala.version>
            <hive.version>2.3.7</hive.version>
            <mysqlconnect.version>5.1.47</mysqlconnect.version>
            
            <spark.version>3.0.0</spark.version>
        </properties>
    
        <dependencies>
    
    
    
    
    
    
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-runtime-web_2.12</artifactId>
                <version>${flink.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-clients_2.12</artifactId>
                <version>${flink.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-streaming-scala_2.12</artifactId>
                <version>${flink.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-connector-kafka_2.12</artifactId>
                <version>${flink.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-table-planner_2.12</artifactId>
                <version>${flink.version}</version>
            </dependency>
    
    
    
    
    
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-table-api-scala-bridge_2.12</artifactId>
                <version>${flink.version}</version>
                
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-table-common</artifactId>
                <version>${flink.version}</version>
                <type>pom</type>
            </dependency>
    
    
    
    
    
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-csv</artifactId>
                <version>${flink.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.bahir</groupId>
                <artifactId>flink-connector-redis_2.12</artifactId>
                <version>1.1.0</version>
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-avro</artifactId>
                <version>${flink.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-connector-filesystem_2.12</artifactId>
                <version>1.10.2</version>
            </dependency>
    
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-table-planner-blink_2.12</artifactId>
                <version>1.10.2</version>
            </dependency>
    
            <dependency>
                <groupId>org.apache.hive</groupId>
                <artifactId>hive-exec</artifactId>
                <version>${hive.version}</version>
                <scope>provided</scope>
            </dependency>
    
            <dependency>
                <groupId>mysql</groupId>
                <artifactId>mysql-connector-java</artifactId>
                <version>${mysqlconnect.version}</version>
            </dependency>
    
            
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-core_${scala.version}</artifactId>
                <version>${spark.version}</version>
            </dependency>
    
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-sql_${scala.version}</artifactId>
                <version>${spark.version}</version>
            </dependency>
    
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-mllib_${scala.version}</artifactId>
                <version>${spark.version}</version>
            </dependency>
    
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-hive_${scala.version}</artifactId>
                <version>${spark.version}</version>
            </dependency>
    
            <dependency>
                <groupId>org.apache.logging.log4j</groupId>
                <artifactId>log4j-core</artifactId>
                <version>2.8.2</version>
            </dependency>
    
            
            <dependency>
                <groupId>org.dom4j</groupId>
                <artifactId>dom4j</artifactId>
                <version>2.1.3</version>
            </dependency>
    
        </dependencies>
    
        <build>
            
            <resources>
                <resource>
                    <directory>src/main/scala</directory>
                </resource>
                <resource>
                    <directory>src/main/java</directory>
                </resource>
            </resources>
            <plugins>
                <plugin>
                    <groupId>net.alchim31.maven</groupId>
                    <artifactId>scala-maven-plugin</artifactId>
                    <version>3.2.2</version>
                    <configuration>
                        <recompileMode>incremental</recompileMode>
                    </configuration>
                    <executions>
                        <execution>
                            <goals>
                                <goal>compile</goal>
                                <goal>testCompile</goal>
                            </goals>
                        </execution>
                    </executions>
                </plugin>
                <plugin>
                    <groupId>org.apache.maven.plugins</groupId>
                    <artifactId>maven-compiler-plugin</artifactId>
                    <configuration>
                        <source>8</source>
                        <target>8</target>
                    </configuration>
                </plugin>
            </plugins>
        </build>

导包异常可以检查maven中是否有对应的jar包,如果确认有的话可以换一下maven配置

在windows关闭防火墙(防止端口数据被防火墙拦截)

### 4.3 实时数据分析代码开发 ###

参考教程（1-114）：[【尚硅谷】Flink1.13教程（Scala版）\_哔哩哔哩\_bilibili][Flink1.13_Scala_bilibili]

创建package edu.jl,并在package下创建Hello.scala:

在hello.scala中设置scala的sdk:

package edu.jl
    
    object hello {
      def main(args: Array[String]): Unit = {
        println("hello")
      }
    }

执行hello,确认scala环境是可用的

在edu.jl下创建readKafka.scala:

在readKafka.scala中写入:

package edu.jl
    
    import org.apache.flink.api.common.serialization.SimpleStringSchema
    import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
    import org.apache.flink.streaming.api.scala._
    import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer
    
    import java.util.Properties
    
    
    object readKafka {
    
      def main(args: Array[String]): Unit = {
        // 获取flink流式执行环境
        val env: StreamExecutionEnvironment = StreamExecutionEnvironment.getExecutionEnvironment
        env.setParallelism(1) // 设置代码并行度为1
    
        //设置kafka的properties
        val properties = new Properties()
        properties.setProperty("bootstrap.servers","192.168.1.100:9092")
    
        // 设置Flink的数据源为kafka,创建数据流
        val ds: DataStream[String] = env.addSource(new FlinkKafkaConsumer[String]("order", new SimpleStringSchema(), properties).setStartFromLatest())
    
        // 打印从kafka获取到的数据
        ds.print()
    
        // 执行流式环境
        env.execute()
      }
    }

重启端口和flume后,运行代码文件,结果从idea的输出框中可以看到信息,证明windows的flink代码环境可以消费到数据:

### 4.4 统计SKU商品的总额,将值存入Redis ###

启动redis:

[root@master ~]# redis-server /root/my_redis.conf

创建readKafkaToRedis.scala文件,并在文件内写入:

package edu.jl
    
    import org.apache.flink.api.common.serialization.SimpleStringSchema
    import org.apache.flink.streaming.api.scala.{StreamExecutionEnvironment, _}
    import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer
    import org.apache.flink.streaming.connectors.redis.RedisSink
    import org.apache.flink.streaming.connectors.redis.common.config.FlinkJedisPoolConfig
    import org.apache.flink.streaming.connectors.redis.common.mapper.{RedisCommand, RedisCommandDescription, RedisMapper}
    
    import java.util.Properties
    
    
    object readKafkaToRedis {
    
      def main(args: Array[String]): Unit = {
        // 获取flink流式执行环境
        val env: StreamExecutionEnvironment = StreamExecutionEnvironment.getExecutionEnvironment
        env.setParallelism(1) // 设置代码并行度为1
    
        //设置kafka的properties
        val properties = new Properties()
        properties.setProperty("bootstrap.servers","192.168.1.100:9092")
    
        // 设置Flink的数据源为kafka,创建数据流
        val ds: DataStream[String] = env.addSource(new FlinkKafkaConsumer[String]("order", new SimpleStringSchema(), properties).setStartFromLatest())
    
        // 过滤掉表头的数据 生成新的数据流filter_ds
        val filter_ds: DataStream[String] = ds.filter(!_.split(",")(1).equals("\"id\""))
    
        // 从filter_ds中提取出需要分析的数据
        // 取出 sku_id相同的 sku_price 的和
        val map_ds = filter_ds.map(line => {
          val words: Array[String] = line.split(",")
          val dat: String = words(0)
    
          if (dat.trim == "D") {
            val sku_price: Double = words(6).split('"')(1).toDouble
            val sku_id: String = words(3).split('"')(1)
            (sku_id, sku_price)
          } else {
            ("报错", 1.0)
          }
        }).keyBy(_._1).sum(1)
    
        map_ds.print()
        map_ds.addSink(new RedisSink[(String, Double)](flinkJedisPoolConfig,new MyRedisMapper))
    
        // 执行流式环境
        env.execute()
      }
      class MyRedisMapper extends RedisMapper[Tuple2[String,Double]] {
    
        // 定义保存数据到redis的命令，HSET 表名 key value
        override def getCommandDescription: RedisCommandDescription = new RedisCommandDescription(RedisCommand.SET)
    
        // 将id转换为key
        override def getKeyFromData(t: (String, Double)): String = t._1
    
        // 将price值指定为value
        override def getValueFromData(t: (String, Double)): String = t._2.toString
    
      }
    
      private val flinkJedisPoolConfig: FlinkJedisPoolConfig = new FlinkJedisPoolConfig.Builder()
        .setHost("192.168.1.100")
        .setPort(6379)
        .build()
    }

代码运行结果：

在Redis中查询(获取所有的key `keys 星号`，获取具体的值 `get key`)：

keys * // 获取所有的key
    get key // 获取对应key的值
    例如
    192.168.1.100:6379> get 4
    "1442.0"

结果

192.168.1.100:6379> keys *
     1) "10"
     2) "\"11\""
     3) "\"6\""
     4) "\"14\""
     5) "6"
     6) "\"7\""
     7) "\"4\""
     8) "\"8\""
     9) "\"15\""
    10) "\"13\""
    11) "\"12\""
    12) "\"9\""
    13) "\"2\""
    14) "\"1\""
    15) "\"5\""
    16) "15"
    17) "\"16\""
    18) "\"10\""
    19) "\xe6\x8a\xa5\xe9\x94\x99"
    20) "14"
    21) "3"
    192.168.1.100:6379> get 3
    "3100.0"
    192.168.1.100:6379> get 14
    "496.0"
    192.168.1.100:6379> get 4
    "1442.0"

--------------------

至此，本篇文章就已经全部结束了，感谢大家的观看。

已许久许久许久……未更新。

忙于考试。

加油加油加油！！！

/(ㄒoㄒ)/~~

--------------------

## **🥇Summary** ##

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> 我非轻舟

> 2024年第二期，继续加油！！！

> **希望大家有好的意见或者建议，欢迎私信，一起加油**

--------------------

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[16df0128c2fc4761be10983e3e8c7ec5.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/28/e02a5cbd9bb84af4900a178a971c0f0b.png
[837b11390fd2464cb748a84aef98ffc4.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/28/a734e6ea69cc41fa97425e72377dae43.png
[http_192.168.1.100_8081_overview]: http://192.168.1.100:8081/#/overview
[20200527215137201.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/28/ca7c8ac3d5be41dfb5f479e40dfcc95e.png
[Hive_hive3.x_hive3.1.2_bilibili]: https://www.bilibili.com/video/BV1EZ4y1G7iL/?spm_id_from=333.337.search-card.all.click&vd_source=83dc0e423b7b1e88bcbfc8517b53b7eb
[Spark_bilibili]: https://www.bilibili.com/video/BV11A411L7CK/?spm_id_from=333.337.search-card.all.click&vd_source=83dc0e423b7b1e88bcbfc8517b53b7eb
[Windows_Hadoop_ -]: http://t.zoukankan.com/Kaivenblog-p-9311328.html
[Flink1.13_Scala_bilibili]: https://www.bilibili.com/video/BV1zr4y157XV/?spm_id_from=333.337.search-card.all.click&vd_source=83dc0e423b7b1e88bcbfc8517b53b7eb