docker运行hbase

文章目录

1. 1. docker部署hbase
   1. 1.1. 一,docker安装
   2. 1.2. 二,docker-compose来实现单节点容器的编排
   3. 1.3. 三,使用docker stack来实现
      1. 1.3.1. 1.创建swarm的网络保证各个节点都能平等的被编排
      2. 1.3.2. 2.docker node ls 查看目前的网络
      3. 1.3.3. 3.使用docker stack ls来查看创建stack
      4. 1.3.4. 4.使用docker service ls来查看service列表
      5. 1.3.5. 5.使用yml中visualizer组件来显示部署的情况
   4. 1.4. 十,遇到的坑
      1. 1.4.1. 1.在hadoop配置的需要主要
      2. 1.4.2. 2.使用docker stack 初始化的环境

docker部署hbase

系统为 centos7

docker 安装的版本为 20.10.9

一,docker安装

卸载系统仓库自带的docker

sudo yum remove docker \
                  docker-client \
                  docker-client-latest \
                  docker-common \
                  docker-latest \
                  docker-latest-logrotate \
                  docker-logrotate \
                  docker-engine

有三种方式来安装docker

1. 更新官方仓库后yum安装
2. 手动下载文件安装
3. 脚本文件安装

目前准备使用第三种方式来安装

curl -fsSL https://get.docker.com -o get-docker.sh && sh get-docker.sh

二,docker-compose来实现单节点容器的编排

curl -L https://get.daocloud.io/docker/compose/releases/download/1.25.1/docker-compose-`uname -s`-`uname -m` -o /usr/local/bin/docker-compose

chmod +x /usr/local/bin/docker-compose

/usr/local/bin/docker-compose -f docker-compose-distributed-local.yml up -d

resourcemanager  8088 

hbase-master 16000

hbase-regionserver 16020

zookeeper 2888 2181 3888

historyserver 8188

namenode 50070

datanode 50075

nodemanager 8042

三,使用docker stack来实现

1.创建swarm的网络保证各个节点都能平等的被编排

docker swarm init 初始化一个swarm 的网络

docker swarm join-token worker 显示 加入的token

docker swarm join-token manager 显示加入的token

目前使用下面加入manager,因为worker节点不能显示集群的细节

在其他服务器上输入 下面类似的内容加入节点

docker swarm join –token SWMTKN-1-0w6kjxx0j4epupf6r844dxpzoyxikrxqqgrqg319vqfg0y1gw7-31q237m76pyii2g0pw1c8nmtu 192.168.31.136:2377

2.docker node ls 查看目前的网络

docker network create –driver overlay –scope swarm hbase

docker stack deploy –compose-file docker-compose-v3.yml hdp

docker stack ls

docker stack down hadoop

docker network create –driver overlay –attachable –subnet 10.11.0.0/24 sg-hadoop

Creating service hdp_nodemanager
Creating service hdp_hbase-master

/opt/hbase-1.2.6/bin/hbase-daemon.sh restart regionserver

echo -e “hbase-region2\nhbase-region” > /etc/hbase/regionservers

docker service update –with-registry-auth

需要追加 –with-registry-auth

docker exec -t 70f261259630 netstat -an | grep LISTEN | grep 50070

version: '3'

services:
  namenode:
    image: bde2020/hadoop-namenode:2.0.0-hadoop3.2.1-java8
    networks:
      - hbase
    volumes:
      - namenode:/hadoop/dfs/name
    environment:
      - CLUSTER_NAME=test
    env_file:
      - ./hadoop.env
    deploy:
      mode: global
      #   replicas: 1
      restart_policy:
        condition: on-failure
      # placement:
      #   constraints:
      #     - node.hostname == akswnc4.aksw.uni-leipzig.de
      labels:
        traefik.docker.network: hbase
        traefik.port: 9000
    ports:
      - 9000:9000
      # - 50070:50070

  datanode:
    image: bde2020/hadoop-datanode:2.0.0-hadoop3.2.1-java8
    networks:
      - hbase
    volumes:
      - datanode:/hadoop/dfs/data
    env_file:
      - ./hadoop.env
    environment:
      SERVICE_PRECONDITION: "namenode:9000"
    deploy:
      mode: global
      restart_policy:
        condition: on-failure
      labels:
        traefik.docker.network: hbase
        traefik.port: 9867
    ports:
      - 9867:9867

  resourcemanager:
    image: bde2020/hadoop-resourcemanager:2.0.0-hadoop3.2.1-java8
    networks:
      - hbase
    environment:
      SERVICE_PRECONDITION: "namenode:9000 datanode:9867"
    env_file:
      - ./hadoop.env
    deploy:
      mode: global
    #     replicas: 1
      restart_policy:
        condition: on-failure
      # placement:
      #   constraints:
      #     - node.hostname == akswnc4.aksw.uni-leipzig.de
      labels:
        traefik.docker.network: hbase
        traefik.port: 8088
    healthcheck:
      disable: true
    ports:
      - 8088:8088


  nodemanager:
    image: bde2020/hadoop-nodemanager:2.0.0-hadoop3.2.1-java8
    networks:
      - hbase
    environment:
      SERVICE_PRECONDITION: "namenode:9000 datanode:9867 resourcemanager:8088"
    env_file:
      - ./hadoop.env
    deploy:
      mode: global
      restart_policy:
        condition: on-failure
      labels:
        traefik.docker.network: hbase
        traefik.port: 8042
    ports:
      - 8042:8042


  historyserver:
    image: bde2020/hadoop-historyserver:2.0.0-hadoop3.2.1-java8
    networks:
      - hbase
    volumes:
      - hadoop_historyserver:/hadoop/yarn/timeline
    environment:
      SERVICE_PRECONDITION: "namenode:9000 datanode:9867 resourcemanager:8088"
    env_file:
      - ./hadoop.env
    deploy:
      mode: global
    #  replicas: 1
      # placement:
      #   constraints:
      #     - node.hostname == akswnc4.aksw.uni-leipzig.de
      labels:
        traefik.docker.network: hbase
        traefik.port: 8188
    ports:
      - 8188:8188
  zookeeper:
    image: zookeeper:3.4.10
    networks:
      - hbase
    environment:
      ZOO_MY_ID: 1
      ZOO_SERVERS: server.1=0.0.0.0:2888:3888
    ports:
      - 2181:2181

  hbase-master:
    image: bde2020/hbase-master:1.0.0-hbase1.2.6
    hostname: hbase-master
    networks:
      - hbase
    env_file:
      - ./hbase-distributed-local.env
    environment:
      SERVICE_PRECONDITION: "namenode:9000 datanode:9867 zookeeper:2181"
    ports:
      - 16000:16000
      - 16010:16010

  hbase-region:
    image: bde2020/hbase-regionserver:1.0.0-hbase1.2.6
    hostname: hbase-regionserver
    networks:
      - hbase
    env_file:
      - ./hbase-distributed-local.env
    environment:
      HBASE_CONF_hbase_regionserver_hostname: hbase-region
      SERVICE_PRECONDITION: "namenode:9000 datanode:9867 zookeepe:2181 hbase-master:16010"
    ports:
      - 16020:16020
      - 16030:16030

  visualizer:
    image: dockersamples/visualizer:stable
    ports:
      - "8080:8080"
    stop_grace_period: 1m30s
    deploy:
      mode: global
    volumes:
      - "/var/run/docker.sock:/var/run/docker.sock"
    deploy:
      placement:
        constraints: [node.role == manager]

volumes:
  datanode:
  namenode:
  hadoop_historyserver:

networks:
  hbase:
    external:
      name: hbase

将自动创建service

3.使用docker stack ls来查看创建stack

4.使用docker service ls来查看service列表

5.使用yml中visualizer组件来显示部署的情况

组件	节点	默认端口	配置	用途说明
HDFS	DateNode	50010	dfs.datanode.address	datanode服务端口，用于数据传输
HDFS	DateNode	50075	dfs.datanode.http.address	http服务的端口
HDFS	DateNode	50475	dfs.datanode.https.address	http服务的端口
HDFS	DateNode	50020	dfs.datanode.ipc.address	ipc服务的端口
HDFS	NameNode	50070	dfs.namenode.http-address	http服务的端口
HDFS	NameNode	50470	dfs.namenode.https-address	https服务的端口
HDFS	NameNode	8020	fs.defaultFS	接收Client连接的RPC端口，用于获取文件系统metadata信息。
HDFS	journalnode	8485	dfs.journalnode.rpc-address	RPC服务
HDFS	journalnode	8480	dfs.journalnode.http-address	HTTP服务
HDFS	ZKFC	8019	dfs.ha.zkfc.port	ZooKeeper FailoverController，用于NN HA
YARN	ResourceManage	8032	yarn.resourcemanager.address	RM的applications manager(ASM)端口
YARN	ResourceManage	8030	yarn.resourcemanager.scheduler.address	scheduler组件的IPC端口
YARN	ResourceManage	8031	yarn.resourcemanager.resource-tracker.address	IPC
YARN	ResourceManage	8033	yarn.resourcemanager.admin.address	IPC
YARN	ResourceManage	8088	yarn.resourcemanager.webapp.address	http服务端口
YARN	NodeManager	8040	yarn.nodemanager.localizer.address	localizer IPC
YARN	NodeManager	8042	yarn.nodemanager.webapp.address	http服务端口
YARN	NodeManager	8041	yarn.nodemanager.address	NM中container manager的端口
YARN	JobHistory Server	10020	mapreduce.jobhistory.address	IPC
YARN	JobHistory Server	19888	mapreduce.jobhistory.webapp.address	http服务端口
HBase	Master	60000	hbase.master.port	IPC (主节点（HBase 主节点和任何备份的 HBase 主节点）
HBase	Master	60010	hbase.master.info.port	http服务端口 (主节点（HBase 主节点和备份 HBase 主节点如果有))
HBase	RegionServer	60020	hbase.regionserver.port	IPC( 所有从节点)
HBase	RegionServer	60030	hbase.regionserver.info.port	http服务端口
HBase	HQuorumPeer	2181	hbase.zookeeper.property.clientPort	HBase-managed ZK mode，使用独立的ZooKeeper集群则不会启用该端口。
HBase	HQuorumPeer	2888	hbase.zookeeper.peerport	HBase-managed ZK mode，使用独立的ZooKeeper集群则不会启用该端口。
HBase	HQuorumPeer	3888	hbase.zookeeper.leaderport	HBase-managed ZK mode，使用独立的ZooKeeper集群则不会启用该端口。
Hive	Metastore	9085	/etc/default/hive-metastore中export PORT=来更新默认端口
Hive	HiveServer	10000	/etc/hive/conf/hive-env.sh中export HIVE_SERVER2_THRIFT_PORT=来更新默认端口
ZooKeeper	Server	2181	/etc/zookeeper/conf/zoo.cfg中clientPort=	来自 ZooKeeper 的 config 的属性zoo.cfg。客户端将连接的端口。
ZooKeeper	Server	2888	/etc/zookeeper/conf/zoo.cfg中server.x=[hostname]:nnnnn[:nnnnn]，标蓝部分	follower用来连接到leader，只在leader上监听该端口
ZooKeeper	Server	3888	/etc/zookeeper/conf/zoo.cfg中server.x=[hostname]:nnnnn[:nnnnn]，标蓝部分	ZooKeeper 对等点用于相互通信的端口。有关更多信息，请参见此处

十,遇到的坑

1.在hadoop配置的需要主要

配置url类似于 host:port 这种时 host 不能报考_ 等字符,否则会报 contain a valid host:port authority 包含 _

2.使用docker stack 初始化的环境

所有的服务会有个stack名称的前缀,且不能修改

在集群中加入容器中后可以通过 服务名称就是 STACK_NAME 来调用也可以通过在yml中定义的services下面的节点名称来调用这个需要注意

初始化后出现所有的service会加前缀导致域名不能和访问

3.哈哈哈

File /hbase/.tmp/hbase.version could only be written to 0 of the 1 minReplication nodes. There are 1 datanode(s) running and 1 node(s) are excluded in this operation

4.配置出错导致服务绑定对应的ip

java.io.IOException: Problem binding to hbase-region/10.0.4.107:16040 : Cannot assign requested address. To switch ports use the 'hbase.regionserver.port' configuration property.