2020系统综合实践

Posted 2021-02-18 ycj202595

使用Docker-compose实现Tomcat+nginx负载均衡

nginx反向代理原理

nginx代理tomcat集群，代理2个以上tomcat；

拉取tomcat镜像

docker-compose.yml

version: "3"
services:
    nginx:
        image: nginx
        container_name: c_nginxtomcat
        ports:
            - 80:2438
        volumes:
            - ./nginx/default.conf:/etc/nginx/conf.d/default.conf # 挂载配置文件
        depends_on:
            - tomcat1
            - tomcat2
            - tomcat3

    tomcat1:
        image: tomcat
        container_name: c_tomcat1   # 容器名,与conf对应
        volumes:
           - ./tomcat1:/usr/local/tomcat/webapps/ROOT

    tomcat2:
        image: tomcat
        container_name: c_tomcat2
        volumes:
           - ./tomcat2:/usr/local/tomcat/webapps/ROOT

    tomcat3:
        image: tomcat
        container_name: c_tomcat3
        volumes:
           - ./tomcat3:/usr/local/tomcat/webapps/ROOT

default.conf

upstream tomcats {
    server c_tomcat1:8080 ; # 容器名，与docker-compose.yml里面相对应
    server c_tomcat2:8080 ;# tomcat默认端口号8080
    server c_tomcat3:8080 ; # 默认使用轮询策略
}

server {
    listen 2438;
    server_name localhost;

    location / {
        proxy_pass http://tomcats; # 请求转向tomcats
    }
}

tomcat1/index.html

tomcat1

tomcat2和tomcat3参照tomcat1
运行docker-compose

docker-compose up -d

刷新浏览器

权重策略测试负载均衡

修改default.conf

upstream tomcats {
    server c_tomcat1:8080 weight=1; # 容器名，与docker-compose.yml里面相对应
    server c_tomcat2:8080 weight=2;# tomcat默认端口号8080
    server c_tomcat3:8080 weight=7; # 使用权重策略
}

server {
    listen 2438;
    server_name localhost;

    location / {
        proxy_pass http://tomcats; # 请求转向tomcats
    }
}

使用Docker-compose部署javaweb运行环境

docker-compose.yml

version: ‘2‘
services:
  tomcat:
    image: tomcat
    hostname: hostname
    container_name: c_tomcat_javaweb
    ports:
     - "5050:8080"
    volumes:
     - "./webapps:/usr/local/tomcat/webapps"
     - ./wait-for-it.sh:/wait-for-it.sh 
    networks:
      webnet:
        ipv4_address: 15.22.0.15
  mysql:
    build: .   #通过MySQL的Dockerfile文件构建MySQL
    image: mysql
    container_name: c_mysql_javaweb
    ports:
      - "3309:3306"
    command: [
            ‘--character-set-server=utf8mb4‘,
            ‘--collation-server=utf8mb4_unicode_ci‘
    ]
    environment:
      MYSQL_ROOT_PASSWORD: "123456"
    networks:
      webnet:
        ipv4_address: 15.22.0.6
  nginx:
    image: nginx
    container_name: c_nginx_javaweb
    ports:
      - "8080:8080"
    volumes:
      - ./default.conf:/etc/nginx/conf.d/default.conf #挂载配置文件
    networks:
     webnet:
       ipv4_address: 15.22.0.7
networks:
 webnet:
   driver: bridge
   ipam:
     config:
       - subnet: 15.22.0.0/24
         gateway: 15.22.0.2

default.conf

upstream tomcat123 {
    server c_tomcat_javaweb:8080;
}

server {
    listen 8080;
    server_name localhost;

    location / {
        proxy_pass http://tomcat123;
    }
}

修改jdbc.properties


运行docker-compose up -d --build后，查看结果

使用Docker搭建大数据集群环境

创建hadoop环境

Dockerfile

source.list

创建并运行容器

sudo docker build -t ubuntu:18.04 .
sudo docker run -it --name ubuntu ubuntu:18.04

容器进行初始化

apt-get update
apt-get install vim # 用于修改配置文件
apt-get install ssh # 分布式hadoop通过ssh连接
vim ~/.bashrc #在该文件中最后一行添加如下内容，实现进入Ubuntu系统时，都能自动启动sshd服务    
/etc/init.d/ssh start  

实现ssh无密码登陆

cd ~/.ssh       
ssh-keygen -t rsa # 一直按回车即可
cat id_rsa.pub >> authorized_keys #这一步要在~/.ssh目录下进行

安装jdk

apt install openjdk-8-jdk
vim ~/.bashrc       # 在文件末尾添加以下两行，配置Java环境变量：
export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64/
export PATH=$PATH:$JAVA_HOME/bin
source ~/.bashrc 
java -version #查看是否安装成功

安装hadoop

docker cp ./build/hadoop-3.1.3.tar.gz 容器ID：/root/build
cd /root/build
tar -zxvf hadoop-3.1.3.tar.gz -C /usr/local
vim ~/.bashrc  
export HADOOP_HOME=/usr/local/hadoop-3.1.3
export CLASSPATH=.:$JAVA_HOME/lib:$JRE_HOME/lib
export PATH=$PATH:$HADOOP_HOME/sbin:$HADOOP_HOME/bin:$JAVA_HOME/bin
source ~/.bashrc # 使.bashrc生效
hadoop version

配置hadoop集群

进入到以下目录

cd /usr/local/hadoop-3.1.3/etc/hadoop

修改hadoop-env.sh

export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64/ # 在任意位置添加

修改core-site.xml

<configuration>
          <property> 
                  <name>hadoop.tmp.dir</name>
                  <value>file:/usr/local/hadoop-3.1.3/tmp</value>
                  <description>Abase for other temporary directories.</description>
          </property>
          <property>
                  <name>fs.defaultFS</name>
                  <value>hdfs://master:9000</value>
          </property>
</configuration>

修改hdfs-site.xml

<configuration>
        <property>
                <name>dfs.replication</name>
                <value>1</value>
        </property>
        <property>
                <name>dfs.namenode.name.dir</name>
		        <value>file:/usr/local/hadoop-3.1.3/tmp/dfs/name</value>
	</property>
	<property>
                <name>dfs.datanode.data.dir</name>
                <value>file:/usr/local/hadoop-3.1.3/tmp/dfs/data</value>
	</property>
	<property>
                <name>dfs.permissions.enabled</name>
                <value>false</value>
        </property>
</configuration>

修改mapred-site.xml

<configuration>
    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
    </property>
    <property>
        <name>yarn.app.mapreduce.am.env</name>
        <value>HADOOP_MAPRED_HOME=/usr/local/hadoop-3.1.3</value>
    </property>
    <property>
        <name>mapreduce.map.env</name>
        <value>HADOOP_MAPRED_HOME=/usr/local/hadoop-3.1.3</value>
    </property>
    <property>
        <name>mapreduce.reduce.env</name>
        <value>HADOOP_MAPRED_HOME=/usr/local/hadoop-3.1.3</value>
    </property>
</configuration>

修改yarn-site.xml

<?xml version="1.0" ?>
<configuration>
<!-- Site specific YARN configuration properties -->
        <property>
               <name>yarn.nodemanager.aux-services</name>
               <value>mapreduce_shuffle</value>
        </property>
        <property>
               <name>yarn.resourcemanager.hostname</name>
               <value>Master</value>
        </property>
        <!--虚拟内存和物理内存比，不加这个模块程序可能跑不起来-->
        <property>
               <name>yarn.nodemanager.vmem-pmem-ratio</name>
               <value>2.5</value>
        </property>
</configuration>

进入脚本目录

cd /usr/local/hadoop-3.1.3/sbin

修改start-dfs.sh和stop-dfs.sh文件，添加下列参数

HDFS_DATANODE_USER=root
HADOOP_SECURE_DN_USER=hdfs
HDFS_NAMENODE_USER=root
HDFS_SECONDARYNAMENODE_USER=root

修改start-yarn.sh和stop-yarn.sh，添加下列参数

YARN_RESOURCEMANAGER_USER=root
HADOOP_SECURE_DN_USER=yarn
YARN_NODEMANAGER_USER=root

构建镜像

docker commit 容器ID ubuntu/hadoop

用构建好的镜像运行主机,分别在三个终端运行如下命令

# 第一个终端
docker run -it -h master --name master ubuntu/hadoop
# 第二个终端
docker run -it -h slave01 --name slave01 ubuntu/hadoop
# 第三个终端
docker run -it -h slave02 --name slave02 ubuntu/hadoop

三个终端分别打开/etc/hosts,根据各自ip修改为如下

172.17.0.3      master
172.17.0.4      slave01
172.17.0.5      slave02

master结点测试链接slave

ssh slave01
ssh slave02
exit #退出

master主机上修改workers

vim /usr/local/hadoop-3.1.3/etc/hadoop/workers
slave01
slave02

测试Hadoop集群

#在master上操作
cd /usr/local/hadoop-3.1.3
bin/hdfs namenode -format      #首次启动Hadoop需要格式化
sbin/start-all.sh              #启动所有服务
jps                            #分别查看三个终端

运行Hadoop实例

bin/hdfs dfs -mkdir -p /user/hadoop/input
bin/hdfs dfs -put ./etc/hadoop/*.xml /user/hadoop/input
bin/hdfs dfs -ls /user/hadoop/input
bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-3.1.3.jar grep /user/hadoop/input output ‘dfs[a-z.]+‘
bin/hdfs dfs -cat output/*

总结

遇到问题

解决方法：
第一次用192.168.17.130，出现上述问题；第二次改用192.168.17.2，直接无法访问；第三次问了同学，他说让我换回192.168.17.130，再试一次，结果可以了。。。。我人傻了，这是靠运气做实验吗。
用时
学习4h+做实验6h+写博客1h