【生产级实践】Docker部署配置Hadoop3.x + HBase2.x实现真正分布式集群环境

【生产级实践】Docker部署配置Hadoop3.x + HBase2.x实现真正分布式集群环境

网上找了很多资料，但能够实现Docker安装Hadoop3.X和Hbase2.X真正分布式集群的教程很零散，坑很多， 把经验做了整理， 避免趟坑。

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： .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 .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 192.168.1.101:2377To 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
l

进入目录：

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

修改 l的具体配置：

version: '3'services:namenode:image: bde2020/hadoop-namenode:2.0.0-hadoop3.1.3-java8networks:- hbaseports:- 19870:9870- 19000:9000volumes:- namenode:/hadoop/dfs/nameenvironment:- CLUSTER_NAME=testenv_file:- ./vdeploy:mode: replicatedreplicas: 1restart_policy:condition: on-failuremax_attempts: 3placement:constraints:- node.hostname == hadoop1labels:traefik.dockerwork: hbasetraefik.port: 9870datanode:image: bde2020/hadoop-datanode:2.0.0-hadoop3.1.3-java8networks:- hbaseports:- 19864:9864volumes:- datanode:/hadoop/dfs/dataenv_file:- ./venvironment:SERVICE_PRECONDITION: "namenode:9870"deploy:mode: globalrestart_policy:condition: on-failuremax_attempts: 3placement:constraints:- node.labels.hadoop-datanode == datanodelabels:traefik.dockerwork: hbasetraefik.port: 9864resourcemanager:image: bde2020/hadoop-resourcemanager:2.0.0-hadoop3.1.3-java8networks:- hbaseports:- 18088:8088environment:SERVICE_PRECONDITION: "namenode:9000 datanode:9864"env_file:- ./vdeploy:mode: replicatedreplicas: 1restart_policy:condition: on-failuremax_attempts: 3placement:constraints:- node.hostname == hadoop1labels:traefik.dockerwork: hbasetraefik.port: 8088healthcheck:disable: truenodemanager:image: bde2020/hadoop-nodemanager:2.0.0-hadoop3.1.3-java8networks:- hbaseports:- 18042:8042environment:SERVICE_PRECONDITION: "namenode:9000 datanode:9864 resourcemanager:8088"env_file:- ./vdeploy:mode: globalrestart_policy:condition: on-failuremax_attempts: 3placement:constraints:- node.labels.hadoop-datanode == datanodelabels:traefik.dockerwork: hbasetraefik.port: 8042historyserver:image: bde2020/hadoop-historyserver:2.0.0-hadoop3.1.3-java8networks:- hbaseports:- 18188:8188volumes:- hadoophistoryserver:/hadoop/yarn/timelineenvironment:SERVICE_PRECONDITION: "namenode:9000 datanode:9864 nodemanager:8042 resourcemanager:8088"env_file:- ./vdeploy:mode: replicatedreplicas: 1placement:constraints:- node.hostname == hadoop1labels:traefik.dockerwork: hbasetraefik.port: 8188volumes:datanode:namenode:hadoophistoryserver:networks:hbase:external:name: hbase        

10、部署hadoop集群环境

docker stack deploy -l 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：

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:9MAINTAINER Mirson <mirson.ho@gmail>RUN echo > /etc/apt/sources.list
RUN echo  "deb / stretch main non-free contrib ndeb-src / stretch main non-free contrib ndeb  stretch/updates main ndeb-src  stretch/updates main ndeb / stretch-updates main non-free contrib ndeb-src / stretch-updates main non-free contrib ndeb / stretch-backports main non-free contrib ndeb-src / stretch-backports main non-free contrib" > /etc/apt/sources.listRUN 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 /$HBASE_VERSION/hbase-$HBASE_
RUN set -x && curl -fSL "$HBASE_URL" -o /tmp/ && curl -fSL "$HBASE_URL.asc" -o /tmp/asc && tar -xvf /tmp/ -C /opt/ && rm /tmp/*RUN ln -s /opt/hbase-$HBASE_VERSION/conf /etc/hbase
RUN mkdir /opt/hbase-$HBASE_VERSION/logs
l /opt/hbase-$HBASE_VERSION/conf
l /opt/hbase-$HBASE_VERSION/conf
RUN mkdir /hadoop-dataENV HBASE_PREFIX=/opt/hbase-$HBASE_VERSION
ENV HBASE_CONF_DIR=/etc/hbaseENV USER=root
ENV PATH $HBASE_PREFIX/bin/:$PATHADD entrypoint.sh /entrypoint.sh
RUN chmod a+x /entrypoint.shEXPOSE 16000 16010 16020 16030ENTRYPOINT ["/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/l .
docker cp b1e6:/opt/hadoop-3.1.3/etc/l .

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

#!/bin/bashfunction addProperty() {local path=$1local name=$2local value=$3local entry="<property><name>$name</name><value>${value}</value></property>"local escapedEntry=$(echo $entry | sed 's///\//g')sed -i "/</configuration>/ s/.*/${escapedEntry}n&/" $path
}function configure() {local path=$1local module=$2local envPrefix=$3local varlocal valueecho "Configuring $module"for c in `printenv | perl -sne 'print "$1 " if m/^${envPrefix}_(.+?)=.*/' -- -envPrefix=$envPrefix`; doname=`echo ${c} | perl -pe 's/___/-/g; s/__/_/g; s/_/./g'`var="${envPrefix}_${c}"value=${!var}echo " - Setting $name=$value"addProperty /etc/hbase/$l $name "$value"done
}configure /etc/l hbase HBASE_CONFfunction wait_for_it()
{local serviceport=$1local service=${serviceport%%:*}local port=${serviceport#*:}local retry_seconds=5local max_try=100let i=1nc -z $service $portresult=$?until [ $result -eq 0 ]; doecho "[$i/$max_try] check for ${service}:${port}..."echo "[$i/$max_try] ${service}:${port} is not available yet"if (( $i == $max_try )); thenecho "[$i/$max_try] ${service}:${port} is still not available; giving up after ${max_try} tries. :/"exit 1fiecho "[$i/$max_try] try in ${retry_seconds}s once again ..."let "i++"sleep $retry_secondsnc -z $service $portresult=$?doneecho "[$i/$max_try] $service:${port} is available."
}for i in "${SERVICE_PRECONDITION[@]}"
dowait_for_it ${i}
doneexec $@

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. /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 root@192.168.102:/root
scp hbase_image.tar root@192.168.103:/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:3.4.10networks:- hbasevolumes:- zoo1_data:/datadeploy:mode: replicatedreplicas: 1restart_policy:condition: on-failureplacement:constraints:- node.hostname == hadoop1environment:ZOO_MY_ID: 1ZOO_SERVERS: server.1=0.0.0.0:2888:3888 server.2=zoo2:2888:3888 server.3=zoo3:2888:3888zoo2:image: zookeeper:3.4.10networks:- hbasevolumes:- zoo2_data:/datadeploy:mode: replicatedreplicas: 1restart_policy:condition: on-failureplacement:constraints:- node.hostname == hadoop2environment:ZOO_MY_ID: 2ZOO_SERVERS: server.1=zoo1:2888:3888 server.2=0.0.0.0:2888:3888 server.3=zoo3:2888:3888zoo3:image: zookeeper:3.4.10networks:- hbasevolumes:- zoo3_data:/datadeploy:mode: replicatedreplicas: 1restart_policy:condition: on-failureplacement:constraints:- node.hostname == hadoop3environment:ZOO_MY_ID: 3ZOO_SERVERS: server.1=zoo1:2888:3888 server.2=zoo2:2888:3888 server.3=0.0.0.0:2888:3888volumes:zoo1_data:zoo2_data:zoo3_data:networks:hbase: external: name: hbase

2） 部署Zookeeper集群：

docker stack deploy -l 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） l配置脚本：

version: '3.2'services:HMaster:image: bde2020/hadoop-hmaster:2.0.0-hmaster2.3.5-java8networks:- hbaseports:- target: 16000published: 16000protocol: tcpmode: host- target: 16010published: 16010protocol: tcpmode: hostenv_file:- ./vcommand:- /opt/hbase-2.3.5/bin/hbase master start          deploy:mode: replicatedreplicas: 1endpoint_mode: dnsrrrestart_policy:condition: noneplacement:constraints:- node.hostname == hadoop1labels:traefik.dockerwork: hbasetraefik.port: 16010RegionServer1:image: bde2020/hadoop-hmaster:2.0.0-hmaster2.3.5-java8networks:- hbaseports:- target: 16020published: 26020protocol: tcpmode: host- target: 16030published: 26030protocol: tcpmode: hostenv_file:- ./v    command:- /opt/hbase-2.3.5/bin/hbase regionserver start            deploy:mode: replicatedreplicas: 1endpoint_mode: dnsrrrestart_policy:condition: noneplacement:constraints:- node.hostname == hadoop2environment:HBASE_CONF_hbase_regionserver_hostname: RegionServer1RegionServer2:image: bde2020/hadoop-hmaster:2.0.0-hmaster2.3.5-java8networks:- hbaseports:- target: 16020published: 36020protocol: tcpmode: host- target: 16030published: 36030protocol: tcpmode: hostenv_file:- ./v    command:- /opt/hbase-2.3.5/bin/hbase regionserver start            deploy:mode: replicatedreplicas: 1endpoint_mode: dnsrrrestart_policy:condition: noneplacement:constraints:- node.hostname == hadoop3environment:HBASE_CONF_hbase_regionserver_hostname: RegionServer2networks:hbase:external:name: hbase

2&#v 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,zoo3HBASE_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=16030HBASE_MANAGES_ZK=false

5、部署Hbase集群环境

docker stack deploy -l 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：

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l与l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: 3000published: 3000protocol: tcpmode: host