一、安装Docker Hadoop3.X分布式集群

1、机器环境

这里采用三台机器来部署分布式集群环境：

192.168.1.101 hadoop1 （docker管理节点）

192.168.1.102 hadoop2

192.168.1.103 hadoop3

2、下载Docker Hadoop的配置文件

地址： https://github.com/big-data-europe/docker-hadoop/tree/2.0.0-hadoop3.1.3-java8

根据需要切换分支选择版本，这里选择hadoop3.1.3版本。

3、安装Docker

自行参考之前教程，这里安装版本为docker-ce-3:20.10.8-3.el7.x86_64

4、系统配置

# 关闭防火墙
systemctl stop firewalld
# 永久关闭
systemctl disable firewalld
# 重启docker（更改网络环境需要重启）
systemctl restart docker

5、安装Docker Compose

# 下载配置Compose
curl -SL https://github.com/docker/compose/releases/download/1.29.0/docker-compose-linux-x86_64 -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose
# 查看版本
[root@localhost ~]# docker-compose  version
docker-compose version 1.29.0, build 07737305
docker-py version: 5.0.0
CPython version: 3.7.10
OpenSSL version: OpenSSL 1.1.0l  10 Sep 2019

6、拉取相关镜像

1）拉取hadoop的镜像

# 解压docker-hadoop-2.0.0-hadoop3.1.3-java8
tar -xvf docker-hadoop-2.0.0-hadoop3.1.3-java8.zip
# 运行docker-compose脚本， 拉取hadoop相关的镜像
docker-compose up

成功之后可以看到相关的容器实例：

运行完成后，删除容器实例：

docker rm $(docker ps -aq)

删除磁盘卷：

docker volume rm $(docker volume ls |awk '{print $2}')

删除网络：

docker network rm docker-hadoop-200-hadoop313-java8_default

2）拉取traefik镜像

traefik是一款网络工具，能够实现容器内部的反向代理与负载均衡

docker pull traefik:2.9.10

3）拉取zookeeper镜像

docker pull zookeeper:3.4.10

以上步骤，三台机器都分别执行，确保docker环境与镜像都已经准备好。

7、配置docker swarm环境

在管理节点执行：

[root@hadoop1 ~]# docker swarm init --advertise-addr 192.168.1.101
Swarm initialized: current node (swfdinosstcc5h9k1wkz1bp9l) is now a manager.

To add a worker to this swarm, run the following command:

    docker swarm join --token SWMTKN-1-1xlri07uvjsjscxalipmtcqrfzk6bh9rasrh1mnx0xt2trq20h-6h1szze1p8d7ag6in1ejxc6wi 192.168.1.101:2377

To add a manager to this swarm, run 'docker swarm join-token manager' and follow the instructions.

其他两个节点执行生成join命令，加入swarm管理

加入成功后，检查：

[root@hadoop1 ~]# docker node ls
ID                            HOSTNAME   STATUS    AVAILABILITY   MANAGER STATUS   ENGINE VERSION
swfdinosstcc5h9k1wkz1bp9l *   hadoop1    Ready     Active         Leader           20.10.8
o3v4fekz682vl7whgzov9nybd     hadoop2    Ready     Active                          20.10.8
1cptz9kcz4d65llkq8j7kwrnn     hadoop3    Ready     Active                          20.10.8

8、配置集群网络环境

1) 创建hbase集群内部网络： 
# docker network create --driver overlay --attachable --subnet 10.20.0.0/24 hbase
docker network create -d overlay --attachable hbase
2) 给swarm的子节点增加标签, 标识为数据节点datanode：
# 这里集群配置两个数据节点, 视具体情况配置，在docker compose的yml配置文件中会使用到：
docker node update --label-add hadoop-datanode=datanode hadoop2
docker node update --label-add hadoop-datanode=datanode hadoop3

9、配置Hadoop的docker-compose文件

这里主节点部署一个namenode、resourcemanager和historyserver，两个从节点分各部署一个datanode和nodemanager。

# 修改配置文件名称
mv docker-compose-v3.yml docker-compose-hadoop.yml

进入目录：

cd /usr/local/hadoop-hbase/docker-hadoop-2.0.0-hadoop3.1.3-java8

修改 docker-compose-hadoop.yml的具体配置：

version: '3'

services:
  namenode:
    image: bde2020/hadoop-namenode:2.0.0-hadoop3.1.3-java8
    networks:
      - hbase
    ports:
      - 19870:9870
      - 19000:9000
    volumes:
      - namenode:/hadoop/dfs/name
    environment:
      - CLUSTER_NAME=test
    env_file:
      - ./hadoop.env
    deploy:
      mode: replicated
      replicas: 1
      restart_policy:
        condition: on-failure
        max_attempts: 3
      placement:
        constraints:
          - node.hostname == hadoop1
      labels:
        traefik.docker.network: hbase
        traefik.port: 9870

  datanode:
    image: bde2020/hadoop-datanode:2.0.0-hadoop3.1.3-java8
    networks:
      - hbase
    ports:
      - 19864:9864
    volumes:
      - datanode:/hadoop/dfs/data
    env_file:
      - ./hadoop.env
    environment:
      SERVICE_PRECONDITION: "namenode:9870"
    deploy:
      mode: global
      restart_policy:
        condition: on-failure
        max_attempts: 3
      placement:
        constraints:
          - node.labels.hadoop-datanode == datanode
      labels:
        traefik.docker.network: hbase
        traefik.port: 9864
  resourcemanager:
    image: bde2020/hadoop-resourcemanager:2.0.0-hadoop3.1.3-java8
    networks:
      - hbase
    ports:
      - 18088:8088
    environment:
      SERVICE_PRECONDITION: "namenode:9000 datanode:9864"
    env_file:
      - ./hadoop.env
    deploy:
      mode: replicated
      replicas: 1
      restart_policy:
        condition: on-failure
        max_attempts: 3
      placement:
        constraints:
          - node.hostname == hadoop1
      labels:
        traefik.docker.network: hbase
        traefik.port: 8088
    healthcheck:
      disable: true

  nodemanager:
    image: bde2020/hadoop-nodemanager:2.0.0-hadoop3.1.3-java8
    networks:
      - hbase
    ports:
      - 18042:8042
    environment:
      SERVICE_PRECONDITION: "namenode:9000 datanode:9864 resourcemanager:8088"
    env_file:
      - ./hadoop.env
    deploy:
      mode: global
      restart_policy:
        condition: on-failure
        max_attempts: 3
      placement:
        constraints:
          - node.labels.hadoop-datanode == datanode
      labels:
        traefik.docker.network: hbase
        traefik.port: 8042
  historyserver:
    image: bde2020/hadoop-historyserver:2.0.0-hadoop3.1.3-java8
    networks:
      - hbase
    ports:
      - 18188:8188
    volumes:
      - hadoophistoryserver:/hadoop/yarn/timeline
    environment:
      SERVICE_PRECONDITION: "namenode:9000 datanode:9864 nodemanager:8042 resourcemanager:8088"
    env_file:
      - ./hadoop.env
    deploy:
      mode: replicated
      replicas: 1
      placement:
        constraints:
          - node.hostname == hadoop1
      labels:
        traefik.docker.network: hbase
        traefik.port: 8188

volumes:
  datanode:
  namenode:
  hadoophistoryserver:

networks:
  hbase:
    external:
      name: hbase

10、部署hadoop集群环境

docker stack deploy -c docker-compose-hadoop.yml hadoop

成功启动后，主节点可以看到对应的实例信息：

其他两个节点，可以看到nodemanager与datanode实例：

如果失败，删除重建：

docker stack rm  hadoop

11、访问管理界面

安装成功后，可以通过宿主机的映射端口直接访问：

http://192.168.1.101:19870/

二、安装Docker HBase2.X分布式集群

1、自定义生成Hbase镜像

1) 构建Dockerfile脚本：

进入目录：

mkdir -p /usr/local/hadoop-hbase/docker-hbase-master/hbase_base
cd /usr/local/hadoop-hbase/docker-hbase-master/hbase_base

Dockerfile脚本

FROM debian:9

MAINTAINER Mirson <[email protected]>

RUN echo > /etc/apt/sources.list
RUN echo  "deb http://mirrors.aliyun.com/debian/ stretch main non-free contrib \ndeb-src http://mirrors.aliyun.com/debian/ stretch main non-free contrib \ndeb http://mirrors.aliyun.com/debian-security stretch/updates main \ndeb-src http://mirrors.aliyun.com/debian-security stretch/updates main \ndeb http://mirrors.aliyun.com/debian/ stretch-updates main non-free contrib \ndeb-src http://mirrors.aliyun.com/debian/ stretch-updates main non-free contrib \ndeb http://mirrors.aliyun.com/debian/ stretch-backports main non-free contrib \ndeb-src http://mirrors.aliyun.com/debian/ stretch-backports main non-free contrib" > /etc/apt/sources.list

RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
      openjdk-8-jdk \
      net-tools \
      curl \
      netcat \
      gnupg \
      libtinfo5 \
      vim \
    && rm -rf /var/lib/apt/lists/*

ENV JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64/

ENV HBASE_VERSION 2.3.5
ENV HBASE_URL http://archive.apache.org/dist/hbase/$HBASE_VERSION/hbase-$HBASE_VERSION-bin.tar.gz
RUN set -x \
    && curl -fSL "$HBASE_URL" -o /tmp/hbase.tar.gz \
    && curl -fSL "$HBASE_URL.asc" -o /tmp/hbase.tar.gz.asc \
    && tar -xvf /tmp/hbase.tar.gz -C /opt/ \
    && rm /tmp/hbase.tar.gz*

RUN ln -s /opt/hbase-$HBASE_VERSION/conf /etc/hbase
RUN mkdir /opt/hbase-$HBASE_VERSION/logs
COPY core-site.xml /opt/hbase-$HBASE_VERSION/conf
COPY hdfs-site.xml /opt/hbase-$HBASE_VERSION/conf
RUN mkdir /hadoop-data

ENV HBASE_PREFIX=/opt/hbase-$HBASE_VERSION
ENV HBASE_CONF_DIR=/etc/hbase

ENV USER=root
ENV PATH $HBASE_PREFIX/bin/:$PATH

ADD entrypoint.sh /entrypoint.sh
RUN chmod a+x /entrypoint.sh

EXPOSE 16000 16010 16020 16030

ENTRYPOINT ["/entrypoint.sh"]

将hadoop的配置文件COPY至当前目录下

docker cp b1e6:/opt/hadoop-3.1.3/etc/hadoop/core-site.xml .
docker cp b1e6:/opt/hadoop-3.1.3/etc/hadoop/hdfs-site.xml .

2) 创建entrypoint.sh脚本，用于实现对hbase的参数配置管理

#!/bin/bash

function addProperty() {
  local path=$1
  local name=$2
  local value=$3

  local entry="<property><name>$name</name><value>${value}</value></property>"
  local escapedEntry=$(echo $entry | sed 's/\//\\\//g')
  sed -i "/<\/configuration>/ s/.*/${escapedEntry}\n&/" $path
}

function configure() {
    local path=$1
    local module=$2
    local envPrefix=$3

    local var
    local value

    echo "Configuring $module"
    for c in `printenv | perl -sne 'print "$1 " if m/^${envPrefix}_(.+?)=.*/' -- -envPrefix=$envPrefix`; do
        name=`echo ${c} | perl -pe 's/___/-/g; s/__/_/g; s/_/./g'`
        var="${envPrefix}_${c}"
        value=${!var}
        echo " - Setting $name=$value"
        addProperty /etc/hbase/$module-site.xml $name "$value"
    done
}

configure /etc/hbase/hbase-site.xml hbase HBASE_CONF

function wait_for_it()
{
    local serviceport=$1
    local service=${serviceport%%:*}
    local port=${serviceport#*:}
    local retry_seconds=5
    local max_try=100
    let i=1

    nc -z $service $port
    result=$?

    until [ $result -eq 0 ]; do
      echo "[$i/$max_try] check for ${service}:${port}..."
      echo "[$i/$max_try] ${service}:${port} is not available yet"
      if (( $i == $max_try )); then
        echo "[$i/$max_try] ${service}:${port} is still not available; giving up after ${max_try} tries. :/"
        exit 1
      fi

      echo "[$i/$max_try] try in ${retry_seconds}s once again ..."
      let "i++"
      sleep $retry_seconds

      nc -z $service $port
      result=$?
    done
    echo "[$i/$max_try] $service:${port} is available."
}

for i in "${SERVICE_PRECONDITION[@]}"
do
    wait_for_it ${i}
done

exec $@

3) 构建镜像

进入Dockerfile目录，执行：

docker build -f ./Dockerfile -t  bde2020/hadoop-hmaster:2.0.0-hmaster2.3.5-java8 .

注意后面要有个点号“.”，如果下载hbase包太慢，可以先下载好，再上传

...

ENV HBASE_VERSION 2.3.5
ADD hbase-2.3.5-bin.tar.gz /opt/
RUN ln -s /opt/hbase-$HBASE_VERSION/conf /etc/hbase
...

ADD与COPY命令不同，会自行解压。

4）将生成的镜像同步至其他节点

# 导出镜像
docker save bde2020/hadoop-hmaster:2.0.0-hmaster2.3.5-java8 > hbase_image.tar
# 复制其他节点
scp hbase_image.tar [email protected]:/root
scp hbase_image.tar [email protected]:/root
# 导入镜像
docker load -i hbase_image.tar

2、部署ZooKeeper

这里搭建三个节点的Zookeeper集群。

1) docker-compose-zookeeper集群配置脚本：

version: '3'

services:
  zoo1:
    image: zookeeper:3.4.10
    networks:
      - hbase
    volumes:
      - zoo1_data:/data
    deploy:
      mode: replicated
      replicas: 1
      restart_policy:
        condition: on-failure
      placement:
        constraints:
          - node.hostname == hadoop1
    environment:
      ZOO_MY_ID: 1
      ZOO_SERVERS: server.1=0.0.0.0:2888:3888 server.2=zoo2:2888:3888 server.3=zoo3:2888:3888
  zoo2:
    image: zookeeper:3.4.10
    networks:
      - hbase
    volumes:
      - zoo2_data:/data
    deploy:
      mode: replicated
      replicas: 1
      restart_policy:
        condition: on-failure
      placement:
        constraints:
          - node.hostname == hadoop2
    environment:
      ZOO_MY_ID: 2
      ZOO_SERVERS: server.1=zoo1:2888:3888 server.2=0.0.0.0:2888:3888 server.3=zoo3:2888:3888
  zoo3:
    image: zookeeper:3.4.10
    networks:
      - hbase
    volumes:
      - zoo3_data:/data
    deploy:
      mode: replicated
      replicas: 1
      restart_policy:
        condition: on-failure
      placement:
        constraints:
          - node.hostname == hadoop3
    environment:
      ZOO_MY_ID: 3
      ZOO_SERVERS: server.1=zoo1:2888:3888 server.2=zoo2:2888:3888 server.3=0.0.0.0:2888:3888

volumes:
  zoo1_data:
  zoo2_data:
  zoo3_data:

networks:
  hbase: 
    external: 
      name: hbase

2）部署Zookeeper集群：

docker stack deploy -c docker-compose-zookeeper.yml zookeeper

3) 查看容器

[root@hadoop1 docker-hbase-master]# docker ps -a
CONTAINER ID   IMAGE                                                    COMMAND                   CREATED          STATUS                 PORTS                          NAMES
fe84630dce2d   zookeeper:3.4.10                                         "/docker-entrypoint.…"   48 seconds ago   Up 47 seconds          2181/tcp, 2888/tcp, 3888/tcp   zookeeper_zoo1.1.r98xzm9bklsdau1ydu4eug5d3
...

执行成功，每台节点会新增一个zookeeper的实例。

如果失败，删除重新部署：

docker stack rm zookeeper

3、部署traefik

需安装此组件，用于负责管理hbase内部节点的名称连接。

docker service create --name traefik --constraint node.hostname==hadoop1 --publish 18880:80 --publish 18080:8080 --mount type=bind,source=/var/run/docker.sock,target=/var/run/docker.sock --network hbase traefik --api.insecure=true --providers.docker

成功后可以看到对应服务名：

访问后台管理界面：

4、配置Hbase的docker-compose文件

这里在主节点运行一个HMaster，其余两个节点运行regionserver。

1) docker-compose-hbase.yml配置脚本：

version: '3.2'

services:
  HMaster:
    image: bde2020/hadoop-hmaster:2.0.0-hmaster2.3.5-java8
    networks:
      - hbase
    ports:
      - target: 16000
        published: 16000
        protocol: tcp
        mode: host
      - target: 16010
        published: 16010
        protocol: tcp
        mode: host
    env_file:
      - ./hbase.env
    command:
      - /opt/hbase-2.3.5/bin/hbase master start          
    deploy:
      mode: replicated
      replicas: 1
      endpoint_mode: dnsrr
      restart_policy:
        condition: none
      placement:
        constraints:
          - node.hostname == hadoop1
      labels:
        traefik.docker.network: hbase
        traefik.port: 16010
    

  RegionServer1:
    image: bde2020/hadoop-hmaster:2.0.0-hmaster2.3.5-java8
    networks:
      - hbase
    ports:
      - target: 16020
        published: 26020
        protocol: tcp
        mode: host
      - target: 16030
        published: 26030
        protocol: tcp
        mode: host
    env_file:
      - ./hbase.env    
    command:
      - /opt/hbase-2.3.5/bin/hbase regionserver start            
    deploy:
      mode: replicated
      replicas: 1
      endpoint_mode: dnsrr
      restart_policy:
        condition: none
      placement:
        constraints:
          - node.hostname == hadoop2
    environment:
      HBASE_CONF_hbase_regionserver_hostname: RegionServer1

  RegionServer2:
    image: bde2020/hadoop-hmaster:2.0.0-hmaster2.3.5-java8
    networks:
      - hbase
    ports:
      - target: 16020
        published: 36020
        protocol: tcp
        mode: host
      - target: 16030
        published: 36030
        protocol: tcp
        mode: host
    env_file:
      - ./hbase.env    
    command:
      - /opt/hbase-2.3.5/bin/hbase regionserver start            
    deploy:
      mode: replicated
      replicas: 1
      endpoint_mode: dnsrr
      restart_policy:
        condition: none
      placement:
        constraints:
          - node.hostname == hadoop3
    environment:
      HBASE_CONF_hbase_regionserver_hostname: RegionServer2

networks:
  hbase:
    external:
      name: hbase

2) hbase.env 配置文件，管理hbase的配置

HBASE_CONF_hbase_rootdir=hdfs://namenode:9000/hbase
HBASE_CONF_hbase_cluster_distributed=true
HBASE_CONF_hbase_zookeeper_quorum=zoo1,zoo2,zoo3

HBASE_CONF_hbase_master=HMaster:16000
HBASE_CONF_hbase_master_hostname=HMaster
HBASE_CONF_hbase_master_port=16000
HBASE_CONF_hbase_master_info_port=16010
HBASE_CONF_hbase_regionserver_port=16020
HBASE_CONF_hbase_regionserver_info_port=16030

HBASE_MANAGES_ZK=false

5、部署Hbase集群环境

docker stack deploy -c docker-compose-hbase.yml hbase

访问HBase的管理界面：

6、验证Hbase环境

# 进入HMaster容器
docker exec -it 6a5b bash
# 进入Shell
hbase shell
# 创建表
hbase(main):001:0> create 'mirson','country','address','email'
Created table mirson
Took 1.2737 seconds 
# 查看表
hbase(main):002:0> list
TABLE                     
mirson                     
1 row(s)
Took 0.0209 seconds          
=> ["mirson"]

查看管理界面，显示刚才创建的表：

至此， Hadoop3.X + Hbase2.X的分布式集群环境已搭建完成。

所有配置文件的资源已上传，可下载参考：

https://download.csdn.net/download/hxx688/87668984

7、FAQ问题

1）如果启动hbase集群后报错： There are 2 datanode(s) running and 2 node(s) are excluded in this operation...

将hadoop下的core-site.xml与hdfs-site.xml复制到Hbase的配置目录下。

2）如果出现： port published with ingress mode can't be used with dnsrr mode

在docker-compose配置文件中，将端口改成此方式映射：

ports:
    - target: 3000
      published: 3000
      protocol: tcp
      mode: host

Docker部署配置Hadoop3.x + HBase2.x实现真正分布式集群

一、安装Docker Hadoop3.X分布式集群

1、机器环境

2、下载Docker Hadoop的配置文件

3、安装Docker

4、系统配置

5、安装Docker Compose

6、拉取相关镜像

7、配置docker swarm环境

8、配置集群网络环境

9、配置Hadoop的docker-compose文件

10、部署hadoop集群环境

11、访问管理界面

二、安装Docker HBase2.X分布式集群

1、自定义生成Hbase镜像

2、部署ZooKeeper

3、部署traefik

4、配置Hbase的docker-compose文件

5、部署Hbase集群环境

6、验证Hbase环境

7、FAQ问题

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